Content:
Presentation type:
NH – Natural Hazards

EGU24-4270 | Orals | NH2.1 | Highlight | Plinius Medal Lecture

Hazard forecasting: is it a matter of time? 

Jacopo Selva

Hazard models aim at making explicit our forecasting capability about future potentially adverse natural events. Hazard events are typically rare and not deterministically predictable, forcing hazard models to speak the language of certainty and uncertainty, that is, of probability. This is valid for any forecasting time window, from years to days/hours in the future (long- to short-term hazard), to the evaluation of the potential impact of an ongoing event in the next seconds/minutes/hours (warning/now-casting to urgent computing). Even though the definition of the target time window is driven by the users of the forecast (e.g. civil protections) and is not a scientific matter, the quantification of existing uncertainty given the time frame is certainly a scientific matter. Probabilistic hazard is commonly discussed mainly for long-term hazards, where large uncertainty dominates. In shorter-term forecasts, uncertainty may deacrease and practitioners are often tempted by simplified approaches that neglect uncertainty, like for eruption forecasting during volcanic crises, or for tsunami warning models after seismic or volcanic events. Nevertheless, uncertainty may still exist, and a rational scientific approach should let the results to speak about existing uncertainty, rather than to neglect it by definition. Is it possible to define a unified approach to probabilistic hazard entailing all time scales? The long-term integral hazard integrating all potential sources and generation/propagation conditions can be adapted to the different forecasting time windows, generating a unified framework in which the different time scales may feed to each other, producing homogeneous and easy-to-interpret results. This unified vision of hazard models, embracing long- to short-term hazard as well as warning and urgent computing models, is here discussed based on the recent advancements in models for volcanic, seismic and tsunami hazard and warning.

How to cite: Selva, J.: Hazard forecasting: is it a matter of time?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4270, https://doi.org/10.5194/egusphere-egu24-4270, 2024.

The intensification of extreme precipitation in a warming climate has been shown in observations and climate models to follow approximately theoretical Clausius-Clapeyron scaling. However, larger changes have been indicated in events of short-duration which frequently trigger flash floods or landslides, causing loss of life. Global analyses of continental-scale convection-permitting climate models (CPCMs) and new observational datasets will be presented that provide the state-of-the-art in understanding changes to extreme weather (rainfall, wind, hail, lightning) and their compounding effects with global warming. These analyses suggest that not only warming, but dynamical circulation changes, are important in the manifestation of change to some types of extreme weather, which must be addressed in the design of new CPCM ensembles. We use our projections to provide the first analyses of impacts on infrastructure systems using a new consequence forecasting framework and show the implications for adaptation. It will be argued that a shift in focus is needed towards examining extreme weather events in the context of their ‘ingredients’ through their evolution in time and space. Coupled with exploration of their causal pathways, sequencing, and compounding effects – ‘storylines’ –, this can be used to improve both early warning systems and projections of extreme weather events for climate adaptation.

How to cite: Fowler, H.: Rapidly intensifying extreme weather events in a warming world: how important are large-scale dynamics in generating extreme floods?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22472, https://doi.org/10.5194/egusphere-egu24-22472, 2024.

EGU24-10624 | ECS | Orals | NH10.1 | Highlight | NH Division Outstanding ECS Award Lecture

Advancing multi-(hazard)risk science: embracing complexity and cross-disciplinary collaborations 

Marleen de Ruiter

Recent disasters have demonstrated the growing challenges faced by society as a result of multi-hazards and compound events. The impacts of such disasters differ significantly from those caused by single hazard disasters: often the impacts of a multi-hazard disaster exceed those of the sum of the impacts of the individual hazards. Recognizing this complexity, the scientific community and international organizations, such as the UNDRR, have been advocating for a more integrated approach in multi-(hazard)risk research. This requires bridging across individual hazard types, but also learning from methodological advances made in neighbouring research fields such as the compound events community.

This talk aims to highlight recent advances in assessing the complexities of multi-(hazard)risk and discusses opportunities for further enhancing our modeling capabilities through multidisciplinary collaboration. A crucial challenge of modelling compound and multi-hazard risk, is that of the spatiotemporal dynamics of risk. This includes for example, an improved understanding of post-disaster recovery after multi-hazard disasters and the role of (changing) local contexts within which disasters take place such as the dynamics of socioeconomic vulnerability and the likelihood of post-disaster disease outbreaks. Embracing these challenges and opportunities can support more comprehensive and effective disaster risk management strategies in the future.

How to cite: de Ruiter, M.: Advancing multi-(hazard)risk science: embracing complexity and cross-disciplinary collaborations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10624, https://doi.org/10.5194/egusphere-egu24-10624, 2024.

NH1 – Hydro-Meteorological Hazards

Introduction: The increasing number of heat events of summer 2003, 2010 and 2015 induced a rising impact on heat health morbidity and mortality in Germany. A considerable proportion of urban population is affected by thermal discomfort due to the urban heat island burden during summer, particularly vulnerable people at risk. As contribution to the National Adaptation Strategy to Climate Change a federal expert working group prepared and published ‘Recommendations for Action for the Preparation of Heat Action Plans to Protect Human Health’ in 2017, on the basis of the 2008 WHO Heat Health Guidance. A first country-wide project had been conducted in Germany between 2019 and 2023 which investigated the status and impact of current or planned Heat Health Action Plans (HHAP), and adaptation measures appropriate to protect and prevent human health. One aim of this study was to conduct an online survey on the awareness and degree of use of the 2017 recommendations and the development and implementation of HHAP.

 

Methods: The online survey questionnaire referred to climate change, heat and health aspects. The survey had been conducted in May/June 2020 to assess the current state of affairs as well as factors of success and barriers in the development and implementation of HHAP, with a particular focus on municipal administrations. Therefore, various networks of national, regional and local environment and health administrations, as well as stakeholders had been invited via an Email, web and social media campaign to participate anonymously. 

 

Results: The study fell in the period of increasing incidence of COVID19 pandemic, which influenced and limited the responses from the public health sector country-wide. Nonetheless, the online survey had been conducted in May/June 2020. In total 116 questionnaires had been responded, mainly by participants from the environment sector (53%), and 32% from the public health sector. More than half of the respondents (n=67) indicated to be aware of the 2017 recommendations (very well-known at the federal state level: 90%, at county level known by 43%). The recommended health-related adaptation measures were appreciated very or helpful by 81%. Respondents from large cities (> 100 000 inhabitants) were main contributors to the study (41 of 81 large cities replied, while 34 rural counties responded). So far, no federal state responded, but four municipalities and one county indicated to start planning activities on HHAP.

 

Conclusion: Recent heat events clearly indicate the demand to protect public health against heat extremes in Germany. The results of this first country-wide survey show on the one hand that currently HHAP are being developed rarely. On the other hand, results reflect that first HHAP actions turned into force after 2017 recommendation had been launched. Federal states and municipalities feel motivated and act responsible to take health-related adaptation measures in advance, such as HHAP, to prevent heat-related illnesses and deaths sustainable. Policy and decision makers must develop structures and regulations that anchor HHAP as a nationwide instrument to be established timely. 

How to cite: Mücke, H.-G.: Climate change induced heat health challenges – a study on the development of health-related adaption measures in Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1224, https://doi.org/10.5194/egusphere-egu24-1224, 2024.

EGU24-1262 | ECS | Posters on site | NH1.1

A systematic review on climate change, trending outcomes for the care of older adults, and financial expenditure 

Keriin Katsaros and Jo-Ting Huang-Lachmann

As global populations age, life expectancy increases, and the impacts of climate change intensify, there is a corresponding rise in financial expenditure associated with both extreme climate events and a growing demand for long-term healthcare. There is a gap in research showing how climate change, the care of aging populations, and financial expenditure are interconnected.  A systematic review of literature is carried out to identify the interrelationships and to explore existing trends and evidence on senior care during the time of climate change. This work is important to identify barriers and priority action areas for adaptation, mitigation, and future planning to increase health gain and achieve positive economic outcomes.

The systematic review of existing peer-reviewed publications is carried out by following PRISMA guidelines.  The methodology is guided by recommendations from Cochrane and in the WHO Guidance on Research Methods for Health Emergency and Disaster Risk Management. Three electronic databases have been searched (PubMed, Web of Science, and Scopus) to assess available literature on climate change, the care of older persons, and financial expenditure. A risk of bias assessment is completed using CASP checklists.

Initial results of this review have identified significant adverse impacts for older society members including decreased physical and mental health during extreme weather events resulting in increased medical and care costs. Preliminary results also highlight a need for energy-efficient built environments, clean and affordable energy sources to overcome energy poverty, and a new way of rethinking how we care for senior society members, including increased support from families and communities.

This research aims to contribute to increasing transdisciplinary knowledge from the fields of health and care, energy, and climate change to create societies for older people that are friendly, affordable, and resilient to the adverse effects of climate change. The results aim to advance the transdisciplinary knowledge of climate services, health, and energy economics; co-creating synergies and actionable solutions; and working with societal actors for implementation, transfer, and upscaling of research.

How to cite: Katsaros, K. and Huang-Lachmann, J.-T.: A systematic review on climate change, trending outcomes for the care of older adults, and financial expenditure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1262, https://doi.org/10.5194/egusphere-egu24-1262, 2024.

EGU24-1762 | ECS | Orals | NH1.1

Assessing the impact of mobility on heat exposure 

Guo-Shiuan Lin and Gabriele Manoli

Higher temperatures are linked to elevated mortality risk and reduced economic productivity. In urban centers, human mobility and the urban heat island effect generally result in higher population density and increased temperatures. Yet, existing studies on urban heat exposure rely on static residential population data, thus neglecting population dynamics and their covariation with the spatial distribution of urban temperatures. Here, we evaluate how seasonal and daily mobility modify heat exposure and risk across 80 European cities by combining monthly daytime and nighttime population estimates with high-resolution urban climate simulations. Our findings reveal that, on a daily scale, mobility increases population and summer heat exposure in most cities due to daily commuting behavior. Conversely, commuting to warmer city centers (from colder rural areas) may be advantageous in winter. On seasonal timescales, summer populations decrease in most cities as urban residents travel outward for holidays but heat exposure increases significantly in touristic destinations where population peaks during the June-August period. These results emphasize the significant impact of mobility on the space-time distribution of heat exposure in cities and offer valuable insights for mitigating temperature-related risks in diverse climatic and urban contexts.

How to cite: Lin, G.-S. and Manoli, G.: Assessing the impact of mobility on heat exposure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1762, https://doi.org/10.5194/egusphere-egu24-1762, 2024.

EGU24-1899 | ECS | Posters on site | NH1.1

Heatwave social vulnerability index validated on mortality data in Europe 

Benedetta Sestito, Lena Reimann, Maurizio Mazzoleni, Wouter Botzen, and Jeroen Aerts

Climate change projections underscore an imminent temperature escalation of 1.1°C to 6.4°C above the 1990 baseline by 2100, leading to heatwaves of higher frequency, intensity, and duration. In the last decades, Europe has experienced severe heatwave events, such as the catastrophic one in summer 2003 that claimed over 70,000 lives. Thus, it is of pivotal importance to better understand the drivers of heatwave impacts to promote effective adaptation and mitigation strategies. While many studies have been carried out to explore the social vulnerability to heat-related impacts at local and regional scales, a large-scale continental analysis is still missing. This study aims at exploring the temporal and spatial dynamics of social vulnerability to heatwaves in Europe. This will be achieved by developing a dynamic spatial and temporal social vulnerability index for heatwaves in Europe. The index is validated against impact metrics such as mortality, which remains underexplored in large-scale assessments. In particular, a regression analysis between heatwave mortality and socio-economic and demographic factors, including population changes, income variations, and alterations in social infrastructure is carried out to assess the degree to which these factors are associated with heatwave mortality. The regression coefficients serve as the weights in the composite social vulnerability index. Such validation enhances the credibility, accuracy, and applicability of social vulnerability indices, bridging the divide between theoretical assessments and real-world consequences. Our empirical results indicate that diverse socio-economic and demographic variables exhibit distinct correlations with heatwave mortality. Consequently, an index incorporating ad hoc weighting of its constituent terms more effectively captures the social vulnerability component to heatwaves. This research provided new insights to better understand social vulnerability to heatwaves and allow better-informed decision-making to enable the development of resilient communities. Moreover, our findings advanced the understanding of heat risks in the broader context of escalating climate change challenges across Europe.

How to cite: Sestito, B., Reimann, L., Mazzoleni, M., Botzen, W., and Aerts, J.: Heatwave social vulnerability index validated on mortality data in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1899, https://doi.org/10.5194/egusphere-egu24-1899, 2024.

EGU24-2014 | ECS | Posters on site | NH1.1

Developing a Multivariate System for Predicting and Mitigating the Health Effects ofHeat waves in Niterói, Rio de Janeiro 

Vitor Luiz Galves, Marcio Cataldi, and Joan Souza

This study aims to develop a heat wave forecasting system using a new multivariate index that encompasses hydration-related mitigation measures. Heatwaves have increasingly occurred with greater frequency and intensity in various regions worldwide, particularly in Europe and Asia since 1990, although they are not exclusive to these areas. The principal health effects of heatwaves on populations include heat-related illnesses and fatalities, cardiovascular and kidney diseases, as well as adverse reproductive effects. These detrimental impacts are widespread and commonly affect individuals aged 65 and above. Many nations have established metrics to assess the prevalence of this occurrence within their borders. These metrics typically utilize specific thresholds and/or temperature ranges at a height of 2 meters, which denote extreme percentiles of values from past records. While some of these metrics consider the persistence of the phenomenon, few take into account the relative humidity. It is noteworthy that, in most instances, the temperature thresholds lead to a linear escalation in conditions posing a risk to the population. This can result in a biased perception of the actual level of risk involved. To thoroughly evaluate the health hazards associated with heatwaves, it is essential to acknowledge the considerable variability in global climate, as well as the diverse responses of living organisms to extreme temperature and humidity conditions. Furthermore, factors such as individuals' gender, race, age, pre-existing medical conditions, and geographical location should be taken into account.This study is divided into several components to reach a comprehensive solution. The first step involves determining the monthly distribution curve of accumulated daily maximum temperatures for each grid point of the ERA 5 data. After completing this process, machine learning models must be developed to calibrate the temperature values to the percentile of the cumulative distribution. Subsequently, the temperature value exceeding 95% of the distribution will be applied to this coefficient Coef = (eTpe*Ur)/1000, where Tpe is the value of the distribution that exceeds 95% and Ur is the relative humidity. These adjusted values will then be used to compute the normalized index I=(Coef-0.022)/9.7, accounting for the exponential temperature increase and providing weightage to the relative humidity. Upon establishment of these functions, a time series of the index value will be generated. This value will be multiplied by the hours of the day during which the index deviates from zero, facilitating the evaluation of its correlation with hospitalization and mortality data related to diseases such as thrombosis, which may be linked to heat waves. The results of this phase will be presented at the Niterói region in Rio de Janeiro, Brazil, during the upcoming congress. Moreover, according to previous analyzes, since 2010 the frequency and intensity of heat waves have increased, being apparently modulated by Enso events and also by indices developed at LAMMOC/UFF related to anomalies of sea surface temperature of the Equatorial Atlantic Ocean and the South Atlantic Convergence Zone. Furthermore, the index data will subsequently undergo validation based on body water loss rates and their impact on blood viscosity fluctuations.

How to cite: Galves, V. L., Cataldi, M., and Souza, J.: Developing a Multivariate System for Predicting and Mitigating the Health Effects ofHeat waves in Niterói, Rio de Janeiro, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2014, https://doi.org/10.5194/egusphere-egu24-2014, 2024.

EGU24-3061 | ECS | Posters on site | NH1.1

Links between weather variability and Dengue outbreaks in Sao Paulo, Brazil 

Falak Naz, Júlia Araújo, Sheila Oliveira, Seyma Celina, Aleš Urban, and Jiří Černý

Mosquito-borne diseases are among the most dangerous threats for all people living in tropical areas. Previous research has shown that the highest incidence of mosquito-borne diseases is associated with a particular type of weather (usually wet and hot) as mosquitos’ activity and development are highly dependent on meteorological conditions. However, short-term associations (on the scale of days up to a few weeks) have been less understood.

In this study, we collected weekly data on the incidence of Dengue on a municipality level in the state of Sao Paulo, Brazil, 2016–2022, and matched it with ERA5-based weather variables (ambient temperature, relative humidity, wind speed and precipitation). We employed a multilevel meta-regression analysis to i) analyse the links between Dengue incidence and weather variability in, and ii) develop a model to predict a Dengue fever outbreak based on actual weather conditions and socioeconomic variables.

Our preliminary results suggest a significant association of a Dengue outbreak with above-average daily mean temperature and humidity, heavy rainfalls, and calm conditions in previous 2-6 weeks. Further analysis is needed to identify spatial differences in these patterns based on socioeconomic conditions.

How to cite: Naz, F., Araújo, J., Oliveira, S., Celina, S., Urban, A., and Černý, J.: Links between weather variability and Dengue outbreaks in Sao Paulo, Brazil, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3061, https://doi.org/10.5194/egusphere-egu24-3061, 2024.

EGU24-3081 | Orals | NH1.1

Developing a Multivariate System for Predicting and Mitigating the Health Impacts of Heatwaves 

Marcio Cataldi, Vitor Galvez, Victoria Gallardo Fernandez, Juan Pedro Montávez, Pedro Jiménez-Guerrero, Guillermo Felipe Lopez Sanchez, and Christian Jair Martínez Urrutia

The main purpose of this study is to develop a heatwave impact-based forecasting system using a new multivariate index, that also encompasses a mitigation action plan with hydration-related measures. Since 1990, heatwaves have become more frequent and intense in various regions worldwide, particularly in Europe and Asia. The principal health effects of heatwaves include organs' strain and damage, complications of cardiovascular and kidney diseases, as well as adverse reproductive effects. These detrimental impacts are widespread and commonly affect individuals aged 65 and above. Many nations have established metrics to assess the prevalence of this occurrence within their borders. These metrics typically use specific threshold values and/or ranges of the near-surface (2 m) air temperature, usually denoted by the extreme values from past records. To the best of our knowledge, only some of these metrics take into account the persistence of the phenomenon and few consider the relative humidity. It is noteworthy that in most of these metrics the temperature thresholds lead to a linear escalation of the conditions posing a risk to the population, which may lead to a misperception of the actual level of risk involved. To thoroughly evaluate the health hazards associated with heatwaves, it is essential to consider the climate variability and change at regional and local scales, as well as the diverse responses of living organisms to extreme (and long-lasting) temperature and humidity conditions. Factors such as individuals' sex, ancestry, age, pre-existing medical conditions, and geographical location should be considered too. The first step of this study consisted of the characterization of the monthly Cumulative Distribution Function of the daily maximum near-surface air temperature (TX) in summer, in recent climate. We used the ERA5-Land reanalysis dataset and performed the analysis for each grid point, considering 1960-1990 as baseline period.  Subsequently, in order to compute the index, the temperature values exceeding the 95th percentile (TX95p) were subjected to a normalized scaling function whose values grow exponentially with the magnitude of the temperature and also depend on the ambient relative humidity. The resulting index values range from 0 to 1, only being greater than zero when the temperature exceeds TX95p. To calibrate the index, we considered the hours of the day during which the index deviates from zero and its correlation with hospitalization and mortality data, mainly related to cardiovascular diseases such as thrombosis. The preliminary work concerned the Region of Murcia, in Spain. The index was validated in the period 2000-2022. Results show the sensitivity of the index, which displays its largest values in the summer of 2022, coinciding with the high number of heat-related deaths observed that year in Spain. Future research will be focused on index calibration and validation in other regions which are also subjected to extreme heat conditions.

How to cite: Cataldi, M., Galvez, V., Gallardo Fernandez, V., Montávez, J. P., Jiménez-Guerrero, P., Lopez Sanchez, G. F., and Martínez Urrutia, C. J.: Developing a Multivariate System for Predicting and Mitigating the Health Impacts of Heatwaves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3081, https://doi.org/10.5194/egusphere-egu24-3081, 2024.

EGU24-3446 | Orals | NH1.1

Drivers of the time-varying heat-cold-mortality association in Spain 

Hicham Achebak, Grégoire Rey, Simon Lloyd, Marcos Quijal-Zamorano, Raúl Fernando Méndez-Turrubiates, and Joan Ballester

Background: A number of studies have reported reductions in mortality risk due to heat and cold over time. However, questions remain about the drivers of these adaptation processes to ambient temperatures. We aimed to analyse the demographic and socioeconomic drivers of the downward trends in vulnerability to heat- and cold-related mortality observed in Spain during recent decades (1980-2018).

Methods: We collected data on all-cause mortality, temperature and relevant contextual indicators for 48 provinces in mainland Spain and the Balearic Islands between Jan 1, 1980, and Dec 31, 2018. Fourteen contextual indicators were analysed representing ageing, isolation, urbanicity, heating, air conditioning (AC), house antiquity and ownership, education, life expectancy, macroeconomics, socioeconomics, and health investment. The statistical analysis was separately performed for the range of months mostly causing heat- (June-September) and cold- (October-May) related mortality. We first applied a quasi-Poisson generalised linear regression in combination with distributed lag non-linear models (DLNM) to estimate province-specific temperature-mortality associations for different periods, and then we fitted univariable and multivariable multilevel spatiotemporal meta-regression models to evaluate the effect modification of the contextual characteristics on heat- and cold-related mortality risks over time.

Findings: The average annual mean temperature has risen at an average rate of 0·36°C per decade in Spain over 1980-2012, although the increase in temperature has been more pronounced in summer (0·40°C per decade in June-September) than during the rest of the year (0·33°C per decade). This warming has been observed, however, in parallel with a progressive reduction in the mortality risk associated to both hot and cold temperatures. We found independent associations for AC with heat-related mortality, and heating with cold-related mortality. AC was responsible for about 28·6% (31·5%) of the decrease in deaths due to heat (extreme heat) between 1989-1993 and 2009-2013, and heating for about 38·3% (50·8%) of the reductions in deaths due to cold (extreme cold) temperatures. Ageing (ie, proportion of population over 64 years) attenuated the decrease in cold-related mortality.

Conclusion: AC and heating are effective societal adaptive measures to heat and cold temperatures. This evidence holds important implications for climate change health adaptation policies, and for the projections of climate change impacts on human health.

How to cite: Achebak, H., Rey, G., Lloyd, S., Quijal-Zamorano, M., Méndez-Turrubiates, R. F., and Ballester, J.: Drivers of the time-varying heat-cold-mortality association in Spain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3446, https://doi.org/10.5194/egusphere-egu24-3446, 2024.

Humid heatwaves, defined as extreme temperatures combined with high relative humidity, can affect large populations and result in crop damage, causing public health emergencies and threatening food security. The consequences for society are even more severe when extreme rainfall follows a humid heatwave. There is evidence of the increasing occurrence of humid heatwaves—extreme rainfall compound events in several parts of the globe. Their compound impact depends on the response time, the statistical interdependency between the two interacting causal drivers, and their severity. While the correlation between temperature and rainfall tends to be negative at daily or monthly time scales, the correlation between short-duration rainfall extremes and high temperatures is often positive at shorter time scales during the summer. A positive (negative) correlation can result in a higher (lower) risk of compound heatwave-extreme rainfall events. Across the coasts, the dependence strengths between these two variables are often elusive due to the influence of large-scale atmospheric teleconnection. On a global scale, the statistical coupling between humid heatwaves and extreme rainfall events has not been investigated across the coasts. To fill this knowledge gap, this study provides an observational assessment of the compound interactions of summer heatwave amplitude (i.e., the peak temperature of the hottest day during the heatwave episode) and extreme rainfall (described by > 90th percentile threshold of daily rainfall magnitude) across 29 major coastal cities in the tropics (23.5°N - 23.5°S), subtropics (23.5°N - 35°N and 23.5°S - 35°S) and mid-latitudes (35°N – 60°N and 35°S - 60°S). It finds a significant (P < 0.05) increase in the frequency of compound humid heatwaves-extreme rainfall events in the past few decades, with a more robust increase over the northern hemisphere compared to the southern hemisphere. The mean response times between the heatwave amplitude and the peak rainfall tend to be shorter for the southern sub-tropics than the northern hemisphere sites, indicating a swift transition between two extremes in these regions. Using a multivariate probabilistic framework, we further demonstrate that a modest to substantial increase in heatwave amplitude in summer can enhance the rainfall extremes by 80%, with the most significant increase occurring in the sub-tropics. The findings reveal a strong coupling between humid heatwaves and extreme rainfall in sub-tropical climate regimes, contrasted by a relatively weak coupling across the tropics. Understanding the interactions between humid heatwaves and extreme precipitation across coastal megacities will help decision-makers and stakeholders to adapt and mitigate these compound hazards in densely populated settlements.

How to cite: Ganguli, P. and Merz, B.: A Global Assessment of Compound Humid Heatwaves-Extreme Rainfall in Major Coastal Cities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4088, https://doi.org/10.5194/egusphere-egu24-4088, 2024.

EGU24-4858 | Posters on site | NH1.1

Significant reduction of unequal population exposure to climate extremes by achieving the carbon neutrality 

Jung Choi, Seok-Geun Oh, Min-Jee Kang, Sujong Jeong, Seung-Ki Min, Sang-Wook Yeh, Yeon-Hee Kim, and Seok-Woo Son

Climate extremes, such as hot temperature and heavy precipitation events, have devastating effects on human societies. As the planet warms, they have become more intense and more frequent. To avoid irreversible damage from climate extremes, many countries have committed to achieving net-zero anthropogenic carbon emissions, or carbon neutrality, by 2050s. Here, we quantify the impact of carbon neutrality on population exposure to climate extremes using multi-model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on the Shared Socioeconomic Pathway (SSP)1-1.9 and SSP3-7.0 scenarios. It is found that the increasing exposure of the population to hot-temperature and heavy-precipitation extremes can be substantially reduced by 87–98% in the late 21st century by achieving carbon neutrality. The benefits of carbon neutrality are particularly pronounced in Africa and Asia. The potential benefits of carbon neutrality are also significant in North America, Europe, and Oceania, where a reduction in climate extremes is more than twice as important as population decline in reducing population exposure to climate extremes. These results provide important scientific support for ongoing efforts to achieve net-zero carbon emissions by 2050s to reduce potential climate risk and its inequity across continents.

How to cite: Choi, J., Oh, S.-G., Kang, M.-J., Jeong, S., Min, S.-K., Yeh, S.-W., Kim, Y.-H., and Son, S.-W.: Significant reduction of unequal population exposure to climate extremes by achieving the carbon neutrality, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4858, https://doi.org/10.5194/egusphere-egu24-4858, 2024.

EGU24-4898 | ECS | Orals | NH1.1

Assessment of humidity-inclusive heat index models over tropical megacities: Indonesia case 

Muhammad Rezza Ferdiansyah, Alberth Nahas, and Ardhasena Sopaheluwakan

One of the impacts on humans in megacities experiencing rapid urbanization is the increase in heat risk, primarily due to the urban heat island (UHI) phenomenon. One of the reasons for the intensification of UHI can be attributed to changes in land use and population growth. Additionally, global warming and climate change conditions that are currently occurring exacerbate this issue. For megacities located in tropical regions, such as Indonesia, there is limited available data regarding the impact of heat stress. Therefore, it is essential to develop a heat index suitable for tropical climates, characterized by high temperatures and humidity levels. Temperature and humidity are two crucial factors in quantifying the heat index to mitigate the risk of heat-related disasters. Consequently, when modeling the heat index for megacities in tropical regions, it is necessary to incorporate humidity. This study aims to compare different models for humidity-inclusive temperature indices, specifically Apparent Temperature (AT), Heat Index (HI), and Wet Bulb Globe Temperature (WBGT). These indices are computed using standard weather measurement data and re-analysis data to obtain spatial distribution. The current results demonstrate that these indices effectively captured the unusual heat conditions in Indonesia during the September 2023 period.

How to cite: Ferdiansyah, M. R., Nahas, A., and Sopaheluwakan, A.: Assessment of humidity-inclusive heat index models over tropical megacities: Indonesia case, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4898, https://doi.org/10.5194/egusphere-egu24-4898, 2024.

EGU24-6555 | ECS | Posters on site | NH1.1

Mapping the vulnerability to heat: an application in the city of Bern 

Sujung Lee, Moritz Burger, Moritz Gubler, Stefan Brönnimann, and Ana Maria Vicedo-Cabrera

Background: Heat is widely acknowledged as one of the most hazardous climate-related risk factors affecting human health. Increasing urban development has led to an amplification of its health impacts due to the Urban Heat Island (UHI) effect. However, our understanding of neighbourhood-level vulnerability to the UHI effect remains limited. This information can be crucial for policymakers to identify high-risk areas in cities and develop more targeted public health interventions. Thus, we propose a comprehensive approach to map the vulnerability to UHI in the city of Bern (Switzerland) by (1) assessing the demographic and socio-economic factors contributing to increased UHI exposure and (2) analysing the spatial distribution of vulnerability to the UHI effect.

Methods: We collected population and household statistics at the individual level from 2012 to 2021 from the Federal Statistical Office of Switzerland. Firstly, we calculated the intensity of UHI (representing the temperature difference between the inner city and the rural surroundings) in each district of Bern using high-resolution (50mx50m) modelled urban temperature data. Next, we performed univariate logistic regression models to estimate the association between UHI exposure and population characteristics, reporting odds ratio (OR) and 95% confidence intervals (CI). We defined UHI exposure as individuals being exposed to UHI intensity exceeding the city-mean for the corresponding census year. Subsequently, we established the Heat Vulnerability Index (HVI) by selecting key determinants: 1) the elderly population (aged ≥65 years), 2) females, and 3) individuals with low socio-economic status. The overall percentile ranks for districts were calculated by summing variable rankings.

Result: First, our study identified several factors contributing to increased UHI exposure, in particular, single individuals had 60% higher odds of UHI exposure (OR:1.60; CI:1.59-1.62) compared to married individuals, and individuals aged 26-44 (1.71; 1.70-1.74) compared to those aged 0-17. Also, wealthier individuals appeared to have higher odds of UHI exposure (medium: 2.32; 2.30-2.35, high: 1.66; 1.64-1.67) compared to the lowest group. In the context of the work environment, individuals in large-size companies (≥250 employees) had an increased risk (1.85; 0.77-6.05) of UHI exposure compared to those in micro-size companies (<10 employees) and employees of public companies (1.17; 0.88-1.62) compared to their counterparts in private companies. Our results highlighted varying vulnerability patterns in different districts. In the city centre, despite a medium HVI, UHI intensity surpassed other areas, intensifying vulnerability to heat. The western part showed lower UHI but had high HVI due to a concentration of individuals with the lowest socio-economic status.

Conclusion: Our preliminary results emphasize the importance of considering demographic and socioeconomic characteristics when assessing the impact of UHI exposure on population health. Building upon these findings, we plan to develop a heat vulnerability map of the city of Bern by applying a more advanced epidemiological analysis using Bayesian methods to assess the spatial distribution of the UHI mortality risk. This investigation will provide valuable evidence and methods to improve our understanding of the impact of UHI on health and aid in developing targeted interventions to protect at-risk communities.

How to cite: Lee, S., Burger, M., Gubler, M., Brönnimann, S., and Vicedo-Cabrera, A. M.: Mapping the vulnerability to heat: an application in the city of Bern, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6555, https://doi.org/10.5194/egusphere-egu24-6555, 2024.

EGU24-7213 | Posters on site | NH1.1

Assessing Present-Day and Future Perspectives of Climate Impact on Thermal Stress Risks in Korea from 1km High Resolution Scenarios 

Jae-Hee Lee, Hyun Min Sung, Jin-Uk Kim, Sungbo Shim, Chu-Yong Chung, and Young-Hwa Byun

Among the various thermal stress indices, apparent temperature (AT) is closely related to public health indicators, and consequently is widely used by weather agencies around the world. Therefore, in this study we estimate the changes in AT and contributing components in Korea as a whole and in five major cities (Seoul, Gwanju, Daegu, Daejeon, and Busan) using national standard climate scenarios based on the coupled model inter-comparison project (CMIP6). In the present day, high AT occurs in major cities due to high temperature (TAS) and relative humidity (RH). Our findings reveal that even when TAS is relatively low, large AT occurs with higher humidity. Notably, in future warmer climate conditions, high AT may first appear in the five major cities and then extend to the surrounding areas. An increase in TAS and RH during the pre-hot season (March to June) may lead to earlier occurrence of thermal risks in future warmer climate conditions and more frequent occurrence of high thermal stress events. Our study can serve as a reference for future information on thermal risk changes in Korea. Considering those who have not adapted to high temperature environments, our findings imply that thermal risks will become more serious and that heat adaptation strategies will be needed during the pre-hot season under future warmer climate conditions.

How to cite: Lee, J.-H., Sung, H. M., Kim, J.-U., Shim, S., Chung, C.-Y., and Byun, Y.-H.: Assessing Present-Day and Future Perspectives of Climate Impact on Thermal Stress Risks in Korea from 1km High Resolution Scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7213, https://doi.org/10.5194/egusphere-egu24-7213, 2024.

EGU24-8032 | ECS | Posters on site | NH1.1

The interconnections between household energy, health, and climate change: a comprehensive umbrella review 

Clemens Marggraf and Jo-Ting Huang-Lachmann

Household energy is becoming increasingly important for the maintenance of good health, especially as people spend 90% of their lifetime indoors. However, there are a number of health and climate impacts associated with the generation and use of household energy. To date, there is no holistic picture in the literature describing the interlinkages between household energy, health outcomes and climate change. In order to systematically synthesize the fragmented evidence, an umbrella review will be conducted.

Therefore, a systematic review of peer-reviewed literature was carried out following PRISMA guidelines. Five electronic databases were searched (PubMed, Web of Science, Google Scholar, Cochrane and Scopus) to assess available literature on climate change, health and household energy, from January 1, 1900 through to June 5, 2023.

Preliminary findings highlight the dynamic interactions between the three issues, e.g., the impact of climate change on energy use/production and health outcomes, as well as the impact of different methods of energy use/production on climate change and health outcomes. In addition, the lack of consideration of the current literature on climate change  in the context of health and energy is a further finding of the umbrella review. Furthermore, the literature reviewed tends to ignore inclusion criteria (e.g., gender, socioeconomic or spatial aspects), which are also essential for a just transition to a more climate-friendly society in the future.

The goal of the umbrella review is to help policymakers understand the complex interrelationships between the three topics, both now and in the future, as climate change progresses and humanity is forced to adopt different mitigation and adaptation methods that affect energy use and production, as well as health outcomes.

How to cite: Marggraf, C. and Huang-Lachmann, J.-T.: The interconnections between household energy, health, and climate change: a comprehensive umbrella review, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8032, https://doi.org/10.5194/egusphere-egu24-8032, 2024.

EGU24-8234 * | Orals | NH1.1 | Highlight

Urgency of Climate Change through the lens of COVID-19 Pandemic: the case of heat-related mortality 

Fulden Batibeniz, Sonia Isabelle Seneviratne, Srinidhi Jha, Andreia Ribeiro, Laura Suarez Gutierrez, Christoph C. Raible, Ben Armstrong, Michelle L. Bell, Eric Lavigne, Antonio Gasparrini, Yuming Guo, Masahiro Hashizume, Pierre Masselot, Susana Pereira da Silva, Dominic Royé, Francesco Sera, Shilu Tong, Aleš Urban, and Ana M. Vicedo-Cabrera and the Multi-Country Multi-City Collaborative Research Network

The COVID-19 pandemic and climate change are both urgent global health concerns. However, their impact on human lives has not been compared on the same scale. In this study, we compared mortality due to heat with COVID-19 in 38 cities worldwide, considering different levels of global warming (+1°C, +1.5°C, +2°C, and +3°C). Our findings reveal that even at a global warming level of +1.0ºC, 6 cities are already at a point where heat-related deaths could equal COVID-19 deaths within 15 years. Regardless of high or low COVID-19 mortality in the cities, the number of years to reach the level of COVID-19 mortality decreases with higher global warming levels. In 18.4% to 47.4% of the cities, heat-related mortality is projected to equal COVID-19 mortality within 15 years, ranging from +1.0ºC to +3.0ºC of global warming. The vulnerability to climate change varies among regions, with European, Mediterranean, and North American cities experiencing a significant rise in heat-related mortality with higher global warming levels. It is important to note that the given number of years represents the time required to reach COVID-19 mortality. However, unlike the peak and decline of COVID-19, climate change-driven heat-related deaths will persistently worsen unless substantial adaptation measures are taken. This emphasizes the crucial need to integrate climate change into public health discourse and policy.

How to cite: Batibeniz, F., Seneviratne, S. I., Jha, S., Ribeiro, A., Gutierrez, L. S., Raible, C. C., Armstrong, B., Bell, M. L., Lavigne, E., Gasparrini, A., Guo, Y., Hashizume, M., Masselot, P., Pereira da Silva, S., Royé, D., Sera, F., Tong, S., Urban, A., and Vicedo-Cabrera, A. M. and the Multi-Country Multi-City Collaborative Research Network: Urgency of Climate Change through the lens of COVID-19 Pandemic: the case of heat-related mortality, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8234, https://doi.org/10.5194/egusphere-egu24-8234, 2024.

EGU24-8342 * | Orals | NH1.1 | Highlight

Global assessment of atmospheric and land surface drivers of heatwaves 

Yigit Uckan, Melissa Ruiz-Vasquez, Kelley De Polt, and Rene Orth

Heatwaves are extreme weather events characterized by exceptionally high temperatures that have severe impacts on society and ecosystems. Their magnitude and frequency are increasing with climate change in many regions. They are driven by both atmospheric and land surface processes such as advection or reduced evaporative cooling. The contributions of these individual drivers to the formation of heatwaves have been analyzed in case studies for major past events with model experiments. At the same time, the global relevance of heatwave drivers remains unclear.

We perform a global analysis with reanalysis data to determine the relation of heatwave temperatures to (i) atmospheric variables such as wind, pressure, and pressure differences, each at different geopotential heights, as well as (ii) land surface variables such as evaporative fraction, enhanced vegetation index, and surface net radiation. First, we identify the hottest day in each grid cell during the period 2001-2020. We also determine the values of the driver variables on this day. Then, for each driver variable, we select five days from the entire study period where the variables’ value most closely matched the hottest day value (=analogues). Next, we compare the averaged temperature anomalies of these analogues to those of the hottest day. The more similar the analogue temperature anomalies are (=hotter), the more relevant the driver variable is deemed. This is done for the three hottest days in each grid cell, ensuring that they are at least 15 days apart from each other to belong to separate heatwave events. 

The results show that pressure at the 500 hPa level is the most relevant driver of heatwaves in the mid-latitudes, while in the tropics a combination of variables plays a more important role than individual variables. Radiation is the second most relevant driver in many regions, particularly in tropical areas. In most cases, several drivers seem to contribute to the heatwave events such that only their aggregated analogue temperature anomalies can match the observed anomalies. These findings confirm previous case studies which highlighted the relevance of atmospheric circulation patterns such as blocking as well as reduced evaporation related to vegetation water stress. For the first time we identify the relevance of these processes across the globe, and with observation-based data. This can contribute to a better management and potential mitigation of heatwave temperatures and their impacts.



How to cite: Uckan, Y., Ruiz-Vasquez, M., De Polt, K., and Orth, R.: Global assessment of atmospheric and land surface drivers of heatwaves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8342, https://doi.org/10.5194/egusphere-egu24-8342, 2024.

EGU24-8448 | ECS | Posters on site | NH1.1 | Highlight

 Beyond Ambient Temperature: A Comparative Analysis of Heat Metrics for Detecting Heatwaves on a Country Level 

Tobias Monthaler, Katharina Wieser, and Chloe Brimicombe

Ambient temperature is the standard metric for the detection of heatwaves. However, when considering the impacts on humans the severity in terms of our wellbeing may be underestimated. The field of detecting human-perceived heatwaves is new and fast growing. It is important to recognise the difference in measuring heatwaves using heat metrics in comparison to the standard of ambient temperature. For this approach we develop an algorithm to track heatwaves on a country level through time for the last 30 years. Maximum daily temperature data is used in comparison to the heat metrics of WBGT and UTCI. Through all this, a substantiated knowledge basis should be established of how well the stated heat metrics are detecting heatwave impacts. The findings contribute to the development of standardized and robust approaches for utilizing reanalysis data in conjunction with heat indices, ultimately improving heatwave detection, forecasting and policy development.

How to cite: Monthaler, T., Wieser, K., and Brimicombe, C.:  Beyond Ambient Temperature: A Comparative Analysis of Heat Metrics for Detecting Heatwaves on a Country Level, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8448, https://doi.org/10.5194/egusphere-egu24-8448, 2024.

EGU24-8713 | ECS | Orals | NH1.1

Future Exposure to Extreme Heat in Southeast Asia 

Sonali Manimaran, Dennis Wagenaar, Christine Nam, Ludwig Lierhammer, Laurens Bouwer, and David Lallemant

Southeast Asia has seen an increasing trend in extreme temperatures, with records of the highest surface air temperature being set in recent years. Heat waves are also increasing in frequency, severity and duration, with higher maximum temperatures being recorded both in daytime and nighttime. These trends are expected to intensify in the coming decades with climate change, with many implications for human health. For Southeast Asia, however, the number of studies quantifying future heat hazards and exposure are severely limited, but first analyses show that several countries in the region could see dramatic shifts in risk due to climate change. Therefore, it is imperative to quantify the heat stress that populations will be exposed to due to future extremes in the region. To this end, this study uses projections from Regional Climate Models to compute the Wet Bulb Globe Temperature (WBGT) and Universal Thermal Climate Index (UTCI) as measures of extreme heat. WBGT has been widely used in studies of extreme heat and impacts, particularly in the case of outdoor physical work, and has been shown to be representative of heat stress in hot and humid environments, such as Southeast Asia. On the other hand, the UTCI is a newer metric which has been demonstrated to be applicable in a range of climatic conditions and representative of the human physiological response. Using the novel CORDEX-CORE dataset for Asia, WBGT and UTCI metrics for Southeast Asia are developed at a 22x22 km resolution up till 2100 using a wide range of ensemble simulations. Future population exposure to extreme heat is then computed for each country in the region, across a range of Shared Socioeconomic Pathway (SSP) scenarios. Our first results show that nearly the entire region will experience strong heat stress by mid-century and some countries will experience strong heat stress for most of the year by the end of the century.

How to cite: Manimaran, S., Wagenaar, D., Nam, C., Lierhammer, L., Bouwer, L., and Lallemant, D.: Future Exposure to Extreme Heat in Southeast Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8713, https://doi.org/10.5194/egusphere-egu24-8713, 2024.

EGU24-9026 | ECS | Orals | NH1.1

The compound effect of acute respiratory infections and temperatures on mortality in the Czech Republic, 1982–2019 

Ekaterina Borisova, Aleš Urban, Hana Hanzlíková, Eva Plavcová, Jan Kyselý, Jan Kynčl, and Joan Ballester

Numerous studies have thoroughly documented the contribution of non-optimal temperatures and acute respiratory infections (ARIs) to increased mortality. However, there is still a gap in understanding how these factors interact together to affect human mortality during the cold season, and how this impacts population susceptibility to heat waves in the summer.

In this study we conduct an analysis over a period spanning 38 years (1982–2019), utilizing: a) daily all-cause mortality counts across the Czech Republic, b) daily proxies of acute respiratory infections (ARIs) incidence, interpolated from weekly healthcare surveillance data, and distinguished regarding three dominant influenza viruses (A/H3N2, A/H1N1, and B), and c) a suite of weather variables, sourced from E-OBS gridded data, including daily mean, maximum, and minimum temperatures, daily precipitation, daily mean sea level pressure, daily mean wind speed, daily mean relative humidity, and radiation level.

To investigate the complex associations between mortality rates, ARI incidence, and weather variability, we employ a distributed lag non-linear model (DLNM) with multiple cross-bases. This approach facilitates the adjustment for confounding meteorological variables and provides a better understanding of their impact as fluctuating confounders. From these refined models, we derived the fraction of mortality attributable to ARIs and low temperatures, offering a quantification of their impact on excess mortality in the cold season. Additionally, we analyse changes in seasonal patterns of mortality according to the meteorological and epidemiological characteristics and assess temporal associations between air temperature and mortality in summer considering factors like intensity of ARI outbreaks and the mean winter temperature in the previous cold season. Our results contribute to better understanding of the links between temperature variability, respiratory infection dynamics and the seasonal variations in mortality.

How to cite: Borisova, E., Urban, A., Hanzlíková, H., Plavcová, E., Kyselý, J., Kynčl, J., and Ballester, J.: The compound effect of acute respiratory infections and temperatures on mortality in the Czech Republic, 1982–2019, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9026, https://doi.org/10.5194/egusphere-egu24-9026, 2024.

In recent years, the escalation of climate change has led to a discernible increase in occurrences of extreme heat events, subjecting individuals to heightened and more recurrent heat stress. This phenomenon is particularly pronounced among socioeconomically disadvantaged populations, the elderly, and other vulnerable groups. Prolonged exposure to elevated temperatures has been identified as a significant factor contributing to adverse health outcomes within these demographics. Concurrently, alterations in land use and land cover (LULC) exert a notable influence on the thermal environment. While rural areas experience relatively modest changes in land use compared to urban counterparts, the expansion of non-vegetative zones in these regions still engenders temperature fluctuations. 

This study endeavors to ascertain the spatial-temporal characteristics of the thermal environment and heat-related comfort levels in aging rural areas, a facet that has been largely overlooked in prior research. The focal area of investigation is Yunlin County in Taiwan, a pivotal agricultural region characterized by a noteworthy aging demographic. The research methodology involves an analysis of the spatial distribution of meteorological parameters to discern the thermal landscape in Yunlin. Additionally, a thermal comfort index, Physiological Equivalent Temperature (PET), is employed to gauge the impact of spatial characteristics on human comfortability within this aging rural enclave. LULC data are acquired through supervised classification of remote sensing images. The computation of PET and associated parameters in the Yunlin region is facilitated by the Python package, Pythermalcomfort. 

The analysis reveals thermal comfort and environmental conditions for the elderly in Yunlin, identifying specific hotspots and periods characterized by elevated PET. Notably, the influence of LULC on thermal conditions is discerned, with built-up and bare soil areas exhibiting elevated temperatures. Furthermore, projections of future scenarios indicate an escalating trend of discomfort for the elderly, manifesting in a heightened frequency of PET exceeding 42°C. The study also undertakes an exposure analysis to identify individuals susceptible to heat injuries under diverse scenarios. Ultimately, a set of preventive measures and recommendations are delineated, encompassing the augmentation of green spaces, provision of adequate shading, identification of cooler areas during heatwaves, and scheduling physically demanding activities during cooler hours (between 4:00 and 7:00). In summation, this research utilizes PET to pinpoint high-risk periods and locations for aging rural areas in Yunlin during the summer, with the overarching aim of furnishing valuable insights into heat-related risks.

How to cite: Juang, J.-Y.: Examining the temporospatial patterns of thermal risk for the elderly in an aging rural area in Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9262, https://doi.org/10.5194/egusphere-egu24-9262, 2024.

EGU24-11600 | ECS | Orals | NH1.1

Assessment of heat exposure under a high-end climate change scenario and projected population scenario around Africa’s Lake Victoria region. 

Delphine Ramon, Clare Heaviside, Oscar Brousse, Charles Simpson, Irene Amuron, Eddie Jjemba, Jonas Van de Walle, Wim Thiery, and Nicole P.M. van Lipzig

Recent global temperature increases and extreme heat events have raised concerns about their impact on health. The area surrounding Lake Victoria, accommodating over 45 million people and ranking among Africa's most densely populated regions, faces rapid population growth and urbanization, set to double its population by 2050 compared to 2022 for most countries in the region. Global-scale projections indicate a potential amplification in heat stress, reaching levels up to 200 times the current rates under high-end scenarios, with the Democratic Republic of the Congo and Uganda facing the most pronounced impacts. Children born in this area in 2020 may face about 1.4 times more heatwaves than their counterparts elsewhere. The combination of population growth and intensifying heat renders the region around the Lake Victoria particularly susceptible to future heat stress.

This research investigates the impacts of climate and population changes on heat exposure and heat stress in the region surrounding Lake Victoria. We analyze how dangerous heat stress by the end-of-the century could change under the ensemble mean climate change signal of the high-end SSP5-8.5 climate change scenario compared to the recent past. Furthermore, we evaluate to what extent and where the population could be affected by dangerous heat stress by these changes. Climate model simulations performed with the COSMO-CLM regional climate model at 0.025° are used, forced with ERA-5 data, applying a pseudo global warming approach for the end-of-century run. Dangerous heat stress is assessed based on categories of heat index and humidex heat stress metrics.

Results indicate a substantial rise in dangerous heat stress across the region. By the 2080s, up to 122 million people (i.e. 44% of the projected population) may experience dangerous heat stress for over 5% of the year (i.e. ~18 days), in contrast to an estimated 1 million people (i.e. 1% of the population) in 2010. Moreover, around 28% of the population (i.e. ~78 million people) might face such dangerous heat for 15% of the time (i.e. ~55 days) by the 2080s. The inhabitants most exposed to dangerous heat stress are notably clustered along the northern shores of Lake Victoria and the southern region, including their urban areas. These findings emphasize the urgent need to address the escalating threat of dangerous heat stress in this region.

How to cite: Ramon, D., Heaviside, C., Brousse, O., Simpson, C., Amuron, I., Jjemba, E., Van de Walle, J., Thiery, W., and van Lipzig, N. P. M.: Assessment of heat exposure under a high-end climate change scenario and projected population scenario around Africa’s Lake Victoria region., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11600, https://doi.org/10.5194/egusphere-egu24-11600, 2024.

EGU24-14155 * | ECS | Orals | NH1.1 | Highlight

Mortality burden in 35 European countries attributed to anthropogenic warming during the record-breaking summer of 2022  

Thessa M Beck, Dominik L Schumacher, Ana M Vicedo Cabrera, Sonia I Seneviratne, Hicham Achebak, and Joan Ballester

More than 61,000 heat-related deaths were associated with the record-breaking temperatures in Europe during the summer of 2022. In this study, we quantify the number of heat-related deaths that would have been avoided in the absence of anthropogenic warming.

For this study, we utilize epidemiological models calibrated for the period 2015–2019 to estimate the heat-related mortality burden in the summer of 2022 for the factual and counterfactual scenario. We derive a counterfactual scenario by removing the regional summer mean warming that arises in response to rising global mean temperatures from the factual temperatures. We use ERA5-Land temperature data and mortality counts from the Eurostat database to estimate the heat-related deaths across 823 distinct administrative regions spanning 35 European countries. 

At 1.15 °C of global warming since pre-industrial times, we obtain a population-weighted median increase over all regions in Europe of more than 2 °C in summer mean temperatures, with the Mediterranean regions being most affected by the increase. By comparing the factual and counterfactual heat-related mortality, we estimate that approx. 70% [95th CI 53.33%– 82.17%] of the total heat-related deaths would not have occurred without anthropogenic warming. Southern Europe has been the most affected by dangerous heat and consequently features the highest number of heat-related deaths attributable to climate change [64.19% of the climate change-attributable deaths]. In relative terms, however, the impact of anthropogenic warming is strongest in Central Europe where approx. 78% of the heat-related deaths are attributable to anthropogenic warming.

How to cite: Beck, T. M., Schumacher, D. L., Vicedo Cabrera, A. M., Seneviratne, S. I., Achebak, H., and Ballester, J.: Mortality burden in 35 European countries attributed to anthropogenic warming during the record-breaking summer of 2022 , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14155, https://doi.org/10.5194/egusphere-egu24-14155, 2024.

EGU24-14273 | ECS | Posters on site | NH1.1

Heat, humidity and health impacts: How causal diagrams can help tell the complex story 

Sidharth Sivaraj, Jonathan Buzan, Olivia Romppainen-Martius, and Ana M. Vicedo-Cabrera

The global health burden associated with exposure to heat is a grave concern and is projected to further increase under global warming. While physiological studies have demonstrated the role of humidity alongside temperature in exacerbating heat stress for humans, epidemiological findings remain conflicted to date. Understanding the intricate relationships between heat, humidity, and health outcomes are crucial for future adaptation and mitigation. This project introduces 'directed acyclic graphs' (DAGs) as causal models to elucidate the analytical complexity in observational epidemiological studies focusing on humid heat related health impacts. DAGs are employed to delineate implicit assumptions often overlooked in such studies, depicting humidity as a confounder, a mediator, or an effect modifier. The complexities arising from using composite heat-stress indices such as wet-bulb temperature, emphasizing the limitations induced in extracting individual effects of humidity are also portrayed through DAGs. Theoretical generalisations for regression models corresponding to each of the causal assumptions are also discussed. The goal of the study is not to prioritize one causal model, but to explicitly discuss the potential causal models suitable for representing associations between heat, humidity, and related health impacts. In the process, we highlight the implications of selecting one model over another. The project aims to inspire further quantitative studies on the topic and motivate researchers to explicitly characterize the assumptions underlying the analytical models with DAGs, facilitating accurate interpretations of the findings. This extends beyond analysing the role of humidity in heat-related health impacts, encompassing similarly complex research questions associated with other compound events.

How to cite: Sivaraj, S., Buzan, J., Romppainen-Martius, O., and Vicedo-Cabrera, A. M.: Heat, humidity and health impacts: How causal diagrams can help tell the complex story, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14273, https://doi.org/10.5194/egusphere-egu24-14273, 2024.

EGU24-15322 | Orals | NH1.1 | Highlight

The Role of Rainfall in Humid Heat Extremes across the Global Tropics 

Lawrence Jackson, Cathryn Birch, Guillaume Chagnoud, John Marsham, and Christopher Taylor

Extreme humid heat poses a serious risk to human health, reducing the body’s ability to cool itself through sweating. The impact on humans will increase under climate change, particularly in tropical regions, such as the Indian subcontinent, that are highly populated and already hot and humid. Whilst there is a growing body of research on dry-bulb temperature extremes, there is limited understanding of the meteorological drivers of humid heat extremes, particularly the role of moisture transport, rainfall, and evaporation of moisture from the Earth’s surface.

In this study, we use ERA5 data to identify and analyse extreme humid heat events in the global tropics during 1993-2022. In particular, we focus on the relationship between rainfall and the occurrence of humid heat and use extremes in wet-bulb temperatures to define the humid heat events.

We find that rainfall is a key driver of humid heat extremes across much of the global tropics. In monsoon regions, dry-bulb temperature extremes typically occur in the pre-monsoon period whereas wet-bulb extremes occur more frequently during the monsoon season. The role of rainfall varies between humid heat events characterised by extremes in dry-bulb temperature versus those characterised by extremes in humidity. In much of the global tropics, rainfall followed by a few days of dry clear weather primes the surface and boundary layer climates for the initiation of humid heat events. These events typically have extremes in dry-bulb temperatures accompanied by what we characterise as a sufficiently high level of humidity. In arid regions, away from irrigated areas, rainfall is critical for the initiation of humid heat and frequently occurs locally on the first day of humid heat events. These events typically have extremes in humidity whereas dry-bulb temperatures are less likely to be extreme.

These findings are a step towards greater understanding of the meteorological drivers of humid heat extremes at the regional scale. They will be valuable in the evaluation of weather and climate models, will aid the use and interpretation of climate model projections, and ultimately inform the design of much needed early warning systems for humid heat extremes.

How to cite: Jackson, L., Birch, C., Chagnoud, G., Marsham, J., and Taylor, C.: The Role of Rainfall in Humid Heat Extremes across the Global Tropics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15322, https://doi.org/10.5194/egusphere-egu24-15322, 2024.

EGU24-15748 | ECS | Posters virtual | NH1.1

Building a heat wave anticipatory action plan for the Sahelian city of Ouagadougou 

Rachidate Wend-layolsda D. Somdakouma, Bakari Sankara, Ilyassa Sawadogo, Emmanuel Poan, Dorothy Heinrich, and Kiswendsida Guigma

The West African Sahel is one of the hottest regions of the globe, but as in other African regions, heat waves largely remain a neglected hazard from both a preparedness and a research perspective. They are deadly and underestimated. Yet, there is a large potential to decrease their impacts through early warning and anticipatory action, particularly because they are so predictable. In this research, we present a case study of the development of a heat wave early action protocol for the Sahelian city of Ouagadougou, Burkina Faso. The work was led by the Burkina Faso Red Cross (BFRC), with support from the Red Cross Red Crescent Climate Centre and partners. Two research questions guided the process: (i) are heat waves a concern to various actors in the city of Ouagadougou and if so, why? (ii) What are the impacts of heatwaves in Ouagadougou and what can be done to mitigate them?

In collaboration with the National Meteorological Agency (ANAM), the first ever definition for heat waves in the city of Ouagadougou was developed based on statistical analyses of meteorological records and reports of historical severe events. Heat waves were thus defined as spells of three or more days where the daytime and/or night-time temperature exceeds the 90th percentile of the distribution of the hottest month of the year i.e. April in Ouagadougou. This definition has now been incorporated by ANAM into its early warning platform and will automatically alert BFRC when needed.

Faced with the lack of quantitative impact data about heatwave impacts in the Sahel region, a qualitative cross-sectional study based on focus group discussions, and key informant interviews, and a review of grey literature (especially media reports) were used. The target audience population for this study was experts/practitioners from various disaster management sectors including health, water, energy and municipal officers, vulnerable social groups and vulnerable communities living in slums.

Experts, practitioners, vulnerable social groups and communities all stressed that extreme heat is a major concern in Ouagadougou, has become more severe in recent years and should be better tackled at the individual, community and national levels. The elderly, children under the age of five and people suffering from chronic diseases such as albinism, leprosy and other conditions were frequently mentioned by interviewees as the most vulnerable to extreme heat. From a geographical perspective,

slums, which are generally located in the periphery of the city, were identified as the most vulnerable neighbourhoods, mainly because of the poverty rates and the lack of infrastructures. The most recurrent impacts found across the study were around insufficient water and power availability, increase in some diseases, thermal discomfort and subsequent social and economic impacts. Among the suggested solutions, BFRC and their partners have decided to prioritise in the Early Action Protocol: early warning dissemination, potable water distribution, medical monitoring of chronically ill people and cash distribution.

Keywords: heat waves, Ouagadougou, slums, anticipatory action, Red Cross

How to cite: Somdakouma, R. W.-D., Sankara, B., Sawadogo, I., Poan, E., Heinrich, D., and Guigma, K.: Building a heat wave anticipatory action plan for the Sahelian city of Ouagadougou, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15748, https://doi.org/10.5194/egusphere-egu24-15748, 2024.

EGU24-17242 | ECS | Posters on site | NH1.1 | Highlight

Limits to adaptation strategies for heat impacts on rural labors filtered through stabilized climate mitigation scenarios.  

Jonathan Buzan, Yona Silvy, Fabrice Larcoix, Friedrich Burger, Jens Terhaar, Thomas Frölicher, Édouard Davin, and Fortunat Joos

With global warming, increased heat stress will substantially impact the rural labor force. Understanding and quantifying this impact is difficult, especially due to regional differences: Does the temperature increase? Is there more solar exposure? Does humidity respond non-linearly with respect to temperature changes? Furthermore, humans are resourceful, and local environments could provide adaptation methods to decrease heat impacts.

 

A policy-relevant assessment in the context of the Paris Agreement is even more difficult with existing CMIP-type simulations with prescribed greenhouse gas trajectories that lead to a different and often non-stable warming for each model. To resolve the impacts climate mitigation and adaptation on heat stress on warming levels with specific relevance for the Paris Agreement, we use the Community Earth System Model (CESM2) driven by emissions from the Adaptive Emissions Reduction Approach (AERA) to generate climate mitigation scenarios stabilized at 1.5°C, 2.0°C and 3.0°C of global warming.

 

One form of adaptation to heat stress impacts is to use the local environment for cooling. Within CESM2, we compare the direct and indirect exposure to solar radiation within the vegetated canopy as an inexpensive form adaptation. To diagnose the heat stress conditions we use the International Organization for Standardization (ISO) 7243, the Wet Bulb Globe Temperature (WBGT), realized by first principles representation of the globe, dry bulb, and natural wet bulb thermometers utilizing CESM2’s temperature, humidity, winds, and radiation. The WBGT values are transformed into labor capacity using standardized algorithms (e.g. NIOSH or Lancet) and the above canopy (no adaptation) and below canopy (with adaptation) labor capacity are directly compared to each other.

 

We show that the potential to adapt by using the local environment for cooling is not uniform across regions. For example, evaluating the hottest seasonal period (defined as a local summer), at the 3.0°C mitigation scenario in equatorial Southeast Asia, adaptation can save up to 50% of total labor capacity losses. However, in northern South Asia, adaptation saves only 10% of the seasonal labor capacity losses. These results demonstrate that rural laborers in some locations may have limited capacity to adapt to differing global mitigation strategies and may require mechanical cooling or other expensive forms of adaptation.

How to cite: Buzan, J., Silvy, Y., Larcoix, F., Burger, F., Terhaar, J., Frölicher, T., Davin, É., and Joos, F.: Limits to adaptation strategies for heat impacts on rural labors filtered through stabilized climate mitigation scenarios. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17242, https://doi.org/10.5194/egusphere-egu24-17242, 2024.

EGU24-17545 | Orals | NH1.1 | Highlight

Development of a deep learning based system for heatwave detection using seasonal forecast data 

Fatemeh Heidari, Qing lin, Yanet Díaz Esteban, Edgar Espitia Sarmiento1, and Elena Xoplaki

Heatwaves have been widely studied in recent years because of their major impact on human health, mortality, ecosystems, agriculture, and the economy. Globally, heatwaves are becoming more severe, longer, and recurrent with global temperature rise. Therefore, the study of heat waves and the development of an early warning system for prediction of regional heatwaves help climate preparedness and decision-making. In this research, we propose a heatwave prediction algorithm based on a deep learning model, a convolutional neural network (CNN). This CNN model is trained with reanalysis data ERA5 and real heatwave events from EMO observation data for years from 1993 to 2021. We illustrate the relationship between the patterns in geopotential height at 500 hpa (GPH), sea surface temperature (SST), and the real heatwaves that happened in the last 20 years. This study employs the hindcast data from SEAS5.1 with 25 ensemble members, available at C3S. GPH and SST from observation data are input to the model and the heatwave magnitude at every single grid point is the output. The heatwave is defined as a period of three or more consecutive hot days and nights when the daily maximum and minimum temperature (TX/TN) exceeds the long‐term (1993–2022) daily 90th percentile. For estimating the heat wave magnitude we accumulated TX exceedance the local 90th percentile for all heat wave days over a user-defined interval (monthly, seasonal, etc.) as in Zampieri et al. (2017), Toreti et al. (2019). The results show the CNN model using atmospheric circulation fields (SST and GPH) with adjusted parameters is able to forecast extreme events in Europe, and it can potentially enhance the AI-based early warning systems for extreme weather.

Zampieri, M., Ceglar, A., Dentener, F., and Toreti, A. (2017). Wheat yield loss attributable to heat waves, drought and water excess at the global, national and subnational scales. Environmental Research Letters, 12 (6), 064008. doi:10.1088/1748-9326/aa723b

Toreti, A., Cronie, O., and Zampieri, M. (2019). Concurrent climate extremes in the key wheat producing regions of the world. Scientific Reports, 9(1), 5493. doi:10.1038/s41598-019-41932-5

How to cite: Heidari, F., lin, Q., Díaz Esteban, Y., Espitia Sarmiento1, E., and Xoplaki, E.: Development of a deep learning based system for heatwave detection using seasonal forecast data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17545, https://doi.org/10.5194/egusphere-egu24-17545, 2024.

EGU24-18354 | ECS | Orals | NH1.1 | Highlight

Projecting heat-related excess mortality under climate change scenarios in Europe: A multi-domain analysis 

Hélder Relvas, Silvia Coelho, Vera Rodrigues, Ana Isabel Miranda, Myriam Lopes, Daniel Graça, Bruno Augusto, João Basso, and Joana Ferreira

Recent studies have highlighted the diverse health consequences associated with climate change. However, a comprehensive evaluation of the specific susceptibilities of individuals and cities to these changes remains lacking. Addressing this gap, our study offers insights into potential excess mortality risks attributable to heat-related events under various climate change scenarios across diverse European regions, within the framework of the European Project DISTENDER.

The primary objective of this research is to assess the potential impact of climate change scenarios, specifically Shared Socioeconomic Pathways (SSPs) SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, on heat-related excess mortality in a range of European locations. Focusing on Austria, the EURAF domain (encompassing parts of Portugal and Spain), a region in the Netherlands, the metropolitan area of Turin (Italy), and the urban area of Guimarães (Portugal), our investigation spans varied socio-geographic domains.

By employing local-specific relative risk functions and daily average temperature data spanning 2015 to 2049, derived through statistical downscaling from CanESM5, EC-EARTH3, and MPI-ESM1-2-HR global climate models, our analysis encompasses resolutions ranging from 9000 to 500 meters, depending on the specific domain. This multidomain approach allows for capturing localized variations in climate impacts with high spatial resolution.

The significance of our findings lies in their contribution to informing adaptive strategies, public health policies, and urban planning efforts aimed at mitigating the effects of climate change on vulnerable populations. Preliminary results indicate a distinct upward trend in heat-related excess mortality over the years, with the highest values observed for SSP5-8.5. Furthermore, there exists considerable variability among climate models.

Acknowledgements:

The authors would also like to acknowledge the support of CESAM (UIDP/50017/2020 + UIDB/50017/2020 + LA/P/0094/2020) and C2TN (UIDB/04349/2020). Thanks are due to the DISTENDER Project (Grant agreement ID: 101056836). Thanks are due to FCT/MCTES for the contract granted to Helder Relvas (10.54499/2021.00185.CEECIND/CP1659/CT0026).

How to cite: Relvas, H., Coelho, S., Rodrigues, V., Isabel Miranda, A., Lopes, M., Graça, D., Augusto, B., Basso, J., and Ferreira, J.: Projecting heat-related excess mortality under climate change scenarios in Europe: A multi-domain analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18354, https://doi.org/10.5194/egusphere-egu24-18354, 2024.

EGU24-18980 | Posters on site | NH1.1

So, will you live an unprecedented life? 

Wim Thiery

Under a continued increase in global warming, extreme events such as heatwaves will further rise in frequency, intensity, and duration over the next decades. Climate change impact studies routinely assess hazard and exposure change across discrete time windows, but thereby ignore how vulnerability and climate risk evolve across a person’s lifetime. Conversely, demographic research has a long tradition of assessing population processes and vulnerability from a cohort perspective, but generally neglects climate impacts. 

In the soon-to-start ERC CoG project LACRIMA (LAgrangian Climate Risk and Impact Attribution), we will develop novel concepts and methodologies to express climate change impacts and risk from a cohort perspective. More specifically, the project pursues to (i) to reconstruct two iconic climate change impacts on people around the world using machine learning (heat-related mortality and burned area), (ii) to uncover age-specific vulnerability to climate extremes including heatwaves, wildfires, river floods, droughts, tropical cyclones, and crop failures, (iii) to detect and attribute changes in lifetime extreme event exposure and climate impacts on mortality across generations and regions, (iv) to quantify how these attributable cohort impacts change country-level life expectancy around the world under a range of warming scenarios, and finally (v) to project how lifetime exposure to extreme events including compound events may trigger irreversible impacts under scenarios of temporary overshooting of long-term warming targets.

By bridging physical climate science, demography, and planetary health, LACRIMA will comprehensively identify whether and where people will live an unprecedented life in terms of climate impacts, and how mitigation choices can alter the climate change burden on current young generations around the world

How to cite: Thiery, W.: So, will you live an unprecedented life?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18980, https://doi.org/10.5194/egusphere-egu24-18980, 2024.

EGU24-19866 | ECS | Orals | NH1.1 | Highlight

Developing a proof-of-concept within Destination Earth for heat-stress adaptation under climate change scenarios, with a special focus on public health management 

Joshua Lizundia-Loiola, Nieves Peña, Efren Feliu, Jorge Paz Jiménez, Niels Souverijns, Dirk Lauwaet, and Filip Lefebre

According to the World Health Organization, between 2000 and 2016, the number of people exposed to heat waves increased by around 125 million. In Europe in 2003, 70.000 people died as a result of the June-August events and in Spain, that summer produced a total of 6.534 deaths.  2022 summer was even worst and its record-breaking heat caused 61.672 deaths in Europe, 11.324 of them in Spain, according to Ballester et al. (2023) [1].

The most worrying thing is not that all these episodes confirm the global warming, but that what is coming is even worse. If greenhouse gas emissions are not significantly curtailed, extreme temperatures and specifically heatwaves will become more frequent, more intense and longer every year that coupled with urban population growth and the trend towards an ageing population will produce devastating impacts on human health especially on vulnerable populations (see  https://www.eea.europa.eu/publications/europes-changing-climate-hazards-1/heat-and-cold/heat-and-cold-extreme-heat). Impacts will depend on local factors related with exposure, vulnerability to climate-related stresses and the capacity to cope with, so well-prepared health systems and well-suited adaptation measures at different levels are essential to protect populations, limit adverse impacts of heat and therefore reduce the magnitude of their risks.

Current information and heat simulation models are limited in time and space due to the high computational costs, so sometimes make it too complex for multiple stakeholders to have a good understanding of heat-stress assessment. This situation leads to ambiguity among stakeholders when implementing adaptation measures.  The idea of this ongoing work is to use Destination Earth’s Climate Adaptation digital twin to develop an interactive tool that will support decision-makers in the assessment of different adaptation options for heat stress adaptation under climate change scenarios, with a special focus on public health management. The tool will allow to have a better understanding of heat-stress assessment by simulating different type of climate change scenarios and, hence, identifying hotspot areas, and high-risk populations and locating opportunities to incorporate solutions to reduce impacts.

The architecture of DestinE provides a unique opportunity to develop an operational environment in which different but interconnected components give guidance and advice to decision makers in their process of designing adaptation pathways. From the data provided by Destination Earth Data Lake, it will be developed a proof-of-concept over the Basque region based on data-driven statistical models, physically based simulations, cost-impact analysis and algorithms. The demonstrator will also include a web-based graphical interface providing easy and accessible dashboards to support decision-makers in the assessment of adaptation options for heat stress adaptation under different climate change scenarios.
Key words: Destination Earth, Climate Adaptation digital Twin, heat-stress, adaptation, health, Copernicus, Europe. 


1. Ballester, J., Quijal-Zamorano, M., Méndez Turrubiates, R.F. et al. Heat-related mortality in Europe during the summer of 2022. Nat Med 29, 1857–1866 (2023). https://doi.org/10.1038/s41591-023-02419-z

How to cite: Lizundia-Loiola, J., Peña, N., Feliu, E., Paz Jiménez, J., Souverijns, N., Lauwaet, D., and Lefebre, F.: Developing a proof-of-concept within Destination Earth for heat-stress adaptation under climate change scenarios, with a special focus on public health management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19866, https://doi.org/10.5194/egusphere-egu24-19866, 2024.

EGU24-20179 | Orals | NH1.1

Heat waves and health impacts in the northern part of Senegal: implementation of an early warning system to support Health National Adaptation Plan (HNAP) 

Ibrahima Sy, Birane Cissé, Babacar Ndao, Mory Touré, Abdoul Aziz Diouf, Mamadou Adama Sarr, and Ousmane Ndiaye

The Sahelian zone of Senegal experienced heat waves in the previous decades, such as 2013, 2016 and 2018 that were characterised by temperatures exceeding 45°C for up to 3 successive days. The health impacts of these heat waves are not yet analysed in Senegal although their negative efects have been shown in many countries. This study analyses the health impacts of observed extreme temperatures in the Sahelian zone of the country, focusing on morbidity and mortality by com[1]bining data from station observation, climate model projections, and household survey to investigate heat wave detection, occurrence of climate-sensitive diseases and risk factors for exposure. To do this, a set of climatic (temperatures) and health (morbidity, mortality) data were collected for the months of April, May and June from 2009 to 2019. These data have been completed with 1246 households’ surveys on risk factor exposure. Statistical methods were used to carry out univariate and bivariate analyses while cartographic techniques allowed mapping of the main climatic and health indicators. The results show an increase in temperatures compared to seasonal normal for the 1971–2000 reference period with threshold exceed[1]ances of the 90th percentiles (42°C) for the maxima and (27°C) the minima and higher temperatures during the months of May and June. From health perspective, it was noted an increase in cases of consultation in health facilities as well as a rise in declared morbidity by households especially in the departments of Kanel (17.7%), Ranérou (16.1 %), Matam (13.7%) and Bakel (13.7%). The heat waves of May 2013 were also associated with cases of death with a reported mortality (observed by medical staf) of 12.4% unequally distributed according to the departments with a higher number of deaths in Matam (25, 2%) and in Bakel (23.5%) than in Podor (8.4%) and Kanel (0.8%). The morbidity and mortality distribution according to gender shows that women (57%) were more afected than men (43%). These health risks have been associated with a number of factors including age, access to drinkable water, type of fuel, type of housing and construction materials, existence of fan and an air conditioner, and health history.The heat wave recurrence has led to a frequency in certain diseases sensitive to rising temperatures, which is increasingly a public health issue in the Sahelian zone of Senegal. The main scientific evidence and findings generated from this research initiative support the adaptation options of health national adaptation plan (HNAP) with the implementation of an early warning system for local communities and health system workers.

Keywords: Climate · Temperature · Heat waves · Diseases · Health risks, adaptation, Senegal

How to cite: Sy, I., Cissé, B., Ndao, B., Touré, M., Diouf, A. A., Sarr, M. A., and Ndiaye, O.: Heat waves and health impacts in the northern part of Senegal: implementation of an early warning system to support Health National Adaptation Plan (HNAP), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20179, https://doi.org/10.5194/egusphere-egu24-20179, 2024.

Employing seasonal forecasting in the domain of impact and risk assessment is particularly beneficial. It facilitates early warning systems and proactive adaptation strategies, which are essential for minimizing the adverse effects of heat waves. This proactive approach is crucial for public health, urban planning, and disaster management, where timely information can significantly alter response strategies and mitigation measures.

This study, we underscore the value of integrating high-quality climate data with impact assessment models. It demonstrates how bridging the gap between climate science and practical risk management can lead to more effective and informed decision-making processes in the face of climate change challenges.

In our study, we integrate Copernicus seasonal forecasting data with the CLIMADA platform, adopting a forward-looking approach to assess the potential impacts of heat waves on populations. This integration involved developing a bespoke pipeline to seamlessly bridge the gap between raw forecasting data from Copernicus and the analytical capabilities of CLIMADA, an ETH Zurich-developed tool for climate impact and risk assessment. The focus is not only on facilitating data integration but also on automating the processing and communication of results.

One significant aspect of this work is managing extensive datasets containing multiple simulations. To efficiently handle this, we implemented an automated system for data extraction, transformation, and loading. This is crucial in maintaining the integrity and usability of the data within CLIMADA's impact modeling framework. Part of this process also entailed resolving spatial and temporal alignment issues, a step essential to ensuring the ability of the seasonal forecasting data to reflect the potential heat wave impacts. Our approach aim to streamline the complexities of large-scale climate data, enhancing the precision and effectiveness of our assessments.

Building a pipeline that links these probabilistic forecasting with impact assessment tools has multiple benefits. It enhances the capability to identify critical data needs and model improvements, thus fostering a feedback loop that drives data and model refinement. Furthermore, it contributes to laying the groundwork for the effective use of the next generation of seasonal forecast data, potentially transforming how we prepare for and adapt to climate risks.

How to cite: Araya, D., Kropf, C. M., and Bresch, D. N.: Integrating Copernicus Seasonal Forecasting Data with CLIMADA for Heat Wave Impact Analysis: Challenges and Solutions in Pipeline Development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20478, https://doi.org/10.5194/egusphere-egu24-20478, 2024.

EGU24-108 | Orals | NH1.2

Reconstructing Historical Flood Events: A Monte Carlo-Based Uncertainty Approach 

Ramtin Sabeti, Thomas R. Kjeldsen, and Ioanna Stamataki

Reconstructing historical flood events can offer critical insight into past hydrological responses to extreme weather, informing contemporary flood risk management and infrastructure design. This study employs reverse engineering, based on historical data such as recorded rainfall, flood marks, visual records, and eyewitness accounts to reconstruct a flood event. Historical data was collected by the team during a workshop with the local community. The approach involves hydrological (HEC-HMS) and hydraulic (HEC-RAS) models to simulate the flood event. The July 1968 UK storm, remarkable for record rainfall reaching 175 millimetres within 18 hours, caused extensive devastation in south-west England. This study focuses on reconstructing the 1968 flash flood on the River Chew, notably the peak hydrograph in the village of Pensford. A Monte Carlo simulation approach is used in conjunction with the HEC-HMS and HEC-RAS models to produce a range of potential input hydrographs with uncertainty input parameters (primarily event rainfall and Manning’s roughness) that match the historical evidence.  In particular, the Monte Carlo approach is implemented using a series of Python scripts enabling multiple HEC-RAS simulations to be conducted and the results synthesised in the form of an uncertainty analysis of key parameters such as peak flow. 

How to cite: Sabeti, R., R. Kjeldsen, T., and Stamataki, I.: Reconstructing Historical Flood Events: A Monte Carlo-Based Uncertainty Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-108, https://doi.org/10.5194/egusphere-egu24-108, 2024.

EGU24-395 | ECS | Orals | NH1.2

Beyond Extreme Temperature: Spatiotemporal Analysis of Humid Heat Stress  

Jency Maria Sojan and Jayaraman Srinivasan

Extreme humid heat stress presents significant challenges to human health and productivity. Traditional heat action plans formulated to tackle dry heat stress are insufficient to address the complexities associated with humid heat stress. Furthermore, there is limited quantitative evidence on the evolving patterns of humid heat stress under changing climate. This study investigates the spatiotemporal trends of extreme heat stress across the Global South from 1964 to 2023, distinguishing between dry and humid heat, using high-resolution ERA5 reanalysis hourly data and the Heat Index (HI).

Notably, South Asia and the Middle East experience the highest frequency of extremely humid heat stress. Specific regions in peninsular South Asia have extremely humid heat stress hours from May to June due to persistent high humidity levels. In contrast, western regions of South Asia encounter extreme dry heat stress preceding the monsoon season, followed by a transition to humid heat stress immediately after the onset of the monsoon. The temporal analysis reveals a more rapid increase in the occurrence of extremely humid heat stress compared to that of dry heat stress from May to July over the past 60 years. This underscores the evolving nature of heat stress and the intensification of humid conditions compared to dry ones.

In conclusion, this study advocates for a shift from exclusively addressing dry stress to a comprehensive approach that accounts for the diverse impacts of humid heat stress, particularly on vulnerable populations. This understanding is critical for policymakers to formulate adaptive strategies tailored to the changing landscape of extreme heat stress. 

How to cite: Sojan, J. M. and Srinivasan, J.: Beyond Extreme Temperature: Spatiotemporal Analysis of Humid Heat Stress , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-395, https://doi.org/10.5194/egusphere-egu24-395, 2024.

EGU24-737 | ECS | Posters on site | NH1.2

A database for the outer sizes of tropical cyclones over the Middle Americas 

Adolfo Perez Estrada and Christian Domínguez Sarmiento

Tropical cyclones (TCs) pose a constant threat to populations residing within tropical and subtropical regions. The direct impacts of TCs, such as intense surface winds, storm surge, and heavy precipitation near the center, are well known. However, the indirect effects (e.g, disruption of the upper-level mean wind flow resulting in continental convection, and precipitation associated with cloud bands away from the cyclone's center), are often underestimated.

It is crucial to comprehensively characterize the size of TCs, taking into account both direct and indirect effects, as this new size definition  could improve early warning systems. While various studies employ different parameterizations to describe cyclone size, many of them overlook precipitation. To address this gap, the ROCLOUD technique was developed using  a Python-based algorithm. This algorithm utilizes information on the TC’s position, the extent of cloud bands, and the size of the wind field to define an outersize for TCs located over the oceanic basins in the Middle Americas. In addition to ROCLOUD, we also developed a technique that uses the spatial distribution of TC rainfall to define the outer TC size, named as RPB algorithm. This technique  utilizes a threshold of 2.5 mm in the precipitation satellite products for depicting TC rainfall. Our dual approach provides a comprehensive understanding of TC  sizes, considering the presence of rainfall that can lead to disasters.

Our database shows  external sizes and positions of TCs (recorded every 6 hours) over the North Atlantic (NA) and Eastern Pacific (EP) Oceans during the 2000-2020 period. We got 191 and 336 positions  from the NA and EP basins, respectively. Statistical analysis reveals the coverage of oceanic basins and highlights their differences. We conclude that ROCLOUD offers an operational approximation of the external size of TCs, especially in situations where storms pose a threat to continental regions. The study discusses the utility of both versions of ROCLOUD and RPB for  the Tropical Cyclone Early Warning System over Mexico (EWS-TC), shedding light on the impact of TC sizes that can lead to disasters.

How to cite: Perez Estrada, A. and Domínguez Sarmiento, C.: A database for the outer sizes of tropical cyclones over the Middle Americas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-737, https://doi.org/10.5194/egusphere-egu24-737, 2024.

EGU24-1525 | ECS | Orals | NH1.2

Objective Identification of Tropical Cyclones with Severe Storm Surge Potential for the North-west Pacific 

Xiaoqi Zhang, Gregor C Leckebusch, and Kelvin S Ng

Storm surges caused by tropical cyclones can significantly impact on coastal areas in East Asia, including megacities e.g., in China. To inform effective adaptation and mitigation planning, a robust storm surge hazard assessment is essential. Unfortunately, the real frequency-intensity distribution of relevant storm-surge levels can only be estimated with large uncertainly based on limited historical observations.

This study demonstrates the successful development of a two-step, objective and automated identification and selection approach of storm-surge relevant TCs for large model data sets where no ground truth verification is possible. In our approach, we combine for the first time two established identification and tracking tools originally developed for extra-tropical cyclones and storms and apply these to identify tropical cyclones. In the first step, we adapted the widely used Murray & Simmonds (1991) University of Melbourne tracking scheme (MS-Track) to the specific conditions of TC tracking in the North-west Pacific. In the second step, we apply the windstorm tracking tool WiTRACK to TC-induced severe wind fields to provide and attach the potential storm-surge relevant information in addition to just the core track provided by the MS-Track.

By validating our results with ERA5 reanalysis data and IBTrACS, we show that our method is simple yet has a well comparable performance in detecting and assessing relevant TC events than more complex tracking approaches. Based on this performance this approach is well-designed and specifically intended to specific applications in CAT modelling approaches, e.g. for the creation of physically consistent event sets for storm surges.

How to cite: Zhang, X., Leckebusch, G. C., and Ng, K. S.: Objective Identification of Tropical Cyclones with Severe Storm Surge Potential for the North-west Pacific, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1525, https://doi.org/10.5194/egusphere-egu24-1525, 2024.

The physical mechanisms underlying extreme precipitation events linked to atmospheric moisture transport (IVT-P) are investigated in this study. It investigates changes in synoptic-scale weather patterns over the Indian subcontinent and identifies regions where IVT influences extreme precipitation. The study discovers a strong relationship between daily IVT and precipitation over the core monsoon region and the complex terrains of the Western Ghats and Himalayas. Event Coincidence Analysis reveals that extreme IVT can be used to forecast extreme precipitation in these regions. The dynamic component of moisture transport has a strong influence on daily and extreme precipitation over complex terrains. In contrast, the thermodynamic component has an influence on precipitation over regions with an abundance of water vapor and weak horizontal winds. The study also identifies synoptic features and moisture transport ahead of IVT-P events and finds intense low-pressure anomalies, the transition from ridge to trough patterns, and intense 700 hPa relative humidity in the specified regions. Overall, the study provides insights into the physical mechanisms underlying IVT-linked extreme precipitation events.

How to cite: Raghuvanshi, A. S. and Agarwal, A.: Deciphering the connections between extreme precipitation events, atmospheric moisture transport, and associated synoptic features over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1625, https://doi.org/10.5194/egusphere-egu24-1625, 2024.

EGU24-1631 | ECS | Orals | NH1.2

Shift of soil moisture-temperature coupling exacerbated 2022 compound hot-dry event in eastern China 

Yueyang Ni, Bo Qiu, Xin Miao, Lingfeng Li, Jiuyi Chen, Xiaohui Tian, Siwen Zhao, and Weidong Guo

Compound hot-dry events (CHDEs) are among the deadliest climate hazards and are occurring with increasing frequency under global warming. The Yangtze River Basin in China experienced a record-breaking CHDE in the summer of 2022, causing severe damage to human societies and ecosystems. Recent studies have emphasized the role of atmospheric circulation anomalies in driving this event. However, the contribution of land–atmosphere feedback to the development of this event remains unclear. Here, we investigated the impacts of soil moisture-temperature coupling on the development of this concurrent heatwave and drought. We showed that large amounts of surface net radiation were partitioned to sensible heat instead of latent heat as the soil moisture-temperature coupling pattern shifted from energy-limited to water-limited under low soil moisture conditions, forming positive land–atmosphere feedback and leading to unprecedented hot extremes in August. The spatial heterogeneity of hot extremes was also largely modulated by the land–atmosphere coupling strength. Furthermore, enhanced land–atmosphere feedback has played an important role in intensifying CHDEs in this traditional humid region. This study improves the understanding of the development of CHDEs from three aspects, including timing, intensity, and spatial distribution, and enables more effective early warning of CHDEs.

How to cite: Ni, Y., Qiu, B., Miao, X., Li, L., Chen, J., Tian, X., Zhao, S., and Guo, W.: Shift of soil moisture-temperature coupling exacerbated 2022 compound hot-dry event in eastern China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1631, https://doi.org/10.5194/egusphere-egu24-1631, 2024.

EGU24-2445 | ECS | Posters virtual | NH1.2

A method of dynamic diagnosis for regional drought degree 

Ruxin Zhao, Hongquan Sun, and Lisong Xing

In view of the difficulty in quantifying the severity of regional drought, this study proposes a method that can quantify and dynamically diagnose the severity of regional drought events, and consider the cumulative superposition effect of drought in the process of spatial and temporal development and evolution. Starting from the site drought index, the method firstly establishes a regional drought index to determine whether drought occurs in the study area in the same month; secondly, it constructs a two-dimensional Copula joint probability model by counting the cumulative duration and cumulative severity of droughts; and finally, it uses the percentile method to classify the joint probability of two-dimensional cumulative drought characteristics into four degree levels of regional drought: light, moderate, severe, and extreme. In the study, the SPEI drought index from 1961 to 2022 was used as the basic data, and the drought centers of China, such as North China Plain, Yangtze River Basin, and Yunnan Province, were selected as the case validation zones, and the results showed that this method can effectively identify the historical drought events in the study area and dynamically diagnose the development process of severe and extreme droughts therein. 

How to cite: Zhao, R., Sun, H., and Xing, L.: A method of dynamic diagnosis for regional drought degree, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2445, https://doi.org/10.5194/egusphere-egu24-2445, 2024.

        Using multi-source global station and grid monitoring data, FY-2H satellite, and ERA5 reanalysis data, the life history and precipitation characteristics of tropical cyclone "Freddy" as well as the causes of heavy precipitation in southern Mozambique were analyzed. The results show that "Freddy" had a lifespan of 35.5 days which made it the longest lived tropical cyclone in the world, as well as the widest latitude-crossing TC in the southern hemisphere. The extreme long life cycle of "Freddy" was related to favorable large-scale circulation conditions. The strong and sustained subtropical high pressure system made "Freddy" moving westward over the Southern Indian Ocean stably, without the opportunity to combine with the mid latitude trough or cold air which may cause the path turning, intensity weakening, or transformation. After the generation of "Freddy", more than 70% of its life time was over the sea, and the surrounding SST was generally abnormally high, which provided favorable conditions for the development or maintenance of TC intensity. Especially, the SST within the Mozambique Strait remained above 28 ℃, providing excellent underlying conditions for the enhancement of TC intensity, allowing "Freddy" to develop and strengthen rapidly twice after experiencing intensity weakening caused by landfall. The combined influence of favorable circulation conditions and warm sea surface temperature led to the extreme long life of "Freddy".

        "Freddy" made three landfall, bringing sustained heavy precipitation and severe floods to countries in Southeastern Africa. Especially in the southern part of Mozambique, precipitation had characteristics such as long duration, concentrated areas, and large accumulated amount. After landing in Mozambique, "Freddy" was located in a saddle field, leading to weakened steering airflow. Combined with high-level divergence and sustained transportation of warm and humid air by low-level jet, the large-scale circulation system provided favorable background conditions for the slow movement and maintenance of tropical cyclone. The development of low-level convergence and vorticity bands in lower troposphere, as well as strong and sustained water vapor transport, led to the persistence of heavy rainfall in Mozambique. The invasion of cold air induced the formation of a pseudo equivalent potential temperature high-gradient zone in southern Mozambique, and the cold air in the middle layer enhanced atmospheric instability, which was conducive to the development of convection. The southern part of Mozambique was continuously affected by several mesoscale convective systems (MCSs), which not only improved precipitation efficiency but also prolonged the duration of precipitation. The evolution of MCSs had obvious diurnal variation characteristics, with its rapid development and maturity stages almost concentrating in the afternoon to the earlier evening of local time. The increase in low-level wind speed promoted the enhancement of both water vapor and energy, and under the above conditions, the convergence of tropical cyclone wind direction and wind speed triggered the generation of MCSs continuously.

How to cite: Yang, S.: Analysis on the Characteristics of Extreme Long Life Cycle Tropical Cyclone "Freddy" and the Causes of Heavy Rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2724, https://doi.org/10.5194/egusphere-egu24-2724, 2024.

Extreme temperature changes from one day to another, either associated with warming or cooling, can have a significant impact on health, environment, and society. Previous studies have quantified that such day-to-day temperature (DTDT) variations and extremes are typically more pronounced in mid-and high latitudes compared to tropical zones. However, the underlying physical processes and the relationship between extreme events and large-scale atmospheric circulation remain poorly understood. Here, such processes are investigated for different locations around the globe based on Observation, ERA5 reanalysis data, and Lagrangian backward trajectory calculations. In the extratropics, extreme DTDT changes are generally associated with changes in air mass transport, in particular shifts from warm to cold air advection or vice versa, linked to regionally specific synoptic-scale circulation anomalies (ridge or through patterns). Lagrangian temperature changes in the advected air masses are due to adiabatic warming, which is dominant in the local winter season, and diabatic warming, most importantly in summer. In contrast, for extreme DTDT changes in the tropics, local processes are more important than changes in advection. For instance, the strongest DTDT decreases over central South America in December-February are linked to a transition from mostly cloud-free to cloudy conditions, indicating an important role of radiative heating. The mechanistic insights into extreme DTDT changes obtained in this study can be helpful for improving the prediction of such events and anticipating future changes in their occurrence frequency and intensity.

 

How to cite: Hamal, K.: Quantification of the Physical Process Leading to Extreme Day-to-Day Temperature Changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3564, https://doi.org/10.5194/egusphere-egu24-3564, 2024.

EGU24-3613 | ECS | Orals | NH1.2

Assessing windstorm hazard emerging from multiple types of storms 

Nasrin Fathollahzadeh Attar, Francesco Marra, and Antonio Canale

In the context of global climate change, windstorms pose significant environmental, ecological, and socioeconomic challenges. Mountainous and forested regions of Europe, including the Veneto region in northern Italy, have been devastated by unprecedented events such as the storms in July 2023 and Vaia in October 2018, raising the question whether such events may occur more frequently in the future. The probability of observing such extremes in present-day climate can be quantified using cumulative distribution functions of annual maxima wind speeds, obtained from extreme value analysis methods. Once these are derived, however, is it near to impossible to project future changes in these distributions as extreme wind speeds are caused by storms driven by diverse synoptic conditions, the characteristics and occurrence frequency of which may change differently in response to climate change.

This study introduces a method to derive cumulative distribution functions of annual maximum wind speeds explicitly considering the intensity and occurrence frequency of multiple types of storms. Independent windstorms are separated and their maximum hourly wind speed is isolated. Storms are then organized into types based on their local wind direction using a clustering technique. We then use a multi-type Simplified Metastatistical Extreme Value distribution (SMEV) to estimate the cumulative distribution function of annual maximum wind speed for the location of interest. The study focuses on mountainous areas, seeking a simpler relation between typical wind directions and synoptic conditions.

A thorough leave-one-out evaluation with benchmark models, including the traditional Generalized Extreme Value distribution (GEV) and a single-type SMEV, is conducted on 22 mountain stations in the Veneto region (northern Italy). We show that, overall, the proposed multi-type method provides estimates of extreme return levels that are comparable with the ones of single-type SMEV and GEV. Our results demonstrate that it is possible to derive cumulative distribution functions of annual maximum wind speeds explicitly considering storms emerging from different marginal processes. This paves the way to the use of projections of large-scale atmospheric dynamics from climate models to improve our prediction of future extreme wind speeds.

 

Keywords: Windstorm; Extreme events; Wind direction classification; Multiple types; Simplified Metastatistical Extreme Value (SMEV); Mountainous areas.

How to cite: Fathollahzadeh Attar, N., Marra, F., and Canale, A.: Assessing windstorm hazard emerging from multiple types of storms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3613, https://doi.org/10.5194/egusphere-egu24-3613, 2024.

EGU24-3992 | Posters on site | NH1.2

Synoptic and Mesoscale Conditions of Deep Moist Convection during the Cold Season in Croatia 

Maja Telišman Prtenjak, Domagoj Dolički, Petra Mikuš Jurković, and Damjan Jelić

In this study, thunderstorm activity during the cold part of the year was analyzed based on Thunderstorm Intensity Index (TSII) data on a pre-defined grid with a resolution of 3 km x 3 km in Croatia. The study covered a five-year period from 2016 to 2020, focusing on the months from October to March. The goal of the research was to conduct a spatial and temporal analysis of thunderstorm activity and determine the synoptic and thermodynamic conditions under which it occurs. The analysis aimed to provide an overview of the fundamental characteristics, thereby improving the understanding of deep moist convection in the cold part of the year, which poses a significant challenge in operational forecasting due to its lower frequency and more difficult intensity assessment. The occurrence of surface frontal disturbances was detected based on surface and upper-level synoptic charts, and the flow regime at the 500 hPa level was determined. Thermodynamic and kinematic parameters were calculated from radiosonde profiles from stations in San Pietro Capofiume, Brindisi, Pratica di Mare, Zagreb, and Zadar, using the thundeR free software package.

        A total of 290 convective days were selected for analysis from the observed period. The results indicate that synoptic forcing plays a significantly greater role in the development of convection during the cold part of the year compared to the warm part, while the dominant upper-level flow regime is southwest. The obtained values of CAPE (Convective Available Potential Energy) in the cold part of the year are much lower than those in the warmer part, with a significant contribution from the considerably lower amount of solar surface heating. Additionally, most thunderstorms developed under conditions of strong vertical wind shear, indicating that the atmospheric environment conducive to winter thunderstorms is predominantly a High Shear-Low CAPE (HSLC) environment.

How to cite: Telišman Prtenjak, M., Dolički, D., Mikuš Jurković, P., and Jelić, D.: Synoptic and Mesoscale Conditions of Deep Moist Convection during the Cold Season in Croatia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3992, https://doi.org/10.5194/egusphere-egu24-3992, 2024.

EGU24-4050 | ECS | Posters on site | NH1.2

Compound dry and hot extreme events in the Mediterranean region 

André Correia Lourenço, Ana Russo, Virgílio A. Bento, and João Lucas Geirinhas

Over the last few decades, the frequency, duration, magnitude of heatwaves in Europe have increased considerably, with major natural and socioeconomic impacts (Basarin et al., 2020; K.P. Tripathy et al., 2022). In climate change scenarios, these events are expected to present an increasing trend (Zscheischler et al., 2018) due to variations in dynamic and thermodynamic mechanisms, triggering unusually longer and more intense periods of drought and causing a reduction in agricultural production and the supply of water reservoirs. The Mediterranean region is a climate change hotspot and therefore a region susceptible to the development and intensification of single or compound hot and dry events (Giorgio and Linello, 2008).

This work aims at studying single and compound heatwaves and droughts based on ERA5 and ERA5-Land databases for Southern Europe on a 0.25º x 0.25º and 0.1º x 0.1º spatial resolution, respectively.

The results show positive trends for the duration and intensity of heatwaves and droughts and, conversely, negative trends for soil moisture. Most of the study area shows statistically significant negative trends when aggregating spatially. On the other hand, the annual temperature means tends to migrate towards higher values and precipitation means show a small decrease. Furthermore, the relation between large scale climatic patterns such as the North Atlantic Oscillation (NAO) and compound drought and heatwaves are studied here.

It is expected that compound hot and dry events will have a positive trend in their frequency, duration and intensity, as a consequence of climatic phenomena, such as the synoptic systems, or even due to previous dry characteristics of the soil. Our findings highlight the intricate interplay between different mechanisms in the occurrence of extreme events in Mediterranean Europe, putting into evidence the need for better representation this interplay in climate models.

A.L., A.R., V.B. and J.G. have been supported by the Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC, grant no. UIDB/50019/2020, https://doi.org/10.54499/UIDP/50019/2020, and LA/P/0068/2020, https://doi.org/10.54499/LA/P/0068/2020, to Instituto Dom Luiz; project DHEFEUS, https://doi.org/10.54499/2022.09185.PTDC). J.G. acknowledges Fundação para a Ciência e a Tecnologia (FCT) for the PhD Grant 2020.05198.BD.

 

References:

Basarin, Biljana, Tin Lukić, and Andreas Matzarakis. 2020. "Review of Biometeorology of Heatwaves and Warm Extremes in Europe" Atmosphere 11, no. 12: 1276. https://doi.org/10.3390/atmos11121276.

Giorgi, F., Lionello, P., 2008. Climate change projections for the Mediterranean region. Global Planet. Change 63 (2), 90–104.

Tripathy, K. P., & Mishra, A. K. (2023). How unusual is the 2022 European compound drought and heatwave event? Geophysical Research Letters, 50, e2023GL105453. https://doi.org/10.1029/2023GL105453.

Zscheischler, J., Westra, S., van den Hurk, B. J. J. M., Seneviratne, S. I., Ward, P. J., Pitman, A., et al. (2018). Future climate risk from compound events. Nat. Clim. Change 8, 469–477. doi: 10.1038/s41558-018-0156-3.

How to cite: Lourenço, A. C., Russo, A., Bento, V. A., and Geirinhas, J. L.: Compound dry and hot extreme events in the Mediterranean region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4050, https://doi.org/10.5194/egusphere-egu24-4050, 2024.

Rainfall return levels are guiding hazard protection, insurance models, infrastructure design, construction, and planning of cities. When deriving information about the frequency and intensity of extremes by fitting extreme value models to pointwise observations, the regionalization of these models is challenging. Rain gauges are distributed unevenly, where some regions suffer from data scarcity in space and time. To address this, topographical and/or climatological covariates are often used for the spatial interpolation. On the other hand, high-resolution climate simulations are available to provide spatial information on rainfall extremes. However, these simulations are still governed by model biases, where the bias adjustment of extremes at ungauged locations is also inducing uncertainty.   

In this study, we propose a combination of observations and a high-resolution convection-permitting climate model simulation in the framework of smooth spatial Generalized Extreme Value (GEV) models in order to estimate spatial rainfall return levels. We choose a study area over southern Germany with complex terrain, which is densely monitored with 1132 rain gauges providing more than 30-year daily rainfall observations. There, a 30-year simulation of the Weather and Forecasting Research (WRF) model is available at 1.5 km resolution driven by ERA5 reanalysis data. We combine observations and covariates from the WRF simulation in the spatial GEV and refer to this approach as sGEV-WRF.

We want to answer three research questions to assess the added value of the proposed framework:

  • Is it worth the effort? Does the sGEV-WRF improve the generation of rainfall return levels compared to the WRF alone?
  • Does the WRF simulation as covariate add value? Can the sGEV-WRF outperform a topography-only spatial GEV?
  • Does the dynamical downscaling at high resolution add value? Can sGEV-WRF outperform a spatial GEV based on observations and covariates from the coarser resolution ERA5?

By evaluating the percentage bias, mean absolute error, and root-mean-square error, we show that the combination of observations and WRF can improve the representation of 10-year and 100-year return levels of daily rainfall.

In addition, we aim to assess the performance of this framework under data-scarce conditions. Therefore, we devise an extensive cross-validation study. We select 5%, 10%, 20%, 50%, 80%, 90%, and 95% of all 1132 rain gauges to re-build the spatial GEV models with 1000 random folds each. We show that the performance is robust under these conditions, highlighting the potential for the application in data-scarce regions. Furthermore, in a non-stationary setup with climate model future projections, it can serve as a reliable tool to assess climate change effects on heavy rainfall.     

How to cite: Poschlod, B. and Koh, J.: Combining observations and a high-resolution climate model for the generation of spatial rainfall return levels, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5310, https://doi.org/10.5194/egusphere-egu24-5310, 2024.

EGU24-5441 | ECS | Orals | NH1.2

Compounding drivers amplify the severity of river floods  

Shijie Jiang, Larisa Tarasova, Guo Yu, and Jakob Zscheischler

Estimating the risk of river flooding under global warming is challenging, mainly due to the compound nature of the various drivers, which is not yet fully understood. Our study aims to quantitatively unravel the complex dynamics of multiple factors that interact and influence river flooding. Using interpretable machine learning techniques, we analyzed thousands of global catchments to identify the role of compounding drivers in river flooding. Our results indicate that these compounding drivers have played a significant role in increasing the magnitude of river floods over the past four decades. In particular, the influence of the interaction effects between these drivers becomes more pronounced with increasing flood magnitude, and the degree is modulated by specific physioclimatic conditions. Importantly, traditional flood analysis will underestimate the magnitude of extreme floods due to insufficient consideration of the varying compounding effects in flood generation. Overall, our results emphasize the need to more carefully incorporate compounding factors to improve extreme flood estimates.

How to cite: Jiang, S., Tarasova, L., Yu, G., and Zscheischler, J.: Compounding drivers amplify the severity of river floods , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5441, https://doi.org/10.5194/egusphere-egu24-5441, 2024.

EGU24-5446 | ECS | Posters on site | NH1.2

Enhancing flood forecasting and prevention: The multidisciplinary approach of Flood2Now project and its innovative solutions 

Carlo Guzzon, Raül Marcos, Maria Carmen Llasat, Montserrat Llasat-Botija, Dimitri Marinelli, Albert Diaz Guilera, Luis Mediero, Luis Garrote, Alicia Cabañas Ibañez, Javier Arbaizar Gonzalez, and Olga Varela

Spain and the Mediterranean coast are largely affected by flash floods, which are generated by intense, localized storms within smaller basins, typically less than 100 km2 (Gaume et al., 2016). Predicting these events remains challenging as they are frequently triggered by convective systems operating at scales below the resolution of conventional meteorological models. In Spain, floods are the country's primary recurring natural disaster, accounting for nearly 70% of the compensation amount issued by the Consorcio de Compensación de Seguros (CCS, 2011). 

In this hydrogeological risk context, the ultimate goal of the Flood2Now project is to support the population and mitigate the risk associated with this natural hazard, through the implementation of an automatic real-time warning system in two basins (Francolí and Arga) located in the north-east part of the Iberian peninsula. Multidisciplinarity plays a pivotal role in defining this system, integrating various disciplines and information sources, ranging from complex systems physics and hydrometeorological data to citizen science and socio-economic statistics.

Flood2Now embodies a collaborative effort between universities, companies, and social foundations, to explore the following technical aspects: (i) establishing a comprehensive digital database spanning four decades of flood occurrences; (ii) exploring complex systems methodologies to discern interrelationships among various factors influencing flood impacts; (iii) studying weather patterns associated with diverse flood events, accounting for their impact; (iv) implementing analogous methodologies to enhance flood risk forecasting; and (v) integrating this knowledge to enhance operational systems aiding flood-related decision-making.

This research extends its impact on society by implementing citizen science methodologies to gather supplementary data for flood risk management, enhancing early warning systems' precision, and raising community awareness of flood risks and climate change. Innovative approaches include integrating historical and citizen-collected data into decision-making, employing ensemble prediction systems, and implementing advanced hydrological modeling techniques for streamflow prediction and decision support.

This contribution shows the selected basins and case studies, the proposed applied hydrometeorological chain to forecast flash flood impacts, and the improvements that citizen science can provide, on the one hand, in obtaining flow data and the state of rivers, especially in ungauged basins, and, on the other, in increasing risk awareness.

This research has been done in the framework of the Flood2Now project, Grant PLEC2022-009403 funded by MCIN/AEI/10.13039/501100011033 and by the European UnionNextGenerationEU/PRTR. 

 

References:

Gaume, E., Llasat M.C., et al., 2016. Mediterranean extreme floods and flash floods. Into Hydro-meteorological extremes, chapter 3, The Mediterranean Region under Climate Change. A Scientific Update (coordinated byAllEnvi).133-144. ISBN : 978-2-7099-2219-7.

CCS, 2021, Estadística riesgos extraordinarios. Serie 1971-2020. Available at: https://www.consorseguros.es/web/documents/1018/4419/Estadistica_Riesgos_Extraordinarios_1971_2014/14ca6778-2081-4060-a86d-728d9a17c522

 

 

How to cite: Guzzon, C., Marcos, R., Llasat, M. C., Llasat-Botija, M., Marinelli, D., Diaz Guilera, A., Mediero, L., Garrote, L., Cabañas Ibañez, A., Arbaizar Gonzalez, J., and Varela, O.: Enhancing flood forecasting and prevention: The multidisciplinary approach of Flood2Now project and its innovative solutions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5446, https://doi.org/10.5194/egusphere-egu24-5446, 2024.

Hail is by far the greatest contributor worldwide to insured losses from severe convective storms on an annual basis. Individual outbreaks can cause losses well above EUR 1 bn. In Italy, severe convective storm losses have been dominating the market in the last 5-7 years, with a record of EUR 1.4 bn in 2019 prior to year 2023. On 18-25 July 2023 an unprecedented outbreak brought large hail and strong winds to Lombardy, Veneto, Friuli-Venezia Giulia, Piedmont and Emilia-Romagna, with affected cities including Parma, Turin, Milan and Venice. There were many reports of large hailstones, causing significant damage to property and motor vehicle. The European hail record was breached too. Twice. On 19 July, a hailstone measuring 16 cm in diameter was recorded in Carmignano di Brenta, and broke the previous largest hail record in Europe, which was held by a 15 cm stone found in Romania in 2016. Just five days later, a new record was set, when a 19 cm hailstone was found in the town of Azzano Decimo. This is very close to the all-time largest hail recorded of 20.3 cm, found in 2010 in South Dakota, US. Total loss estimates, of which hail was by far the largest contributor, exceeds EUR 3 bn, of which 70-80% in the property sector (residential and commercial buildings), and the remaining 20-30% in the motor vehicle sector. These were the largest hail events in Italy in recorded history, and the costliest cat event in the third quarter of 2023 for the global insurance market.

Following in the footsteps of the severe convective storm outbreak that impacted France in June 2022, these storms came after a record-hot air mass that languished over Southern Europe much of the week prior. Persistent meteorological conditions conducive to rotating supercell thunderstorms were observed for several consecutive days. These compounded with local conditions favorable for the development of severe hail over the Po Valley. In this study we present a reconstruction of these events based on event reports from European Severe Weather Database. We analyze the synoptic configurations and pre-convective environments that characterized them, with focus on those properties and features that are peculiar to severe hail-forming thunderstorms. We look at different formulations of CAPE and vertical wind shear, as well as composite parameters such as the Significant Hail Parameter and the Supercell Composite Parameter. We make use of Gallagher Re’s Severe Convective Storm Index to contextualize these events historically, and to discuss climate change trends over Northern Italy. Finally, we discuss the implications that such events and their expected frequency under climate change have on the (re)insurance market.

How to cite: Panosetti, D. and Tomassetti, U.: The July 2023 Northern Italy hailstorms from a climatological and (re)insurance market perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5962, https://doi.org/10.5194/egusphere-egu24-5962, 2024.

The consensus of climatic research indicates that the likelihoods of extreme precipitation events are going to change significantly, but specific trends depend on the type of dominant weather system, and regional landscape and climate details. Despite the effort of increasingly accurate and converging global circulation models, the uncertainties in the ensemble of CMIP6 models, and the often course spatial resolution make translation of climate models to actionable information of flood forecasts complex and uncertain. We carried out an analysis of a large ensemble of Global Circulation Models (GCMs) of the CMIP6 ensemble that were downscaled statistically as part of the NASA NEX-GDDP-CMIP6 dataset. The analysis looked at segmented windowed return period analysis using the method of l moments to fit general extreme value distributions to global climate models. With analysis of 1, 3 and 7 day duration, median, 15 and 85 percent quantiles, between 5 and 100 year return period, and global spatial coverage, the results show variations in how precipitation events of various return periods and durational are predicted to change in GCMs, and what the associated uncertainty is for various regions of the world. Intermediate analysis outputs show artifacts in yearly extreme precipitation due to the applied statistical downscaling, but relative factors to be used in precipitation scaling under climate change resolves these. Average increases in precipitation extremes of percent are observed globally (+5.1%), with many local outliers for the SSP585 scenario in 2050 (e.g. regions such as the Himalayan region (+23.4 percent median), the Sahel region(+21.6%) or South-Western Spain (-3.9%)). The other SSP scenarios change the global average factors to +3.75% and +4.32% for SPP245 and SSP370 Respectively. Very low variability in the changes is observed for return periods, indicating that the intensity probability curves shift uniformly in the model output. Precipitation events duration does more significantly alter the analysis outputs, and various areas show differences here that correlate with flash and fluvial flood susceptibility. Finally, we open-source the analysis code and link the output as a built-in dataset in the fastflood.org rapid flood simulation platform. Here, automatically derived extreme precipitation events from era5 datasets can be rescaled under climate change conditions by applying the scaling factors derived in this work.

How to cite: van den Bout, B.: Global changes in extreme precipitation linked with rapid flood simulation tools, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7617, https://doi.org/10.5194/egusphere-egu24-7617, 2024.

EGU24-8116 | ECS | Posters on site | NH1.2

IMERG-E and IMERG-L: A Comprehensive Evaluation of the Medicane Daniel in Thessaly, Greece 

Evangelos Leivadiotis, Silvia Kohnová, and Aris Psilovikos

On 4 September 2023, the area of Thessaly (Greece) experienced a catastrophic flood as a result of the Daniel hurricane sequence. This severe phenomenon is characterized by extreme rainfall records ranging from 305 mm to 1096 mm between 4 and 7 September, causing severe damage to infrastructure, agriculture and buildings. Seventeen casaulties were recorded. The aim of the study is to complete the integrated multi-satellite harvesting of the Global Precipitation Measurement Mission (IMERG) using 10 precipitation stations distributed in the Thessaly region. Specifically, two precipitation products (IMERG-E and IMERG-L) were used to evaluate the early and late extreme precipitation events of IMERG version 7. In order to obtain the rainfall data needed for the research, a time period of 4 September 2023 (0000UTC) to 7 September 2023 (2330UTC) was chosen. This window corresponds to the approximate time at which Daniel's storm convective zone was on the area of interest. The National Meteorological Agency collected six of the ten precipitation stations and four of the Public Electricity Agency. The evaluation process was divided into two parts: the first part aimed at estimating the total rainfall of IMERG-E and IMERG-L, and the second part aimed at estimating the total daily rainfall of both products. Two statistical assessment indicators were used: the Pearson correlation coefficient and the root mean square error (RMSE) to quantitatively assess the performance of satellite precipitation products using rain-gauge data. Firstly, the correlation coefficient between IMERG-E, IMERG-L and total precipitation at IMERG-E, IMERG-L and IMERG-L is -0.03 and 0.27, respectively. Early products did not correlate with ground data, but later versions showed weak positive linear relationships. The RMSE values are 0.8 and 0.52, respectively. The daily analyses of IMERG-E showed moderate negative correlations on September 4 (-0.29), September 5 (-0.15), and September 7 (-0.25), and moderate positive correlations on September 6 (0.37). In terms of daily performance, the correlation coefficients suggest weak positive correlations (0.22 in 4 September, 0.13 in 5 September, 0.23 in 7 September), with the exception of -0.3 in 6 September. RMSE values remain low (0.31 on 4 September, 0.34 on 5 September, 0.20 on 7 September), except for 6, September, where values (0.95) indicate high levels of error. Overall, the late version is more efficient than the early version, but there are rooms for improvements when the IMERG final version will be available.

How to cite: Leivadiotis, E., Kohnová, S., and Psilovikos, A.: IMERG-E and IMERG-L: A Comprehensive Evaluation of the Medicane Daniel in Thessaly, Greece, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8116, https://doi.org/10.5194/egusphere-egu24-8116, 2024.

EGU24-9412 | Orals | NH1.2

Extratropical intrusions and their role in tropical flood events: A South Pacific perspective 

Romain Pilon, Andries de Vries, and Daniela Domeisen

Extratropical Rossby waves are a potential source of instability for driving convective disturbances in the tropics. In the South Pacific, island nations are subject to flooding associated with such convective disturbances, yet these have not been conclusively linked to any large-scale processes. Using an object-based approach, this study specifically explores in particular how Rossby waves propagating into the tropics can contribute to the formation of extratropical-tropical cloud bands, which can cause flooding events. These cloud bands are associated with substantial precipitation events and serve as easily detectable proxies to identify when such intrusions occur. Building upon this foundation we use ERA5 reanalysis along with a detection analysis for tropical-extratropical cloud bands and potential vorticity streamers and cutoffs to establish a climatology of such intrusions and cloud bands. This allows us to demonstrate the statistical association of extratropical intrusions with intensified deep convection, in particular over the tropical central South Pacific. We find that these intrusions contribute significantly to the occurrence of floods in the Polynesian islands. In summary, this study allows us to connect the interaction between the extratropics and the tropics with flood events in the South Pacific.

How to cite: Pilon, R., de Vries, A., and Domeisen, D.: Extratropical intrusions and their role in tropical flood events: A South Pacific perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9412, https://doi.org/10.5194/egusphere-egu24-9412, 2024.

EGU24-10058 | ECS | Orals | NH1.2

Detection of past extreme precipitation events and connection to recorded impacts: a multi-data and multi-method assessment over the Central-Eastern Alps 

Katharina Enigl, Alice Crespi, Sebastian Lehner, Klaus Haslinger, and Massimiliano Pittore

Extreme hydro-meteorological events are increasingly observed in southern Europe and especially in the European Alps, where they threaten ecological and socio-economic systems. To detect such events and analyse the changes in their occurrence, a proper definition of an extreme event is needed. Statistically, we define extremes from the tails of the probability distributions. However, these events are not necessarily extreme in terms of impact, and impact-related thresholds may vary spatially and temporally, i.e., single absolute thresholds do not necessarily reflect the extremes at all locations, in all time periods and all seasons. Moreover, the availability of harmonized and consistent datasets is crucial for investigating extremes in a transnational context. In this study, we focus on the identification and characterisation of extreme hydro-meteorological events affecting a transboundary Alpine region between Austria and Italy from 2003 to 2021 based on different definitions of extreme events considering spatiotemporal aspects and multiple datasets. Daily accumulated precipitation is used as the main proxy parameter to describe the potential for severe consequences, as it as it is the most broadly available quantity across different datasets compared to e.g., sub-daily precipitation sums. Moreover, its role as a triggering factor for various hazards (e.g., landslides, debris flows, pluvial and fluvial floods) is widely recognised. We analyse three different statistical methods for the detection of extreme events: (i) the identification of the highest daily precipitation amounts on a regional scale, (ii) the detection of daily precipitation values of high intensity on a local scale and (iii) the identification of exceptional daily precipitation records not in absolute terms but with respect to average conditions associated to a specific period of the year. All detection algorithms are applied to four gridded precipitation datasets, including both observation and reanalysis products, with different technical specifications. Subsequently, identified events for each method-dataset combination are blended with existing records of gravitational mass movements and fluvial floods in the Austrian-Italian border region to analyse the suitability of each combination to detect actual occurred impacts. First results indicate that most detected precipitation extremes relate to actual observed impacts (e.g., 74% for regional scale identification with reanalysis data). However, different method-dataset combinations have different strengths and weaknesses, which reflect inherent characteristics of the dataset and/or of the statistical method employed. Furthermore, some combinations show lower performance in detecting impactful events, because the dataset and method applied conflict with each other (e.g., a coarse-resolution dataset not resolving local-scale features conflicts with a statistical method searching for locally high intensities). The findings could contribute to better inform civil protection authorities about risks related to extreme hydrometeorological events, possibly affected by climate change.

How to cite: Enigl, K., Crespi, A., Lehner, S., Haslinger, K., and Pittore, M.: Detection of past extreme precipitation events and connection to recorded impacts: a multi-data and multi-method assessment over the Central-Eastern Alps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10058, https://doi.org/10.5194/egusphere-egu24-10058, 2024.

EGU24-10451 | Posters on site | NH1.2

Influence of Design Storm Profiles on Flood Peak Discharge in a Small River Catchment 

Kazimierz Banasik, Leszek Hejduk, Adam Krajewski, Donald E. Woodward, Andrzej Wałęga, and Beniamin Więzik

Estimations of flood peak discharges of low probability of exceedance are required for designing and maintaining hydraulic and road structures (reservoirs, weirs, water intakes, bridges, culverts) as well as for flood protection, including assessment of the risk of flooding. Rainfall-runoff models are usually the only alternative for such estimations in case of small catchments, as there is a lack of sufficient, good quality historic data to be used for applying the traditional i.e. statistical methods. The aim of this study was to check responses of a small agro-forested, lowland catchment located in center of Poland to rainfall of assumed probability of exceedance and of three profiles of intensity (i.e. a/ constant intensity, b/ asymmetric one with highest intensity between 0.3 and 0.5 its duration, c/ symmetric one with single peaked intensity) and various storm duration.

A regional formula, developed by state hydrological service, on relationship of intensity-duration-frequency, applicable also for region of center of Poland, has been used to find rainfall depths of the events with probability of exceedance of 1% (return period of 100 years) and various duration (i.e. D = 6, 12, 18, 24, 30, 36, 42, 48, 60 and 72 h), as input data for runoff hydrograph simulation. As the catchment, which area is 82.4 km2, has long term monitoring history, the model parameters, as Curve Number of NRCS (Natural Resources Conservation Service), used for extracting the effective rainfall (direct runoff) from total rainfall depth and parameters of Nash model, used for transformation of effective rainfall into direct runoff hydrograph, were estimated from recorded rainfall-runoff events. Over 50-year-continuous discharge record allowed us to estimate the 100 year flood, by applying statistical method for the investigated catchment, as 25,6 m3/s which form a base for comparison of the results of application of the rainfall-runoff model.

Results of modelling of the of rainfall-runoff process indicate: a/ that critical rainfall duration (producing highest peak discharges) of the three storm profiles were between 24 and 60 hours, and b/ higher peak discharges at critical rainfall durations of the three storm profiles than one of statistical method. The differences (overestimates) were from 1.6% for the constant intensity to 30.0% for the symmetric single peaked intensity.

How to cite: Banasik, K., Hejduk, L., Krajewski, A., Woodward, D. E., Wałęga, A., and Więzik, B.: Influence of Design Storm Profiles on Flood Peak Discharge in a Small River Catchment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10451, https://doi.org/10.5194/egusphere-egu24-10451, 2024.

EGU24-10531 | Orals | NH1.2

Evaluating Standard Precipitation Index (SPI) using MIROC6 historicclimate simulations and ERA 5 reanalysis data as a tool to map theimpacts of climate change in rainfall regime in Brazil 

Gean Paulo Michel, Aimée Guida Barroso, Franciele Zanandrea, Márcio Vinicius Aguiar Soares, Gabriel Ferreira Subtil de Almeida, Marcio Cataldi, Priscila Esposte Coutinho, Lívia Sancho, and Vitor Luiz Galves

Rising global average temperatures, as a consequence of climate change, have worsened the occurrences of extreme weather events, causing disruptions in rainfall patterns around the world. In Brazil, such effects are already observed with the increase of heat waves, floods, droughts, and wildfires. The correlation between disruptions in precipitation patterns and fires is complex, nevertheless, the intensity, frequency, and duration of drought events have significant impacts on fuel flammability and fire behavior. Drought monitoring is particularly relevant in Brazil, where the vast majority of forest fires have an anthropogenic ignition and prolonged dry periods favor such fires to spread out of control. The Standardized Precipitation Index (SPI) is one of the most important tools used to evaluate precipitation variability, offering simple yet robust statistical information on the distribution, duration, and frequency of rainfalls and, consequently, droughts. The SPI uses precipitation as input data to standardize the deviation of cumulated rainfall from the mean of historical precipitation, detecting water deficit (negative values) or water surplus (positive values) for a given location. In doing so, this index allows direct spatial comparability between arid and humid regions. This is an advantageous characteristic when drought analysis is applied to a country with different regional rainfall regimes, such as Brazil. The applicability of SPI as a source of drought prediction was investigated by observing its performance with historical climate simulations of the 6th phase of the Model for Interdisciplinary Research on Climate (MIROC6) and the fifth generation ECMWF atmospheric reanalysis of the global climate, ERA5. The direct comparison of the SPI data, employing the climatology extending from 1980-2014 in Brazil, derived both from the climate simulation model and the reanalysis data - which combines observations and models – has provided valuable insights. Preliminary results show an overall consistency in the calculated indexes from both sources, which are in line with seasonal regional rainfall patterns in Brazil. On average, the SPI indexes recognize water deficits for the North-east, north of the South-east and central regions of Brazil. During the months of winter, both indexes detect droughts in these regions, with ERA-5 SPI index registering severe droughts in central Brazil. These results suggest that the SPI index calculated using the reanalysis data seems to register droughts with greater severity and longer duration, identifying more precisely periods with little to no rainfall, whilst the SPI derived from the MIROC6 simulation data, although able to acceptably identify and delimitate droughts, records less severity for the same period. These findings are important to recognize the MIROC6-derived SPI index as a valuable tool in drought prediction. However, they also highlight the necessity of acknowledging the limitations of the model regarding the severity of droughts. The understanding and prediction of precipitation anomalies is fundamental to coping with the impacts of climate change on water resources, agriculture, and biodiversity, guiding mitigation and adaptation strategies in Brazil.

How to cite: Michel, G. P., Guida Barroso, A., Zanandrea, F., Aguiar Soares, M. V., Ferreira Subtil de Almeida, G., Cataldi, M., Esposte Coutinho, P., Sancho, L., and Galves, V. L.: Evaluating Standard Precipitation Index (SPI) using MIROC6 historicclimate simulations and ERA 5 reanalysis data as a tool to map theimpacts of climate change in rainfall regime in Brazil, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10531, https://doi.org/10.5194/egusphere-egu24-10531, 2024.

EGU24-10737 | ECS | Orals | NH1.2

Projecting Extreme Rainfall in Sicily: Integrating Simple Scaling and Hourly Projections into Depth-Duration-Frequency Analysis 

Gaetano Buonacera, David J. Peres, Nunziarita Palazzolo, and Antonino Cancelliere

In this present work, we propose a robust methodology for the derivation of future rainfall depth-duration-frequency curves (DDFs), utilizing hourly projections, the assumption of simple scaling of precipitation, and the application of the method of moments for parameter estimation in dimensionless precipitation height distributions. The methodology introduced herein involves the application of change factors derived from climate projections to precipitation averages across various durations (1, 3, 6, 12, and 24 hours) and to the dimensionless moments of the precipitation series. To implement this methodology, we leverage regional scale models (RCM) from the EURO-CORDEX initiative, characterized by hourly temporal resolution. The direct utilization of hourly projection data allows to bypass the necessity for temporal disaggregation techniques. Change factors are calculated through an analysis of annual maxima derived from both future and control series (1971-2000) generated via RCMs. We consider two distinct emission scenarios, namely RCP (Representative Concentration Pathways) 4.5 and 8.5, spanning three future periods: near future (2021-2050), middle future (2051-2070), and far future (2071-2100). Our methodology is applied to multiple rain gauges located across the Sicily region. The outcomes of our investigation underscore an upward trend in future DDFs, particularly pronounced in the RCP 4.5 scenario and during the far future period. This trend is attributed to an observed intensification in the variability of rainfall events. Depending on the specific geographic location, chosen emission scenario, and future time period, future Depth-Duration-Frequency (DDF) curves may correspond to return periods that more than double those observed in the control climate. The methodology, given the easy availability of the exploited data, can turn useful for updating hydrological design criteria for flood mitigation.  

 

How to cite: Buonacera, G., Peres, D. J., Palazzolo, N., and Cancelliere, A.: Projecting Extreme Rainfall in Sicily: Integrating Simple Scaling and Hourly Projections into Depth-Duration-Frequency Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10737, https://doi.org/10.5194/egusphere-egu24-10737, 2024.

EGU24-10848 | ECS | Orals | NH1.2

Extreme precipitation – temperature scaling: disentangling causality and covariation 

Sarosh Alam Ghausi, Erwin Zehe, Subimal Ghosh, Yinglin Tian, and Axel Kleidon

Warmer temperatures are expected to cause more intense rainfall, primarily due to the rise in atmospheric moisture at the rate of 7%/K, as indicated by the Clausius-Clapeyron (CC) equation. To evaluate this effect, studies use a statistical approach known as precipitation-temperature scaling that involves fitting an exponential regression between observations of extreme rainfall events and local temperatures, resembling how saturation-vapor pressure scales with temperature. However, the estimated sensitivities (also called scaling rates), exhibit notable deviations from the CC scaling (7%/K). These rates remain mostly negative in the tropics as the rainfall extremes exhibit a general monotonic decrease with temperature and “hook-shape” structures in most parts of tropics and mid-latitudes.

Here we show that most of the variability in the observed scaling rates arises from the confounding radiative effect of clouds associated with rainfall events. Clouds substantially reduce the net radiative heating of the surface during the storms by up to 100 W/m2 in the tropics, leading to the cooling of surface temperatures by up to 8K. This cloud-induced cooling results in a covariation between precipitation and local temperature, inducing a two-way causality in the observed scaling rates. To isolate this cooling effect, we used a thermodynamically constrained surface energy balance model and force it with radiative fluxes under both "clear" and "cloudy" sky conditions. We then quantified the changes in surface temperatures due to clouds and remove it from temperature observations during rainy days. After removing this effect, we found positive scaling across the global land areas, closely aligning with CC rates of 7%/K. We demonstrate that cloud radiative effects alone can explain the observed negative and hook-shaped relationships found in precipitation-temperature scaling.

Our findings imply that projected intensification of rainfall extremes with temperature by climate models is consistent with observations after the cloud-cooling effect is corrected for. Our results emphasize on making a clear distinction between causality and covariation by explicitly separating the temperatures before the rainfall event that are shaped by less clouds from temperature during the rainfall event which include clouds. This adds a crucial effect to the debate of interpreting observed precipitation - temperature scaling rates. Furthermore, our methodology of removing cloud effects on temperatures can be extended to estimate climate sensitivities from observations beyond precipitation extremes.

How to cite: Ghausi, S. A., Zehe, E., Ghosh, S., Tian, Y., and Kleidon, A.: Extreme precipitation – temperature scaling: disentangling causality and covariation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10848, https://doi.org/10.5194/egusphere-egu24-10848, 2024.

EGU24-11716 | ECS | Posters on site | NH1.2

Tropical Cyclone Rainfall Asymmetries Inferred from GPM-IMERG: A Focus on Lesser Antilles 

Catherine Nabukulu, Janneke Ettema, Victor Jetten, and Bastian van den Bout

Abstract

This study utilizes GPM-IMERG satellite rainfall estimates to assess the asymmetric rainfall patterns in 27 tropical cyclones (TCs) across the Lesser Antilles region from 2000 to 2020. The aim is to evaluate whether there is a persistent relationship between precipitation and wind characteristics, which could support improved TC-related flood risk assessment for these islands. With a focus on hurricane and tropical storm categories, the 30-minute precipitation variability was assessed within a radius of 500 km from the TC’s eye during its path in the study area. In addition, TC’s forward speed and wind characteristics, like  TC’s category and the extent of 34-knot winds (R34), are included. The analysis reveals temporal trends, indicating increased TC rainfall events in the study area during the second decade. Correlations show positive relationships between rainfall total (RT), rainfall area (RA), and rainfall intensity at the 90th percentile (RI0.9), with RT and RI0.9 showing the strongest link in the majority of the observations. Contrary to conventional assumptions, this research challenges the idea that highest category TCs in the wind intensity always produce higher rainfall, as we see that higher-category hurricanes such as H4 (209-251km/hr) and H5 (>=252km/hr) were often associated with lower rainfall values in RT and RI0.9 compared to tropical storms (63 - 118 km/hr). Tropical storms, like higher-category hurricanes, can display large rainfall areas. In addition,  quadrant analysis of rainfall zones around the TC eye highlights that the NE and SE quadrants in TC have significantly more rainfall impact. However, it also reveals the danger posed by weaker quadrants in wind characteristics such as SW and NW, as they can exhibit high rainfall values in RA and RT. The study indicates complex, non-linear relationships between TC’s wind and precipitation characteristics in the Lesser Antilles region. Incorporating the rainfall variability observed in TC dynamics into early warning systems and risk assessment is essential for a more effective emergency response and mitigation planning.

General methodology

The satellite rainfall estimates were obtained within a defined buffer of a diameter of 500km around the TC eye while following the TC trajectory. The buffer was further dissected into quadrant spatial zones  (NE, SE, SW and NW) to provide a detailed perspective on rainfall distribution in different parts of the TC impact area. For each eye position, rainfall characteristics (RT, RA and  RI0.9) were computed for the whole buffer and later individual quadrant partitions. The computed rainfall characteristics were then investigated for potential correlation relationships with the TC wind intensity. In addition, quadrant rainfall patterns were analyzed for persistence throughout the TC duration.

 

How to cite: Nabukulu, C., Ettema, J., Jetten, V., and van den Bout, B.: Tropical Cyclone Rainfall Asymmetries Inferred from GPM-IMERG: A Focus on Lesser Antilles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11716, https://doi.org/10.5194/egusphere-egu24-11716, 2024.

EGU24-12191 | ECS | Posters on site | NH1.2

Prediction and predictability of drought events in the Spree region 

Clara Hauke, Uwe Ulbrich, and Henning Rust

The predictability of drought events in the Spree region is analyzed, aiming at developing hydrological extreme events forecast and warning systems and long-term solutions regarding sustainable, interdisciplinary and integrated water resources management in the project SpreeWasser:N.

Predictors acting as potential indicators of imminent drought risk are inferred from statistical analyses, modeling and literature. Connections between certain states of the atmosphere (large-scale weather patterns) and local drought events are drawn, focussing mainly on agriculture as a user group. Special attention is paid to the succession of certain weather patterns and their impact on precipitation.

A drought forecast based on k-nearest neighbor regression is being developed using an algorithm which automatically selects the meteorological variables and regions yielding the largest forecast skill as input predictor variables during a hindcast period. This machine learning approach supports the discovery of underlying physical links in atmospheric phenomena.

The analysis and software development is based on ECMWF ERA5 reanalysis data and the objective weather type classification by the German Weather Service (DWD), spanning the years 1980 to 2021.

How to cite: Hauke, C., Ulbrich, U., and Rust, H.: Prediction and predictability of drought events in the Spree region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12191, https://doi.org/10.5194/egusphere-egu24-12191, 2024.

Tornadoes represent major meteorological hazards, in terms of damages to buildings, vehicles and structures and casualties. Because of their small space scale (order of 1km or less), duration (order of 1000s), strongly nonlinear and chaotic dynamics, tornadoes cannot be reproduced in operational weather prediction and climate models. It is important to develop approaches overcoming this limitation and capable of delivering reliable early warnings by civil protection services and estimating whether frequency and strength of tornadoes will change because of anthropogenic climate change. Recently, a probabilistic approach has been developed that resulted in analytical expressions of the probability of tornadoes occurrence based on meteorological parameters that can be extracted from weather prediction and climate models, such as WMAX (updraft maximum parcel vertical velocity, linked to the Convective Available Potential Energy CAPE), WS700 (the wind shear in the lower troposphere), LCL (the lifting condensation level), SRH900 (low-level storm relative helicity). An example is the formula log10(P)=-6.6+WMAX/(3.1+5.2 · WMAX/WS700), which is meant to describe dependence of probability P of occurrence of a tornadoes  on the surrounding environmental conditions and to distinguish among conditions with low and high probability. In this study this and similar formulas are applied to hindcasting the probability of tornadoes using ERA5 data. The purpose is to assess the skill of the method for operational prediction and explore its validity for climate change studies.

The methodology supporting this formula is extensively described in Ingrosso, R., Lionello, P., Miglietta, M. M., and Salvadori, G.: Brief communication: Towards a universal formula for the probability of tornadoes, Nat. Hazards Earth Syst. Sci., 23, 2443–2448, https://doi.org/10.5194/nhess-23-2443-2023, 2023.

How to cite: Lionello, P. and Muhammadi, A.: Testing the skill of an analytical expression for the probability of occurrence of tornadoes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12741, https://doi.org/10.5194/egusphere-egu24-12741, 2024.

EGU24-15012 | ECS | Orals | NH1.2

Drought projections and associated uncertainties over the Arabian Peninsula from CMIP6 models 

Md Saquib Saharwardi, Hari Prasad Dasari, Waqar Ul Hassan, Harikishan Gandham, Raju Pathak, Karumuri Ashok, and Ibrahim Hoteit

Drought frequency and severity have increased over the water-stressed Arid regions. This research employs multiple CMIP6 global climate models (GCMs) for projecting droughts over the Arabian Peninsula (AP) until the end of the 21st century. We utilized the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) to generate projected future statistics of droughts along with uncertainties assessment from inter-model spread, scenarios, timescale, and methods therein.

For this purpose, after a meticulous analysis, we first identify the most suitable GCMs for better representation of AP's drought spatiotemporal pattern over the historical period (1985-2014). Our results indicate an increase in potential evapotranspiration (PET), which dominates simulated drought statistics relative to the precipitation. The projected evolution of the SPEI, which is derived from both precipitation and PET, indicates droughts  consistently increasing from low to high emission scenarios, In contrast, the SPI, owing to relatively-weaker amplification of the precipitation shows a moderately increasing wetness, except for a few northern regions where both indices evolve in agreement The fidelity of the simulated precipitation by many models over the historical period is also relatively poor compared to the PET, which may also be potentially adding to the uncertainties. In general, the principal sources of uncertainty in drought projections evolve from the choices of index, followed by scenarios, and inter-model variability, whereas methods and timescale mostly impact the magnitude of the trend in drought statistics.  

How to cite: Saharwardi, M. S., Dasari, H. P., Hassan, W. U., Gandham, H., Pathak, R., Ashok, K., and Hoteit, I.: Drought projections and associated uncertainties over the Arabian Peninsula from CMIP6 models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15012, https://doi.org/10.5194/egusphere-egu24-15012, 2024.

EGU24-15295 | Orals | NH1.2

Creation of an automatic workflow for a National Flood assessment in Aotearoa New Zealand 

Alice Harang, Emily Lane, Cyprien Bosserelle, Rose Pearson, Celine Cattoën-Gilbert, Trevor Carey-Smith, Hisako Shiona, Sam Dean, Raghav Srinivasan, Graeme Smart, and Matt Wilkins

To manage current flood hazard and help develop climate change adaptation strategies, the government-funded project “Mā te haumaru ō ngā puna wai: Increasing flood resilience across Aotearoa” aims to better understand flood hazard and risk across all Aotearoa New Zealand, now and in the future. A crucial part of this project is the generation of nationally consistent flood maps across the whole country for the current climate and future climate projections.

First, the workflow requires as input the identification of independent floodplains. Each floodplain will be associated to its catchment and be considered a computational unit. For each domain, a design storm is generated for a given scenario (Annual Exceedance Probability, climate projection, antecedent conditions) or an historical storm is used for validation purposes. The runoff and flow routing of streams and rivers on the steep part of the catchment are simulated with the NIWA TopNET model (McMillan et al. 2016). Used uncalibrated, this hydrological model was modified to include a physically realistic soil conductivity and provide a consistent response between gauge and ungauged catchments. The model is spun up to an average base flow with consistent soil and ground water antecedent conditions. The design storm is then run through the model to provide realistic flow boundary conditions to the hydrodynamic model in the populated lower catchment. Before the inundation modelling, the spatial maps are generated, using the GeoFabrics suite (Pearson et al. 2023), across the lower catchment, based on the latest LiDAR data available and complementary databases such as OpenStreetMap for infrastructure. This process produces a hydrologically conditioned DEM (Digital Elevation Model), including waterways opening and a basic riverbed estimation, associated to a roughness length map. Finally, the flood is simulated using the hydrodynamic model BG_Flood (Bosserelle et al. 2022). The model is a GPU-enabled inundation model using a modern shock-capturing St Venant solver. The model uses a quadtree type mesh that is well suited for GPU computation and allows iterative refinement of the mesh. A first coarse resolution run is used to define the expected flood extent. This flood extent and external data such as stop bank locations, is then used to produce a refinement map defining areas where higher resolution is needed. The model is then run a second time using the variably refined mesh.

Figure 1: Scheme of the cascade of model used to develop consistent flood maps in Aotearoa New Zealand.

This workflow has been validated on several historic flood events including a fluvial flood in Westport, ANZ (56h duration, 60-year flood), a fluvial and pluvial flood in Waikanae, ANZ (12h duration, 80-year flood) and the floods in the Hawkes Bay and Tairāwhiti regions (ANZ) following the Tropical Cyclone Gabrielle in February 2023 (over 100-year flood in some areas).

This workflow is based on open-sources tools; it is modular and automated for continual improvement, to enable data update and to facilitate the creation of new scenarios.

How to cite: Harang, A., Lane, E., Bosserelle, C., Pearson, R., Cattoën-Gilbert, C., Carey-Smith, T., Shiona, H., Dean, S., Srinivasan, R., Smart, G., and Wilkins, M.: Creation of an automatic workflow for a National Flood assessment in Aotearoa New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15295, https://doi.org/10.5194/egusphere-egu24-15295, 2024.

EGU24-15755 | ECS | Orals | NH1.2

The September 2023 flood in Derna, Libya: an extreme weather event or man-made disaster? 

Elad Dente, Moshe Armon, and Yuval Shmilovitz

Storm Daniel, the deadliest recorded Mediterranean tropical-like (medicane) storm, led to severe floods in large parts of the eastern-central Mediterranean, including Greece and northern Libya. Extreme rainfall, reaching more than 400 mm day-1, triggered a flash flood in Wadi Derna (Libya)– an ephemeral river with a drainage area of 575 km2 that crosses the city of Derna at its outlet to the Mediterranean Sea. Historical measures to mitigate flood risks included dam construction in the Wadi Dernah basin since the 1970s. However, during Storm Daniel, at least two of the dams were breached, resulting in a devastating flood that inundated much of the city of Derna, with over 4,000 casualties, 8,000 missing persons, and the displacement of tens of thousands. The devastating event was the focus of media coverage for a long time, but questions regarding the role of dams and their collapse remain open, and are relevant for other dammed regions as well: How extreme was the storm? How extreme the flood would have been if the dams had not been breached? What would the outcomes of the flood look like if dams were not built in the first place?

To analyze the characteristics of the storm over Wadi Derna, the catchment’s hydrological response, and the impact of the flood on the city of Derna, we integrate various datasets and models. Satellite-based precipitation estimations (IMERG) were used to quantify spatiotemporal storm properties and the catchment-scale rainfall, which were fed into the KINEROS2 hydrological model to quantify surface runoff upstream of the collapsed dams. The modeled flood hydrograph is then fed into a 2D hydraulic model (HEC-RAS) to test three end-member scenarios: (a) dam filling, overflow, and collapse, (b) dam overflow but no collapse, and (c) no dams exist in the wadi. This combination of methods reveals that the peak discharge during the flood was ~1,400 m3 s-1, just below the expected maximum extreme flood for this region. In the dam-collapse scenario, the populated flooded area is 40% larger than the no-dam scenario. These results emphasize the anthropogenic influence of damming natural streams on flood impacts. Given the high variability of precipitation in arid and semi-arid areas and the projected increase in extreme precipitation intensity with climate change, the Wadi Derna flood should serve as a warning sign for other populated areas downstream of a man-made dam in similar environments.

How to cite: Dente, E., Armon, M., and Shmilovitz, Y.: The September 2023 flood in Derna, Libya: an extreme weather event or man-made disaster?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15755, https://doi.org/10.5194/egusphere-egu24-15755, 2024.

EGU24-16370 | ECS | Posters on site | NH1.2

Analysis of historical flood events in Denmark with information from digital news media 

Jonas Wied Pedersen, Peter Steen Mikkelsen, and Michael Brian Butts

Reliable information on historical flood events is critical for flood risk analysis, climate change adaptation, verification of forecast models, etc. Unfortunately, such information is often difficult to find, due to e.g. lack of monitoring equipment at the location of a flood. In Denmark, management of water has traditionally been the responsibility of local authorities, which means there is a limited national overview of historical events and their consequences. Previous studies have employed different strategies for compiling a flood event inventory, including mining information from (1) insurance data, (2) social media data, and (3) newspaper archives. The aim of this study is to exploit a comprehensive digital news media archive to compile an inventory of Danish flood events in the period 2007-2020 with information on the time and location of the event, to classify the type of flood, and note any available information on local consequences and damages.

We have gained access to the company Infomedia’s large digital media archive, which consists of digitized articles from news sources ranging from major national newspapers to small, local outlets. The archive contains more than 75 million news articles with the earliest articles dating back to 1990. The archive is searchable through calls to an API with a custom search language that combine user-specified keywords. A hydrologist has read all articles that match the keywords, noting all the relevant information.

1,118 distinct flooded locations where identified over the 14-year period of 2007-2020. Results show that there is large year-to-year variability in the different types of floods. Urban pluvial floods are experienced somewhere in Denmark every single year, while the number of both fluvial and storm surge floods are very low (or entirely missing) in some years. Urban pluvial floods occur throughout the year but are highly concentrated in the summer months with a mean date of occurrence in late July, while storm surges are observed only between September and March with a mean date in mid-December. Fluvial floods are the least concentrated type of floods and occur throughout the year with a slight overweight in winter months (mean date in early January). The spatial distribution of floods is uneven with four out the 10 municipalities that experience the highest number of floods being located in Eastern Jutland (Vejle, Horsens, Kolding, Aarhus) and another four located in the Northern half of Zealand (Copenhagen, Roskilde, Gribskov, Holbæk).

Storm surge events occur over large geographical areas and we therefore speculate that they are more likely to be reported in news media than urban pluvial floods, which are often local events due to the small-scale nature of convective rainfall cells. Ongoing work is trying to quantify these aspects and validate the individual flood events in the inventory using additional data sources.

How to cite: Pedersen, J. W., Mikkelsen, P. S., and Butts, M. B.: Analysis of historical flood events in Denmark with information from digital news media, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16370, https://doi.org/10.5194/egusphere-egu24-16370, 2024.

EGU24-16614 | Posters on site | NH1.2

A 172-year Drought Atlas for Romania  

Mihai-Gabriel Cotos, Monica Ionita, Catalin-Constantin Roibu, Adrian-Bogdan Antonescu, Petru-Cosmin Vaideanu, and Viorica Nagavciuc

In this study, we have created a 172-year historic drought catalogue for Romania by applying both the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) to 16 long-term meteorological records/stations, covering the period 1852 – 2023. The long-term meteorological records together with documentary sources (e.g., newspapers, meteorological archives) spanning the last 172 years, are used to analyze the spatio-temporal patterns of variability, trends, and potential drivers of drought conditions, thus contributing to a nuanced understanding of Romania's hydroclimatic conditions over time. The results based on the SPEI point to the fact that the southern and eastern parts of Romania are becoming drier due to an increase in the potential evapotranspiration and mean air temperature, especially after the 1990’s. By contrast, the SPI drought index does not reveal these changes in the drought variability, mainly due to the fact that the precipitation does not exhibit a significant change. Five major drought-rich periods, in terms of duration and severity, were identified at the country level from 1852–2023, based on SPEI: 1866 – 1867, 1918 – 1920, 1947 – 1948, 2000 – 2001, and 2019 – 2022, respectively. The most pronounced drought event occurred during 2019 – 2022, followed by the 1866 – 1867 event. When analyzing the SPI-based events, similar results are found over the period 1852 – 1980, but the drought event from 2019 – 2022 is not captured by the SPI index. The most pronounced drought event, based on SPI, is the 1866 – 1867 event, followed by the 1919 – 1920 event. Nevertheless, due to the influence of the Carpathian Mountains, there are also strong regional differences in the drought events and their magnitude, with the southern and eastern parts of Romania being more affected by long-lasting drought events compared to the north-western part. Highlighting the above, a Drought Atlas for Romania (1852 – 2023) was developed using long-term meteorological data, which can provide comprehensive information on drought occurrence, magnitude and impacts over a period that goes beyond the currently available products.

How to cite: Cotos, M.-G., Ionita, M., Roibu, C.-C., Antonescu, A.-B., Vaideanu, P.-C., and Nagavciuc, V.: A 172-year Drought Atlas for Romania , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16614, https://doi.org/10.5194/egusphere-egu24-16614, 2024.

EGU24-17041 | ECS | Orals | NH1.2

Evaluation of the performance of hydrological model LISFLOOD using the ECMWF seasonal meteorological forecast at 1arcmin-1day spatiotemporal resolution over German catchments 

Edgar Fabian Espitia Espitia, Yanet Diaz Esteban, Fatemeh Heidari, Qing Lin, and Elena Xoplaki

Floods and their devastating effects on society and economy have increased dramatically in Germany, and Europe in recent years. At the end of 2023, rivers and streams across Germany burst their banks due to heavy rainfall, affecting property, transport and power supplies and necessitating rescue operations and evacuations to protect human lives. One measure to deal with flooding and safeguard lives and property is the implementation of early warning systems, such as the European Flood Awareness System (EFAS), which provides short-term hydrological forecasts in real time. However, preparedness is essential along the responders value chain and longer term forecasts are important to anticipate, take precautions, raise awareness and generally mitigate the effects of flooding. The objective of this study is to evaluate the performance of hydrological forecasting using the seasonal meteorological forecast at a spatio-temporal resolution of 1 arcmin and day over Germany including all transboundary catchments for the period from 1990 to 2020. The hydrological model used was LISFLOOD. In the first step, LISFLOOD was calibrated using the meteorological observations, the EMO 1arcmin dataset and the discharge data from the transnational hydrological portal for all federal states and neighboring countries. The characteristics of land use, land cover, soil, groundwater, and human activity referred to as surface fields for global environmental modelling, were provided by EFAS. The second step, downscaling of the seasonal (long-term) forecast meteorological forcing to 1arcmin, is performed using a Deep Residual Neural Network (DRNN), and a bilinear interpolation approach over the seasonal forecast information of atmospheric conditions up to seven months into the future provided by the European Center for Medium-Range Weather Forecasts (ECMWF), 25 ensemble members in total. In the third step, the discharge is simulated by feeding the LISFLOOD model with two meteorological forcing scenarios, the DRNN downscaled and the bilinear approach of the seasonal meteorological forecast, to finally compare the performance with the observed runoff using the modified Kling-Gupta efficiency criteria (KGE'). The calibrated and validated LISFLOOD parameters showed a good and acceptable performance in all catchments, KGE' between 0.6 and 0.9. The DRNN downscaling technique shows a promising result, providing a good agreement between downscaled and observed dataset. Finally, the hydrological performance, KGE', is expected to be improved by 0.05 to 1 in the hydrological stations with good and poor performance, respectively, by using the DRNN downscaled seasonal forecast.

How to cite: Espitia Espitia, E. F., Diaz Esteban, Y., Heidari, F., Lin, Q., and Xoplaki, E.: Evaluation of the performance of hydrological model LISFLOOD using the ECMWF seasonal meteorological forecast at 1arcmin-1day spatiotemporal resolution over German catchments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17041, https://doi.org/10.5194/egusphere-egu24-17041, 2024.

EGU24-18684 | ECS | Orals | NH1.2

Modeling Uncertainty of Copula-based Joint Return Period of Flood Events under Climate Change 

Ankita Manekar and Meenu Ramadas

Modeling the joint behavior of flood characteristics under climate change is necessary for understanding the potential changes in associated flood risk and hazards. In this study, we assessed the changes in flood duration, peak, and volume between historical and future periods through copula-based flood frequency analysis, employing the Soil and Water Assessment Tool (SWAT) hydrological model for modeling flood risk in a tropical watershed (Govindpur) lying in eastern India. Observed streamflow at the watershed outlet is obtained for the baseline period (1990-2014) for flood analysis. A suitable copula model is selected for bivariate flood frequency analysis while assuming copula parameters vary between baseline and future periods under climate change. In this study, high-resolution (12-km) climate reanalysis dataset from the Indian Monsoon Data Assimilation and Analysis (IMDAA) and future climate projections from general circulation models (BCC-CSM2-MR, MPI-ESM1-2-HR) after downscaling and bias correction, are used for simulating flood events using SWAT. The use of high-resolution climate data for hydrological modeling and flood frequency analysis is a novel aspect of the presented study. Uncertainty in the estimation of joint return periods of flood events under climate change due to climate model selection and assumption of stationarity is also quantified in this study for the near future (2041-2070) period under the shared socio-economic pathway (SSP585) scenario. Among the GCMs used, BCC-CSM2-MR performed relatively better in simulating baseline period streamflow in the study watershed. In this study, the Clayton copula is obtained as the most suitable based on its lowest Akaike information criterion (AIC) value, and joint return periods are then derived with the help of a conditional copula. It is found that flood events are projected to become more severe in the near future; the flood peak value increased by more than 90%, while the duration is projected to decrease. Flood volume may likely double in the future, as per our analysis, suggesting the need for mitigation and precautionary measures to reduce flood risk in the watershed. Based on the analysis, uncertainty in flood return period estimation under changed future climate is to be accounted for extreme event studies, and that can aid in managing and minimizing the flood-associated risks.

Keywords: Climate Change, Flood Frequency Analysis, Soil and Water Assessment Tool, Copula, General Circulation Model, Uncertainty Analysis

How to cite: Manekar, A. and Ramadas, M.: Modeling Uncertainty of Copula-based Joint Return Period of Flood Events under Climate Change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18684, https://doi.org/10.5194/egusphere-egu24-18684, 2024.

The flood events in Germany during the summer of 2021 have once again brought to the forefront the challenges in translating scientific knowledge into effective disaster risk management practices. This paper examines the critical gap between the scientific understanding of flood risks and the practical needs of those who manage these risks. We delve into the limitations of current scientific approaches, such as flood risk and hazard mapping, in fully addressing the complexities and nuances required for practical disaster risk management, especially in the face of uncertain climate change impacts. We examine the dynamics of how flood risk information, inclusive of uncertainties, is perceived and acted upon, highlighting the psychological factors influencing these processes. The paper discusses the challenges and opportunities in translating scientific risk assessments and forecasts into practical, actionable strategies for communities and stakeholders. By highlighting the disconnects and potential areas for improvement in the science-practice interface, this paper seeks to foster a more coherent and comprehensive approach to disaster risk management. Within the framework of the Safe Development Paradox, the importance of communicating uncertainties and evaluating their potential impacts on planning and emergency responses is discussed. This paper addresses uncertainties at multiple levels and for different stakeholders, highlighting the integration of uncertainty information as a vital step in preparing for surprises and ambiguities in the context of extreme meteorological and hydrological events induced by severe weather and climate change.

How to cite: Höllermann, B.: Navigating Uncertainty in Flood Risk Perception in the Context of Climate-Induced Extremes , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18692, https://doi.org/10.5194/egusphere-egu24-18692, 2024.

EGU24-19701 | Orals | NH1.2

Counterfactual floods: What if the storm track would have taken a different path? 

Bruno Merz, Viet Dung Nguyen, Guse Björn, Li Han, Xiaoxiang Guan, Oldrich Rakovec, Luis Samaniego, Bodo Ahrens, and Sergiy Vorogushyn

When a flood disaster occurs, there is an opportunity for affected individuals and decision-makers to learn from the experience. However, this learning tends to be narrowly focused on the specific event, missing the chance to discuss and prepare for even more severe or different events. For instance, regions that have been spared from havoc might feel safe and underestimate the risk. We suggest spatial counterfactual floods to encourage society to engage in discussions about exceptional events and appropriate risk management strategies. We create a series of floods across Germany by spatially shifting the rainfall fields of the 10 most expensive floods, arguing that past storm tracks could have occurred several tens of kilometers away from their actual paths. The set of spatial counterfactual floods generated includes events that are more than twice as severe as the most devastating flood in Germany since 1950. Our approach obtains peak flows that exceed the current flood-of-record at more than 70% of the gauges (369 out of 516). Spatial counterfactuals are proposed as an easy-to-understand approach to overcome society's unwillingness to consider and prepare for exceptional floods, which are expected to occur more frequently in a warmer world.

How to cite: Merz, B., Nguyen, V. D., Björn, G., Han, L., Guan, X., Rakovec, O., Samaniego, L., Ahrens, B., and Vorogushyn, S.: Counterfactual floods: What if the storm track would have taken a different path?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19701, https://doi.org/10.5194/egusphere-egu24-19701, 2024.

EGU24-19897 | Orals | NH1.2

Long-Term Trends and Drivers of Hailstorms in Switzerland 

Lena Wilhelm, Olivia Martius, Katharina Schröer, and Cornelia Schwierz

Climate change affects the severity and frequency of extreme meteorological events, including hailstorms. In this regard, it is imperative to understand the factors driving the intra- and interannual variability of hailstorms. In Switzerland, this remains insufficiently understood. To address this knowledge gap, our study conducts a long-term analysis to identify potential drivers and precursors of Swiss hailstorm variability. Due to the lack of long-term data on Swiss hailstorms, we developed statistical models reconstructing hail days from 1959 to 2022, utilizing radar-based hail observations and environmental data from ERA-5. Our hailday time series shows a statistically significant positive trend in yearly hail days in both southern and northern Switzerland. This trend is mainly attributed to heightened atmospheric instability and moisture content evident in recent decades' ERA-5 data. Noteworthy natural variability is observed in both regions. To delve into the large-scale mechanisms influencing Swiss hail activity, our study uses composites to explore potential drivers and precursors. Those include soil moisture conditions, sea surface temperature anomalies, large-scale variability patterns (Piper and Kunz 2017), central European weather types (e.g., Rohrer et al. 2018), cold fronts (Schemm et al. 2015, 2016), and atmospheric blocks (e.g. Barras et al. 2021). 

How to cite: Wilhelm, L., Martius, O., Schröer, K., and Schwierz, C.: Long-Term Trends and Drivers of Hailstorms in Switzerland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19897, https://doi.org/10.5194/egusphere-egu24-19897, 2024.

EGU24-19970 | ECS | Posters on site | NH1.2

Freva for ClimXtreme: helping to systematize holistic analysis of extreme events 

Etor E. Lucio-Eceiza, Christopher Kadow, Martin Bergemann, Andrej Fast, and Thomas Ludwig

Climate change is responsible for more extreme weather situations with damaging consequences. Public interest projects such as ClimXtreme [1, 2] were conceived to improve our knowledge on extreme events, the role of climate change, and their impacts. Focusing on an integrated approach, ClimXtreme evaluates the physical processes behind the extremes, their statistical assessment and their societal impact. On its second phase ClimXtreme [3] aims to open up its findings to a wider stakeholder base of different kinds.

Frameworks such as Freva (Free Evaluation System Framework [4, 5]) offer an efficient solution to handle customisable evaluation systems of large research projects, institutes or universities in the Earth system community [6-8] via the HPC environment and in a centralised manner. Mainly written in Python, Freva offers:

  • Centralised access. Freva can be accessed via command line interface, web, and a Python module with similar functionality.
  • Standardised data search. Freva allows quick and intuitive integration and searching of multiple, centrally stored data sets.
  • Flexible analysis. Freva provides a common interface for user-defined data analysis routines to be plugged into the system, regardless of the programming language. These plugins are able to search from and integrate their own results back into Freva. This environment enables an ecosystem of plugins that promotes the exchange of results and ideas between researchers, and facilitates the portability to any other research project using a Freva instance.
  • Transparent and reproducible results. Every analysis run through Freva (including parameter configuration and plugin version information) is stored in a central database and can be viewed, shared, modified and re-run by anyone within the project. Freva optimises the use of computing and storage resources and paves the way for traceability in line with the FAIR data principles [9].

The Freva instance of ClimXtreme (XCES [7]), hosted at DKRZ, provides fast access to more than 10 million data files from models (e.g. CMIP, CORDEX), observations (e.g. ERA5, HYRAS, stations) and plugin outputs. The ClimXtreme community has actively contributed plugins to XCES, its biggest asset, with nearly 20 plugins of different disciplines available to all within the project.

We would like to show a practical application of the capabilities of XCES by using it to systematise the characterisation (e.g. return periods, severity, co-occurrence...) of several past extreme events extracted from the ClimXtreme Phase 1 catalogue. Such an application can be extended to create workflows focused, for example, on the rapid assessment of the analysis of currently occurring events, allowing a quicker response to stakeholders or the public in general.

 

References:

[1] https://www.fona.de/de/massnahmen/foerdermassnahmen/climxtreme.php

[2] https://www.climxtreme.net/index.php/en/

[3] https://www.fona.de/de/aktuelles/nachrichten/2023/231207_ClimXtreme_Phase_2_b.php

[4] http://doi.org/10.5334/jors.253

[5] https://github.com/FREVA-CLINT/freva-deployment

[6] freva.met.fu-berlin.de

[7] https://www.xces.dkrz.de/

[8] www-regiklim.dkrz.de

[9] https://www.go-fair.org/fair-principles/

 

 

How to cite: Lucio-Eceiza, E. E., Kadow, C., Bergemann, M., Fast, A., and Ludwig, T.: Freva for ClimXtreme: helping to systematize holistic analysis of extreme events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19970, https://doi.org/10.5194/egusphere-egu24-19970, 2024.

EGU24-20455 | Posters virtual | NH1.2

Investigating the effects of initial soil moisture and the uncertainty of Manning friction coefficient on flood hazard estimation and mapping. 

Athanasios Loukas, Anastasios Katsiolas, and George Papaioannou

Floods are among the most devastating water-related hazards and are primarily responsible for the loss of human life and destruction of the natural and man-made environment. This study addresses the estimation and mapping of flood hazard in small mountain watersheds with urban areas at the lowlands and the related uncertainty. Specifically, this research studies the flood hazard for the Metropolitan city of Volos in Central Greece, which is frequently affected by intense storms that cause flash floods. The above study area is crossed by three (3) streams.The methodology used in the study is divided into three stages. At first the 24-hour design storm hydrographs were constructed for the three sub-basins of the study area with using the mean IDF parameters and the relevant confidence limits. The Alternating Block Method was used for the design hyetographs for return periods, T = 50-year, T=100-year and T=1000-year (worst-case scenario). The second stage concerns the hydrological analysis using a rainfall-runoff model. Firstly, the net rainfall was estimated by using the U.S. Soil Conservation Service (SCS-CN) method for three (3) soil's Antecedent Moisture Conditions (AMC) for dry-average-wet conditions. Then, the net rainfall was transformed by using the Instantaneous Unit Clark hydrograph into discharge and the flood hydrographs for each return period were estimated. At the final stage, the flood hydrograph estimated for each watershed was routed through the hydrographic network using the HEC-RAS 2D hydraulic-hydrodynamic simulation (2D) model.  For the flow routing, Manning’s n was estimated for various cross sections by visual inspection and corresponding values reported in international reports. The “upper” and “lower” boundaries of Manning’s n were estimated as the -50% and +50% of the average Manning’s n values, respectively. In this simulation approach, flood hazard maps for three return periods, T=50, T=100 and T=1000 years considering three different soil moisture conditions and three different values of Manning’s n have been estimated. The values of Manning’s n in the flood plain were estimated by using land cover/land use data.  The flow routing with in the urban areas was simulated by the block rising method. In total twenty-seven (27) flood scenarios have been simulated for each watershed. The results were validated with the flooded areas during a specific historical flood event using the Critical Success Index (CSI) method and reports and photographs of the historical flood event. The results of hydrological analysis and hydraulic simulation were also compared with the results of the Greek Flood Hazard Management Plans.

How to cite: Loukas, A., Katsiolas, A., and Papaioannou, G.: Investigating the effects of initial soil moisture and the uncertainty of Manning friction coefficient on flood hazard estimation and mapping., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20455, https://doi.org/10.5194/egusphere-egu24-20455, 2024.

EGU24-22160 | Posters on site | NH1.2

Novel approach to quantifying long-term rainfall distribution variation: the region of Europe 

Andrew Barnes and Ioanna Stamataki

Climate change is changing rainfall and flood regimes across the world with severe and widespread impacts on society. Rainfall extremes are intensifying in frequency and magnitude due to the effects of climate change, and thus in this research, we introduce a new, novel framework for understanding how rainfall distributions are changing through time, enabling more accurate flood risk analysis. The framework offers two approaches to comparing rainfall distributions, the first of these utilises a stagnant benchmark distribution and the second highlights a moving benchmark approach. When combined the framework enables the identification of significant sudden and gradual changes in the distributions without the need to fit statistical distributions to the data.

 The region of Europe is selected as the case study and analysed in the four UN regions of Europe: Northern Europe, Eastern Europe, Southern Europe, and Western Europe. Using daily precipitation data generated using the ERA5 Reanalysis hourly data from the ECMWF’s Copernicus data store, the case study is used to highlight the capability of both frameworks to capture different forms of rainfall distribution shift.

 Comparing the frameworks presented revealed similar long term changes in the rainfall variation. The stagnant comparison showed that rainfall distributions have intensified since 1940 with a clear increase across all four regions of Europe regarding the percentage of days with rainfall, averaging at 2.75% across Europe. The largest changes seen are in the last comparison period for Eastern Europe (1960-1975) at 3.07% and in the latest comparison period (2005-2020) for Northern Europe (2.64%). The moving comparison method unveiled the strongest changes between the periods 1940-1960 and 1960-1980 with an average of 2.09% of rainfall days being intensified across all Europe. The most considerable shifts in rainfall variability occurred in Eastern (2.39%) and Western Europe (2.72%) during the 1960-1980 period.

 By applying it over the European region, this paper demonstrated how this novel approach can be used to identify long-term rainfall variation in the 20th century. The suggested frameworks do not rely on fitting statistical distributions and thus enable both long and short term change identification, providing flood risk managers a new solution to understanding local, regional and global rainfall variability and quantification. The analysis of the changing dynamics of precipitation patterns and the increase of the intensity of precipitation events, offers considerable potential for further investigations in the mitigation strategies of a resilient future.

How to cite: Barnes, A. and Stamataki, I.: Novel approach to quantifying long-term rainfall distribution variation: the region of Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22160, https://doi.org/10.5194/egusphere-egu24-22160, 2024.

The intensification of extreme precipitation in a warming climate has been shown in observations and climate models to follow approximately theoretical Clausius-Clapeyron scaling. However, larger changes have been indicated in events of short-duration which frequently trigger flash floods or landslides, causing loss of life. Global analyses of continental-scale convection-permitting climate models (CPCMs) and new observational datasets will be presented that provide the state-of-the-art in understanding changes to extreme weather (rainfall, wind, hail, lightning) and their compounding effects with global warming. These analyses suggest that not only warming, but dynamical circulation changes, are important in the manifestation of change to some types of extreme weather, which must be addressed in the design of new CPCM ensembles. We use our projections to provide the first analyses of impacts on infrastructure systems using a new consequence forecasting framework and show the implications for adaptation. It will be argued that a shift in focus is needed towards examining extreme weather events in the context of their ‘ingredients’ through their evolution in time and space. Coupled with exploration of their causal pathways, sequencing, and compounding effects – ‘storylines’ –, this can be used to improve both early warning systems and projections of extreme weather events for climate adaptation.

How to cite: Fowler, H.: Rapidly intensifying extreme weather events in a warming world: how important are large-scale dynamics in generating extreme floods?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22472, https://doi.org/10.5194/egusphere-egu24-22472, 2024.

EGU24-532 | ECS | Orals | NH1.3 | Highlight

Rapid unsupervised economic assessment of urban flood damage using SAR images 

jeremy Eudaric, Andres Camero, Kasra Rafiezadeh Shahi, Heidi Kreibich, Sandro Martinis, and Xiao Xiang Zhu

Climate change projections for 2030 indicate a concerning increase in the frequency of floods, which is expected to result in significant economic damages and losses on a global scale. The growth of urbanization has indeed increased flood risk, highlighting the need for a prompt evaluation of economic losses to facilitate rapid response and effective reconstruction. However, providing timely and accurate economic damage assessment immediately after a flood event is difficult and associated with high uncertainty. Remote sensing  data can support this task, but challenges such as cloud cover, infrequent return times from satellites, and the lack of ground truth data make supervised approaches challenging. To address these challenges, we propose a new economic damage assessment approach based on the analysis of multi-temporal and multi-source, Synthetic Aperture Radar (SAR) images before and after the flood peak with an unsupervised change detection method. This method utilizes computer vision techniques, specifically a pixel-based approach with SAR data (Sentinel-1 and TerraSAR-X/TanDEM-X) to monitor changes in buildings and the flood extension. It employs various threshold techniques and parameters to determine the optimal threshold values for highlighting changes and the presence of water. By using this method, our aim is to obtain an economic model based on pixels, which represents the volume of water surrounding or on each building and the flood extension. The purpose of this study is to support governments in decision-making processes and enable insurers to efficiently assess and compensate for damages caused by flood events. 

How to cite: Eudaric, J., Camero, A., Rafiezadeh Shahi, K., Kreibich, H., Martinis, S., and Zhu, X. X.: Rapid unsupervised economic assessment of urban flood damage using SAR images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-532, https://doi.org/10.5194/egusphere-egu24-532, 2024.

EGU24-957 | ECS | Posters on site | NH1.3

Flood Mapping Using High-Resolution Topography and Crowdsourced Data with the Geomorphic HAND Approach in Rural Plains 

Hassan Sabeh, Marie-George Tournoud, Nanée Chahinian, Chadi Abdallah, Roger Moussa, and Rouya Hdeib

Flood mapping is essential for risk management and emergency response. The most common approach is hydraulic modelling, a method that is still challenging and demanding in terms of data and computation. Low complexity models are an increasingly adopted alternative that are capable of achieving good results while using minimal data input and low calculation time. Yet, the reliability and effectiveness of such approaches remain unclear in flat and engineered plains. In this study we aim to optimize flood hazard mapping based on the Height Above Nearest Drainage (HAND) geomorphic approach by utilizing a high-resolution digital elevation model (15 cm) with crowdsourced data. The approach is tested on the Ostouane river basin (144 km2) in Lebanon, and validated using crowdsourced data of the January 2019 flood, which was the most intense flood within the past decade. The workflow begins by developing a database of spatial and topographic information, including the digital elevation model, bathymetry, land use and crowdsourced flood depths. Five scenarios representing different terrain configurations with varying levels of hydro-conditioning and feature inclusion (e.g. bathymetry, canals and levees) are simulated. The model’s thresholding is then optimized by integrating rating curves produced by 1D HEC-RAS hydraulic model to assess and correct HAND based synthetic rating curves (SRC). Results shows that extensive hydro-conditioning is necessary to improve the inundation extents within the floodplains. Correcting synthetic rating curves is essential to overcome errors produced by terrain conditioning. Overall, the model is able to yield high accuracy of flood extent when ensuring hydrologic connectivity between the river and floodplain and within the floodplain itself. Our findings indicate that leveraging high-resolution topography and crowdsourced inputs can enhance the accuracy of flood mapping results. However, achieving this precision necessitates a meticulous optimization procedure.

How to cite: Sabeh, H., Tournoud, M.-G., Chahinian, N., Abdallah, C., Moussa, R., and Hdeib, R.: Flood Mapping Using High-Resolution Topography and Crowdsourced Data with the Geomorphic HAND Approach in Rural Plains, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-957, https://doi.org/10.5194/egusphere-egu24-957, 2024.

EGU24-1081 | ECS | Orals | NH1.3

CFD modelling to investigate hydrodynamic forces on bridges in case of submergence and material deposition  

Natasha Petruccelli, Diego Panici, Alessio Domeneghetti, and Armando Brath

Increasingly frequent and intense flood events, combined with the remarkable industrialization process of cities, are placing transportation networks under stress. The loads that roads and railways must resist are nowadays often greater than those considered for their design; furthermore, their state of ageing is such that any disturbance (flood, earthquake, landslide) could cause a total or partial interruption of traffic resulting in socio-economic losses.
Bridges represent the most vulnerable component of a transport system and their failure can compromise the functionality of the entire network, as well as causing loss of life. During floods, bridges can be partially or completely submerged, having to withstand higher hydrodynamic loads which can lead to the collapse of the structure itself. Furthermore, accumulations of large wood and scour total around the bridge piers can reduce the load-bearing capacity of the structure and therefore its structural integrity.
In this study, we investigated the hydrodynamic actions and the 3-dimensional flow field at a model bridge (comprising deck and pier) using CFD (Computational Fluid Dynamics) modelling. Drag and lift forces acting on the rectangular-shaped deck were estimated for different submergence values to evaluate the structure's maximum permissible load. In particular, drag and lift coefficients were calculated by simulating various flow conditions (Froude number varying between  0.16 and 0.50) and adopting three different turbulence models (RNG, k-ε, k-ω).
In addition, the effect on the drag coefficient of the accumulation of large wood around the pier was also examined, considering different geometries. Numerical simulations, performed for both fixed and live river bed conditions, were validated using experimental data. However, the trends of the synthetic curves constructed so far have presented characteristics similar to those present in the literature, with all positive values ​​for the drag coefficient and negative ​​for the lift coefficient. 
The emerging evaluations allow us to provide useful indications to designers to evaluate the possible state of stresses on existing bridges and improve knowledge for designing new ones.

How to cite: Petruccelli, N., Panici, D., Domeneghetti, A., and Brath, A.: CFD modelling to investigate hydrodynamic forces on bridges in case of submergence and material deposition , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1081, https://doi.org/10.5194/egusphere-egu24-1081, 2024.

EGU24-1594 | ECS | Orals | NH1.3

Drivers of coastal real estate demand under flood model predictions in the UK 

Avidesh Seenath, Scott Mark Romeo Mahadeo, Matthew Blackett, and Jade Catterson

Flood model predictions are becoming increasingly available online through open access flood risk maps and communications. While these predictions are important for flood management, their inherent uncertainty presents a considerable risk for real estate markets, a leading indicator of macroeconomic performance.  We, therefore, need to understand the factors influencing real estate demand in an era of open access flood model predictions. Here, we investigate the role of gender, education, employment, place of residence, caring responsibilities, income, insurance, location preferences, level of risk aversion, and flood experience and awareness on coastal real estate demand decisions in the UK in response to flood model predictions. Here, our objective is test whether access to flood predictions is a leading driver of real estate demand decisions or whether alternative factors influence how people perceive such predictions. We achieve this by applying an inter-disciplinary approach, involving numerical flood modelling, a novel experimental willingness-to-pay real estate survey of UK residents in response to flood model outputs, statistical and geospatial modelling, and thematic analysis. Our preliminary findings indicate that access to flood model predictions is the primary factor influencing real estate demand decisions, whereas alternative factors considered have negligible impact. Such preliminary findings suggest that we need to re-think how flood model predictions are communicated in order to minimise real estate risks.  

How to cite: Seenath, A., Mahadeo, S. M. R., Blackett, M., and Catterson, J.: Drivers of coastal real estate demand under flood model predictions in the UK, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1594, https://doi.org/10.5194/egusphere-egu24-1594, 2024.

EGU24-1692 | Orals | NH1.3 | Highlight

A Fresh Start for Flood Estimation in Ungauged Catchments 

Ross Woods, Yiming Yin, Giulia Evangelista, Pierluigi Claps, Giulia Giani, Yanchen Zheng, Gemma Coxon, Roberto Quaglia, Dawei Han, and Miguel Rico-Ramirez

Flood estimation in ungauged basins is important for flood design, and for improving our understanding of the sensitivity of flood magnitude to changes in climate and land cover. Flood estimates in ungauged basins by current methods (e.g. statistical regression, unit hydrograph) have high uncertainty, even in places with dense observing networks (e.g. +/- 50-100% in the UK). Reductions in this uncertainty are being sought by using alternative methods, such as continuous simulation using hydrological models (spatially-distributed or lumped), and event-scale derived distribution approaches. The very significant challenges for reliable application of continuous simulation models in ungauged catchments are well known. So far there has been only limited application of machine learning techniques to this problem, but it seems an obvious route to try, but to exploit the big-data strengths of this approach, the problem must be recast to extract information from many more events at each site than just annual maximum events.

The event-scale derived distribution approach also has challenges, which we explore below. The derived distribution approach at the event scale typically combines the following elements: a stochastic rainfall model, an event-scale rainfall-runoff model (including “losses” and a “baseflow” component), and a runoff routing model. In principle, every element of this approach may be considered as a (seasonally varying) random variable. The flood peak distribution is obtained by integrating over joint distributions of the model elements. After giving an overview of our approach, I will focus on challenges regarding the catchment response time associated with flood events.

How should we define catchment response time? Why do we need this quantity and how will it be used? What are the relative merits of empirical and model/theory-based approaches? Specifically, I will discuss the empirical DMCA method for catchment response time of Giani et al, https://doi.org/10.1029/2020wr028201). How is it relevant for ungauged catchments? What does DMCA really measure? How do we assign hydrological meaning to this empirical response time? How does this response time vary between events and catchments?

How to cite: Woods, R., Yin, Y., Evangelista, G., Claps, P., Giani, G., Zheng, Y., Coxon, G., Quaglia, R., Han, D., and Rico-Ramirez, M.: A Fresh Start for Flood Estimation in Ungauged Catchments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1692, https://doi.org/10.5194/egusphere-egu24-1692, 2024.

EGU24-3629 | ECS | Orals | NH1.3

Flood plain inundation modeling with explicit description of land surface macrotopography 

Simone Pizzileo, Giovanni Moretti, and Stefano Orlandini

Land surface topography plays an essential role in flood plain inundation modeling. High-resolution digital surface models (DSMs) based on LiDAR surveys have become increasingly accessible in various geographical areas. Nevertheless, common practice involves filtering out land surface macrostructures, such as trees and buildings, by using obtained digital terrain models (DTMs) to represent the land surface hydraulic geometry. This is done by letting resistance coefficients represent the effects of both micro and macrostructures on surface flow propagation. In addition, significant information loss is observed when digital terrain models are coarsened for computational efficiency.

In the present study, physically meaningful unstructured meshes are automatically extracted from high-resolution digital surface models to explicitly describe land surface macrostructures. This is achieved by extracting relevant ridges at a selected level of representation without applying any coarsening or depression filling pre-processing. The effects of these macrostructures on floodwater propagation are evaluated by comparing simulations obtained by using digital terrain models and related Manning coefficients, simulations obtained by using digital surface models representing land surface macrostructures and related Manning coefficients, and observations for a real flood inundation event occurred after a levee failure in the lowlands adjoining the Panaro River in Northern Italy in 2020.

The explicit description of land surface macrostructures based on a 1-m digital surface model is found to yield a 42% improvement in the prediction of flooded area extent, a 36% improvement in the prediction of flooded areal position, and a 24% improvement in the prediction of flood plain inundation travel time with respect to the case in which resistance coefficients representing both land surface micro and macrostructures are used. Unstructured meshing of land surface macrostructures based on extracted ridge networks is essential for achieving a detailed description of land surface hydraulic geometry without altering the original topographic data, while also preserving computational efficiency. The obtained results highlight the role of natural and human-made macrotopographic structures in delineating flood plain inundation models and generating flood hazard mapping. These tools represent valuable assets in the context of Emergency Action Planning (EAP) and prevention strategies.

How to cite: Pizzileo, S., Moretti, G., and Orlandini, S.: Flood plain inundation modeling with explicit description of land surface macrotopography, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3629, https://doi.org/10.5194/egusphere-egu24-3629, 2024.

EGU24-3747 | Posters on site | NH1.3

Developing a flood image detection model using deep learning algorithms 

Cheng-Lin Yang

As the impact of climate change intensifies, the frequency of short-duration heavy rainfall events gradually increases, posing a serious challenge to urban infrastructure and underground drainage systems. Assessing flood-prone areas and disaster extents relies heavily on manual surveys, lacking real-time and effective methodologies. Our study uses Mask R-CNN deep learning and closed-circuit television (CCTV) flood images to develop a real-time and effective flood detection model. The results of our study demonstrate that the proposed flood image recognition model achieves a precision of 60.6%, a recall rate of 92.2%, and an F1 score of 73.1 for the flood category. These results signify the model's exceptional capability of the model in flood detection. Additionally, through on-site measurements of road dimensions and binary matrix-based area estimation, the average error is only 1.6%. This model can be applied effectively and serves as a reference for authorities to promptly determine the occurrence of flooding and the extent of the disaster, thus facilitating the formulation of more effective disaster response measures. The developed model exhibits promising potential for real-time flood detection in urban disaster management, providing a valuable tool for authorities to respond promptly to the dynamic challenges posed by climate change.

How to cite: Yang, C.-L.: Developing a flood image detection model using deep learning algorithms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3747, https://doi.org/10.5194/egusphere-egu24-3747, 2024.

EGU24-4842 | ECS | Posters on site | NH1.3

Substantial increase in future fluvial flood risk projected in China's major urban agglomerations 

Ruijie Jiang, Hui Lu, Kun Yang, Deliang Chen, Jiayue Zhou, Dai Yamazaki, Ming Pan, Wenyu Li, Nan Xu, Yuan Yang, Dabo Guan, and Fuqiang Tian

Floods are one of the most destructive natural disasters and projecting future flood risk is essential for protecting lives and livelihoods. China is in the process of rapid urbanization, and most of the urban agglomerations are distributed on floodplains, facing high fluvial flood risk. The effect of urban spatial expansion, instead of densification of assets within existing urban cells, on flood risk has rarely been reported. Here, based on the latest projected urban land data and bias-corrected CMIP6 outputs, we project the future flood risk of seven urban agglomerations in China, home to over 750 million people. The inundated urban land areas in the future are projected to be 4 to 19 times that at present, with southern China facing the greatest increase. Although climate change is the main driver for this strong projected rise in flood risk, the inundated urban land areas will be underestimated by 10-50% if the urban spatial expansion is not considered. Urban land is more likely to be inundated than non-urban land, and the newly-developed urban land will be inundated more easily than the historical urban land due to the marginal expansion of urban land. The results demonstrate the urgency of integrating climate change mitigation, reasonable urban land expansion, and increased flood protection levels to minimize the flood risk in urban land.

How to cite: Jiang, R., Lu, H., Yang, K., Chen, D., Zhou, J., Yamazaki, D., Pan, M., Li, W., Xu, N., Yang, Y., Guan, D., and Tian, F.: Substantial increase in future fluvial flood risk projected in China's major urban agglomerations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4842, https://doi.org/10.5194/egusphere-egu24-4842, 2024.

EGU24-5935 | ECS | Orals | NH1.3

Assessing the flooding hazard through a probabilistic approach including earthen levees vulnerability estimate     

Bianca Bonaccorsi, Silvia Barbetta, and Giuseppe Tito Aronica

Levees collapse cause huge financial and social losses, especially in highly developed areas of many countries. Since that 2563 floods occurred in Europe between 1980 and 2010 (EEA, 2018), the European Parliament issued the Floods Directive, approved in 2009, in which EU Member States are invited to minimise this risk of failure, improving methods and finding simple solutions for large-scale application. For this reason, the scientific community is gradually performing stochastic approaches allow a large number of simulations runs in a Monte Carlo framework, providing the basis for a probabilistic risk assessment considering also the influence of levee breaches on the flood risk (Apel et al., 2006, Castellarin et al., 2011). Indeed, in many studies, seepage analyses account only the hydraulic boundary conditions, i.e.  the water head upstream of the embankment (Tracy et al., 2016, 2020).  

In this context, the present work is focused on the evaluation of the residual flood risk through the analysis of earthen levees’ seepage vulnerability. In particular, the levee fragility curves determined with the use of simplified and expeditious approaches and those assessed by using geotechnical finite element models (i.e. PLAXIS 2D) are compared. Furthermore, the goal of this study is to find the relation between the frequency of levee’s failure due to hydraulic and geotechnical conditions, to aim of define the conditional probability of the residual flood risk.

 

References

Apel, H., Annegret, H. T., Bruno, M., & Günter, B. (2006). A probabilistic modelling system for assessing flood risks. Natural Hazard, 38, 79-100. https://doi.org/10.1007/s11069-005-8603-7.

Castellarin, A., Di Baldassare, G., & Brath, A. (2011). Floodplain management strategies for flood attenuation in the River Po. River Research and Applications, 27(8), 1037 –1047. https://doi.org/10.1002/rra.1405.

EEA, European Environment Agency. (2018). European past floods [Online]. Copenhagen, Denmark: Author. Retrieved from https://www.eea.europa.eu/data-and-maps/data/european-past-floods/ .

Tracy, F.T., Brandon, T. L., Corcoran, M.K. (2016). Transient seepage analyses in levee engineering practice, Technical Report TR-16-8, U.S. Army Engineer Research and Development Center, Vicksburg, MS, http://acwc.sdp.sirsi.net/client/en_US/search/asset/1050667.

Tracy, F.T., Ryder, J.L., Schultz, M.T., Ellithy, G.S., Breland, B.R., Massey, T.C., Corcoran, M.K. (2020). Monte Carlo Simulations of Coupled Transient Seepage Flow and Soil Deformation in Levees. Scalable Computing Practice and Experience 21(1):147-156. https://doi.org/10.12694/scpe.v21i1.1629.

How to cite: Bonaccorsi, B., Barbetta, S., and Aronica, G. T.: Assessing the flooding hazard through a probabilistic approach including earthen levees vulnerability estimate    , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5935, https://doi.org/10.5194/egusphere-egu24-5935, 2024.

EGU24-6509 | Orals | NH1.3

Dam operating strategies and hydrodynamic modeling to mitigate floods in the lower Tagus valley similar to the 1979 catastrophic event  

Diego Fernández-Nóvoa, Alexandre M. Ramos, José González-Cao, Orlando García-Feal, Cristina Catita, Moncho Gómez-Gesteira, and Ricardo M. Trigo

The lower valley of the Tagus River, one of the most important rivers in the Iberian Peninsula, is a particularly relevant and vulnerable area in terms of flood impact. This valley is characterized by a flattened and large alluvial plain, which implies that floods can affect large areas of territory, causing significant damage and affecting a large number of people. Although several floods have occurred in the lower Tagus valley, the one in February 1979 stands out, since the vast flooded area affected around 10,000 people, many of whom were evacuated or made homeless. The Tagus River flow in its lower valley is controlled, to a large extent, by the functioning of the Alcántara dam, which has the largest water storage in the Tagus basin. In this context, this study aims to develop strategies to take advantage of this infrastructure to effectively mitigate floods in the lower Tagus valley. For that, dam operating strategies, focused on flood mitigation, are developed sustained on a sequence of logical principles, such as avoiding inducing man-made floods or maintaining average water storage similar to the actual one. The effectiveness of the proposed strategies, in terms of flood mitigation, is analyzed by applying the Iber+ hydrodynamic model. For this, the numerical model is validated in the lower Tagus valley by evaluating its ability to reproduce the outstanding flood of 1979. Additionally, several Digital Elevation Models (DEMs) are also analyzed to determine which is the most accurate for the area under scope. The results show that Iber+ model, coupled with Copernicus DEM, is able to provide an efficient reproduction of this flood. In particular, the simulation shows good agreement with some descriptions and watermarks available for the 1979 event. This also allows the analysis of this historical event from a hydrologic-hydraulic perspective, which contributes to improving knowledge and understanding of how floods occur and develop in the lower Tagus valley.

Regarding flood mitigation, results indicate that, since 1970, when data is available, the frequency of floods is reduced by more than 80%, compared to the natural flow regime, with the application of the proposed strategies. In addition, the mitigation of the most extreme floods that occurred during the analyzed period, is also achieved. In particular, peak river flows are reduced for the most extreme events. This implies that flood extension is reduced by around 5-10% in the lower Tagus valley. A more efficient mitigation is achieved for flood indicators closely linked to the damage caused by these events. Thus, water depth is reduced by around 25% and water velocity by around 25-30%, in the flooded areas, for the most extreme events. This corroborates the effectiveness of the proposed dam operating strategies to mitigate floods in the lower Tagus valley through an adequate dam functioning.

The developed proposal provides an affordable approach to flood mitigation in comparison with the construction of additional structural measures, which could also be applicable to other areas vulnerable to floods affected by dam-regulated rivers.

How to cite: Fernández-Nóvoa, D., Ramos, A. M., González-Cao, J., García-Feal, O., Catita, C., Gómez-Gesteira, M., and Trigo, R. M.: Dam operating strategies and hydrodynamic modeling to mitigate floods in the lower Tagus valley similar to the 1979 catastrophic event , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6509, https://doi.org/10.5194/egusphere-egu24-6509, 2024.

Developing reliable and efficient flood modelling systems on a large scale is crucial for addressing errors and inconsistencies in both observations and modelling. However, the computational demands of hydrodynamic models have constrained their widespread application to coarse resolutions (30m-1km), compromising accuracy by neglecting the local and small-scale features that may significantly influence flooding, especially in urban areas. Furthermore, traditional models struggle to effectively incorporate river bathymetry, especially given the significant flood volume conveyed by the river channel during floods. These models often rely on surveyed cross-sections for river channel representation, leading to missing topography between cross-sections and hindering the resolution of complex floodplain flow paths. To resolve small-scale effects in limited areas while simulating large domains, grid adaptation methodologies are implemented in this project to locally adjust the resolution of the computation in a static or a dynamic way. A hybrid 1D-2D flood model is developed, incorporating the static/dynamic adaptive mesh generation and an integrated sub-/super grid channel model. The sub-/super grid channel is applied to accommodate situations where river channel width exceeds or fall below the grid resolution. Parallelized with GPU architecture, the performance of hybrid 1D-2D with either static or dynamics nonuniform structured grid was thoroughly evaluated, benchmarked with the full resolution CPU solver, shedding light on their effectiveness in enhancing flood modelling approach.

How to cite: Rong, Y., Bates, P., and Neal, J.: Towards a large-scale locally relevant flood modelling using adaptive mesh generation and an integrated sub-/super grid channel solver, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6787, https://doi.org/10.5194/egusphere-egu24-6787, 2024.

Recent climate change has led to extreme floods surpassing levee design criteria, posing a threat to safety. Consequently, there is a demand for the development of technologies capable of handling such severe floods. In this study, a method assessing failure probabilities, represented by fragility curves, was developed for the levee slope under rapid drawdown. The time-dependent probabilistic stability assessment of the levee slope due to a water level drop was explored. Integrating seepage analysis results from finite element analysis with slope stability analysis, Monte Carlo simulations were conducted to scrutinize the time-dependent behavior of the levee slope under rapid drawdown conditions. The probability of failure was calculated to develop fragility curves for the levee slope. The developed fragility curves were significantly influenced by the drawdown rate. Since the drawdown rate is determined through hydraulic analysis based on flood scenarios, the stability of the water-side slope of the embankment due to a water level drop will be greatly affected by climate change. The fragility curves obtained using the proposed methods are valuable for risk assessment, offering information to evaluate the performance of the levee under various water level drawdown conditions.

How to cite: Cho, S. E.: Fragility assessment of levee based on time-dependent reliability analysis under rapid drawdown, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7672, https://doi.org/10.5194/egusphere-egu24-7672, 2024.

Levees are linear structures that can be thousands of kilometers long and play a very important role in flood protection. They are usually monitored by traditional direct survey techniques, such as CPTU or coring, or piezometers, which provide high accuracy, but are localized and performed in predetermined locations.

As a result, long distances between investigated sections limit the detailed analysis of the entire structure. In addition, predetermined locations may not cover areas of actual potential weakness. Recently, new survey technologies from aerial media (drones) have been successfully applied to obtain a first level of levee investigation in order to identify the location of possible weak areas or potential locations of levee failure, so as to plan further local investigations in those areas.

Usually, levee failures are localized in the presence of:

(i) concrete or other materials structures passing the levee;

(ii) large trees, which can be dangerous because their roots are a preferred route for water infiltration. In addition, at higher erosion levels of the river bank, large trees can promote bank collapse due to their weight (i.e. cantilever failure);

(iii) sections where unfavorable conditions of the levee body, such as soils with high permeability or the presence of animal burrows crossing the levee or obstructed drains, prevent proper drainage and bring the phreatic surface close to the levee surface.

From previous experience, we have noticed that several times levee failures have occurred at sections previously vegetated by reeds. Reed canes usually grow on sandy soils and, in addition, are characterized by very deep and large roots, possible routes of localized infiltration through the body of the levee. From these observations comes the idea of using reedbeds as indicators of sandy soils and possible weak levee sections;

Thus, we performed two UAV-supported surveys on the same test area aimed at identifying the position and extension of the reeds vegetated areas, in combination with local on-site surveys with soil sampling along levee transversal sections, to compare and combine the obtained results. The RGB orthophotos obtained by the two surveys have been elaborated to determine the DSM and the vegetation cover map of the embankment, to compare them in different seasons. The obtained data have been calibrated with on-site surveys conducted by vegetation experts. To facilitate the identification of reedbeds, the first campaign has been carried out in winter, when reedbeds are yellowish in color, unlike short grass. In areas identified as reedbed vegetated, the soil has been sampled by coring and fully classified in the geotechnical laboratory to check if reedbed can effectively be an indicator of sandy soils. Similarly, other samples have been taken from sections not covered by reeds for comparison.

The final aim is to test the possibility of using vegetation maps as an indicator of weak sections of the embankment, thus to develop an innovative method of low-cost aerial monitoring of levee structures that can provide an initial state of information and identify areas in need of further direct investigation in order to define the necessary maintenance works, decreasing associated risks.

How to cite: Dalla Santa, G. and Simonini, P.: Reeds influence of levee hazards: detection through UAV survey and soil geotechnical analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8071, https://doi.org/10.5194/egusphere-egu24-8071, 2024.

EGU24-9050 | ECS | Orals | NH1.3 | Highlight

Is 3D modelling necessary for simulating long-duration urban flooding? 

Shuyue Yu, Xuefang Li, Vasileios Kitsikoudis, Guilhem Dellinger, and Benjamin Dewals

Urban flood modeling within complex urban environments demands sophisticated methodologies. While 2D computational models have historically served as foundational tools, their inherent limitations in capturing the intricate three-dimensional dynamics necessitate further exploration. Our research endeavors to expand this understanding by delving into 3D computational simulations, providing a more holistic perspective on urban flood dynamics.

In the current research, we conducted 3D simulations to replicate urban flood processes, drawing comparisons with earlier 2D modeling results and experimental observations. The simulations were executed considering various urban layouts and turbulence closure models. The urban layouts include two groups, totaling 13 architectural models. These models feature varying numbers or positions of openings on their exterior walls to represent architectural elements such as doors and windows that could allow floodwaters to enter in the interior of the buildings. As for the turbulence equations, k-omega SST and k-epsilon were considered. By analyzing the surface velocity, flow depth, and flowrate distribution, preliminary findings indicate that 3D simulations offer enhanced accuracy in capturing intricate flow patterns within urban settings compared to their 2D counterparts. Moreover, the tested simulations from various turbulence models influence the 2D and 3D simulations in different ways. This direct comparison allowed us to dissect and understand the influence of turbulence modeling on the accuracy of 3D simulations, thereby enhancing the robustness of our findings.

After obtaining the relevant results, we applied them to flood risk analysis. Compared to traditional 2D analyses, we derived some new insights to guide informed decision-making, enhancing the applicability of our approach. By integrating sophisticated modeling techniques and risk evaluations, this study paves the way for more resilient and adaptive urban planning strategies, ensuring safer and more sustainable urban environments in the face of increasing flood challenges.

How to cite: Yu, S., Li, X., Kitsikoudis, V., Dellinger, G., and Dewals, B.: Is 3D modelling necessary for simulating long-duration urban flooding?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9050, https://doi.org/10.5194/egusphere-egu24-9050, 2024.

EGU24-9555 | ECS | Orals | NH1.3

A tracer-aided criterion to discretize pluvial and fluvial flood hazard maps in catchment scale shallow water models 

Pasquale Perrini, Luis Cea, Andrea Gioia, and Vito Iacobellis

Knowing the nature of the flood hazard is a crucial factor for improving the resilience of the urban areas, since awareness, preparedness and early warning systems are based on the scientific tools such as the 2D depth-averaged shallow water models. Inland flood hazard primarily stems from pluvial and fluvial inundations, typically modeled separately respecting the pertaining spatial domains of the assessment, namely the urban areas and the riverine floodplains. Considering the high computational power and efficiency of both hardware and codes, the catchment scale hydrological-hydrodynamic modeling is becoming an increasingly adopted approach in flood hazard assessments. Since a complete rainfall-induced routing is preserved, these simulators determine fluvial, pluvial and compound inundations caused by heavy storm events within the entire watershed.

However, this approach leads to flood extent maps in which the inundations such as those resulting from pluvial and fluvial processes, are usually not differentiated, even if significant disparity in the space-time scales and volumes of water are involved. Indeed, these two hazards follow distinct normative and regulatory flood risk management rules among different countries. 

With such a rationale we established a tracer-aided criterion to systematically categorize and map pluvial and fluvial hazard in a catchment scale shallow water model, exploiting the advection process of a conservative tracer. The physically based methodology, implemented in the GPU-parallelized Iber+ software and its water-quality module (IberWQ+), is applied in a small urban catchment for multiple probabilistic scenarios. The results demonstrate the effectiveness of nesting transport and shallow water equations, univocally discretizing the two inundation sources in function of the computational cells reached by the tracer. This enables to define the spatial domains of the pluvial and fluvial processes, providing valuable insights for holistic catchment-scale flood risk management. Additionally, the advancements achieved by the proposed method are showcased in comparison to commonly employed modeling techniques for mapping fluvial inundations. As the tracers continue to improve our understanding of catchment sciences, we conceptualized them role through an abstraction that can aid surface hydrodynamic modelling to identify pluvial and fluvial sources of hazard.

How to cite: Perrini, P., Cea, L., Gioia, A., and Iacobellis, V.: A tracer-aided criterion to discretize pluvial and fluvial flood hazard maps in catchment scale shallow water models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9555, https://doi.org/10.5194/egusphere-egu24-9555, 2024.

EGU24-11106 | ECS | Posters virtual | NH1.3

Impact of vegetation on urban open-channel flow: Practical experiment with 2D IBER hydraulic simulations in Monterrey, Mexico. 

Jacob Jesús Nieto Butrón, Nelly Lucero Ramírez Serrato, Selene Barco Coyote, Fabiola Doracely Yépez Rincon, and Mariana Patricia Jácome Paz

Flooding is a constant danger in many cities. To prevent and mitigate their impacts, mathematical modeling is carried out to simulate the behavior of the flow within the environment and define the possible flood zones. Incorporating vegetation in hydraulic models is pivotal for understanding its impact on flow characteristics, sediment transport, and channel morphology.

The Santa Catarina River in Monterrey, Nuevo León, Mexico, grapples with irregular water flows. During dry seasons, minimal water levels promote unchecked vegetation growth along its banks and bed, potentially obstructing normal flow. Conversely, extreme weather events like hurricanes lead to rapid surges, sweeping away vegetation and debris. Balancing this fluctuation—from sparse to intense flows—presents challenges in managing the river's vegetation, necessitating strategies that reconcile environmental preservation with urban infrastructure resilience.

For this purpose, This study utilized two hydraulic models through IBER to assess vegetation's impact on flood simulations. One model employed a Digital Elevation Model (DEM), portraying terrain topography. The second model used a Digital Surface Model (DSM) integrating manually digitized vegetation from (2020) Google Earth imagery. Assigned heights of 3m for shrubs and 15m for trees emulated their impact on water flow. Both the DEM and DSM, with a 5-meter resolution, were obtained via LiDAR techniques from the INEGI government web platform. the models also utilized a land use classification obtained from a Sentinel-2 satellite image (from 2023). Hydrological data for both models were derived from the cumulative rainfall during Hurricane Alex in 2010.

The findings highlight significant changes in flood patterns attributed to vegetation. Its presence alters the flow, shifting the flood zone towards a southwest residential-commercial area. In this integrated model, the maximum depth reaches 16.78 meters, compared to 10.70 meters in the DEM-based hydraulic model. Additionally, the consistently affected area deepens from 2 meters to 4.37 meters when considering the vegetation-inclusive DSM-based approach.

These findings underscore the crucial role of vegetation in shaping flood pathways within urban environments, emphasizing the need to consider both natural and human-introduced elements in flood risk management strategies. Future research directions could explore the evolving impact on populations across varied flood zones and conduct comprehensive cost evaluations regarding risk mitigation, recovery efforts, and infrastructure fortification. These avenues present promising trajectories for further studies, offering insights into the socio-economic and financial implications of diverse flooding patterns in urban settings.

How to cite: Nieto Butrón, J. J., Ramírez Serrato, N. L., Barco Coyote, S., Yépez Rincon, F. D., and Jácome Paz, M. P.: Impact of vegetation on urban open-channel flow: Practical experiment with 2D IBER hydraulic simulations in Monterrey, Mexico., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11106, https://doi.org/10.5194/egusphere-egu24-11106, 2024.

EGU24-11521 | ECS | Orals | NH1.3

Assessment of sewer network data quality on urban pluvial flood modeling with a 2D/1D dual drainage model 

Carlos Montalvo, Paolo Tamagnone, and Luis Cea

Urban pluvial floods are one of the most common water-related hazards and are going to become more frequent and severe looking at the upsetting climate projections. These events mainly occur due to intense and short precipitation events, leading to the overload of the sewer network and resulting in physical, economic, and even human losses. To address this hazard, effective methods are needed to estimate the scale and impact of pluvial flood events and to develop mitigation strategies. In this context, 2D/1D dual drainage models have become one of the most useful tools for these purposes, being able to simulate all hydraulic phenomena occurring on and beneath the surface. However, these models require detailed information about the topography and geometrical specifications of the sewer network, which are not always readily accessible or, when available, are often incomplete or of poor quality, particularly in large urban environments.

In this work, considering that pluvial flood studies are becoming more popular and several numerical tools are available, we wanted to address a recurrent question raised by the flood modeler community: is the effort/level of complexity of implementing a detailed dual drainage model worth it? To answer this question, we assess the influence of sewer network data quality on the results of water depth and velocity obtained with a 2D/1D dual drainage model applied to urban flood modelling. For this purpose, an ad-hoc 2D/1D hydraulic model was implemented to simulate the complex network system of the city of Differdange (LU) exploiting the recently developed Iber-SWMM. This city was chosen as study case because it has experienced several flooding events in recent years, such as those recorded in 2021, and it has an extensive dataset of detailed geospatial data available, enabling the setup of a high-resolution resolution and fully coupled 2D/1D dual drainage model.

Sewer network links were classified based on their physical properties, such as diameter and length. The sewer network layout was gradually simplified, starting from the minor links to the more complex segments of the network, obtaining new simplified versions of the network that could represent incomplete or poor-quality scenarios. These simplified versions were successively implemented in the 2D/1D model. The comparison between the results of the complete and comprehensive model and the simplified scenarios reveals the impacts of the quality of the sewer network information on pluvial flood modeling.

How to cite: Montalvo, C., Tamagnone, P., and Cea, L.: Assessment of sewer network data quality on urban pluvial flood modeling with a 2D/1D dual drainage model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11521, https://doi.org/10.5194/egusphere-egu24-11521, 2024.

EGU24-11904 | ECS | Posters on site | NH1.3

The role of predisposing factors in determining the rainfall intensity necessary to cause flash floods in Portugal 

Caio Vidaurre Nassif Villaça, José Luís Zêzere, and Pedro Pinto Santos

Flash floods are often responsible for deaths and damage to infrastructure. The general objective of this work is to create data-based models to understand how the predisposing factors influence the triggering factor (precipitation) in the case of flash floods in the continental area of Portugal. Flash floods occurrences were extracted from the DISASTER database, which contains the location and date of historical flood events in the study region. Historical daily rainfall data was collected automatically from the Copernicus database. We extracted the accumulated precipitation for 3 days preceding each event and calculated the rainfall intensity. The predisposing factors were extracted considering the whole basin that corresponds to each flood event. The  analyzed predisposing factors were: accumulated flow, average slope, average elevation, predominant slope aspect, predominant lithology and soil properties (percentage of clay, coarse sand and coarse elements and field capacity). Elevation can often define different climatic and vegetation zones, while slope influences both the concentration and the infiltration capacity. The slope aspect can influence the amount and intensity of rainfall that affects the hillslope, as well as the amount and intensity of solar radiation. Lithology represents the properties of bedrock and the soils properties influence water infiltration and percolation. The Random Forest algorithm and the Leave-One-Out cross-validation technique were used to evaluate the model's performance and create a final model that identifies the relationship between the predisposing factors and the different rainfall intensities related to each flash flood occurrence. The final model obtained a root mean square error (RMSE) value of 3, an acceptable value for the objectives of the work. The percentage of coarse elements in the soil, average slope and field capacity were defined as the most important factors in the model for defining the amount of rainfall needed for flash floods to occur in mainland Portugal. The model developed can help to predict flash flood occurrence and future work involves combining the susceptibility model with the model created in this project to create a warning system that can be updated in real time, taking into account rainfall forecasts.

Acknowledgements: This work was financed by national funds through the FCT – Fundação Portuguesa para a Ciência e Tecnologia, I.P., under the grant to support the completion of the doctoral dissertation with the reference 2022.14473.BD.

How to cite: Vidaurre Nassif Villaça, C., Luís Zêzere, J., and Pinto Santos, P.: The role of predisposing factors in determining the rainfall intensity necessary to cause flash floods in Portugal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11904, https://doi.org/10.5194/egusphere-egu24-11904, 2024.

EGU24-12195 | ECS | Orals | NH1.3

Modeling flood fatalities in the Italian context: an empirical approach 

Mina Yazdani, Christian N. Gencarelli, Paola Salvati, and Daniela Molinari

Floods are among the most frequent and damaging natural hazards, affecting millions of people worldwide, and the risk of catastrophic losses due to flooding is expected to increase as a result of climate change. The possibility of predicting and estimating the expected fatalities in flood-prone regions is among the top priorities of decision-makers in flood risk management. Thus, predicting the conditions leading to loss of life is crucial for assessing the risk to the population. Here we focus on the Po River District in Northern Italy which covers the largest Italian hydrographic basin. We demonstrate that the occurrence of flood-related fatalities can be estimated by utilizing a random forest (RF) algorithm applied to a dataset of fatalities that occurred in this area from 1970 to 2019. This method relies on nine explanatory variables that describe the hazard intensity, and the environmental and sociodemographic conditions leading to fatalities. The proposed model is a primary attempt to estimate the probability of flood-related fatalities in the Italian context, and it provides a proxy for the quantitative estimation of flood risk to the population.

How to cite: Yazdani, M., N. Gencarelli, C., Salvati, P., and Molinari, D.: Modeling flood fatalities in the Italian context: an empirical approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12195, https://doi.org/10.5194/egusphere-egu24-12195, 2024.

EGU24-12935 | ECS | Orals | NH1.3

Estimating flood exceedance probabilities for several levee breach scenarios for an urban riverine environment in Toronto, Canada 

Florence Mainguenaud, Usman Khan, Laurent Peyras, Claudio Carvajal, Jitendra Sharma, and Bruno Beullac

Assessing flood risk requires the combination of flood hazard, exposure, and vulnerability.  Hence, flood hazard is a key component of flood risk assessments. As flood propagation is impacted by hydraulic structures built along the river, flood defense such as levees have gained attention as they are rarely included in large scaled flood risk assessments. However, flood events such as hurricane Katrina showcased the impact that levee failure has on flow depth, velocity, and flood extent. Therefore, its consideration should be regularly implemented in flood risk assessments. However, with current flood risk assessment methods, considering different levee failure scenarios results in numerous flood scenarios, simulations, and hazard maps. The multiplication of simulations and maps increases the complexity of flood risk management. We propose to improve flood hazard assessments by considering a single probabilistic flood map accounting for several flood events and levee breaching scenarios. For flood events enabling the performance assessment of the levee (i.e. levee breaching), we assessed levee failure probabilities, associating each levee segment to a fragility curve. Then, we defined breaching and non-breaching scenarios and ran flood simulations using HEC-RAS and its integrated parametric levee breaching model. We propose a new method to compute flood scenario probabilities and flood exceedance probabilities. The cumulative flood exceedance probability provides a curve for every location of the flooded area. Using GIS, we applied this method to the entire flooded area, resulting in an interactive flood hazard map. An application to the Etobicoke Creek located in the Greater Toronto Area showed that this new approach provides an operational levee breaching flood hazard method that can be used in integrated flood risk assessments.

How to cite: Mainguenaud, F., Khan, U., Peyras, L., Carvajal, C., Sharma, J., and Beullac, B.: Estimating flood exceedance probabilities for several levee breach scenarios for an urban riverine environment in Toronto, Canada, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12935, https://doi.org/10.5194/egusphere-egu24-12935, 2024.

EGU24-15306 | ECS | Posters on site | NH1.3

Numerical modelling of flood hazard mitigation strategies: the case of the Baganza River after the 2014 inundation of the city of Parma 

Alessia Ferrari, Renato Vacondio, and Paolo Mignosa

Urban flood risk mitigation is a paramount priority given the increasing frequency of flood events, which have become predominant natural disasters in recent decades. Over half of the global populace now resides in urbanized areas, amplifying the vulnerability to such events that is further accentuated by climatic shifts and rapid urban sprawl. In addressing these challenges, sophisticated flood risk management strategies often integrate advanced numerical models for precise hydrological assessments. These models can support e.g. urban planning, emergency response preparedness and the design of structural measures. In the present work, the Baganza River in the city of Parma (Northern Italy) is investigated with particular emphasis on recent modifications that have been designed with outcomes deriving from a computationally efficient parallel 2D numerical model solving the Shallow Water Equations (SWEs).

On October 2014, a severe flood event occurring on the Baganza River caused the inundation of the southwestern part of the city of Parma. Since the urban river reach showed limitations in the propagation of the flood wave, a comprehensive re-evaluation of the river's hydraulic conveyance capacities was required. Thus, in 2015, hydraulic authorities started designing and realizing several modifications along this river reach, including levee modification and removal, in order to increase its conveyance. With the aim of assessing the effectiveness of these strategies, the PARFLOOD numerical model, which solves the 2D-SWEs on a finite volume scheme and ensures high computational efficiency due to its parallel implementation on GPU, was adopted. The model was initially calibrated and adopted to simulate the 2014 flood event. Thereafter, leveraging a refined spatial resolution and incorporating detailed urban topographies, the model delineated residual flood hazard maps, facilitating evidence-based mitigation strategy refinements.

Once the most promising strategies were outlined and implemented over these last ten years, a new high-resolution Digital Terrain Model (DTM) deriving from a LiDAR survey was provided in 2023. By simulating the same synthetic discharge hydrograph, e.g. with a return period of 100 and 200 years, using both the 2014 DTM and the 2023 one, it clearly emerged that the current asset strongly reduces the residual flood hazard in these districts of the city of Parma, both in terms of flood extent and magnitude.

How to cite: Ferrari, A., Vacondio, R., and Mignosa, P.: Numerical modelling of flood hazard mitigation strategies: the case of the Baganza River after the 2014 inundation of the city of Parma, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15306, https://doi.org/10.5194/egusphere-egu24-15306, 2024.

With the worsening of climate change, extreme weather events are on the rise, leading to more frequent occurrences of climate-related disasters. Analyzing people's perceptions and attitudes towards disasters after they occur can help determine the spatial pattern of the disaster intensity and the post-disaster needs of different populations. The implication is to provide references for disaster assessment and post-disaster relief needs analysis.

 

Starting from July 29, 2023, due to the influence of Typhoon Dusrayi and Typhoon Canu, the Beijing-Tianjin-Hebei region in China suffered from catastrophic rainfall, resulting in severe flooding in multiple areas. This study utilized web crawlers to collect relevant Weibo data during the disaster, applied machine learning models to conduct public opinion analysis on the flooding disaster, developed the evolutionary patterns of public opinions on the disaster, and obtained heat maps and sentiment indicators for different cities. The results will contribute to the rapid assessment of post-disaster losses and guide the resource allocation in the initial emergency rescue process after the disaster.

How to cite: Zhang, X.:  A rapid disaster intensity assessment method using social media data: a case study of the flood disaster in the Beijing-Tianjin-Hebei region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15415, https://doi.org/10.5194/egusphere-egu24-15415, 2024.

EGU24-15605 | ECS | Orals | NH1.3

Establishing a Germany-wide Standardized Indication Map Representing the Flood Situation Caused by Heavy Rainfall 

Lukas Wimmer, Michael Hovenbitzer, and Patrick Merita

Recent studies on climate change show an increasing trend in the frequency of extreme weather events (IPCC, 2021; Tradowsky et al., 2023). These include storms with high-intensity precipitation, known as heavy rainfall. During those events the amounts of precipitation can be so high in a very short period of time that catastrophic flooding can also develop far away from rivers and lakes. Heavy rainfall events have occurred more frequently in Germany in recent years, resulting in severe damage and therefore focusing attention on risk management and prevention.

Contributing to an optimal preparation for the consequences of heavy rainfall events the Federal Agency for Cartography and Geodesy (BKG) is working with federal and state authorities to develop a Germany-wide indication map representing simulated flood situations after heavy rainfall events based on standardized guidelines. Once the mapping has been completed within the first half of 2024, it will be freely available as OpenData to politicians, the public administration and the general public for damage prevention and civil protection.

Geodata of the federal and state governments are essential for the hydronumerical two-dimensional modelling. A digital terrain model with a grid width of one meter forms the basis. Road culverts with corresponding dimensions, 3D building models, pumping stations as well as land cover data representing the surface roughness are integrated into this model in order to achieve a hydrologically effective modification and thus a realistic discharge.

The heavy rainfall indication map shows realistic simulation events for possible flooding scenarios that follow the heavy rainfall index according to Schmitt et al., 2018. The index describes the hazardous character of heavy rainfall events based on the return period and is commonly used in heavy rainfall risk communication by German federal and state authorities. Two scenarios are simulated: First, a 100-year event based on KOSTRA data from the German Weather Service (DWD), a dataset including regionalized precipitation heights as a function of precipitation duration and annularity. Second, an extreme heavy rainfall event with a precipitation of 100 mm/h. For both scenarios flood depths, flow velocities and flow directions are simulated.

The indication map for heavy rainfall provides an initial assessment of the risk potential, which, in combination with existing local expertise, should considerably simplify the planning of measures. It serves as an important tool for identifying areas at risk from heavy rainfall. This enables local authorities, planners and emergency services throughout Germany to derive appropriate measures, both preventively and in the event of an actual disaster.

 

References

Intergovernmental Panel on Climate Change (Ed.): Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, <doi:10.1017/9781009157896>.

Schmitt, T. G. et al.: Einheitliches Konzept zur Bewertung von Starkregenereignissen mittels Starkregenindex, KA Korrespondenz Abwasser, Abfall, 2018(65), Nr. 2.

Tradowsky, J.S., Philip, S.Y., Kreienkamp, F. et al.: Attribution of the heavy rainfall events leading to severe flooding in Western Europe during July 2021. Climatic Change 176, 90 (2023). <https://doi.org/10.1007/s10584-023-03502-7>.

How to cite: Wimmer, L., Hovenbitzer, M., and Merita, P.: Establishing a Germany-wide Standardized Indication Map Representing the Flood Situation Caused by Heavy Rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15605, https://doi.org/10.5194/egusphere-egu24-15605, 2024.

The subject of the study is the considerable uncertainty in determining flood risk when long-term climate change projections are developed. Risk management decision-making involves comparing options based on their benefits and costs. The purpose of the analysis is to reveal the uncertainty robustness of alternative flood protection measures. The treatment of different sources of uncertainty is done by using probabilistic net present value (NPV) analysis as well as by using Information-gap decision theory (IGDT). The case study is a settlement in northern Bulgaria with a record of severe flooding in the past, for which different climate change projections are generated under RCP 4.5 and RCP 8.5 scenarios. The behaviour of three civil protection options under these uncertainty conditions is investigated for an extended 30-year time period to 2050. A probabilistic analysis with NPV performance criterion is performed sequentially, followed by Info-gap decision theory analysis.

After discussing the results, the advantages and disadvantages of the two methods are compared. Some limitations and advantages of the Information gap theory are discussed. Finally, it is highlighted that when making decisions about long-term flood protection, it is recommended to use multiple methods that differ in data and assumptions, necessarily taking into account the hydrological uncertainty arising from climate change, which can radically change our choices.

How to cite: Mavrova-Guirguinova, M.: Impact of Uncertainty on the Choice of Long-Term Flood Protection Option under Climate Change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16798, https://doi.org/10.5194/egusphere-egu24-16798, 2024.

EGU24-17663 | ECS | Posters on site | NH1.3

Flood Risk Mapping Through Advanced Machine Learning Techniques and Geomorphic Data Integration 

Jorge Saavedra Navarro, Ruodan Zhuang, Cinzia Albertini, and Salvatore Manfreda

Flood events rank among the most destructive natural hazards, necessitating comprehensive risk management strategies to mitigate their impact on human health, the environment, cultural heritage, and economic activities. In this context, various approaches have been developed for identifying flood-prone areas, but there is still a need to enhance their capabilities due to dynamic changes in landscape and infrastructure.

In recent years, there has been a proliferation of remote sensing observations that can support dynamic and continuous mapping of flood-prone areas by integrating the most updated information. This study explores the potential of machine learning (ML) techniques, including Random Forest, Support Vector Machine, and Navies Bayer model, utilizing geomorphic information such as slope, elevation, precipitation, land use/land cover, elevation difference to the nearest river, and others as predictor variables. The best model and set of variables were explored by adopting approximately 30 variables spanning types, hydrologic, topographic, and categorical categories. Careful consideration was given to avoiding high correlations between variables in test subsets, ensuring relevance, and avoiding redundancy. Calibration and validation of the model employ Copernicus Emergency Management Service maps from Sentinel-2 satellite coupled with regional maps of past flood events.

Results highlight that the best ML technique is represented by the Random Forest, adopting a range of 5 to 8 variables for effective delineation of flood-prone areas. Among the selected variables, the most relevant ones include Rainfall, Geomorphic Flood index - GFI, Lithology, and others. The study demonstrates that a minimal amount of information (between 0.1% and 10%) suffices for optimal model performance (AUC greater than 0.8).

The study covered the entire territory of Italy, resulting in a flood-prone map at a 90m resolution, validated with flood maps provided by national agencies and obtained through traditional hydraulic models.

Keywords: satellite images, flood-prone areas, Machine Learning, GFI, flood risk.

How to cite: Saavedra Navarro, J., Zhuang, R., Albertini, C., and Manfreda, S.: Flood Risk Mapping Through Advanced Machine Learning Techniques and Geomorphic Data Integration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17663, https://doi.org/10.5194/egusphere-egu24-17663, 2024.

EGU24-18219 | ECS | Posters on site | NH1.3

Meta-heuristic Algorithms Applied to Urban Flood Evacuation Routes: A case study in Beijing, China 

Chuannan Li, Changbo Jiang, Reza Ahmadian, Man Yue Lam, and Jie Chen

Abstract: Climate change and urbanization have increased the occurrence of natural disasters, including floods, tsunamis and hurricanes. Among these disasters, floods occur with high frequency, impact a large number of people, cause high economic losses, and lead to high toll of deaths. Examples include floods in Indonesia in 2021 and Pakistan in 2022. The flood in Indonesia affected about 1 million people. The flood in Pakistan affected 33 million and killed 1,739 people and costed US$15 billion in economic damage. Flood risk assessment and evacuation are effective mitigation measures to create flood-resilient cities. Previous studies have focused on flood modelling and risk assessment, yet it is recently recognized that optimal evacuation routes are necessary and critical for social adaptation to flood risks. To date, there are limited research on evacuation route optimisation problem.

There are two approaches for evacuation route optimisation: namely exact methods and meta-heuristic methods. The exact methods such as linear programming, weighted summation, and mixed integer programming have been widely applied. Nevertheless, meta-heuristic algorithms are gaining attention as flexible, non-problem-specific, and computationally efficient optimisation methods. The principle of Meta-heuristic algorithms is based on simulating the optimisations that occur naturally in biological or physicochemical processes. For example, there is a commonality between an animal herd searching for routes and a population searching for routes in a flood disaster. Commonly applied meta-heuristic algorithms are Genetic Algorithms, Ant Colony Algorithms, Particle Swarm Algorithms, and Sparrow’s Algorithms. This is because these algorithms have simple structures and high adaptability, desirable local and global convergence properties and require few parameters.

In this study, the flood in Beijing, China, in late July and early August 2023 will be simulated. The flood claimed at least 33 lives, damaged 209,000 homes and more than 15,000 hectares of cropland and caused 127 thousand people to evacuate. The flood extent, water depth and flow velocity will be obtained from a two-dimensional hydrodynamic flood model. The flood risk for pedestrians or vehicles will be estimated with the hydrodynamic model result and a mechanic-based stability method. Optimal evacuation routes will be obtained with Genetic Algorithm, Ant Colony Algorithm, Particle Swarm Algorithm, and Sparrow’s Algorithm. The performance of the optimisation algorithms will be compared and evaluated.  This study contributes to the scientific planning of urban flood evacuation routes and provides insight for urban planners and managers to enhance urban resilience.

Keywords: Urban floods, evacuation routes, Meta-heuristic algorithms.

How to cite: Li, C., Jiang, C., Ahmadian, R., Lam, M. Y., and Chen, J.: Meta-heuristic Algorithms Applied to Urban Flood Evacuation Routes: A case study in Beijing, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18219, https://doi.org/10.5194/egusphere-egu24-18219, 2024.

EGU24-18287 | ECS | Orals | NH1.3

Sensitivity Analysis of Image Augmentation Methods to Improve Flooded Area Detection Performance 

Seon Woo Kim, Soon Ho Kwon, Sanghoon Jun, and Donghwi Jung

Recently, detecting flooded areas in CCTV images was performed based on semantic segmentation models (e.g., U-Net, FCN, etc.). However, these flooded area detection techniques are based on large-scale manually annotated images, which consume manpower and time. Image augmentation is one of the ways to overcome the limitations mentioned above. Some previous studies have used image augmentation to improve the performance of flooded area detection by combining two or more methods. However, there has been no study quantifying which augmentation methods are reasonable. This study aims to verify which image augmentation method is reasonable to improve the performance of urban flooded area detection techniques. First, this study develops a flood area detection technology corresponding to training images augmented with five different methods (Brightness, Blur, Contrast, Rotation, Crop). Subsequently, the performance changes for each technique were quantified, and characteristics related to the performance variations of each method were examined.

How to cite: Kim, S. W., Kwon, S. H., Jun, S., and Jung, D.: Sensitivity Analysis of Image Augmentation Methods to Improve Flooded Area Detection Performance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18287, https://doi.org/10.5194/egusphere-egu24-18287, 2024.

EGU24-22491 | ECS | Posters virtual | NH1.3

Application of Advanced Deep Learning Models for Flood Image Processing and Semantic Segmentation 

Sai Praneeth Dulam, Vidya Samadi, and Carlos Toxtli-Hernández

In developing Version 2.0 of our Flood Image Classifier, we underscore the significant role of Convolutional Neural Networks (CNNs), mainly Faster R-CNN and YOLOv3, in detecting and segmenting flood-related labels in images. Additionally, our research delves into the potential of Vision Transformers (ViT) for advanced object detection and image classification for flood-related images extracted for the USGS river cameras. Transformer methods offer improved predictions of flood depth and inundation areas, marking a substantial step forward in flood vision technology. The integration of advanced image processing techniques, the enhancement of CNN capabilities, and the incorporation of cutting-edge detection and classification models are pivotal in developing a comprehensive, real-time flood monitoring system. This system is designed to equip frontline decision-makers and emergency responders with essential insights into flooding conditions, thereby significantly contributing to disaster management and response through the innovative use of our flood image classifier, Version 2.0.

How to cite: Dulam, S. P., Samadi, V., and Toxtli-Hernández, C.: Application of Advanced Deep Learning Models for Flood Image Processing and Semantic Segmentation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22491, https://doi.org/10.5194/egusphere-egu24-22491, 2024.

EGU24-529 | ECS | Posters on site | NH1.5

The Attachment Process of Negative Connecting Leader to the Lateral Surface of Downward Positive Leader in a +CG Lightning Flash 

Qi Qi, Bin Wu, Weitao Lyu, Ying Ma, Lyuwen Chen, Fanchao Lyu, and Yan Gao

In the lightning attachment process, the leader connecting behavior is an interesting topic. In the attachment process of a negative cloud-to-ground lightning flash, the “Tip to the lateral surface” connection type has been widely observed, and researchers have carried out a series of studies and discussions on the characteristics and the physical mechanisms of the leader connecting behavior. However, is there also a “Tip to the lateral surface” connecting behavior in the attachment process of the positive cloud-to-ground lightning flash? In this study, using high-speed video cameras operating with framing rates of 20 and 50 kiloframes per second, we captured an attachment process during a positive cloud-to-ground flash, which demonstrates the connection of the negative connecting leader (NCL) to the lateral surface of the downward positive leader (DPL) for the first time. When the NCL was initiated, the tip of the DPL had passed the initiation position of the NCL for about 50 m. A common streamer zone (CSZ) was observed when the three-dimensional distance between the NCL tip and the lateral surface of DPL was about 30 m. It is remarkable to note that a luminous segment (space stem/leader) with a length of about 7 m was captured within the CSZ during the attachment process. The connection between the NCL tip and the lateral surface of the DPL was caused by the development of the CSZ and its inner space leader.

How to cite: Qi, Q., Wu, B., Lyu, W., Ma, Y., Chen, L., Lyu, F., and Gao, Y.: The Attachment Process of Negative Connecting Leader to the Lateral Surface of Downward Positive Leader in a +CG Lightning Flash, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-529, https://doi.org/10.5194/egusphere-egu24-529, 2024.

EGU24-1238 | ECS | Posters on site | NH1.5

Optical observations of needles evolving into negative leaders in a positive cloud-to-ground lightning flash 

Bin Wu, Qi Qi, Weitao Lyu, Ying Ma, Lyuwen Chen, and Vladimir Rakov

High-speed video records of a single-stroke positive cloud-to-ground (+CG) flash were used to examine the evolution of eight needles developing more or less radially from the +CG channel. All these eight needles occurred during the later return-stroke stage and the following continuing current stage. Six needles, after their initial extension from the lateral surface of the parent channel core, elongated via bidirectional recoil events, which are responsible for flickering, and two of them evolved into negative stepped leaders. For the latter two, the mean extension speed decreased from 5.3 × 10^6 to 3.4 × 10^5 and then to 1.3 × 10^5 m/s during the initial, recoil-event, and stepping stages, respectively. The initial needle extension ranged from 70 to 320 m (N = 8), extension via recoil events from 50 to 210 m (N = 6), and extension via stepping from 810 to 1,870 m (N = 2). Compared with needles developing from leader channels, the different behavior of needle flickering, the longer length, the faster extension speed, and the higher flickering rate observed in this work may be attributed to a considerably higher current (rate of charge supply) during the return-stroke and early continuing-current stages of +CG flashes.

How to cite: Wu, B., Qi, Q., Lyu, W., Ma, Y., Chen, L., and Rakov, V.: Optical observations of needles evolving into negative leaders in a positive cloud-to-ground lightning flash, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1238, https://doi.org/10.5194/egusphere-egu24-1238, 2024.

EGU24-1639 | Orals | NH1.5

Modelling the collision of streamers using the AMReX framework 

Christoph Köhn, Angel Ricardo Jara, Morten Jung Westermann, Mathias Gammelmark, and Elloise Fangel-Lloyd

Streamers, precursors of the hot, long lightning leaders, are small filamentary discharges with high electric fields at their tips. Experiments of laboratory discharges have shown that streamers in their corona can approach each other and it has been suggested that such collisions enhance the electric field in-between beyond the thermal runaway electric field accelerating electrons to the runaway regime thus generating X-rays. Streamer collision also plays a role in the interaction of wind turbine blades with lightning when streamers locally incept from the surface of blades and attract the downward moving lightning leader. Despite the relevance of streamer collisions in the runaway process or their role in the interaction of lightning with wind turbine blades, there have only been a few numerical studies due to computational limitations. We have therefore developed a novel 3D fluid model for streamer propagation implemented in the AMREX framework. AMREX allows us to solve drift-diffusion and Poisson equation using parallelization and GPU support to accelerate the block structured adaptive mesh refinement. We will present details of the implementation as well as a parameter study on typical streamer parameters (electron density, electric field, tip width and velocity,…) during streamer collision in various ambient fields and for various initial electron densities. We will also study various geometries with different displacements of the initial electrons perpendicular to the ambient electric field. Finally, we will interpret our results with respect to the runaway process and wind turbine-lightning interaction.

How to cite: Köhn, C., Jara, A. R., Westermann, M. J., Gammelmark, M., and Fangel-Lloyd, E.: Modelling the collision of streamers using the AMReX framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1639, https://doi.org/10.5194/egusphere-egu24-1639, 2024.

The ground-level potential gradient (PG) or the atmospheric electric field, the air-Earth current density as well as the main Global Electric Circuit (GEC) parameters such as the ionospheric potential, global resistance and the total current, can be obtained from the EGATEC engineering model of the GEC (Odzimek et al. 2010) at the resolution of 3 hours. The model input data based on satellite cloud and lightning observation datasets from the period 1998-2006 for evaluating the activity of the GEC cloud generators, and the summer/winter and low/high solar activity conductivity model of Tinsley and Zhou (2006) allow calculating the GEC parameters in the summers and winters of the period. In this work we compare the modelling results to observations from the Stanislaw Kalinowski Geophysical Observatory in Świder, Poland (52°07' N, 21°14' E) of the ground-level potential gradient and conduction current density calculated from the newly digitised PG and positive conductivity data from 1965-2005. We also look for connections in the time variations of the model meteorological input and atmospheric electricity observational data. The work is supported by the Polish National Science Centre grant no 2021/41/B/ST10/04448.

How to cite: Odzimek, A., Tacza, J., Pawlak, I., and Kępski, D.: Analysis of time variations in the Global Electric Circuit parameters from the EGATEC model and Świder atmospheric electricity data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1658, https://doi.org/10.5194/egusphere-egu24-1658, 2024.

The different morphologies of lightning channels are caused by different electrical environments within the cloud, the charge distribution determines the lightning channel morphology, and the lightning morphology can reflect the charge structure to some extent. The distribution of charges is mainly determined by the dynamics and microphysical conditions in clouds, and turbulence plays a significant role in the distribution of charges. Due to the dependence of lightning morphology on the distribution of thunderstorm charges, which is regulated by thunderstorm dynamic effects, a relationship can be established between lightning morphology and thunderstorm dynamic effects.

In this study, the lightning channel was obtained from three-dimensional radiation source localization data from the Lightning Mapping Array at the Langmuir Laboratory of the New Mexico Institute of Mining and Technology. The fractal dimension was used to characterize the complexity of lightning channels, which was calculated by the box-counting method. The S-band dual-polarization Doppler radar data was used to estimate the cube root of the eddy dissipation rate (EDR, the EDR was estimated using the Python Turbulence Detection Algorithm). The EDR and radar radial velocity were used to represent the thunderstorm dynamic characteristics.

Superimposing EDR and radar radial velocities with LMA radiation sources, our analysis shows that the overall morphology and detailed morphology of the lightning channel correspond to different EDR characteristics. Lightning with complex channel morphology has a larger average FD and occurs in regions with large EDRs. In single lightning events, channels that extend directly within a certain height range without significant bifurcation and turning tend to propagate in the direction of decreasing EDRs, while channel bifurcations and turns usually occur in regions with large radial velocity gradients and large EDRs. This study shows the relationship between channel morphology and thunderstorm dynamics and provides a new method for the direct application of channel-level localization data to understand thunderstorm dynamics characteristics.

How to cite: Li, Y., Zhang, Y., Zhang, Y., and Krehbiel, P. R.: Analysis of the Relationship between the Morphological Characteristics of Lightning Channels and Turbulent Dynamics Based on the Localization of VHF Radiation Sources, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2144, https://doi.org/10.5194/egusphere-egu24-2144, 2024.

EGU24-2536 | Posters on site | NH1.5

Lightning Activities near the Red Sea: Effects of Aerosols Morphology and Local Meteorology 

Ashraf Farahat and Maher Dayeh

Lightning activity is one of the global natural hazards that pose significant risks to human life and numerous aspects of society's technological infrastructure. Understanding the linkage between aerosols present in the atmosphere and lightning activity is important to further advance our knowledge of the global lightning activity cycle.

Saudi Arabia and Yemen host one of the world’s largest desert areas namely the Empty Quarter (al-Rubea Al-Khali). Moreover, Saudi Arabia is one of the world’s largest oil exporters with many water desalination, petrochemical, and cement industrial plants, while large cities in both Saudi Arabia and Yemen have large construction projects and vehicle emissions. This increases both natural and anthropogenic aerosol loading in both countries.  Meanwhile, the inland regions close to the Red Sea are one of the 500 hottest lightning regions in the world. This work identifies a possible correlation between lightning activity and aerosol loading.

Using data of individual lightning strokes from the Global Lightning Detection Network (GLD360), in conjunction with remote sensing measurements of the aerosol optical depth (AOD) obtained at 500 nm from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites during active lightning days, we examine the evolution of lightning activity in two geographically and topologically different regions over Saudi Arabia and Yemen. One region extends inland to the desert (R1) and the other is in the southwest mountainous region that is close to the Red Sea (R2). In both regions, results from thunder days only indicate that lightning is strongly and positively correlated with the AOD loading, up to AOD ~ 0.8, after which the trend flattens or reverses direction. Results suggest the two opposite effects that aerosols could indirectly have on lightning activity are at play. The mountainous region exhibits a much stronger linear relation compared to the inland region. Furthermore, both regions exhibit seasonal and asynchronous lightning activity and AOD loading. The year 2018 in R1 shows very high lightning activity, likely linked to the 2018 intense dust storms in the region.

How to cite: Farahat, A. and Dayeh, M.: Lightning Activities near the Red Sea: Effects of Aerosols Morphology and Local Meteorology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2536, https://doi.org/10.5194/egusphere-egu24-2536, 2024.

EGU24-3358 | Orals | NH1.5

Investigation of the Electric Fields Related to Elves Simulations 

Petr Kaspar, Ivana Kolmasova, Ondrej Santolik, and Martin Popek

Elves are transient luminous events occurring above thunderclouds. They appear as an expanding ring of light at altitudes of 85 – 95 km with diameters of more than 200 km and lasting less than 1 ms. The elves are produced by electromagnetic pulses emitted by underlying high-peak current lightning discharges, which excite nitrogen molecules at the bottom of the ionosphere. We develop an electromagnetic model of elves, which consists of two steps. As the first step, we compute the horizontal part of the electric field at a height of 15 km from transmission line return stroke (RS) models without damping, with linear, and/or exponential damping of the current wave. Subsequently, we solve Maxwell’s equations self consistently for altitudes from 15 km to 95 km, including finite neutral and electron densities, and nonlinearities related to heating, ionization, and attachment of free electrons caused by the RS transient electric field. We show computed electric fields and optical emission rates at the heights of the development of elves. This procedure allows us to distinguish between the electrostatic, induction, and radiation part of the electric field and to investigate their role in the evolution of elves in the full wave simulations.

How to cite: Kaspar, P., Kolmasova, I., Santolik, O., and Popek, M.: Investigation of the Electric Fields Related to Elves Simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3358, https://doi.org/10.5194/egusphere-egu24-3358, 2024.

EGU24-3628 | Orals | NH1.5

Glow-terminating terrestrial gamma-ray flashes observed during the ALOFT Campaign 

Steven Cummer, Yunjiao Pu, Andrew Mezentsev, Marni Pazos, Morris Cohen, Nikolai Ostgaard, Mark Stanley, Timothy Lang, Martino Marisaldi, J. Eric Grove, Mason Quick, Hugh Christian, Christopher Schultz, Richard Blakeslee, Ian Adams, Phillip Bitzer, Martin Fullekrug, Bilal Qureshi, Bendik Husa, and Gerald Heymsfield and the additional members of ALOFT team

The ALOFT campaign targeted aircraft measurements of terrestrial gamma-ray flashes (TGFs) through NASA ER-2 overflights of strong thunderstorms.  We report here the analysis of glow-terminating TGFs (GT-TGFs) that occur at the end of some gamma-ray glows.  GT-TGFs were generated by most of the observed storms during the campaign and were prolifically generated by two specific storms that were particularly active in gamma ray production.  One unique feature of GT-TGFs is that they always occur within several tens of microseconds of a narrow bipolar event (NBE).  The characteristics of GT-TGFs and the associated NBE radio emissions will be described in detail.

How to cite: Cummer, S., Pu, Y., Mezentsev, A., Pazos, M., Cohen, M., Ostgaard, N., Stanley, M., Lang, T., Marisaldi, M., Grove, J. E., Quick, M., Christian, H., Schultz, C., Blakeslee, R., Adams, I., Bitzer, P., Fullekrug, M., Qureshi, B., Husa, B., and Heymsfield, G. and the additional members of ALOFT team: Glow-terminating terrestrial gamma-ray flashes observed during the ALOFT Campaign, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3628, https://doi.org/10.5194/egusphere-egu24-3628, 2024.

EGU24-3670 | ECS | Orals | NH1.5

Using meteorological reanalysis to identify weather conditions for classifying atmospheric electricity data  

Hripsime Mkrtchyan, Giles Harrison, and Keri Nicoll

Atmospheric electricity Potential Gradient (PG) data has typically been classified by local weather conditions, such as by identifying data recorded during “fair weather” (FW) or in the absence of rainfall “no hydrometeors” (NH), to try and obtain globally representative values. In general, this approach is essential in obtaining global atmospheric circuit (GEC) signals. The weather information needed to do this is, however, only available from some of the sites providing atmospheric electricity measurements. For other sites, meteorological reanalysis – of which there are many products available, spanning different times and scales - may provide a data source for such classification of PG data. This study investigates the integration of ERA5 meteorological reanalysis data to identify FW and NH conditions and improves the quality of data used in long-term atmospheric electricity studies.  

Initial findings investigating the meteorological quantities show a strong correlation between wind speed, total cloud coverage and total precipitation from ERA5 and observed ground-based measurements at the Eskdalemuir and Lerwick sites. This is to be applied to classifying past atmospheric electricity data, specifically of the hourly potential gradient (PG), which were obtained at the Lerwick observatory from 1925 to 1984, and Eskdalemuir observatory, which made atmospheric electricity measurements from 1911-1981 (Harrison & Riddick, 2022; Märcz & Harrison, 2003). 

Identified criteria from ERA5 which best match for FW and NH conditions are implemented in historical data from the Lerwick and Eskdalemuir observatories, enhancing the reliability of past studies which is important for atmospheric electricity analyses. This supports the potential of ERA5 data for providing information to identify FW and NH conditions. From this, we are evaluating a range of methods to use the meteorological reanalysis, with the aim of recovering representative FW data at sites lacking meteorological measurements. 

How to cite: Mkrtchyan, H., Harrison, G., and Nicoll, K.: Using meteorological reanalysis to identify weather conditions for classifying atmospheric electricity data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3670, https://doi.org/10.5194/egusphere-egu24-3670, 2024.

EGU24-4116 | Orals | NH1.5

Stream Machine Learning for Lightning Nowcasting - Harnessing the Power of Continuously Updated Data 

Cesar Beneti, Luis Pavam, Luiz Oliveira, Marco Alves, Leonardo Calvetti, and Fernanda Verdelho

Uninterrupted access to electricity is a fundamental feature of civilization. In its absence, an all-embracing cessation of activities occurs, ranging from essential services to more frivolous activities. The maintenance of the energy supply is critical for society's day-to-day functions. The Brazilian state of Paraná (PR) is home to the world's second-largest hydropower plant, Itaipu, which, in conjunction with other power plants in the state, provides almost one-third of the power energy production in Brazil. The transmission lines that pervade PR are essential to Brazil's power distribution system, for hydropower generation is typically made far away from the regions that most demand it, being transported by transmission lines in an interconnected power grid. This type of asset mainly depends on the forecast of Cloud-to-Ground (CG) lightning, as it is one of the leading weather-related causes of power outages. Lightning and wind gusts are the two leading weather-related causes of disruptions, representing at least 23% of the known causes of energy disruption, as declared by the local power distribution company. Our study of lightning incidence and power outages from 2017-2021 indicates a correlation of 0.98 between these events, denoting that more outages must be lightning-related. Reliable CG lightning forecasts are crucial for proactive hazard mitigation. This work expounds on developing a Machine Learning (ML) model for CG lightning forecasting for PR. Our ML model predicts the occurrence or lack of CG lightning near power company assets in PR, defining a binary classification task. The model makes its predictions based on the past spatio-temporal conditions of lightning occurrences, requiring only past lightning data to forecast lightning. We chose to use a stream ML method, i.e., the model is continuously trained as new data arrives. Using a stream ML, we intend to harness the machine's capacity to continuously learn the patterns of lightning occurrence and power outages in real-time -- thus constructing an ever-updating model capable of adapting to transient weather conditions. Given its rapid training time and aptitude for classification tasks, the chosen algorithm was a Very Fast Decision Tree. The stream ML classifier outperforms a classic static ML model by 30% regarding the ROC AUC metric (stream: 71.80%, static: 40.85%) and 50% considering the Micro-f1 score (stream: 91.05%, static: 40.91%). These results arise from the highly dynamic nature of lightning, defining an ideal phenomenon for prediction based on a constantly updated stream of data. An automatic system for CG lightning forecasting for power company assets is helpful for risk management and operational planning. Future steps include increasing the lead time from ten min. to up to one hour, allowing for more time to prepare and anticipate hazards, preventing power outages, and optimizing personnel allocation.

How to cite: Beneti, C., Pavam, L., Oliveira, L., Alves, M., Calvetti, L., and Verdelho, F.: Stream Machine Learning for Lightning Nowcasting - Harnessing the Power of Continuously Updated Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4116, https://doi.org/10.5194/egusphere-egu24-4116, 2024.

EGU24-4214 | Posters on site | NH1.5

Bottom-heavy charge structure and lightning discharges in Tibetan Plateau thunderstorms 

Xiushu Qie, Zhuling Sun, Fengquan Li, Lei Wei, Chunfa Sun, Kexin Zhu, Shanfneg Yuan, Dongxia Liu, and Rubin Jiang

The main charge region in thunderstorms over Lhasa city with an elevation of 3700 m is investigated by using a VHF interferometer, incorporating with fast antenna, weather radar and cloud-to-ground lightning location. The evolution of charge structure and its effects on lightning discharges were discussed in a bottom-heavy thunderstorm. During the early developing stage, the thunderstorm exhibited an inverted dipolar charge structure with negative charge center over the positive, and lower negative intracloud (IC) lightning occurred in between. Then an upper positive charge region appeared as the convection intensifying, and the charge structure exhibited obvious tripolar pattern and with large lower positive charge center (LPCC), and fewer positive IC discharges occurred in the upper dipole but lower negative IC lightning still dominated. As the thunderstorm entered the later mature stage, both negative IC between the lower dipole and positive IC between the upper dipole observed simultaneously. With gradually depleting of the positive charge carriers by precipitation, the LPCC weakened, the positive IC lightning between the upper dipole dominated, and two negative CG flashes were able to occur. In the later stage, positive IC dominated, although not much.  The study further confirms the previous conclusion (Qie et al., GRL, 2005) that weak thunderstorms are characterized by a bottom-heavy charge structure, and in the vigorous stage of thunderstorm, it may exhibit tripolar charge structure with a large LPCC, which has a significant impact on lightning types.

How to cite: Qie, X., Sun, Z., Li, F., Wei, L., Sun, C., Zhu, K., Yuan, S., Liu, D., and Jiang, R.: Bottom-heavy charge structure and lightning discharges in Tibetan Plateau thunderstorms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4214, https://doi.org/10.5194/egusphere-egu24-4214, 2024.

The evolution of charge structure plays a crucial role in thunderstorm electrification. In this paper, the signatures related to the upper charge regions consisting of charged ice crystals are analyzed in an isolated thunderstorm, observed by an X-band dual-polarized phased array weather radar (DP-PAWR), which operates in its normal operational mode which performs a volume scan with 110 elevations at a temporal resolution of 30 seconds. The radar data quality control is applied to polarized parameters of DP-PAWR, including the horizontal reflectivity ZH, differential propagation phase shift, and specific differential phase. The lightning data was obtained by a lightning detection system called LIDEN (LIghtning DEtection Network system) operated by the JMA. A flash group algorithm is employed to group lightning discharges into flash branches according to a spatial range, azimuth interval, and time criterion.

 

To explore the mean structure of upper charge regions in the convective part of the thunderstorms, an expanded quasi-vertical profile method is applied to examine the temporal evolution of microphysical processes of upper charge regions. The convective part in the isolated thunderstorm is defined as one separated from nearby storms by an area of composite ZH larger than 40 dBZ at and above -10℃ layer, and a criterion of correlation coefficient ρHV greater than 0.8 is used to remove poor quality radar data. Meanwhile, only the lightning flashes within the given volume are used to calculate the IC lighting flash rate and explore the signatures with the upper charge regions.

 

The results indicate that during the different stages from the early developing stage of isolated thunderstorms to the end of the mature stage, the upper charge regions above the -10 ℃ layer experienced an evolution process from initiation to development accompanied by the rise of the charge region in the updraft and the enhancement of charge concentration. In the mature stage of thunderstorm, the upper charge regions extended from the -30℃ layer to the cloud top, followed by a decay process in the upper charge region at the end of the mature stage, in which the IC lightning flash rate is larger than 60 flashes/min. At the same time, the mean structure evolution of the upper charge regions exhibited a good relationship with the in-cloud lightning flash rate.

How to cite: Wang, S.: Analysis of the Signatures Related to the Upper Charge Regions in an Isolated Thunderstorm Observed by Dual-Polarized Phased Array Weather Radar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4254, https://doi.org/10.5194/egusphere-egu24-4254, 2024.

Winter thunderstorms often exhibit compact vertical dimensions and lower heights of the major charge centers and are often accompanied by strong wind shear, with a propensity for positive cloud-to-ground strokes that can produce mesospheric transient luminous events (e.g. sprites, haloes, elves and jets). There are many optical observations confirming this over the Sea of Japan and the Mediterranean Sea, which are known to be the most convectively active regions during Northern Hemisphere winter.

We use a 3D quasi-electrostatic model (Haspel et al., 2022) with wintertime thunderstorm charge configurations to evaluate sprite inception regions in the mesosphere under various conditions typical of the Eastern Mediterranean. This is a is a relatively new, numerically robust model based on an analytical solution to Poisson’s equation that was developed specifically to handle non-symmetric charge configurations in a large 3D domain.  We address several key questions related to the onset of sprites in winter: (a) the minimum charge that enables sprite inception under the compact thunderstorm structures, (b) the effect of wind shear (lateral offsets of 3-5 km between the cloud charge centers) on the electric field and the location of the area of possible sprite inception, and (c) how the time difference between consecutive strokes in adjacent cumulonimbus clouds affects the size and location of the area of possible sprite inception. Additionally, we will present results of sensitivity studies on the discharge time and profile, showing how the area of possible sprite inception depends on this factor.

 

Reference

Haspel, C., G. Kurtser and Y. Yair (2022). The feasibility of a 3D time-dependent model for predicting the area of possible sprite inception in the mesosphere based on an analytical solution to Poisson's equation. Jour. Atmos. Sol. Terr. Phys.,230, 105853, doi:10.1016/j.jastp.2022.105853.

How to cite: Haspel, C. and Yair, Y.: Numerical simulations of the mesospheric region for sprite inception in winter thunderstorms over the Eastern Mediterranean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4618, https://doi.org/10.5194/egusphere-egu24-4618, 2024.

EGU24-4634 | ECS | Orals | NH1.5

Regional differences in thunderstorm intensity driven by monsoon and westerlies over the Tibetan Plateau 

Lei Wei, Xiushu Qie, Zhuling Sun, and Chen Xu

Thunderstorms are weak but frequent, and exhibit unique charge structures over the Tibetan Plateau (TP) where the average elevation is higher than 4 km. In this study, all detected thunderstorms over the TP between 1998 and 2013 by TRMM were divided into four intensity categories: weak, median, severe and extreme. This classification was based on the 75%, 90%, and 99% values of flash rate, maximum 40 dBZ height, minimum 85 GHz polarization-corrected temperature (PCT), and minimum 37 GHz PCT, respectively. The monthly distributions of thunderstorm intensity show that all categories mostly occur in summer over most regions of the TP, and in spring near the Himalayas. Although the peaks of thunderstorms occur during 1300-1600 LT, the thunderstorms occurring in the early morning and evening have a high probability of developing into severe and extreme thunderstorms. This is distinct from the thunderstorms over the Sichuan Basin, the surrounding areas, and the middle and lower reaches of the Yangtze River at the same latitude. On the basis of westerlies- and monsoon-dominated regions, as well as the altitude, the TP was divided into four regions: the eastern, northern, southern and western regions of the TP (namely ETP, NTP, STP and WTP, respectively). The ETP and STP are primarily influenced by the monsoon, with the ETP at a lower altitude than the STP. Conversely, the WTP and NTP are affected by the westerlies, with the WTP situated at a higher altitude than the NTP. Thunderstorms over the ETP are more likely to be severe and extreme than those over the NTP. The percentage of weak thunderstorms is highest over the WTP. It is found that the maximum top height, development depth, horizontal development area, and development volume at 20 dBZ, 30 dBZ, and 40 dBZ echoes are largest over the ETP, followed by the NTP and STP, while being smallest over the WTP. The results imply that thunderstorms influenced by the monsoon are larger and more likely to be severe and extreme than those influenced by the westerlies.

How to cite: Wei, L., Qie, X., Sun, Z., and Xu, C.: Regional differences in thunderstorm intensity driven by monsoon and westerlies over the Tibetan Plateau, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4634, https://doi.org/10.5194/egusphere-egu24-4634, 2024.

EGU24-5346 | Posters on site | NH1.5

Spectral Analysis of High-Energy Radiation Events Observed during the ALOFT 2023 Campaign 

David Sarria, Nikolai Østgaard, Martino Marisaldi, Timothy Lang, Eric Grove, Mason Quick, Hugh Christian, Chris Schultz, Richard Blakeslee, Ian Adams, Rachael Kroodsma, Gerald Heymsfield, Andrey Mezentsev, Ingrid Bjørg Engeland, Anders Fuglestad, Nikolai Lehtinen, Kjetil Ullaland, Shiming Yang, Bilal Hasan Quresh, and Jens Søndergaard and the ALOFT Team

The Airborne Lighting Observatory for FEGS and TGFs (ALOFT) is equipped with a comprehensive set of instruments on-board a NASA ER-2 research aircraft for observing Terrestrial Gamma-ray Flashes (TGFs) and gamma-ray glows from thunderclouds. The ER-2 research aircraft flew at about 20 km altitude, above thunderstorms, from July 1st to July 30th, 2023, for a total flight time of about 60 hours.  The onboard instrument suite comprised several X/gamma-ray detectors, which spanned a dynamic range of four orders of magnitude in flux and covered the entire energy spectrum associated with the gamma-ray transients.

    During the campaign, we observed over 130 short gamma-ray transients, along with hundreds of gamma-ray glows. Several of these detections consisted of thousands of photon counts, allowing precise and unprecedented spectral analyses.

    In this study, we present a comprehensive spectral analysis of various events using a forward modeling technique and Monte-Carlo simulations. This approach enables us to constrain the source characteristics of these events, including their source energy spectrum, production altitude and offset, spatial extension, and the brightness (fluence) of the source RREA electrons.

How to cite: Sarria, D., Østgaard, N., Marisaldi, M., Lang, T., Grove, E., Quick, M., Christian, H., Schultz, C., Blakeslee, R., Adams, I., Kroodsma, R., Heymsfield, G., Mezentsev, A., Bjørg Engeland, I., Fuglestad, A., Lehtinen, N., Ullaland, K., Yang, S., Hasan Quresh, B., and Søndergaard, J. and the ALOFT Team: Spectral Analysis of High-Energy Radiation Events Observed during the ALOFT 2023 Campaign, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5346, https://doi.org/10.5194/egusphere-egu24-5346, 2024.

Lightning now has designated as an Essential Climate Variable in the Global Climate Observing System to understand the climate change. Lightning detection from geostationary satellites enables continuous monitoring of lightning activity. The satellite-borne lightning imagers take advantage of optical imaging technology combined with multiple filtering methods to extract the weak signals of lightning from very strong background signals and eventually clustering to reconstruct the original lightning flashes. By using the observation data of Fengyun-4A Lightning Mapper Imager (LMI), the first geostationary satellite-borne lightning imager developed in China, the lightning activity and the optical characteristics of lightning flashes in China were analyzed. The lightning activity observed by LMI exhibits obvious regional, seasonal and diurnal variation properties. The flashes are mainly concentrated in the southeastern coastal region in China and the southwestern China. During the pre-monsoon period (March-May), LMI detected lightning outbreaks in southwestern China and its surrounding areas, while during the monsoon period (June-September), both eastern southwestern China and southeastern coastal region in China show a significant dense distribution of lightning flashes. The climatic characteristics of lightning activity and the simultaneous observations of Lightning Imaging Sensor (LIS) on the International Space Station (ISS) confirm the LMI observations. However, there is a difference between the absolute amounts of the LMI and LIS observations. The overall number of lightning flashes observed by LMI is relatively lower than that observed by LIS. In addition, the detection capability of LMI is higher at low latitudes compared to mid-latitudes, and is higher during daytime hours than that during nighttime hours. As for the flash properties, which mainly refer to the optical radiance, area, and duration of lightning flashes, there are also regional differences for these properties observed by LMI. The high values of flash properties are concentrated in southern China. The LMI observations are related to the radiometric response of its detector and the difference in spatial resolution within the large field of view of geostationary orbit observations.

How to cite: Hui, W. and Zhang, W.: Lightning Activity in China and Its Optical Characteristics Observed by Geostationary Satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5363, https://doi.org/10.5194/egusphere-egu24-5363, 2024.

EGU24-5400 | ECS | Posters on site | NH1.5

The intensity distribution of Terrestrial Gamma-ray Flashes from the ALOFT flight campaign 

Anders Fuglestad and the ALOFT team

In July 2023, the Airborne Lightning Observatory for FEGS and TGFs (ALOFT) flight campaign took place using a NASA ER-2 research aircraft flying over the Gulf of Mexico and the Caribbean Sea. The campaign consisted of about 60 flight hours at a cruise altitude of 20 km, using live telemetry to target gamma-ray glowing thunderclouds.

The payload consisted of several instruments including gamma-ray detectors with a dynamic range spanning four orders of magnitude in flux, an imaging array of optical photometers, electric field change meters, radiometers, and radar systems. In addition to several ground stations measuring very low frequency, low frequency, and very high frequency radio signals.

96 TGFs were detected by ALOFT. For 44 of these events, it was possible to get an estimate of the location of the source using both correlated optical pulses and lightning detection networks.

With the estimate of the source location and the gamma-ray observation from ALOFT. Monte Carlo simulations were used to get an estimate of the source intensity of the TGFs.

Based on the results it was determined that the vast majority of the 44 TGFs investigated have source intensities below the threshold needed to be observed from current satellite instruments, which indicates a large population of low intensity TGFs that has gone previously undetected. These results contribute to the open debate on the rarity of TGFs.

How to cite: Fuglestad, A. and the ALOFT team: The intensity distribution of Terrestrial Gamma-ray Flashes from the ALOFT flight campaign, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5400, https://doi.org/10.5194/egusphere-egu24-5400, 2024.

EGU24-6398 | ECS | Orals | NH1.5

Side discharges on positively charged lightning leaders 

Shanfeng Yuan, Xiushu Qie, Rubin Jiang, and Dongfang Wang

Recent observations unveiled two types of side discharges associated with positive leaders: needle discharges and nearby bidirectional leaders. The formation mechanism and connections of two phenomena remained unclear due to the lack of synchronous optical detection and radio mapping data. Here we present the first high-speed video and low-frequency lightning mapping results. Negative branches of nearby bidirectional leaders can propagate after connecting to the parent positive channel, and needle discharges act as positive connecting leaders. Our research shows that positive leaders exhibit unconventional channel extensions, maintained by frequent recoil leaders, sharing characteristics with streamer discharges. Notably, when two approaching positive leaders develop in this manner, they can eventually collide. These findings significantly advance our understanding of side discharges on positive leaders, offering fresh insights into these intriguing phenomena.

How to cite: Yuan, S., Qie, X., Jiang, R., and Wang, D.: Side discharges on positively charged lightning leaders, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6398, https://doi.org/10.5194/egusphere-egu24-6398, 2024.

EGU24-6468 | Posters on site | NH1.5

On the impact of thunder on cloud droplets and ice crystals  

Konstantinos Kourtidis and Stavros Stathopoulos

In the lightning channel pressures can be of the order of 100 atm and hence in the produced thunder, sound pressure levels (SPL) can be very high. Additionally, the thunder frequency spectra have peaks for peal and claps at around 100 Hz and around 50 Hz for rumble sounds, with intracloud lightning having peaks at even fewer Hz. These low frequencies are ideal for acoustically induced orthokinetic agglomeration of droplets. Thunder occurs in cloud environments where not only large numbers of droplets are present, but additionally the shockwave front expands at supersonic velocities and hence could cause near the lightning channel modulations of droplet size distributions and increase ice crystals numbers through e.g. vibrational breakup. We present calculations for the two mechanisms above (orthokinetic agglomeration and vibrational breakup) for typical cloud droplet sizes and concentrations, including also clouds containing desert dust. In thunderstorm conditions, it is found that acoustic orthokinetic agglomeration of droplets can be very effective and can produce very rapidly changes in the mean cloud droplet diameter. Also, it is found that the critical flow velocities, over which breakup occurs, is easily exceeded near the lightning channel and will lead to droplet and ice crystal breakup. We note that all models of ice crystal generation in clouds substantially underestimate the observed ice crystal numbers, and the mechanism presented here may be responsible for the discrepancy. We also note that these processes need further study to assess how they could interfere with the lightning generation process itself, through both charge redistribution in the modified droplet size distribution spectra, as well as the increase in vertical and turbulent transport velocities of the smaller ice crystals resulting from breakup. 

How to cite: Kourtidis, K. and Stathopoulos, S.: On the impact of thunder on cloud droplets and ice crystals , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6468, https://doi.org/10.5194/egusphere-egu24-6468, 2024.

EGU24-6523 | Posters on site | NH1.5

ESTHER: a small project to investigate gamma-ray emissions in thunderstorms and volcanic lightning 

Alessandro Ursi and Danilo Reitano

Detecting terrestrial gamma-ray flashes (TGFs) from the ground is a relatively new frontier in atmospheric science and has opened up new avenues for research. Also, the recent detection of a TGF produced during the massive Hunga Tonga–Hunga Ha'apai eruption, pointed out the possibility that even volcanic lightning might produce gamma-ray emissions at MeV energies.

In this context, we present the Experiment to Study Thunderstorm High-Energy Radiation (ESTHER), a small project funded by the Italian National Institute for Astrophysics (INAF), aimed at monitoring from the ground gamma-ray emissions produced during thunderstorms and, possibly, by volcanic lightning. The ESTHER set-up consists of a gamma-ray detection system and a VLF radio receiver, to be installed on the top of the Etna volcano (Italy). The selected installation site is the Etnean Observatory of the Italian National Institute of Geophysics and Volcanology (INGV), located at 2,818 m altitude and laying less than 2.7 km from the main volcano craters.

An extensive analysis of the flash rate recorded at Mt. Etna in the last eight years pointed out that the mountain top is interested by strong lightning activity in the summer months, making it a suitable location for the investigation of lightning and associated high-energy phenomena. In particular, the largest fraction of discharges turned out to cluster nearby the mountain peak and right above the main volcano craters, where the frequent presence of volcanic ashes possibly increases the electrical conductivity, under conditions of humid air typical of thunderstorms, making the region above the volcano's top a natural trigger for lightning. Moreover, as for other volcanoes around the world, Etna has been documented to produce volcanic lightning (last times in 2015 and 2022). As a consequence, given the proximity of the Etnean Observatory to the main craters, ESTHER will enjoy a privileged location for investigating potential gamma-ray emissions produced either by thunderstorms and volcanic lightning. In conditions of clear sky, ESTHER will also provide an as much as possible continuous monitoring of the environmental gamma-ray background, allowing to point out potential variations of it before, during, or after volcanic eruptions. The ESTHER set-up will be installed and start its first data acquisitions in spring 2024.

How to cite: Ursi, A. and Reitano, D.: ESTHER: a small project to investigate gamma-ray emissions in thunderstorms and volcanic lightning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6523, https://doi.org/10.5194/egusphere-egu24-6523, 2024.

EGU24-7273 | Orals | NH1.5

Observation of positive Narrow Bipolar Events in the Mediterranean region 

Ivana Kolmašová, Ondřej Santolík, Serge Soula, Eric Defer, Yanan Zhu, Radek Lán, Stéphane Pedeboy, and Andrea Kolínská

Narrow Bipolar Events (NBEs) are brief intracloud (IC) discharge processes that generate powerful radiation in the HF and VHF radio bands. NBEs typically occur in isolation, but they have also been identified as initial events in IC lightning flashes. Their incidence is statistically correlated with the strength of convection. NBEs can exhibit both polarities and usually occur in the upper regions of the thundercloud.

We present, for the first time, properties of NBEs detected in the Mediterranean region. The dataset comprises 37 events recorded by broadband magnetic loops located at two sites in France. The events were identified using the list of NBEs from 2022 provided by the Earth Network. The frequency range of our broadband sensors enabled us to obtain detailed shapes of NBE pulses. We calculated rise times, full width at half maximum times, and zero-crossing times of NBE pulses to facilitate comparisons with observations of NBEs in other parts of the world. The majority of NBE pulses observed in the Mediterranean region were isolated events occurring above the land and displaying a simple bipolar waveform with an overshoot peak of the opposite polarity. For two events, we supplemented our observation with the data from the SAETTA (Suivi de l’Activité Electrique Tridimensionnelle Totale de l’Atmosphère) lightning mapping array. Additionally, we estimated the altitude of the NBE events and placed our observations in the meteorological contexts to determine why NBE occurrences in the Mediterranean region have been overlooked until now.

 

How to cite: Kolmašová, I., Santolík, O., Soula, S., Defer, E., Zhu, Y., Lán, R., Pedeboy, S., and Kolínská, A.: Observation of positive Narrow Bipolar Events in the Mediterranean region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7273, https://doi.org/10.5194/egusphere-egu24-7273, 2024.

EGU24-7900 | Orals | NH1.5

TGF and gamma-ray glow highlights from the ALOFT 2023 flight campaign 

Nikolai Ostgaard, Timothy Lang, Martino Marisaldi, Eric Grove, Mason Quick, Hugh Christian, Cristopher Schultz, Richard Blakeslee, Ian Adams, Rachael Kroodsma, Gerald Heymsfield, Andrey Mezentsev, David Sarria, Ingrid Bjorg Engeland, Anders Fuglestad, Nikolai Lehtinen, Kjetil Ullaland, Shiming Yang, Bilal Hasan Qureshi, and Jens Sondergaard and the ALOFT team

During the summer of 2023 the  Airborne Lighting Observatory for FEGS and TGFs (ALOFT) field campaign was performed. With a NASA ER-2 research aircraft, flying at 20 km altitude, ALOFT was searching for Terrestrial Gamma ray Flashes (TGF) and gamma-glowing thunderclouds in Central America and Caribbean. The ALOFT payload included a comprehensive number of instruments:

1) Several gamma-ray detectors covering four orders of magnitude dynamic range in flux as well as the full energy range for TGF/gamma-ray glow detection (UIB-BGO and ISTORM).

2) Fly’s Eye GLM Simulator (FEGS), an imaging array of photometers sensitive to different wavelengths, and electric field change meters.

3) Lightning Instrument Package (LIP), giving three component electric field measurements.

4) a suite of microwave radiometers and radars for cloud characterization: the Advanced Microwave Precipitation Radiometer (AMPR), Configurable Scanning Submillimeter-wave Instrument/Radiometer (CoSSIR), Cloud Radar System (CRS), and X-band Radar (EXRAD)

 

5) An extensive set of ground-based radio observations.

 

For all the 10 flights, 60 hours total, realtime gamma-ray detections were downlinked. Due to this simple but novel mission concept, we knew in real time if the aircraft was passing a gamma-glowing cloud and the pilot was instructed to return to the same thundercloud as long as the cloud was glowing. During the campaign ALOFT observed a total of 130 transient gamma-ray events and hundreds of gamma-ray glows. With the richness of the ALOFT observations we learned that thundercloud can glow for much longer than minute scale and over much larger areas than previously reported. We also learned that transient gamma-ray events come in a large variety and new types of events were discovered.  In this presentation we will give an overview of the main results and discoveries by the ALOFT campaign

 

How to cite: Ostgaard, N., Lang, T., Marisaldi, M., Grove, E., Quick, M., Christian, H., Schultz, C., Blakeslee, R., Adams, I., Kroodsma, R., Heymsfield, G., Mezentsev, A., Sarria, D., Bjorg Engeland, I., Fuglestad, A., Lehtinen, N., Ullaland, K., Yang, S., Hasan Qureshi, B., and Sondergaard, J. and the ALOFT team: TGF and gamma-ray glow highlights from the ALOFT 2023 flight campaign, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7900, https://doi.org/10.5194/egusphere-egu24-7900, 2024.

EGU24-7927 | Orals | NH1.5

A novel view of gamma-ray glows from the ALOFT 2023 flight campaign 

Martino Marisaldi, Nikolai Østgaard, Timothy J. Lang, J. Eric Grove, Mason Quick, Hugh Christian, Christopher J. Schultz, Richard Blakeslee, Ian S. Adams, Rachael A. Kroodsma, Gerald M. Heymsfield, Andrey Mezentsev, David Sarria, Ingrid Bjørge-Engeland, Anders Fuglestad, Nikolai Lehtinen, Kjetil Ullaland, Shiming Yang, Bilal Hasan Qureshi, and Jens Søndergaard and the ALOFT team

The Airborne Lightning Observatory for FEGS and TGFs (ALOFT) was a field campaign targeted at Terrestrial Gamma-ray Flashes (TGFs) and gamma-ray glows from thunderclouds. The campaign was successfully carried out during July 2023, for a total of 60 flight hours in the Gulf of Mexico and the Caribbean. The scientific payload was flown on a NASA ER-2 research aircraft, capable to fly at 20 km altitude above thunderclouds. The payload included a suite of gamma-ray detectors spanning four orders of magnitude dynamic range in flux, and a complete suite of instruments for the characterisation of the electrical and optical activity, and the thundercloud environment. A key asset of the mission was the real-time downlink of gamma-ray count rates, which enabled the immediate identification of gamma-ray glowing regions. The pilot was then instructed to turn and pass over the same glowing region to explore its spatial extension and duration.

ALOFT resulted in the detection of hundreds of gamma-ray glows, anticipating a revolution in our understanding of the phenomenon. Thunderclouds were observed to glow for hours and over several thousands of square kilometers, making glows a much more pervasive phenomenon than previously reported. Glows show significant time variability from seconds down to millisecond time scale, suggesting a relation to short transients such as TGFs more complex than previously thought. Glows are observed in association with the overpass of active convective cores, 20-25 km in size, yet their time variability and intensity modulation suggest a more complex spatial structure.

These observations challenge the current view of glows as quasi-stationary phenomena related to relatively stable electrification conditions. The observed glows show highly dynamic temporal and spatial structures and are closely related to the development phases of active thunderclouds. These observations call for a rethinking of the assumptions at the basis of current modeling efforts.

How to cite: Marisaldi, M., Østgaard, N., Lang, T. J., Grove, J. E., Quick, M., Christian, H., Schultz, C. J., Blakeslee, R., Adams, I. S., Kroodsma, R. A., Heymsfield, G. M., Mezentsev, A., Sarria, D., Bjørge-Engeland, I., Fuglestad, A., Lehtinen, N., Ullaland, K., Yang, S., Qureshi, B. H., and Søndergaard, J. and the ALOFT team: A novel view of gamma-ray glows from the ALOFT 2023 flight campaign, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7927, https://doi.org/10.5194/egusphere-egu24-7927, 2024.

EGU24-7940 | Orals | NH1.5

LOFAR Observations of the Initial Stage of IC Dart Leaders 

Brian Hare, Olaf Scholten, Paulina Ťureková, Steven Cummer, Joseph Dwyer, Ningyu Liu, Chris Sterpka, and Sander ter Veen

In previous work we have found that dart leaders quench needle activity; where dart leaders are charge pulses that re-trace previously established lightning leader channels, and needles are small repeating negative discharges that propagate away from positive lightning channels. We hypothesized that dart leaders could be quenching needles by carrying negative charge away from the region of needle activity. Therefore, in order to further explore the interactions between dart leaders and needles, we are investigating the beginnings of different dart leaders with the LOFAR radio telescope, which uses hundreds of antennas in northern Netherlands to image lightning in the 30-80 MHz band with meter and nanosecond level accuracy. We have found that, consistent with previous work, dart leaders start slow with weak radio emission and then accelerate over a period roughly around 50 µs in duration until they reach a maximum speed and radio intensity. However, we also observe that the power of the radio emissions from the dart leaders exhibits large, randomly-timed, variations. These variations do not appear to be a form of leader stepping. The time-differences between individual peaks in the time trace is significantly longer than the width of each peak (or pulse) that is dominated by the antenna function, (FWHM ~ 50 ns). One possible explanation could be that the power fluctuations are consistent with Poisson statistical variations of radio sources (possibly streamers), which would imply that at any point in time the radio emission is dominated by a small number of strong emitters, as opposed to millions of small streamers. A second possible explanation is that the fluctuations could be due to small-scale structural variations along the previously established plasma channel, which we have observed in previous work.

How to cite: Hare, B., Scholten, O., Ťureková, P., Cummer, S., Dwyer, J., Liu, N., Sterpka, C., and ter Veen, S.: LOFAR Observations of the Initial Stage of IC Dart Leaders, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7940, https://doi.org/10.5194/egusphere-egu24-7940, 2024.

EGU24-7982 | ECS | Posters virtual | NH1.5

Enhancement of Catastrophic Positive Cloud to Ground Lightning in recent years over Maharashtra (India): Role of Dust Aerosols 

Abhijeet Gangane, Sunil Pawar, Prajna Priyadarshini, and Venkatachalam Gopalakrishnan

Many studies have shown that aerosols can influence microphysical processes inside thunderclouds that could affect charge-generation processes. Cloud to Ground (CG) lightning data from Ground-based observations (IITM-LLN) over the State of Maharashtra, India, from 2014 to 2023, have been analyzed here to study the percentage and physical mechanism associated with the enhancement of catastrophic Positive CG in total CG lightning. Our analysis shows that the average positive CG percentage remains above 25% during the monsoon (July-September) and post-monsoon (October-November). This increased percentage of positive CG is attributed to elevated dust aerosol concentration over the study region during the monsoon and post-monsoon periods. An enormous amount of dust can be seen during the Indian Summer Monsoon (ISM) over the Arabian Desert and neighborhood extending up to the western Indian (Maharashtra) region. Dust aerosol intrusion into the thunderstorm acts as Ice nuclei (IN) as well as Cloud Condensation Nuclei (CCN) and can influence charge separation processes inside the cloud. In recent years, we observed an enhancement of Dust AOT over Maharashtra state, indicating that the increasing trend in Positive CG lightning is closely linked to the transport of desert dust from the Middle East and elevated aerosol content during the post-monsoon season. Here, we propose that these high concentrations of dust aerosols near the cloud base acting as IN produce a high concentration of ice crystals in the lower portion of the cloud, which can form a strong positive charge region in the lower part of the mixed-phase region by non-inductive charging mechanism. This strong positive charge region in the lower portion of the mixed phase region may be responsible for the observed increased percentage of positive CG over the study region.

How to cite: Gangane, A., Pawar, S., Priyadarshini, P., and Gopalakrishnan, V.: Enhancement of Catastrophic Positive Cloud to Ground Lightning in recent years over Maharashtra (India): Role of Dust Aerosols, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7982, https://doi.org/10.5194/egusphere-egu24-7982, 2024.

EGU24-7996 | ECS | Posters on site | NH1.5

Monte Carlo Error Analysis of Lightning Interferometry with LOFAR 

Paulina Turekova, Brian Hare, Olaf Scholten, Steven Cummer, Joseph Dwyer, Ningyu Liu, Chris Sterpka, and Sander ter Veen
The LOFAR radio telescope works on a principle of radio interferometric imaging. It coherently sums the signal of hundreds of antennas in northern Netherlands, covering the 30-80 MHz window of the very high frequency (VHF) band of 30-300 MHz. We are using the TRI-D algorithm to extract 3-D polarization data of a lightning flash observed by LOFAR. TRI-D functions by coherently summing recorded voltages, accounting for the antenna function, polarization, and geometric time delay for each voxel. The result is split into time slices. A coherent intensity is calculated for each time slice, and the maximum of this value is set as a source location. The outcome is a reconstructed source location and polarization as seen by the LOFAR antennas. We are now exploring the accuracy of TRI-D in response to realistic parameters. In this work, we perform a Monte Carlo error analysis which simulates the voltages on each antenna from an assumed dipole emitter, adds normally distributed noise, and then reconstructs the source properties with TRI-D. The difference between the simulated input and the reconstruction gives us an estimate of the resulting error bars. We will show a detailed account of the interferometry technique that produces our data, the Monte Carlo simulation that tests the accuracy of our model and finally, our polarization results.

How to cite: Turekova, P., Hare, B., Scholten, O., Cummer, S., Dwyer, J., Liu, N., Sterpka, C., and ter Veen, S.: Monte Carlo Error Analysis of Lightning Interferometry with LOFAR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7996, https://doi.org/10.5194/egusphere-egu24-7996, 2024.

EGU24-8002 | ECS | Posters on site | NH1.5

Measuring evaporation-condensation charging of individual aerosol particles 

Andrea Stoellner, Isaac Christopher David Lenton, Caroline Muller, and Scott Russell Waitukaitis

Although cloud electrification has been studied for hundreds of years, it is still not fully understood [1]. The most promising charging mechanism – ice crystal-graupel collision charging – answers some of our questions, but leaves us with others. Why do ice crystals and graupel charge on collision in the first place? And why do they reverse their charging behavior below a certain temperature? To get some insights we take a step back and look at the charging behavior of individual aerosol particles in a humid environment. Shavlov et al. [2] suggest that the hydroxide and hydronium ions formed by the autodissociation of water are sufficient to cause charging during evaporation and condensation of water droplets or surface-adsorbed water on solid particles. This small amount of charge could be a precursor to bigger charge exchange during collision.

            We aim to test this hypothesis by levitating individual aerosol particles in an optical trap and measuring their charge while varying humidity. Our setup allows for trapping of different types of solid and liquid particles in the micrometer size range, like water droplets and silica microspheres. In the future we also hope to study ice crystals. Figure 1 shows an illustration of the measurement principle. The particle’s charge is measured by applying a sinusoidal electric field and observing the resulting particle motion. The Mie scattering pattern of the particle furthermore gives information about the particle’s size and refractive index, both at equilibrium and during evaporation/condensation. The experiment allows us to control the relative humidity, pressure and air ion concentration around as well as air flow across the particle.

Ultimately we hope to contribute to a better understanding of the microphysical processes involved in thundercloud electrification and adjacent electrical phenomena in the atmosphere. 

FIGURE 1. Optical tweezers (wavelength λ = 532 nm) holding a solid or liquid aerosol particle. A sinusoidal electric field is applied between the two electrodes and the resulting particle motion as well as the particle’s Mie scattering pattern are recorded.

Acknowledgments

This project has received funding from the European Research Council (ERC) under the European Union’s Starting Grant (A. Stoellner, I.C.D. Lenton & S.R. Waitukaitis received funding from ERC No. 949120, C. Muller received funding from ERC No. 805041).

 

References

  • Berdeklis, P. and List, R. (2001) J Aerosol Sci. 58(18) 2751–2770.
  • Shavlov A. et al. (2018) J Aerosol Sci. 123 17-26.

How to cite: Stoellner, A., Lenton, I. C. D., Muller, C., and Waitukaitis, S. R.: Measuring evaporation-condensation charging of individual aerosol particles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8002, https://doi.org/10.5194/egusphere-egu24-8002, 2024.

EGU24-9355 | Posters on site | NH1.5

Dynamics of global lightning activity on different time scales as indicated by Schumann resonance frequency variations 

Gabriella Sátori, Tamás Bozóki, Earle Williams, Ernő Prácser, Raidiel Puig, and Rachel Albrecht

The electromagnetic waves in the Schumann resonance (SR) frequency range (<100 Hz) radiated by natural “lightning antennas” excite the Earth-ionosphere cavity confined between the Earth’s surface and the ionospheric D-region of ~100 km height. This contribution provides observational evidence for the relationships between the variations of peak frequencies of the first three modes and the global/regional lightning dynamics based on SR observations of the vertical electric field component, EZ, at Nagycenk (NCK), Hungary, Central Europe. Lightning source-observer distance-dependent frequency variations are considered on the annual, seasonal and diurnal time scale as well as during specific events when squall-line formation of lightning activity in South America moves toward NCK. The observations are interpreted with model calculations. The distance-dependent frequency variation has important applications to climate issues as well.

How to cite: Sátori, G., Bozóki, T., Williams, E., Prácser, E., Puig, R., and Albrecht, R.: Dynamics of global lightning activity on different time scales as indicated by Schumann resonance frequency variations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9355, https://doi.org/10.5194/egusphere-egu24-9355, 2024.

EGU24-9526 | Orals | NH1.5

On the radio wave polarization of Saturn lightning 

Georg Fischer, Ulrich Taubenschuss, David Pisa, and Masafumi Imai

The radio waves with Saturn lightning origin have been studied since the first detection by Voyager 1, but their wave polarization has rarely been explored. Fischer et al. (2007, JGR 112, A12308) examined lightning from a storm located at 35° south latitude and found its radio emissions below 2 MHz to be highly polarized (80%) in a right-handed circular sense with respect to the wave propagation direction. They explained this by absorption of the extraordinary mode in Saturn's ionosphere and the dominance of the ordinary mode emission, as the radio waves are propagating against a direction of the magnetic field when coming from a source in the southern hemisphere. A limited examination of Saturn lightning from the so-called Great White Spot at 35° north latitude by Fischer et al. (2011, Nature 475, 75-77) revealed radio wave polarization in the left-handed sense. In this presentation we will show the radio wave polarization of lightning from various other storms in Saturn's atmosphere, which have not been examined until today. In this way we want to corroborate the hypothesis that the sense of the circular radio wave polarization of Saturn lightning depends on the hemispherical location of the storm.

How to cite: Fischer, G., Taubenschuss, U., Pisa, D., and Imai, M.: On the radio wave polarization of Saturn lightning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9526, https://doi.org/10.5194/egusphere-egu24-9526, 2024.

EGU24-9986 | ECS | Orals | NH1.5 | Highlight

Potential gradient as a predictor of fog 

Caleb Miller, Keri Nicoll, Chris Westbrook, and R. Giles Harrison

Although fog is an important weather phenomenon, it remains difficult to predict using traditional methods. This could be improved by new observations-based nowcasting systems. It has long been understood that fog affects measurements of atmospheric electricity. However, there has been disagreement in the literature on whether these changes contain information which is valuable for fog prediction beyond other commonly used methods. Here, results are presented which show that the potential gradient (PG), a measure of atmospheric electricity, could be used as an additional diagnostic in predicting fog for timescales of several hours. A much larger dataset of fog and PG is examined than has been previously possible, which allows for a more robust understanding of the behaviour of the PG during radiation fog. It is found to increase by a median of 58 V/m by the start of the event. In addition, this increase is found to begin over two hours in advance of the fog, 30% of the time. This shows that PG may contain useful fog nowcasting information. A number of individual fog case studies are presented and the applicability of the general results to these specific cases is discussed. 

How to cite: Miller, C., Nicoll, K., Westbrook, C., and Harrison, R. G.: Potential gradient as a predictor of fog, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9986, https://doi.org/10.5194/egusphere-egu24-9986, 2024.

EGU24-10352 | Orals | NH1.5

Cloud Microphysical Characteristics Associated with Blue Corona Discharges at thundercloud tops 

Dongshuai Li, Alejandro Luque, Torsten Neubert, Olivier Chanrion, Yanan Zhu, Jeff Lapierre, Nikolai Østgaard, and Víctor Reglero

Blue corona discharges are bursts of streamer discharges often observed at the top of thunderclouds, but the conditions in the clouds that generate them are not well understood.

The cloud microphysical parameters related to them are important for future empirical studies and for theoretical models and simulations. Previous studies modeled the scattering and absorption emissions from blue corona discharges by assuming mean particle radius of 10–20 μm and densities of 1–2.5 × 10^8 m^−3, resulting in photon mean free paths of 1–20 m.

Here we present the first-ever estimate of important microphysical parameters related to blue corona discharges based on data measurements from the CALIPSO lidar. The results showed that most blue corona discharges were associated with ice particles with a radius of ∼50 μm and a number density of ∼ 2 × 10^7 m^−3, resulting in a photon mean free path of ∼3 m.

Around 20% of the blue corona discharges coincide with Narrow Bipolar Events (NBEs) indentified from the Earth Networks Total Lightning Network.The altitudes of blue corona discharges that were identified as NBEs are derived from both the optical and radio bands. It revealed that in six out of nine cases, the R^2 value was greater than 0.85, indicating a good agreement between the two methods and supporting our estimate of the photon mean free path as 3 m. However, in the shallowest and deepest cases, there was some discrepancy between the altitudes determined by the two methods, suggesting more complex cloud microphysical parameters. Possible reasons for the discrepancy, such as the homogeneous approximation for the cloud's microphysical parameters and the simplification of the source length, will be discussed.

How to cite: Li, D., Luque, A., Neubert, T., Chanrion, O., Zhu, Y., Lapierre, J., Østgaard, N., and Reglero, V.: Cloud Microphysical Characteristics Associated with Blue Corona Discharges at thundercloud tops, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10352, https://doi.org/10.5194/egusphere-egu24-10352, 2024.

EGU24-11101 | Orals | NH1.5

Mapping out lightning processes in both the VHF and VLF using LOFAR and the Met Office’s lightning detection system, LEELA 

Graeme Marlton, Brian Hare, Olaf Scholten, Mike Protts, Ed Stone, Sue Twelves, and Francesco Devoto

Lightning is one of the most destructive meteorological phenomena being a hazard to people and objects on the ground as well as aircraft. In addition to the strong currents and optical emission from a lightning stroke broadband radio emissions are also produced from the VLF to VHF. The LOw Frequency ARray (LOFAR) telescope centred in the Netherlands consists of a large array of VHF (30-300 MHz) receivers which can be configured to image a lightning strike in the 30-80 MHz bandwidth. The Met Office Lightning Electromagnetic Emission Location using Arrival time differencing LEELA system operates in the VLF (3-30 kHz). It also archives the raw incoming VLF data allowing the individual VLF waveforms to be analysed. From a lightning flash recorded in June 2021 over the Netherlands, 8 distinct events were detected by both systems. Here we present an analysis of these 8 events which include dart leaders, negative leaders, an intensely radiating negative leader and a cloud to ground strike. Initial results show that while both systems co-locate the events they are sensitive to different processes within the lightning strike process. VHF emission from a lightning strike is observed for periods of 30-40 ms and captures the development of the lightning channel. However, VLF emission is observed for much shorter periods of a few ms likely corresponding to the rapid vertical movement of charge during the strikes.

How to cite: Marlton, G., Hare, B., Scholten, O., Protts, M., Stone, E., Twelves, S., and Devoto, F.: Mapping out lightning processes in both the VHF and VLF using LOFAR and the Met Office’s lightning detection system, LEELA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11101, https://doi.org/10.5194/egusphere-egu24-11101, 2024.

EGU24-11257 | Orals | NH1.5

Locating charged regions in extensive layer cloud 

R.Giles Harrison and Keri Nicoll

Extensive layer clouds are common in Earth’s atmosphere. They acquire charge at their upper and lower boundaries, from the vertical current flowing in the global atmospheric electric circuit. The quantity of charge collected is related to the current, the transition distance from clear air to cloudy air at the cloud boundary, and the background cosmic ray ionisation. The transition distance is the region in which a change in conductivity occurs, which determines the charge acquisition. This differs between cloud top and cloud base. At cloud top, the boundary transition distance is closely related to the temperature inversion, which can be less than the transition distance at cloud base. At cloud base, the transition distance depends on droplet growth rate and updraft speed. The combined effects of the local ionisation, current flow and conductivity gradient leads to droplet charging.

Using instrumentation carried on enhanced meteorological radiosondes, the extent of the charged region in extensive layer clouds has been observed with specially developed cloud sensors operating at multiple optical wavelengths, simultaneously with the in situ electrical measurements. (Further, in some situations, ceilometer measurements of backscatter are also available). These soundings are compared with modelled profiles of droplet properties and layer cloud charges, for situations characteristic of mid-latitude and polar clouds. Effects of the droplet size distribution on the layer cloud electrification are also investigated, and responses to variations in cosmic ray ion production.

Charging is known to affect some aspects of the microphysical behaviour of droplets, such as their evaporation and growth rates. This may in turn influence properties of layer clouds in the climate system.

How to cite: Harrison, R. G. and Nicoll, K.: Locating charged regions in extensive layer cloud, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11257, https://doi.org/10.5194/egusphere-egu24-11257, 2024.

EGU24-11482 | Orals | NH1.5 | Highlight

Thundercloud high-energy radiation production by long streamers 

Nikolai Lehtinen, David Sarria, Martino Marisaldi, Andrey Mezentsev, Nikolai Østgaard, Steven Cummer, and Yunjiao Pu

The novel Streamer Parameter Model (SPM) [Lehtinen, 2021, doi:10.1007/s11141-021-10108-5] allows to quickly calculate the shape, velocity, and electric field of an electric streamer in air, without resorting to lengthy hydrodynamic simulations. A streamer propagates faster as its length grows. When the streamer length exceeds several meters, the velocity may become comparable to the speed of light, which necessitates correcting the model for relativistic effects. Such long streamers may describe the experimentally observed fast positive and negative breakdown. We propose that they may produce large quantities of relativistic runaway electrons, and therefore x-rays. This is facilitated by several conditions: (1) electric fields at the streamer tip may be sufficiently close to the so-called thermal runaway threshold (~30 MV/m), at which free electrons may accelerate from thermal energies up to relativistic energies; (2) in negative streamers, the energetic electrons are synchronized in velocity with the streamer front; (3) the streamer tip radius may exceed tens of centimeters, providing a large volume of the high field where the thermal runaway acceleration may take place.

We apply SPM to long streamer propagation inside a thundercloud and calculate the relativistic runaway electron production, as well as radio, optical and x-ray radiation. The calculations are compared to the observations of Narrow Bipolar Events (NBE), Terrestrial Gamma Flashes (TGF), and luminous phenomena obtained during the recent ALOFT campaign.

How to cite: Lehtinen, N., Sarria, D., Marisaldi, M., Mezentsev, A., Østgaard, N., Cummer, S., and Pu, Y.: Thundercloud high-energy radiation production by long streamers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11482, https://doi.org/10.5194/egusphere-egu24-11482, 2024.

EGU24-11937 | Orals | NH1.5

Feedback Effects in Positive Corona and Relativistic Runaway Discharges 

Victor Pasko, Sebastien Celestin, Anne Bourdon, Reza Janalizadeh, and Jaroslav Jansky

We discuss characteristic scales and direct physical analogy between the photoionization feedback in conventional positive corona discharges in air and the photoelectric feedback in discharges driven by relativistic runaway electrons in air. In a positive corona system the avalanche of electrons in bulk of discharge volume is initiated by specific distribution of photoionization far away from the electrode.  Under inception conditions in positive corona each electron arriving at the anode creates on average just enough seed electrons in discharge volume through photoionization to replicate itself. Under these self-sustained steady state conditions, photoionization feedback produces just enough secondary electrons upstream of the avalanche to maintain the system in steady state. Analogically, in case of relativistic electron avalanches a feedback process is realized when X-rays emitted by these electrons travel backwards with respect to the electron motion and generate new relativistic electron seeds due to the photoelectric absorption in air. It is demonstrated that terrestrial gamma-ray flashes are produced by growth of long bidirectional lightning leader system consisting of positive and stepping negative leaders. The spatial extent of streamer zones of a typical lightning leader with tip potential exceeding several tens of megavolts is on the order of 10–100 m. The photoelectric absorption of bremsstrahlung radiation generated by avalanching relativistic runaway electrons occurs efficiently on the same spatial scales. The intense multiplication of these electrons is triggered when the size of the negative leader streamer zone crosses a threshold of approximately 100 m (for sea-level air pressure conditions) allowing self-replication of these avalanches due to the upstream relativistic electron seeds generated by the photoelectric absorption.

References: 
Pasko et al., GRL, 50, e2022GL102710, 2023, https://doi.org/10.1029/2022GL102710
Pasko et al., PSST, 32, 075014, 2023, https://doi.org/10.1088/1361-6595/ace6d0

How to cite: Pasko, V., Celestin, S., Bourdon, A., Janalizadeh, R., and Jansky, J.: Feedback Effects in Positive Corona and Relativistic Runaway Discharges, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11937, https://doi.org/10.5194/egusphere-egu24-11937, 2024.

Terrestrial gamma-ray flashes (TGFs), powerful bursts of gamma-rays produced within our atmosphere, often occur in association with lightning. However, the mechanisms for generating the large number of runaway electrons required to account for the TGF luminosities remain uncertain. For example, TGFs might be produced by cold-runaway electron production from streamer heads and/or leader tips in the high-field regions near lightning, or TGFs might be produced by the self-sustained production of runaway electrons by relativistic feedback involving backward propagating runaway positrons and backscattered x-rays. Because both mechanisms could possibly occur in the presence of lightning leaders, it has been challenging to test which TGF production mechanisms are important. In this work, detailed simulations are used to test whether TGFs may be produced by thunderstorm electrification alone, without the presence if lightning. It is found that rapid thunderstorm charging may first produce strong gamma-ray glows, followed by large pulses of gamma-rays, followed by multi-pulsed TGFs similar to the TGFs first observed by CGRO/BATSE. Furthermore, the ionization produced by the high-energy particles partially discharges the electric field in some regions while amplifying the field in other regions, potentially allowing for the initiation of narrow bipolar events (NBEs) and/or lightning. If confirmed, such sequence of events would be strong evidence for the relativistic feedback mechanism.

How to cite: Dwyer, J. and Liu, N.: Gamma-ray glows and terrestrial gamma-ray flashes produced by thunderstorm electrification without lightning , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12103, https://doi.org/10.5194/egusphere-egu24-12103, 2024.

EGU24-12247 | ECS | Orals | NH1.5

Investigating Storm Charge Distribution Trends with Intracloud Lightning Polarity Data 

Elizabeth DiGangi, Jeff Lapierre, and Yanan Zhu

There are, at present, two accepted primary paradigms for thunderstorm charge distribution using a simple tripole model: “normal” polarity storms, which are characterized by a central negative charge region, an upper positive charge region, and sometimes a lower positive charge region; and “inverted” polarity storms, which are characterized by a central positive charge region, an upper negative charge region, and sometimes a lower negative charge region. The real distribution of thunderstorm charge is known to be more complex than the tripole model can represent, but the normal/inverted paradigm is still widely used in the field. Characterizing storms as having a normal or inverted polarity has been a subject of interest in lightning research since discovering that inverted storms produce a larger-than-average fraction of positive amplitude cloud-to-ground (CG) lightning compared with normal storms. +CG lightning is understood to have generally higher peak currents and a much greater probability of producing continuing current than -CGs, which is relevant for research into subjects like lightning-initiated wildfires and transient luminous events. Thunderstorm charge distribution is also directly related to storm microphysics and thermodynamics, which, in turn, links it to the meteorological characteristics of storms and storm environments.

Most published research on storm polarity has either investigated large-scale trends in +CG versus -CG frequency from long-range lightning detection systems (LDSs), or has used LDSs which map lightning in 3D to infer storm polarity directly from intracloud (IC) lightning leader propagation patterns. Data on IC lightning from long-range LDSs is a resource which, to our knowledge, has not yet been used to study bulk storm charge structures. It stands to reason that if inverted storms favor the production of more +CGs than normal storms, then they would also favor the production of more -ICs. The goal of this study is therefore to interrogate several years of lightning data from the Earth Networks Total Lightning Network (ENTLN) to determine whether or not IC peak current information can be used to study storm charge structure and the geographic distributions of inverted and normal polarity storms.

How to cite: DiGangi, E., Lapierre, J., and Zhu, Y.: Investigating Storm Charge Distribution Trends with Intracloud Lightning Polarity Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12247, https://doi.org/10.5194/egusphere-egu24-12247, 2024.

EGU24-12606 | Posters on site | NH1.5

CubeSpark: Space-based 3-D Lightning Mapping using a Constellation of Radio Frequency Sensors 

Sonja Behnke, Kim Katko, Harald Edens, Patrick Gatlin, Timothy Lang, William Haynes, Paul Snow, Jeremiah Rushton, Joellen Renck, Charley Weaver, Larry Bronisz, Jacob Pratt, Steven Dobson, Nikhil Pailoor, Jackson Remington, and Sarah Stough

CubeSpark is a new concept for a constellation of CubeSats that combines bi-spectral optical lightning imaging with radio frequency (RF) sensing to provide a 3-D lightning detection capability with global coverage from low-Earth Orbit. The development of CubeSpark is a collaboration between Los Alamos National Laboratory and NASA Marshall Space Flight Center. CubeSpark innovates over current ground and space-based global lightning capabilities by determining the altitude of lightning radiation sources, enabling new science in thunderstorm processes and the impact of lightning on climate. The key to determining the altitude of lightning is using a constellation of RF sensors to make coordinated measurements of impulsive RF radiation sources, similar to the approach of a ground-based lightning mapping array. The RF measurements will be enhanced with bi-spectral optical sensors to improve overall lightning detection efficiency and provide additional, complementary information about lightning processes.

This presentation introduces the CubeSpark mission concept and science applications with a focus on the RF hardware under development. Two challenges of space-based RF lightning detection are ionospheric effects and RF noise from both the satellite bus and anthropogenic sources from Earth. While the process of removing ionospheric dispersion from broadband waveforms for time-of-arrival (TOA) estimation is well established, CubeSpark further reduces ionospheric impacts on TOA by using a circularly polarized antenna, which suppresses one of the birefringent wave modes. For noise reduction, the CubeSpark receiver leverages programmable high- and low-pass filters to allow for on-orbit modifications of its passband. A benchtop demonstration of the RF hardware has been completed.

How to cite: Behnke, S., Katko, K., Edens, H., Gatlin, P., Lang, T., Haynes, W., Snow, P., Rushton, J., Renck, J., Weaver, C., Bronisz, L., Pratt, J., Dobson, S., Pailoor, N., Remington, J., and Stough, S.: CubeSpark: Space-based 3-D Lightning Mapping using a Constellation of Radio Frequency Sensors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12606, https://doi.org/10.5194/egusphere-egu24-12606, 2024.

EGU24-12658 | Posters on site | NH1.5

GLM lightning flashes observed during ASIM triggers over Tropical South America 

Carlos Morales, Joan Montanyà, Jesus Lopéz, Oscar Van Der Velde, Nicolai Østgaard, Torsten Neubert, and Víctor Reglero

The Atmosphere-Space Interactions Monitor (ASIM) on board the International Space Station (ISS) is collecting data of lightning and Terrestrial Gamma Flashes (TGF) over the globe since April 2018 by means of two suites: i) modular multispectral imaging array (MMIA); and ii) modular X and gamma-ray sensors (MXGS). MMIA responds to lightning flashes, while high energy detector (HED) and low energy detector (LED) of MXGS are employed to estimate TGF spectra and source. Based on these features, ASIM is providing a large dataset of MMIA, LED and HED triggers that are used identify potential TGF events that require an extra imaging analysis to depict the exact location and validation. Upon such measurements, this study employs coincident ASIM and GLM lightning flashes over Tropical South America (90-30W and 20S-10N) to inspect if the electrically active thunderstorms present unequivocal features associated with each ASIM trigger, i.e., MMIA, LED, HED and TGF. Electrically active thunderstorms were identified as contiguous GLM lightning flashes clustered at 0. 1 x 0.1 degrees on ± 30 minutes of ASIM trigger time following Barnes et al. (2015) and Morales et al. (2021) procedures. During the period of 2018 and 2021, we were able to find 30,417 active thunderstorms that have lightning flashes within ± 3 seconds of trigger time (19,546 during the night and 10,871 during the day). Of those thunderstorms, 343 (1,745) were identified with HED, 278 (1,752) with LED, 12,858 (27811) with MMIA and 49 (116) with TGF within 0-200 ms (200ms-3 sec) of the trigger time. The spatial distribution of those thunderstorms do not show any lightning hot spot. MMIA thunderstorms coincide with the location of HED and LED thunderstorms, except HED thunderstorms over the Peruvian Andes mountain range. Moreover, we did not find any TGF thunderstorms along the mountain regions, especially in Peru and Ecuador. The 60 minutes lightning activity (# flashes/per minute) reveal that TGF thunderstorms show higher lightning flash rates than the MMIA, HED and LED triggered thunderstorms, in addition of a sudden lightning flash rate increase prior to the TGF trigger and sustained high lightning activity for the following 10 minutes. HED and LED show similar lightning temporal evolution (flash rate increase before the trigger and decay afterwards), but LED triggered thunderstorms have higher flash rates over the entire 60 minutes time period. MMIA triggered thunderstorms show the lowest flash rates and almost steady lightning activity during the entire 60 minutes. Based on 90% confidence level of T-Student test, we found that TGF and MMIA thunderstorms are statistical different during the entire 60 minute time period, meaning that not all MMIA thunderstorms produce TGFs. In another hand, we can state that HED and LED triggers are good indicators of TGF emissions, since they are not statistically different, meaning that these parameters could be used as triggers to identify TGF occurrences.

How to cite: Morales, C., Montanyà, J., Lopéz, J., Van Der Velde, O., Østgaard, N., Neubert, T., and Reglero, V.: GLM lightning flashes observed during ASIM triggers over Tropical South America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12658, https://doi.org/10.5194/egusphere-egu24-12658, 2024.

EGU24-13074 | ECS | Posters on site | NH1.5 | Highlight

A Deep Learning Approach to Lightning Nowcasting and Forecasting 

Randall Jones, Joel Thornton, Dale Durran, Lyatt Jaeglé, Christopher Wright, and Robert Holzworth

Lightning plays a fundamental role in Earth’s climate system and is a frequently occurring natural hazard. However, lightning remains a relatively unpredictable area of meteorology, especially in terms of lightning frequency per convective event, with limited ability for nowcasting and forecasting of lightning occurrence. The goal of this study is to develop a deep learning algorithm able to replicate lightning stroke density on a climatological average, as well as on a convective feature basis. We use a convolutional neural network (CNN) containing combinations of the following variables at 0.5-degree by 0.5-degree spatial resolution and a 3-hourly temporal-resolution over a domain that encompasses most of the Western Hemisphere: lightning from the World-Wide Lightning Location Network (WWLLN), precipitation rate from NASA’s Integrated Multi-satellite Retrievals for GPM (IMERG) and convective available potential energy (CAPE), cloud base height (CBH), two-meter temperature (T2M) and zero degree level (ZDL) from the European Centre for Medium-Range Weather Forecasting (ECMWF). We train the CNN on the years from 2010 to 2018, and tested on the years 2019 to 2022. Model performance was evaluated on a four-year average through changes to the initial seed used to train the model, the loss function used, transformations to the lightning dataset, and changing the spatial and temporal resolution of the input datasets. We further examined the value of 11 input variable combinations, from single variables to all five variables used in training. Preliminary results show that changing the initial seed, as well as changing the loss function from mean squared error to mean-squared logarithmic error, does not greatly impact model performance when running the model with more than one input variable. Results vary amongst the variable combinations, but amongst the different initial seeds and loss functions, the r-squared values remain above 0.75 for every model configuration over both land and ocean. Model performance is improved when using higher time resolution training set but not necessarily a higher spatial resolution. For example, a 1-degree by 1-degree spatial resolution and a 3-hourly time resolution resulted in an r-squared between predicted and observed lightning frequency 0.1 higher than that using 0.5-degree by 0.5-degree spatial resolution and a daily time resolution. The model is able to reproduce the approximate evolution of lightning stroke density of individual convective events, but tends to overestimate the stroke density on a 3-hourly basis. Future work will include a steeper penalty for overestimating lightning occurrence during training. These results show that larger-scale weather forecasting and earth system models could significantly improve lightning stroke density parameterizations by incorporating deep learning results.

How to cite: Jones, R., Thornton, J., Durran, D., Jaeglé, L., Wright, C., and Holzworth, R.: A Deep Learning Approach to Lightning Nowcasting and Forecasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13074, https://doi.org/10.5194/egusphere-egu24-13074, 2024.

EGU24-13383 | ECS | Posters on site | NH1.5

Peak currents of terminating flashes in thunderstorm ground enhancements around Mt Aragats, Armenia 

Gayane Karapetyan, Earle Williams, Hripsime Mkrtchyan, and Reik V. Donner

Thunderstorm ground enhancements (TGEs) are high-energy particle fluxes detected at the ground level during thunderstorms. It has been observed that some TGEs experience abrupt termination by lightning strikes (Chilingarian 2015, Tsuchiya 2013, Williams et al., 2022) often accompanied by simultaneous reductions in flux. Understanding the origin and parameters of terminating lightning can provide insights into the distribution of electric fields and potential within thunderclouds. 

Thundercloud potential is a key factor in determining the maximum peak current of lightning. One expects a linear relationship between peak current and cloud potential because the charge that is deposited on the leader channel is proportional to the leader potential (e.g. Chronis et. al. 2015). 

This study evaluates peak currents in terminating flashes documented in TGEs observed around Mt Aragats (Armenia) using a ground-based VLF lightning detection network, GLD360. A total of 71 terminating flashes have been identified over a period of 6 years (2017-2022). The events documented at Aragats were detected by particle detectors that showed the abrupt decrease in flux associated with lightning. These events were accurately timed using an EFM100 electric field mill (resolution of 2Hz). Thereafter, correlations between these events and the corresponding GLD360 lightning events were established, using millisecond precision times of GLD360 and electric field mill.

Our findings show that the mean peak current of this collection of terminating flashes (45 kA) is 3.4 times higher than that of the general population of lightning flashes measured in the same location (13.6 kA) over a similar period of time. However, it is difficult to define the relationship between the change in electric field during TGE or lightning and the peak currents. It appears that lightning with smaller peak currents tends to have larger values of the change of electric field, while lightning with larger peak currents is characterized by an average change in the electric field.

This research provides insights into peak currents of terminating lightning flashes with general parameters of the TGEs, such as duration and flash rate. Additionally, it shows that flashes with extremely high peak currents occur during thunderstorms with smaller flash rates and are located within 10 km distance from the particle detectors. Furthermore, flash rates of thunderstorms with terminating lightning are larger compared to general thunderstorms without TGEs.

How to cite: Karapetyan, G., Williams, E., Mkrtchyan, H., and Donner, R. V.: Peak currents of terminating flashes in thunderstorm ground enhancements around Mt Aragats, Armenia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13383, https://doi.org/10.5194/egusphere-egu24-13383, 2024.

EGU24-13989 | Posters on site | NH1.5

C3IEL, the Cluster for Cloud evolution ClImatE and Lightning mission to study convective clouds at high spatial and temporal resolutions 

Eric Defer, Celine Cornet, Daniel Rosenfeld, Cecile Cheymol, Adrien Deschamps, Alex Frid, Laurene Gillot, Vadim Holodovsky, Avner Kaidar, Raphael Peroni, Colin Price, Didier Ricard, Antoine Rimboud, Yoav Schechner, Aviad Shmaryahu, and Yoav Yair

The French-Israeli space-borne C3IEL (Cluster for Cloud evolution, ClImate and Lightning) mission aims at providing new insights on convective clouds, at high spatial and temporal resolutions, close to the scales of the individual convective eddies. The mission will simultaneously characterize the convective cloud dynamics, the interactions of clouds with the surrounding water vapor, and the lightning activity.

The C3IEL mission consists in a short-baseline (~150 km) train of 2 synchronized nano-satellites. Each nano-satellite carries a visible camera (670 nm) for cloud imagery at a spatial resolution of ~20 meters, near-infrared water vapor imagers (1.04, 1.13 et 1.37 µm) measuring in and near the water vapor absorption bands, and a lightning imager (777.4 nm) and at least one photometer (777.4 nm).

The scientific objectives of the C3IEL mission, i.e. documenting the 3D evolution of the clouds’ surface, entrainment of water vapor, and electrification, will be first reminded. Then, we will introduce the satellite train configuration, the different sensors of the mission and the innovative and different observational strategy that will be applied during daytime and nighttime. We will then detail the expected observations and products, including the ones related to lightning.

How to cite: Defer, E., Cornet, C., Rosenfeld, D., Cheymol, C., Deschamps, A., Frid, A., Gillot, L., Holodovsky, V., Kaidar, A., Peroni, R., Price, C., Ricard, D., Rimboud, A., Schechner, Y., Shmaryahu, A., and Yair, Y.: C3IEL, the Cluster for Cloud evolution ClImatE and Lightning mission to study convective clouds at high spatial and temporal resolutions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13989, https://doi.org/10.5194/egusphere-egu24-13989, 2024.

EGU24-14531 | ECS | Posters virtual | NH1.5

Identifying atmospheric conditions for intermittent, small-scale lightning discharges near the top of thunderstorms 

Reinaart van Loon, Jelle Assink, Olaf Scholten, Brian H Hare, and Hidde Leijnse

Despite its impact on society, many aspects of lightning, including the initiation and propagation, remain poorly understood. This also applies to a distinct type of intermittent small-scale lightning discharges recorded by the Low-Frequency Array (LOFAR) in the Netherlands (Scholten et al., 2023). The so-called “sparkles” seem uncorrelated and occur relatively high up in thunder clouds near the tropopause. This research investigates the meteorological conditions under which sparkles exist.  

Previous literature suggests a correlation between sparkles and strong updrafts. One hypothesis proposes that powerful updrafts overshooting the level of neutral buoyancy causes a charged screening layer aloft to be entrained into the cloud, resulting in charge pockets. Alternatively, some hypothesize that turbulence plays a vital role in discharge initiation and charge sedimentation. Therefore, intense turbulence near the top of strong updrafts could not only initiate numerous discharges, but could also influence the lightning structures through the spatial charge distribution. 

This project aims to improve the understanding of sparkles by comparing high- resolution LOFAR lighting data with meteorological data. Specifically, thunderstorm dynamics are studied using data from satellites, radar and the HARMONIE weather forecast model. Following the hypotheses, relations are explored between sparkling activity and factors such as updrafts strength, turbulence, mixing, and entrainment of the air aloft.

Scholten, O., Hare, B. M., Dwyer, J., Liu, N., Sterpka, C., Assink, J., ... & Veen, S. T. (2023). Small‐Scale Discharges Observed Near the Top of a Thunderstorm. Geophysical Research Letters, 50(8), e2022GL101304. 

How to cite: van Loon, R., Assink, J., Scholten, O., Hare, B. H., and Leijnse, H.: Identifying atmospheric conditions for intermittent, small-scale lightning discharges near the top of thunderstorms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14531, https://doi.org/10.5194/egusphere-egu24-14531, 2024.

EGU24-14754 | Orals | NH1.5

Quantitative detection device for NOx of centimeters-discharge and its preliminary applications in laboratory long spark and rocket-triggered lightning 

Rubin Jiang, Yufan Ren, Ruiling Chen, Hongbo Zhang, Mingyuan Liu, Xinran Xia, Jianwen Wu, Dongfang Wang, Kun Liu, and Xiushu Qie

A quantitative detection device for nitrogen oxides (NOx) produced by the centimeters-scale discharge channel is designed, consisting of a container made of high-strength acrylic Plexiglas, two copper metal electrodes fixed to the top and bottom of the container, a pumping system and a back-end NOx detector. Inside the container, the gap between the two copper electrodes is 4 cm in length. When a discharge occurs between the electrodes, the NOx produced by the air ionization are confined within the container to provide a quantitative measurement. The device can be used in the laboratory long spark and rocket-triggered lightning scenarios, with container volumes of 12.2 L and 58.8 L, respectively, both of which ensure an accurate measurement of the discharge current. In the laboratory long spark scenario, the device is placed under the discharge electrode of the Marx generator. As the discharge is generated, the discharge strikes the upper copper metal electrode and leads to the gap breakdown within the container, then the current is released through the bottom copper metal electrode to the ground. In the rocket-triggered lightning scenario, the device is fixed between the current sensor and the grounding system. The triggered discharge leads to the gap breakdown within the container, and the current is also released through the bottom copper metal electrode to the ground. After the discharge, the gas in the canister is pumped to the NOx concentration meter. The instruments used are the Thermo, which uses a chemical method to measure NO and NOx concentrations with a time resolution of 1 minute, and the LGR-NO2, which uses an optical method to measure NO2 concentrations with a time resolution of 1 second. The preliminary experiment shows that the 4 cm long discharge due to the laboratory long spark with a peak current of about 2 kA produced 6.8×1017 NO2 molecules. In an unsuccessful triggering lightning case, the discharges due to the precursors also lead to significant NOx signals.

How to cite: Jiang, R., Ren, Y., Chen, R., Zhang, H., Liu, M., Xia, X., Wu, J., Wang, D., Liu, K., and Qie, X.: Quantitative detection device for NOx of centimeters-discharge and its preliminary applications in laboratory long spark and rocket-triggered lightning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14754, https://doi.org/10.5194/egusphere-egu24-14754, 2024.

EGU24-15389 | ECS | Posters on site | NH1.5

TGFs observed by the ALOFT 2023 flight campaign during an ISS overpass 

Ingrid Bjørge-Engeland, Nikolai Østgaard, Timothy Lang, Martino Marisaldi, J. Eric Grove, Mason Quick, Hugh Christian, Christopher Schultz, Richard Blakeslee, Ian Adams, Rachael Kroodsma, Gerald Heymsfield, Andrey Mezentsev, David Sarria, Anders Fuglestad, Nikolai Lehtinen, Kjetil Ullaland, Shiming Yang, Bilal Hasan Qureshi, and Jens Søndergaard and the ALOFT team

During the Airborne Lightning Observatory for FEGS and TGFs (ALOFT) campaign in July 2023, the International Space Station (ISS), at an altitude of approximately 410 km, passed over the same region as covered by ALOFT within a short time period on the 24th of July. The ALOFT campaign, which carried gamma-ray detectors, photometers, and instruments for characterizing the electrical activity and the cloud environment, flew at an altitude of approximately 20 km and covered thunderstorms over the Gulf of Mexico and Caribbean during its 60 flight hours. The Atmosphere-Space Interactions Monitor (ASIM) is mounted on the ISS, with its Modular X- and Gamma-ray Sensor (MXGS) designed for observing TGFs. During the ISS overpass, ALOFT observed six TGFs within less than two minutes that were all within the field of view of the ASIM instrument. However, none of the TGFs were detected by ASIM. Here we present the six TGFs observed by ALOFT during the ISS overpass and discuss their source properties. The ASIM non-detection provides a strong upper limit on the TGF fluence.

How to cite: Bjørge-Engeland, I., Østgaard, N., Lang, T., Marisaldi, M., Grove, J. E., Quick, M., Christian, H., Schultz, C., Blakeslee, R., Adams, I., Kroodsma, R., Heymsfield, G., Mezentsev, A., Sarria, D., Fuglestad, A., Lehtinen, N., Ullaland, K., Yang, S., Hasan Qureshi, B., and Søndergaard, J. and the ALOFT team: TGFs observed by the ALOFT 2023 flight campaign during an ISS overpass, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15389, https://doi.org/10.5194/egusphere-egu24-15389, 2024.

EGU24-15691 | ECS | Posters on site | NH1.5

Supervised Machine Learning for the Automatic Classification of Triggers from ASIM/MXGS on board the ISS 

Jose E. Adsuara, Javier Navarro-González, Paul Connell, Víctor Reglero, Nikolai Østgaard, and Torsten Neubert

During ASIM operations from June 2018 until the end of 2019, 486 TGFs were observed. For this task, the ASDC (ASIM Science Data Center) dealt with numerous triggers from the instrument (5000 per week). The relocation of the instrument from EPF SDX to EPF SDN (Starboard Deck Nadir) of the Columbus ISS Module on January 10, 2022, demonstrated that the MXGS location capabilities could be used not only for TGF location but also for imaging GRB events, as its Field of View in the SDN port encompasses both Earth and space.

It's worth noting that only a few of the ASIM triggers correspond to TGF events. There is a screening process employing a series of algorithms to detect and discard false positives (triggers that are not TGFs). Nevertheless, the ASIM archive retains all data from every trigger. Due to the extended operational time, there is currently a sufficiently large database that enables us to present the initial results here using novel machine learning methods, such as kernel methods or neural networks, for the automatic categorization of both present and future events.

Furthermore, our interest goes beyond mere classification, as we are currently investigating whether various explainability methods applied to these techniques can assist in identifying the relevant features of the signal for such classification. The aim of this work is to provide a tool to quantify new physical processes that could be the cause of instrument triggers and to examine whether there is a connection with the Earth-Space global circuit.

How to cite: Adsuara, J. E., Navarro-González, J., Connell, P., Reglero, V., Østgaard, N., and Neubert, T.: Supervised Machine Learning for the Automatic Classification of Triggers from ASIM/MXGS on board the ISS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15691, https://doi.org/10.5194/egusphere-egu24-15691, 2024.

EGU24-16929 | Orals | NH1.5

Constraining electrification of volcanic plumes through numerical simulation 

Michael Herzog, Vishnu Nair, Alexa Van Eaton, and Ted Mansell

Technological improvements over the past decade have dramatically increased lightning detection from explosive eruptions worldwide. The underwater Hunga Tonga-Hunga Ha’apai volcano eruption in January 2022 in Tonga produced more lightning than any storm yet documented in the modern satellite era. These observations of volcanic lightning capture the imagination of the public and provide novel ways to monitor explosive hazards in near real time. In this presentation, we present the first results from the numerical simulation of the electrification of a volcanic plume using the volcanic plume model ATHAM. The electrification mechanisms of fracto-emission and triboelectrification along with the macroscopical transport of the charge carrying plume components have been modelled in ATHAM to make this the first numerical model to quantify volcanic electrification. We also present first results of discrete lightning discharges which are diagnosed as continuous branching regions defined by local net charge density and electric potential. 

The enhanced modelling capability of ATHAM opens new routes into the study of explosive eruptions and nowcasting of volcanic ash hazards for aviation and downwind communities. 

How to cite: Herzog, M., Nair, V., Van Eaton, A., and Mansell, T.: Constraining electrification of volcanic plumes through numerical simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16929, https://doi.org/10.5194/egusphere-egu24-16929, 2024.

EGU24-17483 | ECS | Orals | NH1.5

Characterisation and modelling of lightning strikes as point events in time and space 

Uldis Zandovskis, Davide Pigoli, and Bruce D. Malamud

Lightning, a spatio-temporal phenomenon, comprises of individual strikes with specific occurrence times and spatial coordinates. This study models and characterises lightning strikes from single thunderstorms, treating each strike as a point event. Utilising real-world datasets, we characterise and model lightning strikes' physical properties. Our analysis involves two severe UK thunderstorm systems, selected based on published synoptic analyses. These systems enable subdivision of the lightning dataset into subsets, each representing a distinct thunderstorm. Our two major storm systems feature three thunderstorms each: Storm system A with 7955, 11988, and 5655 strikes over the English Midlands on 28 June 2012; Storm system B with 4218, 455, and 1926 strikes characterised over the northern England on 1-2 July 2015. These six datasets exemplify individual thunderstorms and a total of three physical attributes are : movement speed, lightning inter-event time distribution, and spatial spread about the storm track. Applying least-squares plane and linear fits in the spatio-temporal and lag spaces, we estimate movement speeds of 47-59 km/h and 67-111 km/h for Storm systems A and B, respectively. The inter-event time distribution ranges from 0.01 to 100 seconds, with density peaks around 0.1 seconds and at 1-10 seconds. Autocorrelation analysis in natural time reveals significant autocorrelation in all storms, varying from short-range to long-range. For spatial spread, calculated as the distance from the storm track to the strikes, we employ a linear filter to establish the storm track. This analysis yields typical spatial spreads up to 80 km in either northing or easting dimensions, with an outlier of 226 km in the northing dimension for one storm. The paper concludes with a synthetic lightning strike model. This model allows selection of individual storms' starting points, directions, and movement speeds, generating point events based on our characterisation findings. This comprehensive study of lightning strikes in time and space accurately reflects severe thunderstorms' behaviour and informs statistical models for simulating lightning events.

How to cite: Zandovskis, U., Pigoli, D., and Malamud, B. D.: Characterisation and modelling of lightning strikes as point events in time and space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17483, https://doi.org/10.5194/egusphere-egu24-17483, 2024.

EGU24-18529 | Orals | NH1.5

Analysis of an upward discharge above a thundercloud over Mediterranean Sea 

Serge Soula, Gabriel Hausknost, Axel Ventre, Sylvain Coquillat, Janusz Mlynarczyk, and Alex Hermant

On the night of November 1st, 2022, several weather photographers obtained remarkable photos showing a jet-like phenomenon with long blue filaments above a Mediterranean storm. An unprecedented set of optical and electrical data, including two pictures, one movie, VHF sources from a Lightning Mapping Array (LMA), detections from a LLS and Current Moment Waveforms from an ELF detection, makes it possible to characterize this event. It consists of a two-part upward luminous channel emerging from the cloud top at 11.8 km of altitude, developing up to 14.2 km and topped with blue streamers up to 17.2 km. It is embedded in a flash which starts with a positive 25 kA-discharge followed by a continuing current during 75 ms associated with VHF sources at 10 km. Contrary to blue jets and blue starters which have a positive polarity, the luminous event above the cloud is identified as a negative leader followed by three channel brightenings linked to the negative charge of a positive cloud dipole. The luminous event-producing flash is preceded by a convective surge and a production of positive flashes within the same region of the cloud. The triggering conditions and mechanisms of the event share similarities with gigantic jets, especially its polarity and a reduced upper positive charge.

How to cite: Soula, S., Hausknost, G., Ventre, A., Coquillat, S., Mlynarczyk, J., and Hermant, A.: Analysis of an upward discharge above a thundercloud over Mediterranean Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18529, https://doi.org/10.5194/egusphere-egu24-18529, 2024.

EGU24-18594 | Orals | NH1.5 | Highlight

Observations of thunderstorms with a neuromorphic camera: First results of the THOR-DAVIS experiment on the International Space Station. 

Olivier Chanrion, Nicolas Pedersen, Yoav Yair, Martin Stendel, Andreas Mogensen, Dongshuai Li, Andreas Stokholm, and Torsten Neubert

THOR-DAVIS is an experiment on the International Space Station to observe thunderclouds and their electrical activity with a neuromorphic camera and a co-aligned video camera. A neuromorphic camera, or 'event camera,' only reads pixels when there is a change in pixel illumination, allowing for a temporal resolution that may reach 10 microseconds. Launched by the SpaceX Commercial Resupply Service mission on June 5, 2023, THOR-DAVIS was part of Danish ESA astronaut Andreas Mogensen’s Huginn mission. The scientific focus was to conduct video observations of electrical activity at the cloud tops and the stratosphere above and to extract their altitudes. The technical objective was to test the neuromorphic concept for observations of thunderstorms from space. Andreas Mogensen performed 15 days of observations, passing over 48 thunderstorms, most forecasted by us a day in advance following a procedure inherited from previous ISS experiments (THOR (2015), ILAN-ES (2022)) and some at his own initiative. In all, 36 thunderstorms were recorded in both cameras, totaling ~3 hours of observations. Most notably, Andreas Mogensen secured the first observations of sprites and of an elve with a neuromorphic camera. In addition, numerous lightning flashes, including spider lightning with leader branches extending above the clouds, were observed. The presentation will provide an overview of the THOR-DAVIS payload design, laboratory measurements, and some of the observations from the ISS.

How to cite: Chanrion, O., Pedersen, N., Yair, Y., Stendel, M., Mogensen, A., Li, D., Stokholm, A., and Neubert, T.: Observations of thunderstorms with a neuromorphic camera: First results of the THOR-DAVIS experiment on the International Space Station., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18594, https://doi.org/10.5194/egusphere-egu24-18594, 2024.

EGU24-18787 | Orals | NH1.5

Machine Learning to predict Downbursts in Japan Based on Total Lightning and Ground Precipitation Data 

Alexander Shvets, Yasuhide Hobara, Shiho Miyashita, Hiroshi Kikuchi, Jeff Lapierre, and Elizabeth DiGangi(

In this study, using total lightning data from the Japan Total Lightning Network (JTLN) and precipitation data from X-band MP radar, machine learning with a Random Forest model was used to successfully classify the occurrence of downbursts in Japan. TL data associated with the event is collected from JTLN which consists of 11 Earth Networks Total Lightning Sensorsover Japan (data set in 2017, currently 16 stations nationwide) deployed by the UECand jointly operated with Earth Networks. These sensors can detect lightning pulses with a spatial resolution of 500 m. TL parameters such as types of lightning (IC and CG), time of occurrence (UT), location (latitude-longitude), and lightning polarity were collected for each lightning discharge. Ground precipitation data (temporal resolution of 1min, spatial resolution of 250m) from the Ministry of Land, Infrastructure, Transport, and Tourism’s eXtended RAdar Information Network (XRAIN) composed of 26 C-band radars and 39 X-band multiparameter (X-MP) radars are used. Fourteen thunderstorms causing gusty winds and 33 of those without causing gusty winds that occurred in Japan from 2014 to 2017 were analyzed. AITCC (Algorithm for the Identification and Tracking of Convective Cells) was applied to track both precipitation cell and associated lightning discharges. By using Random Forest model, the importance of variables was derived, and it was shown that lightning jump is one of the most important variables for predicting downbursts. This implies that the updrafts inside the clouds are closely related to the occurrence of a significant increase in lightning, followed by a downburst. The prediction accuracy was highest for models that included both lightning and precipitation, followed by lightning-only and precipitation-only models, confirming the importance of data fusion for improving prediction accuracy.

How to cite: Shvets, A., Hobara, Y., Miyashita, S., Kikuchi, H., Lapierre, J., and DiGangi(, E.: Machine Learning to predict Downbursts in Japan Based on Total Lightning and Ground Precipitation Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18787, https://doi.org/10.5194/egusphere-egu24-18787, 2024.

EGU24-20590 | Orals | NH1.5

Re-discharges on preexisting negative leader channels of a positive cloud-to-ground lightning flash  

Zhuling Sun, Xiushu Qie, Mingyuan Liu, and Fengquan Li

Using the lightning VHF interferometer, three types of discharges on the preexisting negative leader channels of a positive cloud-to-ground lightning flash were observed. The first type involved small-scale cluster discharges during the simultaneous development of the upper horizontally negative leader and downward positive leader before the return stroke. These discharges exhibited similar characteristics and radiation features as the needle-like discharges on the positive leader. Over time, their occurrence positions progressed toward the head of the negative leader, and some cluster discharges had the potential to develop into new negative branches. The other two types of re-discharges occurred after the return stroke. Immediately after the return stroke, rapid discharges initiated near the head of the negative leader, developed along the preexisting negative leader channel, and caused the decayed negative leaders to progress forward again. Subsequently, numerous lateral discharges breaking down the air occurred, distributed widely throughout the negative leader channel. These discharges developed rapidly, gradually slowing down over time until the long continuous current ended. In comparison to the positive leader discharges before the return stroke, which showed no obvious recoil leader discharges, the negative leader channel was more prone to extinguish. These re-discharges on the preexisting negative leader channel were influenced by both radial and longitudinal electric fields of flash channels, and they could also generate a backward surging current wave to sustain the discharge process on the positive leader or grounded channel.

How to cite: Sun, Z., Qie, X., Liu, M., and Li, F.: Re-discharges on preexisting negative leader channels of a positive cloud-to-ground lightning flash , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20590, https://doi.org/10.5194/egusphere-egu24-20590, 2024.

EGU24-20630 | Orals | NH1.5

eLMA: Supercells over the Upgraded Ebro 3D Lightning Mapping Array and High-speed Observations of Lightning in the Near-Ultraviolet 

Oscar van der Velde, David Romero, Jesús López, Joan Montanyà, and Nicolau Pineda

In 2011, the Ebro 3D Lightning Mapping Array was the first LMA installed outside the USA, consisting of 12 stations in 2012-2014 and was subsequently split in half in 2015 to facilitate a LMA in Colombia.

Thanks to research infrastructure service funding from the Spanish government and the European Union (MCIN/AEI/10.13039/501100011033/ and NextGenerationEU, project EQC2021-006957-P), the Ebro LMA has been upgraded to a wider area network operating 15 latest technology LMA stations operating on solar power in the Ebro Valley region (western Catalonia and eastern Aragón). New services are offered: (1) Real-time tracking of lightning flashes across northeastern Spain, available to the public via the website elma.upc.edu. (2) Archive of plotted data that can be browsed freely, including for the old Ebro LMA data. (3) Raw/processed data can be requested. (4) LMA rental is possible for field campaigns.

We developed a new processing & visualization tool for flash/thunderstorm analysis and future integration with the new EUMETSAT Lightning Imager (LI). It is written in the Julia programming language for its speed of processing with the Makie interactive graphics package. Additionally, we present a new tool for displaying regional maps of actual (not computed) LMA station contributions to assess the network performance. The capabilities of the new Ebro LMA are showcased with record-setting horizontal lightning flashes, several large-hail producing supercells with high flash rates, a lightning hole, and rising turrets of small flashes and sparks at the cloud top, which can now be isolated and analyzed with the Julia visualization tool. The electrical evolution features of these supercells are examined in relation to their timeline of severe weather production.

Additionally, a Vision Research Phantom TMX 6410 and UV-sensitive Lambert HiCATT 25 image intensifier with optics and filters were acquired, and is also available to third parties via eLMA rental services. During spring/summer 2023 it has been successfully used to image lightning leaders through a 337 nm optical narrowband filter (10 nm width) similar to imaging systems of the Atmosphere-Space Interactions Monitor (ASIM), at speeds of 65,000 to 320,000 frames per second. We found that observation distances <4 km are needed in order to be able to see the stepped leader in negative cloud-to-ground flashes. However, in only one case, of an intense burst of horizontal leader activity below the cloud base, negative streamers can be clearly distinguished and the stepping process analyzed over time. At greater distances only return strokes and dart leaders are tracked through the 337 nm filter. In fact, a >418 ms long continuing current negative return stroke (cut off by end of buffer) was observed. Also, the system captured elves, nocturnal optical emissions at the base of the ionosphere (85 km) over Mediterranean winter thunderstorms, clearly showing the typical double-wave structure originally reported by photometer arrays.

How to cite: van der Velde, O., Romero, D., López, J., Montanyà, J., and Pineda, N.: eLMA: Supercells over the Upgraded Ebro 3D Lightning Mapping Array and High-speed Observations of Lightning in the Near-Ultraviolet, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20630, https://doi.org/10.5194/egusphere-egu24-20630, 2024.

EGU24-20763 | ECS | Orals | NH1.5

Low-frequency sferics associated with consecutive Terrestrial Gamma-ray Flashes  

Hongbo Zhang, Xiushu Qie, and Gaopeng Lu

Terrestrial Gamma-ray Flashes (TGFs) are brief and intense emissions of hard X-rays and gamma-rays originating inside thunderstorms. It has been observed that TGF occurs much less frequently than lightning. However, the TGF generation conditions and mechanism of are not clear, such as why just the TGF-associated lightning produces TGF while others not. Consecutive TGFs detected by space-based platform are usually several seconds to 1-2 minutes apart, and they come from same meteorological environment and even from the same storm cells. This provides a possibility to understand the relationship between lightning and TGF. Based on Fermi high-energy photons observations and the ground low-frequency (LF) lightning sferics measurements, more than 10 pairs of consecutive TGFs with synchronous LF lightning waveform are analyzed. Preliminary results show that the sferics of each TGF pairs are almost same, while they vary with different pairs. More details will be shown. In addition, some TGFs detected by ASIM and the associated lightning will also be introduced.

How to cite: Zhang, H., Qie, X., and Lu, G.: Low-frequency sferics associated with consecutive Terrestrial Gamma-ray Flashes , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20763, https://doi.org/10.5194/egusphere-egu24-20763, 2024.

Based on the work of several PhD students in Amsterdam, we now have a verified model for positive streamers in air. For streamer propagation a fluid model is sufficient, while for branching the discreteness of the photo-ionization events has to be taken into account. The model results on propagation and branching have both been validated on experiments in Eindhoven, and hence a few streamers can now be modeled quantitatively in 3D. However,  bursts or coronas with hundreds and more streamers are computationally not feasible. Instead of this, models of dielectric breakdown type should be developed, but based on the now known microscopic basis. We present two results in this direction: 1. The identification of steady positive and negative streamers and a revision of the concept of the stability field. 2. The analysis of streamer heads as coherent structures which allows a macroscopic characterization of the streamer head dynamics by few parameters such as radius, velocity, maximal and minimal field, ionization degree etc. (up to now only for positive streamers). Together with the branching simulations, these are stepping stones towards a reduced model of dielectric breakdown type for multi-streamer structures.

The models were developed and evaluated by the PhD students Dennis Bouwman, Hani Francisco, Baohong Guo, Xiaoran Li and Zhen Wang under the supervision of Jannis Teunissen and Ute Ebert in Amsterdam, and the experiments used for model validation were performed by Ph.D. students Siebe Dijcks and Yihao Guo under the supervision of Sander Nijdam in Eindhoven. For the reduced model, we collaborate with Alejandro Luque in Granada, Spain.

How to cite: Ebert, U.: Towards quantitative modeling of multi-streamer processes in 3D, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20811, https://doi.org/10.5194/egusphere-egu24-20811, 2024.

EGU24-20835 | ECS | Orals | NH1.5

3D Geolocation of Simulated Lightning Sources from Low-Earth Orbit 

Jackson Remington, Sonja Behnke, Harald Edens, Patrick Gatlin, Timothy Lang, Nikhil Pailoor, Mason Quick, and Sarah Stough

The recent removal of the Lightning Imaging Sensor from the International Space Station has left an observational gap in lightning detection from low-Earth orbit (LEO). However, new studies have demonstrated the potential for 3D geolocation of lightning sources using orbiting sensors. The Cubespark mission concept aims to take advantage of these developments by deploying a constellation of satellites with radio frequency (RF) sensors and optical imagers to not only map lightning locations, but also to collect bi-spectral flash images. These new capabilities include mapping storm charge structure, flash channel structure, and distinguishing microphysical processes throughout flash development, helping link microphysics and convective processes with overall flash and storm structure around the globe from LEO.

In this study, we simulate lightning RF sources in the very high frequency (VHF) band, extrapolate their signals to space-based detection using an improved ionospheric model, and reconstruct their 3D locations using a time-of-arrival (TOA) minimization algorithm. Various constellation configurations, locations, and atmospheric conditions are considered in order to identify and quantify the three main sources of geolocation error: geometric, ionospheric, and instrumental effects. The promising results of this study emphasize the potential of space-based 3D lightning mapping under diverse conditions. 3D resolution is shown to be better than 1-2 km in many cases, enabling new global applications in meteorology and climate sciences. Here we present a selection of these geolocation results as seen from space alongside recent advancements, paving the way for a future generation of LEO lightning mappers.

How to cite: Remington, J., Behnke, S., Edens, H., Gatlin, P., Lang, T., Pailoor, N., Quick, M., and Stough, S.: 3D Geolocation of Simulated Lightning Sources from Low-Earth Orbit, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20835, https://doi.org/10.5194/egusphere-egu24-20835, 2024.

EGU24-20882 | ECS | Orals | NH1.5

Mixed Mode of Charge Transfer During an Upward Positive Flash at Säntis Tower 

Toma Oregel-Chaumont, Antonio Šunjerga, Marcos Rubinstein, and Farhad Rachidi

The term “mixed mode of charge transfer to ground for initial continuous current (ICC) pulses” in the context of upward lightning flashes was first proposed by Zhou et al. 2011 [1] to describe fast pulses, distinct from the classical M-component mode of charge transfer, superposed on the slowly varying initial-stage current of upward negative flashes they observed at the Gaisberg Tower in Austria. The pulses in question were associated with leader/return-stroke processes occurring in decayed or newly created branches of the plasma channel connecting to the grounded, current-carrying channel, with junction points below the cloud base (height < 1 km) [1,2].

Herein, we report, to the best of our knowledge, the first observation of a mixed-mode-type pulse during the initial stage of an upward positive flash that was initiated from the Säntis Tower in Switzerland. The Mt. Säntis Lightning Research Facility, which recorded the flash, consists of a current measurement system installed in the mountaintop tower (2.5 km ASL), slow and fast electric field sensors and X-ray detectors 20 m from the tower base, an additional fast E-field sensor 15 km away, as well as full HD cameras and a high-speed camera (HSC) at various distances, among other systems (see Šunjerga et al. 2021 for details [3]).

The observed flash, categorized as a Type 1 from its current waveform (see Romero et al. 2013 for definition [4]), occurred at 16:24:03 UTC on July 24th, 2021, during the Laser Lightning Rod project [5]. Its “return stroke”-like main pulse was confirmed from HSC footage to have been triggered by a downward-connecting leader with a junction height of approximately 369±5 m AGL, well below the defined cut-off of 1 km. Interestingly, though the 12 kA peak current is reasonable for a mixed-mode pulse, the current and E-field risetimes were both >10 μs, more characteristic of a M-component-type ICC pulse [2].

These observations are important to improving our understanding of the charge transfer mechanisms in upward lightning flashes, which regularly damage wind turbines, telecommunications towers, and airplanes during take-off and landing.

 

References:

[1] Zhou, H., Diendorfer, G., Thottappillil, R., Pichler, H., Mair, M. (2011). Mixed mode of charge transfer to ground for initial continuous current pulses in upward lightning. In 2011 7th Asia-Pacific International Conference on Lightning (pp. 677–681). Chengdu, China: IEEE. https://doi.org/10.1109/APL.2011.6110212

[2] Zhou, H., Rakov, V. A., Diendorfer, G., Thottappillil, R., Pichler, H., Mair, M. (2015). A study of different modes of charge transfer to ground in upward lightning. Journal of Atmospheric and Solar-Terrestrial Physics, 125–126, 38–49. https://doi.org/10.1016/j.jastp.2015.02.008

[3] Šunjerga, A., Mostajabi, A., Paolone, M., Rachidi, F., Romero, C., Hettiarachchi, P., … Smith, D. (2021). Säntis Lightning Research Facility Instrumentation. International Conference on Lightning Protection, 6.

[4] Romero, C., Rachidi, F., Rubinstein, M., Paolone, M., Rakov, V. A., Pavanello, D. (2013). Positive lightning flashes recorded on the Säntis tower from May 2010 to January 2012: POSITIVE LIGHTNING SÄNTIS TOWER. Journal of Geophysical Research: Atmospheres, 118(23), 12,879-12,892. https://doi.org/10.1002/2013JD020242

[5] Houard, A., Walch, P., Produit, T., Moreno, V., Mahieu, B., Šunjerga, A., … Wolf, J.-P. (2023). Laser-guided lightning. Nature Photonics, 17(3), 231–235. https://doi.org/10.1038/s41566-022-01139-z

How to cite: Oregel-Chaumont, T., Šunjerga, A., Rubinstein, M., and Rachidi, F.: Mixed Mode of Charge Transfer During an Upward Positive Flash at Säntis Tower, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20882, https://doi.org/10.5194/egusphere-egu24-20882, 2024.

EGU24-20981 | Orals | NH1.5 | Highlight

Energy from extraterrestrial sources is driving arctic lightning 

Eija Tanskanen and Marzieh Khansari

The possible effect of solar activity on lightning has been studied for a long period of time. Specifically, the relationship between sunspot number and lightning activity has been investigated, although the results still remain inconclusive across regions and time. In some regions, a positive correlation is found, in others a negative one. Thus, it is important to explore other solar-geomagnetic variables possibly influencing lightning activity.

In order to examine the possible relationship between solar activity and lightning activity we will study lightning and geomagnetic activity at the latitudes of 50° to 70° together with the solar and solar wind observations (SDO, ACE, OMNI database).  Data from the Nordic lightning location system (NORDLIS) was used for lightning strikes and geomagnetic measurements from Sodankylä Geophysical Observatory, INTERMAGNET and IMAGE for geomagnetic disturbances. Our analysis showed a strong correlation between high-speed streams and lightning activity as well as with geomagnetic activity during solar cycle 23. All parameters peaked in 2003 during the early declining phase of solar cycle 23 and showed similar trends over the solar cycle. The correlation was strong and significant between latitudes 62° and 66°.  The best coupling was found at 63° and 65°, where solar wind variability explained 86% and 88% of the variability of lightning activity, respectively. We hypothesize that this correlation is because of a much larger number of energetic particles due to an exceptionally high number of HSS during solar cycle 23. Penetration of these highly energetic particles to the atmosphere and production of high energetic secondary electrons can lead to runaway breakdown in thunderclouds and initiation of lightning.

How to cite: Tanskanen, E. and Khansari, M.: Energy from extraterrestrial sources is driving arctic lightning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20981, https://doi.org/10.5194/egusphere-egu24-20981, 2024.

EGU24-21048 | Orals | NH1.5

Employing VLF and field mill measurements to predict lightning activity 

Moacir Lacerda and Carlos Augusto Morales Rodrigues

The STORM-T Laboratory of University of São Paulo (USP) – Brazil operates a VLF long range lightning detection network known as STARNET (Morales et al., 2014) and a local field mill network. We have developed and implemented two operational schemes to predict the thunderstorm activity and propagation for the next 30 minutes (Now-STARNET) and the probability of occurrence of lightning strikes in a local area within 10 minutes (YANSA – Lacerda et al., 2022). Now-STARNET scheme is based on the cell-tracking algorithm proposed by Betz et al. (2008) to identify active thunderstorms over South America (90-30W and 60S-10N). STARNET lightning measurements are hourly accumulated over grids of 0.1 x 0.1 degrees and those cumulative grids are used to identify active thunderstorms that are defined as contiguous lightning grids. For each identified thunderstorm, we retrieve the lightning activity every 1 minute and the area, speed and direction of propagation every 5 minutes. Based on these temporal and dynamical features we adjust polynomial functions to forecast the position of active thunderstorms (must have lightning activity in the last 5 minutes) for the next 30 minutes every 5 minutes. Finally, the projected areas are used to identify the Brazilian cities that will have lightning activity to issue warnings. YANSA tool uses the temporal variation of the vertical electrical field observed by field mills to compute the time between the first lightning pulse and the first cloud-to-ground stroke as defined by Rodrigues and Lacerda (2022). Based on the elapsed time and the magnitude of the electrical field, YANSA issues different warning messages (no-risk, low, moderate, high and extreme risk) that help the users to know the probability of CG occurrence and time spam for lighting activity. YANSA was configured to use 4 field mills deployed in the USP campus transmitting every 1 minute and issue warning of lightning activity in area of the university. For the conference we will present the skills of both Now-STARNET and YANSA tools in predicting lightning activity and lightning strikes by means of contingency table tests, i.e., POD, FAR and CSI. For Now-STARNET we will use STARNET measurements of 2022 and 2023 and explore how the skills change with thunderstorm size and location. For YANSA, we will use LINET and STARNET lightning strokes observed in the vicinity of the University of São Paulo during the period of 2023 to validate each message.

Rodrigues F. and M. Lacerda, "Warning of lightning risk for the first lightning produced by a thunderstorm using electric field mill network records," 2022 36th International Conference on Lightning Protection (ICLP), Cape Town, South Africa, 2022, pp. 720-723, doi: 10.1109/ICLP56858.2022.9942596.

Lacerda, M. Rodrigues, F., Verly, R., Morales C.A.R. (2023). Monitoring lightning activity by using the YANSA platform to emit warnings of lightning risk in real time with an electric field mill network. risk for the first lightning produced by a thunderstorm using electric field mill network records," 2022 36th International Conference on Lightning Protection (ICLP), Cape Town, South Africa, 2022,

 

How to cite: Lacerda, M. and Morales Rodrigues, C. A.: Employing VLF and field mill measurements to predict lightning activity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21048, https://doi.org/10.5194/egusphere-egu24-21048, 2024.

Lightning is an essential climate variable that could be influenced by climate change processes. In this study, wintertime lightning data over the Mediterranean Sea (MS) during the period 2009-2019 from the World-Wide Lightning Location Network were analyzed together with corresponding observational and modeled data of solar activity, atmospheric dynamics and seawater chemistry. The results of this analysis demonstrate that solar activity is the dominant parameter that influences lightning activity over the MS. Where, wintertime lightning intensity and frequency for lightning with energy >0.5 MJ over the MS is 237 and 517 times greater during the solar maximum compared to the minimum, respectively. In contrast, lightning activity parameters have a significantly smaller dependence on climate change parameters, including convective available potential energy, seawater salinity, pH and total alkalinity. Therefore, it is highly unlikely that trends in lightning activity over the MS due to climate change will be detectable in the near future.

How to cite: Asfur, M., Price, C., and Silverman, J.: Is winter cloud-to-sea-surface lightning activity over the Mediterranean Sea during 2009-2019 strongly influenced by solar activity?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22350, https://doi.org/10.5194/egusphere-egu24-22350, 2024.

EGU24-22447 | ECS | Orals | NH1.5

3D location estimation of lightning charges using electrostatic field changes 

Sho Yui, Yukihiro Takahashi, and Mitsutero Sato

Floods caused by the development of cumulonimbus clouds cause significant damage, especially in tropical areas, such as the Southeast Asian region. Lightning strikes in cumulonimbus clouds have been shown to correlate with a time lag of several tens of minutes preceding heavy rainfall. Therefore, it is expected that lightning observations will help us to forecast heavy rainfall. Especially, if we could know the 3-dimensional distribution of lightning charges, this information might be a good proxy way of knowing thunderstorm development.  Here, we improved 3D estimation of lightning charges using electrostatic field measurement. In this method the electrostatic field changes caused by lightning stroke are observed with a network consisting  of sensors installed at multiple locations at about 5 km interval. Based on those data, three-dimensional location and amount of charges removed by lightning stroke can be estimated. A previous study using same kind of data conducted a brute force calculation, which is not practical because it takes about 2 minutes longer than the typical interval of lightning stroke in the active thunderstorm. In this study, we propose a new method using interpolation analysis by kriging, which results in significant reduction of the estimation time to about 8 seconds. This improving will allow us to analyse more data we took so far and make the new model of thunderstorms.

This research is supported by Science and Technology Research, Partnership for Sustainable Development (SATREPS), Japan Science and Technology Agency (JST) / Japan International Cooperation Agency (JICA).

How to cite: Yui, S., Takahashi, Y., and Sato, M.: 3D location estimation of lightning charges using electrostatic field changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22447, https://doi.org/10.5194/egusphere-egu24-22447, 2024.

EGU24-18 | ECS | Posters on site | HS2.4.3

Non-stationary design rainfalls for Australia 

Lalani Jayaweera, Conrad Wasko, Rory Nathan, and Fiona Johnson

Action needs to be taken in response to the changes in future flood risk due to the impact of global warming on the magnitude and frequency of extreme rainfalls. Projected changes in extreme rainfalls can be used to estimate the associated changes in design flood estimates using Intensity-Frequency-Duration (IFD) curves in combination with event-based flood models. IFD curves are estimated from records of historical annual maxima across different storm durations and exceedance probabilities. Past studies investigating changes in extreme rainfall across Australia have been limited in scope as they have focused on single durations, single exceedance probabilities, or limited regional extents. This means that we do not yet have a comprehensive understanding of how projected changes in extreme rainfalls impact on IFD curves.

Here, to fill this gap, we investigate the changes in extreme rainfall changes across different storm durations and exceedance probabilities across 42 stations which span the entire continent of Australia. We begin with examining the trend in annual maximum rainfall across 16 different storm durations (6 min to 7 day) using the Theil-Sen slope estimator, testing for statistical significance using the Mann-Kendall test. To extrapolate 1% annual exceedance probability, we fit non-stationary Generalized Extreme Value Distributions (GEVs) at each site. Non-stationarity was assessed by varying the location parameter, varying the scale parameter, and varying both the location and scale parameters as a linear trend in time.

We find that the short duration (<1 hr) annual maximum rainfalls have increased across Australia, but longer duration annual maxima (>1 hr and 1 day) show fewer positive trends with some sites exhibiting negative trends. Based on Akaike Information Criteria, the GEV models which varied either the location parameter, or both the scale and location parameters, were found to be superior. However, when changes in quantile estimates were examined for rare exceedance probabilities (up to the 1 in 100 AEP), it was found the GEV model which only varied the location parameter was unable to capture the increased rate of change in extreme rainfalls. Accordingly, we conclude that changes in extreme rainfalls is best represented by non-stationary models that incorporate changes in both location and scale parameters.

How to cite: Jayaweera, L., Wasko, C., Nathan, R., and Johnson, F.: Non-stationary design rainfalls for Australia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18, https://doi.org/10.5194/egusphere-egu24-18, 2024.

EGU24-361 | ECS | Orals | HS2.4.3

Evolution of Hydro-Meteorological Whiplash Events (Compound Floods and Droughts) over India 

Debankana Bhattacharjee and Chandrika Thulaseedharan Dhanya

In recent decades, the heightened frequency of extreme hydro-meteorological events such as floods and droughts has emerged as a global concern. These events not only pose a significant threat to individual societies but also exert lasting impacts on entire ecosystems. Of particular concern is the occurrence of whiplash events, where rapid transitions from wet to dry spells or vice versa amplify the already substantial impacts on various spatial and temporal scales. This study delves into the potential risks associated with the immediate succession of dry spells following wet spells and the heightened likelihood of intense compound occurrences fueled by concentrated rainfall distribution. Spanning 7 decades from 1951 to 2019, this research employs Event Coincidence Analysis or ECA to examine the aggregated whiplash behaviour in the Indian subcontinent. Our investigation focuses on the frequency of compound whiplash events, specifically dry spells followed by wet spells. Intriguingly, the findings reveal that, on average, 45 to 60% of dry spells across the majority of India are followed by wet spells within a 3-month window or 90 days. Moreover, our analysis demonstrates that the rate of wet spells triggering subsequent dry spells surpasses the reverse scenario. Consistent with the overall trend, compound flash floods and droughts, categorised by high intensity but brief duration, have been notably prevalent from 1951 to 2019. Although the spatial coverage of these events remains relatively small, recent decades have witnessed a discernible increase of 7–9%, primarily in arid, semi-arid, and tropical monsoon regions. Limited occurrences in tropical savannahs and humid subtropical regions were also noted. While the spatial structures associated with increased whiplash frequency appear less organised compared to individual dry and wet spells, the study underscores significantly higher ratios. This suggests that, despite the modest spatial coverage, whiplash events have experienced a notable increase in frequency over the past three decades. This comprehensive analysis contributes valuable insights into the evolving landscape of hydro-meteorological extremes, emphasising the growing importance of understanding compound events for effective climate resilience and adaptation strategies.

How to cite: Bhattacharjee, D. and Dhanya, C. T.: Evolution of Hydro-Meteorological Whiplash Events (Compound Floods and Droughts) over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-361, https://doi.org/10.5194/egusphere-egu24-361, 2024.

The global hydrological cycle is substantially influenced by climate change, leading to notable alterations in hydroclimatic extremes. This encompasses extreme precipitation and temperature events, ultimately amplifying the frequency and intensity of floods. Analyzing the trends in floods and the related covariates provides insight into regional patterns of flood changes and shifts in flood generation mechanisms within the selected catchments. An improved understanding of the processes driving the historical changes in this natural hazard can provide basic information to enhance our preparation and mitigation efforts. Differences in significant trends (non-stationarities) in the magnitude and frequency of flood-related characteristics are determined for the river basins of Peninsular India through analysis of AMS (Annual Maximum Series) and POT (Peaks Over Threshold) series of streamflow over the period 1979–2019. Scrutiny of the trend detection results provided a better understanding of the strengths and limitations of AMS and PDS approaches in analyzing flood characteristics. Non-stationarity in the flood peaks is attributed to precipitation and temperature dynamics. This is accomplished by developing Generalised Pareto regression models to establish a relationship between the flood peaks and basin-averaged precipitation and temperature at different time scales preceding the flood events. Our findings emphasize the importance of understanding climatic conditions driving flood events and incorporating the same for assessing hydroclimatic risks with changing climate patterns, ultimately fostering more resilient and sustainable strategies.

How to cite: K.v., A. and V.v., S.: Detection and attribution of non-stationarity of flood characteristics across the Peninsular Basins of India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-445, https://doi.org/10.5194/egusphere-egu24-445, 2024.

EGU24-855 | ECS | Orals | HS2.4.3

Meteorological Droughts in India under Climate Change Conditions: A Complex Networks-based Approach 

Devika Chandrababu Salini and Bellie Sivakumar

Droughts pose substantial challenges to water resources, ecosystems, and agriculture. Climate change is anticipated to result in more frequent and greater magnitude droughts in the future. The present study assesses meteorological droughts in India under climate change conditions using a complex networks-based approach. The Standardized Precipitation Index (SPI) values at a duration of 1, 3, 6, and 12 months are used to assess the meteorological droughts. Observed precipitation data from the India Meteorological Department (IMD) and precipitation outputs from 53 GCMs participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used. The data considered are at a spatial resolution of 1° x 1°, covering a total of 288 grids across India. The Shortest Path Length is used as a network measure to rank the GCMs. First, the network is constructed by treating each grid as a node and identifying the links between any pair of grids according to certain threshold conditions in correlations in SPI values. Next, the GCMs are individually ranked for each of the 288 grids based on the difference in the shortest path length between the observed and GCM-simulated SPI networks. Then, the Group Decision-Making (GDM) approach is applied toidentify the top-performing GCMs across all the 288 grids. Finally, the inclusion of a comprehensive rating metric (RM) value provides a unified approach to combine the ranks obtained for GCMs across various duration (1, 3, 6, and 12 months). The results indicate that NorESM2-MM, CESM2-FV2, KACE-1-0-G, SAM0-UNICON, and CMCC-CM2-SR5 are the top five models in terms of performance. Data from these five models are then studied using Event Synchronization (ES) to uncover the spatial connections in drought events across space. This novel approach contributes to a better understanding of the spatial dynamics of meteorological droughts, especially under climate change.

How to cite: Chandrababu Salini, D. and Sivakumar, B.: Meteorological Droughts in India under Climate Change Conditions: A Complex Networks-based Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-855, https://doi.org/10.5194/egusphere-egu24-855, 2024.

EGU24-960 | Posters virtual | HS2.4.3

Examining the spatial and temporal characteristics of hydrological drought in the largest basin of the Indian Peninsula 

Meghomala Ghosal, Somil Swarnkar, and Soumya Kundu

The intensified warming conditions have substantially impacted the occurrence, duration, and magnitude of severe hydroclimatic events worldwide. Consequently, economic conditions have experienced considerable influence in the past decades. Droughts, in particular, are complex catastrophic events, rendering them extremely unpredictable and hard to comprehend. It is a gradual and prolonged catastrophe marked by insufficient rainfall, leading to a scarcity of water. In addition, drought is often defined as a period of reduced rainfall resulting in water shortage. It is frequently assessed by examining combinations of many factors, such as precipitation, temperature, and soil moisture. Specifically, hydrological droughts are precisely characterized as prolonged periods when water levels in rivers and streams fall below a preset threshold value. Furthermore, frequent occurrences of hydrological drought pose a significant threat to freshwater resources. Thus, identifying the spatiotemporal characteristics of preceding droughts is crucial for the effective management of future water resources. Hence, this work focuses on analyzing the spatial and temporal patterns of hydrological drought events that occurred between 1964 and 2020 in the Godavari River Basin (GRB) located in the peninsular area of India. The GRB has an area of roughly 0.3 million square kilometers, making it the biggest river basin in peninsular India. Over the last several decades, the GRB has been confronted with severe drought conditions. Therefore, the present analysis utilized the dataset of daily observed water discharge data collected at 21 gauging stations by the Central Water Commission (CWC). In addition to eliminating minor droughts and aggregating droughts, the 'Variable Threshold' concept is utilized to derive hydrological drought characteristics at various stations, including intensity, deficit, and duration. According to our findings, significant spatial and temporal variation is evident in the regional hydrological drought characteristics of the GRB. Additionally, flash drought conditions have been reported at multiple stations. The results derived from this research contribute to the advancement of knowledge regarding the spatiotemporal patterns of droughts in the GRB.

How to cite: Ghosal, M., Swarnkar, S., and Kundu, S.: Examining the spatial and temporal characteristics of hydrological drought in the largest basin of the Indian Peninsula, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-960, https://doi.org/10.5194/egusphere-egu24-960, 2024.

EGU24-980 | ECS | Posters virtual | HS2.4.3

Spatio-temporal characteristics of floods in the largest basin of the Indian Peninsula 

Shreejit Pandey, Somil Swarnkar, and Soumya Kundu

The intensification of the hydrological cycle is a consequence of the rising global temperatures caused by global warming. This has worsened extreme hydrological occurrences, including floods. Flooding is a substantial global hazard that endangers human livelihoods, infrastructure, and economies. Furthermore, the combination of rising temperatures and human activities has significantly modified the flood patterns that have been documented worldwide by several scientists. More precisely, a substantial area of the Indian sub-continent is greatly impacted by regular instances of flooding. Previous studies have indicated an increase in both the magnitude and frequency of flood events in the Indian river basins during the past several decades. The Godavari River Basin (GRB), which is the biggest peninsular basin in India with an area of 312,812 square kilometers, has been prone to frequent and devastating flood events in recent decades. Nevertheless, the comprehensive flood attributes, such as the maximum intensity, total amount, and length, in the GRB remain unidentified. Hence, in this study, we have employed the peak-over-threshold and Master Recession Curve (MRC) techniques to evaluate the flood features in the GRB. We have utilized the daily recorded water flow information obtained from the Central Water Commission (CWC) from 21 gauging stations in the Godavari River Basin (GRB). The 21 gauging stations are categorized into four main geographical zones. The results of our research indicate that there are notable differences in the regional flood characteristics of the GRB in terms of both spatial and temporal scales. The majority of stations in the GRB exhibit substantial fluctuations in flood characteristics after 1995. More precisely, the western GRB exhibits a notable decrease in the amount, length, and intensity of floods after 1995. The data suggest that human actions have a significant role in the flood generation process in the western GRB area. The conclusions derived from this research will be valuable to policymakers and many stakeholders in their efforts to reduce flooding and promote equitable growth in the GRB.

How to cite: Pandey, S., Swarnkar, S., and Kundu, S.: Spatio-temporal characteristics of floods in the largest basin of the Indian Peninsula, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-980, https://doi.org/10.5194/egusphere-egu24-980, 2024.

EGU24-1108 | Orals | HS2.4.3

Climate Change Effects on Flood Hazard and Risk in Harami̇dere Basin 

Egemen Firat, Buse Özer, Koray K. Yılmaz, Gülçin Türkkan Karaoğlu, and Esra Fitoz

In flood hazard and risk assessment studies, modeling is generally done by examining the hydrometeorological events that have developed by using past datasets. Recently, increasing rainfall per unit time due to climate change may cause flash floods. Hydrographs, which are input to 1D/2D hydrodynamic models, are also likely to change as a result of climate change. Hydrological calculations based on past data may underestimate the predicted values. Therefore, flood risks produced from the results of flood depth and hazard models may also remain at low values. In this study, firstly, a hydrological modeling study was carried out on the streams in Haramdere Basin by using hydrometeorological measurements between 2010-2022 and hydrographs were produced for Q2, Q5, Q10, Q25, Q50, Q100, Q500 and Q1000 returning periods. In mapping studies, river structures, stream geometry, digital surface and terrain model were determined using ground measurements and flight data. Then, flood depth and hazard maps were created with 1D and 2D hydrodynamic models. Economic risk calculation was made using these maps. Then, RCP8.5 scenarios known as having high precipitation anomalies for all climate models included in CMIP6 were re-run in the hydrological model. In this way, flow data were generated for each climate model RCP8.5 scenario. Then, 3 different climate change impacts (worst, medium and best) for Haramidere Basin in regards to flood hazard and risk will be revealed by analyzing the rainfall and runoff extremes produced from the hydrological model for all climate models. In the worst case scenario, the climate model with the highest rainfall and runoff extremes, in the medium case, the average of the values calculated from all climate models and in the best case scenario, the climate model with the lowest extremes will be selected. In this way, climate models specific to this basin will be determined for these 3 different Scenarios. Then, from these selected climate models, coefficients will be determined to be used in hydrological calculations for the effect of climate change on flooding events. Finally, flood risk calculations will be made for these 3 scenarios and the economic value of climate change in terms of flood risk will be quantified by comparing with the flood risk calculated with the measurements between 2010-2022.

How to cite: Firat, E., Özer, B., Yılmaz, K. K., Türkkan Karaoğlu, G., and Fitoz, E.: Climate Change Effects on Flood Hazard and Risk in Harami̇dere Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1108, https://doi.org/10.5194/egusphere-egu24-1108, 2024.

EGU24-1125 | ECS | Posters on site | HS2.4.3

Climate-Informed-Seasonal Mixing Approach to Estimate Flood Quantiles 

Abinesh Ganapathy, Bruno Merz, Sergiy Vorogushyn, and Ankit Agarwal

Traditional flood frequency analysis assumes that the probability distribution is stationary over time. However, this assumption has been challenged, given widespread changes in catchments and climate. One of the inherent handicaps of the stationarity assumption is its non-inclusion of changes in extremes associated with future climatic conditions. To overcome this handicap, climate covariates can be incorporated into the estimation of flood probability through the non-stationary Climate-Informed Flood Frequency Analysis (CIFFA). The CIFFA methodology comprises 1) selection of predictands (usually seasonal maxima), 2) identification of suitable predictors (large-scale climate indices), and 3) derivation of a statistical link between predictands and predictors. Since CIFFA typically considers the flood peaks in the dominant season, its applicability to gauges, where flood extremes occur in several seasons, is limited. Here, we develop and test a novel non-stationary Climate-Informed-Seasonal-Mixing approach across various European basins. In the proposed Climate-Informed-Seasonal-Mixing approach, we fit the seasonal peak distribution (boreal seasons) with the location parameter conditioned on the selected covariate using the Bayesian Inference. The best climate covariates for each season among a set of predictors are identified based on widely applicable information criterion (WAIC), which computes log posterior predictive density and adjusts the overfitting using the effective number of parameters. Even the traditional stationary model could be a preferred model for any season if it has a minimum WAIC value. Following the estimation of seasonal distribution parameters, the annual flood quantiles are derived by multiplicatively mixing all the seasonal distributions. In order to demonstrate the performance of the proposed approach, we split the entire period into calibration and validation sets, fitting the model based only on calibration samples. The projected quantiles during the validation period are then compared with a benchmark model (traditional model fitted solely with validation samples). Our results suggest that for many gauges, the flood quantiles estimated by the proposed Climate-Informed-Seasonal-Mixing approach align with the baseline estimates where the traditional approaches fall short.

How to cite: Ganapathy, A., Merz, B., Vorogushyn, S., and Agarwal, A.: Climate-Informed-Seasonal Mixing Approach to Estimate Flood Quantiles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1125, https://doi.org/10.5194/egusphere-egu24-1125, 2024.

EGU24-1235 | ECS | Posters on site | HS2.4.3

How unusual was Australia's 2017-2019 Tinderbox Drought? 

Georgina Falster and Sloan Coats

Australia’s Murray-Darling Basin experienced three consecutive years of meteorological drought across 2017–2019, collectively named the ‘Tinderbox Drought’. Rainfall deficits during the three-year drought were focussed in the Australian cool season (April to September), and deficits in both the cool season and the annual total were unprecedented in the instrumental record. However, at ~120 years long, Australian rainfall records are not long enough to have captured the full possible range of variability, particularly for multi-year extreme events. That is, observations are an incomplete sampling of the full possible range of rainfall variability. Climate model simulations may provide longer timeseries, however climate models have known biases in Australian rainfall (Grose et al. 2020). Therefore, to determine if the Tinderbox Drought was outside the expected range of internal variability, we constructed Linear Inverse Models (LIMs) that simulate internal variability in Australian rainfall and associated global sea surface temperature (SST) anomalies. We used the LIMs to produce 10000-year-long rainfall records that emulate the stationary statistics of observed Australian rainfall, hence reflecting more of the full possible range of variability.

 

Overall, we find that rainfall deficits were most severe 1) in the northern Murray-Darling Basin; and 2) during the final year of the drought (2019). Global SST anomalies during the drought mostly did not resemble the pattern that is most reliably associated with low rainfall over the Murray-Darling Basin (warm anomalies in the central tropical Pacific and the western Indian Ocean). In fact, global SST anomalies observed during the Tinderbox Drought are not reliably associated with negative rainfall anomalies across the Murray-Darling Basin—this is particularly the case for the first two years of the drought. In terms of single-year rainfall anomalies, the only aspect of the Tinderbox Drought that was beyond the expected natural range was annual-total rainfall over the northern Murray-Darling Basin during 2019. However, when considered in terms of basin-wide rainfall over the full three years, negative anomalies during the Tinderbox Drought were beyond the expected natural range in terms of both cool season and annual rainfall. This suggests an anthropogenic contribution to the severity of the drought. Additionally, we find that Linear Inverse Models are a valuable tool for estimating whether or not an observed extreme rainfall event falls within the expected natural range.

References

Grose, M. R., Narsey, S., Delage, F. P., Dowdy, A. J., Bador, M., Boschat, G., et al. (2020). Insights from CMIP6 for Australia's future climate. Earth's Future, 8, e2019EF001469.

How to cite: Falster, G. and Coats, S.: How unusual was Australia's 2017-2019 Tinderbox Drought?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1235, https://doi.org/10.5194/egusphere-egu24-1235, 2024.

EGU24-1256 | ECS | Posters virtual | HS2.4.3

Runoff variation and progressive aridity during drought in catchments in southern-central Chile 

Guillermo Barrientos, Rafael Rubilar, Efrain Duarte, and Alberto Paredes

Persistent drought events frequently intensify the aridity of ecosystems and cause catchments runoff depletion. Here, using large and long-term data sets of meteorological and hydrologic variables (precipitation, runoff, temperature and potential evapotranspiration) investigated the major causes that modulated catchment runoff depletion between years 1980 and 2020 in southern central Chile. We identify the hydrological years where aridity index intensified and analyzed its relationship with annual runoff, and evaluated the effect of annual evaporation index and annual aridity index on water balance of 44 catchments with different precipitation regimes located between 35° and 40°S. Our results showed that observed precipitation and runoff significantly decreased between 1980 and 2020 in 64% of the catchments in the study area. Potential evapotranspiration increased significantly in 39% of the catchments. The runoff value decreased as the aridity index increased from 0.3 to 6.7, and the Budyko curve captured 98.5% of the annual variability of all catchments. Furthermore, for an extreme aridity index (e.g. 6.5), potential evapotranspiration far exceeds mean annual runoff and precipitation. Catchment runoff is modulated by the aridity index, which is a key indicator of insufficient precipitation. As expected, for any type of drought, precipitation and evapotranspiration are key factors modulating catchment runoff response. Hydrological years in which precipitation decreased, showed a decreased runoff trend. This result suggest that meteorological droughts tend to significantly decrease observed runoff. However, our results suggest that runoff in catchments, under consecutive years of water stress, will suffer from an even more severe water deficit in today’s rapidly changing global climate with negative impacts on ecosystem services and human activities.

How to cite: Barrientos, G., Rubilar, R., Duarte, E., and Paredes, A.: Runoff variation and progressive aridity during drought in catchments in southern-central Chile, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1256, https://doi.org/10.5194/egusphere-egu24-1256, 2024.

EGU24-1738 | ECS | Orals | HS2.4.3

Understanding past changes in Australian droughts and their drivers 

Matt Grant, Anna Ukkola, Elisabeth Vogel, Sanaa Hobeichi, Andy Pitman, and Andrew Hartley

Australia is frequently exposed to considerable impacts from severe and widespread droughts. Despite this, a comprehensive understanding of the past trends and drivers of Australian droughts remains elusive. Existing studies have often characterised past trends based on changes in mean values rather than the extremes. However, given Australia’s exceptionally variable climate, this may fail to capture the full nature of the country’s drought trends. Furthermore, studies often rely on a limited number of drought indicators and may not encompass the diverse meteorological, hydrological and ecological conditions contributing to drought.

This work explores past drought trends in Australia using multiple drought indicators. We analyse changes in traditional drought metrics, including precipitation, runoff and soil moisture, defining droughts as time periods below the 15th percentile. We complement these metrics with an impacts-based drought indicator built from government drought reports using machine learning. We explore the drivers of drought trends using explainable machine learning methods, and consider multiple drivers including large-scale climate features, land surface properties and past conditions. Using a diverse range of metrics allows for a more comprehensive analysis of drought changes experienced over the past decades and will provide greater insight into the main drivers behind Australian droughts.

How to cite: Grant, M., Ukkola, A., Vogel, E., Hobeichi, S., Pitman, A., and Hartley, A.: Understanding past changes in Australian droughts and their drivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1738, https://doi.org/10.5194/egusphere-egu24-1738, 2024.

EGU24-3964 | Orals | HS2.4.3

Extreme flood analysis on the Garonne river at Agen, using historical information since 1435 

Michel Lang, Jérôme Le Coz, Felipe Mendez-Rios, Perrine Guillemin, David Penot, and Didier Scopel

The safety of nuclear power plants in France is assessed based on 1000-year flood estimates, with a safety factor accounting for uncertainty. Previous studies on the Garonne River near Agen, France, used threshold exceedance values from a continuous 85 year-long series at two hydrometric stations: Malause (1915-1966) and Lamagistère (1967-2000), and historical data at Agen since 1770. The estimate of the design flood was very sensitive to the choice of an Exponential or of a Generalized Pareto distribution, yielding 12 600 and 16 000 m3/s, respectively. This communication presents a more comprehensive study based on a GEV distribution fitted from the annual maximum values of a continuous series since 1852 (adding Agen 1852-1914) and historical data at Agen since 1435. The statistical framework accounts for both discharge and sampling uncertainty components. The first uncertainty component is about 3% for the recent years and 35% for the oldest years. The statistical framework is able to account for a multiplicative error on rating curves. This leads to corrections in peak discharge values, with better agreement between historical data at Agen and hydrometric data at Malause-Lamagistère. The final estimate of the design flood is around 10 500-11 600 m3/s, without or with the largest known historical flood of 1435. It confirms the safety of the nuclear plant, based on extensive historical information.

How to cite: Lang, M., Le Coz, J., Mendez-Rios, F., Guillemin, P., Penot, D., and Scopel, D.: Extreme flood analysis on the Garonne river at Agen, using historical information since 1435, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3964, https://doi.org/10.5194/egusphere-egu24-3964, 2024.

EGU24-4044 | Posters on site | HS2.4.3

HYDROLOGICAL DROUGHT – Processes and Estimation Methods for Streamflow and Groundwater 

Lena M. Tallaksen, Henny A.J. Van Lanen, Jamie Hannaford, Hege Hisdal, Daniel G. Kingston, Gregor Laaha, Christel Prudhomme, James H. Stagge, Kerstin Stahl, Anne F. Van Loon, and Niko Wanders

Drought is a worldwide phenomenon that originates from a prolonged deficiency in precipitation, often combined with high evaporation, over an extended region. The resultant meteorological water balance deficiency may cause a hydrological drought to develop into below normal levels of streamflow, lakes, and groundwater. Contemporary knowledge and experiences from an international team of drought experts are consolidated in a textbook (Tallaksen and van Lanen et al., 2023), which builds on an earlier edition from 2004 (URL 1), with significant new material added. An updated synthesis was requested given the high relevance and severe impacts of drought seen in many regions of the world in recent years, along with the increasing knowledge gained over the last two decades. A majority of these studies focus on climate and climatology approaches, whereas the textbook addresses hydrological drought in particular. The textbook consists of three parts; Part I (Drought as a natural hazard) discusses the drought phenomenon, its main features, regional diversity and controlling processes. Part II (Estimation methods) presents contemporary approaches to drought estimation, including data and hydrological drought characteristics, statistical analysis of drought series, incl. frequency analysis, time series analysis and regionalisation procedures, as well as process-based modelling. Part III (Living with drought) addresses aspects related to the interactions between water and people. Topics include historical and future drought, how human interventions influence drought, drought impacts and Drought Early Warning Systems. Knowledge and experiences shared in the book are from regions all over the world although somewhat biased to Europe and rivers that flow most of the year.

This presentation aims to introduce the textbook, its motivation and content to a wide audience. The textbook is supported with worked examples and self-guided tours that are elaborated more extensively on GitHub. Worked examples include online procedures, code, and details of the calculation procedures that enable readers to repeat calculations in a stepwise manner, either with their own data or by using online datasets, and we encourage user’s feedbacks and experiences in testing these. Self-guided tours are demonstrations of advanced methodologies that involve several calculation steps and are given as online presentations. Four datasets are included on GitHub; an international, a regional and two local datasets. The international dataset illustrates the drought phenomenon and its diversity across the world, whereas regional data and local aspects of drought are studied using a combination of hydroclimatological time series and catchment information. Hopefully, the textbook will contribute to an increased awareness of one of our main natural hazards, and thereby increase the preparedness and resilience of society to drought.

How to cite: Tallaksen, L. M., Van Lanen, H. A. J., Hannaford, J., Hisdal, H., Kingston, D. G., Laaha, G., Prudhomme, C., Stagge, J. H., Stahl, K., Van Loon, A. F., and Wanders, N.: HYDROLOGICAL DROUGHT – Processes and Estimation Methods for Streamflow and Groundwater, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4044, https://doi.org/10.5194/egusphere-egu24-4044, 2024.

EGU24-4127 | ECS | Orals | HS2.4.3

Emerging river flow and hydrological drought trends in Great Britain 

Wilson Chan, Maliko Tanguy, Amulya Chevuturi, and Jamie Hannaford

Hydrological drought frequency and severity is projected to increase for the UK. However, there is not yet robust observational evidence for decreasing river flows and increasing hydrological drought severity. This lack of evidence may stem from short observational records, human influences on river flows and internal climate variability. As a result, river flow trends in the past and in the near-term may be different to the trend induced by long-term climate change. This lack of congruency poses significant challenges for decision-makers faced with uncertain future projections on the one hand and an apparent lack of observed changes on the other: underscoring the need for approaches that bridge this gap. Single-Model-Initial-Condition-Large Ensembles (SMILEs) provide an ideal opportunity to reconcile past observations and future projections as they isolate the effect of internal climate variability. Here, we use the 50-member CRCM5 12km SMILE to drive GR6J catchment hydrological models for 190 catchments across Great Britain. Results show that observed trends in precipitation and river flows are within the spread of the large ensemble, which includes both robust wetting and drying trends over the historical period that could have arisen from internal climate variability. We further estimate the time of emergence for each catchment, i.e. the decade at which river flow changes exceed natural climate variability. Winter river flows increase with warming and are estimated to exceed natural climate variability before the 2050s for many catchments, with implications for flood risk. Summer river flows are estimated to reduce with warming, including hotspots in southwest Britain with an early time of emergence, exacerbating existing pressures on water resources. Autumn flows for catchments in southeast England are estimated to decrease but are not estimated to exceed natural climate variability until late 21st century. Establishing water management and adaptation strategies is crucial well in advance of catchments reaching their time of emergence (i.e. before a statistically significant trend is detectable). These results highlight the potential to use SMILEs to explore plausible alternative realisations and explore storylines of low-likelihood, high-impact hydrological extremes.

How to cite: Chan, W., Tanguy, M., Chevuturi, A., and Hannaford, J.: Emerging river flow and hydrological drought trends in Great Britain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4127, https://doi.org/10.5194/egusphere-egu24-4127, 2024.

Several severe drought events occurred in the past years and droughts will likely occur more frequent and be more intense in the future. Hydrological drought, which reflects the shortage of water in the river system, can lead to economic losses and can have severe negative impacts on aquatic ecosystems. Therefore being able to predict and increase insights in which rivers are more vulnerable to hydrological droughts, based on catchment characteristics and human interactions, can be of relevance for water managers. In this analysis, the drought sensitivity of rivers is predicted at a regional scale (Flanders, Belgium). Hereby the interests of multiple stakeholders is taken into account by considering four drought metrics, namely the yearly summer volume, the number of dry days, the drought intensity and drought severity. Whereby the latter three are based on the ecological flow. To predict each of these drought metrics, five models ranging from statistical to tree-based methods are applied using twelve input variables ranging from catchment characteristics to human interactions. Hereby random forest without bootstrap and XGBoost outperforms the other methods. To increase the interpretability of the results, the XGBoost models are used to calculate the SHAP and SHAP interaction values. As a result, the impact of the different input variables on the model results is assessed.

From this analysis, some general conclusions can be drawn. Irrigation is the most important variable for each of the considered drought metrics. However, not for every drought metric a clear, unique dependence between the irrigation and the drought sensitivity of a river could be observed. Rivers which have sand as dominant soil texture in their drainage area are less vulnerable to drought. When there are more human interaction in the drainage area, the river is more vulnerable to drought. Beside this, several other dependencies are observed of which many can be explained by the difference in ease of water transferability between sandy soils and clay soils. Next to this, it became clear that the impact of forest and agricultural area on the drought sensitivity of a river is complex, whereby especially its interaction with soil texture and human activities needs further investigation. The applied method can predict the drought sensitivity of a river based on catchment characteristics and human interactions, and therefore define rivers that are more vulnerable to drought. They moreover can provide additional insights in the importance of catchment characteristics and human interactions, and their relation to the drought sensitivity of a river.

How to cite: De Meester, J. and Willems, P.: Analysing spatial variability in drought sensitivity of rivers using explainable artificial intelligence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4758, https://doi.org/10.5194/egusphere-egu24-4758, 2024.

EGU24-5903 | Orals | HS2.4.3

The expansion of forests and the practice of irrigated agriculture contribute to reduced river flows in southern Europe during dry years 

Sergio Martín Vicente Serrano, Ahmed El Kenawy, Dhais Peña-Angulo, Jorge Lorenzo-Lacruz, Conor Murphy, Jamie Hannaford, Simon Dadson, Kerstin Stahl, Iván Noguera, Magí Franquesa, Beatriz Fernández-Duque, and Fernando Domínguez-Castro

This research examines the changes in annual streamflow across Europe from 1962 to 2017, with a specific focus on the correlation between streamflow trends and climate dynamics, as well as physiographic and land cover characteristics. The spatial distribution of streamflow trends aligns closely with climate patterns, suggesting a climate-related influence. However, a detailed analysis at the basin scale reveals that the significant decline in streamflow in southern Europe cannot be solely attributed to climate dynamics. Instead, a discernible negative trend linked to non-climate factors becomes apparent. Specifically, our study indicates that the primary drivers of negative streamflow trends in southern Europe, especially during dry years, are forest growth and irrigated agriculture. This is attributed to the higher proportion of green water consumption compared to blue water generation. These findings hold substantial implications, particularly in the context of widely adopted nature-based solutions for addressing climate change. This includes concerns about carbon sequestration through forests and the planned expansion of irrigated agricultural lands in central and northern European countries to meet growing crop water demands. Such developments may potentially reduce the availability of water resources, leading to an increased frequency and severity of low flow periods.

How to cite: Vicente Serrano, S. M., El Kenawy, A., Peña-Angulo, D., Lorenzo-Lacruz, J., Murphy, C., Hannaford, J., Dadson, S., Stahl, K., Noguera, I., Franquesa, M., Fernández-Duque, B., and Domínguez-Castro, F.: The expansion of forests and the practice of irrigated agriculture contribute to reduced river flows in southern Europe during dry years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5903, https://doi.org/10.5194/egusphere-egu24-5903, 2024.

EGU24-5969 | ECS | Posters on site | HS2.4.3

New estimation models for determining the Q347 

Yanick Dups, Daniela Pavia Santolamazza, Philipp Staufer, and Henning Lebrenz

In Switzerland, low flows are described by the five percent quantile denoted by Q347. This threshold value not only has consequences for the planning, but also necessitates authorities to adjust the operation of pertinent infrastructure to mitigate ecological impacts on watercourses. Given a discharge timeseries spanning at least a ten-year period, determination of the Q347 can be done using the duration curve. Typically, said timeseries are not available for smaller catchments necessitating the estimation of the threshold value Q347. In Switzerland, the utilization of multiple linear regression has been established to estimate the area-specific discharge q347.

The primary objective of these investigations is to estimate the Q347 value for 383 ungauged catchments in the Canton of Solothurn, each covering an area less than 100 km². Daily discharge, precipitation and temperature timeseries ranging from 1990 to 2020 were collected from 56 gauged catchments smaller than 500 km² surrounding the target area. 30 “static” parameters delineating geometry, topography, geology, land use, and drainage along with nine “climatic” parameters describing temperatures, precipitation distributions, and potential evapotranspiration were defined and computed to characterize gauged and ungauged catchments. Alongside comparing three regression methods, coupled with two adjustment techniques supplementing truncated discharge timeseries, three parameter selection methods are evaluated. The validation of the proposed models shows reduced errors and increased linear correlations between estimated and observed values compared to currently applied models. Notably, a spatially more homogeneous yet catchment-specific distribution of estimated values is observable. Particularly when timeseries remain unadjusted or adjustment is done using the Antecedent Precipitation Index (API) and the flow duration curve from a donor basin (Ridolfi, E.; Kumar, H.; Bárdossy, A., 2020), the proposed models yield promising results.

Furthermore, the temporal variability of low flow events for the glacier-free catchments in the study area has been analysed. The frequency of low flow events below the threshold systematically increased over the last 30 years, while the 10-year Q347 value of said catchments has systematically decreased in the same period. The increase in low flow days leads to large errors in the estimation of the Q347 value, especially when its estimation is based on truncated timeseries. As further changes in runoff behaviour are to be expected due to climate change, extending the definition of "low flow" to include event duration and intensity alongside a fixed threshold value could offer a more suitable description.

How to cite: Dups, Y., Pavia Santolamazza, D., Staufer, P., and Lebrenz, H.: New estimation models for determining the Q347, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5969, https://doi.org/10.5194/egusphere-egu24-5969, 2024.

EGU24-5997 | ECS | Orals | HS2.4.3 | Highlight

Surprising megafloods in Europe – learning from the big picture 

Miriam Bertola and Günter Blöschl and the Team members

Megafloods that far exceed previously observed records at a given location can take citizens and flood managers by surprise. Existing methods based on local and regional information rarely go beyond national borders and cannot predict these floods well because of limited data on megafloods, and because flood generation processes of such extremes differ from those of smaller, more frequently observed events. Here we analyse the most comprehensive dataset of annual maximum discharges in Europe available to date, to assess whether recent locally surprising megafloods could have been anticipated using observations in hydrologically similar catchments across the continent.

We base our analysis on annual maximum river discharge observations from 8023 gauging stations for the period 1810–2021. We identify about 500 “target” catchments where recent (i.e., after 1999) megafloods have occurred that are surprising based on local data. We perform a hindcast experiment of predicting their peak discharge with regional envelope curves, using flood observations from similar “donor” catchments up to the year before their occurrence. From this group of donor catchments we construct an envelope curve which we compare with the megaflood that occurred later in the target catchments. We repeat this analysis for all the detected megafloods in the target catchments.

Our analysis shows that, in 95.5% of the target catchments, the discharge of the envelope is larger than that of the observed megaflood, suggesting that, from a European perspective, almost none of the events can be considered a regional surprise. Similar results are obtained by repeating the analysis on two consecutive sub-periods, indicating that megafloods have not changed much in time relative to their spatial variability. In conclusion, our findings show that recent megafloods could have been anticipated from observations in other parts of Europe, which would not be possible using only national data.

How to cite: Bertola, M. and Blöschl, G. and the Team members: Surprising megafloods in Europe – learning from the big picture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5997, https://doi.org/10.5194/egusphere-egu24-5997, 2024.

Droughts are recurrent phenomena that present a large variety of space and time patterns making rather difficult the assessment of their rarity and the comparison between events. Our study focuses on the space-time “memory effect” of meteorological drought over France using gridded precipitation from the SAFRAN reanalysis over 1950-2022. The proposed easy tool of rarity matrix analyzes how drought events build and persist across time and space. The approach is purely statistic, assuming that drought consequences over a given area depend on the probability of non exceedance (“rarity”) of antecedent rainfall accumulations. In order to cover a large spectrum of “memory effects”, we consider a continuum of accumulation periods ranging from a few weeks to several years and moving windows of size 80x80 to 480x480 km2 over France. The rarity matrix of a given year displays the most severe rarity values encountered during the year as a function of the various accumulation periods and the various spatial scales.

Over the study period of 1950-2022 we show how the shape of rarity matrix discriminate short- and long-term historical droughts, as well as regional to national droughts.

As an additional asset, the rarity matrix is also able to analyze the rarity of precipitation excess over several weeks to months or years, as it was the case in fall 2023 in France.

How to cite: Blanchet, J., Chagnaud, G., and Creutin, J.-D.: The multi-scale rarity matrix – a comprehensive tool to analyze the space-time severity of meteorological drought, with application to France, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6086, https://doi.org/10.5194/egusphere-egu24-6086, 2024.

EGU24-6166 | ECS | Orals | HS2.4.3

Heavy-tailed flood peak distributions: What is the effect of the spatial variability of rainfall and runoff generation? 

Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn

The distributions of many observed time series of daily precipitation and streamflow show heavy tail behaviour. This means that the occurrence of extreme events has a higher probability than would be the case if the tail was receding exponentially. To avoid underestimating extreme flood events in their occurrence probability or their magnitude, a robust estimation of the tail behaviour is required. However, this is often hindered due to the limited length of time series. One way of overcoming this is to enhance the understanding of the processes that govern the tail behaviour of flood peak distributions. Here, we analyse how the spatial variability of rainfall and runoff generation along with the tail behaviour of rainfall affect the flood peak tail behaviour in catchments of various size. To do so, a modelling chain consisting of a stochastic weather generator and a conceptual rainfall-runoff model is used. For a large synthetic catchment (>100,000 km²), long time series of daily rainfall with varying tail behaviour and varying degree of spatial variability are generated and used as input for the rainfall-runoff model. In the rainfall-runoff model, spatially variable runoff is generated by setting respective model parameters accordingly. The tail behaviour of the simulated precipitation and streamflow time series is characterized with the shape parameter of the Generalized Extreme Value (GEV) distribution.

Our analysis shows that heavy-tailed rainfall tends to result in heavy-tailed flood peak distributions, independent of the catchment size. In contrast, first results regarding the effect of the spatial variability of rainfall on flood peak tail behaviour indicate that this relation varies with the size of the catchment. In large catchments, attenuating effects, for example through river routing, might have a stronger impact than in small basins. Regarding the runoff generation, the tail of flood peak distributions tends to be heavier when a fast runoff component is triggered simultaneously in a larger share of the catchment rather than when this is the case only very localized. This in turn is linked to more homogeneous catchment characteristics and rainfall patterns. The results of this study can help with improving the estimation of occurrence probabilities of extreme flood events.

How to cite: Macdonald, E., Merz, B., Nguyen, V. D., and Vorogushyn, S.: Heavy-tailed flood peak distributions: What is the effect of the spatial variability of rainfall and runoff generation?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6166, https://doi.org/10.5194/egusphere-egu24-6166, 2024.

There seem to be two contrasting views on flooding after drought. Subsurface hydrologists pose that with dry antecedent conditions there is more storage available, which leads to lower flood peaks. Surface hydrologists pose that dry, hydrophobic soils support less infiltration and more surface runoff, which leads to higher flood peaks. But which theory is true? Or can both be true? And what happens if you put people and their actions in the mix? In this presentation is discuss the scientific and empirical evidence related to drought-flood events. I draw on scientific literature, global data analysis, a review of reports and news articles, qualitative case studies, and science communication examples. I will mostly focus on hydrological processes, but also highlight some meteorological and anthropogenic aspects.

How to cite: Van Loon, A. and the PerfectSTORM team: On the drought-flood conundrum: do droughts cause more or less flooding? Let’s discuss the science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7811, https://doi.org/10.5194/egusphere-egu24-7811, 2024.

EGU24-8302 | ECS | Posters virtual | HS2.4.3

Projected changes in extreme precipitation and floods in central India 

Nikhil Kumar, Evan G.R. Davies, Manish Kumar Goyal, and Monireh Faramarzi

Precipitation extremes are expected to rise in a warming climate; however, the corresponding increases in flood magnitudes remain a complex and underexplored issue. This study employs the annual maxima approach to assess the relationship between extreme precipitation and floods, using a process-based hydrological model, the Soil & Water Assessment Tool (SWAT), in four river basins of central India (Brahmani and Baitarni, Subarnarekha, Mahanadi and Narmada) for past (1984-2014) and future (2030-2060 and 2070-2100). First, the SWAT models underwent rigorous data selection (climate and land cover data), calibration and validation to ensure a reliable representation of the hydrologic conditions of these basins at a daily scale, based on observations from 26 hydrometric stations for the 1988–2019 period. Second, climate projections from four CMIP6 GCMs were statistically downscaled using Bias Correction/Constructed Analogues with Quantile mapping reordering (BCCAQ) for the SSP245 and SSP585 scenarios. Finally, the SWAT models were used to project future changes in extreme precipitation and flood characteristics in the selected river basins. Considering both daily model performance (Nash-Sutcliffe Efficiency-NSE > 0.60) and catchment representativeness, we selected 10 from 26 hydrometric stations for the extreme value analysis. The analysis of the ensemble mean of the 95th percentile of four GCMs and the modelled 20-year return levels show a future increase in both precipitation (0.27 to 27.93 % and 6.19 to 50.06 %) and discharge (1.31 to 50.35 % and 5.42 to 100.73 %) at 6 out of 10 selected stations, with a more significant increase under the SSP585 scenario than the SSP245 scenario, highlighting a clear link between increased precipitation and discharge The modelling framework developed in this study will improve understanding of processes involved and the thresholds at which the central Indian catchments correspond to extreme precipitation. The findings will help the projection of future flood risks and could help to shape effective adaptation strategies in the region.

How to cite: Kumar, N., G.R. Davies, E., Kumar Goyal, M., and Faramarzi, M.: Projected changes in extreme precipitation and floods in central India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8302, https://doi.org/10.5194/egusphere-egu24-8302, 2024.

EGU24-8320 | Orals | HS2.4.3

Agricultural Drought Propagation over India: A Complex Network Theory Approach  

Kasi Venkatesh and Bellie Sivakumar

Agricultural drought has emerged as a significant threat to global food security and sustainable development. Despite the progress made in the identification and analysis of various characteristics for the assessment and early warning of agricultural drought, our knowledge of the mechanisms governing agricultural drought propagation remains limited. This study aims to address this gap by employing complex network theory. Specifically, the study uses complex network measures to investigate the spatial propagation of agricultural drought propagation across India during 1950–2014. Spatial drought networks are constructed using event synchronization (ES) for mild drought conditions derived from the Standardized Soil Moisture Index (SSMI) at a 3-month aggregated scale (SSMI-3). The investigation delves into the mechanisms of spatial propagation of drought, including propagation source and sink, distance and orientation using directed networks. Several metrics, including network divergence, in-degree, and out-degree, inward and outward distance, inward and outward orientation are used. These metrics play a crucial role in identifying specific locations, namely source and sink regions, propagation distance and orientation, where drought onsets extend to other areas within the regional spatial networks. The results indicate that the northwest India acts as the source region and the west central India and peninsular India act as sinks. The central and east India are identified as vulnerable regions playing crucial roles in spatial drought propagation. The results also reveal that the dominant directions of propagation lead towards the northwestern parts of India. For inward distances, shorter propagation distances of less than 50 km are observed in the peninsular, central, and some parts of the northeastern regions, while longer propagation distances are observed in the western parts of India, exceeding 150 km. For outward distances, shorter propagation distances below 20 km are observed in hilly regions, while longer propagation distances are observed in the peninsular regions of India, exceeding 80 km. These results suggest that most regions propagate droughts inward and outward, covering distances of even hundreds of kilometres. Understanding the dominant inward and outward orientation of drought propagation could play a crucial role in developing early warning systems for droughts.

How to cite: Venkatesh, K. and Sivakumar, B.: Agricultural Drought Propagation over India: A Complex Network Theory Approach , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8320, https://doi.org/10.5194/egusphere-egu24-8320, 2024.

EGU24-8350 | Posters on site | HS2.4.3

Subway Flooding Simulation with US EPA SWMM: A Case Study of the Tamsui-Xindian Line During Taiwan's 2001 Typhoon Nari 

Yong-Jun Lin, Hsiang-Kuan Chang, Jihn-Sung Lai, and Yih-Chi Tan

There have been frequent reports of subway station flooding incidents in recent years. For instance, on October 30, 2012, Hurricane Sandy in the United States caused a storm surge combined with astronomical tide that submerged seven subway lines in New York City. It was the most severe disaster in the New York City subway system. On July 20, 2021, a flooding incident occurred in Zhengzhou, Henan Province, China, with a record hourly rainfall of 201.9mm. The heavy rain caused severe water accumulation at the Wulongkou yard of Zhengzhou Metro Line 5 and its surrounding areas. The temporary flood barrier was breached, allowing water to flood into the subway, with a maximum water depth of 1.75 meters inside the carriages and the flooding length extending approximately 1 kilometer.

In 2001, Typhoon Nari caused flooding at the Taipei Station, with 16 MRT stations also inundated. Surface roads were extensively flooded, and the Taiwan Railways Administration stations in Taipei, Wanhua, and Banqiao were submerged, resulting in a 90-day suspension of the Taipei MRT station. How to quickly evaluate the impacts of subway station flooding is crucial for the extreme weather in the future.

Therefore, this study utilized the US EPA SWMM to simulate the flooding situation of the Tamsui-Xindian line during Typhoon Nari in 2001. The SWMM calculations showed varying degrees of flooding at different stations at different times. For example, Guting Station was not affected by human intervention, while the simulated flooding depth at Taipei Station was only 0.09 m different from the actual depth. Additionally, the September 17, 2001 flood profile at 17:34 showed that Taipei Station was submerged, with water flowing to Zhongshan and Shuanglian stations. The National Taiwan University Hospital station experienced minimal flooding due to its higher elevation. The simulation also displayed the water ingress situation at different stations at various times. However, there were some inaccuracies due to the lack of detailed flood progression and inflow data and the use of a simplified station model. Nonetheless, the overall simulation results reflected the related flooding process.

How to cite: Lin, Y.-J., Chang, H.-K., Lai, J.-S., and Tan, Y.-C.: Subway Flooding Simulation with US EPA SWMM: A Case Study of the Tamsui-Xindian Line During Taiwan's 2001 Typhoon Nari, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8350, https://doi.org/10.5194/egusphere-egu24-8350, 2024.

The aridity of a region plays a pivotal role in shaping a diverse range of hydrological processes, encompassing critical aspects such as the sensitivity of evaporation to variations in temperature and precipitation, water use efficiency, and the intricate interactions between precipitation, soil moisture, and evaporation. These processes, in turn, influence the response of hydrological extremes, such as drought and flood, to global warming. Understanding the impact of aridity on these extreme events in the context of changing climate conditions across global terrestrial ecosystems is essential for comprehending water availability and ecological resilience in different regions. This study investigates the relationships of changes in drought and flood intensities for the end of the twenty-first century with background aridity across global terrestrial ecosystems. Background aridity is quantified using an aridity index, calculated as the ratio between precipitation and evaporation. Drought is characterized by the standardized precipitation index (SPI), and flood by fitting a generalized extreme value distribution (GEV) to the annual maxima flow time series of the Inter-Sectoral Impact Model Intercomparison Project models. The results show opposite responses of drought and floods to background aridity under climate change across global terrestrial ecosystems. As aridity decreases from dry to wet regions, the intensification of flood events in the future is expected to increase. In contrast, drought intensification is more pronounced in dry and semi-dry regions. These findings hold significant implications for developing effective and region-specific water resource management policies to address hydrological extremes in a changing climate.

How to cite: Tabari, H.: Contrasting responses of drought and floods to background aridity in a changing climate across global terrestrial ecosystems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8460, https://doi.org/10.5194/egusphere-egu24-8460, 2024.

EGU24-9058 | ECS | Posters on site | HS2.4.3

Evaluation of soil moisture droughts under climate change in Germany 

Friedrich Boeing, Andreas Marx, Thorsten Wagener, Luis Samaniego, Oldrich Rakovec, Rohini Kumar, and Sabine Attinger

It is projected that the likelyhood and duration of extreme soil moisture (SM) droughts will increase in Germany under future warming scenarios. Annual precipitation changes are small under climate change in Germany with increases in winter and decreasing precipitation in summer for some parts of Germany. Generally, the climate ensemble spread in the future precipitation signal is large. Furthermore, impacts of SM droughts depend largely on the soil volume evaluated. We identified a gradient of stronger soil drying in shallow SM compared to deeper SM under global warming, leading to different effects on shallow-rooted vegetation compared to deep-rooted vegetation (agriculture versus forestry). In addition, spatial characteristics such as soil properties can strongly influence the dynamics of SM and thus shape the response of SM drought to changing meteorological conditions. 
In this work we evaluate the impact of the considered soil depth and spatial features on simulated changes in SM droughts in Germany. We compare this influence to the uncertainty in meteorological changes. We use a large climate ensemble based on Euro-Cordex regional climate model simulations, which were bias-adjusted and spatially disaggregated to run the mesoscale hydrological model (mHM) (mhm-ufz.org) with a high spatial resolution of 1.2x1.2km. 
This work aims to expand the picture of climate change impacts on SM droughts in Germany. The results can contribute to an improved definition of sector-specific drought indicators that will support national efforts to ensure climate change resilient water management.

How to cite: Boeing, F., Marx, A., Wagener, T., Samaniego, L., Rakovec, O., Kumar, R., and Attinger, S.: Evaluation of soil moisture droughts under climate change in Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9058, https://doi.org/10.5194/egusphere-egu24-9058, 2024.

EGU24-9081 | ECS | Posters on site | HS2.4.3

Suitability Mapping for Subsurface Floodwater Storage Schemes 

Lea Augustin and Thomas Baumann

Co-management strategies for floods and droughts offer a promising solution for dealing with two extremes that are increasingly close in time and space. Techniques originally developed for drought prevention, such as managed groundwater recharge (MAR), could use floods as a source of water (Flood-MAR) to simultaneously protect against flooding.

The project Smart-SWS aims to develop this concept further by capturing the flood waves in a river and infiltrating them into aquifers nearby. Subsurface storage is created through geotechnical measures in the aquifer. This storage could secure the seasonal water supply while protecting downstream settlements from flooding.

The main attributes of Smart-SWS sites mirror the overall objective: On the one hand, potential sites for such a system are located in areas that are regularly flooded and, at the same time, have problems with groundwater scarcity. In order to infiltrate large volumes of water into the aquifer and store this water for extended periods, the characteristics of the aquifer, the surface, and the water source must be taken into account to assess the suitability of these sites.

In this work, we have identified suitable sites for such an underground flood storage system by applying a GIS-based multi-criteria decision analysis (MCDA). The workflow for the suitability mapping is based on publicly available data and implemented in Python. The results are shown for the administrative district of Swabia in Bavaria, Germany, where approximately 35% of the study area was identified as having varying degrees of suitability. The robustness of the MCDA is validated with a sensitivity analysis, and the results are checked against expert opinions based on field data.

How to cite: Augustin, L. and Baumann, T.: Suitability Mapping for Subsurface Floodwater Storage Schemes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9081, https://doi.org/10.5194/egusphere-egu24-9081, 2024.

EGU24-9215 | ECS | Posters on site | HS2.4.3

Exploring extreme flow events and associated patterns in Switzerland: a Dense feed-forward Neural Network approach 

Maria Grazia Zanoni, Marius Floriancic, Hansjörg Seybold, and James W. Kirchner

Switzerland relies significantly on sustainable water management to meet its diverse socio-economic and environmental needs. As climate change introduces heightened uncertainty in weather patterns, accurate forecasting of extreme flows from climatic data has become essential for efficient water resource management in the country. Furthermore, these events are likely shaped by nonlinear hydroclimatic and compound conditions distinct from typical average cases. A thorough understanding of these phenomena is therefore crucial for effective adaptation to changing climatic conditions. In this regard, data-driven techniques, such as Machine Learning algorithms, have proven capable of extracting knowledge from vast amounts of data, providing valuable insights into the underlying climate and societal dynamics driving extreme flow events.

The aim of the present study is therefore twofold. First, we evaluate the ability of a Dense feed-forward Neural Network (DNN) model to predict drought and peak flow events in Switzerland based on anthropogenic, environmental and climatic data. On the other side, we investigate the role of each driver in the prediction and we study the temporal trends of the target and the features. The analysis was conducted on a large dataset consisting of daily discharge data from more than 400 sites across the country, from 1999 to 2019.  First, we evaluated the flow distribution at each individual site, considering only the extreme events and developing two distinct DNN models for droughts and for peaks. The DNN performed better in modeling droughts, achieving in the test set a mean Nash-Sutcliffe efficiency coefficient of 0.6 and a mean Kling-Gupta efficiency coefficient of 0.8, compared to 0.1 and 0.38, respectively, for the peaks.  A sensitivity analysis of the features, such as the cumulative precipitation and mean air temperature in the preceding weeks of the event, was performed. In addition, we delved into a detailed examination of the temporal trends of the climatic drivers and the extreme flow rates over the 20 years of the study. In the subsequent phase of the project, we explored a multi-site modeling approach to address the issue of the DNN model's poor performance in predicting peak flows.  We introduced geographic, land use and other anthropogenic factors specific to each watershed. 

By revealing the predictive potential of data-driven models, this study serves as a valuable foundation and resource for addressing extreme flow events and the hydroclimatic and anthropogenic patterns behind them.

How to cite: Zanoni, M. G., Floriancic, M., Seybold, H., and Kirchner, J. W.: Exploring extreme flow events and associated patterns in Switzerland: a Dense feed-forward Neural Network approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9215, https://doi.org/10.5194/egusphere-egu24-9215, 2024.

Climate change affects several sectors and environmental conditions, in particular the statistical characteristics of the runoff processes of a certain watershed. As a consequence of the higher temperature values and the altered precipitation distribution, the intensity and timing of floods and droughts, as well as their severity, may change in the coming decades. In order to develop adaptation strategies and implement an adequate water management, it is necessary to project the future trends of variables that can essentially influence water management, taking into account possible climate change scenarios, including the quantification of uncertainty.

Our aim is to investigate the runoff conditions with a special focus on the frequency of critical low water levels and the different levels of flood warnings for selected river sections (i.e. Tiszabecs, Uszti Csorna, Rahiv) in the Uppest-Tisza Basin, located in Central-Eastern Europe. For this purpose, simulations with the physically based, distributed DIWA hydrological model driven by a regional climate model simulation are completed. In order to analyse the projected changes, simulations are made for a historical period (1972–2001) as well as for two future periods (2021–2050 and 2069–2098). We also investigate how the choice of the RCP scenario (i.e. RCP2.6, RCP4.5 or RCP8.5) affects the output of the hydrological simulation. In order to assess uncertainty, time series of meteorological parameters (providing inputs for the hydrological model) are generated by a weather-generator embedded in a Monte-Carlo cycle. Therefore, several hundreds of scenarios with equal probability are available, by using only one climate model. Furthermore, a bias-correction of the climate model simulation is implemented for which the weather-generator is used by fitting the crucial distribution parameters to the reference, i.e. the so-called CARPATCLIM database.

How to cite: Kis, A., Pongrácz, R., and Szabó, J. A.: Analysis of the frequency of critical low water levels and flood warning water levels for the Uppest-Tisza catchment for the 21st century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9343, https://doi.org/10.5194/egusphere-egu24-9343, 2024.

EGU24-9553 | ECS | Orals | HS2.4.3

Climate adaptation to change in high-flows: Comparison of high-resolution climate model projections 

Aparna Chandrasekar, Friedrich Boeing, Andreas Marx, Oldrich Rakovec, Sebastian Mueller, Ehsan Sharifi, Jeisson Javier Leal Rojas, Luis Samaniego, and Stephan Thober

Climate change is altering the water cycle from the global to the local scale. The increase in temperatures and changing precipitation patterns intensify not only mean values, but also the frequency and severity of extreme weather events, leading to alterations in water availability and distribution.

This study assesses the impact of climate change on flood patterns (maximum annual river discharge) in Germany. Climate models ranging from different spatial scales will be compared for the five largest German catchments outlets (including headwaters). The climate model ensembles from the EURO-CORDEX initiative, and the ICON climate model from the Destination Earth Initiative / NextGEMS project will be used along with the mHM (mhm-ufz.org) model. The river discharge values produced from the mHM model will be used to calculate the Q90 (90th percentile of daily discharge) and the Qmax (maximum annual discharge) parameters.

Initial results from the EURO-CORDEX initiative predict a 5-15% reduction in Q90 and Qmax in the summer half year, and a 5-30% increase in Q90 and Qmax in the winter half year, in the alpine regions in Germany. In the Elbe and Oder catchments (north-eastern part of Germany) there in a greater increase in Q90 and Qmax in the summer half year than the winter half year. This increase becomes more prominent with increasing warming. However, there is a large spread in the ensemble predictions, with uncertainty reducing with increasing warming. These parameters and results will be compared with the results from the ICON climate model to understand the contribution of spatial and/or temporal resoltion towards flood prediction.

How to cite: Chandrasekar, A., Boeing, F., Marx, A., Rakovec, O., Mueller, S., Sharifi, E., Leal Rojas, J. J., Samaniego, L., and Thober, S.: Climate adaptation to change in high-flows: Comparison of high-resolution climate model projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9553, https://doi.org/10.5194/egusphere-egu24-9553, 2024.

EGU24-9626 | ECS | Orals | HS2.4.3

From drought to Storm Daniel: an overall assessment on the fragility of the Mediterranean region 

Junliang Qiu, Wei Zhao, Luca Brocca, and Paolo Tarolli

In 2022, Europe experienced an unprecedented drought. 2023 marked the warmest year globally on meteorological records, leading to droughts and wildfires in Greece during the summer. In July 2023, certain areas of the Mediterranean experienced sea surface temperatures 5.5°C higher than the annual average, contributing to severe summer heatwaves and wildfires in the Greek region. These conditions also provided ample thermal energy for the formation of Storm Daniel. From September 4th to 6th, Storm Daniel struck Greece, resulting in significant rainfall and flooding. Coordinated satellite monitoring revealed that the flooded area in central Greece reached 875.28 km². On September 10th, Storm Daniel hit Libya, leading to dam collapses and claiming the lives of over 11,000 people. Concurrently, the flood area in the northern deserts of Libya exceeded 1,000 km². From a global perspective, Europe has witnessed an increased frequency of extreme droughts and floods in recent years, while North Africa grapples with geopolitical instability. Climate change-induced natural disasters are further heightening the vulnerability of the Mediterranean region. Consequently, this study underscores the importance of (1) enhancing hydrological monitoring in arid and semi-arid regions of the Mediterranean, (2) developing a Mediterranean scale early warning system, and (3) stressing the imperative for the European Union and North African countries to collaboratively establish climate change adaptation strategies, aiming to avert humanitarian disasters triggered by climate crises.

How to cite: Qiu, J., Zhao, W., Brocca, L., and Tarolli, P.: From drought to Storm Daniel: an overall assessment on the fragility of the Mediterranean region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9626, https://doi.org/10.5194/egusphere-egu24-9626, 2024.

EGU24-9639 | ECS | Orals | HS2.4.3

Interpretable Machine Learning to Uncover Key Compound Drivers of Hydrological Droughts 

Georgios Blougouras, Markus Reichstein, Mirco Migliavacca, Alexander Brenning, and Shijie Jiang

Hydrological drought (negative streamflow anomalies) can have significant societal and ecosystem impacts, and understanding its drivers is crucial for interpreting past and present droughts, as well as assessing future drought risk. However, despite recent research advancements, a comprehensive multivariate perspective on the drivers of hydrological drought remains elusive, particularly in the context of global warming, where distributional changes in drivers could result in an increased frequency of complex, compound events. In order to address this, quantifying the contribution of each driver is necessary. In our research, we devise an interpretable machine learning framework that can explain which hydrometeorological variables contribute to streamflow predictions. This is done by encoding a conceptual hydrological model into a neural network architecture, creating a physics-encoded hybrid model that allows us to maintain physical consistency and ensure a more causal understanding. We apply our framework to numerous North American basins across spatiotemporal scales and quantify the contribution of each potential driver to identified streamflow deficit events. We also investigate the mechanisms associated with compound drivers and assess if drought drivers are becoming increasingly complex due to climate change based on the defined compoundness index.  Overall, our framework has managed to capture the contribution of diverse drought drivers to events across different hydroclimatological regimes. The results demonstrate the effectiveness of our novel method in improving hydrological drought process understanding, especially the mechanisms and severity of droughts associated with compound drivers, thereby facilitating increased preparedness for future drought risks.

How to cite: Blougouras, G., Reichstein, M., Migliavacca, M., Brenning, A., and Jiang, S.: Interpretable Machine Learning to Uncover Key Compound Drivers of Hydrological Droughts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9639, https://doi.org/10.5194/egusphere-egu24-9639, 2024.

Understanding and quantifying severe low flows is crucial for the management of hydropower or thermal power plants. Moreover, low flows are strongly related to the climatic regime and will be affected by climate change. Therefore, we propose a modelling chain to estimate severe low flow values for several human-influenced catchments in France, both under current and future climate.

Firstly, a bivariate weather generator (Touron, 2019) of daily temperature and precipitation, representing the average of 28 catchments spread out over France, was trained, and used to generate 1000 meteorological time series over a 30-year period. Average daily precipitation and temperature are then spatially disaggregated to produce 1000 local time series for each of the 28 catchments using an analogue approach. Thirdly, MORDOR-SD a lumped conceptual rainfall-runoff model, developed and used at EDF (Garavaglia et al. 2017), combined with upstream-downstream propagation and water management module was forced by the 1000 local meteorological time series. The resulting 1000 time series of simulated river flows are then used to calculate an empirical rare percentile estimate of low flows across 12 large catchments of interest.

The methodology is applied on historical period (1981-2010) using precipitation and temperature observations to train the weather generator. The robustness of the method is evaluated by comparing return levels of low flows obtained through the proposed method and the ones estimated through river flow observations available. Finally, to assess the impact of climate change, the weather generator is also trained/used with 5 downscaled climate projections from the CMIP5 experiments corresponding to: (1) the historical period (1981-2010) and, (2) 4 storylines representing different levels of warming/drying (2036-2065).

The comparison over the historical period has shown the relative agreement between simulated and observed severe low flows. Furthermore, under future conditions, the climatic differences between the 4 storylines lead to logical differences in the estimation of severe low flows, i.e. warmer/drier storylines lead to lower estimation of severe low flows.

How to cite: Devers, A., Gailhard, J., Parey, S., and Froidurot, S.: Estimating severe low flows on human-influenced catchments by combining weather generator, analogue spatial disaggregation, and hydrological modelling under historical and future climate., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10393, https://doi.org/10.5194/egusphere-egu24-10393, 2024.

EGU24-10718 | ECS | Orals | HS2.4.3

Exploring Extreme Climate Transitions in Kerala, India: A Multi-Decadal Investigation (1980-2020) 

Meera G Mohan, Arathy Nair Geetha Raveendran Nair, and Adarsh Sankaran

In response to the escalating challenges posed by climate change, this study addresses the critical need to understand the dynamics of extreme climatic events within Kerala, India. Focusing on the years spanning 1980 to 2020, specifically during 12 identified drought years within, we meticulously examine transitions between droughts and floods, recognizing the profound impact on the region's hydrological landscape. With a strategic selection of 17 stream gauge locations covering high, mid, and low lands, representing varied climatic zones, our investigation delves into the intricacies of climatic shifts. The study deals with the analysis of discernible trend of increasing frequency in extreme events over time, by employing a thorough approach incorporating statistical significance testing, frequency analysis of extreme events, and lag analysis and then to unravel the intricate relationships between streamflow and precipitation during distinct phases such as pre-drought, drought, and post-drought years. The research findings illustrate an erratic pattern in the occurrence of contradictory extremes, such as transitions between drought and flood. The timing and duration of these transitions are also found to be inconsistent, showing varying periods in-between and occasionally consecutive occurrences of the same extremes, which in turn highlights the complexity and irregularity of extreme event patterns present in Kerala. Notably, our analysis reveals a concerning trend where the frequency of extreme events is progressively increasing, indicating a higher occurrence of climatic extremes over the years. Specifically, from 2015 to 2020, the observed transitions are striking, in the case that, the total incidences of heavy rain (64.5-115.5 mm per day) were 360 across 10 months in 2015 whereas in the succeeding year (2016), followed by an unprecedented 100-year return period drought. The year 2017 again saw incidences of heavy rain climbing to a total of 360 events. Astonishingly, the anomaly continued with the recurrence of devastating floods in 2018, which persisted for a broadened period up to 2020. While extending the future dynamics for the coming decade, the study predicted the frequency and patterns of extreme events in Kerala by incorporating future General Circulation Model (GCM) precipitation data. The results indicate a substantial increase in the frequency of extreme events, coupled with the anticipated emergence of prolonged dry periods in Kerala's future hydroclimatic landscape. The integration of this data into the analysis enabled the estimation of variations in future streamflow, providing valuable insights into the evolving climatic scenario. This forward-looking approach allowed for the inference of potential patterns of extreme events over the past decade in Kerala, contributing to proactive strategies for climate resilience and adaptive water resource management in the region.

How to cite: G Mohan, M., Geetha Raveendran Nair, A. N., and Sankaran, A.: Exploring Extreme Climate Transitions in Kerala, India: A Multi-Decadal Investigation (1980-2020), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10718, https://doi.org/10.5194/egusphere-egu24-10718, 2024.

EGU24-11083 | ECS | Orals | HS2.4.3

Evidence of Flash/ Rapid Drought in India based on Precipitation Deficit- A new Climatic Threat 

Pallavi Kumari and Rajendran Vinnarasi

Rapid intense droughts (Flash Drought) under climatic warming are of widespread concern owing to their catastrophic impacts on agricultural production, eco-system, and nation’s economy. Several studies highlight the need to develop an improved understanding of flash drought to manage its effect better, However the lack of consistent definitions have limited progress toward its assessments. A number of variables, climatic drivers are generally linked to flash drought development thus it is possible that no single description might adequately capture the flash drought. However, it is crucial to make sure that the rapid onset, fast intensification, and severe nature of flash drought can be identified and distinguished from more conventional drought (longer duration) events. With the increasing use of flash drought term within the scientific community, this study presents an evidence-based result by identifying flash droughts using pentad-scale precipitation series across India. The results demonstrate that one of the factors causing and accelerating the flash drought – rapid drought intensification and lasts for shorter duration (3 pentads to 18 pentads) is the meteorological variable precipitation. The results of this study can be further utilised in the accurate characterization of flash drought and its assessment with the strong evidence of precipitation series in finding of flash drought events across the nation.

How to cite: Kumari, P. and Vinnarasi, R.: Evidence of Flash/ Rapid Drought in India based on Precipitation Deficit- A new Climatic Threat, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11083, https://doi.org/10.5194/egusphere-egu24-11083, 2024.

EGU24-11404 | ECS | Orals | HS2.4.3

On the use of weather generators for the estimation oflow-frequency floods under climate change scenarios 

Carles Beneyto, José Ángel Aranda, and Félix Francés

The present work presents a novel methodology based on the use of stochastic Weather Generators (WG) for the estimation of high return period floods under climate change scenarios. Starting from the premise that the 30-years climate projections, commonly used for future flood studies, do not provide enough information to obtain accurate extreme quantile estimations (especially in arid and semi-arid climates), we propose to exploit the available information by performing a regional study of maximum precipitation of the bias-corrected climate projections (mid-term and long-term), the outputs of which will improve the WG implementation.

This methodology has been applied in a case study, Rambla de la Viuda (Spain), a typical Mediterranean ephemeral river located in eastern Spain. The river is ca. 36 km in length and 1513 km2 in catchment surface, with a remarked variability: large floods are a significant element of this irregular hydrological regime, producing up to 80% of annual discharge volume. Precipitation and temperatures were obtained from the EUROCORDEX project: twelve combinations of Global Circulation Models and Regional Circulation Models were evaluated for a RCP8.5 emissions scenario.

The results obtained shown a clear increase in maximum and minimum temperatures for both projections (up to 3.6ºC), this increase being greater for the long-term projection, where the heat waves intensify importantly in both magnitude and frequency. In terms of precipitation, the results are similar, with precipitation quantiles increasing for practically all models and for both projections, although slightly reducing the annual amount of precipitation. The long synthetic series of precipitation that fed a fully-distributed hydrological model translated into substantial shifts in the river flows regimes, presenting, in general, lower flows during the year but increasing the frequency and magnitude of extreme flood events, reaching 100 years return period quantile values up to 58% higher at the river outlet and up to 130% at a smaller upper subcatchment. 

These results have demonstrated the solidity and effectiveness of the proposed methodology. In the field of meteorological modeling, the results have been consistent and satisfactory, demonstrating the methodology's ability to accurately represent the complexities of extreme climate patterns. Likewise, in the hydrological field, the methodology has exhibited an effective capacity to represent and simulate the processes related to the water cycle, offering coherent and satisfactory results in the estimation of low frequency flood events under climate change scenarios. This consistency in the robustness of the methodology, both in meteorological and hydrological modeling, supports its applicability and reliability in diverse environments and climatic conditions.

How to cite: Beneyto, C., Aranda, J. Á., and Francés, F.: On the use of weather generators for the estimation oflow-frequency floods under climate change scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11404, https://doi.org/10.5194/egusphere-egu24-11404, 2024.

EGU24-11499 | ECS | Posters on site | HS2.4.3

The role of meteorological drivers and initial hydrologic conditions on streamflow drought-to-flood transition events 

Eduardo Muñoz-Castro, Bailey Anderson, Paul Astagneau, Joren Janzing, Pablo A. Mendoza, and Manuela I. Brunner

Extreme hydrometeorological events such as streamflow droughts and floods may have severe impacts on infrastructure, agriculture, water supply, and hydropower generation, as well as social and political systems. Even though such impacts can be enhanced if the two types of events occur consecutively, the occurrence and drivers of drought-to-flood transitions are not well understood. Here, we ask: ‘How do the properties of drought-to-flood transitions change with different meteorological drivers and initial hydrologic conditions?’ To address this question, we configure the PCR-GlobWB hydrological model in a suite of near-natural gauged catchments, included in the quasi-global large sample dataset CARAVAN, that comprise different hydroclimatic conditions and physiographic characteristics. We run numerical experiments to understand the sensitivity of consecutive drought-to-flood properties (e.g., duration, extension, intensity, etc.) to different driver scenarios. Additionally, we perform, for each catchment, a flux-mapping analysis to explore whether different combinations of drivers can lead to a similar catchment response through different combinations of fluxes. Finally, we define clusters of catchments with similar drivers and sensitivities of consecutive hydrological extremes to the different stress tests. Ongoing analyses suggest that the drivers of drought-to-flood transitions vary substantially across catchments.

How to cite: Muñoz-Castro, E., Anderson, B., Astagneau, P., Janzing, J., Mendoza, P. A., and Brunner, M. I.: The role of meteorological drivers and initial hydrologic conditions on streamflow drought-to-flood transition events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11499, https://doi.org/10.5194/egusphere-egu24-11499, 2024.

EGU24-12331 | Orals | HS2.4.3

The recent European droughts within the nudged storyline context 

Oldrich Rakovec, Antonio Sanchez Benitez, Helge Gößling, and Luis Samaniego

Europe has experienced a series of hot and dry weather conditions with significant socioeconomic and environmental consequences over the past decade. Here, using a novel storyline approach, we examine the extremity of the recent European droughts, and we aim to isolate the thermodynamical component of climate change from changes in atmospheric patterns, which remain controversial in climate model simulations. Our climate analysis is currently based on an ensemble (n=5) of three storyline scenarios (pre-industrial, PI; PD, present-day; 4K warming) using a CMIP6 model (AWI-CM1) with the free-troposphere winds, including the jet stream, constrained toward ERA5 data. The meteorological variables at the land surface are further used as input to a hydrological impact modelling framework using the mesoscale Hydrologic Model (mHM). 

Regarding the 2022 drought analysis, first, using our experiments, we quantify the extremity of the present-day (PD) European drought against pre-industrial (PI) simulations. The potential evapotranspiration shows an apparent increase across the entire ensemble between the PD and PI periods in all of Europe. The same increase holds for actual evapotranspiration in northern Europe and most of central Europe, while the Mediterranean shows a relative decrease of 15%; however, there is no clear separation between PD and PI ensembles. The river runoff exhibits significant reductions of 35-50% in the Mediterranean regions, while changes between -15% and 15% occur over the rest of Europe (with less agreement on the signal). 

Second, we compare how the present 2022 droughts will be further amplified under different warming-level climate scenarios. Our results suggest that the 2022 river runoff drought would be much more strongly pronounced for the 4K world concerning the PD period, by up to 50% in the Mediterranean. A clear decline, although of slightly less extremity (-15% up to -40%), would also be projected across the majority of Central Europe. These changes align with observed trends associated with anthropogenic climate change. Our ongoing efforts aim to quantify possible stress on water resources and ecosystems, by providing insights into the potential future hydrological impact of different global warming levels. The aforementioned results will be further extended to address the multi-year drought perspective during the 2018-2022 periods. 

This work was supported by funding from the Federal Ministry of Education and Research (BMBF) and the Helmholtz Research Field Earth & Environment for the Innovation Pool Project SCENIC.

How to cite: Rakovec, O., Sanchez Benitez, A., Gößling, H., and Samaniego, L.: The recent European droughts within the nudged storyline context, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12331, https://doi.org/10.5194/egusphere-egu24-12331, 2024.

EGU24-12387 | Posters on site | HS2.4.3

Drought and flood episodes during the 19th Century in Catalonia (NE Iberian Peninsula)  

David Pino, Josep Barriendos, Mariano Barriendos, Carles Balasch, Jordi Tuset, and Laia Andreu-Hayles

The current context of climate change is leading to an increase in hydroclimate variability in the Mediterranean region. This situation is resulting in more frequent and longer dry periods but also in an increase of torrential rainfall events. Current situation justifies the study of the behaviour of droughts and floods from an integrated long-term perspective.

This study aims to study droughts, floods and their interaction during the 19th century in Catalonia using historical and administrative documentary sources. The 19th century corresponds to a climatic period of transition between the Little Ice Age and the current climatic period that includes the appearance of different climatic forcing factors such as solar minimums and extraordinary volcanic eruptions.

In Catalonia 19th century stands out for having some of the most important droughts recorded in the instrumental series of Barcelona (1812-1825), along with experiencing some notable catastrophic flood events. Administrative documentary data allowed us to study at daily resolution flood episodes such as in August 1842, May 1853, September 1874 and January 1898, together with the duration and frequency of drought episodes. Complementarily, in order to characterize the atmospheric general patterns during these episodes, we also generated daily barometric synoptic maps using old instrumental pressure data from different points of Europe. This approach provided the identification of different atmospheric anomalies driving these extreme hydrometeorological events.

How to cite: Pino, D., Barriendos, J., Barriendos, M., Balasch, C., Tuset, J., and Andreu-Hayles, L.: Drought and flood episodes during the 19th Century in Catalonia (NE Iberian Peninsula) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12387, https://doi.org/10.5194/egusphere-egu24-12387, 2024.

EGU24-12436 | ECS | Orals | HS2.4.3

Detecting Trends In Hydrological Extremes And Non-Stationary Extreme Value Analysis Of Flood Data In Kwazulu-Natal, South Africa 

Demian Vusimusi Mukansi, Jeff Smithers, Katelyn Johnson, Thomas Kjeldsen, and Macdex Mutema

In this study, the annual maximum streamflow from 14 stations in KwaZulu-Natal, along the East Coast of South Africa, were analysed. Trends were investigated using the non-parametric Mann-Kendall test and the Sen Slope tests, and the results indicate that the annual maximum streamflow has been decreasing in magnitude at 78 % of stations. Extreme value analysis was performed using both stationary and non-stationary models using time and rainfall as covariates. The results show that the stationary models are superior to non-stationary models at most stations with time as a covariate. Where possible, streamflow stations were linked with rainfall stations to determine the impact of rainfall on annual maximum streamflow. The results indicate that the non-stationary model incorporating observed rainfall as a covariate performed better than the stationary and non-stationary models with only time as a covariate. Therefore, incorporating rainfall in design flood estimation should be considered to account for non-stationary trends and to mitigate the risk of failure of hydraulic structures. Regional magnification factors to account for non-stationarity were not investigated further in this study as the majority of the stations showed a negative trend, which means the application of a regional magnification factor will result in a reduction of the magnitude of the estimated design floods.

How to cite: Mukansi, D. V., Smithers, J., Johnson, K., Kjeldsen, T., and Mutema, M.: Detecting Trends In Hydrological Extremes And Non-Stationary Extreme Value Analysis Of Flood Data In Kwazulu-Natal, South Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12436, https://doi.org/10.5194/egusphere-egu24-12436, 2024.

EGU24-13019 | ECS | Orals | HS2.4.3

Analyzing drought legacy effects on streamflow with machine learning 

Anne Hoek van Dijke, Sungmin Oh, Xin Yu, and Rene Orth

Prolonged periods of below-average precipitation decrease streamflow, deplete soil moisture and groundwater reservoirs, and affect vegetation health. These effects can last for several years even after precipitation returns to normal. This way, droughts can decrease or increase streamflow for post-drought years. These drought legacy effects were found in a few local studies, but they have not yet been studied at global scale. 
Here, we study drought legacy effects on streamflow in > 1100 catchments distributed across the globe using Long-Short Term Memory (LSTM) models. This type of data-driven model is very suitable for time-series predictions with long-term dependencies, and LSTMs are therefore frequently used to model streamflow. We train our LSTM model for each catchment to predict streamflow based on meteorological forcing data. For training, we include all available data between 1980 – 2019, but we exclude the drought legacy years (the two years after each drought year). We assume that our models do therefore not know about the drought legacy effects. After training we use the LSTM models to predict streamflow for drought legacy years. We then define the legacy effects as the difference between model errors (the difference between the predicted and measured streamflow) for drought legacy years, in comparison to the model errors for normal years.
Using this methodology, we find catchments that show no, positive, or negative drought legacy effects. In the next step we will study if these legacy effects vary along climate or land cover gradients. And we additionally include satellite data of vegetation greenness, evaporation, and terrestrial water storage in the LSTM training to study two hypotheses: 1) we find negative drought legacy effects due to a depletion of groundwater, and 2) we find positive drought legacy effects, because vegetation mortality leads to decreased evaporation after the drought.
Our study offers a new perspective on understanding drought legacy effects on streamflow using observational data and demonstrates the usefulness of machine learning in uncovering complex drought impacts. 

How to cite: Hoek van Dijke, A., Oh, S., Yu, X., and Orth, R.: Analyzing drought legacy effects on streamflow with machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13019, https://doi.org/10.5194/egusphere-egu24-13019, 2024.

EGU24-13029 | ECS | Posters on site | HS2.4.3

Variable Drought Threshold Method for Low-Flow Behavior Reveals Distinct Clustering Across the Continental United States 

Ryan van der Heijden, Ali Dadkhah, Amin Aghababaei, Xueyi Li, Eniola Webster-Esho, Prabhakar Clement, Mandar Dewoolkar, Ehsan Ghazanfari, Norm Jones, Gustavious Williams, and Donna Rizzo

Groundwater and surface water are interconnected in most climatic regions. Baseflow, the contribution of streamflow not directly associated with precipitation forcing, is a critical component of streamflow prediction and water resource allocation. Baseflow is often considered to be a low-frequency component of streamflow and many of the methods for estimating it are based on this premise. The climatic and physiographic attributes of a region will contribute to the low-flow behavior of its surface waterways. For example, baseflow in a snowmelt-driven basin may produce a distinct hydrologic signature compared to baseflow in a precipitation-driven basin.

In this study, we developed a unique metric based on the variable drought threshold method (VDTM) for characterizing historical streamflow timeseries and performed cluster analysis on a large set of gages in the continental United States (CONUS). Our study goal was to observe correlations between low-flow characteristics and distinct hydrologic, physiographic, and climatic regions to provide insight into the underlying mechanisms influencing baseflow.

The VDTM applies a non-exceedance percentile (NEP) computed based on the distribution of flow recorded at a stream gage over a given time frame (i.e., month, season) throughout the complete record of measurement. This study used daily streamflow records for 1,462 reference quality gages across the CONUS from the USGS GAGES-II data set; each gage contained at least 20 years of complete daily streamflow measurements. We computed the 10th NEP for each month at all 1,462 gages and normalized this value by the mean streamflow to develop the parameter r10. We performed K-means clustering on the monthly r10 values, forming seven clusters of low-flow behavior.

We observed clusters with distinct low-flow behavior across different ecoregions related to possible mechanisms driving streamflow and baseflow in those regions. For example, a cluster located in the intermountain-west shows unique behavior largely seen nowhere else in the CONUS, possibly a result of the predominantly snowmelt-driven shallow subsurface flow that contributes to baseflow seen in that region. Conversely, clusters located in the Pacific Northwest and parts of the Appalachians show a different behavior, possibly a result of the predominantly rainfall-driven streamflow observed in those regions. Principal components analysis suggests that the critical months associated with clustered gages are during the summer (June, July) and winter (January, February).

The spatial distribution of the clusters largely adheres to the defined physiographic and climatic regions of the CONUS despite the absence of any physiographic or climatic variables used for clustering, suggesting a possible linkage between these attributes and the low-flow behavior of surface waterways. Analysis of the trend and magnitude of r10 may provide insight into whether (and when) a stream is losing water to or gaining water from groundwater as well as the magnitude of the transfer. The results of this study suggest that using NEPs and the r10 metric may be an effective method for defining regionalization based on low-flow metrics.

How to cite: van der Heijden, R., Dadkhah, A., Aghababaei, A., Li, X., Webster-Esho, E., Clement, P., Dewoolkar, M., Ghazanfari, E., Jones, N., Williams, G., and Rizzo, D.: Variable Drought Threshold Method for Low-Flow Behavior Reveals Distinct Clustering Across the Continental United States, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13029, https://doi.org/10.5194/egusphere-egu24-13029, 2024.

EGU24-13741 | Orals | HS2.4.3

Compound events and hydro-climate extremes – how they are impacting Australia, now and in the future 

Wendy Sharples, Sur Sharmila, Bende-Michl Ulrike, Navid Ghajarnia, Katayoon Bharamian, Jiawei Hou, Christopher Pickett-Heaps, and Elisabetta Carrara

Many natural disasters in Australia are the result of compound events, where the assessment of single climate system drivers in isolation do not fully capture hydro-climate extremes. Multivariate compound events such as ‘hot and dry’ and ‘wet and windy’ events, portend a multitude of hazards from heatwaves and bushfires through to coastal inundation and floods. The multiple drivers compounding together in these events, lead to extreme conditions ripe for natural disasters to occur. Presently, compound events are negatively impacting Australia’s ability to protect its population and environmental and economic assets, as Australia tries to adjust to the greenhouse gas driven climatic shifts, with potential projected increases in hazard severity. We aim to understand the change in frequency, duration and intensity of ‘hot and dry’ and ‘wet and windy’ compound events, at current and increased global warming levels. The ‘hot and dry’ compound event is defined as the co-occurrence of SPI drought conditions, and at least 3 consecutive days of hot temperatures. The ‘wet and windy’ compound event is defined as the co-occurrence of both extreme wind and precipitation. These two compound events were chosen to begin with due to the historic severity of their associated impacts. However further research is planned to understand all types of compound events including preconditioned, and, spatially and temporally compounding, in order to fully gauge Australia’s potential vulnerability to natural disasters now and in the future.

How to cite: Sharples, W., Sharmila, S., Ulrike, B.-M., Ghajarnia, N., Bharamian, K., Hou, J., Pickett-Heaps, C., and Carrara, E.: Compound events and hydro-climate extremes – how they are impacting Australia, now and in the future, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13741, https://doi.org/10.5194/egusphere-egu24-13741, 2024.

The Harz mountains in Germany have experienced floods and droughts in recent years. On the one hand, a major flood event affected the city of Goslar in 2017, and on the other hand, drought conditions since 2018 have led to tree mortality in the forested catchment area upstream. The frequency of such extreme events is expected to increase as a result of climate change. Here, we aim at assessing the impacts of the ongoing tree mortality on hydrology. To this end, we employ the ecohydrological model SWAT+ to assess changes in water balance components. The model is specifically calibrated for extreme conditions by evaluating the model performance for different segments of the flow duration curve. Satellite-derived changes in forest cover are used to assess the impact on water balance components. The analysis of the model performance indicates that the calibration strategy improved model performance for drought conditions. Furthermore, first model results indicate that tree mortality led to a decrease in evapotranspiration and an increase in surface runoff. The spatial assessment suggests stronger effects at the sub-catchment scale than at the catchment scale. However, the faster response of the catchment due to tree mortality potentially increases the severity of flood events and the flood risk in downstream areas. Therefore, afforestation with climate-resilient trees is needed to improve both flood and drought resilience in the Harz mountains.

How to cite: Wagner, P. and Fohrer, N.: Impacts of hydrological extremes in a mountainous forest catchment: Experiences from the Harz mountains, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14209, https://doi.org/10.5194/egusphere-egu24-14209, 2024.

EGU24-14703 | Posters on site | HS2.4.3

Evaluating the seasonal patterns of low flow in  Nakdong River basin using SWAT 

Wonjin Kim, Si Jung Choi, and Seong Kyu Kang

ABSTRACT

This study focuses on the seasonal patterns of low flow in the Nakdong River basin (23,635 km2), considering its vital role as a seasonal phenomenon and integral component of the flow regime. Low flow, derived from groundwater discharge or surface discharge from lakes and reservoirs, exhibits varying magnitudes and durations under seasonal changes, thereby holding significant implications for agricultural activities, aquatic species, and water quality. In the absence of gauge stations for small streams, Soil and Water Assessment Tool (SWAT) was employed to ensure reliable simulation for low flow along the target watershed, and the model was calibrated for the period of ten years (2010~2019) using observed data from multipurpose dams and multifunctional weirs within the target watershed. Based on the model results, spatio-temporal variations of low flow were estimated, and seasonality indices were adopted by means of understanding and analysing low flow characteristics. The indices include seasonlity histograms (SHs) depicting the monthly distribution of low flows, seasonlity index (SI) representing the average timing of low flows within a year, and seasonality ratio (SR) showing the ratio of summer to winter low flows. Subsequently, seasonal patterns of low flow in target watershed were evaluated under three indices to figure out the response of low flow in relation to watershed characteristics and climate variability.

 

Acknowledgements

Research for this paper was carried out under the KICT Research Program, Development of IWRM-Korea Technical Convergence Platform Based on Digital New Deal) funded by the Ministry of Science and ICT.

How to cite: Kim, W., Choi, S. J., and Kang, S. K.: Evaluating the seasonal patterns of low flow in  Nakdong River basin using SWAT, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14703, https://doi.org/10.5194/egusphere-egu24-14703, 2024.

EGU24-14737 | ECS | Posters on site | HS2.4.3

Identifying Flash Flood-Prone Subbasins in India Using Geomorphological and Meteorological Parameters  

Nandana Dilip K, Urmin Vegad, and Vimal Mishra

Flash Floods are one of the crucial disasters in India which causes high mortality and damage due to its sudden onset and devastating impact. These events are projected to increase in India due to the warming climate and increasing unplanned urbanization.  However, India still lacks a robust analysis on flash flood susceptibility at a subbasin scale. In our study, we have considered meteorological and geomorphological factors to improve the susceptibility mapping, as flash floods are the result of high intensity rainfall in a short period of time and the geomorphology of the basin. We analyzed 17 different geomorphological factors of drainage, relief and areal aspects. Further, we calculated the flashiness index for all the subbasins within India using the model simulated streamflow. We forced a hydrodynamic routing model with reanalysis data to simulate streamflow at the subbasin outlets. We prepared subbasin-level flash flood susceptibility maps based on geomorphology, flashiness index and a combination of both. The integrated use of geomorphology and meteorology will provide a more robust framework for identifying the flash flood prone subbasins in India. This will help the authorities in focusing on the probable regions to plan mitigation strategies.  

How to cite: Dilip K, N., Vegad, U., and Mishra, V.: Identifying Flash Flood-Prone Subbasins in India Using Geomorphological and Meteorological Parameters , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14737, https://doi.org/10.5194/egusphere-egu24-14737, 2024.

EGU24-14818 | ECS | Posters virtual | HS2.4.3

Beyond the Extremes: Interpretable insights based on Attention framework  

Ashish Pathania and Vivek Gupta

Extreme weather events significantly impact the economy, agriculture, infrastructure, and ecosystems of a region. According to the Center for Science and Environment (CSE), extreme weather events caused the loss of nearly 3000 lives, 2 million hectares of crops, and the death of 90,000 cattle in India in 2023 alone. Effective mitigation and adaptation strategies for the region necessitate a reliable forecasting system. The spatiotemporal interactions of several hydroclimatic components at different scales make it difficult to provide reliable forecasts for a region with multiple climate zones. The present research proposes an encoder-decoder-based deep learning framework with an attention mechanism to develop a reliable forecasting model. Attention frameworks have exhibited considerable potential in learning contextual awareness within the time series domain which will help in identifying the temporal dependencies between the meteorological variables and extreme events. The proposed architecture of the forecasting model is made interpretable as it is crucial to comprehend the underlying mechanism of climatic extremes. It recognizes the contributing variables influencing the intensity and frequency of extreme events. The study employed 0.12° × 0.12° high-resolution IMDAA (Indian Monsoon Data Assimilation and Analysis) dataset encompassing climatic variables like precipitation and temperature.

Various studies have supported the association of the ENSO parameters with the anomalous climatic conditions over India. The present study also aims to ascertain the distinct contributions of ENSO variables through the implementation of an interpretable framework. Explainability results underscore the significance of precipitation patterns while forecasting drought conditions in the region. Moreover, the results highlight the complex interaction of climatic variables that affect the intensity of the extremes.

How to cite: Pathania, A. and Gupta, V.: Beyond the Extremes: Interpretable insights based on Attention framework , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14818, https://doi.org/10.5194/egusphere-egu24-14818, 2024.

Reliable Tropical Cyclone (TC) precipitation and flood nowcasting play an important role in disaster prevention and mitigation. Especially for small-scale reservoirs, timely and accurate inflow forecasts are required to provide safe space for capturing high flows without having to resort to hazardous and damaging releases. Numerous studies have investigated the ability of deep learning in TC precipitation nowcasts. However, few of them focus on the skill of deep-learned TC precipitation forecasts in inflow flood forecasts. In this study, a novel framework is developed by introducing TC track information together with antecedent precipitation in the Convolution LSTM model (PTC-ConvLSTM). The ConvLSTM forecast precipitation is then input to an event-based Xinanjiang hydrological model for inflow flood forecasting, and the propagation of errors from TC track forecasts to inflow forecasts is further analyzed. The results show that TC track information enables a further 5% improvement compared to outputs from ConvLSTM with only precipitation information. PTC-ConvLSTM precipitation nowcasts present a probability of detection (POD) greater than 0.34 for a threshold of 5mm/h in a lead time of 6h. The nowcasts-driven flood forecasts have an NSE greater than 0 with a lead time of 5h at least. It is also indicated that the 100km error in TC track forecasts could generally result in a 10% degradation in precipitation forecasts and a further 8% deterioration in the driven flood forecasts. The effectiveness of our model indicates that the precipitation nowcasts from deep learning have strong applicability in disaster mitigation.

How to cite: Liu, L., Xu, Y.-P., and Gu, H.: Enhanced tropical cyclone inflow flood forecasts by using deep learning and spatial‑temporal information, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14963, https://doi.org/10.5194/egusphere-egu24-14963, 2024.

Heatwaves and droughts are among the natural hazards with frequencies and severities expected to increase due to climate change. Furthermore, they are responsible for a large range of social and economic impacts, such as agricultural losses, energy shortages, heat related mortality, etc. Previous works have shown that co-occurring drought and heatwave events lead to higher significant socio-economic damages compared to independent events. However, limited knowledge is available on quantifying spatial patterns of co-occurring droughts and heatwaves events, their severity, and frequency of occurrence, especially at high spatial and temporal resolution.

The aim of this study is to quantify spatio-temporal changes of compound drought and heat wave events in a large anthropized alpine Italian basin, the Adige basin, located in the North of Italy, with area greater than 10,000km2 and containing a wide range of elevation from 160m to 3905m. We quantify changes in single and multiple drought and heat wave hazards during the period 1980-2018, based on hydrological simulations performed using a recently produced hydrological digital twin model at high spatial (5 km2) and temporal (daily) resolution. The model also includes artificial reservoirs and the combination of high resolution hydrological modeling and compound hazard estimation framework has a key advantage that: i) it captures single hazard evolution at daily time scale and ii) explicitly estimate the dependence between co-occurred events directly mapping critical susceptible regions.

Preliminary results show increasing trends in number and severity of compound heat waves and drought events. Ongoing work aim to quantify the spatial distribution of the analysed compound events and the exposure in terms of population impacted and main land cover types. The proposed modeling framework may help improve the prediction and assessment of occurrences of compound heat waves and droughts events and the possible implementation of mitigation actions. The authors are supported by the WATERSTEM MUR PRIN 2020 (Prot. Number 20202WF53Z) and the COACH-WAT PRIN 2022 (Prot. Number 2022FXJ3NN).

How to cite: Formetta, G. and Morlot, M.: Compound heatwave and drought hazard quantification in a large anthropized alpine basin., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15136, https://doi.org/10.5194/egusphere-egu24-15136, 2024.

EGU24-15522 | ECS | Orals | HS2.4.3

Flood control capacity of a large reservoir under moderate and extreme flood conditions 

Pratik Chakraborty, Sophie De Kock, Pierre Archambeau, Michel Pirotton, Sébastien Erpicum, and Benjamin Dewals

Dams, prevalent globally as major hydraulic structures, play essential roles in water supply, hydroelectric power, and flood management. However, they are known to significantly transform hydrological regimes by, among others, regulating flood and base flow dynamics. This, in turn, necessitates a meticulous understanding of the nature of these alterations.

Focused on the Eupen dam in Belgium, this study examines its storage dynamics in relation to moderate and extreme flood events. The study analyses time-series of inflow and outflow discharges at the dam for the period from 1995 to 2023. The inclusion of the July 2021 extreme event provides valuable insights into the dam’s performance (or lack thereof) during such mega-events. Notable aspects of the methodology include adjustments for an ungauged sub-basin, the use of a Savitsky-Golay filter to refine (field-)data quality without compromising peak details and a fundamental mass-balance approach to compute outflow data from the inflow time-series.

The examination of 18 flood events during this period reveals significant findings: the dam's ability to reduce peak discharge by 8.6 to 91%, delay peak discharge by up to 68 hours, decrease flood volume by 2 to 94%, and reduce the rising rate by 1.09 to 11.16 times. Distinctly, the study also reveals a strong correlation between the damping ratio of the flood wave and the ratio of the volumes of the incoming flood to that available in the reservoir (at the start of an event). The outcomes of the flood frequency analysis are also presented and interpreted in detail.

The present study features a marked shift from existing dam-effects research, wherein the analysis is often focused on mean annual flow characteristics or aggregated data across numerous dams. It highlights the rewards of such a singular case study, in terms of being able to scrutinise individual flood events. This, in turn, provides the scope to understand more complex underlying conditions that prompt a dam's effects on streamflow characteristics. Finally, this research evidences the benefits provided by dam reservoirs on flood wave damping, but also their limits in doing so.

How to cite: Chakraborty, P., De Kock, S., Archambeau, P., Pirotton, M., Erpicum, S., and Dewals, B.: Flood control capacity of a large reservoir under moderate and extreme flood conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15522, https://doi.org/10.5194/egusphere-egu24-15522, 2024.

EGU24-15968 | ECS | Posters virtual | HS2.4.3

Regional Flood Frequency Analysis Utilizing LH-moment based framework for Godavari River Basin 

Amit Singh and Sagar Chavan

Regional flood frequency analysis (RFFA) helps in estimating the design flood at ungauged locations within a hydrologically homogeneous region. LH moment is a statistical method often used in hydrology for estimating distribution parameter. The LH moment are the linear combination of higher probability weighted moment. It offers an alternative to traditional moments and is particularly useful when dealing with skewed distributions. The Godavari River, one of the major river systems in India, experiences varying hydro climatic conditions across the basin. This study presents a comprehensive regional flood frequency analysis (RFFA) conducted in the Godavari River basin employing LH moment as a robust statistical tool. The present study incorporates the formation of region using region of Influence approach (ROI) approach. In this study, five probability distributions namely generalized extreme value (GEV), generalized logistic (GLO), Pearson Type III (PE3), Generalized Normal (GNO) and generalized Pareto (GPA) are considered for performing RFFA for estimating ungauged flood quantiles corresponding to various return periods (e.g., 50, 100, and, 200 years) in the Godavari River basin. The discordancy measure and heterogeneity measure in LH-Moment framework are considered for screening of peak flow data and checking the heterogeneity of the region formed using ROI. The suitability of GEV, GLO, PE3, GNO, and GPA distribution is judged through the LH-moment ratio diagram and the Z-statistic criteria. The performance of LH-moment based RFFA is evaluated through Leave-One-Out Cross Validation (LOOCV). Results indicate that the LH-moment based RFFA yields more reliable estimates of flood quantiles.

How to cite: Singh, A. and Chavan, S.: Regional Flood Frequency Analysis Utilizing LH-moment based framework for Godavari River Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15968, https://doi.org/10.5194/egusphere-egu24-15968, 2024.

Three homogeneity tests were carried out on the lower Columbia River basin namely, Standard normal homogeneity test, Pettit test and Buishand test for daily gridded rainfall data having spatial resolution of 0.5o spanning a period of 43 years from 1980 to 2022. These tests were employed to estimate the breakpoint year for each grid and plotted on a map for spatial visualization. It was observed that a close relation follows between the elevation of a place, its changepoint year and the land use land cover of that area. The elevation of an area affects the direction of propagation of moisture laden winds that are developed over the Southwestern part of US from Pacific Ocean and gulf of California. And eventually governing where and how much precipitation they will bring. Additionally, the land cover of an area governs the amount of evapotranspiration and hence the pressure difference between the moisture laden winds and the atmosphere over that land cover. When the daily precipitation records of 4 decades were analysed for homogeneity and changepoint year observed spatially, it was noted that a particular elevation and land cover showed similar breakpoint and a trend is being followed. This study provides a novel way of understanding the behaviour of changing precipitation patterns taking into account the long-term variability of 4 decades.

Keywords: Homogeneity test, Change point analysis, Land use land cover, Lower Columbia River basin

How to cite: Hamid, I. and Jothiprakash, V.: Analysing the relation between changepoint year, elevation, and land cover over lower Columbia River basin in North America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16296, https://doi.org/10.5194/egusphere-egu24-16296, 2024.

EGU24-16427 | ECS | Posters on site | HS2.4.3

Development of a river breakup prediction model 

Marie Sæteren, Kolbjørn Engeland, Ånund S. Kvambekk, and Lena M. Tallaksen

The dynamic breakup of river ice can initiate ice runs where large masses of ice floes accumulate as ice jams. These ice jams can cause severe inundation and infrastructure damage. Several Norwegian rivers are prone to ice run events, however there are currently no models available in Norway for predicting this specific hydrological phenomenon. Ice-related problems are often dealt with on a site-to-site basis and rely heavily on local knowledge. Other countries, such as Canada and Sweden, have implemented statistical, machine learning and process-based modelling approaches. Being able to accurately predict the timing and severity of ice run and ice jam events improves the ability to take suitable mitigation measures and limit negative consequences. The aim of this work is to develop a model to predict ice run events in two Norwegian rivers, the Beiarn River and the Stjørdal River, and thereby address the need for predicting this hydrological hazard.

The work presented here is part of a master thesis study that will be completed by May 2023. Both Stjørdal and Beiarn River have been monitored by NVE in the latter half of the 20th century, and the timing and severity of historical ice run events are obtained from this data. The predictors are given by hydrometeorological and ice thickness data, both observed and modelled. The Distance Distribution Dynamics (DDD) model developed by NVE is used for simulating daily discharge, and a simple ice growth model from NVE is used for modelling ice thickness. The prediction model itself is a work in progress, initially taking a logistic regression approach. If time allows, other approaches within machine learning such as random forest will be attempted. The dataset is severely imbalanced given the rarity of ice run events and the limited length of the observed series. Different methods are evaluated in terms of their ability to deal with this issue. The ultimate objective of this project is to develop a model providing daily probabilistic forecasts of the likelihood of ice run events in the coming days.

How to cite: Sæteren, M., Engeland, K., Kvambekk, Å. S., and Tallaksen, L. M.: Development of a river breakup prediction model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16427, https://doi.org/10.5194/egusphere-egu24-16427, 2024.

EGU24-17185 | Posters on site | HS2.4.3

Using ERA-5 reanalysis to characterize extreme rainfall in Italy 

Francesco Chiaravalloti, Roberto Coscarelli, and Tommaso Caloiero

Heavy precipitation events are likely to become more frequent in most parts of Europe; yet, records of hourly precipitation are often insufficient to study trends and changes in heavy rainfall. Atmospheric reanalyses are an important source of long-term meteorological data, often considered as a solution to overcome the unavailability of direct measurements. The reanalysis procedure makes use of a large amount of heterogeneous historical observations, both sensed and remotely measured (in situ, satellite, etc), assimilated within a dynamical model to reconstruct the state of the atmosphere, land surface and oceans in the past. Among the available reanalyses, the ERA5 dataset released by the ECMWF, can be considered one of the state-of-the-art products. Atmospheric and surface variables are provided hourly, from 1950 to almost real time, with a horizontal resolution of 31 km. The land model of the ERA5, driven by the downscaled meteorological forcing from the lowest ERA5 model level, and with an elevation correction for the thermodynamic near-surface state, is also used to derive the ERA5-land dataset, characterized by a higher spatial resolution (9 km) and finer precipitation distribution details.

In this paper, data from the ERA5-land reanalysis dataset were used to characterize the 1-hour maximum yearly rainfall values in Italy. Specifically, 3215 grid series of 1-hour rainfall for the period 1950-2020 have been first extracted. Then, for each grid series the 71 1-hour maximum yearly rainfall values have been evaluated. Moreover, the time frame 1950-2020 has been divided into several intervals, and for each one, the frequency distribution of the months recording the annual maxima was calculated. Finally, a cluster analysis has been performed to evaluate the area with a similar monthly distribution of these values. Results showed that, considering the data over the whole of Italy, the monthly distribution of occurrences of annual maxima of 1-hr rainfall is characterized by a peak in September occurring in all the time windows considered. Furthermore, clustering cells with a similar distribution of annual hourly rainfall maxima, using k-means, allowed to identify three groups characterised by different months with the highest frequency of occurrence of the maximum.

This work was funded by the Next Generation EU - Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of 'Innovation Ecosystems', building 'Territorial R&D Leaders' (Directorial Decree n. 2021/3277) - project Tech4You - Technologies for climate change adaptation and quality of life improvement, n. ECS0000009. This work reflects only the authors’ views and opinions, neither the Ministry for University and Research nor the European Commission can be considered responsible for them.

How to cite: Chiaravalloti, F., Coscarelli, R., and Caloiero, T.: Using ERA-5 reanalysis to characterize extreme rainfall in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17185, https://doi.org/10.5194/egusphere-egu24-17185, 2024.

EGU24-17249 | ECS | Posters on site | HS2.4.3

Global trend and drought analysis of near-natural river flows: The ROBIN Initiative 

Amit Kumar, Jamie Hannaford, Stephen Turner, Lucy J. Barker, Harry Dixon, Adam Griffin, Gayatri Suman, and Rachael Armitage

With hydrological extremes becoming more frequent and intense in a changing world, the impact on livelihoods, infrastructure, and economies is crucial. River flow data is a valuable resource and can be used to understand and analyse trends in both flow and extreme events. It is essential to systematically examine trends and anomalies within river flow across the globe. To capture the true natural trends, the river flow data should be from natural catchments and free from anthropogenic influences, such as the construction of dams, alterations in land use, and extraction of water from rivers. Special attention must be directed towards delineating these factors to enhance our understanding of the complex dynamics governing river systems. 

Existing challenges in attributing trends in river flows to climate change demands for a comprehensive, worldwide Reference Hydrometric Network (RHN) with minimal human impacts, to ensure integrity of climate change signals in river flow data. This global initiative, the Reference Observatory of Basins for INternational hydrological climate change detection (ROBIN) is a global collaboration to bring together the first global RHN. Currently consisting of partners from almost 30 countries spanning every continent, the first iteration of the ROBIN dataset is now available – a consistently defined network of over 3,000 near-natural catchments. 

The ROBIN team estimated the first truly global analysis of trends in river flows using near-natural catchments for periods of 40 (1975-2016) and 60 (1956-2016) years. This research showcases the first global drought assessment using the subset of ROBIN network, investigating variations in river flow trends and their impact on drought events, and trends at a global scale. The research focused on the spatial and temporal variability of trends and drought characteristics in different countries and hydro-belts across the ROBIN network. It also shows the great potential of serving as benchmark for future hydrological trend assessments. 

Efforts are ongoing to broaden the ROBIN network to bring together more countries, incorporating additional catchments representing diverse geographical characteristics. With the support of international organizations such as WMO, UNESCO, and IPCC, ROBIN establishes the groundwork for a sustainable network of catchments, enabling comprehensive assessments of climate-induced trends, variability, and occurrences of drought on a global scale. This initiative makes a substantial contribution to enhancing our understanding of the impact of climate change on river flows and the corresponding global patterns of drought. 

How to cite: Kumar, A., Hannaford, J., Turner, S., Barker, L. J., Dixon, H., Griffin, A., Suman, G., and Armitage, R.: Global trend and drought analysis of near-natural river flows: The ROBIN Initiative, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17249, https://doi.org/10.5194/egusphere-egu24-17249, 2024.

EGU24-17464 | Orals | HS2.4.3

Patterns of extreme high flows in relation to their dominant generating processes across Sweden 

Yeshewatesfa Hundecha, Jonas Olsson, Lennart Simonsson, and Jörgen Rosberg

Understanding the nature of flooding of a region is key for flood management. The impact of flooding depends on how spatially extensive it is and this, in turn, is influenced by the processes generating the flood. In this study, we investigated the relative importance of rainfall and snowmelt in the generation of floods of different magnitudes and characterized their spatial patterns in different climate regions of Sweden. We generated a large number of spatially diverse extreme river flow scenarios across Sweden that are statistically consistent with the observations by employing a multi-site weather generator and a highly resolved semi-distributed hydrological model. The extreme flows within each of the main rivers were classified based on their generating meteorological forcing and the spatial distribution of the flow magnitudes was assessed. The results reveal that rainfall is the main contributor of extreme flows of all magnitudes in the southern part followed by rain-on-snow, while in the northern part, rain-on-snow is the main process resulting in extreme flows followed by rainfall. Pure snowmelt is the least contributor of extremes in all regions and its contribution decreases with increasing magnitude of the flow. The proportion of events generated by rainfall increases with the magnitude of the flow in all regions. Extremes of lower magnitudes are generally more spatially widespread than the higher extremes and events generated by snowmelt and rain-on-snow are spatially more widespread than events generated by rainfall.

The possible impact of climate change was also assessed by generating extreme flows for end-of-century climate change scenarios by perturbing the weather inputs generated by the weather generator using data from a set of regional climate models and using them to force the hydrologic model. The results show that the main generating processes in each region remain the same. However, the proportion of rainfall generated events will be markedly higher than under the present climate. 

How to cite: Hundecha, Y., Olsson, J., Simonsson, L., and Rosberg, J.: Patterns of extreme high flows in relation to their dominant generating processes across Sweden, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17464, https://doi.org/10.5194/egusphere-egu24-17464, 2024.

EGU24-17479 | Posters on site | HS2.4.3

MAKAHO: An interactive cartographic Tool for Trend Analysis of hydrological extremes in France  

Louis Héraut, Michel Lang, Benjamin Renard, Éric Sauquet, and Jean-Philippe Vidal

Analysing the significance of trends in hydrological variables across different components of the streamflow regime, from low flows to high flows, provides an overview of the state of a region in the context of ongoing global changes. This information is crucial for decision-making regarding adaptation but also for evaluating hydrological projections.

 

MAKAHO (MAnn-Kendall Analysis of Hydrological Observations) is an interactive cartographic visualization system designed to examine trends in hydrometric observations from the 232 stations belonging to the French Reference Hydrometric Network (Giuntoli et al., 2013). These stations show a high measurement quality, time series with a historical depth of over 30 years, and they crucially gauge near-natural catchments. The statistical test used for trend detection is a variant of the Mann-Kendall test accounting for first-order autocorrelation. The trend slope is provided by the Theil-Sen estimator.

 

The hydrological situation in France shows a marked contrast between the northern and southern regions. Between 1968 and 2020, 22 % of stations show a significantly trend in the annual maximum daily streamflow at the 90 % confidence level. Of these stations, 27 % exhibit an upward trend, with an average increase of 13 % per decade. Almost all of these stations are located in the northern part of the country.

 

This north-south divide is also visible for low flows, with the demarcation line extending further north. 39 % of stations show a decreasing trend in the annual minimum monthly discharge, with an average intensity of about 11 % per decade. The signal in the northern part of the country is less significant. The duration of low flows has significantly increased in the south, particularly in the southwest, with an average of more than ten days per decade, reaching almost a month in extreme cases.

 

The tool, developed using the R Shiny library, takes the form of an online graphical interface (https://makaho.sk8.inrae.fr/). It enables direct communication with the R Exstat package (https://github.com/super-lou/EXstat), which is essential for data aggregation and trend analysis. Calculations are performed on the fly, allowing greater customisation of analyses. MAKAHO users can choose the analysis period, the hydrological variable (from low flows to high flows), display time series for the variable of interest and extract summary sheets for a set of hydrometric stations. The interactive map and graphs allow switching from an overview to a detailed view of the results for each station. MAKAHO has been designed based on previous research projects involving stakeholders to encourage water managers to develop robust strategies for adapting to climate change and has received financial support from the French Ministry of Ecology.

 

Giuntoli, I., Renard, B., Vidal, J.-P., and Bard, A. (2013). Low flows in france and their relationship to large-scale climate indices. Journal of Hydrology, 482:105–118. https:/doi.org/10.1016/j.jhydrol.2012.12.038

How to cite: Héraut, L., Lang, M., Renard, B., Sauquet, É., and Vidal, J.-P.: MAKAHO: An interactive cartographic Tool for Trend Analysis of hydrological extremes in France , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17479, https://doi.org/10.5194/egusphere-egu24-17479, 2024.

EGU24-18032 | ECS | Orals | HS2.4.3

Challenges in analysing and modelling extreme floods: The case study of Ahr catchment 

Bora Shehu and Axel Bronstert

The extreme weather conditions of July 2021 caused major flooding’s in multiple tributaries of the Meuse and Rhine rivers. Particularly the Ahr Valley in Germany was greatly affected, where exceptional damage and severe human loss was registered. Since then, several studies have been conducted to understand the extremity, the major driving forces, the particular mechanisms of this flood and the possible impacts of climate change on the generation of such an event. Here the main objective is to perform a hydrological analysis of the July 2021 Ahr event and discuss the challenges in modelling or analysing this event.

First, we show that particularly the rainfall field is associated with high uncertainty, as seen by the high variability between the different rainfall products available. The average areal rainfall volume can differ between products with as much as 50mm/day, which constitutes almost 55% of the rainfall volume estimated by Radolan. To capture the full uncertainty-range of the rainfall field, rainfall simulations conditioned both on radar and station observations are implemented.  

Next, based on rainfall simulations and reconstructed discharge data, runoff coefficients (Rc) are shown to be ranging between 0.6 to 1.2 (median 0.7). These values are clearly higher than expected in continental climate (Rc ~ 0.20-0.51) and the latest 100-year return flood observed in 2016 (with Rc ~ 0.4). The high lower range suggests, that the dominant processes have changed, with slower components of surface runoff shifting to faster ones. This agrees well with the observed traces of erosion, surface water and flow paths in parts of the catchment.

Lastly, the reconstructed discharge data are also subjected to uncertainty due to lack of observations and the non-representativeness of the stage-discharge curve during the flood wave. Hence, high Rc values do not only originate from underestimated rainfall but as well from possible overestimated flood volume. For this purpose, discharge was estimated with the Larsim model. As expected due to the change of the dominant processes, the pre-event parameter set underestimates considerably the flood volume, while the post-calibration one agrees better with the reconstructed data. On both cases, the computed runoff coefficient ranges between 0.4 to 0.7.

To conclude, extraordinary events such as the July 2021 in Ahr Catchment, are accompanied with high uncertainty and as such are difficult to be analysed or modelled. Nevertheless, the results dictate that the surface runoff played an important role in July 2021. At the same time, it is clear that the landscape still has a considerable retention effect, between 30% and 50%, even for such a heavy rainfall.

How to cite: Shehu, B. and Bronstert, A.: Challenges in analysing and modelling extreme floods: The case study of Ahr catchment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18032, https://doi.org/10.5194/egusphere-egu24-18032, 2024.

EGU24-18080 | ECS | Posters on site | HS2.4.3

Investigation of combined regional trends of extreme precipitation and temperature in southern Italy 

Gholamreza Nikravesh, Alfonso Senatore, and Giuseppe Mendicino

This contribution proposes an integrated analysis of climate regime trends in southern Italy (Calabria Region), focusing on both extreme precipitation and temperature events. Provided several precipitation and temperature observations available in the period 1955-2023 for a relatively dense monitoring network (approximately a rain gauge station per 110 km2 and a temperature station per 100 km2), four precipitation-related variables like total precipitation (PRCPTOT), maximum one-day precipitation (RX1day), maximum five-day precipitation (RX5day) and Consecutive Dry Days (CDD) were chosen. Also, three temperature-based variables were selected, i.e., the maximum of the maximum daily temperatures (TXx), the mean of the mean daily temperatures (Tmean), and the minimum of the minimum daily temperatures (TNn). The trends of these seven selected variables were assessed and combined through three approaches at the annual and seasonal scales, considering each available monitoring station (namely, 134 precipitation and 148 temperature stations). First, we combined PRCPTOT and RX1day to highlight which stations have an increased probability of both drought and flood risks, developing a novel integrated climate regime index (ICRI). Then, we considered the three temperature indices, TXx, Tmean, and TNn, to pinpoint stations that have experienced more robust rising trends. The third analysis combined PRCPTOT, RX1day and temperature (using alternatively TXx, TNn and Tmean) to investigate the compound risk of flood, drought and, to a certain extent, wildfires. The results indicate a rather homogeneous increase of all temperature-related variables, especially starting from 1990, and that since 1955, a considerable number of stations have experienced increasing trends for RX1day and falling trends for PRCTOT. Therefore, most of the territory of the region is more likely to confront water stress, flood and forest fires.

How to cite: Nikravesh, G., Senatore, A., and Mendicino, G.: Investigation of combined regional trends of extreme precipitation and temperature in southern Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18080, https://doi.org/10.5194/egusphere-egu24-18080, 2024.

EGU24-18942 | Orals | HS2.4.3

Changes in maximum and minimum runoff of Eurasian Arctic rivers during the climate change epoch 

Maria Kireeva, Dmitriy Magritskiy, and Natalia Frolova

The study is devoted to the analysis of daily time series of river runoff in the Arctic zone of Eurasia. Unique data on daily water discharges in the closing gauges of Arctic rivers were collected and processed in the package grwat (https://cloud.r-project.org/web/packages/grwat/index.html ), which identifies genetic components of runoff. As a result, 53 runoff characteristics were obtained for each of the 25 rivers flowing into the Arctic Ocean and the contribution of snowmelt, rainfall, and groundwater components to the total runoff was analyzed. Particular attention was paid to extreme characteristics - maximum water discharges of spring freshet, rain events and minimum 1, 5, 10-averaged discharges during summer and winter.
The study of maximum water discharges has shown that, in general there are trends of decreasing annual maximums for both large and medium-sized Arctic rivers. This trend, however, is not yet statistically significant everywhere. The most intensive decrease in maximums localized in the Northern Dvina, Ob, and Yenisei rivers, for which flow regulation by reservoirs has a significant impact. For the Kolyma, Yana and Indigirka rivers, there are periods of increase in maximums and their decrease lasting 5-7 years, with a general tendency to increase during 1960-2001 up to 15-20%.
In contrast, the minimum discharges with different averaging intervals increases by 25-56 % everywhere; this trend is presumably related to the general climate warming, increased infiltration and the role of groundwater flow, and for the rivers in the eastern part of the Arctic zone - to the degradation of permafrost.
The study also included analysis of the runoff signature transformation in Arctic zone by every year, as well as on average for the modern and historical period. The typing methodology consisted in classifying hydrographs according to two main features: a) exceedance of maximum discharge relative to the average annual discharge b) the share of flood runoff volume in the total annual runoff. The analysis showed a noticeable increase in the frequency of occurrence of smoothed hydrographs on the rivers of the Arctic zone of the Asia-Pacific region, for some basins the number of such years increased by 1.5-2 times (Polui, Turukhan, Ob rivers).

How to cite: Kireeva, M., Magritskiy, D., and Frolova, N.: Changes in maximum and minimum runoff of Eurasian Arctic rivers during the climate change epoch, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18942, https://doi.org/10.5194/egusphere-egu24-18942, 2024.

EGU24-19269 | ECS | Posters on site | HS2.4.3

Dynamics of Intraseasonal Compound Whiplash Event: A Retrospective Analysis in India 

Aman Kumar and Dhyan Singh Arya

Hydroclimatic Whiplash events refer to the extreme variability characterising the rapid transitions from one hydroclimatic extreme to another, occurring in consecutive periods. Rapid transition from one extreme to the other. The compound consecutive extremes impact often exceeds the magnitude of individual events given their occurrence at distinct times. This study introduces a comprehensive investigation into Intraseasonal compound whiplash occurrences in India, focusing on the rapid shifts between drought/heat and pluvial conditions. The data used in the study is taken from IMD precipitation of 0.25˚ x 0.25˚ and temperature at 1˚x 1˚ for the time span 1901 to 2022. This study involves distinct thresholds for duration and intensity to identify the heat dry and wet events. Dry events are characterised by prolonged low rainfall and sustained minimum temperatures throughout the dry period. Conversely, wet events exhibit high intensity within relatively shorter durations. Emphasising the 70th percentile for temperature thresholds acknowledges that extreme conditions in each component aren't mandatory for a compound event's occurrence. Our study delves into the frequency of individual extremes and compound whiplash occurrences, calculating swing severity using mean temperature quantiles for warm/dry spells alongside precipitation anomalies. The Mann-Kendall test and Sen’s slope is used for the check frequency and severity evolution at the grid level. Results highlight diverse regions witnessing increasing trends in wet and dry events, signifying a notable surge in compound whiplash incidents. This is especially worrying in areas that have typically been dry because the increase in rain can disrupt the usual climate there. This concerning trend raises alarms for local ecosystems, water resources, and socio-economic activities. Recognising these evolving patterns is critical for making strategies and long-term planning in the recent climate variability.

How to cite: Kumar, A. and Arya, D. S.: Dynamics of Intraseasonal Compound Whiplash Event: A Retrospective Analysis in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19269, https://doi.org/10.5194/egusphere-egu24-19269, 2024.

Hydroclimatic whiplash, a lagged compound hazard combined with preceding drought (flood) and following flood (drought), may induce significant environmental, hydrological, and socio-economic impacts worldwide. North America is one of the hot spots becoming susceptible to the transitions or shifts between two extremes. These compound events are also expected to become more frequent and intense in the future under climate change. To better understand the climate influence, overall decadal changes in climate variables and related hydroclimatic swing events need to be analyzed considering two components: anthropogenic external forcing and natural internal variability. External forcing is induced by anthropogenic activities imposing greenhouse gas emissions on the climate system, resulting in the signal of global warming. Internal climate variability (ICV), also termed climate noise, is an irreducible uncertainty induced by the chaotic nature thus unpredictable evolution of the climate system. In this study, we use four single-model initial-condition large ensembles (SMILEs) under historical and future forcing scenarios (RCP8.5), CanLEAD-EWEMBI, CanLEAD-S14FD, CanRCM4-LE, and GFDL-SPEAR, to quantify the relative role of external forcing and ICV on variations in compound dry-wet swing events across North America. The SMILE enables the robust quantification of the externally forced response and internal variability via computation of ensemble statistics, provided the ensemble size is large enough. On the virtue of this advantage, the standardized precipitation evaporation index is estimated to identify dry and wet spells and their transitions based on ensemble pooling and threshold-based event extraction methods. Frequency, intensity, transition time, transition intensity, and relative role of preceding and following spells, etc. are quantified for each warming period (1.5°C-4 °C global warming levels) and compared with those of the baseline period to investigate their projected changes and trends. The relative contribution of ACC and ICV to compound dry-wet spells is quantified by the ratio of changes and trends in the ensemble mean and the spread (standard deviation) among the ensemble members of each SMILE, respectively. The results of this study suggest that hydroclimatic swing events across North America are expected to become more frequent and intensified in a warmer climate, which is induced by significant emergence of external forcing. In addition, the transition time and transition intensity are projected to be more dominated by anthropogenic forcing over ICV than other characteristics indicating that more abrupt and severe shifts can occur in the future. The findings of this study support the necessity of developing appropriate measures for mitigating the anthropogenic forcing impact because it increases the risk of lagged compound floods and droughts that can lead to severe disasters in North America.

How to cite: Najafi, M. R., Na, W., and Grgas-Svirac, A.: Relative Contribution of External Forcing and Internal Climate Variability to Lagged Dry-Wet Swing Projections in North America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20728, https://doi.org/10.5194/egusphere-egu24-20728, 2024.

Desertification is a worldwide issue receiving broad attention due to deforestation, climate change, and land abuse. In India, nearly 81.4 million ha are undergoing the desertification process. A long-term assessment of the key drivers of desertification and land degradation (DLD) was done over the state of Jharkhand in the central highlands of India. The region is highly vulnerable to desertification and land degradation due to its unique geographical and climatic features, with 68.77% (5.48 Mha) of the total geographical area of 7.97 Mha undergoing DLD. This study aims to quantify desertification in Jharkhand using various satellite imageries and supervised classification using machine learning (ML) techniques. The results showed five distinct classes of DLD cases, i.e., severe, intense, moderate, light, and no desertification. The severe and intense class areas make up about 5.11 Mha (64.43%) of the total geographic area (TGA). The moderate and light classes of DLD make up 0.93 Mha (11.79%) and 1.40 Mha (17.73%) of TGA, respectively. Remarkably, the districts of Giridih, Gumla, Ranchi, Dumka, Jamtara, Deoghar, Garhwa, and Palamu are considered to be the most prone regions to DLD. This study will help to demonstrate the application of remote sensing techniques to quantify DLD-prone regions and severity over the regions, which can help policymakers manage the local administrative bodies and state government departments to demarcate the region to continuously monitor and lay policies to tackle desertification.

Keywords: Desertification, Central Highlands, GEE, Random Forest, Vulnerability, Machine Learning

How to cite: Mahato, T. and Kumar, M.: Understanding the Drivers of Desertification and Land Degradation (DLD) over the Central Highlands of India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20795, https://doi.org/10.5194/egusphere-egu24-20795, 2024.

EGU24-82 | ECS | Orals | HS7.5

Proposal for a new meteotsunami intensity index. 

Clare Lewis

Atmospherically generated coastal waves labelled as meteotsunami are known to cause destruction, injury and fatality due to their rapid onset and unexpected nature. These progressive shallow water waves with a period of 2 to 120 minutes tend to be initiated by sudden pressure changes (±1 mb over a few tens of minutes) and wind stress from moving atmospheric systems out on the open water. As these waves arrive at the shoreline they are amplified by localised resonances. Unlike other related coastal hazards such as tsunami, there exists no standardised means of quantifying this phenomenon which is crucial for understanding its impacts and to establish a shared language and framework for meteotsunami analysis and comparison.

In this study, we present a new 5-level Lewis Meteotsunami Intensity Index (LMTI) primarily trialled in the United Kingdom (UK) but designed for global applicability. A comprehensive dataset of meteotsunami events recorded in the UK were verified and applied to the index which yielded results that identified a predominant occurrence of Level 2 or moderate intensity meteotsunamis (69%), with distinct hotspots identified in Southwest England and Scotland. Further trial implementation and calibration of the LMTI in a global capacity revealed its adaptability to other meteotsunami prone regions facilitating the potential for further research into preparedness and hazard mitigation strategies.

How to cite: Lewis, C.: Proposal for a new meteotsunami intensity index., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-82, https://doi.org/10.5194/egusphere-egu24-82, 2024.

EGU24-611 | ECS | Posters virtual | HS7.5

Hydrological Analysis of Monsoon Rain Spells in the Indian Ganga Basin over the Last Century 

Amit Kumar Maurya, Somil Swarnkar, and Shivendra Prakash

The Indian Ganga Basin (IGB) is a highly prominent socioeconomic region in the Indian subcontinent. The IGB supports about 500 million individuals by providing sufficient freshwater for agro-industrial activities, mainly through the contribution of Indian Summer Monsoon (ISM) rainfall, which accounts for around 85% of the total rainfall received throughout the IGB. Any modifications in ISM patterns would substantially impact the availability of freshwater, and consequently, the socio-economic activities of the IGB region will be affected. This study aims to evaluate the historical changes in the monsoon rainfall characteristics from 1901 to 2019. Here, we conducted a detailed rainfall analysis in different sub-basins of the IGB where changes in monsoon rain spells are most noticeable and examined the hydrological extremes. We found that monsoon rain spell peaks have significantly increased across the major sub-basins of the IGB after 1960, implying the increased probability of flash flood hazards. At the same time, the monsoon rain spell has been depleted across the IGB after 1960, especially in the lower Indo-Gangetic plains. These results imply a rise in the occurrence of droughts. In addition, our interpretations also indicate a growing potential for combined hydrological extremes in the IGB. Further, the continuous rise in temperature and human-induced perturbations might exacerbate the existing extreme hydrological conditions. Thus, the findings of this study will be beneficial in implementing river basin management methods to assess the complex patterns of major hydrological catastrophes in the IGB.

How to cite: Maurya, A. K., Swarnkar, S., and Prakash, S.: Hydrological Analysis of Monsoon Rain Spells in the Indian Ganga Basin over the Last Century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-611, https://doi.org/10.5194/egusphere-egu24-611, 2024.

EGU24-669 | ECS | Orals | HS7.5

Assessing Local Community Vulnerability to Landslides and Floods: A Household Survey Approach in North-Western Rwanda  

Clemence Idukunda, Caroline Michellier, Emmanuel Twarabamenye, Florence De Longueville, and Sabine Henry

North-Western Rwanda's hilly and mountainous topography, high elevation, frequent torrential rainfall, and high population density render it highly susceptible to landslides and floods. A comprehensive understanding of community vulnerability to these hazards is crucial for effective risk assessment and mitigation strategies. To address data scarcity in the region, this study is based on a household survey approach that incorporates hazard-specific variables to compare vulnerability across three hazard categories: landslides, floods, and a combination of both. The survey encompasses 904 households across 50 cells (local administrative units), purposively selected according to hazard susceptibility distribution. Principal Component Analysis (PCA) was applied to derive a contextualized Social Vulnerability Index (SoVI). Five principal components accounting for 73.2% of the variance were identified. The first component, contributing 23.4%, highlights the vulnerability associated with unplanned settlements and low income. The second component, representing 19.5% of the variance, emphasizes demographic and social factors. The third component (12.6% of the variance) points to the vulnerability of households solely reliant on agriculture for their income. The fourth component (9% variance) is associated with land ownership, with households lacking land assets experiencing lower vulnerability. The fifth component (8.7% variance) underlines the relevance of household structure variables, indicating the high vulnerability of single-person households. SoVI scores classified 19 cells in the very high or high vulnerability category, predominantly those prone to landslides. These highly vulnerable cells are concentrated in the Northern Province, emphasizing the need to prioritize interventions in this region, such as effective land use planning and livelihood improvement strategies. This study provides a comprehensive vulnerability assessment and valuable insights for prioritizing interventions. The inclusion of hazard-specific variables and a comparative vulnerability approach across areas susceptible to landslides, floods, and both hazard types enhances the specificity and applicability of the findings. These insights are invaluable for local policymakers and disaster prevention and management authorities, enabling them to develop context-specific strategies to improve community resilience and reduce vulnerability to natural hazards.

Keywords: Community Vulnerability, Landslides, Floods, Noth-Western Rwanda, Social Vulnerability Index

How to cite: Idukunda, C., Michellier, C., Twarabamenye, E., De Longueville, F., and Henry, S.: Assessing Local Community Vulnerability to Landslides and Floods: A Household Survey Approach in North-Western Rwanda , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-669, https://doi.org/10.5194/egusphere-egu24-669, 2024.

EGU24-677 | ECS | Orals | HS7.5 | Highlight

A new climate impact database using generative AI 

Ni Li, Wim Thiery, Jakob Zscheischler, Gabriele Messori, Liane Guillou, Joakim Nivre, Olof Görnerup, Seppe Lampe, Clare Flynn, Mariana Madruga de Brito, and Aglae Jezequel

Storms, heat waves, wildfires, floods, and other extreme weather climate-related disasters pose a significant threat to society and ecosystems, which in many cases is being aggravated by climate change. Understanding and quantifying the impacts of extreme weather climate events is thus a crucial scientific and societal challenge. Disaster databases are extremely useful for establishing the link between climate events and socio-economic impacts. However, publicly available data on impacts is generally scarce. Apart from existing open disaster databases such as EM-DAT, robust data on the impacts of climate extremes can also be found in textual documents, such as newspapers, reports and Wikipedia articles. Here we present a new climate impact database that has been built based on multiple public textual entries using a pipeline of data cleaning, key information extraction and validation. In particular, we constructed the database by using the state-of-the-art generative artificial intelligence language models GPT4, Llama2 and other advanced natural language processing techniques. We note that our dataset contains more records in the early time period of 1900-1960 and in specific areas such as than the benchmark database EM-DAT. Our research highlights the opportunities of natural language processing to collect data on climate impacts, which can complement existing open impact datasets to provide a more robust information on the impacts of weather and climate events.

How to cite: Li, N., Thiery, W., Zscheischler, J., Messori, G., Guillou, L., Nivre, J., Görnerup, O., Lampe, S., Flynn, C., Madruga de Brito, M., and Jezequel, A.: A new climate impact database using generative AI, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-677, https://doi.org/10.5194/egusphere-egu24-677, 2024.

Climate change, an increasing urban population, and poor urban planning have increased flood-risk and the accompanying solid waste challenge in many coastal urban areas in developing countries. These challenges are more pronounced in informal settlements because: (a) they are often built on environmentally fragile locations such as river banks and coastal shores with high exposure to floods, (b) high poverty levels among residents resulting in low adaptive capacity, and (c) marginalisation of these localities emanating from their non-recognition in the larger city framework. Against this background, flood-risk assessments and response initiatives in these areas have primarily been informed by scientific approaches such as geographical information systems, without adequate incorporation of other forms of knowledge. Using the case of the coastal city of Durban, South Africa, our project explores the benefits of combining perspectives from different knowledge systems in understanding flood-risk and the accompanying solid waste challenge in urban informal settlements, towards developing solutions that are based on contextual and experiential aspects. Methodological techniques used include interviews and workshops with key experts and with informal settlement residents, and extensive reviews of literature.  Emerging findings show that holders of scientific, practitioner, and local knowledge vis-à-vis flood risk and waste management are active in the selected case study informal settlement. They have, in isolated cases, collaborated particularly around a) generation and distribution of flood early warnings, b) river clean-up initiatives, and c) catchment rehabilitation projects, with clear benefits for flood resilience and solid waste management. We find that there is need for a clear framework for integrating knowledge systems towards flood resilience and solid waste management in these contexts and the project has developed a draft framework. Integrating knowledge systems will: i) ensure the participation of different actors in mapping flood risk thereby creating a sense of ownership and ensuring uptake of and support for solutions crafted to deal with flood risk and the solid waste challenge; and ii) open up opportunities for coordinated support from various actors for a range of decisions around flood risk response preparation, flood and waste infrastructural design and mitigation of waste-induced flood destruction of infrastructure.

How to cite: Johnson, K. and Nyamwanza, A.: Integrated knowledge systems towards flood resilience and sustainable solid waste management in South African urban informal settlements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-867, https://doi.org/10.5194/egusphere-egu24-867, 2024.

EGU24-2163 | ECS | Posters on site | HS7.5

Climate risk-reduction potential of gridded precipitation data for agricultural index-based insurance development 

Sarvarbek Eltazarov, Ihtiyor Bobojonov, and Lena Kuhn

Index insurance has been introduced as an innovative and potential solution to mitigate several challenges caused by climate change in the agricultural sector. Despite the promising potential of index insurance, dissemination in developing countries is slow due to a lack of reliable weather data, which is essential for the design and operation of index insurance products. The increasing availability of model- and satellite-based data could ease the constraints of data access. However, their accuracy and suitability have to undergo a thorough assessment. Therefore, this study statistically and financially analyzes and compares the risk reduction potential of index insurance products designed employing various in-situ-, model- and satellite-based precipitation products (e.g., CMOPH, CPC, IMERG, GSMaP, MERRA, GLDAS, ERA5, PERSIANN, MSWEP, and MERRA2). This study employed county-level spring wheat yield data between 1982 and 2018 from 56 counties overall in Kazakhstan and Mongolia. The results showed that in the majority of cases in both countries, the hedging effectiveness of index insurance products designed based on IMERG is the highest. Moreover, among other data sources, the index insurance products designed using the PERSIANN, GLDAS and FLDAS showed higher risk reduction potential. Overall, this study highlights that satellite- and model-based precipitation products have higher accuracy and potential for index insurance design and operation than in-situ-based precipitation data.

How to cite: Eltazarov, S., Bobojonov, I., and Kuhn, L.: Climate risk-reduction potential of gridded precipitation data for agricultural index-based insurance development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2163, https://doi.org/10.5194/egusphere-egu24-2163, 2024.

A severe and complex, polygenetic flood event occurred in Muktinath area of Mustang, Nepal on the evening of August 13, 2023 causing significant damage to property and infra-structures worth approximately of USD 7.4 million at Kagbeni Village, which is nestled along both banks of Kagkhola, a major left bank tributary of the Kali Gandaki River. About 29 houses, 1 motorable bridge, 1 steel truss bridge and 3 temporary bridges were destroyed, while more than 25 cows and other livestock were killed. Fortunately, human lives were spared because the community was warned to move to safety before the mud and sludge hit the village. A study was conducted in order to know what had caused this unusual flash-flood in Mustang. Kagbeni (2810 m) lies in the north Himalayan, rain-shadow area and normally receives few rainfall (<300 mm/yr). However, for several years, the trend (confirmed by local residents) has been towards increased rainfall, leading to more landslides and floods. Although rainfall data from the nearest monitoring station, Jomsom (2720 m), shows that rainfall was high, there is not detailed information about the rainfall amount at Jhong (3600 m), and Muktinath  (3760 m), source area of Kagbeni flood. From the video taken there (Jhong, Muktinath) during this flash-flood event (hyper-concentrated flow), it can be concluded that it was a landslide lake outburst flood. However due to the difficult terrain and inaccessible path, it has not yet been possible to visit the source area of the landslide in detail. Heavy rainfall over a short period and flash-flood-like disasters are becoming a trend in the mountain regions in Nepal. Furthermore, this part of Mustang is fragile (Spiti shales), and heavy rainfalls have an immediate impact, since there is little soil to absorb the excess water. Former studies have also shown that temperature in Mustang is rising which is causing the monsoon air to move northward and upward. As a result, more rainfall is taking place in Trans-Himalayan areas like Mustang and Manang (North of Annapurna Himal, 8091 m). Therefore, it is believed that climate change and the rise in temperature could be the significant reasons for heavy rainfall that caused such a flash-flood in Kagbeni, Mustang. On the other hand, people are inviting disaster in Kagbeni by settling on the very low terraces or in flood-plains and encroaching on the bed of the local Kagkhola. Given the fragile geology of upstream area of Kagkhola, ongoing anthropogenic activities (agriculture and tourism) and the effect of climate change, the possibility of flash floods reoccurring in the future at Kagbeni remains high. Sadly, locals at Kagbeni have already started rebuilding houses damaged by the recent Kagbeni flood and continue to live in potentially threatened flood plains.   

How to cite: Fort, M., Gurung, N., Arnaud-Fassetta, G., and Bell, R.: Retrospect of the polygenetic Kagbeni flood event (August 13, 2023) in Mustang, Nepal. Are rapid hydromorphological processes relays and sediment cascades in the catchment well taken into account in the risk equation?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2563, https://doi.org/10.5194/egusphere-egu24-2563, 2024.

EGU24-3076 | ECS | Orals | HS7.5

Assessing Surface Drainage Efficiency in Urban Pluvial Flood Hazard and Risk Mitigation: A Case Study of Braunschweig City 

Shahin Khosh Bin Ghomash, Heiko Apel, Kai Schroeter, and Max Steinhausen

Due to rapid urbanization and the increase of extreme precipitation events driven by climate change, urban areas have experienced more frequent and severe pluvial floods in recent years. This trend is anticipated to continue in the future. One of the causes of flooding in these urban zones is the limited effectiveness or temporary reduction in surface drainage capacity, even when storm sewers adhere to technical standards. A notable instance was the June 2023 flooding in Braunschweig, situated in Lower Saxony, Germany, where the city received 60 liters per square meter of rainfall within a short time span, largely excessing sewer system capacity and leading to widespread inundation.

This research investigates the impact of implementing diverse strategies aimed at expanding urban drainage capacity to mitigate pluvial flood risk in Braunschweig. To accomplish this, a moderately detailed hydrodynamic model for the city was set up using the RIM2D hydrodynamic model, allowing for quick computational processing times which enabled the exploration of various measures through sensitivity analysis. The setup involved employing a high-resolution digital elevation model and various remote sensing data for land classification. The model incorporated high-resolution precipitation radar data from the 2023 event and additional precipitation scenarios of varying occurrence probabilities. Validation of the model against available event data and existing flood hazard maps specific to Braunschweig was conducted.

The validated model was then utilized to assess the effectiveness of different surface de-sealing scenarios within the city. These scenarios aim to enhance drainage capacity by means of increased infiltration to complement the existing sewer drainage system. The evaluation of these de-sealing scenarios focused on reducing surface inundation and anticipated damage, serving as a foundational aspect for conducting a cost-benefit analysis and detailed planning. This analysis can contribute to future-oriented urban pluvial flood risk management plans for the city.

How to cite: Khosh Bin Ghomash, S., Apel, H., Schroeter, K., and Steinhausen, M.: Assessing Surface Drainage Efficiency in Urban Pluvial Flood Hazard and Risk Mitigation: A Case Study of Braunschweig City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3076, https://doi.org/10.5194/egusphere-egu24-3076, 2024.

EGU24-3170 | ECS | Orals | HS7.5

Influences of moisture transport on changes in extreme precipitation in Central Plains Urban Agglomeration, China  

Yufan Chen, Shuyu Zhang, Deliang Chen, and Junguo Liu

In recent decades, the Central Plains Urban Agglomeration of China (CPUA) has faced recurring extreme precipitation events (EPEs), causing severe flood disasters, endangering residents, and inducing significant property losses. This study examines the spatiotemporal patterns of summer EPEs in the CPUA from 1961 to 2022. The Hybrid Single-Particle Lagrangian Integrated Trajectory model was used to trace the water vapor trajectories associated with these events and the atmospheric circulations linked to diverse moisture transports were identified. The findings reveal an overall increase in both the intensity and frequency of summer EPEs, particularly intensifying over urban areas while displaying more frequent yet weaker precipitation in mountainous regions. Moisture contributing to these events originates from sources including Eurasia, the northern and southern Western North Pacific, as well as the Bay of Bengal and South China Sea. Notably, contributions from Eurasia and the Northern Western North Pacific have increased, whereas those from the Bay of Bengal and the South China Sea have decreased. Events fueled by Western North Pacific moisture show intensified impacts on urban areas, driven by anomalous anticyclonic patterns and the formation of the Huang-Huai cyclone, inducing vigorous convective activity over the CPUA. The proliferation of the Western North Pacific Subtropical High facilitates warm air transport, converging with colder air from inland areas, resulting in extreme precipitation.

How to cite: Chen, Y., Zhang, S., Chen, D., and Liu, J.: Influences of moisture transport on changes in extreme precipitation in Central Plains Urban Agglomeration, China , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3170, https://doi.org/10.5194/egusphere-egu24-3170, 2024.

EGU24-3602 | ECS | Posters on site | HS7.5

FLOODGAMA: the new INUNGAMA. Beyond a flood events database for Catalonia 

Montserrat Llasat-Botija, Maria Carmen Llasat, Dimitri Marinelli, Raül Marcos, Carlo Guzzon, and Albert Díaz

Floods represent a complex natural hazard, influenced not only by meteorological factors but also by geophysical aspects such as terrain topography, social factors such as the value of exposed assets, and cultural factors like risk awareness. For this reason, the study of these phenomena requires a holistic approach. This requires the correct organization of the information. In addition, given that the information comes from different sources, the traceability of the data must also be contrasted and preserved in order to guarantee its quality and robustness. Databases make it possible to conserve and document historical information, to analyze it and to support smart flood risk management.

With this objective in mind, in 2000 the GAMA team developed the INUNGAMA flood database, following the example of other natural hazards databases. This communication will present the new version of this database, FLOODGAMA, and the main results of its analysis. FLOODGAMA contains information on 456 flood events that affected Catalonia (NE of Spain), between 1900 and 2020, which have caused 1,253 casualties. The events are classified according to the impacts. It includes linked tables with information on event dates, descriptions, fatalities, economic damages, affected municipalities, recorded rainfall and recorded flow. Other tables contain historical marks, codifications and the geographical information of municipalities, counties, basins and rivers, as well as meteorological stations. Its structure has been simplified and standardized with Python and migrated to PostgreSQL (PostGIS) from an ACCESS format. The new database allows for more general and straightforward analysis, introduces GIS tool compatibility, and simplifies the addition of new data and new data sources. This last point has been one of the key points in this transformation as it will provide the database with the flexibility to respond to the challenges posed by the digital transformation that is currently taking place and as a tool for the improvement of adaptation.

The contribution shows the structure of this flood database and the results obtained after its analysis that allows the characterization of flood events in Catalonia.

This research has been done in the framework of the C3Riskmed project, Grant PID2020-113638RB-C22 funded by MCIN/AEI/10.13039/501100011033 and Flood2Now project, Grant PLEC2022-009403 funded by MCIN/AEI/10.13039/501100011033 and by the European Union Next Generation EU/PRTR.

How to cite: Llasat-Botija, M., Llasat, M. C., Marinelli, D., Marcos, R., Guzzon, C., and Díaz, A.: FLOODGAMA: the new INUNGAMA. Beyond a flood events database for Catalonia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3602, https://doi.org/10.5194/egusphere-egu24-3602, 2024.

EGU24-3951 | ECS | Orals | HS7.5

Multi-day precipitation extremes ranking and their association with atmospheric moisture fluxes over India 

Tomás Gaspar, Ricardo M. Trigo, Alexandre M. Ramos, Akash Singh Raghuvanshi, Ana Russo, Pedro M.M. Soares, Tiago Ferreira, and Ankit Agarwal

The Indian subcontinent is characterized by a pronounced summer monsoon season with substantial rainfall from June to September and a less intense autumn monsoon, albeit both posing major challenges to the densely populated regions through flash floods and landslides. During monsoons, different regions of India are affected by extreme precipitation events with distinct durations and triggered by several mechanisms. Here, considering 10 different regions of India characterized by different climatic regimes, we apply an objective ranking of extreme precipitation events, across various time scales, ranging from 1 to 10 days, making use of a high-resolution daily precipitation dataset covering the entire Indian territory from 1951 to 2022. The results confirm that the method accurately detects and ranks the most extreme precipitation events in each region, providing information on the daily evolution of the magnitude (and spatial extent affected) of high precipitation values in each region. Moreover, results show that top rank events can be associated with different types of storms affecting the four main coastal regions of India. In particular, some top rank events can be critically linked to long duration events (e.g., 10 days), which can be missed in ranks for shorter duration (e.g., 1-3 days) periods, thus stressing the need to employ multi-day precipitation extremes ranking. Finally, an in-depth analysis of the large-scale atmospheric circulation and moisture transport is presented for the top 10-day events affecting four coastal regions of India. Overall, we are confident that our findings are valuable in advancing disaster risk reduction strategies, optimizing water resource management practices, and formulating climate change adaptation strategies specifically tailored for the Indian subcontinent.

 

R.M.T., A.R., S.P. and A.T.M. thank Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). A.R. and R.M.T. thank also FCT (https://doi.org/10.54499/2022.09185.PTDC, http://doi.org/10.54499/JPIOCEANS/0001/2019, https://doi.org/10.54499/DRI/India/0098/2020). A.R. was supported by FCT through https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006.

 

How to cite: Gaspar, T., M. Trigo, R., M. Ramos, A., Singh Raghuvanshi, A., Russo, A., M.M. Soares, P., Ferreira, T., and Agarwal, A.: Multi-day precipitation extremes ranking and their association with atmospheric moisture fluxes over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3951, https://doi.org/10.5194/egusphere-egu24-3951, 2024.

EGU24-5587 | ECS | Orals | HS7.5

Socio-Economic Vulnerability assessment and validation in Seoul, South Korea  

Chi Vuong Tai, Dongkyun Kim, Soohyun Kim, Yongchan Kim, Hyojeong Choi, and Jeonghun Lee

Vulnerability is regarded as a crucial element in disaster risk reduction, garnering increasing attention from researchers. However, these assessments typically conclude with the spatial representation and analysis of vulnerability index values, with very few attempts made on vulnerability validation. This study has employed Principal Component Analysis (PCA) algorithm for the entire 38 selected socio-economic features, resulting in 9 principal components (or factors) to estimate Socio-Economic Vulnerability Index (SEVI). The results reveal consistent vulnerability levels in over half of the dongs (administrative units), compared with SEVI estimated from a subjective weighting scheme based on expert experience. Meanwhile, the remaining dongs exhibit a change in only one level of vulnerability. SEVI values and ranks from PCA were subsequently internally validated through global uncertainty and sensitivity analyses using Monte Carlo method. The vulnerability scores of all input features were randomly generated based on their fitted probability distribution functions, serving as input parameters for 39,936 Monte Carlo simulations. The median statistic was employed to evaluate the vulnerability uncertainty based on both bias of estimated SEVI values and ranks in comparison with simulated data. The findings from this analysis revealed that medium-low and medium vulnerability levels tend to be underestimated, while medium-high and high levels primarily witness an overestimation tendency. The bias in SEVI ranks was further employed to assess the vulnerability uncertainty. In the sensitivity test, a tornado diagram was created to illustrate the explanation of each feature to the overall SEVI variability. The results indicate that the feature with highest explanation of SEVI variability is the number of families with only children and a mother, accounting for more than 5%. The methodology employed in this study is applicable to areas with limited social and economic data sources. Based on our findings, we suggest that the areas with low bias on SEVI values or ranks are reliable for developing disaster risk mitigation strategies, while other areas require further consideration. Additionally, the results from the sensitivity test provide valuable support for future research when selecting input features for socio-economic vulnerability assessment.

Acknowledgement:

This study was supported by: (1) The National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1A4A3032838) (50 % grant); (2) Korea Environment Industry & Technology Institute (KEITI) through R&D Program for Innovative Flood Protection Technologies against Climate Crisis Project, funded by Korea Ministry of Environment (MOE) (RS-2023-00218873) (50 % grant).

How to cite: Vuong Tai, C., Kim, D., Kim, S., Kim, Y., Choi, H., and Lee, J.: Socio-Economic Vulnerability assessment and validation in Seoul, South Korea , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5587, https://doi.org/10.5194/egusphere-egu24-5587, 2024.

EGU24-5774 | Orals | HS7.5

myDewetra-VOLTALARM: a transboundary impact-based early warning system increasing resilience of Volta basin communities against hydrometeorological hazards 

Anna Mapelli, Andrea Libertino, Giulia Ercolani, Mirko D'Andrea, Nicola Testa, Matteo Darienzo, Simone Gabellani, Marco Massabò, Rafatou Fofana, Salifou Dene, Boukary Niampa, Maxime Teblekou, and Ramesh Tripathi and the Voltalarm member states national agencies

The Volta Basin, spanning six countries in West Africa, faces significant challenges from both floods and extreme precipitation. To address these challenges, the myDewetra-VOLTALARM system was developed as a collaborative transboundary early warning system (EWS) through the joint efforts of an international Consortium, composed by the Volta Basin Authority (VBA), the Global Water Partnership for West Africa (GWP-WA) and the World Meteorological Organization (WMO), and national institutions of the six riparian countries.  

myDewetra-VOLTALARM embraces an impact-based forecasting approach, focusing on the potential consequences of severe hydrological events on vulnerable communities. This is achieved through state-of-the-art hydro-meteorological modelling chain generating precipitation and discharge forecast with lead times of up to five days, coupled with impact assessment tools that translate these forecasts into actionable warnings based on real-time risk information for sectors like civil protection, agriculture and livelihoods, protected areas. By focusing on potential impacts,  myDewetra-VOLTALARM empowers stakeholders to make risk-informed decisions and implement timely mitigation actions, thereby reducing vulnerabilities and enhancing community resilience. The strength of myDewetra-VOLTALARM hinges on the collaboration, built-up through the implementation process, among the riparian countries, fostering data exchange and enabling a comprehensive understanding of hydrological dynamics across the entire basin. Harmonized risk assessments lead to consistent warning products and mitigation strategies, while the publication of the results on the open-source  myDewetra-VOLTALARM platform ensures transparency and accessibility for all stakeholders. 

A cornerstone of myDewetra-VOLTALARM's impact is the co-produced flood and heavy rainfall impact bulletin, issued jointly by national and regional authorities twice per week. This bulletin provides critical information, enriching and validating the model results with the expertise and local information/measurements of the national institutions, on which the Volta Basin Authority bases its advisories, tailored to specific locations and sectors. The Flood and Heavy Rainfall Impact Bulletin ensures a consistent flow of information at the basin scale and it integrates in the existing national procedures for early warning and civil protection, allowing all the stakeholders to stay informed and adapt their preparedness measures as the hydrometeorological situation evolves. 

myDewetra-VOLTALARM serves as a model for effective early warning systems in shared river basins. Its impact-based forecasting, transboundary cooperation, and co-produced Flood and Heavy Rainfall Impact Bulletin hold the potential to significantly reduce the impacts of floods and extreme precipitation, contributing to a more resilient and sustainable future for the Volta Basin communities.

How to cite: Mapelli, A., Libertino, A., Ercolani, G., D'Andrea, M., Testa, N., Darienzo, M., Gabellani, S., Massabò, M., Fofana, R., Dene, S., Niampa, B., Teblekou, M., and Tripathi, R. and the Voltalarm member states national agencies: myDewetra-VOLTALARM: a transboundary impact-based early warning system increasing resilience of Volta basin communities against hydrometeorological hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5774, https://doi.org/10.5194/egusphere-egu24-5774, 2024.

EGU24-6088 | ECS | Posters on site | HS7.5

Modelling and Prediction of Unprecedented Heavy Rainfall Event Over North India  

Rohtash Saini and Raju Attada

Widespread and multi-day heavy rainfall events, recorded during 08-09 July 2023 in northwest India, significantly impacted Himachal Pradesh, Punjab, and the Chandigarh region. These events resulted in devastating floods and extensive landslides, causing a substantial loss of lives and properties. Understanding such extreme weather phenomena is imperative for enhancing predictive capabilities and mitigating associated impacts. However, due to the complex topography of the Himalayas and limited observational data, poses challenges for investigating precipitation extremes. Against the background, in this study, we employ the Weather Research and Forecasting (WRF) model to investigate the atmospheric processes that led to unprecedented extreme precipitation. The innermost domain is configured with a horizontal grid spacing of 3 km, successfully reproduces the observed extreme rainfall. To assess the performance of different microphysics schemes in capturing key characteristics associated with heavy rainfall events, sensitivity experiments were conducted with five distinct schemes. Preliminary findings reveal that the Goddard microphysics scheme demonstrates good agreement with observations, closely followed by the Thompson scheme. Statistical analyses, including skill scores, further suggest that the Goddard microphysics scheme skillfully simulates the observed rainfall, displaying robust reflectivity values exceeding 35 dBZ in the core regions. The strong reflectivity indicates substantial hydrometeor concentrations, suggesting potential locations of deep convective activity associated with heavy rainfall. Detailed results of simulating the rainfall extremes over northwest India, along with feasible mechanisms influencing atmospheric conditions during extreme will be comprehensively discussed.

How to cite: Saini, R. and Attada, R.: Modelling and Prediction of Unprecedented Heavy Rainfall Event Over North India , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6088, https://doi.org/10.5194/egusphere-egu24-6088, 2024.

EGU24-6148 | ECS | Posters on site | HS7.5

Functionality assessment of road network combining flood roadworthiness and graph topology 

Ke He, Maria Pregnolato, Neil Carhart, Jeffrey Neal, and Raffaele De Risi

In the realm of critical infrastructure, the road network plays an indispensable role in facilitating daily activities, communication, and economic interactions. However, it remains susceptible to the persistent challenge of flood hazards, leading to both structural and non-structural damages (e.g., physical collapse and service interruption). In normal flood disasters, physical collapse may not occur, but service interruptions often occur. Such disruptions manifest in the form of increased travel distances, prolong the travel times, and, in severe cases, complete travel impossibility. This has resulted in a reduction in transportation efficiency, leading to an increase in the social cost of transportation.

This study presents a novel approach that integrated flood hazard, transportation network topology, and vehicle vulnerability to evaluate the functionality of road network. A severity factor is defined to assess the accessibility of expected links (roads and bridges), considering different vehicle types such as cars and SUVs. Then, this study analyses the overall road network functionality loss under varying flood return periods by evaluating the severity of each network link based on the different types of vehicles. Identification of links with the lowest functionality allows for the assessment of the entire network’s performance using topology-based measures, including the average node degree, average clustering, average shortest path, and reachable areas (isochrones). This research employs the transportation network of Bristol, UK, as a case study to investigate the dynamic relationship between the network status and vehicle typology in the context of flooding events. Findings reveal a discernible correlation, wherein the resilience of the network in influenced by the specific characteristics of different vehicle types. Notably, SUVs emerge as inherently more resistant to flood-related disruptions compared to conventional cars.

The insights presented in this paper hold significant implications for the development of robust mitigation strategies geared towards bolstering the resilience of road networks and optimizing the rerouting of emergency response vehicles in flood-prone areas. By elucidating the interplay between vehicle characteristics, network functionality, and flood impacts, the research provides a foundation for informed decision-making in the formulation and implementation of effective preparedness measures. The outcomes of this study offer a strategic roadmap for authorities and policymakers, enabling them to proactively address the challenges posed by future flood events and enhance the overall adaptability and responsiveness of road networks in emergency situations.

How to cite: He, K., Pregnolato, M., Carhart, N., Neal, J., and De Risi, R.: Functionality assessment of road network combining flood roadworthiness and graph topology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6148, https://doi.org/10.5194/egusphere-egu24-6148, 2024.

EGU24-7026 | ECS | Orals | HS7.5

Characteristics of Disaster-causing Heavy Rainfall in Taipei City and Its Application 

Chi-June Jung, Radiant Rong-Guang Hsiu, Yu-Cheng Kao, Mon-Liang Chiang, Wen-Bin Hung, Jing-Ting Wang, and Ben Jong-Dao Jou

The most challenging weather phenomenon for disaster response in Taipei City is localized short-duration heavy rainfall. The capacity of each administrative district to withstand rainfall intensity varies, leading to incidents of flooding even when the rainfall falls short of the designed protection standard of 78.8 mm/h for drainage systems. To enhance disaster response, the Taipei City Fire Department conducts investigations and reports based on rainfall conditions. By integrating the intelligence and reporting system and raising the dispatching standard from 20 to 40 mm/h, the "Heavy Rainfall Response Process Improvement" project has successfully reduced response operation time and alleviated service burdens, advocating for adopting higher standards.

This study explores the correlation between intense rainfall and disaster occurrences, examining thunderstorm events that caused significant flooding in over three administrative districts. The study compares the earliest reported flooding time in each district with the corresponding rainfall, revealing that several districts experienced flooding with less than 60 mm/h of rainfall at the onset, indicating heightened vulnerability. Additionally, the study delves into the relationship between rainfall patterns and disaster potentials. When it accumulates 40 mm of rainfall within 30 minutes, there is a 63% chance of reaching 60 mm accumulation in the following 10 to 20 minutes. This analysis underscores the potential application of cumulative rainfall within the first 30 minutes for predicting subsequent rainfall trends and issuing disaster warnings.

How to cite: Jung, C.-J., Hsiu, R. R.-G., Kao, Y.-C., Chiang, M.-L., Hung, W.-B., Wang, J.-T., and Jou, B. J.-D.: Characteristics of Disaster-causing Heavy Rainfall in Taipei City and Its Application, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7026, https://doi.org/10.5194/egusphere-egu24-7026, 2024.

EGU24-7347 | Posters on site | HS7.5

Impacts comparison by using different hydraulic models on the 2011 flood in Thailand 

Morgane Terrier and Mathis Joffrain

The 2011 flood event in Thailand was devastating both in terms of lives and economic losses. Following this event, the (re)insurance industry have deeply transformed its underwriting practices and used new modeling tools, both external and internal.

A loss is linked both to hazard and sites characteristics. As an insurer's exposure changes, losses for the same event can differ greatly from past observations. Therefore, hazard maps representing a past event can be used to estimate losses as of today.

Building an internal flood risk model requires to create a large set of spatial grids of flood depth. The water depth spatialisation, based on the water level of identified rivers, is a crucial part of the modeling and called the hydraulic modeling.

This poster will :

(i) the use of two hydraulic models to obtain a flood footprint: The software Super-Fast Inundation of CoastS (SFINCS) (Leijnse et al., 2021), a 2D open-source fast numerical model, and LISFLOOD-FP (Bates, 2004).

(ii) calculate insured losses on a fictive portfolio in Thailand using these two models with the same inputs.

(iii) describe and explain the discrepancies steming from (ii).

How to cite: Terrier, M. and Joffrain, M.: Impacts comparison by using different hydraulic models on the 2011 flood in Thailand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7347, https://doi.org/10.5194/egusphere-egu24-7347, 2024.

EGU24-7770 | Posters on site | HS7.5

Historical database for multi-hazard zonation and damage trend analysis in a Mediterranean study area (southern Italy) 

Olga Petrucci, Massimo Conforti, Giovanni Cosentini, and Graziella Emanuela Scarcella

The occurrence of extreme hydro-meteorological events is globally on the rise, due to the combined effects of climate change and increasing urban development in vulnerable areas. Each year, landslides, floods, urban flooding, storm surges, snow and thunderstorm events cause casualties, huge damage to urban areas, farmland, and communication infrastructures. This work presents the preliminary results of an historical research aiming to identify the series of geo-hydrological events which affected the municipality of Catanzaro (Calabria, South Italy), having an area of 112.7 km2 and a population density of 746.84 ab./km², throughout the latest two Centuries. The purpose is to implement a GIS-platform using the historical series of past events to realize density maps resulting is a zonation of municipal area which depict the vulnerability of municipal sectors per type of damaging phenomena and type of damaged elements, and their trends throughout the decades. We firstly extracted those events contained in the database named ASICal (Italian acronym of historically flooded areas), a catalogue collecting damaging geo-hydrological events occurred in Calabria in the latest centuries and maintained by CNR-IRPI researchers. Then, to improve and enrich our series, we performed an historical research throughout the documents of the State Archive of Catanzaro. As a total, we gathered data about around 270 events which occurred in the study area between 1830 to 2023, highlighting the strong territorial vulnerability of the selected area. Considering the average number of events per year as a proxy of events impact, we can observe as this value increases during the study period, moving from one event per year (in the period 1900 – 1950) to 3 events per year (in the period 1950 – 2023). To be uploaded in the GIS platform and mapped, the 270 events were split in around 1500 records, according to the kind of damaging phenomena (flood, landslide, urban flooding, storm surges, snow, thunderstorm) and the affected place. 44% of cases were widespread events, while the remaining 56% affected single sites. Urban flooding seems the most frequent damaging phenomena (68% of records), followed by landslides (21%), while the other phenomena show lower frequencies. As far as damaged elements, the most frequently affected were public and private buildings (64%) and road and railway network (26%), while people were affected in a few cases (5%). Data elaboration as multi-hazard maps, also crosschecked to either physical or anthropogenic data can be used to identify hazard-prone areas and to support the multi risk management in terms of monitoring, planning of remedial works, and realization/updating of civil protection plans, as far as in the realization of educational campaigns aiming to raise people awareness.

This work was funded by the Next Generation EU—Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of ‘Innovation Ecosystems’, building ‘Territorial R&D Leaders’ (Directorial Decree n. 2021/3277)—project Tech4You—Technologies for climate change adaptation and quality of life improvement, n. ECS0000009. This work reflects only the authors' views and opinions, neither the Ministry for University and Research nor the European Commission can be considered responsible for them.

How to cite: Petrucci, O., Conforti, M., Cosentini, G., and Scarcella, G. E.: Historical database for multi-hazard zonation and damage trend analysis in a Mediterranean study area (southern Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7770, https://doi.org/10.5194/egusphere-egu24-7770, 2024.

EGU24-8205 | ECS | Posters on site | HS7.5

A Multi-Criteria Analysis procedure for the evaluation and classification of flood risk mitigation strategies 

Alice Gallazzi, Daniela Molinari, Francesco Ballio, Marina Credali, Immacolata Tolone, Simona Muratori, and Panagiotis Asaridis

The study aims to provide the Lombardy Region, the primary stakeholder in the project, with a procedure for evaluating and classifying structural flood risk mitigation measures. The primary objective is to assist the regional authority in identifying priority interventions for public funding. A step-by-step procedure has been developed to assess and rank all projects submitted to the Region, selecting priority projects based on technical considerations—evaluating feasibility, effectiveness, and sustainability of the proposed measures—and the preferences of policymakers. The assessment procedure's conceptual structure was tested using case studies, including both feasibility studies and executive projects, to determine the level of technical insights required at each planning phase of public works. The methodology relies on Multiple Criteria Analysis (MCA) techniques, enabling the simultaneous consideration of various, non-directly comparable criteria in a complex decision-making context. These criteria encompass technical features of proposed works, potential territorial constraints, and interferences in the intervention area (feasibility); the effectiveness of measures in reducing flood risk and associated costs; and the environmental and social co-benefits and disbenefits of each intervention (sustainability). Specific indicators, either ad hoc defined for the study or referenced from current regulations and guidelines at national and regional levels, are employed to evaluate the criteria. Stakeholder participation, particularly from the Region, River District Authorities, and Municipalities, is crucial throughout the process, especially in the final phase of aggregating (weighting) all criteria. This aggregation produces an overall performance score for each option, enabling the derivation of a regional ranking of flood risk mitigation strategies. The collaboration between academia and public institutions is highlighted as essential for enhancing the efficiency of disaster risk reduction policies.

How to cite: Gallazzi, A., Molinari, D., Ballio, F., Credali, M., Tolone, I., Muratori, S., and Asaridis, P.: A Multi-Criteria Analysis procedure for the evaluation and classification of flood risk mitigation strategies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8205, https://doi.org/10.5194/egusphere-egu24-8205, 2024.

Since the 1950s, global irrigated area has expanded dramatically, with complex effects on regional climate worldwide. The North China Plain (NCP) is among the most intensively irrigated regions in the world, but the effects of historical irrigation expansion on climate extremes over multi-decadal timescale are largely uncertain. Combining statistical methods with model simulations, we found that NCP experienced a decreasing trend of 0.2–0.25 ℃ decade−1 (p < 0.1) in daily maximum temperature (Tmax) during May-June of 1961–2000 along with irrigation expansion, which is distinct from other regions experiencing strong warming such as most of western China. The cooling effect on Tmax is 0.092 ℃ decade−1 (p < 0.01), relatively lower than that in California’s Central Valley but comparable to the trend in Northwest China and larger than the trend in Tibetan Plateau. The correlation coefficients between irrigation expansion and temperature change from 1960 to 2000 for Tmax and mean air temperature (Tmean) are –0.58 and –0.33 (p < 0.01), respectively, suggesting the ability of irrigation to alleviate regional warming and temperature extremes. Such effect varies over time, continuously strengthening from 1961 to 1980 because of intensive irrigation expansion, but then remaining relatively unchanged or weakening during 1980–2005 with moderate expansion. After 2005, the cooling effect is not detectable, which implies that it is completely canceled out by other forcings such as greenhouse gas warming, compensation of urban area expansion, small irrigation expansion rate and decline in irrigation water use. Despite that, irrigation is still able to reduce the number of extreme heat days after 1980. Compared with other factors, we found that irrigation expansion is the second most important contributor (27%) to the decrease in Tmax during the study period, after aerosol pollution (54%). This work emphasizes the ability of irrigation expansion to adapt agriculture to climate change over the past decades, and highlights the need for sustainable irrigation expansion in the future.

How to cite: Yuan, T., Tai, A. P. K., and Wu, J.: Irrigation expansion in North China Plain has historically decelerated regional warming and mitigated temperature extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8291, https://doi.org/10.5194/egusphere-egu24-8291, 2024.

The occurrence probability of rare floods is linked to the right-tail behavior of flood frequency distributions. Specifically, heavy-tailed behavior of flood distributions often signals significant hazards due to the unexpected extremeness of event magnitudes. However, conducting reliable analyses of flood tail heaviness across regions remains challenging due to the varying record lengths of available data.

In this study, instead of relying solely on statistical methods to evaluate flood tail behavior, we adopt a physical-based approach—hydrograph recession analysis—to quantify the nonlinearity of catchment hydrological responses. This method has shown its efficacy in identifying heavy-tailed flood behavior across analyses with different data lengths. Our analysis covers 575 river gauges, spanning drainage areas from 4 to 40,504 km2, across Atlantic-influenced European areas, Northwestern European areas, and the Continental United States. We categorize these regions based on the Köppen climate classification to explore the relationship between physiographic/climatic conditions and heavy-tailed flood behavior, and distinguish regional characteristics using the aridity index and potential evapotranspiration.

Our findings reveal a prevalence of heavy-tailed flood propensity in Atlantic-influenced European areas, prevalent nonheavy-tailed flood propensity in Northwestern European areas, and a mixed distribution with a balanced propensity in the Continental United States. Generally, drier catchments exhibit higher nonlinearity in hydrological responses, facilitating heavy-tailed floods, while catchments in which snow dynamics dominate the flood generation process tend to present linear responses. Excessively dry catchments, however, are less likely to exhibit heavy-tail floods due to insufficient moisture. Moreover, around one-third of catchments display varying tail behavior across seasons, underscoring the potential underestimation of flood tail heaviness in annual analyses. The seasonality of flood tail behavior—where instances of heavy-tailed flood behavior increase from spring to autumn but decrease in winter—is influenced by the seasonal variation of potential evapotranspiration.

Our study contributes to advancing the understanding of the impact of inherent physiographic and climatic features on regional and seasonal patterns of heavy-tailed flood behavior, providing valuable insights into the emergence of a considerable occurrence probability associated with very large magnitudes of rare floods.

How to cite: Wang, H.-J., Merz, R., and Basso, S.: Physiographic and Climatic Controls on Heavy-Tailed Flood Behavior: Insights from Catchment Nonlinear Responses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8389, https://doi.org/10.5194/egusphere-egu24-8389, 2024.

EGU24-8531 | Orals | HS7.5

Appraising and reducing riverine flood risk: a case study from Central Italy 

Francesco Dottori, Matteo Darienzo, Giacomo Fagugli, Simone Gabellani, Tatiana Ghizzoni, Daria Ottonelli, Flavio Pignone, and Eva Trasforini

On 15 September 2022 a catastrophic flood event hit the Misa river basin in Central Italy. The magnitude of the event (intensity of precipitation, water discharge, debris and sediment transport) and the subsequent impacts were far more severe and extended than previous flood events in the same area, thus calling for a radical change in current practices of flood risk management. In this framework, the present study aims at 1) providing a comprehensive assessment of flood risk for the Misa river basin, and 2) designing appropriate risk reduction measures at river basin scale. We reconstructed the September 2022 event by integrating in-field surveys, hydrological data, hydraulic models, observations of the event (e.g. flood extent maps) and historical data of past flood events, taking into account the incompleteness and uncertainty of both models and observations. Moreover, we modelled exposure and vulnerability of population and economic activities in the area, using detailed surveys of observed impacts to inform the model set-up. The outcomes of these activities allowed to review the risk analysis tools currently available in the Misa river basin, and to design updated risk scenarios for present and future climate conditions. Finally, the risk scenarios have been used to explore different alternatives for flood risk reduction, in agreement with local authorities and stakeholders. We evaluated a range of structural measures (strengthening of dike systems, detention areas, river diversions) and non-structural measures (land-use planning, relocation, flood-proofing measures), considering existing risk management plans and new analyses carried out in this study (e.g. cost effectiveness of measures).

How to cite: Dottori, F., Darienzo, M., Fagugli, G., Gabellani, S., Ghizzoni, T., Ottonelli, D., Pignone, F., and Trasforini, E.: Appraising and reducing riverine flood risk: a case study from Central Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8531, https://doi.org/10.5194/egusphere-egu24-8531, 2024.

EGU24-8564 | Orals | HS7.5

High-Resolution Dynamic Flood Susceptibility Mapping Across the Mediterranean Region 

Hamidreza Mosaffa and Luca Brocca

Effective disaster prevention necessitates the production of high-resolution flood susceptibility maps (FSM) that accurately identify potential flood-prone areas. Conventional FSMs, however, provide static representations that overlook the inherent dynamicity of flood susceptibility, which is influenced by temporal variations, precipitation intensities, and other factors. Additionally, traditional FSMs often lack the high-resolution climate data required for precise risk assessment. To address these limitations, we propose a novel dynamic FSM approach that incorporates temporal variations and high-resolution climate data.

Our approach employs the Random Forest machine learning algorithm, trained on a comprehensive dataset of flooded and non-flooded areas (Global Flood Database v1). The algorithm considers seven critical factors influencing flooding events: elevation, slope, land cover, proximity to rivers, drainage density, soil moisture, and precipitation. This approach enables the generation of high-resolution (1 km) dynamic FSMs for the Mediterranean region, under varying seasonal conditions, precipitation intensities, and post-drought scenarios.

To assess and compare the model's performance, we employed both training and testing datasets, conducting evaluations using various metrics. The study results demonstrate the superior performance of the Random Forest model, establishing its efficacy as a robust tool for mapping dynamic flood susceptibility. The accuracy and reliability of the results obtained through this approach offer crucial insights for mitigating flood-related risks and enhancing disaster management strategies. This study is an integral part of the Open-Earth-Monitor Cyberinfrastructure (OEMC) project. As our next step, we aim to expand the application of our dynamic flood susceptibility mapping methodology to cover the European region.

How to cite: Mosaffa, H. and Brocca, L.: High-Resolution Dynamic Flood Susceptibility Mapping Across the Mediterranean Region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8564, https://doi.org/10.5194/egusphere-egu24-8564, 2024.

Floods impact natural and human systems from multiple dimensions. The vulnerability to flood consequences is intricately linked to the hydrogeomorphic and socio-economic properties of the region. In a long run flood control infrastructure such as embankments evolve with the hydrogeomorphic and socio-economic properties and co produce the new set of vulnerabilities. Assessment of maladaptive contribution of flood control infrastructure is crucial in adaptive decision making and building resilience.The study analyzed flood vulnerability of the population residing inside the embankment area of the Kosi River basin from multidisciplinary parameters. The Kosi River embankment area covers around 890 Sq Km area and is home to nearly 0.8 million people who are facing a trifecta of issues, including regular flooding, scarcity of basic amenities, and loss of livelihood. The basin went through numerous flood-related research based on geomorphology, hydrology, and other physical factors; however, the flood impact assessment of embankments and its role within the socioeconomic dimension still needs to be explored. The present study unpacks flood vulnerability in 283 villages located within the Kosi embankment. Drawing upon thirteen attributes—comprising eight socio-economic and five hydro-geomorphic parameters—the analysis incorporates data from Sentinel-2, IMD, FMIS, the 2011 census report, and other pertinent survey reports. The study utilized analytical hierarchical process (AHP) to obtain relative priority order of parameters. Through the application of GIS analysis, we systematically formulated exhaustive vulnerability maps encapsulating socio-economic, hydrogeomorphic, and composite dimensions based on the weightage assigned to the selected parameters. The analysis highlights that nearly the entire population in the embankment region is susceptible to the effects of flooding, with ∼66% of the region having high and very high flood risk and ∼26% in areas with moderate risk. Furthermore, the outcomes reveal the maladaptive consequences of infrastructure solutions, manifesting as socio-economic disparities and exclusionary effects. The population living inside the embankment region exhibit notably impoverished socio-economic characteristics,including 32 % female literacy, approximately 90 houses constructed by  around 90 percent of houses are Kachha ( mud house), and highly rely on farm labor activities, which is highly lower than the region outside the embankment. Additionally, the outcomes bring to light the maladaptive consequences of infrastructure solutions, manifesting as socio-economic disparities and exclusionary effects. Residents within the embankment area exhibit notably impoverished socio-economic indicators, including a 32% female literacy rate, approximately 90% of houses are Katchha ( made from mud and straw), and economic dependency on agriculture labor activities, which is significantly lower than outside of the embankment. Moreover, the annual flood and longer periods of waterlogging cut off the population from other parts of the state. Lastly, the study discussed the source of vulnerability and adaptation options, which could be useful in developing comprehensive flood adaptation programs, including socioeconomic considerations.

How to cite: Devda, A. and Verma, V.: Assessing Flood Vulnerability and Maladaptive Effects Associated with Embankment-Based Flood Control Infrastructure : Hydrogeomorphic and Socioeconomic Analysis Kosi River Embankment Region, Bihar, India., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8741, https://doi.org/10.5194/egusphere-egu24-8741, 2024.

EGU24-9209 | ECS | Posters on site | HS7.5

Spatial analysis of catastrophic flooding in the metropolitan area of Murcia over the last 100 years 

Ester García Fernández, Juan Francisco Albaladejo-Gómez, Andrina Gincheva, Salvador Gil-Guirado, and Alfredo Pérez-Morales

Floods represent the most diverse, destructive and frequent natural hazard worldwide and are one of the most significant causes of loss of economic and social assets. In recent years, an increase in the quantity and intensity of this phenomenon can be observed. The factors are manifold, but two stand out: increased hazards as a consequence of anthropogenic climate change and increased exposure and vulnerability of the population and its economic assets. One of the most conflictive areas of the planet are the Mediterranean regions, due to the combination of both factors. Among the hot spots, the Southeast of Spain stands out, with a situation aggravated by a semi-arid climate, but with a highly irregular and torrential rainfall distribution.

These factors are particularly problematic in urban areas, making it necessary to precisely locate the areas at risk in order to establish effective adaptation measures. For this reason, this paper compiles historical information on the main flood events from 1900 to the present in the metropolitan area of Murcia, the main urban area in southeast Spain. The information collected comes from newspaper sources. Subsequently, this information has been geolocated and analyzed with Geographic Information Systems. The results reveal that, in general terms, the damage is concentrated mainly in the areas near the Segura River. Additionally, and to a lesser extent, there is a significant concentration in its main tributary, the Guadalentín River. However, it should be noted that during recent flooding episodes, the areas affected are being modified, involving new urbanized areas, far from the main riverbeds and located in flood zones due to the passage of secondary watercourses such as wadis. Finally, it is worth noting that there has been an increase in the number of low-intensity damage points. However, on a positive note, it has been observed that higher intensity damage is decreasing.

How to cite: García Fernández, E., Albaladejo-Gómez, J. F., Gincheva, A., Gil-Guirado, S., and Pérez-Morales, A.: Spatial analysis of catastrophic flooding in the metropolitan area of Murcia over the last 100 years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9209, https://doi.org/10.5194/egusphere-egu24-9209, 2024.

EGU24-9257 | ECS | Orals | HS7.5

Multi-hazard assessment of long- and short-term extreme hydrometeorological events in southeastern South America 

M. Josefina Pierrestegui, Miguel A. Lovino, Gabriela V. Müller, and Omar V. Müller

Extreme hydrometeorological events (EHE) negatively affect ecosystems, human settlements, food production, water resources, and public health worldwide. In southeastern South America (SESA), the frequency and intensity of temperature and precipitation extremes have increased over recent decades. SESA is particularly vulnerable to EHE due to its high population rates and an economy heavily reliant on agricultural activities; therefore, advancing towards a climate-resilient development is a key goal for the region. This study presents a multi-hazard analysis of EHE and their changes over SESA.

Our study assesses the frequency, duration, and intensity of short- and long-term EHE for the 1961-1990 and 1991-2020 periods. ERA5 precipitation, soil moisture, and temperature data at multiple time scales (from daily to monthly) are used, with a spatial resolution of 0.25°×0.25° latitude-longitude grid. Long-term EHE are studied using nonparametric standardized indices—specifically, the Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI)—at 3- and 18-month timescales to analyze agricultural and hydrological impacts. Short-term EHE are characterized by heavy precipitation, flash droughts, and heat waves events to analyze immediate impacts in urban areas and in agriculture. Individual hazard components are derived by multiplying the frequency, duration, and intensity of the identified events, followed by a rescaling to a 0-1 range using range normalization (with minimum and maximum values). The long-term and short-term EHE hazard indices are formulated by aggregating the rescaled individual hazard components and dividing by the total number of components. Changes in observed EHE hazard components are determined by comparing the EHE hazard indices for the 1991-2020 and 1961-1990 periods.

Our findings underscore significant precipitation excess hazard, mainly concentrated in agriculture-prone areas spanning central-eastern Argentina, Uruguay, and southern Brazil across both 3- and 18-month timescales. In contrast, precipitation deficit hazard predominantly manifests in the western regions of SESA. Regarding short-term EHE, the highest hazard magnitudes are observed in northeastern Argentina, southern Brazil, and southeastern Paraguay. Heat waves occur frequently in the region, with hazardous intensities over the northern part of SESA. Additionally, heavy precipitation events constitute a significant hazard component for urban and rural infrastructure primarily in northeastern Argentina. Flash droughts also affect agriculture-prone areas, particularly with high intensity in southern Brazil, northeastern Argentina, and Uruguay.

Our results reveal that the most significant changes are observed in short-term hazard indices in northeastern SESA. This region, which includes eastern Paraguay, northeastern Argentina, southern Brazil, and Uruguay, has experienced an increase in heat wave hazard, primarily due to a significant rise in the frequency of heat waves. Hazards associated with heavy precipitation and flash drought events have also increased, with a rise in their frequency and duration observed mainly over northeastern Argentina and southern Brazil. In contrast, long-term hazard indices exhibit non-uniform patterns of change. Our findings suggest that weather-related hazards have undergone changes over the last decades. We expect that these findings provide valuable insights to enhance SESA's hydroclimatic risk management systems by identifying areas susceptible to both short- and long-term hazards.

How to cite: Pierrestegui, M. J., Lovino, M. A., Müller, G. V., and Müller, O. V.: Multi-hazard assessment of long- and short-term extreme hydrometeorological events in southeastern South America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9257, https://doi.org/10.5194/egusphere-egu24-9257, 2024.

EGU24-9313 | ECS | Orals | HS7.5

The Effects of Geographic Risk Complementarity on Reducing Flood Insurance Costs 

Shibo Cui and Jianshi Zhao

Flood insurance is an important non-structural measure for flood risk management. However, a significant protection gap in flood insurance exists in many countries and the high cost of flood insurance is a primary reason. Reducing the flood insurance costs for both policyholders and insurance companies is crucial for the effective implementation of flood insurance. Here, we use portfolio theory to derive fundamental principles of reducing overall insurance cost including premiums and risk reserves through geographic risk complementarity. Furthermore, we propose a reasonable premiums distribution approach among different risk agents to analyze the effect of geographic risk complementarity on individual cost, based on the cooperative game theory. We applied our method in China, which has a large territory but lacks a national flood insurance program. We show there is a low correlation of flood losses across most provinces in China. Compared to the separate insurance in each province, national flood insurance can reduce total premiums by 14.5% and total risk reserves by 61.0%. The regions with highest proportion of premium reduction are the middle and lower Yellow River reaches, which have a lower flood risk correlation with the portfolios of other regions. In conclusion, the geographic complementarity in flood risk has a significant effect on reducing flood insurance cost and the degree of cost reduction depends on the flood risk correlation among different entities. We recommend that China should utilize the geographic risk complementarity to implement a national-level flood insurance program. The method proposed can also provide references for catastrophe insurances around the world.

How to cite: Cui, S. and Zhao, J.: The Effects of Geographic Risk Complementarity on Reducing Flood Insurance Costs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9313, https://doi.org/10.5194/egusphere-egu24-9313, 2024.

EGU24-10245 | ECS | Orals | HS7.5

A time-dependent non-asymptotic statistical analysis of extreme precipitation events 

Matteo Pesce, Eleonora Dallan, Francesco Marra, and Marco Borga

Time-dependent precipitation frequency analyses were often hampered by the availability of relatively short data records, which result in large uncertainty in the estimation of extremes. The recently developed non-asymptotic statistical methods, based on fitting ordinary events rather than extreme events only, represent a potential solution to the problem of data scarcity and are finding wide application in literature under assumptions of stationarity. Recent studies investigated the use of non-asymptotic methods under non-stationary conditions (e.g., Vidrio-Sahagún and He, 2022) and advocated their use over other methods for non-stationary frequency analysis of extreme precipitation. In this study we formalize a non-stationary time-dependent approach for the statistical analysis of multi-duration precipitation extremes using simplified metastatistical extreme value (SMEV) approach. The study focuses on a catchment in the Eastern Italian Alps, where trends in extreme precipitation where reported (Dallan et al., 2022) and which was impacted by the exceptional Vaia event in 2018. We provide an estimation of extreme return levels of precipitation in six stations in the neighborhood of the catchment and compare them with precipitation maxima observed during Vaia storm. The results show that using a non-stationary left-censored Weibull distribution, with both scale and shape parameters linearly dependent on time, allows to properly describe the observed trends of intense precipitation for different durations. Our results suggest that the probability of observing events like Vaia increased over the past decades, leading to the need for updating local adaptation measures.

 

References:

Dallan, E., Borga, M., Zaramella, M., & Marra, F. (2022). Enhanced summer convection explains observed trends in extreme subdaily precipitation in the eastern Italian Alps. Geophysical Research Letters49(5), e2021GL096727.

Vidrio-Sahagún, C. T., & He, J. (2022). Hydrological frequency analysis under nonstationarity using the Metastatistical approach and its simplified version. Advances in Water Resources166, 104244.

How to cite: Pesce, M., Dallan, E., Marra, F., and Borga, M.: A time-dependent non-asymptotic statistical analysis of extreme precipitation events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10245, https://doi.org/10.5194/egusphere-egu24-10245, 2024.

EGU24-10297 | ECS | Orals | HS7.5

Projected amplification of rainfall extremes due to warming-induced reduction of snow fraction: an assessment based on convection-permitting simulations 

Petr Vohnicky, Eleonora Dallan, Francesco Marra, Giorgia Fosser, Matteo Pesce, and Marco Borga

In mountainous regions, temperature determines the state of precipitation (liquid or solid) and in turn significantly affects runoff formation and flood generation. Projected temperature increase due to global warming may therefore affect the rainfall/precipitation ratio during heavy storms, hence intensifying the flood regime. This study aims to assess the projected variations in liquid/solid fraction of precipitation during heavy precipitation events in the upper Adige River, Italy (Eastern Italian Alps). The study utilizes simulations from an ensemble of convection-permitting climate models (CPM), which are suitable to the task given their ability to explicitly represent deep convection and to resolve the mountainous topography. The CPM data provided by the CORDEX-FPS Convection project at 1-hour temporal and remapped to 3 km spatial resolution, cover historical and far-future (2090-2099) time periods under the extreme climate change scenario (RCP8.5). Observational data from the densely instrumented river system are utilized for bias evaluation. Lastly, the Simplified Metastatistical Extreme Value (SMEV) approach, known for the reduced uncertainty compared to conventional approaches, is incorporated for frequency analysis. This method proves particularly useful for analyzing extremes from short time periods, such as those in CPM simulations. The projected changes in both sub-daily mean areal precipitation and liquid rainfall return levels are examined at various spatial scales based on the sub-basins total area. Our preliminary results underscore the significance of leveraging advanced statistical techniques and high-resolution climate models to address emerging challenges in hydrology and climate science. The climate-induced shifts in return period of liquid precipitation identified in this study are expected to have implications for both water resources management and adaptation measures.

How to cite: Vohnicky, P., Dallan, E., Marra, F., Fosser, G., Pesce, M., and Borga, M.: Projected amplification of rainfall extremes due to warming-induced reduction of snow fraction: an assessment based on convection-permitting simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10297, https://doi.org/10.5194/egusphere-egu24-10297, 2024.

EGU24-10877 | ECS | Posters on site | HS7.5

Exploring Diverse Perceptions of Multiple Risks among the Public in Rome 

Mara Lucantonio, Elena Ridolfi, Patrizia Cicini, Fabio Russo, and Francesco Napolitano

Risk is given by the combination of exposure, hazard, and vulnerability, and it is perceived by individuals in different ways. Some people may be unaware of the potential occurrence of a given hazard, while others may misjudge their level of exposure, vulnerability, or both. The knowledge of the population’s risk perception is a fundamental aspect for the analysis of potentially catastrophic phenomena and for the development of prevention policies to intervene and mitigate the expected damage. Questionnaires are widely used in social science research to acquire information about the attitudes, social characteristics, beliefs, and behaviors of participants. This information when combined through a mixed method can provide robust, comprehensive, and quantifiable results, adding a valuable perspective for the development of appropriate hazard mitigation and adaptation strategies. Here we present a case study that involves the analysis of a data set based on a questionnaire submitted to around 300 citizens of the city of Rome (Italy) in spring 2023. The proposed questionnaire investigates specific areas, which are: experience and knowledge of the phenomena, probability of occurrence perceived by the respondent, potential impact, and preparedness to deal with the phenomena.The use of questionnaires to study citizens’ perception of both natural and man-made hazards enables the acquisition of valuable information for authorities dealing with emergency management. The resulting dataset has the potential to improve the communication efficiency between authorities and citizens in risk situations, and provide relevant information for future studies relying on the knowledge of citizens’ risk perception.

How to cite: Lucantonio, M., Ridolfi, E., Cicini, P., Russo, F., and Napolitano, F.: Exploring Diverse Perceptions of Multiple Risks among the Public in Rome, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10877, https://doi.org/10.5194/egusphere-egu24-10877, 2024.

EGU24-10950 | ECS | Posters on site | HS7.5

Temporal and spatial analysis of mortality associated with landslides on São Miguel Island (Portugal) from 1900 to 2020 

Rui Fagundes Silva, Rui Marques, and José Luís Zêzere

The São Miguel Island covers an area of 744.6 km² and has a total population of 133,390, distributed across six municipalities: Ponta Delgada, Ribeira Grande, Vila Franca do Campo, Povoação, Lagoa, and Nordeste. The island features two extinct volcanic systems and three active central volcanoes with calderas connected by two fissure volcanic systems. Two distinct seasons can be identified based on rainfall patterns: from October to March (wet season) and from April to September (dry season). Since the settlement of the island in the mid-15th century, there have been records of landslides, some with significant socio-economic impact. The analysis of the spatial distribution and temporal patterns of mortality associated to landslides was carried out using the NATHA (Natural Hazards in Azores) database for the period 1900–2020. Data collection involved the analysis of more than 55,500 newspaper specimens. A total of 236 landslides events were catalogued on São Miguel Island, which caused 82 fatalities. The municipality of Povoação accounted for 48 fatalities, approximately 59% of the total. Ponta Delgada reported 14 fatalities, Ribeira Grande eight, Vila Franca do Campo seven, Nordeste three, and Lagoa two. On São Miguel Island, an average of 0.7 fatalities per year were recorded, resulting in a landslide mortality rate of 0.35 (calculated as the ratio between deaths and total events). The events with the highest number of fatalities occurred on October 31, 1997 (29 fatalities) and on October 14, 1942 (7 fatalities). The annual mortality rate per decade reveals two distinct periods with higher values: 1930-1949 and 1990-1999. No fatalities were recorded from 1900 to 1929. The landslide mortality rate has a first increase in the 1930s and 1940s (≈0.1 fatalities/10,000 inhabitants). From 1950 to 1989, there was a decrease (≈0.02 fatalities/10,000 inhabitants), with a slight increase in the 1960s. The period from 1990 to 1999 has the highest mortality rate (≈0.26 fatalities/10,000 inhabitants). However, excluding the extreme event of October 31, 1997 from the analysis reveals that the 1990s had a mortality rate in line with the previous four decades (0.02 fatalities/10,000 inhabitants). Along the two first decades of the 21st century, the mortality rate increased again, maintaining a stable trend (≈0.05 fatalities/10,000 inhabitants). The data also indicates that males had a higher frequency of fatalities. The circumstances surrounding the incidents varied, with most fatalities occurring outdoors when individuals were on foot in rural areas. However, it is noteworthy that there were also fatalities inside houses in urban areas, emphasizing the diverse contexts in which these tragic events took place. This information provides valuable insights to temporal patterns and spatial distribution of landslide-induced fatalities on São Miguel Island.

How to cite: Silva, R. F., Marques, R., and Zêzere, J. L.: Temporal and spatial analysis of mortality associated with landslides on São Miguel Island (Portugal) from 1900 to 2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10950, https://doi.org/10.5194/egusphere-egu24-10950, 2024.

EGU24-11090 | ECS | Orals | HS7.5

From indices to impacts: Understanding the dynamics of drought impacts through socio-economic clustering 

Rhoda Odongo, Hans De Moel, Marthe Wens, Natalia Limones, Dim Coumou, and Anne Van Loon

Over the past decade, the Horn of Africa (HoA) has been plagued by recurrent drought events that have had devastating impacts on the population. The frequency, duration and severity of these droughts are expected to increase in the wake of global warming, leading to higher losses and damages if the vulnerability of the population is not reduced. Monitoring and early warning systems for droughts are based on various drought hazard indicators. However, assessments of how these indicators are linked to impacts are rare. For adequate drought management, it is essential to understand and characterise the drivers of drought impacts, especially in the HoA, where most studies focus either on meteorological droughts, agricultural droughts or the propagation of droughts through the hydrological cycle, without considering the relationship between hazard and impact. Drought hazard indices alone cannot capture the vulnerability of the system. In this study, we identify meaningful indices for the occurrence of region- and sector-specific impacts. We assess the effectiveness of socio-economic clustering in categorising counties based on common characteristics and their correlation with historical drought impacts (malnutrition, milk production and trekking distances to water sources). Using Random Forest (RF) and Spearman correlation analyses, we examine the link between drought indices (Standardised Precipitation Index, Standardised Precipitation Evapotranspiration Index, Standardised Soil Moisture Index, Standardised Streamflow Index and Vegetation Condition Index) with different accumulation periods and the impact data. We find that clustering regions based on vulnerability proxies significantly improves the hazard-impact relationship, emphasising the importance of considering vulnerability factors in drought risk assessment. Our results indicate an impact-specific relationship that is strongly influenced by the vulnerability of the region. In particular, household and livestock distance to water is most strongly associated with medium- to long-term precipitation-based indices (2-10 months), while milk production can be associated with a variety of indices with different accumulation periods (5-24 months), and malnutrition is correlated with precipitation- and streamflow-based indices (5-24 months). Household and livestock distance to water is well modelled by clusters reflecting low access to improved sanitation and safe water sources, high poverty, aridity and gender disparities. Malnutrition was well modelled by clusters related to aridity, average precipitation, food consumption score, access to water sources, improved sanitation and poverty levels. The type of clustering used in modelling the impact of drought on milk production does not have a major impact on the performance of the models. We then apply this relationship to hindcast drought indices to obtain impact data on individual counties for periods when no impact monitoring was done yet. With that information we estimate the associated risk under specific climatic conditions. By recognising the drivers and vulnerability factors that influence the sensitivity of counties to drought, communities can better prepare and mitigate the impacts of drought.

How to cite: Odongo, R., De Moel, H., Wens, M., Limones, N., Coumou, D., and Van Loon, A.: From indices to impacts: Understanding the dynamics of drought impacts through socio-economic clustering, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11090, https://doi.org/10.5194/egusphere-egu24-11090, 2024.

EGU24-11493 | ECS | Posters on site | HS7.5

Dry spell frequency and duration analysis using different spell definitions 

Pedro Henrique Lima Alencar and Eva Nora Paton

Dry spells, characterized by consecutive days with little to no precipitation, pose significant challenges, particularly in agriculture, and can impact various sectors including health when compounded by high temperatures, increased evaporation rates, or pollution. However, defining the thresholds for what constitutes a significant lack of precipitation or the number of consecutive days to define a notable dry spell remains ambiguous. In this study, we investigate the occurrence of different types of dry spells across Germany using twelve diverse definitions. These definitions encompass not only the conventional criteria of low/no precipitation but also consider associations with other extreme weather conditions occurring simultaneously (such as high temperatures, and potential evapotranspiration) or following the dry spell (like intense precipitation events). Leveraging continuous weather station data spanning the last 50 years, we employ the Mann-Kendall test to analyse seasonal and regional trends in the duration and frequency of these various dry spell events across Germany. Our findings reveal positive trends in both the frequency and duration of dry spells in Germany, notably prominent in the southern regions. These trends are observed in conventional low-precipitation dry spells and compound heat-dry events. Additionally, to facilitate event identification, we have consolidated these diverse dry spell definitions into an R-package called DryER (Dry spell Events in R).

 

How to cite: Lima Alencar, P. H. and Paton, E. N.: Dry spell frequency and duration analysis using different spell definitions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11493, https://doi.org/10.5194/egusphere-egu24-11493, 2024.

EGU24-11733 | ECS | Orals | HS7.5

Exploring vulnerability to flash floods in a water-scarce MENA city: Challenges and possible solutions  

Clara Hohmann, Christina Maus, Ahmad Awad, Dörte Ziegler, Hanna Leberke, Maram Al Naimat, Wafaa Abuhammour, and Katja Brinkmann

Jordan is one of the water scarcest regions worldwide, but regularly hit by severe flash floods caused by heavy rainfall events. Such events will likely intensify in future and increase flash flood damages, especially in rapidly developing urban areas. Therefore, flood vulnerability analysis and assessment are urgently needed to improve urban risk management and to protect the local population. To date, however, such analyses in Jordan, as in many other MENA regions, have been hampered by the lack of spatial and temporal high-resolution climate, economic and social data. Furthermore, conducted hydrological analyses have only considered physical parameters in assessing flash flood risk.

Our aim is to investigate the vulnerability in a data scarce urban region and find solutions to overcome the challenges by combining different disciplinary perspectives with local knowledge. Jordan’s capital, Amman was selected as study region, which is a prime example of a rapidly growing city in the MENA region.

To analyze and assess the vulnerability of people, infrastructure and ecosystem to flash flood events in a watershed of Amman, a mixed-method approach was applied within a transdisciplinary research project called CapTain Rain (Capture and retain heavy rainfall in Jordan). To gain insights into flash flood risks, we explore the vulnerability dimensions exposure and sensitivity from the hydrological, hydraulic and social perspectives, and the adaptive capacity of the local population. For the assessment of each vulnerability dimension, different physical, social and ecological indicators were used. Several indicators, such as damage potential, were adapted to local conditions based on focus group discussions with Jordanian stakeholders.

The vulnerability dimensions exposure, sensitivity and adaptive capacity were assessed for the current situation and several possible scenarios with changing future conditions in climate (intensity of rainfall) and land cover (urbanization trends). As one sensitivity indicator the damage potential was analyzed. The resulting damage potential map shows e.g. the locations of critical infrastructure, and also includes the word heritage sites, which were identified as vulnerable infrastructure of high importance by the Jordanian stakeholders. Regarding future scenarios our first hydrological and hydraulic modelling results show that a moderate climate change of 20% more intense rainfall has a stronger influence compared to land cover changes. Land cover changes with more sealed surfaces have little influence on the runoff caused by the low infiltration capacity of soils in the area according to the available data.

Through interdisciplinary collaboration and local stakeholder engagement, this work demonstrates a noteworthy strategy to addressing flash flood risks in situations where data is limited. The results of the integrated scenario analysis and vulnerability assessment serve as a decision-support tool for urban planning.

How to cite: Hohmann, C., Maus, C., Awad, A., Ziegler, D., Leberke, H., Al Naimat, M., Abuhammour, W., and Brinkmann, K.: Exploring vulnerability to flash floods in a water-scarce MENA city: Challenges and possible solutions , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11733, https://doi.org/10.5194/egusphere-egu24-11733, 2024.

EGU24-14198 | ECS | Orals | HS7.5

Assessing the Influenced Zone of Debris Flow Using Numerical Simulation 

Kai-Lun Wei, Kuo-Wei Liao, Guan-Yu Lin, Poshuan Lin, and Tsungyu Hsieh

Taiwan is located at the boundary between the Philippine Sea Plate and the Eurasian Plate, characterized by steep terrain and high river gradients. Combined with frequent events such as typhoons leading to substantial rainfall, this has resulted in disasters like debris flows. Several available tools such as HEC-RAS two-dimensional hydraulic, SRH-2D, FLO-2D and FLOW-3D are used to analyze the area of flooding and the impact of debris flow in the watershed. The simulation results are compared with historical disaster data to validate the feasibility of model. Furthermore, the results are used to evaluate the suitability of current government-designated evacuation locations and routes.

Among several analysis tools, the debris flow modeling in HEC-RAS two-dimensional hydraulic is considered as the best platform to analyze debris risk. The results show the sections of evacuation routes on the left bank of the downstream area near the estuary pass through the debris flow impact area. However, there is no suitable evacuation facility in the vicinity. Therefore, during warning issuance, residents need to be cautious and evacuate promptly. On the other hand, collaboration with government authorities can be pursued to establish new shelters or activity centers nearby, serving as alternative evacuation sites.

How to cite: Wei, K.-L., Liao, K.-W., Lin, G.-Y., Lin, P., and Hsieh, T.: Assessing the Influenced Zone of Debris Flow Using Numerical Simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14198, https://doi.org/10.5194/egusphere-egu24-14198, 2024.

EGU24-14698 | Posters on site | HS7.5

Monthly flood frequency regionalization for comprehensive flood damage assessment to crops 

Anna Rita Scorzini, Charlie Dayane Paz Idarraga, and Daniela Molinari

Quantitative flood risk assessments rely on damage models, which relate information on flood hazard and vulnerability of exposed assets to estimate expected losses. Differently from other sectors, crop damage depends not only on typical hazards variables (including water depth, flow velocity, inundation duration, water salinity, yield of sediments and/or contaminants) but also on the month of flood occurrence. Indeed, plant vulnerability changes over the different phenological phases that are strictly related to the seasonality of crop production. Considering the time of occurrence of the flood would imply a shift from the traditional representation of inundation scenarios based on annual probability to monthly-based hazard estimations. When risk assessment is carried out at large spatial scale, a detailed understanding of seasonal flood patterns is then required for the different sub-catchments of the basins, including un-gauged ones. In this study we present a clustering approach to flood frequency regionalization applied to the Po River District in Northern Italy, within the risk assessment process required by the European Floods Directive. The  area is characterized by complex climatic and topographic conditions, highlighting the representativeness of the case study for the implementation of the proposed approach in other geographical contexts. Utilizing observed monthly flow data from over 100 gauging stations, the approach combines both physical and statistical criteria to identify homogeneous regions in terms of flood generation mechanisms and seasonality. The process enables the assignment of distinct monthly flood probabilities to all catchments within the district, thereby supporting a comprehensive flood risk assessment for the agricultural sector.

How to cite: Scorzini, A. R., Paz Idarraga, C. D., and Molinari, D.: Monthly flood frequency regionalization for comprehensive flood damage assessment to crops, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14698, https://doi.org/10.5194/egusphere-egu24-14698, 2024.

The insurance sector plays a critical role in promoting disaster resilience and recovery by providing financial protection, speeding up rebuilding and recovery, and managing the financial impact of natural disasters. To fulfill this role, insurance companies must meet the capital requirements imposed by regulators. For example, the European Solvency II regulatory framework requires insurers to hold enough capital to withstand a natural catastrophe loss with a return period of 1 in 200 years. As the historical loss data are scarce and incomplete, the insurance sector uses stochastic catastrophe models (cat models) to assess the potential cost of rare but devastating events like floods.

A stochastic event set is a crucial element of cat models. It is a collection of possible disasters with their likelihood and severity. One method to generate stochastic flood events is to use numerical models of the atmosphere to generate realistic precipitation fields, and then apply rainfall-runoff models to estimate how much water will flow into rivers and streams from precipitation and snowmelt. By running many simulations with different inputs and parameters, stochastic flood models can provide a range of possible outcomes, including floods with spatial patterns and magnitude missing in historical data.

Output of such simulations are spatio-temporal hazard grids: precipitation grids for pluvial risk and river discharge grids for fluvial risk. These grids are large as the models typically run over large geographies (countries or continents) and simulate 10,000 years or more. This contribution will (i) provide overview of existing methods how to identify flood events in such huge discharge and precipitation datasets (i.e. peak-over threshold method), (ii) show their limitations for identifying flood events, and finally (iii) propose a new methodology designed to address specific needs of reinsurance industry such as the hours-clause condition, which specifies the time period within which losses from a single event must occur in order to be covered.

As many severe floods are composed from several sub-waves (for example 2002 floods in Czech Republic), proper event identification and separation is highly relevant topic as it influences the amount of reinsurance payouts after some types of flood events and thus capital available for rebuilding and recovery. 

How to cite: Kadlec, M.: Identification of flood events in large discharge datasets - reinsurance industry perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14743, https://doi.org/10.5194/egusphere-egu24-14743, 2024.

EGU24-14898 | Posters on site | HS7.5

The diverse impacts of extreme storms in the European South. The case of Storm Daniel (2023) in Greece. 

Michalis Diakakis, Spyridon Mavroulis, Christos Filis, Yiannis Bantekas, Marilia Gogou, Katerina-Nafsika Katsetsiadou, Maria Mavrouli, Vasilis Giannopoulos, Andromachi Sarantopoulou, Panagiotis Nastos, Emmanuel Vassilakis, Aliki Konsolaki, Evelina Kotsi, Sotiris Moraitis, Eleftheria Stamati, Athanasia Bakopoulou, Emmanuel Skourtsos, Panayotis Carydis, and Efthymios Lekkas

On September 4, 2023, Storm Daniel moved inland from the Ionian Sea, intensifying due to the warmth of the post-summer Mediterranean Sea, resulting in intense rainfall and thunderstorms over the Balkans. Central Greece was particularly affected, experiencing the highest daily rainfall totals recorded in the region.

The storm caused widespread devastation, especially in the Thessaly region, with significant impacts including intense erosion, mass movement phenomena triggered by rainfall, damages from strong winds, inundation, agricultural land damage, loss of life and injuries, impacts on residences and businesses, as well as a substantial toll on the environment and cultural sites.

This study focuses on Storm Daniel and its effects in Thessaly, Greece, by creating a database of distinct impact elements based on field surveys and public records. Through this archive, the study explores the range of its impacts, developing a systematic categorization to provide an in-depth understanding of the types and mechanisms of these impacts.

Examining extreme storms through post-flood surveys and emphasizing their impacts can enhance our comprehension of associated risks. This knowledge will facilitate more accurate predictions and strategic planning for such events, contributing to improved emergency management and recovery efforts. Anticipating the impacts becomes crucial, particularly in the context of the projected increase in the frequency of such events due to climate change, thereby strengthening our preparedness.

How to cite: Diakakis, M., Mavroulis, S., Filis, C., Bantekas, Y., Gogou, M., Katsetsiadou, K.-N., Mavrouli, M., Giannopoulos, V., Sarantopoulou, A., Nastos, P., Vassilakis, E., Konsolaki, A., Kotsi, E., Moraitis, S., Stamati, E., Bakopoulou, A., Skourtsos, E., Carydis, P., and Lekkas, E.: The diverse impacts of extreme storms in the European South. The case of Storm Daniel (2023) in Greece., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14898, https://doi.org/10.5194/egusphere-egu24-14898, 2024.

EGU24-15286 | ECS | Posters on site | HS7.5

A 10-Year climatology of hail in France: towards an estimate of the hail hazard 

Maxime Trevisani

According to France Assureur (French insurance unions), 2022 hail damage in France is estimated at more than €6.5 billion, i.e. more than half of all climate-related damage in 2022, or 60% of all hail damage accumulated between 2013 and 2021. This record-breaking year is in line with the growing concern about hail in France among public and private stakeholders. Despite its increasing impact on society the hail hazard in France remains largely unknown or under investigated at the national level, with a single 20x20 km hail risk map produced up in 1998 by F. Vinet using economic data (insurance) and measurements (hailpad). Hail hazard is poorly studied in France due to the great difficulty of observing or modelling hailfall, which are highly localised in time and space. The emergence of social networks since the late 2000s has led to a proliferation of potential hail observers across France. These new data, combined with insurance data, make it possible to study hail at a level of resolution never seen before in France.

The main objectives of our study are therefore to update the geographical assessment of the hail hazard in France, while improving the granularity of the existing geographical hail assessment. To this end we studied the hail hazard in terms of frequency and maximum diameter at the municipal level (average 16 km²), using hail reports (Keraunos, European Sever Weather Database) and insurance data (Generali France, around 5% market share) over the period 2013-2022.

Our study thus provides a resolution 25 times finer than that of Vinet and reveals a southwest - northeast axis dividing France into two parts: the southern part is heavily affected by hail while the northern part is less affected. It also highlights 3 main geographical areas with the highest hail hazard. The Massif Central stands out as the main hail-prone area in France, with a notable maximum in its northern part. The Bordeaux-Paris axis comes second, with a local maximum in the southwest Atlantic coast. In third place comes the Provence-Alpes-Côte d'Azur region, particularly in the Pre-Alps and Pre-Atlantic massifs. There also seems to be a correlation between orography and areas of high hail hazard, particularly noticeable in the Massif Central and Pre-Alps regions, but this assumption needs to be further investigated.

How to cite: Trevisani, M.: A 10-Year climatology of hail in France: towards an estimate of the hail hazard, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15286, https://doi.org/10.5194/egusphere-egu24-15286, 2024.

EGU24-15556 | Orals | HS7.5

Climate Stress Testing for Enhanced Understanding of the Flood Hazard and its Socioeconomic Impacts in Italy 

Francesca Perosa, Alastair Clarke, Punit Bhola, Caroline McMullan, Emma Lewington, and Bernhard Reinhardt

To contribute to a more resilient flood risk management in Italy, we employ the recently published Verisk Inland Flood Model for Italy to conduct climate stress testing. We focus on the sensitivity of modeled losses to precipitation and leverage the meteorological dataset obtained from the Climate Model Intercomparison Project Phase 6 (CMIP6) for identifying projected precipitation trends and analyzing the potential effects of climate change on inland flood losses in the future, exploring different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). The methodology involves analyzing correlations between annual or seasonal precipitation and the corresponding annual loss cost, which is defined as annual loss divided by the total insured value. By exploring these relationships, we seek to enhance our understanding of how precipitation patterns influence the financial implications of flood events in various Italian regions. Additionally, we use the 10,000-year stochastic catalog embedded in the Verisk Inland Flood Model to explore the impact of expected climate change-related changes in annual precipitation for each Italian region, addressing the climate change-based precipitation targets. This enables us to run the fully probabilistic Verisk Inland Flood model and to assess whether anticipated alterations in precipitation levels correspond to expected changes in Annual Average Loss (AAL). This approach allows us to dynamically adapt our flood risk model to varying climate scenarios, providing valuable insights for the (re)insurance industry, as well as academia and government agencies that are seeking to navigate the evolving landscape of flood-related risks.

How to cite: Perosa, F., Clarke, A., Bhola, P., McMullan, C., Lewington, E., and Reinhardt, B.: Climate Stress Testing for Enhanced Understanding of the Flood Hazard and its Socioeconomic Impacts in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15556, https://doi.org/10.5194/egusphere-egu24-15556, 2024.

EGU24-15848 | Posters on site | HS7.5

The use of radar information for improving the knowledge about landslides and floods events: an application to Calabria region (Italy) 

Vincenzo Totaro, Simona de Sario, Francesco Chiaravalloti, and Olga Petrucci

Floods and landslides are common natural phenomena that threaten society and ecosystems causing significant losses in term of human lives and financial damages. An in-depth investigation about the past occurrences of these events is of paramount importance for providing advances in the knowledge of natural and anthropogenic factors responsible for their generation. Considering rainfall as one of the key drivers for triggering physical mechanisms responsible for the occurrences of floods and landslides, a proper description of its characteristics needs to contemplate the intrinsic spatial and temporal variability. Despite the importance of such elements, rainfall monitoring often relies on sparse rain gauges, which lead to uncertainty in the identification of real rainfall patterns, making difficult to link precipitation records with observed damages. Meteorological radar represents a relevant tool for detecting rainfall spatiotemporal variability and providing ancillary information about the evolution of the events.

Goal of the work is to develop a methodology that aims in reconcile records of landslides and floods events with the rainfall structures obtained by the joint use of data recorded by rain gauge network and radar data. The research has been carried out by moving from a consolidated catalogue of damaging events occurred in correspondence of floods and landslides in Calabria region (Italy) in 2019 and 2020. Rainfall was investigated integrating rain gauge data and maps of Surface Rainfall Intensity with resolution of 1x1 km2.

Exploiting the availability of an accurate spatiotemporal reconstruction of precipitation structures, our investigation allowed to improve the specific knowledge about dynamics responsible of selected floods and landslides events. Preliminary results are supportive of the use of the proposed approach for integrating different sources of information in the assessment of the real dynamics of damaging events and for enhancing the use of their joint scientific content in the framework of risk assessment and mitigation.

How to cite: Totaro, V., de Sario, S., Chiaravalloti, F., and Petrucci, O.: The use of radar information for improving the knowledge about landslides and floods events: an application to Calabria region (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15848, https://doi.org/10.5194/egusphere-egu24-15848, 2024.

EGU24-17412 | Orals | HS7.5 | Highlight

It could have come worse –  an analysis of spatial counterfactual scenarios for the July 2021 flood in the Ahr Valley, Germany 

Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz

After a flood disaster, the question often arises: “What if the event had gone differently?” For example, what would be the effects of a flood if the path of a pressure system and thus the precipitation field had occurred taken a different trajectory? The analysis of such alternative scenarios of precipitation footprints (“counterfactuals”) is a valuable approach for flood risk management in addition to classical extreme value statistical analyses. It helps to think about and prepare for extremes that have not occurred in this way, but which appear quite plausible.

Here, we analyze the spatial alternative scenarios of the deadly July 2021 flood in the Ahr Valley, Germany. The hydrological model mHM is driven with precipitation fields systematically shifted in space. The resulting runoff is transformed into inundation and flood impact indicators using the high-resolution hydrodynamic model RIM2D.

The results show that even a slight shift of the precipitation field by 15-20 km, which does not seem implausible due to orographic conditions, causes an increase in peak flows at the Altenahr gauge of over 30% and at individual tributaries of up to 160%. Also, significantly larger flood volumes can be expected due to precipitation shifts. This results in markable differences in inundation depths in a number of areas along the Ahr river valley. The presented results should encourage critical thinking about precautionary measures and risk management plans for extreme and unprecedented events.

How to cite: Vorogushyn, S., Han, L., Apel, H., Nguyen, V. D., Guse, B., Guan, X., Rakovec, O., Najafi, H., Samaniego, L., and Merz, B.: It could have come worse –  an analysis of spatial counterfactual scenarios for the July 2021 flood in the Ahr Valley, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17412, https://doi.org/10.5194/egusphere-egu24-17412, 2024.

EGU24-17516 | Posters on site | HS7.5

Spatial patterns and determinants of severe geomorphological changes due to the extreme flood event in the Ahr valley, western Germany in July 2021 

Fabian Weidt, Rainer Bell, Lothar Schrott, Alexander Brenning, Michael Dietze, Lisa Burghardt, and Joshua Groeßer

The extreme flood event of July 14/15, 2021 caused massive geomorphological changes along the Ahr river in western Germany. The processes include mass movement and bank erosion, channel displacement and widening and deposition of material at the floodplains, all of which contributed to extreme damage. With the aim of gaining a more comprehensive understanding of the factors controlling these processes, spatial patterns of geomorphological changes on a regional scale are analyzed. A differential terrain model (DoD), calculated from digital terrain models (DTM) collected before and after the event using airborne laser scanning (ALS), serves as the data basis. The course of the river is divided into 120 m wide and 100 m long segments. Analyzing the cumulated volumetric loss per segment, which represents the explained variable proxying spatial variability in flood power, is conducted by using a multiple linear regression model. The independent variables considered in this investigation include peak discharge, valley floor width and river curvature. Additionally, a time series model, incorporating ARIMA and GARCH components, is applied to unravel patterns and anomalies along the course of the river while accounting for the autocorrelative and heteroscedastic structure of data. Both the native data and the residuals of all model types are used to examine effects of bridge failure and subsequent outburst waves on volumetric loss. The analysis shows that the strongest geomorphological changes are associated with high peak discharge and a small valley floor width. River segments containing destroyed arch bridges show significantly higher volumetric loss values than segments with destroyed slab bridges, intact bridges or no bridge at all. Spatially limited amplification of volumetric loss to 200 m downstream of destroyed slab bridges suggests a more rapid decrease in outburst wave power for those type of bridges in contrast to arch bridges. These findings provide evidence that there are construction types more appropriate than traditional arch bridges to prevent local augmentation of flood power caused by outburst waves resulting from bridge clogging and failure.

How to cite: Weidt, F., Bell, R., Schrott, L., Brenning, A., Dietze, M., Burghardt, L., and Groeßer, J.: Spatial patterns and determinants of severe geomorphological changes due to the extreme flood event in the Ahr valley, western Germany in July 2021, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17516, https://doi.org/10.5194/egusphere-egu24-17516, 2024.

EGU24-18244 | ECS | Orals | HS7.5

The effects of extreme rainfall trends on compound flood risk: A case study over Greater Boston 

Stergios Emmanouil, Andreas Langousis, Elizabeth Perry, Luke Madaus, Joshua Hacker, and Emmanouil N. Anagnostou

Climate adaptation strategies and vulnerability assessments over coastal areas require proper modeling of the interplay and nonstationary nature of the physical processes involved in compound flooding. As a result of the reported upward trajectories of rainfall intensity over the Contiguous United States, flood risk estimates are also expected to vary. However, given the systematic and random inconsistencies of traditional extreme rainfall estimation approaches and the increased uncertainty surrounding climate model projections, the effects of climate change on the estimation of flood risk from compound hazards remains an open question. In this effort we aim to: (a) combine the observed rainfall intensity trends from the past 40 years (i.e., from 1979 to 2020; see also Emmanouil et al., 2022) across various scales of temporal averaging, with storm surge and antecedent streamflow conditions, to estimate how flood inundation levels evolve, and (b) assess the effects of those trends on flood risk estimation within areas affected by compound hydrological events. In doing so, we use hydrodynamic simulations of reported flood occurrences over the Greater Boston area (MA, United States) for a period of 20 years (i.e., from 2000 to 2019), along with the parametric modeling scheme proposed by Emmanouil et al. (2023). The latter has been shown to properly weight and link the exceedance probabilities of the main flood-driving mechanisms to the return periods of the maximum inundation levels, thus providing a sufficient depiction of the conditions over the studied domain and allowing for estimation beyond the range covered by the available simulations. Assuming that the dependence structure of the driving mechanisms remains time-invariant, our findings aim to enhance the understanding of how flood risk from compound hazards has been affected by extreme rainfall trends induced by the changing climatic conditions and, therefore, support decision-making on the design and protection of critical infrastructure.

References

Emmanouil, S., Langousis, A., Nikolopoulos, E. I., & Anagnostou, E. N. (2022). The Spatiotemporal Evolution of Rainfall Extremes in a Changing Climate: A CONUS‐Wide Assessment Based on Multifractal Scaling Arguments. Earth’s Future, 10(3). https://doi.org/10.1029/2021ef002539

Emmanouil, S., Langousis, A., Perry, E., Madaus, L., Hacker, J., and Emmanouil, E.N. (2023) Decomposing the effects of compound mechanisms on flood risk estimation for urban environments: A case study over Greater Boston, UrbanRain23, 12th International Workshop on Precipitation in Urban Areas, Pontresina, Switzerland, 29 November – 2 December 2023.

How to cite: Emmanouil, S., Langousis, A., Perry, E., Madaus, L., Hacker, J., and Anagnostou, E. N.: The effects of extreme rainfall trends on compound flood risk: A case study over Greater Boston, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18244, https://doi.org/10.5194/egusphere-egu24-18244, 2024.

EGU24-18357 | ECS | Posters on site | HS7.5

Unveiling the complexity of social vulnerability: An analysis of the Social Vulnerability Index in Sweden (SVIS) 

Konstantinos Karagiorgos, Lars Nyberg, Nikos Kavallaris, Jenni Koivisto, Tonje Grahn, Ruth Björkholm, Johanna Gustavsson, and Sven Fuchs

In recent decades, social vulnerability assessments have become a valuable tool for gaining a deeper understanding of the effects of natural hazards on societies. These assessments aim to quantify and map human characteristics that contribute to potential loss, enabling the development of capacities and capabilities to respond to the emerging threats. Assessment methods range from qualitative approaches to semi-quantitative, often spatially explicit, place-based approaches, many of them with empirical background in respective case studies around the world. Despite these efforts, it is still important to carefully examine the potential benefits and limitations of these assessments, particularly those that focus on mapping and place-based approaches, in order to fully understand their value.

The purpose of this study (Karagiorgos et al., 2023) was to systematically evaluate the Social Vulnerability Index in Sweden (SVIS) developed by Haas et al. (2022) using a sensitivity analysis approach. This evaluation focuses on the sensitivity around the impact of changing aggregation scale levels, the influence of different options in constructing the index, the weight/contribution of each factor to social vulnerability and the indicators set. The aim was to determine the influence of input factor variation on model response.

Concerning the influence of scale variations on assessment outcomes, the SVIS algorithm demonstrated robustness when employed across various scales. In contrast, the factor retention method utilized yielded considerable differences in the results. Likewise, the weights' effect exerted a noteworthy influence on the index formation. The consideration of different subsets of variables revealed a high impact in certain scenarios.

The sensitivity analysis conducted in the index construction outlined in this study, recommends that the development of indexes proceed cautiously, accompanied by expert guidance. This approach ensures that the portrayal of social vulnerability remains both reasonable and consistent. Furthermore, the existence of other dimensions of vulnerability, such as physical, economic, and institutional, suggests that the SVIS be integrated with these dimensions. This integration can offer a comprehensive perspective on vulnerability, helping to identify and comprehend the primary pillars for use in Disaster Risk Reduction (DRR). It also contributes to a deeper understanding of the connections between social vulnerability models and the outcomes of disasters.

Haas, J.; Karagiorgos, K.; Pettersson, A.; de Goër de Herve, M.; Gustavsson, J.; Koivisto, J.; Turesson, K. & L. Nyberg (2022): Social sårbarhet för klimatrelaterade hot. Delstudie 2: Generella och hotspecifika index för social sårbarhet i Sverige. Myndigheten för samhällsskydd och beredskap, (MSB) rapport nr 1978, Karlstad.

Karagiorgos, K.; Kavallaris, N.; Björnholm, R.; Koivisto, J. & S. Fuchs (2023): Evaluation of the Social Vulnerability Index (SVIS) in Sweden. Swedish Civil Contingencies Agency (MSB), MSB report nr 2185, Karlstad. 

How to cite: Karagiorgos, K., Nyberg, L., Kavallaris, N., Koivisto, J., Grahn, T., Björkholm, R., Gustavsson, J., and Fuchs, S.: Unveiling the complexity of social vulnerability: An analysis of the Social Vulnerability Index in Sweden (SVIS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18357, https://doi.org/10.5194/egusphere-egu24-18357, 2024.

EGU24-19140 | ECS | Posters virtual | HS7.5

Sensitivity analysis of agricultural and hydrological droughts to rainfall deficits across India 

Syed Bakhtawar Bilal and Vivek Gupta

Drought is a natural phenomenon characterized by an extended period of insufficient rainfall for a particular area. These deficit in rainfall leads to shortage of water reserves across surface and sub-surface storages. Variations in these shortages arise from diverse factors such as regional climatic variations, geographical features, and land-use patterns. The primary objective of this study is to assess the sensitivity of agricultural and hydrological systems to rainfall deficits across different climatic zones. We aim to quantify the degree of responsiveness of agricultural and hydrological droughts to varying precipitation deficiencies using various statistical and modeling techniques. By examining the diverse responses in different regions, this research seeks to enhance our understanding of precipitation shortages on drought dynamics.

How to cite: Bilal, S. B. and Gupta, V.: Sensitivity analysis of agricultural and hydrological droughts to rainfall deficits across India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19140, https://doi.org/10.5194/egusphere-egu24-19140, 2024.

EGU24-19393 | ECS | Orals | HS7.5

Impact of long-lasting flood water on agricultural productivity: a case study of the May 2023 Emilia Romagna floods 

Margherita Sarcinella, Jeremy S. Pal, and Jaroslav Mysiak

Heavy rainfall events occurred in the Emilia-Romagna region in Northern Italy as a result of two major storms on May 2nd and 17th that led to the overflow of 22 rivers and triggered over 250 landslides. This event claimed 15 lives, forced 10 thousand people to evacuate and caused over 400 road closures. Due to a prior long-lasting winter drought and poor land use management that hampered effective water drainage, floodwaters stagnated for over a month in some areas, exacerbating the crisis. Over 40% of regional agricultural land was flooded leading to irreversible crop damage, in some instances, entire harvest loss. The objective of this study is to build a consistent and replicable methodology to quantify the agricultural damages and economic loss resulting from stagnated floodwater over cropland using the Emilia Romagna floods as a case study. The study emphasises the use of remote sensing data as a tool to achieve accurate impact estimates. Sentinel-1 SAR imagery is used to derive 10-meter resolution flood extent and duration maps at a revisit time of 3 to 6 days. The maps are matched with crop data available for the region from the iColt database and damages are computed as a function of ponded water duration and crop type as well as resistance to oxygen deprivation. The data, comprised of crop type, growing season and sowing date, allow for the characterization of the growth state of each crop at the time of flooding, implicitly providing insights on the probability of plant survival. The use of satellite-derived vegetation indices as markers for post-disaster crop recovery, with a focus on identifying crop-specific recovery rates and patterns is highlighted. This study highlights the need for collaborative efforts with key regional entities and can provide factual-hazard-based agricultural loss estimates to local institutions. These findings can guide targeted adaptation strategies, improve the spatial accuracy of loss assessment, and improve our comprehension of the aftermath of prolonged floods on agricultural output.

How to cite: Sarcinella, M., Pal, J. S., and Mysiak, J.: Impact of long-lasting flood water on agricultural productivity: a case study of the May 2023 Emilia Romagna floods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19393, https://doi.org/10.5194/egusphere-egu24-19393, 2024.

EGU24-19552 | Posters on site | HS7.5 | Highlight

Unveiling global sub-daily precipitation extremes: Insights and development of the INTENSE Project  

Hayley Fowler, Amy Green, Elizabeth Lewis, David Pritchard, Stephen Blenkinsop, Luis Patino Velasquez, and Anna Whitford

Precipitation extremes result in flooding and droughts, causing substantial damages and loss of life. Understanding the variability of precipitation extremes with climate change is challenging, as we do no fully understand processes causing extreme precipitation under current climate variability. The INTENSE project focuses on understanding of the nature and drivers of global sub-daily precipitation extremes and change on societally relevant timescales. As part of this a Global sub-daily precipitation dataset has been collected, containing hourly rainfall data from approximately 25,000 rain gauges across over 200 territories, from a wide range of sources. This has been quality controlled using a rule-based open-source methodology, combining a number of checks against neighbouring gauges, known biases and errors, and thresholds based on the Expert Team on Climate Change Detection and Indices (ETCCDI) Climate Change Indices.  

A set of global hydroclimatic indices have been produced, characterising key aspects of shorter duration precipitation variability, including intensity, duration and frequency properties. An analysis of the indices, trends and corresponding climatology is carried out, providing information on various sub-daily precipitation characteristics (including extremes) across large parts of the world. These indices are publicly available for as many gauges as possible, alongside a gridded dataset that also incorporates indices calculated for additional restricted-access gauge records. To progress further with this work, updates to the dataset are required, with work ongoing to update resources for 2016 onwards, and attempts to automate the process where open-source datasets are available. Any collaborations, information, suggested contacts and relevant resources for developing the dataset are welcomed. 

How to cite: Fowler, H., Green, A., Lewis, E., Pritchard, D., Blenkinsop, S., Patino Velasquez, L., and Whitford, A.: Unveiling global sub-daily precipitation extremes: Insights and development of the INTENSE Project , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19552, https://doi.org/10.5194/egusphere-egu24-19552, 2024.

Draught is one of the major climate related disaster that Italy has been fighting in the recent years .It is a complex multidimensional phenomenon that is dependent upon on a wide variety of parameters ranging from climatic to socioeconomic ones. In this study we are considering watershed area of lake Bolsena, which is one of the most important water resources in central Italy, to asses in drought vulnerability using Geographical Information System (GIS)  in combination with the Analytic Hierarchy Process (AHP). GIS is used for the spatial analysis of drought for Lake Bolsena watershed area for the year 2022 which was one of the worst draught affected year in the history for the country. Parameters such as Monthly rainfall, Land use/Landcover (LULC), elevation , soil type, Normalized difference vegetation index (NDVI), Normalized Difference turbidity Index (NDTI),Normalized differentiate chlorophyl index(NDCI), Normalized Difference Water Index (NDWI),Storm power index (SPI)  were chosen and considered for the study. AHP is used to calculate weightage factors of each criterion based on the pairwise comparison matrices. The thematic maps of all the parameters were analyzed and Drought Vulnerability Assessment (DVA) map was generated using GIS. The output DVA map will provide valuable information on drought severity in the area and vulnerability related to water availability.

How to cite: Mazumdar, T., Di Francesco, S., Giannone, F., and Santini, M.: Drought vulnerability assessment and mapping using Multi-Criteria decision making (MCDM) and application of Analytic Hierarchy process (AHP) for watershed area of Lake Bolsena of Central Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19949, https://doi.org/10.5194/egusphere-egu24-19949, 2024.

Rich in biodiversity, Tumaco is a focal point for REDD+ projects that aim to combat deforestation and promote sustainable land use. Cacao farming, vital to the local economy, offers an opportunity to reconcile livelihoods and conservation. However, challenges remain in reconciling cacao and forest conservation. This study explores the benefits of sustainable cacao practices, such as agroforestry, for economic development and environmental conservation. It also looks at the challenges farmers face and the implications for the success of REDD+. Perceptions of climate change profoundly influence farmers' perspectives and behaviours in the context of REDD+ initiatives, shaping the sustainability and effectiveness of such efforts. Therefore, fostering a robust understanding of climate change among local farmers is critical to improving the integration of sustainable cacao production into REDD+ frameworks. This research aims to provide insights for policy makers and project implementers to advance both conservation and development goals in the Tumaco region, by addressing potential synergies and trade-offs between cacao production and REDD+ initiatives. The farmers' lack of knowledge is particularly worrying, not only for the fight against climate change, but also because if the cacao farmers of Tumaco do not see the incentives of carbon credits as a sustainable source of income, they will be forced to return to illegal crops, and the socio-environmental development of these communities will be compromised.

How to cite: Quiroga, S., Hernanz, V., Suarez, C., and Aguiño, J. E.: Evaluating the merit of Carbon Credits: Is there a lack of effectiveness in transitioning from direct Payments for Ecosystem Services to REDD+ community-based incentives?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20767, https://doi.org/10.5194/egusphere-egu24-20767, 2024.

EGU24-20944 | ECS | Posters on site | HS7.5

Towards optimizing the operation of controlled flood detention basins 

Mara Ruf and Daniel Straub

Floods are one of the most hazardous natural phenomena worldwide and they are predicted to increase both in intensity and frequency due to climate change. This necessitates comprehensive flood risk mitigation measures that are planned and controlled from a regional as well as a strategic trans-regional perspective.

Controlled flood detention basins can be effective measures for dealing with extreme flood events [1]. By temporally storing water in the detention basin, the discharge in a river is reduced. If the water is removed from the river at the optimal time, this should reduce the peak water level at downstream locations and hence the flood risk.

However, the identification of the optimal operation of flood detention basins is a non-trivial as well as non-deterministic problem. Flood forecast uncertainty, dilatation of the wave along the river channel and the uncertainty in the breaching process turns the polder operation into a stochastic optimization problem with multiple possible optimization targets. Hence, this optimization belongs to the class of sequential decision problems under uncertainty. In this contribution, we utilize a developed dynamic-probabilistic flood risk model [2] to analyze and optimize different control strategies as well as the effect of uncertainties on the optimality of the detention basin operation. We consider the case of a single detention basin as well as that of multiple detention basins that are arranged in series.

 

[1] De Kork, J.-L.; Grossmann, M. (2009): Large-scale assessment of flood risk and the effects of mitigation measures along the Elbe River. Natural Hazards (2010) 52:143-166.

[2] Ruf, M., Hoffmann, A., Straub, D. (2023): Application of a decision sensitivity measure for the cost-benefit analysis of a flood polder at the Bavarian Danube. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP 14). Dublin, Ireland.

How to cite: Ruf, M. and Straub, D.: Towards optimizing the operation of controlled flood detention basins, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20944, https://doi.org/10.5194/egusphere-egu24-20944, 2024.

EGU24-20988 | ECS | Posters on site | HS7.5

Assessment of future climate risk and vulnerability of local communities in High Mountain Asia 

Anju Vijayan Nair, Rahim Dobariya, Deo Raj Gurung, and Efthymios Nikolopoulos

Higher altitude regions like High Mountain Asia (HMA) are particularly affected by future climate change where the increasing temperature coupled with inconsistent precipitation results in rapid glacier melting during summers and less regeneration of glaciers in winters affecting the livelihoods of billions of people. Access to information on future climate change and related hazards is essential to significantly reduce the impacts on socio-economic systems in HMA. In this study, we focus on identifying the areas in northwest HMA where climate extremes are projected to increase in magnitude and/or frequency. For this, statistically downscaled climate projections (at 5km resolution) derived from a 30-member ensemble of GFDL SPEAR CMIP6 are used to evaluate the projected trends in precipitation and temperature (for years 2015 to 2100) over Afghanistan, Tajikistan, and northern Pakistan under SSP2-4.5 and SSP5-8.5 scenarios. Analysis of changes in precipitation and temperature with respect to the historic climate (1990 to 2014) is done to evaluate the vulnerability to climate hazards including droughts and heatwaves. Analysis of the changes in future climate revealed a rapid increase in the occurrence of droughts and heatwaves towards the end of the century, affecting several communities in the region. Following the methodology developed by the Implementation Platform of the EU Mission on Adaptation to Climate Change (MIP4Adapt), the climate risk and vulnerability of local communities in the region is quantified. The results of this study provide critical information to stakeholders and the local communities to proactively prepare for the anticipated climate risks in the future and to adopt appropriate mitigation measures.

How to cite: Vijayan Nair, A., Dobariya, R., Gurung, D. R., and Nikolopoulos, E.: Assessment of future climate risk and vulnerability of local communities in High Mountain Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20988, https://doi.org/10.5194/egusphere-egu24-20988, 2024.

EGU24-21687 | Orals | HS7.5 | Highlight

Understanding the dynamics of multi-sector impacts of hydro-meteorological extremes: a methods overview 

Mariana Madruga de Brito, Jan Sodoge, Alexander Fekete, Michael Hagenlocher, Elco Koks, Christian Kuhlicke, Gabriele Messori, Marleen de Ruiter, Pia-Johanna Schweizer, and Philip J. Ward

Hydro-meteorological extremes, such as droughts and floods, often trigger a series of compound and cascading impacts due to interdependencies between coupled natural and social systems. However, studies typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to inform effective adaptation planning. Here, we present a collection of methods that can be used for assessing the dynamics of the multi-sector compound and cascading impacts (CCI) of hydro-meteorological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary or even convergent roles for analyses based on quantitative (e.g. data-mining, systems modeling) and qualitative methods (e.g. mental models, qualitative storylines). The data-driven and knowledge-driven methods provided here can serve as a useful starting point for understanding the dynamics of both high-frequency CCI and low-likelihood but high-impact CCI.

How to cite: Madruga de Brito, M., Sodoge, J., Fekete, A., Hagenlocher, M., Koks, E., Kuhlicke, C., Messori, G., de Ruiter, M., Schweizer, P.-J., and Ward, P. J.: Understanding the dynamics of multi-sector impacts of hydro-meteorological extremes: a methods overview, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21687, https://doi.org/10.5194/egusphere-egu24-21687, 2024.

EGU24-969 | ECS | Posters on site | HS6.6

Integration of Sentinel-1 and Sentinel-2 Datasets for River Discharge Estimation 

Ceren Yazıgülü Tural, Koray K. Yilmaz, and Angellica Tarpanelli

Rivers are corridors of freshwater that provide vital services for sustainable development and ecosystem functioning. Moreover, increase in frequency and severity of droughts and floods due to climatic change necessitates innovative and reliable techniques enabling continuous monitoring of river discharge to effectively manage risk. Since ground-based flow gauging stations are difficult to install and maintain, especially in remote regions, remote sensing methodologies have gained attention over the last decades.

In this study, we integrate Sentinel-1 Synthetic Aperture Radar (SAR) data and Sentinel-2 optical data to make best use of their advantages, namely, observation capability on cloudy-days and higher spatio-temporal resolutions, respectively. In our methodology, we first identify the water surface area at selected river reaches where flow observations are also available. The conceptual framework for computing water surface areas within the specified study boundaries entails the utilization of water indices, specifically the Normalized Difference Water Index (NDWI) and Modified Normalized Water Index (MNDWI), for Sentinel-2 and histogram-based backscattering intensity thresholding for the Sentinel-1 platform. Later, we establish relationships between the computed surface water areas and corresponding flow measurements. The Google Earth Engine (GEE) platform serves as the operational foundation for executing the methodology. We validate the satellite-based discharge estimations using observed in-situ discharge data obtained from three selected USGS gauging stations along the Mississippi River, USA. According to our preliminary results, the coefficient of determination values between estimated and observed discharge datasets range between 0.49-0.79, 0.44-0.77 and 0.49-0.74 for the studied river reaches. The methodology is being tested for other river reaches along the globe to test and improve its river discharge estimation accuracy.

How to cite: Tural, C. Y., Yilmaz, K. K., and Tarpanelli, A.: Integration of Sentinel-1 and Sentinel-2 Datasets for River Discharge Estimation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-969, https://doi.org/10.5194/egusphere-egu24-969, 2024.

EGU24-1141 | ECS | Orals | HS6.6

Towards Accurate Flood Mapping in Arid Regions: Sentinel-1 SAR-based insights and explainable machine learning.  

Shagun Garg, Antara Dasgupta, Sakthy Selvakumaran, Mahdi Motagh, and Sandro Martinis

Floods are not only frequent but also one of the costliest natural disasters. The use of satellite remote sensing is a cost-effective and widely adopted method for near real-time flood monitoring. Optical satellite imagery excels at distinguishing water from other land cover types by leveraging the spectral behavior in visible and infrared ranges. However, a major limitation of optical sensors is their inability to penetrate through clouds. This results in images with missing information, impeding their use for flood monitoring. In the past decade, Sentinel-1 Synthetic Aperture Radar (SAR) imagery has emerged as a valuable tool in operational flood management, overcoming the challenges posed by optical sensors. SAR is an active imaging technique that provides cloud-free images day and night by utilizing specular reflection from smooth water surfaces. In SAR imagery, water appears dark due to its unique backscatter characteristics. While SAR amplitude has been widely used for flood detection and monitoring, it tends to overestimate flooded areas, especially in arid and semi-arid regions, because the radar backscatter over sand and open water surfaces is similar. 

In our study, we explore the potential of Sentinel-1 amplitude and interferometric coherence in arid-flood mapping. We conduct multiple case studies and employ the random forest method to train, test, and validate our model predictions against flood masks derived from cloud-free optical imagery. We design several scenarios to investigate the contribution of different layers of information in improving flood mapping accuracy in arid regions along with feature importance analysis to understand the role of each feature to reduce model complexity. Our results demonstrate the effectiveness of fusing amplitude and coherence information in flood mapping,  as compared to coherence or amplitude alone. By utilizing the key features derived using permutation feature importance, flood mapping accuracy was significantly improved by approximately 50%, while also reducing response time, which is crucial for effective emergency management. The findings hold promise and emphasize the versatility of the proposed approach across different sensors and scenes. This offers significant potential for global flood mapping in arid regions, particularly in countries with limited resources. As future missions and advancements in SAR systems continue to evolve, the detection capabilities for floods will further improve, leading to enhanced flood management in arid areas. 

How to cite: Garg, S., Dasgupta, A., Selvakumaran, S., Motagh, M., and Martinis, S.: Towards Accurate Flood Mapping in Arid Regions: Sentinel-1 SAR-based insights and explainable machine learning. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1141, https://doi.org/10.5194/egusphere-egu24-1141, 2024.

EGU24-1789 | ECS | Posters virtual | HS6.6

Applicability Of Multi-National Digital Elevation Model (DEM) For Cross-Boundary Flash Flood Modeling 

Mohammedawel Jeneto Mohammed

In July 2021, the northwestern European continent experienced a devastating flood caused by unusually high rainfall, resulting in significant socio-economic destruction. One of the areas that was highly affected by this flooding was Southern Limburg (Geul River) in the Netherlands. The Geul River, located between Belgium, Germany, and the Netherlands, posed a challenging situation for modeling the catchment due to its cross-boundary nature. The need to harmonize input datasets from different countries with varying characteristics arose despite the abundance of available data in the study area. This study assesses the feasibility of combining multi-national Digital Elevation Models (DEM) for cross-boundary flash flood modeling purposes.

The quality of the DEM significantly impacts the accuracy of flood dynamics. However, it should be noted that elevation data from various sources creates elevation mismatches, particularly in the overlapping areas between different DEMs. A comprehensive quality assessment is indispensable to ensure the compatibility and reliability of these datasets for hydrology and flood modeling. Thus, To evaluate the accuracy of the DEMs, various statistical measures such as Root Mean Square Error (RMSE), Mean and Standard Deviation (STD) have been calculated. Initially, a pixel-by-pixel-based elevation difference map was generated. Upon analysis, it was observed that the overall elevation differences ranged from -7.0 to 7.0 meters. Despite certain pixels exhibiting pronounced differences in elevation, the overall statistical analysis indicated minimal variation. The calculated RMSE and STD values were both ≤ 0.3 meters for the overlapping parts of the DEM. These errors were considered negligible in relation to the actual slope values and had no significant impact on the flow direction within the catchment. This merged dataset provides a comprehensive representation of the terrain, enabling more accurate and reliable flood modeling simulations compared with calibrated result.

How to cite: Mohammed, M. J.: Applicability Of Multi-National Digital Elevation Model (DEM) For Cross-Boundary Flash Flood Modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1789, https://doi.org/10.5194/egusphere-egu24-1789, 2024.

EGU24-2941 | Posters on site | HS6.6

Use of Remote Sensing Flood Inundation Maps (FIM) for Evaluating Model-predicted FIM: Challenges and Strategies 

Sagy Cohen, Dan Tian, Anupal Baruah, Hongxing Liu, and Parvaneh Nikrou

Remote sensing (RS)-derived Flood Inundation Maps (RS-FIM) are, in principle, a desirable source of observed data for the development, calibration, and validation of (model) predicted FIM. Advantages of using RS-FIM for evaluating predicted FIM include its spatial continuity (compared to point observations), and the representation of real flooding events (compared to synthetic events (e.g. 100-yr) or other models). Disadvantages may include low/mismatched spatial resolution, insufficient classification accuracy, lack of water depth information, and gaps in coverage (due to dense vegetation, buildings, clouds, etc.). Gaps in inundation coverage are very common in RS-FIM. While these may not be a major issue for some RS-FIM applications, they are a major, yet unacknowledged, issue for fair and robust evaluation of predicted FIM. This is because the evaluated model may correctly predict flooding in these gaps while the (RS-FIM) benchmark data is classified as non-flooded (leading to inaccurate identification of 'False-positives'). Techniques for 'closing the gaps' in RS-FIM using hydraulic models or terrain analysis can yield improved FIM but, depending on the scale of the 'gap-filling', can result in an RS-model hybrid which undermines the observational nature of RS-FIM. Here we will demonstrate and discuss the challenges in using RS-FIM for the evaluation of predicted FIM and present tools and analysis demonstrating a new framework for fair and robust evaluation of FIM predictions using RS-FIM.

How to cite: Cohen, S., Tian, D., Baruah, A., Liu, H., and Nikrou, P.: Use of Remote Sensing Flood Inundation Maps (FIM) for Evaluating Model-predicted FIM: Challenges and Strategies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2941, https://doi.org/10.5194/egusphere-egu24-2941, 2024.

EGU24-4031 | Orals | HS6.6 | Highlight

 Satellite Video Remote Sensing for Flood Model Validation  

Christopher Masafu and Richard Williams

Satellite-based optical video sensors are poised as the next frontier in remote sensing. Satellite video offers the unique advantage of capturing the transient dynamics of floods with the potential to supply hitherto unavailable data for the assessment of hydraulic models. A prerequisite for the successful application of hydraulic models is their proper calibration and validation. In this investigation, we validate 2D flood model predictions using satellite video-derived flood extents and velocities. Hydraulic simulations of a flood event with a 5-year return period (discharge of 722 m3 s-1) were conducted using HEC-RAS 2D in the Darling River at Tilpa, Australia. To extract flood extents from satellite video of the studied flood event, we use a hybrid transformer-encoder convolutional neural network (CNN)-decoder deep neural network. We evaluate the influence of test-time augmentation (TTA) – the application of transformations on test satellite video image ensembles, during deep neural network inference. We employ Large Scale Particle Image Velocimetry (LSPIV) for non-contact-based river surface velocity estimation from sequential satellite video frames.When validating hydraulic model simulations using deep neural network segmented flood extents, critical success index peaked at 94% and on average improved by 9.5% when TTA was implemented. We show that TTA offers significant value in deep neural network-based image segmentation, compensating for aleatoric uncertainties. The correlations between model predictions and LSPIV velocities were reasonable and averaged 0.78. Overall, our investigation demonstrates the potential of optical space-based video sensors for validating flood models and studying flood dynamics.

How to cite: Masafu, C. and Williams, R.:  Satellite Video Remote Sensing for Flood Model Validation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4031, https://doi.org/10.5194/egusphere-egu24-4031, 2024.

EGU24-5438 | ECS | Posters virtual | HS6.6

A novel framework for the selection of spectral input to pixel-based river discharge estimation model using Sentinel-2 imagery 

Amirhossein Tayebi-Alashti and Mohammad Danesh-Yazdi

While access to discharge data is key to hydrologic studies, it is a serious obstacle in ungauged basins. Currently, Sentinel-2 imagery at high spatiotemporal resolution offers a unique opportunity to infer the relation between pixel-based discharge rate and surface reflectance. One promising approach in this respect has been to find the complex relationship between river discharge and the spectral ratio between two benchmark pixels, namely the wet and dry pixels, whose dynamics resembles river discharge variation. However, this has been challenging due to the adverse impact of soil moisture and mixed land cover on the spectral behavior of the dry pixel. The selection of the wet pixel must also guarantee sufficient sensitivity of its spectral response to water depth fluctuations. To tackle the above issues, in this study, we developed a novel framework that automatizes the selection of the wet and dry pixels by using Sentinel-2 imagery. We also introduced the Normalized Difference Discharge Index (NDDI), as the best band combination, to predict river discharge. We used linear regression with leave-one-out cross-validation as the prediction model, which leverages limited satellite data due to the cloud cover. By implementing the developed framework at multiple gauged points across the continental United States, the best location of the dry pixel was consistently found in urban pixels whose longwave reflectance fall within a certain range. By analyzing the pixel-wised correlation coefficient between surface reflectance at NIR band and river discharge across the studied river widths, we found that the best wet pixels are located along river banks with shallow water depth. These pixels were characterized by the average reflectance higher than the 98th percentile in the green band. Finally, by testing over 4000 band combinations as input to the river discharge prediction model, we found that the normalized difference between B11 and B4 for the wet pixel, as well as the B11 ratioing between the dry and wet pixels yielded the most accurate predictions with R2 = 0.88 and R2 = 0.73, respectively.

How to cite: Tayebi-Alashti, A. and Danesh-Yazdi, M.: A novel framework for the selection of spectral input to pixel-based river discharge estimation model using Sentinel-2 imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5438, https://doi.org/10.5194/egusphere-egu24-5438, 2024.

EGU24-5543 | ECS | Posters on site | HS6.6

Satellite-based Mapping of Flood Extent in Denmark 

Mark Hansen, Jacob Vejby, and Julian Koch

Floods stand out as the most frequent and costly natural disaster in Europe. In the EU alone, there have been documented more than 1500 flood events since 1980, causing over 4300 deaths and more than €170 billion in economic damages.

Due to the compounded developments of urbanization and climate change, the frequency of floods is expected to increase with severe impacts, possibly endangering lives and leading to economic losses. Moreover, floods mobilize pollutants stored in the subsurface and urban areas. Thus, current efforts, such as coastal barriers, restoration of river courses, or resilient city and landscape planning, focus on reducing vulnerability and risks from flooding. But to implement such measures, detailed information on where and when flooding occurs is necessary. This study aims to improve and implement satellite-based mapping of flood extent under Danish conditions by presenting different methods and algorithms utilizing Sentinel-1 (S1) Synthetic Aperture Radar (SAR) imagery, digital elevation models (DEM) and river geometry. In the broader literature, various methods have been proven to successfully map flood extent, such as deep learning (DL) and change detection (CD) as employed in the Global Flood Awareness System. However, DL require extensive training and labeled data that are often not available, and CD is reliant on a comprehensive pre-processing procedure of antecedent satellite imagery or accompanied with a datacube-based algorithm that exploits the satellite orbit repetition. While these methods can provide excellent results, the steep data requirements and pre-processing procedures hinder practical usage. On the other hand, single-temporal image flood extent mapping algorithms relying on histogram analysis offering a straightforward approach potentially yielding satisfying results, especially when accompanied by techniques such as image decomposition, region-growing, active contour models or image texture algorithms. But for single-temporal image histogram analysis to work in an automated setup, the two main problems, namely class imbalance and class overlap must be addressed properly. This study proposes a novel approach for single-temporal image histogram analysis by combining automatic local histogram thresholding with two image decomposition techniques for image tiling using a quadtree and a novel combination of k-means clustering and box tiling. This study implements a bimodality test and a subsequent local-threshold selection using gaussian mixture modelling and kernel-density smoothening, followed by contextual segmentation using region-growing. Furthermore, a novel approach for improving flood extent segmentation using a combination of DEM information, geographical stream location and region-growing is presented. The proposed method is showcased for two different flood events in Denmark from 2015 to 2022 using 10 x 10 m interferometric wide swath S1 SAR imagery. Results are evaluated using Sentinel-2 optical imagery where available, and otherwise evaluated against high-precision permanent water maps. Moreover, we utilize gauged timeseries of stream water level to evaluate the temporal evolution of flood extent over the period of a flood event.  

How to cite: Hansen, M., Vejby, J., and Koch, J.: Satellite-based Mapping of Flood Extent in Denmark, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5543, https://doi.org/10.5194/egusphere-egu24-5543, 2024.

EGU24-6430 | ECS | Posters on site | HS6.6

A Stacking Ensemble Method for Comprehensive Flood Susceptibility Mapping in Yemen 

Mustafa Ghaleb, Ahmed Al-Areeq, Nabil Al-Areeq, Radhwan Saleh, Anas AbuDaqa, and Atef kawara

The necessity of flood risk mapping is critical for effective planning and disaster response, particularly in flood-prone regions like the Qaa'Jahran watersheds in Dhamar, Yemen. This research implements various machine learning methods, including Support Vector Machines (SVM), K-Nearest Neighbors (kNN), Random Forest (RF), Artificial Neural Networks (ANN), and Logistic Regression (LR), with the latter also functioning as the meta-model in our stacking ensemble approach for mapping flood susceptibility. The process began with creating a flood inventory map using SAR images and historical flood records. Our model integrates the individual strengths of each technique and employs a meta-model to synthesize their forecasts. This stacked ensemble approach demonstrated superior performance over each model alone, achieving a remarkable AUC score of 0.9848 compared to the individual scores of SVM, LR, kNN, ANN, and RF. It also surpassed two innovative models, ABRBF and TPOT, in accurately pinpointing all high-risk zones identified in historical flood data. This advancement in flood risk mapping for the Qaa'Jahran watersheds exemplifies the potential of our model in enhancing disaster management and prevention efforts. It offers a significant tool for identifying at-risk areas and guiding mitigation strategies to safeguard communities in Dhamar, Yemen, against the catastrophic impacts of flooding.

How to cite: Ghaleb, M., Al-Areeq, A., Al-Areeq, N., Saleh, R., AbuDaqa, A., and kawara, A.: A Stacking Ensemble Method for Comprehensive Flood Susceptibility Mapping in Yemen, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6430, https://doi.org/10.5194/egusphere-egu24-6430, 2024.

EGU24-8214 | ECS | Posters on site | HS6.6

Multi-source in situ and satellite variational data assimilation into a fully distributed hydrological model for floods and droughts modeling over poorly gauged and ungauged areas 

Mouad Ettalbi, Pierre-Andre Garambois, Nicolas Baghdadi, Emmanuel Ferreira, and Ngo-Nghi-Truyen Huynh

Estimating water flows and stocks in surface hydrology is crucial for addressing important socio-economic issues, such as managing water resources and predicting extreme events like floods and droughts. These challenges become more significant with the ongoing global climate change, which may intensify the hydrological cycle. Advanced modeling tools are necessary for making precise and reliable local forecasts. However, hydrological models, regardless of their complexity and status, encounter difficulties in accurately and reliably predicting quantities of interest such as river flows or soil moisture states, and in accounting for meteorological-climatic effects on hydrology. Given the complexity of the physical processes involved and their heterogeneous and limited observability, hydrological modeling is a challenging task, and internal flows often have significant uncertainties. These uncertainties could be reduced by integrating new observations from remote sensing applied to continental surfaces, which is rapidly evolving. A variety of satellites and sensors now allow the observation of watershed surface characteristics and hydrological responses with increasing spatial-temporal resolutions. In particular, products of soil moisture, evaporation, and land use are now available at relatively high spatial-temporal resolution. This work focuses on improving the integration of satellite and in-situ land surface data into spatially distributed hydrological models. The Hybrid Data Assimilation and Parameter Regionalization (HDA-PR) approach incorporating learnable regionalization mappings, based on neural networks into the differentiable hydrological model SMASH, is modified to account for satellite moisture maps in addition to discharge at gauging stations and basins physical descriptors maps. Regional optimizations are performed on flash-flood-prone areas located in the South of France and their accuracy and robustness is evaluated in terms of simulated discharge and moisture against observations. 

How to cite: Ettalbi, M., Garambois, P.-A., Baghdadi, N., Ferreira, E., and Huynh, N.-N.-T.: Multi-source in situ and satellite variational data assimilation into a fully distributed hydrological model for floods and droughts modeling over poorly gauged and ungauged areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8214, https://doi.org/10.5194/egusphere-egu24-8214, 2024.

Synthetic Aperture Radar (SAR) satellites have emerged as the predominant information source for large-scale flood mapping, owing to their ability to map the Earth's surface regardless of weather conditions. Additionally, the classification of permanent water bodies and inundated areas from SAR images appears to be relatively straightforward given that calm water surfaces show up as dark patches in SAR images. Yet, a naïve approach to water body and flood classification from single SAR images can be misleading for many reasons. Firstly, in most environments SAR sensors under-detect the surface water extent due to challenging land cover and rough water surfaces. Secondly, there are water-look-alike surfaces such as tarmac or grasslands that are misclassified as water. Last but not least, the definition of permanent water bodies, wetlands, and floods is not trivial and only possible when using historic observations as reference. Some of this challenges can be addressed by experts when classifying only a limited set of SAR images. However, the difficulty significantly increases when attempting to map water bodies and floods in a fully automatic manner without prior knowledge of the environmental conditions. This becomes essential, for instance, when investigating the dynamics of wetland areas or the recurrence of floods over extended time periods or regions, or when employing SAR data for near-real-time flood monitoring. In this presentation, I will provide an overview of these challenges, drawing on the outcomes of research on this topic carried out at TU Wien over the last two decades and the preliminary experiences gained from the operationalization of the new fully-automated Sentinel-1 based Global Flood Monitoring service, which is operated as one of the components of the Copernicus Emergency Management Service.

How to cite: Wagner, W.: Scientific challenges when using SAR images for mapping of water bodies and floods everywhere and anytime, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8642, https://doi.org/10.5194/egusphere-egu24-8642, 2024.

EGU24-11162 | ECS | Orals | HS6.6 | Highlight

Urban Flood Classification in SAR Images 

Rotem Mayo, Tal Ikan, and Adi Gerzi Rosenthal

Detecting flooding in Synthetic Aperture Radar (SAR) satellite imagery is crucial for the ability of Google’s flood forecasting team to train predictive models and identify regions at risk of flooding, making it possible to give prior warning to people in soon to be flooded areas.  However, flood detection in urban areas is currently very poor, preventing the extension of these advanced warning systems to large parts of the population. This is a long known challenge in the field of flood detection using remote sensing methods. In this study, we discuss a possible method to overcome this problem.

SAR satellites are preferred for flood monitoring due to their effectiveness regardless of weather or environmental conditions. They operate by sending pulse signals to Earth and measuring the reflected backscatter. Smooth surfaces like water typically reflect signals away, appearing darker in SAR images. However, in urban areas, the 'Double Bounce' effect caused by 90-degree surfaces, causes larger backscatter, making water detection challenging.

Our methodology involves analyzing abnormally bright pixels in urban areas, attributed to the amplification of the double bounce effect by flooding. We deviate from the traditional thresholding per image approach used in rural settings, instead focusing on the historical brightness levels of each pixel separately to identify significant deviations. We then aggregate the data over large urban areas to infer potential flooding.

We optimize and evaluate the model using a train-validation split of a dataset consisting of approximately 70 urban flood events, manually curated from news stories and paired with corresponding SAR images. The evaluation, which compares these images with randomly selected images, yields a precision of 86% and a recall of 62%.  Acquiring high quality ground truth data proved to be one of the big challenges in this project, and we are currently working on other ways to evaluate the model and improve its accuracy.

These results demonstrate the potential of using SAR images for urban flood classification by focusing on the unique characteristics of urban areas, such as the double bounce effect. This method shows promise in providing alerts and forecasts for urban regions, a crucial need for disaster management. Further research and more accurate ground truth data could enhance the effectiveness and accuracy of detecting urban floods through SAR images.

How to cite: Mayo, R., Ikan, T., and Gerzi Rosenthal, A.: Urban Flood Classification in SAR Images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11162, https://doi.org/10.5194/egusphere-egu24-11162, 2024.

EGU24-11215 | ECS | Posters on site | HS6.6

Flood inundation Mapping for the Sept. 2023 Derna, Libya flood event using Sentinel-1 SAR data: An Integration of SAR intensity and interferometric coherence 

M. Sulaiman Fayez Hotaki, Mahdi Motagh, and Mahmud Haghshenas Haghighi

Flood mapping, particularly in data-scarce regions, poses challenges including inadequate observational data to understand the hydrological characteristics of the floods. This study addresses this research gap by utilizing remotely sensed data, specifically Sentinel-1 Synthetic Aperture Radar (SAR) images, to delineate flood extent related to the September 11, 2023 Derna flood event in Libya. The objective is to extract flood extent from both SAR intensity and coherence and integrate these characteristics to generate a confidence flood map.

Our approach involves radiometric terrain correction of SAR data, flood pixel identification using anomaly detection techniques based on SAR intensity, and coherence analysis of pre-and post-flood SAR images. Flooded areas are categorized into 3 main classes. These include (1) High Confidence Flood (HCF), which is the intersection of SAR intensity and coherence in VV and VH bands in both Ascending and Descending directions; (2) Medium Confidence Flood (MCF), extracted from intensity and coherence in either the Ascending or Descending direction in both VV and VH bands; and (3) Low Confidence Flood (LCF), extracted from a single direction in either VV or VH band. LCF includes all pixels not confidently identified as part of either HCF or MCF.  The effectiveness of flood segmentation utilizing the integration of anomaly detection of SAR intensity and coherence analysis method is evaluated through a comparison between Sentinel-1 SAR data and optical Planet imagery.

Our findings indicate HCF covering approximately 8 hectares, MCF covering around 24 hectares, and LCF covering more than 227 hectares. These findings offer valuable insights into the observed flood extent at varying confidence levels. However, the moderate temporal resolution of Sentinel-1 data, with a revisit time of 12 days, introduces challenges in promptly detecting the entire extent of the flood. Overall, this study underscores the significance of remote sensing technology in near-real-time flood monitoring, emphasizing its role in identifying vulnerable areas, prioritizing resources, planning for potential risks, and supporting decision-making in relief efforts.

How to cite: Hotaki, M. S. F., Motagh, M., and Haghshenas Haghighi, M.: Flood inundation Mapping for the Sept. 2023 Derna, Libya flood event using Sentinel-1 SAR data: An Integration of SAR intensity and interferometric coherence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11215, https://doi.org/10.5194/egusphere-egu24-11215, 2024.

EGU24-13278 | Orals | HS6.6 | Highlight

Leveraging SWOT's water elevation pixel cloud to comprehend analyse the spatial dynamics of flood events 

Nicolas Gasnier, Roger Fjørtoft, Lionel Zawadzki, Damien Desroches, Santiago Pena Luque, Pottier Claire, Thérèse Barroso, and Picot Nicolas

Satellite data have been used for over 40 years, along with airborne and in situ measurements, for monitoring extreme hydrological events, and enabled major progress in our understanding of floods. The available satellite data have long been mostly limited to imagery (SAR, optical, and thermal) providing a map of the flood extent and conventional nadir altimetry providing a 1-dimensional water elevation along the satellite ground track. Since its launch in late 20232, SWOT has opened a new dimension in space altimetry by providing two-dimensional maps of water elevation. Its main instrument is a near-nadir, bistatic, Ka-band SAR altimeter that uses interferometry to measure the elevation of the water pixels (10-60x22m resolution). Although its revisit time (at least twice per 21-day nominal cycle up to 78° latitude) and spatial resolution limits its usability for operational flood monitoring, SWOT opens new perspectives in the understanding of flood dynamics, particularly if used in synergy with high-resolution imagery and real-time in situ measurements. Indeed, water elevation maps can be used to calibrate and validate hydraulic models through their comparison with the elevation of the modeled free surface at the corresponding point in time. In addition, estimations of the river flows are part of the standard SWOT products distributed on the PODAAC and hydroweb.next platforms.

While the early results on recent flood events demonstrated the utility of the SWOT data for understanding the dynamics of floods, research efforts are still needed to fully leverage its scientific and socioeconomic benefits. On the one hand, there is a scope for improvement in the production of the water elevation pixel cloud from the SLC images: the baseline data processing is dedicated to lakes and river monitoring, and custom processing for flood events may improve the quality of the water elevation data in flooded areas. On the other hand, due to their relative novelty, further adaptations will be needed to operationalize their use for key applications (e.g., more accurate modeling of floods to engineer flood-risk infrastructure, assimilation in operational hydraulic models along with other sources of data, improved risk assessment on buildings through better forecasting of water levels,...). Further research works will be able to draw on SWOT's open data, including the calibration and validation phase, which lasted from end of  March to early July 2023 on selected orbits with a 1-day repeat cycle. This phase enabled SWOT acquisitions every 24 hours for multiple flood events, including the flooding caused by the destruction of the Kakhovka Dam in Ukraine. This high temporal revisit allows for fine-scale analysis of the temporal evolution of the water elevation of the flooded area.

In our contribution, we will present early results on selected examples of flood events, and some scientific and technical issues that we believe to be of particular interest.

How to cite: Gasnier, N., Fjørtoft, R., Zawadzki, L., Desroches, D., Pena Luque, S., Claire, P., Barroso, T., and Nicolas, P.: Leveraging SWOT's water elevation pixel cloud to comprehend analyse the spatial dynamics of flood events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13278, https://doi.org/10.5194/egusphere-egu24-13278, 2024.

EGU24-13550 | ECS | Posters on site | HS6.6

Initial steps towards implementation of an early warning system with distributed hydrologic-hydrodynamic modeling for an urban basin with quantitative precipitation estimation (QPE) from meteorology radar. 

Mateo Hernandez Sanchez, Luis Miguel Castillo Rapalo, Pedro Gustavo Silva, and Eduardo Mario Mediondo

Continuous megacities' development, aging infrastructure, and increasing frequency and magnitude of extreme events, the lack of flood resilience becomes a pressing issue due to inadequate planning of existing hydraulic structures to handle future threats. A more resilient urban flood risk management strategy is required to efficiently mitigate the impacts of climate change, particularly floods resulting from river and urban channel overflows. This is evident within the Aricanduva River watershed area in the east zone of São Paulo City, Brazil, a region with flood challenges arise because existent hydraulic infrastructures are ineffective in inundation control, due to extensive urbanization in the lower and middle parts of the basin. To achieve resilience in urbanized areas and reduce the risk of flash floods, the development of Early Warning Systems (EWS) is crucial. An EWS serves as a predictive tool for accurately forecasting water levels in rivers or channels in real-time, providing enough time to take action in order to reduce potential risk. Hydrologic-hydrodynamic models are increasingly employed in EWS to enhance their effectiveness. However, many urban basins lack monitoring systems, whereas products such as meteorological radar represent a feasible option since they effectively capture the spatial and temporal distribution of rainfall. In urban basins like the Aricanduva River, where the quantity and distribution of pluviometers are insufficient to spatially represent an event, the use of Quantitative Precipitation Estimation (QPE) from meteorology radar becomes essential to improve hydrological-hydrodynamic analyses. The objective of this work is to propose the presentation of a distributed hydrological-hydrodynamic model (HydroPol2D) for the Aricanduva basin, calibrated with QPEs from meteorological radar. Additionally, rainfall data from 15 gauges within and around the basin were utilized, covering a 5-year period, to generate spatial rainfall using Inverse Distance Weighted (IDW) interpolation. The results of the two rainfall databases were compared using metrics such as the Nash-Sutcliffe efficiency index, Efficiency of Kling-Gupta (KGE) index, and the percentage of bias to assess model accuracy. The findings indicate that (i) the distributed model coupled with QPEs produces favorable results and better represents the basin's dynamics, (ii) the model accurately reflects the hydraulics of existing flood control infrastructure within the basin, and (iii) the generation of an accurate and rapid rainfall-runoff model forms the initial steps in identifying risk areas, establish critical points for the early warning systems and analyzing the factors contributing to or generating the risk. The next step of this work is to assess the model with more events and to include in the model strategies to automate flow control in existing flood control infrastructures.  

Keywords: Urban flooding risk management, Early Warning Systems (EWS), Hydrological-hydrodynamic models, Radar Quantitative Precipitation Estimation (QPE), Climate Change.

How to cite: Hernandez Sanchez, M., Castillo Rapalo, L. M., Silva, P. G., and Mediondo, E. M.: Initial steps towards implementation of an early warning system with distributed hydrologic-hydrodynamic modeling for an urban basin with quantitative precipitation estimation (QPE) from meteorology radar., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13550, https://doi.org/10.5194/egusphere-egu24-13550, 2024.

EGU24-13922 | Orals | HS6.6

Developing near-real time flood mapping capabilities in Australia 

Jiawei Hou, Wendy Sharples, Luigi Renzullo, Fitsum Woldemeskel, Christoph Rudiger, and Elisabetta Carrara

Floods rank as the second-most deadly natural hazard in Australia, surpassed only by heatwaves. The ability to monitor flood extent and depth in near real-time is key to mitigating the loss of human life and minimizing the adverse socio-economic and environmental impacts. This study aims to discover the best way to map flood extent and depth in near-real time based on the most up-to-date  available information (i.e., gauge data, hydrological and hydrodynamic models, earth observations) in Australia. High resolution (i.e., 1-5 metres) airborne LiDAR DEMs are available across most of Australia's flood-prone east coast regions. The accessibility  of this information facilitates the creation of detailed, LiDAR-derived Height above Nearest Drainage (HAND) maps, which serve as an essential baseline for accurately mapping flood events. In gauged catchments, we utilized the Bureau of Meteorology’s environmental data management system, WISKI, an API solution that provides access to in-situ water levels at gauged locations across Australia. In ungauged catchments, we routed the Bureau’s operational runoff simulations (AWRA-L v7) using CaMa-flood to estimate flood level dynamics. By integrating these estimates into the HAND mapping approach, we generated a dynamic temporal profile of flood events in near-real time, effectively capturing the spatial-temporal onset, peak, and recession stages of flooding - essential information for emergency services. As the accuracy of the modelling approach is affected by uncertainties from runoff simulation and river morphology parameters, we additionally develop a multi-satellites-based flood monitor system to bolster the accuracy of modelled information. This system utilizes data from multiple medium-resolution satellite sources, including Sentinel-1 and -2, and Landsat -7 and -8/9. By extracting updated remote sensing imagery from Google Earth Engine and Digital Earth Australia, our approach simplifies and optimizes the process of deriving flood extent and depth from satellite and airborne LiDAR observations. Notably, this remote sensing approach significantly reduces interference from clouds, cloud shadows, terrain shadows, and vegetation cover, which are common challenges in optical remote sensing. Additionally, it effectively mitigates the 'double-bounce' effects often caused by vegetation and buildings in Synthetic Aperture Radar (SAR). To verify our end to end near real time flood mapping product, we used ICEYE (commercial SAR company) flood product to benchmark flood maps derived in this study and assessed the feasibilities of developing near-real time flood mapping network in Australia. Crucially, the immediate availability of data is essential in facilitating efficient allocation of resources and safeguarding infrastructure. Simultaneously, near real-time flood mapping plays a crucial role in enhancing community preparedness, allowing for strategic planning and swift action in response to hazardous situations.

How to cite: Hou, J., Sharples, W., Renzullo, L., Woldemeskel, F., Rudiger, C., and Carrara, E.: Developing near-real time flood mapping capabilities in Australia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13922, https://doi.org/10.5194/egusphere-egu24-13922, 2024.

EGU24-14669 | ECS | Posters on site | HS6.6

Improving 2D hydraulic modeling in floodplain areas with ICESat-2 data: A case study in Upstream Yellow River 

Monica Coppo Frias, Suxia Liu, Xingguo Mo, Daniel Druce, Dai Yamazaki, Aske Folkmann Musaeus, Karina Nielsen, and Peter Bauer-Gottwein

Climate change intensifies the occurrence of severe flood events, increasing the demand for flood modeling studies. Hydrodynamic models can effectively represent flood events, but they are limited by the quality of available observations. Accurate topographic elevation is essential to replicate channel-floodplain interaction. Elevation is normally retrieved using satellite-based DEMs. However, freely available DEMs have a low spatial resolution, which is a limitation in identifying small-scale channel features in complex floodplain topography. In addition, these products can present issues such as vertical offset, random noise, or vegetation biases. These issues can lead to large errors when used in hydraulic modeling to simulate water levels and inundation extent. FABDEM is a 1 arcsec DEM, that removes forest and building artifacts from Copernicus DEM, but to map complex floodplain topography, finer resolution is needed. ICESat-2 mission offers a large spatial coverage with an along-track resolution down to 70 cm in the ATL03 product. This data product has shown great potential when mapping river topography and identifying small-scale channel features. ATL03 can be used as a control point dataset, to correct biases and refine DEMs

To improve the accuracy of 2D hydraulic models, FABDEM was corrected on selected floodplain areas using supplementary data and machine learning methods. Artificial Neural Network (ANN) was used in the correction of FABDEM. This regression algorithm can predict differences between FABDEM floodplain elevation and ATL03 reference elevation, inputting data from Sentinel-2 and water occurrence maps produced from spectral and SAR imagery. The output floodplain elevation has a reduced vertical offset and a spatial resolution of 10 m, which can detect small-scale channel features. Flood inundation was simulated using the updated DEM. The high computational cost of 2D hydraulic models is a limitation when using discharge time series. To deal with computational cost, discharge classes were defined to represent different inundation scenarios that provide a good indicator for flood risk management, and steady-state inundation patterns were simulated for each discharge class.

The method is demonstrated in a section of the Upstream Yellow River characterized by large floodplains with complex topography, and small-scale channels. Discharge observations from the Jimai in-situ station are used to define discharge classes. The discharge classes are defined by calculating the exceedance probability of a discharge value. The inundation scenarios are simulated for high flow discharge values for an exceedance probability of 25% (Q25) and 10% (Q10), and medium flow discharge values with 50% (Q50), and are compared with the corresponding water occurrence map produced from spectral and SAR imagery for the given discharge class. The critical success index (CSI) of the inundation map improves by about 5% using FABDEM corrected version for Q10 and Q25, and about 4% for Q50. In addition, we observe a consistent Bias reduction of about 20% for Q10 and Q25.

How to cite: Coppo Frias, M., Liu, S., Mo, X., Druce, D., Yamazaki, D., Folkmann Musaeus, A., Nielsen, K., and Bauer-Gottwein, P.: Improving 2D hydraulic modeling in floodplain areas with ICESat-2 data: A case study in Upstream Yellow River, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14669, https://doi.org/10.5194/egusphere-egu24-14669, 2024.

EGU24-15280 | ECS | Posters on site | HS6.6

Flood risk assessment in the Ganga Basin, India: A multi-criteria geospatial analysis with NASA’s Black Marble Nighttime light Data 

Ekta Aggarwal, Marleen C. de Ruiter, Sophie Buijs, Alexander C. Whittaker, Sanjeev Gupta, Kartikeya S. Sangwan, and Ranjay Shrestha

Changing climate, intense rainfall, and geomorphological conditions within the Indo-Gangetic Basin (IGB) have led to recurring flooding within the area in the recent past. The devastating August 2022 floods in Pakistan affected 33 million people causing severe loss of life and property. The occurrence of such flooding events has increased the need to understand the complexities of the interplay between flood hazards, exposure, vulnerability, and risk. This study delves into flood risk within India's Ganga Basin, examining the flood-inducing factors, vulnerability, and exposure through an innovative approach using NASA's Black Marble Nighttime Lights Product Suite (VNP46).  The product suite, available globally on daily, monthly, and annual composite scales, corrects extraneous sources of noise in nighttime light (NTL) radiance signals and has proven effective in disaster monitoring, risk assessment and reduction, humanitarian response, preparedness, resilience, and sustainable development.

Our work to date has successfully utilized these NTL data to quantify flood exposure and the impact of flooding in both urban and rural areas by analyzing changes in radiance across time and space. However, to improve our understanding of human response to floods, we now focus on a more intricate analysis: incorporating geomorphological and socio-hydrological factors into a risk assessment approach.

Our study evaluates flood hazard, exposure, and vulnerability as three separate entities and combines them using a multi-criterion decision tool to assess flood risk within the basin. Flood hazards are studied as a relationship between geomorphological and hydrological parameters, whereas flood vulnerability is studied using land use and land cover data. The novelty of this research is using NASA’s Black Marble nightlights as a proxy to study flood exposure. We argue that the NTL data can more effectively capture the human presence and economic activities compared to some conventional parameters for flood exposure such as population count, household density, and literacy amongst others. By integrating these diverse data layers using the robust Analytical Hierarchical Process (AHP), we generate comprehensive flood risk maps across the Ganga Basin spanning a decade. The accuracy of these maps is validated against historical flood event data from the EM-DAT database. Ultimately, our research culminates in a spatially explicit and data-driven approach to flood risk assessment, which can empower targeted mitigation strategies and proactive planning within the basin.

How to cite: Aggarwal, E., de Ruiter, M. C., Buijs, S., Whittaker, A. C., Gupta, S., Sangwan, K. S., and Shrestha, R.: Flood risk assessment in the Ganga Basin, India: A multi-criteria geospatial analysis with NASA’s Black Marble Nighttime light Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15280, https://doi.org/10.5194/egusphere-egu24-15280, 2024.

EGU24-15378 | Orals | HS6.6 | Highlight

Earth Observation-Driven Flood Response for Emilia-Romagna: The SaferPlaces Platform 

Paolo Mazzoli, Valerio Luzzi, Marco Renzi, Marianne Bargiotti, Sabrina Outmani, Stefania Pasetti, Stefano Bagli, and Francesca Renzi

In May 2023, the region of Emilia-Romagna, Italy, experienced an unprecedented hydrological event when 350 million cubic meters of rain fell over 36 hours, leading to widespread flooding and landslides. This disaster, affecting 100 municipalities, was compounded by antecedent drought conditions that had decreased the soil's water absorption capacity. Earth observation (EO) data became critical, providing emergency services with the means to assess and manage the catastrophe and facilitate post-event damage evaluation.

The SaferPlaces platform, supported by the ESA InCubed programme, played a pivotal role in disaster response. It provided the Civil Protection of Emilia-Romagna with high-resolution flood water and depth maps, crucial for decision-making in the aftermath of the floods. This cloud-based platform integrates satellite data, climatic records, and AI algorithms to generate global flood forecasts.

Leveraging AI, SaferPlaces processed terrain data alongside inundated area information, combining in situ measurements with satellite data from Copernicus Sentinel-2, CosmoSky-Med, Planet, and SPOT. This was further enriched with local data from municipalities and the Emilia-Romagna Civil Protection, enhancing urban flood area accuracy.

Detailed maps illustrating flood extent in the severely hit municipalities of Faenza, Cesena, Forlì, and Conselice were generated. These contained vital data on water depth and volume, forming the basis for a preliminary Flood Damage Assessment. These assessments were crucial for authorities to estimate economic losses swiftly.

The suite of tailored algorithms within SaferPlaces, extracts flood water masks from satellite imagery. This module, accessible on-demand through a user-friendly interface, requires few parameters from users to accurately delineate flooded areas and contribute to the Global Flood Monitoring system.

The main workflow of algorithm includes the GFM procedure for baseline flood extent retrieval, the Hydraflood method for flood mask extraction via GEE, and the CommSNAP pipeline for processing commercial data. The final output is a flood mask for the area and event of interest, which can also feed into the GFI model to identify flood-prone areas.

This study underscores the essential role of integrated EO and AI technologies in managing hydrological disasters. The SaferPlaces platform's capacity to synthesize multi-source data and provide actionable intelligence marks a milestone in the power of interdisciplinary approaches in enhancing disaster resilience and preparedness.

How to cite: Mazzoli, P., Luzzi, V., Renzi, M., Bargiotti, M., Outmani, S., Pasetti, S., Bagli, S., and Renzi, F.: Earth Observation-Driven Flood Response for Emilia-Romagna: The SaferPlaces Platform, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15378, https://doi.org/10.5194/egusphere-egu24-15378, 2024.

EGU24-15446 | ECS | Posters on site | HS6.6

Floods automatic rapid mapping through Sentinel-2 MSI multitemporal data 

Valeria Satriano, Emanuele Ciancia, Nicola Pergola, and Valerio Tramutoli

Floods are widespread natural disasters on Earth affecting the planet with increasing frequency and intensity. Climate changes are responsible of the increasing number of heavy and persistent rains generating these destructive events often resulting in fatalities, injuries, and extensive infrastructural damages. A near real time monitoring system able to provide timely and accurate information about location and extent of the flooded areas is crucial for the authorities to implement the right mitigation actions. Currently, the Copernicus Emergency Management Service (CEMS) supports at European level the crisis management activities in the immediate aftermath of a flood, exploiting multi-source satellite data to provide flood delineation with a release time ranging from 7 to 48 hours (from the satellite acquisition). Map characterization and relative information are retrieved through semi-automatic or manual methodologies which do not allow for a complete automation of the analysis crucial to speed up the procedure and shorten the release time.

In this study, carried out in the framework of the MITIGO project (funded by MIUR PON R&I 2014-2020 Program), results coming from a multi-temporal optical satellite technique able to quick detect and accurately map flooded areas will be presented. This technique, namely RST-Flood, exploits the statistical characterization of the satellite observed signal to retrieve accurate background information useful to promptly and automatically identify ground changes directly linked to events occurrence. RST-Flood has already been successfully implemented with mid-low spatial resolution (from 1000 to 375m) optical satellite data sensors (i.e., Advanced Very High Resolution Radiometer, Moderate Resolution Imaging Spectroradiometer, Visible Infrared Imaging Radiometer Suite), and here is for the first time exported to Sentinel-2 Multi Spectral Instrument (MSI) data at mid-high spatial resolution (20m) to study recent floods events. The achieved results demonstrated the easy implementation of RST-Flood to different sensors and geographic areas and its capability in providing fast (processing time less than 15 min from data availability) and robust mapping of flooded areas. Furthermore, its design developed to work in the Google Earth Engine (GEE) environment makes it suitable for global scale implementation without altering its performance.

How to cite: Satriano, V., Ciancia, E., Pergola, N., and Tramutoli, V.: Floods automatic rapid mapping through Sentinel-2 MSI multitemporal data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15446, https://doi.org/10.5194/egusphere-egu24-15446, 2024.

EGU24-15576 | ECS | Posters virtual | HS6.6

Resilience Assessment of Flood Detention Zones in the 2023 catchment-scale floods in Hai River Basin, China 

Yiling Lin, Xie Hu, Fang Wang, and Yong Zhao

As a typical flood-prone area, the Hai River Basin (HRB) in the Beijing-Tianjin-Hebei metropolis of China has been struck by devastating floods in history. Since the 1960s, a series of flood-control programmes in the HRB have been launched to reduce the flood risks. As planned, flood detention zones serve as the last line by storing and detaining floodwaters when the water levels exceed the defense limits of reservoirs, levees, and diversion channels. Land use crisis has been a long-lasting problem in China. People are allowed to use the flood detention zones as their residential communities when these zones are not in use. A dual role played by these specific zones requires not only an effective floodwater storage in response to floods, but also an efficient floodwater recession in the aftermath of floods. However, we lack a quantitative assessment of the functionability of flood detention zones. Our study synergizes multi-source SAR images from Sentinel-1 and Gaofen-3 satellites in the framework of deep learning to accurately and efficiently extract inundation paths which evolved for two months encompassing HBR. A joint use of digital elevation model allows us to recover the three-dimensional inundation structures. We also propose the flood detention resilient coefficient based on our derived lifespan of floodwaters. Our results demonstrate that the flood detention zones in HRB can effectively trap the floodwater within to secure lives and properties, but resilience of some flood detention zones can still be improved.

How to cite: Lin, Y., Hu, X., Wang, F., and Zhao, Y.: Resilience Assessment of Flood Detention Zones in the 2023 catchment-scale floods in Hai River Basin, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15576, https://doi.org/10.5194/egusphere-egu24-15576, 2024.

EGU24-16923 | ECS | Posters on site | HS6.6

Flood Segmentation with Optical Satellite Images Under Clouds Using Physically Constrained Machine Learning 

Chloe Campo, Paolo Tamagnone, Guillaume Gallion, and Guy Schumann

Timely and accurate flood map production plays a key role in enhancing effective flood risk assessment and management. Satellite imagery is frequently employed in flood mapping as it can capture flooding across vast spatial and temporal scales. Floods are usually caused by prolonged or heavy precipitation correlated with dense cloudy conditions, posing challenges for accurate mapping.

The Synthetic Aperture Radar (SAR) active sensor is a popular option due to its feature of being weather agnostic, penetrating through clouds, fog, and darkness, providing images for the detection of flooded areas regardless of the weather conditions. However, this advantage is at the expense of low temporal resolution and double bounces in urban and heavily vegetated areas, which increase signal processing difficulty and misinterpretation. Passive microwave radiometry has also been explored for flood mapping, but its coarse spatial resolution limits the utility of the resulting flood maps. Multispectral optical imagery offers a balanced trade-off between temporal and spatial resolutions, with the only limitation that the acquired images might be hindered by the presence of clouds. Capitalizing on the utility of optical imagery, FloodSENS, a machine-learning (ML) algorithm consisting of a SENet and UNet, precisely delineates flooded areas from non-flooded areas in clear and partially clouded optical imagery. Although the current algorithm version enforces flood delineation involving topography-derived information in the ML processing, it is not capable of detecting floods under clouds; thus, we propose a new iteration of FloodSENS that utilizes auxiliary data in post-processing to improve the inferred flood maps.

The post-processing pipeline utilizes the inferred flood map generated by FloodSENS and the Digital Elevation Model (DEM) of the target area to accurately delineate the flood extent beneath clouds, adhering to the physical constraints in the topography. First, Pixels at elevations equal to or lower than the water level are designated as flooded pixels. These pixels are further refined with geoprocessing to establish hydrological connectivity and topographic consistency. Pixels that are both marked as flooded and hydrologically connected are confirmed as flooded pixels for the final flood map.

The post-processing proves essential in tropical and subtropical regions that frequently have high cloud cover during the monsoon seasons, making it imperative to map the affected areas during flooding events. The FloodSENS detection with the post-processing pipeline has been tested on partly clouded optical imagery obtained from the 2023 autumn flooding in southern Somalia.

How to cite: Campo, C., Tamagnone, P., Gallion, G., and Schumann, G.: Flood Segmentation with Optical Satellite Images Under Clouds Using Physically Constrained Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16923, https://doi.org/10.5194/egusphere-egu24-16923, 2024.

EGU24-16998 | ECS | Posters virtual | HS6.6

Assessing the sensitivity of geomorphological attributes to DEM source and Spatial Resolutions  

Saroj Rana and Sagar Rohidas Chavan

Digital Elevation Models (DEMs)are used for extracting the geomorphological attributes of catchments. These attributes play crucial role in determining the hydrological responses of the catchments. However past research has highlighted the sensitivity of the geomorphological attributes to various DEM sources as well as special resolutions. This study is envisaged to assess the impact of different DEM sources and DEM resolutions on geomorphological attributes proposed by Moussa (2008) on Upper Yamuna River Basin which flows in 5 states (Uttarakhand, Himachal Pradesh, Uttar Pradesh, and Haryana) of India. For this purpose, different DEM sources, Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) DEMs are used. To investigate the impact of DEM spatial resolution, 5 different resampled scenarios (grid size 90m, 120m, 150m, 180m, 210m) for each source of DEM was considered using the SRTM 30m DEM as a base DEM. The comparative assessment revealed notable discrepancies in the derived attributes among the DEMs of different resolutions and sources. The evaluation of variation in geomorphological attributes derived from various DEM sources and resolutions, yielded insightful observations. Furthermore, variations were observed between the different satellite sources, highlighting inherent differences in elevation data acquisition and processing methodologies. These findings underscore the critical influence of spatial resolution and data source on the accuracy and reliability of geomorphological attributes derived from DEMs, emphasizing the significance of careful consideration in selecting DEMs for terrain analysis and related applications.

How to cite: Rana, S. and Chavan, S. R.: Assessing the sensitivity of geomorphological attributes to DEM source and Spatial Resolutions , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16998, https://doi.org/10.5194/egusphere-egu24-16998, 2024.

EGU24-18873 | ECS | Orals | HS6.6 | Highlight

A Comparative Analysis of Flood Frequency Mapping Approaches for Climate-Resilience in South Sudan 

Ignacio Borlaf-Mena, Èlia Cantoni, Antonio Franco-Nieto, Marta Toro-Bermejo, Beatriz Revilla-Romero, Antonio Rodriguez Serrano, Lukas Loescher, Danielle Monsef Abboud, Carlos Domenech, and Clément Albergel

In 2022, South Sudan was ranked as the world’s most vulnerable country to climate change and the one most lacking in coping capacity. Furthermore, it is also one of the world’s most politically fragile nations. The country is facing challenges related to riverine flooding, including four consecutive years of floods (2019-2022) that have displaced hundreds of thousands of people and left many struggling to access food.

Flood extent and frequency mapping based on remote sensing products is being explored by the European Space Agency's Global Development Assistance (GDA) programme's thematic area of Climate Resilience, as a collaboration between GMV and the World Bank in South Sudan.

Floods are mapped with Synthetic Aperture Radar (SAR) imagery from Sentinel-1 (S-1), and the 5-day VIIRS flood fraction product. The former has a native pixel size of 10 m (GRD), whereas it is 375 m for the latter. This resolution disparity is bridged aggregating 9x9 S-1 pixels (which also reduces speckle “noise”) and downscaling the VIIRS product using the flood fraction and the 90 m Copernicus Digital Elevation Model to determine which pixels are more likely to be flooded.

Sentinel-1 flood delineation detects significant deviations from the standard 'dry' stratus using by-track geo-median (sigma-nought) or terrain-flattened gamma-nought image classification. The latter method includes the closest VIIRS 8-day mosaics to prevent false positives in semi-arid regions. Both approaches aim to identify flooding, even beneath vegetation canopies.

Due to the absence of in-situ data, it was not possible to validate the results but an intercomparison was conducted, including different S-1 methods. The downscaled VIIRS product yielded the largest flood extents and frequencies, likely due to its higher imaging frequency (14 h). Consequently, the deviation-based Sentinel-1 products exhibit similar spatial patterns but with lower frequencies and extents due to longer revisit times. These S-1 methods failed to detect flooding in some areas marked as high-frequency flooding by VIIRS, this is attributed to a mischaracterization when the reference image is already flooded. In contrast, the classification-based Sentinel-1 product captured actual flood frequency but was prone to omission and commission errors. Combining maximum flood frequency from both Sentinel-1 products, while masking false positives with VIIRS, reduces errors while preserving maximum spatial detail.

The resulting Earth Observation (EO)-based maps provide key information on the extent, frequency, and persistence of recent flooding seasons (2017-2022). This detailed flood hazard information can raise awareness of flood risk among local institutions and communities. For such purpose, EO data is consolidating its role in helping reduce flood risk to citizens’ lives and livelihoods, as ground data is very sparse across many countries. By combining EO-based flood hazard maps with exposure datasets such as for population, building or crops, we provide additional country-wide information on the potential impacts of recent floods. The service covers the entire country of South Sudan and enables the creation of a flood hazard and exposure index, allowing the World Bank team to detect flooding hotspots and prioritize investment accordingly. These efforts will help the government develop detailed flood risk management plans.

How to cite: Borlaf-Mena, I., Cantoni, È., Franco-Nieto, A., Toro-Bermejo, M., Revilla-Romero, B., Rodriguez Serrano, A., Loescher, L., Monsef Abboud, D., Domenech, C., and Albergel, C.: A Comparative Analysis of Flood Frequency Mapping Approaches for Climate-Resilience in South Sudan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18873, https://doi.org/10.5194/egusphere-egu24-18873, 2024.

EGU24-18986 | ECS | Orals | HS6.6

Rapid flood mapping: Fusion of Synthetic Aperture Radar flood extents with flood hazard maps 

Ambika Khadka, Annett Anders, and Ian Millinship

Rigorous flood monitoring by ICEYE is enabled by the large-scale and systematic availability of synthetic aperture radar (SAR) data from the satellite constellation deployed and operated by ICEYE [1, 2]. However, in dense urban areas and under tree canopy cover, using single X-band based SAR images directly for rapid flood detection inherits large uncertainties due to its complex backscattering mechanisms. This study addresses this gap by proposing an approach to rapidly detect flooding in urban areas by merging real-time SAR flood extents from surrounding rural areas with hydrodynamically modeled flood hazard maps. If a flood is fully contained within an urban area, other auxiliary flood evidences are merged with JBA’s high resolution global flood hazard maps at 5 and 30m resolution. 

 

The precomputed simulation library approach used in Mason et al. 2021 appeared as a challenge, as floods are dynamic in nature [3], they suggested the benefits of using assimilation to integrate SAR data and model outputs in dynamic situations. Thus, the proposed approach builds upon Mason et al. 2021[3] and the framework for improved near real-time flood mapping [2], wherein SAR data is assimilated to enhance future flood predictions and improve the quality of flood hazard maps. This process, in turn, enhances further real-time rapid flood mapping aiding governments, NGOs and disaster responder to make accurate timely decisions in the immediate aftermath of an event. 

 

References:

[1] Dupeyrat, A., Almaksour, A., Vinholi, J., and Friberg, T.: Deep learning for automatic flood mapping from high resolution SAR images, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6790, https://doi.org/10.5194/egusphere-egu23-6790, 2023.

[2] Friberg, T., Khadka, A., and Dupeyrat, A.: A framework for improved near real-time flood mapping, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8520, https://doi.org/10.5194/egusphere-egu23-8520, 2023.

[3] Mason, D.C., Bevington, J., Dance, S.L., Revilla-Romero, B., Smith, R., Vetra-Carvalho, S., Cloke, H.L.: Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps, Water 2021, 13, 1577, https://doi.org/10.3390/w13111577

How to cite: Khadka, A., Anders, A., and Millinship, I.: Rapid flood mapping: Fusion of Synthetic Aperture Radar flood extents with flood hazard maps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18986, https://doi.org/10.5194/egusphere-egu24-18986, 2024.

EGU24-19378 | ECS | Posters on site | HS6.6

Integrated GIS analysis for flood risk assessment in Norwegian Rivers: a case study of Sokna river 

Adina Moraru, Raffa Ahmed, Mulubirhan G. Tekle, Knut Alfredsen, and Oddbjørn Bruland

This research aims to simplify and enhance the analysis and visualization of flood-prone areas in Norwegian rivers, with a primary emphasis on Sokna river. Utilizing remote sensing and GIS analysis, our objective is to advance flood risk assessment and management by integrating hydraulic data from numerical models, remotely sensed geomorphic features, and publicly available natural hazard maps. In this study, we develop GIS models, analyze geomorphic features related to erosion and deposition processes, and optimize flood risk analysis using hydro-morphodynamic indicators such as shear stress, stream power, Froude number, Shields formula, and the Hjulström diagram.

To locate flood-prone areas and estimate their severity, different influencing factors to flood risk were identified, among them fluvial dynamics, terrain characteristics, land use, and anthropic activities. Within the 12.65 km lowermost reach of Sokna river, near its confluence with Gaula river and Lundamo urban area, we conducted a comprehensive analysis of the geomorphological features (e.g. river width, soil type), natural hazards maps, and anthropic footprint (i.e. land use, infrastructure, safety measures), supported by hydrodynamics information from HEC-RAS models. Special attention was given to the analysis of sediments, erodible materials, and land use along the riverbanks while integrating flood areas with return periods ranging from 10 to 500 years, as well as other natural hazards such as rockfall- and snow erosion and deposition areas, avalanche records, landslides, debris, and quick clay landslide areas.

A temporal analysis was conducted using orthophotos from 1956, 2011, and 2021. The river channels in these orthophotos, captured in the same month to ensure similar discharges, were digitized to assess changes in river width and deposition processes. Additionally, DEM of Differences (DoD) supported refining documented river changes. The erodible sediment particle size was estimated using the Shields formula based on HEC-RAS model outputs, including Froude number, shear stress, and stream power. The erodible fraction was plotted into Shields and Hjulström diagrams and compared with the soil map. Identified locations with erodible material were complemented with land use data and other anthropic activities. Vulnerable infrastructure to erosion and deposition processes, such as culverts and bridges, were considered in flood risk assessments, with areas having safety measures (such as channel embankments) marked as having lower flood risk.

The step-by-step workflow, integrated into a GIS model using the Model Builder feature in ArcGIS Pro, is replicable for other rivers. These findings provide insights into the factors influencing flood risk, including potential erosion areas, the impact of natural hazards, and the temporal evolution of river channels. This methodology serves as a versatile tool for flood risk assessment and management in other river systems, contributing to the broader field of fluvial geomorphology and hydraulic engineering.

How to cite: Moraru, A., Ahmed, R., Tekle, M. G., Alfredsen, K., and Bruland, O.: Integrated GIS analysis for flood risk assessment in Norwegian Rivers: a case study of Sokna river, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19378, https://doi.org/10.5194/egusphere-egu24-19378, 2024.

EGU24-20575 | Orals | HS6.6 | Highlight

Low-latency flood inundation mapping with airborne GNSS-R 

Konstantinos Andreadis and Delwyn Moller

The Rongowai project, based in New Zealand, represents a groundbreaking initiative in earth observation using next-generation Global Navigation Satellite Systems Reflectometry (GNSS-R) sensors. A NASA-developed sensor mounted on an Air New Zealand Q300 passenger aircraft collects land-surface and coastal data daily between airport hubs across the country. This project builds upon NASA's CYGNSS constellation, initially designed for sensing ocean surface winds but later expanded to terrestrial sensing due to the sensitivity of GNSS-R measurements to various surface properties of water. The next-generation GNSS-R receiver (NGRx) offers enhanced capabilities beyond CYGNSS, providing increased simultaneous measurements and introducing new measurement capabilities like polarimetry for improved land characterization. The unique mission model of Rongowai emphasizes sustainability while maintaining high-quality observations, utilizing an existing commercial Air New Zealand aircraft for data collection, thereby achieving unprecedented spatio-temporal sampling throughout New Zealand. The Air New Zealand Q300 operates approximately 7-8 flights daily in a hub-and-spoke pattern across major centers in New Zealand, offering near-ideal operational characteristics for capturing dynamic events. Here, we present a system that leverages the flight characteristics of the Q300 to deliver low-latency inundation observations immediately after landing, providing near real-time data transmission from the preceding flight. The framework, named the Flood Assessment Spatial Triage (FAST) addresses the challenge of data latency in flood reconnaissance by providing rapid inundation detection and visualization on an on-demand flight-by-flight basis within an hour after landing. The processing chain of FAST involves geolocation of specular points, coherence detection, and overlaying transects on a high-resolution digital elevation model (DEM) using a simplified flood inundation model. Analysis of GNSS-R waveforms demonstrates the ability to robustly observe inundation even in challenging conditions such as cloud cover, nighttime, and vegetated areas. Our study period captured flooding events in New Zealand's North Island during the Southern hemisphere summer of 2023, particularly in areas affected by Cyclone Gabrielle. The inundation observations from February 2023 depicted regions with surface water not classified as permanent water bodies, and a combination with a physically-based algorithm allowed for mapping flood inundation from the relatively sparse Rongowai observations. Our results align with ground reports of flooding, highlighting the potential for valuable reconnaissance information from GNSS-R when transiting affected regions. Rongowai's higher spatial resolution, combined with its hub-and-spoke flight pattern, enables rapid revisits over affected regions, making it well-suited for dynamic and rapidly evolving processes like floods.

How to cite: Andreadis, K. and Moller, D.: Low-latency flood inundation mapping with airborne GNSS-R, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20575, https://doi.org/10.5194/egusphere-egu24-20575, 2024.

EGU24-20702 | ECS | Posters on site | HS6.6

 DeepFuse: Towards Frequent Flood Inundation Monitoring using AI and EO 

Antara Dasgupta, Rakesh Sahu, Lasse Hybbeneth, and Björn Waske

Despite the increase in the number of Earth Observation satellites with active microwave sensors suitable for flood mapping, the frequency of observations still limits adequate characterization of inundation dynamics. Particularly, capturing the flood peak or maximum inundation extent, still remains elusive and a major research gap in the remote sensing of floods. Rapidly growing archives of multimodal satellite hydrology datasets combined with the recent deep learning revolution provide an opportunity to solve this problem adequate observation frequency. DeepFuse is a scalable data fusion methodology, leveraging deep learning (DL) and Earth Observation data, to estimate daily flood inundation at scale with a high spatial resolution. In this proof-of-concept study, the potential of Convolutional Neural Networks (CNN) to simulate flood inundation at the Sentinel-1 (S1) spatial resolution is demonstrated. Leveraging coarse resolution but temporally frequent datasets such as soil moisture/accumulated precipitation data from NASA’s SMAP/GPM missions and static topographical/land-use predictors, a CNN was trained on flood maps derived from S1 to predict high-resolution flood inundation. The proposed methodology was tested in southwest France at the confluence of its two main rivers, Adour and Luy, for the December 2019 flood event. The predicted high-resolution maps were independently evaluated against flood masks derived from Sentinel-2 using the Random Forest Classifier. First results confirm that the CNN can generalize some hydrological/hydraulic relationships leading to inundation based on the provided inputs, even for some rather complex topographies. However, further tests in catchments with strongly divergent land-use, hydrological, and elevation profiles is necessary to evaluate model sensitivity towards different land surface conditions. Achieving daily cadence for flood monitoring will enable an improved understanding of spatial inundation dynamics, as well as help develop better parametric hazard re/insurance products to effectively bridge the flood protection gap.

How to cite: Dasgupta, A., Sahu, R., Hybbeneth, L., and Waske, B.:  DeepFuse: Towards Frequent Flood Inundation Monitoring using AI and EO, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20702, https://doi.org/10.5194/egusphere-egu24-20702, 2024.

EGU24-731 | ECS | Orals | HS4.2

Exploring Drought Monitoring in Morocco: A Review of Remote Sensing and Machine Learning Techniques 

Said El Goumi, Mustapha Namous, Abdenbi Elaloui, Samira Krimissa, and Nafia El-alaouy

The challenges of climate change and water scarcity in Morocco highlight the need for Remote Sensing (RS) and Machine Learning (ML) for drought monitoring. Droughts pose socio-economic and environmental challenges and have significant impacts on the country's agriculture-based economy and water management strategies. This study provides a comprehensive review of advanced RS technologies and ML algorithms, with a focus on their effectiveness in monitoring and forecasting drought conditions. RS provides extensive spatial coverage and captures important data on factors such as vegetation health, soil moisture, and precipitation trends, which are crucial for early detection and response to droughts. Incorporating ML algorithms significantly improves the precision and efficiency of drought prediction models, aiding in the development of comprehensive drought indices and forecasting models for agricultural planning and effective water resource management.

The study evaluates various RS methods utilized in Morocco, including the analysis of satellite imagery and vegetation indices such as NDVI, and assesses ML techniques like support vector machines (SVM) and artificial neural networks (ANN) for predicting drought-induced agricultural impacts. The combined use of these technologies provides a holistic approach to drought monitoring, enabling timely interventions to assist communities affected by drought. However, the study also highlights challenges in areas such as data availability, model validation, and associated costs. To effectively manage drought risks, the paper recommends that Moroccan policymakers and stakeholders leverage these technological advancements while emphasizing the importance of continuing research, interdisciplinary collaboration, and capacity building in these areas.

Key words: Drought,remote sensing, machine learning, climate change, Morocco

How to cite: El Goumi, S., Namous, M., Elaloui, A., Krimissa, S., and El-alaouy, N.: Exploring Drought Monitoring in Morocco: A Review of Remote Sensing and Machine Learning Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-731, https://doi.org/10.5194/egusphere-egu24-731, 2024.

Drought, as a natural calamity, has serious economic and environmental implications, especially as the impacts of climate change continue to escalate globally. In many regions, monitoring and comprehending changes in drought patterns have become imperative. As climate change increasingly influences hydrological cycles, there is a need to grasp and interpret drought behaviour in diverse geographical areas. This study is particularly focused on a landlocked state in the north-eastern region of India, which is characterised by a predominantly monsoon climate with high humidity and an annual rainfall of 1800–2500 mm. The study focuses on the state of Nagaland, India, and is aimed at evaluating the efficacy of artificial intelligence (AI) models such as Multilayer Perceptron (MLP), Long Short-Term Memory (LSTM), and Genetic-Algorithm Adaptive Neuro-Fuzzy Inference System in predicting drought. For analysing the drought conditions, the Effective Drought Index (EDI) is used. By utilising rainfall data from 1987–2021, the EDI drought index has been computed, recognising the pivotal role of rainfall in comprehending prevailing drought conditions. The drought conditions are categorised from extremely dry to near normal, excluding the wet conditions in the study region. The investigation into the effectiveness of AI in predicting and detecting drought yielded insightful results, highlighting the informative and promising capabilities of AI models. The results of the study facilitate a comparative analysis of the three models, MLP, LSTM, and GA-ANFIS, using the evaluation metrics. The study findings indicate that LSTM exhibits superior prediction accuracy in the study region in terms of its ability to predict drought conditions in the given geographical area. This outcome is crucial for understanding and addressing the impacts of drought. This study contributes to the broader understanding of drought prediction and emphasises how AI models can improve their ability to predict drought conditions, which will ultimately contribute to enhanced water resource management and climate adaptability.

How to cite: Kikon, A.: Exploring the effectiveness of Artificial Intelligence-powered insights in drought study in Nagaland, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-853, https://doi.org/10.5194/egusphere-egu24-853, 2024.

EGU24-1425 | Posters on site | HS4.2

Occurrence of drought in groundwater over the last 12 years 

Valeria Slivova and Michaela Kurejova Stojkovova

Groundwater is a very important component of water circulation in nature, it is indispensable in every country’s wealth. Ensuring protection of its sustainable use is the most important requirement for preserving the quality of life, health of natural conditions and economic development of each sector. Groundwater is the main source of drinking water in Slovakia. This contribution assesses groundwater drought occurrence recorded at 207 objects in the Slovak groundwater monitoring network.  This comprises 141 groundwater level boreholes and 66 spring yield gauging stations. The Sandre method was used for this assessment. This method is based on a statistical comparison of the average monthly values of the hydrological year evaluated with the long-term monthly average over the reference period 1981-2010. For each month of the reporting period, five separate categories are established on the basis of the statistical treatment of the average monthly values of spring yields and groundwater levels. The period of the last 12 years (2011-2012) has been evaluated.

 

The results show that 3 years (2012, 2019 and 2022) were assessed as the dry years, 3 years were assessed as wet (2011, 2013 and 2021) and 6 years were assessed as average (period 2014 - 2016, 2018 and 2020). Within each years, groundwater drought occurred most frequently in winter, spring and summer. The main source of groundwater is the spring melting of snow. In the last years we can see, there is earlier melting of the snow as a result of warm winters and has been a lack of snow cover in the lower positions in the Slovakia. These are the main causes of the occurrence of droughts in groundwater in the winter and spring period. During the summer period, groundwater drought is caused by high evapotranspiration and rainfall deficits. The occurrence of local storms does not have a significant impact on the replenishment of groundwater resources.

 

 

 

 

Keywords: groundwater drought, rainfall deficit, spring yield, groundwater level

How to cite: Slivova, V. and Kurejova Stojkovova, M.: Occurrence of drought in groundwater over the last 12 years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1425, https://doi.org/10.5194/egusphere-egu24-1425, 2024.

EGU24-1946 | ECS | Orals | HS4.2

Monitoring agricultural drought in the Mediterranean region using a high-resolution (1-km) standardized evaporation deficit index 

Irina Yu. Petrova, Diego G. Miralles, Sergio M. Vicente-Serrano, and Christian Massari

Droughts, with their far-reaching and detrimental effects across multiple domains, remain critical climate events that demand better monitoring and early warning capabilities. Regions that are highly dependent on water supply for agriculture, such as the Mediterranean, are vitally dependent on timely monitoring of drought conditions. The crop losses in the region as a consequence of drought events continue to rise. Simultaneously, climate models agree regarding the exacerbation of drought following global warming in the region. Therefore, better understanding and monitoring of drought occurrence is imperative to mitigate drought adverse effects and improve water resource management in the region and beyond.
Operational drought monitoring, whether based on models or observed data, commonly employs a set of drought indices designed to assess anomalies in land or atmosphere dryness. However, these indices are typically available at relatively coarse spatio-temporal scales, rendering them unsuitable for evaluating the local drought impacts that are relevant to agriculture and ecosystems. This limitation does not facilitate decision-making by local authorities and farmers and impedes the straightforward development of on-site adaptation strategies.
In this study, we undertake the assessment and validation of an evaporation-based drought index, the Standardized Evaporation Deficit Index (SEDI: Kim&Rhee 2016, GRL), at an unprecedentedly high resolution (1 km, daily) over the Mediterranean domain. The index is constructed using data of potential and actual evaporation derived using GLEAM (Miralles et al. 2011, HESS), as part of the ESA 4DMED-Hydrology project. Unlike most other drought indices, SEDI is directly related to plant water stress, given the significance of the evaporation deficit for plant hydraulic and physiological processes. Such approach offers the potential to provide early-warning information on ecological and agricultural plant water stress at local scales. Our study of the relationship between SEDI and vegetation stress over seven years (2015–2021) and across 28 Mediterranean river basins, sheds light on critical factors that cause differential stress in crops and natural ecosystems under drought conditions. We also explore the role of irrigation in the SEDI–vegetation stress relationship using 1 km irrigation volumes obtained during the 4DMED-Hydrology project. In the future, the framework will be extended globally, with the subsequent aim to provide valuable information for optimizing irrigation timing in major irrigated breadbasket regions. 

How to cite: Yu. Petrova, I., G. Miralles, D., M. Vicente-Serrano, S., and Massari, C.: Monitoring agricultural drought in the Mediterranean region using a high-resolution (1-km) standardized evaporation deficit index, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1946, https://doi.org/10.5194/egusphere-egu24-1946, 2024.

EGU24-2072 | ECS | Orals | HS4.2

Soil moisture forecasting for dryland fields in Australia 

Qazi Muqeet Amir and Thomas Bishop

Australia is frequently susceptible to droughts. Major droughts within the last 50 years such as that of 1982-1983 and the Millennial drought of 1997-2010 severely impacted crop growth across the country. Soil moisture can be in deficit during droughts due to a lack of recharge and high evapotranspiration from the soil. Dryland agriculture is particularly sensitive to droughts as there is no irrigation input into the soil. Soil water availability is a critical constraint to agricultural productivity, so the ability to predict its current and future state accurately is key in informing decisions relating to irrigation, fertiliser use, and yield targets. While soil moisture forecasting has been conducted in literature previously, there is limited understanding of the spatial, seasonal, and meteorological patterns that underlie the forecastability of soil moisture in a particular field. Hence this research aims to understand the spatial, seasonal, and meteorological factors that influence the forecast accuracy of soil moisture in dryland fields in Australia. 

Across Australia an increasing number of growers have soil moisture probes, which report current and historic soil moisture. The domain of this work is in the CosmOz probe network, consisting of 26 cosmic ray soil moisture probes across Australia, accounting for various geophysical and climatic regions. The probes measure average soil moisture to depths in the soil between 10 to 50 cm. Forecasting soil moisture requires the addition of various modelled/remotely sensed data such as meteorological, vegetation type, and soil property data. Using this data and lagged soil moisture as predictors, soil moisture has been forecasted at the locations of each CosmOz probe. With up to 13 years of training data, machine learning models have been fitted to forecast soil moisture with high accuracy forecasts of up to 30 days. To improve predictions a neural network autoencoder has been employed to engineer features that account for anomalous periods in the predictors.

A key outcome of this study is identifying patterns in forecast accuracy and predictor importance with respect to region, soil type, meteorological conditions, and time of year. These patterns create a nationwide perspective of soil moisture forecastability and the potential for forecasting in areas with no soil moisture probe data available. 

How to cite: Amir, Q. M. and Bishop, T.: Soil moisture forecasting for dryland fields in Australia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2072, https://doi.org/10.5194/egusphere-egu24-2072, 2024.

EGU24-2075 | ECS | Orals | HS4.2

Drought duration and spatial dependence increase during propagation 

Manuela Irene Brunner and Corentin Chartier-Rescan

As droughts propagate both in time and space, their impacts increase because of changes in drought properties. Even though drought propagation has two dimensions – a temporal and spatial one – these are mostly studied separately, which neglects that the propagation of droughts through the hydrological cycle may extend from local to spatial characteristics. Therefore, it is yet unknown how the spatial extent and connectedness of droughts change as droughts propagate from the atmosphere to and through the hydrosphere.
In this study, we assess not only how local meteorological droughts propagate through the hydrological cycle to streamflow and groundwater but also how drought spatial extent and connectedness change with drought propagation. To do so, we use a large-sample dataset of 70 catchments in the Central Alps for which both observed streamflow and groundwater data are available.
We show that drought propagation from the atmosphere to the hydrosphere affects both local and spatial drought characteristics and leads to longer, delayed, and fewer droughts with larger spatial extents. 75% of the precipitation droughts propagate to P-ET or further, 20% to streamflow, and only 10% to groundwater. Of the streamflow droughts, 40% propagate to groundwater but 60% do not propagate.  Drought extent and connectedness increase during drought propagation from precipitation to streamflow thanks to synchronizing effects of the land-surface such as widespread soil moisture deficits but decrease again for groundwater because of sub-surface heterogeneity. These findings have implications for drought prediction and management. They suggest a partial predictability of streamflow and groundwater droughts by atmospheric and hydrological deficits and that large scale streamflow deficits may be partly compensated by groundwater, which shows less frequent and spatially extensive droughts than streamflow.

How to cite: Brunner, M. I. and Chartier-Rescan, C.: Drought duration and spatial dependence increase during propagation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2075, https://doi.org/10.5194/egusphere-egu24-2075, 2024.

EGU24-2560 | ECS | Orals | HS4.2

A novel multivariate drought severity index: study of short-term hydrological signals within Amazon river basin 

Artur Lenczuk, Christopher Ndehedehe, Anna Klos, and Janusz Bogusz

The pace of Earth’s climate warming obviously sped up, especially after 2000s. Droughts are increasingly becoming  frequent, longer and more severe, with lasting impacts on ecosystems, communities and people. Thus, addressing the problem of monitoring global (or regional) climate trends and  water storage changes is crucial. We propose a novel Multivariate Drought Severity Index (MDSI) estimated through the concept of Frank copulas that is based on DSIs determined from satellite-based geodetic data. The new multivariate approach is based on data provided by the Global Positioning System (GPS) and the Gravity Recovery and Climate Experiment (GRACE).

In this study, we analyze short-term (<9 months) signals of monthly-resampled vertical displacements for 25 GPS stations that are classified as benchmarks for hydrogeodesy within Amazon river basin. We show that despite GPS and/or GRACE limitations arising in data products or their quality, the GPS- and GRACE-based DSIs are characterized with a general coherent spatial pattern to the traditional climate indices (Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)). Moreover, GPS- and GRACE-based DSIs are capable of capturing extreme hydrometeorological events reported for the Amazon basin. However, DSI variations from GPS and GRACE do not always reflect real hydrological changes as they could sometimes under- or overestimate them. Our analyses show that the newly proposed MDSI is a step towards strengthening  the credibility of combined GPS and GRACE data in drought assessment to improve  understanding of climate change impact on freshwater. We demonstrate that the MDSI recognizes the exact number of events, or one event less than index chosen as the most reliable for over 90% of selected stations. We notice that MDSI series are temporally consistent with extreme precipitation values. The wet and dry periods captured by MDSI are related with precipitation anomalies over 400 mm/month and below 100 mm/month, respectively.

How to cite: Lenczuk, A., Ndehedehe, C., Klos, A., and Bogusz, J.: A novel multivariate drought severity index: study of short-term hydrological signals within Amazon river basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2560, https://doi.org/10.5194/egusphere-egu24-2560, 2024.

EGU24-2685 | ECS | Orals | HS4.2

Drought propagation from meteorological to hydrological drought in the Krishna River Basin of India 

Ajay Gupta, Manoj Kumar Jain, and Rajendra Prasad Pandey

Understanding the propagation of drought from one form to another has become a prime topic of research during recent decades. The majority of research has used a correlation-based approach to study drought propagation; however, such techniques are ineffective in areas with considerable seasonality in precipitation, such as India. Only a few studies have employed an event-based approach to study drought propagation. Moreover, none of the previous studies considered the sequential propagation of drought, starting from meteorological to hydrological drought through agricultural drought. This work aims to analyse drought propagation from meteorological to hydrological drought through agricultural drought using an event-based approach in the Krishna River Basin of India. The Standardised Precipitation Evapotranspiration Index (SPEI) represents meteorological drought, the Standardised Soil Moisture Index (SSMI) represents agricultural drought, and the Standardized Streamflow Index (SSI) represents hydrological drought is estimated at a 1-month timescale at sub-basin scale. The precipitation and temperature data are procured from the India Meteorological Department (IMD) Pune, the soil moisture data is obtained from the European Space Agency (ESA) Climate Change Initiative (CCI) v03.3, and the streamflow data is downloaded from India-WRIS. Two different cases of drought propagation are analysed: meteorological to agricultural drought (SPEI-SSMI) and agricultural to hydrological drought (SSMI-SSI). Propagation of drought is quantified through the estimation of three-time matrices: (1) the time difference between the initiation of droughts, (2) the time difference between the peak of droughts, and (3) the time difference between the termination of droughts. The results from the study revealed that the SSMI drought was initiated after 6.4 months of the SPEI drought, while the SSI drought was initiated after 8.4 months of the SSMI drought. The peak of SSMI drought is found to be after 6.3 months of the peak of SPEI drought, while the peak of SSI drought is found to be after 34.7 months of the peak of SSMI drought. Once the SPEI drought terminates, it lasts for 8.3 months for the SSMI drought to terminate, while after the SSMI drought terminates, it lasts for 30.7 months for the SSI drought to terminate. Thus, it was found that the propagation of drought from SPEI-SSMI is faster than the propagation of drought from SSMI-SSI. The present work will provide essential information on drought propagation, which will be helpful in the management and mitigation of droughts in India. 

Keywords: Drought Propagation, Propagation Time, SPEI, SSMI, SSI.

How to cite: Gupta, A., Jain, M. K., and Pandey, R. P.: Drought propagation from meteorological to hydrological drought in the Krishna River Basin of India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2685, https://doi.org/10.5194/egusphere-egu24-2685, 2024.

EGU24-2852 | ECS | Posters virtual | HS4.2

Predicting longer lead droughts with Bayesian model averaging ensemble vine copula (BMAViC) model 

Haijiang Wu, Xiaoling Su, and Vijay P. Singh

In the face of global anthropogenic climate warming, particularly since the 1990s, the world has witnessed numerous extreme weather and climate events (e.g., droughts, heatwaves, and extreme precipitation), leading to economic losses and ecosystem degradation. In particular, drought prediction lies at the core of overall drought risk management and is critical for food security, early warning, and drought preparedness and mitigation. However, drought prediction models generally focus on shorter lead times (1–3-months) as their performance drastically declines at longer lead times (> 3 months). The vine copula can decompose complex non-linear, multi-variates into pairwise variables via bivariate copula forms which can well depict the diverse dependencies among variables (note that a vine copula possesses numerous vine structures, especially under higher-dimensional situations), while the Bayesian model averaging (BMA) can assign different weights to each ensemble member which depends on the explanatory power of the member itself for the specified objective. We therefore developed a new drought prediction model utilizing the BMA coupled with vine copula, called the Bayesian Model Averaging ensemble Vine Copula (BMAViC) model. Two drought types, i.e., hydrological drought (characterized by the standardized streamflow index (SSFI)) and agricultural drought (depicted by standardized soil moisture index (SSI)), were predicted with different lead times based on the BMAViC model under four-dimensional situations. Our model first was applied to predict the hydrological drought with the 1–3-month lead times for five hydrological stations (i.e., Tangnaihai, Minhe, Hongqi, Zheqiao, and Xiangtang) in the Upper Yellow River basin, in which previous meteorological drought, antecedent evaporative drought, and preceding hydrological drought were selected as three predictors. The BMAViC model showed robust skills during calibration and validation periods for 1–3-month lead hydrological drought predictions. In comparison with the meta-Gaussian model (reference model), the skills of the proposed model were relatively stable and superior under diverse lead times. Good performances under the 1–3-month lead times strongly implied that the BMAViC model yielded robust and accurate hydrological drought predictions. Considering the previous meteorological drought, antecedent hot condition, and agricultural drought persistence as three predictors, our proposed BMAViC model was further leveraged to predict the agricultural drought in the summer season over China with the 1–6-month lead times. Compared with optimal vine copula (OViC), average vine copula (AViC), and persistence-based models, the BMAViC model performed better for the 1–6-month lead agricultural drought predictions. Besides, the BMAViC model yielded a good prediction ability for extreme droughts. These findings enhance our confidence in seasonal drought prediction and help us understand drought dynamics in future months.

How to cite: Wu, H., Su, X., and Singh, V. P.: Predicting longer lead droughts with Bayesian model averaging ensemble vine copula (BMAViC) model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2852, https://doi.org/10.5194/egusphere-egu24-2852, 2024.

In recent decades, the phenomenon of drought has become a hazard with increasing frequency, with multiple societal and environmental impacts. One of these impacts concerns water resources and their availability for various uses. Numerous indices have been used over time to quantify the severity of drought and to assess its effects on socio-economic activities and environmental components. Among the spatial indices, the most numerous belong to remote sensing, being easy to use to analyse drought consequences especially on landcover and vegetation. However, regarding the hydrological drought, the indices used are mainly calculated based on hydroclimatic data, without taking into account spatial variables, such as the topographical, geological or pedological characteristics. The aim for this study is to compute a hydrological drought index which integrates several drought control variables, using both GIS and remote sensing techniques in order to map the susceptibility to hydrological drought within the Teleorman watershed.

Located in the central-southern part of Romania, the Teleorman River has a length of 169 km and a catchment area of 1.427 km2. The most part of  the catchment overlaps the central sector of the Romanian Plain, an important agricultural area, highly sensitive to water deficit. According to Köppen-Geiger classification, the analyzed catchment has a humid continental climate with hot summers (Dfa), meaning that the drought could occur in the basin.

A series of free data and information sources has been accessed in order to compute the hydrological drought index, such as: Worldclim, Landsat Archive, Geological Map of Romania, Pedological Map of Romania, Shuttle Radar Topography Mission (SRTM), Topographical Map of Romania. The following parameters were derived from these sources: Topograhic Wetness Index (TWI); Drainage Density (resulted from hydrographic network); Normalized Difference Drough Index (NDDI), resulted from ratio between Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI); Temperature Condition Index (TCI), extracted from Land Surface Temperature (LST); Aridity Index (AI) computed as a ratio between Precipitation and Potential Evapotranspiration (PET); De Martonne Index (based on ratio between Precipitation and Air temperature); Lithology and Soil Texture. Because some of the parameters had a different spatial resolution, the regridding method was used to bring the database to a resolution of 30 meters. Analytic hierarchy process method (AHP) was used to determine the influence of each factor and for the bonitation process. Based on the total obtained score, 5 classes from to lowest to highest hydrological drought susceptibility resulted. Finally, the Weighted Overlay and Raster Calculator tools from ArcGisPro software were used to map the index.

The resulted map allows the identification in the studied watershed of areas the most susceptible to hydroclimatic drought allowing the focus in these areas of appropriate actions to improve drought risk management. GIS and Remote sensing proved to be useful tools in spatial analysis of drought based on a composite index integrating several drought control factors. In the future, we intend to improve the method by considering other variables controlling the hydrological drought, such as the streamflow and the groundwater depth.

How to cite: Costache, M.-Ș. and Zaharia, L.: Mapping the susceptibility to hydrological drought using GIS and remote sensing techniques in the Teleorman watershed (Romania), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3408, https://doi.org/10.5194/egusphere-egu24-3408, 2024.

Drought projection is critical for water resource planning and management, as well as disaster prevention and mitigation. As a strategic national water source for China, the Yangtze River Basin (YRB) plays a vital role in the connectivity of rivers and economic development, flowing through 11 provincial administrative regions and is injected into the East China Sea, with a total length of 6,397 km. The watershed covers an area of 1.8 million square kilometers, accounting for about 1/5 of China's total land area. However, frequent droughts have caused water shortages in the YRB in recent years. Based on observed meteorological and hydrological data, the CMIP6 model and SPEI (standardized precipitation evapotranspiration index) drought models were used to elucidate the risk of future simultaneous droughts in the upper and mid-lower reaches of the YRB from 2015 to 2100. SRI has been used based on SWAT model to study the transfer process of meteorological drought to hydrological drought. The results indicated that, (1) The average of 10 CMIP6 models showed a good verification of historical precipitation and temperature for drought predictions. The MMK and Sen’s slope demonstrated consistency for historical and future droughts in the YRB. From a historical perspective (1961–2019), the middle reaches of the YRB experienced intensifying drought frequency with the highest total drought (Moderate and above drought events) frequency (> 17%); (2) In the future (2020–2100), the higher emission signifies higher moderate and total drought frequency, intensity, and scope of the YRB in FF, lower in NF. The ratio of autumn severe and extreme droughts would increase in mid-twenty-first century; (3) Severe drought risk encounters were projected in the upper and meanwhile in the middle-lower reaches in YRB, especially in the 2030–2040 period. Under all three scenarios, severe droughts occurred more frequently with SPEI close to − 2. The middle-lower reaches of the YRB are forecast to witness the largest scope and highest intensity of drought under the SSP1-2.6 scenario.; (4) The future runoff in the YRB during the dry period varied less, but in May and June during the main flood season the runoff under SSP1-2.6 would be the largest. Maximum decrease in runoff in the mid-lower reaches under the SSP2-4.5 scenario would be 2045, reaching 13.9%. Extreme flooding events and extreme meteorological droughts would happen accompanying with hydrological droughts would occur more frequently and severely under different scenarios. More attention and improved strategies should be brought to bear to address future simultaneous droughts in the upper and mid-lower YRB.

How to cite: Zhang, Y. and Zhang, Z.: The increasing risk of future simultaneous droughts over the Yangtze River basin based on CMIP6 models , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3557, https://doi.org/10.5194/egusphere-egu24-3557, 2024.

EGU24-3746 | Posters on site | HS4.2

Drought Forecasting with ML-based Regionalized Climate Indices 

Taesam Lee, Yejin Kong, Sunghyun Hwang, and Sejeong Lee

Drought forecasting in South Korea has become imperative due to the increased frequency of occurrence leading various damages such as property loss and casualties. Precipitation in South Korea is distributed with high deviation, substantially concentrated in summer. Other seasons have a comparatively low amount of precipitation resulting unbalanced water resources of each season. To overcome the skewed seasonal precipitation, numerous dams and reservoirs have been constructed and operated. The management of those water-related structures should be carried out carefully to meet seasonal requests of water resources, and the precipitation prediction for each season has become critical. However, the seasonal precipitation forecasting has been a challenging task due to complex weather systems and climate patterns. The current study proposes a novel procedure for forecasting seasonal precipitation as: (1) regionalization of climate variables; (2) extraction of features with PCA, ICA and Autoencoder; and (3) finally regression model applications. Two globally gridded climate variables, Mean Sea Level Pressure (MSLP) and Sea Surface Temperature (SST) were teleconnected with the Accumulated Seasonal Precipitation (ASP) of South Korea. The results indicate that the k-means clustering successfully regionalizes the highly correlated climate variables with the ASP and all three feature selection algorithms, PCA, ICA, and Autoencoder present their superiority in different seasons combining GLM and SVM models. Especially, the PCA performs better with the linear GLM model and the Autoencoder shows better performance with the nonlinear SVM model. Overall, it can be concluded that the proposed seasonal precipitation forecasting procedure combining ML-based algorithms can be a good alternative.

How to cite: Lee, T., Kong, Y., Hwang, S., and Lee, S.: Drought Forecasting with ML-based Regionalized Climate Indices, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3746, https://doi.org/10.5194/egusphere-egu24-3746, 2024.

EGU24-3770 | ECS | Posters on site | HS4.2

From development of multi-sectoral drought hazard indicators to global drought hazard propagation 

Neda Abbasi, Stefan Siebert, Malte Weller, Tina Trautmann, Jan Weber, Tinh Vu, Ehsan Eyshi Rezaei, Harald Kunstmann, Harald Koethe, Christof Lorenz, and Petra Döll

Droughts pose a substantial threat to various sectors, including agriculture, human water supply but also natural ecosystems. While various studies have been conducted for drought evaluation, the majority of them have focused on a particular drought type. This may lead to a lack of comprehensive understanding of the features and progression of droughts among different drought types through time. For example, for water resources management and planning purposes, it is critical to understand the changes and temporal development of drought signals from abnormal meteorological conditions to soil moisture, groundwater levels, and streamflow. Within the OUTLAST project, which aims at developing an operational, multi-sectoral global drought hazard forecasting system, we develop a near real-time drought hazard monitoring and forecasting system which, for the first time, includes tailored indicators for various sectors, including water supply, riverine and non-agricultural land ecosystems, as well as rainfed and irrigated agriculture. In this context, the primary objectives of this study are to 1) develop different drought hazard indicators (DHI) to monitor and forecast the drought across different sectors; and 2) assess the spread and propagation of droughts across different sectors and regions at a global scale. For this purpose, DHIs were computed for a 40-year reference period (1981 to 2020) using ERA5 as meteorological forcing data to drive the DHIs using the global hydrological model (WaterGAP) and the global crop water model (GCWM). These DHIs cover meteorological (SPEI and SPI), hydrological (empirical percentiles and relative deviations of soil moisture and streamflow), as well as agricultural droughts (crop-specific DHIs for rainfed and irrigated croplands). In this project, we focus on the period 2011 to 2015, with 2012 being a year in which droughts had major impacts on various regions and sectors. The study investigates drought propagation from meteorological drought, extending to rainfed agriculture due to soil moisture deficiency, over streamflow, and eventually reaching irrigated agriculture. In doing so, region-specific features and the dependency of drought propagation on the magnitude of the drought are highlighted. Finally, as monitoring and projecting drought characteristics are important for comprehending drought-related issues, our multi-sectoral drought hazard forecasting system enables us to evaluate the state of drought propagation at a global scale. 

How to cite: Abbasi, N., Siebert, S., Weller, M., Trautmann, T., Weber, J., Vu, T., Eyshi Rezaei, E., Kunstmann, H., Koethe, H., Lorenz, C., and Döll, P.: From development of multi-sectoral drought hazard indicators to global drought hazard propagation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3770, https://doi.org/10.5194/egusphere-egu24-3770, 2024.

EGU24-3933 | ECS | Posters on site | HS4.2

Spatiotemporal characteristics of drought in the Yili River basin in Northwest China over the past 40 years 

Mengzhen Huang, Ruijie Lu, Peiru Li, and Yutong Han

The Yili River basin is commonly referred to as a "wet island" in the Central Asian Dry Zone. It functions as a vital security barrier in the western part of China. Droughts frequently occur in the basin due to global change and pose a significant threat to food security and ecological stability in the region. Currently, droughts in the basin have not received the attention they deserve, and the mechanisms behind the occurrence, development, and impacts of drought in the basin have not yet been clarified. Based on the Standardized Precipitation Evapotranspiration Index (SPEI), this research identified drought events over the past 40 years, extracted drought characteristics and drought trends, and explored future drought. The following results were found: 1) The basin has experienced frequent wet and dry changes on monthly and seasonal scales, and entered a period of high drought since 2005, specifically the successive severe droughts of 2007-2009 and 2012-2015. 2) There were drought events approximately one-quarter of the time in the basin. Each drought event lasted an average of 2.23 months with a medium intensity. The most prominent droughts occurred in spring and summer. Droughts in the middle and southwest of the basin had short durations but higher intensities, which significantly impacted the area. 3) Over the last 40 years, there has been a general increase in aridity in the basin, especially in spring and summer. The aridity trend was more severe in the northwestern part. 4) In the future, annual drought is predicted to decrease but will increase in summer. It’s recommended that emergency management of drought disasters in the basin be strengthened and, in particular, to improve the monitoring, early warning and prevention in summer.

How to cite: Huang, M., Lu, R., Li, P., and Han, Y.: Spatiotemporal characteristics of drought in the Yili River basin in Northwest China over the past 40 years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3933, https://doi.org/10.5194/egusphere-egu24-3933, 2024.

EGU24-4094 | Orals | HS4.2

Identification of low flow events by machine learning algorithms 

Henning Lebrenz, Daniela Pavia, and Philipp Staufer

An improved forecast of low flow events in catchment basins could be a valuable tool for the operation and decision making of dependent infrastructure (e.g. wastewater discharge, water abstraction) along corresponding rivers. Therefore, the classification of 6642 independent low-flow-events (being the Q347 as the discharge less than the 95%- exceedance quantile of the FDC) from 55 catchment basins within the Kanton Solothurn (Switzerland) was performed by five different machine learning algorithms (i.e. knn, decision tree, random forest, support vector machine, logistic regression). Herein, each low flow event was characterized by 47 static and dynamic parameters (i.e. description of catchment and event history), being supplemented by differently defined (near) non-low-flow events, leading up to a total population of approx. 18000 discharge events.

The validation and verification showed different qualities of the classification accuracy for the forecast of low-flow events, being dependent on the selection of the defined event populations, the selected machine learning algorithm and the definition of classes. In general, the support vector machine and random forest may lead, with the presumption of carefully selected classes, to forecast accuracies of >90%.

How to cite: Lebrenz, H., Pavia, D., and Staufer, P.: Identification of low flow events by machine learning algorithms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4094, https://doi.org/10.5194/egusphere-egu24-4094, 2024.

EGU24-4330 | ECS | Orals | HS4.2

Predicting Food-Security Crises in the Horn of Africa Using Machine Learning 

Tim Busker, Bart van den Hurk, Hans de Moel, Marc van den Homberg, Chiem van Straaten, Rhoda A. Odongo, and Jeroen C.J.H. Aerts

Food insecurity is a global concern resulting from various complex processes and a diverse range of drivers. Due to its complexity, it is one of the most challenging drought impacts to predict. In this study, we introduce a novel machine learning model designed to forecast food crises in the Horn of Africa up to 12 months in advance. We trained an “XGBoost” model using more than 20 different input datasets to capture key food security drivers such as drought, economic shocks, conflicts and livelihood vulnerability. The model shows a promising ability to predict food security dynamics several months in advance (R2>0.6, three months in advance). Notably, it accurately predicted 20% of crisis onsets in pastoral regions (n = 84) and 40% of crisis onsets in agro-pastoral regions (n = 23) with a 3-month lead time. We compared these results to the established FEWS NET early warning system, and found a similar performance over these regions. However, our model is clearly less skilled in predicting food security for crop-farming regions than FEWS NET. This study underscores the importance of integrating machine learning into operational early-warning systems like FEWS NET and expanding these techniques to the continental or global-scale.   

How to cite: Busker, T., van den Hurk, B., de Moel, H., van den Homberg, M., van Straaten, C., A. Odongo, R., and C.J.H. Aerts, J.: Predicting Food-Security Crises in the Horn of Africa Using Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4330, https://doi.org/10.5194/egusphere-egu24-4330, 2024.

EGU24-4814 | ECS | Posters on site | HS4.2

Global dryness could intensify vegetation failure even after net-negative emission is achieved 

Sanjit Kumar Mondal, Soon-Il An, Seung-Ki Min, Tong Jiang, Buda Su, Seungmok Paik, and Soong-Ki Kim

The response of global dryness and vegetation to CO2 removal experiments, especially for net-
 negative emission is immature. Here we conducted a thorough investigation to identify hysteresis and reversibility in global dryness, as well as the vegetation productivity’s response to dry and wet episodes, considering their asymmetrical nature. The asymmetry index (AI) includes two important aspects such as positive AI indicates a dominant increase of vegetation productivity during wet episodes compared to the decline in dry episodes and negative AI implies a larger reduction of productivity in dry years compared to an increase in wet years. Aggregate results from various drought indices and vegetation productivity reveal a dominant dryness in the CO2 decrease phase. Global dryness shows strong hysteresis and irreversible behavior over half of the global land with significant regional disparity. Irreversible changes in dryness are concentrated in specific areas, i.e., hotspots, covering over 14% of the global land, particularly pronounced in Northern Africa, Southwest Russia, and Central America. Moreover, a wider spread of negative asymmetry indicates a significant decrease in vegetation productivity caused by dryness. Importantly, the potential evapotranspiration is projected to be the primary driver of global dryness as well as vegetation asymmetry. Our findings suggest only CO2 alleviation is not enough to cope with drought rather implementing advanced water management strategies is a must to mitigate the impact of drought effectively.

How to cite: Mondal, S. K., An, S.-I., Min, S.-K., Jiang, T., Su, B., Paik, S., and Kim, S.-K.: Global dryness could intensify vegetation failure even after net-negative emission is achieved, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4814, https://doi.org/10.5194/egusphere-egu24-4814, 2024.

Hydrological drought occurs frequently all over the world and has a great impact on human beings. Hydrological drought attribution contributes to a better understanding of the mechanisms of drought occurrence, improves the accuracy of predictions of drought events, and can provide a basis for drought risk reduction. At present, hydrological models which possess physical mechanisms are widely used in attribution analysis. However, this kind of models is complex in calculation, and has very limited time scale. In this study, we developed a hydrological drought attribution method via AdaBoost algorithm. The method divided the study period into natural period unaffected by non-climatic factors and impacted period. Taken the natural period as training period, the impacted period as test, the runoff was obtained to calculate the three-months standardized runoff index (SRI-3). Based on the run-length theory, we calculated average drought characteristics in the impacted period. Finally, the proportion of the average drought characteristics obtained by simulated SRI-3 series to those obtained by observed SRI-3 series is considered as the contribution of the climatic factors to the drought events.

We applied this method in the Yangtze River Basin and the results showed that climatic factors are the dominate factors affecting hydrological droughts in this region, with the contributions at all the gauge stations are over 50%. Among all the drought characteristics, average drought severity is the most affected by the climatic factors, the corresponding contributions are all greater than 100%, shown as “excess contributions” (with non-climatic factors shown as negative contributions). Through the applications in various sub-basins of the Yangtze River Basin, the method was shown to provide new ideas for hydrological drought attribution, and the method can also be extended for applications such as meteorological hazards attribution, stock market volatility attribution and so on.

How to cite: Wang, W., She, D., and Xia, J.: Separate the impact of climate change and non-climatic factors on hydrological drought based on AdaBoost algorithm, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4870, https://doi.org/10.5194/egusphere-egu24-4870, 2024.

EGU24-5040 | ECS | Posters on site | HS4.2

Links between heat waves, drought, and atmospheric circulation in Central Europe 

Zuzana Bešťáková, Ondřej Lhotka, Jan Stryhal, and Jan Kyselý

Heat waves and drought are phenomena associated with large negative impacts on society and environment. Their common features include increasing frequency and intensity in recent decades in many regions of Europe, as well as interconnectedness of the factors that contribute to their development. In this study, we evaluate links between heat waves and drought in Central Europe using E-OBS data and ERA-5 reanalysis in the 1979–2022 period. Heat waves are classified according to their 3-dimensional structure of positive temperature anomalies into near-surface, lower-tropospheric, higher-tropospheric, and omnipresent types. We show that the associations to soil moisture conditions and development of flash drought (based on the daily climatic water balance index) differ for the individual heat wave types; the links are most pronounced for near-surface heat waves, illustrating the compound nature of the heat-drought events. We also employ the Jenkinson–Collison classification to identify circulation types with significantly increased frequency during periods of heat waves and droughts, and study changes in their occurrence. The analysis contributes to better understanding of the interrelationships between drought, heat waves, atmospheric circulation and other driving mechanisms.

How to cite: Bešťáková, Z., Lhotka, O., Stryhal, J., and Kyselý, J.: Links between heat waves, drought, and atmospheric circulation in Central Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5040, https://doi.org/10.5194/egusphere-egu24-5040, 2024.

EGU24-5291 | ECS | Orals | HS4.2

High-resolution drought monitoring with Sentinel-1: A case-study over Mozambique 

Samuel Massart, Mariette Vreugdenhil, Sebastian Hahn, Pavan Muguda Sanjeevamurthy, Carina Villegas-Lituma, and Wolfgang Wagner

Droughts are characterized by periods of below-average precipitation leading to an imbalance in the hydrological cycle and reduced water availability.
In the last decades, higher average temperatures and shifts in annual rainfall patterns have increased the frequency, intensity, and length of droughts across the globe.

With the majority of its population living in rural areas and a high economic dependency on rain-fed agriculture, Mozambique is particularly vulnerable to droughts, as water shortages have devastating environmental, agricultural, and economic impacts. Therefore, monitoring droughts in Mozambique is key to developing early warning systems and adequate planning for drought impact mitigation.

In this study, we propose a novel approach to retrieve a drought index at a kilometer-scale resolution based on surface soil moisture (SSM) products derived from Sentinel-1 (S1) and ASCAT. First, both SSM products are processed over the Mozambican region using a change detection method (Sentinel-1 sampled at 1km and ASCAT at 6.25km) and compared to SSM from ERA5-Land. Then, by combining the long-term ASCAT data record with the high spatial resolution of Sentinel-1, we generate a monthly kilometer-scale drought index for the period 2016 to 2023 over six study areas located in South-central Mozambique (Chokwé, Mabote, Massinga, Buzi, Muanza and Govuro). The S1-ASCAT indicator is then evaluated against state-of-the-art drought indices based on precipitation data (Standardised precipitation index from CHIRPS (Rainfall Estimates from Rain Gauge and Satellite Observations)) and vegetation data (Normalized difference vegetation index from the Copernicus Global Land Service.

This study explores the potential of high-resolution SSM based on active microwave remote sensing to monitor agricultural droughts. Our results show that a drought indicator based on Sentinel-1 and ASCAT can temporally and spatially capture sub-regional drought patterns over Mozambique.

How to cite: Massart, S., Vreugdenhil, M., Hahn, S., Muguda Sanjeevamurthy, P., Villegas-Lituma, C., and Wagner, W.: High-resolution drought monitoring with Sentinel-1: A case-study over Mozambique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5291, https://doi.org/10.5194/egusphere-egu24-5291, 2024.

EGU24-5692 | ECS | Orals | HS4.2

High vulnerability yet strong resilience of China's lakes to drought 

Siyu Ma, Almudena Garcia-Garcia, Xueying Li, and Jian Peng

Lakes play a crucial role in the global hydrological cycle and biogeochemical cycle. In China, lakes are an important part of water resources, providing 40.6% of drinking water. In recent years, droughts in the middle and lower reaches of the Yangtze River in China have led to a significant shrinkage of important freshwater lakes, such as Dongting Lake and Poyang Lake, posing a threat to local water security. However, there has been limited research on the extent to which thousands of lakes across China are affected by droughts. This study used remote sensing product of lake area to comprehensively investigate the impact of drought on the area of 4,702 lakes (natural lakes and reservoirs) in China from 1985 to 2018, covering the three stages of response, shrinkage, and recovery. The results indicate that lakes in China are highly vulnerable to drought. The average response probability of lakes is 72.8%, which typically occurs within six months to two years after the onset of drought. The shrinking area of the lake is 12.7% of the original area, and the shrinking process takes an average of 14 months. Lakes also show a strong resilience to drought, with 95.7% of lakes more likely to experience an increase in area following drought-induced shrinkage. However, only 49.4% of lakes are more likely to grow beyond their pre-shrinkage levels. Compared to natural lakes, artificial reservoirs exhibit a higher response probability by 4.6%, a larger shrinkage area percentage by 1.2%, and a higher recovery probability by 2.9%. Consequently, artificial reservoirs exhibit greater vulnerability and resilience to drought, reflecting the impact of human activities. Furthermore, the spatial distribution of vulnerability and resilience is inconsistent. In Northeast China, including the Songhua and Liaohe river basins, and the Mongolian endorheic basin, lakes exhibit higher vulnerability but lower resilience. Therefore, this region is considered a hotspot where the impact of drought on lake area is particularly severe. This study is expected to provide a basis for the implementation of sustainable water resource management and effective drought mitigation measures in China.

How to cite: Ma, S., Garcia-Garcia, A., Li, X., and Peng, J.: High vulnerability yet strong resilience of China's lakes to drought, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5692, https://doi.org/10.5194/egusphere-egu24-5692, 2024.

EGU24-5875 | Posters on site | HS4.2

Parameter optimization of an agro-ecological model for regional NUTS-3 yield data 

Olga Wold, Roland Baatz, Michael Berg-Monicke, Ehsan Rezaei, Eyshi, and Claas Nendel

Climate change increasingly affects agricultural systems in Central Europe, necessitating the development of robust forecasting models for drought, heat, and fire events (DHF). These hazards pose significant threats to crop production and require proactive measures to enhance resilience and adaptation.

This research project is dedicated to constructing a thorough framework for forecasting DHF events in Central Europe. It integrates an agro-ecosystem model aimed at examining how crops respond, particularly when it comes to water availability. The focus of this research extends to the region's awareness to climate-related threats and the robustness of its agricultural systems.

We utilize the MONICA (Model for Nitrogen and Carbon in Agriculture) crop model to simulate crop growth and response across a spectrum of environmental conditions. The MONICA model is designed to represent the complexity of crop development, considering factors such as soil properties and weather variations. MONICA model has the capacity to explore various scenarios, including heat stress and drought sensitivity, providing a comprehensive view of how crops respond to these challenges.

 The used data includes high-resolution meteorological (1km resolution, daily), topographic, historical crop records and soil information for whole Germany. The dataset covers the past two decades, encompassing vital information such as crop yield records.

By sensitivity analysiswe systematically identified key parameters influencing simulated crop yield and above ground biomass, particularly in the context of drought and heat stress. These insights are invaluable for advancing our understanding of how crops respond to environmental stressors.

Moving forward, our focus shifts to the calibration and optimization routines to quantify specific parameter sets for individual NUTS-3 regions within Germany.

In the poster presentation, we look forward to sharing the newest findings from our ongoing research on advanced calibration tools and yield simulations conducted over Germany. Simulation results are compared to observed yield data, providing valuable insights into the effectiveness and real-world applicability of the modelling approaches.

How to cite: Wold, O., Baatz, R., Berg-Monicke, M., Rezaei, Eyshi, E., and Nendel, C.: Parameter optimization of an agro-ecological model for regional NUTS-3 yield data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5875, https://doi.org/10.5194/egusphere-egu24-5875, 2024.

Given their profound socio-economic impact and increasing occurrence, compound heat and drought extremes (CHDEs) have become a focal point of widespread concern. Numerous studies have attempted to reproduce and predict these extremes using general circulation models (GCMs); however, the performance of these models in capturing extreme events remains controversial. This study presents an improved historical simulation of CHDEs over China by using the regional Climate-Weather Research and Forecasting model (CWRF) to downscale the projections of two GCMs that participated in the Coupled Model Intercomparison Project Phase 6. The CWRF downscaling improved GCMs in capturing the thresholds of extreme hot and extreme dry conditions and demonstrates a better agreement with observations in the temporal trends and spatial patterns of extreme heat and extreme drought events. The performance of CWRF downscaling to reproduce CHDEs also surpasses that of GCMs, with an even greater enhancement compared to univariate extreme events. The improvement is particularly pronounced in sub-humid areas, which is primarily attributed to the enhanced simulation of temperature-precipitation coupling relationships by CWRF downscaling. This superiority is found to be associated with the finer land surface processes and land-atmosphere interaction processes of CWRF. This study highlights the important role of land-atmosphere interactions in shaping CHDEs and the efficacy of using regional climate models to reduce uncertainty in extreme event simulations.

How to cite: Zhang, S. and Zhang, H.: Towards improved prediction of compound heat and drought extremes by CWRF downscaling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8013, https://doi.org/10.5194/egusphere-egu24-8013, 2024.

EGU24-9170 | ECS | Orals | HS4.2

Analysis of droughts and arid conditions in Central Asia using climate indices 

Milena Latinovic, Valeria Selyuzhenok, and Abror Gafurov

Droughts pose significant challenges to water resources, agriculture, and socioeconomic stability, particularly in regions susceptible to climatic extremes such as Central Asia (CA) with its complex topography and diverse ecosystem. In the past several years there has been a substantial decrease in water storage in the region which further could lead to socioeconomic instability. Water is mainly used for irrigation and hydropower production in the region.

In CA, the availability of ground observations is restricted, with most of the measurement stations being outdated since the Soviet era with little or no data sharing between the countries. Consequently, the utilization of widely available remotely sensed data proves advantageous in overcoming these limitations and improving the accuracy of water availability assessment in the region.

CA relies predominantly on water resources derived from the melting of snow and glaciers in the Pamir, Tian Shan, and Hindukush mountains. In the study, we consider the two largest upstream river basins, Amu Darya and Naryn, the eastern headstream of Syr Darya. These two largest rivers in CA are crucial sources of water in the region, supporting agriculture and the ecosystem in the whole of CA.

The study specifically focuses on evaluating snow cover and Snow Water Equivalent (SWE) during the winter months, especially preceding the onset of drought periods, and the Total Water Storage (TWS) in the drought months. The objective is to comprehend and quantify the correlation between these climatic elements and historical droughts, utilizing the Drought Severity Index (DSI) and the widely used Standardized Precipitation Index (SPI).  DSI is based on the TWS value that is derived from the GRACE and GRACE-FO satellite missions. It shows a significant decrease in water storage in both basins since the start of the GRACE mission in 2002, with more intense arid conditions in the last 6 years. SPI-6 and SPI-9 based on precipitation and SWE data, show a slight increase in the trend in the Amu Darya basin, while in Naryn all indices show an increase in drought periods. This indicates that the arid conditions in the summer months in the Amu Darya basins are driven by human-induced water depletion. Finally, all indices can depict severe droughts in 2008, 2011 and 2018 in both basins. The study shows the potential of using globally available TWS data for drought assessment on a regional scale such as in CA.

How to cite: Latinovic, M., Selyuzhenok, V., and Gafurov, A.: Analysis of droughts and arid conditions in Central Asia using climate indices, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9170, https://doi.org/10.5194/egusphere-egu24-9170, 2024.

EGU24-9531 | Posters on site | HS4.2

Building a hybrid drought monitor model based on U.S. Drought Monitor 

Haiting Xu, Jianhui Wei, and Ying Pan

Drought is one of the costliest natural disasters, capable of causing significant losses in agriculture, economy, and ecosystems. Different definitions of drought from multiple perspectives made drought research complicate. Exploring droughts from a comprehensive perspective improves our understanding of the evolution and drivers of drought, while there are few such comprehensive studies. The establishment of the United States Drought Monitor (USDM) marks a significant milestone in the development of composite drought indices, amalgamating objective inputs with subjective evaluations from local experts. Its uniqueness lies in integrating subjective assessments from climate and water resource experts across the United States. However, due to the human subjectivity involved in creating USDM maps, its algorithms are challenging to apply beyond the United States. In this study, a Hybrid Drought Monitor Model (HDMM)  was built using the random forest algorithm to predict drought categories based on USDM drought categories, input drought indices, and 10 static variables. The results indicate that during the testing phase, the overall accuracy of the 0.04° resolution HDMM reached 95%, surpassing the 91% overall accuracy at 1° resolution. Among the categories, D-1 (Normal or wet conditions) drought accuracy was the highest, while D0 (Abnormally Dry) drought accuracy was the lowest. During the validation phase, the HDMM exhibited good overall prediction of drought levels, yet spatial discrepancies existed across the continent. It performed poorly in the southwestern and northern regions, with overestimation of drought severity in many areas. Case studies of the 2017 Northern Plains Drought and the 2021 Southwestern Drought demonstrate that HDMM provided reliable drought classification and possessed good predictive capability. The HDMM can be adapted to other regions worldwide, offering a promising tool for land managers and local governments to prepare for and mitigate the impacts of drought.

How to cite: Xu, H., Wei, J., and Pan, Y.: Building a hybrid drought monitor model based on U.S. Drought Monitor, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9531, https://doi.org/10.5194/egusphere-egu24-9531, 2024.

EGU24-10512 | Orals | HS4.2 | Highlight

Water scarcity under droughts and heatwaves: understanding the complex interplay of water quality and sectoral water use 

Michelle van Vliet, Gabriel Cardenas Belleza, Duncan Graham, and Edward Jones

Droughts and heatwaves pose serious challenges for water management and severely increase water scarcity in many regions of the world. It is increasingly recognized that water scarcity represents more than just a physical lack of water, referring to the imbalance between the supply and the demand of water of suitable quality for different uses. Changes in both climate and socioeconomic systems influence the availability, use and quality of water resources. Water scarcity thus amplifies when either one or more of the following three driving mechanisms intensify: 1) decreasing water availability; 2) increasing sectoral water use, and 3) deterioration of water quality resulting in unsuitability for use. Droughts and heatwaves are particularly critical as they adversely affect all three driving mechanisms, which are also highly interrelated1. However, limited understanding exists regarding the complex interplay, particularly between water quality and sectoral water use. Here we show responses in sectoral water use and water quality under droughts and heatwaves based on reported data for 1980-2019 globally and discuss a global assessment framework to unravel water scarcity and its drivers under these hydroclimatic extremes.

Our results show that heatwaves and compound drought-heatwave events increase water use mainly for domestic and irrigation water use sectors2. River water quality tends to deteriorate during droughts and heatwaves in most cases as demonstrated based on a global literature survey3 and analyses of river water quality records of 314,046 water quality monitoring stations globally4. This showed for instance on average a 17% decrease in dissolved oxygen and 24% increase in river salinity under droughts and heatwaves over 1980-2019 globally4. Increasing sectoral water use, deterioration of water quality and decreasing water availability each amplify water scarcity in their own right, but more so together due to important interactions. For instance, a decline in water availability during a drought increases water scarcity directly, but also indirectly as less water is available to dilute pollutants, thereby leading to a deterioration of water quality3,4. This may result in higher water scarcity, when water quality thresholds for certain uses are temporary exceeded (e.g., increased salinity for irrigation). Increases in sectoral water use, such as for domestic use and irrigation2, result in higher water scarcity directly, but also indirectly due to water quality impacts. We propose a new integrated modelling framework building on the PCR-GLOBWB2 hydrological model coupled to the DynQual global surface water quality model5 to quantify water scarcity under droughts and heatwaves. Here we consider the two-way interactions between sectoral water use, water quality and water availability to improve understanding of the complex interplay between these water scarcity drivers, and test solutions options towards sustainable water management.

 

1 van Vliet, M.T.H. (2023) Nature Water 1, 902–904

2 Cárdenas Belleza, G.A., M.F.P. Bierkens, M.T.H. van Vliet (2023) Environ. Res. Lett. 18 104008

3 van Vliet, M.T.H. et al (2023) Nature Reviews Earth Environ. 4, 687–702

4 Graham D.J., M.F.P. Bierkens, M.T.H. van Vliet (2024), J. of Hydrology 629, 130590

5 Jones, E.R., M.F.P. Bierkens, N. Wanders, E.H. Sutanudjaja, L.P.H. van Beek, M.T.H. van Vliet (2023) Geosci. Model Dev. 16, 4481–4500

How to cite: van Vliet, M., Cardenas Belleza, G., Graham, D., and Jones, E.: Water scarcity under droughts and heatwaves: understanding the complex interplay of water quality and sectoral water use, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10512, https://doi.org/10.5194/egusphere-egu24-10512, 2024.

EGU24-10886 | ECS | Orals | HS4.2

Explainable machine learning revealing the mechanism behind drought events in northern Italy: the case of the 2022 drought 

Chenli Xue, Aurora Ghirardelli, Jianping Chen, and Paolo Tarolli

Drought is a complex natural hazard involving multiple variables that, depending on the measured parameters, can be categorized into meteorological, hydrological or agricultural drought. Among them, agricultural drought, which refers to soil moisture deficits that fail to meet crop growth, has been attracting more attention for severely threatening food security worldwide. In the context of climate change and the increased occurrence of drought events, it is crucial to monitor drought drivers and progression to plan the subsequent efforts in drought prevention, adaptation, and migration. However, the comprehensive knowledge of agriculture drought still needs to be clarified. Previous works often focused on precipitation or evapotranspiration and failed to capture other potential drivers of drought. This study proposes a novel framework to comprehensively monitor agricultural drought with ensemble machine learning by constructing an integrated agriculture drought index with high temporal-spatial resolution. In addition, the Shapley Additive Explanation (SHAP) explainable model was applied to reveal the driving mechanism behind the drought event that occurred in northern Italy in the summer of 2022. Results indicate that the proposed explainable ensemble machine learning model could effectively reflect the evolution of agricultural drought with spatially continuous maps on a weekly scale. The SHAP analysis demonstrated that the severe agricultural drought in the summer of 2022 was closely related to meteorological indicators, namely precipitation and land surface temperature, crucial in controlling soil moisture. Moreover, the new findings also revealed that soil textures could significantly affect agricultural drought. By combining explainable ensemble machine learning and various earth-observation data involving meteorology, soil, geomorphology, and vegetation conditions, the study constructed an integrated index to monitor and assess agricultural drought in northern Italy. The proposed research framework could effectively contribute to improving the methodology in agricultural drought research, potentially bringing more instructive insights for drought prevention and mitigation.

How to cite: Xue, C., Ghirardelli, A., Chen, J., and Tarolli, P.: Explainable machine learning revealing the mechanism behind drought events in northern Italy: the case of the 2022 drought, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10886, https://doi.org/10.5194/egusphere-egu24-10886, 2024.

EGU24-10948 | Posters on site | HS4.2

On the use of standardized drought indices (SPI and SPEI) for assessing future climate change impacts on drought: introducing a dynamic approach   

David J. Peres, Brunella Bonaccorso, Nunziarita Palazzolo, Antonino Cancelliere, Giuseppe Mendicino, and Alfonso Senatore

Drought is frequently monitored using standardized indices, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI). The latter was specifically designed to incorporate climate variability in terms of temperature. Consequently, by definition, it is more suitable for assessing variations in drought frequency and magnitude induced by climate change across various potential future scenarios. 

However, standardization presents a challenge when employing indices to evaluate the potential impacts of future climate change on drought. This is because, by definition, these indices are drawn from a standard normal random variable (null average and unit variance). The assessment of these impacts involves comparing occurrences in a future period and scenario with those in a historical control period. If the indices are separately calibrated for each period (one calibration for the future period and one for the control period), any differences observed may result solely from the sampling variability of a series drawn from a standard normal random variable. Numerous studies have assessed climate change impacts on droughts using this imperfect approach. Conversely, an alternative approach involves computing future indices using parameters from the control period. This represents a "worst-case scenario" as it overlooks potential climate change adaptation measures that could mitigate the impacts. To address this issue, our study introduces a dynamic approach wherein future changes are evaluated by computing climate normals using moving time windows. This approach enables an understanding of how impacts change with the timing of the implementation of adaptation measures. We apply this approach to Sicily and Calabria in Southern Italy, considering various climate change scenarios (Representative Concentration Scenarios). The results suggest that the region is likely to experience an increase in drought events due to climate change. These findings underscore the necessity for revised drought identification strategies that consider the non-stationarity in climate. 

How to cite: Peres, D. J., Bonaccorso, B., Palazzolo, N., Cancelliere, A., Mendicino, G., and Senatore, A.: On the use of standardized drought indices (SPI and SPEI) for assessing future climate change impacts on drought: introducing a dynamic approach  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10948, https://doi.org/10.5194/egusphere-egu24-10948, 2024.

EGU24-11049 | Orals | HS4.2 | Highlight

On the predictability of the seasonal droughts at global scale 

Luis Samaniego, Ehsan Modiri, E.H. (Edwin) Sutanudjaja, Pallav Shrestha, Alberto Martinez-de la Torre, Oldrich Rakovec, Robert Schweppe, Matthias Kelbling, Katie Facer-Childs, Amulya Chevuturi, Maliko Tanguy, Niko Wanders, Rohini Kumar, and Stephan Thober

Long-lasting droughts have become more common worldwide in recent decades, such as in Australia (2001-2009), California (2012-2014), Chile (2010-2023), and Europe (2018-2022). The combination of droughts and heatwaves has led to intense flash droughts, worsening soil moisture deficits. This has resulted in global shortages of essential food, serious public health issues, and prolonged forest fires that harm air quality in populated areas. Extended droughts also contribute to food insecurity, reduced energy production, increased health crises, and the destruction of natural landscapes, causing significant economic setbacks in various regions. International agencies, such as the WMO, and water authorities are actively promoting the advancement of seasonal soil moisture monitoring and forecasting systems. In this presentation, we'll give you an update on ULYSSES [2], the global multi-model hydrological seasonal predictions system supported by the Copernicus Climate Change Service. This fully operational system runs directly at the ECMWF's HPC and aims to be the first seamless multi-model hydrological seasonal prediction system with global coverage at a spatial resolution of 0.1 degrees.

The ULYSSES modeling chain builds on the successful EDgE proof of concept [3], employing four advanced hydrological models (Jules, HTESSEL, mHM, PCR-GLOBWB). Notably, this production chain features a distinctive aspect: the utilization of a standard set of physiographical datasets (e.g., DEM, soil properties) with consistent spatio-temporal resolutions and similar forecast inputs for all hydrological models, as well as the same multi-scale routing model (mRM). The seasonal forecasts are initialized using the ERA5-land product from ECMWF. The Equitable Thread Score (ETS) skill is employed to assess the ensemble forecasting abilities for drought events, specifically when soil moisture exceeds 80% of the time, across lead times ranging from one to three months.

In a recent assessment, the global ensemble Equitable Thread Score (ETS) for the system stands at 63%, 43%, and 34% for lead times ranging from 1 to 3 months. Notably, over Europe, the ensemble ETS is significantly higher, reaching 91%, 71%, and 61% for the corresponding lead times. Contrasting these findings with a prior study that employed the mHM initialized with E-OBS forcing and the NMME ensemble over Europe [4], our analysis suggests potential reasons for the diminished performance of the current system. These factors may include: 1) the meteorological forcings utilized for initializing the hydrological models, and/or 2) the skill level of the NWF model ensemble. In this study, we will present the sensitivity of ETS when one of the models (mHM) is initialized with different available forcings procucts available such as EM-EARTH, MSWEP, WE5E, and E-OBS. Finding of this study is key for the further improvement of the system.

References

  • [1] https://doi.org/10.1029/2021EF002394
  • [2] https://www.ufz.de/ulysses
  • [3] https://doi.org/10.1175/BAMS-D-17-0274.1
  • [4] https://doi.org/10.1175/JHM-D-12-075.1
  • [5] https://doi.org/10.1175/JHM-D-19-0095.1

How to cite: Samaniego, L., Modiri, E., Sutanudjaja, E. H. (., Shrestha, P., Martinez-de la Torre, A., Rakovec, O., Schweppe, R., Kelbling, M., Facer-Childs, K., Chevuturi, A., Tanguy, M., Wanders, N., Kumar, R., and Thober, S.: On the predictability of the seasonal droughts at global scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11049, https://doi.org/10.5194/egusphere-egu24-11049, 2024.

EGU24-12175 | Posters on site | HS4.2

Evaluation of daily SPI and SPEI indices for near-real time drought monitoring over CONUS 

Olivier Prat, David Coates, Scott Wilkins, Denis Willett, Ronald Leeper, Brian Nelson, Michael Shaw, and Steve Ansari

Two drought indices; the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are computed over CONUS using daily precipitation and temperature estimates from the NOAA Daily U.S. Climate Gridded Dataset (NClimGrid-Daily). The NClimGrid-Daily dataset consists of four climate variables derived from the GHCN-D dataset: maximum, minimum, and average temperatures and precipitation from 1951 to the present with a 5-km grid resolution. While SPI only uses precipitation as an input to assess drought conditions, SPEI uses both precipitation and potential evapotranspiration (PET). The daily SPI and SPEI are computed over various time scales (30-, 90-, 180-, 270-, 365-, 730-day). The differences between the two indices are being evaluated focusing on the influence accumulation period, differing period of record, and various SPI (McKee et al 1993, Guttman 1999) and daily PET (Thornthwaite and Mather 1957, Camargo et al. 1999, Pereira and Pruitt 2004) formulations. The impact of the period of reference is analyzed to account for the impact of precipitation and temperature changes over time (i.e., 1952-present, 1960-1990, and 1990-2020 for instance). For the most recent period (2000-present), the NClimGrid-SPI and NClimGrid-SPEI are compared against existing droughts monitoring resources such as the weekly US Drought Monitor (USDM). The use of cloud-scale computing resources reduces considerably the computation time and allows for the near-real time computation of daily SPI and SPEI indices. The effort to transfer the SPI and SPEI from research to operation (R2O) and to provide near-real time drought monitoring capabilities is also presented.

How to cite: Prat, O., Coates, D., Wilkins, S., Willett, D., Leeper, R., Nelson, B., Shaw, M., and Ansari, S.: Evaluation of daily SPI and SPEI indices for near-real time drought monitoring over CONUS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12175, https://doi.org/10.5194/egusphere-egu24-12175, 2024.

EGU24-12211 | ECS | Posters on site | HS4.2

Developing a national scale drought modelling and short to medium-term forecasting framework for Scotland 

Shaini Naha, Zisis Gagkas, Nick Schurch, Johan Strömqvist, Alena Bartosova, Kit Macleod, and Miriam Glendell

Climate change is resulting in many countries including Scotland being increasingly vulnerable to periods of dry weather, impacting water users and the natural environment. In 2022, large parts of Scotland experienced water shortages, resulting in Scotland Environmental Protection Act (SEPA) suspending water abstractions for abstraction licence holders in some Scottish catchments. Managing these water scarcity events requires the development of a national-scale short- to medium- term drought forecasting capability. In this study, the applicability of widely used open source hydrological models for simulating low flows depends on how various hydrological processes are accounted for in the model structures, the use of diverse calibration criteria and analysis of the associated uncertainties. Currently, few studies exist that consider all these criteria for modelling low flow events. In this study, we choose a lumped conceptual model, GR6J and a semi distributed hydrological response unit-based model, HYPE, for simulating river discharge across 81 catchments in Scotland, used by SEPA to assess water scarcity events. Our modelling framework considered model structural uncertainties by using models of different complexities and model parametric uncertainties, through robust multi-objective model calibration. We first tested this framework on an experimental Scottish catchment where GR6J outperformed HYPE in simulating river discharge after automatic calibration against objective functions KGE and logNSE. Further, calibration against logNSE improved low flow simulation in both models. We then upscaled this methodology for 81 catchments using GR6J, resulting in overall a very good model performance in simulating river discharge in both calibration and validation period with KGE and logNSE ranging from 0.37-0.96 and 0.2-0.93 for 81 gauged catchments respectively. Our next task is to calibrate HYPE for these 81 catchments and use both calibrated models to derive an ensemble of short-term river flow forecasts using 5-days meteorological forecasts from the UK Met Office. Results in overall shall highlight the need for using ensemble of hydrological models and also indicate careful consideration of objective functions, while simulating and forecasting low flows.

How to cite: Naha, S., Gagkas, Z., Schurch, N., Strömqvist, J., Bartosova, A., Macleod, K., and Glendell, M.: Developing a national scale drought modelling and short to medium-term forecasting framework for Scotland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12211, https://doi.org/10.5194/egusphere-egu24-12211, 2024.

Drought is one of the natural hazard risks that badly affect both agricultural and socio-economic sectors. Hungary, which is located in Eastern Europe, has already been suffering from different drought periods, and the driest year since 1901 was 2011 when the annual precipitation in Hungary was only 72 percent of the normal value. To better understand droughts and to provide information for adaptation strategies and risk-management systems, there is a strong need for a methodological framework to simulate drought events. However, it is uncertain whether climate models can simulate extreme droughts given the well-known model bias of simulating too light rainfall too frequently. So, the aim of the current study is to investigate the effects of the different model settings on the reproduction of drought characteristics.

In order to quantify the impact of the use of different parameterization schemes on regional climate model outputs, hindcast experiments were completed applying RegCM4.7 to the Carpathian region and its surroundings at 10-km horizontal resolution using ERA-Interim reanalysis data as initial and boundary conditions. In this study, we are testing various combinations of the physics schemes (land surface, microphysics, cumulus and boundary layer schemes) for the year 2011. Each parameterization combination leads to different simulated climates, so their spread is an estimate of the model uncertainty arising from the representation of the unresolved phenomena. The analysis of the RegCM-output ensemble indicates systematic precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons.

Based on the results, RegCM is sensitive to the applied convection scheme, but the interactions with the other schemes (e.g., land surface or microphysics) affect the precipitation. Due to the different treatment of moisture in the schemes, there are differences not only between the representation of the precipitation cycle, but also in other climatological variables such as soil moisture, latent and sensible heat fluxes and cloud cover, which affect the drought characteristics.

 

The research was funded by the NKFIH-471-3/2021 project (the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014).

How to cite: Kalmár, T. and Pongrácz, R.: Parameterization-based uncertainties in RegCM simulations over Hungary in a dry year – a case study , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12456, https://doi.org/10.5194/egusphere-egu24-12456, 2024.

Agricultural drought threatens global water security, food security, and natural ecosystems. Accurate identification of agricultural drought is a crucial task to mitigate its consequences. However, it is challenging to achieve reliable and accurate regional agricultural drought assessment in both wet and dry climates at the same time. Therefore, the objective of this study is to identify a reliable and accurate agricultural drought index that performs well in both dry and wet climates. Drought indices such as the Standardized Precipitation Index (SPI), the Vegetation Condition Index (VCI), the Soil Moisture Anomaly index (SMA), and the Drought Severity Index (DSI) were calculated and compared against in situ drought information devised by official sources in China. The results showed that: (1) DSI based on the Global Land Data Assimilation System (GLDAS) products performed the best in identifying agricultural drought in both dry and wet climate regions of China. (2) Agricultural regions such as Northern arid and semiarid regions, Northeast China Plain, Huang-Huai-Hai Plain, and Loess Plateau, experienced moderate and severe agricultural droughts with a frequency of 20%. (3) The frequency of agricultural droughts observed in Northern arid and semi-arid regions and Northeast China Plain has slowed significantly over the last two decades with a significance level of 0.01. On the other hand, the number of agricultural droughts has increased in Yunnan-Guizhou Plateau since 2002.

How to cite: Pan, Y. and Xu, H.: Accuracy of agricultural drought indices and analysis of agricultural drought characteristics in China between 2000 and 2019, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12858, https://doi.org/10.5194/egusphere-egu24-12858, 2024.

EGU24-12984 | ECS | Posters on site | HS4.2 | Highlight

Understanding the Causalities between Multiple Environmental Variables and Droughts in Amazon Basin 

Weikang Qian, Yixin Wen, Alireza Farahmand, and Jesse Kisembe

Establishing an early-warning system for droughts in the Amazon Basin holds paramount importance due to the region's critical role in global climate regulation and biodiversity. Droughts in the Amazon not only impact local ecosystems and communities but also have far-reaching effects on global weather patterns and carbon storage capabilities. To fully understand the drought mechanism and improve early-warning monitoring, it is important not only to detect drought conditions by creating indicators but also to extract signals that could describe the risk of drought outbreaks. To reach this goal, our research characterizes pre-drought signals from multiple environmental variables using causal inference and information theory. This study focuses on environmental variables, such as temperature, precipitation, vapor pressure deficit, evapotranspiration rate, and relative humidity from three perspectives, spatiotemporal characteristic, anomalies, and accumulation. Environmental variables are obtained from satellite observations and reanalysis datasets. We harness the potential of these characteristics, exploring their intricate connections as precursors to drought formation and propagation. Expanding on simple association, we introduce causal inference techniques to discover causalities among environmental variables, and between environmental variables and droughts, while information theory helps us capture non-linear relationships among environmental variables. Thereby, we identify critical thresholds and pre-drought signals where these characteristics contribute to drought onset. This causality-based approach marks a departure from traditional indices, integrating temporal dynamics with a detailed understanding of system interactions. Our findings aim to contribute to sustainable land and water management in the Amazon, ultimately aiding in the preservation of its unique ecosystems and the services they provide.

How to cite: Qian, W., Wen, Y., Farahmand, A., and Kisembe, J.: Understanding the Causalities between Multiple Environmental Variables and Droughts in Amazon Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12984, https://doi.org/10.5194/egusphere-egu24-12984, 2024.

EGU24-13224 | Posters on site | HS4.2

The GRUVO web application: Bringing groundwater level predictions across Germany to the public 

Stefan Broda, Maximilian Nölscher, Matthias Heber, Patrick Clos, Markus Zaepke, and Wolfgang Stolz

The provision of current and predicted groundwater levels across Germany has become increasingly important, particularly due to the increasing likelihood of consecutive dry years. To address this issue, we present the interactive web application GRUVO, which was developed as a first step to provide groundwater level forecasts and relevant information in a targeted manner for different user groups. We also provide an overview of the features and operation of the application in its current version.

In addition to the visualisation of current groundwater levels, this mainly includes the presentation of monthly updated groundwater level forecasts and projections for short-term (up to 3 months), medium-term (up to 10 years) and long-term (up to 2100) forecast horizons at over 100 so-called reference monitoring sites (RM) distributed throughout Germany. Each of these RMs represents the groundwater levels or dynamics of a few thousand so-called cluster monitoring sites (CMs). This mapping of RMs to CMs was previously determined using a clustering approach. The RM prediction is based on 1-D convolutional neural networks (CNN), which are trained using time series of measured groundwater level data from the responsible state offices as target variables and measured meteorological forcing data from the German Weather Service (DWD) as predictors. Forecasted or projected meteorological information from the DWD is then used to predict future groundwater levels.

Apart from the available features of the current version, this contribution highlights operational challenges and nuances. It also outlines possible extensions for future development.

How to cite: Broda, S., Nölscher, M., Heber, M., Clos, P., Zaepke, M., and Stolz, W.: The GRUVO web application: Bringing groundwater level predictions across Germany to the public, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13224, https://doi.org/10.5194/egusphere-egu24-13224, 2024.

EGU24-13279 | ECS | Orals | HS4.2

Navigating Water Resource Management: A Forecasting Framework for Interannual Drought Projections 

Ze Jiang, Golam Kibria, and Ashish Sharma

Can CMIP6 decadal projections be effective for multi-decadal water resources planning? This is the underlying question that motivates the present research, investigating what are the key deficiencies that limit their direct use for applications, and whether cleverly formulated mathematical alternatives can be used as effective postprocessors. This study focuses on the development of a robust framework for predicting droughts over interannual to decadal scales to enhance water resource management. The proposed framework utilizes the Wavelet System Prediction (WASP) methodology, which refines the spectral attributes inherent to climate indices to improve the skill of drought forecasts. Further improvement in forecasting capability is achieved through the Hierarchical Linear Combination (HLC) logic, which incorporates forecasts from ten climate indices. These indices, including ENSO-related sea surface temperature anomalies and other climate drivers closely linked to Australian rainfall, are derived from decadal predictions of the Decadal Climate Prediction Project (DCPP). The results of projected drought indices across various scales in Australia demonstrate the substantial potential of the integrated HLC-WASP framework to significantly improve the forecast skills of medium to long-term drought scenarios. This advancement enables the water industry to adapt their strategic plans and optimize reservoir operations effectively. By providing more reliable near-term projections of water availability, this research contributes to effective water resource management, facilitating informed decision-making for water allocation and conservation initiatives.

How to cite: Jiang, Z., Kibria, G., and Sharma, A.: Navigating Water Resource Management: A Forecasting Framework for Interannual Drought Projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13279, https://doi.org/10.5194/egusphere-egu24-13279, 2024.

The availability of water resources generally refers to the volume of total water resources on the surface, sub-surface, and soil. For a precise assessment of the availability of water resources, it is necessary to secure the accuracy of meteorological forecasts such as precipitation and temperature forecasting and to be able to accurately evaluate the volume of invisible water resources under the surface. Metropolitan areas around large rivers can use water stably even in the event of a drought, but the upstream areas with small and medium-sized rivers are vulnerable to water supply stability in drought season. Therefore, highly reliable evaluation and prediction of river discharge is necessary to prepare comprehensive solutions such as efficient operation of water supply facilities and optimal use of available water resources during drought season.  In this study, river discharge was evaluated for 20-16 standard basins in the Yeongsan-Seomjin river basins, respectively, among major river basins in the republic of Korea. The Dynamic Water resources Assessment Tool (DWAT) was used as a assessment model. DWAT is a water resources assessment tool that can be used free of charge worldwide and can be applied to small and medium-sized river basins for water resource planning and management that considers surface water as well as groundwater and water usage for various purposes. The calibration period was set from 2012 to 2019, and the validation period was set from 2020 to 2021. In addition, simulation accuracy was calculated through a 1:1 comparison of observed and simulated discharge data based on the calibration point, and model efficiency (Nash Sutcliffe Efficiency, NSE)

How to cite: Jang, C., Kim, D., Choi, J., Shin, H., and Kim, H.: Evaluation of the River Discharge Considering Interaction of Surface water and Groundwater in the Yeongsan-Seomjin River in the Republic of Korea Using DWAT (Dynamic Water Resources Assessment Tool, DWAT), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13771, https://doi.org/10.5194/egusphere-egu24-13771, 2024.

EGU24-15433 | ECS | Orals | HS4.2

Exploring the Interplay of Climatic Trends, Reservoir Fluctuations, and Vegetation Dynamics in Paphos, Cyprus: A Decade-Long Study Towards Sustainable Resource Management 

Eleni Loulli, Ioannis Varvaris, Marinos Eliades, Christiana Papoutsa, and Marios Tzouvaras

Drought is a complex phenomenon that cannot be easily detected in its early stages and advances slowly, but cumulatively. Its consequences can be short-term, such as water deficiency in rivers and dams, and long-term like saltwater intrusion and ecosystem degradation. These impacts make agricultural productivity vulnerable, exacerbate waterborne diseases and increase the risk or wildfires, posing a threat to food security, safety and sovereignty. Cyprus, characterized by a semi-arid climate, experienced in recent years prolonged and frequent droughts that had multiple impacts on agricultural production and consequently the ecosystem and the economy. In the face of a changing climate and increased frequency of droughts, monitoring and understanding such phenomena is crucial in mitigating their impacts. Our overall goal is to investigate the relationships between climatic trends, reservoir fluctuations and vegetation dynamics over the study period. Therefore, we provide a comprehensive analysis of the previously mentioned relationships for the hydrological region of Paphos, (Cyprus) for the period between 2013 and 2023. Vegetated areas are extracted using the European Space Agency WorldCover tree cover, shrubland, grassland, and cropland land cover classes. The study integrates measurements at meteorological stations and satellite-derived time series to assess the relationship between climatic variables and vegetation processes. In particular, we compare the Standardized Precipitation Index (SPI) calculated using CHIRPS data (Climate Hazards Group InfraRed Precipitation with Station Data), with hydrological drought indices provided by the Water Development Department. The latter are estimated on the basis of a drought indicator system that utilizes monthly dam Inflows and mean daily flows of hydrometric stations. Additionally, we analyze spatial climatic variables (such as the MODIS Land Surface Temperature and Evapotranspiration) and vegetation indices (such as MODIS and Sentinel-2 Normalized Difference Vegetation Index, Enhanced Vegetation Index, and Green Chlorophyll Index). Preliminary results show that vegetation dynamics and drought patterns vary based on seasons and the studied land cover classes. The findings of our study are anticipated to contribute to sustainable land and water resources management in the Paphos region.

Acknowledgements

The authors acknowledge the ‘GreenCarbonCY’: Transitioning to Green agriculture by assessing and mitigating Carbon emissions from agricultural soils in Cyprus. The ‘GreenCarbonCy project has received funding from the European Union - Next Generation, the Recovery and Resilience Plan “Cyprus_tomorrow”, and the Research & Innovation Foundation of Cyprus under the Restart 2016-2020 Program with contract number CODEVELOP-GT/0322/0023.

How to cite: Loulli, E., Varvaris, I., Eliades, M., Papoutsa, C., and Tzouvaras, M.: Exploring the Interplay of Climatic Trends, Reservoir Fluctuations, and Vegetation Dynamics in Paphos, Cyprus: A Decade-Long Study Towards Sustainable Resource Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15433, https://doi.org/10.5194/egusphere-egu24-15433, 2024.

EGU24-15845 | Posters on site | HS4.2

Large scale modeling of clay shrink-swell risk for current and future climate scenarios. 

Aurelien Boiselet and Gregory Seiller

In recent years, the risk of clay shrinkage-swelling has emerged as a significant concern for land use planning and for insurance companies. These superficial clay soils exhibit vertical movement (contraction and expansion), linked to meteorological conditions. Despite the slow pace of these fluctuations, they can reach an amplitude large enough to damage buildings located on these soils. In France, this hazard appears in second rank in terms of losses with events that can generate more than one billion euros in losses .

To better mitigate this risk, the French geological and mining risks office (BRGM) conducted a detailed mapping of exposure to clay shrink-swell across France. This departmental-scale analysis is based on the lithological nature of the soil, the mineralogical composition, geotechnical behavior, but also the loss experience observed. However, the susceptibility of a soil to swell has not been studied at global scale but rather over some territories. Given the current climate change, it is also necessary to understand the conditions linked to the occurrence of these events as well as the inherent impacts. This study focus on these two aspects: exposure and impact.

To estimate whether a soil might be prone to swelling, we developed a machine learning model based on exposure maps published for France and the USA with a set of pedological parameters (CEC of clay, soil texture, bulk density, etc. coming from Soilgrids & Harmonized World Soil Database models) and geological parameters; associated with the presence of clayey soils with swelling capacity. We achieved a prediction accuracy of nearly 70% on our test set in these 2 countries. For France, this approach allows us to estimate that 52% of the territory presents a medium or high exposure to this peril, which is consistent with the BRGM analysis of 49%. With this approach we also estimated that 52% of Germany’s territory is exposed to medium to high swelling susceptibility.

The impact analysis of this hazard is performed on France based on the publication of the CatNat decrees by the French Central Reinsurance fund, the loss ratio observed by AXA and climate indicators such as the Standardized Precipitation-Evapotranspiration Index (SPEI). The SPEI is a climatic indicator that is sensitive to water-balance variations, calculated over different time scales, allowing for the assessment of both short-term and long-term climatic conditions. The SPEI is particularly useful in regions where evapotranspiration plays a significant role in moisture availability. By analyzing the SPEI in conjunction with the CatNat decrees and the loss ratio observed by AXA, we can gain a comprehensive understanding of the current clay shrink-swell risk. This multi-faceted approach allows us to not only assess the current state of the hazard but also predict future trends.

How to cite: Boiselet, A. and Seiller, G.: Large scale modeling of clay shrink-swell risk for current and future climate scenarios., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15845, https://doi.org/10.5194/egusphere-egu24-15845, 2024.

EGU24-16037 | ECS | Orals | HS4.2

A drought monitoring and forecasting system for Switzerland 

Vincent Humphrey, Fabia Hüsler, Simone Bircher-Adrot, and Adel Imamovic

The intensity and frequency of dry spells in Switzerland have increased in recent years and are likely to increase in the future. Meanwhile, increases in water use and competition between different actors also place a greater pressure on existing water resources. Because drought has been identified as one of the main risks for various economic sectors in Switzerland, a national monitoring and forecasting system is to be established through the joint efforts of three different governmental agencies (federal offices for the environment, meteorology and climatology, and topography). The project also actively involves stakeholders in its development.

In this contribution, we introduce the Swiss national drought project with a particular focus on user-centered design, in situ and satellite-based monitoring, and the integration of sub-seasonal forecasts. Results from a user-survey revealed that even though drought is multi-dimensional and affects stakeholders in different ways, one of their primary needs is still a holistic “combined” drought index that can serve as a common ground for discussion and decision-making. Simple, local-scale-focused designs were assessed as the most efficient and useful, whereas designs showcasing nationwide maps or scientific quantities (SPI, etc.) were the least meaningful to educated but not expert users.

Further efforts include the creation of a national in situ soil moisture monitoring network with approximately 30 stations, the development of meteorological and agricultural drought products and indices, as well as the establishment of near real time, downscaled, sub-seasonal forecasts derived from existing systems (ECMWF IFS Extended). Integrating these highly heterogeneous data streams into seamless products ranging from historical observations to sub-seasonal forecasts, all within a consistent climatological baseline, is expected to represent both a major technical challenge but also a significant step forward that will greatly benefit downstream user applications. This novel meteorological basis will directly feed into impact-relevant drought indices and hydrological models, with the aim of better supporting an early warning system that has to take into consideration the needs of a very diverse user community, such as hydropower production, navigation, agriculture, forestry, artificial snow production, or ecology.

How to cite: Humphrey, V., Hüsler, F., Bircher-Adrot, S., and Imamovic, A.: A drought monitoring and forecasting system for Switzerland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16037, https://doi.org/10.5194/egusphere-egu24-16037, 2024.

EGU24-16800 | Posters on site | HS4.2

Multi-Source Earth Observation Data for Drought Monitoring in the Borena Region in Southern Ethiopia 

Elias Cherenet Weldemariam, Getachew Mehabie Mulualem, Tinebeb Yohannes, Héctor Nieto, Ana Andreu, and Vicente Burchard-Levine

Drought is a recurring phenomenon in the Borena region of Southern Ethiopia. The imbalance between potential evaporation and precipitation during the growing season often results in drought conditions, posing significant threats to the biodiversity, agriculture and human activities. The zone has endured severe drought risk due to consecutive years of no rainfall, significantly impacting ecosystem services, livestock and agro-pastoralist communities. To mitigate the effects of droughts and to provide quick decision-making with timely information for an effective response, it is crucial to regularly analyze the information about its severity and its extent in terms of spatial and temporal pattern. This study analyzes the spatial and temporal pattern of drought in the Borena region, using integrated indices such the Composite Drought Index (CDI) from 2000 to 2022. The CDI, which incorporates the Precipitation Drought Index (PDI), the Temperature Drought Index (TDI), and the Vegetation Drought Index (VDI), are used as input to examine spatial and temporal drought patterns, providing a comprehensive view of drought conditions over the given area. Additionally, the Mann–Kendall trend test and Sen’s slope were employed to understand the trends of these indices and determine their magnitude of change.

The study identified the occurrence of extreme drought events in recent years during 2007, 2011, 2014, 2016, 2017, and 2021 in Borena Zone. The findings also showed a decreasing trend in rainfall, an increase in temperature, and a diminishing trend in vegetation condition during the study period. Specifically, the computed mean growing season of the Normalized Difference Vegetation Index (NDVI) values ranged between -0.02352 to 0.0312, with 57.67% of the Borena region showing a decreasing trend. Future work will incorporate actual evapotranspiration (ET) estimates based on thermal infrared (TIR) imagery within the CDI, as this has the potential to more rapidly detect water stress in vegetation compared to spectral indices such as NDVI. These findings can guide the development of climate policies, disaster risk reduction and strategies in Ethiopia, contributing to the mitigation of future drought impacts and the promotion of sustainable dryland natural resources practices, including supporting early drought warning detection systems for agro-pastoralist communities.

How to cite: Weldemariam, E. C., Mulualem, G. M., Yohannes, T., Nieto, H., Andreu, A., and Burchard-Levine, V.: Multi-Source Earth Observation Data for Drought Monitoring in the Borena Region in Southern Ethiopia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16800, https://doi.org/10.5194/egusphere-egu24-16800, 2024.

EGU24-17245 | Orals | HS4.2

Evaluation of opportunities to characterize and monitor moisture in the unsaturated zone above the Western Mountain Aquifer 

Peter Dietrich, Ulrich Maier, Alireza Kavousi, Anna Rieß, Irina Engelhardt, and Martin Sauter

The GRaCCE project (Groundwater Recharge and Climate Change Effects - Quantification of resilience of water resources in carbonate aquifers to drought conditions) aims to develop process-based integrated and data-driven surrogate methods for determining groundwater recharge and predicting droughts in order to support water management in semi-arid regions such as Israel, Palestine and Jordan. Previous studies have shown that the thick vadose zones (several hundred meters) prevalent in the region can be relevant for water management as long-term reservoirs and, if considered as a dynamic water resource, can contribute to mitigating supply shortages during long-term droughts. In order to evaluate this water resource, it is necessary to characterize and monitor the moisture distribution in the vadose zone. In principle, borehole- and surface-based geophysical methods as well as remote sensing data can be used for this purpose. In order to assess the possibilities of the various methods for the specific site conditions of the Western Mountain Aquifer, the water balance of the area was investigated for the period from 1950 to 2020 using a double permeability variably saturated HydroGeoSphere model. Moreover, the distribution of soil moisture content at four intervals up to a cumulative depth of two-meter was inspected utilizing FLDAS2 NASA daily dataset. The temporal development of vertical moisture profiles was extracted from the HydroGeoSphere and FLDAS2 models for some selected locations. The profiles show a strong “intra-annual variation” at soil level which is strongly dampened by a depth two meter. This variability is generally not observed in higher depth profiles, as generated by HydroGeoSphere, where the shift from wet to dry periods made some “inter-annual variation” of moisture content. This result further supports the former studies claiming the importance of vadose zone on regulation of drought periods at aquifer level. Moreover, based on this assessment, a site-specific initial assessment of the suitability of the measurement methods such as cosmic ray neutron sensing, ground penetrating radar, resistivity measurements, nuclear magnetic resonance and remote sensing was carried out.

How to cite: Dietrich, P., Maier, U., Kavousi, A., Rieß, A., Engelhardt, I., and Sauter, M.: Evaluation of opportunities to characterize and monitor moisture in the unsaturated zone above the Western Mountain Aquifer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17245, https://doi.org/10.5194/egusphere-egu24-17245, 2024.

EGU24-17370 | Orals | HS4.2

Empowering communities through seasonal forecasts use: a lesson learned from the Euro Mediterranean 2021-2023 drought event 

Massimiliano Pasqui, Ramona Magno, Arianna Di Paola, Sara Quaresima, Elena Rapisardi, Lenadro Rocchi, and Edmondo Di Giuseppe

In the period between 2021 and 2023, the Euro-Mediterranean region experienced a series of significant thermo-pluviometric anomalies. In particular, in the central Mediterranean, the Copernicus Climate Change Service identified exceptional temperature anomalies and a complex and intense drought, also highlighted in the "European State of the Climate (ESOTC)" reports. Prolonged periods characterised by extreme weather events pose a serious threat to both society and human activities, even in advanced countries. 

Water scarcity and water resources management play a prominent role among the climatic threats, as their impacts represent the main pressure mechanisms for human beings, ecosystems, and many human activities. Therefore, it becomes imperative to develop advanced systems for forecasting and anticipating climate variability to provide crucial information to decision-makers and users, facilitating preparation for mitigation actions. Addressing this challenge requires the implementation of operational predictive systems on a seasonal scale that are reliable, salient, and easily adaptable, aiming to enhance economic and societal resilience. To this end, the Drought Observatory (DO) of CNR IBE, a web-based climate service open to the public, has developed and maintained a prediction system based on various components: a seamless prediction system based on the European model SEAS5, coupled with a bias adjustment algorithm; a Non-Homogeneous Poisson process trend analysis of individual drought severity classes; and an evaluation of vegetation stress trough indices calculated from both atmospheric variables and remotely sensed quantities. The DO has been conceived to share both the outcomes of ever-evolving scientific research and a structured set of scientific information. Tailored to different levels of complexity, this information aims to address the informational needs of both technical experts and decision-makers, as well as a wider audience and media representatives.

The DO develops these components in close collaboration with stakeholders and users engaged in institutional activities and national and international research projects. This interaction strengthens decision-making processes for adapting to meteorological and climatic risks and adversities.

An integrated approach, that relies on “converging evidence”, has been adopted to achieve an even more pertinent level of information. The 2021-2023 period, characterized by extreme climatic conditions, has been studied as a rare multiyear event to assess the effectiveness of seasonal-scale anticipation systems for climate anomalies. Moreover, this timeframe proves particularly valuable for understanding and addressing challenges associated with climate change.

Verification analysis shows that seasonal forecast skills vary over time and geographical areas. It is thus possible to identify windows of opportunity for specific tasks in cooperation with users. Within this framework, bias-corrected seasonal forecasts provide valuable supporting information for water resources management and decision-making processes. Throughout the drought period from 2021 to 2023, the Drought Observatory played a pivotal role, extensively utilized by national and international media to disseminate precise information regarding the drought trend in Italy. This underscores the crucial requirement for timely and science-based data to enlighten the broader public.

How to cite: Pasqui, M., Magno, R., Di Paola, A., Quaresima, S., Rapisardi, E., Rocchi, L., and Di Giuseppe, E.: Empowering communities through seasonal forecasts use: a lesson learned from the Euro Mediterranean 2021-2023 drought event, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17370, https://doi.org/10.5194/egusphere-egu24-17370, 2024.

EGU24-18825 | ECS | Posters on site | HS4.2

Groundwater Resilience under Extreme Drought  

Eleyna McGrady, Claire Walsh, Stephen Birkinshaw, and Elizabeth Lewis

Abstract:

Government guidance suggests that, by 2050, water companies should be resilient to a 1-in-500-year drought, allowing them to maintain supply in all except the most extreme droughts. However, drought is poorly defined with no universally accepted definition. This is because drought is often the result of many complex processes, is not a distinct event, and is usually only recognisable after a period of time. This leads to problems when predicting, quantifying, and assessing the impact and magnitude of drought within the environment. Consequently, how do water companies prepare themselves for an extreme drought when such drought cannot be quantified? Particularly, how do they ensure that groundwater resources are resilient, given the dependence on these resources to provide public water supply? These questions are particularly prevalent due to the predicted changes in climate and the current lack of understanding of how and to what magnitude groundwater resources will be affected.

Global warming has already been shown to affect groundwater droughts in the UK, however its impact on groundwater resources has not been quantified due to the challenges associated with defining groundwater drought onset and termination, as well as the difficulties with identifying how precursor conditions affect the magnitude and duration of groundwater drought. This lack of knowledge makes groundwater resources vulnerable to direct climate change and also to the indirect socioeconomic pressures associated with climate change.

Modelling is an important process in the assessment of the impacts of drought on groundwater, however, the principle focus of climate change research with regards to groundwater has been on assessing the likely direct impacts of a general changes in precipitation and temperature patterns, using a range of modelling techniques such as soil water balance models, empirical models, conceptual models, and distributed models. However, model development has been focusses within specific fields, for example surface hydrology and flooding, groundwater, distribution networks, and water resource systems and the integration of these separate models has been limited. Integrated, physically-based, and spatially distributed models have generally not been used in large sample studies due to their extensive time, data, and computational resource requirements, however they are key to representing surface water-groundwater interactions accurately, which is key in determining how groundwater will be affected by changes in climate, and hence drought.

Subsequently, this research uses SHETRAN, a physically-based, spatially-distributed hydrological model, in a large sample size study of UK river catchments. Through using this model, the aim of this research is to address gaps in knowledge and fully understand the response of groundwater resources to changing climate, the impact of pre-cursor conditions on drought magnitude and duration, and aims to improve the current issue that is the lack of an adequate model that can be used to investigate these issues.

How to cite: McGrady, E., Walsh, C., Birkinshaw, S., and Lewis, E.: Groundwater Resilience under Extreme Drought , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18825, https://doi.org/10.5194/egusphere-egu24-18825, 2024.

EGU24-19051 | Orals | HS4.2

Multi-model seasonal forecasting service for meteorological droughts 

Hector Macian-Sorribes, Dariana Avila-Velasquez, and Manuel Pulido-Velazquez

Drought indicators have been proven to be powerful tools to improve drought awareness and decision-making, being a key information source for water resource management in many countries and regions over the world. However, the integration of meteorological drought indicators and seasonal forecasts is not fully explored yet, since most of the drought prediction and early warning services (e.g. European Drought Observatory, Climate Prediction Center) offer limited information on drought forecasting at the seasonal scale.

This contribution presents a multi-model seasonal forecasting service of selected meteorological drought indicators, developed in the context of the WATER4CAST project, for the Jucar River Basin (Spain). This service offers seasonal forecasts (up to 6-7 months in advance) of SPI and SPEI indicators with time aggregations of 6, 12, 18 and 24 months. Input meteorological forecasts to compute them are obtained from the Copernicus Climate Change Service (C3S) for the ECMWF-SEAS5, MétéoFrance-System8, DWD-GCFS21 and CMCC-SPSv35 forecasting systems. These forecasts are post-processed against ERA5 reference data to ensure they are tailored to the climatic patterns of the Jucar River Basin, employing artificial intelligence algorithms (fuzzy logic) trained for the 1995-2014 period. Reference evapotranspiration for the calculation of SPEI indicators is estimated using the Hargreaves method. Once meteorological forecasts are post-processed and upscaled to the monthly scale, aggregated forecasts required to compute SPI and SPEI are made by combining them with past data from ERA5 (e.g. an SPI12 forecast for the next month would require 12-month aggregated precipitation forecasts made up by combining precipitation predictions for the next month with past precipitation records for the last 11 months). Finally, aggregated forecasts of precipitation (for SPI) and precipitation less reference evapotranspiration (for SPEI) are transformed into SPI and SPEI by standardizing them using the gamma (SPI) and the loglogistic (SPEI) probability functions, fitted for each ERA5 point using reference data for the 1973-2022 period. All the calculation process is coded in Python, and it is automatically launched as soon as new seasonal forecasts are available in the C3S.

The resulting service offers seasonal forecasts at the monthly scale, from 1 to 6/7 months in advance (depending on the forecasting system), of SPI and SPEI for the aggregations given at each point of the ERA5 grid overlapping the Jucar River Basin. These forecasts are uploaded into a web platform (https://water4cast-app.upv.es/) that offers information both for a given point (in with the ensemble of SPI and SPEI forecast is displayed using box-whisker plots) and with a general picture (depicting the probability of being in a dry (index <= -1), normal (-1 < index < 1) or wet (1 <= index) period.

Acknowledgements:

This study has received funding from the SOS-WATER project, under the European Union’s Horizon Europe research and innovation programme (GA No. 101059264) and the subvencions del Programa per a la promoció de la investigación científica, el desenvolupament tecnològic i la innovació a la Comunitat Valenciana (PROMETEO) under the WATER4CAST project.

How to cite: Macian-Sorribes, H., Avila-Velasquez, D., and Pulido-Velazquez, M.: Multi-model seasonal forecasting service for meteorological droughts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19051, https://doi.org/10.5194/egusphere-egu24-19051, 2024.

EGU24-19099 | Orals | HS4.2

Drought’s trends over continental Chile using climatic variables of water demand and supply, soil moisture, and vegetation productivity 

Francisco Zambrano, Francisco Meza, Nicolas Raab, and Iongel Duran-Llacer

A persistent drought is impacting Chile. It affects the hydrological system and vegetation development. Research studies have focused on the central part of the country. This is due to a persistent period of water scarcity. This scarcity has been found to be a megadrought. This megadrought was defined by the Standardized Precipitation Index (SPI) of twelve months in December. The SPI only considers precipitation as a drought indicator. It does not account for atmospheric evaporative demand (AED), soil moisture, or their combined effect on vegetation productivity, which are key to understanding the impact of climate on ecological and agricultural drought. We use monthly climatic variables for precipitation, temperature, and soil moisture (1 meter depth) from the ERA5-Land reanalysis product for 1981–2023. Also, we used the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2000–2023. We calculated the atmospheric evaporative demand (AED) using temperature and the Hargreaves-Samani equation. Then, to evaluate water supply, we derived the SPI. For water demand, we calculated the Evaporative Demand Drought Index (EDDI). We propose the standardized anomaly of cumulative soil moisture at one meter (zcSM) as a multi-scalar drought index for soil moisture. The above indices were calculated for time scales of 1, 3, 6, 12, 24, and 36 months. Lastly, we calculated a drought index for vegetation (a proxy for vegetation productivity), the standardized anomaly of the cumulative NDVI of six months (zcNDVI-6). We use the zcNDVI-6 to assess the impact of variations in water demand and supply on vegetation. We use a Mann-Kendall test to analyze the historical trend of the drought indices in continental Chile. Also, we calculated the temporal correlation between the indices of water supply, water demand, and soil moisture with the zcNDVI. To summarize the results, we divide Chile into five macrozones regarding a latitudinal gradient (north to south): i) “Norte Chico," ii) “Norte Grande," iii) "Centro," iv) "Sur," and v) "Austral." The analysis of trend showed that in the macrozones "Norte Chico," "Centro," and "Sur," the SPI has a decreasing trend that increases at longer time scales (from 1 to 36 months). The trend on EDDI reaches its maximum in the macrozones "Norte Grande" and "Norte Chico," being higher at longer time scales. Regarding the correlation with zcNDVI-6, it was higher for the drought index of soil moisture accumulated over 12 months (zcSM-12), having a r-squared of 0.49 for the “Norte Chico” and 0.44 for the "Centro." Followed by a r-squared of 0.41 with SPI-36 (precipitation accumulated over three years) in the macrozone “Norte Chico.” We conclude that Chile has a persistent decline in water supply for the central part of the country ("Norte Chico" and "Centro") and an increase in water demand in the north ("Norte Grande," "Norte Chico," and "Centro"). The combined effect has contributed to exacerbate the impact on vegetation in the "Norte Chico" and "Centro." The variability of drought conditions in vegetation can be explained in ~50% by de zcSM-12.

How to cite: Zambrano, F., Meza, F., Raab, N., and Duran-Llacer, I.: Drought’s trends over continental Chile using climatic variables of water demand and supply, soil moisture, and vegetation productivity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19099, https://doi.org/10.5194/egusphere-egu24-19099, 2024.

EGU24-19536 | Orals | HS4.2

Drought monitoring and early warning with satellite soil moisture data 

Mariette Vreugdenhil, Samuel Massart, Pavan Muguda Sanjeevamurthy, Carina Villegas-Lituma, Markus Enenkel, and Wolfgang Wagner

Many developing countries strongly depend on agriculture, but the sector is challenged by the increasing occurrence of droughts.  Unfortunately, advanced agricultural drought monitoring that can trigger early warning and early action is still not widely available for many countries even though it is crucial to stakeholders including local and regional governments, NGOs, farmers, and vulnerable households. Classic drought monitoring tools often rely on precipitation data, which are influenced by the density of station data. Recently, satellite soil moisture data has gained interest, because of its direct link to plant available water content and the increased availability and quality of satellite soil moisture products over remote regions.  Furthermore, when using radar observations, such as those from Sentinel-1 and Metop ASCAT spatial resolutions up to kilometers can be achieved and information on spatial variability of drought within districts can be provided. Despite advancements in the development of satellite soil moisture products, there remains a significant gap in their adoption and utilization by stakeholders in drought monitoring tools and operational systems. Although a large number of drought indicators are available (Vreugdenhil. et al. 2022), they lack rigorous quality-control with impact data and are not analysis-ready. In addition, users are not familiar with the data or its benefits and have difficulties interpreting the indicators in the context of operational decision-support. 

This study will demonstrate the potential of satellite soil moisture for drought monitoring and yield prediction over Eastern Africa, highlighting strengths and weaknesses of satellite soil moisture. Particularly during the growing season, high correlations are found between different soil moisture products from H SAF Metop ASCAT, ESA CCI and ERA5-Land. During the dry season deviations occur due to subsurface scattering effects on the soil moisture signal.  When analyzing droughts, the onset, intensity and duration of droughts differ strongly with the different indicators. For example, for the Gaza region in Mozambique, severe to extreme drought conditions occurred for 1, 4 or 47 months within a 15 year period depending on the chosen drought indicator.  The impact of using different drought indicators and thresholds on drought severity classification creates challenges for integrating satellite soil moisture drought indicators in operational systems and parametric drought insurance. 

 

This research is funded by the Austrian Space Application Programme ROSSIHNI project : Remote Sensing and Social Interest for Humanitarian Insights.

Vreugdenhil, M., Greimeister-Pfeil, I., Preimesberger, W., Camici, S., Dorigo, W., Enenkel, M., van der Schalie, R., Steele-Dunne, S., Wagner, W., 2022. Microwave remote sensing for agricultural drought monitoring: Recent developments and challenges. Frontiers in Water 4.

How to cite: Vreugdenhil, M., Massart, S., Muguda Sanjeevamurthy, P., Villegas-Lituma, C., Enenkel, M., and Wagner, W.: Drought monitoring and early warning with satellite soil moisture data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19536, https://doi.org/10.5194/egusphere-egu24-19536, 2024.

EGU24-20109 | Posters on site | HS4.2

Using droughts indicators as triggers for water resources management in semiarid mountain regions 

Rafael Pimentel, Pedro Torralbo, Javier Aparicio, Eva Contreras, Ana Adreu, Cristina Aguilar, and María José Polo

In the current context of global warming, droughts frequency and severity have increased in the Mediterranean Region. The past hydrological year, 2022-2023, was a clear example of water scarcity after some years with precipitation below the historical mean threshold. In mountain catchments, this reduction in precipitation has resulted in a significant decrease of the seasonal snow and a shift in the common snowfall patterns. The coastal-mountain catchments in the Sierra Nevada mountain range (southern Spain) exemplify this situation. 

The use of drought indices, which are defined using hydrometeorological information, has been the most used tool for the development of warning systems and the definition of adaptation strategies. Indexes like the Standardised Precipitation Index (SPI) or the Streamflow Drought Index (SSDI), have been widely used when characterising both meteorological and hydrological droughts. However, in high mountain areas, the role of snowfall should also be taken into account in this index definition. Snowfall patterns clearly modifies the precipitation-runoff response on a seasonal basis, changing the water balance at different time scales. Therefore, “snow drought” might result in scarcity conditions even though no warning stage has been reached regarding drought’s alerts yet, and it should also be taken into account in the defintion of these indexes. Furthermore, the intrinsic characteristics of the snow cover in these regions: seasonality, with snow generally present from mid-autumn to mid-spring; low thickness and high density; various accumulation-ablation cycles throughout the year; and, high losses due to evaposublimation, make the specific definition even more necessary.

This work aims to characterise snowfall droughts in semiarid mountains, understanding its connection to precipitation and hydrological droughts, assessing the viability of using drought indexes as tools for a better water-management decision-making. The Guadalfeo Catchment in the Sierra Nevada Mountain Range has been chosen as a representative coastal-mountain catchment of the Mediterranean basin to carry out this analysis.

Both SPI and a Standardised Snowfall Index (SSI, defined as SPI but using snowfall data) were calculated in the study area on different time scales for a reference period of 40 years (1960-2020), together with SSDI from the available streamflow time series. The joint analysis of SSI and SPI on each time scale has allowed us to classify the four potential situations in relation to the occurrence of hydrological drought in the study catchments. The results show the relevant seasonality of snowfall droughts in this area, and the importance of persistent precipitation drought as antecedent conditions for the impacts of low-snow years on the spring and summer streamflow. The validation performed points to an increase of the annual variability of the snowfall regime, very much related to a higher torrentiality of the precipitation regime on an annual basis than to changes in temperature.


Acknowledgement: This research was funded by the Spanish Ministry of Science and Innovation through the research project PID2021-12323SNB-I00, HYPOMED—“Incorporating hydrological uncertainty and risk analysis to the operation of hydropower facilities in Mediterranean mountain watersheds”.

How to cite: Pimentel, R., Torralbo, P., Aparicio, J., Contreras, E., Adreu, A., Aguilar, C., and Polo, M. J.: Using droughts indicators as triggers for water resources management in semiarid mountain regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20109, https://doi.org/10.5194/egusphere-egu24-20109, 2024.

EGU24-20678 | Posters on site | HS4.2

Assessing potential future subsidence due to groundwater depletion in “Alto Genil” Basin (Southern Spain). 

Rosa Maria Mateos, Antonio Juan Collados-Lara, David Pulido-Velazquez, and Leticia Baena-Ruiz

The Vega de Granada aquifer stands out as one of the primary detrital aquifers in the "Alto Genil" Basin in Southern Spain. Its significance lies in its vast extension, covering nearly 200 km2, and its substantial renewable water resources amounting to approximately 160 hm3/yr. Positioned strategically in the metropolitan area of Granada, it holds great relevance from a social point of view. Historically, it has been a crucial water source for meeting agricultural and urban water demands in various municipalities within the Vega de Granada. Over recent decades, groundwater extraction has escalated significantly, driven by urban expansion, and especially during severe droughts that periodically impact the region, resulting in high subsidence rates related to substantial groundwater level depletions.

 

Historical subsidence rates have been monitored using remote sensing techniques, specifically Differential Interferometric Synthetic Aperture Radar (DInSAR). Previous studies utilized 3 independent sets of images from different satellites: the ENVISAT satellite (C-band) and Sentinel-1A satellites (C-band) from the European Space Agency, and the Cosmo-skyMed constellation (X-band) from the Italian Space Agency. The integration of these datasets has enhanced the definition of the affected area by ground deformation and its temporal evolution. Presently, the European Ground Motion Service from Copernicus provides user-friendly information about ground deformation rates across Europe. EGMS represents a novel tool for the study of natural/induced processes such as land subsidence.

 

We utilized compiled historical information to devise a preliminary method for assessing groundwater level depletion and its associated subsidence rates in potential future scenarios. The method simulates future groundwater level drawdowns through the application of a straightforward lumped balance equation proposed by Scott (2011). Various approaches, including simple conceptual models and machine learning techniques, were tested to simulate groundwater level dynamics. These approaches aided in a more comprehensive assessment, considering the structural uncertainty associated with different simulation methods. Additionally, we explored linear regression models and neural network approaches (such as NAR or ELMAN) to assess subsidence resulting from groundwater level depletion. Machine learning techniques proved effective in providing better insights into non-linear subsidence processes. In selected points, potential future subsidence in the horizon of 2071-2100 may double in a business-as-usual scenario within the aquifer.

Based on the analysis of potential future subsidence values, we identified constraints that should be imposed on groundwater policies due to the associated risk of land subsidence resulting from groundwater level depletion.

 

 

Acknowledgments: This research has been partially supported by the projects: STAGES-IPCC (TED2021-130744B-C21) and SIGLO-PRO (PID2021-128021OB-I00), from the Spanish Ministry of Science, Innovation and Universities.

How to cite: Mateos, R. M., Collados-Lara, A. J., Pulido-Velazquez, D., and Baena-Ruiz, L.: Assessing potential future subsidence due to groundwater depletion in “Alto Genil” Basin (Southern Spain)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20678, https://doi.org/10.5194/egusphere-egu24-20678, 2024.

EGU24-21136 | Orals | HS4.2

Enabling long-lead forecasting of agriculture production shocks with soil moisture monitoring and forecasting products to support food insecurity early warning 

Shraddhanand Shukla, Frank Davenport, Eric Yoon, Barnali Das, Weston Anderson, Abheera Hazara, Kim Slinski, and Amy L. McNally

As per USAID’s Famine Early Warning System Network Team (FEWS NET) 110-120 million people are projected to need emergency food assistance across all FEWS NET-monitored countries. Climate shocks such as droughts contribute to acute food insecurity. Better identification and earlier warning of anomalous conditions leading to food insecurity are critical to support decision-making to mitigate the impacts of food insecurity on lives and livelihoods. Agricultural production outlooks are one of the critical components of the famine early warning scenario generation process. Thus far these outlooks have mainly been based on estimates of seasonal rainfall or remotely sensed indicators of vegetation greenness whereas soil moisture estimates (remotely sensed or modeled) have been used as drought indicators but not directly used for crop yield forecasting to assess production shocks, particularly in operational settings. Our past research, which focused on crop yield forecasting in southern Africa, revealed a promising level of skill when soil moisture monitoring products or forecasts were used as predictors of crop yield, relative to traditional predictors such as December to February ENSO. Additionally, a separate study focused on East Africa revealed when and where soil moisture can be the best predictor of crop yield relative to other earth observations. Building upon this initial research, here we investigate the applicability of soil moisture monitoring and forecasting products in crop yield forecasting in up to 20 FEWS NET monitored countries for which processed crop yield data are available at sub-national scale. We first use soil moisture monitoring products, both remotely sensed (such as ESA-CCI) and modeled (such as FEWS NET Land Data Assimilation System) to implement and validate machine learning based within-season crop yield forecasting. We then use seasonal-scale soil moisture forecasts (up to 6 months in future) to enhance the lead-time of crop yield forecasting and implement and validate pre-season (before the start of a crop growing season) long-lead crop yield forecasting, as earlier estimates of food insecurity can provide additional critical time needed for launching famine prevention responses by governments and donor agencies.

How to cite: Shukla, S., Davenport, F., Yoon, E., Das, B., Anderson, W., Hazara, A., Slinski, K., and McNally, A. L.: Enabling long-lead forecasting of agriculture production shocks with soil moisture monitoring and forecasting products to support food insecurity early warning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21136, https://doi.org/10.5194/egusphere-egu24-21136, 2024.

EGU24-118 | Posters on site | HS2.1.5

Precipitation, temperature, and vegetation indices analysis for Saudi Arabia region: Feasibility of Google Earth Engine 

Zaher Mundher Yaseen, Bijay Halder, Mohamed A. Yassin, and Sani I. Abba

Climatic disaster is continuously triggering environmental degradation and thermal diversification over the earth's surface. Global warming and anthropogenic activities are the triggering factors for thermal variation and ecological diversification. Saudi Arabia has also recorded precipitation, temperature, and vegetation dynamics over the past decades. Therefore, monitoring past precipitation, temperature, and vegetation condition information can help to prepare future disaster management plans and awareness strategies. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR) from the Center for Hydrometeorology and Remote Sensing (CHRS) data portal and Moderate Resolution Imaging Spectroradiometer (MODIS) are applied for precipitation, Land Surface Temperature (LST), Enhance Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) from 2003 to 2021 respectively. Yearly mean LST, EVI, NDVI, and precipitation values are calculated through the Google Earth Engine (GEE) cloud computing platform. MODIS-based LST datasets recorded the highest temperatures is 43.02 °C (2003), 45.56 °C (2009), 47.83 °C (2015), and 49.24 °C (2021) respectively. In between nineteen years, the average mean LST increased by 6.22 °C and the most affected areas are Riyadh, Jeddah, Abha, Dammam, and Al Bahah. The mean Precipitation is recorded around 776 mm, 842 mm, 1239 mm, and 1555 mm for the four study periods, while the high precipitation area is Jazan, Asir, Baha, and Makkah provinces. In between nineteen years, 779 mm of precipitation is increasing in Saudi Arabia.  Similarly, the NDVI vegetation indices observed 0.885 (2003), 0.871 (2009), 0.891 (2015), and 0.943 (2021), while EVI observed 0.775 (2003), 0.776 (2009), 0.744 (2015), and 0.847 (2021). The R2 values of the LST and EVI correlation is 0.0239 (2003), 0.0336 (2009), 0.0136 (2015) and 0.0175 (2021) similarly correlation between LST and NDVI is 0.0352 (2003), 0.0265 (2009), 0.0183 (2015) and 0.0161 (2021) respectively. The vegetation indices indicate that the green space is gradually increasing in Saudi Arabia and the highly vegetated lands are Meegowa, An Nibaj, Tabuk, Wadi Al Dawasir, Al Hofuf, and part of Qaryat Al Ulya. This analysis indicates that the temperature is increasing but precipitation and green spaces are increasing because of the groundwater recharge through dam construction, precision agriculture, and planned build-up is helps to prepare Saudi Arabia as a green country. Therefore, more attention to preparing the strategic agricultural plants as well as other vegetation and artificial groundwater recharge can improve the country as a green nation. This analysis might help to prepare future planning, awareness, and disaster management teams to prepare for future disasters and strategic steps for sustainable development.

How to cite: Yaseen, Z. M., Halder, B., Yassin, M. A., and Abba, S. I.: Precipitation, temperature, and vegetation indices analysis for Saudi Arabia region: Feasibility of Google Earth Engine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-118, https://doi.org/10.5194/egusphere-egu24-118, 2024.

Water is scarce in the northern Chihuahuan Desert, with ~350 mm/yr precipitation, potential evapotranspiration at 1800mm/yr, and rising mean annual temperatures by >2°C since 1960. The main water resources are the Ogallala, Pecos Valley, Dockum, and Edwards-Trinity Plateau aquifers, with depletion rates of ~1 m/yr. Despite the arid climate, the Monahans and Kermit dune fields host perched water tables 1-10 m below the surface, in up to 40 m of aeolian sand spanning the past ca. 2.6 ma, and isolated from the underlying Pecos Valley Aquifer by a Pliocene/Pleistocene fluvial gravel-rich clay. A 3D model based on borehole lithology shows a topographic inversion with a southwest-trending paleo-slope infilled with aeolian sand. The aeolian stratigraphy and basin modeling indicate progressive infilling by aeolian sand with periods of pluvial lake formation and soil development, with groundwater providing dune field stability for vertical accretion and limiting aeolian erosion. Cores of sediments retrieved from the Monahans and Kermit dune fields were sampled for OSL ages and yielded ages up to 500 ka 20 m below the surface of the dunes, with identified deposition periods between 545-470 ka, 300-260 ka, 70-45 ka and post 16 ka. A set of three monitoring wells equipped with data loggers revealed aquifer recharge of 35-40 cm in the Spring and Fall consistent with regional precipitation variability, and a daily recharge cycle of 3-8 mm potentially linked to plant uptake or gravitational forces. Deuterium and 18O isotopic ratios for the dune field aquifers indicate an evaporative enriched water source compared to the Pecos Valley Aquifer, Pecos River, and Chihuahuan Desert precipitation, consistent with local precipitation. Apparent 14C ages <1360 yr for aquifer waters from the upper 1 m indicate recent meteoric recharge. Older 14C ages of > 1.3 to 2.2 ka for waters ~30 m deep and at the western edge of the aquifer indicate mixing with Holocene recharge waters in a southwest flowing aquifer. In contrast, the Pecos Valley Aquifer yields 14C ages of ca. 0.9 to 40 ka with the youngest ages near the dune fields, which suggests recharge from these perched aquifers.

How to cite: Fournier, A. and Forman, S.: Origin, gradient, and recharge processes of perched aquifers of the Monahans and Kermit dune fields, northern Chihuahuan Desert, Texas, USA , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-765, https://doi.org/10.5194/egusphere-egu24-765, 2024.

EGU24-1165 | ECS | Orals | HS2.1.5

Agrohydrological modelling approach for assessing the impact of climate change on water resources and land management in the Messinian region, Greece. 

ismail bouizrou, Giulio Castelli, Gonzalo Cabrera, Lorenzo Villani, and Elena Bresci

The Mediterranean region is highly susceptible to the consequences of warming, leading to an increasing of extreme events such as droughts, severe heat waves, and precipitation events. The Messinia watershed (MW) is predominantly characterized by olive cultivation, encompassing approximately 70% of the landscape. These olive orchards constitute a vital component of the Mediterranean ecosystem, playing a crucial role in regional agriculture. The MW is a perfect illustration of a Mediterranean watershed significantly impacted by climate change, as well as soil degradation and a lack of effective land management practices.

In this context, agro-hydrological modelling emerges as a potent tool to address soil degradation and enhance water resource retention within the olive orchards at the watershed scale. To achieve this objective, the SWAT+ agrohydrological model was chosen for a comprehensive assessment of the potential impacts of climate change on water resources and ecosystems in the Messinia region. The adopted modelling approach involved both hard and soft calibration techniques, simulating four sub-watersheds of Messinia by incorporating remote sensing data, including evaporation and soil moisture, for multi-criteria model calibration.

The calibrated model was subsequently employed to assess the potential impacts of climate change on water resources and ecosystems in the Messinia region, utilizing various RCM climate scenarios. Our findings are valuable for addressing soil degradation, as well as for guiding land and water management practices in the Messinian watershed.

 

 

This research was carried out within the SALAM-MED project, funded by the Partnership for Research and Innovation in the Mediterranean Area Programme (PRIMA).

The content of this abstract reflects the views only of the author, and the Commission cannot be held responsible for any use that may be made of the information contained therein.

 

How to cite: bouizrou, I., Castelli, G., Cabrera, G., Villani, L., and Bresci, E.: Agrohydrological modelling approach for assessing the impact of climate change on water resources and land management in the Messinian region, Greece., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1165, https://doi.org/10.5194/egusphere-egu24-1165, 2024.

Desertification on the Mongolian Plateau is deepening, and sand and dust have great negative impacts on many countries in East Asia. Based on meteorological and socio-economic data in the context of climate change, this study analyzed the driving mechanisms and impacts of desertification and water body area response on the Mongolian Plateau using, among others, the GTWR model. The following conclusions were drawn: the area of the Mongolian Plateau showed a decreasing trend from 1990 to 2019, and the number of lakes larger than 1 km2 decreased by 173 or 537.3 km2 in Inner Mongolia, and by 737 or 2875.1 km2 in Mongolia, and all of them were dominated by lakes of 1-10 km2; and the analysis of the correlation between the area of the water bodies showed that the The reasons driving the change of water body area in Inner Mongolia Autonomous Region and Mongolia are similar and different, soil moisture and precipitation have obvious promotion effects, economic development and livestock numbers have different degrees of negative impacts on different countries; The GTWR model is used to represent the impacts of different influencing factors on the water body area in time and space, and the evaporation and GDP are shifted from slight inhibition to promotion, and the population and temperature are both inhibited. Soil moisture and livestock numbers are contributing; Surface water resource monitoring is important to deepen the desertification of the Mongolian Plateau and to provide better water resource recommendations and protection measures for the Mongolian Plateau.

How to cite: Yan, Y. and Cheng, Y.: Study of water body area changes in the desertification process of the Mongolian Plateau and analysis of driving factors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1185, https://doi.org/10.5194/egusphere-egu24-1185, 2024.

EGU24-2567 | ECS | Orals | HS2.1.5 | Highlight

GIRHAF (Gridded hIgh-resolution Rainfall for the Horn of AFrica): a new rainfall product for detailed applications in a region beset by climate hazards 

Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer

Rainfall is one of the most important inputs for applications such as hydrological modelling, water resource allocation, flood/drought analysis, and climatic risk assessments. Currently, there exist numerous (global) products offering rainfall estimates at various spatio-temporal resolutions. Nevertheless, there are still places on Earth where the coverage and/or quality of such products is limited due to sparse ground-control data, thus constraining the robustness of input rainfall for hydrological and climate applications. Located in Eastern Africa, the Horn of Africa (HOA) is a place where climate impacts like droughts and floods frequently inflict a huge toll on the lives and livelihoods of millions residing in subsistence rural communities. For places like this, high resolution rainfall data are fundamental to understanding the availability of water resources, flood hazard, and soil moisture dynamics relevant to crop yields and pasture availability.

Here we introduce GIRHAF (Gridded hIgh-resolution Rainfall for the Horn of AFrica), which is a 20-year rainfall product, with a spatio-temporal resolution of 0.05°×0.05°, every 30 minutes. GIRHAF is based on downscaling CHIMES (Climate Hazards center IMErg with Stations) a pentad operational rainfall product which corrects microwave signals in IMERG (Integrated Multi-satellitE Retrievals for GPM -Global Precipitation Measurement mission-) by in situ rain gauging networks. The goal of this product is to offer the HOA region high-resolution rainfall fields that can support more detailed mechanistic analyses of historical rainfall and can also provide the base dataset required to develop stochastic rainfall models capable of simulating forecasted or projected climate scenarios. It is our aspiration that GIRHAF will enable improved responses to climatic hazards as well as better water resources management in the HOA region, and perhaps to allow people of this region to better prepare to future climate scenarios.

How to cite: Rios Gaona, M. F., Michaelides, K., and Singer, M. B.: GIRHAF (Gridded hIgh-resolution Rainfall for the Horn of AFrica): a new rainfall product for detailed applications in a region beset by climate hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2567, https://doi.org/10.5194/egusphere-egu24-2567, 2024.

EGU24-4462 | ECS | Posters on site | HS2.1.5

Modeling the impact of climate and land use changes on future water resources dynamics in central Sicily, Italy 

Shewandagn Lemma Tekle and Brunella Bonaccorso

Drought events, worsened by climate change, produce detrimental impacts on freshwater availability especially in arid and semi-arid regions. The situation becomes more critical when these hydrologic extremes combine with land use change mainly caused by anthropogenic factors, such as urbanization, intensive farming, and industrial activities. The present study is designed to investigate the combined impacts of climate and land use changes on the future freshwater  stored in the artificial reservoirs of three adjacent river basins located in the central Sicily (Italy), i.e: Verdura (2 active reservoirs with capacities 9.2 Mmc and 4.19 Mmc), Imera Meridionale (one active reservoir with capacity 15 Mmc), and Platani (one active reservoir with capacity 20.7Mmc), using the Soil and Water Assessment Tool (SWAT) model. The reservoirs are used for irrigation, drinking water supply, and electric power generation. Future climate variables such as rainfall, minimum and maximum temperatures were derived from an ensemble Regional Climate Models for two main representative concentration pathway (RCP) scenarios, such as an intermediate emission scenario (RCP4.5) and a severe emission scenario (RCP8.5). A coupled multi-layer perceptron neural networks and cellular automata (MLP-CA) model was implemented to simulate future land use of the region considering the CORINE land cover in 2000, 2006, 2012, and 2018 as a reference dataset. The future land use is then projected until the mid-century (2048) in a six-year interval using the validated MLP-CA model. The soil data from the European soil data center (EUSDAC) was used as input for the SWAT model. The result indicated that the basins could experience a decrease in inflows to the reservoirs. The separate evaluation of climate change and land use changes indicated that the effect of climate change on streamflow variation is more pronounced than the effect of land use change only. In this study, we introduced new hydrological insights into the region by analyzing the attributions of climate change, land use change, and coupled climate and land use changes on the future freshwater availability which were overlooked in the previous studies. The implementation of the proposed approach can contribute to design environmentally sustainable and climate resilient river basin management strategies.

 

Keywords: MLP-CA, Land use change, Climate change, SWAT, Hydrological modeling, Water availability

How to cite: Tekle, S. L. and Bonaccorso, B.: Modeling the impact of climate and land use changes on future water resources dynamics in central Sicily, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4462, https://doi.org/10.5194/egusphere-egu24-4462, 2024.

EGU24-5604 | Orals | HS2.1.5

An integrated hydrological modeling approach to assess the natural groundwater recharge trends in a Mediterranean coastal aquifer 

Anis Chekirbane, Khaoula Khemiri, Constantinos Panagiotou, and Catalin Stefan

Integrating physical models with socio-economic considerations is essential to sufficiently analyze complex hydrological systems and design effective strategies for groundwater management. This integrated approach offers an effective means of detecting links between aquifer properties and groundwater processes. This study aims to assess the impact of human activities and climate changes on groundwater resources. In particular, the final goal is to quantify the spatial distribution of natural groundwater recharge, which is needed to assess the impact of anthropogenic factors on sustainable groundwater management in the Chiba watershed, NE of Tunisia as an example of a stressed hydrosystem.

The proposed methodology is based on the estimation of natural groundwater recharge through hydrological modeling with the use of the SWAT model while considering land use/land cover changes occurring within the study area, coupled with the DPSIR (Drivers-Pressures-States-Impacts-Responses) socio-economic approach for time period 1985-2021. The surveys were constructed and processed based on the probability of occurrence for the degree of satisfaction with arguments related to the DPSIR parameter within the category of the 5-point Likert scale (ranging from level 1 - very low to level 5 - very high), including mean, standard deviation, and the consensus (CnS).
Chiba watershed was selected as a case study since its climate is representative of the Tunisian semi-arid context, and due to the high vulnerability of the existing groundwater systems with respect to human activities.

The hydrological simulations suggest a gradual decrease of 33% in the aquifer's natural recharge over the entire time period. The long-term average value of the annual recharge rate per sub-basin does not exceed 3 mm/year, keeping groundwater recharge levels in the basin relatively low. This observation is mainly attributed to climate change with CnS of 0.6 and over-exploitation of the water sources for irrigation purposes (CnS = 0.62), leading to aquifer depletion and degradation of groundwater-dependent ecosystems (CnS = 0.73). These results suggest that different management practices, such as more conservative water use (CnS = 0.6), long-term monitoring and Managed Aquifer Recharge (MAR) with wastewater (CnS = 0.76), can help rural residents to diversify their economies while preserving these water resources. However, although attempts of MAR have been undertaken, they remain insufficient to counter the pressure on the coastal aquifer, underlining the importance of preserving the fragile semi-arid landscape.

The proposed approach is applicable to other regions having similar climatic and socio-economic conditions. It also demonstrates that pure modeling solutions need to be coupled to the socio-economic approaches to be able to constitute a solid asset for sustainable water resources management of stressed hydro-systems.

 

Acknowledgments

This work is funded by National Funding Agencies from Germany,  Cyprus, Portugal, Spain, and Tunisia under the Partnership for Research and Innovation in the Mediterranean Area (PRIMA) and supported under Horizon 2020 by the European Union’s Framework for Research and Innovation.

How to cite: Chekirbane, A., Khemiri, K., Panagiotou, C., and Stefan, C.: An integrated hydrological modeling approach to assess the natural groundwater recharge trends in a Mediterranean coastal aquifer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5604, https://doi.org/10.5194/egusphere-egu24-5604, 2024.

EGU24-6984 | ECS | Posters on site | HS2.1.5

Westerly aridity in the western Tarim Basin driven by global cooling since the mid-Pleistocene transition 

Hongye Liu, Rui Zhang, Gaowen Dai, and Yansheng Gu

To explore the relationship between the global change, westerlies, and central Asian aridity, we report ~1.1 Ma local sedimentary environment changes according to high-resolution gamma ray (GR) from downhole logging, Grain size, magnetic susceptibility (MS), rubidium/strontium (Rb/Sr) ratios and total organic carbon (TOC) of an 800-m core (KT11) from the Kashgar region in the western Tarim Basin, arid zone of China. Four dominant sedimentation types, including lacustrine facies, delta facies, fluvial facies, and aeolian dunes, were identified through lithology and grain size frequency curves. The 1.1 Ma sedimentary successions experienced delta deposits with fluvial and aeolian deposits and lacustrines (1.1-0.6 Ma), alternating fluvial and aeolian facies with the occurrence of deltas and lacustrines (0.6-0.15 Ma), and aeolian facies interbedded with deltas and fluvial facies (0.15 Ma-present). Spectral analyses of the GR, MS, and Rb/Sr data reveal cycles with ~70 m, ~30 m and ~14 m wavelengths. These cycles represent ~100-kyr short-eccentricity, ~40-kyr obliquity and ~20-kyr precession frequencies, respectively and mainly are driven by orbitally forced climate change.

Stepwise drying sedimentary conditions and enhanced desertification indicated by increasing Rb/Sr ratios and proportion of aeolian sands, and decreasing TOC since the past 1.1 Ma, implied intensified westerlies, likely resulted from ice volume expansion and ongoing global cooling according to geological record comparison and simulations during the Last Glacial Maximum compared to preindustrial conditions, which may have controlled the expansion of the permanent deserts in inland Asia. These persistent drying trends and intensified westerly circulation in arid regions during glacial periods after the mid-Pleistocene Transition indicated by larger amplitudes of aeolian sand proportion than prior to 0.6 Ma are similar to those in the interior monsoonal Asia, where the larger-amplitude of median grain size indicated enhanced East Asian Winter monsoon intensity and drier glacials.

How to cite: Liu, H., Zhang, R., Dai, G., and Gu, Y.: Westerly aridity in the western Tarim Basin driven by global cooling since the mid-Pleistocene transition, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6984, https://doi.org/10.5194/egusphere-egu24-6984, 2024.

EGU24-7068 | ECS | Orals | HS2.1.5

Exploring Drought Patterns in the Headwaters of the Tarim River Basin through an Integrated Surface-Groundwater Drought Index 

Xiaohan Yu, Xiankui Zeng, Dongwei Gui, Dong Wang, and Jichun Wu

The Tarim River Basin, China's largest inland river, has been grappling with persistent drought challenges. Over 90% of its water resources originate from the headwaters, heavily relying on groundwater. Existing drought indices often compartmentalize considerations of surface water and groundwater variables. Consequently, there is a necessity for a comprehensive drought index that accounts for the interplay between surface water and groundwater. This study employs the Copula function to formulate the Standardized Precipitation Evapotranspiration Groundwater Index (SPEGI), incorporating surface water (precipitation minus evaporation) and groundwater (changes in total water storage observed by GRACE satellite minus changes in output from the VIC model). SPEGI is computed using a moving average approach across various time scales (1, 3, 6, 12 months) and is juxtaposed with traditional indices such as Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI), and Standardized Groundwater Index (SGI). The findings underscore that SPEGI, grounded in the integrated consideration of surface and groundwater variables, provides a more comprehensive depiction of drought conditions in the study area. In contrast to traditional indices, SPEGI not only accounts for short-term precipitation and evaporation changes but also effectively reveals the characteristics of groundwater fluctuations. Additionally, by comparing SPEGI with NDVI data, the study delves into the desertification process in the region. The research discerns that SPEGI's assessment of drought resilience is more sensitive, manifesting an increasing trend in the desertification process with the enlargement of SPEGI's sliding window. Overall, this research contributes novel methodologies and empirical evidence for fostering sustainable water resource utilization and informing climate change adaptation decisions within the basin.

How to cite: Yu, X., Zeng, X., Gui, D., Wang, D., and Wu, J.: Exploring Drought Patterns in the Headwaters of the Tarim River Basin through an Integrated Surface-Groundwater Drought Index, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7068, https://doi.org/10.5194/egusphere-egu24-7068, 2024.

EGU24-7611 | ECS | Orals | HS2.1.5

Locating unsustainable water supplies for supporting ecological restoration in China's drylands 

Fengyu Fu, Shuai Wang, and Xutong Wu

China, with vast dryland areas, has undertaken extensive ecological restoration (ER) projects since the late 1970s. While ER is a crucial means against desertification and land degradation, it must be implemented in a water-sustainable manner to avoid exacerbating the carbon–water trade-off, especially in water-limited drylands. However, there is still limited research on accurately identifying water unsustainable ER regions in China's drylands. Here, we developed a water supply–demand indicator, namely, the water self-sufficiency (WSS), defined as the ratio of water availability to precipitation. With the use of remote sensing and multisource synthesis datasets combined with trend analysis and time series detection, we conducted a spatially explicit assessment of the water sustainability risk of ER in China's drylands over the period from 1987 to 2015. The results showed that 17.15% (6.36 Mha) of ER areas face a negative shift in the WSS (indicating a risk of unsustainability), mainly in Inner Mongolia, Shanxi, and Xinjiang provinces, driven by evapotranspiration. Moreover, 29.34% (10.9 Mha) of the total ER areas, whose area is roughly double that of water unsustainable ER areas, exhibit a potential water shortage with a significant WSS decline (-0.014 yr-1), concentrated in Inner Mongolia, Shaanxi, and Gansu provinces. The reliability of our findings was demonstrated through previous studies at the local scale and an analysis of soil moisture changes. Our findings offer precise identification of water unsustainable ER regions at the grid scale, providing more specific spatial guidance for ER implementation and adaptation in China's drylands.

How to cite: Fu, F., Wang, S., and Wu, X.: Locating unsustainable water supplies for supporting ecological restoration in China's drylands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7611, https://doi.org/10.5194/egusphere-egu24-7611, 2024.

EGU24-8825 | ECS | Orals | HS2.1.5

Assessing stream water scarcity and groundwater roles under global change in a Mediterranean watershed: the Onyar River basin (NE Catalonia, Spain) 

Paula Gabriela Cordoba Ariza, Ramon J. Batalla, Sergi Sabater, and Josep Mas-Pla

Mediterranean basins face significant water scarcity which requires examining long-term data to evaluate their trends in water availability and quality and assess management options. In this presentation, we explore the historical streamflow changes, the influencing climatic —streamflow, precipitation, temperature, and evapotranspiration (PET and AET)— and land-use factors, and the evolution of surface water quality in the Onyar River (Inner Catalan basins, NE Spain; 295 km2) during the last decades (1960-2020).

Results highlight a consistent decline in streamflow, most pronounced over the last two decades, accompanied by an increase in PET, and a probable decrease in groundwater recharge. These changes co-occurred with higher concentrations of river water ammonium and nitrate. We attribute these patterns to changes in land use such as afforestation and intensive fertilization, as well as increased groundwater withdrawal, particularly during irrigation seasons. Additional factors include growing urban water demand and the discharges of treated wastewater back into the river system. Evaluation of the relationship between groundwater and surface water using end-member mixing analysis of hydrochemical data points out an interesting scale-dependence behaviour: groundwater baseflow from alluvial formations was relevant in the smallest subbasins, whereas regional groundwater flow involving deeper aquifers could significantly contribute to stream discharge in the lowest zones of the basin. Since water balance alteration in the future climate scenarios will reduce the contribution of the headwater flow as well as groundwater storage and baseflow generation, reclaimed wastewater shows up as a relevant source to maintain stream runoff, yet its quality is low and might not be properly diluted by rainfall originated runoff.

These observations provide a comprehensive overview of the declining water quantity and quality in the Onyar River network, attributing these trends to an interplay of climatic and anthropogenic factors. They urge for integrated water resources management strategies to mitigate the implications of these environmental changes, such as protecting baseflow generating areas as well as controlling reclaimed wastewater quality.

Funding: G. Córdoba-Ariza acknowledges funding from Secretariat of Universities and Research from Generalitat de Catalunya and European Social Fund for her FI fellowship (2022 FI_B1 00105). 

How to cite: Cordoba Ariza, P. G., Batalla, R. J., Sabater, S., and Mas-Pla, J.: Assessing stream water scarcity and groundwater roles under global change in a Mediterranean watershed: the Onyar River basin (NE Catalonia, Spain), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8825, https://doi.org/10.5194/egusphere-egu24-8825, 2024.

Intermittent rivers and ephemeral streams represent half of the global river network and span all climates. The intermittent rivers and ephemeral streams is a short-hand term for all flowing water that ceases to flow or that dries up completely at some point in time and/or space They are more frequent in arid and semi-arid areas but are also present in temperate, tropical humid, boreal, and alpine areas, where they are mainly located in headwaters. Their abundance is increasing due to climate change and water withdrawals for human activities.

The objective of this study is to represent the spatio-temporal dynamics of flow intermittence at the reach level in river of the seven sub-catchments of the Maures massif (between 1.5 km² and 70 km²).

First, two hydrological continuous models of varying complexities are performed: GR6J (lumped and conceptual), and SMASH (spatially distributed and conceptual) in terms of temporal calibration/validation, by dissociating dry and wet years, to asses the models’ability to simulate observed drying event over time. The metrics are based on daily flow records observed in the 7 catchments since 1968 to 2023.

In the second part, a regionalization method is tested on the spatially distributed model (SMASH). The HDA-PR approach (Hybrid Data Assimilation and Parameter Regionalization) incorporating learnable regionalization mappings, based on multivariate regressions is used. This approach consist to search for a transfer function that quantitatively relates physical descriptors to conceptual model parameters from multi-gauge discharge in order to produce a regional model.

Flow condition observed from multiple data sources (daily flow time series from gauging stations, phototrap installed along the river network taking daily pictures from 2021-04-01 to 2023-31-12, daily conductivity measurements series from 2021-01-01) are used to validate the ability of the regional model to simulate flow intermittence (prediction of dry events) at river section level.

The distributed modelling approach, with a high-resolution conceptual hydrological modeling at 0.250 km² and coupled with Hybrid Data Assimilation and Parameter Regionalization descriptors shows results highlight the effectiveness of HDA-PR surpassing the performance of a uniform regionalization method with lumped model parameters. However, the results on smallest catchments area are lowest.

The study shows the interest of using daily photos which are a good indication of the hydrogical state of the streams to obtain intermittence data and increasing the spatial coverage of observations in order to validate regional model.

How to cite: Folton, N., De Fournas, T., Colléoni, F., and Tolsa, M.: Modelling the intermittence of watercourses in the small French Mediterranean catchments of the Maures massif (Réal Collobrier ) with the SMASH platform (Spatially distributed Modelling and ASsimilation for Hydrology) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9681, https://doi.org/10.5194/egusphere-egu24-9681, 2024.

EGU24-9899 | Orals | HS2.1.5

60,000 years of hydrologic connectivity on the Australian dryland margins: the case of the Willandra Lakes World Heritage Area 

Kathryn Fitzsimmons, Markus Fischer, Colin Murray-Wallace, Edward Rhodes, Tobias Lauer, Maike Nowatzki, Kanchan Mishra, and Nicola Stern

Australia is big, flat, old and arid: it is the driest inhabited continent on Earth. The catastrophic flooding of recent years has demonstrated not only the potential for extreme conditions at both ends of the hydroclimatic scale, but also how little we understand of the interplay between climatic, hydrological, and surface-process mechanisms affecting this part of the world. We know still less about long-term hydrological dynamics, particularly for the dry inland where water resources are scarce and land surfaces are susceptible to erosion, requiring careful management.

Records of past hydrological variability can help inform us about changing hydroclimate states and their impact on the land surface. The Willandra lakes system, located on the desert margins of southeastern Australia, is one of the few dryland areas which preserves long-term sedimentary records of hydrologic change. The headwaters of these lakes lie in the temperate highlands hundreds of kilometres to the east; as a result, lake filling and drying reflects the interaction between rainfall in the watershed and hydrologic connectivity across the catchment and between the lakes. Environmental change in the Willandra is recorded in the sediments of the lake shoreline dunes, preserved as semi-continuous deposition of different lake facies over 60,000 years.

Here we investigate long-term hydrologic connectivity across the Willandra lakes and their catchment. Our approach uses a novel integration of lake-level reconstruction based on lunette sedimentology, stratigraphy and luminescence geochronology, with hydrologic and palaeoclimatic modelling of key event time slices over the last 60 ky. We characterize the land-surface response to various hydroclimate states, so improving our understanding of dryland atmosphere-hydrosphere interactions.

How to cite: Fitzsimmons, K., Fischer, M., Murray-Wallace, C., Rhodes, E., Lauer, T., Nowatzki, M., Mishra, K., and Stern, N.: 60,000 years of hydrologic connectivity on the Australian dryland margins: the case of the Willandra Lakes World Heritage Area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9899, https://doi.org/10.5194/egusphere-egu24-9899, 2024.

EGU24-10078 | ECS | Orals | HS2.1.5 | Highlight

Wheat irrigation in Marrakech conditions: A Simulation Study using SALTMED 

El Houcine El Moussaoui, Aicha Moumni, Said Khabba, and Abderrahman Lahrouni

In Morocco, agriculture accounts for 80-90% of water resources. Available data show that the performance of current irrigation systems remains low to medium, with water losses at plots ranging from 30 to 40%, divided between percolation and evaporation. Gravity irrigation is almost total in the study area, resulting in significant percolation losses. In principle, this percolation contributes mainly to the recharge of the aquifer.

The purpose of this study was to evaluate, by simulation, the impact of irrigation techniques on wheat yield and growth using the generic agro-environmental model SALTMED under the climatic and soil conditions of zone R3, which is an irrigation area located in the region of Sidi Rahal about 40 km east of the city of Marrakech in the plain of Haouz. We started the study by calibrating the model based on two parameters: photosynthetic efficiency and harvest index. After calibration, we compared different irrigation techniques implemented in the model (surface irrigation, sprinkler irrigation, and drip irrigation). Simulation results showed that the drip irrigation technique is the most economical, exhibiting the lowest losses attributed to percolation and soil evaporation. Notably, percolation, a significant contributor to groundwater recharge, measured approximately 255.5 mm/season. In addition, the irrigation practice in the study area appears to be overestimated during the observed season and could be reduced by half, according to SALTMED. When the irrigation dose is halved, the simulated yield (grain and total biomass) decreases by only 1.33%.

How to cite: El Moussaoui, E. H., Moumni, A., Khabba, S., and Lahrouni, A.: Wheat irrigation in Marrakech conditions: A Simulation Study using SALTMED, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10078, https://doi.org/10.5194/egusphere-egu24-10078, 2024.

EGU24-10387 | ECS | Orals | HS2.1.5

Nitrogen modeling and performance of Multi-Soil-Layering (MSL)bioreactor treating domestic wastewater in rural community 

Sofyan Sbahi, Naaila Ouazzani, Abdessamed Hejjaj, Abderrahman Lahrouni, and Laila Mandi

The multi-soil-layering (MSL) bioreactor has been considered in the latest research as an
innovative bioreactor for reducing the level of pollutants in wastewater. The efficiency of the
MSL bioreactor towards nitrogen pollution is due to the mineralization of organic nitrogen in
aerobic layers to ammonia, and reactivity of ammonia nitrogen with soil and gravel by its
adsorption into soil layers followed by nitrification and denitrification processes when the
alternating phases of oxygenated/anoxic conditions occurs in the filter. In this study, we have
examined the performance of the MSL bioreactor at different hydraulic loading rates (HLRs)
and predicted the removal rate of nitrogen. To improve the prediction accuracy of the models,
the feature selection technique was performed before conducting the Neural Network model.
The results showed a significant removal (p <0.05) efficiency for five-day biochemical
oxygen demand (BOD 5,  86%), ammonium (NH 4 + , 83%), nitrates (NO 3 − , 81%), total kjeldahl
nitrogen (TKN, 84%), total nitrogen (TN, 84%), orthophosphates (PO 4 3− , 91%), and total
coliforms (TC, 1.62 Log units). However, no significant change was observed in the nitrite
(NO 2 − ) concentration as it is an intermediate nitrogen form. The MSL treatment efficiency
demonstrated a good capacity even when HLR increased from 250 to 4000 L/m 2 /day,
respectively (e.g., between 64% and 86% for BOD 5 ). The HLR was selected as the most
significant (p < 0.05) input variable that contribute to predict the removal rates of nitrogen.
The developed models predict accurately the output variables (R 2  > 0.93) and could help to
investigate the MSL behavior.

How to cite: Sbahi, S., Ouazzani, N., Hejjaj, A., Lahrouni, A., and Mandi, L.: Nitrogen modeling and performance of Multi-Soil-Layering (MSL)bioreactor treating domestic wastewater in rural community, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10387, https://doi.org/10.5194/egusphere-egu24-10387, 2024.

EGU24-11799 | ECS | Orals | HS2.1.5 | Highlight

Exploring the mechanisms controlling dryland hydroclimate in past 'warmer worlds' 

Monika Markowska, Hubert B. Vonhof, Huw S. Groucutt, Michael D. Petraglia, Denis Scholz, Michael Weber, Axel Gerdes, Richard Albert, Julian Schroeder, Yves S. Krüger, Anna Nele Meckler, Jens Fiebig, Matthew Stewart, Nicole Boivin, Samuel L. Nicholson, Paul S. Breeze, Nicholas Drake, Julia C. Tindall, Alan M. Haywood, and Gerald Haug

Drylands cover almost half of Earth’s land surfaces, supporting ~30% of the world’s population. The International Panel on Climate Change predicts increasing aridification and expansion of drylands over the course of this century. As we approach new climate states without societal precedent, Earth’s geological past may offer the best tool to understand hydroclimate change under previously, allowing us to elucidate responses to external forcing. Paleo-records from previously warm and high-CO2 periods in Earth’s past, such as the mid-Pliocene (~3 Ma), point towards higher humidity in many dryland regions. 

Here, we examine desert speleothems from the hyper-arid desert in central Arabia, part of the largest near-continuous chain of drylands in the world, stretching from north-western Africa to the northern China, to elucidate substantial and recurrent humid phases over the past 8 million years. Independent quantitative paleo-thermometers suggest that mean annual air temperatures in central Arabia were approximately between 1 to 5 °C warmer than today. The analyses of the isotopic composition (δ18O and δ2H) of speleothem fluid inclusion waters, representing ‘fossil rainwater’, reveal an aridification trend in Arabia from the Late Miocene to Late Pleistocene during Earth’s transition from a largely ‘ice-free’ northern hemisphere to an ‘ice-age’ world. Together, our data provide evidence for recurrent discrete wetter intervals during past warmer periods, such as the Pliocene. Data-model comparisons allow us to assess the agreement between our paleoclimate data and climate model output using the HadCM3 isotope-enabled model simulations during past ‘warmer worlds’ – namely the mid-Piacenzian warm period (3.264 to 3.025 Ma). To assess the hydroclimate response to external forcing, we examine model output from a series of sensitivity experiments with different orbital configurations allowing us to postulate the mechanisms responsible for the occurrence of humid episodes in the Arabian desert, with potential implications for other dryland regions at similar latitudes. Together, our approach unveils the long-term controls on Arabian hydroclimate and may provide crucial insights into the future variability.

How to cite: Markowska, M., Vonhof, H. B., Groucutt, H. S., Petraglia, M. D., Scholz, D., Weber, M., Gerdes, A., Albert, R., Schroeder, J., Krüger, Y. S., Meckler, A. N., Fiebig, J., Stewart, M., Boivin, N., Nicholson, S. L., Breeze, P. S., Drake, N., Tindall, J. C., Haywood, A. M., and Haug, G.: Exploring the mechanisms controlling dryland hydroclimate in past 'warmer worlds', EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11799, https://doi.org/10.5194/egusphere-egu24-11799, 2024.

EGU24-12194 | ECS | Orals | HS2.1.5

High resolution surface soil moisture microwave products: intercomparison and evaluation over Spain 

Nadia Ouaadi, Lionel Jarlan, Michel Le Page, Mehrez Zribi, Giovani Paolini, Bouchra Ait Hssaine, Maria Jose Escorihuela, Pascal Fanise, Olivier Merlin, Nicolas Baghdadi, and Aaron Boone

Surface soil moisture (SSM) products at high spatial resolution are increasingly available, either from the disaggregation of coarse-resolution products such as SMAP and SMOS, or from high-resolution radar data such as Sentinel-1. In contrast to coarse resolution products, there is a lack of intercomparison studies of high spatial resolution products, which are more relevant for applications requiring the plot scale. In this context, the objective of this work is the evaluation and intercomparison of three high spatial resolution SSM products on a large database of in situ SSM measurements collected on two different sites in the Urgell region (Catalonia, Spain) in 2021. The satellite SSM products are: i) SSMTheia product at the plot scale derived from a synergy of Sentinel-1 and Sentinel-2 using a machine learning algorithm; ii) SSMρ product at 14 m resolution derived from the Sentinel-1 backscattering coefficient and interferometric coherence using a brute-force algorithm; and iii) SSMSMAP20m product at 20 m resolution obtained from the disaggregation of SMAP using Sentinel-3 and Sentinel-2 data. Evaluation of the three products over the entire database showed that SSMTheia and SSMρ yielded a better estimate than SSMSMAP20m, and SSMρ is slightly better than SSMTheia. In particular, the correlation coefficient is higher than 0.4 for 72%, 40% and 27% of the fields using SSMρ, SSMTheia and SSMSMAP20m, respectively. The lower performance of SSMTheia compared to SSMρ is due to the saturation of SSMTheia at 0.3 m3/m3. The time series analysis shows that SSMSMAP20m is able to detect rainfall events occurring at large scale while irrigation at the plot scale are not caught. This is explained by the use of Sentinel-2 reflectances, which are not linked to surface water status, for the disaggregation of Sentinel-3 land surface temperature. The approach can therefore be improved by using high spatial and temporal resolution thermal data in the perspective of new missions such as TRISHNA and LSTM. Finally, the results show that although reasonable estimates are obtained for annual crops using SSMTheia and SSMρ, poor performance is observed for trees, suggesting the need for better representation of canopy components for tree crops in SSM inversion approaches.

How to cite: Ouaadi, N., Jarlan, L., Le Page, M., Zribi, M., Paolini, G., Ait Hssaine, B., Escorihuela, M. J., Fanise, P., Merlin, O., Baghdadi, N., and Boone, A.: High resolution surface soil moisture microwave products: intercomparison and evaluation over Spain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12194, https://doi.org/10.5194/egusphere-egu24-12194, 2024.

    The Yellow River (YR) is 5464 km long and the cradle of Chinese civilization. It is also well known for being the most sediment-laden river and having the largest vertical drop over its course. Although the YR accounts for only 3% of China’s water resources, it irrigates 13% of its cropland. Exceptional historical documents have recorded frequent occurrence of YR flooding events that resulted in huge losses of lives and property.
    The earliest observational record of YR runoff, beginning in 1919 at the Shanxian gauge station, is too short to study centennial-scale variability. Since the start of the Anthropocene in the 1960s, frequent human activities have resulted in large deviation between observed streamflow. The reconstruction of annual historical natural runoff of the YR is necessary to quantify the amount of anthropogenic YR water consumption in recent decades. Tree rings, with the merits of accurate dating and annual resolution, have been widely used in runoff reconstruction worldwide. In this study, 31 moisture-sensitive tree-ring width chronologies, including 860 trees and 1707 cores, collected within the upper-middle YR basins were used to reconstruct natural runoff for the middle YR course over the period 1492–2013 CE.
    The reconstruction provides a record of natural YR runoff variability prior to large-scale human interference. Most of the extreme high/low runoff events in the reconstruction can be verified with historical documents. The lowest YR flow since 1492 CE occurred during 1926–1932 CE and the YR runoff in 1781 is the highest. These two extreme values could be regarded as a benchmark for future judicious planning of water allocation. Since the late 1980s, observed YR runoff has fallen out of its natural range of variability, and there was even no water flow for several months each year in the lower YR course during 1995 to 1998. Especially concerning was that the inherent 11-year and 24-year cycles of YR became disordered following the severe drought event in late 1920s, and eventually disappeared after the 1960s.
    Year-to-year variability in YR water consumption by human activities (WCHA) was quantified, which showed good association between crop yields and acreage in Ningxia and Inner Mongolia irrigation regions. Meanwhile, WCHA was strongly negatively correlated with sediment load at Toudaoguai and Shanxian stations, which led to a 58% reduction of sediment load in Toudaoguai (upper reach) and 29% in Shanxian (middle reach). 
    If human activities continue to intensify, future YR runoff will be further reduced, and this will negatively impact agriculture, human lives, and socioeconomic development in the middle and lower basins of the YR. To reduce the risk of recurring cutoff of streamflow in the YR lower basin, water should be allocated judiciously. Our reconstructed YR natural runoff series are important for future YR water resource management. In addition, our results also provide an important model of how to distinguish and quantify anthropogenic influence from natural variability in global change studies.

How to cite: Liu, Y.: Changes and attribution of natural runoff in the Yellow River over the past 500 years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13979, https://doi.org/10.5194/egusphere-egu24-13979, 2024.

EGU24-14057 | ECS | Posters on site | HS2.1.5

Turbulent fluxes at kilometer scale determined by optical-microwave scintillometry in a heterogeneous oasis cropland of the Heihe River Basin 

Feinan Xu, Weizhen Wang, Chunlin Huang, Jiaojiao Feng, and Jiemin Wang

Observations of kilometer-scale turbulent fluxes of sensible (H) and latent heat (LE) are required for the validation of flux estimate algorithms from satellite remote-sensing data and the development of parameterization schemes in the hydro-meteorological models. Since 2019, two sets of Optical and Microwave scintillometer (OMS) systems have been operated in the Heihe River Basin of northwestern China, one on an alpine grassland of upper reaches, another on an oasis cropland of middle reaches, to measure both the areal H and LE. Combined with the observations of eddy-covariance (EC) and meteorological tower systems in both sites, an improved procedure for OMS data processing is proposed. The newly proposed procedure especially improves the preprocessing of raw scintillation data, properly uses the current probably better Lüdi et al. (2005) method in deriving meteorological structure parameters, and chooses the coefficients of similarity functions by Kooijmans and Hartogensis (2016) in calculating fluxes. Evaluated with the results of rather homogeneous grassland, the area-averaged H and LE over the heterogeneous oasis are then determined. Estimates of H and LE agree reasonably well with those obtained from EC in most cases. However, the most interesting is that LE over the oasis during the early crop growing stages is clearly larger than that of EC; while both agree well during the longer crop grown periods. Footprint analysis shows that, compared with EC, the OMS has clearly larger source area that contains a slight area of orchard and shelterbelts distributed near the light path, leading to larger LE during the early stages of crop growth. The area-averaged evapotranspiration (ET) over the oasis is then analyzed more acceptably, which varies from 3 to 5 mm day-1 depending on meteorological conditions during the 39 days of the crop growing period. These results are used to validate the Penman-Menteith-Leuning Version 2 (PML-V2) scheme.

How to cite: Xu, F., Wang, W., Huang, C., Feng, J., and Wang, J.: Turbulent fluxes at kilometer scale determined by optical-microwave scintillometry in a heterogeneous oasis cropland of the Heihe River Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14057, https://doi.org/10.5194/egusphere-egu24-14057, 2024.

    Recurrent droughts in history, especially climatic aridity since the mid-20th century have aroused great social anxiety about the water resources in the Chinese Loess Plateau (CLP). Given lacking of extended instrumental-like records, new precipitation reconstructions in the CLP are badly needed for objectively evaluating the current precipitation situation, understanding the spatial-temporal differences, and serving for predicting the future. Here we present a tree-ring-based 248-year regional precipitation reconstruction (P8–7) in the Heichashan Mountain, which can significantly represent the past dry-wet variations in the eastern CLP (ECLP). P8–7 explains 48.72% of the instrumental record, reveals a wetting trend since the early 2000s and attains the second wettest period over the past 248 years in 2014–2020 AD. The 1920s/2010s is recorded as the driest/wettest decade. 1910–1932 AD ranks as the driest period over the past centuries. The 19th century is comparatively wet while the 20th century is dry. Precipitation in the ECLP and western CLP (WCLP) has changed synchronously over most time of the past two centuries. However, regional difference exists in the 1890s–1920s when a gradually drying occurred in the ECLP, while not evident in the WCLP, although the 1920s megadrought occurred in the CLP. Moreover, the 20th-century drying in the ECLP begins in the 1950s, later than the WCLP. It reveals that P8–7 variability is primarily influenced by the Asian Summer Monsoon and related large-scale circulations. The seismic phase shift of the contemporaneous Northern Hemispheric temperature may also be responsible for the 1920s megadrought.

How to cite: Cai, Q. and Liu, Y.: Hydroclimatic characteristics on the Chinese Loess Plateau over the past 250 years inferred from tree rings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14189, https://doi.org/10.5194/egusphere-egu24-14189, 2024.

EGU24-16291 | ECS | Orals | HS2.1.5

A New Perspective on Agricultural Drought Periods: A Mediterranean Semi-Arid Context 

Kaoutar Oukaddour, Michel Le Page, and Younes Fakir

Extreme weather events have an increasing repercussions on ecosystems in recent years. By comprehending how vegetation responds to climatic extremes, their effects may be mitigated. In a semi-arid Mediterranean region, this study examines the temporal connections of the main triggers of agricultural drought, low precipitation, vegetation growth, thermal stress, and soil water deficit. Drought periods and their characteristics were determined using a revised run theory approach. The Pearson correlations across various spatial scales revealed a moderate to low degree of concordance among the drought indices. This discrepancy can be attributed to the geographical heterogeneity and climatic variations observed among the agrosystems within the basin.

The cross-correlation analysis demonstrated the cascading impacts resulting from reduced precipitation. During drought events, the significant connection between precipitation deficits and vegetation persists for at least one month across most index pairs. This suggests that agricultural drought occurrences can be temporally linked through the selected drought indices. The study unveiled short-, mid-, and long-term effects of precipitation deficiencies on soil moisture, vegetation, and temperature. As anticipated, variables like soil moisture and surface temperature, being more instantaneous, exhibited no lag in response to precipitation. Notably, vegetation anomalies at the monthly time step displayed a two-month lag, indicating a preceding impact of vegetation on precipitation.

Employing the run theory to identify drought events and stages with different thresholds revealed substantial variability in drought characteristics namely the duration, the magnitude magnitude, and the intensity. This variability was notably influenced by the selection of both normality and drought thresholds.

How to cite: Oukaddour, K., Le Page, M., and Fakir, Y.: A New Perspective on Agricultural Drought Periods: A Mediterranean Semi-Arid Context, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16291, https://doi.org/10.5194/egusphere-egu24-16291, 2024.

EGU24-17049 | ECS | Orals | HS2.1.5

Potential of the Photochemical Reflectance Index in Understanding Photoinhibition and Improving Irrigation Water Efficiency in the Mediterranean Zone 

Zoubair Rafi, Saïd Khabba, Valérie Le Dantec, Patrick Mordelet, Salah Er-Raki, Abdelghani Chehbouni, and Olivier Merlin

Morocco's semi-arid region faces challenges due to limited water resources, necessitating efficient irrigation practices for sustainable agriculture. Precision agriculture, coupled with advanced technologies like the Photochemical Reflectance Index (PRI), holds great potential for optimizing irrigation water usage and enhancing crop productivity in this environment. This abstract provides a comprehensive overview of integrating precision agriculture techniques, PRI, and Net Radiation (Rn) to improve irrigation water efficiency and maximize crop productivity in Morocco's semi-arid zone. The study presents and analyzes an experimental investigation of the PRI signal in a winter wheat field throughout an agricultural season to comprehend its dependence on agro-environmental parameters such as global radiation (Rg) and Rn. Rn directly impacts the energy absorbed by plants, a crucial factor for photosynthesis. Elevated Rn levels generally increase energy availability for photosynthetic processes, resulting in higher chlorophyll fluorescence and PRI values. However, excessive Rn can lead to photoinhibition, damaging the photosynthetic apparatus and reducing photosynthetic efficiency. Understanding the interplay between net radiation, PRI, and photoinhibition is crucial for optimizing agricultural practices. Monitoring and managing net radiation levels allow farmers to ensure that the energy available for photosynthesis remains within the optimal range, minimizing the risk of photoinhibition while maximizing crop productivity. Additionally, the daily water stress index based on PRI (PRIj), developed independently of structural effects related to leaf area index (LAI), showed a coefficient of determination (R2) of 0.74 between PRIj and Rn. This reflects the extent of excessive light stress experienced by the wheat field throughout the experiment. In conclusion, the integration of precision agriculture techniques, specifically PRI, offers a promising approach to enhance irrigation water efficiency in Morocco's semi-arid zone. By employing this innovative tool, farmers can optimize water usage, reduce environmental impacts, and ensure the long-term sustainability of agriculture.

How to cite: Rafi, Z., Khabba, S., Le Dantec, V., Mordelet, P., Er-Raki, S., Chehbouni, A., and Merlin, O.: Potential of the Photochemical Reflectance Index in Understanding Photoinhibition and Improving Irrigation Water Efficiency in the Mediterranean Zone, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17049, https://doi.org/10.5194/egusphere-egu24-17049, 2024.

EGU24-17321 | ECS | Orals | HS2.1.5

Quantifying Olive Tree Evapotranspiration in Semi-Arid Regions through Remote Sensing-Based SEBAL Model: Validation with Optical-Microwave Scintillometer 

Hamza Barguache, Jamal Ezzahar, Mohamed Hakim Kharrou, Said Khabba, Jamal Elfarkh, Abderrahim Laalyej, Salah Er-Raki, and Abdelghani Chehbouni

Accurately assessing sensible (H) and latent (LE) heat fluxes, along with evapotranspiration, is crucial for comprehending the energy balance at the biosphere-atmosphere interface and enhancing agricultural water management. Although the eddy covariance (EC) method is commonly employed for these measurements, it has limitations in providing spatial representativeness beyond a few hundred meters. Addressing this challenge, optical-microwave scintillometers (OMS) have emerged as a valuable tool, directly measuring kilometer-scale H and LE fluxes. These measurements serve to validate satellite remote sensing products and model simulations, such as the Surface Energy Balance Algorithm for Land (SEBAL). In this study, OMS measurements were utilized to assess the fluxes simulated by the SEBAL model at the Agdal olive orchard near Marrakech city. The results revealed that SEBAL's estimated sensible heat fluxes were 3% higher than those measured by OMS, while latent heat fluxes were approximately 15% lower. Based on these findings, we infer that OMS can effectively validate satellite-driven surface energy balance models, thereby supporting agricultural water management.

How to cite: Barguache, H., Ezzahar, J., Kharrou, M. H., Khabba, S., Elfarkh, J., Laalyej, A., Er-Raki, S., and Chehbouni, A.: Quantifying Olive Tree Evapotranspiration in Semi-Arid Regions through Remote Sensing-Based SEBAL Model: Validation with Optical-Microwave Scintillometer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17321, https://doi.org/10.5194/egusphere-egu24-17321, 2024.

EGU24-17560 | ECS | Posters virtual | HS2.1.5

Estimation of Irrigation Water Demand in the Southern Mediterranean Region through Explicit Integration of Irrigation Processes in a Land Surface Model: A Case Study of the Tensift Catchment (Morocco). 

Ahmed Moucha, Lionel Jarlan, Pére Quintana-Segui, Anais Barella-Ortiz, Michel Le Page, Simon Munier, Adnane Chakir, Aaron Boone, Fathallah Sghrer, Jean-christophe Calvet, and Lahoucine Hanich

The utilization of water by various socio-economic sectors has made this resource highly sought after, especially in arid to semi-arid zones where water is already scarce and limited. In this context, effective management of this resource proves to be crucial. Our study aims to: evaluate the performance of the new irrigation module in ISBA, quantify the water balance, and assess the impact of climate change and anthropogenic factors on this resource by the horizon of 2041-2060, utilizing high-resolution futuristic forcings from the study (Moucha et al., 2021). To assess the ISBA model with its new irrigation module, we initially compared observed and predicted fluxes with and without activation of the irrigation module. Subsequently, we compared irrigation water inputs at the ORMVAH-defined irrigated perimeters within the Tensift basin. The results of this evaluation showed that the predictions of latent heat flux (LE) considering all available stations in the basin shifted from -60 W/m² for the model without irrigation to -15 W/m². This indicates that the integration of the new irrigation system into ISBA significantly improves the predictions of latent heat flux (LE) over the period 2004-2014 compared to the regular model. Considering the irrigated perimeters, the study results demonstrated that the model with the integration of the irrigation module was capable of replicating the overall magnitude and seasonality of water quantities provided by ORMVAH despite a positive bias. Exploration of the water balance at the Tensift basin level revealed the ISBA model's ability, equipped with its irrigation module, to describe complex relationships among precipitation, irrigation, evapotranspiration, and drainage. Finally, the assessment of the impact of climate change and vegetation cover for the period 2041-2060, utilizing high-resolution SAFRAN forcings projected to the same horizon (Moucha et al., 2021), revealed an increase in irrigation water needs. These results are of paramount importance in the context of sustainable water resource management in arid and semi-arid regions.

How to cite: Moucha, A., Jarlan, L., Quintana-Segui, P., Barella-Ortiz, A., Le Page, M., Munier, S., Chakir, A., Boone, A., Sghrer, F., Calvet, J., and Hanich, L.: Estimation of Irrigation Water Demand in the Southern Mediterranean Region through Explicit Integration of Irrigation Processes in a Land Surface Model: A Case Study of the Tensift Catchment (Morocco)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17560, https://doi.org/10.5194/egusphere-egu24-17560, 2024.

EGU24-17649 | ECS | Orals | HS2.1.5

Comprehensive Analysis of Hydrological Dynamics and Uncertainties in the Moroccan High Atlas: A Focus on Seasonal Precipitation, Runoff, and Flood Events 

Myriam Benkirane, Abdelhakim Amazirh, El Houssaine Bouras, Adnane Chakir, and Said Khabba

The Mediterranean regions, particularly the Moroccan High Atlas, is exposed to natural risks associated with the hydrological cycle, notably intense precipitation events that trigger sudden floods. This research delves into the subtleties of hydrological dynamics in the High Atlas watersheds, specifically in the Zat watershed, to comprehend the seasonality of precipitation and runoff and elucidate the origins of floods.

The results reveal a strong correlation between observed and simulated hydrographs, affirming the model's capability to capture complex hydrological processes. Evaluation metrics, particularly the Nash coefficient, demonstrate a robust model performance during the calibration phase, ranging from 61.9% to 90%. This attests to the model's ability to reproduce the dynamic nature of hydrological systems in the Moroccan High Atlas.

It is noteworthy that the study identifies the snowmelt process as a significant factor of uncertainty in runoff flooding parameters. The complexities associated with snowmelt, especially in the context of spring precipitation, emerge as a crucial factor influencing uncertainties in the simulated results. This finding underscores the importance of accurately representing snowmelt dynamics in hydrological simulations for regions prone to natural risks.

Moreover, the integration of Probability Distribution Functions and Monte Carlo simulations, coupled with rigorous evaluation metrics, enhances our understanding of calibration parameter uncertainties and validates the model's performance. The identified influence of snowmelt on runoff flooding parameters provides crucial insights for future model improvements and the development of effective mitigation strategies in regions vulnerable to natural risks. This research contributes to advancing hydrological modeling practices in complex terrain.

 

Keywords: Seasonality, Rainfall-Runoff, Floods, Calibration, Monte Carlo simulation, Parameter Uncertainty, Hydrological Modeling, Snowmelt Dynamics, Natural Risks.

How to cite: Benkirane, M., Amazirh, A., Bouras, E. H., Chakir, A., and Khabba, S.: Comprehensive Analysis of Hydrological Dynamics and Uncertainties in the Moroccan High Atlas: A Focus on Seasonal Precipitation, Runoff, and Flood Events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17649, https://doi.org/10.5194/egusphere-egu24-17649, 2024.

The Mediterranean area is recognized as a hotspot for climate change challenges, with noticeable patterns of rising temperatures and dryness. Olive agroecosystems are particularly affected by the increasing aridity and global climatic changes. Despite being a symbol of the Mediterranean and traditionally grown using rainfed agricultural practices, olive growers have to adapt to cope with higher temperatures, drought, and more frequent severe weather incidents, necessitating their attention and adaptation (Fraga et al., 2020). Moreover, crop production in Morocco heavily relies on irrigation because rainfed cropping has limited productivity (Taheripour et al., 2020). The olive sector is of great importance in Morocco, and there is an urgent need to implement sustainable water management practices. This includes water-saving strategies such as regulated and sustained deficit irrigation (RDI and SDI) to sustain olive production and strengthen the sector's resilience to climate change and water scarcity. These strategies primarily differ in terms of their irrigation timing and the quantity of water applied (Ibba et al., 2023). This study aims to evaluate the effect of two deficit irrigation strategies on productive parameters of the Menara olive cultivar, to serve as a tool for operational irrigation water management and appraise the adaptive responses of this cultivar under conditions of induced drought stress. In pursuit of this aim, an experiment was carried out in an olive orchard over two consecutive years (2021 and 2022), comparing four treatments of regulated deficit irrigation (RDI): T1 (SP 100- NP 70% ETc), T2 (SP 100- NP 60% ETc), T3 (SP 80- NP 70% ETc), T4 (SP 80- NP 60% ETc) and two treatments of sustained deficit irrigation (SDI): T5 (70% ETc) and T6 (60% ETc), with fully irrigated trees T0 (100% ETc). The findings showed that controlled water stress, as applied through regulated deficit irrigation (RDI), did not exert a severe impact on the flowering traits and yield of the Menara olive cultivar. Notably, the RDI strategy, particularly under T4 treatment, allowed for the reduction of supplied water by 20% in sensitive periods (SP) flowering and from the beginning of oil synthesis to harvest and by 40% in the normal period (NP)during pit hardening, respectively, without compromising fruit yield. However, the SDI strategy, characterized by restricted water availability, which reduced total water application under T5 and T6 treatments by 30% and 40% throughout the entire season, led to a decline in the fruit yield by about 50% and resulted in the most significant drop in water productivity, ranging from 19% to 33% compared to the control T0. Furthermore, the findings underscored the adaptability of responses to water stress and elucidated the consequential impact of each irrigation strategy on the performance of Menara olive trees across successive years, particularly the importance of regulated deficit irrigation as a water management strategy and the need to consider its implication on flowering traits and crop yield over successive growing seasons to establish the enduring adaptability of this locally cultivated olive cultivar.

How to cite: Ibba, K., Er-Raki, S., Bouizgaren, A., and Hadria, R.: Sustainable Water Management for Menara Olive Cultivar: Unveiling the Potential of Regulated and Sustained Deficit Irrigation Strategies in Morocco, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17808, https://doi.org/10.5194/egusphere-egu24-17808, 2024.

EGU24-17983 | ECS | Orals | HS2.1.5

Comparison of C-band radar and infrared thermal data for monitoring corn field in semi-arid area. 

Abdelhafid Elallaoui, Pierre-Louis Frison, Saïd Khabba, and Lionel Jarlan

In semi-arid Mediterranean regions, the scarcity and limitations of water resources pose major challenges. These invaluable resources are threatened by various factors such as climate change, population growth, urban expansion, and agricultural intensification. Specifically, agriculture, which consumes approximately 85% of the water in the semi-arid zone of the South Mediterranean region, directly contributes to the depletion of groundwater. To promote rational irrigation management, it becomes imperative to monitor the water status of crops. Remote sensing is a valuable technique allowing for monitoring crop fields in different parts of the electromagnetic spectrum giving complementary information about crop parameters. The main objective of this study is to assess the potential of radar and Infrared Thermal data for monitoring the water status of crops in semi-arid regions. In this context, a radar system was installed in Morocco, in the Chichaoua region, consisting of 6 C-band antennas mounted on a 20-meter tower. These antennas are directed towards a maize field. This system allowed for radar data acquisition in three different polarizations (VV, VH, HH) with a 15-minute time-step over the time period extending from September to December 2021. Additionally, the system is complemented by continuous acquisitions from a Thermal Infrared Radiometer (IRT) at 30-minute intervals. These data are further supplemented by in-situ measurements characterizing crop parameters (state of the cover, soil moisture, evapotranspiration and meteorological variables). The study initially focused on analyzing the diurnal cycle of radar temporal coherence. The results indicated that coherence was highly sensitive to wind-induced movements of scatterers, with minimal coherence when wind speed was highest in the late afternoon. Moreover, coherence was also responsive to vegetation activity, particularly its water content, as the morning coherence drop coincided with the onset of plant activity. Subsequently, the study examined the potential of the relative difference between surface vegetation temperature and air temperature to monitor the water status of crops. The results showed that during a period of imposed water stress, the amplitude of this difference increased. These results open perspectives for monitoring the water status of crops using radar and thermal observations with a high revisit frequency.

How to cite: Elallaoui, A., Frison, P.-L., Khabba, S., and Jarlan, L.: Comparison of C-band radar and infrared thermal data for monitoring corn field in semi-arid area., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17983, https://doi.org/10.5194/egusphere-egu24-17983, 2024.

EGU24-18201 | ECS | Orals | HS2.1.5

Analyzing Tree Degradation in the Haouz Plain through Remote Sensing: Assessing the Impact of Drought and Spatial Extent 

Youness Ablila, Abdelhakim Amazirh, Saïd Khabba, El Houssaine Bouras, Mohamed hakim Kharrou, Salah Er-Raki, and Abdelghani Chehbouni

Trees characterized by persistent foliage, like olive trees, serve as indispensable assets in arid and semi-arid regions, exemplified by the Haouz plain in central Morocco. The decline in water resources for irrigation, attributed to climate change and excessive underground water extraction, has led to significant degradation of tree orchards in recent years. Employing remote sensing data, we conducted a spatial analysis of tree degradation from 2013 to 2022 using the supervised classification method. Subsequently, a drying speed index (DS) was computed based on the Normalized Difference Vegetation Index (NDVI) derived from Landsat-8 data, specifically focusing on the identified trees. This DS was then correlated with the Standardized Precipitation Index (SPIn) to elucidate the connection between tree degradation and drought, as indicated by precipitation deficit. The findings reveal a discernible declining trend in trees, with an average decrease in NDVI by 0.02 between 2019 and 2022 compared to the reference period (2013-2019). This decline has impacted an extensive area of 37,550 hectares. Furthermore, the outcomes derived from the analysis of SPI profiles depict a prolonged period of dryness, particularly extreme drought in the past four years, characterized by SPI values consistently below -2. Notably, a high correlation coefficient (R) of -0.87 and -0.88 was observed between DS and SPI9 and SPI12 respectively, emphasizing the strong linkage between drying speed and the duration and intensity of drought. These findings emphasize the reliability of NDVI as an effective tool for precise classification of tree land cover. Additionally, they underscore the significant influence of drought on the degradation of trees in the Haouz plain.

How to cite: Ablila, Y., Amazirh, A., Khabba, S., Bouras, E. H., Kharrou, M. H., Er-Raki, S., and Chehbouni, A.: Analyzing Tree Degradation in the Haouz Plain through Remote Sensing: Assessing the Impact of Drought and Spatial Extent, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18201, https://doi.org/10.5194/egusphere-egu24-18201, 2024.

EGU24-18295 | ECS | Posters on site | HS2.1.5

The relevance of Rossby wave breaking for precipitation in the world’s arid regions 

Andries Jan De Vries, Moshe Armon, Klaus Klingmüller, Raphael Portmann, Matthias Röthlisberger, and Daniela I.V. Domeisen

Precipitation-related extremes in drylands expose more than a third of the world population living in these regions to drought and flooding. While weather systems generating precipitation in humid low- and high-latitude regions are widely studied, our understanding of the atmospheric processes governing precipitation formation in arid regions remains fragmented at best. Regional studies have suggested a key role of the extratropical forcing for precipitation in arid regions. Here we quantify the contribution of Rossby wave breaking for precipitation formation in arid regions worldwide. We combine potential vorticity streamers and cutoffs identified from ERA5 as indicators of Rossby wave breaking and use four different precipitation products based on satellite-based estimates, station data, and reanalysis. Rossby wave breaking is significantly associated with up to 80% of annual precipitation and up to 90% of daily precipitation extremes in arid regions equatorward and downstream of the midlatitude storm tracks. The relevance of wave breaking for precipitation increases with increasing land aridity. Contributions of wave breaking to precipitation dominate in the poleward and westward portions of subtropical arid regions during the cool season. In these regions, climate projections for the future suggest a strong precipitation decline, while projections of precipitation extremes are highly uncertain due to the influence of the atmospheric circulation. Thus, our findings emphasize the importance of Rossby wave breaking as an atmospheric driver of precipitation in arid regions with large implications for understanding projections and constraining uncertainties of future precipitation changes in arid regions that are disproportionally at risk of freshwater shortages and flood hazards.

How to cite: De Vries, A. J., Armon, M., Klingmüller, K., Portmann, R., Röthlisberger, M., and Domeisen, D. I. V.: The relevance of Rossby wave breaking for precipitation in the world’s arid regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18295, https://doi.org/10.5194/egusphere-egu24-18295, 2024.

EGU24-19012 | Orals | HS2.1.5

Decoupling the Influence of Climate Change and Natural Variability on the Middle Eastern Shamal Wind  

Hamza Kunhu Bangalth, Jerry Raj, Udaya Bhaskar Gunturu, and Georgiy Stenchikov

The Middle Eastern Shamal, a prominent north-northwesterly wind, plays a crucial role in the Arabian Peninsula's climate and environment. Originating from the interaction between a semipermanent anticyclone over northern Saudi Arabia and a cyclone over southern Iran, it influences regional climate. The Shamal is essential in transporting dust and pollutants from the Tigris-Euphrates to the Persian Gulf, affecting air quality, health, and travel. Its potential as a renewable energy source also highlights its importance for the region's future energy strategies.

However, understanding the time series of the Shamal wind is a complex task, owing to the intertwined influences of natural climate variability and human-induced climate change. While climate change is a critical factor, natural variability driven by internal climate modes like the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) also significantly influences these winds. These oscillations, operating over multidecadal scales, alongside the overarching trend of climate change, form a complex web affecting the regional climate. 

This study addresses the challenge of decoupling the impacts of climate change and natural climate variability on the Shamal wind. Our analysis employs Empirical Mode Decomposition (EMD), a relatively new approach that allows us to decouple the influence of various internal climate modes from that of anthropogenic climate change. This method surpasses traditional techniques by avoiding assumptions of linearity and stationarity. The study utilizes ERA5 reanalysis data to analyze summer and winter Shamal winds.

Preliminary findings indicate that internal climate modes like the AMO are equally significant as climate change in influencing Shamal wind in the past. This insight is crucial for more accurate projections and predictions of future Shamal wind behavior, benefiting the Middle East's environmental management, health, and renewable energy sectors.

How to cite: Bangalth, H. K., Raj, J., Gunturu, U. B., and Stenchikov, G.: Decoupling the Influence of Climate Change and Natural Variability on the Middle Eastern Shamal Wind , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19012, https://doi.org/10.5194/egusphere-egu24-19012, 2024.

EGU24-19172 | Orals | HS2.1.5

Assessing the possibilities of Sentinel products for qualifying and quantifying soil water status of agricultural systems in southern France  

Claude Doussan, Urcel Kalenga Tshingomba, Nicolas Baghdadi, Fabrice Flamain, Arnaud Chapelet, Guillaume Pouget, and Dominique Courault

Water management poses a pervasive challenge in southern France, exacerbated by increasing summer droughts linked to global warming. Water use during spring and summer increases and gets more variable in term of quantity used for crops. Agricultural water use is highly influenced by the diversity in irrigation practices and technics (sprinkler irrigation, drip irrigation, flooding, etc.) ; and can lead to tensions among water users. It is thus essential to estimate field water use at basin scale, as well as crop water status, in order to further optimize water delivered for irrigation. Advances in remote sensing, particularly with Sentinel 1 (S1) and 2 (S2) data, facilitated the development of soil moisture products (SMP) with improved spatial and temporal resolution to characterize soil water in agricultural plots. These SMP products are accessible through the Theia French public platform and suitable for main crops, with NDVI below 0.75 or surfaces with moderate roughness. These specifications can be met for a variety of crop conditions in the south of France. Yet, the validity of the SMP products under various agricultural plot conditions, considering slope, orientation, roughness, and soil moisture, remains to be assessed over extended time periods. From another point of view, such SMP products do not presently apply to orchards plots, which are however, an essential but overlooked component of water use in irrigation and deserve further examination with S1 and S2 data. The objective of our study is twofold: (i) to test SMP products for field crops in different settings and among years, (ii) to preliminary test if S1 data, combined to S2 data, may be linked to soil moisture in orchard plots. Results reveal for (i) that differences can appear between SMP products and soil moisture in various monitored plots, primarily due to variability within farming systems. Beyond a specific slope and vegetation threshold, the correlation does not improve significantly. For (ii), in orchards plots, using a time smoothing of data, S1 VV-retrodiffusion data and NDVI from S2 seem to correlate with soil moisture measurements, with an RMSE < 0.05 cm3/cm3 and enable detection of irrigation events. This study shows that S1 and S2 data are valuable in estimating soil moisture of agricultural plots, giving however some limits in their use, and gives some hope in their further use for orchards water management.

How to cite: Doussan, C., Kalenga Tshingomba, U., Baghdadi, N., Flamain, F., Chapelet, A., Pouget, G., and Courault, D.: Assessing the possibilities of Sentinel products for qualifying and quantifying soil water status of agricultural systems in southern France , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19172, https://doi.org/10.5194/egusphere-egu24-19172, 2024.

EGU24-19511 | Posters on site | HS2.1.5

OurMED PRIMA-funded Project: Sustainable Water Storage and Distribution in the Mediterranean 

Seifeddine Jomaa, Amir Rouhani, Maria Schade, J. Jaime Gómez-Hernández, Antonio Moya Diez, Maroua Oueslati, Anis Guelmami, George P. Karatzas, Emmanouil A Varouchakis, Maria Giovanna Tanda, Pier Paolo Roggero, Salvatore Manfreda, Nashat Hamidan, Yousra Madani, Patrícia Lourenço, Slaheddine Khlifi, Irem Daloglu Cetinkaya, Michael Rode, and Nadim K Copty

The Mediterranean Region is a unique mosaic of different cultures and climates that shape its peoples, natural environment, and species diversity. However, rapid population growth, urbanisation and increased anthropogenic pressures are threatening water quantity, quality, and related ecosystem services. Known as a climate change hotspot, the Mediterranean region is increasingly experiencing intensifying droughts, diminished river flows, and drier soils making water management even more challenging. This situation calls for an urgent need for water management to shift from a mono-sectoral water management approach based on trade-offs, to more balanced multisectoral management that considers the requirement of all stakeholders. This means that sustainable water management requires ensuring that water is stored and shared fairly across all sectors at the basin scale.

The research project OurMED (https://www.ourmed.eu/) is part of the Partnership for Research and Innovation in the Mediterranean Area (PRIMA) Programme supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 2222. The project was launched in June 2023 and will continue for three years with a grant of 4.4 million euros to develop a holistic water storage and distribution approach tightly integrated into ecosystem services at the river basin scale.

OurMED builds on the multidisciplinary skills of 15 consortium Partners and comprises universities, NGOs, research centres and SMEs from ten countries with complementary expertise in hydrology, hydrogeology, agronomy, climate change, social sciences, remote sensing, digital twins, ecology, and environmental sciences, among others, making it a truly interdisciplinary project. OurMED includes eight distinct demo sites, representing diverse water-related ecosystem properties of the Mediterranean landscape. These include the catchment areas of Bode (Germany), Agia (Crete, Greece), Konya (Turkey), Mujib (Jordan), Medjerda (Tunisia), Sebou (Morocco), Arborea (Sardinia, Italy), and Júcar (Spain). The Mediterranean basin, as a whole, is considered as an additional regional demo site to ensure replicability and reproducibility of proposed solutions at larger scales. 

OurMED vision combines not only technologically-advanced monitoring, smart modelling and optimization capabilities, but also provides data fusion and integrated digital twin technologies to make optimized solutions readily available for decision making. OurMED concept and its implementation to the different demo sites will be presented and discussed.

How to cite: Jomaa, S., Rouhani, A., Schade, M., Gómez-Hernández, J. J., Moya Diez, A., Oueslati, M., Guelmami, A., Karatzas, G. P., Varouchakis, E. A., Tanda, M. G., Roggero, P. P., Manfreda, S., Hamidan, N., Madani, Y., Lourenço, P., Khlifi, S., Daloglu Cetinkaya, I., Rode, M., and Copty, N. K.: OurMED PRIMA-funded Project: Sustainable Water Storage and Distribution in the Mediterranean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19511, https://doi.org/10.5194/egusphere-egu24-19511, 2024.

EGU24-20067 | ECS | Orals | HS2.1.5

Impact Of Ocean Layer Thickness on The Simulation Of African Easterly Waves in High-Resolution Coupled General Circulation Model Simulations 

Jerry Raj, Elsa Mohino Harris, Maria Belen Rodriguez de Fonseca, and Teresa Losada Doval

African easterly waves (AEWs) play a crucial role in the high-frequency variability of West African Monsoon (WAM) precipitation. AEWs are linked to more than 40% of the total Mesoscale Convective Systems (MCSs) in the region and these MCSs contribute approximately 80% of the total annual rainfall over the Sahel. Moreover, around 60% of all Atlantic hurricanes, including 80% of major hurricanes, have their genesis associated with AEWs. The simulation of AEWs poses challenges for General Circulation Models (GCMs), for instance, coarse-resolution models in CMIP5 cannot simulate distinct northern and southern AEW tracks. Additionally, accurately simulating rainfall over West Africa proves to be a challenge for these models due to the involvement of multiscale processes and the influence of complex topography and coastlines. 

The present study investigates the impact of ocean layer thickness on the simulation of African easterly waves (AEWs) using a high-resolution coupled General Circulation Model (GCM). The study employs high-resolution global simulations conducted using the climate model ICON as part of the next Generation Earth System Modeling Systems (nextGEMS) project. Two experiments, each spanning 30 years with a horizontal resolution of 10 km, are conducted. These experiments vary in terms of the thickness of the layers in the upper 20m of the ocean. In one experiment, the upper 20m ocean layers have a thickness of 2m, whereas in the other, it is 10m. The representation of two types of AEWs with periods of 3-5 days and 6-9 days are analyzed in the simulations. There is a notable disparity in the representation of African easterly waves (AEWs) between these two experiments. The simulation with thicker ocean layers exhibits less intense wave activity over the Sahel and equatorial Atlantic for 3-5 day AEWs which is evident in the eddy kinetic energy field. This corresponds to diminished convection and negative precipitation anomalies for 3-5 day AEWs compared to the 2m upper ocean layer thickness simulation. In the case of 6-9 day AEWs, the simulation with thicker ocean layers exhibits intensification of wave activity over northern West Africa.

How to cite: Raj, J., Mohino Harris, E., Rodriguez de Fonseca, M. B., and Losada Doval, T.: Impact Of Ocean Layer Thickness on The Simulation Of African Easterly Waves in High-Resolution Coupled General Circulation Model Simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20067, https://doi.org/10.5194/egusphere-egu24-20067, 2024.

EGU24-20356 | ECS | Posters on site | HS2.1.5

Seasonal Water Turbidity Dynamics in Arid Central Asia: A Case Study of Lake Balkhash, Kazakhstan, Under Changing Environmental Conditions 

Kanchan Mishra, Kathryn E. Fitzsimmons, and Bharat Choudhary

Lake Balkhash, one of the largest inland lakes in Central Asia, plays a pivotal role in providing water and ecosystem services to approximately 3 million people. However, like many water bodies in dryland regions worldwide, Lake Balkhash's hydrology has been significantly affected by climate change and land cover and land-use shifts driven by population growth and water-intensive economic activities. To manage these vital water resources effectively, monitoring the health of water bodies is essential for effective water resource management, security, and environmental conservation. Turbidity, a water quality indicator, measures the water clarity and represents a broader environmental change, allowing us to assess the water body's health and the extent of anthropogenic impact on the entire catchment. It is a measure of water clarity and serves as a crucial indicator of water health, as it represents the primary mechanism for transporting pollutants, algae, and suspended particles.

The present study investigates the temporal and spatial variability of turbidity in Lake Balkhash. We utilize the normalized difference turbidity index (NDTI) with Landsat satellite data spanning from 1991 to 2022 to map turbidity. We consider various climatic and anthropogenic factors, including precipitation, temperature, wind speed and direction, and water levels in and around the lake.

Our findings reveal an overall declining turbidity trend over interannual and seasonal timescales. The results provide a significant negative correlation between turbidity, temperature, and water levels at both temporal scales. However, no straightforward relationship emerges between turbidity and precipitation or wind variables. Specifically, during spring and summer, turbidity exhibits a strong association with temperature and water levels, while in the fall season, water levels are more closely correlated with turbidity. These results underscore the substantial impact of rising temperatures and fluctuations in water levels on the turbidity dynamics of Lake Balkhash. These findings highlight that the warming climate and alterations in lake hydrology pose significant risks to water quality, indicating that monitoring water health alone may not suffice to mitigate the impacts of climate change and human activities.  

How to cite: Mishra, K., Fitzsimmons, K. E., and Choudhary, B.: Seasonal Water Turbidity Dynamics in Arid Central Asia: A Case Study of Lake Balkhash, Kazakhstan, Under Changing Environmental Conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20356, https://doi.org/10.5194/egusphere-egu24-20356, 2024.

EGU24-20398 | Posters on site | HS2.1.5

Analysis of operational droughts in an alpine Mediterranean basin using a conjunctive use model of surface and groundwater resources 

Juan-de-Dios Gómez-Gómez, Antonio Collados-Lara, David Pulido-Velázquez, Leticia Baena-Ruiz, Jose-David Hidalgo-Hidalgo, Víctor Cruz-Gallegos, Patricia Jimeno-Sáez, Javier Senent-Aparicio, Fernando Delgado-Ramos, and Francisco Rueda-Valdivia

Extreme events, and particularly, droughts are a main concern in Mediterranean basins that will be increased in the future due to climate change (CC), according to the forecasting for the region made by researchers. A novel integrated approach is proposed to analyze operational droughts and their propagation in future CC scenarios at a basin scale. This approach has been applied to the Alto Genil basin (Granada, Spain), an alpine Mediterranean basin with the singularity of having an important snow component in its precipitation regime. The Standardized Precipitation Index (SPI) methodology has been applied to the variable Demand Satisfaction Index (DSI) at a monthly scale to evaluate operational droughts. A conjunctive use model of surface and groundwater resources developed with the code Aquatool has been used to obtain historical and future DSI monthly series. It is an integrated management model that includes all water demands, water resources (surface, groundwater, and their interaction), regulation and distribution infrastructures in the Alto Genil system. The Vega de Granada aquifer is a key element of the water supply system such for agricultural needs as for guarantee the urban supply to the city of Granada. Groundwater flow in this important aquifer has been simulated with a distributed approach defined by an eigenvalue model to integrate it in the management model, and in order to obtain a more detailed analysis of its future evolution. The proposed methodology consists of the sequential application of the following steps: (1) generation of future scenarios for the period 2071-2100 to obtain series of precipitation (P) and temperature (T); (2) application of a chain of models: a rainfall-runoff model (Témez) coupled with a snowmelt model to obtain runoff (Q) series in subbasins of Alto Genil basin, a crop water requirement model (Cropwat) to get agricultural demand series, and an integrated management model (Aquatool) to get historical and future series of DSI; and (3) analysis of operational droughts comparing historical and future series of the Standardized Demand Satisfaction Index (SDSI), which is the application of the SPI methodology to the variable DSI. A cluster analysis of variables P and Q has been made in order to define homogeneous hydroclimatic areas by aggregation of subbasins. It will allow us to perform an analyses of the heterogeneity in  the propagation of droughts.

Aknowledments: This research has been partially supported by the projects: STAGES-IPCC (TED2021-130744B-C21), SIGLO-PRO (PID2021-128021OB-I00), from the Spanish Ministry of Science, Innovation and Universities, RISRYEARTH (Recovery funds), and “Programa Investigo” (NextGenerationEU).

How to cite: Gómez-Gómez, J.-D., Collados-Lara, A., Pulido-Velázquez, D., Baena-Ruiz, L., Hidalgo-Hidalgo, J.-D., Cruz-Gallegos, V., Jimeno-Sáez, P., Senent-Aparicio, J., Delgado-Ramos, F., and Rueda-Valdivia, F.: Analysis of operational droughts in an alpine Mediterranean basin using a conjunctive use model of surface and groundwater resources, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20398, https://doi.org/10.5194/egusphere-egu24-20398, 2024.

EGU24-20616 | Orals | HS2.1.5

Integrating Multi-Sensor and Multi-Platform Technologies for Enhanced Assessment of Spectral Indices and Phenological Dynamics in a Seasonal Tropical Dry Forest 

Magna Moura, Rodolfo Nobrega, Anne Verhoef, Josicleda Galvíncio, Rodrigo Miranda, Bruna Alberton, Desiree Marques, Cloves Santos, Bruno Nascimento, Maria Maraiza Pereira, and Patricia Morellato

The Seasonal Tropical Dry Forest (STDF) known as Caatinga occupies approx. 10% of the Brazilian territory. Its vegetation exhibits rapid phenological responses to rainfall resulting in corresponding increases in gross primary productivity and biomass production. Determining the timing of the start and end of the growing season is very important to ecosystem studies and to precisely quantify the carbon balance. Satellite-derived vegetation indices have been widely used to capture the vegetation dynamics in response to fluctuating environmental conditions. However, the spatial and temporal resolution of these indices cannot capture fine vegetation features and phenology metrics in a highly biodiverse and heterogeneous environment such as the Caatinga. On the other hand, phenocameras have been successfully used for this particular purpose for tropical and dry ecosystems. Complementarily, proximal spectral response sensors (SRS) have been used to allow computation of vegetation indices as phenology proxies. Due to their ability to capture high spatial resolution imagery, Unmanned Aerial Systems (UAS) or drones, can deliver an excellent spatial and a very good temporal resolution for diverse detailed vegetation studies. In this context, the objective of this study was to verify whether multi-sensor and multi-platform technologies provide an enhanced assessment of spectral indices and phenological dynamics of the Caatinga. The field campaign occurred in a pristine area of caatinga vegetation, located at the Legal Reserve of Caatinga, Embrapa Semi-Arid, Petrolina, Brazil. Indices for detecting phenology dynamics were obtained using multi-spectral cameras installed on unmanned aerial vehicles (UAV), field spectral response sensors (SRS), phenocameras (digital RGB cameras) and MODIS satellite data (visible and near infrared) from 2020 to 2023. Environmental driving data were measured via instrumentation installed on a flux tower. Standard statistical measures, including correlation coefficients were employed to verify the relationship observed on Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), and Green Chromatic Coordinate (Gcc) determined by different sensors and platforms. We observed a substantial and fast increase in Gcc, NDVI and PRI immediately after rainfall events. The sensitivity of NDVI and PRI to changes in vegetation can vary depending on factors such as vegetation greenness, overall plant health, and stress responses according to the environmental conditions of the study area. Particularly during the dry season, indices derived from higher spatial resolution sensors consistently showed lower NDVI values compared to those obtained from proximal spectral response sensors (SRS) and drones. Our observations indicate that the representation of vegetation captured by satellites and drones aligns well with the data obtained from phenocamera and proximal SRS platforms. The combination of high temporal resolution provided by SRS and phenocameras resulted in improved and more reliable indices that will be indispensable for evaluating the response of Caatinga vegetation to current and future conditions.

Funding: This study was supported by the São Paulo Research Foundation-FAPESP (grants ##2015/50488-5, #2019/11835-2; #2021/10639-5; #2022/07735-5), the Coordination for the Improvement of Higher Education Personnel - CAPES (Finance Code 001), the National Council for Scientific and Technological Development - CNPq (306563/2022-3).

How to cite: Moura, M., Nobrega, R., Verhoef, A., Galvíncio, J., Miranda, R., Alberton, B., Marques, D., Santos, C., Nascimento, B., Pereira, M. M., and Morellato, P.: Integrating Multi-Sensor and Multi-Platform Technologies for Enhanced Assessment of Spectral Indices and Phenological Dynamics in a Seasonal Tropical Dry Forest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20616, https://doi.org/10.5194/egusphere-egu24-20616, 2024.

EGU24-20999 | ECS | Orals | HS2.1.5

Soil and rock water dynamics in a semiarid karst savanna undergoing woody plant encroachment

Pedro Leite, Bradford Wilcox, Daniella Rempe, and Logan Schmidt

EGU24-58 | ECS | Orals | HS2.4.2

Unveiling Hydrological Dynamics in Data-Scarce Regions:A Comprehensive Integrated Approach 

Ayenew Desalegn Ayalew, Paul D. Wagner, Dejene Sahlu, and Nicola Fohrer

The hydrological system of Rift Valley Lakes in Ethiopia has recently experienced changes since the past two decades. Potential causes for these changes include anthropogenic, hydro-climatic and geological factors. The main objective of this study was to utilize an integrated methodology to gain a comprehensive understanding of the hydrological systems and potential driving factors within a complex and data-scarce region. To this end, we integrated a hydrologic model, change point analysis, indicators of hydrological alteration (IHA), and bathymetry survey to investigate hydrological dynamics and potential causes. A hydrologic model (SWAT+) was parameterized for the gauged watersheds and extended to the ungauged watersheds using multisite regionalization techniques. The SWAT+ model performed very good to satisfactory for daily streamflow in all watersheds with respect to the objective functions, Kling–Gupta efficiency (KGE), the Nash–Sutcliffe efficiency (NSE), Percent bias (PBIAS). The findings reveal notable changes of lake inflows and lake levels over the past two decades. Chamo Lake experienced an increase in area by 11.86 km², in depth by 4.4 m, and in volume by 7.8 x 108 m³. In contrast, Lake Abijata witnessed an extraordinary 68% decrease in area and a depth decrease of 1.6 m. During the impact period, the mean annual rainfall experienced a decrease of 6.5% and 2.7% over the Abijata Lake and the Chamo Lake, respectively. Actual evapotranspiration decreased by 2.9% in Abijata Lake but increased by up to 0.5% in Chamo Lake. Surface inflow to Abijata Lake decreased by 12.5%, while Lake Chamo experienced an 80.5% increase in surface inflow. Sediment depth in Chamo Lake also increased by 0.6 m. The results highlight that the changing hydrological regime in Chamo Lake is driven by increased surface runoff and sediment intrusion associated with anthropogenic influences. The hydrological regime of Abijata Lake is affected by water abstraction from feeding rivers and lakes for industrial and irrigation purposes. This integrated methodology provides a holistic understanding of complex data-scarce hydrological systems and potential driving factors in the Rift Valley Lakes in Ethiopia, which could have global applicability.

How to cite: Ayalew, A. D., Wagner, P. D., Sahlu, D., and Fohrer, N.: Unveiling Hydrological Dynamics in Data-Scarce Regions:A Comprehensive Integrated Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-58, https://doi.org/10.5194/egusphere-egu24-58, 2024.

EGU24-95 | ECS | Orals | HS2.4.2

Flood prediction based on weather parameters using advanced machine learning-metaheuristic approaches 

Sandeep Samantaray, Abinash Sahoo, and Deba P Satapathy

Flood prediction has become more popular worldwide because of the devastating socioeconomic effects of this hazard and the predicted rise in its frequency in the near future. In India, public health, civil engineering, and agriculture are all greatly affected by flooding. Anything can be flooded, with levels ranging from a few inches to many feet. They may appear suddenly or develop gradually. The intensity and frequency of flooding will frequently increase due to human modifications to the environment. More frequent and severe weather occurrences could lead to more violent floods. Utilizing data-driven and machine-learning models to solve flow- and flood-related problems has lately gained traction as a subject of study. ML model shows two key advantages over traditional physically-based models controlled by differential equation systems. Firstly, without requiring a complete a priori understanding of the phenomenon, data-driven models are able to generate reasonably accurate predictions. The quantity, quality, and variety of data that are accessible all affect how accurate the model is. This feature shows that we can avoid the complexity of problems faced by physical-based models caused by the growing number of important components by learning from observational data. Second, data-driven flood models replace numerical integration of differential equations, which is an iterative process, with non-iterative procedures like forward propagation of neural networks.

We chose to study the floods in the Barak River basin (BRB), India, a high-elevation and quickly urbanized river basin that is prone to frequent flooding because of recent evidence of the impacts of regional climate change on the hydrological cycle. Using principal component analysis (PCA), the optimal inputs were found. Decision-makers in the hydrological field of research need accurate information regarding effective predictors. This study looks into the viability of using weather input data (rainfall, humidity, evapotranspiration, temperature) to predict monthly floods using a support vector machine customized with Manta-Ray foraging optimization (SVM-MRFO). The accuracy of SVM-MRFO was assessed by comparing it against SVM tuned by the Firefly algorithm, whale optimization algorithm, Salp swarm algorithm based on mean absolute errors (MAE), root mean square errors (RMSE), determination coefficient (R2), and Nash-Sutcliffe Efficiency (NSE). Implementing the FFA, WOA, SSA, and MRFO algorithms enhances the accuracy of the SVM.

The best performance metrics, NSE of 0.9914, RMSE of 0.0182, MAE of 0.0073, and BIAS of were obtained by the SVM model constructed using the MRFO training procedure, suggesting the model's potential for use in flood forecasting. The flood models in this study are significant since they were created using a mix of different inputs and AI algorithms. In conclusion, this study demonstrated the ability of AI algorithm-based models to forecast floods and produced a number of practical methods that the flood control departments of different states, regions, and nations might employ to estimate the likelihood of floods.

How to cite: Samantaray, S., Sahoo, A., and Satapathy, D. P.: Flood prediction based on weather parameters using advanced machine learning-metaheuristic approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-95, https://doi.org/10.5194/egusphere-egu24-95, 2024.

Despite rising rainfall constraints on global climate-resilient agriculture, there is no clear consensus on the quantification of the wet season, leading to contentious issues in rainfall regime evolution and subsequent impacts on phenology and vegetation productivity. Hence, we conducted a comprehensive assessment of rainfall regimes between 1982 and 2020 by using a modified anomalous accumulation method on a daily scale at the pixel level. We observed divergent patterns of “wet areas becoming drier, and dry areas becoming wetter” with rainfall amount and rainy days increasing in dry regions, and decreasing in humid regions. The length of the wet season was extended in the dry regions and shortened in the wet regions, and the trends were linearly related on dryness. Simultaneously, as dryness increased, so did the length, number, and cumulative number of dry days. Concurrent increases in rainy days and dry spells indicated a seasonal rainfall regime trend toward more frequent extreme conditions in drier areas, which was not entirely consistent with a global intensification pattern of “dry getting drier and wet getting wetter”, implying increased potential risks of both floods and droughts in dry areas. For climate risk prediction, water resource allocation, and agricultural management, we advocate for a finer and more precise dynamic assessment of the wetting-drying pattern.

How to cite: Hu, Y.: Divergent patterns of rainfall regimes in dry and humid areas of China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-126, https://doi.org/10.5194/egusphere-egu24-126, 2024.

Long-term variations in catchment evapotranspiration control water availability for human societies and freshwater ecosystems, with potential negative impacts particularly during low-flow conditions. Previous studies reported increases in water balance-derived evapotranspiration for parts of Central Europe, mostly between 1980s and 2010s. However, knowledge gaps still remain around (i) the extent of these increases in space and time, and (ii) uncertainties from the catchment water balance. Here we analyse trends in water balance-derived evapotranspiration for 461 German near-natural catchments, over multiple time windows in the last six decades. We constrain uncertainties through estimates of storage changes derived from recession analysis and the use of multiple precipitation products. Results show wide-spread, significant increases in catchment evapotranspiration during 1970s–2000s (for example, average regional trends of 3.2 mm year-2 with an uncertainty from precipitation of ±1 mm year-2 for the period 1970–2002). Yet, catchment evapotranspiration shows no significant changes or rather a tendency to the decrease after 2000s (-3.6±1.4 mm year-2 for Pre-Alpine catchments over 2000–2019). The directions of these variations are robust to the considered uncertainties and consistent with sparse in-situ data. We further discuss implications of these variations with respect to low-flow conditions.  This study offers a comprehensive synthesis on past variations in catchment evapotranspiration and their uncertainties, which is critical for a proper understanding of recent hydrological changes.   

How to cite: Bruno, G. and Duethmann, D.: Inter-decadal variations in water balance-derived catchment evapotranspiration in Central Europe and their uncertainties, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1145, https://doi.org/10.5194/egusphere-egu24-1145, 2024.

EGU24-1420 | Orals | HS2.4.2 | Highlight

Storylines of climate variability for hydrological impact studies 

Theodore Shepherd

Physical climate storylines (physically-based unfoldings of past climate or weather events, or of plausible future events or pathways) are increasingly being used to represent the epistemic uncertainty in the forced response to climate change. But storylines can also be used to systematically explore the uncertainty space of climate variability, e.g. to construct plausible worst-case events. Their use in this latter context is perhaps less obvious since variability is generally considered to be an aleatoric rather than an epistemic uncertainty. However, for impact studies, variability is often hugely undersampled, which is a serious problem that storylines can help address. In this talk I will review the rationale behind the use of storylines, discuss some of the concerns and questions about storylines that continue to arise, and provide some examples of their use in this particular context and of how storyline and probabilistic representations of uncertainty can be usefully combined.

How to cite: Shepherd, T.: Storylines of climate variability for hydrological impact studies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1420, https://doi.org/10.5194/egusphere-egu24-1420, 2024.

EGU24-1538 | ECS | Posters on site | HS2.4.2

Small, flashy catchments response to variation in rainfall profile shape 

Alexandra Seawell

Flash flooding has the potential for severe consequences but is much less well understood or predictable than longer duration flooding. It is important to improve understanding of patterns of rainfall and behaviour of responding catchments in order to manage flash flooding effectively. One aspect of rainfall that could potentially affect flood hydrographs is the temporal shape of rainfall profiles.

Design flood estimation in the UK is principally based on the FSR /FEH/ReFH methodology, which uses a symmetrical centre-loaded profile for rainfall. However, recent research undertaken during Roberto Villalobos Herrera’s PhD is that front-loaded and back-loaded rainstorms occur just as frequently as centre-loaded. My PhD seeks to test how different rain profile shapes change the river flow hydrograph and flooding across the catchment.

My PhD concentrates on small catchments which have typically been less studied and because they are likely to be responsive to short, intense rainfall that can cause flash flooding. Hydrological modelling has been undertaken for 24 identified study catchments using ReFH2.3 software, which is the standard flood estimation design software in the UK. Results indicate that use of symmetrical profiles risks underestimating potential flood peaks compared to back-loaded storms. Meanwhile, time-to-peak is typically shorter for frontloaded storms indicating the hydrograph rises faster, but lagtime is shorter for back-loaded storms indicating the peak flow occurs more quickly after the peak rain. As well as modelled responses, I have also begun identifying and analysing observed hydrographs for selected study catchments to see if these show any pattern in their response to rainfall profile shapes.

How to cite: Seawell, A.: Small, flashy catchments response to variation in rainfall profile shape, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1538, https://doi.org/10.5194/egusphere-egu24-1538, 2024.

EGU24-1918 | ECS | Posters on site | HS2.4.2

Evaporation and hydrology of the Orinoco and Amazon basins modulated by the Atlantic 

Nicolas Duque-Gardeazabal, Andrew R. Friedman, and Stefan Brönnimann

El Niño/Southern Oscillation (ENSO) strongly impacts the hydroclimate of tropical South America. However, other ocean-atmospheric oscillations in the Atlantic also have teleconnections over the continent with the most extensive tropical rainforest; these oscillations influence hydroclimate extremes (i.e. droughts and floods). Our research focuses on the physical mechanisms that link the Atlantic Sea Surface Temperature conditions with the hydrological anomalies, i.e. soil moisture, streamflow and evaporation.

This research is grounded on the consistency of a multi-evidence approach between datasets. We use independent observations of land-surface and atmospheric variables whose robustness comes from gauges, physically consistent interpolations (i.e. reanalysis), simulations or satellite-based observations. The research focuses on the satellite era (1980-) to compare several datasets. Apart from the Amazon, other important basins such as the Orinoco, Magdalena and Tocantis have received little attention; hence, we also focused on them.

The Atlantic Meridional Mode (AMM) consists of cross-equatorial Sea Level Pressure anomalies that deflect climatological winds northward or southward. Hence, the seesaw of wind anomalies produces anomalous atmospheric transport, convergence and precipitation. When dividing the analysis by independent seasons, the results show changing impacts over different subbasins of the Orinoco and Amazon. On the other hand, the Atlantic El Niño/La Niña (Atl3) weakens or strengthens the trade winds from June to August, producing moisture convergence or divergence over the Guianas and eastern Orinoco.

The SST impact on evaporation is a complex consequence of the anomalous atmospheric circulation. The cascade of abnormal atmospheric circulation modifies not just the surface water but also the radiation availability, causing hydrological anomalies. The radiation anomalies combined with the soil moisture memory control the evaporation anomalies. This dynamic also depends on the season analysed.

How to cite: Duque-Gardeazabal, N., Friedman, A. R., and Brönnimann, S.: Evaporation and hydrology of the Orinoco and Amazon basins modulated by the Atlantic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1918, https://doi.org/10.5194/egusphere-egu24-1918, 2024.

EGU24-2089 | ECS | Orals | HS2.4.2

Groundwater level reconstruction using long-term climate reanalysis data and deep neural networks  

Sivarama Krishna Reddy Chidepudi, Nicolas Massei, Abderrahim Jardani, and Abel Henriot

Assessing long-term changes in groundwater is crucial for understanding the impacts of climate change on aquifers and for managing water resources. However, long-term groundwater level (GWL) records are often scarce, limiting understanding of historical trends and variability. In this study, we present a deep learning approach to reconstruct GWLs up to several decades back in time using recurrent-based neural networks with wavelet pre-processing and climate reanalysis data as inputs. GWLs are reconstructed using two different reanalysis datasets with distinct spatial resolutions (ERA5: 0.25◦ x 0.25◦ & ERA20C: 1◦ x 1◦) and monthly time resolution, and the performance of the simulations was evaluated.  Long term GWL timeseries are now available for northern France, corresponding to extended versions of observational timeseries back to the early 20th century. All three types of piezometric behaviors could be reconstructed reliably and consistently capture the multidecadal variability even at coarser resolutions, which is crucial for understanding long-term hydroclimatic trends and cycles. GWLs’multidecadal variability was consistent with the Atlantic multidecadal oscillation. From a synthetic experiment involving a modified long-term observational time series, we highlighted the need for longer training datasets for some low frequency signals. Nevertheless, our study demonstrated the potential of using DL models together with reanalysis data to extend GWL observations and improve our understanding of groundwater variability and climate interactions. 

How to cite: Chidepudi, S. K. R., Massei, N., Jardani, A., and Henriot, A.: Groundwater level reconstruction using long-term climate reanalysis data and deep neural networks , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2089, https://doi.org/10.5194/egusphere-egu24-2089, 2024.

EGU24-3925 | ECS | Orals | HS2.4.2

Multi-decadal changes in root zone water storage capacity through vegetation adaptation to hydro-climatic variability 

Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups

Climate change can considerably affect catchment-scale root zone storage capacity (Sumax) which may further influence the moisture exchange between land and atmosphere, as well as stream flow and biogeochemical processes in terrestrial hydrological systems. However, direct quantification of the evolution of Sumax over multi-decadal time periods at the catchment scale has so far been rare. As a consequence, it remains unclear how climate change affects Sumax (e.g., precipitation regime, canopy water demand) and how changes in Sumax may control the partitioning of water fluxes as well as the hydrological response at catchment scale. The objectives of this study in the upper Neckar river basin in Germany are therefore to provide an analysis of muti-decadal changes in Sumax that can be observed as a result of changing climatic conditions over the past century and how this has further affected hydrological dynamics. More specifically, we test the hypotheses that (1) Sumax significantly changes over multiple decades reflecting vegetation adaptation to climate variability, (2) changes in Sumax control water availability for evapotranspiration and thus multi-decadal deviations from long-term average positions in the Budyko framework, (3) a time-dynamic implementation of Sumax affects the hydrological response, which in return can improve the performance of a hydrological model.

We found that, indeed, a hydroclimatic condition considerably changed over time in the 1953 to 2022 study period, which was reflected by related fluctuations in the values of Sumax derived directly from observed water balance data These ΔSumax values varied by up to -20% in relatively wet decades to +20% in drier decades, which was very similar to ΔSumax obtained from calibration of a hydrological model (R2=0.95, p<0.05) in individual decades. However, evaporation estimated by the hydrological model using a long-term average Sumax for the study period was almost the same as that reproduced by the model when allowing dynamically changing root-zone storage capacities over multiple decades. In addition, no significant improvement in the reproduction of the hydrological response was observed when implementing a time-variant representation of decadally varying Sumax in the model compared with the implementation of a stationary Sumax irrespective of the hydroclimatic conditions in the individual decades.

Overall, this study provides quantitative evidence that Sumax significantly changes over multiple decades reflecting vegetation adaptation to climate variability. However, these changes are not responsible for deviations from the Budyko curves in different climatic conditions, in other words, the temporal evolution of Sumax in the study region is not a major control on the partitioning of water fluxes into evapotranspiration and drainage and does have therefore no significant effects on fundamental hydrological response characteristics of the upper Neckar catchment. This suggests that model predictions of future stream flows remain rather insensitive to uncertainties introduced by the use of time-invariant long-term average values of Sumax as model parameters.

How to cite: Wang, S., Hrachowitz, M., and Schoups, G.: Multi-decadal changes in root zone water storage capacity through vegetation adaptation to hydro-climatic variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3925, https://doi.org/10.5194/egusphere-egu24-3925, 2024.

EGU24-6799 | ECS | Orals | HS2.4.2

Identification of extreme climatic events using SMOS 

Nitu Ojha, Yann Kerr, and Arnaud Mialon

Soil moisture (SM) is a crucial parameter in the hydrological cycle. SM wet and dry trends help to identify extreme weather events, with a rapid increase in SM suggesting heavy rainfall or flood events and a significant or prolonged decrease in SM representing drought events. SMOS and SMAP remote sensing satellites provide surface SM data globally. The surface SM is highly variable in terms of space and time. In contrast, root zone soil moisture (RZSM) is stable and retains long-term information, making it a better indicator of prolonged drought/wet conditions. In this context, SMOS RZSM is computed from the SMOS surface SM using a simple physical model to integrate surface SM information to a root zone. The study benefits from the availability of long-term series data of the SMOS RZSM on a global scale from 2010 to 2023 (approximately 14 years). Then, the SM index is developed using long-time series data of the SMOS RZSM for a better understanding of the distribution of wet and dry SM and its link to extreme events. The study primarily focuses on Australia and Europe. The results show that the developed SMOS SM index captures heavy rainfall/flood and drought conditions. The analysis determines the occurrence of floods due to La Niña and El Niño effects over Australia and the existence of drought in Europe due to the North Atlantic oscillation. This study can help to understand the interconnected factors that influence extreme climatic conditions, ranging from natural climatic phenomena to human-induced activities.

How to cite: Ojha, N., Kerr, Y., and Mialon, A.: Identification of extreme climatic events using SMOS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6799, https://doi.org/10.5194/egusphere-egu24-6799, 2024.

EGU24-7568 | Posters on site | HS2.4.2

Mapping UK Drought Teleconnections from Ocean to Land 

Amulya Chevuturi, Marilena Oltmanns, Maliko Tanguy, Ben Harvey, Cecilia Svensson, and Jamie Hannaford

Given the anticipated changes in future UK drought occurrences attributable to climate change, there is an imminent requirement for a thorough understanding of the underlying influences behind UK drought events, particularly the most extreme events. In this context, our study aims to understand the North Atlantic oceanic drivers responsible for drought events in the UK, subsequently tracing the teleconnection pathways that connect these drivers to meteorological and hydrological droughts within the region. We examine the teleconnection pathways associated with drought conditions by assessing the concurrent and lagged statistical links between the UK's standardized precipitation index (SPI) and standardized streamflow index (SSI) and two distinct North Atlantic Sea surface temperature (SST) patterns, which are associated with freshening events. Our findings reveal that these North Atlantic SST patterns exert varying influences on two distinct regions of the UK (northwest and southeast), each of which have distinct hydrometeorological characteristics. The identified SST patterns are linked to the dominant modes of SST variability in the North Atlantic, thereby contributing to the predictability of drought occurrences across seasonal to multi-annual timescales, including at some very long lead times. Our research therefore has significant potential in practical applications for quantifying and managing drought risk, and for advancing drought forecasting and early warning systems through the identification of novel, skilful predictors. Ultimately, our work endeavours to contribute to the progress of sustainable water resource management amidst the escalating drought risks in the UK.

How to cite: Chevuturi, A., Oltmanns, M., Tanguy, M., Harvey, B., Svensson, C., and Hannaford, J.: Mapping UK Drought Teleconnections from Ocean to Land, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7568, https://doi.org/10.5194/egusphere-egu24-7568, 2024.

EGU24-7930 | Posters on site | HS2.4.2

An increasing role of subsurface processes in the water circulation in the High Arctic catchment – the results from Fuglebekken, SW Spitsbergen 

Marzena Osuch, Abhishek Alphonse, Nicole Hanselmann, and Tomasz Wawrzyniak

Changes in the depth of the active layer thickness (ALT) in Arctic and permafrost regions significantly impact the transformation of rainfall into runoff. Due to climate change, permafrost thawing and ALT alterations modify how water is transported and stored within catchments, affecting surface and subsurface hydrological processes. This study investigates the associations between temporal changes in active layer thickness, hydrological model parameters, and variations in catchment responses.

The study area covers the unglaciated catchment Fuglebekken, located near the Polish Polar Station Hornsund on Spitsbergen. For hydrological modelling, the conceptual rainfall-runoff HBV model was used. Model calibration and validation were carried out on runoff data within subperiods. A moving window approach (3-week duration) using data from the summer seasons 2014-2023 was applied to derive temporal variations of parameters. Model calibration, along with an evaluation of parametric uncertainty, was performed using the Shuffled Complex Evolution Metropolis algorithm.

A comprehensive investigation of the temporal variability of HBV model parameters demonstrated consistency in the results. The smallest parametric uncertainty and the largest temporal changes were estimated for the parameter KS representing a slow runoff reservoir. Temporal variability of the KS parameter is characterized by the presence of two maxima, the first maximum at the beginning of the ablation season (due to snowmelt and ice-rich permafrost thawing) and the second maximum in September (a result of high precipitation). The temporal variability of other parameters was smaller and usually within their parametric uncertainty.

In addition, the use of the HBV model allowed for the assessment of water storage in five conceptual reservoirs characterizing catchment processes. The outcomes highlighted large changes in slow runoff reservoir, demonstrating an increasing significance of subsurface processes in the water circulation in the High Arctic catchment. 

The study was supported by the Polish National Science Centre (grant no. 2020/38/E/ST10/00139).

How to cite: Osuch, M., Alphonse, A., Hanselmann, N., and Wawrzyniak, T.: An increasing role of subsurface processes in the water circulation in the High Arctic catchment – the results from Fuglebekken, SW Spitsbergen, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7930, https://doi.org/10.5194/egusphere-egu24-7930, 2024.

Ice-induced winter flooding, intensified by sustained low temperatures, holds the potential for severe natural disasters, but is seldom explored probabilistically considering warming climate impacts. This study established both marginal and copula-based joint probability distributions of the upstream (QH) and downstream (QL) ice-induced floods in the Lower Yellow River, a hanging river above the ground, under four parametric scenarios (constant, time as covariates, mean air temperature as covariates, and accumulated negative air temperature as covariates), to compare historical and design flood regimes using six inference methods (UNI, OR, AND, KEN, SKEN, and COND) under air temperature changes. The results show that the Lognormal and Weibull marginal distribution models with accumulated negative air temperature as covariate parameters were optimal for QH and QL, respectively and the positive dependence between QH and QL was best described by the Gumbel-Hougaard copula. Impacts of increasing air temperature on flood downtrends and yearly change-points (1990 for QH and 1985 for QL) reduced both historical QH-QL flood magnitude combinations and projected return periods, thus denoting declining flood severities over time. Due to such flood downtrends, the most probable composition (MPC) values of 100-year design floods varied from the highest (1656 m3/s for QH and 1645 m3/s for QL using the OR method) to the lowest (624 m3/s for QH and 342m3/s for QL using the SKEN method). The average decreasing rates of MPC values before and after the discerned flood change-points were 17.4% for QH and 39.6% for QL. When conditioned on the occurrence of upstream QH having flood magnitudes less than 100-year design floods, large floods downstream exceeding a 50-year return period were inferred as improbable. This study can provide a paradigm of flood projections to meet diverse flood control objectives under changing climate.

How to cite: Li, L. and Xu, C.-Y.: Probabilistic projections of winter floods considering cumulative effect of air temperature changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8371, https://doi.org/10.5194/egusphere-egu24-8371, 2024.

EGU24-10340 | ECS | Orals | HS2.4.2

The Impact of GRACE Data Assimilation on Water Storage Dynamics in CLM3.5 and CLM5 

Yorck Ewerdwalbesloh, Anne Springer, and Jürgen Kusche

The GRACE (Gravity Recovery And Climate Experiment) satellite mission as well as its successor GRACE Follow-On have monitored global and regional variability of total water storage (TWS) for the past two decades. Assimilating observations from these missions into hydrological models helps to improve modeled water storages and fluxes, to overcome deficits arising from simplifications or processes that are not considered in the model (e.g. unmodeled anthropogenic impacts), and to disaggregate GRACE observations temporally and spatially. Determining the optimal approach for assimilating these observations into hydrological models remains an ongoing area of research. The choice often depends on specific applications and the characteristics of the model itself.

In this study, we analyze the water storage dynamics of two versions of the Community Land Model (CLM) - versions 3.5 and 5 - within a GRACE data assimilation framework over a 12.5 km grid covering Europe. The analysis focuses on assessing (i) the skill of both models without data assimilation, (ii) the impact of GRACE data assimilation on the model performance and (iii) the distribution of assimilation increments to different storage compartments. We evaluate water storages and fluxes simulated by both models against independent observations such as discharge from river gauges and satellite derived soil moisture. The results offer valuable insights into the impact of advancements made in biophysical processes and the representation of the carbon cycle in CLM5. Furthermore, we discuss the effectiveness of GRACE data assimilation and its influence on the behavior of CLM3.5 and CLM5, analyzing whether the assimilation helps to address differences between the two model versions - particularly considering the advancements in CLM5 - which would underline the ability of GRACE data assimilation in mitigating model deficits.

How to cite: Ewerdwalbesloh, Y., Springer, A., and Kusche, J.: The Impact of GRACE Data Assimilation on Water Storage Dynamics in CLM3.5 and CLM5, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10340, https://doi.org/10.5194/egusphere-egu24-10340, 2024.

EGU24-10459 | ECS | Posters on site | HS2.4.2

Past, Present, and Future Impacts of Climate Change and Variability on Flood Hazards in Sub-Saharan Africa 

Job Ekolu, Bastien Dieppois, Yves Tramblay, Jonathan Eden, Moussa Sidibe, Gabriele Villarini, Simon Moulds, Louise Slater, Stefania Grimaldi, Peter Salamon, Pierre Camberlin, Benjamin Pohl, Gil Mahé, and Marco van de Wiel

Sub-Saharan Africa (SSA) is strongly affected by flood hazards, which endanger human lives and disrupt economic stability. It is therefore critical to further understand the potential impact of climate change and variability on historical and future flood hazards in SSA. To do so, we first reconstructed a complete 65-yearlong daily streamflow, presenting over 600 stations distributed throughout SSA. Using this new dataset, we found that historical trends in flood frequency, duration, and intensity were strongly modulated by decadal to multidecadal variability. We then identified internal modes of climate variability in the Pacific and Indian Oceans as primary drivers of decadal variations in flood occurrence in southern and eastern Africa. Meanwhile, decadal sea-surface temperature anomalies (SSTa) over the eastern Mediterranean region and the North Atlantic were primarily driving decadal trends in floods occurring over western and central Africa. Using 12 climate model large ensembles from the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and 6), we also found such decadal variations in SSTa in the Mediterranean Atlantic, Pacific, and Indian oceans could modulate the occurrence of flood hazards by up to 50% in SSA during the 21st century. Finally, combining bias-corrected CMIP6 data and the open-source hydrological model LISFLOOD, we examine the potential impact of climate change on future trends affecting the intensity, frequency, and duration of floods in West Africa. This study therefore enabled us to compare for the first time the relative importance of climate change and climate variability on future changes affecting flood hazards in SSA.

How to cite: Ekolu, J., Dieppois, B., Tramblay, Y., Eden, J., Sidibe, M., Villarini, G., Moulds, S., Slater, L., Grimaldi, S., Salamon, P., Camberlin, P., Pohl, B., Mahé, G., and van de Wiel, M.: Past, Present, and Future Impacts of Climate Change and Variability on Flood Hazards in Sub-Saharan Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10459, https://doi.org/10.5194/egusphere-egu24-10459, 2024.

EGU24-10963 | ECS | Orals | HS2.4.2

Future changes in tropical vertical velocity variance and precipitation variability 

Zhenghe Xuan, Clarissa Kroll, and Robert Jnglin Wills

Understanding precipitation variability on subseasonal-to-decadal timescales is important because of its influence on regional water resources and hydrological extremes. The response of precipitation to global warming can be understood in terms of a superposition of thermodynamic and dynamic effects. The former has been studied on a range of timescales, including ENSO variability and precipitation extremes, and is strongly constrained by Clausius-Clapeyron scaling. Changes in dynamics, however, modulate the overall change significantly and represent an important source of uncertainty in projected changes of hydrological cycle variability.

Here, we investigate changes in the variance of vertical velocity in the tropics based on monthly outputs from the Community Earth System Model 2 Large Ensemble. We find a robust decrease in the tropical vertical velocity variance under the SSP3-7.0 scenario, even in periods where the underlying ENSO-related SST variance increases. This reduction in vertical velocity variance can be explained by the deepening of the troposphere, which increases the gross moist stability and thus the energetic demands for vertical motion. Finally, we investigate the influence of reduced vertical velocity variance on precipitation probability distribution and intensity.

How to cite: Xuan, Z., Kroll, C., and Jnglin Wills, R.: Future changes in tropical vertical velocity variance and precipitation variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10963, https://doi.org/10.5194/egusphere-egu24-10963, 2024.

EGU24-11244 | ECS | Orals | HS2.4.2

Inter-annual and long-term variability in streamflow elasticity to precipitation reveal bias in estimates of hydrological sensitivity 

Bailey Anderson, Louise Slater, Jessica Rapson, Manuela Brunner, Simon Dadson, Jiabo Yin, and Marcus Buechel

Empirically derived sensitivities of streamflow to precipitation are often assumed to be temporally unchanging. This assumption may be unrealistic because changes in climate and storage are known to alter this relationship. We present a non-stationary regional regression approach which is functionally similar to typical elasticity estimation approaches. This is applied to 2967 catchments in the United States to estimate variability in interannual, and trends in long-term, streamflow elasticity to precipitation over a 39-year period. We show that interannual elasticity is highly variable in water-limited catchments, indicating that these are especially sensitive to year-to-year climate variability, as compared to other regions. Interannual elasticity is more often correlated with the one-year lagged standardized precipitation index than with temperature or in-phase standardized precipitation index, suggesting that antecedent soil moisture, groundwater storage, and precipitation seasonality influence streamflow sensitivity. Finally, statistically significant long-term trends in elasticity exist in some regions, but trend magnitude is generally small. These findings suggest that an assumption of stationarity in long-term average elasticity may still be appropriate at the regional scale, however, year-to-year variation in streamflow responsiveness to precipitation is often substantial.    

How to cite: Anderson, B., Slater, L., Rapson, J., Brunner, M., Dadson, S., Yin, J., and Buechel, M.: Inter-annual and long-term variability in streamflow elasticity to precipitation reveal bias in estimates of hydrological sensitivity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11244, https://doi.org/10.5194/egusphere-egu24-11244, 2024.

EGU24-12189 | ECS | Orals | HS2.4.2

Surface and groundwater drought impact on natural vegetation growth and drought recovery. 

Jorge Vega Briones, Steven De Jong, Wiebe Nijland, and Niko Wanders

Droughts' persistent impact and growing use of surface water and groundwater will likely exacerbate hydrological droughts. Variations in precipitation patterns worsen the effects in particular catchment regions as a result to climate change. The end result is less groundwater recharge and multi-year droughts that impact vegetation and rivers.

An essential factor to better understand the recovery in catchments affected by drought is to understand the interaction between water availability and vegetation dynamics. At the same time, the vegetation recovery in terms of growth and productivity can also be assessed with this framework. In this study, we focus on natural catchments of central Chile which have experienced drought and multi-year drought periods with severe impacts on surface water and groundwater.

We collected 250 tree ring samples of 5 species that are susceptible to droughts in central Chile in natural catchments, and used CAMELS-CL for statistical analysis. Cross correlation analysis between surface, groundwater and vegetation dynamics was performed for each catchment to quantify the interaction between these factors. To further determine the influence of drought events on vegetation, the compound NDVI correlation and SPEI at a catchment level were used. Finally, the drought termination framework was applied to understand the recovery response of surface, groundwater and vegetation.

Our analysis identifies the typical time lag between droughts in surface water, groundwater and  their impact on vegetation growth. This is done on an annual time scale as we are looking at multi-year events. We find that the typical response time varies throughout the country, depending on the local natural water availability. These findings highlight that the multi-year drought impact on vegetation and its recovery is not uniform and should be better understand in light of climate change and the global increase in multi-year drought events.

How to cite: Vega Briones, J., De Jong, S., Nijland, W., and Wanders, N.: Surface and groundwater drought impact on natural vegetation growth and drought recovery., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12189, https://doi.org/10.5194/egusphere-egu24-12189, 2024.

EGU24-14039 | ECS | Orals | HS2.4.2

Historical changes in the seasonality and timing of extreme precipitation events 

Gaby Gründemann, Enrico Zorzetto, Nick van de Giesen, and Ruud van der Ent
Global warming alters the hydrological cycle, influencing the seasonality and timing of extreme precipitation events. Understanding historical changes in the occurrence of extreme precipitation is important for assessing their effects. This study examines the timing and seasonality of extreme precipitation using 63 years of ERA5 data. By using relative entropy, we can assess changes in extreme daily precipitation occurrence on the global domain. Findings show notable regional differences. In the second half of the 20th century, Africa and Asia had high clustering of extreme precipitation events. Over 60 years, clustering intensified in Africa but became more spread out in Asia. North America and Australia, initially with less clustering, saw slight increases. Extreme precipitation events in extra-tropical land regions mainly occurred in summer, with minor shifts in timing. These results are important for improving risk management for hazards like flash floods and landslides and highlight the need for region-specific strategies in adapting to these changes.

How to cite: Gründemann, G., Zorzetto, E., van de Giesen, N., and van der Ent, R.: Historical changes in the seasonality and timing of extreme precipitation events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14039, https://doi.org/10.5194/egusphere-egu24-14039, 2024.

EGU24-14414 | ECS | Orals | HS2.4.2

Navigating Hydroclimatic Extremes: Understanding the Interplay of Climate Change and Variability 

Achala Singh, Priyank J. Sharma, and Ramesh S. V. Teegavarapu

Increased frequency of extreme and rare hydroclimatic events leading to substantial disruptions in hydrological patterns worldwide can be attributed to climate variability and change. The stationarity assumption routinely used for hydrologic design and water resources planning is no longer valid under an evolving climate. Conventional notions about hydrological stability are now challenged, considering the intricate connection between climate fluctuations and the rising prevalence of extreme weather events. High spatial and temporal variability of extreme events in tropical and semi-arid climatic regions pose challenges in assessing non-stationarity considering available data and understanding processing contributing to short and long-term changes in regional climate. This study proposes and evaluates a novel approach using nonparametric statistical tests to explore the presence of non-stationarity in hydroclimatic extremes for a tropical river basin. Further, changes in the return levels of hydroclimatic extremes under stationary and non-stationary conditions will be carried out using statistical modelling approaches. Using the proposed approach, the identification of pivotal climatic drivers, such as oceanic oscillations and atmospheric circulation patterns, and their roles in influencing hydroclimatic extremes is possible. Long-term observational data is assessed in this work to discern trends and patterns in frequency, intensity, and spatial distribution of extremes and their links to climate change and variability. The impact of shifting precipitation patterns, temperature extremes, and seasonal variations is evaluated. This research study helps to investigate the implications of climate-induced hydroclimatic extremes under diverse geographical and climatic settings. This research can help understand the impact of climate change in river basins driven by the shifts in precipitation, temperature patterns, and extremes and address water availability and management issues.

Keywords: Non-stationarity, Hydroclimatic extremes, Climatic drivers, Statistical modelling, Tropical River basin.

How to cite: Singh, A., Sharma, P. J., and Teegavarapu, R. S. V.: Navigating Hydroclimatic Extremes: Understanding the Interplay of Climate Change and Variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14414, https://doi.org/10.5194/egusphere-egu24-14414, 2024.

EGU24-15120 | ECS | Orals | HS2.4.2

Groundwater storage trends in northern Italy as observed by GRACE, well measurements, and vertical land motion 

Grace Carlson, Christian Massari, Marco Rotiroti, Elisabetta Preziosi, Tullia Bonomi, Andrew Wilder, Susanna Werth, Destinee Whitaker, Tianxin Wang, Marianne Cowherd, and Manuela Girotto

Geodetic observations of the Earth’s gravitational and deformational response to changes in terrestrial water storage (∆TWS) have been essential measurements to identify regions experiencing long-term wetting and drying driven by a combination of climate and anthropogenic forces. The northern Italian Plains, home to a third of the country’s population and contributing more than half of the agricultural output, have experienced a dryer-than-normal two decades. Here, we investigate what impact these dry conditions have on the long-term groundwater storage (GWS) using observations of change in terrestrial water storage (∆TWS) from the Gravity Recovery and Climate Experiment (GRACE) and the second-generation follow-on (GRACE-FO) missions and in-situ groundwater level time series from 820 wells over the period of 2003-2022. We use a wavelet time-frequency analysis to deconstruct each signal into seasonal and long-term components and identify multi-year dry and wet epochs. We find two long periods of declining groundwater storage (2003-2007, 2015-2022), two short periods of groundwater recovery (2008-2009, 2012-2014), and one period of near-zero ∆GWS (2010-2011). We find a net volume loss of 12.0 km3 from 2003-2022. Further, we validate these ∆GWS trends and total volume loss estimates using a combination of in-situ groundwater level variations and vertical land motion observed at nearly 500 Global Navigation Satellite System (GNSS) stations. These stations show poroelastic deformation over aquifers related to groundwater storage changes and elastic loading deformation that is highly correlated with predicted elastic loading displacements from GRACE(-FO) ∆TWS outside of aquifer areas. To calculate groundwater storage from groundwater level, we estimate spatially- and depth-variable aquifer storage coefficients using a combination of lithologic information and co-located well and GNSS observations. By analyzing all three datasets in combination we can evaluate the impacts of multi-year dry- and wet- periods on groundwater resources, providing essential contextual information for future water management.

How to cite: Carlson, G., Massari, C., Rotiroti, M., Preziosi, E., Bonomi, T., Wilder, A., Werth, S., Whitaker, D., Wang, T., Cowherd, M., and Girotto, M.: Groundwater storage trends in northern Italy as observed by GRACE, well measurements, and vertical land motion, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15120, https://doi.org/10.5194/egusphere-egu24-15120, 2024.

EGU24-15252 | ECS | Orals | HS2.4.2

Spatiotemporal Variability in Hydrological Drought Recovery Time Estimations from GRACE and GRACE-FO Data  

Çağatay Çakan, M. Tuğrul Yılmaz, Henryk Dobslaw, Fatih Evrendilek, Christoph Förste, E. Sinem Ince, and Ali L. Yağcı

This study aimed to explore the global spatiotemporal variability in hydrological drought recovery time (DRT) estimated using terrestrial water storage (TWS) and station-based precipitation data. TWS data were gathered from the Gravity Recovery and Climate Experiment (GRACE) between April 2002 and June 2017 and GRACE Follow-On (GRACE-FO) between June 2018 and September 2023. The GRACE and GRACE-FO mascon (RL06) solution were used. Precipitation data were obtained from the Global Precipitation Climatology Project (GPCP) monthly analysis product. DRT was derived from the following two approaches: (1) TWS data via storage deficit and (2) TWS and precipitation data via absolute required precipitation. Storage deficit was computed as the negative deviation of detrended TWS from climatological values. Absolute required precipitation to fill the storage deficit was estimated from the linear relationship between the cumulative detrended smoothed precipitation anomalies (cdPA) and detrended smoothed TWS anomalies (dTWSA). The end of hydrological drought was assumed as when TWS deviation turned positive for the first methodology and as when observed precipitation exceeded absolute required precipitation for the second one. Mean DRT values across continents were obtained for both the GRACE and GRACE-FO periods, and the temporal variability between these periods was explored across different continents. On average, DRT estimate was 29% higher during the GRACE period (11.2 months) than during the GRACE-FO period (8.6 months). The TWS-based method (11.5 months) yielded 38% higher DRT than did the TWS- and precipitation-based one (8.3 months). Overall, Australia exhibited the highest DRT estimate (averaging 11.3 months) among all continents for both methods, whereas Europe showed the lowest one (averaging 8.6 months), with a global average of 9.9 months. Analysis of the temporal consistency between DRT estimates from both methods revealed that 28% of estimates aligned during the GRACE period, increasing to 49% during the GRACE-FO period. In particular, the highest consistency (61%) was observed over Africa during GRACE-FO period, contrasting with the lowest consistency (17%) over Australia during the GRACE period. Overall, the consistency between the DRT estimates from the two methods increased from the GRACE period to the GRACE-FO period across all the continents by 18% to 40%, except for Europe, where consistency dropped by 3%. These findings provide insights not only into the potential of TWS data in globally estimating DRT with significant consistency but also into understanding the dynamics of global hydrological droughts, thus proving beneficial in devising management strategies for water resources.

How to cite: Çakan, Ç., Yılmaz, M. T., Dobslaw, H., Evrendilek, F., Förste, C., Ince, E. S., and Yağcı, A. L.: Spatiotemporal Variability in Hydrological Drought Recovery Time Estimations from GRACE and GRACE-FO Data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15252, https://doi.org/10.5194/egusphere-egu24-15252, 2024.

EGU24-19475 | ECS | Orals | HS2.4.2

Long-term changes in water resources: the challenge of disentangling water management, climate change, and natural variability 

Vincent Humphrey, Marius Egli, Johanna Wittholm, Laura Jensen, Sebastian Sippel, Annette Eicker, Gionata Ghiggi, and Reto Knutti

Every year, natural climate variability leads to droughts and floods which have significant impacts for ecosystems and societies. Water reservoirs like soil moisture, lakes, and groundwater act as natural buffers and balance these fluctuations by providing water supply during dry conditions and by storing water surplus after rain and snow events. Such natural fluctuations unfold over time scales that can reach several decades, making it challenging to assess the extent to which trends in water reservoirs observed over the recent past are caused by anthropogenic modifications. Such modifications can themselves be further partitioned into different terms. For instance, one can contrast the contribution of regional land and water management on the one hand, and the contribution of climate change on the other. Another frequent framework is to causally relate changes in water storage to individual changes in precipitation, evapotranspiration, and runoff.

In this contribution, we review the strengths and weaknesses of recent approaches used to causally attribute observed as well as projected changes in water availability. Ensembles of model simulations and factorial experiments typically represent a powerful way of assessing individual responses to drivers and developing a plausible and mechanistic understanding. However, contradictions also quickly emerge between global hydrological model simulations, which typically represent water reservoirs and water management more thoroughly, and Earth system (climate) model simulations, which include biogeochemical effects, like CO2 fertilization, that are typically neglected by hydrological models. We will show that these two incomplete modeling worlds can be reconciled with large-scale satellite observations in only a few regions, while very large uncertainties remain in other parts of the world and in particular over tropical areas.

How to cite: Humphrey, V., Egli, M., Wittholm, J., Jensen, L., Sippel, S., Eicker, A., Ghiggi, G., and Knutti, R.: Long-term changes in water resources: the challenge of disentangling water management, climate change, and natural variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19475, https://doi.org/10.5194/egusphere-egu24-19475, 2024.

Several continental regions on Earth are getting wetter, while others are drying out not only in terms of precipitation but also measured by the increase or decrease in surface water, water stored in the soils, the plant root zone, and in groundwater. Drying and wetting as seen in terrestrial, space-geodetic and remote sensing data are generally ascribed to combined effects of global warming due to greenhouse gas forcing, natural variability, and anthropogenic modification of the water cycle. Existing climate models that account for these effects fail to explain observed patterns of hydrological change sufficiently. Contrary to common beliefs, observations also do not support a simple dry-gets-dryer and wet-gets-wetter logic. Instead, the observed trends, e.g. in precipitation, soil moisture, water storage, or flood discharge, differ considerably from a simplified logic.
The CRC 1502 DETECT, a collaborative research centre of the Universities of Bonn and Göttingen, the Geomar, the Research Centre Jülich and the German National Meteorological Service DWD, has been established by the German Research Foundation DFG with the objective of closing this gap of understanding. To better comprehend the origin of these patterns, DETECT  is developing a regional coupled modeling framework further that explains past observations as realistically as possible, accounts for potential drivers of change that may have been understudied in the past, and that can predict future changes. Our modelling framework is based on the TerrSysMP platform (i.e. the coupling of ICON/COSMO, CLM and ParFlow with/without data assimilation) and it ingests various conventional and new satellite and terrestrial data sets.
By applying this modelling framework to both historical and IPCC-type simulations, DETECT will test the hypothesis that humans – through several decades of land use change, and intensified water use and management – have caused persistent modifications in the coupled land and atmospheric water and energy cycles. It is hypothesized that (1) these human-induced modifications contribute considerably, compared to greenhouse gas (GHG) forcing and natural variability, to the observed trends in water storage at the regional scale, (2) land management and land and water use changes have modified the regional atmospheric circulation and related water transports and (3) these changes in the spatial patterns of the water balance have created and magnified imbalances that lead to excessive drying or wetting in more remote regions.
We test this hypothesis for the Euro-CORDEX region. In later phases, we evaluate the transferability of our approach for regions with different environmental conditions. We will develop evidence-based sustainability criteria for land and water use activities. The presentation will provide an overview on the central hypotheses and objectives of our research programme, the study logic and common approach, as well as anticipated results and contributions to the community. After two years, we highlight some first  findings.

How to cite: Siegismund, F. and Kusche, J.: Collaborative Research Centre 1502 DETECT: 'Regional Climate Change: Disentangling the Role of Land Use and Water Management', EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20232, https://doi.org/10.5194/egusphere-egu24-20232, 2024.

EGU24-20247 | Posters on site | HS2.4.2

Towards a coupled km-scale Atmosphere-Land Reanalysis for Europe 

Bernd Schalge, Jane Roque Mamani, Olaf Stein, Stefan Poll, Klaus Görgen, Jan Keller, and Arianna Valmassoi

Modelling studies in hydrology depend on a good representation of forcing data, in particular precipitation, for a good process representation, especially at the catchment  or sub-catchment scale. Forcing data is often provided through reanalysis, that use observations to obtain model states with the smallest possible errors and biases. Here, we present a prototype convection-permitting reanalysis system using a coupled atmosphere-land model system utilizing ICON-eCLM for the EURO-CORDEX domain at a resolution of 3km. Due to the high resolution it is expected that in particular precipitation will be better represented than in existing reanalyses, leading to more realistic forcing data. We analyzed precipitation and other near-surface observables from preliminary model runs and evaluated them in comparison to other widely used reanalysis products such as ERA-5 as well as to output of an ICON standalone simulation to assess potential improvements of the new reanalysis. We show potential use cases of the new reanalysis and discuss limitations of this dataset, which are related to the currently short available time series.

How to cite: Schalge, B., Mamani, J. R., Stein, O., Poll, S., Görgen, K., Keller, J., and Valmassoi, A.: Towards a coupled km-scale Atmosphere-Land Reanalysis for Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20247, https://doi.org/10.5194/egusphere-egu24-20247, 2024.

EGU24-21583 | ECS | Posters on site | HS2.4.2 | Highlight

Influence of ENSO on extreme precipitation and peak river flow in the US 

Natalie Lord, Simbi Hatchard, Jorge Sebastian Moraga, Nans Addor, and Pete Uhe

Flooding in the US results in billions of dollars of losses every year. This is projected to increase further in many regions as the climate warms, due to a combination of more frequent and severe extreme rainfall events, with resulting impacts on flooding, and increased exposure as the population increases and development in flood-prone areas continues. Superimposed on this warming signal are the impacts of different internal cycles operating within the climate system on various timescales, such as El Niño Southern Oscillation (ENSO). These cycles may act to either exacerbate or reduce the severity of extreme precipitation and flooding, and on interannual timescales, ENSO is a dominant mode of variability. A better understanding of the influence of ENSO and other modes of variability on extreme precipitation and flooding, including under climate change, is important for a number of applications. These include climate change impact assessments, policy and decision-making, early warning systems for flooding and disaster response planning, and climate-related risk planning in the (re)insurance sector.

Here, we investigate the influence of ENSO on extreme precipitation and peak river flow in the US, under both historical and future climate conditions. For the historical period, we calculate annual maximum (AMAX) daily precipitation and flow, from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) precipitation and USGS river gauge datasets, respectively. To assess whether positive, neutral, or negative phases of ENSO have a significant impact on extreme precipitation and flood magnitude, we calculate the correlation between AMAX and different ENSO phases. We use a number of different ENSO indices, including the Oceanic Niño Index (ONI) used operationally by NOAA, in order to test the sensitivity of these relationships to the method used to characterise ENSO.

We also assess the impacts of ENSO on projected future changes in AMAX precipitation, using climate model data from the Community Earth System Model Large Ensemble Project Phase 2 (CESM2-LENS). For this, we calculate the relative change in AMAX daily precipitation for positive, neutral, and negative phases of ENSO, to determine how projected extreme precipitation changes differ between the phases, and how this varies spatially across the US.

How to cite: Lord, N., Hatchard, S., Moraga, J. S., Addor, N., and Uhe, P.: Influence of ENSO on extreme precipitation and peak river flow in the US, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21583, https://doi.org/10.5194/egusphere-egu24-21583, 2024.

EGU24-466 | ECS | Orals | HS8.2.14

Combination of Multiple Investigation Methods to Reveal the Recharge Area of a Karst Aquifer 

Suleyman Selim Calli, Mehmet Celik, and Zehra Semra Karakas

Karst aquifers are heterogeneous groundwater systems having both diffuse and concentrated recharge mechanisms. Since their complex recharge, storage, and discharge characteristics, the groundwater divide is generally different from the topographical catchment borders. As a result, karst hydrogeologists are using different methods to obtain more certain recharge areas. Tracer tests are very important and preferred tools to obtain the groundwater recharge areas. An ideal tracer must be detectable in very low concentrations, conservative along the pathways, and cost-effective. In this manner, mineralogical analysis of the suspended particles would be a very good alternative to the isotopic, biochemical, and dye tracers due to the easy collection and cost-efficient analysis methods. In the present study, we collected rock samples from approximately 10 locations surrounding the potential recharge area of the karst aquifer covering all lithological units surrounding the study area. Then, we collected sediment samples at the discharge outlet of the karst spring and suspended particles by filtering the water samples. We analyzed both the sediments and rock samples by the petrographic thin-sections, XRD whole rock, and XRD-clay fraction analysis to compare the minerals between the rock and sediment samples. We obtained Eocene-aged Planktonic Foraminiferal fossils in the spring sediments (in the thin sections), which perfectly fit the Eocene-aged limestone formation in the study area. By overlapping the lithological outcrop of the formation with the isotope-derived recharge elevation, we obtained the locations of two major dolines in the study area. As the final step, we validated our results by conducting dye-tracer tests from these points, and we recovered the tracer dye from the karst springs.

How to cite: Calli, S. S., Celik, M., and Karakas, Z. S.: Combination of Multiple Investigation Methods to Reveal the Recharge Area of a Karst Aquifer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-466, https://doi.org/10.5194/egusphere-egu24-466, 2024.

EGU24-602 | ECS | Orals | HS8.2.14

Using contrasting tracers to characterize groundwater dynamics under a prolonged drought in the lowland catchments in the North German Plain 

Zhengtao Ying, Doerthe Tetzlaff, Jonas Freymueller, Jean-Christophe Comte, Tobias Goldhammer, Axel Schmidt, and Chris Soulsby

Groundwater, as the key strategic reserve in times of drought, is sensitive to climate change, especially unconfined, shallow aquifers. Frequent and prolonged drought provides an urgent impetus to improve understanding of groundwater dynamics and its residence times in drought-sensitive areas where water and food security are threatened. The Demnitzer Mill Creek catchment is a long-term environmental observatory typical lowland of North German Plain where streams are dominated by groundwater, however its groundwater recharge and dynamics remain poorly constrained. We applied water table observations, isotopic (δ18O, δ2H, 3H), hydrogeochemical, and geophysical investigations to characterize the spatial and temporal patterns of groundwater recharge in a shallow, unconfined aquifer system. Long-term groundwater levels showed a declining trend since 2011, which accelerated after 2018 resulting in increasingly intermittent seasonal streamflow. Geophysical surveys and groundwater monitoring indicated that shallow water tables (typically <3 m deep) in low to moderate permeability surficial deposits are generally recharged during winter, leading to higher groundwater – surface water connectivity in riparian alluvial aquifers, which is the first order control on streamflow generation. This was supported by similar geochemical characteristics of groundwater and streamflow. Water stable isotopes indicated a high damping in groundwater with a bias towards winter precipitation and direct recharge. Although 3H dating showed that the age of shallow groundwater was young (~5 years) and generally similar to streamflow, estimates had high uncertainty and some deeper groundwater was free of 3H. Such multiple approaches help understand changes in groundwater recharge and dynamics during droughts and contribute to the development of sustainable land and water management strategies for groundwater systems that are sensitive to climate change.

How to cite: Ying, Z., Tetzlaff, D., Freymueller, J., Comte, J.-C., Goldhammer, T., Schmidt, A., and Soulsby, C.: Using contrasting tracers to characterize groundwater dynamics under a prolonged drought in the lowland catchments in the North German Plain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-602, https://doi.org/10.5194/egusphere-egu24-602, 2024.

EGU24-1565 | ECS | Posters on site | HS8.2.14

Advancing in the estimation of effective recharge and its propagation in karst aquifers by combining soil moisture observations and the natural responses of springs. An example from Southern Spain. 

Alejandro Carrasco Martín, Matías Mudarra Martínez, Beatriz De la Torre Martínez, Andreas Hartmann, and Bartolomé Andreo Navarro

Improving our comprehension of infiltration processes in karst systems is crucial for a better adaptation to the global change regarding water resources availability and management. In this work, the effective recharge under different meteorological conditions and its transfer along the vertically distributed compartments of a geologically complex karst aquifer in southern Spain have been evaluated. Continuous records of soil moisture and temperature values (at 5 and 10 cm depth and the soil-rock transition -average depth of 28 cm-) have been combined with hourly hydrodynamic and hydrothermal responses recorded at two springs with a marked influence of the unsaturated zone (UZ) and the saturated zone (SZ), respectively.

Most rainfalls generate soil moisture signal in the shallowest probes. However, a mean increase of soil water content of 10.5% in summer (from background values of 2.5%) and 6.1% in autumn-winter (from 9.6%) at the soil-rock interface were needed to produce hydrodynamic responses in the system: first in the spring related to the UZ, with a time delay of 4-9 hours after moisture peaks, and then (14-18 hours) in the spring draining the SZ, but only during autumn-winter recharge events. In addition, recharge caused decreases (up to 0.9°C) in the temperature of the water drained by the first spring, while lagged rises (up to 0.6°C) occurred in the second outlet.

Transmission of the input signal would be favoured by stronger karstification, but the presence of inter-bedded detrital formations in the lithological sequence of the aquifer (partially confined in the SE border) filter and buffer groundwater flows before being drained by the spring related to the SZ. These findings will help to assess thresholds for effective infiltration and to predict groundwater recharge in karst aquifers under different climate change scenarios.

How to cite: Carrasco Martín, A., Mudarra Martínez, M., De la Torre Martínez, B., Hartmann, A., and Andreo Navarro, B.: Advancing in the estimation of effective recharge and its propagation in karst aquifers by combining soil moisture observations and the natural responses of springs. An example from Southern Spain., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1565, https://doi.org/10.5194/egusphere-egu24-1565, 2024.

In the epikarst zone of carbonate areas, numerous fractures have different sizes, shapes, and filling materials. Determining the fractures' horizontal hydraulic conductivity (Kh) simply using slug tests is challenging due to variable flow states (e.g., steady and unsteady). In this study, we characterized fracture features of apertures and soil fillings in terms of 260 fractures of 25 borehole logs at five sites in a karst area of southwest China. The Bouwer and Rice (B & R) solution and a numerical model were used to determine Kh based on the best fitting of observed water head in 105 slug tests. The results comparatively show that Kh from the B & R solution is significantly underestimated. For numerical modeling, the non-linear flow expressed by the Dupuit and Forchheimer equation can improve the water head fitting when the Reynolds number (Re) > 17.27. The optimized Kh ranges 0.014 – 2673 m/d. The mean value of Kh is about 100 times the median value, suggesting that epikarst flow might be controlled by a limited number of larger fractures. Expectedly, Kh exponentially increases with d, but three is a turning point for the fracture aperture d around 10 mm, Kh abruptly decreases due to soil filling. The hydraulic permeability in the naturally full-filling fractures resembles the soil matrix. In contrast, the partial-filling fractures can create preferential pathway with a high Kh around the soil-rock interfaces, allowing preferential flow in fractures. These results fundamentally improve our understanding of water infiltration, retention, and availability for plant uses. 

How to cite: Liu, X.: Estimating fracture characteristics and hydraulic conductivity from slug tests in epikarst of southwest China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2436, https://doi.org/10.5194/egusphere-egu24-2436, 2024.

EGU24-2828 | ECS | Orals | HS8.2.14

An ancient river disappears in a Mediterranean karst land: the old history of Cana River (Apulia, Southern Italy)  

Vito Cofano, Umberto Samuele D'Ettorre, Isabella Serena Liso, Domenico Capolongo, and Mario Parise

Apulia is one of the most interesting karst lands in the Mediterranean area, hosting a variety of distinctive surficial and underground landforms. Among these, polje, a wide and flat depression of tectono-karstic origin, represents one of the most typical epigean landforms in karst. The “Canale di Pirro” polje, located in the central part of Apulia (SE Italy), is the largest in the region (Pisano et al., 2020), bounded on both sides by tectonically-controlled ridges, with an overall length of some 12km and a remarkable underground system of caves, among which there is the deepest of Apulia, where the water table is reached at -264 m from the ground (Parise & Benedetto, 2018). As a karst land, within the polje the water rapidly infiltrates into the ground, making difficult its accumulation at the surface, with the exception of the period of heavy rainfall, when wide sectors of Canale di Pirro become temporary lakes which require several hours to days to be absorbed underground. In ancient documents and maps, with particular regard to historical cartography, the Canale di Pirro polje was drawn as being crossed by a long river, nowadays missing, called Cana (from this river, it seems that the same toponym of the polje took its name). The first written testimonies concern in particular a parchment dating back from the twelfth century; the more recent document we found, still showing the presence of the river, instead, is an ancient map of the nineteenth century. Considering the time span in which Cana River is still represented in historical writings and maps, it is possible to identify its existence between 1195 and 1840, and to hypothesize a presumed coincidance with the Little Ice Age, a climate interval characterized by a long cooling period, especially in the northern hemisphere. In this work, we present a series of historical documents about the existence of the Cana River, collected through literature research, in order to evaluate all the possible causes that led to the river disappearance over the centuries.

References

Parise M. & Benedetto L. (2018). Surface landforms and speleological investigation for a better understanding of karst hydrogeological processes: a history of research in southeastern Italy. In: Parise M., Gabrovsek F., Kaufmann G. & Ravbar N. (Eds.), Advances in Karst Research: Theory, Fieldwork and Applications. Geological Society, London, Special Publications, 466, p. 137-153, https://doi.org/10.1144/SP466.25.

Pisano, L., Zumpano, V., Liso, I. S., & Parise, M. (2020). Geomorphological and structural characterization of the ‘Canale di Pirro’ polje, Apulia (Southern Italy). Journal of Maps16(2), 479-487, https://doi.org/10.1080/17445647.2020.1778550.

How to cite: Cofano, V., D'Ettorre, U. S., Liso, I. S., Capolongo, D., and Parise, M.: An ancient river disappears in a Mediterranean karst land: the old history of Cana River (Apulia, Southern Italy) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2828, https://doi.org/10.5194/egusphere-egu24-2828, 2024.

EGU24-3029 | ECS | Orals | HS8.2.14

Application of anomalous transport modeling for karst aquifer discharge response to rainfall 

Dan Elhanati, Simon Frank, Nadine Goeppert, and Brian Berkowitz

Discharge in many karst aquifers exhibits distinctive long tails during recession that follow recharge events, a phenomenon often associated with the intricate flow paths that develop due to the underground structure of karst systems. This complexity poses a unique task from the perspective of modeling the flow and discharge patterns. In this study, we propose a novel approach to address long tail discharge during base-flow conditions, by adapting the continuous time random walk (CTRW) framework, known as a robust tool for modeling the long-tailed behavior observed in breakthrough curves of chemical species during transport, under diverse flow conditions. By establishing a theoretical analogy between partially saturated karst flow and chemical transport, we develop and implement a particle tracking (CTRW-PT) model that provides robust fits of three years of data from the Disnergschroef high alpine study site in the Austrian Alps, underscoring the predominance of slow diffusive flow over the rapid conduit flow. The agreement between measured and simulated data not only validates the proposed analogy between partially saturated karst flow and chemical transport but also highlights the utility of the CTRW-PT model, offering valuable insights and enhanced modeling capabilities for future research in this complex field.

How to cite: Elhanati, D., Frank, S., Goeppert, N., and Berkowitz, B.: Application of anomalous transport modeling for karst aquifer discharge response to rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3029, https://doi.org/10.5194/egusphere-egu24-3029, 2024.

EGU24-3143 | ECS | Posters on site | HS8.2.14

Geomorphological and hydrogeological features of submerged coastal sinkholes in the Apulian karst 

Michele Onorato, Raffaele Onorato, Isabella Serena Liso, Sergio Orsini, Pino Palmisano, Mario Parise, and Luca Zini

Low coastal karst is often characterized by widespread presence of sinkholes flooded by mixing of fresh and salt water. Such a mixture creates peculiar environments and ecosystems, at the same time predisposing the areas to possible hazards, in the form of formation of new sinkholes, or enlargement and coalescence of the existing ones through failures at their rims. This is definitely the situation for the south-western coast of Salento (Apulia, southern Italy), where the local karst setting is dominated at the surface by presence of flooded sinkholes, and by bays and inlets of circular shape along the coast. These latter are typically the result of coalescing processes of original individual sinkholes, which outer rim is eventually broken by the action of sea waves. Such a situation characterizes actually many other sites in the region, not only limited to the Ionian side but also involving the Adriatic coastine of Apulia, to the east (Liso & Parise, 2023).

In the coastal stretch extending from Torre Castiglione to Palude del Capitano, we have started a variety of activities, with further more on the way: among these, mapping of the sinkholes and interpretation of their mechanisms of formation, both along the coast and inland; identification of the main structural lineations, and of the likely control they exert on sinkhole development and evolution; monitoring of the physico-chemical parameters of the waters, with particular focus on those where upwelling of sulphureous waters has been observed; evaluation of the dissolution rate of carbonate rocks within the submerged areas; assessment of the sinkhole hazard, also in relation to the widespread presence of tourist sites, highly frequented during the summer season. Comprehension of the main flowpath of groundwater, from the inland areas toward the coast, is one of the main goals of our research, which is part of a wider project addressed also to evaluate the biological aspects in these peculiar, high biodiversity, ecosystems.

 

References

 

Liso I.S. & Parise M., 2023, Sinkhole development at the freshwater-saltwater interface in Apulia (southern Italy). In: Land L., Kromhout C. & Suter S. (Eds.), Proceedings of the 17th Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst, Tampa (Florida, USA), 27-31 March 2023, NCKRI Symposium no. 9, p. 229-238.

Parise M., Palmisano P. & Onorato R., 2017, Contributo alla conoscenza dei fenomeni carsici di collasso in zone costiere del Salento Jonico (Puglia): la Spunnulata della Pajara. Thalassia Salentina, n. 39, p. 99-121. 

How to cite: Onorato, M., Onorato, R., Liso, I. S., Orsini, S., Palmisano, P., Parise, M., and Zini, L.: Geomorphological and hydrogeological features of submerged coastal sinkholes in the Apulian karst, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3143, https://doi.org/10.5194/egusphere-egu24-3143, 2024.

EGU24-4793 | Orals | HS8.2.14

Changes in the residence time of a spring in a tectonic active zone of central Mexico 

Betsabe Atalia Sierra Garcia, Selene Olea-Olea, and Priscila Medina Ortega

The residence time of a spring located in central Mexico has been affected by seismic activity. The region is influenced by the interaction of five tectonic plates - Cocos, North American, Pacific, Rivera, and Caribbean - with convergent, divergent, and transform boundaries, leading to frequent earthquakes.

The spring, known as the name “Agua Hedionda”, has therapeutic properties due to sulfate concentrations exceeding 1 g/L that contributes significantly to the local economy. However, the earthquake of magnitude 7.1 in 2017 had a substantial impact, particularly on the flow quantity and sulfate concentrations, evidencing the vulnerability of the spring and, consequently, the community's economy.

To comprehend the vulnerability and changes in the spring, data of tracers (O-18, H-2, H-3, C-14), major ions and flow measurements were collected in 2022.Then, these data were compared with pre- and post-earthquake information.

Tracers facilitated the estimation of residence time for water reaching the spring, indicating a regional flow after the earthquake and an intermediate flow before and currently. The chemical and isotopic data suggest a mixing of flows.

Tectonic movements imply that the spring received water with a longer residence time compared to its original state. The combined analysis of these data in tectonically active areas offers valuable insights into changes in residence times, thereby understanding variations and the vulnerability of groundwater resources.

How to cite: Sierra Garcia, B. A., Olea-Olea, S., and Medina Ortega, P.: Changes in the residence time of a spring in a tectonic active zone of central Mexico, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4793, https://doi.org/10.5194/egusphere-egu24-4793, 2024.

EGU24-5158 | ECS | Orals | HS8.2.14

Flux tracking of groundwater via integrated modelling for abstraction management 

Leyang Liu, Marco Bianchi, Christopher Jackson, and Ana Mijic

In systems where surface water and groundwater interact, management of the water resource often involves conflicting objectives between water supply and baseflow maintenance. Balancing such objectives requires understanding of the role of groundwater in integrated water systems to inform the design of an efficient strategy to minimise abstraction impacts. This study first develops a reduced-complexity, processed-based groundwater model within the water systems integration modelling framework (WSIMOD). This model is applied to the Lea catchment, UK, as a case study and evaluated against monitored groundwater level and river flow data. A flux tracking approach is developed to reveal the origins of both river baseflow at a critical assessment point and abstracted groundwater across the systems. The insights obtained are used to design two strategies for groundwater abstraction reduction. Results show that the model has good performance in simulating the groundwater and river flow dynamics. Three aquifer bodies that contribute the most to the river baseflow in the dry season at the assessment point are identified; contributions being 17%, 15%, and 5%. The spatial distribution of abstracted groundwater originating from these aquifer bodies is illustrated. Compared to the default equal-ratio reduction, the strategy prioritising abstraction reduction in these three aquifer bodies increases a similar amount of baseflow (13%) by reducing much less abstraction (23%). The other strategy, which further decreases abstraction in the adjacent aquifer bodies, increases more baseflow (16%) with a similar abstraction reduction (30%). Both strategies can more efficiently improve the baseflow. The flux tracking approach can be further implemented to trace water from other origins, including runoff, stormwater, and wastewater, to enable coordinated management for better systems-level performance.

How to cite: Liu, L., Bianchi, M., Jackson, C., and Mijic, A.: Flux tracking of groundwater via integrated modelling for abstraction management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5158, https://doi.org/10.5194/egusphere-egu24-5158, 2024.

EGU24-6096 | Posters on site | HS8.2.14

Investigating the hydrological behaviour of a shallow karst aquifer flooding intermittently: the Pivka Karst Aquifer (Slovenia) 

Cyril Mayaud, Blaž Kogovšek, Metka Petrič, Nataša Ravbar, Matej Blatnik, and Franci Gabrovšek

The Pivka Karst Aquifer is a shallow karst aquifer located under the Upper Pivka Valley, about 40 km SW from Ljubljana (Slovenia). This aquifer is connected to the larger Javorniki Karst Aquifer that borders the Upper Pivka Valley on the NE. While the geometry of the conduit system in the Pivka Karst Aquifer is practically unknown, the geometry of the Javorniki Karst Aquifer is better characterized. Under low water conditions, water from the Pivka Karst Aquifer drains through the Javorniki Karst Aquifer towards the Unica and Malenščica Springs in the N, which are the terminal outlets of the region. Under high-water situations, the regional groundwater level rises up to 45 m, and the regional flow direction is modified. The Pivka Karst Aquifer receives water from the Javorniki Karst Aquifer which provides in the meantime autogenic water to the Unica and Malenščica Springs. The rise of water level in the Pivka Karst Aquifer result in the appearance of 17 intermittent lakes in the Upper Pivka Valley. This work aims establishing a conceptual hydrological model of the Pivka Karst Aquifer to better understand its interaction with the Javorniki Karst Aquifer. To do so, a network of automatic stations recording water level, specific electrical conductivity and water temperature at a 30 min interval has been progressively established in the Upper Pivka Valley since 2020. The four years dataset were analysed with data collected in the water active caves of the Javorniki Karst Aquifer and at the Unica and Malenščica Springs. The interpretation of water level records suggest that the Javorniki Karst Aquifer is a large recharge contributor of the Pivka Karst Aquifer, which act as an overflow of the whole system. However, the southern and western parts of the Pivka Karst Aquifer are also recharged locally. Such finding is supported by the analysis of specific electric conductivity data, which suggests the existence of several preferential flow paths in the Pivka Karst Aquifer that activate during flooding.

How to cite: Mayaud, C., Kogovšek, B., Petrič, M., Ravbar, N., Blatnik, M., and Gabrovšek, F.: Investigating the hydrological behaviour of a shallow karst aquifer flooding intermittently: the Pivka Karst Aquifer (Slovenia), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6096, https://doi.org/10.5194/egusphere-egu24-6096, 2024.

EGU24-6376 | ECS | Orals | HS8.2.14 | Highlight

Understanding groundwater chemistry and residence times of two thermal springs in east-central Mexico. 

Lorena Ramírez González, Oscar Escolero, Selene Olea-Olea, and Priscila Medina-Ortega

Thermal springs are natural discharge points that can offer valuable information on groundwater circulation. The use of tracers to determine residence times can help us understand complex hydrogeochemical processes despite limited data availability.

The present work aims to determine groundwater chemistry composition of two thermal springs located in east-central Mexico as well as understand some of the processes that may impact residence time estimation.

Tritium and carbon-14 tracers indicated a significant component of pre-modern water. Major ions data collected showed both springs have concentrations of HCO3- greater than 1,000 mg/l and temperatures around 41 °C. Saturation indices showed water-rock interaction with geological formations present in the area, such as limestone sequence ‘El Doctor’, that could influence groundwater residence time. Isotope data (δ18O) was used to determine a recharge elevation ranging from 2900 to 3000 meters above sea level. Additionally, SiO2 geothermometers were also applied to quantify circulation depth and reservoir temperature.

Analysis of hydrochemical composition, residence times, and any other information obtained from tracers, such as tritium and C-14, allows us to gain a better understanding of how groundwater systems work, along with a more accurate interpretation of results.

How to cite: Ramírez González, L., Escolero, O., Olea-Olea, S., and Medina-Ortega, P.: Understanding groundwater chemistry and residence times of two thermal springs in east-central Mexico., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6376, https://doi.org/10.5194/egusphere-egu24-6376, 2024.

EGU24-7450 | ECS | Posters on site | HS8.2.14

Spatial variability of lacustrine groundwater discharge at basin scale 

Xiaoliang Sun, Yao Du, and Yiqun Gan

Lacustrine groundwater discharge (LGD) is a crucial component of water balance in lakes. However, research on the spatial variability of LGD on a large basin scale is scarce, and the factors controlling this variability are not well understood. In this study, we examined various lakes located throughout the CYRB using multiple tracers and field surveys to determine the occurrence of LGD. We employed a 222Rn mass balance model to determine LGD rates in various lakes within the central Yangtze River basin (CYRB). Additionally, we identified the factors controlling the spatial variability of the LGD rates using correlation analysis and a multiple linear regression model. Our findings revealed that while the 222Rn concentration in groundwater (6082.27 ± 3860.16 Bq/m3) was within the global average, the concentration in lake water (306.97 ± 239.45 Bq/m3) was relatively high, indicating a stronger LGD in the CYRB. The stable isotopes, 222Rn concentration, and the groundwater seepage and springs, collectively confirm the occurrence of LGD. The LGD rates in lakes within the CYRB area exhibited significant spatial variability, ranging from 13.76 to 83.96 mm/d, with larger LGD rates found at the interior of the basin than at the edges. Hydrological connectivity, location within basin, and lake water depth collectively control the LGD rate, with each contributing 53.95%, 22.90%, and 23.16%, respectively. This study not only enriches our understanding of LGD, serving as a reference for global research on LGD, but also provides theoretical guidance for local water resource management.

How to cite: Sun, X., Du, Y., and Gan, Y.: Spatial variability of lacustrine groundwater discharge at basin scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7450, https://doi.org/10.5194/egusphere-egu24-7450, 2024.

Bedding plane partitions are an important geological medium to guide cave passages during the early stages of karstification in limestone formations. However, how stress load affects karst genesis processes along the large rough fractures remains poorly understood. Here, we develop a novel coupled hydro-mechanical-chemical (HMC) model to improve the understanding of this complicated process. This model considers a two-way mechanical-chemical coupling where dissolution perturbs the contact-stress distribution, in return impacting the fracture dissolutional enlargement. A non-linear correlation between the local fracture stiffness and contact stress is further incorporated. We study a two-dimensional horizontal fracture surface embedded in a three-dimensional rock block subjected to vertical stress loading. Simulation results show that dissolution causes local stress reduction (mechanical weakening), simultaneously accompanied by stress concentration at its fringe. The competition between dissolution-induced aperture enlargement and compaction-induced closure significantly retards the dissolution evolution. Without mechanical effect, linear dissolution fingering exhibits. As the applied stress increases, the secondary karstic conduits become more pronounced and a ramiform dissolution fingering featuring branching and winding is induced. Our results also provide important implications for understanding other engineering applications such as geothermal development and carbonate acidification.

How to cite: Jiang, C., Wang, X., and Jourde, H.: Stress-induced ramiform karstic conduits along a bedding plane: insights from a coupled hydro-mechanical-chemical (HMC) model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9657, https://doi.org/10.5194/egusphere-egu24-9657, 2024.

EGU24-9697 | ECS | Orals | HS8.2.14

Optimizing Water Storage in a Mediterranean Karst Aquifer: A Comprehensive Vadose and Phreatic Modeling Approach 

Lysander Bresinsky, Jannes Kordilla, Yakov Livshitz, and Martin Sauter

This study focuses on the role of karst aquifers in the Mediterranean Basin as a buffered storage of freshwater, especially considering the anticipated increase in drought periods due to climate change. Climate change underscores the need for innovative groundwater management approaches to maximize the storage capacity of these aquifers. This study emphasizes the importance of enhancing aquifer recharge during normal or high rainfall to mitigate the impacts of droughts. Notably, many karst aquifers in this region, which developed extensively during the lower base levels of the Messinian Salinity Crisis, exhibit a dual-domain flow pattern. This pattern consists of a slower flow through the rock matrix and a faster flow through conduits. Despite the rapid drainage of these mature karst systems, some, particularly those in the Mediterranean, are limited in their outflow to the sea by marine clay deposits, as highlighted by Bakalowicz (2015, Environmental Earth Sciences). These systems have shown a significant capacity for storage over several years.

In our study, we applied dual-permeability flow modeling to evaluate the storage potential of the Western Mountain Aquifer in Israel and the West Bank. The model utilizes the volume-averaged Richards' equation and integrates a term to account for the characteristic preferential infiltration in karst aquifers, even under nearly dry conditions. The model includes phreatic and vadose zone flows to comprehensively assess the storage capacities of the aquifer comprehensively. The results indicate that despite its advanced karst development, the Western Mountain Aquifer possesses a notable long-term storage capability. This is attributed to its extensive vadose zone and the restricted outflow, which is constrained by surrounding and overlying low-permeability formations (such as the Talme-Yafe, Negba, Daliya, and Menuha Formations, composed mainly of chalk and marl). The study explores various infiltration sites for managed aquifer recharge and considers current and future climatic conditions based on the RCP4.5 climate change scenario.

How to cite: Bresinsky, L., Kordilla, J., Livshitz, Y., and Sauter, M.: Optimizing Water Storage in a Mediterranean Karst Aquifer: A Comprehensive Vadose and Phreatic Modeling Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9697, https://doi.org/10.5194/egusphere-egu24-9697, 2024.

EGU24-11063 | ECS | Orals | HS8.2.14

Understanding the impacts of human wastewater effluent pollution on karst springs using chemical contamination fingerprinting techniques 

Luka Vucinic, David O'Connell, Donata Dubber, Patrice Behan, Quentin Crowley, Catherine Coxon, and Laurence Gill

Groundwater from karst aquifers is a major source of drinking water worldwide. These complex aquifer systems are exceptionally vulnerable to pollution and may be impacted by multiple contamination sources. Consequently, water contaminated with pollutants, such as microbial and chemical, from different sources can reach water sources used for human supplies (i.e. karst springs, boreholes, and wells that are being used for domestic purposes and/or irrigation).

In rural and suburban areas, human wastewater effluent (from on-site domestic wastewater treatment systems - DWTSs) and agricultural sources are generally considered among the most significant threats to groundwater quality. This is particularly of concern in Ireland given that more than one third of the population (>500,000 homes) use DWTSs. However, significant knowledge gaps exist with respect to linking contaminants with the origins of pollution and quantifying different pollution impacts on groundwater quality in karst environments.

The domestic wastewater is primarily discharged from toilets, washing machines, showers, and dishwashers, therefore, a wide range of contaminants (including source-specific contaminants) eventually reach the environment even after on-site wastewater treatment processes. We evaluated a range of chemical contamination fingerprinting techniques in terms of their ability to determine human wastewater pollution impacts on karst aquifers. Springs provide appropriate natural locations for monitoring pollutant concentrations in karst aquifer systems as they provide an integrated picture of contaminant transport through a karst conduit network, compared to wells and boreholes which are not necessarily directly connected to the most transmissive parts of the aquifer. Hence, nine separate karst springs in the West of Ireland (of varying catchment sizes) were studied and monitored over a 14-month period.

The results demonstrate how fluorescent whitening compounds (FWCs; well-known indicators of human contamination since their origin is mostly from laundry detergents), microplastic particles, and faecal sterols and stanols can be used together to cover different detectability chances, and provide useful information about DWTSs pollution impacts on karst springs. This study also provides an important benchmark for microplastic contamination in low-lying karst aquifer systems. Furthermore, a link between changes in FWCs signals and microplastic concentration changes in karst groundwater has been found, which indicates that the majority of microplastic particles originated from human wastewater sources. Unsurprisingly, the highest detection rates of FWCs and high concentrations of microplastic particles were found in karst catchments with very high densities of DWTSs and high percentages of DWTSs in the catchment that are within 200 m of at least one karst feature (such as swallow hole), indicating a direct pathway into the underlying aquifer. Moreover, the results suggest that while total sterol content in collected groundwater samples was generally low, faecal sterols and stanols can still be used as chemical faecal markers at karst springs.

How to cite: Vucinic, L., O'Connell, D., Dubber, D., Behan, P., Crowley, Q., Coxon, C., and Gill, L.: Understanding the impacts of human wastewater effluent pollution on karst springs using chemical contamination fingerprinting techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11063, https://doi.org/10.5194/egusphere-egu24-11063, 2024.

EGU24-11841 | Posters on site | HS8.2.14

Karst geomorphology, hydrogeology and caves in the areas of the Prespa Lakes, at the Albania-Macedonia-Greece border 

Mario Parise, Viacheslav Andreychouk, Isabella Serena Liso, Antonio Trocino, and Romeo Eftimi

The lakes of Prespa and Ohrid represent a very important hydrogeological system shared between Albania, FYR of Macedonia and Greece, and are the largest tectonic lakes in Europe. Prespa Lake is about 150 m higher in elevation than Ohrid, and the twos are separated by high mountains (Mali Thate, 2,287 m, and Galičica Mt., 2,262 m a.s.l.), built up during the Pliocene-Quaternary tectonic events. These mountains mainly consist of Upper Triassic–Lower Jurassic limestones, with wide graben to the E (Prespa) and the W (Ohrid). Pliocene clays, sandstones, and conglomerates fill most of the lakes. In 2002, an artificial tracer experiment physically demonstrated the underground connection between them (Amataj et al., 2007).

In the past, periodical oscillations of the level at Prespa Lake were in the 1-3 m range. After middle 1980’s, a steady decrease of water level has been recorded, producing serious disturbance to its ecological balance. Shape of Lake Prespa is quite irregular: the narrow sandy isthmus Gladno Polje separates it into Macro and Micro Prespa. In the recent past, Micro Prespa was a gulf of Macro Prespa, but then, due to erosion and sedimentation processes, the isthmus has been formed and the lakes separated (Popovska & Bonacci, 2007).

In this contribution we illustrate the main karst geomorphological characters, also providing updated information on its hydrogeology. In Galičica Mt. the most important surface karst forms are the Petrinska Plateau, a 20 km2 feature developed at elevation of 1500 m a.s.l., and the Samari blind valley, about 7 km long, in the NE part at about 1300–1400 m a.s.l. At least 12 high elevation caves have been documented, the longest being Samoska Dupka with length of 279 m. Numerous small caves are also situated along the Prespa Lake coastline near the villages of Stenie and Gollomboc; the longest is Treni cave (315 m long) at the W point of MicroPrespa Lake (Trocino et al., 2010). The Zaver swallow hole is situated at the Prespa W border, near Mala Gorica, with an extensive karst cave just uphill. Other smaller swallow holes are near Gollomboc; about in the same area, several caves of limited size (up to some tens of meters) are present, too. All these elements are important to describe the Prespa Lakes area as a sector of potential interest for further karstological studies, addressed to a better comprehension of the karst phases that interested this trans-boundary sector.

 

References

Amataj S. et al., 2007, Tracer methods used to verify the hypothesis of Cvijic about the underground connection between Prespa and Ohrid lake. Environ. Geol. 51 (5), 749-753.

Eftimi R., Stevanovic Z. & Stojov V., 2021, Hydrogeology of Mali Thate–Galičica karst massif related to the catastrophic decrease of the level of Lake Prespa. Environ. Earth Sci. 80, 708.

Popovska & Bonacci O., 2007, Basic data on the hydrology of Lakes Ohrid and Prespa. Hydrol. Proc. 21, 658-664.

Trocino A., Parise M. & Rizzi A., 2010, Ricerche speleologiche in Albania: primi dati sulle cavità nei pressi del lago di Prespa. XII Reg. Meeting Speleology “Spelaion 07”, 246-259.

How to cite: Parise, M., Andreychouk, V., Liso, I. S., Trocino, A., and Eftimi, R.: Karst geomorphology, hydrogeology and caves in the areas of the Prespa Lakes, at the Albania-Macedonia-Greece border, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11841, https://doi.org/10.5194/egusphere-egu24-11841, 2024.

EGU24-12200 | Orals | HS8.2.14

Data-driven approaches to infer transit time distributions from high-resolution tracer data 

Paolo Benettin, Quentin Duchemin, Maria Grazia Zanoni, Andrea Rinaldo, and James Kirchner

Catchment transit times are often inferred by assuming a transit time distribution (TTD) or a SAS function and calibrating their parameters against measured tracer data. In the presence of high-resolution tracer data, machine learning tools may offer a promising avenue for advancing TTD estimation by leveraging data-driven approaches, integrating diverse data sources, and improving accuracy, scalability, and adaptability. Here, we lump together ideas coming from Large Languages Models, survival analysis and sum of squares techniques to introduce a novel data-driven model for estimating TTDs. Our model is influenced by SAS-based approaches; however, unlike previous studies, we avoid imposing strong parametric assumptions on the SAS function. We showcase the performance of our model against a benchmark of eight virtual datasets that differ in precipitation amounts, seasonality and runoff flashiness. We find that machine learning methods may effectively predict solute concentration in streamflow yet struggle to accurately estimate the true TTDs. However, when the appropriate inductive bias is incorporated, numerous key aspects of TTDs, such as the young water fraction and the average TTDs, can be estimated robustly. We also identify settings where the estimation task is more challenging for our model. This analysis, based on reproducible virtual benchmarks, provides a first overview of machine learning capabilities in estimating TTDs and inspires future TTD model inter-comparisons.

How to cite: Benettin, P., Duchemin, Q., Zanoni, M. G., Rinaldo, A., and Kirchner, J.: Data-driven approaches to infer transit time distributions from high-resolution tracer data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12200, https://doi.org/10.5194/egusphere-egu24-12200, 2024.

EGU24-12814 | Posters on site | HS8.2.14

Helium-isotope data and groundwater ages of 700 shallow and deep groundwater sites in and around the Austrian Eastern Alps  

Martin Kralik, Heike Brielmann, Franko Humer, and Jürgen Sültenfuß

Groundwater ages provide valuable insights for water managers and users, helping them understand the timeframe required for water quality improvement measures to become effective and the timeframe in which groundwater bodies are renewed. To estimate groundwater ages in important shallow Austrian aquifers more than 700 tritium/helium-3 analyses and some tracer gas (CFC, SF6) investigations were conducted within the national groundwater monitoring and additional research projects. Noble gases 3He, He and 20Ne were measured at the Institute of Environmental Physics (IUP), University of Bremen, Germany and some at the Isotope Hydrology Section of the IAEA in Vienna, Austria. Groundwater ages vary across Austria and within groundwater bodies due to hydrogeological heterogeneities and depending on gradients of precipitation amounts and recharge rates. They range generally between 0 – 25 yrs. Tritium/helium-3 analyses are an essential tool for groundwater age estimation and the respective piston flow model ages of the shallow aquifers are mostly in the range of 0 – 15 years. However, the missing correlation with the sampling depth indicate partly an internal mixing in the observation wells due to large screen lengths.

The existent of elevated 4He-concentrations in aquifers with low background U and Th-content are good indicators of the admixture of old groundwater or just increased 4He-fluxes. The 4He concentrations range from air-equilibrium up to 1.6E-03 (cm3 STP /kg).  The 3He/4He- ratio decreases down to 8.0E-08. Preliminary studies of increased 4He-data with major tectonic fault zones indicate a positive correlation. Clear indications of the admixture of mantle helium were discovered at the end of Eastern Alps toward the western border of the Pannonian Basin.

 

[1]        Kralik, M., Humer, F., Fank, J., Harum, T., Klammler, D., Gooddy, D., Sültenfuß, J., Gerber, C., Purtschert, R. (2014): Using 18O/2H, 3H/3He, 85Kr and CFCs to determine mean residence times and water origin in the Grazer and Leibnitzer Feld groundwater bodies (Austria). Applied Geochemistry, 50 (2014), 150-163 http://dx.doi.org/10.1016/j.apgeochem.2014.04.001

[2]        Bundesministerium für Land- und Forstwirtschaft, Regionen und Wasserwirtschaft, Grundwasseralter 2009-2021, Wien (2022).

 (https://info.bml.gv.at/themen/wasser/wasserqualitaet/grundwasser/grundwasseralter2019-2021.html)

How to cite: Kralik, M., Brielmann, H., Humer, F., and Sültenfuß, J.: Helium-isotope data and groundwater ages of 700 shallow and deep groundwater sites in and around the Austrian Eastern Alps , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12814, https://doi.org/10.5194/egusphere-egu24-12814, 2024.

EGU24-13483 | ECS | Posters on site | HS8.2.14

Groundwater travel time distribution in the subsurface of a high energy beach – a multi tracer approach 

Rena Meyer, Janek Greskowiak, Anja Reckhardt, Stephan Seibert, Jürgen Sültenfuß, and Gudrun Massmann

In beach aquifers two water bodies, relatively old terrestrial freshwater and young oceanic saltwater mix, biogeochemical reactions change the solute composition of the water and groundwater discharge modifies element net fluxes to the ocean. Residence times are baseline information for the biogeochemical interpretation and help to understand groundwater flow and transport regimes. In the present study we used environmental tracers, i.e. apparent tritium-helium (3H/He) ages, temperatures and silica (Si) concentrations to derive groundwater ages and travel times in the subsurface along a cross-shore transect at the high energy beach aquifer on Spiekeroog, a barrier island in North-Western Germany. Recent generic modelling studies suggested that in beach aquifers under high energy conditions, characterized by high waves and tidal amplitudes as well as seasonal storm floods, flow and transport patterns in space and time are highly variable. As a consequence, the typical salinity and age stratification is distorted as compared to the classical stable concept of water bodies in beach aquifers derived from more embayed sites. To advance the understanding of such highly dynamic systems we obtained two sets of apparent 3H/He ages one year apart at three permanently installed multilevel wells each filtered in four depths (6, 12, 18, 24 m bgs), located at the dune base, near the mean high water line and near the mean low water line respectively. At the same locations, data loggers continuously recorded groundwater temperatures and were used to calculate travel times. In addition, Si was measured in samples taken every six weeks over one year. The results show relatively young apparent 3H/He ages in all samples, ranging from weeks to approximately 18 years. The water was youngest in the shallow part and near the high water line and ages increased with depth and towards the low water line and dune base. Interestingly, 3H/He ages vary significantly at some locations in the two data sets. Temperature derived travel times, representing the young water component (from the North Sea), overall agree well with the mixed apparent 3H/He ages. Si accumulating with time shows a similar trend. In the next steps, the results will help to constrain site specific groundwater modelling and support the interpretation of geochemical data and underlying processes in order to finally better understand the functioning  of high energy beach systems.

How to cite: Meyer, R., Greskowiak, J., Reckhardt, A., Seibert, S., Sültenfuß, J., and Massmann, G.: Groundwater travel time distribution in the subsurface of a high energy beach – a multi tracer approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13483, https://doi.org/10.5194/egusphere-egu24-13483, 2024.

Karst landscapes develop distinct surface landforms intricately connected to a more complex subsurface drainage system due to the highly soluble nature of its bedrock. Because of this, surface processes can more directly affect the groundwater system through conduits such as caves and sinkholes. Due to high hydraulic conductivity, aside from surface and groundwater, the soil produced from weathering and erosion of karst is also affected. Samcheok, found in southeastern Gangwon Province, is an example of an area that is underlain by limestone-bearing formations, allowing the formation of karst. In this study, the patterns in the hydrochemical characteristics of surface water and the land use of areas adjacent to the streams in Samcheok karst were explored through geospatial analyses. Additionally, recent land use change in the area was also investigated. Surface waters from four streams in Samcheok were analyzed: Osipcheon River, Yeosam Stream, Sohan Stream, and Gyogok River. Results show that hydrochemical parameters in northeast Samcheok karst are mostly varied and to an extent dependent on the stream where the samples were taken from more than the sampling distance from the coast. Usual patterns for pH and dissolved oxygen in terms of salinity were not observed. Concentrations of cations and anions mostly varied between the two sampling seasons (winter and spring for February and April 2020 samples, respectively) and were also varied in terms of linear correlation for concentration vs. distance to stream outlet graphs. High linear correlation was observed for spring samples from Gyogok River for the following ions: Ca2+ (R2 = 0.976), Mg2+ (R2 = 0.9321), SO42- (R2 = 0.879), and HCO3- (R2 = 0.955). More than 50% of the area adjacent to streams is classified as “other bare land”. Between 2019 and 2020, there was an increase in the total land area for coniferous forests and a decrease in mixed forest and undeveloped arable field. Research on geospatial patterns for hydrochemical parameters and land use change in environments susceptible to pollution such as karst areas are useful for land use planning and erosion studies. This research was funded by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (Nos. 2019R1I1A2A01057002, and 2019R1A6A1A03033167) and the Korea Ministry of Environment as "The SS (Surface Soil conservation and management)” project (No. 2019002820004).

How to cite: Lumongsod, R. M. and Kim*, H.: Geospatial patterns in surface water parameters and recent land use change in the karst of Samcheok, South Korea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13787, https://doi.org/10.5194/egusphere-egu24-13787, 2024.

The study of hydrogeochemical processes in Karst Critical Zone (KCZ) is of great significance for scientific understanding of their internal evolutionary environment and structural characteristics. Karst groundwater is the main information carrier after water-rock interaction. Quantitative analysis of its hydrochemical characteristics and causes is an effective means to reveal the medium environment and hydrodynamic conditions of aquifer system in KCZ. In this paper, three typical karst aquifer systems in the KCZ of central Yunnan Plateau are taken as the research objects. Through field sampling and laboratory testing of karst springs exposed by different aquifer systems, mathematical statistics analysis, hydrochemical diagram, ion ratio coefficient and hydrogeochemical simulation are comprehensively used to deeply analyze the characteristics of hydrochemical components, genesis and aquifer medium of karst groundwater in each aquifer system, and the internal relationship and law between water cycle and hydrochemistry in the key belt are discussed. The results show that : (1)  HCO3 and Ca2+ are the highest and stable ion components in regional karst groundwater, and Mg2+ is the key factor to control the alienation of hydrochemical types in each aquifer system ; (2)  The rock weathering and mineral dissolution of carbonate rocks are the main causes of the chemical composition characteristics of karst water in each aquifer system, and the karst groundwater dissolution on the aquifer of Huaning aquifer system is still occurring. The alternation of cation adsorption and the weathering and dissolution of silicate rocks are the main sources of Na+ and K+ in regional karst groundwater. (3)  The development intensity of regional karst, the exposed condition of karst aquifer and the lithology and connectivity of aquifer medium jointly shape the groundwater chemical characteristics of different aquifer systems in the KCZ of central Yunnan Plateau.

How to cite: Xu, M. and Huang, J.: Hydrochemical characteristics and genesis analysis of typical aquifer system in Karst Critical Zone of central Yunnan Platea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14478, https://doi.org/10.5194/egusphere-egu24-14478, 2024.

The characteristics of groundwater flow and solute transport in karst aquifers differ considerably from those in intergranular and fissured aquifers. To understand how they function, appropriately adapted hydrogeological research techniques and analyses are required. In this study, a binary karst aquifer in the recharge area of the Malenščica and Unica springs, which covers an area of about 820 km2 in southwestern Slovenia, was selected as the study area. A monitoring network was set up to obtain data on precipitation and discharge at the two springs, two sinking streams and two water-active caves in their catchment over a period of two hydrological years. First, a classical approach of correlation and spectral analysis of these time series data was applied to determine and compare the flow characteristics and storage capacity of selected springs and their recharge areas. The allogenic and autogenic recharges were considered separately as input functions and the results of the analysis were compared. Although these widely used methods provided a good characterization of the studied karst system, the interpretation can be ambiguous due to the interference of the two input components. To avoid this problem, an innovative method of partial cross-correlation analysis was used, which has previously only been applied to separate the influence of different precipitation stations in karst. Here, its application was extended to the evaluation of the influence of allogenic recharge. By controlling the input parameters precipitation and discharge of one of the sinking streams, it was possible to determine the contribution of the other sinking stream to the observed spring. The differences in the recharge characteristics of the Unica and Malenščica springs were revealed, and the ability of this innovative approach to provide additional insights into the functioning of binary karst aquifers was confirmed.

 

Key words: karst aquifer, autogenic and allogenic recharge, time series analysis, partial cross-correlation, Slovenia.

How to cite: Kogovšek, B., Jemcov, I., and Petrič, M.: Distinguishing between different sources of recharge in a complex binary karst aquifer: a case study of the Unica springs (SW Slovenia), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14951, https://doi.org/10.5194/egusphere-egu24-14951, 2024.

EGU24-15310 | ECS | Posters on site | HS8.2.14 | Highlight

Assessing tritium and persistent organic micropollutants as tracers for investigating surface and groundwater interaction in a large river system (Moselle River)  

Jessica Landgraf, Liza-Marie Beckers, Sabrina Quanz, Dirk Radny, and Axel Schmidt

Understanding the couplings of surface-groundwater interaction as well as their environmental impact is crucial for sustainable water management. However, water fluxes vary depending on external factors like water levels or heavy rain events and may alter the quantity and quality of surface and groundwater. As direct measurements of the ongoing mixing processes are challenging, various tracers are utilized to estimate water fluxes and transit times. Tritium as an environmental radioactive tracer introduced into the environment via nuclear bomb tests in the late 1950s has widely been used for water flux and transit time analyses. However, the tritium concentrations in surface waters in most regions declined to background concentrations due to the nuclear decay of tritium. Therefore, scientists are searching for alternatives like stable water isotopes or other chemical tracers to investigate surface-groundwater fluxes. Persistent organic micropollutants emitted into surface waters might present suitable alternative tracers.

The Moselle River has its source in the southern Vosges mountains and flows through France, along Luxembourg and through western Germany. The river contains high tritium concentrations (up to 50 Bq/l) induced by the French nuclear power plant Cattenom. Hence, tritium concentrations of the Moselle River surface water surpass the naturally abundant tritium concentrations ( ~1 Bq/l) found in groundwater reservoirs adjacent to the river. The German part of the Moselle River was monitored in 2020 to 2022 with monthly to quarterly intervals. Two spatially distributed sampling campaigns along the German Moselle River as well as continuous monthly investigations of a barrage site at Lehmen roughly 20 km upstream of Koblenz were conducted. The analysis of the water samples involves on-site parameters, cations, anions, metals, dissolved organic carbon, stable water isotopes, radon-222, tritium, and organic trace substances like pharmaceuticals. The study found significant surface-groundwater interaction at Lehmen. Thus, we evaluated correlations between tritium and detected organic micropollutants at this site. So far, seven organic micropollutants including the corrosion inhibitor benzotriazole and its derivative 5-methyl-1H-benzotriazole as well as the pharmaceuticals carbamazepine, lamotrigine, tramadol, candesartan and olmesartan were selected for this investigation. These pollutants enter the environment via wastewater release.

In this study, we explored the capability of tritium and persistent organic micropollutants tracers to reflect surface-groundwater interaction. So far, we compared the suitability of different organic micropollutants to reflect the observed water fluxes and transit time estimations with estimated results from tritium. Furthermore, we discuss the possible utility of benzotriazole or other organic compounds for future investigations of surface-groundwater-interaction.

How to cite: Landgraf, J., Beckers, L.-M., Quanz, S., Radny, D., and Schmidt, A.: Assessing tritium and persistent organic micropollutants as tracers for investigating surface and groundwater interaction in a large river system (Moselle River) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15310, https://doi.org/10.5194/egusphere-egu24-15310, 2024.

EGU24-18008 | Orals | HS8.2.14 | Highlight

Characterisation of drainage dynamics of karst landscapes over Europe 

Tunde Olarinoye, Nane Weber, Tom Gleeson, Vera Marx, Yan Liu, and Andreas Hartmann

Karst aquifers play a crucial role as water sources globally, with several European countries relying significantly on them for their water supply. Managing these aquifers is challenging due to their subsurface hydraulic heterogeneity. Hydrological modeling has proven valuable, offering insights into the hydraulic dynamics and management of karst water resources. However, characterizing karst drainage attributes at large catchment and regional scales remains challenging, hindering the incorporation of spatial heterogeneity and complexity in large-scale models and leading to unrealistic estimations in karst regions. This study addresses the issue by providing the first regional estimation of karst drainage attribute across Europe, this attribute is herein called Karstification Index (KI). Leveraging a newly developed automated karst spring recession analysis tool, and extensive climatic and physiographic datasets, we applied a regression-based regionalization model to estimate slow and quick flow parameters in karstic landscapes. By estimating KI as the ratio of quick to slow flow parameters, we were able to identify sub-regions with higher and lower degrees of karstification. Our findings highlight the significance of drainage density metrics, particularly in combination with specific climate signals, as predictors of KI. The regionalization model demonstrated high performance, validated by high R2 values, especially in well-gauged European catchments. Encouraged by these results, the analysis is being extended to a global scale, marking the first attempt to estimate karstic drainage attributes globally. We believe that this large-scale parameterization of karstification will enhance regional and global karst water resource management. By improving the parameterization and consideration of karst processes in large-scale hydrological models, our research contributes to a more accurate understanding of karst aquifers on a global scale.

How to cite: Olarinoye, T., Weber, N., Gleeson, T., Marx, V., Liu, Y., and Hartmann, A.: Characterisation of drainage dynamics of karst landscapes over Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18008, https://doi.org/10.5194/egusphere-egu24-18008, 2024.

EGU24-18110 | ECS | Posters on site | HS8.2.14

Monitoring of microfiber pollutants in karst environments 

Valentina Balestra, Adriano Fiorucci, Paola Marini, and Rossana Bellopede

Recent studies highlighted a preoccupant pollutant which impact natural environments: the microfibres. The term “anthropogenic microfibres” (MFs) includes fibres <5 mm in length of any composition (natural, regenerated and synthetic) derived from larger primary textiles manufactured for human use. MFs have been detected in different environments, as well as in human and animal organs, and adverse effects on animal health have been studied. Not-synthetic MFs have been often considered microplastics because of their colours, and because a lot of them are extruded and processed industrially. However, natural and regenerated fibres are a source of carbon for organisms, and are generally considered biodegradable. However, despite the general consensus on the reduced dangerousness of the not-synthetic fibres in the environment, little is known about their degradation in ecosystems. Their potential faster degradation could release toxic compounds into the environment, such as resins, dyes, and flame retardants. In addition, natural and regenerated textiles release more fibres than synthetic ones during laundering. All these factors may explain a long-term accumulation of MFs in the environment over time.

The Classical Karst Region represents important habitats characterized by the presence of dissolution feature in carbonate rock such as caves and sinkholes, which connect surface and subterranean environments. The Classical Karst waters played an important role for the development of this region: thanks to the high water quality, this area has been heavily exploited and was strongly altered by human activities, which irreversibly modified the hydrology of the system.

In this preliminary study we collected and investigated several water and submerged sediment samples in different caves and springs of the Classical Karst Region. MFs from 5 to 0.1 mm were counted and characterized by size, color and shape via visual identification under a microscope, with and without UV light. Spectroscopic analyses were carried out on 10% particles.

MFs were found in all samples, highlighting MF pollution in surface and subterranean habitats in the karst system. The 81% in water and 74% in submerged sediments were natural and regenerated fibres, while only 13% and 10% respectively were synthetics. The size distribution of collected MFs indicated that big MFs (1-5 mm) are less abundant (<22%). More than 80% of fibres were fluorescent under UV light. Of the fluorescent MFs, 91% were transparent; non-fluorescent MFs were mainly black and blue. Of the synthetic fibres, samples contained especially polyesters and copolymers.

Our results improve knowledge on micro pollutants in aquatic and karst environments, laying the foundations for future research. MF pollution monitoring in karst areas must become a priority for species protection, habitat conservation, and waters management, improving analyses on a larger number of aquatic environments, taking into account the ecological connections between surface and subterranean habitats.

How to cite: Balestra, V., Fiorucci, A., Marini, P., and Bellopede, R.: Monitoring of microfiber pollutants in karst environments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18110, https://doi.org/10.5194/egusphere-egu24-18110, 2024.

EGU24-18189 | ECS | Orals | HS8.2.14

Use of dissolved gases as tracers to study the impacts of floods and river works on Surface water – Groundwater interactions. 

Théo Blanc, Friederike Currle, Morgan Peel, Matthias S. Brennwald, Yama Tomonaga, Oliver S. Schilling, Daniel Hunkeler, Rolf Kipfer, and Philip Brunner

Alluvial aquifers have a significant potential for pumping large quantities of groundwater, essential for meeting drinking water needs. Abstracted water typically consists of a mix of regional groundwater and freshly infiltrated river water. A good understanding of surface water – groundwater interactions in these types of systems is required for managing both qualitative and quantitative aspects of riverbank filtration or river renaturations. Tracers are important tools in these contexts, as they provide crucial information on travel times and mixing ratios.

We present data from a comprehensive multi-tracer approach obtained in a field experiment conducted in a pre-alpine valley in central Switzerland. Over several months, river works were undertaken in an infiltrating river in the proximity of an important field of groundwater wells used for drinking water production. We investigated the impact of these river modifications on surface water - groundwater dynamics by monitoring the natural concentrations of (noble) gases with multiple potable mass spectrometers (miniRuedi, Gasometrix) and radon detectors (Rad7, Durridge). Additionally, we injected different noble gas species as artificial tracers both in the river and in groundwater and gained valuable insights into the evolving dynamics of the system.

The combination of these different tracers provided insights that could not have been obtained by a single tracer. Our results demonstrate that during and immediately after restoration works the infiltration of river water increases temporarily and provide insights about the time it takes for a riverbed to recover after restoration works and for river-groundwater interactions to reach a new dynamic equilibrium.

How to cite: Blanc, T., Currle, F., Peel, M., Brennwald, M. S., Tomonaga, Y., Schilling, O. S., Hunkeler, D., Kipfer, R., and Brunner, P.: Use of dissolved gases as tracers to study the impacts of floods and river works on Surface water – Groundwater interactions., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18189, https://doi.org/10.5194/egusphere-egu24-18189, 2024.

EGU24-19597 | ECS | Orals | HS8.2.14

Simulation of Carbonated Fault Zones Hydrodynamics and Transport Considering Parametric and Predictive Uncertainty 

Boura Aurelie, Cousquer Yohann, Clauzon Victor, Valois Rémi, and Leonardi Véronique

Hydrodynamic understanding of karstic aquifers is a real challenge due to the complexity of their internal structures. However, their societal significance lies in the substantial quantity of groundwater resources they embody. Among these complexities, faults partially control the organization of flows in these systems. The nature of this control can either facilitate rapid flow transfer or act as a barrier, impacting both groundwater quality and quantity. Understanding the behavior of fault zone features is crucial for efficiently management of karstic aquifer resources. However, there is a lack of studies that estimate and simulate flow within fault zones. In this study we estimate the hydraulic properties of the fault zone within carbonate karstic aquifers for flow and transport forecasting purposes based on cross-hole pumping tests simulation and inversion. The flow and transport are modeled using MODFLOW6 and MODPATH7. The inverse modeling approach is based on the Gauss-Levenberg-Marquardt Algorithm (GLMA) and the Iterative Ensemble Smoother (IES) integrated into the PEST++ code. Initially, we applied and validated the approach on a synthetic fault zone and subsequently on a real case studies within karstic carbonate aquifers of interest (Lez aquifer, Montpellier (France)). The inverse modeling approach has proven efficient in exploring hydrodynamic properties and then obtained both flow and transport forecasts with a satisfactory level of uncertainty. These works contribute to a better understanding of the hydrodynamic aspects of fault zones in carbonate environments through an innovative approach specific to its application. This study offers a reproducible method to understand and quantify hydrodynamics in aquifer in general and carbonated aquifer fault zones in particular. This improvement enhances the management strategies for groundwater resources in carbonated aquifers.

How to cite: Aurelie, B., Yohann, C., Victor, C., Rémi, V., and Véronique, L.: Simulation of Carbonated Fault Zones Hydrodynamics and Transport Considering Parametric and Predictive Uncertainty, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19597, https://doi.org/10.5194/egusphere-egu24-19597, 2024.

EGU24-20334 | ECS | Orals | HS8.2.14

Conclusions from an IAEA Meeting on the sample preparation and measurement of radio sulfur in natural water samples 

Stephen Kamau, El Mostafa Amghar, Richard Bibby, Lorenzo Copia, Laura Coulson, Sandra Damatto, Astrid Harjung, Juergen Kopitz, Martin Kralik, Bradley McGuire, Michael Schubert, and Stefan Terzer-Wassmuth

Research on groundwater residence times is essential for evaluating groundwater abstraction rates and aquifer vulnerabilities, and hence, for sustainable water resources management. Naturally occurring radionuclides are suitable tools for related investigations. While the applicability of several long-lived radionuclides for the investigation of long-term processes has been demonstrated frequently, tracer-based approaches for studying residence times of less than one year have not been fully exploited. That is due to the rather small number of applicable radionuclides that show adequately short half-lives. A promising approach for investigating sub-yearly residence times applies radioactive Sulphur (35S). Radio-Sulphur is naturally produced by high-energy cosmic radiation in the upper atmosphere from where it is transferred with precipitation to the groundwater. As soon as the meteoric water enters the subsurface its 35S activity concentration decreases with an 87.4-day half-life. This makes 35S suitable for investigating sub-yearly groundwater residence times. However, the low 35S activities in natural waters require sulphate pre-concentration for 35S detection by means of liquid scintillation counting. This is done by sulphate extraction from large water samples with anion-exchange resins or/and precipitation as BaSO4. The resulting samples are usually associated with background interferences and quenching. The presented experiments aim at (i) optimizing the sample preparation procedure by simplifying the pre-concentration of sulphate to make it applicable for field sampling and at (ii) reducing quench and background during measurement. We will discuss the different sample preparation methods and lessons learned for the detection and quantification of 35S pre-concentrated from natural water samples that contain a wide range of SO42− concentrations.

How to cite: Kamau, S., Mostafa Amghar, E., Bibby, R., Copia, L., Coulson, L., Damatto, S., Harjung, A., Kopitz, J., Kralik, M., McGuire, B., Schubert, M., and Terzer-Wassmuth, S.: Conclusions from an IAEA Meeting on the sample preparation and measurement of radio sulfur in natural water samples, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20334, https://doi.org/10.5194/egusphere-egu24-20334, 2024.

During flood events, due to extreme hydraulic loading in recharge areas of aquifers, groundwater flow dynamics can change, causing a risk of pathogens being flushed into aquifers used for drinking water supplies. Extreme flood events, as they are increasingly experienced with climate change, have potential to cause impacts not seen before, and drinking water sources that were free of pathogen contamination in the past may become contaminated in the future.

As an example, in the Heretaunga Plains, Hawkes Bay, contaminated water from heavy rain inundated paddocks entered an unconfined part of the aquifer and drinking water wells in it, resulting in >6260 cases of illness including 42 hospitalizations, and Campylobacter infection contributed to at least four deaths.

Most of the c. 30 drinking water wells in the Heretaunga Plains, including those supplying the cities of Hastings and Napier, are, however, in the confined part of the aquifer and these were not affected by pathogen contamination. But will more extreme flood events, predicted with climate change, eventually also compromise drinking water sources in the confined aquifer which were deemed safe in the past? Wells in the confined aquifer have shown indications of changing groundwater flow dynamics, for example variable water age, and changing hydrochemistry after flood events, which might be associated with younger water, bearing the risk of pathogen intrusion.

On 13 and 14 February, 2023, Cyclone Gabrielle lashed Hawke’s Bay, with record rainfalls causing rivers to burst their banks causing a death toll of 11. To improve understanding of the impact of the extreme hydraulic loading on the aquifers through such events, specifically changes to the water flow dynamics with potential for new, previously unrecognised contaminant pathways and associated risks for drinking-water supply wells, we measured age-tracers in selected wells again, two months after Cyclone Gabrielle. Comparing the results of this survey with age-tracer data from just three months prior to the cyclone provided an opportunity to test how extreme events like
Cyclone Gabrielle change groundwater flow dynamics in confined aquifers.

On 12 and 13 April 2023 we re-sampled for age tracers a selection of drinking-water supply wells in partnership with Hastings District Council and Napier City Council, and of private and monitoring
wells in the central and marginal confined parts of the aquifer system in partnership with
Hawkes Bay Regional Council.

The data indicate that groundwater ages in these wells have not changed significantly because of Cyclone Gabrielle. The wells that showed slight changes in age-tracer concentrations consistently showed older water after Cyclone Gabrielle. Other wells, despite showing no detectable changes in age-tracer concentrations, contained water that was more evolved after the cyclone, indicated by decreased dissolved oxygen and elevated methane, ammonia, and phosphorous concentrations.

These observations all point toward older (probably deeper) groundwater having been
pushed into the active groundwater flow paths by the increased hydraulic loading. With no younger water detected in the investigated wells following Cyclone Gabrielle, there is no indication of increased risk of pathogen contamination in the confined aquifer system following extreme flood events.

How to cite: Morgenstern, U.: Did Cyclone Gabrielle increase the risk of pathogen contamination for drinking water supply wells in the confined aquifer of the Heretaunga Plains, New Zealand?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20783, https://doi.org/10.5194/egusphere-egu24-20783, 2024.

EGU24-772 | ECS | Orals | HS7.8

Exploring Precipitation Intensity-Duration-Area-Frequency Patterns using Weather Radar Data  

Talia Rosin, Efrat Morin, and Francesco Marra

Extreme precipitation is the main trigger of hazardous phenomena such as floods and flash-floods, that pose a serious threat to human beings and livelihood worldwide. Extreme precipitation is highly variable in both space and time, thus understanding and managing the related risks necessitates improved knowledge of their probability at different spatial-temporal scales.

We employ the simplified metastatistical extreme value (SMEV) framework, a novel non-asymptotic framework, to estimate extreme return levels (up to 100 years) at multiple temporal (10 min–24 h) and, for the first time, spatial (0.25 km2–500 km2) scales using weather radar precipitation estimates. The SMEV framework reduces uncertainties and enables the use of relatively short archives typical of weather radar data (12 years in this case).

Focusing on the eastern Mediterranean - a region characterised by sharp climatic gradients and susceptibility to flash floods - we derive at-site intensity-duration-area-frequency relations at various scales. Comparison with extreme return levels derived from daily rain gauge data over areas with dense gauge networks yields comparable results, demonstrating that radar precipitation data can provide important information for the understanding of extreme precipitation climatology.

We then examine the climatological differences in extreme precipitation emerging from coastal, mountainous, and desert regions at different spatial and temporal scales. Three key findings emerge:

  • At the pixel scale, precipitation and duration exhibit simple scaling, but this relationship breaks down with increasing area - this has significance for temporal downscaling.
  • Precipitation intensity is dissimilar for different area sizes at short durations but becomes increasingly similar at long durations - thus areal reduction factors may be unnecessary when computing precipitation for long durations.
  • The reverse orographic effect causes increased precipitation for multihour events and decreased precipitation for hourly and sub-hourly durations; however, this phenomenon decreases over larger areas.

How to cite: Rosin, T., Morin, E., and Marra, F.: Exploring Precipitation Intensity-Duration-Area-Frequency Patterns using Weather Radar Data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-772, https://doi.org/10.5194/egusphere-egu24-772, 2024.

EGU24-1126 | ECS | Posters on site | HS7.8

Intercomparison of Different Automatic Threshold Selection Methods in Modelling Precipitation Extremes via Peak Over Threshold Model 

Sree Anusha Ganapathiraju and Maheswaran Rathinasamy

The peak-over-threshold (POT) model is the most extensively used for regional precipitation frequency analysis (RPFA) for estimating extreme precipitation events (EPEs). Yet, choosing proper threshold values is critical and challenging while estimating rainfall quantiles for the Indian subcontinent due to the diverse climatic conditions and physical barriers. This study investigates and compares various threshold methodologies, including graphical, analytical, and multiple threshold methods (MTM) for identifying EPEs. These extracted extreme events with high thresholds followed the Generalized Pareto distribution (GPD), whose shape and scale parameters remain constant and increase linearly with increased threshold values. Therefore, the POT-GPD model was employed in the current work, and the parameters were estimated using L-moments to explore and quantify the heavy tail behavior. In addition, the uncertainty associated with the quantiles was also evaluated using nonparametric bootstrapping techniques and later understanding the spatial variability of the GPD parameters from various methods. The effectiveness of the models is assessed on daily gridded precipitation datasets for the Indian region and validated using synthetic datasets generated through Monte Carlo simulations. Results reveal the importance of combining the MTM and analytical threshold methods for identifying a range of critical thresholds to overcome the subjectivity of graphical methods and quantify the uncertainty. These findings contribute to developing region-specific thresholds, highlighting the importance of modifying thresholds to the regional characteristics rather than relying on a fixed percentile for characterizing the EPEs. The proposed approach is essential for assessing the increasing intensity and frequency of precipitation extremes associated with climate change while allowing for more focused mitigation actions and disaster risk reduction.

How to cite: Ganapathiraju, S. A. and Rathinasamy, M.: Intercomparison of Different Automatic Threshold Selection Methods in Modelling Precipitation Extremes via Peak Over Threshold Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1126, https://doi.org/10.5194/egusphere-egu24-1126, 2024.

EGU24-1997 | ECS | Orals | HS7.8 | Highlight

Spatial coherences of flood-generating processes in Europe and their impact on flood statistics 

Svenja Fischer and Andreas Schumann

Flood events in Europe are caused by different generating mechanisms that lead to events with different peaks, volumes and hydrographs. Understanding such mechanisms is crucial not only for deterministic or stochastic modelling of floods, but also for practical purposes such as hydrological planning and design estimation. In this study, driving mechanisms of floods are analysed and the associated catchment and atmospheric attributes controlling these flood types are identified through a classification and regression tree approach. In addition, the role of flood types in flood statistics is analysed using type-based flood statistics. It is shown which flood types dominate the more frequent floods and which flood types are most frequently associated with extreme floods. Ordinary and extraordinary floods are identified by a Likelihood-Ratio test and tested for a significant difference in the frequency distribution of flood types. Our results show that the flood types vary regionally in Europe. In the Alpine region, heavy rainfall floods are responsible for the most extreme flood events, while in the northern parts of Europe flood events caused by snowmelt lead to the largest peaks. This is reflected in the flood statistics in the type-specific distributions, which have a different tail heaviness. These findings provide information to identify the most crucial circumstances in which floods become extreme and on the flood event itself.

How to cite: Fischer, S. and Schumann, A.: Spatial coherences of flood-generating processes in Europe and their impact on flood statistics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1997, https://doi.org/10.5194/egusphere-egu24-1997, 2024.

EGU24-2195 | ECS | Posters on site | HS7.8

Examining Daily Snow Depths at the Catchment Scale in Canada Using CMIP6 

Hebatallah Abdelmoaty, Simon Papalexiou, Abhishek Gaur, and Yannis Markonis

The lack of reliable data on daily snow depth (SD) is a significant challenge for studying water systems, ecology, and resources. Climate models present a potential solution for generating daily SD data, but the literature has not thoroughly explored how accurately they simulate this data. This study investigates the capabilities of CMIP6 climate models to replicate daily SD characteristics in eleven major Canadian catchments. The results depict that CMIP6 simulations overestimate the average SD values by a median of 57.7% (6.9 cm). In the Arctic and Pacific regions, this overestimation becomes particularly pronounced. However, the simulations align more closely with observations in smaller catchments with homogenous land characteristics. This finding suggests a shortcoming in how these models simulate different land types within the grid. Additionally, the models appear to overestimate the snow cover duration, with a median underestimation of 30.5 days. This overestimation could be due to the models failing to accurately account for the rates at which snow accumulates and melts away. However, the models perform relatively well when predicting extreme SD conditions. This study carries valuable implications for refining the outputs of climate models and effectively utilizing them in impact studies.

How to cite: Abdelmoaty, H., Papalexiou, S., Gaur, A., and Markonis, Y.: Examining Daily Snow Depths at the Catchment Scale in Canada Using CMIP6, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2195, https://doi.org/10.5194/egusphere-egu24-2195, 2024.

EGU24-2908 | Posters on site | HS7.8

Modeling drought effects on rainfed crop yields using probabilistic and machine learning approaches 

Clement Sohoulande and Prakash Khedun

Drought is a major hazard with significant impacts on agriculture, water resource availability, and terrestrial ecosystems. Under climate change drought events are expected to increase in frequency, severity, duration, and propagation with consequent impacts on crop yields. Given these circumstances, a thorough understanding of drought is needed to increase societal preparedness to drought effects on food production particularly in regions where agriculture is dominantly rainfed. Unfortunately, drought events remain very unpredictable suggesting the need to enhance the understanding of drought effects on rainfed crops. Hence, this study aims to examine the relationships between drought characteristics and rainfed crop yields. Particularly, the study uses probabilistic and machine learning (i.e., random forest) approaches to investigate the influence of standardized precipitation and evapotranspiration index (SPEI) severity and duration on the yield of corn, cotton, peanuts, and soybeans in the southeast region of the United State (US). County wise analyses were conducted for three contiguous southeastern States including North Carolina, South Carolina, and Georgia. Preliminary results outlined different performances depending on the approach, the counties, and the crops. Highly performing approaches could be considered for modeling drought effect on crops at county, State, or regional levels.

How to cite: Sohoulande, C. and Khedun, P.: Modeling drought effects on rainfed crop yields using probabilistic and machine learning approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2908, https://doi.org/10.5194/egusphere-egu24-2908, 2024.

EGU24-2918 | Orals | HS7.8 | Highlight

Spatio-temporal clustering of storm surges along the global coastline 

Thomas Wahl, Alejandra Enriquez, and Ariadna Martin

When storm surges often affect the same coastline stretches simultaneously (i.e., they cluster in space, leading to spatial compounding) or if they occur in close succession (i.e., they cluster in time, leading to temporal compounding), the impacts are often greatly amplified. Hurricanes Irma and Maria in 2017 in the eastern Caribbean and Hurricanes Ian and Nicole in Florida were recent reminders how back-to-back storm surges affecting long coastline stretches can cripple economies and societies which are still in recovery mode. This can be a significant burden for the (re-)insurance industry and government budgets, as has been shown for the case of river floods (Jongman et al., 2014). Despite many examples where spatial or temporal compounding effects worsened coastal flooding impacts, developing appropriate tools to incorporate such events into present-day and future coastal flood impact assessments and hazard mitigation planning is still at its infancy. This presentation will showcase a novel algorithm to identify independent storm surge events and preliminary results from applying it to a global tide gauge data set to detect hotspots of temporal storm surge clusters at different time scales and different levels of extremeness. Results from identifying spatial storm surge footprints along the global coast and associated non-stationarity (for selected coastline stretches) will also be presented. The latter will be linked to large-scale weather patterns causing shifts in the spatial footprints at seasonal to decadal time scales. The results can inform the development of flexible statistical models capable of capturing both spatial and temporal dependences to overcome existing limitations in flood risk assessments where this is typically ignored.

How to cite: Wahl, T., Enriquez, A., and Martin, A.: Spatio-temporal clustering of storm surges along the global coastline, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2918, https://doi.org/10.5194/egusphere-egu24-2918, 2024.

EGU24-5024 | ECS | Posters on site | HS7.8

Time Varying Copula based formulations for Flood Risk Assessment of two Tropical basins of Kerala, India 

Adarsh Sankaran, Meera G Mohan, Ananya Raj, and Anagha Shaji

Flood frequency analysis is a challenging but essential hydrologic problem for design of control structures and water resources management. The design flood estimates based on traditional stationary assumption may lead to inaccurate estimation of flood risk because of non-stationarity and the compounding impacts of several drivers in a dynamic environment. Copulas are a useful and adaptable technique for determining the multivariate joint dependency amongst flood variables. This study employed time-varying copula models to investigate the nonstationary dependence structures between two highly correlated flood variables, such as flood peak and flood volume, in order to determine the joint and conditional return periods of the flood events revealed by the 2018 Great Kerala floods. The proposed approach is executed for two potential locations of high flood risk namely, Periyar river basin and Greater Pamba river basin of Kerala, India. The Archimedean copula (Clayton, Frank and Gumbel) parameters were estimated using Maximum likelihood estimation and the optimal copula selection was made using Akaike Information Criterion. The non-stationary joint return time was found to be shorter than the stationary joint return period, suggesting that the extreme flood occurrences happened more frequently in the non-stationary bivariate study. Thus, it can be demonstrated that the extreme flood episodes are underestimated by stationary bivariate flood frequency analysis. The validation of results by comparing the flood magnitude of Neeleswaram station for 2018 flood quantile ascertained the necessity of non-stationary flood risk estimation. The study advocates the conduct of multivariate frequency analysis over the univariate analysis for the risk assessment of hydrological extremes. The results demonstrate that the long-term decision-making methods need to be updated to account for the oddities of the nonstationary climate. This study rendered flood risk assessment indicators as well as a risk-based design approach for hydraulic infrastructures in a non-stationary environment, which is crucial for climate change adaption and water security management.

How to cite: Sankaran, A., Mohan, M. G., Raj, A., and Shaji, A.: Time Varying Copula based formulations for Flood Risk Assessment of two Tropical basins of Kerala, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5024, https://doi.org/10.5194/egusphere-egu24-5024, 2024.

EGU24-5234 | ECS | Posters on site | HS7.8

Metereological Drought in the western Po river basin: trends and characteristics from 1958 to 2023 

Emanuele Mombrini, Stefania Tamea, Alberto Viglione, and Roberto Revelli

Since the start of the 21st century, greater focus has been put on drought and its wide range of environmental and socioeconomic effects, particularly in the context of climate change. This is especially true for the North-western region of Italy, comprising the Piedmont and Aosta valley, which have been affected in recent years by droughts that have had acute effects on water resources and water security in all sectors, including agriculture, energy and domestic use. The region also belongs to the Mediterranean hot-spot, characterized by faster than global average warming rates and higher vulnerability to their effects. Therefore, characterizing the observed changes and trends in drought conditions is of particular significance. To this end, 60 years of precipitation and temperature data from the North West Italy Optimum Interpolation data set are used to calculate the drought indices SPI (Standardized Precipitation Index) and SPEI (Standardized Precipitation Evapotranspiration Index) at a shorter (3-month) and at a longer (12-month) time scale. First, trend analysis on precipitation and temperature is performed, finding limited areas with significant precipitation decrease and, conversely, a general temperature increase over the region, with higher values found in the higher elevation areas. Changes in meteorological drought are then evaluated, both in terms of drought indices trends and in terms of changes in the characteristics of drought periods, on both a local and regional scale. A relation between the altitude of the area and the observed changes is highlighted, with significant differences between the plain and mountainous portion of the region. The differences are mainly related to the observed trends, with the low-altitude part of the region displaying a tendency towards dryer conditions not in common with the mountainous area. Significantly, no trend is found at a region-wide level but is instead found when considering homogeneous areas defined by terrain ruggedness. Furthermore, changes in the number of drought episodes and in their severity, duration and intensity are found to be correlated with terrain ruggedness at all time scales.

How to cite: Mombrini, E., Tamea, S., Viglione, A., and Revelli, R.: Metereological Drought in the western Po river basin: trends and characteristics from 1958 to 2023, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5234, https://doi.org/10.5194/egusphere-egu24-5234, 2024.

EGU24-5685 | ECS | Posters on site | HS7.8

Exploring Multivariate Return Periods: Enhancing Accuracy in Hydrological Analysis for Flood Prediction  

Diego Armando Urrea Méndez, Dina V. Gómez, and Manuel Del Jesus Peñil

The assessment of multivariate return periods determines how frequently different variables co-occur within a specific region. Recent studies have used two- and three-dimensional copulas for this assessment. G. Salvadori et al., (2011) introduced an approach based on Archimedean copulas and the Kendall measure. Gräler et al., (2013) calculated the trivariate return period using Vine copulas and Kendall distribution functions, incorporating annual maximum peak discharge, volume, and duration. Tosunoglu et al., (2020) applied three-dimensional Archimedean, Elliptical, and Vine copulas to study flood characteristics. These methodologies enhance the accuracy of extreme events risk measurement, emphasizing the importance of understanding tail dependence and the appropriate selection of copulas.

In multivariate analysis of compound extreme events, addressing the dependence structure in the tails of the variables of interest becomes essential. If the selected copula fails to accurately capture this extreme dependence, the estimation of extreme values may be significantly affected by uncertainty (Hangshing & Dabral, 2018). Therefore, conducting a comprehensive assessment of the copula model fit to the data is crucial, with a particular focus on tail dependence (Serinaldi, 2015). This process guides the choice of the most suitable copula family to model these compound extreme events.

We propose a two-part methodology: (I) In this phase, we focus on comparing various multivariate models that address the entirety of uncertainty. This involves analyzing different models and copula structures. The main objective is to evaluate how goodness of fit and tail dependence impact the calculation of design events, where, in some cases, underestimation may occur.

(II) In a subsequent stage, we formulate a more robust approach that encompasses the study, evaluation, and implementation of various statistical and machine learning techniques. The focus is on using the results obtained in the previous stage to develop flood models. These models enable us to compare multivariate approaches in terms of their performance in flood prediction and other associated impacts.

The study results highlight the importance of diversifying approaches in the hydrological analysis of precipitation-conditioned design events. It was found that the use of a multivariate approach provides more accurate estimations of precipitation compared to the univariate method. The careful choice of the multivariate model is crucial, as Gaussian models underestimate extreme events, while extreme vine copula models yield more tightly fitted results. This advancement benefits engineering by reducing uncertainty in design processes and providing a more precise approximation of climate impacts, with the potential to enhance territorial management.

References

Salvadori, C. De Michele, & F. Durante., 2011. On the return period and design in a multivariate framework. Hydrol. Earth Syst. Sci., 15(11), 3293–3305.

Gräler, B., Berg, M. J. van den, Vandenberghe, S., Petroselli, A., Grimaldi, S., De Baets, B. & Verhoest, N. E. C., 2013. Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation. Hydrol. Earth Syst. Sci., 17(4), 1281–1296.

Hangshing, L. & Dabral, P. P., 2018. Multivariate Frequency Analysis of Meteorological Drought Using Copula. Water Resour Manage, 32(5), 1741–1758.

Serinaldi, F., 2015. Dismissing return periods! Stoch Environ Res Risk Assess, 29(4), 1179–1189.

How to cite: Urrea Méndez, D. A., V. Gómez, D., and Del Jesus Peñil, M.: Exploring Multivariate Return Periods: Enhancing Accuracy in Hydrological Analysis for Flood Prediction , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5685, https://doi.org/10.5194/egusphere-egu24-5685, 2024.

EGU24-6170 | Posters on site | HS7.8

On the Vulnerability of NATO Installations to Climate Variability and Change: A System-Level Perspective 

Gabriele Villarini, Sandro Carniel, Taereem Kim, Hanbeen Kim, Aniello Russo, Wenchang Yang, Gabriel Vecchi, and Thomas Wahl

This task focuses on the understanding of the spatial connections among 91 NATO installations subject to hydroclimatological extremes, including precipitation, surface temperature, and wet bulb temperature, under both historical and future conditions. It allows a system-level view of the vulnerabilities of NATO installations to climate change and the associated extremes. We first perform statistical bias correction and evaluate how well global climate models (GCMs) part of the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) are able to reproduce the historical trends. Based on these analyses, we select a subset of well-performing models, which we use to examine how the spatial dependence in climate extremes is projected to change. In particular, we consider two future periods (Mid-of-Century: 2015-2048; End-of-Century: 2067-2100) with respect to the 1981-2014 period, under four shared socioeconomic pathway scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5).

We show that temperature-based extremes are correlated in space and have a large footprint, impacting more than one base at once. When we focus on precipitation extremes, we find that their spatial correlation is much weaker, with a much smaller chance of impacting more than one installation. Moreover, GCMs can reproduce these observed behaviors. In analyzing the future projections of these hydroclimatic extremes, we show that the spatial correlation in temperature-based extremes across NATO installations is projected to increase, especially toward the end of the 21st century and for higher emission scenarios. These results highlight the current and future susceptibility of the NATO installations to climate extremes in light of climate change when viewed through a system-level perspective.

How to cite: Villarini, G., Carniel, S., Kim, T., Kim, H., Russo, A., Yang, W., Vecchi, G., and Wahl, T.: On the Vulnerability of NATO Installations to Climate Variability and Change: A System-Level Perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6170, https://doi.org/10.5194/egusphere-egu24-6170, 2024.

EGU24-6265 | ECS | Orals | HS7.8

Understanding Compound Flooding hazard in Estuaries: Insights and Implications 

Dina Vanessa Gomez Rave, Diego Armando Urrea Mendez, and Manuel Del Jesus Peñil

Estuaries are highly prone to compound flooding. These areas often face flooding prompted by fluvial discharge, coastal water levels, wind and pluvial (rainfall) conditions (Moftakhari et al. 2017). Flooding drivers, even if they are not extreme individually, can combine and generate extreme local impacts. Nevertheless, their dependence and co-occurrence are often ignored, leading to misinterpretation of flooding risk. 

In this regard, assessing multivariate extremes requires understanding their stochastic structure and interconnections. Sensitivity relies on modeling properties like tail dependence strength and symmetry (Hua and Joe 2011). Copulas enable the study of tail dependency, providing insights into the relative strength between the extremes (De Luca et al, 2023). Once these primary dependencies and interconnected relationships are appropriately captured and modelled, the next step involves translating them into potential impacts (Zscheischler 2020). Therefore, defining hazard scenarios establishes the connection between the dependence structure of multiple drivers and the associated impacts. 

The critical level or return period used in risk analysis and infrastructure design inherently represents a hazard scenario. It can be seen as upper sets encompassing all occurrences deemed hazardous, potentially leading to impacts and damages based on certain criteria. This definition implies a connection with the upper tails of variables, which depicts specific dangerous conditions. In contrast to univariate analysis, where critical events are defined by surpassing a specific threshold, the multivariate hazard scenario lacks a singular definition (Bernardi et al. 2018). Moreover, in an n-dimensional framework, this set collects all 'dangerous' values based on suitable criteria and consequently defines the (n-1) iso-hyper-surface that generates the 'dangerous region', known as the 'critical layer' (Salvadori et al, 2011). In higher dimensions, this critical layer possesses more of a mathematical than a graphical definition, entailing theoretical and computational challenges.

This study aims to robustly characterize compound flooding in estuaries, employing high-dimensional analysis alongside multivariate statistical techniques and computational optimizations. Using a 100-year return level, critical events that compose the iso-hypersurface (critical layer) are identified. These design events capture variability, enabling the incorporation of uncertainty involved in predicting these dynamics.


References

Bernardi, M., Durante, F., Jaworski, P., Petrella, L., & Salvadori, G. (2018). Conditional risk based on multivariate hazard scenarios. Stochastic Environmental Research and Risk Assessment, 32, 203-211.
De Luca, G., Ruscone, M. N., & Amati, V. (2023). The use of conditional copula for studying the influence of economic sectors. Expert Systems with Applications, 120582.
Hua, L., & Joe, H. (2011). Tail order and intermediate tail dependence of multivariate copulas. Journal of Multivariate Analysis, 102(10), 1454-1471.
Moftakhari, H. R., Salvadori, G., AghaKouchak, A., Sanders, B. F., & Matthew, R. A. (2017). Compounding effects of sea level rise and fluvial flooding. Proceedings of the National Academy of Sciences, 114(37), 9785-9790.
Salvadori, G., De Michele, C., & Durante, F. (2011). On the return period and design in a multivariate framework. Hydrology and Earth System Sciences, 15(11), 3293-3305.
Zscheischler, J., Van Den Hurk, B., Ward, P. J., & Westra, S. (2020). Multivariate extremes and compound events. In Climate extremes and their implications for impact and risk assessment (pp. 59-76). Elsevier.

 

How to cite: Gomez Rave, D. V., Urrea Mendez, D. A., and Del Jesus Peñil, M.: Understanding Compound Flooding hazard in Estuaries: Insights and Implications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6265, https://doi.org/10.5194/egusphere-egu24-6265, 2024.

EGU24-6701 | ECS | Posters on site | HS7.8

Detecting the heaviness of daily rainfall probability distributions in Europe through an expeditious method, the Obesity Index 

Flavia Marconi, Benedetta Moccia, Elena Ridolfi, Fabio Russo, and Francesco Napolitano

Extreme precipitation events have a significant impact on hydraulic infrastructure design and risk management. The World Climate Research Programme (WCRP) Grand Challenges highlights the need for further investigation in analyzing and modeling weather and climate extremes due to their substantial effects. These rare meteorological occurrences represent the upper tail of the probability distribution, which can be effectively defined as heavy or light. The Obesity Index (OB) represents a user-friendly, non-parametric, empirical method capable of quantitatively assessing the heaviness of probability distribution tails directly from the original dataset, without the need to extract only extreme values. Our assessment of OB involves two distinct gridded datasets: one specific to Italy (SCIA) and another covering the entire Europe (E-OBS). The analysis shows a robust correlation between OB and L-moment ratios (L-variation, L-skewness, L-kurtosis), along with the Coefficient of Variation (CV). It is interesting to note that the tail heaviness in a specific region may vary depending on the dataset employed. For instance, OB indicates a prevalence of heavy tails across Italy or lighter tails in specific areas of the peninsula when employing SCIA or E-OBS dataset, respectively. This divergence could be attributed to an excessive smoothing of rainfall observations during the interpolation procedures used in generating E-OBS dataset. Thus, our findings reinforce the thesis of using light-tail probability distributions with caution when addressing rainfall extremes.

How to cite: Marconi, F., Moccia, B., Ridolfi, E., Russo, F., and Napolitano, F.: Detecting the heaviness of daily rainfall probability distributions in Europe through an expeditious method, the Obesity Index, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6701, https://doi.org/10.5194/egusphere-egu24-6701, 2024.

EGU24-7433 | Orals | HS7.8

Flash Flood Hazard: A Counterfactual Analysis for Germany 

Paul Voit and Maik Heistermann

In response to heavy rainfall, flash floods can arise from rapid runoff concentration in the landscape, presenting significant damage potential due to high flow velocities and minimal lead times. Flash floods are among the most destructive natural hazards. Managing their risks usually necessitates the application of extreme value statistics. However, the small temporal and spatial scale of flash floods poses a challenge, as the requisite data for statistical methods is often unavailable or incomplete.  Furthermore, the effects of climate change may compromise the robustness of extreme value statistics.

To enhance our understanding of flash flood hazards in Germany, we present a novel "counterfactual" scenario analysis. This approach considers alternative ways of how events could have unfolded. To identify worst-case scenarios is particularly interesting for risk assessment. Accordingly, we assumed that historical rainfall events could have happened anywhere else in Germany: What would have happened if a particular rainfall event occurred in a different area? Would it result in a flash flood?

To address these questions, we created a catalog of extreme rainfall events for the years 2001-2022 from radar rainfall estimates. Because flash flood triggering rainfall is often embedded in precipitation fields of larger spatio-temporal extent, we used the cross-scale weather extremity index (xWEI) to identify and rate the events. We then shifted the ten most extreme events systematically across Germany and modeled the peak discharge for every shifted realization (counterfactual peaks), thus creating close to a billion runoff datasets. This approach preserves the spatio-temporal event structure that significantly influences the overlapping scales of runoff processes and hence the hazard. Results are provided to users via an interactive web interface.

Our results reveal that, on average, the worst case counterfactual peaks would exceed the maximum original peak by a factor 5.3. Furthermore, it shows that not every event is equally likely to trigger high runoff peaks, even when rated similarly extreme. Our study might help to expand the view on what could happen in case certain extreme events occurred elsewhere, help to identify flash flood prone areas, and thereby reduce the element of surprise in disaster risk management. The proposed method is transferable and could be a valuable asset, especially in data-scarce regions.

How to cite: Voit, P. and Heistermann, M.: Flash Flood Hazard: A Counterfactual Analysis for Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7433, https://doi.org/10.5194/egusphere-egu24-7433, 2024.

EGU24-10268 | ECS | Posters on site | HS7.8

Changing spatio-temporal characteristics of extreme rainfall events under climate change using high resolution climate projections  

Laura Devitt, Gemma Coxon, Jeffrey Neal, Leanne Archer, Paul Bates, and Elizabeth Kendon

Extreme precipitation is projected to intensify and occur more frequently under climate change. However, the effect of global warming on the spatial and temporal structure of extreme rainfall events at the local scale is uncertain. In the UK, the current method for estimating changes in flood hazard under climate change involves applying a simple multiplicative uplift to spatially uniform catchment rainfall. This approach neglects spatio-temporal characteristics of rainfall, which are known to be important for flood hazards. The UCKP Local Convection Permitting Model (CPM) has for the first time provided the capacity to assess these characteristics of rainfall at the local scale. Here, we use an ensemble of 2.2km hourly convection-permitting transient projections from UKCP Local to identify changes in the spatial and temporal characteristics of precipitation extremes over 100-years (1981-2080) across the UK. The analysis uses an ‘event-based’ approach, exploring seasonal changes in the peak intensity, total rainfall, and duration of events, but also changes in the spatial extent and temporal clustering of events through time. We identify ~13000 extreme rainfall events across the UK over the 100-year period. Event peaks are identified using a seasonal and time-varying threshold (99th percentile) on hourly rainfall rates, and event start and stop times are extracted using a lower threshold (20th percentile). We identify seasonal differences in how spatial extents of rainfall extremes will change, with winter and spring events growing, but summer and autumn events reducing in areal coverage. We also identify changes in the sub-seasonal timing of rainfall extremes, with events becoming more clustered, particularly during the winter months. Understanding changes in the spatial and temporal characteristics of rainfall events is critical as they may compound with increases in rainfall intensity, exacerbating the impacts of flooding.

How to cite: Devitt, L., Coxon, G., Neal, J., Archer, L., Bates, P., and Kendon, E.: Changing spatio-temporal characteristics of extreme rainfall events under climate change using high resolution climate projections , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10268, https://doi.org/10.5194/egusphere-egu24-10268, 2024.

EGU24-11587 | ECS | Posters on site | HS7.8

Climatology and moisture sources of heavy rainfall in the Andes of southern Ecuador 

Diego Urdiales-Flores, Gregoire Mariethoz, Rolando Célleri, and Nadav Peleg

Mountains cover approximately one-quarter of the total land surface on the planet, and a significant fraction of the world’s population lives in their vicinity. Orography critically affects weather processes at all scales and, in connection with factors such as land-cover heterogeneity and mesoscale atmospheric process, is responsible for high spatial variability in mountain weather, such as the Tropical Andes. Due to this high complexity, monitoring the atmosphere in the Ecuadorian Andes has remained a challenge due to the lack of high spatio-temporal resolution operational observing systems. We studied heavy rainfall associated with floods to identify the main rain types and their sources of moisture based on non-stationary rainfall-similarity indices and Lagrangian approaches. We analyzed five years of data collected from a high space-time resolution (5 min and 500 m) X-band weather radar that was located at 4450 m a.s.l in the Tropical Andes of southern Ecuador. To identify the origin and trajectories of water vapor masses, we used the NOAA meteorological database (GDAS, global data assimilation system, at 0.5° resolution). Our analysis shows that the heavy rainfall in the region can be divided into five rainfall types: two spatially-clustered rain types (convective) and three spatially-homogenous rain types (stratiform). We found that air masses typing as convective reach the study area preferentially from the eastern flank of the Andes through the Amazon basin (~ 70% of all events). We also compared discharge data with rain types and discussed the type and source of rainfall potentially responsible for triggering flash floods in the Andes of southern Ecuador.

How to cite: Urdiales-Flores, D., Mariethoz, G., Célleri, R., and Peleg, N.: Climatology and moisture sources of heavy rainfall in the Andes of southern Ecuador, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11587, https://doi.org/10.5194/egusphere-egu24-11587, 2024.

EGU24-13301 | ECS | Posters on site | HS7.8

A Global Analysis of Daily Streamflow Data to Unravel the Heaviness of Flood Distribution 

Masoud Zaerpour, Simon Michael Papalexiou, and Alain Pietroniro

Hydroclimatic extremes, such as floods, present complex challenges in risk assessment due to their spatial and temporal compounding nature. This research aims to improve our understanding and modelling capabilities by investigating the complex interactions among record length, flow regime, and upper tail of floods. Our study resolves conflicting results in prior studies by utilizing a quasi-global peak-over-threshold (POT) analysis of flood with the Generalized Pareto (GP) distribution. Based on an analysis of 4,482 streamflow series over six different regime types with record lengths ranging from 30 to 213 years, our results show a strong relationship between the GP shape parameter and record length. The results show that the variance of the shape parameter of GP distribution diminishes with record length, and it eventually converges to a single value depending on the flow regime. We show that the shape parameter of snow-dominated streams is the lowest, whereas intermittent streams have the highest. Our research reveals regime-specific patterns in the impact of hydroclimatic and catchment controls on flood tails, underscoring the necessity of regime-specific strategies for flood risk management. Identifying catchments that are more likely to experience extreme flooding provides useful information for determining which mitigation measures to prioritize.

How to cite: Zaerpour, M., Papalexiou, S. M., and Pietroniro, A.: A Global Analysis of Daily Streamflow Data to Unravel the Heaviness of Flood Distribution, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13301, https://doi.org/10.5194/egusphere-egu24-13301, 2024.

EGU24-14054 | ECS | Posters on site | HS7.8 | Highlight

Climate Change both Increases and Decreases Winter Snowmelt across North America 

Shadi Hatami, Masoud Zaerpour, Jan Adamowski, and Simon Michael Papalexiou

Snowmelt is a vital source of freshwater for a large proportion of North America’s population. Sudden snowmelt can also lead to various extreme events and environmental hazards, such as floods in the cold season and droughts in the upcoming warmer months. However, this natural water resource is at risk due to climate change and variability. Temperature and precipitation are significant climatic controllers that regulate snowmelt dynamics. Warmer temperatures can affect snowmelt extremes, persistence, and distribution, while changing precipitation alters the available snow budget and, consequently, the snowmelt amount. Yet, the precise role of the compound changes in temperature and precipitation under changing climate on future snowmelt dynamics is unknown. To address this knowledge gap, we use observation-driven data and future projections to quantify the response of winter snowmelt to changes in temperature and precipitation across North America (United States and Canada). Our analysis of far-future (2091-2100) changes reveals a significant increase (> 60%) in winter (November-March) snowmelt in northern latitudes, while it declined (by up to< 38%) in southern latitudes. Higher temperatures proved to be the primary driver of the increased snowmelt, whereas decreased snowfall modulated the declines in snowmelt, with variability seen across the study domain. Our findings suggest that the probability of an increase in winter snowmelt is high under the warmer and wetter climatic conditions prevailing in northern regions. In contrast, winter snowmelt across southern latitudes is likely to decline. These findings have significant implications for freshwater availability in the future in the affected areas. 

How to cite: Hatami, S., Zaerpour, M., Adamowski, J., and Papalexiou, S. M.: Climate Change both Increases and Decreases Winter Snowmelt across North America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14054, https://doi.org/10.5194/egusphere-egu24-14054, 2024.

EGU24-14140 | ECS | Posters virtual | HS7.8

Unfolding Multivariate Drought Risk in Large River Basins accounting Onset Seasonality and Event Magnitude 

Aparna Raut and Poulomi Ganguli

The frequency and severity of droughts are expected to increase in the warming climate. Understanding mutually interacting drought properties, such as their severity (deficit volume) and time to onset, is crucial for managing reservoir operations and low flows. Previous studies have performed bivariate drought frequency analysis considering drought severity and duration across different climate regions. However, little is known about the role of drought seasonality in shaping drought severity. This study aims to investigate the dependence between onset time (i.e., directional occurrence date) and deficit volume and evaluate the impact of drought seasonality on the deficit volume distributions in disparate climate regions across the global tropics. Leveraging streamflow observations from representative catchments in the northern and southern hemispheres and considering the nonlinear dependence strengths between onset time and deficit volume, we implemented a multivariate drought frequency model that yields a conditional probability of drought severity given the timing of peak drought intensity. We consider multiple univariate probability functions for modelling drought deficit volume, whereas drought onset time is modelled using von Mises distribution. Further, the joint dependence between drought onset and deficit volume is modeled using a bivariate Archimedean class of copulas. First, we show temporal variations of exceedance probabilities of drought deficit volume and their seasonal clustering behavior during dry/wet phases and then explore any possible shift in the risk of peak drought intensity based on its seasonality. Finally, employing a flexible multivariate probabilistic tool, we demonstrate different scenarios of drought characteristics combinations and a seasonality-informed drought probability model, aiding understanding complex processes of drought propagations across disparate climate regimes and assessing possible climatic shifts to drought frequency.

How to cite: Raut, A. and Ganguli, P.: Unfolding Multivariate Drought Risk in Large River Basins accounting Onset Seasonality and Event Magnitude, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14140, https://doi.org/10.5194/egusphere-egu24-14140, 2024.

EGU24-14570 | ECS | Posters on site | HS7.8

Regional Flood Risk Assessment Using Ensemble of GCMs 

Kiran Kezhkepurath Gangadhara, Sarath Muraleedharan, Raja Bharath, and Martin Kadlec

Flood risk assessment is generally carried out at a basin scale by developing hydrologic and hydraulic models with an objective to arrive at hazard/inundation maps for the river segments/reaches. A hydrologic model is used to derive a flood hydrograph corresponding to a specific return period and this is routed through the flood plain of the study area with the aid of a hydraulic model to obtain water surface elevations and inundation extents. This approach is best suited to represent a flood event at a river segment accurately, but the risks associated with floods need to be analyzed on a regional scale for effective flood risk management. As the size of the region increases beyond one basin, this approach fails to realistically represent the flood events across different river segments and basins. The simultaneous occurrences of different return periods on different river segments cannot be captured by this approach. The traditional approach to model these simultaneous occurrences is by using the streamflow records to arrive at spatially correlated stochastic simulations of streamflow. One issue that compounds this problem is the data scarcity in certain regions to accurately estimate the return periods of floods at distinct locations.

To address these issues, Impact Forecasting, Aon’s catastrophe model development team, has undertaken a study to simulate stochastic flood events in the Southeast Asian region by considering Malaysia as a case study. The approach involves (i) downscaling of precipitation and temperature data from an ensemble of Global Circulation Models (GCMs), (ii) calibration of a grid-based Rainfall-Runoff (RR) model using available historical data of meteorological variables and streamflow, (iii) providing the downscaled precipitation and temperature data as input to the calibrated RR model to simulate streamflow across the study area and (iv) identifying flood events from the simulated streamflow to extract an exhaustive set of realistic flood events in the region. The approach involves the use of meteorological data of 15,000 years from 7 different GCMs, downscaled to 10 km grids from 100 km resolution. This enables capturing a broader spectrum of potential climate conditions and therefore generating a wide range of possible flood events without relying significantly on in-situ data. The proposed methodology considers the uncertainty inherent in climate models, providing a robust framework for assessing flood risk and results in a more reliable and realistic representation of stochastic flood events over a region. The approach presents a physically based alternative to the commonly used statistical approaches based on extreme value theory and could be a valuable tool for policymakers, researchers, and practitioners in making informed decisions in the face of evolving climate conditions.

How to cite: Kezhkepurath Gangadhara, K., Muraleedharan, S., Bharath, R., and Kadlec, M.: Regional Flood Risk Assessment Using Ensemble of GCMs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14570, https://doi.org/10.5194/egusphere-egu24-14570, 2024.

EGU24-16999 | ECS | Orals | HS7.8

Spatio-Temporal Dynamics of Extreme Precipitation and Dry Spells in Alpine Catchments under Changing Climatic Conditions 

Tatjana Milojevic, Christian R. Steger, and Michael Lehning

Heavy and extreme precipitation and drought events are expected to increase in frequency and intensity as a result of climate change. Investigating the projected evolution of these events in terms of their spatio-temporal dynamics is important for understanding if certain regions are more susceptible to negative impacts of the changes in extremes. The spatio-temporal dynamics of extremes in complex terrain, such as in the Swiss Alps, is of particular interest as the same event might impact nearby catchments in different ways. Using climate model data at a horizontal resolution of 2.2km, dynamically downscaled with the regional climate model COSMO for the emission scenario RCP8.5, we explore projected extreme precipitation and dry spells for the end of the 21st century (2090-2099) relative to present conditions. We apply connected component labelling (CCL) to define precipitation clusters and identify the spatio-temporal changes in extreme precipitation events in alpine catchments of the southern Swiss Alps. In addition, we investigate changes between present and possible future drought conditions. The main aim is to determine if certain watersheds in the southern Alps are expected to experience different vulnerabilities to climate change-driven extreme precipitation and drought events and if the propensity to a certain type of extreme varies between different catchments. Preliminary results indicate that, relative to present-day conditions, the total amount of precipitation tends to decrease in the future scenario with increasing temperature across multiple sites. Initial assessment of the CCL results indicates that a higher overall number of extreme precipitation clusters may be found in the future summer season relative to present conditions, with weaker differences for the remaining seasons. We also expect to find shifts in the spatial range and duration of the precipitation clusters and dry spells between the present and end of century conditions.

How to cite: Milojevic, T., Steger, C. R., and Lehning, M.: Spatio-Temporal Dynamics of Extreme Precipitation and Dry Spells in Alpine Catchments under Changing Climatic Conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16999, https://doi.org/10.5194/egusphere-egu24-16999, 2024.

EGU24-17547 | Orals | HS7.8 | Highlight

The space-time representation of extraordinary rainfall events 

Salvatore Manfreda

Extraordinary events are rarely observable in a single rainfall gauge, and this make extremely challenging the correct prediction of their arrivals. However, it may be possible to develop a more robust approach by employing a space-time modelling scheme that is able to capture the spatial dynamics of such phenomena. Therefore, a space-time Poisson model of rainfall cells with circular shape and random depth has been exploited for the first time to interpret the behaviour of this family of extraordinary events. This category of events that may be connected to larger meteorological phenomena not necessarily connected with local heterogeneity of the landscape. Following the identification of the observed extraordinary event across southern Italy, six zones with significantly different dynamics in terms of the frequency of such extremes were identified. Subsequently, a simple mathematical representation was adopted to calibrate the model parameters, leading to an estimate of regional probability distributions defined on the space-time occurrences of extraordinary events over homogeneous zones. The approach allows to overcome the limitations posed by point observations allowed the definition of a probability distribution that pertains to an entire area rather than just a point. The obtained quantiles of rainfall estimated seems to align well with the upper bound of the probability distribution of the annual maxima observed over the areas of interests.

Keywords: Rainfall statistics, Space-time Poisson models; Extraordinary events.

How to cite: Manfreda, S.: The space-time representation of extraordinary rainfall events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17547, https://doi.org/10.5194/egusphere-egu24-17547, 2024.

EGU24-19682 | ECS | Orals | HS7.8

Informativeness of teleconnections in local and regional frequency analysis of rainfall extremes 

Andrea Magnini and Attilio Castellarin

Numerous studies have established strong long-range relationships (teleconnections) between global climatic indexes and precipitation across diverse geographical regions worldwide. Typically, these investigations focus on the number of wet days or cumulative rainfall over specific seasons or the entire year, while only a few explicitly explore the informative value of teleconnections in describing the frequency regime of sub-daily rainfall annual maxima. Furthermore, most studies analyze the correlation between rainfall characteristics and teleconnection index values at individual gauge stations within the same season and without considering any time lag. 

Our study provides a comprehensive assessment of the potential and informative content of teleconnections for representing and modeling the frequency regime of rainfall extremes, addressing the limitations mentioned above. Our dataset comprises annual maximum series (AMS) of sub-daily rainfall depth recorded between 1921 and 2022 at approximately 2300 rain gauges spanning a large and climatically diverse region in Northern Italy. Based on a comprehensive literature review, we selected six global climate indexes and evaluated their correlation with time series of gridded regional L-moments, statistical measures characterizing the distribution of sub-daily rainfall extremes. In analyzing the spatial patterns of gridded L-moments, we considered time aggregation intervals (durations) ranging from 1 to 24 hours, discretization of the study region with tile sizes (resolutions) up to 100 km, and time lags in teleconnections up to 30 years. Our results reveal significant spatial patterns in the teleconnections, with the Western Mediterranean Oscillation Index exhibiting stronger relationships. The robustness of these spatial patterns is confirmed by their limited sensitivity to the chosen grid resolution and time lag, likely arising from the utilization of time series of spatially smoothed statistics of AMSs (gridded L-moments) rather than raw annual sequences of rainfall maxima. Consequently, our research suggests promising pathways for climate-informed local and regional frequency analysis of rainfall extremes. 

How to cite: Magnini, A. and Castellarin, A.: Informativeness of teleconnections in local and regional frequency analysis of rainfall extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19682, https://doi.org/10.5194/egusphere-egu24-19682, 2024.

EGU24-20390 | ECS,ECS | Orals | HS7.8

Evaluating Compound Risks of Heatwaves and Droughts on Crop Yield and Food Security in Morocco 

Bouchra Zellou, El Houcine Bergou, and Nabil El Moçayd

In an era marked by climate change, heatwaves and droughts have increasingly begun to co-occur within a single growing season, significantly impacting crop yields in key agricultural regions globally. Against this backdrop, the current study is dedicated to quantitatively evaluating the effects of these combined hot-dry episodes on agricultural productivity in Morocco, a country where such climatic extremes pose a significant threat to food security and economic stability. Utilizing high-resolution gridded precipitation and temperature data that closely aligns with 29 ground station observations, we calculate the Standardized Precipitation Index (SPI) and the Standardized Temperature Index (STI) across Moroccan arable regions in the agricultural season (September-May) during 1981-2018. Employing a vine-copula conditional probability model, the study explores the complex interactions between drought and heatwaves and their joint impact on vegetation, as indicated by the Normalized Difference Vegetation Index (NDVI). The focus is on identifying the conditional probability of vegetation loss under multiple compound dry-hot episodes. The findings highlight that the combined effects of droughts and heatwaves can have catastrophic consequences for crop yields, especially during the growth season. This underscores the critical need to assess their compound impact on agricultural productivity, rather than examining each factor separately. This study provides a robust understanding of compound hot-dry events and their impacts on crop yields, highlighting the emerging need for comprehensive adaptation strategies that bolster agricultural resilience and support sustainable productivity in the face of evolving climatic challenges.

Keywords: Compound, drought, heat waves, NDVI, vine-copula, conditional probability.

How to cite: Zellou, B., Bergou, E. H., and El Moçayd, N.: Evaluating Compound Risks of Heatwaves and Droughts on Crop Yield and Food Security in Morocco, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20390, https://doi.org/10.5194/egusphere-egu24-20390, 2024.

This study aims to identify key characteristics of rainfall events, such as critical duration, extent, and severity (i.e., return period), to unveil potential dependencies with the resulting impact scenarios. Severity diagrams, introduced by Ramos et al. (2005) serve here as a straightforward tool, providing a synthetic visualization of storm severity while accounting for the complexity associated with rainfall spatial variability and duration. The method emphasizes the coexistence of extreme and ordinary (non-extreme) rainfall intensities. In contrast, the conventional approach of assigning a single return period to an event obscures a significant portion of storm complexity by overlooking spatial variability. Maximum mean areal precipitations observed over different areas during the storm event are evaluated. Subsequently, maximum equivalent point rainfalls are derived using ARF (Areal Reduction Factor) estimation, and their return period values deduced from the IDF (Intensity Duration Frequency) curves. The return periods are eventually mapped as a function of area and duration of rainfall accumulation. Several damaging storm events observed in the Calabria region (south Italy) over the last 20 years have been selected as illustrative examples for the analysis.

How to cite: Biondi, D. and Bloise, S.: Characterization of Extreme Rainfall Events Severity in Calabria: Exploring Spatial-Temporal Variability through Severity Diagrams, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20687, https://doi.org/10.5194/egusphere-egu24-20687, 2024.

Nature depends on the inherent unpredictability of randomness, a significant force influencing hydrometeorological processes. While physics provides sophisticated models, understanding the variability within randomness is crucial for evaluating environmental risks. Despite the availability of numerous stochastic models tailored to specific statistical properties, identifying essential features for accurate simulations across time, space, and scales remains a challenge. This presentation outlines the progress in CoSMoS, a user-friendly stochastic modeling framework that advances from basic scenarios to complex multisite and space-time simulations. The underlying philosophy of this framework is to faithfully replicate the probabilities describing the occurrences of magnitudes and correlations in space and time. CoSMoS excels in generating time series for various hydroclimatic variables and simulating intricate space-time phenomena, as demonstrated by its effectiveness in replicating storms, cyclones, and air mass collisions. This showcases its versatility in capturing complex behaviors across different scales.

References

  • Papalexiou, S. M., Serinaldi, F., & Clark, M. P. (2023). Large-Domain Multisite Precipitation Generation: Operational Blueprint and Demonstration for 1,000 Sites. Water Resources Research, 59(3), e2022WR034094. https://doi.org/10.1029/2022WR034094
  • Papalexiou, S. M. (2022). Rainfall Generation Revisited: Introducing CoSMoS-2s and Advancing Copula-Based Intermittent Time Series Modeling. Water Resources Research, 58(6), e2021WR031641. https://doi.org/10.1029/2021WR031641
  • Papalexiou, S. M., Serinaldi, F., & Porcu, E. (2021). Advancing Space-Time Simulation of Random Fields: From Storms to Cyclones and Beyond. Water Resources Research, 57(8), e2020WR029466. https://doi.org/10.1029/2020WR029466
  • Papalexiou, S. M., & Serinaldi, F. (2020). Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity. Water Resources Research, 56(2), e2019WR026331. https://doi.org/10.1029/2019WR026331
  • Papalexiou, S. M. (2018). Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency. Advances in Water Resources, 115, 234–252. https://doi.org/10.1016/j.advwatres.2018.02.013
  • Papalexiou, S. M., Markonis, Y., Lombardo, F., AghaKouchak, A., & Foufoula‐Georgiou, E. (2018). Precise Temporal Disaggregation Preserving Marginals and Correlations (DiPMaC) for Stationary and Nonstationary Processes. Water Resources Research, 54(10), 7435–7458. https://doi.org/10.1029/2018WR022726

How to cite: Papalexiou, S. M.: Simulating Nature’s randomness with CoSMoS - A Versatile Stochastic Modeling Framework for Hydrometeorological Phenomena, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21666, https://doi.org/10.5194/egusphere-egu24-21666, 2024.

EGU24-599 | ECS | Posters on site | AS1.22

Langragian analysis of the extreme-windstorm dynamics associated to post-tropical cyclone Leslie landfall in Portugal 

Miguel Lima, Luana C. Santos, Rita M. Cardoso, Pedro M. M. Soares, and Ricardo M. Trigo

Windstorms in Europe are responsible for more than half of the economic loss associated with natural disasters. In October 2018 a post-tropical cyclone, formerly Hurricane Leslie, made landfall in continental Portugal. This event was characterized by very intense winds, with a gust record-hitting value of 176 km/h registered near Figueira da Foz, a coastal city located in the center of the country. The main factors causing this event of extreme winds were likely a “cold-conveyor belt jet” or a “jet sting”, roughly 12 hours after losing its main tropical characteristics. Despite the strong impact associated with this windstorm there are still few studies modeling this kind of dynamics, and here we present a simulation and thorough analysis of the rare dynamics linked with this post-tropical cyclone affecting western Europe.

The WRF-ARW model, version 4.4.1, was used to numerically model Leslie as it transitioned from a hurricane to post-tropical cyclone. Three one-way nested domains were used with a large (5 km), medium (1 km), and lower (200m) resolution, with 68 hybrid levels (15 m - 20 hPa). The larger domain covers the Iberian Peninsula and a large portion of the Atlantic Ocean nearby, while the inner ones are focussed in the central and northern sectors of continental Portugal - the most affected areas. Initial and boundary conditions were retrieved from the GFS operational analysis at 0.25º spacing, in 6-hour intervals. Due to the difficulties modeling this cyclone, nudging was used in the outer domain to ensure that the cyclone would make landfall as close as possible to the real location.

Several state-of-the-art thermodynamics-based diagnostics were used to analyze in-depth the midlatitude cyclone dynamics observed in the recently transitioned cyclone Leslie. Midlatitude cyclone-related dynamics were identified in the simulation, leading to the extreme winds in the most impacted region. The set of final simulated data reveals a close resemblance to the real event, with parameterized wind gusts presenting a lower intensity around 140 km/h, but the largest values impacting approximately the same region of center Portugal. A Langragian approach was also used to study particle trajectories and evaluate the atmospheric circulation leading to the extreme winds showing vertical downdrafts up to 4 m/s. This study highlights the catastrophic potential a post-tropical cyclone such as Leslie has and, while at the end of their life-time with presumably less intensity, storms of this type should not be disregarded for warnings and need to be considered in general evaluations of midlatitude storm impacts.

Acknowledgements: This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020. M. M. Lima was supported through the PhD MIT Portugal MPP2030-FCT programme grant PRT/BD/154680/2023. L. C. Santos is supported by the EarthSystems Doctoral School, at University of Lisbon, supported by Portuguese Fundação para a Ciência e a Tecnologia (FCT) project UIDP/50019/2020-2023, University of Lisbon.

How to cite: Lima, M., C. Santos, L., M. Cardoso, R., M. M. Soares, P., and M. Trigo, R.: Langragian analysis of the extreme-windstorm dynamics associated to post-tropical cyclone Leslie landfall in Portugal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-599, https://doi.org/10.5194/egusphere-egu24-599, 2024.

EGU24-1418 | ECS | Posters on site | AS1.22 | Highlight

Windstorm losses in Europe - What to gain from damage datasets 

Julia Moemken, Gabriele Messori, and Joaquim G. Pinto

Windstorms are among the most impacting natural hazards affecting Western and Central Europe. Information on the associated impacts and losses are essential for risk assessment and the development of adaptation and mitigation strategies. In this study, we compare reported and estimated windstorm losses from five datasets belonging to three categories: Indices combining meteorological and insurance aspects, natural hazard databases, and loss reports from insurance companies. We analyse the similarities and differences between the datasets in terms of reported events, the number of storms per dataset and the ranking of specific storm events for the period October 1999 to March 2022 across 21 European countries.

A total of 94 individual windstorms were documented. Only 11 of them were reported in all five datasets, while the large majority (roughly 60%) was solely recorded in single datasets. Results show that the total number of storms is different in the various datasets, although for the meteorological indices such number is fixed a priori. Additionally, the datasets often disagree on the storm frequency per winter season. Moreover, the ranking of storms based on reported/estimated losses varies in the datasets. However, these differences are reduced when the ranking is calculated relative to storm events that are common in the various datasets. The results generally hold for losses aggregated at European and at country level.

Overall, the datasets provide different views on windstorm impacts. Thus, to avoid misleading conclusions, we use no dataset as “ground truth” but treat all of them as equal. We suggest that these different views can be used to test which features are relevant for calibrating windstorm models in specific regions. Furthermore, it could enable users to assign an uncertainty range to windstorm losses. We conclude that a combination of different datasets is crucial to obtain a representative picture of windstorm associated impacts.

How to cite: Moemken, J., Messori, G., and Pinto, J. G.: Windstorm losses in Europe - What to gain from damage datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1418, https://doi.org/10.5194/egusphere-egu24-1418, 2024.

EGU24-1553 | ECS | Posters on site | AS1.22

An Investigation into the Role of the Ocean for Seasonal Predictability of European Windstorms 

Kelvin S. Ng and Gregor C. Leckebusch

Extreme extra-tropical cyclones and related windstorms are the most dangerous and costly meteorological hazards in Europe. The latest state-of-the-art seasonal forecast suites show now usable forecast skill for basic parameters like mean temperature or precipitation for mid-latitude Europe on lead times of up to 4 months (Nov-Feb). One avenue for skilful prediction of extremes is the now-proven forecast skill for large-scale climate modes, as these directly influence extreme windstorms. Improved ability to simulate successfully the relevant large-scale climate patterns like e.g., the North-Atlantic Oscillation, the East-Atlantic pattern, and/or the Scandinavian pattern opens up a prominent route to progress the forecast skill for extreme storms.

Nevertheless, recent publications have shown that even in the current model suites, the existing skill for forecasting the frequency or intensity of windstorm tail events, is not fully explained by those dominant large-scale variability patterns. Furthermore, studies revealed a potential connectivity of storm count predictions to stratospheric sudden warming events and also highlighting the influence of atmosphere-ocean coupling. Recent developments in the forecast skill of the upper-ocean heat content and the role of re-emerging temperature anomalies for the European winter climate allow to explore another pathway with potentially predictive power, the role of ocean-atmosphere interaction. Ocean-atmosphere interaction caused e.g., by the NAO have been increasingly recognised but have not been systematically linked to the ability to predict extreme severe windstorms on a seasonal time scale. In this presentation, we will present preliminary results of the role of ocean on the predictability of European windstorms.

How to cite: Ng, K. S. and Leckebusch, G. C.: An Investigation into the Role of the Ocean for Seasonal Predictability of European Windstorms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1553, https://doi.org/10.5194/egusphere-egu24-1553, 2024.

EGU24-1736 | ECS | Posters on site | AS1.22 | Highlight

Intra-seasonal variability of temporal clustering of European winter windstorms 

Sophie Feltz, Gregor C. Leckebusch, Kelvin S. Ng, and Tim Kruschke

Severe European winter windstorms are one of the most damaging natural hazards and thus a major threat to societies. Clustered European winter windstorms, storms that occur in quick succession over a specific period of time over a fixed location, can result in amplified structural and environmental damage and accumulated losses. Yet, variability of storm clustering on intra-seasonal timescales has not been fully investigated. We analyse winters (DJF) for the period 1981-2016 from ERA5 reanalysis, where tracks and storm impact footprints are identified through the impact-oriented wind-based tracking algorithm WiTRACK.  

We quantify the magnitude of clustering using the widely employed dispersion statistic as used in Mailier et al. (2006). The spatial distribution of clustering on 45- and 30-day timescales as well as the time development of clustering on even shorter 30-, 20-, 15- and 11-days reference periods are investigated. Thus, in a seamless approach from seasonal to synoptic clustering. Results from both windstorm clustering of tracks and the storm footprints will be presented. Preliminary findings suggest an increase in clustering occurrence in the later half of the winter season on 45- and 30-day timescales.  On shorter timescales (<30 days), depending on location, distinct periods of increased clustering e.g., in the middle and the end of the season can be identified.

How to cite: Feltz, S., Leckebusch, G. C., Ng, K. S., and Kruschke, T.: Intra-seasonal variability of temporal clustering of European winter windstorms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1736, https://doi.org/10.5194/egusphere-egu24-1736, 2024.

EGU24-1974 | ECS | Posters virtual | AS1.22

Shifting of Western Disturbances winter precipitation over Western Himalayas 

Pooja Pooja and Ashok Priyadarshan Dimri

The Indian Himalayan region receives an enormous amount of precipitation due to synoptic weather systems known as Western Disturbances (WDs). WDs are east-ward propagating systems embedded in the Subtropical Westerly Jetstream (SWJ). The main objective of this study is to investigate the change in magnitude and dynamics of WDs precipitation over the western Himalayan region. In this study, different observational datasets (IMD, AHRODITE, GPCP, GPCC, and ERA5) were selected to compare and assess the magnitude of WDs precipitation for the period 1987–2020 during the winters (DJF: December, January, and February). Further, to examine the structure of WDs precipitation at the pressure level of 200hPa, ERA5 Reanalysis datasets having a similar resolution of 25 km with the gridded dataset of the Indian Meteorological Department (IMD) are used for the analysis. WDs moisture sources from the Arabian Sea are assessed at 23 pressure levels (1000–200 hPa) for further understanding of WDs dynamics. Our study shows the daily shifting of WDs precipitation towards February during the winters and an intriguing decrease in daily WDs precipitation in recent years. During the study, we found that WDs precipitation contributed a significant amount of precipitation (~80%) over the Western Himalayan region of the Indian subcontinent. Using Theil-Sen method, trend analysis was performed, showing a decreased trend of WDs precipitation in recent years The present findings indicate that WDs have changed their precipitation characteristics and dynamics due to climate change. The number of active WDs days is decreasing. Our results show there is enough moisture present over the Bay of Bengal region other than WDs which helps in sustaining and replenishing glaciers over the Indian Himalayan region.

How to cite: Pooja, P. and Dimri, A. P.: Shifting of Western Disturbances winter precipitation over Western Himalayas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1974, https://doi.org/10.5194/egusphere-egu24-1974, 2024.

EGU24-3651 | ECS | Orals | AS1.22

Air-Sea Flux Influences on Extratropical Cyclone and Atmospheric River Mesoscale Development and Upstream Temporal Clustering 

Juan Crespo, Catherine Naud, Rosa Luna-Niño, James Booth, and Derek Posselt

Latent and sensible heat fluxes (LHF and SHF, respectively) within the marine boundary layer are believed to play a significant role in the genesis and evolution of Extratropical Cyclones (ETCs) and Atmospheric Rivers (ARs, often associated with ETCs in the midlatitudes). However, consistent observations of air-sea interactions with in-situ observatories are limited in both time and space, and traditional polar orbiting satellites may miss large swaths in the lower midlatitudes due to their orbits, leading to daily gaps in coverage where the most robust fluxes often occur and change rapidly. Satellite missions like CYGNSS (Cyclone Global Navigation Satellite System) have filled in data gaps by providing improved observations over the lower midlatitudes of air-sea interactions. These improved observations of air-sea processes, coupled with observations of cloud and precipitation structure within ETCs and ARs from other satellites, like GPM and MODIS, can help one begin to link the correlations between surface heat fluxes to changes of the mesoscale features within these synoptic-scale systems. Previous studies have shown the correlation of observed surface heat fluxes to precipitation and cloud thickness increases along the frontal regions. Still, they have only looked at the connections between ETCs and ARs when LHF and SHF were at their strongest or the peak intensity of the system, not during its early formation (or just before formation) when they may be at their strongest. 

Additionally, recent studies have examined through idealized models how surface heat fluxes within an ETC can impact the development of ETCs and ARs upstream of the primary cyclone and lead to multiple ETCs in succession, often called a family or temporal clustering of ETCs and ARs. This clustering can lead to significant and excessive precipitation over parts of the globe, such as the United States West Coast in early 2023, with successive ARs over one month. Improved observations of real-world conditions can help us better understand the interplay within these systems. This presentation will highlight the role air-sea interactions may have during the genesis and early evolution of ETCs and ARs, the correlations to cloud and precipitation structure changes, the upstream impacts, and setting the groundwork that will be able to show that air-sea interactions directly impact the development of these systems.

How to cite: Crespo, J., Naud, C., Luna-Niño, R., Booth, J., and Posselt, D.: Air-Sea Flux Influences on Extratropical Cyclone and Atmospheric River Mesoscale Development and Upstream Temporal Clustering, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3651, https://doi.org/10.5194/egusphere-egu24-3651, 2024.

EGU24-3675 | Orals | AS1.22 | Highlight

Poleward intensification of midlatitude extreme winds under warmer climate 

Emanuele Silvio Gentile, Ming Zhao, and Kevin Hodges

In this work, we investigate the global impact of midlatitude cyclones on the geographical distribution and intensity of near-surface extreme wind speeds in a warmer climate. We use  state-of-the-art high-resolution general circulation models developed by the Geophysical Fluid Dynamics Laboratory. Results indicate a clear poleward shift of extreme wind speeds, driven by the associated shift in midlatitude storm tracks, and attributed to global warming and associated changes in general circulations. The total number of midlatitude cyclones decreases by roughly 4%, but the proportion of cyclone-associated extreme wind speed events increases by 10% in a warmer climate. Notably, the research has identified Northwestern Europe, the British Isles, and the West Coast of North America as hot spots with the greatest socio-economic impacts from increased cyclone-associated extreme winds. In addition, we also use the GFDL ultra-high resolution global storm resolving model to study cyclone-associated extreme winds.

How to cite: Gentile, E. S., Zhao, M., and Hodges, K.: Poleward intensification of midlatitude extreme winds under warmer climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3675, https://doi.org/10.5194/egusphere-egu24-3675, 2024.

EGU24-3750 | ECS | Orals | AS1.22

Perturbation Energetics of the December 2022 Bomb Cyclone over North America 

Emerson DeLarme, Jianping Li, Hongyuan Zhao, Yuan Liu, and Ruipeng Sun

Bomb cyclones over land are an understudied phenomenon. As such, there are open questions about the underlying physical processes, for example, why do bomb cyclones stop deepening. Atmospheric energetics is a prevalent approach to solve such problems, however the commonly used method of Available Potential Energy is not valid at local scales. Therefore, this study aims to provide further insight into the life cycle of bomb cyclones, specifically over land, by conducting a case study of the bomb cyclone that occurred over North America at the end of December 2022, focusing on the energetics using the Perturbation Potential Energy (PPE) framework. Hourly ERA5 reanalysis data provides the improved time resolution needed to study the evolution of such a rapidly developing system. PPE analysis of the evolution of this bomb cyclone reveals a possible stop signal to the positive feedback loop associated with explosive deepening. Further research is needed to clarify the mechanics associated with this thermodynamic signal.

How to cite: DeLarme, E., Li, J., Zhao, H., Liu, Y., and Sun, R.: Perturbation Energetics of the December 2022 Bomb Cyclone over North America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3750, https://doi.org/10.5194/egusphere-egu24-3750, 2024.

EGU24-5188 | ECS | Posters on site | AS1.22

A climatology of Mediterranean cyclones and compound weather extremes 

Alice Portal, Olivia Martius, Shira Raveh-Rubin, and Jennifer L Catto

Mediterranean cyclones are the main driver of surface weather extremes in the Mediterranean region. In this work we establish a new procedure for the attribution of different types of meteorological extremes to Mediterranean cyclones, where we also distinguish the presence of different airflows (warm conveyor belts, dry intrusions) and fronts composing the structure of a cyclone. We apply the procedure to a dataset of rain-wind and wave-wind compound extremes extracted from ERA5 reanalysis in a recent climatological period, and show that the majority of weather compounds occurring in the Mediterranean area is indeed linked to the presence of a nearby cyclone. The association of compound rain-wind events with Mediterranean cyclones locally surpasses an 80% level, while interesting differences between transition seasons and winter are detected. Winter cyclones - generally stronger, larger and distinctively baroclinic - are associated with a higher compound density. The de-construction of the cyclone in airflows and fronts evidences a strong association of rain-wind compounds with regions of warm conveyor belt ascent, and of wave-wind compounds with regions of dry intrusion outflow.

How to cite: Portal, A., Martius, O., Raveh-Rubin, S., and Catto, J. L.: A climatology of Mediterranean cyclones and compound weather extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5188, https://doi.org/10.5194/egusphere-egu24-5188, 2024.

EGU24-6370 | ECS | Posters on site | AS1.22

A catastrophe model for Windstorm in Italy: developing a stochastic windstorm event set adjusted with open-access reanalysis datasets 

Lorenzo Aiazzi, Simone Persiano, Michele Bottazzi, Glauco Gallotti, Antonio Petruccelli, Farid Ait-Chaalal, and Giovanni Leoncini

Windstorms are one of the most destructive natural disasters in Europe, causing considerable human and economic impacts, ranging from fatalities and injuries to damage to agriculture, infrastructures, and properties. The European Commission’s Joint Research Centre (JRC) estimates annual losses of 5 €-billion for the European Union and United Kingdom (Spinoni et al., 2020). While in these areas there is not high confidence on the projected changes in windstorm intensity and frequency due to climate change (Ranasinghe et al., 2021), damages resulting from windstorms will most likely increase in the future due to the appreciation of asset values (Spinoni et al., 2020).

Although Italy is one of the most affected European countries, with annual absolute losses estimated above 0.5 €-billion (Spinoni et al., 2020), windstorm is still considered to be a secondary peril. However, severe windstorm events in the last few years (e.g., Storm Vaia in October 2018) have raised an increasing interest of the Italian insurance industry in understanding and modelling this peril.

In this context, we aim at developing a catastrophe model that quantifies the financial impacts of windstorms on the insurance market in Italy. To this aim, here we perform the calibration of a stochastic windstorm event set for the hazard component of the model. Uncalibrated footprints are obtained from simulation outputs of global and regional numerical models. Then, historical event footprints are extracted from open-access reanalysis datasets (e.g., ERA5, CERRA) and used to correct the climatology of the stochastic set and to adjust the wind-speeds of its individual events. This analysis is expected to be preparatory for the development of a comprehensive catastrophe model that combines wind hazard with exposure and vulnerability to assess windstorm-related financial losses in Italy.

 

References:

Ranasinghe, R., et al., 2021: Climate Change Information for Regional Impact and for Risk Assessment. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., et al., (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1767–1926, doi: 10.1017/9781009157896.014.

Spinoni, J., et al., 2020: Global warming and windstorm impacts in the EU, EUR 29960 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-12955-4, doi:10.2760/039014. JRC118595.

How to cite: Aiazzi, L., Persiano, S., Bottazzi, M., Gallotti, G., Petruccelli, A., Ait-Chaalal, F., and Leoncini, G.: A catastrophe model for Windstorm in Italy: developing a stochastic windstorm event set adjusted with open-access reanalysis datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6370, https://doi.org/10.5194/egusphere-egu24-6370, 2024.

EGU24-7310 | ECS | Orals | AS1.22

Unlocking the dynamics of extreme wind speeds of North Atlantic storms 

Jun-Hyeok Son, Christian L.E. Franzke, and Seok-Woo Son

North Atlantic extra-tropical storms are some of the most severe weather systems, causing enormous economic damages and threatening human lives. In general, these storms are characterized by strong cyclonic convergent surface winds, upward vertical flow, and precipitation. In specific confined areas inside the storm where downward flows occur with clear sky, extreme surface wind speeds are observed. Such a horizontal variation of vertical wind direction and surface wind speed can cause severe and damaging impacts; however, the underlying key dynamics are not understood. Here we show the dynamical and thermodynamical linkage between the horizontal wind impinging on the frontal surface at the lower troposphere, downward flow, and very intense surface wind speeds inside the storm. The anti-clockwise cyclonic wind into the cold frontal area is mainly responsible for generating the downward flow, which transports the high-altitude horizontal momentum to the surface layer causing intense surface wind speeds. About half of North Atlantic storms accompany the downward wind, and that downward flow is more frequently observed in the southern and western part of the storm center. Overall results illuminated in this paper have a far-reaching impact in multiple ways to enhance forecasting skills for devastating weather events associated with extra-tropical storms.

How to cite: Son, J.-H., Franzke, C. L. E., and Son, S.-W.: Unlocking the dynamics of extreme wind speeds of North Atlantic storms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7310, https://doi.org/10.5194/egusphere-egu24-7310, 2024.

EGU24-7801 | ECS | Posters on site | AS1.22

Environmental Characteristics Associated with the Tropical Transition of Mediterranean Cyclones 

Lisa Bernini, Leone Cavicchia, Fabien Desbiolles, Antonio Parodi, Claudia Pasquero, and Enrico Scoccimarro

Using tracks from a reference dataset (Flaounas et al., 2023), cyclones in the Mediterranean Sea have been classified based on thermal winds (Hart, 2003). This classification allowed us to explore the major differences between extra-tropical cyclones with a cold inner core and tropical-like cyclones with a
deep inner warm core. For that purpose, the time evolution along the cyclones’ lifetime of different environmental characteristics taken from the ERA5 reanalysis has been studied. Warm-core cyclones are characterized by higher surface wind speeds, larger air-sea fluxes, and more intense precipitations. In comparison to cold-core cyclones, their development is favored by low wind shear and high moisture levels in the mid-troposphere. Different proxies also attest the major importance of the convective process in the establishment of the warm core. Finally, their dissipation seems to be driven by an abrupt decrease in the mid-level moisture content. This decrease is possibly related to the occlusion phase of the cyclone, and not to a limitation of moisture supply at the surface due to landfall.

How to cite: Bernini, L., Cavicchia, L., Desbiolles, F., Parodi, A., Pasquero, C., and Scoccimarro, E.: Environmental Characteristics Associated with the Tropical Transition of Mediterranean Cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7801, https://doi.org/10.5194/egusphere-egu24-7801, 2024.

EGU24-8101 | ECS | Posters on site | AS1.22

Past and future Mediterranean cyclone characteristics using a regional climate model 

Onno Doensen, Martina Messmer, Woon Mi Kim, and Christoph Raible

Extratropical cyclones play a dominant role in the Mediterranean. They are important for local water supplies, but they can also cause severe damage due to heavy winds, extreme precipitation and coastal floods. Over the last decades, a decrease in the number of extratropical cyclones in the Mediterranean has been observed. Climate models suggest that this decreasing trend will continue in the future under global warming, leading to fewer storms and dryer conditions over the region compared to the present. However, it is much less clear how extreme cyclones in the Mediterranean will respond to climate change. Our previous study, based on a simulation from the Community Earth System Model (CESM) covering the last 3500 years, indicates that extreme cyclones show a distinct centennial variability in frequency, cyclone-related precipitation and wind speed. In addition, we found a weak relation between atmospheric circulation modes and varying cyclone characteristics across different regions in the Mediterranean. However, the coarse horizontal resolution of CESM (2.0°×2.5°) is not very well suited to resolve the mesoscale cyclones that often occur in the Mediterranean. For this study, we downscaled the CESM simulation for the period 1821–2100 (RCP8.5 scenario from 2005 onwards) to a horizontal grid resolution of 20 km using the Weather Research and Forecasting (WRF) model. The WRF simulation can resolve the cyclone characteristics in the Mediterranean more accurately than CESM. Additionally, the WRF simulation is able to reproduce the complexity of cyclone-related wind speed and precipitation in a much more detailed way. Preliminary results show a strong decrease in cyclone frequency as a result of global warming. However, this trend is much less clear for extreme cyclones with respect to wind speed and precipitation. Using the long downscaled WRF simulation, we intend to identify characteristics in CESM that lead to extreme wind and precipitation in the downscaled simulation. Additionally, we will investigate the most extreme wind and precipitation events in the Mediterranean to understand what processes are better captured at smaller scales than in the global model.

How to cite: Doensen, O., Messmer, M., Kim, W. M., and Raible, C.: Past and future Mediterranean cyclone characteristics using a regional climate model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8101, https://doi.org/10.5194/egusphere-egu24-8101, 2024.

EGU24-10642 | ECS | Orals | AS1.22

Synoptic perspective on the conversion and maintenance of local available potential energy in extratropical cyclones 

Marc Federer, Lukas Papritz, Michael Sprenger, Christian M. Grams, and Marta Wenta

The global atmospheric circulation is maintained by the conversion of available potential energy (APE) into kinetic energy. At midlatitudes, this conversion occurs to a large extent in extratropical cyclones through baroclinic instability. Although kinetic energy is easily defined locally, APE is typically defined as a global integral. Therefore, local APE conversion is not well understood.

Here, we investigate local APE conversion within the North Atlantic storm track using ERA5 reanalysis data. We utilize a recently introduced formulation of APE, which is exact and defined locally for individual air parcels. First, we explore APE conversion during a period of rapid cyclogenesis, which we then extend to a climatology of extratropical cyclones.

Our results indicate that the synoptic upper-level flow determines the distribution of high APE values, which are primarily located in the high-latitude upper troposphere. We show that APE is converted locally into kinetic energy by descending air parcels within the ageostrophic circulation, for example, induced by a jet streak upstream of an extratropical cyclone. The local APE originates not only from advection from the polar, upper-tropospheric APE reservoir, but also from local generation by vertical motion. In fact, the net baroclinic conversion of APE to kinetic energy is the result of much larger positive and negative local contributions. Thus, the global Lorenz energy cycle is more complex on synoptic scales. In addition, we show that surface heat fluxes resulting from air-sea interactions and latent heat release act as diabatic sinks for APE. However, the effect of surface heat fluxes is small compared to the conversion of APE to kinetic energy, as little APE is located in the mid-latitude lower troposphere.

In summary, the study shows that the local APE perspective allows the energetics of North Atlantic extratropical cyclones to be better understood in terms of local APE advection as well as adiabatic (ascent and descent) and diabatic effects.

How to cite: Federer, M., Papritz, L., Sprenger, M., Grams, C. M., and Wenta, M.: Synoptic perspective on the conversion and maintenance of local available potential energy in extratropical cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10642, https://doi.org/10.5194/egusphere-egu24-10642, 2024.

EGU24-11704 | Posters on site | AS1.22

Climate change signature on Euro-Mediterranean lee cyclogenesis 

Lorenzo Sangelantoni, Stefano Tibaldi, Leone Cavicchia, Daniele Peano, and Enrico Scoccimarro

This study explores whether and why a warmer climate induces alterations in climatological statistics and the underlying physical features of lee cyclogenesis in the Euro-Mediterranean region.

The investigation focuses on a specific cyclogenesis type, wherein orography (the Alps), influences the spatial structure and growth rate of the cyclone.

This regional scale phenomenon is inspected within the framework of a general weakening and poleward shift of the mid-latitude jet. This large-scale signal, despite being evident in zonal-averaged results from the majority of climate models, remains subject to considerable uncertainty when specific regions and seasons are considered. This uncertainty stems from the intricate interplay and delicate equilibrium among numerous competing mechanisms.

The analysis focuses on historical and future trends during the cold semesters across the Euro-Mediterranean region. The historical period is examined using ERA5 reanalysis spanning from 1940 to the present, supplemented by a higher-resolution regional reanalysis product (COSMO-REA6) at approximately 6 km resolution, covering the period 1995-2019 over the Euro-CORDEX (EUR11) domain. State-of-the-art high-resolution climate models are employed to assess historical reproducibility and future trends through an ensemble of global climate models from the HighResMIP initiative.

Methodologically, two distinct approaches are pursued. Firstly, changes in statistical properties of lee cyclogenesis are examined, along with composites of precipitation and wind extremes footprint, utilizing two tracking algorithms: TempestExtremes (Ullrich et al., 2021) and TRACK (Hodges, 1994). These algorithms differ in their identification/tracking variables, i.e., mean sea level pressure and 850hPa relative vorticity, respectively. Secondly, an empirical orthogonal function (EOF) analysis is employed to evaluate whether dominant spatial patterns of relevant variables (e.g., mean sea level pressure and 500hPa geopotential height) associated with cyclogenesis undergo significant changes across different time segments.

This investigation is conducted as a spin-off of the Copernicus-ECMWF-funded contract C3S2_413 - Enhanced Operational Windstorm Service. The findings aim to enhance our understanding of the complex dynamics of Euro-Mediterranean lee cyclogenesis in the context of a changing climate, providing further insights for climate science and operational windstorm services.

How to cite: Sangelantoni, L., Tibaldi, S., Cavicchia, L., Peano, D., and Scoccimarro, E.: Climate change signature on Euro-Mediterranean lee cyclogenesis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11704, https://doi.org/10.5194/egusphere-egu24-11704, 2024.

EGU24-13459 | ECS | Orals | AS1.22

Assessing high-resolution global climate models in simulating subtropical cyclones over the southeast coast of Brazil 

Andressa Andrade Cardoso and Rosmeri Porfírio da Rocha

Subtropical cyclones when occurring close to the coast can be very dangerous for human activities bringing high amounts of precipitation, intense winds and gusts in the coastal cities. This can lead to natural hazards and risks, such as floods, inundations, and even deaths. Over the southeast coast of Brazil, seven subtropical cyclones occur on average each year, with higher frequency in austral summer and autumn.  However, there are still few studies focusing on its global models climatology and future projections. It is crucial to evaluate how accurate are the global climate models of the new HighResMIP-CMIP6 dataset, with fine horizontal high-resolution, in representing subtropical cyclones in the historical period. Thus, this study assesses the classification of the subtropical cyclones based on two reanalyses (ERA5 and ERA-Interim) to evaluate the fine-resolution HighResMIP-CMIP6 datasets.  First, we tracked all cyclones over the South Atlantic Ocean applying an automatic scheme using relative vorticity at 925 hPa. Then, the vertical structure of the cyclones are accessed by calculating three parameters (symmetry, thermal wind at low and upper levels) from the cyclone phase space approach. Finally, we classified subtropical features using an automatic scheme based on a pre-establish threshold. In general, the approach is able for classifying subtropical cyclones providing realistic climatology. Overall, for the total of cyclones, ERA5, ERAInterim and HighResMIP-CMIP6 reproduce similar areas of great cyclogenetic activity over the eastern coast of South America.  In terms of frequency, it is greater in ERA5 than ERAInterim, for both total and subtropical cyclones, while a similar behavior is noted in relation to the seasonal frequency. HighResMIP-CMIP6 tends to overestimate the total of cyclones in subtropical latitudes, impacting directly the frequency of the subtropical ones. 

How to cite: Andrade Cardoso, A. and Porfírio da Rocha, R.: Assessing high-resolution global climate models in simulating subtropical cyclones over the southeast coast of Brazil, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13459, https://doi.org/10.5194/egusphere-egu24-13459, 2024.

EGU24-14305 | Posters on site | AS1.22

Towards AI-enhanced prediction of Mediterranean cyclones 

Leone Cavicchia, Enrico Scoccimarro, and Silvio Gualdi

Intense cyclones form frequently in the Mediterranean region, with the potential to cause damage to life and property when they hit highly populated coastal areas. Cyclone impacts are caused by the associated strong winds, flash flooding and storm surge. The social and economic impacts are not limited to the Mediterranean area, as cyclones forming in the region can affect Central Europe. While the skill of weather models to forecast such events has dramatically improved over the last decade, the seasonal predictability of Mediterranean cyclones lags behind due to the limitations on horizontal resolution in probabilistic forecasts requiring a large ensemble of simulationss. Improving the climate prediction at a seasonal scale of those extreme events would be of great benefit for society, enabling better disaster risk management and reducing the economic losses they cause. A better prediction of climate extremes would also directly benefit a number of economic sectors such as the insurance and re-insurance industry.

The ambition of the CYCLOPS project is to use Artificial Intelligence techniques to enhance the prediction skills of Mediterranean cyclones in a state-of-the-art Seasonal Prediction System. Here we present initial results making use of AI to link those extreme events to their large-scale driver. The training of different machine learning models is performed using ERA5 reanalysis data. The assessment of model skill is evaluated on the C3S operational seasonal forecast in hindcast mode. The performance of machine learning models of varying complexity (e.g. random forest, artificial neural networks) is evaluated.

How to cite: Cavicchia, L., Scoccimarro, E., and Gualdi, S.: Towards AI-enhanced prediction of Mediterranean cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14305, https://doi.org/10.5194/egusphere-egu24-14305, 2024.

EGU24-14720 | ECS | Posters on site | AS1.22

Mergers as the Maintenance Mechanism of Cutoff Lows: A Case Study over Europe in July 2021 

Koryu Yamamoto, Keita Iga, and Akira Yamazaki

A cutoff low that covered Central Europe in the middle of July 2021 brought heavy rainfall and severe flooding, resulting in more than 200 fatalities. This low was formed by a trough on 11 July and merged with another cutoff low around 12–13 July. Analysis of the energy budget and potential vorticity suggests that the main cutoff low was maintained through the merger with another cutoff low; this was the dominant contributor to maintenance of the main cutoff low around 12–13 July. The results of Lagrangian trajectory analyses support this conclusion. Analysis of diabatic PV modification during the merger indicates that radiation acts mainly to enhance the potential vorticity of the parcels when they move from another cutoff low into the main cutoff low, especially in the upper layer (~ 350 K). However, that effect is not pronounced in the lower layer (~ 330 K). These results demonstrate that cutoff lows can be maintained through the merger with another cutoff low and underline the need to consider diabatic processes when investigating mergers.

How to cite: Yamamoto, K., Iga, K., and Yamazaki, A.: Mergers as the Maintenance Mechanism of Cutoff Lows: A Case Study over Europe in July 2021, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14720, https://doi.org/10.5194/egusphere-egu24-14720, 2024.

EGU24-16593 | ECS | Posters on site | AS1.22

High-impact storms during the extended winters of 2018–2021 in the Iberian Peninsula 

Ana C. R. Gonçalves, Raquel Nieto, and Margarida L. R. Liberato

During the extended winter period from December 2017 to April 2021, the Iberian Peninsula (IP) was impacted by several high-impact storms characterized by intense precipitation and/or strong winds. This study provides a detailed assessment of the events, including synoptic conditions, large-scale dynamics associated with the storms, and a climatological analysis aimed at improving public understanding and preventing natural disasters. The analysis of the cyclones’ variability indicates that their maximum intensity varies between 955 hPa and 985 hPa, with a duration of two to four days, and the most frequent occurrence (eight events) was in January. At the peak of maximum intensity, the composite anomaly patterns showed lower mean sea level pressure (MSLP) values (−21.6 hPa), higher water vapor values (327.6 kg m−1s−1), and wind speed at 250 hPa exceeding 29.6 m s−1 the mean values. Additionally, there were high anomaly values of equivalent potential temperature (θe) of 19.1 °C at 850 hPa, sea surface temperature (SST) anomaly values of −1 °C, and negative anomaly values of surface latent heat flux (QE) (−150 W m−2) close to the IP. During the days impacted by the storms, the recorded values surpassed the 98th percentile in a significant percentage of days for daily accumulated precipitation (34%), instantaneous wind gusts (46%), wind speed at 10 m (47%), and concurrent events of wind/instantaneous wind gusts and precipitation (26% and 29%, respectively). These findings allow us to describe their meteorological consequences on the IP, particularly the effects resulting from intense precipitation such as floods, and strong winds associated with various destructive impacts. Finally, clear, real-time, and predictive information about weather systems and their impacts is crucial for the public to understand and enable effective responses to mitigate these natural hazards damage.

Keywords: extreme events; extratropical cyclones; explosive development cyclones; winter storms; Iberian Peninsula.

 

Acknowledgments

This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC)–UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020), and project WEx-Atlantic (PTDC/CTAMET/29233/2017, LISBOA-01-0145-FEDER-029233, NORTE-01-0145-FEDER-029233). FCT is also providing for Ana Gonçalves doctoral grant (2021.04927.BD). The EPhysLab group was also funded by Xunta de Galicia, Consellería de Cultura, Educación e Universidade, under project ED431C 2021/44 “Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas.

 

 References

Gonçalves, A.C.R.; Nieto, R.; Liberato, M.L.R. Synoptic and Dynamical Characteristics of High-Impact Storms Affecting the Iberian Peninsula during the 2018–2021 Extended Winters. Atmosphere 2023, 14, 1353. https://doi.org/10.3390/atmos14091353

How to cite: C. R. Gonçalves, A., Nieto, R., and L. R. Liberato, M.: High-impact storms during the extended winters of 2018–2021 in the Iberian Peninsula, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16593, https://doi.org/10.5194/egusphere-egu24-16593, 2024.

EGU24-16634 | ECS | Posters on site | AS1.22

Drivers of Cold Frontal Hourly Extreme Precipitation: A Climatological Study 

Armin Schaffer, Tobias Lichtenegger, Douglas Maraun, Heimo Truhetz, and Albert Ossó

Understanding the processes driving extreme precipitation is paramount to socioeconomic interest. In the mid-latitudes extreme precipitation events are strongly associated with cold fronts. By exploring drivers across a wide range of scales, this study aims to improve our understanding of processes influencing frontal precipitation. Past research predominately focused on detailed studies of individual frontal extreme events. Here we present the first climatological study of frontal characteristics and their impact on precipitation.
Using hourly resolved ERA5 data, cold fronts are detected using the equivalent potential temperature gradient, and associated conditions from the synoptic to the meso-scale are identified. Further, seasonal and regional dependencies are explored. Quantile regression models are employed to find the strongest drivers of frontal precipitation and to quantify these relationships. Additionally, composite analysis are used to study the synoptic conditions and meso-scale structure of extreme events.
Findings reveal that humidity close to the frontal boundary, convergence of different scales and the low level jet speed contribute most to formation of extreme precipitation events. Interestingly, we discovered that stronger fronts, characterized by a significant change in humidity, do not always lead to a higher chance of extreme precipitation. This is evident in the weak correlation between the humidity gradient and frontal precipitation, in contrast with the relationship observed for the temperature gradient.
The findings of this study improve our understanding of cold frontal processes. Additionally, they provide the foundation to evaluate model performance and climate change projections. 

How to cite: Schaffer, A., Lichtenegger, T., Maraun, D., Truhetz, H., and Ossó, A.: Drivers of Cold Frontal Hourly Extreme Precipitation: A Climatological Study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16634, https://doi.org/10.5194/egusphere-egu24-16634, 2024.

EGU24-17127 | ECS | Orals | AS1.22

A Cold Frontal Life Cycle Climatology and Front-Cyclone Relationships over the North Atlantic and Europe during Winter 

Tobias Lichtenegger, Armin Schaffer, Douglas Maraun, Albert Osso Castillon, and Heimo Truhetz

Atmospheric fronts and cyclones play an important role in day-to-day weather variability, especially in the mid-latitudes and during the winter season. Severe rainfall and windstorm events are often associated with the passage of a front or a cyclone. While there are many studies of individual fronts and climatologies based on objectively detected fronts, there is no comprehensive study considering the whole frontal life cycle over time. Therefore, a front and cyclone tracking algorithm, based on overlapping features at consecutive time steps, is used together with an improved front detection method to detect and track cold fronts and cyclones over the North Atlantic and Europe in the extended winter season (October - March) in the ERA5 reanalysis dataset. Several life cycle characteristics, e.g. the duration, velocity, frontogenesis and -lysis regions as well as dynamic and thermodynamic frontal parameters are defined to investigate the frontal life cycle and the conditions and processes in the frontal region. Fronts are linked to their parent cyclone to study relationships between frontal and cyclonic properties. The study confirms that fronts are mostly formed over the western and central North Atlantic and travelling along the main storm track into the European continent. During positive phases of the North Atlantic Oscillation, fronts are travelling faster and further and are associated with stronger precipitation and surface wind speeds over their whole life cycle. Stronger cyclones are related to stronger dynamics in the frontal region.

How to cite: Lichtenegger, T., Schaffer, A., Maraun, D., Osso Castillon, A., and Truhetz, H.: A Cold Frontal Life Cycle Climatology and Front-Cyclone Relationships over the North Atlantic and Europe during Winter, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17127, https://doi.org/10.5194/egusphere-egu24-17127, 2024.

EGU24-18002 | ECS | Orals | AS1.22

Power outages in windstorms: the influence of rainfall preconditioning, wind direction and season 

Colin Manning, Sean Wilkinson, Hayley Fowler, Elizabeth Kendon, and Sarah Dunn

Windstorms are the main cause of large power outages in the UK. Faults to electricity distribution networks during windstorms are predominantly a result of windthrow, the uprooting or breakage of trees by winds that then fall on assets such as overhead lines. The impact of strong winds on windthrow is influenced by a several conditions: trees uproot more easily in saturated soils, they are more vulnerable to strong winds from unusual directions, and they are more susceptible to strong winds in the growing season when their leaves catch the wind. Despite this, risk assessments of impacts, such as power outages, during windstorms generally focus on wind intensity alone. Here, we quantify the influence of contributing variables of windthrow including antecedent rainfall, wind direction of the maximum wind gust, and the season a windstorm occurs in. We demonstrate that including them in a logistic regression model alongside wind speed can improve the predictive skill of the number of electricity faults during windstorms compared to a reference model that only includes wind speed. The analysis uses fault data from the National Fault and Interruption Scheme (NaFIRs) database during the period 2006-2018 in four regions in the UK: South Wales, Southwest England, East Midlands, and West Midlands. Meteorological data is provided by ERA5. Each variable is shown to modulate the impact of strong winds and improve predictive skill, though with some regional variability. The probability of a high fault numbers in a windstorm with winds exceeding 25 m/s can be doubled following high rainfall accumulations and five times higher when strong winds come from a direction that deviates more than 40 degrees south or west from the prevailing south-westerly direction. Furthermore, this probability is doubled in summer months compared to winter. These results can help improve impact forecasting during windstorms and highlight the importance of including these variables in historical and future risk assessments of assets vulnerable to windthrow. Ignoring such contributions may lead to misrepresentation of risk and potential maladaptation, particularly for electricity distribution networks that will undergo a huge transformation as we reduce our dependence on greenhouse gases in the future.

How to cite: Manning, C., Wilkinson, S., Fowler, H., Kendon, E., and Dunn, S.: Power outages in windstorms: the influence of rainfall preconditioning, wind direction and season, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18002, https://doi.org/10.5194/egusphere-egu24-18002, 2024.

EGU24-19896 | ECS | Posters on site | AS1.22

Climate change's influence on Cut-off Lows in the future 

Aditya N. Mishra, Douglas Maraun, Reinhard Schiemann, Kevin Hodges, and Giuseppe Zappa

Cut-off Lows (COLs) are mid-latitude storms that are detached from the main westerly flow. They tend to propagate slower than other mid-latitude storms and are often harbingers of heavy and persistent rainfall. COLs have long been subject to thorough studies that have examined the physical structure and climatology across both hemispheres, however, their assessment in models is relatively low. In fact, there is no study on future changes in COLs in models. In this study, we analyze the cut-off lows in the northern hemisphere in the historic and future time slices in the CMIP6 dataset to study the frequency, duration, and intensity of the cut-off lows alongside the changes in velocity. Results show that the COL season, which is currently mostly limited to summer, extends into spring over Europe, North America, and Asia. This rise in activity in spring is more pronounced for COLs that are long-lasting and also have higher intensity maxima, i.e., the most impactful ones. Moreover, COL propagation velocity for persistent systems is due to slow down over North America in the summer. Slow-moving COLs are known to cause heavy localized rainfall. Through this study, we fill the information gap on the first insights of projected future changes in COLs by using TRACK to detect and trace COLs in the SSP5-8.5 projections of the CMIP6 ensemble.

 

How to cite: Mishra, A. N., Maraun, D., Schiemann, R., Hodges, K., and Zappa, G.: Climate change's influence on Cut-off Lows in the future, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19896, https://doi.org/10.5194/egusphere-egu24-19896, 2024.

EGU24-20374 | ECS | Orals | AS1.22

How do winter-time extratropical cyclones change in the future over South Africa? 

Sandeep Chinta, Adam Schlosser, Xiang Gao, and Kevin Hodges

Extratropical cyclones (ETCs) in South Africa usually occur during the winter (June to August), specifically influencing the Western Cape, causing extreme rain and strong winds. We investigate future changes in these winter-time ETCs using the simulations from three CORDEX-CORE Africa models. Each of these models was driven by three Coupled Model Intercomparison Project phase 5 (CMIP5) General Circulation Models (GCMs), resulting in nine sets of simulations. The simulations are from 1970-2100, with scenarios starting from 2006. We identified the cyclone tracks using the Hodges tracking algorithm, which used 6-hourly relative vorticity data at 850 hPa level. We chose a 20-year historical period from 1986 to 2005 for comparison with a future period of the same length from 2080 to 2099, focusing on the Representative Concentration Pathway (RCP) 8.5 scenario for the future projections. We observed a projected decrease in the number of ETCs in the future. The average track distance and duration are also projected to reduce. These reductions are statistically significant. We explored the future changes in the ETC-associated rainfall, which is also projected to be reduced in the future. We are currently looking at extending our analysis with the high-resolution 4 km gridded Climate Predictions for Africa (CP4A) data and see how our earlier results compare with the high-resolution data.

How to cite: Chinta, S., Schlosser, A., Gao, X., and Hodges, K.: How do winter-time extratropical cyclones change in the future over South Africa?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20374, https://doi.org/10.5194/egusphere-egu24-20374, 2024.

EGU24-3548 | Posters on site | AS1.2

Improving the Completion of Weather Radar Missing Data with Deep Learning 

Aofan Gong, Haonan Chen, and Guangheng Ni

Weather radars commonly suffer from the data-missing problem that limits their data quality and applications. Traditional methods for the completion of weather radar missing data, which are based on radar physics and statistics, have shown defects in various aspects. Several deep learning (DL) models have been designed and applied to weather radar completion tasks but have been limited by low accuracy. This study proposes a dilated and self-attentional UNet (DSA-UNet) model to improve the completion of weather radar missing data. The model is trained and evaluated on a radar dataset built with random sector masking from the Yizhuang radar observations during the warm seasons from 2017 to 2019, which is further analyzed with two cases from the dataset. The performance of the DSA-UNet model is compared to two traditional statistical methods and a DL model. The evaluation methods consist of three quantitative metrics and three diagrams. The results show that the DL models can produce less biased and more accurate radar reflectivity values for data-missing areas than traditional statistical methods. Compared to the other DL model, the DSA-UNet model can not only produce a completion closer to the observation, especially for extreme values, but also improve the detection and reconstruction of local-scale radar echo patterns. Our study provides an effective solution for improving the completion of weather radar missing data, which is indispensable in radar quantitative applications.

How to cite: Gong, A., Chen, H., and Ni, G.: Improving the Completion of Weather Radar Missing Data with Deep Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3548, https://doi.org/10.5194/egusphere-egu24-3548, 2024.

EGU24-5373 | ECS | Orals | AS1.2 | Highlight

Convective environments in AI-models - What have AI-models learned about atmospheric profiles? 

Monika Feldmann, Louis Poulain-Auzeau, Milton Gomez, Tom Beucler, and Olivia Martius
The recently released suite of AI-based medium-range forecast models can produce multi-day forecasts within seconds, with a skill on par with the IFS model of ECMWF. Traditional model evaluation predominantly targets global scores on single levels. Specific prediction tasks, such as severe convective environments, require much more precision on a local scale and with the correct vertical gradients in between levels. With a focus on the North American and European convective season of 2020, we assess the performance of Panguweather, Graphcast and Fourcastnet for convective available potential energy (CAPE) and storm relative helicity (SRH) at lead times of up to 7 days.
Looking at the example of a US tornado outbreak on April 12 and 13, 2020, all models predict elevated CAPE and SRH values multiple days in advance. The spatial structures in the AI-models are smoothed in comparison to IFS and the reanalysis ERA5. The models show differing biases in the prediction of CAPE values, with Graphcast capturing the value distribution the most accurately and Fourcastnet showing a consistent underestimation.
By advancing the assessment of large AI-models towards process-based evaluations we lay the foundation for hazard-driven applications of AI-weather-forecasts.

How to cite: Feldmann, M., Poulain-Auzeau, L., Gomez, M., Beucler, T., and Martius, O.: Convective environments in AI-models - What have AI-models learned about atmospheric profiles?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5373, https://doi.org/10.5194/egusphere-egu24-5373, 2024.

EGU24-5571 | ECS | Orals | AS1.2

SHADECast: Enhancing solar energy integration through probabilistic regional forecasts 

Alberto Carpentieri, Doris Folini, Jussi Leinonen, and Angela Meyer

Surface solar irradiance (SSI) is a pivotal component in addressing climate change. As an abundant and non-fossil energy source, it is harnessed through photovoltaic (PV) energy production. As the contribution of PV to total energy production grows, the stability of the power grid faces challenges due to the volatile nature of solar energy, predominantly influenced by stochastic cloud dynamics. To address this challenge, there is a need for accurate, uncertainty-aware, near real-time, and regional-scale SSI forecasts with forecast horizons ranging from minutes to a few hours.

Existing state-of-the-art SSI nowcasting methods only partially meet these requirements. In our study, we introduce SHADECast [1], a deep generative diffusion model designed for probabilistic nowcasting of cloudiness fields. SHADECast is uniquely structured, incorporating deterministic aspects of cloud evolution to guide the probabilistic ensemble forecast, relying only on previous satellite images. Our model showcases significant advancements in forecast quality, reliability, and accuracy across various weather scenarios.

Through comprehensive evaluations, SHADECast demonstrates superior performance, surpassing the state of the art by 15% in the continuous ranked probability score (CRPS) over diverse regions up to 512 km × 512 km, extending the state-of-the-art forecast horizon by 30 minutes. The conditioning of ensemble generation on deterministic forecasts further enhances reliability and performance by more than 7% on CRPS.

SHADECast forecasts equip grid operators and energy traders with essential insights for informed decision-making, thereby guaranteeing grid stability and facilitating the smooth integration of regionally distributed PV energy sources. Our research contributes to the advancement of sustainable energy practices and underscores the significance of accurate probabilistic nowcasting for effective solar power grid management.

 

References

[1] Carpentieri A. et al., 2023, Extending intraday solar forecast horizons with deep generative models. Preprint at ArXiv. https://arxiv.org/abs/2312.11966 

How to cite: Carpentieri, A., Folini, D., Leinonen, J., and Meyer, A.: SHADECast: Enhancing solar energy integration through probabilistic regional forecasts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5571, https://doi.org/10.5194/egusphere-egu24-5571, 2024.

EGU24-5849 | ECS | Posters on site | AS1.2

Towards seamless rainfall and flood forecasting in the Netherlands: improvements to and validation of blending in pysteps 

Ruben Imhoff, Michiel Van Ginderachter, Klaas-Jan van Heeringen, Mees Radema, Simon De Kock, Ricardo Reinoso-Rondinel, and Lesley De Cruz

Flood early warning in fast responding catchments challenges our forecasting systems. It requires frequently updated, accurate and high-resolution rainfall forecasts to provide timely warning of rainfall amounts that will reach a catchment in the coming hours. The Netherlands is a typical example, with polder systems below sea level, a high level of urbanization and catchments with short response times. The need for better short-term rainfall forecasts is clearly present, but this is generally not feasible with numerical weather prediction (NWP) models alone. Hence, an alternative rainfall forecasting method is desirable for the first few hours into the future.

Rainfall nowcasting can provide this alternative but quickly loses skill after the first few hours. A promising way forward is a seamless forecasting system, which tries to optimally combine rainfall products from nowcasting and NWP. In this study, we applied the STEPS blending method to combine rainfall forecasts from ensemble radar nowcasts with those from the Harmonie-AROME configuration of the ACCORD NWP model in the Netherlands. This blending method is part of the open-source nowcasting initiative pysteps. To make blending possible in an operational setup, including the needs of involved water authorities, we made several adjustments to the blending implementation in pysteps, for instance:

  • We reduced the computational time by using a faster preprocessing and advection scheme.
  • We improved the noise initialization (needed for generating ensemble members) to allow for stable forecasts, also when one or both product(s) contain(s) no rain.
  • We enabled a dynamic disaggregation of the 1-hour resolution NWP forecasts to match the temporal resolution of the radar nowcast.

We operationalized the updated blending framework in the flood forecasting platforms of the involved water authorities. Given a forecast duration of 12 hours for the blended forecast and a 10-minute time step, average computation times are 3.4 minutes for a deterministic run and 12.3 minutes for an ensemble forecast with 10 members on a 4-core machine. Preprocessing takes approximately 10 minutes and only needs to occur when a new NWP forecast is issued. We tested the implementation for an entire, rainy summer month (July 15 to August 15, 2023) and analyzed the results over the entire domain. The results demonstrate that the blending method effectively combines radar nowcasts with NWP forecasts. Depending on the statistical score considered (such as RMSE and critical success index), the blending method performs either better or on par with the best-performing individual product (radar nowcast or NWP). A consistent finding is that the blending closely tracks the nowcast quality during the initial 1 to 2 hours of the forecast (in this study, the nowcast had lower errors than NWP during the first 2 – 2.5 hours), after which it gradually transitions into the NWP forecast. At longer lead times, the seamless product retains local precipitation structures and extremes better than the NWP product. It does this by leveraging information from the radar nowcast and the stochastic perturbations. Based on these results, a seamless forecasting approach can be regarded as an improvement for the involved water authorities.

How to cite: Imhoff, R., Van Ginderachter, M., van Heeringen, K.-J., Radema, M., De Kock, S., Reinoso-Rondinel, R., and De Cruz, L.: Towards seamless rainfall and flood forecasting in the Netherlands: improvements to and validation of blending in pysteps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5849, https://doi.org/10.5194/egusphere-egu24-5849, 2024.

EGU24-5909 | ECS | Posters on site | AS1.2

Impact of Spatial Density of Automatic Weather Station Data on Assimilation Effectiveness in WRF-3DVar Model 

Zeyu Qiao, Bu Li, Aofan Gong, and Guangheng Ni

Implementing the 3-Dimensional Variational (3DVar) data assimilation technique using high-density automatic weather station (AWS) observations substantially improves the precipitation simulation and forecast capabilities in the Weather Research and Forecasting (WRF) model. Given the impact of spatial distribution and quantity of observation data on assimilation effectiveness, there is a growing need to assimilate the most efficient amount of observation data to improve the precipitation forecast accuracy, especially in the context of the proliferation of data from diverse sources. This study investigates the impacts of spatial density of assimilated data on enhancing model predictions, focusing on a squall line event in Beijing on 2 August 2017 which has approximately 2400 AWSs in the simulation domain. Seven experiment groups assimilating varying proportions of AWS data (3.125, 6.25, 12.5, 25, 50, 75, and 100 percent of total AWSs) were conducted, comprising 10 experiments per group. The results were then compared with the experiment without data assimilation (CTRL) and the observations. Results show that while the WRF model roughly captured the evolution of this event, it overestimated the precipitation amount with significant deviations in precipitation locations. A general positive correlation was observed between the spatial density of assimilated data and the enhancement in model performance. However, there is a notable threshold beyond which additional data ceases to enhance forecast accuracy. The model performs best when the ratio of the number of assimilated AWSs to the model simulated area reaches 1/40 km-2. Moreover, significant variations in improvement effects across experiments within the same group indicate the substantial impact of spatial distribution of assimilated AWSs on forecast outcomes. This study provides a reference for devising more efficient and cost-effective data assimilation strategies in numerical weather prediction.

How to cite: Qiao, Z., Li, B., Gong, A., and Ni, G.: Impact of Spatial Density of Automatic Weather Station Data on Assimilation Effectiveness in WRF-3DVar Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5909, https://doi.org/10.5194/egusphere-egu24-5909, 2024.

EGU24-6155 | ECS | Orals | AS1.2

Enhanced Foundation Model through Efficient Finetuning for Extended-Range Weather Prediction 

Shan Zhao, Zhitong Xiong, and Xiao Xiang Zhu

Weather forecasting is a vital topic in meteorological analysis, agriculture planning, disaster management, etc. The accuracy of forecasts varies with the prediction horizon, spanning from nowcasting to long-range forecasts. The extended range forecast, which predicts weather conditions beyond two weeks to months ahead, is particularly challenging. This difficulty arises from the inherent variability in weather systems, where minor disturbances in the initial condition can lead to significantly divergent future trajectories.

Numerical Weather Prediction (NWP) has been the predominant approach in this field. Recently, deep learning (DL) techniques have emerged as a promising alternative, achieving performance comparable to NWP [1, 2]. However, their lack of embedded physical knowledge often limits their acceptance within the research community. To enhance the trustworthiness of DL-based weather forecasts, we explore a transformer-based framework which considers complex geospatial-temporal (4D) processes and interactions. Specifically, we select the Pangu model [3] with a 24-hour lead time as the initial framework. To extend the prediction horizon to two weeks ahead, we employ a low-rank adaptation for model finetuning, which saves computation resources by reducing the number of parameters to only 1.1% of the original model. Besides, we incorporate multiple oceanic and atmospheric indices to capture a broad spectrum of global teleconnections, aiding in the selection of important features.

Our contributions are threefold: first, we provide an operational framework for foundation models, improving their applicability in versatile tasks by enabling training rather than limiting them to inference stages. Second, we demonstrate how to leverage these models with limited resources effectively and contribute to the development of green AI. Last, our method improves performance in extended-range weather forecasting, offering enhanced prediction skills, physical consistency, and finer spatial granularity. Our methodology achieved reduced RMSE on T2M, Z500, and T850 for 0.13, 139.2, and 0.52, respectively, compared to IFS. In the future, we plan to explore other settings, such as predicting precipitation and extreme temperatures.

REFERENCES
[1] Nguyen, Tung, et al. "ClimaX: A foundation model for weather and climate." arXiv preprint arXiv:2301.10343 (2023).
[2] Lam, Remi, et al. "Learning skillful medium-range global weather forecasting." Science (2023): eadi2336.
[3] Bi, Kaifeng, et al. "Accurate medium-range global weather forecasting with 3D neural networks." Nature 619.7970 (2023): 533-538.

How to cite: Zhao, S., Xiong, Z., and Zhu, X. X.: Enhanced Foundation Model through Efficient Finetuning for Extended-Range Weather Prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6155, https://doi.org/10.5194/egusphere-egu24-6155, 2024.

EGU24-6545 | Posters on site | AS1.2

Improving precipitation nowcasting using deep generative models: a case-study and experiences in R2O  

Kirien Whan, Charlotte Cambier van Nooten, Maurice Schmeits, Jasper Wijnands, Koert Schreurs, and Yuliya Shapovalova

Precipitation nowcasting is essential for weather-dependent decision-making. The combination of radar data and deep learning methods has opened new avenues for research. Deep learning approaches have demonstrated equal or better performance than optical flow methods for low-intensity precipitation, but nowcasting high-intensity events remains a challenge. We use radar data from the Royal Netherlands Meteorological Institute (KNMI) and explore various extensions of deep learning architectures (i.e. loss function, additional inputs) to improve nowcasting of heavy precipitation intensities. Our model outperforms other state-of-the-art models and benchmarks and is skilful at nowcasting precipitation for high rainfall intensities, up to 60-min lead time. 

Transferring research to operations is difficult for many meteorological institutes, particularly for new applications that use AI/ML methods. We discuss some of these challenges that KNMI is facing in this domain. 

How to cite: Whan, K., Cambier van Nooten, C., Schmeits, M., Wijnands, J., Schreurs, K., and Shapovalova, Y.: Improving precipitation nowcasting using deep generative models: a case-study and experiences in R2O , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6545, https://doi.org/10.5194/egusphere-egu24-6545, 2024.

EGU24-6856 | Posters on site | AS1.2

Very Short-Range Precipitation Forecast in Korea Meteorological Administration 

ho yong lee, Jongseong Kim, Joohyung Son, and Seong-Jin Kim

Korea Meteorological Administration (KMA) has been providing the public with an hourly precipitation forecast updated every 10 minutes for the next 6 hours since 2015. This forecasts, named as the Very Short-Range Forecast (VSRF), differs from other longer forecasts ? such as short-range and medium-range forecasts issued by forecasters. The VSRF is automatically generated by a system based on two different models: MAPLE (McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation) and KLAPS (Korea Local Analysis and Prediction System). 

MAPLE, based on Variational Echo Tracking (VET) from radar observations, has an intrinsic disadvantage: its performance decreases rapidly. On the other hand, numerical weather prediction systems like KLAPS are not initially as effective as MAPLE due to model balancing factors such as spin-up, but they maintain initial skill for a slightly longer period. Therefore, to provide the best predictions to the public, it is necessary to merge the two models properly. KMA conducted tests to determine the optimal way to utilize both models and established weights for each model based on their performance and precipitation tendencies. According to a 4-year evaluation, MAPLE outperforms for up to 2 hours, while KLAPS performs better after 4 hours. Consequently, the two models were merged with a hyperbolic tangent weight applied between 2 and 4 hours, and we named it as the best guidance. 

The best guidance was verified against precipitation observed by 720 raingauges over South Korea during the summer seasons from 2020 to 2023. It demonstrated better skill compared to both MAPLE and KLAPS. The average threat scores, with a rain intensity threshold of 0.5 mm/h throughout the forecast period, were 0.40 for the best guidance, 0.38 for MAPLE, and 0.35 for KLAPS.

The best guidance depends on both MAPLE and KLAPS. Therefore, KMA is actively working to improve the performance of each model. Additionally, a very short-range model based on AI is currently under development and running in semi-operations.

How to cite: lee, H. Y., Kim, J., Son, J., and Kim, S.-J.: Very Short-Range Precipitation Forecast in Korea Meteorological Administration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6856, https://doi.org/10.5194/egusphere-egu24-6856, 2024.

EGU24-6873 | Posters on site | AS1.2

Does more frequent Very Short-Range Forecast provide more useful information? 

Joohyung Son, Jongseong Kim, and Seongjin Kim

The Very Short-Range Forecast (VSRF) for precipitation from the Korea Meteorological Administration (KMA) is released every 10 minutes, providing forecasts for the next 6 hours at 10-minute intervals. However, when the forecast is provided to the public, it is updated at 10-minute interval, but only provides up to 6 hours at every hour. Consequently, from the public's perspective, forecasts for specific times may change every 10 minutes. While this allows users to access the latest updates, it also poses a challenge in terms of reduced reliability due to constantly changing predictions.

This study aims to assess the prediction performance and variability between forecasts released at 10-minute intervals and those at 1-hour intervals. We evaluated with the Very Short-Range Forecast numerical model KLAPS in VSRF and seek to determine which approach offers more valuable information from the public's standpoint. The assessment focuses on two distinct types of precipitation. The first involves convective showers, which sporadically appear over short durations, driven by atmospheric instability during the Korean Peninsula's summer. The second relates to systematic precipitation associated with a frontal boundary accompanying a medium-scale low-pressure system. For convective showers, the 1-hour interval exhibits better performance and continuity, particularly as the forecast time extends. In the case of systematic precipitation, the 1-hour interval remains superior, though the skill is not as prominent as with convective showers. This highlights that an abundance of information doesn't always equate to high-quality information.

How to cite: Son, J., Kim, J., and Kim, S.: Does more frequent Very Short-Range Forecast provide more useful information?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6873, https://doi.org/10.5194/egusphere-egu24-6873, 2024.

EGU24-7086 | Posters on site | AS1.2

Development of stadium-specific numerical forecast guidance for weather forecast for the 2024 Gangwon Winter Youth Olympic Games 

Yeon-Hee Kim, Eunju Cho, Sungbin Jang, Junsu Kim, Hyejeong Bok, and Seungbum Kim

The 2024 Gangwon Winter Youth Olympic Games (GANGWON 2024) will be held in the province of Gangwon in the Republic of Korea from January 19 to February 1, 2024, which already hosted the Olympic Winter Games PyeongChang 2018. In order to successfully host these first Winter YOG to be held in Asia, which will be held for the first time in Asia, it is necessary to provide customized weather information for decision-making in game operation and support in establishing game strategies for athletes and their teams. Accordingly, the Korea Meteorological Administration develops point-specific numerical forecast guidance for major stadiums and provides it to the field to support successful hosting of YOG and improvement of performance. Numerical forecast guidance is the final data delivered to consumers or forecasters as post-processed numerical model data that has been corrected by applying altitude correction and statistical methods to produce highly accurate forecasts. For a total of 13 forecast elements (temperature, minimum/maximum temperature, humidity, wind direction/speed, precipitation, new snow cover, sky conditions, precipitation probability, precipitation type), we developed user-customized numerical forecast guidance specialized for competition points  (Gangneung Olympic Park, Pyeongchang Alpensia Venue, Biathlon Center, Olympic Sliding Center departure/arrival, Wellyhilli departure/arrival, High1 departure/arrival). Through the process of Perfect Prognostic Method (PPM), Model Output Statistics (MOS), optimization, and optimal merging, the systematic errors inherent in the numerical model are removed, and the optimal data (BEST) with improved forecasting performance is provided as customized numerical forecast guidance specific to stadium locations.  In the prediction performance evaluation for the period of December 2023, the accuracy (improvement rate) compared to the average of available models was temperature 1.49℃ (18%), humidity 12% (25%), wind speed 1.87m/s (33%), and visibility 12.8km (17%).

How to cite: Kim, Y.-H., Cho, E., Jang, S., Kim, J., Bok, H., and Kim, S.: Development of stadium-specific numerical forecast guidance for weather forecast for the 2024 Gangwon Winter Youth Olympic Games, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7086, https://doi.org/10.5194/egusphere-egu24-7086, 2024.

EGU24-7091 | Posters on site | AS1.2

The Development of precipitation model modifed with ECMWF IFS and XGBoost and its performance verification 

Eunju Cho, Yeon-Hee Kim, Seungbum Kim, and Young Cheol Kwon

This study was conducted to develop a modified precipitation model for its amount and existence by combining machine learning method, Extreme Gradient Boosting(XGBoost), with ECMWF IFS(Integrated forecasting system) and, finally, estimate the related performance.

According to the analysis of regional precipitation characteristic, prior to its development, the ratio of precipitation existence was various on a basis of a forecast’s district and its season. These different patterns on each district makes it necessary to develop the regional and seasonal model respectively.

And, the first attempt at the machine learning showed the importance of each feature as input-variables, as a result of which cloud physics-related features, for example large-area precipitation, total precipitation, visibility and what not, proved so significant. However, the insufficient amount of these feature’s data seemed to result in overfitting. And therefore, the feasible features, except for cloud physics-related things, of IFS data were used. In addition, auxiliary features and their gradient for every lead-time were calculated and added: relative vorticity, divergence, equivalent potential temperature, main 6 patterns for Korean summer and so on. The number of features amounted to around 144 with which for the 9-year training set, 2013~2021, based learning to be conducted regionally, followed by using validation-set of 2022.

As a result of validation for precipitation existence and its amount up to 135 hours ahead on the 10 regions at 00UTC in summer of 2022, Critical Success Index(CSI) was more improved by 10.3% than before. Accuracy(ACC) for each lead-time rose by 6% and its fluctuation also decreased. And the correction by this machine learning alleviated the overfitting trend of precipitation forecast amount produced by the original model, and improved correlation and linearity between observation and forecast. In particular, while the machine learning prevailed over the original model up to 100 hours ahead, from then on, both of them showed similar performance or that of the former was downward slightly. If the above-mentioned cloud physics features are used to further sharpen machine learning technique, its performance should be enhanced more and more.

How to cite: Cho, E., Kim, Y.-H., Kim, S., and Kwon, Y. C.: The Development of precipitation model modifed with ECMWF IFS and XGBoost and its performance verification, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7091, https://doi.org/10.5194/egusphere-egu24-7091, 2024.

EGU24-7291 | ECS | Posters on site | AS1.2

Improvements in fog predictions via a modified reconstruction of moisture distribution using the Weather Research and Forecasting(WRF) model 

Eunji Kim, Soon-Young Park, Jung-Woo You, and Soon-Hwan Lee

Since fog is an important weather phenomenon affecting the traffic safety, accurate fog forecasting should be attained to minimize meteorological disasters. Most fog forecasts determine only the presence or absence of fog based on less visibility than 1 km, which is known as the visibility diagnostic method. During this process, fog could be predicted by the visibility calculated in the numerical weather prediction (NWP) model using the cloud liquid water content (LWC) near the surface. In this study, we investigated to increase the accuracy of fog forecast by optimizing the reconstruction of moisture distribution method, which can simulate the intensity of fog as well as the presence or absence of fog. The performances of the fog simulations were examined by modifying the relative humidity threshold at a height of 2 m and the stability parameters which affect turbulence and also one of the important criteria for fog occurrence. When we applied the optimize parameters to fog prediction in the winter seasons, the probability of detection (POD) has been increased significantly from 0.21 to 0.54. These improvements were attributed to the corrected relative humidity threshold and the stability parameters. Although the false alarm rate (FAR) remained almost unchanged, the critical success index (CSI) has been improved slightly lesser than those of the POD. When we analyzed the life cycle of fog, it takes time for the NWP model to simulate water droplets in the fog-developing stage. Therefore, the accuracy of the fog simulation is intimately related to the reconstruction of moisture distribution. The NWP model, however, showed a better performance in the process of fog dissipation than the reconstruction of moisture distribution method that was sensitive to temperature and turbulence. In conclusion, the reconstruction of moisture distribution led to a considerable improvement of the fog prediction in the generation and development stage since we used the optimized humidity threshold. It is also expected that accurate fog prediction could be achieved in the future by considering the aerosol effects, which is another importance factor for the fog generation.

How to cite: Kim, E., Park, S.-Y., You, J.-W., and Lee, S.-H.: Improvements in fog predictions via a modified reconstruction of moisture distribution using the Weather Research and Forecasting(WRF) model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7291, https://doi.org/10.5194/egusphere-egu24-7291, 2024.

EGU24-7536 | Orals | AS1.2

Nowcasting with Transformer-based Models using Multi-Source Data  

Çağlar Küçük, Apostolos Giannakos, Stefan Schneider, and Alexander Jann

Rapid advancements in data-driven weather prediction have shown notable success, particularly in nowcasting, where forecast lead times span just a few hours. Transformer-based models, in particular, have proven effective in learning spatiotemporal connections of varying scales by leveraging the attention mechanism with efficient space-time patching of data. This offers potential improvements over traditional nowcasting techniques, enabling early detection of convective activity and reducing computational costs. 

In this presentation, we demonstrate the effectiveness of a modified Earthformer model, a space-time Transformer framework, in addressing two specific nowcasting challenges. First, we introduce a nowcasting model that predicts ground-based 2D radar mosaics up to 2-hour lead time with 5-minute temporal resolution, using geostationary satellite data from the preceding two hours. Trained on a benchmark dataset sampled across the United States, our model exhibits robust performance against various impactful weather events with distinctive features. Through permutation tests, we interpret the model to understand the effects of input channels and input data length. We found that the infrared channel centered at 10.3 µm contains skillful information for all weather conditions, while, interestingly, satellite-based lightning data is the most skilled at predicting severe weather events in short lead times. Both findings align with existing literature, enhancing confidence in our model and guiding better usage of satellite data for nowcasting. Moreover, we found the model is sensitive to input data length in predicting severe weather events, suggesting early detection of convective activity by the model in rapidly growing fields. 

Second, we present the initial attempts to develop a multi-source precipitation nowcasting model for Austria, tailored to predict impactful events with convective activities. This model integrates satellite- and ground-based observations with analysis and numerical weather prediction data to predict precipitation up to 2-hour lead time with 5-minute temporal resolution.  

We conclude by discussing the broad spectrum of applications for such models, ranging from enhancing operational nowcasting systems to providing synthetic data to data-scarce regions, and the challenges therein.

How to cite: Küçük, Ç., Giannakos, A., Schneider, S., and Jann, A.: Nowcasting with Transformer-based Models using Multi-Source Data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7536, https://doi.org/10.5194/egusphere-egu24-7536, 2024.

EGU24-7753 | ECS | Orals | AS1.2

On the usefulness of considering the run-to-run variability for an ensemble prediction system 

Hugo Marchal, François Bouttier, and Olivier Nuissier

The run-to-run variability of numerical weather prediction systems is at the heart of forecasters' concerns, especially in the decision-making process when high-stakes events are considered. Indeed, forecasts that are brutally changing from one run to another may be difficult to handle and can lose credibility. This is all the more true nowadays, as many meteorological centres have adopted the strategy of increasing runs frequency, some reaching hourly frequencies. However, this aspect has received little attention in the literature, and the link with predictability has barely been explored.

In this study, run-to-run variability is investigated through 24h-accumulated precipitations forecasted by AROME-EPS, Météo-France's high resolution ensemble, which is refreshed 4 times a day. Focusing on the probability of some (warning) thresholds being exceeded, results suggest that how forecasts evolve over successive runs can be used to improve their skill, especially reliability. Various possible aspects of run sequence have been studied, from trends to rapid increases or decreases in event probability at short lags, also called "sneaks" or "phantoms", as well as the persistence of a non-zero probability through successive runs. The added value provided by blending successive runs, known as lagging, is also discussed.

How to cite: Marchal, H., Bouttier, F., and Nuissier, O.: On the usefulness of considering the run-to-run variability for an ensemble prediction system, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7753, https://doi.org/10.5194/egusphere-egu24-7753, 2024.

EGU24-8449 | ECS | Orals | AS1.2

Radiation fog nowcasting with XGBoost using station and satellite data 

Michaela Schütz, Jörg Bendix, and Boris Thies

The research project “FOrecasting radiation foG by combining station and satellite data using Machine Learning (FOG-ML)” represents a comprehensive effort to advance radiation fog prediction using machine learning (ML) techniques, with focus on the XGBoost algorithm. The nowcasting period is up to four hours into the future.

The initial phase of the project involved developing a robust classification-based model that could accurately forecast the occurrence of radiation fog, a challenging meteorological phenomenon. Radiation fog is particularly difficult to predict because it depends on a complex interplay of factors such as ground cooling, humidity, and minimal cloud cover. It often forms rapidly and in local areas. This required careful analysis of the chronological order of the data and consideration of autocorrelation to increase the effectiveness of model training.

Building upon this foundation, the next two phases concentrated on improving the model’s forecasting performance for visibility classes (step 2) and for absolute visibility values (step 3). The main focus was then on a nowcasting period of up to two hours. This nowcasting period is critical in fog prediction as it directly impacts transportation planning and safety. The use of ground-level observations in step 2 and integration of satellite data in step 3 provided a rich dataset that allowed for more nuanced model training and validation.

In the latest phase of research, satellite data has been incorporated to further refine the prediction model, especially regarding the fog formation and dissipation. Satellite imagery provides additional variables of atmospheric data that are not readily available from ground-based observations. This integration aims to address one of the inherent limitations in fog forecasting methods, particularly in areas where ground-based observations are sparse.

Throughout the different stages, the project emphasized the need for thorough data processing and validation. This included the implementation of cross-validation techniques to assess the generalizability of the models and the use of various metrics to gauge their predictive power. This has also included the incorporation of trend information, which has proven to be crucial for forecasting with XGBoost. Our research has also shown that not only the overall performance, but also the performance of the transitions (fog formation and resolution) should be analyzed to get a complete picture of the model performance. This finding was consistent throughout the entire study, regardless of classification-based forecast or regression-based forecast.

We have been able to significantly improve the performance of our nowcasting model with each step. We will be presenting the key findings and latest results from this research at EGU24.

All results from step 1 can be found in “Current Training and Validation Weaknesses in Classification-Based Radiation Fog Nowcast Using Machine Learning Algorithms” from Vorndran et al. 2022. All results from step 2 can be found in “Improving classification-based nowcasting of radiation fog with machine learning based on filtered and preprocessed temporal data” from Schütz et al. 2023.

How to cite: Schütz, M., Bendix, J., and Thies, B.: Radiation fog nowcasting with XGBoost using station and satellite data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8449, https://doi.org/10.5194/egusphere-egu24-8449, 2024.

EGU24-9528 | ECS | Orals | AS1.2

Ensemble forecast post-processing based on neural networks and normalizing flows 

Peter Mlakar, Janko Merše, and Jana Faganeli Pucer

Ensemble weather forecast post-processing can generate more reliable probabilistic weather forecasts compared to the raw ensemble. Often, the post-processing method models the future weather probability distribution in terms of a pre-specified distribution family, which can limit their expressive power. To combat these issues, we propose a novel, neural network-based approach, which produces forecasts for multiple lead times jointly, using a single model to post-process forecasts at each station of interest. We use normalizing flows as parametric models to relax the distributional assumption, offering additional modeling flexibility.We evaluate our method for the task of temperature post-processing on the EUPPBench benchmark dataset. We show that our approach exhibits state-of-the-art performance on the benchmark, improving upon other well-performing entries. Additionally, we analyze the performance of different parametric distribution models in conjunction with our parameter regression neural network, to better understand the contribution of normalizing flows in the post-processing context. Finally, we provide a possible explanation as to why our method performs well, exploring per-lead time input importance.

How to cite: Mlakar, P., Merše, J., and Faganeli Pucer, J.: Ensemble forecast post-processing based on neural networks and normalizing flows, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9528, https://doi.org/10.5194/egusphere-egu24-9528, 2024.

EGU24-9659 | Posters on site | AS1.2

Application Research of Multi-source New Detection Data in Snow Depth Prediction for Beijing Winter Olympics 

Jia Du, Bo Yu, Yi Dai, Sang Li, Luyang Xu, Jiaolan Fu, Lin Li, and Hao Jing

According to the demand of the Winter Olympic Organizing Committee for snow depth prediction, the application of multi-source new data in snow depth was studied based on densely artificial snow-depth measurement, microscopic snowflake shape observation and PARSIVEL data. The specific conclusions are as follows: (1) Most of the Snow-Liquid-Ratio(SLR) in Beijing competition zone was between 0.69 and 1.43 (unit: cm/mm, the same below), while that in Yanqing zone was between 0.53 and 1.17. But 7.5% of the SLRs in Yanqing zone exceeded 3.5, which all occurred in the same period of the key service time of 2022 Beijing Winter Olympics, making it more difficult to predict new snow depth. (2) The higher the SLR, the lower the daily minimum surface temperature and lowest air temperature.  Plate or column ice crystals, rimed snowflakes, and dendritic snowflakes were observed, whose corresponding SLRs increased. The average falling speed of particles falling below 2m/s can be used as an indicator of phase transfer. (3) The vertical distributions of temperature and humidity with SLR <1 or >2 were summarized. It was found that when the cloud area coincided with the dendritic growth zone with height close to Yanqing zone, the SLR would be more than 2, higher than that of Beijing zone. (4) A weather concept model generating large SLR was extracted. Snow in Beijing is often accompanied by easterly winds in boundary layer, which is easy to form a wet and ascending layer in the lower troposphere due to the blocking of western mountain. In the late winter season, helped by the temperature’s profile, it tends to produce unrimed dendritic snowflakes, leading to a great SLR.

How to cite: Du, J., Yu, B., Dai, Y., Li, S., Xu, L., Fu, J., Li, L., and Jing, H.: Application Research of Multi-source New Detection Data in Snow Depth Prediction for Beijing Winter Olympics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9659, https://doi.org/10.5194/egusphere-egu24-9659, 2024.

EGU24-9935 | ECS | Posters on site | AS1.2

Machine and Deep Learning algorithms to improve weather forecasts over a complex orography Mediterranean region 

Luca Furnari, Umair Yousuf, Alessio De Rango, Donato D'Ambrosio, Giuseppe Mendicino, and Alfonso Senatore

The rapid development of artificial intelligence algorithms has generated considerable interest in the scientific community. The number of scientific articles relating to applying these algorithms for weather forecasting has increased dramatically in the last few years. In addition, the recent operational launch of products such as GraphCast has put this area of research even more in the spotlight. This work uses different Machine Learning and Deep Learning algorithms, namely ANN (Artificial Neural Network), RF (Random Forest) and GNN (Graph Neural Network), with the aim to improve the short-term (1-day lead time) forecasts provided by a physically-based forecasting system. Specifically, the CeSMMA laboratory, since January 2020, has been producing daily forecasts accessible via the https://cesmma.unical.it/cwfv2/ webpage related to a large portion of southern Italy. The NWP (Numerical Weather Prediction) system is based on the WRF (Weather Research and Forecasting) model, with boundary and initial conditions provided by the GFS (Global Forecasting System) model. The AI algorithms post-process the NWP output, applying correction factors achieved by a two-year training considering the observations of the dense regional monitoring network composed of ca. 150 rain gauges.

The results show that the AI is able to improve daily rainfall forecasts compared to ground-based observations. Specifically, the ANN reduces the average MSE (Mean Square Error) by approximately 29% and the RF by 21% with respect to the WRF forecast for the whole study area (about 15’000 km2). Moreover, the GNN applied to a smaller area (considering only 22 rain gauges) further reduces the MSE by 35% during the heaviest rainfall months.

In addition to improving the performance of the forecast, the AI-based post-processing provides reasonable precipitation spatial patterns, reproducing the main physical phenomena such as the orographic enhancement since it is not a surrogate model and benefits from the original physically-based forecasts.

 

Acknowledgements. This work was funded by the Next Generation EU - Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of ‘Innovation Ecosystems’, building ‘Territorial R&D Leaders’ (Directorial Decree n. 2021/3277) - project Tech4You - Technologies for climate change adaptation and quality of life improvement, n. ECS0000009. This work reflects only the authors’ views and opinions, neither the Ministry for University and Research nor the European Commission can be considered responsible for them.

How to cite: Furnari, L., Yousuf, U., De Rango, A., D'Ambrosio, D., Mendicino, G., and Senatore, A.: Machine and Deep Learning algorithms to improve weather forecasts over a complex orography Mediterranean region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9935, https://doi.org/10.5194/egusphere-egu24-9935, 2024.

On May 17, 2019, a rare severe convective weather occurred in Beijing, accompanied by local heavy rainstorm, hail, thunderstorm and gale. This severe convective weather occurred significantly earlier than normal years, bringing great challenge to the forecast. Using multiple observation data and radar four-dimensional variational assimilation products to analyze the triggering and development evolution of this severe convection. Under the conditions of no obvious weather scale system and local high potential unstable energy, the eastward advancement of the sea breeze front was the main factor triggering strong convection. As the northwest wind in the air increasing, the environmental conditions became stronger vertical wind shear, which was beneficial for the storm to maintain for a longer period of time. The supercell was the main cause of the convective weather. During the development of storms, they split into two parts and moved counterclockwise. The southern echo gradually weakened as it moved northward, while the northern echo moved southward, strengthening and developing into a super cell accompanied by a mesocyclone. The significant fluctuations in the height of the 0 ℃ layer within a small range resulted in different melting rates of hail during its descent, leading to the formation of spiky hail.

How to cite: Yu, B.: Analysis of a rare severe convective weather event in spring in Beijing of China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10809, https://doi.org/10.5194/egusphere-egu24-10809, 2024.

EGU24-12420 | ECS | Orals | AS1.2

Can convection permitting forecasts solve the tropical African precipitation forecasting problem? 

Felix Rein, Andreas H. Fink, Tilmann Gneiting, Philippe Peyrille, James Warner, and Peter Knippertz

Forecasting precipitation over Africa, the largest landmass in the tropics, has been a long standing problem. The unique conditions of the West African monsoon result in large and long lasting mesoscale convective systems. Global numerical weather prediction (NWP) models have gridsizes in the 10s of kilometers, particular when run in ensemble mode, leaving convection to be parameterized. This often results in precipitation being forecast on too large scales, in the wrong places, and with too weak intensity, ultimately leading to little to no skill in tropical Africa.


It has been argued that convection permitting (CP) NWP forecasts would cure some of the problems described above but those have only recently become feasible in an operational setting, although ensembles are still deemed to be too expensive. Here, we systematically compare regional deterministic CP and global ensemble forecasts in the region over multiple rainy seasons for the first time. We analyze CP forecasts from AROME and Met Office Tropical African Model, and seven global ensemble forecasts from the TIGGE archive, both individually and as a multi-model ensemble. In order to create an uncertainty estimate, we create neighborhood ensembles from CP forecasts at surrounding grid points, which allows for a fair comparison to the ensembles and a probabilistic climatology. Considering both precipitation occurrence and amount, we use the Brier score (BS) and the continuous ranked probability score (CRPS), along with their decompositions in discrimination, miscalibration and uncertainty, for evaluation.


Using neighborhood methods, deterministic forecasts are turned into probabilistic forecasts, allowing a fair comparison with ensembles. All numerical forecasts benefit from Neighborhoods, improving their BS and CRPS in terms of both miscalibration and discrimination. We find all individual forecasts to have skill over most of tropical Africa, with some ensemble models lacking skill in some regions and the multi model showing the most overall skill. The CP forecasts TAM and AROME outperform non-CP forecasts mainly in the region of the little dry Season and the Soud. However, large areas of low skill in terms of CRPS remain and even with high resolution, numerical models still struggle to predict precipitation in tropical Africa. 

How to cite: Rein, F., Fink, A. H., Gneiting, T., Peyrille, P., Warner, J., and Knippertz, P.: Can convection permitting forecasts solve the tropical African precipitation forecasting problem?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12420, https://doi.org/10.5194/egusphere-egu24-12420, 2024.

EGU24-12855 | Posters on site | AS1.2

Project IMA: Lessons Learned from Building the Belgian Operational Seamless Ensemble Prediction System 

Lesley De Cruz, Michiel Van Ginderachter, Maarten Reyniers, Alex Deckmyn, Idir Dehmous, Simon De Kock, Wout Dewettinck, Ruben Imhoff, Esteban Montandon, and Ricardo Reinoso-Rondinel

 

In recent years, several national meteorological services (NMSs) have invested considerable resources in the development of a seamless prediction system: rapidly updating forecasts that integrate the latest observations, covering timescales from minutes to days or longer ahead (e.g. DWD's SINFONY; FMI's ULJAS, MetOffice's IMPROVER and Geosphere Austria's SAPHIR) [1]. This move was motivated mainly by rising expectations from end users such as hydrological services, local authorities, the renewable energy sector and the general public. The development of seamless prediction systems was made possible thanks to the increasing availability of high-resolution observations, continuing advances in numerical weather prediction (NWP) models, nowcasting algorithms, and improved strategies to combine multiple information sources optimally. Moreover, the rise of AI/ML techniques in forecasting and nowcasting can further reduce the computational cost to generate frequently updating seamless operational forecast products.

 

We present the journey of building the Belgian seamless prediction system at the Royal Meteorological Institute of Belgium, with the working title "Project IMA". IMA uses both the deterministic INCA-BE and the probabilistic pysteps-BE systems to combine nowcasts with the ALARO and AROME configurations of the ACCORD NWP model. In the lessons learned along the way, we focus on what is often omitted, moving from research to operations, and integrating what we learn from operations back into research. We discuss the benefits of integrating new developments within the free and open-source software (FOSS) pysteps [2]. Our experience shows that using and contributing to FOSS not only leads to more transparency and reproducible, open science; it also enhances international collaboration and can benefit other users, including developing countries, bringing us a step closer to the ambitious goal of Early Warnings for All by 2027 [3].

 

References

 

[1] Bojinski, Stephan, et al. "Towards nowcasting in Europe in 2030." Meteorological Applications 30.4 (2023): e2124.

[2] Imhoff, Ruben O., et al. "Scale‐dependent blending of ensemble rainfall nowcasts and numerical weather prediction in the open‐source pysteps library." Quarterly Journal of the Royal Meteorological Society 149.753 (2023): 1335-1364.

[3] WMO, "Early warnings for all: Executive action plan 2023-2027", 8 Nov 2022,  https://www.preventionweb.net/quick/75125.

How to cite: De Cruz, L., Van Ginderachter, M., Reyniers, M., Deckmyn, A., Dehmous, I., De Kock, S., Dewettinck, W., Imhoff, R., Montandon, E., and Reinoso-Rondinel, R.: Project IMA: Lessons Learned from Building the Belgian Operational Seamless Ensemble Prediction System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12855, https://doi.org/10.5194/egusphere-egu24-12855, 2024.

Moderate to heavy rain produced by slantwise ascent of moist air above the cold high is prevalent in cold season in East China. The slantwise ascent is usually characterized by a southwest moist flow aroused by the so-called southern branch trough of 500hPa level to the south of the Qinghai-Tibet Plateau, while the cold high is usually formed by cold air damming, which is familiar to weather forecasters due to topographic feature of East China. The routine short-range forecast skill for this kind of precipitation of weather forecasters is usually limited by model performance. Through large sample model verification, our study indicates that, for the rainfall produced by southwesterly moist flow ascending above the cold high, the ECMWF model always underestimates the rainfall amount on the northeastern part of the rainfall belt, which could be taken as a systematic bias of the state-of-the-art global model. Our case studies indicate that the underestimation of rainfall amount is related to the weaker slant ascent of moist southwest flow forecast by ECMWF model than observation or reanalysis. The southwest flow above the northeastern flow induced by the cold high forms strong wind shear and warm-moist advection, which favors the occurrence of conditional symmetric instability producing strong slantwise ascent not well reflected by global model.

How to cite: Hu, N. and Fu, J.: Investigating Model Forecast Bias for Rainfall Produced by Slantwise Ascent above Cold High, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13809, https://doi.org/10.5194/egusphere-egu24-13809, 2024.

EGU24-13853 | Orals | AS1.2 | Highlight

A Research Agenda for the Evaluation of AI-Based Weather Forecasting Models 

Imme Ebert-Uphoff, Jebb Q. Stewart, and Jacob T. Radford and the CIRA-NOAA team

Over the past few years purely AI-driven global weather forecasting models have emerged that show increasingly impressive skill, raising the question whether AI models might soon compete with NWP models for selected forecasting tasks. At this point these AI-based models are still in the proof-of-concept stage and not ready to be used for operational forecasting, but entirely new AI-models emerge every 2-3 months, with rapidly increasing abilities. Furthermore, many of these models are orders of magnitude faster than NWP models and can run on modest computational resources enabling repeatable on-demand forecasts competitive with NWP. The low computational cost enables the creation of very large ensembles, which better represent the tails of the forecast distribution, which, if an ensemble is well calibrated, allows for better forecasting of rare and extreme events.

However, these AI-based weather forecasting models have not yet been rigorously tested by the meteorological community, and their utility to operational forecasters is unknown. In this presentation we propose several studies to address the above issues, grouped into two central foci:

(1) Nature of AI models: AI-based models have very different characteristics from NWP models. Thus, in addition to applying evaluation procedures developed for NWP models, we need to develop procedures that test for AI-specific weaknesses. For example, NWP models and their physics backbone guarantee certain properties - such as dynamic coupling between fields - that AI-based models are not required to uphold. Developing suitable tests is based on a fundamental understanding of the AI-based models.

(2) Forecaster Perspective: Evaluation of weather forecasting models should be performed with respect to particular applications of weather forecasts, and it is critical to have research meteorologists and operational forecasters involved in the evaluation process. Our initial evaluation of AI-based models in CIRA weather briefings revealed that these models have characteristics that make interpretation of their forecasts fundamentally different from the physics-based NWP model predictions meteorologists are familiar with. For example, the increasing “blurriness” of AI-based predictions with longer lead times is not a reflection of weaker atmospheric circulations, but rather a reflection of uncertainty. Evaluations aimed at specific meteorological phenomena and atmospheric processes will allow the community to make informed decisions in the future regarding in what environments and for which applications AI-based weather forecasting models may be safe and beneficial to use.

In summary, AI-based weather forecasts have different characteristics from familiar dynamically-based forecasts, and it is thus important to have a robust research plan to evaluate many different characteristics of the models in order to provide guidelines to operational forecasters and feedback to model developers. In this abstract we propose a number of characteristics to evaluate, present results we already obtained, and suggest a research plan for future work.

How to cite: Ebert-Uphoff, I., Stewart, J. Q., and Radford, J. T. and the CIRA-NOAA team: A Research Agenda for the Evaluation of AI-Based Weather Forecasting Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13853, https://doi.org/10.5194/egusphere-egu24-13853, 2024.

Large-eddy simulations of an idealized tropical cyclone (TC) were conducted as benchmarks to provide statistical information about subgrid convective clouds at a convection-permitting resolution over a TC convection system in different stages. The focus was on the vertical and spatial distributions of the subgrid cloud and associated mass flux that need to be parameterized in convection-permitting models. Results showed that the characteristics of the subgrid clouds varied significantly in various parts of the TC convection system. Statistical analysis revealed that the subgrid clouds were mainly located in the lower troposphere and exhibited shallow vertical extents of less than 4 km. The subgrid clouds were also classified into various cloud regimes according to the maximum mass flux height. Local subgrid clouds differed in mass-flux profile shape and magnitude at various regimes in the TC convection system.

How to cite: Zhang, X. and Bao, J.-W.: Statistics of the Subgrid Cloud of an Idealized Tropical Cyclone at Convection-Permitting Resolution, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14232, https://doi.org/10.5194/egusphere-egu24-14232, 2024.

EGU24-14541 | Posters on site | AS1.2

Status and Plan of Standard Verification System for the NWP model in Korea Meteorological Administration 

Sora Park, Hyeja Park, Haejin Lee, Saem Song, Jong-Chul Ha, and Young Cheol Kwon

The Korea Meteorological Administration (KMA) has established and operated a standard verification system of the operational NWP models to evaluate the predictive performance of NWP model and compare them with other NWP models operated by domestic and foreign organization. This secures the objectivity of the verification results by applying the verification standards (WMO-No.485) presented by World Meteorological Organization (WMO), and being able to compare the performance with the numerical forecasting models of other institutions under the same conditions. The NWP models to be verified is a global, a regional, very short-range, and an ensemble prediction system and verification against analyses and observations are performed twice a day (00 UTC, 12 UTC). In addition to standard verification, precipitation, typhoon and various verification indexes (CBS index, KMA index, jumpiness index) are verified and used to evaluate the utilization of NWP models. The Korea Integrated Model (KIM), which is developed for Korea’s own NWP model, has been in operation since April 2020. Since the start of operation, the RMSE of 500hPa geopotential height (in Northern Hemisphere) has decreased every year, showing that forecast performance is improving. In addition, it can be seen that the 72-hour prediction accuracy for 12-hour accumulated precipitation (1.0 mm or more) in the Korean Peninsula area (75 ASOS stations) is also improving. As such, this study intends to discuss the predictive performance of the numerical forecast model based on the standard verification system and plans to improve the verification system in the future. 

How to cite: Park, S., Park, H., Lee, H., Song, S., Ha, J.-C., and Kwon, Y. C.: Status and Plan of Standard Verification System for the NWP model in Korea Meteorological Administration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14541, https://doi.org/10.5194/egusphere-egu24-14541, 2024.

EGU24-15431 | ECS | Orals | AS1.2 | Highlight

Nowcasting of extreme precipitation events: performance assessment of Generative Deep Learning methods 

Gabriele Franch, Elena Tomasi, Rishabh Umesh Wanjari, and Marco Cristoforetti

Radar-based precipitation nowcasting is one of the most prominent applications of deep learning (DL) in weather forecasting. The accurate forecast of extreme precipitation events remains a significant challenge for deep learning models, primarily due to their complex dynamics and the scarcity of data on such events. In this work we present the application of the latest state-of-the-art generative architectures for radar-based nowcasting, focusing on extreme event forecasting performance. We analyze a declination for the nowcasting task of all the three main current architectural approaches for generative modeling, namely: Generative Adversarial Networks (DGMRs), Latent Diffusion (LDCast), and our novel proposed Transformer architecture (GPTCast). These models are trained on a comprehensive 1-km scale, 5-minute timestep radar precipitation dataset that integrates multiple radar data sources from the US, Germany, the UK, and France. To ensure a robust evaluation and to test the generalization ability of the models, we concentrate on a collection of out-of-domain extreme precipitation events over the Italian peninsula extracted from the last 5 years. This focus allows us to assess the improvements these techniques offer compared to extrapolation methods, evaluating continuous (MSE, MAE) and categorical scores (CSI, POD, FAR), ensemble reliability, uncertainty quantification, and warning lead time. Finally, we analyze the computational requirements of these new techniques and highlight the caveats that must be considered when operational usage of these methods is envisaged. 

How to cite: Franch, G., Tomasi, E., Wanjari, R. U., and Cristoforetti, M.: Nowcasting of extreme precipitation events: performance assessment of Generative Deep Learning methods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15431, https://doi.org/10.5194/egusphere-egu24-15431, 2024.

EGU24-16617 | Posters on site | AS1.2

Forecasting extreme events with the crossing-point forecast  

Zied Ben Bouallegue

The crossing-point forecast (CPF) is a new type of ensemble-based forecast developed at the European Centre for Medium-Range Weather Forecasts. The crossing point refers to the intersection between the cumulative probability distribution of a forecast and the cumulative probability distribution of a model climatology. Originally, the CPF has emerged as a consistent forecast with the diagonal score, a weighted version of the continuous ranked probability score targeting high-impact events. Ranging between 0 and 1, the CPF can serve as an index for high-impact weather and thus directly be compared with the well-established extreme forecast index. The CPF is also interpretable in terms of a return period and conveys a sense of a “probabilistic worst-case scenario”.  Using a recent example of an extreme event affecting Europe, we illustrate and discuss the performance and specificities of this new type of forecast for extreme weather forecasting.

Ben Bouallegue, Z (2023).  Seamless prediction of high-impact weather events: a comparison of actionable forecasts. arXiv:2312.01673

How to cite: Ben Bouallegue, Z.: Forecasting extreme events with the crossing-point forecast , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16617, https://doi.org/10.5194/egusphere-egu24-16617, 2024.

EGU24-17158 | Orals | AS1.2 | Highlight

AIFS – ECMWF’s Data-Driven Probabilistic Forecasting  

Zied Ben Bouallegue, Mihai Alexe, Matthew Chantry, Mariana Clare, Jesper Dramsch, Simon Lang, Christian Lessig, Linus Magnusson, Ana Prieto Nemesio, Florian Pinault, Baudouin Raoult, and Steffen Tietsche

In just two years, the idea of an operational data-driven system for medium-range weather forecasting has been transformed from dream to very real possibility. This has occurred through a series of publications from innovators, which have rapidly improved deterministic forecast skill. Our own evaluation confirms that these forecasts have comparable deterministic skill to NWP models across a range of variables. However, on medium-range timescales probabilistic forecasting, typically achieved through ensembles, is key for providing actionable insights to users. ECMWF is building on top of these recent works to develop a probabilistic forecasting system, AIFS. We will showcase results from our progress towards this system and outline our roadmap to operationalisation.

How to cite: Ben Bouallegue, Z., Alexe, M., Chantry, M., Clare, M., Dramsch, J., Lang, S., Lessig, C., Magnusson, L., Prieto Nemesio, A., Pinault, F., Raoult, B., and Tietsche, S.: AIFS – ECMWF’s Data-Driven Probabilistic Forecasting , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17158, https://doi.org/10.5194/egusphere-egu24-17158, 2024.

The increasing integration of renewable energy resources to the national grids necessitates
accurate prediction of power generation from those sources in terms of secure operation of
electricity grid system and energy trading. Electricity generation of renewable energy power
plants such as wind and solar are inherently affected by weather conditions. The wind condition
particularly is affected by surface characteristics such as orography and vegetation, therefore it is
the one of the near surface atmospheric variables having the strongest local variability. The high-
resolution Numerical Weather Prediction (NWP) models are utilized to take the local conditions
into account. WRF model is the one of the most common NWP models having been widely
investigated by various researchers. On the other hand, The Model for Prediction Across Scales
(MPAS) is a relatively new NWP model utilizing non-uniform mesh structures, developed by the
National Center for Environmental Predictions (NCEP). However, there are limited studies in the
literature which compare the prediction performance of WRF and MPAS model in terms of
surface wind speed. This study evaluates the prediction accuracy of near surface wind of two
downscaled NWP models namely, WRF-ARW and MPAS. Both models are configured with
almost identical physics suites and initialized with 3 hourly 00-UTC initialization of Global
Forecast System (GFS) data. The model outputs are obtained at 10 minutes interval for 48 hours
horizon. Hourly averaged model results are compared with observations from 104 on-site
meteorological stations located in Turkiye having different complexity in terms of correlation
coefficient and RMSE.

How to cite: Yalcin, R. D., Yilmaz, M. T., and Yucel, İ.: Evaluation of the Impact of Uniform and Non-Uniform Resolution Implementations in Numerical Weather Prediction Models over the Accuracy of Short-Term Wind Prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17339, https://doi.org/10.5194/egusphere-egu24-17339, 2024.

EGU24-18548 | ECS | Posters on site | AS1.2

Enhancing Regional NWP Model with GNSS Zenith Total Delay Assimilation: A WRF and WRFDA 3D-Var Approach in the Greater Region of Luxembourg 

Haseeb Ur Rehman, Felix Norman Teferle, Addissu Hunegnaw, Guy Schumann, Florian Zus, and Rohith Muraleedharan Thundathil

Compared to alluvial floods, flash or pluvial floods are difficult to predict because they result from intense and brief periods of extreme precipitation. Luxembourg has a history of being impacted by floods, with notable occurrences in January 2011, May 2016, December 2017, January 2018, February 2019, and February 2020. However, July 2021 stands out as the most severe flood year on record in the region. In this study we are aiming to develop, a high-resolution numerical weather prediction (NWP) model for effective local heavy rainfall prediction in a nowcasting scenario and provide real time for flood simulation. The modeling relies on the Weather Research and Forecasting (WRF) model, which incorporates local Global Navigation Satellite System (GNSS) data assimilation and local precipitation observations to simulate small-scale, high-intensity convective precipitation.

As part of this, we will also test run the LISFlood flood model in an operational inundation forecast mode, meaning that the flood model will be run with the WRF precipitation forecasts as inputs.

The WRF model was configured for the Greater Region, utilizing a horizontal grid resolution of 12 km and incorporating high-resolution static datasets. Meteorological data i.e. July 13 -14 2021, from the Global Forecast System (GFS) were employed in the model setup as initial boundary condition. Zenith Total Delay (ZTD) data collected from various GNSS stations (112) across Germany and Luxembourg were assimilated into the model. Additionally, observational datasets including Surface Synoptic Observations (SYNOP), Upper Air Data, Radiosonde measurements (TEMP), and Tropospheric Airborne Meteorological Data Reporting (TAMDAR) were assimilated. Following this integration, an sensitivity analysis of various meteorological parameters such as precipitation, surface temperature (T2), and relative humidity was performed.

 

Keywords: NWP, WRF, Flash flood, LISFlood, Weather forecast, High-Resolution, GNSS, ZTD

How to cite: Rehman, H. U., Teferle, F. N., Hunegnaw, A., Schumann, G., Zus, F., and Muraleedharan Thundathil, R.: Enhancing Regional NWP Model with GNSS Zenith Total Delay Assimilation: A WRF and WRFDA 3D-Var Approach in the Greater Region of Luxembourg, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18548, https://doi.org/10.5194/egusphere-egu24-18548, 2024.

EGU24-18938 | Posters on site | AS1.2

Forecasting tropical high-impact rainfall events using a hybrid statistical dynamical technique based on equatorial waves 

Samantha Ferrett, Gabriel Wolf, John Methven, Tom Frame, Christopher Holloway, Oscar Martinez-Alvarado, and Steve Woolnough

Recent work within the WCSSP FORSEA project and its successor FORWARDS has demonstrated that a hybrid statistical-dynamical forecasting technique combining model ensemble forecasts of equatorial waves with climatological rainfall statistics conditioned on wave phase and amplitude can provide additional skill in predicting high impact weather. The underlying rationale for the technique is twofold. Firstly that high impact rainfall events in the tropics are commonly associated with presence of equatorial waves; and secondly that while global models can adequately predict the evolution of dynamical structure of equatorial waves on time-scales of several days they do not predict the relationship between waves and rainfall well. In tests using the Met Office Global and Regional Forecasting System (MOGREPS) the hybrid forecast is found to outperform model rainfall forecasts from both the global and regional convection permitting versions of MOGREPS, however a weighted blend of the MOGREPS forecasts and the hybrid forecast was found to have the highest skill and further improvements in the method may be obtained by taking into consideration the effects of wave-superposition and interaction. To ascertain whether forecasts can be further improved by better predictions of wave amplitude and phase we compare to hypothetical best-case hybrid forecast computed using wave amplitudes and phases taken from reanalysis. This best-case scenario indicates that errors in forecasting all wave types diminish the hybrid forecast's skill, with the most significant reduction observed for Kelvin waves, suggesting that a significant improvement in the prediction of the propagation of equatorial waves would have a significant impact on rainfall prediction in the tropics. 

How to cite: Ferrett, S., Wolf, G., Methven, J., Frame, T., Holloway, C., Martinez-Alvarado, O., and Woolnough, S.: Forecasting tropical high-impact rainfall events using a hybrid statistical dynamical technique based on equatorial waves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18938, https://doi.org/10.5194/egusphere-egu24-18938, 2024.

EGU24-19257 | ECS | Orals | AS1.2

Dynamic Locally Binned Density Loss 

Jan Prosi, Sebastian Otte, and Martin V. Butz

In the field of precipitation nowcasting recent deep learning models now outperform traditional approaches such as optical flow [1,2]. Despite their principled effectiveness, these models and their respective training setups suffer from particular shortcomings.  For instance, they often rely on pixel-wise losses, which lead to blurred predictions by which the model expresses its uncertainty [2]. Additionally, these losses can negatively impact training dynamics by overly penalizing small spatial or temporal discrepancies between predictions and actual observations, i.e., the double penalty problem [3]. Generative methods such as discriminative losses or diffusion models do not suffer from the blurring effect as much [1, 4]. However, training these methods is complicated because training success is highly sensitive to the network architecture as well as to the learning setup and its parameterization [5].

Previous research has shown that spatial verification methods such as the fractions skill score offer an easy-to-implement alternative to solve the problem of pixel-wise losses [6, 7]. However, the fact that each pixel within the neighborhood of a spatial kernel is weighted equally poses a limiting factor to their performance and potential. Inspired by theories of cognitive modeling and in relation to the fractions skill score loss, we introduce a dynamic locally binned density (DLBD) loss: Forecasting target is not the actual precipitation in a grid cell but a target distribution, which encodes the density of binned precipitation values in a locally weighted area of grid cells. The loss is then determined via the cross-entropy of the predicted and the target distribution. We show that our novel prediction loss avoids the double penalty problem.  It thus diminishes the negative impact of small spatial offsets. Moreover, it enables the learning model to gradually shift focus towards progressively more accurate predictions.

We achieve best performance by simultaneously training on multiple concurrent forecasting targets that cover different local extents. We schedule the weighting of the loss terms such that the focus shifts from larger to smaller neighborhoods over the course of training. This way, the DL model first learns density dynamics and basic precipitation shifts. Later, it focuses on minimizing small spatial deviations, tuning into the local dynamics towards the end of training.  Our DLBD loss is easy-to-implement and shows great performance improvements.  We thus believe that DLBD losses can also be used by other forecasting architectures where the current forecasting loss precludes smooth loss landscapes.

 


1: Leinonen et al. 2023: Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification
2: Espeholt et al. 2022: Deep learning for twelve hour precipitation forecasts
3: Grilleland et al. 2009: Intercomparison of spatial forecast verification methods.
4: Ravuri et al. 2021: Skilful precipitation nowcasting using deep generative models of radar
5: Mescheder et al. 2018: Which training methods for GANs do actually converge?
6: Roberts et al. 2008: Scale-selective verification of rainfall accumulations from high resolution forecasts of convective events.
7: Lagerquist et al. 2022: Can we integrate spatial verification methods into neural-network loss functions for atmospheric science?

How to cite: Prosi, J., Otte, S., and Butz, M. V.: Dynamic Locally Binned Density Loss, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19257, https://doi.org/10.5194/egusphere-egu24-19257, 2024.

EGU24-19321 | ECS | Orals | AS1.2

Viability of satellite derived irradiance data for ML-based nowcasts 

Pascal Gfäller, Irene Schicker, and Petrina Papazek

Photovoltaic (PV) power production is increasingly becoming a central pillar in the shift to renewable power sources. The use of solar irradiance has great potential, as it is practically limitless and globally provides magnitudes more energy to the Earth than currently or foreseeable required. Solar irradiance as a power source does, however come with certain downsides. Besides the effects of seasonality and day-night-cycles on its usable potential, it´s broad use suffers mostly from uncertainty through its volatility. The actual extent of solar irradiance at the surface of the Earth is strongly influenced by a variety of atmospheric phenomena, most prominently clouds and atmospheric turbidity. The forecasting of near-future solar irradiance can thereby be beneficial in the estimation of PV power production in itself and with the goal of maintaining a stable equilibrium in electrical grids.

To achieve nowcasts on a larger grid scope, forecasting of solar irradiance from satellite data can substitute forecasting of power output for individual sites. Satellite data, in contrast to ground-based data sources or NWP model estimates, is less reliant on the proper workings of a wide range of externalities. General-purpose spatiotemporal neural networks can be adapted to this task and provide predictions within a very short timeframe, with no requirement of HPC-infrastructure. A sparse model relying on a single satellite-based data source has less points of failure that could affect its forecasting performance and can be very efficient, but this sparsity could also reduce the achievable predictive accuracy. Benefits of smaller and simpler forecasting pipelines therefore may need to be balanced with requirements in terms of accuracy.

To gather more meaningful and reliable results, a variety of spatiotemporal neural networks is implemented and tested to provide a more meaningful foundation. The models were selected and evaluated with respect to their different architectural patterns and designs, to get a notion of architectures beneficial to this task and achieve a more generalizable argument concerning the use satellite data as the sole basis of solar irradiance nowcasting.

In an attempt of improving the viability of satellite-based nowcasting a commonly occurring flaw in near-real-time satellite data sources, missing or skipped frames, solutions to mitigate issues in operational nowcasting are considered. In place of ad-hoc preprocessing such as interpolation of missing data frames, an attempt to condition the models to missing frames is made.

How to cite: Gfäller, P., Schicker, I., and Papazek, P.: Viability of satellite derived irradiance data for ML-based nowcasts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19321, https://doi.org/10.5194/egusphere-egu24-19321, 2024.

EGU24-19377 | ECS | Posters on site | AS1.2

Advancing Spatiotemporal Rainfall Nowcasting through Deep Learning Techniques 

Ahmed Abdelhalim, Miguel Rico-Ramirez, Weiru Liu, and Dawei Han

For weather forecasters and hydrologists, predicting rainfall in the short term – minutes to a few hours – is crucial for a range of applications. While traditional nowcasting methods excel in operational settings, they face limitations in predicting convective storm formation and high-intensity events. Enter deep learning, a powerful tool transforming numerous fields. Convolutional neural networks, in particular, have shown promise in improving nowcasting accuracy. These networks can learn complex patterns and relationships within data, like the intricate tapestry of rainfall variations observed in historical radar sequences. However, capturing long-term dependencies in this data remains a challenge, resulting in fuzzy nowcasts and underestimating high-intensity events. This study proposes a novel deep learning model that goes beyond simple extrapolation, effectively capturing both the spatial correlations and temporal dependencies within rainfall data. Our hybrid convolutional neural network architecture tackles this challenge through three key components: Decoder & Encoder: These modules focus on unraveling the intricate spatial patterns of rainfall and a temporal Module to learn the subtle long-term evolutions and interactions between rain cells over time. By capturing these temporal dependencies, the model can produce more accurate forecasts. To evaluate the model performance, it is compared against both deep learning and optical flow baselines. This presentation will introduce the model and provide a summary of its performance in spatiotemporal rainfall nowcasting.

Keywords: deep learning; spatiotemporal encoding, rainfall nowcasting; radar; optical flow

How to cite: Abdelhalim, A., Rico-Ramirez, M., Liu, W., and Han, D.: Advancing Spatiotemporal Rainfall Nowcasting through Deep Learning Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19377, https://doi.org/10.5194/egusphere-egu24-19377, 2024.

EGU24-19699 | ECS | Posters on site | AS1.2

Evaluation of seamless forecasts for severe weather warnings  

Verena Bessenbacher, Jonas Bhend, Lea Beusch, Daniele Nerini, Colombe Siegenthaler, Christoph Spirig, and Lionel Moret

At MeteoSwiss, NWP and ML-based models are run operationally on a daily basis to provide weather forecasts and weather warnings for the general public. These forecasts come from various models that differ in lead times, initialization frequency, spatial resolution, and extents. We aim at combining those sources into a probabilistic, gridded weather forecast that is seamless in space and time. Creating a seamless forecast needs careful post-processing so as not to introduce cut-offs or unphysical behavior at the seams between the model runs. This includes using multiple forecast sources and forecast initializations (called lagged ensembles) and combining these using comprehensive blending methods. 

The first minimal viable product of a seamless forecast is currently being produced at MeteoSwiss, and will soon be available to the forecasters in real time. 

We evaluate the merit of these forecasts in terms of warning thresholds for rain and wind gusts. To do so, we compare reforecasts and observations from ground stations as well as rain radar observations from a set of past severe weather events over Switzerland. We benchmark the seamless forecast with individual forecast sources and post-processed products to evaluate the added value of seamlessly combining different forecast sources into one blended product. We furthermore plan to compare different methods for blending between sources soon.

How to cite: Bessenbacher, V., Bhend, J., Beusch, L., Nerini, D., Siegenthaler, C., Spirig, C., and Moret, L.: Evaluation of seamless forecasts for severe weather warnings , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19699, https://doi.org/10.5194/egusphere-egu24-19699, 2024.

Integrating the hybrid and multiscale analyses and the parallel computation is necessary for current data assimilation schemes. A local data assimilation method, Local DA, is designed to fulfill these needs. This algorithm follows the grid-independent framework of the local ensemble transform Kalman filter (LETKF) and is more flexible in hybrid analysis than the LETKF. Local DA employs an explicitly computed background error correlation matrix of model variables mapped to observed grid points/columns. This matrix allows Local DA to calculate static covariance with a preset correlation function. It also allows using the conjugate gradient (CG) method to solve the cost function and allows performing localization in model space, observation space, or both spaces (double-space localization). The Local DA performance is evaluated with a simulated multiscale observation network that includes sounding, wind profiler, precipitable water vapor, and radar observations. In the presence of a small-size time-lagged ensemble, Local DA can produce a small analysis error by combining multiscale hybrid covariance and double-space localization. The multiscale covariance is computed using error samples decomposed into several scales and independently assigning the localization radius for each scale. Multiscale covariance is conducive to error reduction, especially at a small scale. The results further indicate that applying the CG method for each local analysis does not result in a discontinuity issue. The wall clock time of Local DA implemented in parallel is halved as the number of cores doubles, indicating a reasonable parallel computational efficiency of Local DA.

How to cite: Wang, S. and Qiao, X.: A Local Data Assimilation Method (Local DA v1.0) and its Application in a Simulated Typhoon Case, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21770, https://doi.org/10.5194/egusphere-egu24-21770, 2024.

EGU24-21772 | Orals | AS1.2

Calibration of Convective-scale Hourly Precipitation Based on the Frequency-Matching Method 

Xiaoshi Qiao, Shizhang Wang, and Mingjian Zeng

Calibration of convective-scale hourly precipitation based on the frequency-matching method was carried on using CMPASS observation and CMA-MESO 3km forecast data. The character of hourly precipitation bias was studied.The effect of frequency-matching method (FMM) on the bias correction of CMA-MESO 3km hourly precipitation forecasts was analyzed. In the bias characteristic analysis, the differences in precipitation intensity in different regions of the country and the differences in precipitation in different months were considered. The whole country was divided into 7 sub-regions for monthly analysis. In the bias correction based on the frequency-matching method, the daily variations of precipitation bias and the impact of increasing and decreasing precipitation values on the corrected precipitation scores were analyzed. The results show that CMA-MESO 3km forecasts have a wet bias in light rainfall in the cold season, while a dry bias dominates in moderate to heavy rainfall. In the warm season, except for the Tibet region, the hourly precipitation forecast bias of CMA-MESO 3km shows significant daily variations, with more precipitation in the afternoon and less at night and in the morning, especially for heavy rainfall. Therefore, whether to consider the daily variations of precipitation bias in the use of FMM correction mainly reflects in the summer, especially at night and in the morning. Considering the daily variations of precipitation bias is beneficial to improving the forecast skills (TS scores) for nighttime and morning in the summer. Further analysis shows that the positive contribution of FMM correction to forecast scores mainly comes from the increase in frequency adjustment, especially for heavy rainfall. However, for light rainfall with wet bias, FMM often results in negative contribution. Therefore, FMM has a significant improvement effect on heavy rainfall in winter and nighttime rainfall in summer. The reason for this result is that the hit rate of CMA-MESO hourly precipitation forecast is low, and the false alarm rate is generally high, especially for heavy rainfall. In this case, the increased precipitation significantly increases the hit rate, while the false alarm rate increases to a lesser extent, thereby improving the precipitation scores.

How to cite: Qiao, X., Wang, S., and Zeng, M.: Calibration of Convective-scale Hourly Precipitation Based on the Frequency-Matching Method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21772, https://doi.org/10.5194/egusphere-egu24-21772, 2024.

NH2 – Volcanic Hazards

EGU24-1402 | ECS | Posters on site | NH2.1

Global Sensitivity Analysis of tephra models for forecasting 

Emmy Scott, Melody Whitehead, Stuart Mead, Mark Bebbington, and Jonathan Procter

Accurate forecasts are needed to help mitigate the risks of volcanic hazards to society. Current approaches use probabilistic estimates based on sparse data, supplemented with expert judgment, to describe likely future eruption characteristics. These probabilistic eruption characteristics then inform input parameters required by hazard models.

This process requires a lot of simulations with varying input parameters to constrain uncertainty around a future eruption’s hazard characteristics. It is also computationally intensive, and the outputs may quantify, but do not reduce eruption uncertainty. As hazard models become increasingly more complex, so do the number of input parameters that need to be estimated, thus increasing the number of sources of uncertainty. As input parameters used for volcanic hazard models are fundamentally uncertain before (and often also after) an eruption, how do they affect the accuracy and utility of forecasts made using these models?

This research explores the input space of volcanic hazard models to understand the interactions between model complexity and robustness of hazard model forecasts. We use the exemplar of volcanic ash distribution models Tephra2 and Fall3D at Mt. Taranaki, Aotearoa-New Zealand (30-50% chance of eruption in the next 50 years). Sampling strategies for Tephra2 and Fall3D were developed to ensure that the input parameter space was fully covered and represent real-world values – both through independent and dependent sampling of parameters. For example, plume height is dependent on the amount of mass ejected during an eruption. A Global Sensitivity Analysis is presented here to investigate the input parameters that significantly influence model output variance. This exploration is conducted through the statistical assessment of Sobol’ indices and eFAST (extended Fourier Amplitude Sensitivity Tests) to discern the key parameters that contribute to variations in the model’s outputs. The results also shed light on which inputs are vital to robust short-term and real-time hazard forecasting, and ultimately require better understanding/quantification before an event.

How to cite: Scott, E., Whitehead, M., Mead, S., Bebbington, M., and Procter, J.: Global Sensitivity Analysis of tephra models for forecasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1402, https://doi.org/10.5194/egusphere-egu24-1402, 2024.

EGU24-1455 | ECS | Orals | NH2.1

Dam-break of shear-thickening suspensions: A new perspective for crystal-rich lava flows and lahars - 

Alexis Bougouin, Henri Lhuissier, Yoel Forterre, and Bloen Metzger

The physical mechanism governing the peculiar behavior of discontinuous shear-thickening suspensions, i.e. a change from liquid-like to solid-like state with increasing applied stress, has recently been described as a frictional transition occuring at the grain scale above a critical shear stress [1, 2, 3]. This understanding offers a new view for describing complex grain-fluid flows, and especially crystal-rich lava flows, which can shear-thicken [4], or lahars, whose heterogeneities affect local friction [5].

In this context, we performed macroscopic and local measurements to characterize dam-break laboratory experiments of model shear-thickening suspensions, for which the volume and the solid fraction of the suspension are varied. Below a critical stress related to the gravitational pressure gradient, the suspension flow is close to that of a viscous Newtonian liquid, i.e. strongly decelerating and with a thickness decreasing progressively from the release side to the spreading front [6]. By contrast, above this critical stress, the front velocity becomes constant, i.e. independent of flow height, and the layer thickness is close to be uniform (Figure 1). We interpret this remarquable behavior by the formation of a highly-dissipative (shear-thickened) flow structure at the front, which keeps the suspension upstream essentially stress-free with a low (frictionless) viscosity. We model the front and provide scaling laws for its velocity in good agreement with experimental observations. These results offer a new perspective for the interpretation and modeling of heavily particle-laden geophysical flows, such as crystal-rich lava flows and lahars, which could also be essentially controlled by their highly-dissipative front.

1. M. Wyart and M. Cates (2014). Discontinuous shear thickening without inertia in dense non-Brownian suspensions. Phys. Rev. Lett., 112:098302, 2014.

2. R. Mari, R. Seto, J. Morris, and M. Denn (2014). Shear thickening, frictionless and frictional rheologies in non-Brownian suspensions. J. Rheol., 58:1693–1724, 2014.

3. C. Clavaud, A. Bérut, B. Metzger, and Y. Forterre (2017). Revealing the frictional transition in shear-thickening suspensions. Proc. Natl. Acad. Sci., 114:5147–52, 2017.

4. J. V. Smith (1997). Shear thickening dilatancy in crystal-rich flows. J. Volcanol. Geotherm. Res., 79:1-8.

5. C. Ancey (2007). Plasticity and geophysical flows : A review. J. Non-Newton. Fluid Mech., 142:4-35.

6. H. E. Huppert (1982). The propagation of two-dimensional and axisymmetric viscous gravity currents over a rigid horizontal surface. J. Fluid Mech., 121:43-58.

How to cite: Bougouin, A., Lhuissier, H., Forterre, Y., and Metzger, B.: Dam-break of shear-thickening suspensions: A new perspective for crystal-rich lava flows and lahars -, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1455, https://doi.org/10.5194/egusphere-egu24-1455, 2024.

EGU24-1510 | ECS | Posters on site | NH2.1

A quantitative analysis of monitoring signals and eruption explosivity 

Brenda Contla Hernandez, Melody Whitehead, Mark Bebbington, and Michael Rowe

Volcanic hazards are dependent on eruption size and explosivity, thus, the forecasts of these is crucial for emergency management decisions. Monitoring a volcano potentially offers valuable insights to assess when, where, and how explosive a future eruption might be. Data are collected from various monitoring equipment, such as seismometers, tiltmeters, and thermometers, that are installed at different locations and distances, from near-vent to satellite. However, establishing direct links between monitoring signals and even eruption onset remains challenging, especially for volcanoes lacking recent eruptions or without monitoring equipment installed prior to eruption. This challenge extends to eruption explosivity, where establishing links becomes even more difficult.

The Global Volcanism Program (GVP) has compiled monitoring data in bulletin reports recorded by observatories and research institutions. These reports start from 1968 and summarise volcanic activity that occurs before, during and after an eruption. Importantly, these reports include descriptions about activity and/or raw data (number of earthquakes, frequencies, plots of the seismic signals or displacements on tiltmeters) from various monitoring equipment, providing a general understanding of precursor activities preceding an eruption. This is potentially key information for forecasting eruption explosivity.

This study aims to establish a quantitative link between monitoring signals and eruption explosivity across multiple volcanoes. Data are compiled from 23 volcanoes worldwide, utilising information from the Global Volcanism Program (GVP) database and local volcano observatory reports where accessible. The different descriptions obtained by each class of monitoring equipment—whether seismic, thermal, deformation, SO2 fluxes, or crater alterations—will be statistically categorized and calibrated into predictor variables to be used in machine learning algorithms. We hope to develop a procedure for estimating the explosivity of the next eruption, as a step towards statistically forecasting future eruption styles.

How to cite: Contla Hernandez, B., Whitehead, M., Bebbington, M., and Rowe, M.: A quantitative analysis of monitoring signals and eruption explosivity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1510, https://doi.org/10.5194/egusphere-egu24-1510, 2024.

EGU24-2811 | ECS | Posters on site | NH2.1 | Highlight

Forecasting the evolution of volcanic unrest 

Salvatore Ferrara, Warner Marzocchi, Jacopo Selva, and Laura Sandri

The management of volcanic unrest near densely inhabited areas requires collaboration between scientists, who are required to provide near real-time information, and decision makers. The ambiguity of pre-eruptive patterns and the inaccessibility and the complexity of the system lead to large uncertainties, suggesting the preference for probabilistic approaches over deterministic ones. The divergence of scientists' opinions regarding pre-eruptive phenomena can lead to extreme confusion, which inevitably translates into the difficulty of reaching an agreement for the optimal management of an emergency. Expert elicitation is a procedure for extracting a collective opinion in a relatively short time despite the incomplete knowledge of the problem and is therefore an effective tool for managing forecasts during volcanic crises in near real-time. In this work we present the results of the latest elicitation sessions at the Campi Flegrei caldera, represented by a list of weighted parameters with their respective thresholds that define the anomalous values and their interpretation, to calibrate BET_EF eruption forecasting model. Our aim is to re-calibrate it using the most recent scientific evidence linked to the increase of the activity of Campi Flegrei which has been observed in the last few years, evaluating the probability that the mechanism underlying the current unrest is a rise of magma, and the probability that this could lead to an eruption. Finally, we demonstrate a practical application showing the variation of the probability of magmatic unrest and eruption as a function of the variation of the values of the monitoring parameters ​​obtained through the elicitation.

How to cite: Ferrara, S., Marzocchi, W., Selva, J., and Sandri, L.: Forecasting the evolution of volcanic unrest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2811, https://doi.org/10.5194/egusphere-egu24-2811, 2024.

EGU24-4270 | Orals | NH2.1 | Highlight | Plinius Medal Lecture

Hazard forecasting: is it a matter of time? 

Jacopo Selva

Hazard models aim at making explicit our forecasting capability about future potentially adverse natural events. Hazard events are typically rare and not deterministically predictable, forcing hazard models to speak the language of certainty and uncertainty, that is, of probability. This is valid for any forecasting time window, from years to days/hours in the future (long- to short-term hazard), to the evaluation of the potential impact of an ongoing event in the next seconds/minutes/hours (warning/now-casting to urgent computing). Even though the definition of the target time window is driven by the users of the forecast (e.g. civil protections) and is not a scientific matter, the quantification of existing uncertainty given the time frame is certainly a scientific matter. Probabilistic hazard is commonly discussed mainly for long-term hazards, where large uncertainty dominates. In shorter-term forecasts, uncertainty may deacrease and practitioners are often tempted by simplified approaches that neglect uncertainty, like for eruption forecasting during volcanic crises, or for tsunami warning models after seismic or volcanic events. Nevertheless, uncertainty may still exist, and a rational scientific approach should let the results to speak about existing uncertainty, rather than to neglect it by definition. Is it possible to define a unified approach to probabilistic hazard entailing all time scales? The long-term integral hazard integrating all potential sources and generation/propagation conditions can be adapted to the different forecasting time windows, generating a unified framework in which the different time scales may feed to each other, producing homogeneous and easy-to-interpret results. This unified vision of hazard models, embracing long- to short-term hazard as well as warning and urgent computing models, is here discussed based on the recent advancements in models for volcanic, seismic and tsunami hazard and warning.

How to cite: Selva, J.: Hazard forecasting: is it a matter of time?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4270, https://doi.org/10.5194/egusphere-egu24-4270, 2024.

In extensional and transtensional basins, the dual action of basin-forming tectonism and explosive volcanic activity results in deposition of complex volcano-sedimentary successions. Since both aspects contemporaneously affect sediment-dispersal systems, it is difficult to distinguish one from the other by analyzing volcano-sedimentary successions. To discriminate tectonic influence, basin fills of the Miocene, pull-apart Janggi Basin were investigated. Here, the contemporaneous influence of tectonic subsidence and explosive volcanism formed <966 m thick, conformable volcano-sedimentary successions composed of laterally extensive, pumice-bearing, unwelded pyroclastic deposits and nonmarine sedimentary rocks formed under humid climatic conditions. Based on Laser Ablation – Multiple Collector – Inductively Coupled Plasma Mass Spectrometry zircon U-Pb age data, these successions were deposited from 21.1 ± 0.2 to 20.1 ± 0.1 Ma. After deposition of basinwide, tens of metres thick, and unwelded pyroclastic deposits, the directly overlying facies successions (FS-1 and FS-2) show contrasting depositional features to the classical model of volcaniclastic sedimentation. Facies succession-1 is represented by fluvial conglomerates composed mostly of (sub)rounded pebble and cobble sourced from basement. The supply of basement-derived clasts through fluvial systems resulted from development of physiographic relief during or soon after the eruption by syndepositional tectonic subsidence. Facies succession-2 occurs directly on pyroclastic deposits that cover FS-1 and show coarsening-upward trends, and is composed of basal lacustrine mudstones and overlying resedimented volcaniclastic sandstones showing a progradational geometry, interpreted as a result of progressive filling of the lake by remobilized volcaniclastic sediments. Occurrence of basal lacustrine laminated mudstones indicates that syndepositional creation of the accommodation by tectonic subsidence exceeded forceful input of pyroclastic and remobilized volcaniclastic sediments, resulting in a delayed sedimentary response to explosive volcanic eruptions. This study shows that, despite voluminous production of volcaniclastic sediments, tectonic activity controlled sediment type and stacking patterns. Therefore, these depositional features allow to discriminate tectonic effects from complex volcano-sedimentary successions, enabling to reconstruct basin evolution. 

How to cite: Gihm, Y., Kim, M.-C., and Chae, Y.-U.: Finding tectonic signals from ancient volcano-sedimentary successions: an example from the Miocene Janggi Basin, SE Korean Peninsula, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6834, https://doi.org/10.5194/egusphere-egu24-6834, 2024.

The Coastal Range of eastern Taiwan is located at the plate boundary of Philippine Sea and Eurasia plates, which is the arc-continent collision zone. Abundant huge blocks, especially in Wushihpi area, which are predominantly composed of the volcanic rocks, are interbedded in the Paliwan Formation. Based on the field surveys, different occurrences of volcanic lithofacies have been recognized in outcrops. They are pillow breccias with and without white vesicle fillings, hyaloclastites, peperites rich and poor in zeolite fillings, lahars, lava flows with columnar structures, weathered brownish and reddish blocks in tuffaceous conglomerates and limestones. Those lithofacies can be grouped into three volcanic facies, the shallow marine, transitional from submarine to subaerial facies and subaerial facies. Those facies occur together chaotically and contact sharply. It infers that the volcanic rocks occurred in Wushihpi of Coastal Range is debris avalanche deposits and the source may come from different volcanic sequences of the Tulunshan volcanics, the major eruption products of Luzon Arc. Meanwhile, similar occurrences of debris avalanche deposits as huge blocks are also widely distributed in whole Coastal Range from the north to the south and Lutao. Those observations suggest that the sedimentation of debris avalanche and tectonics of slope failures may play major roles for denudation of volcanic arc during Taiwan arc-continent collision. 

 

 

How to cite: Song, S.-R. and Lu, Y.-C.: Volcanic Debris Avalanche Deposits in the Coastal Range, Eastern Taiwan: Implications for Sedimentation and Tectonics of Arc-Continent Collision, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7190, https://doi.org/10.5194/egusphere-egu24-7190, 2024.

EGU24-7206 | Posters on site | NH2.1

Distal records of Katla’s explosive past: Ocean-rafted pumice found in archaeological contexts and raised shorelines in Norway 

Anke Zernack, Erlend Kirkeng Jørgensen, Anthony Newton, and Anders Romundset

Ocean-rafted pumice is found on modern and paleo-beaches from the North Atlantic to the South Pacific. Correlation of ocean-rafting events to their volcanic source can help date sedimentary records and landforms, while geochemical fingerprinting of artefacts made from ocean-rafted pumice provides age constraints for pumice-bearing archaeological sites. These pumices also record large explosive eruptions that might not be preserved near the volcano due to extensive erosion or a submarine volcanic source and as such can be used for petrological and geochemical investigations.

This study explores links between spatiotemporal patterns of Holocene pumice deposition along the Norwegian coastline and prehistoric human use of this versatile resource. We first focused on a suite of pumice pieces from archaeological contexts of variable isostatic uplift in Northern Norway with most showing evidence of use as abrasive tools. These samples were geochemically correlated to individual Holocene eruptions or groups of tephras (SILK) from the Katla Volcanic System in Iceland. Our age data revealed that the estimated eruption dates typically predate the contexts by several hundred and up to 2-3,000 years, probably reflecting abundance and availability of certain pumice types at the time.

To investigate how distal resource availability is influenced by geological processes like eruption frequency, ocean-currents, and deposition/preservation we conducted field surveys of two coastal stretches with different climates, geomorphic settings and uplift histories. On Varanger Peninsula in Northern Norway strong Holocene uplift rates and sea-level changes have built a unique record of raised shorelines that provide windows into fossil beach ridges up to the marine limit, covered in little vegetation. We found that pumice was abundant on specific paleo-shorelines and in defined geomorphic settings but absent from older beach ridges. Most samples correlated with the <7 ka Katla record and the distinct mid-Holocene transgression high-stand accumulated the largest variety of pumice types and clast sizes. One sample cluster overlaps with SILK tephra compositions but does not correlate to any known Katla units while a single pumice plots outside the field defined by Katla eruptives, resembling compositions known for Jan Mayen.

In contrast, the Trøndelag and Nordland coast in Southern Norway is heavily vegetated and pumice was only found at isolated sites that displayed the right conditions, important factors being: a) the paleo-setting of the beach (e.g., currents, orientation, morphology) favouring accumulation in the first place, b) rapid uplift and limited erosion enabling preservation of the stranded pumice and c) exposure of pumice-bearing beach ridges (sections cut by rivers/erosion, roads/construction) as subsequent burial by sediment, soil and vegetation further reduces access to previously available pumice resources. This supports our hypothesis of pumice only being readily available for limited periods of time following eruption, rafting and onshore deposition. We will further test this assumption by integrating compositional information of archaeological pumice pieces from a recent archaeological excavation in Lofoten into our data-set.

Overall, our study provides a better understanding of the nature and frequency of Holocene silicic eruptions from Katla while also improving age control for existing relative sea-level curves and archaeological contexts in Norway.

How to cite: Zernack, A., Jørgensen, E. K., Newton, A., and Romundset, A.: Distal records of Katla’s explosive past: Ocean-rafted pumice found in archaeological contexts and raised shorelines in Norway, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7206, https://doi.org/10.5194/egusphere-egu24-7206, 2024.

EGU24-7208 | Posters on site | NH2.1

Characterising transport and emplacement mechanisms of volcanic debris avalanches through 3D Micro Tomography.  

Jonathan Procter, Shannen Mills, Anke Zernack, Stuart Mead, Andrew Stevenson, and Benedicta Arhatari

Volcanic communities near long-lived stratovolcanoes are susceptible to the significant threat associated with edifice collapse events which produce volcanic debris avalanches. These events can have runout distances > 100 km and are the largest mass flows on Earth with volumes ranging from 0.1 to 100 km3 which have the potential to bury large sectors of the landscape posing a severe risk to people and infrastructure. However, the emplacement mechanisms of these large destructive phenomena are still poorly understood with the inability to accurately quantify the physical parameters such as frictional regimes, velocity, and temperature which contribute to the extreme runout. The internal structure and minerology of the avalanche deposits hold the key to understanding the transportation mechanisms. During transportation inter-particle collision and shearing occurs reducing grainsize and generating new minerals such as Pseudotachylytes, Frictionites and Silica polymorphs along shear zones between larger clasts and along the base of the flow. Twenty-five volcanic debris avalanches and rock avalanches of varying sizes were sampled from New Zealand and the USA to provide a representative variety of flow types to better understand transportation mechanisms. Using 3D Micro-Computed Tomography at the Australian Synchrotron the internal structure of the avalanche deposits were analysed to identify different minerals and structures present. Analysis of the microstructures of the samples show a variety of different fracture patterns that can be categorized based on the different source lithologies sampled as well as the different rheological emplacement conditions from the collapse and flow.  Features seen at the micro-scale mimic larger centimeter to meter scale features traditionally observed in the flow.  Investigating the formation of new minerals along collision and shear zones can provide insights on the physical constraints of the flow e.g., velocity and temperature. Data from this study will provide quantitative input parameters forming the foundation for developing a model for transportation and emplacement of long-runout volcanic debris avalanches. Data from these models can be used to assess the volcanic debris avalanche hazards from volcanoes globally, better informing risk assessments.

How to cite: Procter, J., Mills, S., Zernack, A., Mead, S., Stevenson, A., and Arhatari, B.: Characterising transport and emplacement mechanisms of volcanic debris avalanches through 3D Micro Tomography. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7208, https://doi.org/10.5194/egusphere-egu24-7208, 2024.

EGU24-7230 | ECS | Posters on site | NH2.1

Using pyroclastic textures as an index for understanding the impact edifice collapse has on the subvolcanic plumbing system.  

Shannen Mills, Jonathan Procter, Anke Zernack, Stuart Mead, Ian Schipper, Andrew Stevenson, Benedicta Arhatatari, Darren Thompson, and Joseph Fleming

Depressurisation from edifice collapse events can impact the subvolcanic plumbing system as a propagation wave moves down through the system shifting the fragmentation zone. Understanding how this influences the eruptive behaviour at a volcano is important for understanding changes in hazards following a large edifice collapse event. Mt. Taranaki has experienced at least 16 collapse events within its > 200 kyr history. Two of the largest collapse events the 27.3 ka Ngaere and 24.8 ka Pungarehu debris avalanches occurred in close succession and were encompassed by the Poto and Paetahi tephra formations, made up of 28 subplinian eruptions over ~ 4,000 years. This eruptive period provides a unique opportunity to examine and understand the influence that edifice collapse events have on the subvolcanic plumbing system. Using 3D Micro-Computed Tomography at the Australian Synchrotron bubble textural analysis was undertaken to investigate the changes in pyroclastic textures from large explosive eruptions and how these change following an edifice collapse event. The high-resolution 3D scans indicate that the eruptive products from the Poto and Paetahi Formations are dominated by small bubbles (2.7 x 10-7 mm3) with high bubble number densities ranging from 2.56 x 1015 cm-3 to 1.74 x 1016 cm-3. Bubble size distributions for the Poto and Paetahi Formations indicate a range of bubble nucleation and growth processes occurring within the subvolcanic plumbing system below Mt. Taranaki initiating at different depths. Early onset of bubble nucleation and periods of magma stalling are indicated by the presence of large, coalesced bubbles within the eruptive products, while the dominance of smaller bubbles indicates a fast ascent of magma within the system with nucleation occurring higher up in the system. Changes are seen in the textural characteristics of pyroclasts produced following the 27.3 ka 5.85 km3 Ngaere collapse which depressurized the shallow magmatic system and shifted the fragmentation zone. Following the 24.8 ka 7.5 km3 Pungarehu collapse ~2,500 years later the same influence is not seen, due to the cone not having enough time to rebuild between edifice collapse events. The results from this study show that the depressurisation and subsequent propagation wave are dependent on the height above the plumbing system not just the mass removed and therefore two major collapses in close proximity do not show the same systematic impact on the fragmentation zone.

How to cite: Mills, S., Procter, J., Zernack, A., Mead, S., Schipper, I., Stevenson, A., Arhatatari, B., Thompson, D., and Fleming, J.: Using pyroclastic textures as an index for understanding the impact edifice collapse has on the subvolcanic plumbing system. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7230, https://doi.org/10.5194/egusphere-egu24-7230, 2024.

EGU24-8093 | ECS | Posters on site | NH2.1

Improving the efficiency of ensemble-based volcano deformation analyses using Machine Learning 

Matthew Head and Patricia M. Gregg

Geodetic observations are key for assessing the unrest status of volcanoes worldwide, providing critical information about magmatic systems and the potential for magma migration and eruption. Analysing these signals relies on a robust data-model framework. One such approach is the Ensemble Kalman Filter (EnKF), a data assimilation method that has been adapted for analyses of volcanic deformation. The EnKF sequentially assimilates and inverts geodetic observations, using a series of model states to ‘nudge’ the model parameters with each iteration, reducing the misfit between the model and observation. We construct thermomechanical Finite Element (FE) models of volcanic regions, providing the necessary flexibility to incorporate complex 3D geometries and material heterogeneity. However, these simulations are computationally expensive when incorporated into the EnKF workflow, where an ensemble of >200 model states can take several hours to evaluate. This is particularly problematic for the analysis of observational data with high temporal resolution, such as daily GPS measurements.

Here, we aim to reduce the computational cost of the EnKF-FE workflow by using regression machine learning algorithms (MLAs), focusing on reducing the number of model states that need to be evaluated by the FE models. We start by using the ‘Mogi’ deformation model, a simple analytical expression that calculates the three-component displacement field (Ux, Uy, and Uz) due to a point source. We employ a tuneable nearest-neighbour approach to identify model states that occupy a ‘similar’ parameter space, using MLAs to predict the resultant displacements. The Mogi model has significantly reduced complexity compared to that of a FE model, providing a simple platform to test different machine learning approaches. Preliminary results suggests that the k-Nearest Neighbours and Linear Regression algorithms can significantly improve the computational efficiency of the EnKF-FE workflow, with negligible impact on the inferred best-fit model parameters, when a magmatic system is in a steady-state (i.e., static overpressure). Future modelling efforts will consider FE models with a 3D deformation source within a flat-topped domain, and time-varying overpressure scenarios.

How to cite: Head, M. and Gregg, P. M.: Improving the efficiency of ensemble-based volcano deformation analyses using Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8093, https://doi.org/10.5194/egusphere-egu24-8093, 2024.

EGU24-8213 | ECS | Posters on site | NH2.1

First approach to the rheological behaviour of syn-eruptive and post-eruptive lahars. 

Carla Tranquilino, Lizeth Caballero, Mario Flores Guzmán, Damiano Sarocchi, and Fabio Dioguardi

Lahars are two-phase gravity flows which behavior strongly depends on the interaction between the solid phase (large clasts) and the liquid phase (interstitial fluid or matrix). In particular, the rheological behavior of the interstitial fluid is the parameter with the greatest influence on the lahar movement, since the interstitial fluid controls the transportion and sedimentation of the solid phase. The characteristics that define the rheological behavior of the interstitial fluid are particle volumetric concentration, size distribution, and sediment composition. Because of these, here we present the rheological characterization of syn-eruptive and post-eruptive lahars occurred at Popocatepetl volcano, Mexico.

The interstitial fluid characterization was carried out by a strain rate dependence test using a rotational viscometer with a coaxial cylinder geometry. We studied volcanic sediments with different densities and compositions (pumice and lava fragments) sampled from syn- and post-eruptive lahar deposits (at room temperature). In addition, we studied the range of the volumetric sediment concentration that defines the flowage based on the geotechnical characteristics of sediments.

The results suggest a Bingham-type behaviour model with yield strength values between 10-2 and 100 Pa, for shear rate conditions between 50 and 100 s-1. In addition, an inverse relationship of apparent viscosity throw values between 10-2 and 10-1 Pa s at  the same shear rates, suggesting a thinning behaviour. The data suggest exponential relationships between volumetric sediment concentration and yield strength or apparent viscosity. The fitting coefficients describe volcanic sediments, unlike those found in the literature and often used in lahar simulations for hazard modelling, which are derived from the study of soil materials and mine tailings.

The interstitial fluid of syn-eruptive lahars with monolithologic composition (pumice fragments) has yield strength and apparent viscosity values higher than those of syn-eruptive and post-eruptive lahars with heterolithologic composition (pumice and lava fragments). In addition, the dominant clay-sized interstitial fluid has apparent viscosity values between two and three orders of magnitude higher than the dominant silt-sized interstitial fluid.

Finally, the rheological behavior of the studied lahar samples will contribute to solving  the constitutive equations that describe their movement under a viscoelastic flow behavior for the studied shear rates. Furthermore, this information could be implemented in numerical simulations with similar volcanic sediment characteristics and deformation conditions to those studied, with the aim of estimating the inundation area that would be affected by the occurrence of a similar event.

 

 

How to cite: Tranquilino, C., Caballero, L., Flores Guzmán, M., Sarocchi, D., and Dioguardi, F.: First approach to the rheological behaviour of syn-eruptive and post-eruptive lahars., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8213, https://doi.org/10.5194/egusphere-egu24-8213, 2024.

Atmospheric dispersion models are employed during volcanic eruptions to forecast the atmospheric transport and dispersion of the ash cloud. Uncertainties exist in the predicted ash cloud due to uncertainties in the ash emissions, in the atmospheric dispersion model and its parameterisations, and in the driving input meteorological data. A Bayesian inversion method has been developed for estimating the height- and time-varying profile of ash emissions using satellite retrievals of ash column load, atmospheric dispersion modelling and a prior estimate of emissions (Pelley et al., 2021). Gaussian distributions are assumed for the prior distribution of the emissions and for the errors in the satellite retrievals. An optimal emission estimate is obtained by finding the peak of the posterior probability density, subject to an imposed non-negative constraint on the emissions. The method is computationally efficient and suited for operational use.

In the original design of the Bayesian inversion method, uncertainties in the atmospheric dispersion model and its input meteorological data are not considered. Errors in the input meteorological data can lead to discrepancies between the modelled and observed ash cloud locations and can affect the performance of the Bayesian inversion method. We employ ensemble NWP (Numerical Weather Prediction) data sets to overcome issues with meteorological errors. The Bayesian framework enables a model selection approach to be adopted, where a ‘best’ meteorological data set is chosen from within the ensemble. Using the eruption of the Icelandic volcano Grímsvötn in 2011 as a case study, we illustrate the impact meteorological errors can have on ash emission estimates and show how the ‘best’ meteorological data set leads to improvements in ash cloud forecasts.

The posterior probability density is a multi-dimensional Gaussian distribution which contains information on the uncertainty in the estimated emissions. If time permits, I will describe recent attempts to obtain an ensemble of emission estimates by sampling from the posterior distribution. This is challenging because of the high dimensionality and the non-negative emissions constraint. Nonetheless, an ensemble of emission estimates from the posterior distribution would enable the uncertainty in the emissions estimate, and the associated uncertainty in the ash concentrations in the predicted ash cloud, to be quantified.

How to cite: Webster, H., Thomson, D., and Salter, J.: A Bayesian inversion method for estimating ash emissions: accounting for meteorological uncertainty & quantifying uncertainty in the estimated emissions., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9544, https://doi.org/10.5194/egusphere-egu24-9544, 2024.

EGU24-9844 | ECS | Posters on site | NH2.1

Numerical modelling of the lahars generated during the 2015 eruption at Volcán Villarrica (Chile) 

Silvio Kmetyko, Martin Mergili, and José Luis Palma

The Villarrica or Rukapillan is one of the most active volcanoes in South America. In Chile it is the volcano with the highest risk to human life and infrastructure. An eruption on 3rd of March 2015 triggered several lahars that affected four different valleys, where they caused the destruction of touristic infrastructure and parts of the local road network. Adequate numerical simulations of such events can build an important basis for risk management. Various software tools are available to accomplish such task, each of which has its potentials and limitations. This work compares two sets of numerical simulations of the lahars that occurred in the valley Zanjón Seco during the 2015 eruption. The first set is conducted with r.avaflow, a physically-based open-source simulation framework for mass flows and process chains which runs in the GRASS GIS environment. The second is realized with Laharz, a statistically-based tool which runs in an ArcGIS environment. Strengths and weaknesses of both simulation tools in regard to the adequate reconstruction of the observed lahar events reproducing such volcanic hazards are discussed. For this purpose, the model outputs are evaluated against the lahar deposits mapped in the valley and qualitatively compared with each other.

How to cite: Kmetyko, S., Mergili, M., and Palma, J. L.: Numerical modelling of the lahars generated during the 2015 eruption at Volcán Villarrica (Chile), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9844, https://doi.org/10.5194/egusphere-egu24-9844, 2024.

EGU24-9948 | ECS | Posters on site | NH2.1

Incorporating eruption source parameter and meteorological variability in the generation of probabilistic volcanic ash hazard forecasts 

Shannon Williams, Frances Beckett, Susan Leadbetter, Jeremy Phillips, Anthony Lee, and Mark Woodhouse

Volcanic ash represents a hazard to aviation and a global network of Volcanic Ash Advisory Centres (VAACs) are tasked with providing advice and guidance to the aviation industry on its presence in the atmosphere. Forecasts of the expected location of the ash cloud are generated using atmospheric transport and dispersion models, initialised with a set of Eruption Source Parameters (ESPs) and driven by forecast meteorological data. In the future the VAACs will be required to adopt a Quantitative Volcanic Ash (QVA) approach of issuing probabilistic volcanic ash concentration information to the aviation industry, as such there is a need to develop a framework for producing a probabilistic forecast which incorporates both the uncertainty in forecast meteorology and in the eruption source parameters (ESPs). Variability in the meteorological forecasts is typically expressed as an ensemble of meteorological data, which can be provided to an atmospheric dispersion model to produce an ensemble of simulations in which ESPs are kept constant, and outputs are aggregated to remove the conditioning on the meteorology. Dispersion model forecasts are also sensitive to the ESPs used to initialise the simulations, notably the plume height and the mass eruption rate (MER) of volcanic ash injected into the atmosphere. The latter is difficult to measure in real-time, and for event response it is assumed to scale with the plume height. There remains a high degree of uncertainty in these linked ESPs, which can be modelled via a Bayesian linear modelling approach. We will present a method for incorporating the combined variability of ESPs and meteorological forcing into the ensemble to obtain values of exceedance probabilities for airborne volcanic ash concentrations of interest, using standard statistical techniques and numerical methods, whilst keeping computational and time costs down for efficient evaluation in an emergency. 

How to cite: Williams, S., Beckett, F., Leadbetter, S., Phillips, J., Lee, A., and Woodhouse, M.: Incorporating eruption source parameter and meteorological variability in the generation of probabilistic volcanic ash hazard forecasts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9948, https://doi.org/10.5194/egusphere-egu24-9948, 2024.

EGU24-15962 | ECS | Posters virtual | NH2.1

Understanding the dynamics of unsteady buoyant Jets: an experimental analogue of Vulcanian and Strombolian style eruptions 

Morgan Hetherington, Alan Cuthbertson, Sue Dawson, and Fabio Dioguardi

Explosive volcanic eruptions, which are characterized by the discharge of ash and gas from the vent into the atmosphere, are an example of a naturally occurring buoyant jet.  These buoyant jets can significantly impact the surrounding environment; for example, the presence of fine ash particles in the atmosphere can damage aircraft engines, potentially leading to engine failure. Therefore, during an explosive eruption, volcanic ash advisory centers (VAACs) consistently monitor the concentration of ash in the atmosphere using numerical models. These numerical models require the definition of a source term (i.e., source mass eruption rate, plume height and total grain size distribution), which is often obtained from simpler one-dimensional models. One-dimensional models derived from well-established theories successfully replicate the dynamics of the initial buoyant jet; however, they assume time-averaged source conditions which are not observed in field-scale vulcanian and strombolian style eruptions. As such, there is a disconnect between these well-established theories assuming time averaged source conditions and reality. This disconnect may introduce uncertainties in ash concentration forecasts, potentially resulting in practical implications such as unnecessary airspace closures or flights operating in hazardous conditions. The present contribution utilizes scaled laboratory experiments to quantify the influence of source variability on the dynamics of buoyant jets and evaluates potential deviations from time-average assumptions.

Scaled laboratory experiments were conducted in an acrylic tank measuring 1200x670x450 mm, filled with water to a depth of 870 mm. A vertical pipe, 18 mm in diameter, was used to release fresh water (density ρ = 1000 kg/m³), which was combined with dye or particles, into saline water (ambient density  = 1000 - 1030 kg/m³). This configuration resulted in the generation of a vertical buoyant jet.  The flow rate was controlled and measured using a valve and ultrasonic flow meter. For the generation of unsteady discharges, a solenoid valve was employed, facilitating pulsed source conditions with discharge intervals ranging between ½ second to 2 seconds. Image analysis techniques, specifically light-induced fluorescence (LIF) and particle image velocimetry (PIV), were employed to measure buoyant jet characteristics, including concentration profiles, velocity fields, and jet geometry. These characteristics were measured under both steady and unsteady source conditions, facilitating a comparative analysis of the changes in behaviour arising from source condition variations.

The experimental results were compared with integral assumptions of one-dimensional models. These findings will be presented, and their significance will be explored within the context of vulcanian and strombolian style eruptions.

How to cite: Hetherington, M., Cuthbertson, A., Dawson, S., and Dioguardi, F.: Understanding the dynamics of unsteady buoyant Jets: an experimental analogue of Vulcanian and Strombolian style eruptions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15962, https://doi.org/10.5194/egusphere-egu24-15962, 2024.

EGU24-16350 | ECS | Posters on site | NH2.1

The role of hydrological circulation in the initiation process of debris flows in the Campanian volcanic terrain 

Letizia Pace, Capolongo Domenico, Capparelli Giovanna, Clausi Gabriele, Dioguardi Fabio, and Sulpizio Roberto

Volcaniclastic debris flows are highly concentrated flows of rock debris, mud and water in which the sediment is of volcanic origin. These phenomena can be syneruptive, posteruptive, or unrelated to an eruption. To be generated, the coexistence of steep slopes, unconsolidated sediments and an adequate amount of water is necessary.

The aim of this project is to investigate the role of water circulation in the initiation processes of debris flows to enhance our ability to anticipate potential new debris flows in the Campanian Volcanism area, focusing on the Sarno area. Sarno is a small municipality located in the Vesuvius Volcanism area (western side of the Campanian Apennines) that is sadly infamous for the major debris flow events that, on the 6th of May 1998, destroyed the town and killed around 150 people.

The study area exhibits a convergence of geomorphological and lithostratigraphic settings that contribute to enhancing its exposure to hazards: i) the presence of a calcareous bedrock with very steep slopes (30-45°) mantled by ii) an alternation of colluvium and pyroclastic deposits, and iii) natural scarps and man-made cuts that further worsen the stability conditions.

This research employs a multimethodological approach including i) geotechnical and rheological analyses of the sediments; ii) X-ray Diffraction for the mineralogical characterisation, particularly of the clay fraction; iii) large-scale experiments to investigate the role of water circulation in the sediments during simulated rainfall in the triggering of volcaniclastic debris flows; iv) in situ Time-Domain Reflectometry measurements at Pizzo D’Alvano for soil moisture vertical distribution and v) simultaneously acquisition-surveys by using a drone-mounted passive radiometer for spatial soil moisture distribution. Integrating these methods aims to achieve understanding of the water content distribution in the debris flow initiation process that could be potentially used in the rainfall-triggered landslide early-warning systems.

How to cite: Pace, L., Domenico, C., Giovanna, C., Gabriele, C., Fabio, D., and Roberto, S.: The role of hydrological circulation in the initiation process of debris flows in the Campanian volcanic terrain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16350, https://doi.org/10.5194/egusphere-egu24-16350, 2024.

Caldera-forming eruptions sequences produce a wide range of volcanogenic sedimentary deposits, from primary mesobreccia (blocks > 1m) that form from the collapse of caldera wall scarps during the eruption, to co-ignimbrite ash plumes (particles < 2mm) deposited during the waning of outflowing pyroclastic density currents, and even secondary aqueously reworked sediments deposited within caldera lakes. Understanding the temporal and special distribution of these deposits is vital to both locate and reconstruct the collapse sequence of these catastrophic events. However, research of caldera volcanoes is greatly hindered at modern examples due to subsequent burial of their own deposits.

Ordovician deposits (452 Ma) of the Borrowdale Volcanic Group (BVG) in the English Lake District are dominated by large-scale, caldera-forming deposits that have been tectonically uplifted and dissected by glacial erosion. Each of the BVG calderas have the potential to provide a wealth of knowledge regarding how calderas erupt, collapse, and continue to shape geological processes when their explosive activity ceases. However, due to intense faulting, alteration, and impersistent exposure across the Lake District, in-depth research of these calderas has been largely prevented using standard field-mapping techniques. This leaves most of the understanding for the overall nested caldera complex to be inferred.

This investigation utilizes whole-rock geochemistry as the primary method to establish correlations between potential large-scale, caldera-forming pyroclastic deposits across large distances. Once the extent of each deposit was determined, they were individually traced back to their source vents. Detailed fieldwork was then conducted to identify characteristic caldera-forming features, such as rapid thickness changes over volcanotectonic faults, and extensive intercalated mesobreccia deposits.

Geochemical analysis of immobile elements, including Nb, Th, Y, and Zr, of potential caldera-forming pyroclastic deposits has allowed for several notable correlations to be established, or disproven. Firstly, proximal outflow sheets from Langdale Caldera have been successfully correlated to pyroclastic sheets over 15 km from the caldera margin and suggest a multi-phase collapse sequence. Secondly, significant differences in the geochemistry of deposits associated with the Lincomb Tarns Formation (> 500 km2 ignimbrite) indicates the presence numerous pyroclastic sheets, originating from two separate caldera volcanoes within the Helvellyn and Ambleside areas. Finally, geochemical variations within the Haweswater ‘caldera’ infill deposit prove that sudden thickness changes, previously associated with syn-collapse volcanotectonic faulting, are the result of separate eruption events that have since between adjacently faulted.

How to cite: McGowan, E., Barry, T., and Branney, M.: A geochemical reevaluation of caldera-forming eruption deposits in the Upper Borrowdale Volcanic Group, English Lake District., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16506, https://doi.org/10.5194/egusphere-egu24-16506, 2024.

EGU24-17769 | Posters on site | NH2.1

A laboratory study of plumes associated with pyroclastic density currents 

Guillaume Carazzo and Geoffrey Robert

Volcanic plumes associated with propagating pyroclastic density currents can rise tens of kilometers into the atmosphere, dispersing fine ash particles over large areas with a potential hazard for aviation safety. Such plumes originate from the buoyancy reversal of the pyroclastic density currents caused by the entrainment and heating of ambient air combined with the sedimentation of coarse particles. Several experimental and numerical studies investigated the formation, dynamics and impacts of these plumes but the mechanisms controlling the mass partitioning between the buoyant rising plume and the dense propagating current have received less attention despite its crucial importance for hazard assessment. Here, we present a new laboratory study aimed at investigating the controls on the mass partitioning during the plume lift-off. The experimental set-up is designed to simulate a gravity current of ethanol and ethylene glycol (EEG) flowing under a sloping roof in a tank of fresh water. The EEG mixture is less dense than fresh water but may become denser when mixed with water allowing us to generate a plume associated with the gravity current. Depending on the source conditions, the turbulent gravity current may either fully lift-off to form a buoyant plume, separate in a dense propagating flow and a buoyant plume, or propagate along the slope with no plume formation. We show that the transition between the three regimes is strongly controlled by the Richardson number defined at the source and by the slope. The results are consistent with the theoretical predictions of a simple 1D model and provide constraints on the mass partitioning during the formation of the plume.

How to cite: Carazzo, G. and Robert, G.: A laboratory study of plumes associated with pyroclastic density currents, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17769, https://doi.org/10.5194/egusphere-egu24-17769, 2024.

EGU24-18995 | ECS | Posters on site | NH2.1

Evaluation of the wall friction angle of dry volcanic materials from laboratory experiments. 

Ilaria Rucco, Fabio Dioguardi, Mauro Antonio Di Vito, Nikhil Nedumpallile-Vasu, Damiano Sarocchi, and Raffaella Ocone

Granular materials are widely involved in several processes, from the food, cosmetic, and pharmaceutical industries to natural phenomena such as pyroclastic density currents and landslides. Therefore, the study and understanding of their behaviour and rheology are of paramount importance in terms of hazard assessment and for developing and implementing mathematical and numerical models. The simulations try to reproduce the complexity of the flows taking into account several parameters, but, despite the advances in the theoretical descriptions of granular flows, a gap still exists between the empirical models and the experimental observations.

In this work, we present the results of the characterization of volcanic samples carried out with the FT4 Powder Rheometer (Freeman Technology). Shear tests, compressibility tests, and wall friction tests were performed to characterize the flowability of the powders. We particularly focus on the wall (or basal) friction angle, which describes the interaction of the particles with a variable-roughness substrate. Some glass beads have also been investigated, as a reference value. The results show how the ratio between the roughness of the surface and the average particle size of the samples influences the wall friction angle. Moreover, the comparison with the glass beads also reveals the influence of the irregular shape of the particles.

How to cite: Rucco, I., Dioguardi, F., Di Vito, M. A., Nedumpallile-Vasu, N., Sarocchi, D., and Ocone, R.: Evaluation of the wall friction angle of dry volcanic materials from laboratory experiments., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18995, https://doi.org/10.5194/egusphere-egu24-18995, 2024.

EGU24-19093 | Posters on site | NH2.1 | Highlight

Lahars as repeated hazardous phenomenon around Vesuvius volcano (Italy) during and after impacting explosive eruptions 

Mauro Di Vito, Mattia de'Michieli Vitturi, Laura Sandri, Antonio Costa, Marina Bisson, Sandro de Vita, Domenico Doronzo, Roberto Gianardi, Mauro Rosi, Ilaria Rucco, Roberto Sulpizio, Giovanni Zanchetta, and Elena Zanella

Lahars represent some of the most dangerous phenomena in volcanic areas for their destructive power, causing dramatic changes in the landscape with no premonitory signs and impacting on population and infrastructures. In this regard, the Campanian Plain turns out to be very prone to the development of these phenomena, since the slopes of the Somma-Vesuvius and Campi Flegrei volcanoes, as well as the nearby Apennine reliefs, are mantled by pyroclastic deposits that can be easily remobilized, especially after intense and/or prolonged rainfall. Our recent studies focus on the analysis of the pyroclastic fall and flow deposits, and of the syn- and post-eruptive lahar deposits related to two sub-Plinian eruptions of Vesuvius, 472 CE (Pollena) and 1631. Historical and field data from the existing literature and from hundreds of outcrops were collected and organized into a database. Stratigraphic, sedimentological, and archaeological analyses were carried out, in addition to rock magnetic investigations and impact parameter estimations. The field data analyses show that in both eruptions the dispersal area of the primary pyroclastic deposits is wider than previously known. Such distribution of the deposits directly affects the one of the lahar deposits, even because a significant remobilization took place during and after the studied eruptions, involving the distal phreatomagmatic ash. From these analyses, it was possible to constrain the timing of the deposition, and to estimate the thicknesses, velocities and dynamic pressures (impact parameters) of the lahars. A new shallow layer model based on depth-averaged variables, named IMEX-SfloW2D, was developed for the simulation of lahar dynamics. A thorough sensitivity analysis was carried out to identify the critical processes (erosion and deposition) and parameters (numerical and physical) controlling lahar runout, using both synthetic and real cases topographies. Effects of erosion and deposition were investigated by comparing field data with the output of simulations including vs. excluding these processes. By comparing observed and simulated flow thickness and area covered by the flows, and their evolution over time, it can be shown that the inclusion of erosion and deposition is important to properly simulate the impact parameters of lahars, particularly on uneven terrain. Lastly, a novel workflow for Probabilistic Volcanic Hazard Assessment (PVHA) for lahars was developed and applied to the Vesuvius case study. Such a workflow explores the effect of uncertainty of the flow initial conditions on the impact parameters of lahars on the target area, by sampling coherent sets of values for the input model parameters and running thousand simulations. The simulation outputs were processed to produce hazard curves, hazard maps, and probability maps for the maximum flow thickness, and hazard surface and probability maps for joint thresholds in flow thickness and dynamic pressure. It is believed that the latter hazard products represent a novel product in PVHA for lahars around Vesuvius volcano and can be applied worldwide. The multidisciplinary approach adopted in this work shows how it is crucial to assess the impact of lahars in densely populated areas, even at distances of several to tens of km from active volcanoes like Vesuvius.

How to cite: Di Vito, M., de'Michieli Vitturi, M., Sandri, L., Costa, A., Bisson, M., de Vita, S., Doronzo, D., Gianardi, R., Rosi, M., Rucco, I., Sulpizio, R., Zanchetta, G., and Zanella, E.: Lahars as repeated hazardous phenomenon around Vesuvius volcano (Italy) during and after impacting explosive eruptions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19093, https://doi.org/10.5194/egusphere-egu24-19093, 2024.

EGU24-19194 | Orals | NH2.1

Thermal transient PDC behavior induced by topographic drops: A test case at Mt. St. Helens, USA 

Matteo Cerminara, Matteo Trolese, Guido Giordano, Brittany Brand, Nicholas Pollock, Francesca Cifelli, and Massimo Mattei

This study investigates the influence of topography on the internal structure and dynamics of pyroclastic density currents (PDCs), using the 1980 Mt. St. Helens eruption as a case study. By integrating paleomagnetic data and numerical models, we observe significant temperature differences (approximately 100°C) in PDC deposits on different flanks of the volcano. These variations are attributed to local topographic features affecting air entrainment in PDCs. We find that topographic drops induce a transient regime in PDCs, altering their internal temperature, velocity, and concentration. The duration of the transient phase is proportional to the ratio between the drop height and the square root of the current thickness. The influence of topography on PDC dynamics decreases with distance from these drops or when a stationary phase is reached. Taken together, our dataset allows us to estimate a local sedimentation rate of approximately 150 ± 100 mm/s for PDC deposits in a proximal reattachment region. This research emphasizes the importance of transient dynamics in understanding PDC behavior, introduces a new method for measuring sedimentation rates, and highlights the need to consider topographic effects in hazard assessments.

How to cite: Cerminara, M., Trolese, M., Giordano, G., Brand, B., Pollock, N., Cifelli, F., and Mattei, M.: Thermal transient PDC behavior induced by topographic drops: A test case at Mt. St. Helens, USA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19194, https://doi.org/10.5194/egusphere-egu24-19194, 2024.

EGU24-22220 | ECS | Posters on site | NH2.1

Shape evolution of pyroclasts in tumbling experiments 

Carolina Figueiredo, Halil Sarp Esenyel, Ulrich Kueppers, and Donald Bruce Dingwell

During explosive volcanic eruptions involving felsic magmas, angular porous pyroclasts are generated and ejected into the atmosphere. As these pyroclasts are mechanically weak, transport processes after fragmentation can alter their shape. Rotary tumbling experiments have been used to mimic particle-particle interaction during Pyroclastic Density Currents (PDC) or sedimentation and to understand the role of transport mechanisms on fine ash generation and changes in pyroclast morphology. We used clasts generated by Hornby et al. (2020) to statistically quantify the shape evolution of pre- and post-tumbling pyroclasts. Two types of Laacher See pumice were used as starting material. LSB (Laacher See Bims) was industrially processed by ROTEC® by wet sieving, while ULST (Upper Laacher See Tephra) represents pristine clasts from fall units of the Laacher See eruption. Four sets of tumbling experiments (T1, T2, T3A, T3B) were performed. All lasted in total 120 minutes and ash generation was quantified after 15, 30, 45, 60 and 120th minutes. In T1 experiments, ash generated was added back into the drum after each increment but left out and stored separately in T2 experiments. In T3 steel balls were added to the drum to simulate the impact of lithics on the mechanical response of pumice lapilli. All other boundary conditions of T3A experiments mimic those of T1 while T3B experiments mimic T2. We quantified three values for each set of clasts: 1) amount of ash generated (dry sieving), 2) clast volumes (following Pisello et al., 2023), and 3) clast morphology. For the latter, we used shadowgraphs of 100 clasts per sample set independently, processed the images on Photoshop (clast contours delimitation and binarization) and calculated shape parameters (Convexity, Solidity, Form factor and Axial ratio, see Liu et al., 2015) using ImageJ. As expected, a striking distinction between starting material and tumbled clasts was found. We present data for 1) ash generation efficiency (≤ 53%), 2) clast volume (reduction), and 3) shape parameters (≤ 0.15 increase) to evidence the importance of pyroclast overprinting during transport-related processes. As clasts collected from fall units (see ULST here or Pisello et al., 2023) are angular, particle-particle interaction during gas-pyroclast flow inside conduits is found to have been of minor importance.

How to cite: Figueiredo, C., Esenyel, H. S., Kueppers, U., and Dingwell, D. B.: Shape evolution of pyroclasts in tumbling experiments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22220, https://doi.org/10.5194/egusphere-egu24-22220, 2024.

For years now, proliferation of technological tools has been taking hold, albeit with some resistance, in the public sector since, as reflected in the agendas and public policies of EU member states, digitalization is a non-deferrable need, a prerequisite for the implementation of further reforms. This report’s purpose is to ascertain whether and how, data in AI can support administrations and stakeholders in coping with unforeseen events, such as earthquakes and volcanic eruptions. Among disaster protection risks, volcanic activity is often considered a foreseeable risk because it is thought that phenomena that presage rising magma to surface can be recognized and measured. These phenomena are called precursors although this is a simplification that does not take into account the complexity and extreme variability of volcanic phenomena and the difficulty in assessing and interpreting them. Precursor phenomena, as indicators of an ongoing process that if properly and adequately studied, analyzed and monitored, can give an idea of the state of volcano activity and its possible evolutions, allowing for the detection of possible anomalies. For this reason, data and processing by AIs can provide support and decrease errors in the calculation of phenomena even if only a quantitative reduction. Data and their processing can provide a reliable index to support prevention activities. Potential issues for the jurist involve ownership of database management, interoperability, errors in the management of the same knowledge. Assessment by AI and data has the advantage of being rapid and devoid of operator discretion. Machine learning, in fact, has a capacity of about 98 percent to correctly attribute a rock of unknown origin. Central to the discussion is to determine the ownership of data and the AI tools deputed to process them, whether to endow public facilities, or outsource this function to the private sector.

How to cite: Brigante, V.: Dialogue between technique and administration in volcanic risk management; Data issues, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22287, https://doi.org/10.5194/egusphere-egu24-22287, 2024.

EGU24-22289 | Posters on site | NH2.1

Trilemma, complexity, administration and exceptional events 

Loredana Nada Elvira Giani and Gianluca Casagrande

The aim of the paper is to identify a key to understanding that allows us to overcome the regulatory trilemma that has emerged, seeking to offer a perspective according to which the exceptional event, an expression of the (ineliminable) complexity of reality, is included (in the competent political and institutional fora) in a broader case, encompassing contingencies. And this is not to foresee them, often asking science to do the impossible, nor to block activities considered dangerous through an exaggeration of the principles of prevention and precaution, but simply to allow the legal system to assume a broader vision, inclusive of the unusual case in point, to provide a toolbox of possible reactions to be triggered in the event (even remote) of the occurrence of an exceptional event.

How to cite: Giani, L. N. E. and Casagrande, G.: Trilemma, complexity, administration and exceptional events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22289, https://doi.org/10.5194/egusphere-egu24-22289, 2024.

EGU24-22292 | Posters on site | NH2.1

Precaution and prevention in the jurisprudence of the administrative judge 

Annarita Iacopino

This paper aims to analyse the path of administrative jurisprudence on how the principles of prevention and precaution behave, the role they assume for the public decision-maker and the judge's review. In this perspective, priority is given to examining the nature and ratio of the two principles, as well as the relationship between them. It is then necessary to define their sphere of operation and the essentially “methodological and bidirectional” dimension in which they move. They, in fact, offer rules for proceeding and not for deciding, thus allowing the identification of the path of proceduralisation of public decisions in situations of danger (prevention) or in situations of risk (precaution), enabling the minimisation of risks, respectively, through intervention on the causes of the possible emergence of danger and through the identification of the solution that makes it possible to balance the minimisation of risks with the maximisation of benefits. In an emergency phase, as in the case of compulsory vaccination, this may require operating in a “counter-intuitive” manner with the imposition of instruments-therapies- that ensure more benefits than risks, since the potential risk of an adverse event for an individual is far less than the actual damage to society as a whole. In all these hypotheses, the scientific basis represents a guarantee of the reasonableness of the choices, since the public decision-maker's assessment must be based on acquisition of the best science of the moment and on the rigour of the relevant method; a “reserve of science” whose reasonableness and proportionality is subject to the administrative judge's review.

How to cite: Iacopino, A.: Precaution and prevention in the jurisprudence of the administrative judge, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22292, https://doi.org/10.5194/egusphere-egu24-22292, 2024.

EGU24-22294 | Posters virtual | NH2.1

Exceptions to the ordinary rules for awarding public contracts: the volcanic risk paradigm 

Marco Calabrò and Allessandro di Martino

The topic of exceptions to the ordinary rules of public contracts in the management of risks and emergencies resulting from volcanological phenomena allows for numerous considerations on the aspects of public contracts and administrative law. The topic must obviously be analysed through an interdisciplinary approach focusing on the relationship between technology and law. For example, to verify the legitimacy of the application of derogatory regulations, it is necessary to consider the three-phase structure of volcanic risk: risk assessment, hazard assessment and mitigation of the event. The centrality of the technical issues requires, first of all, an examination of the legal profiles: the first aspect concerns the delimitation of both the concept of "paramount urgency" - a prerequisite for derogating from the ordinary rules - and of which events (whether they have already occurred or have not yet occurred) are susceptible to fall within the scope of the provision. In this context, this research focuses on the practices of individual local authorities from which a significant interpretative and methodological distance emerges.

A further profile of interest concerns organisational issues: this work aims to examine the benefits of a centralisation of competences in the hands of the regions, from two points of view. The first concerns the attempt to reduce potential corruption phenomena that could occur in territories where unpredictable maintenance events frequently occur. The second is based on the consideration that leaving the choice to individual local administrations could lead to different assessments of 'extreme urgency' conditions between neighbouring authorities Centralisation would therefore go in the direction of uniformity of decisions.

There are, in conclusion, two other aspects that deserve further study. The first concerns the need for ex-post controls, linked to the centrality of the assessment of the conditions of extreme urgency, which risks being ineffective given the extremely tight timeframe. The second seeks to understand whether the derogation to the procurement regime also drags on the regime of landscape authorisations or environmental impact assessments: if this were not the case, and if therefore ex ante intervention were still necessary, the process of simplifying the activities of economic operators would inevitably be thwarted. In addition to the theoretical reflections carried out on the derogation to the ordinary regime of contracting in cases of volcanic risk, this work will also analyse the so-called Campi Flegrei Decree, which allows recourse to the derogatory techniques mainly for two reasons: to provide for the acquisition of instrumental resources necessary to ensure the effective management of civil protection activities; and to provide for the setting up of temporary areas and services for the reception of the population.

How to cite: Calabrò, M. and di Martino, A.: Exceptions to the ordinary rules for awarding public contracts: the volcanic risk paradigm, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22294, https://doi.org/10.5194/egusphere-egu24-22294, 2024.

EGU24-22298 | Posters on site | NH2.1

Costs of emergency and the role of Court of Auditors 

Vanessa Manzetti

The Court of Auditors is assigned the scrutiny of the economic-financial balance of the Public administrations in order to protect the economic unity of the Italian Republic.  Such prerogatives have a great importance in the framework outlined by art. 2 §1 of the Constitutional Law n.1/2012, which, in line with the European Union legal system, recalls the Public Administrations as a whole to ensure balanced budgets and the sustainability of the public debt. This means that the surveys of the Court of Auditors in the performance of its functions (judicial, control and advisory) should indirectly also reveal the emergency costs.

The paper will examine some fundamental documents such as the Report on the financial management of the local authorities 2019-2021, the deliberations of the Regional Audit sections of the Court on budgets of the local health authorities, as well as the Reports on the result of the controls on the financial management of the companies subject to the control of the Court of Auditors ex art. 12 of the Law n. 259 of 1958. The examination will also focus on the controls that the Regional Control Sections of the Court of Auditors carries out on the budgets and final accounts of Local Authorities to verify the compliance with the annual objectives set by the Internal Stability Pact and the compliance with the obligation provided by article 119 § 6 of the Italian Constitution. These controls aim also to verify the debt sustainability and the absence of irregularities that could jeopardize the balance economic-financial aspects of the Local Authorities.

An important perspective to better quantify the costs of the emergency is also identified by article 103 of the Italian Constitution which attributes to the Court of Auditors the jurisdiction on public accounting, civil, military and war pensions, as well as the jurisdiction on the liability of public accountants, public administrators and public officials in judgements concerning the management of the public money. This approach could also lead to reflect on the relationship between public debt and emergency, and on the possibility of judgments raised by a party before the Court of Auditors. Lastly, the examination of the Opinions drawn up by the Court of Auditors in the exercise of its advisory function could be also useful to trace the unclear perimeter of the costs of the emergency

How to cite: Manzetti, V.: Costs of emergency and the role of Court of Auditors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22298, https://doi.org/10.5194/egusphere-egu24-22298, 2024.

EGU24-22302 | Posters on site | NH2.1 | Highlight

Managing different eruptive scenarios at Phlegraean Fields and Vesuvius 

Claudia Principe

The two "hottest" areas of Italy from the point of view of forecasting and mitigating volcanic hazard at the moment are the Phlegraean Fields and Vesuvius. At the Phlegraean Fields the bradyseismic crisis continues with noticeable changes in the fumarole regime and bradyseismic movements in the Solfatara area. Depending on the various conceptual models created by the various groups of scientists working in this area, it is possible to foresee different possible future scenarios, also assuming the persistence of magmatic degassing and conductive heat transfer from the magma to the overlying rocks and the absence of external, such as the occurrence of one or more regional earthquakes and the release of fresh magma into the reservoir located 8 km deep.

At Vesuvius, different scenarios are possible for the reactivation of the most famous volcano in the world. The first scenario involves the emplacement, maturation and eruption of magma from a sub-surface magma chamber, following the pattern of the last large explosive eruption which occurred in 1631 with the occurrence of a small-scale Plinian eruption. A disastrous scenario but one that requires fairly long warning times. A further scenario, proposed more recently, involves the ascent of magma along fractures linked to regional tectonic trends and its emplacement through rapidly moving flows with probable opening at the base of the volcanic edifice and much shorter warning times.

How can we manage these different situations in terms of Civil Protection and resilience?

How to cite: Principe, C.: Managing different eruptive scenarios at Phlegraean Fields and Vesuvius, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22302, https://doi.org/10.5194/egusphere-egu24-22302, 2024.

The catastrophic events linked to natural phenomena that periodically strike Italy generate an increasingly irremediable rift between the State and the population, which is also tangible in the litigation that has become an increasingly frequent consequence of disasters in recent times. The media clamour that judicial events take on increasingly generates an image of a State that is impeccable in the solidarity phase but remains highly negligent in risk prevention policies. Compared to this vision, the recent commitment of the legislator to prevent the damaging effects of bradyseism in the Phlegraean Fields area goes against the trend.

However, many of the prevention activities identified, which can be implemented thanks to the appropriations provided, risk being compromised on a practical level due to the considerable rate of abuse in the area concerned, which makes the territory more fragile and the population less safe.     

It is strategically necessary to increase the level of public safety in an area that, on this point, presents undeniable criticalities: among the measures that can be implemented, it is desirable, for example, to perform an immediate analysis of the seismic vulnerability of the public and private building stock so as to allow preventive safety measures. In addition, an update of the General Evacuation Plan is needed, which currently, according to studies, would not allow the area, with its very high population density, to be cleared in a few hours.

How to cite: d'Orsogna, M. and Valentini, F.: Environmental surveillance and volcanic risk. Bradyseismic crisis and vulnerability of built-up areas: new intervention strategies on public and private heritage., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22379, https://doi.org/10.5194/egusphere-egu24-22379, 2024.

EGU24-22382 | Posters virtual | NH2.1 | Highlight

Data privacy in volcanic hazard scenarios 

Emanuele Fratto Rosi Grippaudo and Luigi Rufo

This paper aims to analyse the use of artificial intelligence tools to implement an active contact tracing system for individuals living in at-risk territories. Thus, not only a 'state of alert' communication system, but a 'contact tracing' system similar to that used in some States during the SARS pandemic COVID-19. From a legal point of view, it is necessary to balance the right to privacy with the right to health/right to life. In this perspective, the necessary prerequisites will be analysed: state regulation, rigorously proportionate and, furthermore, the security of the data. This must be placed on a server that is strictly publicly owned and managed, to prevent tracing being used as a bargaining chip, and ensure that the personal data collected by the platform or application are only those necessary to warn users of the danger and are not used for any other purpose, without prejudice to the possibility of using them in aggregate or in any case anonymous form, for statistical or scientific research purposes only.

How to cite: Fratto Rosi Grippaudo, E. and Rufo, L.: Data privacy in volcanic hazard scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22382, https://doi.org/10.5194/egusphere-egu24-22382, 2024.

NH3 – Landslide and Snow Avalanche Hazards

Lahars are a common and potentially long-lived hazard in river basins affected by explosive volcanic eruptions. They result from the hydrological disturbance of surrounding landscapes, driven by the destruction of vegetation and deposition of pyroclastic material. These modifications typically result in heightened rainfall runoff responses, via reduced interception and infiltration, leading to increased water and sediment flux, manifesting as lahars. With time, landscapes recover via removal of sediment, establishment and stabilisation of channels, and the redevelopment of vegetation. This recovery subsequently reduces the runoff response to rainfall and in turn limits the potential magnitude and frequency of lahars. Numerical modelling is an important approach for assessing the hazard posed by lahars. Most modelling approaches related to lahars consider the remobilisation susceptibility of pyroclastic deposits under particular conditions, or the runout/inundation potential of individual or probabilistic ensembles of flows. To date, very limited research has sought to address the longer-term (years to decade) evolution of lahar activity in affected catchments as they respond to and recover from disturbance. Here we present and discuss SedCas_Volcano, a simple model designed to simulate the longer-term evolution of lahar incidence in a catchment on the island of Montserrat that has been repeatedly disturbed by episodic volcanic activity since 1995. Using this simple and computationally inexpensive numerical framework, we account for variability in sediment supply, vegetation cover, and rainfall. Here we will discuss the merits of this model and identify possible next steps for continued model development.

How to cite: Christie, J. and Bennett, G.: SedCas_Volcano: a novel approach to modelling decadal evolution of lahar hazard in response to episodic volcanic eruptions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1051, https://doi.org/10.5194/egusphere-egu24-1051, 2024.

EGU24-3161 | ECS | Orals | NH3.1

Prediction of runoff-generated debris flows using hydrological modeling 

Martino Bernard, Matteo Barbini, Matteo Berti, Mauro Boreggio, Massimiliano Schiavo, Alessandro Simoni, Sandivel Vesco Lopez, and Carlo Gregoretti

In the Dolomites area, steep rocky cliffs are incised by several chutes that concentrate runoff and deliver it to the scree at their base. This interaction prompts erosive actions, creating channels for debris flows. After intense, short-lasting rainfall, the resulting runoff carries a significant amount of loose debris, forming a solid-liquid surge. This surging flow entrains boulders, gravel, and sand along its path, transforming into an increasingly substantial stony debris flow. To explore how headwater rocky catchments respond hydrologically and trigger stony debris flows, we utilize data gathered from three monitoring stations placed in distinct debris-flow catchments. These stations, located in the debris-flow initiation area of the basins, capture videos and flow-stage data, enabling us to observe the timing and type of the incoming flows. Over 15 years of monitoring, numerous instances of runoff and mass-transport phenomena have been documented. This comprehensive dataset is precious for analyzing the hydrological behavior of small, steep headwater basins and investigating stony debris flow initiation. An existing hydrological model has been partially reformulated, and its updated version was calibrated using the hydrographs measured via a sharp-crested weir. Testing this updated model against observations from two larger debris-flow catchments affirms its capability to replicate the initial phases of a debris flow, particularly when the sediment concentration is quickly increasing. Moreover, combining simulated runoff volume with the entrained sediment volume in the Rovina di Cancia catchment, estimated through DEM of Differences for the debris-flow events that occurred from 2009 to 2022, provides values for solid concentration suitable for predicting sediment volumes carried by debris flows.

How to cite: Bernard, M., Barbini, M., Berti, M., Boreggio, M., Schiavo, M., Simoni, A., Vesco Lopez, S., and Gregoretti, C.: Prediction of runoff-generated debris flows using hydrological modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3161, https://doi.org/10.5194/egusphere-egu24-3161, 2024.

EGU24-3898 | ECS | Orals | NH3.1

Probabilistic delineation of debris-flow routing pathways in cones and fans within a Monte Carlo framework 

Massimiliano Schiavo, Martino Bernard, Matteo Barbini, Mauro Boreggio, Sandy Lopez, and Carlo Gregoretti

Debris flow phenomena are difficult to predict because their occurrence depends on multiple factors (e.g. availability of sediment, volume, and rainfall intensity, as well as slope conditions before an intense rainfall event, etc.). When they occur, debris flows can significantly modify the topographic surface of conical-shaped fans and cones via erosion and deposition phenomena.
This contribution aims, for the first time, to use a Monte Carlo approach to simulate the most probable avulsion paths of debris flows and define those conveying a certain drainage area with a minimum occurrence probability. We rely upon various digital terrain models (DEM) available for the Fiames area (Cortina d'Ampezzo, BL), covering approximately 1.6 km2 , and the average local elevation and the standard deviation of each cell of the domain are evaluated. We then generate N=2000 Monte Carlo realizations of possible topographic (equiprobable) surfaces, according to the geostatistical procedure known as Sequential Gaussian Simulations (SGSIMs). On each topographic surface obtained, the optimal drainage network is extracted using algorithms that guide the flow, by gravity, along the directions of maximum slope, as commonly used in hydrology. It is therefore possible to obtain as many drainage networks as there are simulated topographies. The ensemble of drainage networks (networks) is used to obtain the most probable network, extracted from the average topographic surface among the simulated ones.
Furthermore, we set a threshold on the drainage area variable, thus it is possible to calculate the probability of having, in a domain's location, a flow conveyance (per unit of area) higher than the threshold one. Finally, it is possible to (at least preliminarily) evaluate the probability of existing infrastructure vulnerability by appraising the probability that they are located along possible drainage routes or not. The presented approach moves the analysis of avulsion paths within the probability space. It can be validated by verifying the correspondence between a part of the probable (synthetic) pathways with those that historically occurred. Furthermore, it allows us to define routes and (synthetic) triggering points different from the historical ones.

How to cite: Schiavo, M., Bernard, M., Barbini, M., Boreggio, M., Lopez, S., and Gregoretti, C.: Probabilistic delineation of debris-flow routing pathways in cones and fans within a Monte Carlo framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3898, https://doi.org/10.5194/egusphere-egu24-3898, 2024.

EGU24-4018 | ECS | Posters on site | NH3.1

Waveform behaviour in pressure varying debris flow models 

Daniel Mckinnell and Chris Johnson

Debris flows are composed primarily of densely packed
particles of rock, surrounded by water. Excess pressure (that is greater
than hydrostatic) in the water decreases the stress supported the
granular matrix, and correspondingly reduces the overall frictional
resistance of the debris flow, allowing for larger velocities. Waves in
these flows can increase their run-out by creating deeper fronts of high
fluid concentration and high fluid pressure. Continuum models of debris
flows have been refined with the inclusion of variation in excess fluid
pressure. In this talk we will aim to examine the mechanisms in this
model by studying the idealised case of flow on an inclined plane. We
will solve for periodic waveforms to show the impact of varying fluid
pressure throughout the wave, and examine unexpected behaviour within
the model.

How to cite: Mckinnell, D. and Johnson, C.: Waveform behaviour in pressure varying debris flow models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4018, https://doi.org/10.5194/egusphere-egu24-4018, 2024.

EGU24-4141 | ECS | Posters on site | NH3.1

DEBRA: A multi-rheological 2D steep shallow water finite volume scheme for debris flow propagation in mountain areas 

Riccardo Bonomelli, Marco Pilotti, and Payam Heidarian

In steep mountain areas, rapid mass movements such as avalanches and debris flows are surface processes which are characterized by large masses of granular material flowing at high speed. These processes may pose a serious threat whenever their path crosses populated areas, or damage key infrastructures. Numerical methods describing the motion of granular material coupled with remote sensing are the only option to assess run-off distance, velocity and depositional height, ultimately used to construct hazard maps. State of the art numerical modelling include three-dimensional and multiphase description of the phenomena. Despite the technical advancement provided by these implementations, which tend towards a complete model, in which both solid and liquid phases are considered, complexity, computational burdens and calibrating parameters scale accordingly. However, due to the intrinsic unknowns connected to debris flows (e.g. rheology, availability of sediments, liquid discharge), in the context of hazard mapping using a monophasic assumption regarding the physics of the flow is still a viable option because of the relatively low model complexity and computations times, allowing the user to perform multiple simulations to account for uncertainties. In the literature there are various numerical codes able to describe monophasic granular flow on complex topography both commercial (e.g. RAMMS, FLO-2D), and open source (e.g. HEC-RAS Mud and Debris flow), with different rheologic assumptions. Most models solve the classical Shallow Water Equations (SWE) which may not be valid in steep mountain bathymetry. Furthermore defining the flow depth orthogonally to the bottom may lead to practical difficulties in some situations, only solvable by introducing laborious pre- and/or post- processing calculations which may be complex on irregular topography. In this contribution we present some advances on a shock-capturing finite volume numerical scheme able to solve the recently introduced monophasic 2D Steep Slope Shallow Water Equations (SSSWE) on an unstructured grid using a set of different rheological laws (Manning, Voellmy and O’Brien). The use of an unstructured grid allows the user to capture in a simplified way the interaction between the flow and the buildings or channel beds naturally present in the computational domain regardless of the mesh size used. Furthermore, we present a novel analytical solution of a dam break test case on a sloping channel in presence of the O’Brien rheology, useful to benchmark existing numerical models. The numerical model implemented is called DEBRA (Debris-flow Evolution and Behaviour for Risk Assessment) and we assess its performance against other widely used commercial software for debris flow simulation.

How to cite: Bonomelli, R., Pilotti, M., and Heidarian, P.: DEBRA: A multi-rheological 2D steep shallow water finite volume scheme for debris flow propagation in mountain areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4141, https://doi.org/10.5194/egusphere-egu24-4141, 2024.

EGU24-6819 | ECS | Orals | NH3.1

Assessing Debris Flow Susceptibility in Deglaciated Alpine Catchments: A Novel Approach Integrating Flow-path Connectivity and Sediment Availability 

Tzu-Yin Kasha Chen, Leonard Sklar, Bryanna Pilkington, Emily Dickson, and Roland Kaitna

Debris flows pose significant natural hazards in mountainous regions globally, with the potential to cause substantial damage to villages and infrastructure in lowland areas. To effectively mitigate these hazards, it is essential to identify catchments prone to delivering debris flows to fan areas. Topographic metrics such as fan slope and catchment Melton number are useful at a regional scale but in recently deglaciated alpine landscapes do not explain high variability in debris flow frequency among neighboring catchments. Here we assess debris flow susceptibility by quantifying the spatial extent of sediment cover across upstream catchment areas and the connectivity of potential debris flow source areas to fans at catchment outlets.

The Pitztal Valley in the Austrian Alps serves as the study site, benefiting from elevation data (digital terrain model) and historical debris flow event data since the 1950s for 28 catchments, along with sediment cover maps for 18 catchments. To assess the likelihood that debris flows originating within sediment covered areas could reach the fan, we calculated the minimum mean slope angle along every flow path to the fan apex. Source areas with minimum angles lower than a dynamic friction angle are assumed to be disconnected from the fan apex because potential debris flows would come to rest and form coarse deposits upstream of the fan. This concept is utilized to calculate the fractional connectivity for sediment areas in each catchment as a function of dynamic friction angle.  Rather than assume a single friction angle, we compare catchments based on the angle corresponding to a connectivity rate of 50% for the sediment covered areas (referred to as the 50% connectivity angle).

We find a highly significant positive exponential correlation between the 50% connectivity angle and the historical debris flow frequency (in units of debris flow events per square kilometer of catchment area) using data from the 18 catchments with sediment cover maps. Validation is performed in 10 additional catchments where we identified sediment covered areas using a new algorithm that can distinguish bare bedrock from sediment deposits from the local topographic roughness. The observed debris flow event frequencies align closely with or fall within the confidence bounds predicted by the 50% connectivity angles, confirming that the combined evaluation of catchment connectivity and sediment availability successfully explains debris flow frequency in this landscape.

Lastly, the results are compared to models employing previously published metrics of connectivity and debris flow susceptibility, providing insights into the contribution and efficacy of this new approach.

How to cite: Chen, T.-Y. K., Sklar, L., Pilkington, B., Dickson, E., and Kaitna, R.: Assessing Debris Flow Susceptibility in Deglaciated Alpine Catchments: A Novel Approach Integrating Flow-path Connectivity and Sediment Availability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6819, https://doi.org/10.5194/egusphere-egu24-6819, 2024.

EGU24-7084 | Posters on site | NH3.1

Depth-resolved model for debris flows based on a two-phase fluid 

Jinbo Tang, Peng Cui, Hao Wang, Yu Lei, and Yu Wang

Debris flows are prevalent natural hazards in mountainous regions, posing threats to human safety and resulting in property damage. Recent research has focused increased attention on characterizing the dynamic properties of these flows, especially in the vertical direction. The present study puts forth a mathematical model to describe the physics of debris flows. Specifically, concentration-weighted averaging is employed to represent the mass and momentum balance equations of the bulk granular-fluid mixture. Furthermore, an evolution equation for the slip velocity between the granular solid and liquid phases is derived in order to capture the separation between these constituents. The model determines the particle pressure based on frictional-collisional relations and the fluid stress via a Herschel-Bulkley rheological formulation. The coupled differential equations are solved numerically using a two-step finite difference projection method. The free surface profile is tracked using a volume of fluid approach. Favorable comparisons with experimental measurements validate the numerical model. Finally, analyses provide insight into the influence of the slip velocity on the dynamics of granular-liquid flows.

How to cite: Tang, J., Cui, P., Wang, H., Lei, Y., and Wang, Y.: Depth-resolved model for debris flows based on a two-phase fluid, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7084, https://doi.org/10.5194/egusphere-egu24-7084, 2024.

EGU24-7378 | Orals | NH3.1

Critical channel runoff as direct trigger of debris flows in mountainous terrain. 

Markus Hrachowitz, Leonard Sklar, and Roland Kaitna

As a natural hazard in mountainous terrain, debris flows cause considerable disruptions, human casualties and economic damage in many regions world-wide. However, the spatially localized nature of debris flows together with the lack of data at sufficient temporal and spatial resolutions make the triggering processes difficult to describe. As a result, debris flows are problematic to predict. Effective regional and local early warning systems, built on both process-based or statistical models, have therefore so far remained elusive. Even more, common statistical models, such as  precipitation-intensity threshold models, rely on precipitation. As debris flows are essentially in-channel processes, precipitation is an indirect predictor and proxy for in-channel processes. As such it is not surprising that precipitation has limited predictive power. In spite of recent progress, general and detailed descriptions of in-channel processes that control debris flow triggering only start to emerge. Most generally, sediment supply and channel flow magnitudes can be considered major direct controls on debris flow occurence. As both are difficult to observe, they have so far not been systematically exploited and quantitatively described for their role as debris flow triggers.  


Based on 20-year records of hydro-climatic data, several dozens of well documented debris flow events in three contrasting head-water catchments in the Central Alps and a semi-distributed, process-based hydrological model, the objectives of our analysis are to (1) quantify the critical channel runoff magnitudes that have triggered past debris flows and to establish whether characteristic magnitudes can be found as a function of topography, soils, geology and other factors, (2) identify the relevance of snow melt vs. rainfall for the generation of debris flow triggering critical channel runoff, and (3) to test whether modelled critical channel runoff has higher power to predict debris flows than standard precipitation-intensity models.


Overall, we have found that indeed, relatively well-defined minimum critical channel flows as lower limits above which debris flows occur feature each of the three study catchments. It was also found that the general magnitudes are highly site specific. In spite of that, no obvious relation between the average critical flow magnitudes and landscape characteristics, such as local terrain or channel slopes, vegetation cover, soil type or geology at the three sites could be identified. In general, it was found that flow peaks, generated by short-duration, high-intensity rainfall events, mostly during summer, dominated the debris flow trigger dynamics at the study sites. In addition, several instances when debris flows were triggered by flow peaks of similar magnitudes but generated by high-intensity snow melt in combination with rain-on-snow were observed, highlighting the importance of quantifying liquid water input dynamics instead of bulk precipitation as system input that causally leads to the occurrence of debris flows. Intrinsically accounting not only for this distinction but also additional effects by evaporation, modelled channel flow magnitudes were found to be better predictors of debris flows, with respect to both, higher rates of true positives (correctly predicted debris flows) and lower rates of false positives (predicted but not occurred in reality), than traditional precipitation thresholds. 

How to cite: Hrachowitz, M., Sklar, L., and Kaitna, R.: Critical channel runoff as direct trigger of debris flows in mountainous terrain., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7378, https://doi.org/10.5194/egusphere-egu24-7378, 2024.

EGU24-7750 | ECS | Orals | NH3.1

Hitting rock bottom - Experimental study of bedrock erosion by debris flows 

Caroline Friedl, Lonneke Roelofs, Joëlle Hansen-Löve, Christian Scheidl, and Tjalling de Haas

While there are field observations and studies on erosion of debris flows over loose sediment, bedrock erosion by debris flows has not yet been studied comprehensively. Nevertheless, traces of erosion in the bedrock channel after debris-flow events, such as scars, ridges, grooves or individual impacts, indicate a non-negligible entrainment of material as a result of process-related impact and shear forces. In the Alps, such erosion phenomena are often found in the upper steep and inaccessible parts of the catchment areas and are thus difficult to analyse.

In this study we therefore investigate the potential erosion capacity of debris flows of different rheological characteristics on immobile channel beds with a small-scale physical model. We try to understand how bedrock strength influences erosion and if shear or impact forces dominate bedrock erosion by debris flows. To this end, erosion rates in terms of volume and the forces causing erosion are examined in over 100 laboratory experiments. We also compare and scale these rates to natural bedrock erosion caused by debris flows.

In our small-scale laboratory investigation, polyurethane foam boards act as bedrock surrogates. This material has already been used as a bedrock simulant in studies into fluvial bedrock erosion. The boards were installed in the lower 2.5 m of the flume channel, which has a total length of 5.6 m. Different board strengths ­­– indicating different erosion susceptibility – were tested with three different debris-flow mixtures. The slope of the channel was kept constant at 34°. After each debris flow, the change in bed elevation was measured with a laser scanner to determine erosion rates at submillimeter accuracy. Laser distance sensors, pore water pressure sensors, a load cell and a geophone were used to quantify debris-flow dynamics and different erosion forces, including shear and impact.

Our results show an exponential increase in erosion with a decreasing tensile strength of the bedrock simulant. While impact and shear forces both influence erosion rates, the decisive erosion force component appears to depend on the proportion of gravel and clay in the debris-flow mixture. The results of this study serve to deepen our understanding of the debris-flow process and expand our knowledge of erosion processes in the upper reaches of debris-flow catchments. In addition, our results can be used to tune existing models for longer-term landscape evolution.

How to cite: Friedl, C., Roelofs, L., Hansen-Löve, J., Scheidl, C., and de Haas, T.: Hitting rock bottom - Experimental study of bedrock erosion by debris flows, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7750, https://doi.org/10.5194/egusphere-egu24-7750, 2024.

EGU24-8554 | ECS | Posters on site | NH3.1

Regional scale debris flow susceptibility mapping in Barla Mountains (NW Taurus), Türkiye 

Furkan Karabacak and Tolga Görüm

As in many high mountainous regions of the world, Türkiye is also a country heavily affected by landslides. Considering that Turkey has the highest number of landslide-related deaths in Europe (14 per year), debris flows also have a devastating impact on the southern part of the country. On July 13, 1995, a debris flow killed 74 people and destroyed 180 houses in Senirkent District in Barla Mountain. Barla Mountain, where physical weathering is predominantly effective on widespread limestone, exhibits mainly arid/semi-arid climatic conditions. After the 1995 event, check dams were built within the scope of debris flow prevention. This study aims to perform susceptibility analyses of debris flow hazard using a spatially distributed empirical model (Flow-r) on the northern slopes of the Barla Mountain Belt.

All sub-catchments along the Barla Mountain Belt where the model was applied were afforested to mitigate debris flows. The Flow-r model consists of two stages: identifying potential source areas and calculating areas that could be affected by debris flows using flow direction algorithms. Potential debris flow source points and a digital elevation model with a spatial resolution of 5 m were used as model inputs. Model results were calibrated in each basin through reports of previous debris flow events (for Senirkent), aerial photographs, and field observations. Regarding the study's results, 7°-15 m/s model output was determined as the worst-case scenario, and 6°-17 m/s model output was determined as the extreme scenario. Through the field observations, physical weathering and debris production continued at elevations higher than the timberline depending on lithology and climate, and we observed that the check dams were filled with debris. According to the validation results of the Flow-R model we performed at this site, the accuracy, precision, and positive predictive power are 87.78%, 46.45%, and 23.03%, respectively. As a result of the study, considering the complex structure of debris flows, regional-scale debris flow susceptibility maps were produced with minimum data requirements and short computation times, and a primary source was provided in pre-disaster risk management studies. In the Barla Mountain, our findings identified differential weathering variations of limestone lithologies attributes and substantial debris generation as factors contributing to areas with a discriminating likelihood of debris flows under worst-case scenarios. Furthermore, the results of the model supported by the field observations revealed that the check dams in the region have lost their functionality. Moreover, on hillslopes subjected to afforestation, our findings indicated that the model's predicted spread areas did not align with historical debris flow occurrences.

How to cite: Karabacak, F. and Görüm, T.: Regional scale debris flow susceptibility mapping in Barla Mountains (NW Taurus), Türkiye, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8554, https://doi.org/10.5194/egusphere-egu24-8554, 2024.

EGU24-9068 | ECS | Orals | NH3.1 | Highlight

Grain size distributions, from a single grain size to well-graded distributions, on dry and immersed flows 

Oscar Polanía, Emilien Azéma, Mathieu Renouf, Nicolas Estrada, and Miguel Cabrera

Landslides and debris flows are massive geophysical processes that could occur in subaerial or submerged conditions. They involve granular materials in a wide range of Grain Size Distributions (GSD). In such processes, granular materials are subjected to large deformations, reaching a state where strains accumulate at constant shear stress. This state is known in the geotechnical community as the residual or critical state. The influence of the GSD on the residual state has been a matter of discussion between conflicting experimental and numerical observations. In this work, we confirm, at a grain scale and in dry conditions, that the residual shear strength is independent of the GSD. Moreover, we experimentally validate this result on dry granular flows, comparing the influence from monodisperse materials (materials with one grain size) to well-graded materials (materials with multiple grain sizes) on the mobility of a granular column. In this configuration, a granular column is let to collapse by self-weight and spread horizontally. The column mobility can be interpreted as a macro representation of the material's effective shear strength. Furthermore, we explore the effect of the GSD in immersed columns, finding a strong dependence of the GSD on the flow dynamics arising from the evolution of basal pore pressure P. At the flow initiation, negative P changes beneath the column produce a temporary increase in the column strength. This positive change lasts longer and with a larger amplitude in granular flows with well graded materials than in monodisperse ones. Then, during the column horizontal spreading, positive changes of P provoke a decrease in shear strength. For column collapses of graded materials, the excess of P lasts longer, allowing the collapses to reach farther distances compared with collapses of monodisperse materials. Finally, considering the relevance of mobility in granular flows, we propose a mobility model that scales the final runout with the collapse kinetic energy. This model works for both dry and immersed flows with different GSDs and has been validated for results from different authors, methodologies, and grain characteristics. Our results offer a novel perspective on the influence of GSD on the complex relationships between solid and fluid phases in granular flows, highlighting features that can be extended to massive natural processes.

How to cite: Polanía, O., Azéma, E., Renouf, M., Estrada, N., and Cabrera, M.: Grain size distributions, from a single grain size to well-graded distributions, on dry and immersed flows, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9068, https://doi.org/10.5194/egusphere-egu24-9068, 2024.

EGU24-9580 | Orals | NH3.1

Experimental study of viscoplastic surges down complex topographies and comparisons with numerical simulations. 

Colin Ginot, Guillaume Chambon, Maxime Wallon, Paul Vigneaux, and Pierre Philippe

In a context of climate change, sediment availability and occurrence of heavy rainfall episodes are tending to increase, resulting in a likely rise in frequency and magnitude of debris flows. For effective hazard management, predicting the velocity, depth, and run-out of these flows in realistic settings, while considering all relevant processes, is crucial. In particular, as debris flows may exhibit viscoplastic characteristics, a better understanding of the interplay between inertia, rheology and topographical features is necessary. We report on well-controlled laboratory experiments of viscoplastic surges flowing down a model topography. A volume of viscoplastic fluid (Carbopol) is released onto four 3D-printed topographies featuring different patterns of mounds and ridge. Using Moiré projection, we monitor flow depth with a temporal resolution of 250 Hz, exploring a wide range of configurations involving varying volumes and fluid rheological properties. This set-up enables us to investigate the front velocity, the deviation and accumulation of fluid induced by the obstacles and the shape of the deposit. Two distinct flow regimes are observed. Initially, a rapid regime develops with a high front velocity, and the fluid spreads in both transversal and longitudinal directions. This regime is driven mainly by inertial forces. Subsequently, the front velocity drops drastically and the fluid flows mainly along the slope. In this second regime, controlled by rheological effects, the flow is strongly influenced by the topography with various mechanisms depending on the case (deceleration, accumulation, channelization, etc.). These experimental results are then systematically compared with depth-averaged numerical simulations based on shallow-water hypothesis. We compare the outcomes of two models implementing different representations of the complex rheology. The experimental data serves as a benchmark to assess the predicting capabilities of the models and evaluate the resulting uncertainties. These findings offer new insights into the physical processes driving debris flows, and they will ultimately contribute to the enhancement of simulation tools used in hazard management.

How to cite: Ginot, C., Chambon, G., Wallon, M., Vigneaux, P., and Philippe, P.: Experimental study of viscoplastic surges down complex topographies and comparisons with numerical simulations., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9580, https://doi.org/10.5194/egusphere-egu24-9580, 2024.

On October 5, 2021, a landslide-debris flow disaster chain occurred suddenly in Hanping village, Shaanxi Province, China. This catastrophic disaster chain damaged 7 houses, 41.9 hectares of arable land and 3 roads and resulted in 1 death. Based on a detailed field investigation of the disaster site, we analyzed the dynamic evolution of the disaster chain by using experimental analysis, unmanned aerial vehicle (UAV) photogrammetry, satellite remote sensing interpretation and the SBAS-InSAR technique and then preliminarily revealed the movement process and causal mechanism of the disaster chain. The results suggested that the first landslide initiated in the upper part of Canger cliff, which is the result of the combined effects of slope structure, earthquake damage, engineering disturbance, and rainfall infiltration. Among them, extreme rainfall events are the primary factors that induce landslides. Before the landslide, InSAR results showed that deformations had already appeared in the source area, and the deformation rate had a strong correlation with precipitation. Then, the potential-to-kinetic transformation effect and air cushion effects generated by the landslide movement in the narrow and steep section of Canger cliff led to the disintegration of the sliding body. With replenished surface runoff, the clastic flow gradually transformed into debris flow. Moreover, due to the dam-breaching effects at bayonets and bends and the entrainment effect of the high-density debris flow along the gully, the scale of debris flow increases gradually, resulting in catastrophic damage during the movement. The findings of this study provide a significant reference and guidance for understanding the chain-generation mechanism of landslide-debris flow disaster chains, as well as informing disaster prevention and mitigation strategies.

How to cite: Zhan, J. and Yao, Z.: Characteristics and mechanism of a catastrophic landslide-debris flow disaster chain triggered by extreme rainfall in Shaanxi, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9638, https://doi.org/10.5194/egusphere-egu24-9638, 2024.

EGU24-9914 | ECS | Orals | NH3.1 | Highlight

High-fidelity modeling of landslide dam overtopping failure using SPH-DEM method  

Zhengyang Su, Shun Wang, and Dianqing Li

Corresponding author: Shun Wang       E-mail: shun.wang@whu.edu.cn

Abstract: Overtopping failure of landslide dams is a complex process that involves strong soil-water coupling and structural failure. Physically based numerical models are needed for breach mechanism as well as failure process and flood prediction. In this study, we establish an SPH-DEM dam-break model that considers the combined effect of seepage and overflow. The key feature of the proposed high-fidelity dam-break model is that both solid and fluid phases are solved simultaneously in two different sets of Lagrangian particles using their own governing equations. In the numerical framework, the water phase is modeled as weakly-compressible Newtonian fluid using the SPH method, and the soil phase is modeled using the DEM method. The interactions between these two phases including drag force, buoyancy and adhesion. The capillary force generated by the meniscus between two soil particles is solved to characterize the saturated and unsaturated processes of soil. The model is validated by three benchmarks including the simulations of seepage through an earth dam, a small-scale dam-break test and the whole progress of dam profile erosion. In a small-scale dam break test, the calculation error of overtopping peak flow is 3.5%. Simulation results predicted by the SPH-DEM dam-break model show good agreements with the finite element method and experimental results. Furthermore, the high-fidelity dam-break model is able to simulate many other soil-water coupling processes, such as reservoir water infiltration, dam slope erosion and collapse, breach development, and dam failure. In the future, the proposed SPH-DEM soil-water coupling framework could be applied to the modeling of geohazard chain triggered by rainfall-induced landslides, blocking river and dam outburst flood.

Keywords: landslide dam; overtopping modeling; SPH-DEM; soil-water coupling

How to cite: Su, Z., Wang, S., and Li, D.: High-fidelity modeling of landslide dam overtopping failure using SPH-DEM method , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9914, https://doi.org/10.5194/egusphere-egu24-9914, 2024.

EGU24-10028 | Posters on site | NH3.1

On the still unpredictable but recurrent lahars: the November 26, 2022 case study at Ischia island (Italy) 

Domenico Doronzo, Dario Delle Donne, Eliana Bellucci Sessa, Vincenzo Convertito, Mattia de'Michieli Vitturi, Sandro de Vita, Federico Di Traglia, Rosa Nappi, Lucia Nardone, Rosella Nave, Fabio Sansivero, and Mauro Di Vito

Lahars, landslides and debris flows are rapid natural phenomena that can heavily impact on and modify the environment, not only that from which they are triggered but also the one in which they propagate or leave deposits. In particular, lahars can reach significant runout distances from source areas (e.g., several km) and this can mainly depend, among other factors, on the morphology experienced by such propagation. There are cases in the recent history of natural occurrences in which lahars impacted catastrophically on rural and urban settings, such as for example at Nevado del Ruiz volcano (Colombia) in 1985 causing the death of thousands of people living around there. A more recent event occurred on November 26, 2022 at Ischia island (Italy), which is an active volcano particularly subjected to the recurrence of these phenomena. In this case, the emplacement of some lahars caused the death of a few tens of people and the damaging of tens of building, besides the direct impact on local agriculture and tourism. In the nearby Neapolitan volcanic area, several other lahar events occurred in the historical past, not only during but also after or well after explosive eruptions, as the evidence that these phenomena are still to be considered as complex and often unpredictable extreme natural events, also exacerbated by the climate changes, but also that they have some recurrence that cannot be neglected. Such kind of recurrence is mainly related to the local weather, which can even affect the intrinsic behavior of the flows that detach from the source areas and invade the territory. On the other hand, this is not a strictly statistical issue, as there are instrumental measurements that support the fact that heavy rains can exacerbate a landscape already prone to sliding, avalanching, and other catastrophic phenomena. For this, the November 26, 2022 Ischia case study was chosen with the goal of reconstructing the physical features that led to the lahar generation and invasion, which is something that might occur in the future but that should be experienced with a dedicated scientific and territorial consciousness. What was done is an integration of multidisciplinary approaches, corroborated by data from the INGV-OV monitoring network installed on the volcano, capable of detecting the otherwise lost flow timing and dynamical behavior. In particular, the seismic evidence that accompanied the Ischia lahar events, along with the consideration of some lithological features leading to an estimation of flow velocity and dynamic pressure, allow to discriminate multiple lahar pulses over the early morning of November 26, 2022. The main findings of this contribution are that the potential of the Ischia lahars had a sort of recharge timespan which depended on the local weather and lithological features, while the threshold of the lahar trigger depended on the hydrogeological conditions. The seismic reconstruction of the entire event allowed to quantify the first of these two critical issues at Ischia island.

How to cite: Doronzo, D., Delle Donne, D., Bellucci Sessa, E., Convertito, V., de'Michieli Vitturi, M., de Vita, S., Di Traglia, F., Nappi, R., Nardone, L., Nave, R., Sansivero, F., and Di Vito, M.: On the still unpredictable but recurrent lahars: the November 26, 2022 case study at Ischia island (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10028, https://doi.org/10.5194/egusphere-egu24-10028, 2024.

EGU24-10832 | ECS | Orals | NH3.1

Estimating the hydrograph of a debris flow event through low-cost field camera monitoring and Digital Particle Image Velocimetry 

Alessandro Zuccarini, Elena Ioriatti, Marco Redaelli, Luca Albertelli, Mauro Reguzzoni, Edoardo Reguzzoni, Nikhil Nedumpallile Vasu, Vanessa Banks, Elisabeth Bowman, Alessandro Leonardi, and Matteo Berti

Debris flows are extremely fast landslides whose complex dynamics are still not fully understood, primarily due to challenges in acquiring direct field measurements. In modern monitoring stations, cameras represent cost-effective data sources, providing essential information for characterising the documented events.

Digital Particle Image Velocimetry (DPIV) algorithms have been extensively employed in the literature to reconstruct velocity fields in laboratory physical models under controlled conditions. However, the resolution of field camera footage is typically suboptimal due to weather and lighting conditions, as well as non-zenithal recording geometry, hindering a straightforward application of DPIV. Landslide flume experiments, conducted in collaboration with the Civil and Structural Engineering Department of the University of Sheffield and the British Geological Survey office in Keyworth, revealed that also suboptimal quality footage can be effectively utilised provided appropriate orthorectification algorithms are applied to eliminate the original image distortions.

In this study, the methodology established through the laboratory flume experiments was applied to analyse a real debris flow event in an active catchment in the Camonica Valley (Lombardia, Italian Alps) between the municipalities of Ono San Pietro and Cerveno. The Blè Stream catchment, with a drainage area of approximately 3.5 km², a maximum elevation of 2,527 m a.s.l.,  and a main channel length of about 2.9 km, experienced a debris flow event on October 22, 2022. This was documented by several monitoring stations equipped with cameras and a flow-depth radar sensor along the main channel track.

The frame-by-frame orthorectified surface velocity field of the recorded debris flow was obtained through a DPIV analysis, employing two open-source tools in Matlab sequentially: PIVlab (Thielicke & Stamhuis 2014) and RIVeR (Patalano et al. 2017). The discharge at a specific instant along a reference section was computed as the product of the reconstructed flow velocity distribution and the area of the section defined by its topography, known from pre- and post-event LiDAR and drone surveys, and the measured flow level. Throughout this phase, careful consideration was given to assessing the primary sources of uncertainty arising from the continuously changing section geometry and the measured surface velocity, which typically overestimates the actual depth-averaged velocity, with a divergence depending on flow rheology. Calculating the discharge for each frame along the reference section ultimately yielded the hydrograph of the documented debris flow event, along with an estimate of the involved volume of material.

 

References:

Patalano A, García C, Rodriguez A, 2017. Rectification of Image Velocity Results (RIVeR): A simple and user-friendly toolbox for large scale water surface Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV). Computers and Geosciences. 109. 323-330. 10.1016/j.cageo.2017.07.009.

Thielicke W, Stamhuis EJ, 2014. PIVlab – towards user-friendly, affordable and accurate digital Particle Image Velocimetry in MATLAB. J. Open Res. Softw. 2 http://dx.doi.org/10.5334/jors.bl. 

How to cite: Zuccarini, A., Ioriatti, E., Redaelli, M., Albertelli, L., Reguzzoni, M., Reguzzoni, E., Nedumpallile Vasu, N., Banks, V., Bowman, E., Leonardi, A., and Berti, M.: Estimating the hydrograph of a debris flow event through low-cost field camera monitoring and Digital Particle Image Velocimetry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10832, https://doi.org/10.5194/egusphere-egu24-10832, 2024.

EGU24-11956 | Orals | NH3.1

A dynamic earthflow model 

Shiva P. Pudasaini and Martin Mergili

Earthflows are landslide processes characterized by the viscous movement of predominantly fine-grained and often water-saturated material down a slope or gully. They occur at a broad range of velocities, but generally do not display extremely rapid movement (such as debris flows, snow avalanches, or rock avalanches). Examples include the Gschliefgraben earthflow in the Austrian Alps and the Chirlești earthflow in the Romanian Carpathians. Although earthflows are common mass movement processes, they have not received the same attention as extremely rapid flows when it comes the development of dynamic simulation models. Here, we present a novel mechanical model and dynamical solution technique for earthflows. We develop a strategy of balancing the flux, viscous, and other forces. Our model essentially employs the flux-controller, viscosity-controller, and the deformation-controller. Within a single unified frame, we can now simulate a broad range of earthflows for different viscous, plastic, or visco-plastic behaviors and any degree of mechanically controlled deformation over a wide spectrum of time scales. We demonstrate the performance of the new earthflow model and its applicability with the advanced open-source computational mass flow simulation tool r.avaflow. Simulated earthflow deformation and motion are very smooth, typical of a hugely viscous material, as it is anticipated for earthflows as commonly observed for real-world events. As expected, the motion and deformation are exceptionally sensitive to the changes in the viscosity of the earthflow.

How to cite: Pudasaini, S. P. and Mergili, M.: A dynamic earthflow model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11956, https://doi.org/10.5194/egusphere-egu24-11956, 2024.

EGU24-12479 | Posters on site | NH3.1

Triggering rainfall for torrent floods and debris flows in Austria and assessment of climate change impact 

Roland Kaitna, Benedikt Becsi, Matthias Schlögl, Tobias Schöffl, Markus Hrachowitz, Harald Rieder, and Herbert Formayer

Debris flows represent a severe hazard in Alpine regions. The initiation of debris flows is connected to several hydro-meteorological and geomorphological factors. For operational early warning and assessment of climate change impact, knowledge about critical rainfall conditions is needed. For several regions of the European Alps intensity-duration (I-D) thresholds for debris flows have been derived in recent years. In this study we provide triggering rainfall conditions of high temporal and spatial resolution for > 3700 documented torrent processes including debris flows that occurred in Austria between 2003 and 2022. Additionally, we estimate the change in their probability of occurrence in a future climate, based on an ensemble of bias corrected and localized EURO-CORDEX simulations. We find slightly steeper I-D curves for debris flows than for torrent floods and no clear trend indicating substantial influence of antecedent rainfall on the triggering rainfall. For all process types, it is shown that both the probability of occurrence and the areas affected by triggering precipitation events increase substantially in the future, with clear dependences on the emission scenarios (RCPs). The results of this study provide a basis for improved event forecasting in a changing climate. 

How to cite: Kaitna, R., Becsi, B., Schlögl, M., Schöffl, T., Hrachowitz, M., Rieder, H., and Formayer, H.: Triggering rainfall for torrent floods and debris flows in Austria and assessment of climate change impact, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12479, https://doi.org/10.5194/egusphere-egu24-12479, 2024.

EGU24-13638 | ECS | Orals | NH3.1 | Highlight

Exploring the entrainment of liquefied bed material in landslides 

Alexandra Waring and Andy Take

Landslide runout analyses are conducted to predict the motion and distal reach of potential future landslides to inform landside hazard zonation, risk management, and the design of the optimal location and height of mitigation strategies such as barrier systems. A key uncertainty in these analyses relates to the erodibility and entrainment of sediment which may unexpectedly increase the volume of the landslide and affect travel distance. In this study we explore the case of a landslide overriding and entraining loose saturated valley floor sediments; in particular, whether such a scenario may cause the overridden sediments to liquefy, and if so, the extent to which that liquefaction affects the depth of erosion of the bed material and mobility of the slide.

The presence of a loose saturated layer of soil at the base of a slope inherently introduces a soil region potentially prone to static liquefaction. This scenario fulfills the criteria required for instability: a) loose contractive soil, which happens to be co-located in an area that is both b) fully saturated, and c) within reach of a shear trigger (i.e., being overridden by the landslide). This scenario was reproduced in the Queen’s landslide flume, using a horizontal liquefiable bed of saturated fine sand 2 m in width, 7 m in length, and 0.3 m in height located at the bottom of the inclined portion of the flume. Landslides of up to 1,200 kg of granular material were then released from the top of a 6.5 m long slope inclined at 30 degrees to impact the bed at speeds of up to 6 m/s. Behaviour of the sand bed upon impact was captured using ultrahigh speed imaging of the landslide and bed profiles, a Blickfeld LiDAR sensor positioned opposite to the landslide to capture point cloud scans of the slide, and a linear array of porewater pressure sensors within the sand bed. Preliminary results of experiments attempting to liquefy the valley floor sediments are presented as we explore the requisite conditions for different rates of entrainment, and in extreme cases, liquefaction, of the sand bed, as well as the effect of liquefaction and entrainment on the speed and volume of the slide.  

How to cite: Waring, A. and Take, A.: Exploring the entrainment of liquefied bed material in landslides, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13638, https://doi.org/10.5194/egusphere-egu24-13638, 2024.

EGU24-13686 | ECS | Orals | NH3.1

Integrated UAV and Field Data Analysis for High-Resolution DEM Enhancement, Rectification, and Debris Flow Modeling 

Krishna Priya Vk, Rajaneesh Ambujendran, Nikhil Nedumpallile-Vasu, Vanessa J Banks, Christian Arnhardt, and Sajinkumar Ks

To accurately assess landslide susceptibility and model debris flow paths, acquisition of high-resolution elevation data is essential. These data enable precise topographical analysis, considering factors like slope and curvature. But most of the time such high-resolution data will have inaccuracies due to vegetation, especially in tropical region. This study proposes a comprehensive approach that integrates field data and Structure from Motion (SfM) technology to rectify such DEM inaccuracies caused by dense vegetation. The goal is to enhance the accuracy of landslide simulations and volumetric analysis for effective post-disaster management. The Western Ghats, running parallel to India's western coast, has experienced a surge in rainfall-induced landslides, resulting in significant casualties in recent years. Notably, the Pettimudi village landslide in 2020 caused 70 deaths. The unique geomorphological features of the Western Ghats, such as concave curvature, colluvium deposits, and evidence of paleo landslides, contribute to the area's susceptibility. The study emphasizes the need for detailed assessment and mitigation strategies. The proposed method aims to improve the post-event high-resolution DEM accuracy by integrating field-collected elevation values and utilizing Agisoft Metashape software with the SfM algorithm. The rectification process involves combining elevation differences measured during a field study with photogrammetric elevation data. The field-collected elevation differences are crucial for rectifying these points, and enhancing the Digital Elevation Model (DEM) accuracy. The inaccessible source region is improved using a SfM-created DEM from drone footage, resulting in a more accurate post-event DEM. Correcting the 1 m DEM using an SfM-generated DEM proves challenging but significantly improves detail and accuracy, especially over the landslide source area. The impact of the rectification on accuracy is assessed by comparing volumes calculated from the initial DEM and the newly corrected DEM. The difference in volumes of debris depletion and accumulation, computed using initial and corrected DEMs, highlights variations, with depleted volumes being significantly larger due to the extensive depth increase over the landslide source region. These volumes are then utilized in Rapid Mass Movement Simulation (RAMMS) to validate the rectification process and enhance landslide impact predictions. Debris flow simulations in RAMMS, utilizing the rectified 1 m DEM, show specific outcomes at the landslide source region and toe of the landslide. The study emphasizes the importance of integrating SfM technology with field data to improve DEM accuracy, acknowledging the significance of additional field data for further refinement. The potential adoption of highly precise aerial imagery from Unmanned Aerial Vehicle (UAV) surveys is suggested to further enhance the SfM DEM. Debris flow modeling with RAMMS serves as a vital step in validating the accuracy and reliability of the rectified elevation model.

Keywords: Landslides, Western Ghats, Pettimudi, Digital elevation model (DEM), Structure-from-Motion (SfM) technology, Rapid Mass Movement Simulation (RAMMS)

How to cite: Vk, K. P., Ambujendran, R., Nedumpallile-Vasu, N., J Banks, V., Arnhardt, C., and Ks, S.: Integrated UAV and Field Data Analysis for High-Resolution DEM Enhancement, Rectification, and Debris Flow Modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13686, https://doi.org/10.5194/egusphere-egu24-13686, 2024.

EGU24-13891 | ECS | Orals | NH3.1

A SLAM-based high-resolution full-character debris-flow channel morphological mapping system 

Ping Shen, Tengfei Wang, Fucheng Lu, and Hui Kong

Enhancing the study of channelized debris flow necessitates precise and high-resolution mapping of channel topography and deposit conditions. Existing mapping technologies like satellite imaging and drone photogrammetry face challenges in accurately observing the interiors of extensive mountainous gullies, particularly in regions affected by events like the Wenchuan Earthquake. Despite the emergence of Simultaneous Localization and Mapping (SLAM) as a 3D mapping technology, its efficacy is hampered in rugged gullies due to two primary challenges: (1) Unusual terrain features and (2) Severe sensor swaying and oscillation, causing significant deviations and noise in SLAM-generated results. Addressing these challenges, we propose an innovative SLAM-based debris-flow channel detection and mapping system. It incorporates three key enhancements to refine SLAM outcomes: (1) A deviation correction algorithm assisted by digital orthophoto maps effectively mitigates systematic errors; (2) A point cloud smoothing algorithm significantly reduces noise levels; and (3) A cross-section extraction algorithm enables quantitative assessment of channel deposits and alterations. Conducting field experiments in Chutou Gully, Wenchuan County, China, in February and November 2023—representing pre and post-rainy season observations—validated the system's capabilities in markedly improving SLAM results. This advancement facilitates SLAM's efficacy in mapping challenging terrains, compensating for existing technology limitations in detecting debris flow channel interiors. The system aids in delineating detailed channel morphology, erosion patterns, deposit differentiation, volume estimation, and change detection. By rectifying the shortcomings of current methodologies, this methodological approach serves to augment the understanding of full-scale debris flow mechanisms, long-term post-seismic evolution, and hazard assessment in affected regions.

How to cite: Shen, P., Wang, T., Lu, F., and Kong, H.: A SLAM-based high-resolution full-character debris-flow channel morphological mapping system, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13891, https://doi.org/10.5194/egusphere-egu24-13891, 2024.

EGU24-14131 | Posters on site | NH3.1 | Highlight

Prediction of debris flow deposition based on particle segregation 

Shuai Li, Xiao-qing Chen, Xiao-jun Guo, Jian-gang Chen, Hua-yong Chen, and Xu-yan Wu

Predicting the deposition of debris flow is of great significance for hazard mapping, disaster reduction designing, construction of engineering, and settlements in vulnerable areas. There are many factors affecting debris flow deposition, such as landform, geological structure, debris flow characteristics, etc. However, these factors are finally realized by changing the migration and redistribution of particles in debris flow (particle sorting effect), and then through pore water pressure, shear force, friction resistance and momentum transfer. To this end, the laboratory flume experiments were conducted, focusing on the runout distance, deposit area, and maximum height, under different initial and boundary conditions such as water mass fraction and particle size. The experimental results reveal that the deposit morphology (e.g., runouts distance, deposit depth, and deposit width) of debris flow is closely related to the degree of particle size-segregation. Increasing water content first increase the degree of particle size-segregation which leads to longer longitudinal distance, however, too much water then reduced the degree of particle size-segregation, thus decreased the deposit distance. That is, the optimal water fraction corresponds to the well-distributed particle size-segregation, resulting in the longest deposit distance. In this condition, the friction among particles causes coarse particles to tend to move upward and forward, eventually accumulating at the front and surface, whereas fine particles tend to flow backward and downward, finally accumulating at the bottom and middle. Changing coarse particles size can only increases runout a little. However, well-distributed coarse particles can promote runout significant. The research can improve the understanding of debris flow accumulation and have important significance for quantitative risk assessment and risk zoning of debris flow.

How to cite: Li, S., Chen, X., Guo, X., Chen, J., Chen, H., and Wu, X.: Prediction of debris flow deposition based on particle segregation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14131, https://doi.org/10.5194/egusphere-egu24-14131, 2024.

EGU24-14834 | ECS | Posters on site | NH3.1

A finite volume code for simulating debris-flow routing: preliminary results 

Matteo Barbini, Martino Bernard, Stefano Lanzoni, and Carlo Gregoretti

The bi-phase governing flow equations of a solid-liquid mixture are numerically integrated within the shallow water approximation using the finite volume method. The one-dimensional FORCE scheme is extended to the two-dimensional case and reviewed for use with a structured computational grid comprising quadratic cells.  The intermediate points, at which the solution is computed at time , correspond to the corners of a cell, and this solution is derived from the values of the four surrounding cells adjacent to the corner. Consequently, the solution for a (i, j) cell within the domain depends on the four intermediate solutions computed at the corners: ,, ,. Subsequently, for a (i, j) cell, the t+1 solution is reliant on the value of the at that cell and the values of its eight neighbouring cells. The model is used for replicating the flow depth, velocity, and solid concentration values observed in a systematic series of flume experiments documented in the literature. The comparison shows good agreement for solid concentration and satisfactory alignment for flow depth and velocity values. Finally, the model is used for reproducing the flow pattern of the debris flow that occurred on Rio Lazer on November 4th, 1966. The comparison results are satisfactory.

How to cite: Barbini, M., Bernard, M., Lanzoni, S., and Gregoretti, C.: A finite volume code for simulating debris-flow routing: preliminary results, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14834, https://doi.org/10.5194/egusphere-egu24-14834, 2024.

EGU24-14924 | ECS | Orals | NH3.1

Comparative Analysis of Geophysical Flow Models: Voellmy, μ(I), and μ(R) Rheologies  

Yu Zhuang, Brian McArdell, and Perry Bartelt

The experimental-based μ(I) rheology is now prevalent to describe the movement of gravitational mass flows. Though the μ(I) rheology has been successfully applied to the modelling of historical debris flows and rock avalanches, its physical implication is not fully understood. In this study, we re-formulate the μ(I) rheology as a Voellmy-type relationship, which is composed of a Coulomb friction term and a turbulent term. We find that different from the classic Voellmy rheology (ξ is a constant), the turbulent coefficient ξ in the μ(I) rheology is heavily dependent on the avalanche height and velocity, indicating the shear-thinning features. However, as μ(I) rheology is a pure function of velocity (for a constant height), the friction exhibits no change during the acceleration and deceleration stage. With this purpose, we introduce a newly proposed μ(R) rheology that relates the friction to the production and decay of fluctuation energy (granular temperature) R. Using one-dimensional block models, we show the equivalence of I and R, and elucidate why similar results of μ(I) and μ(R) rheologies are easily obtained. Ultimately, this comparative analysis offers valuable insights into improving geophysical flow models, enhancing our understanding of flow behavior's dependence on various factors and leading to more accurate assessments and mitigation of geophysical hazards.

How to cite: Zhuang, Y., McArdell, B., and Bartelt, P.: Comparative Analysis of Geophysical Flow Models: Voellmy, μ(I), and μ(R) Rheologies , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14924, https://doi.org/10.5194/egusphere-egu24-14924, 2024.

Debris flow, a prevalent natural hazard in mountainous terrains, exhibits distinct flow dynamics depending on its occurrence over a bedrock (rigid bed) or atop a substantial deposition (erodible bed). The investigation of this flow transition is imperative for the comprehension and mitigation of debris flow dangers. This study introduces a unsteady, and non-uniform model, conceptualized to simulate the transition between rigid and erodible beds in debris flows. The model's foundation lies in the principles of mass, momentum, and kinetic energy conservation. It integrates a linearized mu(I) rheology to articulate granular flow deformation, thereby capturing the intricate interplay among particles during flow. Additionally, the model considers the impact of Coulomb friction along the sidewalls. To derive numerical solutions, the governing equations undergo depth integration, employing the HLL scheme (Harten, Lax, and Van Leer) in synergy with a finite volume numerical method. Furthermore, to corroborate the model's predictions, a novel granular dam break experiment was conducted. These experiments utilized a narrow glass channel (3.5 meters in length and 0.04 meters in width), with variations in the initial deposit depth downstream to establish diverse basal boundary conditions. High-speed camera footage facilitated the application of the Particle Tracking Velocimetry (PTV) method for capturing granular motion and generating a velocity field. A thorough analysis of the measured velocity field enabled the validation of the model's predictions, affirming its efficacy in accurately simulating the flow transition between rigid and erodible beds in debris flows.

How to cite: Hung, C.-Y. and Tsai, I.-L.: Simulating Flow Dynamics in Debris Flows: Transition from Rigid to Erodible Beds in Granular Dam Break Experiments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15247, https://doi.org/10.5194/egusphere-egu24-15247, 2024.

EGU24-17437 | ECS | Posters on site | NH3.1

Constraining erosion in debris flow models: A correlation analysis in contrasting erosional settings 

Katharina Boie, Verena Stammberger, and Michael Krautblatter

Erosion and entrainment can significantly increase the volume and hazard potential of a debris flow. Therefore, understanding those processes is crucial for creating numerical models that can accurately predict the extend of depositions and impact forces. The quantitative controls of erosion and entrainment are however still not fully understood nor implemented in predictive models. In this work, the erosivity along eight different debris flows is analysed. Data on the eroded volumes was acquired using geomorphic change detection on aerial and terrestrial laser scans from before and after the debris flow events. Flow width, flow velocity, momentum, basal shear stress, flow pressure and flow height were determined using back-calculated RAMMS Debris Flow models. Erosion was implemented in those models by successively increasing the flow volume in 20 m intervals along the debris flow channel based on the geomorphic change detection results. Additionally, channel characteristics like the average slope for each interval as well as the geologic conditions were considered. For all analysed parameters correlations with erosivity were found. However, among the observed debris flows, the parameters that correlate best differ and they have varying degrees of significance. The geological setting has a notable effect on erosivity as well as the correlations. Peaks in erosivity can be observed at transitions from a bed with lower erodibility, like bedrock, to a more easily erodible bed. Using the parameters that correlate best with erosivity for each individual debris flow, linear and multiple regression models were created, that relate erosivity to the respective parameters for each site.

How to cite: Boie, K., Stammberger, V., and Krautblatter, M.: Constraining erosion in debris flow models: A correlation analysis in contrasting erosional settings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17437, https://doi.org/10.5194/egusphere-egu24-17437, 2024.

EGU24-17806 | ECS | Orals | NH3.1

Budgeting sediment volumes mobilised during Storm Alex in the upper part of the Roya valley 

Raphaël Kerverdo, Sara Lafuerza, Christian Gorini, Alain Rabaute, Didier Granjeon, and Eric Fouache

2nd October 2020, the Atlantic storm « Alex » triggered an exceptional Mediterranean flood event in the south-eastern region of France, affecting the coastal Alpine valleys of the Tinée, Vésubie and Roya rivers. The event is considered exceptional due to the unprecedented rainfall recorded within a 24-hour period, surpassing 650 mm at Mesche dam and the elevated liquid peak flows around 1 350 m3/s at Breil-sur-Roya. Geomorphological changes consequence of the flood event includes river-related effects such as debris flows, landslides and partial destruction of the forest cover on the slopes, together with the destruction of bridges, roads, and houses.

Our study focuses on the Viévola sub-watershed upstream of the Roya river, made up of 4 confined torrential sub-valleys: Dente, Morte, Para, Scabrie and Rabay valleys. Theses generated numerous of debris flows feeding the Viévola alluvial fan. Our observations show that these valleys were responsible for massive input of sediment which led to widening of the active channel of Roya river,bank erosion and embankments during the Alex flood event.

The major areas of sediment accumulation were quantified in order to determine the balance between the 'initial' volumes eroded such as upstream gullies sediments and landslide deposits and the 'deposited' volumes (Viévola alluvial fan). The sediment volumes were quantified by Digital Elevation Model of Differences (DoD) from aerial imagery available before and after the flood.

Pre-flood topographical data is of low quality while post-flood topography are better thanks to LiDAR datasets acquired in october 2020 and june 2021. A statistical study of tree heights on tributary slopes, using aerial and infrared images, allowed us to subtract them from the pre-flood digital surface model, creating a tree-free pseudo topographic surface.

Our results show that the Viévola sub-watershed produced approximately 304,000 m3 of sediment within a 24-hour period, with a margin of error of +/- 40,000m3 (an average error of 13%). The gullies at the head of the Dente and Rabay valleys produced 125,000 m3 of sediment, with an error margin of +/- 21,000 m3. These initial inputs from these gullies caused significant bank erosion in the Dente valley, resulting in the release of over 140,000 m3 of sediments, with an error margin of +/- 5,000 m3. This erosion led to a considerable widening of the Dente torrent channel, which expanded from an average width of 6.1m before the flood to 18.6m after the event. Based on field studies, we found that the cause of the bank erosion is linked to the debris flows that occurred in the Dente valley.

Comparatively, the Morte, Para and Scabrie valleys primarily contributed sediment from landslides, totalling around 21,000 m3, with an error margin of +/- 6.300m3. On average, the width of the torrents in these valleys doubled, with a factor of 2.1. Moreover, an alluvial cone formed at the Vievola holiday resort, resulting in a deposited volume of approximately 90,000 m3, with an error margin of +/- 20,000 m3. Consequently, an estimated 214,000m3 of sediment was exported to the Roya River.

How to cite: Kerverdo, R., Lafuerza, S., Gorini, C., Rabaute, A., Granjeon, D., and Fouache, E.: Budgeting sediment volumes mobilised during Storm Alex in the upper part of the Roya valley, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17806, https://doi.org/10.5194/egusphere-egu24-17806, 2024.

Debris flows represent a typical hazard of Alpine mountainous areas, which can generate serious impacts on natural and socio-economic systems of affected territories. In the recent years, intense precipitation events caused numerous damage-causing erosional processes and mass movements, including debris flows, within Alpine torrential channels. Changes in the intensity or frequency of heavy precipitation events under climate change are likely to influence debris-flows occurrence. Understanding ongoing and future changes in debris flow hazard is essential for risk management procedures in Alpine territories, in particular for delineating current and future hazard zones. Since the underlying debris-flow simulations frequently build upon historical statistics of triggering rainfall intensities, accounting for non-stationary precipitation conditions may be relevant for further improving the management of debris-flow risk in the context of climate change.

This work tests a modelling workflow to explore how changes in the intensity and frequency of heavy rainfall, can be incorporated into official hazard assessment procedures and if such changes lead to relevant alterations in the current zonation patterns. Possible changes in the Intensity-Duration-Frequency (IDF) curves are derived from observations and climate model projections and corresponding hydrological responses are simulated through the Peakflow model. Hydraulic processes are then modelled by entering resulting hydrographs as input of the WEEZARD software and outcomes for the current and future climate conditions are compared. The contribution presents the first results obtained for the Toverino river test basin in the Province of South Tyrol (Eastern Italian Alps), and it discusses the strengths and limitations of integrating a climate-change perspective into standardized debris-flow hazard zonation procedures.

The research leading to these results has received funding from Interreg Alpine Space Program 2021-27 under the project number ASP0100101, “How to adapt to changing weather eXtremes and associated compound and cascading RISKs in the context of Climate Change” (X-RISK-CC).

How to cite: Bozzoli, L., Crespi, A., Steger, S., and Moreno, M.: Incorporating climate change projections into operational debris flow hazard mapping: Initial insights from the Toverino River Basin in South Tyrol (Eastern Italian Alps)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19520, https://doi.org/10.5194/egusphere-egu24-19520, 2024.

EGU24-19786 | Posters on site | NH3.1

Measurement of friction in debris flows, floods, and intermediate flows 

Brian McArdell, Jacob Hirschberg, and Perry Bartelt

Many different rheological models describing the behavior of debris flows are available, yet there is no general agreement on the appropriate rheology for a given problem. Here we report on full-scale observations of friction in debris flows, which can be used to help constrain the selection of flow rheology. Using measurements from a large force plate (area = 8m2), we investigate the frictional behavior using the ratio of shear (s) to normal force (n) of debris flows recorded at the Illgraben debris flow observation station, in southwest Switzerland. Due to practical constraints the force plate is installed in a horizontal concrete structure in the channel bed, and not tilted to match the slope of the natural channel bed upstream of the force plate (slope S=0.08), which may induce a small deceleration of the flow, which we assume is negligible, especially for flows with large depths. Flow depth is recorded at the center of the force plate using either a laser sensor (point measurement) or radar sensor (average value). Debris flows are characterized with relatively large friction values (s/n ~0.15) at the front of the flows which are about twice as large as the slope of the channel bed. This result is consistent with ideas from the literature describing large friction at the flow front. Flood flows, in contrast, have frontal friction values (s/n ~0.1) approximately equal to the slope of the channel, indicating approximately steady and uniform flow over periods of 10’s of seconds.  Several transitional events have been recorded with properties intermediate between debris flows and flood flows, with corresponding s/n values also intermediate between debris flows and floods. These friction observations were recently incorporated into a debris flow model (Meyrat et al., 2023) which is capable of predicting the transition between debris-flows and glacial-lake outburst floods. While these results are promising, more research is necessary to further explore the controls on debris-flow friction, also for events characterized by multiple roll waves or erosion-depostion waves.

 

Citation:

Meyrat, G., Munch, J., Cicoira, A., McArdell, B., Müller, C. R., Frey, H., & Bartelt, P. (2023). Simulating glacier lake outburst floods (GLOFs) with a two-phase/layer debris flow model considering fluid-solid flow transitions. Landslides. https://doi.org/10.1007/s10346-023-02157-w.

How to cite: McArdell, B., Hirschberg, J., and Bartelt, P.: Measurement of friction in debris flows, floods, and intermediate flows, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19786, https://doi.org/10.5194/egusphere-egu24-19786, 2024.

EGU24-20566 | Posters on site | NH3.1

Susceptibility Based on System Failure: A Case Study of the Congduipu River Basin in Nyalam , Tibet 

Wei Qian, Juan Du, Bo Chai, Hong yuan Kang, and Yu Wang

Global warming induces the number of glacial lakes and the risk of glacier lake outburst of debris flow (GLODF) increasing in the high-mountain region, especially in Peru and the Himalayan region. GLODF Susceptibility assessment is a critical work that uses the spatial occurrence probability of debris flow to guide risk management and mitigation. Multiple glacial lakes in the basin could trigger GLODFs. The possibilities of multiple glacial lake outburst floods, flood flow paths, the likelihood of transformation into debris flows, and the overlapping relationships of flow paths within the river basin need to be considered in susceptibility assessment, which is a system instability problem characterized by multiple triggering factors and pathways. This paper considered the system failure of GLODF and proposed a new method to analyze it. The method includes seven steps, i.e. setp1-Determine the range of the assessment area or watershed, step2-Screen and classify glacial lakes and gullies, step3- Draw flow path and key node diagram, step4-Label the switches and conductance parameters, step5- Construct the series relationships of flow paths, step6- Evaluate the susceptibility of GLODF and step7- Zone the susceptibility grade. Moreover, the susceptibility indexes of GLODF were proposed in this paper, which considered the main factor affecting glacial lake outbursts and debris flow along the gully. This method was applied to a case that is in the Congduipu River basin in Tibet, China. The river basin is approximately 366 km2 and has 6 glacial lakes (>0.1 km2), 11 gullies, and more than 4 GLODF events. The results indicate that among the evaluated glacial lakes, one has a very high probability of outbursts, two have a high probability, and there are three instances each of debris flow disasters with very high and high susceptibility, respectively. The historical disaster records and field investigation results in the Congduipu River basin have verified the evaluation method. This method is applicable to quickly evaluate the susceptibility of GLODF in the river basin with multiple glacial lakes and gullies. 

How to cite: Qian, W., Du, J., Chai, B., Kang, H. Y., and Wang, Y.: Susceptibility Based on System Failure: A Case Study of the Congduipu River Basin in Nyalam , Tibet, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20566, https://doi.org/10.5194/egusphere-egu24-20566, 2024.

Debris flows are characterized by rapid movement of a mixture of water, mud, and unsorted debris along natural channels due to gravity. With propagation speeds exceeding 5 m/s and lack of premonitory signals, evacuating local populations is challenging, mitigation measures like barriers become necessary . The current difficulties in designing barriers regard the simplified methods employed that overlook event variability, hindering optimal structural design.

In this study, continuum numerical models, specifically depth-averaged (DA) and three-dimensional (3D) models, are employed to investigate debris flows. DA models depth-average Navier-Stokes equations, reducing the number of variables, allowing for efficient analyses of entire mountain valleys in a short timeframe. However, due to depth-averaging, essential details of vertical momentum transfer are missing, crucial for studying flow-structure interaction (FSI). By contrast, 3D models faithfully replicate FSI but are computationally demanding, making their application challenging for valley-scale flow propagation studies.

The study proposes a novel approach by coupling DA and 3D models to comprehensively investigate a flow propagating in a mountain valley and impinging against barriers. This approach combines the efficiency of DA models with the precision of 3D models, without neglecting upstream flow evolution. The DA model is employed when the flow is far from barriers, and a coupling section is placed upstream of a barrier, with the DA results as input for the 3D model to study the FSI.

The DA-3D coupled model is validated through replicating a laboratory experiment and a real-world event, with the same rheological law in DA and 3D frameworks for consistency.

A laboratory experiment with glass beads in a flume was replicated. Using µ(I) rheology, the study initially compared 3D results with the original experiment. Subsequently, the DA-3D model, employing µ(I) rheology, replicated the experiment. Striking similarity were found in DA-3D results when compared with 3D and experimental results. Additionally, forces on the barrier were compared between the 3D and DA-3D models, affirming results consistency and effectiveness of the DA-3D model.

In the site-scale investigation of an event occurred in St. Vincent (Aosta Valley, Italy), the study focused on a filter barrier installed to mitigate the risk associate to debris flows in the area. Field data are available because  the barrier was monitored to evaluate forces.  In this scenario, the DA-3D model was utilised, avoiding the the µ(I) rheology due to calibration challenges and because it was formulated for dry flows. Instead, the study opted for Voellmy rheology, extensively used in DA frameworks and specifically adapted for the 3D framework. The examination of debris flow impact on the barrier involved a comparison of field data with numerical values. The findings highlighted the realistic representation of FSI and forces by the DA-3D model at the site scale, emphasizing its potential for the comprehensive study of debris flows.

Acknowledgments

This study was carried out within the RETURN Extended Partnership and received funding from the

142 European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4,

143 Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005) – SPOKE VS 2.

How to cite: Pasqua, A., Leonardi, A., and Pirulli, M.: The impact of debris flow on mitigation structures: a novel depth-averaged and three-dimensional coupled model for the flow dynamic simulation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20635, https://doi.org/10.5194/egusphere-egu24-20635, 2024.

EGU24-20781 | ECS | Orals | NH3.1

Evaluating uncertainty in debris flood modelling for the design of a steep built channel 

Isabelle Cheff, Julie Taylor, Andrew Mitchell, Kathleen Horita, Darren Shepherd, Steven Rintoul, and Rob Millar

Hydrogeomorphic hazards are natural hazards that involve the mobilization, transport, and deposition of mixtures of water and debris or sediment and can take the form of floods, debris floods and debris flows. Such hazards occur in a continuum with varying size and concentration of entrained sediment and debris. Within this continuum, debris floods occur when large volumes of water in a creek or river entrain the gravel, cobbles, and boulders on the channel bed; also known as “full bed mobilization”. Debris floods have transient behaviour over the duration of the event with pulses of sediment laden (i.e., boulders and woody debris) flow and more diluted (i.e., water-like) flows. There is limited guidance in available literature on the hydraulic modelling of debris floods, in particular, Type 2 debris floods (i.e., diluted debris flows). There are several fluid dynamics models that could be used, and several rheologies that can be used to parametrize the flows, however, the complexity of real debris flood behaviour generally needs to be simplified to an equivalent fluid rheology in practice.

Following heavy, prolonged rainfall in southwestern British Columbia, Canada, in mid-November 2021, several road and railway crossings were damaged by hydrogeomorphic hazards and erosion. These events highlight the need for the design and construction of bridge crossings able to withstand hydrogeomorphic hazards for transportation network resiliency. The modelling work described in this study was in support of the design of an armoured channel for a site that was impacted by a debris flood in November 2021.

The proposed crossing is a steep and complex channel geometry, with channel slopes between 8 and 35%. Estimates of, flow depths, velocities, and shear stresses, were required for design. To capture the full effects of the steep and complex geometry of the proposed channel, debris floods were modelled in both two-and three-dimension using HEC-RAS and FLOW-3D, respectively. To provide conservative but realistic design values, multiple debris flood scenarios were modelled with the intention of capturing the range of transient behaviour expected over the duration of a debris flood and evaluate the uncertainties in the model parameterization. The debris flood model parameterization included a high and low mobility Bingham rheological parameters set (e.g. viscosity and yield stress) and modelling the flood as laminar or turbulent flow. The higher mobility turbulent flows are more representative of a flood condition that has a lower sediment concentration during the later stages of a debris flood event, while the lower mobility laminar cases are expected to be more representative of surge fronts with a higher sediment concentration.

Different debris flood cases provided critical design values for different parameters. Generally, the low mobility laminar flow was the most conservative for flow depth. Modelled velocity and shear stress were not only dependent on the debris flood case, but varied within the channel sections between the two and three-dimensional results. Design values were proposed using a percentile of the amalgamated results of all debris flood cases modelled to capture the variation of the modelled cases.

How to cite: Cheff, I., Taylor, J., Mitchell, A., Horita, K., Shepherd, D., Rintoul, S., and Millar, R.: Evaluating uncertainty in debris flood modelling for the design of a steep built channel, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20781, https://doi.org/10.5194/egusphere-egu24-20781, 2024.

EGU24-21970 | Posters on site | NH3.1

Kinematics and scaling of granular flows within a centrifugal acceleration field 

Alessandro Leonardi and Miguel Angel Cabrera

Physical modelling of debris flow has been instrumental for decades in enhancing our understanding of these processes. The geotechnical centrifuge plays a crucial role in this regard, enabling the creation of scaled models with stress fields closely resembling real-world scenarios. Despite its potential, the utilization of the geotechnical centrifuge is limited due to various challenges. Firstly, the technological complexity of designing and conducting experiments involving runout within the confined space of a centrifuge box poses a significant obstacle. Moreover, the interpretation of experimental results is hindered by the presence of apparent Coriolis acceleration, particularly for all kinematic processes. The Coriolis acceleration can potentially disrupt traditional scaling laws used for kinematic processes and lead to instability in simulated flows. Investigating this issue requires testing the same configuration on centrifuges of different radii, which is a formidable task.
In light of these challenges, this study proposes employing high-fidelity numerical simulations to examine the behaviour of an idealized granular flow in a centrifugal acceleration field. These simulations, based on the discrete element method, replicate an acceleration field analogous to that found within a geotechnical centrifuge. Unlike experimental setups, simulations are not constrained by technological limitations, allowing for the exploration of fully realized, steady-state flows under various conditions. The findings from the simulations indicate that traditional scaling can still be applicable, provided a sufficiently large centrifuge is utilized. However, in certain configurations, the Coriolis acceleration may induce instability, causing the flow to dilute, lose coherence, and disperse.

How to cite: Leonardi, A. and Cabrera, M. A.: Kinematics and scaling of granular flows within a centrifugal acceleration field, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21970, https://doi.org/10.5194/egusphere-egu24-21970, 2024.

EGU24-1624 | ECS | Posters on site | NH3.2

Reconstructing the history of landslides in northern Japan through dendrogeomorphology 

Reona Kawakami, Ching-Ying Tsou, Yukio Ishikawa, Ami Matsumoto, Shigeru Ogita, Kazunori Hayashi, and Daisuke Kuriyama

Dendrogeomorphology serves as a method to determine the timing of historical landslide events. This approach entails scrutinizing the spatial and temporal aspects of landslide occurrences by investigating their impact on tree growth by analyzing variations in tree-ring width, recovery timeline of injured tree stem, as well as the age of tree invasion and establishment in areas affected by landsliding. The method's advantage lies in its capacity to yield a large number of samples where trees are growing. This study encompasses research conducted in both the Sansukezawa landslide in Aomori Prefecture and the Kamitokitozawa landslide in Akita Prefecture, Japan. The examination includes an analysis of the reactions of a combined total of 187 tilted deciduous broadleaved trees and coniferous trees aged between 100 and 102 years in response to landslide events. The findings, revealed by variations in tree-ring width, suggested multiple landslide occurrences at the Sansukezawa landslide between 1901 and 2000. The magnitude of these events varied, encompassing localized activities such as the enlargement of landslide scarps to more extensive landslide movements. In the Kamitokitozawa landslide area, the development of impending landslide events, inferred from the recovery timeline of injured tree stems, included scarp expansion. There were five instances of landslide activities recorded during the period from 1999 to 2019.

How to cite: Kawakami, R., Tsou, C.-Y., Ishikawa, Y., Matsumoto, A., Ogita, S., Hayashi, K., and Kuriyama, D.: Reconstructing the history of landslides in northern Japan through dendrogeomorphology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1624, https://doi.org/10.5194/egusphere-egu24-1624, 2024.

EGU24-2036 | ECS | Orals | NH3.2

Spatio-temporal distribution of extreme rock-ice avalanches in the Cordillera Blanca (Peru) 

Benjamin Lehmann, Swann Zerathe, Ronald Concha, Julien Carcaillet, Pierre G. Valla, Juan C. Torres-Lázaro, W. Harrinso Jara, and Manuel Cosi

The Cordillera Blanca, located in Peru between latitudes 8-10°S, is the most glacierized intertropical mountain range in the world, with peaks over 6,000 meters still carrying numerous glaciers today. Ongoing climate change has resulted in a 41.50% reduction in glacier extent from 1962 to 2020, increasing natural hazards such as icefall, glacial lake overflow flooding, and rock avalanches. These events mainly affect the highest reliefs, but can reach the low elevation valleys, where around 300,000 inhabitants are exposed. Since the 1950s, these hazards have caused tens of thousands of casualties, including two major disasters: rock-ice avalanches from the northern summit of Huascaran (6,757m) traveling over considerable distances and destroying populated areas such as Ranrahirca (1962) and Yungay (1970), resulting in approximately 7,000 casualties in total.

In this context, our objective is to construct a comprehensive "spatio-temporal" inventory of substantial rock-ice avalanches (volume > 106 m3) within the Cordillera Blanca. Our aim is to enhance our understanding of their spatial distribution, temporal frequency, and magnitude while pinpointing potential triggering factors. Our specific focus involves investigating potential correlations between avalanche records and climatic oscillations spanning the past hundred thousand years. The primary area of interest is the Yungay site, situated directly downstream from Huascaran North, where successive debris avalanche (historical and paleo) have accumulated, forming debris cones that extend across several square kilometers. Preliminary field observations have identified numerous large boulders indicative of events surpassing the reported magnitude for historical avalanches and their associated deposits.

Employing a multi-method approach that integrates fieldwork, remote sensing, geochronology, and numerical modeling, we intend to assess rock-avalanche deposits and volumes. A preliminary field mission conducted in August 2023 in Yungay facilitated the mapping and sampling of approximately 30 boulders of pluri-decametric size for surface-exposure dating (in situ 10Be on quartz). Anticipating dating results by early 2024, one of the primary expected outcomes of this study is to achieve a comprehensive reconstruction of the geomorphic response of the high Cordillera Blanca during past climate oscillations. This understanding will contribute to better anticipating the future evolution of natural hazards within the context of ongoing global climate warming, glacial retreat, and accelerated permafrost degradation. Additionally, our objective is to characterize the triggering mechanisms for low-frequency (recurrence time >100 yr) high-magnitude (volume >106 m3) events.

How to cite: Lehmann, B., Zerathe, S., Concha, R., Carcaillet, J., Valla, P. G., Torres-Lázaro, J. C., Jara, W. H., and Cosi, M.: Spatio-temporal distribution of extreme rock-ice avalanches in the Cordillera Blanca (Peru), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2036, https://doi.org/10.5194/egusphere-egu24-2036, 2024.

Accurate characterization of riverbed sediment is crucial for monitoring cross-sectional changes in rivers and modeling water dynamics, especially during large water discharge events. The UAV LiDAR technique, with recent advancements, offers enhanced capabilities for detailed riverbed topography mapping by eliminating surface vegetation. Despite its potential, the adoption of UAV LiDAR for riverbed cross-sectional profiling has faced delays and skepticism in regular practices. In this study, we applied the UAV LiDAR technique to measure the riverbed topography of a relatively wide river in the Ilan plain, northeast Taiwan. Our findings reveal that UAV LiDAR provides significantly more detailed results compared to Airborne LiDAR and surpasses topography measurements obtained through photogrammetry. The accuracy of UAV LiDAR-derived point clouds outperforms photogrammetry, especially when ground control points for the work of photogrammetry are insufficient or poorly distributed. Despite challenges posed by water bodies absorbing LiDAR signals, UAV LiDAR allows the production of complete riverbed topography, offering reliable estimates during dry seasons. Utilizing UAV LiDAR data, we conducted a comprehensive analysis of both cross-sectional and longitudinal riverbed profiles. The longitudinal profiles exhibit wavy frequencies associated with sediment transport processes, opening avenues for further investigation. Additionally, we evaluated Digital Elevation Models (DEMs) of Differencing (DoD) using previously acquired Airborne LiDAR point clouds. The DoD analysis unveiled the substantial magnitude of sediment movement and redistribution following an extreme rainfall event and dam failure, with a height difference exceeding 9m. This analysis, extending along the river's longitudinal profile, serves as a ground-truth field dataset illustrating how extreme rainfall events can trigger large sediment movements, posing potential hazards to the residents near rivers. Our study demonstrates the utility of UAV LiDAR in high-resolution mapping of riverbed sediment topography and provides valuable insights into sediment dynamics under extreme events, contributing to improved monitoring and hazard assessment practices.

How to cite: Chan, Y.-C. and Sun, C.-W.: Riverbed Sediment Topography Mapping Using UAV LiDAR and Insights into Sediment Redistribution Following an Extreme Rainfall Event and Dam Failure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2327, https://doi.org/10.5194/egusphere-egu24-2327, 2024.

EGU24-2547 | ECS | Posters on site | NH3.2

SAR Monitoring and Finite Element based Stability Modeling for the Zero Landslide in the Darjeeling Himalayas, India 

Suvam Das, Koushik Pandit, Debi Prasanna Kanungo, and Shantanu Sarkar

Landslides are one of the recurring geological hazards in the Indian Himalayas, often leading to loss of life and economy. For the present study, the Zero landslide located in the Darjeeling Himalayas, India has been investigated. This landslide was first activated on July 16, 2014 and its subsequent occurrences have affected a total area of 1×105 sq.m. Field investigations revealed that a local school building, its nearby roads and a few residential buildings are at risk from this landslide. Therefore, monitoring and stability modeling becomes imperative to assess the associated hazard level. For the studied case, the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique was applied to monitor the surface level deformation. For this purpose, Sentinel-1 SLC images captured from January 2022 to November 2023 were collected, and processed using the HyP3 and OpenSARLab platforms. The SBAS-InSAR results revealed maximum subsidence i.e., Line-of-Sight (LOS) velocity (cm/y) of –8.2 and –11.5 for ascending and descending orbit directions, respectively. The presence of transverse tension cracks in the crown and flanks of this landslide supports the SBAS-InSAR results and indicate an active sliding. Furthermore, to assess the slope stability, continuum based two-dimensional finite element modeling (FEM) was carried out. For this, the Shear Strength Reduction (SSR) method was employed in the FE analysis to compute the safety factors for different scenarios. To incorporate material properties within the configured FEM, the Mohr-Coulomb strength criterion was used for soil overburden, and the Generalized Hoek-Brown strength criterion was used for bed-rock profile. The FE analysis revealed a critical Factor of Safety (FoS) value of 1.07 for dry condition and 0.78 for wet condition (Ru). The obtained FoS values suggest that the studied slope section is marginally stable in dry condition; however, instability may be induced during a rainfall event in future. Based on these findings, the design and implementation of landslide risk mitigation measures have been encouraged prior to any major landslide event at the study location.

How to cite: Das, S., Pandit, K., Kanungo, D. P., and Sarkar, S.: SAR Monitoring and Finite Element based Stability Modeling for the Zero Landslide in the Darjeeling Himalayas, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2547, https://doi.org/10.5194/egusphere-egu24-2547, 2024.

EGU24-2625 | Orals | NH3.2

Rheological behavior of Crushed Rock Flows 

wei hu and Mauri McSaveney

The enduring mystery surrounding the unexpectedly high mobility of expansive geophysical flows has persistently tantalized researchers since Albert Heim's investigation following the catastrophic landslide at Elm, Switzerland. Despite numerous claims of resolution, the mechanism underpinning this remarkable mobility has remained elusive. To delve into the flow dynamics of crushable dense granular material exhibiting high mobility, a series of high-speed rotary shear experiments was conducted using various mineral particles. Our findings revealed a more explicable flow behavior when interpreting shear resistance as viscous rather than purely frictional. Notably, we observed a dramatic decrease in viscosity for crushable materials, stabilizing at a consistently low level, crucial in dictating the remarkable fluidity observed in large-scale geophysical flows like rock avalanches. The flow exhibited two distinct phases, demarcated by a critical point of weakening within accumulated strain for crushable material. The initial phase reflected a simple Newtonian or non-Newtonian-like flow, while the subsequent phase was more intricate, displaying a profound viscosity drop stabilizing at a constant level under substantial strain. This discovery holds significant implications for understanding hypermobile geophysical phenomena, including rock avalanche dynamics, natural faulting, and crater collapse. In particular, we demonstrate that the behavior of rock avalanches is similar to that of complicated fluids with extensive weakening and that the viscosity of this special “liquid” is as low as 500 Pa·s. This finding can also help improve the accuracy and reliability of the numerical simulation of rock avalanches by using the viscous model obtained from the experiments.

How to cite: hu, W. and McSaveney, M.: Rheological behavior of Crushed Rock Flows, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2625, https://doi.org/10.5194/egusphere-egu24-2625, 2024.

EGU24-3883 | Posters on site | NH3.2

Evolution of large-scale landslide at Tuchang creek, Taiwan 

Chia-Ming Lo and Yu-Chen Wu

The D077 study area is located on the right bank of Tuchang Creek in Wufeng Township, Hsinchu County, Taiwan. Two large-scale landslide events occurred in the D077 study area in 2004 and 2013, causing 14 casualties and disrupting traffic, seriously threatening downstream settlements. Until now, the rock slopes in the D077 study area are still in a state of toppling deformation and instability. In view of this, this study used multi-stage remote sensing, terrain analysis, geological survey, geophysical prospecting, drilling, and other data in the analysis of the evolution of large-scale landslides at D077 study area. The results show that the evolution of large-scale landslides (the D077 study area contains three sliding masses: S1, S2, and S3) can be divided into six periods: (1) the period of severe erosion of Tuchang creek and Chingchuan anticline, (2) rock mass decompression and toppling deformation period, (3) development of wedge failure trend of rock slopes at S1 sliding mass, (4) movement of S1 sliding mass and violent erosion of the S2 sliding mass slope toe, (5) toppling deformation develops rapidly at S2 sliding mass, (6) movement of S2 sliding mass and S3 sliding mass toppling deformation continues to develop. In the future, we predict that S2 and S3 will again cause debris sliding and large-scale rock mass sliding. This activity is also expected to threaten the safety of inhabitants and property in downstream of Tuchang creek.

Key words: large-scale landslide, toppling deformation, remote sensing, geological survey, geophysical prospecting, drilling

How to cite: Lo, C.-M. and Wu, Y.-C.: Evolution of large-scale landslide at Tuchang creek, Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3883, https://doi.org/10.5194/egusphere-egu24-3883, 2024.

Slope monitoring is a commonly way to mitigate the hazard of landslide. The displacement is one of the main parameters being used in slope monitoring, however it is not significant until landslide occurs. According to the literature, energy will accumulate, transfer and dissipate during the development of landslide. So, it is possible to take energy as one of parameters used in slope monitoring if it’s property was understood sufficiently. This study is aimed to find the relationship between energy evolution, displacement of sliding mass and mechanical behavior of rock materials during the development of landslide. In addition, the energy data and displacement data were compared to find the difference between them. Science the mechanical properties of rock mass is affected by scale, four kind of numerical models were created using different scales. Then the energy data and displacement data of specific particles inside each models were recorded during the simulation. The small-scale models include direct shear test model and uniaxial compression test model. The large-scale models include simplified toppling failure model and full-scale landslide model. The results show that in the large-scale models, the variation of energy data is more significant than displacement data. However, in the small-scale models, the variation of displacement data is more significant.

How to cite: Wu, Y. C. and Lo, C. M.: Study on energy and displacement evolution of rock slope during the development of landslide by multi-scale modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4336, https://doi.org/10.5194/egusphere-egu24-4336, 2024.

EGU24-5778 | ECS | Orals | NH3.2

Monitoring 4D landslide displacement using very high resolution Pléiades satellite remote sensing.Case study of the La Valette landslide, French Alps 

Sheng Fu, Steven M. de Jong, Wiebe Nijland, Mathieu Gravey, Philip Kraaijenbrink, and Tjalling de Haas

Slow-moving landslides may pose a substantial threat to communities and infrastructure, with annual creeping distances ranging from a few mm to 100 m. To protect local communities from the landslide motion, landslide displacement monitoring is necessary. However, traditional field investigations are time- and labor-consuming, which may limit the understanding of the landslide evolution and thereby mitigation. Here we propose a 4D landslide displacement framework using optical very high resolution (0.5m) Pléiades satellite constellation imagery. We use our method to monitor the annual movement of the ‘La Valette’ landslide, southern French Alps, between 2012 and 2022. During this period, the landslide moved most actively during the years 2012 and 2013, with average 3D displacement rates of 1.22 and 0.89 cm / day, respectively. Furthermore, we found a decelerating trend in movement rate from 2012 to 2022, which we attribute to warmer weather, decreasing precipitation rates, drier air conditions, and the implementation of a drainage installation. Our study demonstrates the great potential of very-high resolution satellite imagery for near-real time monitoring of 4D landslide displacement, which may benefit research and may contribute to the mitigation of damage and fatalities of slow-moving landslides.

How to cite: Fu, S., de Jong, S. M., Nijland, W., Gravey, M., Kraaijenbrink, P., and de Haas, T.: Monitoring 4D landslide displacement using very high resolution Pléiades satellite remote sensing.Case study of the La Valette landslide, French Alps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5778, https://doi.org/10.5194/egusphere-egu24-5778, 2024.

EGU24-6050 | Posters on site | NH3.2

A case study integrating in-situ monitoring data and numerical simulation method to slope stability assessment of a remote village in southwest Taiwan 

Huai-Houh Hsu, Ting-Wei Chen, Chen-Hsun Hsieh, Chia-Chi Chang, and Tsung-Yi He

The Baoshan Village, a remote village deep in southwest Taiwan, is located near the Tengjhih National Forest Recreation Area. The strata at the site of this study belong to the Miocene Changshan Formation. Its lithology is mainly slate, occasionally intercalated with thin sandstone layers, and the Chaochou Fault passes through it on the east side. Headward erosion and weathering effects made landfall while heavy rainfall and typhoons hit Taiwan. Typhoon Morakot (2009) impacted Taiwan and brought catastrophic damage. Landslides and significant damage happened in the Baoshan Village neighborhood. This study compiles the long-term in-situ monitoring data of the Baoshan Village from 2018 to the present. Monitoring results show that the east side of the Baoshan Elementary School has an apparent slide surface at a depth of 46m. The limit equilibrium method is adopted for the numerical simulation of slope stability by the digital elevation model (DEM), site investigations, and monitoring data. Results show that Baoshan Village contains many potential slide surfaces distributed in different areas, three of which have high potential sliding surfaces. The assessment of slope stability analysis can provide a tremendously meaningful reference for disaster mitigation of Baoshan Village.

How to cite: Hsu, H.-H., Chen, T.-W., Hsieh, C.-H., Chang, C.-C., and He, T.-Y.: A case study integrating in-situ monitoring data and numerical simulation method to slope stability assessment of a remote village in southwest Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6050, https://doi.org/10.5194/egusphere-egu24-6050, 2024.

Rock slope failures are the catastrophic expression of long-term geomorphological processes occurring in alpine regions. Their impact is often limited to single slopes; however, rock and debris material can occasionally travel very long distances and affect landscape, infrastructures, as well as endanger human life several kilometers away from the source area. Monitoring the evolution of surface activity is recognized as a suitable method to timely identify changes potentially leading to such failure events. Satellite based remote sensing, and in particular Synthetic Aperture Radar (SAR), has shown to be an efficient alternative to in-situ sensors to monitor displacements, especially in situations where the area of interest is large and/or barely accessible. Despite the advent of satellite missions like the ESA Copernicus Sentinel-1, operational monitoring and early warning on single slopes exhibiting surface displacement acceleration potentially leading to failure is still not viable from satellite radars. This is mainly because of the current limitations in spatial and temporal resolution, which prevent obtaining the accuracy and the timeliness often needed for such scenarios.

Here we demonstrate how high spatial and temporal resolution SAR imagery can improve monitoring and characterization of the evolution of a rock slope instability prior and after catastrophic failure. We benefit from ICEYE imagery (X-Band, SPOT mode, 5x5 km scene size, ~50cm resolution) acquired over the Brienz/Brinzauls slope instability in the Swiss Alps between March and August 2023. Among 100 SAR images, we have identified a subset of 30 datasets (ascending orbit, left looking) providing an optimal viewing of the moving slope and imaging the area of interest with revisit times ranging from 3 days to a few hours. We use digital image correlation to measure surface displacements and change detection analyses to map rockfall activity and the slope failure event on June 15th, 2023. We also applied SAR interferometry on data pairs exhibiting suitable perpendicular baselines and computed topographic models at different times and determine failed volumes. The latter have been validated with local terrain models based on photogrammetric drone flights. We discuss the results obtained with ICEYE imagery versus the possibilities with Sentinel-1 data and focus on advantages and specific problems. Our results provide an important step forward towards the use of satellite SAR imagery for operational landslide monitoring scenarios and in the identification and forecasting of catastrophic slope failure events in alpine areas. 

How to cite: Manconi, A., Bühler, Y., Tolpekyn, V., Rankl, M., and Wollersheim, M.: Monitoring impending rock slope failure in alpine scenarios: impact of high spatial and temporal resolution satellite SAR imagery in the investigation of the June 15, 2023, failure event in Brienz/Brinzauls, Swiss Alps  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6091, https://doi.org/10.5194/egusphere-egu24-6091, 2024.

Deep-seated landslide monitoring can require extensive insitu monitoring tools, typically involving equipping boreholes with extensometers, thermometers, and piezometers – proving to be an expensive and labor-intensive task. This work focuses on assessing deep-seated landslide stability by using the physics-based modeling, in partnership with Interferometric Synthetic Aperture Radar (InSAR), as a diagnostic tool for assessing stability in remote regions. We use the case of the insitu monitored El Forn landslide in Canillo, Andorra. We used available Sentinel-1 data to create a velocity map from deformation time series in 2019 and inputted it into a calibrated physics-based predictive model. Using the correlation between the model’s velocity, the insitu observed velocity and the velocity derived from InSAR, we create a normalized real-time risk map of the landslide.

How to cite: Lau, R.: Physics-based uncertainty modeling of deep-seated landslides using InSAR: A case of El Forn (Andorra), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6304, https://doi.org/10.5194/egusphere-egu24-6304, 2024.

EGU24-8090 | ECS | Posters on site | NH3.2

The discovery of a large-scale gravitational collapse in the Gulf of Squillace, Calabria region (central Mediterranean) 

Giacomo Mangano, Silvia Ceramicola, Tiago M. Alves, Massimo Zecchin, Dario Civile, Anna Del Ben, and Salvatore Critelli

The discovery of a large-scale gravitational complex, named in this work Squillace Complex, has been reported in the Gulf of Squillace, Southern Italy, spanning from the continental shelf (c. 1.5 km from the coastline) to the distal sector, covering an area of roughly 600 km2.  The integration between seismic reflection data, borehole and bathymetric information has revealed that this complex exhibits a NE-trending headwall domain made up of sinuous and continuous seafloor scarps linked to a E-W morphological high, via a basal detachment layer between the Messinian evaporites and Tortonian shaleys.

The initiation of the Squillace Complex dates back to the Zanclean (~ 4 Ma) and persisted in movement through the Gelasian (~ 2.1 Ma) at an average rate of 1.9 mm/year. Later in the Calabrian (Middle Pleistocene), the movement underwent a braking and continued sliding to the present day at a reduced rate of 0.1 mm/year. The gravitational collapse of the Squillace Complex aligns temporally with distinct contractional/transpressional events impacting the Calabrian region. These events resulted from basin shortening under a setting of Calabrian Arc stop migration, as well as tectonic uplift affecting the study area since 0.45 million years ago.

In contrast, the diminished movement observed in the Squillace Complex since the Calabrian (Middle Pleistocene) has been inferred as a consequence of conditions of basin stretching in the framework of Ionian plate rollback beneath the Calabrian Arc.

How to cite: Mangano, G., Ceramicola, S., Alves, T. M., Zecchin, M., Civile, D., Del Ben, A., and Critelli, S.: The discovery of a large-scale gravitational collapse in the Gulf of Squillace, Calabria region (central Mediterranean), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8090, https://doi.org/10.5194/egusphere-egu24-8090, 2024.

EGU24-11027 | ECS | Posters on site | NH3.2

Deep-seated gravitational slope deformations of Friuli Venezia Giulia Region (NE Italy) 

Christian Leone, Stefano Devoto, and Luca Zini

Deep-seated Gravitational Slope Deformations (DGSDs) are common phenomena and are observed across various mountain belts worldwide. These phenomena are characterized by the presence of multiple landforms which are important for the recognition of the occurrence of DGSDs. The latter pose significant geological hazard due to their impact on society, economy and environment. They can affect vast areas, potentially endangering large sections of infrastructure, transportation routes, settlements and natural habitats. Furthermore, they cause collateral landslides that can evolve in catastrophic events.

In the past, a comprehensive inventory detailing DGSDs at the scale of the entire European Alps was compiled. This work shows a relatively limited DGSD population in Friuli Venezia Giulia, if compared to other mountain areas such as Central or Western Alps. The final objective of this study is to produce a detailed inventory of DGSDs that affect Alps of Friuli Venezia Giulia Region. Preliminary activities were aimed to desk activities such as analysis of historical documents, reports, aerial images and geomorphological interpretation of LiDAR-derived DTMs. We identified during preliminary activities several DGSDs and tens of possible gravity-induced landforms such as double ridges, ridge top depressions, uphill and downhill-facing scarps, trenches, toe bulges and persistent discontinuities. These gravity-induced features were validated by extensive field surveys carried out in 2023 and the beginning of 2024, also using HR images provided by low-altitude UAV surveys. DGSDs and their landforms were mapped and stored in a GIS.

DGSDs of Friuli Venezia Giulia Alps are favored by: (i) exceptionally high mean annual precipitation (ranging from 1400 to 3400 mm/y), (ii) the presence of several regional faults, (iii) the high-energy relief, (iv) the presence of different rock units (rigid materials and plastic terrains).

How to cite: Leone, C., Devoto, S., and Zini, L.: Deep-seated gravitational slope deformations of Friuli Venezia Giulia Region (NE Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11027, https://doi.org/10.5194/egusphere-egu24-11027, 2024.

EGU24-11468 | Orals | NH3.2

Dynamic simulation of rock-avalanche fragmentation 

Shiva P. Pudasaini, Martin Mergili, Qiwen Lin, and Yufeng Wang

Fragmentation is a common phenomenon in rock avalanches with complex features. The fragmentation intensity and process determines exceptional spreading and mobility of rock-avalanches in the run-out zone. However, studies focusing on the simulation of these phenomena are still limited and no operational dynamic simulation model including the effects of fragmentation has been proposed yet. By enhancing the mechanically controlled landslide deformation model, we propose a novel, unified dynamic simulation method for rock-avalanche fragmentation during propagation. Our formally derived method relies on the continuum mechanics that is applicable to rock masses of any size. The model includes three important aspects: mechanically controlled rock mass deformation, the momentum loss while the rock-mass fiercely impacts the ground, and the energy transfer during fragmentation resulting in the generation of dispersive lateral pressure. We reveal that the dynamic fragmentation, resulting from the overcoming of the tensile strength of the rock mass by the impact on the ground, leads to spreading, thinning, and run-out of the rock avalanche, and to its hypermobility. The elastic strain energy release caused by fragmentation is an important process. Energy conversion between the front and rear parts of the mass caused by the fragmentation process results in the forward movement of the frontal material and the hindered motion of the rear portion of the rock avalanche. Our new model describes this by amplifying the lateral pressure gradient in the opposite direction: enhanced for the frontal particles and reduced for the rear particles after the fragmentation process. The main principle is the switching between the compressional stress and the tensile stress, and therefore from the controlled deformation to substantial spreading of the frontal part of the mass in the flow direction while backward stretching of the rear part of the rock mass. In principle, observations in the laboratory and field events support our simulation results.

How to cite: Pudasaini, S. P., Mergili, M., Lin, Q., and Wang, Y.: Dynamic simulation of rock-avalanche fragmentation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11468, https://doi.org/10.5194/egusphere-egu24-11468, 2024.

Far-traveled landslides greatly increase hazard and risk. Although pervasive liquefaction in debris flows and flow slides can dramatically boost their mobility, the effects of liquefaction on the mobility of coherent landslides is more difficult to forecast. In 2014, the Oso landslide in Washington State, USA failed rapidly and swept across more than 1 km of the adjacent flat alluvial valley, killing 43 people. We mapped over 350 sand boils that emanated from the alluvium under the debris-avalanche hummock deposit. Although transient, these sand boils represent definitive evidence of sub-bottom (basal) liquefaction of the alluvium beneath the overriding slide. The hummocks in the slide mass were not liquefied and they commonly rafted upright vegetation, including coniferous trees, and intact layered glacial sediments across the valley floor. A liquefied base provides little shear resistance, greatly enhancing slide mobility. Our extensive laboratory testing and numerical modeling revealed that several mechanisms may have enhanced basal liquefaction at Oso: rapid undrained loading, shearing of contractive alluvial sediments, and cyclical loading from ground shaking associated with rapid emplacement. 

Here we further investigate the potential for a rapidly moving slide mass to dynamically liquefy underlying alluvial sediments through undrained loading. We use a fully coupled poro-elastic numerical model with parameters determined by laboratory tests of the valley alluvium at the Oso landslide site. Given a landslide speed of 10 m/s, estimated from seismic records of the event, our modeling demonstrates that rapid loading induces transiently elevated pore-fluid pressures nearly equal to the overriding landslide load. These pore-fluid pressures are capable of liquefying the saturated alluvium, reducing its shear strength, and enhancing mobility. Both landslide speed and the hydraulic conductivity of the underlying alluvium strongly modulate the potential for liquefaction. Slower landslide speeds and/or greater alluvial hydraulic conductivity allow simulated pore pressures from loading to dissipate before reaching liquefaction levels. Only specific combinations of these parameters promote basal liquefaction. Such basal liquefaction effects may enhance the mobility of other slides traveling rapidly across saturated alluvium in adjacent valley floors.

How to cite: Reid, M. and Collins, B.: Landslide mobility enhanced by dynamic basal liquefaction of underlying sediments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11528, https://doi.org/10.5194/egusphere-egu24-11528, 2024.

EGU24-12171 | ECS | Orals | NH3.2

Detecting Mass Movements using Fractal-based algorithm 

Quratulain Jaffar, Qi Zhou, and Hui Tang

Rapid climate change is triggering an increase in the frequency and magnitude of catastrophic mass movements on the Earth's surface. Real-time detection of these hazards can improve existing early warning systems and mitigate risks to both humans and society. However, effectively isolating seismic signals from mass movements within continuous seismic recordings remains a significant challenge due to persistent background noise interference. Therefore, It is essential to develop robust detection algorithms for automatic detection. To address this issue, this study proposes the utilization of fractal geometry, which offers a quantitative description of the intricate structures and patterns within a signal across different scales. By using fractal dimensions, this approach aims to differentiate the seismic signal from background noise, because noise typically has a higher fractal dimension than the seismic signal. Two methods, namely, i) variogram estimator and ii) detrended fluctuation analysis, are investigated and applied to the continuous seismic data recorded in the Illgraben catchment in Switzerland to compute the fractal dimension. The findings demonstrate that both methods exhibit power law behaviors in spatio-temporal data, unveiling consistent patterns across scales. The observed variation in fractal dimensions along the seismic traces suggests the reliability of this approach, showcasing reduced susceptibility to false positive detection errors even in the presence of high noise levels. Furthermore, this study also aims to categorize various types of mass movements. This involves defining distinct ranges of fractal dimensions derived from measured data, facilitating the differentiation of various types of mass movements.

How to cite: Jaffar, Q., Zhou, Q., and Tang, H.: Detecting Mass Movements using Fractal-based algorithm, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12171, https://doi.org/10.5194/egusphere-egu24-12171, 2024.

EGU24-13255 | Orals | NH3.2

Unifying endo-exo classification of episodic landslide movements 

Qinghua Lei and Didier Sornette

Landslides, a widespread form of mass wasting, involve complex gravity-driven downslope movements developing over days to years before the final major collapse, which are commonly boosted by external events like precipitations and earthquakes. The reasons behind these episodic movements, characterised by alternating cycles of accelerating and decelerating creeps (marked by intermittent bursts of displacement followed by sustained periods of relaxation dynamics), and how these relate to the final instability, remain poorly understood. Here, we propose the new “endo-exo” classification of landslide bursts, based on the dynamical signatures of pre- and post-burst displacement rates. The underlying concept is based on the existence of cascades of triggered frictional slip and damage responses around a burst. The general theory of multiple cascades of triggered events predicts the existence of four classes of bursts: (i) exogenous non-critical, (ii) exogenous critical, (iii) endogenous non-critical, and (iv) endogenous critical, with respective displacement rates relaxing as power laws around the time tc of the burst respectively as (i) 1/(ttc)1+ϑ for t > tc, (ii) 1/(ttc)1–ϑ for t > tc, (iii) 1/ttc0, and (iv) 1/ttc1–2ϑ, thus depending on a single parameter ϑ. We test these predictions on the precursory and recovery signatures associated with bursts recorded in the long-term monitoring dataset of a rainfall-induced landslide at Preonzo, Switzerland, which exhibited significant episodic movements over many years prior to a catastrophic failure in 2012. Exogenous critical bursts (ii), provoked by external rainfall events, occur abruptly and relax gradually with a power-law exponent around 0.5. In contrast, for endogenous critical bursts (iv) that occur spontaneously under no external triggering, the landslide progressively accelerates prior to the burst and then slowly decelerates afterwards, showing a semi-symmetrical acceleration-deceleration behaviour governed by a small power-law exponent around 0.1. The longer-lived influence of an endogenous critical burst (as reflected by its small relaxation exponent) results from the precursory process that impregnates the system much more than its exogenous counterpart. Additionally, we document a unique exogeneous subcritical burst (i) triggered by the sudden collapse of a downslope sector; it is characterised by an immediate peak followed by a rapid recovery with a power-law exponent around 1.4, consistent with the absence of cascading failures. Endogenous non-critical bursts (iii) are largely driven by fluctuations and thus show no time-dependent recovery. The obtained power laws for these different burst classes are compatible with the existence of a single exponent ϑ ≈ 0.4±0.1, providing strong support for our theory. Our novel conceptual framework points at the existence of a deep quantitative relationship between episodic landslide movements, external triggering events (e.g. rainfall, snowmelt, and seismicity), and internal frictional slip, damage, and healing processes within the landmass.

How to cite: Lei, Q. and Sornette, D.: Unifying endo-exo classification of episodic landslide movements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13255, https://doi.org/10.5194/egusphere-egu24-13255, 2024.

EGU24-14609 | Posters on site | NH3.2

The Parraguirre ice-rock avalanche 1987, semi-arid Andes, Chile -  A holistic revision 

Johannes J. Fürst, David Farías-Barahona, Lucía Scaff, Thomas Bruckner, and Martin Mergili

On November 29 in 1987, a massive ice-rock avalanche detached near Cerro Rubicano in the Dry Andes east of Santiago de Chile. The avalanche developed into a highly destructive debris flow, which reached a run-out distance of more than 50 km resulting in important damage of infrastructure and causing numerous fatalities. In the wake of the event, several studies have shed light on the event history as well as on the geological, volcano-seismic, meteorological and glacio-hydrological pre-conditioning. Although the El-Niño event, that prevailed in 1987, and the presence of glaciers are considered important factors for the development of such a massive debris flow, a holistic analysis of observational evidence, meteorological conditions and debris-flow simulations remains, to this day, absent.

Here, we present new insights obtained from historic aerial photographs and satellite imagery, climate reanalysis, weather stations, hydrographic monitoring and physically-based debris-flow modelling. First, we are able to better constrain the trigger volume and to delineate a first map of the impact area. Second, time records and modelling results affirm the assumed multi-stage character of the event. Third, we postulate that the Parraguirre event can be considered a compound weather event, pre-conditioned by anomalously high temperatures and exceptionally deep snow cover in the days and weeks before the devastating debris flow.

How to cite: Fürst, J. J., Farías-Barahona, D., Scaff, L., Bruckner, T., and Mergili, M.: The Parraguirre ice-rock avalanche 1987, semi-arid Andes, Chile -  A holistic revision, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14609, https://doi.org/10.5194/egusphere-egu24-14609, 2024.

EGU24-15258 | ECS | Orals | NH3.2

Effects of rainfall Intensity-Duration on landslides’ velocity variations: insights from long-term monitoring of case studies in Emilia-Romagna and South Tyrol (Italy) 

Melissa Tondo, Vincenzo Critelli, Marco Mulas, Francesco Lelli, Giuseppe Ciccarese, Giovanni Truffelli, Volkmar Mair, and Alessandro Corsini

What is known, nowadays, is that shallow landslides are mostly influenced by intense short-duration rainfall events while deep-seated ones are mainly affected by long-duration cumulated rainfall. However, the correlation between precipitation and displacement rates, especially for deep-seated landslides, is still poorly investigated on a quantitative basis. In order to understand the mechanisms of acceleration and deceleration of landslides and how they are related to rainfall regimes, long-term, possibly continuous, monitoring of displacement is essential. This contribute aims to present and discuss this issue based on results from about 15 long-term monitored landslides, ranging from earthslides-earthflows to deep-seated rockslides, located in Emilia-Romagna region and South Tyrol. Displacement time series in these case studies have been collected with different in-situ techniques such as principally periodic and continuous GNSS and Robotic Total Stations (RTS), covering periods up to more than ten years. After analysing displacement plots, each identified acceleration event was correlated to rainfall by considering the last significant precipitation event antecedent to the first date of velocity variation, recorded by local meteo stations. Then, Duration (h) and Intensity (mm/h) were retrieved for each event and an Intensity-Duration (ID) plot was built with all data together. It could be observed that the ID-points were distributed along a line with extremely slow deep-seated landslides on one side and rapid earthslides-earthflows on the other, representing the two opposites of the spectrum. Secondly, another aspect that was considered in this framework is the difference between velocity variations of monitored points (such as GNSS benchmarks or RTS prisms) and the velocity of movement propagation along the landslide body. Examples on this topic are presented from Ca’ Lita and Corvara landslides, located in Emilia-Romagna and South Tyrol, respectively. Landslides response to precipitation events is the result of a complex combination of geological, geomorphological, geotechnical, and meteo-climatic factors. In accordance with ID-points distribution, the lower the surface of movement the lower duration and intensity are needed to enhance instability and displacement rates. On the other hand, the interaction with rainfall is not as immediate for deep-seated landslides, making their interpretation more complex. This study presents (i) a summary of all the recorded velocity variations affecting the proposed case studies, and (ii) an interpretation of their behavior in terms of acceleration and precipitation conditions.

How to cite: Tondo, M., Critelli, V., Mulas, M., Lelli, F., Ciccarese, G., Truffelli, G., Mair, V., and Corsini, A.: Effects of rainfall Intensity-Duration on landslides’ velocity variations: insights from long-term monitoring of case studies in Emilia-Romagna and South Tyrol (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15258, https://doi.org/10.5194/egusphere-egu24-15258, 2024.

EGU24-15459 | ECS | Orals | NH3.2

Multiscale Numerical Modeling of Ultrasound-Induced Granular Avalanches 

Hugo A. Martin, Anne Mangeney, Xiaoping Jia, Bertrand Maury, Aline Lefebvre-Lepot, Yvon Maday, and Paul Dérand

Understanding the mechanisms of seismic-wave-induced triggering of landslides and earthquakes at micro-strain amplitudes is crucial for quantifying seismic hazards. Granular materials, as an out-of-equilibrium and metastable model system, offer insights into landslides and fault dynamics within the unjamming transition framework from solid to liquid states. Recent experiments suggest that ultrasound-induced granular avalanches result from reduced interparticle friction via shear acoustic lubrication. However, investigating crack growth or slip at the grain contact scale in optically opaque granular media remains challenging.

We present a new multiscale numerical modeling of 2D dense granular flows triggered by basal acoustic vibrations of an inclined plane. We introduce a time-scale separation method, addressing the characteristic scales of grain motion on one hand and the propagation of acoustic vibrations on the other. Our approach results from the coupling between the Convex Optimization Contact Dynamics model (COCD) and the computation of vibration modes.

Numerical simulations of ultrasonic vibrations in the millisecond range and flow onset in the second range reveal a correlation between local rearrangements at the grain scale and continuous flows at the macroscopic scale. Ultrasounds primarily propagate through strong-force chains, while a decrease in interparticle friction occurs in weak contact forces perpendicular to these chains. This friction reduction initiates local rearrangements leading to continuous flows through a percolation process with a delay dependent on proximity to failure. Ultrasound-induced flow, compared to gravity-driven flow, appears more spatially uniform, suggesting the role of effective temperature induced by ultrasonic vibration. The simulations align well with experimental observations of granular flows triggered by ultrasound below avalanche angles, supporting the validity of our numerical method.

How to cite: Martin, H. A., Mangeney, A., Jia, X., Maury, B., Lefebvre-Lepot, A., Maday, Y., and Dérand, P.: Multiscale Numerical Modeling of Ultrasound-Induced Granular Avalanches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15459, https://doi.org/10.5194/egusphere-egu24-15459, 2024.

EGU24-18109 | ECS | Posters on site | NH3.2

Paleo-landslides in the southern France (Larzac plateau) 

Kévin Elkharrat, Catherine Homberg, Sara Lafuerza, Nicolas Loget, Muriel Gasc-Barbier, and Stephanie Gautier

The Larzac carbonate plateau (France) is subject to numerous slope instabilities on its edges, ranging from toppling to landslides. Due to their extremely slow slip rates (3mm/year), these last large rotational instabilities remain poorly understood, particularly in terms of characterisation and dynamics. Our study focuses on several deep paleo-landslides of this type, located in two valleys: the Lergue and the Laurounet. These landslides evolved in sedimentary rocks including the highly fractured Jurassic carbonates overlying the Triassic sandstones and the thick Triassic clays. This work aims to study the initial phase mechanisms. In a climate change context, with extreme precipitations as in southern France (“cevenol events”), understanding paleo-landslide mechanisms has an added value in the comprehension of the future slope stability in similar geological contexts.

We used a multi-method approach to characterize the investigated landslides. Remote sensing and field surveys allowed mapping of the landslides, identification of geomorphological features, main and secondary scarps, and their associated slide blocks. Rock mass fracturing was characterized at localities in and away from the landslides. Mechanical characterization was obtained through the Rock Mass Rating (RMR)/Geological Strength Index (GSI) and laboratory tests. Finally, terrestrial cosmogenic nuclides (36Cl for carbonate surfaces) were used to determine the exposure age of the landslide scarps.

The investigated million-cubic-meter landslides show upslope and secondary circular scarps with counter-slope slide blocks, signifying rotation. However, at deeper levels, the failure surface flattens within the evaporite-rich clays. Dating two paleo-landslides places their occurrence between 10 and 18 kyrs, suggesting the Late Pleistocene/Holocene transition. A directional correlation is evidenced between the dense NNW-SSE joint network that cut the carbonates and N-S faults with the landslide scarps. The study suggests that landslides exhibit a rotational-translational mechanism, influenced by lithological differences between fractured carbonate units and weak underlying clays. This reaffirms the significance of clays in landslide failure, with evaporite levels playing a role in deep rupture surface branching in certain cases. Furthermore, a major structural control is evidenced, with the faults serving for initiation or as lateral ramps of the landslides depending on their orientation relative to the slope. Dating results suggest that increasing precipitation could have led to slope failures.

These geological constraints were employed to test scenarios for the initiation of the rotational-translational landslides of the Larzac carbonate plateau using the distinct elements method 3DEC. Field data supplied geometry, while the mechanical parameters of the multi-layer rock mass were estimated based on the RMR and GSI data. The three families of discontinuities, layering planes, and the sub-vertical NNW-SSE and WSW-ENE joints were also included, as well as the in-situ pore pressure. The stability analysis revealed the significant impact of joints/faults and lithology contrast on the stability and geometry of the failure surface. This study illustrates how landslides can be related to a combination of predisposing parameters such as structural inheritance and variation of properties in the heterogeneous rock mass that control their modes of failure and geometries.

How to cite: Elkharrat, K., Homberg, C., Lafuerza, S., Loget, N., Gasc-Barbier, M., and Gautier, S.: Paleo-landslides in the southern France (Larzac plateau), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18109, https://doi.org/10.5194/egusphere-egu24-18109, 2024.

EGU24-18344 | ECS | Posters virtual | NH3.2

Locating Sediment Evacuation Zones – A Prefatory Action for Early Warning System Development in Mountainous landscapes 

Arkaprabha Sarkar, Vimal Singh, and Sukumar Parida

The past decade has seen an alarming rise in the number of extreme events, most of which are high magnitude hydrological events triggered by focused precipitation, glacial lake outburst or both. During such event large amount of debris is mobilized and get deposited in downstream reaches. Studies have quantified the volumes of debris exported by the events and have shown them to possess potential for future hazard (e.g., Hooke, 2019; Sarkar and Singh, 2022; Westoby et al., 2023). However, a pressing question that remains unaddressed is regarding the identification of storage sites of these sediments prior to the event.

We have employed the concept of index of connectivity (IC) to locate sediment stored in the landscape. We have altered the relationships of the upslope and downslope components of the basic framework of index of connectivity (Borselli et al., 2008), and normalized the values to obtain a dimensionless storage potential index (SPI) that indicates the proneness of a point to arrest sediment flux and disrupt the routing process. Using the SPI and normalized IC, we have formulated a Sediment Evacuation Susceptibility Index (ESIS), the values of which ranges between -1 to 1; lower ESIS values indicate stable zones with higher thresholds of evacuation, and vice versa.

The model has been tested in a small catchment (~93 km2) known as Pranmati catchment in NW Himalayas, India. Our results show that significant volume of sediment gets arrested along the margins of land cover units that have contrasting impedance to sediment transportation. Sediment flux also gets arrested in isolated pockets (e.g., grassland patches) within forested land. Croplands tend arrest and store sediment due to intense anthropogenic modification of hillslopes. Landslide talus deposits are a potential sediment storage unit. Mid-slope regions of hillslope transects tend to have high storage potential. These sites get connected during extreme hydrological conditions and release the stored sediments. Landslides debris deposits are found to be highly stable. However, parts of the hillslope in the vicinity of the stream network have a very high susceptibility to evacuation. The results have been validated in field with reference to two major local high magnitude flash flood events. The evacuation susceptibility assessment can be the first step for risk identification, development of an early warning system for flood hazards and disaster mitigation.

References

Borselli, L., Cassi, P., & Torri, D. (2008). Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment. Catena, 75(3), 268-277.

Hooke, J. M. (2019). Extreme sediment fluxes in a dryland flash flood. Scientific Reports, 9(1), 1686.

Sarkar, A., & Singh, V. (2022). Characterisation and Assessment of a Flash Flood in the Himalaya: Understanding the Significance of High Magnitude Events in Sediment Mobilisation. Journal of the Geological Society of India, 98(5), 678-686.

Westoby, M. J., Dunning, S. A., Carrivick, J. L., Coulthard, T. J., Sain, K., Kumar, A., ... & Shugar, D. H. (2023). Rapid fluvial remobilization of sediments deposited by the 2021 Chamoli disaster, Indian Himalaya. Geology, 51(10), 924-928.ter, Indian Himalaya. Geology, 51(10), 924-928.

How to cite: Sarkar, A., Singh, V., and Parida, S.: Locating Sediment Evacuation Zones – A Prefatory Action for Early Warning System Development in Mountainous landscapes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18344, https://doi.org/10.5194/egusphere-egu24-18344, 2024.

EGU24-20856 | ECS | Posters virtual | NH3.2

“Identification and Characterization of Paleoalluvial Events in the  Ranrahírca Hydrographic Unit, Cordillera Blanca, Perú” 

W. Harrinson Jara Infantes, Manuel Cosi Cosi, Juan C. Torres, Benjamin Lehmann, Swann Zerathe, Hilbert Villafane, Enver Melgarejo, Adriana Caballero, Sara Cachay, and Leila Mamani

Abstracts

The Cordillera Blanca, located in Peru, is a mountain range with peaks exceeding 6000 meters, preserving tropical glaciers on its surface. Currently, due to global climate change resulting from both natural and anthropogenic causes, glaciers are rapidly losing surface area and volume. Over a period of 58 years, between 1962 and 2020, the Cordillera Blanca (CB) has lost 301.4 km2 of glacier surface, equivalent to 41.50% of the total area. This has led to an increased occurrence of ice and rock avalanches, triggering violent overflow events of glacial lakes and alluvial processes. In this context, the Hydrographic Unit (HU) Ranrahírca has recorded the occurrence of two extreme avalanche events originating from the North Peak of Nevado Huascarán, corresponding to the 1962 event in Ranrahírca and the 1970 event in Yungay.

The objective is to identify, differentiate, categorize, and correlate unconsolidated deposits with different historical alluvial events (Paleoalluvions) of significant magnitude that occurred on the north peak of Nevado Huascarán, Cordillera Blanca. This involves a detailed grain size analysis of soils, with emphasis on lithology, dimensions, shape, and degree of weathering of the clasts in their composition, as well as their fine material content, aiding in temporally situating the origin event. The primary study area is the Yungay district, located at the lower part of Nevado Huascarán, where Quaternary material from various paleoalluvions has accumulated in a fan-shaped pattern in the lower part of the Ranrahírca HU. This area extends for several kilometers, currently encompassing the urban areas of Yungay and Ranrahírca.

To achieve this, fieldwork was conducted in August 2023 in the Yungay and Ranrahírca areas. Seven (07) chronostratigraphic columns were surveyed, and thirteen (13) soil samples were collected from different cut sections of slopes. These efforts have allowed the differentiation of various paleoalluvionic events and, in some cases, evidence the transition between them.

Keywords: Cordillera Blanca, rock-ice paleoavalanche, grain size analysis, chronostratigraphic column.

How to cite: Jara Infantes, W. H., Cosi, M. C., Torres, J. C., Lehmann, B., Zerathe, S., Villafane, H., Melgarejo, E., Caballero, A., Cachay, S., and Mamani, L.: “Identification and Characterization of Paleoalluvial Events in the  Ranrahírca Hydrographic Unit, Cordillera Blanca, Perú”, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20856, https://doi.org/10.5194/egusphere-egu24-20856, 2024.

In recent years, with the frequent occurrence of extreme climate, rainfall-induced landslide (RIL) has become one of the main geological hazards that endanger human life and property safety. Understanding the relationship between meteorological factors and RIL is essential for promoting safety. Although the research community has been studying the spatial or temporal probability relationship between climate variability and RIL using quantitative and qualitative methods at different spatial or temporal scales for decades, the spatio-temporal probability of synchronous hazard prediction has rarely been studied. Here, we constructed a hybrid model of Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM) and utilized the spatial feature extraction capability of the CNN model and the temporal feature extraction capability of the LSTM model to infer the causal relationship of RIL and simulate the risk of RIL from the meteorological data from 1980 to 2015. In this study, the Wanzhou District of Chongqing, China was used as the research area to train and test the model, in order to provide a new idea to synchronously predict the spatial probability and temporal probability of RIL. Our results reveal that the spatio-temporal probability prediction model has higher prediction accuracy than the single spatial probability or temporal probability prediction model, and it is more consistent with the actual occurrence of RIL. The predicted results of our model show that the occurrence of RIL is mainly affected by the geological environment, followed by the intensity and duration of rainfall in extreme climates. The inferred patterns show that precipitation extremes are associated with an increased risk of RIL. Therefore, in addition to understanding the geological factors that trigger the hazards themselves, a better understanding of climate-hazard linkages enhances the spatio-temporal modeling capacity for the risk of RIL. In the future, it can be used to analyze the world's risks of RIL caused by climate change.

How to cite: Zhao, Y. and Chen, L.: Spatio-temporal probability prediction of rainfall-induced landslides based on deep learning under climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-68, https://doi.org/10.5194/egusphere-egu24-68, 2024.

EGU24-455 | ECS | PICO | NH3.4

The interplay of Atmospheric Rivers and topography on snowmelt induced landslides in Northern Anatolian Mountains (Türkiye) 

Harun Aslan, Tolga Gorum, Deniz Bozkurt, Omer Lutfi Sen, Yasemin Ezber, Abdullah Akbas, and Seckin Fidan

Landslides triggered by snowmelt, as one of the main hydrometeorological triggering factors, and their interaction with Atmospheric Rivers (ARs—long and narrow horizontal water vapor transport characterized by high water vapor content and strong low-level winds) and topographic conditions are not adequately elucidated. During the February–April 2022 period, extreme snowfalls in the Northern Anatolian Mountains, followed by a rapid snowmelt event, triggered more than 300 landslides. Accordingly, based on local and national news sources as well as public institution reports, an inventory was created by mapping 330 landslide events that occurred as a result of rapid snowmelt during this period. This landslide inventory compiled for the Northern Anatolia Region, one of the most susceptible regions in Europe, as well as Türkiye in terms of landslide events, provides a unique opportunity to understand the process dynamics underlying snowmelt-induced landslides. Revealing the combined and/or individual roles of meteorological weather events such as sudden temperature rises, heat waves, rain-on-snow events, and/or the foehn effect, associated with ARs or synoptic-scale weather events, in triggering these landslides is essential for better understanding possible such events in the near-future and to taking effective measures to mitigate socio-economic losses.

The spatio-temporal distribution of snowmelt, air temperature, and snow-water equivalent (SWE) variables at daily and monthly scales for the February to April 2022 period according to long-term climatology (1993–2022) as well as landslide events triggered by ARs were analyzed. Additionally, the impacts of altitude and slope steepness on the spatio-temporal distribution of landslide events were revealed. Over the study area during February–April 2022, both monthly SWE and snowmelt values had positive anomalies, while air temperature values showed positive anomalies only for February and April. The analysis of landslide events triggered by ARs based on a 5-day window for AR passages showed that ARs as a triggering factor were responsible for 62% of total landslide events. On the other hand, as time progressed during the period February–April 2022, an increase in the altitude and slope steepness values at which landslide events occurred gradually increased. In addition to a gradual escalation of landslide occurrences to higher altitudes with time, we observed that landslides are limited to around 800 m, which further suggested that this may be caused either by limited soil thickness cover above a certain altitude or by the air temperature below the thawing degree.

How to cite: Aslan, H., Gorum, T., Bozkurt, D., Sen, O. L., Ezber, Y., Akbas, A., and Fidan, S.: The interplay of Atmospheric Rivers and topography on snowmelt induced landslides in Northern Anatolian Mountains (Türkiye), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-455, https://doi.org/10.5194/egusphere-egu24-455, 2024.

In mountainous areas, landslides initiation is strongly influenced by temperature and precipitation. Liking temperature and precipitation anomalies to landslides occurrence is among the viable methods to predict the future occurrence frequency of such hazards under climate change. Currently, most of the methods to detect such anomalies rely on in-situ measurements. This demands significant efforts for data retrieval and homogenization, which, together with the constraints on data sharing, pose important challenges to the replicability of the studies and to the comparison among different methods. Open access gridded datasets could overcome these limitations, but their ability to capture meteorological anomalies needs to be assessed. Here we address this issue.

By means of a consolidated statistical-based approach, we here exploit: a) half-hourly precipitation estimates from the Integrated Multi-Satellite Retrievals from GPM (IMERG), b) daily temperature observations from ENSEMBLES OBServation (E-OBS) and c) daily temperature and total precipitation  of global reanalysis ERA5 to demonstrate that open access gridded climate datasets can complement or even replace in-situ data in studies linking meteorological anomalies (defined as percentiles above 0.9 or below 0.1) with the occurrence of geomorphic hazards. We focus on a vast catalogue of 483 different geomorphic hazards (mainly landslides, rockfalls and debris flows) occurred along 2000-2020 over the Italian Alps.

Findings indicate that the statistical significance of the paired anomalies derived by observations and gridded datasets is often achieved. Mismatches are related to limited sample sizes. In general, E-OBS and IMERG demonstrate to provide information on temperature and precipitation anomalies, respectively, that is comparable or even better than the one provided by in-situ observations and ERA5 reanalyses. Additionally, our findings reveal that IMERG, by providing information directly on the initiation zone, can detect precipitation anomalies at the daily scale that in-situ measurements fail to detect, especially in the case of debris/mud flows events triggered by small-scale convective processes.

Overall, gridded datasets can help to improve our knowledge on the statistical relation between landslide initiation and meteorological anomalies, which in the future can be adopted to quantify changes in the occurrence probability of these events under a changing climate.

How to cite: Paranunzio, R. and Marra, F.: Open access gridded climate datasets can help to reveal meteorological anomalies’ role in landslides initiation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3180, https://doi.org/10.5194/egusphere-egu24-3180, 2024.

EGU24-3987 | ECS | PICO | NH3.4

Trends in torrential flooding in the Austrian Alps: Assessing different types of changes to a mountain hazard profile 

Matthias Schlögl, Micha Heiser, Christian Scheidl, and Sven Fuchs

The occurrence of natural hazard events is heavily affected by climatic drivers and triggers. Changes in these climatic drivers are likely to bring about potentially severe consequences for mountain communities due to shifts in natural hazard occurrence patterns and characteristics. Although there is a well-established scientific consensus regarding cause-and-effect relationships from a physical science standpoint, substantiating these connections can pose challenges for specific hazard processes when viewed through an empirical and data-driven lens (Schlögl et al., 2021).

The Sixth Assessment Report (IPCC, 2021) highlighted changes in intensity/magnitude, frequency, duration, timing and spatial extent of a wide range of climate hazards. Following this line we investigated trends in torrential flooding in the Austrian Alps. Torrential flooding comprises a set of natural hazard processes, which originate in small and steep mountain headwater catchments and are characterized by highly variable discharge and sediment transport volumes.

We used a comprehensive data set data of damage-inducing torrential flooding events as collected by the Austrian Torrent and Avalanche Control Service (WLV). Assuming inventory completeness after 1945 (Heiser et al., 2019), our trend analyses with respect to the core climate change characteristics based on nearly 80 years of event data (and more than 11,000 events) yielded the following results:

  • Intensity/magnitude: Using deposition volume as a proxy for event magnitude, a statistically significant decrease over time was detectable. However, caution is warranted due to a potential under-reporting bias for smaller events in earlier years and changes in data recording procedures.
  • Frequency: Event frequency exhibited a significant positive trend, with breakpoints evident in the cumulative number of events. Changes in documentation standards in 2005 and high overdispersion in the dataset contributed to challenges in interpreting trends.
  • Duration: Lack of data on precise event onset and end impeded reliable assessment of changes in event duration.
  • Timing (seasonality): Analysis of date information revealed a peak in event occurrence during summer, particularly in July and August. No significant shifts in seasonality were confirmed, thereby challenging previous reports of changes in timing of maximum discharge or permafrost degradation.
  • Spatial extent: Spatial extent analysis, based on deposition area, was limited to the period 2012-2022, hindering a reliable trend analysis. We acknowledged the lesser relevance of spatial extent for torrential flooding compared to changes in event magnitude.

Summarizing, reliably detecting generalizable trends in torrential flooding characteristics is challenged by issues such as incomplete data, data quality, and dynamically changing drivers. While issues related to documentation techniques can be addressed in future data collection efforts, dynamically changing drivers (including climate change, mitigation activities, exposure dynamics, and land use changes) pose ongoing challenges due to complex interactions and nonlinear effects. We underscore the importance of controlling for these effects when assessing trends in torrential flooding in a changing climate.

References

Heiser M., Hübl J. & Scheidl, C. (2019). Completeness analyses of the Austrian torrential event catalog. Landslides 16, 2115–2126 (2019). https://doi.org/10.1007/s10346-019-01218-3.

Schlögl M., Fuchs S., Scheidl C. & Heiser M. (2021). Trends in torrential flooding in the Austrian Alps: A combination of climate change, exposure dynamics, and mitigation measures. Climate Risk Management 32: 100294. https://doi.org/10.1016/j.crm.2021.100294.

How to cite: Schlögl, M., Heiser, M., Scheidl, C., and Fuchs, S.: Trends in torrential flooding in the Austrian Alps: Assessing different types of changes to a mountain hazard profile, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3987, https://doi.org/10.5194/egusphere-egu24-3987, 2024.

Temperature fluctuations within landslide shear zones can arise from interactions with deeper subsurface layers and the atmosphere crossing the landslide body. Shallow landslides, particularly those with depths less than 10 m, are notably susceptible to seasonal temperature variations and swift climatic shifts. The hydro-mechanical properties of clayey soils exhibit sensitivity to temperature alterations. Some investigations have proposed significant variations in residual shear strength, even within temperature ranges typical of shallow layers in temperate and warm regions.

This study examines the response of two pure clays (Ca-bentonite and kaolin) to shearing at temperatures up to approximately 55 °C, considering various normal stresses (50–150 kPa) and shear rates (0.018–44.5 mm/min). A temperature-control system integrated into a ring-shear device facilitated the experimentation.

Subsequently, we conducted experiments on an ideal slope to quantify the impact of ground temperature on the stability of clay slopes across seasons and prolonged warming. By accounting for the most substantial effects determined experimentally (residual shear strength changing by ±1.5 %/°C), we identified variations in the global factor of safety of approximately 20% for rotational slides at depths of approximately 6 m, solely due to seasonal heating-cooling cycles. A warming of 5 °C over decades would introduce an additional ±7% change in the stability condition.

While acknowledging the simplified geometry and boundary conditions in these results, and the exclusion of triggers, preconditions, and effects of other thermo-hydro-mechanical couplings, they establish an upper limit for the influence of temperature-dependent residual shear strength on the factor of safety. We emphasize that this influence should not be disregarded in slope stability and landslide hazard assessments for clay-rich soils, necessitating thorough experimental analyses and advanced modelling.

How to cite: Loche, M. and Scaringi, G.: Temperature-Dependent Shear Strength in Clay Slopes: Experimental Insights and Implications for Stability Assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5246, https://doi.org/10.5194/egusphere-egu24-5246, 2024.

The shear strength is a fundamental mechanical parameter that controls the occurrence and propagation of landslides. In pure clays, this parameter is temperature-dependent according to the clay’s mineral composition and hydro-mechanical boundary conditions. Landslide soils are typically heterogeneous mixtures with a variable content of clay minerals. Particularly for low-plasticity soils, the impact of changes in temperature on the mechanical response remains to be determined, and little can be said about possible macroscopic alterations of slope stability or landslide dynamics.

In this study, we conducted ring-shear tests using natural soils from the Melamchi catchment in central Nepal, which suffered widespread instabilities and rainfall-induced debris flows. We performed experiments under typical landslide stress levels (50-150 kPa) in water-saturated conditions and under a constant rate of shearing (0.1 mm/min). We controlled the temperature during testing and performed a heating-cooling cycle (20-50-20 °C) only after attaining the residual shear condition. We prepared multiple samples from the same soil by retaining its finest portion under different cutoff grain sizes (0.125-0.020 mm) to evaluate the fine fraction's role in the thermo-shear response.

As expected, we observed a decrease in shear strength with the clay fraction increasing. Samples with a coarser cutoff (and hence a lower clay fraction) did not exhibit any change in shear strength during the heating-cooling cycle. However, as the clay fraction increased, a heating-induced weakening emerged, corresponding to up to a 1° difference in friction angle in the samples with a 0.020 mm cutoff. In the specific case study, this weakening may be minor and will not affect evaluations of slope stability in simple limit equilibrium analyses, especially in the absence of explicitly accounting for spatial heterogeneities in soil properties and boundary conditions. Nevertheless, incorporating this effect into physically-based models, either entailing advanced soil constitutive models or equations for surface flows (both of which can include additional temperature-dependent parameters), may provide useful insights into the complexity of thermo-hydro-mechanical responses and their effects on landslides at the local and regional scales.

How to cite: Dhakal, O. P., Loche, M., and Scaringi, G.: Shear weakening with increasing temperature: effect of clay fraction in low plasticity soils from the Melamchi catchment in Nepal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10778, https://doi.org/10.5194/egusphere-egu24-10778, 2024.

EGU24-11270 | ECS | PICO | NH3.4

Climatic triggering of landslide sediment supply in the Alpine Rhine 

Sophia Demmel, Ludovico Agostini, Sofia Garipova, Elena Leonarduzzi, Fritz Schlunegger, and Peter Molnar

The AlpRhineS2S project, a collaboration between ETH Zurich and the University of Bern, researches the interplay of geological, geomorphological and hydrological processes within the sedimentary system of the Alpine Rhine in the canton of Grisons in Switzerland.

Mechanisms of sediment erosion, transport and deposition determine the pathways of sediment from sources to sinks in a river basin. Long-term basin-averaged denudation rates serve to characterize the geomorphic properties of a catchment and to derive a sediment budget (Garipova et al., 2024), while specific hotspots of erosion considerably contribute to the short-term sediment supply into the fluvial system. Accordingly, mass wasting events play a crucial role in an Alpine geomorphic context by intermittently providing considerable amounts of sediment for transport in the river network. A large part of this sediment is transported in suspension, producing a complex turbidity signal at the outlet (Agostini et al., 2024) that features distinct tracers of source material composition (Garipova et al., 2024).

In this contribution, we investigate the effects of precipitation as a triggering factor for frequent mass wasting events in the Alpine Rhine catchment. We correlate records of shallow landslide, debris flow, and rockfall events from the Swiss natural hazard database (StorMe, Swiss Federal Office for the Environment FOEN) to the gridded daily precipitation product RhiresD (Swiss Federal Office of Meteorology and Climatology MeteoSwiss). We estimate rainfall thresholds for those events by classifying consecutive rainfall days as either triggering or non-triggering events and performing jackknife cross-validation to assess the temporal bias of the event data following Leonarduzzi et al. (2017; 2020). We characterize the regional and seasonal effect of heavy precipitation events on increased sediment supply available for transport in the fluvial system. Finally, we also identify individual erosion hotspots and their link to sediment connectivity and slope stability assessments. Analyzing external drivers, we hypothesize on the effect of changes in climatic forcing on erosion mechanisms over the past decades, particularly due to increasing temperatures and precipitation intensities.

References:

Agostini, L., Demmel, S., Garipova, S., Sinclair, S., Schlunegger, F., Molnar, P. (2024): Suspended sediment transport in a river network: testing signal propagation and modelling approaches. EGU 2024.

Garipova, S., Mair, D., Demmel, S., Agostini, L., Akçar, N., Molnar, P., Schlunegger, F. (2024): Source-to-Sink Sediment Tracing in the Glogn River Catchment. EGU 2024.

Leonarduzzi, E., Molnar, P., McArdell, B.W. (2017): Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data. Water Resources Research 53(8): 6612–6625. https://doi.org/10.1002/2017WR021044.

Leonarduzzi, E. and Molnar, P. (2020): Deriving rainfall thresholds for landsliding at the regional scale: daily and hourly resolutions, normalisation, and antecedent rainfall. Nat. Hazards Earth Syst. Sci., 20, 2905–2919. https://doi.org/10.5194/nhess-20-2905-2020. 

How to cite: Demmel, S., Agostini, L., Garipova, S., Leonarduzzi, E., Schlunegger, F., and Molnar, P.: Climatic triggering of landslide sediment supply in the Alpine Rhine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11270, https://doi.org/10.5194/egusphere-egu24-11270, 2024.

 Landslides are extensively distributed across the globe. About 17% of deaths due to natural hazards reported in the last decade are attributed to landslides. The spatial and temporal distribution of landslides are related to static and dynamic factors. The first group involves terrain aspects and land use, and the second group includes triggering factors, such as rainfall and earthquakes. The  61% of worldwide landslides recorded are triggered by rainfall. In Colombia, the percentage reaches 92%, becoming the main factor that triggers landslides. 

The Aburrá Valley is located in the central northern Andes, characterized by its complex topography and one of Colombia's most densely populated valleys, with 3.9 million inhabitants. In this study, the spatial and temporal relationship between landslides and rainfall in the Aburrá Valley is unraveled. Three kinds of rainfall information are used: pluviograph (145 stations), radar and satellite. Regarding the landslide database, 940 landslides were compiled between 1921 and 2023. The temporal analysis includes the understanding of different time scales: decadal, annual, daily, and hourly because several macroclimatic aspects affect the precipitation regime, such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Intertropical Convergence Zone (ICZ). This understanding leads to knowing on what scale there is clear evidence that regional precipitation changes can affect the occurrence of landslides. Regarding the spatial analysis, the radar and satellite information complements the data of punctual pluviographic stations.

The results show that the ENSO affects the development of rainfall regimes on all time scales. When the PDO and ENSO match, the effects of EL Niño and La Niña phases are exacerbated, resulting in lower and higher landslides, respectively. In general, Aburrá Valley exhibits a bimodal precipitation phase, where the annual cycle peak of landslides matches with the peaks of rainfall annual cycle; the Enso affects the cycle mentioned, showing that, especially in dry periods, the effects of Enso increase the rainfall difference and landslides register. The daily analysis demonstrates a peak shift between the two variables evaluated, showing that the landslides will need antecedent rainy days to trigger them. There is no clear relationship at the hourly scale because of the reduced number of hourly landslide events registered. Concerning the spatial variation, a hot-spot of landslide is located in the valley's east hill, where the rainfall events with more duration are placed. Another finding is that satellite information is highly correlated with on-site measurements when the antecedent precipitation is evaluated for more than 15 days. 

How to cite: Herrera, D. and Aristizábal, E.: Spatial and temporal distribution of precipitation and its relationship with landslides within the Aburrá Valley, northern Colombian Andes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12621, https://doi.org/10.5194/egusphere-egu24-12621, 2024.

Anthropogenic activities, including the operation of reservoirs and infrastructure expansion, coupled with extreme climatic events are increasing landslide hazards worldwide, but information on the detailed impact of these factors on slope stability is often lacking. In-situ monitoring systems in these potential landslide-prone areas are often unavailable, challenging landslide hazard assessment. This study comprises a multi-scale and multi-sensor satellite remote sensing approach in combination with advanced statistical methods to investigate the life cycle of the catastrophic Hoseynabad-e Kalpush landslide failure that occurred in March-April 2019 in Semnan province of North Central Iran. The landslide occurred on the adjacent slope of a nearby reservoir built in early 2013 following an exceptional precipitation period in the spring of 2019. The failure resulted in the damage of more than 300 houses, of which 163 had to be evacuated due to the severity of the destruction.

In our remote sensing approach, we first derived the spatiotemporal evolution of the pre-, co- and post-failure landslide kinematic fields using Digital Image Correlation based on PlanetScope 3-m resolution data (November 2018 and May 2019) and Multi-temporal InSAR using ascending and descending orbits Envisat ASAR (July 2003 to September 2010) and Sentinel-1 (October 2014 to December 2021) acquisitions. Remote sensing results are then integrated with advanced statistical and clustering approaches to derive trends and seasonality in the time series of the analyzed remote sensing data before correlating the results with external triggering factors. Long-term monthly cumulative precipitation observations (2000-2022) were obtained from The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). The reservoir water level was derived by a GIS-based approach using Landsat-8 (April 2013 to August 2016), PlanetScope (August 2016 to December 2021) data and the Shuttle Radar Topography Mission (SRTM) 1 arc-second global digital elevation model.

Our results suggest that the impoundment of the recently built reservoir reactivated the previously relict landslide and triggered a retrogressive destabilization mechanism. During the pre-failure creeping, the landslide stability conditions permanently degraded. The combination of exceptional precipitation of 2019 and the sudden increment of pore-water pressure, was the final trigger of the landslide main failure in March of that same year in what is a typical deep-seated failure mechanism. In the aftermath, the landslide was still active, with trends in displacement rate comparable to the pre-failure phase, which decreased until its final stabilization in the second half of 2021. The outcomes of this study reveal the complex interactions between reservoir water level changes and extreme precipitation events in influencing landslide kinematics and elevating the hazard of landslide reactivation and failure. Thus, the investigation of the Hoseynabad-e Kalpush landslide case is also relevant for other settings where artificial reservoirs have been built adjacent to relict landslide-prone slopes and where no or only limited in-situ monitoring data are available.

How to cite: Vassileva, M., Motagh, M., Roessner, S., and Xia, Z.: A multi-sensor remote sensing approach for understanding slow-moving landslide reactivation: a case study from North Central Iran following reservoir impoundment and extreme precipitations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13222, https://doi.org/10.5194/egusphere-egu24-13222, 2024.

EGU24-14725 | PICO | NH3.4

Modelling approaches to evaluate the role of climate change in landslide activity in Europe 

Stefano Luigi Gariano and Guido Rianna

Landslides are natural phenomena of different types, with high randomness and variability. They are triggered or influenced by multiple natural phenomena, among which rainfall plays by far the main role in most areas of the world. A relevant complication in the evaluation of landslide activity is global warming, in particular the related ongoing and expected changes in rainfall and temperature patterns. Indeed, due to larger atmospheric retention capability, an increase in the frequency and magnitude of intense rainfall events was already observed in many areas and more significant changes are expected due to climate change. Given the high spatial and temporal variability of the landslides, climate change can affect them in multiple ways and at different temporal and geographical scales.

One of the main approaches used to study the impact of climate change on landslides relies on the adoption of landslide models forced with climate projections generated by physically based, data-driven or hybrid simulation chains. Overall, these studies are based on a similar framework, with a climate modelling chain and a landslide model. The climate chain involves the choice of the Earth System models and concentration scenarios, of a downscaling technique for the production of local assessments, and, in most cases, a bias correction technique with the aim of removing the errors (assumed as systematic) in the assessment of the key climatic variables. The landslide models fed with these variables can be either physically-based (geotechnical, hydrological) or statistical (including empirical analyses or susceptibility assessment), and can operate at different spatial scales, from the slope to the regional/national scale.

In the scientific literature, most of the studies that aimed at evaluating the impact of expected climate and environmental changes to landslides considered case studies in the European continent.

We analyze fifty articles, book chapters and proceedings that proposed modelling approaches in the study of climate-change-landslide relationships, published between 1999 and 2023. We study the spatial scale, the investigated period (both the control and future periods), and the considered climate and landslide variables. Moreover, we study all the components of the climate modelling chain and the features of the landslide models.

We observe an increase in the number of basin-, regional- and national-scale works over the years. In addition, we observe that most of the works focusing on the slope scale are related to the hydro-geotechnical modelling of deep-seated landslides, while most of the basin-scale analyses consider shallow landslides and debris flows and use statistical analyses to model the landslide-climate relationships.

How to cite: Gariano, S. L. and Rianna, G.: Modelling approaches to evaluate the role of climate change in landslide activity in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14725, https://doi.org/10.5194/egusphere-egu24-14725, 2024.

EGU24-20172 | PICO | NH3.4

How does future seasonal variability in rainfall affect landslide-prone areas? 

Mateja Jemec Auflič, Nejc Bezak, Ela Šegina, Peter Frantar, Stefano Luigi Gariano, Anže Medved, and Tina Peternel

During the next few decades, changes in rainfall frequency and magnitude are expected to have major impacts on landscape evolution, social, and economic aspects of human society.

We focus on seasonal rainfall variations by the end of the 21st century to define affected landslide-prone areas, future landslide alerts and the impact of shllow and deep-seated landslides on landscape development in the juncture of the Alpine, Pannonian, and Mediterranean region. For this work, we selected the six regional climate models (RCMs) from the EURO-CORDEX project, with the global climate simulations from CMIP5 (Coupled Model Intercomparison Project phase) driven by the six global circulation models (GCMs).  Of the two available spatial resolutions, i.e., 0.11° (12.5 km) and 0.44° (50 km), we considered the 0.11° spatial resolution with a regular 12.5 km grid with spacing between computational points. Six models were selected from 14 combinations of GCMs and RCMs that differ as much as possible from each other while reflecting as closely as possible the measured values of past climate variables. For this study, we considered climate scenarios variable: the daily rainfall datasets of two Representative Concentration Pathways (RCP), namely RCP4.5 (mid-way) and RCP8.5 (worst-case) for the time window from 1981 to 2100. Daily rainfall data were downscaled from 12.5 km resolution to 1 km. The downscaling of the data was performed daily for all six RCMs. To analyse future climate impact on landslides, the calculated models were divided into three 30-year projection periods: 1st period (near-term) between 2011-2040, 2nd period (mid-century) between 2041-2070, 3rd period (end of the century) between 2071-2100. To show the characteristics of seasonal variations, shorter periods within a year were considered, namely four meteorological seasons: winter (December, January, February), spring (March, April, May), summer (June, July, August), and autumn (September, October, November). Future projections represent a 30-year maximum rainfall from the 30-year baseline period in the past (1981-2010).

The observed changes in the occurrence of shallow landslides are significant, especially in the winter months, where we can expect more landslide-prone areas compared to the baseline period. Shallow landslides will have a greater impact on the landscape in spring and summer than deep-seated landslides, especially in vineyards.

Funding

This work was supported by the by the Slovenian Research and Innovation Agency (the research project J1-3024). Additional financial support was provided by the project “Development of research infrastructure for the international competitiveness of the Slovenian RRI space – RI-SI-EPOS” (co-financed by the Republic of Slovenia, Ministry of Education, Science and Sport and the European Union from the European Regional Development Fund).

Reference

Jemec Auflič, M., Bezak, N., Šegina, E. et al. Climate change increases the number of landslides at the juncture of the Alpine, Pannonian and Mediterranean regions. Sci Rep 13, 23085 (2023). https://doi.org/10.1038/s41598-023-50314-x

How to cite: Jemec Auflič, M., Bezak, N., Šegina, E., Frantar, P., Gariano, S. L., Medved, A., and Peternel, T.: How does future seasonal variability in rainfall affect landslide-prone areas?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20172, https://doi.org/10.5194/egusphere-egu24-20172, 2024.

EGU24-703 | ECS | Orals | NH3.5 | Highlight

Integrated Monitoring and Multi-Hazard Early Warning System for Himalayan Region: Insights from the Chamoli Disaster of 2021 

Anil Tiwari, Kalachand Sain, and Amit Kumar

The material/rock failure is not a sudden progression but is preceded by multiple progressive nucleation phases during which relaxation or rearrangement of material leads to creep and accelerates with time before any major rupture. The monitoring of Himalayan surficial dynamics is challenging and expensive to access for scientific research purposes. The unfelt destructions produced by the surficial mass movement activities can only be recognized by satellite images if other monitoring is not possible. We focused on the Chamoli region, which is the most vulnerable or hazard-prone region in the NW Himalaya. Recently, on 7th February 2021, a huge rock-ice mass detached from the Raunthi peak at a height of 5600 m in the Chamoli district of Uttarakhand Himalaya. We found several pre-collapse and unfelt activities,in a post-mortem study, which were recorded at nearby highly sensitive broad-band seismic stations and radon detector instruments. The integrated study of the recorded signatures allows us to reconstruct the complete dynamic time-dependent nucleation phases, which intensify as time gets closer to the main detachment. Continuous monitoring of vulnerable regions, coupled with the identification and characterization of precursory signals, holds the fundamental clue for hazard mitigation. After the Chamoli disaster, we are more focused on monitoring unfelt activities and anomalies linked to hazards in the proximity of potentially endangered zones and also planning to deploy multi-parametric instruments such as automatic weather stations (AWS), broad-band seismometers (BBS), automatic water level recorders (AWLR) and infrasound array for real-time monitoring and integrated analysis with a view to forewarn against the hazards in the Himalayan terrain. The dense network of sensors will allow us to collect high-quality data and crucial information as a way forward for disaster mitigation and societal benefit.

How to cite: Tiwari, A., Sain, K., and Kumar, A.: Integrated Monitoring and Multi-Hazard Early Warning System for Himalayan Region: Insights from the Chamoli Disaster of 2021, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-703, https://doi.org/10.5194/egusphere-egu24-703, 2024.

EGU24-3808 | ECS | Orals | NH3.5

The mountains are falling and I must go: paraglacial landslide response to glacier debuttressing in southern Alaska 

Jane Walden, Mylène Jacquemart, Bretwood Higman, Romain Hugonnet, Andrea Manconi, and Daniel Farinotti

Glacier mass loss due to anthropogenic climate change has far-reaching implications, one of which is the destabilization of paraglacial slopes. The buttressing force, or the support provided by the glacier to adjacent valley walls, changes and eventually decreases to zero as glaciers dwindle. However, the processes governing this (de-)buttressing, the amount of support glaciers can provide, and to what extent glacier retreat is responsible for landslide (re-)mobilization are still poorly understood. Paraglacial landslides can be hazardous, especially in the proximity of deep water, where a catastrophic failure has the potential to produce a tsunami.

We investigated eight large (roughly 20 to 500 million m3) paraglacial landslides in southern Alaska, a region which is experiencing some of the fastest glacier retreat worldwide. The selected landslides have varying degrees of ice contact: some are still experiencing active glacier retreat and thinning, others have already lost contact with the glacier. One of the selected landslides has undergone catastrophic failure, the others have not. We reconstructed the deformation history of the eight sites using Landsat images from the 1980s to present and automated and manual feature tracking. The slope evolution was then compared to ice thinning rates, ice velocity changes, the proximity of the landslide to the glacier terminus, environmental conditions, and seismic energy. 

We found that both thinning and retreat are sufficient conditions for landslide (re-)activation. In two cases we documented periods of acceleration for slopes where ice is still present at the landslide toe but thinning rapidly. In two further cases, substantial thinning did not correspond to any detectable motion. In four cases we observed a rapid retreat of the glacier terminus as the glacier retreated progressively up-fjord which led to the sudden onset of slope motion. This acceleration suggests decreased stability, which may be important in close proximity to water-filled basins, where rapid retreat due to calving is common and catastrophic landslides can cause tsunamis if they impact the water. The association of reduced glacier-slope contact, especially at rapidly retreating termini, with accelerated slope deformation suggests that buttressing is indeed an important stabilizer for paraglacial slopes. Furthermore, the off-and-on nature of deformation suggests there are critical thresholds for buttressing that, when crossed, leave slopes prone to rapid change.

How to cite: Walden, J., Jacquemart, M., Higman, B., Hugonnet, R., Manconi, A., and Farinotti, D.: The mountains are falling and I must go: paraglacial landslide response to glacier debuttressing in southern Alaska, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3808, https://doi.org/10.5194/egusphere-egu24-3808, 2024.

EGU24-3812 | Orals | NH3.5

Millions of years of landslides in the Patagonian tableland 

Tomáš Pánek, Jakub Kilnar, Michal Břežný, and Diego Winocur

Dating the lifespan of slow-moving landslides poses a major challenge, typically limited to the most recent slope evolution within maximally 103 to 104 years. The Patagonian tableland, characterized by plateau basalts overlying weak sedimentary and volcaniclastic rocks, ranks among Earth's largest landslide provinces. Certain contiguous landslide areas, shaped mainly by rotational slides and spreads, exceed 1000 km2, affecting hundreds of kilometers of mesa escarpments. Our new landslide mapping in eastern Patagonia has allowed us to establish an unprecedentedly long history of landslide evolution, utilizing cross-cutting relationships with dated chronological markers such as glacial moraines and trimlines, lacustrine and marine paleoshorelines, and lava flows. Our findings indicate that the escarpments of the Patagonian plateaus primarily evolved in a retrogressive mode. Both mesas within (or nearby) and outside Pleistocene ice limits involve landslides with topographic footprints that have persisted for over 1 Ma; the oldest documented landslide rim is overlain by a lava flow with a 40Ar/39Ar age exceeding 5 Ma. Even in the most arid parts of the Patagonian tableland, repeated landslide reactivations occurred in the Quaternary, including the Late Holocene. In the western glaciated area, this is likely due to glaciation/deglaciation pulses, while in the eastern extraglacial part, it is probably associated with wetter periods linked to the strengthening of the eastern Atlantic circulation. We conclude that the Patagonian tableland boasts the longest documented landslide topographic footprints on Earth. Future research should prioritize high-resolution (direct radiometric) dating of landslide (re)activations and their correlation with paleoenvironmental changes.

How to cite: Pánek, T., Kilnar, J., Břežný, M., and Winocur, D.: Millions of years of landslides in the Patagonian tableland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3812, https://doi.org/10.5194/egusphere-egu24-3812, 2024.

EGU24-3817 | Posters on site | NH3.5

Failed Patagonian tableland: landslides distribution and controls 

Jakub Kilnar, Tomáš Pánek, Michal Břežný, and Diego Winocur

Argentinian Patagonia is formed mostly by tableland relief created by Cenozoic basaltic efusions, general uplift and relief inversion. The tableland is vastly effected by landslides. Using TanDEM-X we manually maped 30 000 km2 of landslides in the Patagonian tableland and conducted spatial analysis of their distribution and controls. Based on relative dating to lava efusions, glaciation and paleoshorlines we propose, that the landslide activity in the region spans across several millions of years. In contrary to general knowledge of landslide distribution, most of the landslides in the Patagonian tableland are located in low-seismicity, tectonicaly stable, semiarid to arid conditions. We propose, that the leading landslide distribution control is the tableland stratigraphy: basaltic caprock overlaying weak sedimentary and volcanoclastic rocks. The caprock protects the underlying weak rocks and thus it becomes elevated above the surroundings over time, forming plateaus and mesas. As long as the topography of the formed tableland becomes high enough to laterally expose underlaying weak rocks, the tableland margins becomes unstable and collapse. It starts as lateral spreading a rotational landslides and later often evolve to flow-like mass movements. Many of the plateaus and mesas in the Patagonian tableland are fringed by almost continuous landslides. Some mesas are already completly consumed by landslides. This study helps to understand distribution and evolvement of landslides in volcanic tablelands.

How to cite: Kilnar, J., Pánek, T., Břežný, M., and Winocur, D.: Failed Patagonian tableland: landslides distribution and controls, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3817, https://doi.org/10.5194/egusphere-egu24-3817, 2024.

EGU24-4203 | Orals | NH3.5

Development of counterscarps by flexural toppling of schist in the Bedretto valley, Swiss Alps 

Masahiro Chigira, Satoru Kojima, Andrea Pedrazzini, Fei Li, and Michel Jaboyedoff

We investigated the geological structure and the development of DGSD in the south side of the Bedretto Valley, Swiss Alps by field survey, topographic analysis, trenching, and 14C dating.

The Bedretto valley has major slope breaks approximately 300 m above the current valley bottom, which separate the area into two domains. Above the slope breaks, and in the catchments of the tributaries of the Bedretto valley, large flexural toppling occurs with counterscarps and troughs on two ridges between tributaries. Their hinges expose on the side of each ridge to suggest that the flexural toppling reaches to the depth of 200 m. The two large flexural toppling accompanied settling down of a wedge-shaped ridge top, which is bounded by two face-to-face normal faults. Below the slope breaks and on the side slopes of Bedretto valley, smaller but sharper counterscarps and terraces, which are of the incipient stage of counterscarps, develop. These counterscarps and troughs appeared by the preferential shearing along tectonic faults, which are pervasive in the area with a ~30 m average spacing. They are nearly parallel to the steeply-dipping schistosity; the faults may originate as lateral faults but reactivated as normal gravitational faults.

Deformation of the trenched sediments suggests that the flexural toppling occurred intermittently along a fault during three events, in which the first event had the largest dip slip of 30 m, much larger than the displacements of the subsequent events.

The third event at least was probably induced by an earthquake shaking, which is strongly suggested by the injection of fault gouge into the overlying sediments in the trough. Such injection should have been caused by pore pressure build up during earthquake shaking.

How to cite: Chigira, M., Kojima, S., Pedrazzini, A., Li, F., and Jaboyedoff, M.: Development of counterscarps by flexural toppling of schist in the Bedretto valley, Swiss Alps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4203, https://doi.org/10.5194/egusphere-egu24-4203, 2024.

EGU24-5228 | ECS | Orals | NH3.5

Influence of structural geology on rock slope failure in a paraglacial environment: insights from the Southern Swiss Alps 

Alessandro De Pedrini, Andrea Manconi, Christian Ambrosi, Federico Agliardi, and Christian Zangerl

The onset and development of large rock slope failures in alpine environments are influenced by a combination of multiple factors, including lithology, inherited structural features on different scales, and the morpho-climatic history of the region. In the Southern Swiss Alps, seven large rock slope failure accumulations can be recognized along the five valleys north of Bellinzona, (Riviera, Leventina and Blenio in Canton Ticino, Calanca and Mesolcina in Canton Graubünden).  
The region exposes a predominance of crystalline rocks as orthogneiss and paragneiss with similar mechanical characteristics, an aspect that limits the lithological control on the rock slope failures. In addition, the availability of detailed geochronological documentation of both glacial retreat following the Last Glacial Maximum LGM and the major slope collapses motivated the search for a potential correlation, which, however, has not been found (De Pedrini et al. 2023). 
For this reason, slope failures in this region are potentially controlled by the peculiar structural setting. 
In this work, we aim at investigating the impact of structural geology on style of activity and timing of the rock avalanches and deep rockslides of the region. We rely on a catalog of the instabilities (Ambrosi and Czerski, 2016 and De Pedrini et al. 2023) and lineament mapping based on the visual interpretation on 0.5 to 2 m resolution hillshade (swissALTI3D multidirectional Hillshade, Federal Office of Topography swisstopo) and stereo-photogrammetry of aerial strips (Image strips swisstopo, Federal Office of Topography swisstopo). The manual tracing of lineaments is compared with an automatic lineaments tracing performed on surface models of Switzerland in the form of a classified point cloud (swissSURFACE3D, Federal Office of Topography swisstopo). Knowledge on structural lineaments and site-specific field surveys allow us to identify the proper structural setting for each large rock slope failure (already collapsed, active or dormant), and to study structural patterns that may promote slope response after deglaciation at regional scale.
The results of this analysis, aimed at the definition of the influence of glacial retreat plus the influence of structural geology, could provide an additional instrument to the comprehension of the paraglacial slope response in crystalline rocks and could thus represent an added value for long-term hazard assessment.

How to cite: De Pedrini, A., Manconi, A., Ambrosi, C., Agliardi, F., and Zangerl, C.: Influence of structural geology on rock slope failure in a paraglacial environment: insights from the Southern Swiss Alps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5228, https://doi.org/10.5194/egusphere-egu24-5228, 2024.

EGU24-5417 | ECS | Posters on site | NH3.5

Numerical modeling of collapsed deep-seated gravitational slope deformations: insights from Velka Fatra Mts., Slovakia 

Andrius Toločka and Veronika Kapustová

Large-scale deep-seated gravitational slope deformations (DSGSDs) are common but not highly investigated phenomena around the world. In the Carpathian Mountains, they played an important role during the Quaternary evolution of typical core mountain ridges formed by crystalline basement and surrounded by Mesozoic deposits. There is evidence that most of the biggest catastrophic rock slope failures (collapses) in the Carpathian Mountains appeared exactly in areas that are affected by DSGSDs. Two DSGSD-affected slopes (Brdo and Žlebiny) on the northeast side of the Velka Fatra Mountains (Western Carpathians, Slovakia) have been subjected to a detailed investigation involving geomorphic mapping, remote sensing analysis, structural data collection, and numerical modeling. To improve our understanding of these gravity-induced processes, we performed a back-analysis of collapsed DSGSDs through a 4-stage continuum-based finite-element model set up using the RS2 code (Rocscience). We used geomechanical rock data from fieldwork and previous laboratory tests, as well as interpretation in RSData software (Rocscience), to obtain the major rock mass parameters for the models. Results show that these DSGSDs are strongly predisposed by regional geological structures given by the intersection of bedding planes, joint sets, and thrust faults. The numerical modeling approach and performed back-analysis have enabled a better view of the development of these deep-seated slope failures in the Velka Fatra Mountains. It suggests a high diversity of mechanisms leading to the origin of these DSGSD cases. The main causal factors influencing their development have been bedrock structure, the lithological composition of dolomite and limestone layers, thrust faulting, and, finally, deep weathering of the rock mass. Both cases have deep basal shear zones and a few series of gravitational faults associated with complex joint sets. According to the numerical modeling results, Brdo DSGSD shows a typical scenario of a symmetrical sackung surrounded by shallow landslide areas, while Žlebiny DSGSD developed into a one-sided deep-seated slide with a few large-scale tilted rock blocks.

How to cite: Toločka, A. and Kapustová, V.: Numerical modeling of collapsed deep-seated gravitational slope deformations: insights from Velka Fatra Mts., Slovakia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5417, https://doi.org/10.5194/egusphere-egu24-5417, 2024.

A fixed point in geodesy is a stable survey point that fulfils the following two conditions: The point is known in coordinates from a previous survey (by position and/or height) and the point is permanently marketed (stabilised) in nature. Fixed points serve as reference points for surveys of all kinds. To determine the coordinates of the fixed points in the modern European reference system ETRS89, not only all previously measured GNSS vectors are used, but also all terrestrial observations measured since 1906, i.e. direction, elevation angle and distance measurements (Otter et al., 2017). More than 20.000 individual RTK measurements on these fixed points by using APOS (Austrian Positioning Service) complete the measurement dataset. Approximately 60.000 triangulation points (TPs) form a three-dimensional point network throughout Austria, whereas about 70 % of all TPs have multiple measurements. Fixed points should be stable, but this is not always the case, as fixed points are often influenced in their spatial position by gravitational mass movements, among other factors.

We have interpreted the entire elevation model/hill shade of Austria (1-metre resolution, based on ALS-data) and mapped all DSGSDs that manifest themselves geomorphologically in the terrain. This data set was intersected with the fixed points in order to identify those points that lie within a DSGSD. By analysing the results of the individual fixed point survey epochs, conclusions can be drawn about deformation rates of mass movements after excluding possible sources of error and statements can be made retrospectively up to the year in which the particular point was created (Otter et al., 2017).

Overall the fixed point measurements of the Federal Office of Metrology and Surveying Austria (BEV) represent a high quality and long term dataset that stands for its own and can support other slope monitoring methods. The interpretation of the dataset concerning slope deformations is not trivial but can deliver information of the range of movements over decades with uncertainties of 0 to 1.5 cm.

By combining different data sources (InSAR, ALS, in-situ measurements, fixed points, ...) we can present a preliminary, comprehensive data set on the activity status and often associated deformation rates of DSGSDs in Austria.

References:

Otter, J.; Imrek, E.; Melzner, S. (2017) Geodätische Grundlagenvermessung als Werkzeug in der Naturgefahrenanalyse in: Wimmer-Frey, I.; Römer, A.; Janda, C. [Hrsg.] Angewandte Geowissenschaften an der GBA. Wien, S. 147–152.

 

 

How to cite: Ostermann, M. and Blauensteiner, F.: Analysing geodetic fixed point survey time series to evaluate the long-term activity of DSGSDs in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5578, https://doi.org/10.5194/egusphere-egu24-5578, 2024.

EGU24-6268 | Posters on site | NH3.5

Enhancing rockfall modelling through an integrated workflow, from source area definition to susceptibility zoning 

Roberto Sarro, Mauro Rossi, Paola Reichenbach, Pablo Vitali Miranda-Garcia, and Rosa María Mateos

The main complexity of rockfall modelling lies in the need for a series of dedicated methodological choices and assumptions. Despite specific aspects of modelling have been largely discussed in the literature, a comprehensive methodology to assess susceptibility posed by rockfalls is still missing. To fill this gap, we have proposed a novel workflow in this study, including methods for identifying source areas, deterministic runout modelling, classifying runout modelling output to establish an objective rockfall probabilistic susceptibility zonation, and comparing and validating the results. This methodology is applied to the island of El Hierro (Canary Islands, Spain), where rockfalls pose a significant threat to structures, infrastructure, and the population.

In the first stage, three different approaches were proposed to identify rockfall source areas, ranging from scenarios with limited data availability to those with extensive topographic, geological, and geomorphological information. The first approach employed a morphometric criterion, establishing a slope angle threshold to identify source areas. The second approach used a statistical method employing Empirical Cumulative Distribution Functions (ECDF) of slope angle values. The third method employed a probabilistic modelling framework that combined multiple multivariate statistical classification models, using mapped source areas as dependent variables and thematic information as independent variables.

Subsequently, a rockfall simulation was carried out using a physically based model using the maps of the three source areas as input. A key result of the rockfall modelling simulations was the rockfall trajectory count maps. These maps, highlighting areas prone to rockfall on El Hierro, indicated the probability that a given pixel would be affected by these processes.

Then, this study also explores the strategies to validate the rockfall susceptibility model outputs, using different types of inventories. Therefore, to get susceptibility maps with a probabilistic approach, two classification methods were applied: unsupervised and supervised statistical techniques using distribution functions. The unsupervised classification used only the raster map of rockfall trajectory counts, while the supervised classification considered additional data on areas already affected by rockfalls.

Diffused metrics comparing modelled and observed values (i.e., ROC plots and correspondent AUCROC) can be used to show the performances of susceptibility models, regardless the adopted classification approach. Finally, the six susceptibility maps were compared to emphasize the impact of source area definition on the distribution of rockfall trajectories.

In summary, the methodology proposed provides guidance for an objective and reliable rockfall modelling, supporting civil protection, emergency authorities, and decision-makers in evaluating and assessing potential rockfall impacts. This contributes to enhanced rockfall hazard assessments and improved mitigation strategies on the island of El Hierro and potentially in similar geological settings globally.

How to cite: Sarro, R., Rossi, M., Reichenbach, P., Miranda-Garcia, P. V., and Mateos, R. M.: Enhancing rockfall modelling through an integrated workflow, from source area definition to susceptibility zoning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6268, https://doi.org/10.5194/egusphere-egu24-6268, 2024.

EGU24-6335 | Orals | NH3.5 | Highlight

Infrasound analysis of break-off events  from Planpincieux glacier, Mount Blanc, Italy 

Emanuele Marchetti, Fabrizio Troilo, Paolo Perret, Giacomo Belli, Duccio Gheri, and Claudia Sanchez

Glacier break-off events constitute a severe hazard in Alpine regions and their effects are expected to increase soon because of climate changes. Within this rapidly changing scenario, the development and implementation of new monitoring solutions and warning systems, able to detect collapses and possibly estimate the volumes, is of critical importance.

In this paper we present the analysis of avalanching activity from Planpincieux glacier (Aosta valley) through infrasound data collected by a small aperture (~ 150 m) array deployed at short distance (~ 2000 m) from the hanging front. The analysis is performed over five time periods between August 2020 and December 2022 summing up into 360 days. From a data set of confirmed events, infrasound wave parameters (intensity, peak amplitude, frequency and duration) are compared with collapse volumes estimated from photogrammetry and experimental relations are defined.

Morerover, characteristics of infrasound signals of confirmed events are used to extract signals that are likely produced by collapses from the whole dataset of infrasound detections and a volumetric flux of collapses from the front of the Planpincieux glacier is derived through time.

 

How to cite: Marchetti, E., Troilo, F., Perret, P., Belli, G., Gheri, D., and Sanchez, C.: Infrasound analysis of break-off events  from Planpincieux glacier, Mount Blanc, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6335, https://doi.org/10.5194/egusphere-egu24-6335, 2024.

EGU24-6627 | ECS | Posters on site | NH3.5

Landslides on the growing folds of the Kura fold-and-thrust belt (Azerbaijan, Georgia) 

Michal Břežný, Tomáš Pánek, Hans-Balder Havenith, and Alessandro Tibaldi

Rising hillslopes in the active fold-and-thrust regions present new landslide-prone slopes. However, studies investigating landslides in newly formed fold-and-thrust belts are limited. In this research, we analyse landslide occurrences in the Kura fold-and-thrust belt, a geologically active region at the southern edge of the Greater Caucasus. This area has experienced significant tectonic shaping over the last 2-3 million years, affecting Miocene to Quaternary sediments. Using satellite imagery, we identified about 1600 landslides, a quarter of which are active. These landslides, although occupying less than 1% of the land, are predominantly found at higher elevations and areas with greater relief. They mainly occur in regions elevated by tectonic forces, especially on steep anticlines and valley slopes cut by active faults. Our findings lead to a conceptual model for the temporal evolution of landslide patterns in weak sediment-based fold-and-thrust belts: 1) Initially, slow deformations at thrust fronts lead to landslides in deep valleys intersecting the uplifting hanging walls. 2) As anticlines rise and steepen, they become more prone to planar sliding when dip slopes exceed friction angle, and valley development creates additional dip slopes resulting in widespread landslides. 3) Finally, erosion lowers relief, forming badlands and reducing landslide occurence.

How to cite: Břežný, M., Pánek, T., Havenith, H.-B., and Tibaldi, A.: Landslides on the growing folds of the Kura fold-and-thrust belt (Azerbaijan, Georgia), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6627, https://doi.org/10.5194/egusphere-egu24-6627, 2024.

EGU24-6726 | Orals | NH3.5

A modified Voellmy rheology for modeling rock avalanches 

Stefan Hergarten

Voellmy's rheology was originally developed for snow avalanches in the 1950s. However, it has also been widely applied to rock avalanches and to debris flows. In its original form, Voellmy's rheology assumes that the effective friction is the sum of Coulomb friction and a velocity-dependent term. While the Coulomb friction term is necessary for letting avalanches stop after a finite time, it causes problems with regard to the long runout of huge rock avalanches. This long runout requires Coulomb friction coefficients much lower than typically assumed for granular media, which finally result in unrealistically smooth morphologies of the deposits. In this presentation, numerical simulations with a recently published modified version of Voellmy's rheology are shown and compared to the conventional version. The modified version assumes two distinct regimes of Coulomb friction and velocity-dependent friction with a transition at a critical velocity derived from the concept of random kinetic energy. The modified rheology explains the long runout of huge rock avalanches without assuming an artificially low Coulomb friction coefficient. Furthermore, it produces hummocky deposit morphologies even with isolated hills similar to toma hills.

How to cite: Hergarten, S.: A modified Voellmy rheology for modeling rock avalanches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6726, https://doi.org/10.5194/egusphere-egu24-6726, 2024.

Landslides, as a ubiquitous type of mass wasting phenomena, occur under various geological and environmental conditions and exhibit diverse failure patterns. Among various factors, weathering has been widely recognised as one of the primary drivers on landslide evolution over geological timescales. However, how weathering induces slope instabilities, including how pre-failure rock mass degradation contributes to the landslide failure development and post-failure deposition of mobilised geomaterials, has not been fully understood. In this study, we develop a novel, physics-based unified computational framework to capture weathering-induced landslide evolution over multiple time scales, from the long-term pre-failure rock mass deformation to the short-term slope rupture and post-failure runout dynamics. Weathering laws and failure criteria are coupled to capture the combined effects of time-dependent strength degradation and strain-driven damage processes, while a frictional velocity-weakening law is adopted to characterise the rapid movement of yielded masses. The non-linear governing equations of landslide dynamics are solved using an implicit particle finite element framework that can model all the landslide stages from the long-term material degradation to short-term failure and runout. We further investigate the effects of weathering conditions (type and rate), geological properties (fracture sets and rock matrix) and slope geometry (angle and shape) on the failure patterns. Our high-fidelity numerical simulations capture the emergence of diverse landslide failure patterns resulting from the complex interplay among rock lithology, fracture distribution, weathering process, and gravitational forcing. Our numerical results show that matrix-dominated weathering tends to produce shallow landslides, while fracture-dominated weathering promotes the occurrence of deep landslides. For fracture-dominated weathering, the orientation of pre-existing fractures and the slope ratio significantly control the failure mode (e.g. falling, toppling, sliding, etc.), which further affects post-failure runout behaviour. Our computational framework opens the door to investigating and understanding weathering-induced rock slope failure evolution across spatial and temporal scales.

How to cite: Wang, L., Loew, S., Gu, X., and Lei, Q.: Emergence of diverse failure patterns in weathering-induced landslides: Insights from high-fidelity particle finite element simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6969, https://doi.org/10.5194/egusphere-egu24-6969, 2024.

In the realm of natural Earth-surface processes, such as mass movements exemplified by rock avalanches, a substantial entrainment of bed material along their trajectory is a common occurrence, amplifying both volume and run-out distance. The heightened mobility of these rapid gravity flows has been frequently ascribed by numerous researchers to the complete or partial fluidization of path material induced by swift undrained loading. An intriguing question arises: are there additional entrainment mechanisms at play in this process? To address this query, we executed a series of flume experiments designed to replicate rock avalanches overriding a saturated bed material. Our experimental findings revealed that the overriding flow induced a state of fluidization in the bed material, rendering it viscous. Furthermore, we observed that the rapid loading by the overriding debris increased pore pressure at the base, although it did not reach the threshold of complete fluidization. Rheological analysis of the bed material unveiled significant shear-thinning behavior, with viscosity diminishing rapidly as shear strain rate increased. Consequently, we posit that the concurrent effects of excess pore pressure at the basal layer and shear-thinning rheology in the flowing mass contributed to the fluidization of bed material and the ensuing extended run-out distance. This discovery offers a plausible natural elucidation for the extraordinary mobility of rock avalanches and holds promise for refining the precision and reliability of numerical simulations through the integration of the viscous model derived from our experimental endeavors.

How to cite: Zheng, Y. and Hu, W.: Flume tests and rheological experiments provide insights into the fluidization of bed material induced by shear thinning during the entrainment of rock avalanches., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7405, https://doi.org/10.5194/egusphere-egu24-7405, 2024.

EGU24-7631 | ECS | Posters on site | NH3.5 | Highlight

Causes, consequences and implications of the 2023 Lake Rasac GLOF, Cordillera Huayhuash, Peru 

Adam Emmer, Oscar Vilca, Cesar Salazar Checa, Sihan Li, Simon Cook, Elena Pummer, Jan Hrebrina, and Wilfried Haeberli

Glacierized Peruvian mountain ranges are experiencing accelerated glacier ice loss, including the second highest mountain range – Cordillera Huayhuash – which has lost about 40% of its glacier area (deglaciated area of approximately 34 km2) since the 1970s. The exposure of a new land is associated with various processes including the formation and evolution of glacial lakes, changing stability conditions of mountain slopes, and rapid mass movements. In this study, we integrate the analysis of meteorological data, remotely sensed images and field observations in order to document the most recent large mass movement-induced glacial lake outburst flood (GLOF) from moraine-dammed Lake Rasac (February 2023). We found that the triggering mass movement (the failure of Rasac arête ridge with an estimated volume of 1.1 to 1.5 ∙ 106 m3) occurred from the frozen rock zone with cold, deep-reaching permafrost and was preceded by several small magnitude precursory events. The stability reduction of the frozen rocks in the detachment zone most likely relates to deep warming, but not to critical conditions of warm permafrost with unfrozen water. Further, we describe the surprisingly short-distanced process chain (attenuated by the Lake Gochacotan located 3.5 km downstream from the detachment zone) and analyze the transport of large boulders with the use of hydrodynamic modelling, revealing that flow velocities > 5 m/s must have been reached in case of translational motion and > 10 m/s in case of rotational motion of the largest transported boulders (diameter > 3.5 m). This study helps us to understand (i) mechanisms, amplification and attenuation elements in GLOF process chains; and (ii) altering frequency-magnitude relationships of extreme processes in rapidly changing high mountain environments on regional scale (both large magnitude rockfalls and GLOFs). Considering the recent Peru-wide GLOF inventory published in 2022, this event corroborates the assumption of increasing frequency of large mass movement-induced GLOFs originating from warming permafrost in recent decades. 

How to cite: Emmer, A., Vilca, O., Salazar Checa, C., Li, S., Cook, S., Pummer, E., Hrebrina, J., and Haeberli, W.: Causes, consequences and implications of the 2023 Lake Rasac GLOF, Cordillera Huayhuash, Peru, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7631, https://doi.org/10.5194/egusphere-egu24-7631, 2024.

EGU24-8202 | ECS | Posters on site | NH3.5

Mapping release and propagation areas of permafrost-related rock slope failures in the French Alps: A new methodological approach at regional scale 

Maeva Cathala, Florence Magnin, Ludovic Ravanel, Luuk Dorren, Nicolas Zuanon, Frederic Berger, Franck Bourrier, and Philip Deline

Permafrost-affected rockwalls are increasingly impacted by the effects of climate change and rising air temperature leading to rock slope failures, threatening human lives and infrastructure. Populations and policy makers need new methods to anticipate these potential hazards and their consequences.  The aim of this study was to propose a mapping approach of susceptible release areas of rock slope failures and resulting runout distances at a regional scale to identify hotspots for hazard assessment.

To do so, we used an inventory of 1389 rock slope failures (volume > 102 m3)recorded in the Mont-Blanc massif from 2007 to 2019 and determined the topographical and permafrost conditions that are most prone to their triggering using a digital terrain model and a permafrost map. These conditions are used in a multi-criteria GIS approach to identify potential unstable slopes at the French Alps scale. Then, the potential release area map is used as input to map the runout of potential events, using a propagation model based on a normalised area dependant energy line principle. The resulting maps of release and propagation areas could be used to point out human assets and lakes which could be impacted by rock slope failure hazards. In this communication we will show how theses maps can be used to identify potential hotspots for a regional hazard assessment.

This work is a first step to identify hot spots for a regional hazard assessment where more detailed analyses will be required to evaluate potential risks at a local scale.

How to cite: Cathala, M., Magnin, F., Ravanel, L., Dorren, L., Zuanon, N., Berger, F., Bourrier, F., and Deline, P.: Mapping release and propagation areas of permafrost-related rock slope failures in the French Alps: A new methodological approach at regional scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8202, https://doi.org/10.5194/egusphere-egu24-8202, 2024.

EGU24-8891 | ECS | Orals | NH3.5

Climate change impact on rock avalanches in metamorphic rock masses in Tyrol, Austria 

Lukas Prandstätter, Christian Zangerl, Christine Fey, Tatiana Klisho, and Herbert Formayer

Rockfalls and rockslides are a common hazard in alpine terrain and are major factor of alpine landscape evolution. They are characterized by a complex combination of geological, hydrological, geomechanical and meteorolocical processes and occur in a wide variety of geological and structural settings and in response to various loading and triggering processes. In the Alps in particular, extremely rapid rock avalanches reaching a volume of several 10000 m3 or more have the potential to cause serious damage to both humans and infrastructure. As global warming progresses, the meteorological and climatological factors that influence rock avalanche formation will change. Especially, in the high mountain environment rock avalanches are strongly influenced by climate change due to thawing of permafrost and the retreat of glaciers. Less obvious is the influence of climate change on the formation of rock avalanches at lower altitudes, and thus there is a need for additional research.

In this study, we investigate the impact of global warming on selected rock avalanche case studies with volumes above several tens of thousands of cubic meters. The study area covers approx. 3400 km2 in the metamorphic rock mass of the Ötztal Stubai Crystalline, the Silvretta and the Glockner Nappes as well as the units of the Engadin Window of the Tyrolian Alps, Austria.

The aim of this work is to identify the processes that led to our case studies and if these processes are influenced by climate change factors, such as changes in temperature, precipitation, freeze-thaw cycles, snow coverage, etc. The climatic factors will be investigated in terms of both their short-term and long-term influence on the trigger mechanisms.

Advanced remote sensing techniques were used on site to carry out small to large-scale investigations. Terrestrial laser scanning (TLS) and Airborne laser scanning (ALS) enables us to create high-resolution recordings of inaccessible rock faces, supported by 3D point cloud analyzing tools. In addition, where TLS campaigns are not possible, we use an unmanned aerial vehicle (UAV) photogrammetry system that provides 3D point clouds and delivers a 3D model of the site. Geological field investigations were performed to record lithological, hydrogeological and structural features. This results in a comprehensive geological model of the failure area. A 3D discontinuity network was developed based on the combined analyses of remote sensing and discontinuity mapping data, providing the basis for structural geological analyses and distinct element modelling studies.

With regard to the above criteria, we have selected several case studies. Most of the case studies are located well above 2500 m above sea level in glaciated or recently glaciated areas. For all case studies, we were able to document at least one rock avalanche event with a volume exceeding several 10000 m3. A high-resolution climate model was created for the documented events. We then began to collect and evaluate the existing literature on the individual case studies.

How to cite: Prandstätter, L., Zangerl, C., Fey, C., Klisho, T., and Formayer, H.: Climate change impact on rock avalanches in metamorphic rock masses in Tyrol, Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8891, https://doi.org/10.5194/egusphere-egu24-8891, 2024.

EGU24-9085 | Orals | NH3.5 | Highlight

Probabilistic rockfall hazard and risk analysis along the El Portal Road in Yosemite National Park (California, USA) 

Federico Agliardi, Paolo Frattini, Greg M. Stock, Teseo Tosi, Camilla Lanfranconi, and Brian D. Collins

Yosemite National Park attracts millions of visitors each year with its stunning landscape, characterized by 1000 m high granite cliffs that are highly susceptible to rockfalls. Between 2010 and 2020, more than 300 rockfalls affected the 12 km long El Portal Road, used by 30% of visitors to enter the park, causing road closures and fatalities. Since National Park policies limit engineering mitigation on natural slopes, risks along roads are managed through traffic practices based on local hazard evaluation.

In this perspective we developed a probabilistic risk analysis workflow, aimed at estimating the annual probability of loss of life for people driving a vehicle along the road. The analysis was carried out for every 10-m-long segment of each travel lane, to and from Yosemite Valley. We based our analyses on 3D rockfall runout simulations performed with the Hy-STONE simulator, and on rockfall event (1857-2022) and vehicle traffic data collected by the U.S. National Park Service. Runout simulations were performed over 18 km2 with a spatial accuracy of 1 m. Simulation parameters were calibrated by back-analysis of past events and validated with field evidence. Fifteen million trajectories were simulated for five volume scenarios (0.01-100 m3), providing local information of transit frequency and kinetic energy.

A probabilistic hazard analysis was developed using the probabilistic rockfall hazard analysis (PRHA) method (Lari et al, 2014), which calculates the kinetic energy that can be exceeded in N years for each road segment. The method integrates different rockfall volume scenarios, with specific return times, in a probabilistic framework accounting for modelling uncertainties. For each considered scenario, the annual rockfall onset frequency was derived by a magnitude-frequency (MF) curve, based on the Yosemite event data from 2010-2020 and combined with a field-based talus MF curve, to redistribute frequency among blocks disaggregated during runout. The annual rockfall frequency at each slope segment was then calculated by combining the onset frequency with the transit frequency provided by runout simulations. The exposure analysis, dependent on block size, vehicle size and speed, considered the probability of a vehicle being in the path of a falling block when it reaches each road segment. Since blocks coming from different sources may converge to a common location based on the 3D topography, we reconstructed the distribution of kinetic energy at each target road segment.

The probability of exceeding specific energy values, combined with the annual frequency of rockfall occurrence, allowed deriving probabilistic hazard curves for each scenario and for the ensemble. Based on expected kinetic energy and considering the number of visitors passing along the road every day as well as assumptions on the vulnerability of vehicles, we calculated the possible annual number of casualties for each road segment and the entire road, to identify the road sectors with the highest risk. Computed risk varies in time with clear weekly and seasonal patterns depending on the number of daily visitors and the weather conditions. Our study will provide park managers with tools to make adaptive decisions for managing risk in dynamically changing conditions.

How to cite: Agliardi, F., Frattini, P., Stock, G. M., Tosi, T., Lanfranconi, C., and Collins, B. D.: Probabilistic rockfall hazard and risk analysis along the El Portal Road in Yosemite National Park (California, USA), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9085, https://doi.org/10.5194/egusphere-egu24-9085, 2024.

EGU24-10312 | Orals | NH3.5

Deep-seated gravitational slope deformations in Sierra Nevada, Spain: insights from InSAR, geomorphic and stability analyses 

Jorge Pedro Galve, Cristina Reyes-Carmona, Federico Agliardi, Mara Cannarozzi, José Vicente Pérez-Peña, Marcos Moreno-Sánchez, David Alfonso-Jorde, Daniel Ballesteros, Davide Torre, José Miguel Azañón, and Rosa María Mateos

Sierra Nevada (Spain) is a mountain range thoroughly studied from a geological-geomorphological perspective due to its anomalously high local relief and the ongoing debate about its origin and geological structure. From the standpoint of slope dynamics, several studies have carried out, but it was not until last year that deep-seated gravitational slope deformations (DSGSDs) were described in this mountain range. Their recognition was facilitated by synergizing geomorphological assessments with data from two well-established techniques: Differential Synthetic Aperture Radar Interferometry (DInSAR) and Landscape Analysis using the normalized channel steepness index (ksn), a geomorphic index commonly used to outline landscape perturbations in tectonically-active mountain ranges. Systematic evaluation of ksn anomalies along rivers illuminated key DSGSD sectors that were studied in detail. This approach resulted in a novel inventory of 17 DSGSDs in the southwestern sector of the range, providing an initial figure of the widespread occurrence of large DSGSDs in Sierra Nevada.

In a second phase, we conducted a detailed study of two slopes affected by DSGSDs in the Poqueira catchment, which provided new insights into Sierra Nevada’s DSGSDs. There, we characterized slope deformations by detailed morpho-structural mapping supported by fieldwork and interpretation of optical and LiDAR-derived imagery, resulting in morpho-structural maps and interpretative cross-sections. Collected data allowed setting up a series of 2DFEM multistage elasto-plastic models, parametrized by laboratory data and field rock mass assessment and validated with field evidence and DInSAR data. The studied cases are characterized by multiple nested landslides that become increasingly shallow, deformed, and active towards the valley. The geometry and kinematics of DSGSDs seem to be partially influenced by the orientation of foliation, indicating rock mass anisotropy, with dip slopes mainly exhibiting translational movements and anti-dip slopes demonstrating prevalence of rotational motions. We tested our initial hypothesis that these slope instabilities in the region were initiated because the development of fluvial incision, favored by the active tectonics and uplifting of the range. Preliminary findings of our analyses suggest that fluvial incision was a key trigger of DSGSDs in Sierra Nevada, but not the only one. Model simulations emphasize that, in addition to fluvial incision, rock mass anisotropy and long-term seismic activity played a crucial role in the onset and accumulation of large deformations of high slopes across the region, favoring the occurrence of significant mass movements. Considering this, rough estimates regarding the timing of incision and seismic activity suggest that initial DSGSD onset took place over a timescale of 104-105 years.

How to cite: Galve, J. P., Reyes-Carmona, C., Agliardi, F., Cannarozzi, M., Pérez-Peña, J. V., Moreno-Sánchez, M., Alfonso-Jorde, D., Ballesteros, D., Torre, D., Azañón, J. M., and Mateos, R. M.: Deep-seated gravitational slope deformations in Sierra Nevada, Spain: insights from InSAR, geomorphic and stability analyses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10312, https://doi.org/10.5194/egusphere-egu24-10312, 2024.

EGU24-10488 | Posters on site | NH3.5

Advanced Discontinuity Detection Algorithm for Geological Formations Using High-Density Point Cloud Data 

Antonin Chale, Michel Jaboyedoff, and Marc-Henri Derron

Advanced Discontinuity Detection Algorithm for Geological Formations Using High-Density Point Cloud Data

Antonin Chale, Michel Jaboyedoff, Marc-Henri Derron

Geological hazard analysis relies on precise identification and characterization of discontinuities in rock formations, crucial for evaluating rock stability. While techniques such as Structure-from-Motion (SFM) and Light Detection and Ranging (LiDAR) have significantly advanced high-density 3D point cloud (PC) data acquisition, detecting structural irregularities in complex geological formations remains a challenge. We have developed a new discontinuity detection algorithm that emulates human visual perception. The algorithm employs multi-angle scanning, point cloud optimization techniques, and efficient multiprocessing to comprehensively survey the point cloud. Density maps are generated to identify and determine the orientation of discontinuities, proving effective in both synthetic models and real LiDAR data. The algorithm comprises three primary steps: an initial point cloud scan, density map generation, and visualization of discontinuities with their initial orientation. A secondary scan focuses on the density map, projecting data into a 2D representation to detect a second vector orientation, crucial for identifying discontinuity sets. Thanks to the previous steps we can deduce the orientation of the discontinuity sets. While the algorithm’s capability to handle both synthetic and real-world data sets highlight its potential significance in structural analysis, ongoing work aims to enhance its applicability for larger and more complex datasets. But also, the possibility of extracting the points involved in the different discontinuity sets.

 

References:

Adrián J. Riquelme, A. Abellán, R. Tomás, M. Jaboyedoff, (2014)  " A new approach for semi-automatic rock mass joints recognition from 3D point clouds," Computers & Geosciences, Volume 68, 2014, Pages 38-52.

Matthew J. Lato, Malte Vöge, (2012) "Automated mapping of rock discontinuities in 3D lidar and photogrammetry models," International Journal of Rock Mechanics and Mining Sciences, Volume 54, 2012, Pages 150-158.

How to cite: Chale, A., Jaboyedoff, M., and Derron, M.-H.: Advanced Discontinuity Detection Algorithm for Geological Formations Using High-Density Point Cloud Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10488, https://doi.org/10.5194/egusphere-egu24-10488, 2024.

The steep terrain in mountainous areas poses a significant threat to people's safety due to frequent geological hazards(e.g., rockfall and slope collapse), making effective management, monitoring, and timely issuance of alerts and warnings are crucial for highway authorities. Previous studies focus on studying the rainfall thresholds for possible rockfall occurrence. Recently, machine learning using seismic signals has been applied to detect rockfall events and monitor rockfall activity. However, supervised machine learning algorithms have relied on predefined labels, and the limited accumulation of data makes predicting model reliability challenging. The time-consuming model training can limit the practical application of the above models. In response to both aforementioned challenges, we first selected the roadside slope with relatively high activity of rockfalls and earthquakes as the study site and installed a seismic station on the crest of the slope. Then, we use an unsupervised machine learning framework to reveal patterns from unlabeled data and cluster seismic signals in continuous seismic records in the single three-component seismic station. Using continuous seismic data over one year, our approach combines a deep scattering network, features extraction, and features cluster to detect structures of signal segments. To illustrate the framework, a deep scattering network performs convolution and pooling on the three-component seismic signal data to extract multiscale information and construct scattering coefficients. For feature extraction, four different algorithms were employed: principal components analysis (PCA), independent components analysis (ICA), singular value decomposition (SVD), and Uniform Manifold Approximation and Projection (UMAP). Subsequently, we cluster the primary features using unsupervised learning algorithms such as K-means and Gaussian Mixture Model(GMM). We demonstrate the group categories belonging to rockfall events with in-situ data time-lapse images and videos. An approach proposed in this study could achieve rapid model training for building on-site rockfall warning systems using only single-station seismic records. Our high capability recognition model of rockfall events is ready to be implemented globally with high rockfall activity.

 

Keywords: unsupervised machine learning, deep scattering network, rockfall, seismic records, on-site early warning 

How to cite: Li, Y.-R. and Chao, W.-A.: A fast unsupervised deep learning algorithm using seismic records of a single station for roadside rockfall recognition, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14088, https://doi.org/10.5194/egusphere-egu24-14088, 2024.

EGU24-15526 | ECS | Posters on site | NH3.5

Investigation into rockslides by the adaptive rock discrete fracture analysis (RDFA) method 

Bin Gong and Tao Zhao

The rock discrete fracture analysis (RDFA) method was proposed as a combination of the rock failure process analysis method and the discrete element method. Leveraging the statistical strength theory and contact mechanics, it can effectively capture the intricate continuum-discontinuum behaviors inherent in rock mechanics, encompassing fracture and fragmentation phenomena. Enabled by a sophisticated nodal updating scheme, RDFA can dynamically adjust nodes at critical crack tips in accordance with strength criteria, facilitating accurate modeling of zero-thickness crack initiation and propagation. Noteworthy is its capacity to accommodate the inherent heterogeneity of rock masses, enabling holistic consideration of localized damage and fine crack development. Rigorously validated through the Brazilian disc and uniaxial compression tests, RDFA consistently aligns with the analytical solutions and experimental data. After that, it was applied to analyze the rockslide characteristics at the Anshan Road station in the Qingdao metro, China, and illuminated crucial insights. The results show that in the presence of 60° oriented joints with 5m spacing, the high stress concentration primarily emerged at the slope toe, leading to the localized tensile damage and the formation of a sliding surface. Subsequent rock sliding induced compression and collision among blocks, precipitating continuous failure within the sliding body. Additionally, the presence of intermittent joints notably contributed to progressive rockslide, particularly triggering the localized failures in the lower part of the slope.

How to cite: Gong, B. and Zhao, T.: Investigation into rockslides by the adaptive rock discrete fracture analysis (RDFA) method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15526, https://doi.org/10.5194/egusphere-egu24-15526, 2024.

EGU24-15711 | ECS | Orals | NH3.5

Rockfalls risk assessment along a E45 motorway section in South Tyrol (Italy) 

Francesco Lelli, Leonardo De Rosa, Lucia Simeoni, Francesco Ronchetti, Vincenzo Critelli, and Alessandro Corsini

The E45 motorway in South Tyrol (Italy) is exposed to rockfalls in many locations. For this reason, a significant number of rockfall risk reduction measures (nets, barriers, etc) has been progressively installed since its construction. Planning of further mitigation and monitoring measures can benefit from the assessment over a large-area and at adequate scale, of the exposure to rockfalls and of the associated risk, a piece of knowledge that this study has provided for a 13.5 km motorway section.

First, susceptibility mapping has been carried out using bivariate statistical methods with supporting evidences from an inventory of rockfalls occurrences covering the period 1993 to 2020. This has allowed to define potential rockfall detachment zones located upslope the E45. For each zone, rockfall runout modelling with RocPro3D software by considering 0.5 m and 2.0 m blocks diameter and high-resolution Lidar DTM has allowed to assess potential interactions between rockfall and different motorway structures (i.e. viaduct piers, tunnel entrances and road embankments). Spatial-temporal frequency of 2 m diameter rockfall (i.e. n° of rockfalls per year and unit area) has been assessed on the basis of the inventory of rockfalls occurrences and of the overall extent of slopes resulting highly susceptible to rockfalls. On such basis, the expected rockfall triggering frequency (n° events/year) in each source area has been assessed by considering its extension.  Hazard has been assessed by using an heuristic matrix-based approach that combines frequency and geomechanics (expressed by the GSI) of the rock masses. Rockfall spatial impact frequency, energy and bounce height determined by runout models have been used to establish exposure and vulnerability (i.e. expected damage level) of the motorway infrastructures. Finally, risk has been evaluated in function of hazard and vulnerability (by using combination matrices tailored to each type of interaction of rockfall – on infrastructures taken into consideration.

Results allowed us to determine and map that, out of the total 13.5 km motorway section considered, about 1.5 km for 0.5 m diameter blocks, and about 3.2 km considering 2.0 m diameter blocks, should be considered at high to very high rockfall risk. This result is also relevant with respect to the identification of priorities for more in-depth slope-scale surveys and monitoring of rockfalls in the perspective of further structural and non-structural mitigation measures implementation.

How to cite: Lelli, F., De Rosa, L., Simeoni, L., Ronchetti, F., Critelli, V., and Corsini, A.: Rockfalls risk assessment along a E45 motorway section in South Tyrol (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15711, https://doi.org/10.5194/egusphere-egu24-15711, 2024.

EGU24-16064 | ECS | Posters on site | NH3.5

Back analysis of the 2023 rockfall event of Martigny (Switzerland): trajectography prediction to future potential hazard along road 

Tiggi Choanji, Antonin Chale, Wei Liu, Li Fei, François Noël, Marc-Henri Derron, and Michel Jaboyedoff

In this study, we back analysed a rockfall that occurred on a road in Martigny, Switzerland, on 15 March 2023 to determine the trajectory involving block fragments of approximately 43 m3 in total with block maximum 15 m3 and to identify factors that could contribute to future rockfalls in the area. A combination of remote sensing techniques such as LiDAR, photomosaic, and SfM (Structure for Motion) from drone have been performed to reconstruct the rockfall event and to predict the future potential for rockfalls. Our results suggest that the rockfall was caused by a combination of factors, including the  sliding failure mechanism occurred along a surface deeping to the valley with an angle of 54.5o, the presence of jointed and cracks in the rock with high aperture. A series of 10,000 of block propagations using the scarring model algorithm from stnParabel to produce an area of deposition in agreement with observation made in the field, with corresponding energy line from simulation average has an angle of 35.5 o. The trajectories of blocks are attributed to the high damping effects of the ground conditions and the vineyard rock fences which reduced the distance travelled by the falling rock, and the vineyard terraces slope angle lower than the average slope. While rock protections fences have been installed for protection on the falling block area, however there is a need to consider additional measures, as the rock structure in this area is larger than the width of the cliff face, which makes it more susceptible to rockfalls. Such study points out that the calibration of rockfall simulation based on only few blocks is very challenging.

How to cite: Choanji, T., Chale, A., Liu, W., Fei, L., Noël, F., Derron, M.-H., and Jaboyedoff, M.: Back analysis of the 2023 rockfall event of Martigny (Switzerland): trajectography prediction to future potential hazard along road, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16064, https://doi.org/10.5194/egusphere-egu24-16064, 2024.

Rock avalanches are one of the most destructive geological phenomena in mountainous regions. Understanding the dynamics and characteristics of rock avalanche movement plays a crucial role in assessing the potential hazards. However, the prediction for rock avalanche propagation is still challenging. Our study used an inventory of rock avalanches from Central Asia containing 412 historical cases from 6 countries provided by A. Strom. Considering several input parameters, the machine learning-based approach of extreme gradient boosting with grid search optimization was proposed. Input parameters including confinement type, headscarp height, mean slope angle of headscrap, length and width of the headscarp base, source volume, and maximal height drop (Hmax) are analyzed and discussed. Our proposed model can multi-output the distance of propagation L and the total impacted area, which outperformed by comparison with other machine learning models. Eleven rock avalanche events in Uzbekistan were introduced to demonstrate that the proposed model can be applied to prediction for limited parameters. For future work, we intend to propose a Convolutional Neural Network (CNN) architecture that combines spatial inputs and metadata as input in machine learning. Spatial inputs including elevation, slope, aspect, curvature, and lithology were used for our proposed model. Additionally, the CNN-based deep learning approach might be possible to predict rock avalanches which are characterized by complex terrain with multiple source areas and diverging paths. 

How to cite: Lin, R.: Travel distance prediction for rock avalanche based on machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16109, https://doi.org/10.5194/egusphere-egu24-16109, 2024.

EGU24-16313 | ECS | Orals | NH3.5

Quantitative vulnerability assessment of buildings susceptible to slow-kinematic landslides 

Francesco Poggi, Francesco Caleca, Davide Festa, Olga Nardini, Francesco Barbadori, Matteo Del Soldato, Claudio De Luca, Francesco Casu, Riccardo Lanari, Nicola Casagli, and Federico Raspini

An approach for assessing the quantitative vulnerability, through empirical fragility and vulnerability curves, of masonry buildings exposed to slow-kinematic landslides is described. More in detail, the fragility curves express the probability of exceeding a given level of damage for a range of landslide intensity values. Starting from these ones, the vulnerability curve provides the mean level of damage severity to a given building (or aggregate of buildings) in relation to the landslide intensity value. The application of the vulnerability curve is exploited in the quantitative risk analysis (QRA), that quantifies the probability of a given level of loss.

The Department of Earth Sciences of the University of Florence has catalogued the severity damage landslide-induced to over four thousand masonry buildings gathered from in situ surveys in the northern Apennines. Moreover, to retrieve the fragility and, consequently, the vulnerability curves for buildings, the proposed method exploits the results of spaceborne Advanced Differential Interferometry SAR (A-DInSAR) analysis. In particular, such a method considers the landslide intensity value equal to the module of the vertical (up-down) and horizontal (east-west) deformation velocity obtained by properly combining ascending and descending Sentinel-1 DInSAR products, retrieved through the P-SBAS (Parallel-Small Baseline Subset) method developed at IREA-CNR.

This approach to assess the vulnerability has been integrated within the well-known QRA procedure, which is based on the application of the risk equation (R=H*V*E), where:

R is the landslide risk in terms of economic loss;

H is the hazard retrieved from the susceptibility map available for the entire Italian territory;

V is the vulnerability obtained directly from the equation of the vulnerability curve;

E is the exposure of buildings assessed from average real estate market parameters reported in the OMI (Osservatorio Mercato Immobliare).

The effectiveness of the proposed procedure has been tested over the municipality of Zeri (Massa-Carrara, Italy), where a large-scale landslide risk map has been produced. In particular, for each building of the study area, the hazard, the vulnerability, the exposure and the risk associated with it, are presented. The analysis estimates a total risk of 33.2 million euro for the Zeri municipality and the identification of specific buildings at highest risk. The provided result can be useful for the civil protection activities of the local administrator identifying areas with higher potentiality of damage on structures.

How to cite: Poggi, F., Caleca, F., Festa, D., Nardini, O., Barbadori, F., Del Soldato, M., De Luca, C., Casu, F., Lanari, R., Casagli, N., and Raspini, F.: Quantitative vulnerability assessment of buildings susceptible to slow-kinematic landslides, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16313, https://doi.org/10.5194/egusphere-egu24-16313, 2024.

EGU24-17618 | ECS | Posters on site | NH3.5

Monitoring techniques for rockfall hazard across Malta, Mediterranean Sea. 

Christopher Gauci, Emanuele Colica, Daniel Fenech, and George Buhagiar

The Maltese Islands are exposed to a variety of environmental impacts because of their geographic position, one such impact being coastal hazards arising from erosion, exacerbated by climate change. The prevailing mitigation approach has traditionally been based on visual assessment of risk in specific sites rather than scientifically gathered information as an evidence basis for action to mitigate such risks. Constant monitoring is required to identify the probability and patterns of these events, which would assist in prediction. This was done using in situ measurements which include tiltmeter readings and topographic nail distances.  Certain sites were chosen across the Maltese islands for both installations, selected through historical research and other datasets including dangerous signage installations. Several nails were designated between primary and secondary signifying more stable to unstable cliff edge respectively. Distances using a total station were then taken from primary nails to the secondary nails for consecutive datasets. Tilt plates were installed in three areas with the nails and data recorded by positioning the tiltmeter at different directional axis. 

How to cite: Gauci, C., Colica, E., Fenech, D., and Buhagiar, G.: Monitoring techniques for rockfall hazard across Malta, Mediterranean Sea., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17618, https://doi.org/10.5194/egusphere-egu24-17618, 2024.

EGU24-17946 | ECS | Orals | NH3.5

Rock avalanche runout prediction for suggested failure scenarios. Case study of Cima del Simano rockslide (Switzerland) 

Charlotte Wolff, Michel Jaboyedoff, Andrea Pedrazzini, and Marc-Henri Derron

Rock avalanches events pose significant concerns in mountainous regions characterised by deep and narrow valleys. This has not deterred the ongoing development in these areas, where population settlements and infrastructure continue to expand, becoming increasingly susceptible to these risks. Cima del Simano instability in the Swiss Alps, located in the narrow Blenio Valley, is a deep-seated rockslide which could trigger such events in the future. A previous work outlined several scenarios for the rockslide failure defined by a specific area, volume (ranging from 2.30x105 m3 to 4.30x106 m3), and susceptibility to happen.

Given the proximity of a major road and several villages on both sides of the Valley, there is a real need to evaluate the potential runout distance in the event of rupture and propagation of the different failure scenarios. 

Literature often presents two distinct approaches for estimating the runout distance and the impacted area, both based on the retrospective analysis of historical landslide occurrence. The first approach is through empirical equations linking volumes of failure V and Fahrböschung angles f (tanf=aV^(-b), with a and b two empirical parameters to determine). The second approach consists in numerically simulating the flow propagation by means of dedicated software and by applying specific rheological models. 

This present work suggests applying both those techniques to evaluate the area that would be affected in the case of a rock avalanche at Cima del Simano, triggered by one of the suggested scenarios. We evaluated the runout distance for different angles f estimated based on the empirical relationship, and Dan3D for simulating the propagation applying the Voellmy rheology. Four simulations were conducted by varying the friction coefficient μ [-] and the parameter of turbulence ξ [m.s-2] in order to assess the minimal and maximal possible propagation in terms of runout distance L and lateral spreading based on domain of validity of those parameters according to literature. 

The distances L obtained empirically are longer than the ones from the simulations. This can be explained by the frontal confinement of the flow slowing down the propagation. The study is completed by an evaluation for each scenario of the probability of exceeding a certain distance L using existing statistical models for f variations. 

Additionally, the numerical simulations highlight the areas in gullies where debris are deposited during the flow propagation. Those areas can be sources for subsequent debris flow events. In a second step, we conducted an analysis of areas susceptible to debris flow with Flow-R and compared them with former debris flow events for validation. 

This study aligns with risk management to assist in making informed decisions regarding the evacuation plan in the event of a rupture and propagation of an important volume at Cima del Simano. 

How to cite: Wolff, C., Jaboyedoff, M., Pedrazzini, A., and Derron, M.-H.: Rock avalanche runout prediction for suggested failure scenarios. Case study of Cima del Simano rockslide (Switzerland), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17946, https://doi.org/10.5194/egusphere-egu24-17946, 2024.

EGU24-18131 | Orals | NH3.5 | Highlight

Introducing uncertainty in hazard analysis in a simple way: example of rockfalls 

Michel Jaboyedoff

One of the main problems of risk assessment is to evaluate the uncertainty of the results. One relevant solution is to provide exceedance curves based on simulations of the risk calculation (Macciotta et al., 2016; Jaboyedoff et al. 2021), as can be done with CAT models. Instead of performing a single calculation, up to 106 are performed with imputed viability based on different approaches such as observed distributions, standard probabilistic laws such as Poisson or uniform distribution, expert knowledge based on triangular distributions, etc. This can be done on the basis of a "deterministic calculation" of the risk, which allows a better assessment of the uncertainty of the risk.

Drawing upon a precedent risk calculation study within a road corridor, a novel risk calculation methodology is suggested, employing stochastic simulations to introduce variability across the parameters in the risk equation. The outcome manifests as an exceedance curve akin to those generated by catastrophe models. This approach systematically introduces uncertainty into the risk calculation, providing a simplistic means to address inadequately documented cases with limited data. This approach tends to minimise risk or call risk calculations into question.

 

References:

Jaboyedoff, M., Choanji, T., Derron, M.-H., Fei, L., Gutierrez, A., Loiotine, L., Noel, F., Sun, C., Wyser, E. & Wolff, C. 2021. Introducing Uncertainty in Risk Calculation along Roads Using a Simple Stochastic Approach. Geosciences, 11, doi: 10.3390/geosciences11030143.

Macciotta, R., Martin, C.D., Morgenstern, N.R. & Cruden, D.M. 2016. Quantitative risk assessment of slope hazards along a section of railway in the Canadian Cordillera—a methodology considering the uncertainty in the results. Landslides, 13, 115-127, doi: 10.1007/s10346-014-0551-4.

How to cite: Jaboyedoff, M.: Introducing uncertainty in hazard analysis in a simple way: example of rockfalls, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18131, https://doi.org/10.5194/egusphere-egu24-18131, 2024.

EGU24-20066 | ECS | Orals | NH3.5 | Highlight

Interdisciplinary insights into an exceptional giant tsunamigenic rockslide on September 16th 2023 in Northeast Greenland 

Kristian Svennevig, Stephen Hicks, Thomas Lecocq, Anne Mangeney, Clément Hibert, Niels Korsgaard, Antoine Lucas, Marie Keiding, Alexis Marboeuf, Sven Schippkus, Søren Rysgaard, Wieter Boone, Steven Gibbons, Kristen Cook, Sylfest Glimsdal, Finn Løvholt, Matteo Spagnolo, Jelle Assink, William Harcourt, and Jean-Philippe Malet and the VLPGreenland

On September 16th, 2023 at 12:35 UTC, a 25.5 M m3 rockslide occurred on the slope of Dickson Fjord in Northeast Greenland. The rockslide impacted a gully glacier, leading to a rock and ice avalanche that entered the fjord causing an up to 200 m high tsunami with observable runup up to 100 km away. The event produced an unprecedented very long period (VLP) seismic event observable on seismic stations worldwide for up to nine days. Here we focus on reconstructing the dynamics of the landslide, while detailed analysis of the VLP seismic signal is presented by Widmer-Schnidrig et al. in Session GM2.1.

Detailed analysis of the landslide reveals that a large body of metamorphic rock, with dimensions up to 150 m thick, 480 m wide, and 600 m long, dropped westwards along a foliation-parallel failure plane. The impact shattered a 200 m-wide outlet glacier, entraining 2.3 M m3 of glacier ice. The event was dynamically preconditioned by the progressive thinning of the glacier that supported the toe of the unstable slope. Subsequent investigations of satellite images and seismic records indicate that up to five minor landslides occurred in the years prior to the largest event in Sept. 2023, and one subsequent landslide has also been recorded.

Seismic signals generated by the landslide-tsunami were observed at nearby seismic stations, providing insights into its dynamics. The seismic signatures, including emergent high-frequency arrivals and low-frequency signals, match with characteristics of landslides involving glacial ice. Infrasound signals were also detected up to 3310 km away.

To reconstruct the landslide run-out, seismic waveforms from the closest stations were analyzed, resulting in a maximum force of 192×109 N, corresponding to a mass estimate of 78-103×109 kg, equating to a volume of ca. 29-38 M m3, consistent with results from photogrammetric reconstruction. The inverted run-out path indicates the initial rockslide impact with the gully wall, followed by entry into the water. The whole slide lasted c. 90 seconds. An independent numerical model to simulate the landslide force-history is in overall agreement with the seismic inversion results. Simulations of the landslide induced tsunami compare well with observations of the tsunami run-up, and also show evidence of longer lasting seiche action.

The landslide is the first glacial debuttressing landslide known from Greenland, and the first tsunamigenic landslide of this magnitude recorded in Northeast Greenland. 

How to cite: Svennevig, K., Hicks, S., Lecocq, T., Mangeney, A., Hibert, C., Korsgaard, N., Lucas, A., Keiding, M., Marboeuf, A., Schippkus, S., Rysgaard, S., Boone, W., Gibbons, S., Cook, K., Glimsdal, S., Løvholt, F., Spagnolo, M., Assink, J., Harcourt, W., and Malet, J.-P. and the VLPGreenland: Interdisciplinary insights into an exceptional giant tsunamigenic rockslide on September 16th 2023 in Northeast Greenland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20066, https://doi.org/10.5194/egusphere-egu24-20066, 2024.

EGU24-20256 | ECS | Posters virtual | NH3.5

Deciphering the force history of 2021 Chamoli rockslide 

Athul Palliath, Himangshu Paul, N Purnachandra Rao, and Venkatesh Vempati

Landslides are a significant hazard, particularly for those living in mountainous regions where the terrain is steep and unstable. Unfortunately, continuous monitoring of landslides is challenging due to their unpredictable nature. However, recent advancements in high-quality, dense broadband seismic networks have made it possible to study the spatial and temporal evolution of mass wasting processes through the analysis of seismic signals. The 2021 Chamoli rockslide which originated from a glaciated ridge of the Ronti Mountain in the western Himalaya caused severe damage to a hydropower project in downslope region and a casualty of about 80 people. CSIR-National Geophysical Research Institute established a regional seismic network in the Uttarakhand Himalaya which provides a great scope to understand this event in greater detail. We have performed dynamic inversion of the long period seismic waves generated by the rockslide to derive its force history. We used multistation data from Uttarakhand regional seismic network. We used IRIS syngine to generate Green’s function based on ak135 velocity model. Long period seismic waveforms from 6 stations within a distance of 80 km were chosen to perform inversion based on the signal to noise ratio and azimuthal coverage. The inversion is done using python package called lsforce. We reconstruct the force time history of the landslide, from the initial detachment of the rock mass to its impact on the ground. The peak upward vertical force corresponds to the detachment and peak downward vertical force corresponds its  the imapct  onto the ground. The result agrees with the centroid single force inversion done for the phases of detachment and impact of the landslide. The result obtained from force time history can be used to constrain parameters for the numerical simulation of the landslide to understand its dynamics in detail.  

How to cite: Palliath, A., Paul, H., Rao, N. P., and Vempati, V.: Deciphering the force history of 2021 Chamoli rockslide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20256, https://doi.org/10.5194/egusphere-egu24-20256, 2024.

EGU24-22276 | Posters on site | NH3.5

Topographic changes in the high-altitude walls of the Mont Blanc massif: quantification at different spatial and temporal scales  

Daniel Uhlmann, Michel Jaboyedoff, Ludovic Ravanel, Joëlle Hélène Vicari, and Marc-Henri Derron

Long-term topographic changes at high altitude in the Alps, at different spatial and temporal scales, are challenging to quantify, often due to lack of direct evidence. Historic rockfalls are not always visually evident and their debris is frequently consumed by surrounding glaciers, and hanging glaciers leave no moraines to mark their evolution. Remote sensing techniques such as Light Detection and Ranging (LiDAR) have become powerful tools for precisely quantifying geomorphometric changes in the 21st century. However, rates of change based on the short time intervals of data produced since the advent of these modern techniques might not reflect longer-term trends. Especially considering the acceleration of Alpine zone erosion rates driven by cryospheric warming trends, extending the record towards the beginning of the 20th century can help resolve if the current rates are anomalous or consistent with the past. To extend the record of topographic changes of rock and glacier surfaces, Structure-from-Motion (SfM) photogrammetry techniques exploiting archival imagery can be used to create 3D models of past Alpine zone topography with which modern LiDAR can be combined to quantify longer-term rates of change. Combining archival SfM and recent LiDAR 3D models allows the estimation of historical erosion rates and glacier surface height change in the Mont-Blanc massif from the southeast face of Grand Pilier d’Angle (GPA; 4,243 m a.s.l.) from 1929-2021, the Brouillard Pillars (BP; 4150 m a.s.l.) from 1950-2021, the Aiguille du Midi (AdM; 3,842 m a.s.l.) from 1909-2022, and the Aiguille Verte (4,122 m a.s.l.) from 1932-2021. 1-year-interval LiDAR surveys of the GPA and AdM from 2020-2021 and 2021-2022, respectively, provide high-resolution erosion rates for a reference against the rates calculated with the SfM method. The GPA had erosion rates of 5.9±2.3mm year-1 and 8.5±0.1 mm year-1 for the 1929-2021 and 2020-2021 time-intervals, respectively. The BP had a rate of 1.0±0.39 mm year-1 for the period 1950-2022, and the AdM had a 16.4± 0.9 mm year-1 rate from 2021-2022. The 6 hanging glaciers of the AdM north face had an average surface height change of -9.39 m from 1909-2022. SfM models from archival photographs show an increase in the annual erosion rate of the GPA.

How to cite: Uhlmann, D., Jaboyedoff, M., Ravanel, L., Vicari, J. H., and Derron, M.-H.: Topographic changes in the high-altitude walls of the Mont Blanc massif: quantification at different spatial and temporal scales , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22276, https://doi.org/10.5194/egusphere-egu24-22276, 2024.

EGU24-22438 | Posters on site | NH3.5

The Steinsholtsjökull rockslide and GLOF in January 1967, South Iceland – a geophysical hazard likely to reoccur elsewhere in Iceland? 

Thorsteinn Saemundsson, Daniel Ben-Yehoshua, Greta Wells, Sinah Toscka, and Andrew J. Dugmore

This paper presents new estimates of the dimensions and impact of the 1967 Steinsholtshlaup in Iceland in order to understand better the event, the hazards it generated, its long-term legacy and the implications for both landscape interpretation and hazard planning in areas of contemporary valley glaciation. On 15th of January 1967 a major rockslide occurred on the northern face of the Innstihaus mountain in southern Iceland, which overlooked the valley glacier called Steinsholtsjökull. The slide occurred during intensive snowmelt, that followed heavy snow accumulation in December 1966. The landslide was a complex paraglacial response to decades of down wasting of Steinholtsjökull. Since the 19th century high stands of the Little Ice age in Iceland, Icelandic glaciers have probably lost about 16% of their mass. Warm conditions in the 1920s and 1930s drove rapid glacier retreat in southern Iceland and resulted in the formation of many pro-glacial lakes, one of which formed in front of Steinsholtsjökull as the terminus of the glacier retreated up valley and the surface down wasted.  The Innstihaus rockslide displaced the southern margin of the glacier and broke up a large amount of the glacier surface. The resulting down valley avalanche of rock incorporated glacier ice, swept into a proglacial lake and the confined pro-glacial valley of Steinsholtsdalur, creating a GLOF that left a trail of ice, rock debris and landscape transformation that entirely overprinted the pre-existing pro-glacial landscape. The Steinsholtsá river was displaced from the centre line of the valley to its southern margin. About 5km from the site of the cliff collapse, boulders up to 80m3 in size were scattered immediately beyond the confluence of the proglacial valley with a wider valley sandur. A paper published by Kjartansson in 1967 recorded the immediate aftermath of the GLOF, but left many questions unanswered, and there have been no subsequent publications. A better understanding of this event is important because, circumstances similar to those found in the Steinsholtsdalur valley prior to 1967 have developed in numerous glacial environments around Iceland’s ice caps.  As in many other montane areas, increased temperatures over the last thirty years have driven renewed and rapid retreat of valley glaciers. Across Iceland, existing proglacial lakes have expanded and many new ones have formed. These glacier fluctuations have affected the stability of neighbouring mountain slopes, which are resulting in slope deformation and mass movements. The potential for a major geomorphological incident in areas that both attract tourists year-round and have seen a recent related infrastructure development raises serious concerns and stresses an urgent need to study and monitor these environments.

How to cite: Saemundsson, T., Ben-Yehoshua, D., Wells, G., Toscka, S., and Dugmore, A. J.: The Steinsholtsjökull rockslide and GLOF in January 1967, South Iceland – a geophysical hazard likely to reoccur elsewhere in Iceland?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22438, https://doi.org/10.5194/egusphere-egu24-22438, 2024.

EGU24-1696 | Orals | NH3.6

The influence of rainfall patterns on shallow landslides in New Zealand 

Hugh Smith, Andrew Neverman, Harley Betts, and Raphael Spiekermann

Understanding how rainfall events influence the pattern and magnitude of landslide response is an important research focus from geomorphological and hazard planning perspectives. Few studies quantitatively relate spatial patterns in rainfall and landslides, largely due to difficulties in acquiring landslide inventories and data on rainfall patterns for individual storm events. Here, we aim to a) identify which factors most influence susceptibility to rapid shallow landslides at the event scale and b) assess how the spatial density of landslides varies in relation to rainfall. While we do not know precisely when individual landslides were triggered during an event, we can examine how the overall pattern of landslides varies spatially in relation to rainfall and geo-environmental factors.

Rapid landslides triggered by intense rainfall occur extensively in New Zealand’s hill country (land <1000 m in elevation with slopes generally between 20-30°). These landslides are typically shallow (approximately 1 m deep) and small (median source areas 50-100 m2). Past deforestation for pastoral farming accelerated landslide erosion. As a result, large rainfall events, such as Cyclone Gabrielle in February 2023, may trigger tens to hundreds of thousands of landslides, causing significant damage to land, infrastructure, and sites of cultural significance to Māori, as well as agricultural production losses and degradation of receiving environments from excess sediment.

In the present study, we focus on four large storm events that generated over 26,000 landslides across mostly hill country terrain on the North Island of New Zealand in 2017-18. High-resolution (0.5 m), before/after satellite imagery was used to map landslides within each study area. Ground-based weather radar data was processed to generate high-spatiotemporal-resolution gauge-calibrated rainfall grids and compute a) maximum intra-event intensities (30 min – 24-h), b) total event rainfall, and c) pre-event accumulations (10 – 90 days) that influence antecedent soil moisture. Rainfall variables were included alongside geo-environmental factors in a binary logistic regression model applied with automated variable selection using the least absolute shrinkage selection operator (LASSO) to assess the influence of different explanatory variables.

Land cover and slope most influenced landslide susceptibility ahead of intra-event rainfall intensities and pre-event rainfall accumulations. Of the rainfall variables, maximum 12-h rainfall normalised by the 10-y recurrence interval intensity and the 10-d pre-event accumulation normalised by mean annual rainfall had the most influence. Forest cover reduced the sensitivity of landslide spatial density to variations in slope, rainfall, and rock type, in contrast to pasture. Mean landslide density increased 3.5-fold once the maximum 12-h intensity exceeded the 10-y recurrence interval intensity by ≥25% for pastoral land on weak sedimentary rocks. This threshold is consistent with the increase in 12-h rainfall by late century under the highest levels of projected warming in New Zealand, which suggests the landslide response to storm rainfall could be significantly amplified by climate change.

How to cite: Smith, H., Neverman, A., Betts, H., and Spiekermann, R.: The influence of rainfall patterns on shallow landslides in New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1696, https://doi.org/10.5194/egusphere-egu24-1696, 2024.

EGU24-2416 | Posters on site | NH3.6

Combined Effect of Wind and Rain on Typhoon-Induced Landslide 

Jui-Yun Hsieh and Yuan-Chien Lin

Landslides which cause numerous casualties and property losses are the crucial natural disaster in Taiwan. Traditionally, typhoon-induced landslides studies mainly focused on the triggering factors, such as geological condition, topographic condition and heavy rainfall. However, typhoons often bring sudden maximum wind which sways trees severely, leading to the soil disturbance which decreasing the slope stability. Moreover, some landslide events occurred on borad-leaved forest along the slopes where were only affected by strong winds of the typhoon and were not particularly affecte by heavy rainfall of the typhoon. In this study, data-driven approach is used to prove that strong winds is one of the important trigger factor, especially strong winds lasting for hours. We examed the significance of the combined rain-wind influence on landslides by Three-dimensional (3D) Histogram and Mann-Whitney U test. The results demonstrated that the wind and rain conditions when a typhoon landslide event occurs are both significantly greater than when no landslide event occurs. And a binary machine learning Random Forest model is constructed to predict the occurrences of landslides based on factors, such as heavy rain, strong winds, traditional geological conditions, and topographical factors. The findings of this study infer that  in addition to heavy rainfall, strong winds is also one of the important factor that may increase or trigger the risk of landslides. Therefore, strong winds can not be ignored when investigating the typhoon-induced landslides.

How to cite: Hsieh, J.-Y. and Lin, Y.-C.: Combined Effect of Wind and Rain on Typhoon-Induced Landslide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2416, https://doi.org/10.5194/egusphere-egu24-2416, 2024.

EGU24-2680 | ECS | Orals | NH3.6

Understanding Delayed Landslides: A Study of 1,118 Fatal Incidents in China Influenced by Post-Precipitation Runoff 

Kanglin Wu, Alessandro Simoni, and Ningsheng Chen

The common understanding of landslides points to intense precipitation as a primary trigger. However, this explanation falters when considering landslides occurring with minimal or no rainfall, challenging the basis of empirical and numerical analyses. Taking advantage of a dataset documenting 1,118 landslide disasters with casualties in China since 1984, this study incorporates field investigations, laboratory experiments, and numerical simulations to unravel the mechanisms behind the delayed initiation of landslides influenced by post-precipitation runoff and infiltration. A noteworthy finding emerges: over 75% of catastrophic landslides in China exhibit a temporal delay compared to triggering rainfalls, typically manifesting within one week following peak precipitation. The temporal dynamics of precipitation-induced landslide delays show a range from months to hours, with the delay positively correlated to both landslide scale and the severity of regional drought. Spatially, delayed landslides are frequently related to runoff recharge by upstream catchment, playing a pivotal role in the initiation process. Consideration of topography, climate, and human activities leads to the identification of four typical runoff recharge patterns. We use such patterns to investigate the relationships with the upstream catchment area and delay time, influenced by surface runoff migration and supplied runoff infiltration. Hydrological and slope stability calculations underscore the significance of the catchment area to landslide area ratio while delay time is predominantly governed by surface runoff migration and supplied runoff infiltration into the sliding soil. Results unveil a consistent sequence: robust runoff recharge facilitates water infiltration into weak rock fractures or soil mass, resulting in a gradual increase of pore water pressure. This sequence culminates in the delay of landslide initiation compared to the peak precipitation. These findings may contribute to a scientific foundation for early warning and prediction related to such landslides, thereby mitigating associated risks.

How to cite: Wu, K., Simoni, A., and Chen, N.: Understanding Delayed Landslides: A Study of 1,118 Fatal Incidents in China Influenced by Post-Precipitation Runoff, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2680, https://doi.org/10.5194/egusphere-egu24-2680, 2024.

EGU24-4772 | ECS | Orals | NH3.6

A Comparison of SimCLR and SwAV Contrastive Self-Supervised Learning Models For Landslide Detection 

Hejar Shahabi, Omid Ghorbanzadeh, Saeid Homayouni, and Pedram Ghamisi

Deep Learning (DL) algorithms have demonstrated superior efficacy compared to traditional Machine Learning (ML) methods in the realm of landslide detection through the analysis of Remote Sensing (RS) imagery. However, their performance is notably contingent upon the quantity of manual annotations utilized during the training process. This investigation delves into the utilization of two distinct Self-Supervised Learning (SSL) models, specifically the Simple Framework for Contrastive Learning of Visual Representations (SimCLR) and Swapping Assignments between multiple Views (SwAV). These models were adapted and enhanced for downstream tasks, particularly in the domain of landslide detection. To train the SSL models, the Landslide4Sense competition dataset was employed, consisting of 3799 training patches, 245 validation patches, and 800 testing patches generated from Sentinel-2 images acquired from diverse regions worldwide. During the training of SimCLR and SwAV models, only the training patches were utilized, with a series of data augmentations applied to the input dataset based on each model's architecture. Both models employed ResNet-50 as the encoder.

For the downstream task of landslide detection, a custom U-Net model was developed. The trained ResNet-50 served as the encoder, and during fine-tuning, only the decoder part was permitted to be trained while the encoder remained frozen. During the fine-tuning process, subsets comprising 1% and 10% of labeled data from the training dataset were randomly selected to train the model, and predictions were exclusively conducted on the testing data. While a conventional supervised ResU-Net model, which was trained on all labeled training datasets, attained an F1 score of 72%, the SSL models achieved F1 scores of 64% and 71% with 1% labeled data, and 68% and 76% with 10% labeled data for SimCLR and SwAV, respectively. In addition, comparisons were conducted with all supervised reference models in the Landslide4Sense competition, revealing that SwAV, with 10% labeled data, outperformed all models, surpassing their top model by 4%. This study underscores the potential of SSL techniques in the segmentation and classification of RS images for natural hazard mapping, particularly in scenarios where labeled data is not available or is limited.

How to cite: Shahabi, H., Ghorbanzadeh, O., Homayouni, S., and Ghamisi, P.: A Comparison of SimCLR and SwAV Contrastive Self-Supervised Learning Models For Landslide Detection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4772, https://doi.org/10.5194/egusphere-egu24-4772, 2024.

EGU24-5116 | ECS | Posters on site | NH3.6

Estimating near-surface reduction in shear-strength on hillslopes caused by strong ground shaking 

Hakan Tanyas, Chuanjie Xi, Luigi Lombardo, Kun He, Xiewen Hu, and Randall Jibson

The weakening of hillslopes during strong earthquakes increases landsliding rates in post-seismic periods. However, very few studies have addressed the amount of coseismic reduction in shear strength of hillslope materials. This makes estimation of post-seismic landslide susceptibility challenging. Here we propose a method to quantify the maximum shear-strength reduction expected on seismically disturbed hillslopes. We focus on a subset of the area affected by the 2008 Mw 7.9 Wenchuan, China earthquake. We combine physical and data-driven modeling approaches. First, we back-analyze shear-strength reduction at locations where post-seismic landslides occurred. Second, we regress the estimated shear-strength reduction against peak ground acceleration, local relief, and topographic position index to extrapolate the shear-strength reduction over the entire study area. Our results show a maximum of 60%-75% reduction in near-surface shear strength over a peak ground acceleration range of 0.5-0.9 g. Reduction percentages can be generalized using a data-driven model.

How to cite: Tanyas, H., Xi, C., Lombardo, L., He, K., Hu, X., and Jibson, R.: Estimating near-surface reduction in shear-strength on hillslopes caused by strong ground shaking, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5116, https://doi.org/10.5194/egusphere-egu24-5116, 2024.

EGU24-5565 | ECS | Orals | NH3.6

A probabilistic model for slope stability analysis including the root reinforcement effects 

Sara Galeazzi, Luca Ciabatta, Luca Brocca, and Diana Salciarini

The presence of vegetation plays an important role in slope stability, especially in triggering of shallow landslides. It influences the mechanical and hydrological behaviour of soils, generating both stabilizing and destabilizing actions [1,2]. Variation in vegetation related to land use change can affect slope stability and can be evidenced in terms of variation of probability of failure.
In this study we implement a module for the calculation of root reinforcement in the slope stability physically-based probabilistic model PG_TRIGRS (Probabilistic, Geostatistic-based, TranSient Rainfall Infiltration and Grid-based Slope stability, [3]). Such model allows the wide-area assessment of the probability of rainfall-induced failure, considering the spatial variability of the soil properties treated as random variables. In this work, we apply the model to an area prone to landslides in Central Italy assuming the spatial variability of vegetation.
To investigate the influence of the spatial layout of plant roots on slope stability, the root reinforcement is implemented in the PG_TRIGRS probabilistic model. The considered root cohesion values  were derived from literature and were determined according to vegetation maps available for the study area. In addition, root cohesion variation is also considered along the vertical profile as a function of rooting depth. Finally, the resulting probability of failure distribution is compared to the results obtained for the bare soil with the absence of roots.


[1] Pollen-Bankhead, N., & Simon, A. (2010). Hydrologic and hydraulic effects of riparian root networks on streambank stability: Is mechanical root-reinforcement the whole story?. Geomorphology, 116(3-4), 353-362.
[2] Masi, E. B., Segoni, S., & Tofani, V. (2021). Root reinforcement in slope stability models: a review. Geosciences, 11(5), 212.
[3] Salciarini, D., Fanelli, G., & Tamagnini, C. (2017). A probabilistic model for rainfall—induced shallow landslide prediction at the regional scale. Landslides, 14, 1731-1746.

How to cite: Galeazzi, S., Ciabatta, L., Brocca, L., and Salciarini, D.: A probabilistic model for slope stability analysis including the root reinforcement effects, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5565, https://doi.org/10.5194/egusphere-egu24-5565, 2024.

EGU24-6201 | Orals | NH3.6

Deep learning forecast of rainfall-induced shallow landslides in Italy 

Fausto Guzzetti, Alessandro C. Mondini, and Massimo Melillo

Rainfall induced landslides occur in all mountain ranges posing severe threats to people, property, and the environment. Given the projected climate changes, in many areas the risk posed by rainfall induced landslides is expected to increase. For this reason, the ability to anticipate their occurrence is key for effective landslide risk reduction. Empirical rainfall thresholds and coupled slope-stability and rainfall infiltration models are commonly adopted to anticipate the short-term (from hours to days) occurrence of rainfall induced shallow landslides. However, empirical evidence suggests that they may not be effective for operational forecasting over large and very large areas. We proposed a deep learning based modelling strategy to link hourly rainfall measurements to landslide occurrence. We constructed a large ensemble of 2400 neural network models which we informed using hourly rainfall measurements taken by more than 2000 rain gauges and information on more than 2400 landslides in the period from February 2002 to December 2020 in Italy. Our results have indicated that (a) it is possible to effectively anticipate the occurrence of the rainfall induced shallow landslides in Italy, and (b) the location and timing of the rainfall-induced shallow landslides are controlled primarily by the precipitation. Our results open to the possibility of operational landslide forecasting in Italy, and possibly elsewhere, based on rainfall measurements and quantitative meteorological forecasts aided by deep learning based modelling.

How to cite: Guzzetti, F., Mondini, A. C., and Melillo, M.: Deep learning forecast of rainfall-induced shallow landslides in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6201, https://doi.org/10.5194/egusphere-egu24-6201, 2024.

EGU24-6480 | ECS | Posters on site | NH3.6

A full probabilistic approach to landslide forecast 

Flavia Ferriero, Warner Marzocchi, Gianfranco Urciuoli, and Simone Mancini

Landslides are among the most destructive natural disasters that occur frequently worldwide, claiming lives and causing severe economic losses. The most common approaches for managing the short-term landslide risk is based on the definition of deterministic thresholds of a triggering event (a seismic quantity, or an amount of rain) above which the landslide is expected to occur. However, landslides, as well as most of natural events, is hardly predictable deterministically, owing to the unavoidable and ubiquitous presence of uncertainties of different kind. In this study, we present the first steps towards the development of a full probabilistic landslide forecasting model that accounts for the probabilistic forecasts of triggering events (such as earthquakes and/or rainfalls), and it includes a full appraisal of different kinds of uncertainty. Within a Bayesian mathematical framework, the model combines the probabilistic distribution of the mechanical parameters of the soil with the probability of observing a certain natural triggering event; the output is a space-time dependent probability of occurrence of landslides as a function of the probability of occurrence of their triggering event. In addition, we describe the landslide forecasts as a distribution of probability instead of one single value, to give a complete description of what we know and what we do not know. This approach provides a suitable scientific output that can be used by land use managers and decision-makers. Indeed, a formal probabilistic assessment fits more adequately the intrinsic non-deterministic nature of landslide occurrence. Moreover, it provides a more suitable framework that help defining  roles and responsibilities of all actors involved in the full risk reduction process.

How to cite: Ferriero, F., Marzocchi, W., Urciuoli, G., and Mancini, S.: A full probabilistic approach to landslide forecast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6480, https://doi.org/10.5194/egusphere-egu24-6480, 2024.

EGU24-7275 | Orals | NH3.6

A fully operational IoT-based slope stability analysis for an unsaturated slope in Norway 

Luca Piciullo, Minu Treesa Abraham, Ida Norderhaug Drøsdal, Erling Singstad Paulsen, Vittoria Capobianco, and Håkon Heyerdahl

The framework proposed by Piciullo et al., 2022 for a Internet of Things (IoT)-based local landslide early warning system (Lo-LEWS) consists of four main components: monitoring, modelling, forecasting, and warning. It was applied to a steep natural slope in Norway, equipped with various hydrological and meteorological sensors since 2016. Volumetric water content (VWC) and pore-water pressure (PWP) sensors were installed in 2016 (Heyerdahl et al., 2018). A weather station was added in 2022 to measure climate variables: rainfall, relative humidity, wind speed, air temperature among others. The sensors and weather station regularly send data to NGIs IoT data platform (NGI Live), which stores and makes the data available real-time through online dashboards and Application Programming Interface (API). GeoStudio software was used to create a reliable digital twin of the slope with the aim of back-calculating the in-situ hydrological conditions. Calibration, climate variables, and vegetation proved crucial for accurately modelling the slope's response . Sensitivity analysis on hydraulic conductivity and permeability anisotropy improved input data and model fitting. The hydrological model adequately represented monitored conditions up to a 1-year period (Piciullo et al., 2022). 

A fully operational IoT-based slope stability analysis has been recently established. The digital twin model has been used to evaluate the slope stability (i.e., factor of safety, FS) coupling SEEP and Slope analyses for 5 different 1-year datasets. Both past and future scenarios have been considered:  2019-2020, 2021-2022, 2022-2023, 2064-2065, 2095-2096. The inputs (i.e., hydrological and weather variables) and the FS results have been used to train different machine learning and statistical models. The feature considered are VWC, PWP, rainfall, temperature, LAI; the target was the FS. The best models able to predict the FS, given the features, are polynomial regression and random forest.

In order to predict the FS for the upcoming three days, PASTAS model (Collenteur et al., 2019) and the Norwegian Meteorological Institute webpage have been used to respectively forecast the hydrological variables (i.e., VWC and PWP) and rainfall, air temperature and relative humidity data. We created a web service that once a day automatically (1) fetches measured data from NGI Live using the NGI Live API, (2) runs predictions for the next three days based on the measured data, (3) sends the predicted values back to NGI Live, making them available for real-time visualization in online dashboards. This case study can be seen as a fully operational example of the use of IoT and digital twinning to provide a real-time stability assessment for a slope as well as a collaborative effort among different expertise: geotechnical, hydrological, instrumental and informatics.  

REFERENCES

Heyerdahl H., et al. (2018). Slope instrumentation and unsaturated stability evaluation for steep natural slope close to railway line. In UNSAT 2018: The 7th International Conference on Unsaturated Soils.

Collenteur R. A., et al. (2019). Pastas: Open Source Software for the Analysis of Groundwater Time Series. Groundwater, 57(6):877–885. URL: https://doi.org/10.1111/gwat.12925, doi:10.1111/gwat.12925.

Piciullo, L., et al. (2022) A first step towards a IoT-based local early warning system for an unsaturated slope in Norway. Nat Hazards 114, 3377–3407 (2022). https://doi.org/10.1007/s11069-022-05524-3 

How to cite: Piciullo, L., Abraham, M. T., Drøsdal, I. N., Paulsen, E. S., Capobianco, V., and Heyerdahl, H.: A fully operational IoT-based slope stability analysis for an unsaturated slope in Norway, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7275, https://doi.org/10.5194/egusphere-egu24-7275, 2024.

EGU24-7330 | Orals | NH3.6

Determination and analysis of the rainfall triggering landslides in the ITALICA catalogue  

Silvia Peruccacci, Stefano Luigi Gariano, Massimo Melillo, Fausto Guzzetti, and Maria Teresa Brunetti

The wide physiographic variability and the abundance of rainfall and landslide data make Italy an appropriate site to study variations in the rainfall conditions responsible for triggering landslides.

For more than two decades, the Research Institute for Geo-Hydrological Protection of the Italian National Research Council (CNR-IRPI) has been carrying out a specific research activity aimed at collecting information on rainfall-induced landslides in Italy. The information comes mainly from chronicle sources (newspapers in print or electronic format, websites, etc.) and institutional sources (reports on interventions carried out by the Fire Brigade and other institutional entities following reports of weather-induced landslides). The information collected has been used to compile the ITAlian rainfall-induced LandslIdes CAtalogue (ITALICA), freely accessible at https://zenodo.org/records/8009366. A description of the main features of the catalogue and the procedures adopted to fill it out can be found at https://essd.copernicus.org/articles/15/2863/2023/.

ITALICA, which is being continuously updated, to date contains data on more than 6300 rainfall-induced landslides that occurred in Italy during the period 1996-2021. The peculiarity and specificity of the catalogue lies in the mastery and control of the landslide records, which have very high levels of spatial and temporal accuracy. In particular, for more than one third of the catalogue, landslides are spatially and temporally localized with an uncertainty of less than one km2 and one hour, respectively. The availability of accurate and up-to-date information on the geographic location and time of onset of landslides is essential for improving the predictive ability of landslides. Different subsets of the catalogue have been already used to calculate national and regional rainfall thresholds implemented in early warning systems in Italy.

The first published version of ITALICA did not contain information on the rainfall conditions associated with the landslides. In the new release, presented here, we add the cumulate rainfall, rainfall duration and mean rainfall intensity values of the rainfall conditions responsible for the failures listed in the catalogue. The rainfall conditions are reconstructed by means of the CTRL-T automatic tool (https://zenodo.org/records/4533719) and using hourly rainfall measurements from more than 3000 rain gauges distributed over the Italian territory. Rainfall records are provided by the Italian National Department for Civil Protection. The spatial and temporal features of the reconstructed landslide-triggering rainfall conditions are analysed in depth.

Given the rising demand for high-quality data to be used in comprehensive analyses and data-driven models, this dataset might be very useful for assessing the rainfall triggering conditions of landslides in Italy, either by empirical or physically based models. In particular, we expect our results to have an impact on the definition of new rainfall thresholds to be implemented in landslide early warning systems at regional and national scales.

 

Work financially supported by the Italian National Department for Civil Protection (Accordo di Collaborazione 2022-2024) and the PRIN-ITALERT project (PRIN2022 call, grant number: 202248MN7N, funded by NextGenerationEU).

How to cite: Peruccacci, S., Gariano, S. L., Melillo, M., Guzzetti, F., and Brunetti, M. T.: Determination and analysis of the rainfall triggering landslides in the ITALICA catalogue , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7330, https://doi.org/10.5194/egusphere-egu24-7330, 2024.

EGU24-7357 | ECS | Orals | NH3.6

Machine learning-based landslide susceptibility mapping for short-term risk assessment in South Korea 

Sujong Lee, Minwoo Roh, Uichan Kim, and Woo-Kyun Lee

Climate change impacts the frequency and intensity of extreme weather events, leading to an increase in natural disasters globally. Heavy rainfall is a notable extreme weather event, acting as an external factor for landslides. In South Korea, where approximately 70% of the terrain is mountainous, the susceptibility to landslides is high. Despite the development and implementation of landslide early warning systems by the Korea Forest Service for local governments, the extent of landslide damage has been significant, reaching approximately 2,345 hectares in the last five years. Especially, last year, landslides occurred more than 800 times with severe human costs. The current early warning system, which focuses on administrative boundaries, has limitations in accurately identifying high-vulnerability landslide areas. To address this issue, this study introduces a landslide diagnostic model designed to assess the daily susceptibility of South Korea with fine spatial resolution. The model employs a semi-automated process that encompasses the acquisition of short-term climate forecast data and the generation of daily landslide susceptibility maps. The core algorithm of the model is based on the random forest method, predicting susceptibility at a spatial resolution of 100 meters. The model integrates various feature datasets, including meteorological, topographic, and land surface data, which are closely linked to landslide occurrences. The training model utilized landslide inventory data from 2016 to 2022, with various performance indicators employed for calibration and validation. Additionally, the landslide inventory data from 2023 was utilized for final model verification. Notably, the model incorporates a 3-day climate forecast data process provided by the Korea Meteorological Administration, enabling the prediction of short-term daily landslide susceptibility. This landslide diagnostic model holds the potential to enhance landslide prevention and preparedness at both local and regional scales.

How to cite: Lee, S., Roh, M., Kim, U., and Lee, W.-K.: Machine learning-based landslide susceptibility mapping for short-term risk assessment in South Korea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7357, https://doi.org/10.5194/egusphere-egu24-7357, 2024.

EGU24-8845 | ECS | Posters on site | NH3.6

Combining meteorological and soil wetness information in machine learning modelling for landslide early warning 

Tobias Halter, Peter Lehmann, Alexander Bast, Jordan Aaron, and Manfred Stähli

Shallow landslides triggered by intense rainfall events pose a serious threat to people and infrastructure in mountainous areas. Regional landslide early warning systems (LEWS) have proven to be a cost-efficient tool for informing the public about the imminent landslide danger. These LEWS are often based on the statistical relationship between rainfall characteristics and landslide inventory information. Previous studies in Switzerland have demonstrated that periods of increased landslide danger are correlated with relative changes in volumetric water content measured at soil moisture stations across the country. In this study, we combine such soil moisture information (including soil water potential) with meteorological data to establish dynamic thresholds for the prediction of landslide probability in both time and space. We train a random forest classifier to separate between critical and non-critical rainfall events. The models are trained and tested on data measured at 136 locations across the entire country during the period from 2008 to 2023. Our trained algorithm allows us to quantify (1) the importance of different climate and soil wetness variables and (2) the benefits of integrating soil wetness and meteorological information within LEWS. We are confident that this study will improve the accuracy and reliability of landslide forecasting at a national scale and contribute to improved landslide risk management in areas with steep slopes.

How to cite: Halter, T., Lehmann, P., Bast, A., Aaron, J., and Stähli, M.: Combining meteorological and soil wetness information in machine learning modelling for landslide early warning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8845, https://doi.org/10.5194/egusphere-egu24-8845, 2024.

EGU24-9311 | ECS | Posters on site | NH3.6

Temporal and spatial analysis of landslide-triggering rainfall conditions in Qinghai-Tibet Plateau, China 

Kezhen Yao, Stefano Luigi Gariano, and Saini Yang

Landslide on the Qinghai-Tibet Plateau (QTP) is expected to be more affected by climate change due to the sensitivity of this unique climatic and geomorphological area to variations in temperature and precipitation. As an important response signal to climate change, a systematic framework for the assessment of landslide hazard and risk in QTP is necessary to investigate the potential impacts of climate change on landslides and related exposures.

The study aims to establish an integrated model that synthesizes spatial and temporal landslide prediction, using statistical analysis, machine learning, and quantitative methods. The temporal landslide prediction is made by means of empirical rainfall thresholds, based on satellite rainfall estimates, whose feasibility for defining landslide-triggering rainfall thresholds was proved by several studies.

A well-documented hazard database of the QTP provided by the China Geological Survey (4519 records from 2001 to 2022) indicates that landslides occurred here are mostly induced by rainfall from April to October, with an obvious seasonal characteristic, resulting in fatalities, damage, and affected population. According to the database, 3542 landslides are associated to a rainfall trigger. Based on the satellite-based rainfall product of CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data, version 2.0 final) daily data, we find that the rainfall of the occurrence day and the antecedent rainfall over the seven days before the landslides are significant indicators for the rainfall induced hazard. Using the frequentist method, the event duration-cumulated event rainfall (ED) thresholds at different non-exceedance probabilities for landslide triggering are calculated for the whole QTP area and for different environmental subdivisions within it. The thresholds show a robust definition with low parameter uncertainty. This is the first attempt to define empirical rainfall thresholds for landslide occurrence specifically for the QTP.

Given the long-term of the used database, temporal and spatial analyses are conducted, to search for variations in the rainfall triggering conditions according to landslide locations and time of occurrence. Variations in the seasonal distribution and in the annual trends (using 5-year moving windows from 2007 to 2002) are evaluated. The impact of variations in rainfall patterns due to climate change making the landscape of the QTP more prone to landslides during the recent-most ten years is demonstrated by the gradual change of thresholds with lower intercepts and slopes. That means, for a certain rainfall duration, there is a tendency of lower rainfall threshold to trigger a landslide.

The thresholds here defined are further combined with landslide susceptibility map based on Random Forest to derive a landslide hazard map for the interested area.

How to cite: Yao, K., Gariano, S. L., and Yang, S.: Temporal and spatial analysis of landslide-triggering rainfall conditions in Qinghai-Tibet Plateau, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9311, https://doi.org/10.5194/egusphere-egu24-9311, 2024.

Landslides are complex and dynamic natural hazards that require a comprehensive understanding of their temporal changes for effective assessment and management. Traditional landslide inventories often focus on static analysis, providing a snapshot of landslide occurrences at a specific point in time. However, to capture the dynamic nature of landslides and assess their evolution over time, multi-temporal inventories are essential. This study aims to go beyond static analysis by proposing the use of multi-temporal inventories for dynamic landslide assessment. The approach involves the integration of remote sensing data, advanced modeling techniques, and deep learning algorithms to analyze and map landslides over multiple time periods. By considering the temporal dimension, the proposed method enables the identification of changes in landslide patterns, movements, and susceptibility over time. We used orthophotos retrieved from WMS and WMTS services provided by the Italian national portal, covering the period from 1989 to 2021, for a study conducted in the Cordevole and Alpago areas (Belluno province, NE Italian Alps). These areas were impacted by two extreme meteorological events (return period > 100 years) in 2018 (October 27th–30th) and 2020 (December 4th–6th). The first, known as windstorm VAIA, has induced severe damage to the forest cover. The generated multi-temporal inventories provide valuable information for understanding the temporal dynamics of landslides, which is crucial for accurate landslide hazard assessment and risk management. The findings of this study highlight the importance of incorporating multi-temporal inventories into landslide assessment methodologies to enhance our understanding of landslide behavior and improve decision-making processes.

Acknowledgement:

This study was carried out within the PNRR research activities of the consortium iNEST (Interconnected North-Est Innovation Ecosystem) funded by the European Union Next-Generation EU (Piano Nazionale diRipresa e Resilienza (PNRR) – Missione 4 Componente 2, Investimento 1.5 – D.D. 1058 23/06/2022, ECS_00000043). This manuscript reflects only the Authors’ views and opinions; neither the European Union nor the European Commission can be considered responsible for them.

How to cite: Bhookya, R. and Floris, M.: Beyond Static Analysis: Importance of Multi-Temporal Inventories in Alpine Environments for Dynamic Landslide Assessment in Belluno Province (Veneto Region, NE, Italy). , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9898, https://doi.org/10.5194/egusphere-egu24-9898, 2024.

EGU24-10552 | Posters on site | NH3.6

Development of a data-driven space-time model to predict precipitation-induced geomorphic impact events at the Alpine Scale 

Raphael Spiekermann, Sebastian Lehner, Stefan Steger, Mateo Moreno, Katharina Enigl, Dominik Imgrüth, Matthias Schlögl, and Georg Pistotnik

Extreme hydro-meteorological impact events are difficult to predict in space and time as they frequently result from localised, high-intensity convective precipitation events. Societal impacts can occur when extreme precipitation events interact with multiple other geomorpholocial, hydrological and societal predisposing and preparatory factors. Due to limitations in spatial and temporal resolution, it is assumed that climate models likely underestimate the magnitude and frequency of future extreme precipitation events (Slingo et al., 2022).

In the context of disaster risk reduction, it is important to understand the relationships between the multiple driving factors of geomorphic high impact events. Knowing when and where potential adverse consequences are likely to occur and under which conditions can support the design and provision of risk reduction measures (e.g., impact-based forecasts and warnings). Moreover, impact models can inform on likely changes in the frequency of extreme events under future climate regimes.

We address this problem by developing a data-driven machine-learning model aimed at predicting the likelihood of past and future weather extremes that cause societal impacts. Using a risk framework as a conceptual underpinning, a stratified space-time modelling approach is implemented, sampling from combined landslide, debris-flow and rock-fall damage inventories across Austria and South Tyrol (Italy) spanning the period 2005-2022. Building on previous method developments (Steger et al., 2023), multiple meteorological indicators available at different spatial scales, including a sub-model used to predict the likelihood of deep convective events, are combined with morphometric, geological, hydrological, land cover data as well as data on potentially exposed assets to train a hierarchical generalised additive mixed model (GAMM) on the basis of slope units. The modelling results are evaluated through multiple perspectives using variable importance assessment, spatial and temporal cross-validation procedures as well as qualitative plausibility checks.

We present first model results, showing the importance of simultaneously considering spatio-temporal variations in hazard components as well as exposure data to predict localised impact events. Further strengths, opportunities and limitations of the approach are discussed. The research leading to these results has received funding from Interreg Alpine Space Program 2021-27 under the project number ASP0100101, “How to adapt to changing weather eXtremes and associated compound and cascading RISKs in the context of Climate Change” (X-RISK-CC).

References

  • Slingo, J., Bates, P., Bauer, P. et al. Ambitious partnership needed for reliable climate prediction. Nat. Clim. Chang. 12, 499–503 (2022). https://doi.org/10.1038/s41558-022-01384-8.
  • Steger, S., Moreno, M., Crespi, A., Zellner, P., Gariano, S.L., Brunetti, M., Melillo, M., Peruccacci, S., Marra, F., Kohrs, R., Goetz, J., Mair, V. & Pittore, M. Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models. Natural Hazards and Earth System Sciences. 23, 1483–1506 (2023). https://doi.org/10.5194/nhess-23-1483-2023.

How to cite: Spiekermann, R., Lehner, S., Steger, S., Moreno, M., Enigl, K., Imgrüth, D., Schlögl, M., and Pistotnik, G.: Development of a data-driven space-time model to predict precipitation-induced geomorphic impact events at the Alpine Scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10552, https://doi.org/10.5194/egusphere-egu24-10552, 2024.

EGU24-10593 | ECS | Orals | NH3.6

Analyses of slow-moving landslides interacting with the road network: case studies in Basilicata region (southern Italy) 

Gaetano Pecoraro, Gianfranco Nicodemo, Rosa Menichini, Davide Luongo, Dario Peduto, and Michele Calvello

Road infrastructure plays a key role in the economic development of a society. Thus, ensuring its functionality and safety conditions over time is a crucial and, at the same time, a demanding task that central and local authorities are asked to address. In Italy, road networks often develop within complex geological contexts, where active slow-moving landslides may generate risks to traveling persons and to the roads themselves, the latter being associated with socio-economic impacts. The identification of the road sections most exposed to landslide risk is critical for reducing the population potentially exposed to risk and for minimizing the repair/replacement costs. However, studies specifically oriented to roads affected by existing slow-moving landslides are quite rare in the scientific literature. This is possibly due to different reasons: landslide inventories with reliable information on the past and current state of activity of the phenomena are often not available; assessing the temporal probability of landslides characterized by a given intensity over large areas is not straightforward; the development of large datasets of road displacements and damage through traditional techniques can be time-consuming and sometimes not affordable.

This study proposes a conceptual model aimed at classifying the level of exposure to slow-moving landslide risk of stretches of roads at municipal scale. The activities have been developed in the context of the “Mitigation of natural risks to ensure safety and mobility in mountain areas of Southern Italy” (MitiGO) project.  Adopting a matrix-based approach, the following data are combined: landslide inventories, thematic information, displacement measurements derived from the interferometric processing of synthetic aperture radar images (DInSAR) and damage records obtained from Google Street View. First, a statistical model based on the bivariate correlations between the independent variables (i.e., each significant spatial variable derived from the thematic maps) and the dependent variable (i.e., the slow-moving landslides inventoried in the official map) is applied for zoning the susceptibility to slow-moving landslides at the municipal scale. Then, the information is combined with the level of damage and a monitored rate of movement based on DInSAR-derived ground-displacement measurements along the road network. The output is a correlation matrix combining all the information and classifying each stretch of the road network.

The proposed procedure has been applied to different access routes from a major regional road, the SS407 Basentana highway, to some urban centers of municipalities located in the Basento river basin (Basilicata region, southern Italy).

The analyses carried out at a municipal scale allow the classification of the road stretches potentially exposed to slow-moving landslide risk adopting a fairly simple qualitative ranking procedure, reliable in relation to the scale of analysis, which is based on a few data that are relatively easy to retrieve and to manage. The obtained results can be used to support studies of road networks over large areas aimed at the prioritization of risk-mitigation measures, as well as at the identification of road sections requiring further geomorphological surveys and geotechnical analyses, to be conducted in more detail at a larger scale.

How to cite: Pecoraro, G., Nicodemo, G., Menichini, R., Luongo, D., Peduto, D., and Calvello, M.: Analyses of slow-moving landslides interacting with the road network: case studies in Basilicata region (southern Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10593, https://doi.org/10.5194/egusphere-egu24-10593, 2024.

EGU24-10837 | ECS | Orals | NH3.6

Comparative analysis of conventional and machine learning techniques for rainfall threshold evaluation under complex geological conditions 

Nicola Dal Seno, Davide Evangelista, Elena Piccolomini, and Matteo Berti

The Emilia-Romagna Region in Italy faces significant challenges due to landslide hazards. With over 80,000 landslides identified in its mountainous regions, some areas see more than a quarter of their land impacted. Despite the generally slow nature of these landslides, they pose a considerable economic burden. For instance, in 2019, the region allocated 1 million euros for immediate safety measures, and it's estimated that an additional 80 million euros are needed to complete safety plans. This makes Emilia-Romagna one of the most landslide-prone areas globally. Factors like the region's geological makeup, increased land use, and climate change are exacerbating the issue. It's becoming evident that emergency measures alone are insufficient, and proactive prevention strategies are essential. Key efforts include better forecasting of rain-induced slope instabilities and predicting reactivations of dormant landslides and new failures. However, the unpredictable nature of landslides makes these goals challenging.

The primary aim of this study is to create AI models to predict landslides in Emilia-Romagna, leveraging 75 years of data collected by the University of Bologna in partnership with the Regional Agency for Civil Protection and the Geological Survey of Emilia-Romagna. Various methods like Bayesian analysis, Neural Networks, XGBoost, TPOT, Random Forest, LDA, QDA, and Linear Regression have been employed. The findings suggest that landslides in this region are primarily driven by rainfall during the event and its location, while prior rainfall seems less critical. The research also found that after a dry summer, a rainfall event of 90-100 mm is typically needed to trigger a landslide, a threshold that decreases later in the year. The best algorithm had an F2 score test result of 0.6, meaning it could correctly predict a true positive (rainfall causing landslide) every 3 positive instances and correctly predict a true negative (rainfall not causing landslide) 95.5% of the time.

How to cite: Dal Seno, N., Evangelista, D., Piccolomini, E., and Berti, M.: Comparative analysis of conventional and machine learning techniques for rainfall threshold evaluation under complex geological conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10837, https://doi.org/10.5194/egusphere-egu24-10837, 2024.

EGU24-11180 | ECS | Posters on site | NH3.6

Identifying Heterogeneous Landslides using Multi-modal Deep Learning 

Xiaochuan Tang, Xuanmei Fan, and Filippo Catani

Automated detection of landslides is an important part of geohazard prevention. In dense vegetation covered area, identifying landslides is a challenging problem. Various types of landslide monitoring technologies have generated heterogeneous data, such as optical imagery, SAR imagery, and LiDAR point clouds. Different types of landslide monitoring methods have their advantages and drawbacks. An ideal landslide detection model should utilize their advantages. However, the complementary information of multi-source landslide monitoring data has not been fully understood. To deal with this problem, we study how to use multi-source data for developing better landslide detection models. First, a multi-modal deep learning model is introduced for landslide detection using multi-source landslide monitoring data. Second, representation learning networks are proposed for extracting landslide detection features from optical imagery and LiDAR-derived data. In addition, an attention-based data fusion network is proposed for merging the feature maps of different data sources. Finally, to improve the explainability of the proposed neural network, a new loss function with domain knowledge constrains is proposed. The proposed multi-modal deep learning method is compared with the existing machine learning-based landslide detection methods. Experimental results demonstrated that the proposed method outperformed the state-of-the-art landslide detection methods, and is able to simultaneously identify earthquake-triggered new landslides and forest-covered ancient landslides. The reason is that optical imagery is appropriate for identifying new landslides, while LiDAR-derived data is able to remove forest cover and suitable for identifying ancient landslides. It can be seen that the complementary information of multi-source data is helpful for improving the performance of landslide detection.

How to cite: Tang, X., Fan, X., and Catani, F.: Identifying Heterogeneous Landslides using Multi-modal Deep Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11180, https://doi.org/10.5194/egusphere-egu24-11180, 2024.

EGU24-12097 | Orals | NH3.6

A deep Learning-based approach for landslide dating from time-series of SAR data 

Wandi Wang, Mahdi Motagh, Zhuge Xia, Simon Plank, Zhe Li, Aiym Orynbaikyzy, Chao Zhou, and Sigrid Roessner

Landslides are a serious geologic hazard common to many countries around the world.  They can result in fatalities and the destruction of infrastructure, buildings, roads, and electrical equipment. Especially rapid-moving landslides, which occur suddenly and travel at high speeds for miles, can pose a serious threat to life and property. Landslide inventories are essential to understand the evolution of landscapes, and to ascertain landslide susceptibility and hazard, and it can be of help for any further hazard and risk analysis. Although  many landslides inventories have already been created worldwide, often these archives of historical landslide events  lack precise information on the date of landslide occurrence. Many of these inventories also lack completeness especially in case of smaller landslides which is also caused by  landslides erosion processes, human impact, and vegetation  regrowth. Precise determination of landslide occurrence time is a big challenge in  landslide research. Optical and Synthetic Aperture Radar (SAR) images with multi-spectral and textural features, multi-temporal revisit rates, and large area coverage provide opportunities for landslide detection and mapping. Landslide-prone regions are frequently obscured by cloud cover, limiting the utility of optical imagery. The capacity of SAR sensors to penetrate clouds allows the use of SAR satellite data to provide a more precise temporal characterization of the occurrence of landslides on a regional scale. The archived Copernicus Sentinel-1 satellite, which has a 6 to 12-day revisit period and covers the majority of the world's landmass, allows for more precise identification of landslide failure timings. The time-series of SAR amplitude, interferometric coherence, and polarimetric features (alpha and entropy) have strong responses to landslide failures in vegetated regions. This is characterized by a sudden increase or decrease in their values. Consequently, the abrupt shifts in the time-series of SAR-derived parameters, triggered by the failure, can be recognized and regarded as the failure occurrence time. The aim of this study is to determine the time period of failure occurrences by automatically detecting abrupt changes in the time series of SAR-derived parameters. We present a strategy for anomaly detection in time-series based on deep-learning to identify the failure time using four parameters derived from SAR time series. In this strategy, we introduce a gated relative position bias to an unsupervised Transformer model to detect anomalies in a multivariate time-series composed of four SAR-derived parameters. We conduct an experiment involving multiple landslides and compare the performance of our proposed strategy for detection of the failure time period with that of the LSTM model. Our strategy successfully identifies the time of landslide failure, which closely approximates the actual time of occurrence when compared to the LSTM model employed in this study.

How to cite: Wang, W., Motagh, M., Xia, Z., Plank, S., Li, Z., Orynbaikyzy, A., Zhou, C., and Roessner, S.: A deep Learning-based approach for landslide dating from time-series of SAR data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12097, https://doi.org/10.5194/egusphere-egu24-12097, 2024.

EGU24-13892 | ECS | Posters on site | NH3.6

Forecasting of rainfall-induced landslides in pyroclastic soil deposits through hydrometeorological information. 

Abdullah Abdullah, Pasquale Marino, Daniel Camilo Roman Quintero, and Roberto Greco

Shallow landslides pose a major geohazard impacting mountainous regions all around the world, and wide slope areas in Campania (southern Italy) covered by loose granular deposits overlapping a karstic bedrock are known for hosting the most destructive landslides of the region in the last decades. The landslide triggering factor in this case is clearly the rainfall. Nonetheless, there are concurring causes linked to the hydrological conditions predisposing slopes to failure (Bogaard and Greco, 2016). In the present study, the landslide-inducing factors are divided in static and dynamic (Moreno et al., 2023). The static factors (e.g., topography, slope, forest ratio) are well investigated in numerous studies on landslide susceptibility assessment. However, the modelling of dynamics factors (e.g., rainfall, soil moisture) is a relatively new issue and has been addressed only in few studies. In this study, Generalized Additive Models (GAMs) were applied for spaciotemporal data-based modelling of landslide prediction for eleven years (2010-2020). The study area is located on the Sarno and Partenio mountains in Campania where pyroclastic soil deposits cover about 370 km2 of carbonate massifs. In a first step, the modelling of static components, controlling landslide susceptibility in the area, was carried out by utilizing the historical data of landslide events along with other factors (slope, forest ratio etc.,) significantly affecting the static probability of landslide occurrence. Afterwards, the dynamic component was modelled by considering the triggering rainfall and the antecedent soil moisture for landslide events. The soil moisture data was taken from ERA5-Land soil moisture product. Lastly, the static and dynamic components were integrated to model the dynamic probability of landslide occurrence. A cross-validation technique was used for model training. The novel integrated model approach showed trustworthy improvements in the assessment of the probability of landslide. The model was also successfully tested for different rainfall events reproducing the landslide triggering conditions in the study area.

How to cite: Abdullah, A., Marino, P., Roman Quintero, D. C., and Greco, R.: Forecasting of rainfall-induced landslides in pyroclastic soil deposits through hydrometeorological information., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13892, https://doi.org/10.5194/egusphere-egu24-13892, 2024.

EGU24-14020 | ECS | Orals | NH3.6

Evaluating Landslide Susceptibility on the Big Sur Coast, California, USA using Complex Network Theory 

Vrinda D. Desai, Alexander L. Handwerger, and Karen E. Daniels

As a result of extreme weather conditions such as heavy precipitation, natural slopes can fail dramatically. While the pre-failure deformation is sometimes apparent in retrospect, it remains challenging to predict the sudden transition from gradual deformation to runaway acceleration. Recent advancements in remote sensing techniques, like satellite radar interferometry (InSAR), enable high spatial and temporal resolution measurements of deformation and topographic information, providing valuable insights into landslide detection and activity. 

Landslides are common on the Big Sur coast, Central California, USA due to active tectonics, mechanically weak rocks, and high seasonal precipitation. We use satellite InSAR data from Copernicus Sentinel-1A/B to identify 23 active landslides within our 175 km2 study site; one is Mud Creek, a slow-moving, deep-seated landslide that catastrophically failed in May 2017 and another is Paul’s Slide, which has experienced nearly constant motion for decades. 

We use multilayer networks to investigate the spatiotemporal patterns of slow deformation on the 23 active landslides. In our analysis, we transform observations of the study site — ground surface displacement (InSAR) and topographic slope (digital elevation model) — into a spatially-embedded multilayer network in which each layer represents a sequential data acquisition period. We use community detection, which identifies strongly-correlated clusters of nodes, to identify patterns of instability. We have previously shown [Desai et al., Physical Review E, 2023] that using high-quality data containing information about the fluidity (via velocity as a proxy) and susceptibility (slope) of the area successfully forecasts the transition of the Mud Creek landslide — the only formally slow-moving landslide in this collection to have catastrophically collapsed — from stable to unstable. 

Using multivariate analysis, we compare the traits of the active landslides, such as precipitation, vegetation, deformation, topography, NDVI, and radar coherence, against the results of the community detection. A strong indicator of instability is a combination of poor InSAR coherence and high displacement. Combined with community detection, we are able to differentiate between creeping landslides that are stable and landslides that display concerning trends that may warn of catastrophic failure.

How to cite: Desai, V. D., Handwerger, A. L., and Daniels, K. E.: Evaluating Landslide Susceptibility on the Big Sur Coast, California, USA using Complex Network Theory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14020, https://doi.org/10.5194/egusphere-egu24-14020, 2024.

EGU24-14188 | ECS | Posters virtual | NH3.6

A Non-Stationary Approach for Temporal Probability of Landslide using Hydrometeorological Thresholds 

Shamla Dilama Shamsudeen and Adarsh Sankaran

Landslides are one of the natural hazards that endanger life and property. Landslide research emphasises prediction based on the probability of triggering factors such as rainfall for use in early warning systems, and has implications for effective risk mitigation. Recent studies have focused on the probability of a landslide occurrence depending on hydrological factors such as soil moisture. The objective of the current study is to determine the temporal probability of landslide occurrence in a non-stationary framework using hydrometeorological parameters such as soil moisture and rainfall. The study was conducted in the Wayanad district of Kerala, India and area was divided into different zones inorder to account the spatial variation of rainfall and the topographical influence on the soil moisture. The non-stationary temporal probability estimation was performed using the generalised extreme value analysis. The hydrometeorological parameters, gridded rainfall and soil moisture data collected over a 42-year period (1981–2021), were analysed for the non-stationarity characteristics using the statistical tests for trend detection and Pettit test for the change point analysis. A monotonical trend in non-stationarity of the parameters were observed in the different regions of Wayanad. The temporal probability estimation for the future time periods was performed using the bias corrected GCM data and the landslide inventory data. The results showed that the exceedance probability of soil moisture based on the covariates improves the temporal probability of landslides when compared to the rainfall-based approach. The study is a novel and effective method for improving landslide prediction based on hydrological and meteorological factors under changing climate conditions, and for incorporating the same in early warning systems.

How to cite: Dilama Shamsudeen, S. and Sankaran, A.: A Non-Stationary Approach for Temporal Probability of Landslide using Hydrometeorological Thresholds, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14188, https://doi.org/10.5194/egusphere-egu24-14188, 2024.

EGU24-14949 | Posters on site | NH3.6

Modeling the impact of Hurricane Maria on Puerto Rico with an eco-hydrological landslide model 

Elisa Arnone, Evren M. Soylu, Furuya Takahiro, and Rafael L. Bras

This study proposes an advanced hydrologic/landslide modeling application to assess the spatial distribution of rainfall-induced landslides for a sub-basin in central Puerto Rico. The framework implements a stability component into a spatially distributed physically-based hydrological model coupled to a model of plant physiology. Puerto Rico is an ideal study site to assess the performance of landslide modeling efforts due to the availability of thousands of catalogued landslides triggered by Hurricane Maria (HMA) during September 19-22, 2017. The main objective of the study is to simulate the observed landslide events forcing a coupled eco-hydrological-stability model, the tRIBS-VEGGIE-Landslide, with weather data of HMA. The tRIBS-VEGGIE-Landslide model has the advantage of accounting for the vegetation dynamics that affect the soil moisture patterns at an hourly scale and for the soil-water characteristic curve and the saturated shear strength parameters (cohesion and friction angle) to assess the factor of safety (FS) in space and time, using an infinite slope model.

The modeling application focuses on two small sub-basins of the Rio Saliente watershed, each smaller than 1 km2. The small study area allows for the use of a 5m DEM resolution topography, which has been derived from a 1m resolution LiDAR measurements. Since many radar and ground stations were destroyed during the hurricane, the hourly time series of the HMA event has been reconstructed by using the NCEP (National Centers for Environmental Prediction) – Environmental Modeling Center (EMC) gridded Stage IV data, produced by NOAA National Weather Service. The precipitation data resulted in a maximum hourly intensity of 64.52 mm/hr, maximum daily intensity of 294.56 mm/day, and rainfall total of 332.15 mm, consistent with other daily reconstructions. Preliminary results demonstrate the importance of the spatial computational mesh and accurate characterization of soil parameters, which play an essential role in simulating landslides with mechanistic models.

How to cite: Arnone, E., Soylu, E. M., Takahiro, F., and Bras, R. L.: Modeling the impact of Hurricane Maria on Puerto Rico with an eco-hydrological landslide model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14949, https://doi.org/10.5194/egusphere-egu24-14949, 2024.

EGU24-15351 | ECS | Posters on site | NH3.6

Mapping landslide susceptibility through physically-based modeling 

Federica Angela Mevoli, Lorenzo Borselli, Michele Santangelo, Angelo Ugenti, Daniela de Lucia, Nunzio Luciano Fazio, and Mauro Rossi

Landslide susceptibility is the likelihood of a landslide occurring in a specific area based on the local terrain conditions. Susceptibility does not take into account the size, duration, or frequency of occurrence of landslides. Different approaches and methods have been proposed to determine the likelihood of occurrence of landslides: geomorphological mapping, analysis of landslide inventories, heuristic terrain zoning, statistically-based classifications and physically based numerical modelling (Aleotti and Chowdhury, 1999; Guzzetti et al., 1999). The last two approaches are preferred for assessing susceptibility in quantitative terms. Today, statistically based methods are preferred for small-scale landslide susceptibility zonations. Performing this task by using physically-based approaches is more challenging, as the performance of numerical analyses usually requires detailed geomechanical and hydrological data, whose collection demands significant time and costly efforts.

However, this work is primarily motivated by the following question: Can landslide susceptibility maps at smaller scales than detail-scale truly not be attained through the application of physically-based approaches?

The authors show their first attempt in answering the question through the combined application of Geographic Information Systems (GIS) and a 2.5D Limit Equilibrium Method (LEM) implemented using the SSAP software (Borselli, 2023). The results obtained in a study area in Southern Italy and the physically-based landslide susceptibility map derived at basin-scale are presented and discussed. This preliminary but yet reproducible analysis allows to drive future efforts in physically-based susceptibility zonation.

 

References

Aleotti, P., & Chowdhury, R. (1999). Landslide hazard assessment: summary review and new perspectives. Bulletin of Engineering Geology and the environment58, 21-44. DOI: https://doi.org/10.1007/s100640050066

Borselli L. (2023). "SSAP 5.2 - slope stability analysis program". Manuale di riferimento. Del codice ssap versione 5.2. Researchgate.   DOI: https://dx.doi.org/10.13140/RG.2.2.19931.03361

Guzzetti, F., Carrara, A., Cardinali, M., & Reichenbach, P. (1999). Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology31(1-4), 181-216. DOI: https://doi.org/10.1016/S0169-555X(99)00078-1

How to cite: Mevoli, F. A., Borselli, L., Santangelo, M., Ugenti, A., de Lucia, D., Fazio, N. L., and Rossi, M.: Mapping landslide susceptibility through physically-based modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15351, https://doi.org/10.5194/egusphere-egu24-15351, 2024.

EGU24-15580 | ECS | Orals | NH3.6

Landsifier 2.0: Towards automating landslide trigger and failure movement identification 

Lorenzo Nava, Kushanav Bhuyan, Manan Kapoor, Kamal Rana, Ascanio Rosi, Joaquin Vicente Ferrer, Ugur Ozturk, Mario Floris, Cees van Westen, and Filippo Catani

Understanding landslide failure processes is pertinent to predict and minimize the effects of landslides. A variety of elements, such as geology, topography, and soil conditions, can lead to slope failures triggered via natural causes e.g., rainfall and earthquakes, setting off the failure movements. Proper geotechnical analysis requires knowledge of both the triggering event and the subsequent movement patterns of the landslide. This information is vital for accurately predicting when and where landslides might occur. To integrate this information into existing landslide inventories, we introduce Landsifier 2.0, a tool designed to meet the needs of the landslide research community. This Python-based library allows seamless usage of machine learning models to extract information regarding landslide triggers and failure movements solely based on inventories of landslides. Powered by topology, a high-dimensional feature extraction module encapsulated within our library, information accessed via a landslide's shapes and configurations allows the identification of triggers (e.g., earthquake-and rainfall-triggered landslides) and failure movements (e.g., rotational slides, translational slides, debris flows, rock falls) of undocumented landslide inventories through continuous remote sensing missions. We showcase the library’s application in diverse geomorphological and climatic settings e.g., South-western China, Denmark, Turkey, Japan, Italy and more. We anticipate that Landsifier 2.0 will be particularly useful in the predictive modelling domain (including susceptibility and hazard modelling) of landslide studies, where precise information about triggers and failure dynamics is essential for developing reliable predictive models.


References:
Rana, Kamal, Uğur Öztürk, and Nishant Malik. 2021. “Landslide Geometry Reveals Its Trigger.” Geophysical Research Letters 48(4). doi: 10.1029/2020gl090848.
Rana, Kamal, Nishant Malik, and Uğur Öztürk. 2022. “Landsifier v1.0: A Python Library to Estimate Likely Triggers of Mapped Landslides.” Natural Hazards and Earth System Sciences 22(11):3751–64. doi: 10.5194/nhess-22-3751-2022.
Rana, Kamal, Kushanav Bhuyan, Joaquin Vicente Ferrer, Fabrice Cotton, Uğur Öztürk, Filippo Catani, and Nishant Malik. 2023. “Landslide Topology Uncovers Failure Movements.” arXiv (Cornell University). doi: 10.48550/arxiv.2310.09631.

How to cite: Nava, L., Bhuyan, K., Kapoor, M., Rana, K., Rosi, A., Vicente Ferrer, J., Ozturk, U., Floris, M., van Westen, C., and Catani, F.: Landsifier 2.0: Towards automating landslide trigger and failure movement identification, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15580, https://doi.org/10.5194/egusphere-egu24-15580, 2024.

Lvliang, located in Shanxi Province, was built on the loess plateau where the loess is characterized by high potential of collapsibility. Monsoonal precipitation, steep slopes, and anthropogenic activities such as coal mining make this terrain even more fragile. To better inform the farmland allocation, village relocation, and resettlement for the local residents, we have to assess the hazard exposure to fractures and landslides across the entire region. Here we use a double differencing method, i.e., computing the differential interferograms after applying distinct filtering windows, to pinpoint high-frequency signals suggesting drastic ground displacement. We further apply small baseline subset (SBAS) time-series analysis using Copernicus Sentinel-1 images collected from July 16th 2015 to May 16th 2023 to generate displacement time series. Our results show seasonal variations in displacement rates distributed on hillslopes. Our study demonstrates the efficacy of InSAR time series analysis in monitoring deformation with various natural and anthropogenic origins for the ultimate goal of disaster prediction, prevention, and reduction.

How to cite: Wu, P. and Hu, X.: Characterization of Ground Displacement over Mining Sites and Landslides in Lvliang, Shanxi Province, China, Using InSAR Time Series Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16453, https://doi.org/10.5194/egusphere-egu24-16453, 2024.

Strong earthquakes on mountain slopes can trigger numerous landslides, a significant secondary hazard responsible for a substantial proportion of fatalities in the affected area. In this study, we present a model framework for rapidly creating coseismic landslide probability distribution maps using machine learning models and optimal conditioning factors. To illustrate our approach, we focus on the case of the Mw 7.2 Haiti earthquake in 2021 and predict the distribution of coseismic landslides based on historical landslide data collected following the Mw 7.0 Haiti earthquake in 2010. To validate our findings, we mapped all the landslides triggered during the 2021 event. Furthermore, we conduct a comparative analysis of various landslide-conditioning factors (seismic, topographic, lithologic, and hydrological variables) in relation to the coseismic landslides occurring during both earthquake events in 2010 and 2021, to reassess the factors feed into the machine learning model. We observed noticeable differences in patterns of several conditioning factors between the two events EQIL distributions (e.g., tectonic and releif factors), but consistent similarities in other terrain factors (e.g., slope, curvature, topographic wetness index, etc.). Our Random Forest (RF) model, initially trained using the 2010 landslide inventory and 15 selected factors, effectively predicts 2021 landslides with an area under curve (AUC) score of 0.83. Improved performance is achieved when we use a reevaluated set of six factors for training, resulting in an AUC score of 0.90, with  93% of landslides falling into the high to medium probability class. These findings demonstrate the feasibility of rapidly generating highly accurate coseismic landslide distribution maps, even when there are considerable differences in key conditioning factors, highlighting the applicability of ML models to complex problems.

How to cite: Thanveer, J. and Pulpadan, Y. A.: Rapid Estimation of Earthquake Induced Landslides using Machine Learning Models: Insights from Haiti Earthquakes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16454, https://doi.org/10.5194/egusphere-egu24-16454, 2024.

Recent works on landslide displacement forecasting using machine learning or deep learning models show relevant performance. However, they are mostly based on the use of historical displacement information and do not provide information on the most predictive features in terms of meteorological and hydrogeological variables for the forecast, and thus the identification of possible precursory factors. In this context, providing approaches based on EXplainable Machine Learning (XML) is essential for landslide forecasting as it concerns making decisions about risk mitigation actions, it supports the identification of possible precursory factors and it increases confidence in the predictions.
The proposed XML-based landslide forecasting approach is developed and tested using ensemble learning methods such as Random Forest and XGBoost. It relies on the use of multi-year and multi-parameter data chronicles to analyse the relationships between surface displacements (target data) and hydro-meteorological conditions (predictor data). Displacement and meteorological data are acquired through the landslide monitoring network. Hydrological data, when not available, are simulated discharge calculated with reservoir based-model; the simulations allow to construct water level time series for each water reservoirs identified in the unstable slope.
The predictive time series are decomposed into a set of 340 descriptive features (mean, variance, difference, number of rainy days, number of consecutive rainy periods of X days, …). The displacement time series are detrended using the multiplicative decomposition method.
This method has been applied to several use cases, such as the Séchilienne landslide located southwest of the Belledonne massif (French Alps). The Random forest and XGBoost models are trained and tested over periods of 12 and 5 years respectively, and applied to three automatic extensometers located in the most active part of the landslide. The results indicate that the main features used include variations in water levels over past 10 to 30 days, as well as the number of consecutive rainy period during the month. These results are associated with accurate predictions for the three extensometers, with coefficients of determination ranging between 0.37 and 0.46.
We show that these models have high predictive power while informing about the most important hydro-meteorological features. The application of the models to trendless displacement time series significantly improves prediction accuracy.

How to cite: Maillard, O., Bertrand, C., and Malet, J.-P.: Forecasting landslide motion with EXplainable Machine Learning models: the use case of Séchilienne landslide (French Alps) to identify the relevant predicting variables, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16825, https://doi.org/10.5194/egusphere-egu24-16825, 2024.

Hybrid, physically constrained machine learning models combine the predictive power of machine learning approaches with the plausibility and interpretability of established physical models. The architecture of artificial neural networks (ANNs) allows to incorporate process-based constraints and physical laws to ensure a physically plausible and therefore generalizable model output.
Hybrid models have proven their utility in a variety of scientific domains and, most recently, in the Earth system sciences. They have been successfully applied to model the global hydrological cycle or ocean currents and sea surface temperatures.
However, up to now, the applicability of hybrid models has not yet been explored for landslide susceptibility and hazard modeling.
It is therefore our objective to shed light on the potential of hybrid, physically constrained slope stability models by assessing the predictive performance and plausibility of results as a prerequisite for a wider adoption of such approaches in landslide studies. We have embedded an established slope stability model in an ANN framework to overcome parameterization issues: The ANNs estimate the spatial distribution of soil properties and local soil cohesion as spatially variable latent inputs to the physically based model structure without requiring field or laboratory data of these parameters. As a case study, in cooperation with the Geological Survey of Slovenia (GeoZS) we have developed a landslide susceptibility map for the municipalities most affected by the disastrous rainfall event in August 2023.
Preliminary results show a good agreement with existing susceptibility maps produced with traditional slope stability models. Model parameters which would require extensive laboratory measurements for calibration could be plausibly estimated by machine learning. The hybrid approach furthermore allowed us to explicitly map these latent variables as a side product that supports model interpretation and can be evaluated with ancillary data that may become available in the future.
Building upon these results, we plan to expand the model's spatial and temporal domains. In doing so, we can assess this novel approach in terms of its transferability and generalization capabilities.

How to cite: Strohmaier, F. and Brenning, A.: Hybrid Physically Constrained Machine Learning Models of Landslide Susceptibility: a Case Study from Slovenia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17248, https://doi.org/10.5194/egusphere-egu24-17248, 2024.

EGU24-17785 | ECS | Posters on site | NH3.6

Application of beta regression for the prediction of landslide areal density in South Tyrol, Italy  

Mateo Moreno, Thomas Opitz, Stefan Steger, Cees van Westen, and Luigi Lombardo

The concept of landslide hazard entails evaluating landslide occurrence in space (i.e., where landslides may occur), in time (i.e., when or how often landslides may occur), and their intensity (i.e., how destructive landslides may be). At regional scales, data-driven methods are implemented to separately analyze the spatial component (i.e., landslide susceptibility) and the temporal conditions leading to landslide occurrence, such as rainfall thresholds. However, assessing how large a landslide may develop once triggered is seldom conducted and poses a persistent challenge to satisfying the complete definition of landslide hazard.

So far, only a few publications have addressed this issue by predicting the total areal extent of landslides based on certain mapping units, such as slope units. Limitations arise since the total areal extent of landslides within a mapping unit is strongly influenced by the size of the mapping unit, leading to larger mapping units being more likely to encompass larger total landslide areas. To tackle these challenges, this study aims to predict the landslide area proportion per slope unit in South Tyrol, Italy (7,400 km²). Our approach built upon past landslide occurrences from 2000 to 2020, systematically related to damage-causing and infrastructure-threatening landslide events. The method involved delineating slope units, filtering the landslide inventory, designing the sampling strategy, removing trivial areas, and aggregating the environmental variables (e.g., topography, lithology, land cover, and precipitation) to the slope unit partition. We tested a generalized additive beta regression model to estimate statistical relationships between the various static predictors and the target landslide areal density. The resulting spatially explicit predictions are evaluated through cross-validation from multiple perspectives. Applications and shortcomings of the approach are discussed.

The proposed method is anticipated to provide valuable insights and alternatives to assessing landslide intensity and moving toward landslide hazard in a data-driven context. The outcomes associated with this research are framed within the PROSLIDE project, which has received funding from the research program Research Südtirol/Alto Adige 2019 of the Autonomous Province of Bozen/Bolzano – Südtirol/Alto Adige.

How to cite: Moreno, M., Opitz, T., Steger, S., van Westen, C., and Lombardo, L.: Application of beta regression for the prediction of landslide areal density in South Tyrol, Italy , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17785, https://doi.org/10.5194/egusphere-egu24-17785, 2024.

EGU24-18279 | ECS | Posters on site | NH3.6

Representative Profile Model (RPM): A new physically-based model for assessing the hazards of colluvial landslides at local scale 

Xiao Feng, Juan Du, Bo Chai, Yang Wang, Fasheng Miao, and Thom Bogaard

The physically-based models for regional landslide hazard assessment typically use straight and homogeneous slope geometry and an infinite slope assumption. They assume that the sliding surface and saturation line are parallel to the surface, neglecting the variations in topography and soil thickness across different sections of the slope. This simplification can result in substantial inaccuracies in the regional landslide hazard assessment. To address these limitations, this study proposes a novel, spatially-distributed and physically-based model known as the Representative Profile Model (RPM). RPM distinguishes itself by using slope units rather than grid units, as the primary units of assessment. It efficiently integrates soil thickness and groundwater level information to automatically generate a detailed representative profile for each slope unit. These profiles include a ground surface line, a sliding surface, and a saturation line. This means that RPM can well take into account the effects of topographic relief and spatially uneven distribution of soil thickness for quantifying regional slope stability. Moreover, RPM combines the residual thrust method with the Monte Carlo method. This integration allows for the calculation of failure probabilities for each slope unit, thereby enabling comprehensive and complex susceptibility and hazard assessments at a local scale. A local scale assessment of landslide susceptibility and hazard in Tiefeng Township, Wanzhou District, Chongqing was carried out, with the RPM model. Subsequently, a comparative analysis was conducted with the TRIGRS model, which is based on grid units. The superior performance of RPM was clearly demonstrated by our findings.

How to cite: Feng, X., Du, J., Chai, B., Wang, Y., Miao, F., and Bogaard, T.: Representative Profile Model (RPM): A new physically-based model for assessing the hazards of colluvial landslides at local scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18279, https://doi.org/10.5194/egusphere-egu24-18279, 2024.

EGU24-18624 | Posters on site | NH3.6

Regional scale landslide susceptibility maps: strengths and weaknesses 

Paola Molin, Andrea Sembroni, and Gioia Vetere

Landslides are among the most dangerous natural hazards impacting on human life claiming lives and affecting economy and society. For this reason, the cost of the repeated occurrence of landslides could become unsustainable for a country. In this respect, the assessment of the susceptibility to landslide of a region becomes crucial to mitigate the economic and societal implications and to save lives. A typical approach starts from the inventory of landslides by field survey coupled with database consulting. This activity could assess the discriminating and predisposing factors, defining the weight of each of them on the slope stability. Overlaying resulting maps in GIS environment, a susceptibility map of each type of landslide could be produced. At local scale, the field survey allows to identify properly the past events and the factors that contributed to the instability. Unfortunately, sometimes managers and policy makers ask for landslide prediction regarding areas that are too large for a detailed field survey. As a consequence it is necessary to work out methods that start from available database. The main problem is to check the quality of the data and to eliminate possible errors. Starting from a classical susceptibility analysis based on landslide inventory derived from filed survey, we propose a modified method applicable to database on regional scale area. In detail, we check the quality of the database with respect to landslide locations eliminating unproper sites according to hillslope interval or rock-type, i.e. the two main discriminating factors. Our results show how this kind of approach allows to produce maps that are useful for general landscape management indicating the areas susceptible to each type of landslide. These preliminary maps are the basis for identifying the areas where more detailed studies are needed.

How to cite: Molin, P., Sembroni, A., and Vetere, G.: Regional scale landslide susceptibility maps: strengths and weaknesses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18624, https://doi.org/10.5194/egusphere-egu24-18624, 2024.

EGU24-18847 | ECS | Orals | NH3.6

A unified Bayesian model selection workflow for geophysical free-surface flow 

V Mithlesh Kumar and Julia Kowalski

The broad family of shallow flow models arises from depth-averaging the underlying governing balance laws. Depth-averaging yields an analytical model complexity reduction, increasing computational efficiency and reducing the number of model parameters. Consequently, shallow flow models become a desirable choice for various scientific and engineering applications, such as landslide prediction and coastal engineering. In the realm of landslide modelling, different variants of shallow flow models are often tailored - sometimes in an ad hoc manner - to specific physical phenomena, such as basal shear, non-hydrostatic effects, kinetics, or phase change processes. Therefore, selecting the most appropriate shallow flow model for a particular scenario based on quantitative reasoning poses a formidable challenge. Quantifying the uncertainty associated with this model selection is essential to assess the reliability of the predictions of these shallow flow models.

Here, we present a unified Bayesian model selection workflow leveraging Gaussian Process emulation — a machine learning technique used for non-intrusive physics-based machine learning. It starts with model calibration, where we generate posterior samples. These are then used to calculate the marginal likelihood, the basis for our model selection. This process faces two computational bottlenecks: significant computational costs involved in numerous model evaluations during calibration and high-dimensional, intractable integrals in the computation of Marginal Likelihood. To address the former, we integrated Gaussian process emulators into the workflow using PSimPy, our in-house Python package, for predictive and probabilistic simulations. For the latter bottleneck, we conducted a comprehensive literature review, with particular emphasis on marginal likelihood computation techniques based on Importance Sampling and implemented single proposal density schemes and integrated them into the workflow.

We demonstrate our approach using elementary landslide runout models across varying fidelity levels, investigating the impact of data representation—specifically, comparing point data to time series data—while considering data characteristics such as velocity and distance. Additionally, we calibrated the discrepancy parameter for robust handling of uncertainties associated with the data. Our future work will focus on implementing advanced importance sampling schemes to enhance the computation of the Marginal Likelihood, especially in high-dimensional scenarios. Furthermore, emphasis will be placed on adopting a hierarchical approach to address data uncertainty in conjunction with model inadequacy, which is not accounted for in the existing workflow.

How to cite: Kumar, V. M. and Kowalski, J.: A unified Bayesian model selection workflow for geophysical free-surface flow, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18847, https://doi.org/10.5194/egusphere-egu24-18847, 2024.

EGU24-20698 | Posters on site | NH3.6

Utilizing deep neural networks for landslide detection and segmentation in remote sensing imagery 

Jasmin Lampert, Lam Pham, Cam Le, Matthias Schlögl, and Alexander Schindler

Understanding the occurrences of historic landslide events is crucial for supporting strategies aimed at reducing disaster risks. Drawing from insights obtained in the 2022 Landslide4Sense competition, we present a methodological framework reliant on a deep neural network design for the detection and segmentation of landslides using input from various remote sensing sources. Our approach involves using a U-Net architecture, initially trained with cross entropy loss, as a baseline. We then enhance this architecture by employing diverse deep learning techniques. Specifically, we engage in feature engineering by creating new band data derived from the original bands, thereby improving the quality of the remote sensing image input. Concerning the network architecture, we substitute the conventional convolutional layers in the U-Net baseline with a residual-convolutional layer. Additionally, we introduce an attention layer that capitalizes on a multi-head attention scheme. Furthermore, we generate multiple output masks at three distinct resolutions, forming an ensemble of three outputs during the inference process to augment performance. Lastly, we propose a composite loss function that integrates focal loss and IoU loss to train the network effectively. Our experiments on the Landslide4Sense challenge's development set yield an F1-score of 84.07 and an mIoU score of 76.07. Our optimized model surpasses both the challenge baseline and the proposed U-Net baseline, improving the F1-score by 6.8/7.4 and the mIoU score by 10.5/8.8, respectively.

How to cite: Lampert, J., Pham, L., Le, C., Schlögl, M., and Schindler, A.: Utilizing deep neural networks for landslide detection and segmentation in remote sensing imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20698, https://doi.org/10.5194/egusphere-egu24-20698, 2024.

Dams, powerlines, and power plants represent strategic energetic infrastructures and their future operativity maintenance is a challenge. Stakeholders are strongly interested in evaluating the potential risks that may affect their functionality, especially regarding natural hazards. In Italy, geo-hydrological hazards triggered by rainfall such as floods and landslides represent a serious threat to electrical infrastructure, since their magnitude is generally difficult to modelling and quantify properly.

Here, we present an application of the model proposed by Borga et. Al. for rainfall-induced shallow landslide hazard assessment. The model merges an infinite slope stability equation with a simplified hydrogeological model evaluating, for a defined rainfall duration, the critical rainfall ratio able to trigger the landslide failure. The model has been adapted to work automatically using Python scripts and has been extended proposing a new strategy for evaluating the Dynamic Contributing Area and for including soil moisture information. Rainfall return time was considered as a proxy of the magnitude of the geo-hydrological events, identifying the most hazardous area with respect to the position of powerlines for the case study basin of Trebbia River, Emilia, Italy. Model results were validated against the currently available local rainfall threshold curves, showing good skill in failure detection.

The instrument could be useful for planning purposes, addressing, and quantifying the location under which the critical infrastructure may encounter risk with respect to geo-hydrological threats, and giving useful insights about possible mitigation strategies to increase the overall electro-energetic system resilience.

How to cite: Abbate, A. and Mancusi, L.: A fast geo-hazard assessment for electro-energetic network systems using a simplified geo-hydrological model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22521, https://doi.org/10.5194/egusphere-egu24-22521, 2024.

Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains. However, as two major factors affecting the stability of railway slopes, few scholars have explored the unstable evolution of railway slopes under the joint action of rainfall-vibration. Based on the model test of sandy soil slope, the unstable evolution process of slope under train vibration, rainfall, and rainfall-vibration joint action conditions is simulated in this paper. By comparing and analyzing the variation trends of soil pressure and water content of slope under these conditions, the change laws of soil pressure and water content under the influence of rainfall-vibration joint action are explored. The main control factors affecting the stability of slope structure under the joint action conditions are further defined. Combined with the slope failure phenomena under these three conditions, the causes of slope instability resulting from each leading factor are clarified. Finally, according to the above conclusions, the unstable evolution of the slope under the rainfall-vibration joint action is determined. The test results show that the unstable evolution process of sandy soil slope, under the rainfall-vibration joint action, can be divided into: rainfall erosion cracking, vibration promotion penetrating, and slope instability sliding three stages. If it is in a short period of time when the vibration starts or ends, the slope will also generate structural changes in vibration densification (vibration loosening). In the process of slope unstable evolution, rainfall and vibration play the roles of inducing and promoting slide respectively. In addition, the deep cracks, which are the premise for the formation of the sliding surface, and the violent irregular fluctuation of soil pressure, which reflects the near penetration of the sliding surface, constitute the instability characteristics of the railway slope together. This paper reveals the unstable evolution of sandy soil slopes under the joint action of rainfall-vibration, hoping to provide the theoretical basis for the early warning and prevention technology of railway slopes.

How to cite: Haoyu, D.: Unstable evolution of railways slope under the rainfall-vibration joint action, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-137, https://doi.org/10.5194/egusphere-egu24-137, 2024.

Much of Aotearoa NZ is hilly or mountainous and experiences high rainfall and frequent earthquakes. Consequently, landslides are an existing or potential hazard in many parts of the country, with the risk from landslides likely to increase with climate change. Cyclone Gabrielle (February 2023) highlighted the devasting impact of such landslides on people, property, and infrastructure networks. To increase the resilience of Aotearoa NZ to landslide-induced disasters, we need robust and consistent information that creates an evidence base to inform effective decision-making in the management of landslide risk nationwide, considering planners, policy-makers, emergency managers and government officials, lifeline and infrastructure managers, as well as other technical experts (e.g., engineers). This decision-relevant information needs to include when and where landslides occur, who and what they may impact, and how people, businesses, and communities perceive, mitigate, and respond to this hazard.

In this presentation we will detail how the new Hōretireti Whenua / Sliding Lands five-year Endeavour programme will integrate social science into the development of new probabilistic and scenario-based, nationally applicable, landslide hazard and risk models that can incorporate climate change scenarios. We will first introduce the vision for the integrated landslide risk models which will include: a) probabilistic models of landslide susceptibility considering earthquakes and rain, b) landslide runout models considering diverse landslide types, c) the multi-hazard risk modelling tool (RiskScape) to integrate hazard and vulnerability model components into forecast models, and d) the MERIT Tool to quantify the socio-economic impact of landslide hazards.

We will then present initial results from the first phase of associated social-science research that has mapped the range of decision maker needs for susceptibility, impact, and risk information, considering different decision sectors, demands, and timescales. Developed from this, a set of user personas and decision-scenarios will inform the effective communication of landslide risk across stakeholder groups, as well as inform effective application of the landslide risk models into decision-making for short-term risk management and long-term resilience. We will also present plans to investigate how individuals and organisations conceptualise landslide phenomena, models, and vulnerabilities using research techniques such as mental models and influence diagrams; with a view to integrating findings to not just improve communication of model outputs, but to also enhance decision-makers understanding of the national risk models. Through this we aim to increase effective uptake of these risk models into stakeholder decision-making across diverse organisations and sectors.

How to cite: Hudson-Doyle, E. and de Vilder, S.: Introducing Hōretireti Whenua / Sliding Lands:  integrating social science into nationally applicable landslide risk models for Aotearoa NZ, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1437, https://doi.org/10.5194/egusphere-egu24-1437, 2024.

EGU24-3185 | ECS | Orals | NH3.7

Dynamic Susceptibility of Rainfall-Induced Landslides: A Gated Recurrent Unit Approach 

Jana Lim, Giorgio Santinelli, Ashok Dahal, Anton Vrieling, and Luigi Lombardo

Globally, there is an urgent need for accurate and effective Landslide Early Warning Systems (LEWS). Most LEWS are currently based on a single aggregated measure of rainfall derived from either in-situ measurements or radar estimates. Relying on a summary metric of precipitation may not capture the intricacies of rainfall dynamics that could improve landslide prediction. Here, we present a proof-of-concept for constructing a LEWS that is based on an integrated spatio-temporal modelling framework. Our proposed protocol builds upon a recent approach that uses the entirety of the rainfall time series instead of the traditional cumulated scalar approximation. Specifically, we use a Gated Recurrent Unit to process the whole rainfall signal and combine the output features with a second neural network dedicated to incorporating terrain characteristics. We benchmark this approach against a baseline run that relies on terrain and a cumulative rainfall metric. Our protocol leads to better performance in the context of hindcasting landslides which uses past rainfall estimates from CHIRPS. This provides a stronger case to repeat the same experiment using weather forecasts. If analogous results are produced in the forecasting context, this could justify adopting such models for operational purposes.  

How to cite: Lim, J., Santinelli, G., Dahal, A., Vrieling, A., and Lombardo, L.: Dynamic Susceptibility of Rainfall-Induced Landslides: A Gated Recurrent Unit Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3185, https://doi.org/10.5194/egusphere-egu24-3185, 2024.

Precipitation-triggered landslides resulting from prolonged and/or intense storms threaten lives and damage infrastructure throughout the world each year.  In the United States, population centers along the West Coast (e.g., Seattle, Washington; Portland, Oregon; San Francisco, California) have particularly high risk from landslides due to the intersection of typical cool season (October through May) Pacific cyclone storm tracks with intense urbanization located on and near steep hillslopes.  Past efforts on landslide early warning in California dating to the late 1970s and running through the mid-1990s were initially focused on the development of rainfall intensity-duration thresholds coupled with a recognition that little landsliding tended to occur prior to an antecedent rainfall condition being reached – essentially a proxy for soil saturation.  However, available technology at the time did not allow for economic and logistically viable subsurface monitoring of in situ hydrologic conditions in steep, landslide prone terrain.  In 2009, the U.S. Geological Survey (USGS) began development of a regional subsurface hydrologic monitoring network in the San Francisco Bay area to assist with keeping emergency managers informed about periods of elevated hazard from rainfall-induced shallow landslides.  The network currently consists of four stations, each located within hillslopes susceptible to shallow landslide initiation and representative of those that have failed in the past.  The stations are spatially arranged to capture the meteorological variability of the approximately 18,000 km2 region.  Each station consists of two monitoring nests with soil moisture and piezometric level sensors placed at variable depths within the typically 0.5 to 1-m-deep soil profiles.  The goal of the monitoring network is to identify the time frame(s) during which soil saturation may be reached during storms and thus enable generation of positive pore water pressures that can cause shallow landslide initiation.


Using the more than 10-year record of soil moisture time series data available from the network stations, combined with piezometric records indicating times of positive pore water pressure and observations of triggered landslides, we developed soil moisture thresholds that are now used for situational awareness to alert for the potential for widespread shallow landsliding and debris flows ahead of incoming storms.  Messaging indicating that hillslope soils are nearing or are at saturation is provided to the U.S. National Weather Service (NWS) several days ahead of storms to provide for sufficient time for communication with emergency managers so that they may identify and prepare appropriate resources for response should landslides occur.  The monitoring network, combined with established USGS-NWS communication protocols, has been successfully used to alert for expected landslide conditions in numerous storm events over the past 10 years, including the precipitation-record-setting 2022-2023 winter season.  Ongoing research is aimed at updating thresholds with recent data and developing semi-automatic routines for monitoring and alerting.

How to cite: Collins, B. D., Corbett, S. C., and Brien, D. L.: Development and implementation of subsurface hydrologic thresholds for identifying widespread shallow landslide and debris flow occurrence in the San Francisco Bay area (California, USA), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7260, https://doi.org/10.5194/egusphere-egu24-7260, 2024.

EGU24-7505 | Posters on site | NH3.7

Demonstration of a deep-learning-based system for rainfall induced shallow landslides forecasting in Italy 

Massimo Melillo, Fausto Guzzetti, Michele Calvello, Gaetano Pecoraro, and Alessandro C. Mondini

A common and largely unresolved problem of national-scale landslide early warning systems is their independent evaluation. In this work, we evaluated the performance of a recently proposed deep-learning-based system for short-term forecasting of rainfall-induced shallow landslides in Italy. For our evaluation, we used hourly rainfall measurements from the same rain gauge network used to construct the forecasting system, and different and independent information on the timing and location of 163 rainfall-induced landslides that occurred in Italy in a period non considered in the construction of the forecasting system, obtained from the FraneItalia catalogue (https://zenodo.org/records/7923683). The independent evaluation confirmed the good predictive performance of the forecasting system and revealed no geographical or temporal bias in the forecasts. The analysis also revealed that the forecasting system was more effective at predicting multiple landslides in the same general area than single landslides. This was a good result, as multiple landslides are potentially more dangerous than single failures. Analysis of the few misclassified landslide cases showed that approximately one-third of the landslides were rockfalls, and for approximately another third there was uncertainty about when or where the landslides occurred. We conclude that, despite the inevitable misclassifications inherent in any probabilistically based national-scale landslide forecasting system, the deep-learning-based system analysed is well suited for short-term operational forecasting of rainfall-induced shallow landslides in Italy.

How to cite: Melillo, M., Guzzetti, F., Calvello, M., Pecoraro, G., and Mondini, A. C.: Demonstration of a deep-learning-based system for rainfall induced shallow landslides forecasting in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7505, https://doi.org/10.5194/egusphere-egu24-7505, 2024.

EGU24-7684 | Posters on site | NH3.7

Weather scenarios associated with rainfall-induced landslides in the Liguria Region, Italy 

Maria Teresa Brunetti, Stefano Luigi Gariano, Monica Solimano, Massimo Melillo, Silvia Peruccacci, Pietro Gabriele De Stefanis, and Michele Cicoria

Liguria is an Italian region bordered on the North by the Alps and on the South by the Thyrrenian Sea. This geographical location and its topography lead to the occurrence of numerous weather scenarios. The rainfall pattern and the steep topography give rise to frequent landslide events in the region.

This work aims to investigate the relationship between the occurrence of landslides and different weather scenarios.

A catalogue with detailed spatial and temporal information on 475 rainfall-induced landslides that occurred in Liguria region in 2019 and 2020 is available and is used to perform the analysis.

Forecasts of local atmospheric conditions for the Liguria region are calculated daily by the Regional Agency for the Environmental Protection of Liguria region (ARPAL), and are used to issue regional weather vigilance bulletins to be used by the civil protection authority to give geo-hydrological alerts. The atmospheric conditions are classified in 7 weather scenarios and 8 sub-scenarios by ARPA. The classification is based on both the synoptic circulation and the types of precipitation and antecedent conditions. We observe that the most frequent scenario associated with landslide occurrences in the region is the “West-Southern weather pattern”, whereas the most frequent sub-scenario is the “Intense rainfall and rainstorms”.

Temporal analyses are carried out to assess variations in the monthly distribution of the weather scenarios. In addition, the characteristics of the rainfall conditions responsible for the failures are evaluated to search for peculiarities related to different weather scenarios.

 

This work was supported by the 2021-2023 Cooperation Agreement between CNR-IRPI and the Regional Agency for the Environmental Protection of Liguria region (ARPAL), Italy, and the PRIN-ITALERT project (PRIN2022 call - grant number: 202248MN7N, CUP: B53D23006720006) funded by NextGenerationEU.

How to cite: Brunetti, M. T., Gariano, S. L., Solimano, M., Melillo, M., Peruccacci, S., De Stefanis, P. G., and Cicoria, M.: Weather scenarios associated with rainfall-induced landslides in the Liguria Region, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7684, https://doi.org/10.5194/egusphere-egu24-7684, 2024.

EGU24-8781 | Posters on site | NH3.7

Technologies and innovative multi-scale tools for landslide risk prevention: the activities of the first year within the Innovation Ecosystem “Tech4You”. 

Roberto Coscarelli, Nicola Moraci, Giovanni Gullà, and Tommaso Moramarco

With the current climate change, the attention is more and more focused on “adaptation strategies”, that take place by multi-stakeholder actions (research, businesses, society and government) towards resilient communities. With these aims, the PNRR Innovation Ecosystem “Tech4You - Technologies for climate change adaptation and quality of life improvement” has been proposed by a partnership including public (University of Calabria, University “Magna Graecia” of Catanzaro, University “Mediterranea” of Reggio Calabria, University of Basilicata, Consiglio Nazionale delle Ricerche, etc.) and some private partners. Tech4You has been funded by means of the Next Generation EU Program, through the Italian Ministry of University and Research and lasts three years. Within the cited R&I Project, the Spoke 1 “ANTARES - CirculAr techNologies to miTigate geo-hydrologicAl and foRest firE riskS” includes the Goal “Technologies and innovative multi-scale tools for landslide risk prevention” articulated in two Pilot Projects (PPs). PPs aim to: a) make multi-scale and interdisciplinary on-site laboratories as demonstration systems and knowledge generators and as decision support for the management of landslide risk (adaptation, mitigation/reduction) and b) propose methods and tools for quantitative modelling of diffuse and local landslides, training the planning, the scheduling and the designing of landslide risk adaptation, mitigation/reduction activities.

The first year of activity has been addressed to the collection of databases, from various sources, regarding climatic, geological, geotechnical, morphological, etc. and models and methods for landslide triggering and evolution, already implemented and tested in other study areas. In this way, a first draft of the Catalogues and Libraries is being created, to be continuously upgraded, during the project and after its end. The proposed approach is circular and multi-scale based, spanning from regional scale (Calabria and Basilicata) to basins and detailed scale, finalized to in-situ laboratories.  Results, at the end of the Project, will be friendly used and updated, with a circularity and multidisciplinary approach, by various stakeholders, such as national, regional and territorial administrations, freelancers, enterprises, communities, etc. For that, the come up with a general platform and dedicated platforms will be realized by companies or Consortium of companies, selected by means of Public Tender (called “Cascade Calls”).         

 

This work was funded by the Next Generation EU - Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of 'Innovation Ecosystems', building 'Territorial R&D Leaders' (Directorial Decree n. 2021/3277) - project Tech4You - Technologies for climate change adaptation and quality of life improvement, n. ECS0000009. This work reflects only the authors’ views and opinions, neither the Ministry for University and Research nor the European Commission can be considered responsible for them.

How to cite: Coscarelli, R., Moraci, N., Gullà, G., and Moramarco, T.: Technologies and innovative multi-scale tools for landslide risk prevention: the activities of the first year within the Innovation Ecosystem “Tech4You”., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8781, https://doi.org/10.5194/egusphere-egu24-8781, 2024.

EGU24-9587 | ECS | Orals | NH3.7

Uncertainty analysis of 3D hydrometeorological thresholds for rainfall-induced landslides forecasting  

Pasquale Marino, Daniel Camilo Roman Quintero, Giovanni Francesco Santonastaso, and Roberto Greco

Rainfall-induced landslides are widespread geohazards, often characterized by shallow and fast movements. Their occurrence is not easily predictable. Particularly, southern Apennines of Campania (Italy), widely covered by loose pyroclastic deposits laying upon limestone bedrock, are often subjected to massive shallow landslides after intense and long precipitation. The operational early warning systems for rainfall-induced landslides (LEWS) usually rely on empirical thresholds based only on the precipitation information (e.g., intensity and duration of rainfall event), which give rise to false and missed alarms. The reliability of landslide prediction would benefit from the inclusion of hydrological information about the state of the slope prior to rainfall events. In fact, in the last decade, novel hydrometeorological thresholds that mix hydrologic predisposing factors and the features of rainfall events have been developed for landslide forecasting. Specifically, adding information linked to major hydrological processes occurring in the slope improves the performance of LEWS.

The study refers to landslide-prone areas nearby the town of Cervinara, on the slopes of Partenio Massif, representative of a geomorphological setting typical of wide areas of Campania (Italy). Firstly, to obtain a significant data series for statistical analyses, a 1000-year hourly synthetic dataset, mimicking the hydrological response of the slope to meteorological forcing, was generated. Specifically, a stochastic NSRP rainfall model was coupled with a physically based model of the unsaturated flow through the soil cover, hydraulically connected to a linear reservoir simulating a perched aquifer which develops in the uppermost part of the bedrock during the wet season. Both the models had been previously calibrated and validated based on field monitoring data. The synthetic dataset of the slope cover response to precipitation is obtained in terms of soil suction and water content, and perched aquifer water level. The stability of the slopes is assessed under the infinite slope hypothesis, allowing the identification of the occurrence of landslides. The results highlight how novel approaches in the definition of thresholds, considering the 3D hydrometeorological space (i.e., root zone soil moisture, aquifer water level and rainfall event depth), can significantly improve their predictive performance, compared to the common bidimensional thresholds based either on meteorological or hydrometeorological variables.

Moreover, in real practical applications for landslide forecasting, it is not always possible to implicitly assume a perfect knowledge of the variables to be measured for defining the thresholds, especially for a wide area. In fact, both the hydrological and meteorological variables are affected by significant uncertainty, mainly owing to spatial variability. Similarly, the calculated factor of safety, based on the simulated soil moisture and pressure and the assumed soil physical parameters, can be affected by uncertainty, as slope morphological characteristics and soil hydraulic and geotechnical properties are also variable in space. Thus, in this respect, the effects of the uncertainty of slope geomorphological characteristics, as well as of soil hydraulic and geotechnical properties, embedded as probabilistic variables, have been investigated on the obtained 3D hydrometeorological thresholds and on the corresponding predictive performance.

How to cite: Marino, P., Roman Quintero, D. C., Santonastaso, G. F., and Greco, R.: Uncertainty analysis of 3D hydrometeorological thresholds for rainfall-induced landslides forecasting , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9587, https://doi.org/10.5194/egusphere-egu24-9587, 2024.

EGU24-9720 | ECS | Posters on site | NH3.7

Regional-scale landslide forecasting using physics-based slope stability models  

Minu Treesa Abraham, Luca Piciullo, Zhongqiang Liu, Haakon Robinson, Erling Singstad Paulsen, and Ann Elisabeth Albright Blomberg

With the increasing frequency of high intensity rainfall events, landslides on natural slopes have become a critical concern from a disaster management perspective. Rainfall-induced landslides are caused by the reduction in the soil shear strength due to the increased pore water pressure induced by rainfall and/or rapid snowmelt. It is important to understand the mechanism of failure for employing reliable early warning and effective risk reduction strategies. Geotechnical slope stability analysis can be carried out easily on a slope scale, however, extending this at a regional scale is demanding due to the spatial variability of hydrological and geotechnical properties. Physics-based landslide susceptibility models are designed with the explicit goal of using hydrological mechanisms for the identification of possible landslide source areas, primarily computing factor of safety (FS) values on a grid.  However, given that the majority of these models operate independently, integrating them into a fully automated Landslide Early Warning Systems (LEWS) remains a significant technical challenge. This work proposes a methodology that leverages meteorological forecasts sourced from the MET Weather Application Programming Interface (API), in conjunction with topographical and soil properties, to project Factor of Safety (FS) values on an hourly basis. A case study from Norway has been used as a pilot for the demonstration of the method proposed. The forecasted FS values are dynamically visualized in real-time within the data platform of the Norwegian Geotechnical Institute, NGI Live, which can also be used as a map overlay for other infrastructure projects in the study area. The proposed method holds the promise of providing physics-based decision support for disaster risk reduction and critical infrastructure management efforts.

How to cite: Abraham, M. T., Piciullo, L., Liu, Z., Robinson, H., Paulsen, E. S., and Blomberg, A. E. A.: Regional-scale landslide forecasting using physics-based slope stability models , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9720, https://doi.org/10.5194/egusphere-egu24-9720, 2024.

EGU24-9805 | ECS | Orals | NH3.7

Improving landslide triggering thresholds using artificial neural networks and reanalysis multi-layer soil moisture information  

Nunziarita Palazzolo, David J. Peres, Pierpaolo Distefano, Luca Piciullo, Pietro Scandura, and Antonino Cancelliere

Landslide prediction is crucial for the design of early warning systems, and the integration of soil moisture information aims to enhance the accuracy of such predictions. This study focuses on the development of artificial neural networks (ANNs) designed to recognize conditions that trigger landslides, incorporating soil moisture data alongside precipitation. Specifically, using ANNs, we investigate the advantage of deriving thresholds without a specific parametric equation, and, due to their flexibility to incorporate multiple input variables, they allow for a comprehensive analysis of landslides. Specifically, the research utilizes observed precipitation and ERA5-Land reanalysis soil moisture data at four different depth layers. To assess the effectiveness of the proposed approach under diverse climatic and geomorphological conditions, two distinct case studies are considered, namely Sicily Island (Italy) and a group of catchments in the Bergen area of Norway. The proposed methodology involves three main steps: i) the acquisition of rainfall and landslide data; ii) the creation of a database of triggering (TE) and non-triggering (NTE) events; iii) the development of ANNs predicting when a landslide is triggered from input precipitation and soil moisture data. A measure of the prediction uncertainty of the developed ANN models, related to the fact that a limited sample of triggering events may be available, is also carried out. Overall, the developed ANN classifiers, incorporating soil moisture information in addition to precipitation, prove to have better predictive performance than those relying solely on precipitation data. In our study, we also carry out comparisons to traditional power law thresholds, derived by optimizing the true skill statistic (TSS) based on cumulative precipitation and duration (E-D). While the power law E-D thresholds reach a TSS equal to 0.50 for both study areas, the inclusion of soil moisture information can lead to significant performance improvements, yielding TSS values up to about 0.90. These results corroborate the potentialities of the use of soil moisture information and machine learning techniques in improving landslide prediction. 

How to cite: Palazzolo, N., Peres, D. J., Distefano, P., Piciullo, L., Scandura, P., and Cancelliere, A.: Improving landslide triggering thresholds using artificial neural networks and reanalysis multi-layer soil moisture information , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9805, https://doi.org/10.5194/egusphere-egu24-9805, 2024.

EGU24-10745 | ECS | Posters on site | NH3.7

IoT monitoring and reanalysis data of soil moisture and rainfall for landslide warning: a test case 

Rosa Menichini, Gaetano Pecoraro, and Michele Calvello

Shallow rainfall-induced landslides are triggered by intense or prolonged rainfall. Warning models employed within territorial landslides early warning systems (Te-LEWS) are typically based on rainfall thresholds expressed in terms of cumulative rainfall or average intensity with respect to the duration of the rainfall event, completely neglecting antecedent conditions. However, recent studies demonstrated that introducing, directly or by means of models, the effects of antecedent soil moisture content in empirical thresholds can improve the performance of the warning models.

This preliminary study focuses on the definition of a pilot monitoring site that produces rainfall and soil moisture data measured by an Internet of Things (IoT) monitoring network and by the use of analogous reanalysis products (i.e., ERA5-Land dataset). The activities are being developed in the context of the Horizon Europe project “The HuT: The Human-Tech Nexus - Building a Safe Haven to cope with Climate Extremes”. The final aim is to use IoT monitoring of rain and soil moisture, combined with reanalysis data, to improve, at municipal level, the territorial warning procedures already existing and operational at regional level.

The test site has been installed within the Campus of the University of Salerno in Fisciano, Campania region (Italy) since February 2023. The pilot site has been instrumented with sensors monitoring soil moisture from different providers and with a weather station; the sensors have been installed at different depths and with different procedures. The collected data were analyzed and processed using various data analysis algorithms, with the aim of: i) establishing correlations between the local weather conditions and the hydrologic soil response; ii) make a comparison between the data collected from different providers and in different local conditions.

Establishing these relationships allowed to evaluate the peculiarities and reliability of the different sensors and to identify the best configuration for future in-situ installations. More generally, this study highlights the importance of developing a monitoring network based on diffuse low-cost sensors and a proper real-time data transmission, analysis and processing, in order to provide further knowledge to system managers of territorial warning systems in the analysis of the monitoring data, and thus support for their decisions before and during extreme weather conditions.

How to cite: Menichini, R., Pecoraro, G., and Calvello, M.: IoT monitoring and reanalysis data of soil moisture and rainfall for landslide warning: a test case, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10745, https://doi.org/10.5194/egusphere-egu24-10745, 2024.

EGU24-11530 | Posters on site | NH3.7

Optimized 3D rainfall thresholds: false alarms reduction and multi-source validation 

Samuele Segoni, Nicola Nocentini, Camilla Medici, Francesco Barbadori, Alessio Gatto, Rachele Franceschini, Matteo Del Soldato, and Ascanio Rosi

A regional-scale landslide forecasting model based on rainfall thresholds was optimized for operational early warning. In particular, we addressed two main issues that usually hinder the operational implementation of this kind of models: (i) the excessive number of false alarms, resulting in civil protection system activation without any real need, and (ii) the validation procedure, usually performed over periods too short to guarantee model reliability.

To overcome these limitations, several techniques for reducing the number of false alarms were applied in this study, and a multiple validation phase was conducted using data from different sources. An intensity-duration threshold system for each of the five alert zones composing the Liguria region (Italy) was identified using a semiautomatic procedure called MaCumBA, considering three levels of criticality: low, moderate, and high. The thresholds were developed using a landslide inventory collected from online newspapers by a data mining technique called SECaGN. This method was chosen to account for only those events that echo on the Internet and therefore impact society, ignoring landslides occurred in remote areas, not of interest for civil protection intervention and resulting in false alarms. A calibration phase was performed to minimize the impact of false alarms, allowing at least one false alarm per year over the moderate criticality level. A novel datset containing only very severe disasters that required national-level emergencies was used to calibrate the high criticality threshold. In addition, we applied an innovative approach to include an antecedent rainfall indicator as third variable. The threshold is thus not represented by a traditional line in a 2D spce, but by a plane in a 3D space.

This approach allowed for a consistent reduction in false alarms. The results were validated through an independent landslide inventory and were compared with (i) the alert issued by the regional civil protection agency to observe the improvements achieved with the proposed model and to evaluate to what extent the proposed model is consistent with the assessments of the civil protection and (ii) a dataset of the national states of emergency to verify the suitability of the developed thresholds for alerting citizens. The 3D thresholds showed high predictive capabilities, confirming their suitability for implementation in an operational landslide early warning system.

How to cite: Segoni, S., Nocentini, N., Medici, C., Barbadori, F., Gatto, A., Franceschini, R., Del Soldato, M., and Rosi, A.: Optimized 3D rainfall thresholds: false alarms reduction and multi-source validation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11530, https://doi.org/10.5194/egusphere-egu24-11530, 2024.

EGU24-11561 | ECS | Posters on site | NH3.7

Submarine landslides, tsunami and hydroacoustic waves: simulation and sensitivity analysis 

Juliette Dubois, Sébastien Imperiale, Anne Mangeney, and Jacques Sainte-Marie

We simulate the generation of acoustic and tsunami waves generated by submarine landslides using the linear model developed in [1]. The model is able to reproduce both acoustic and surface gravity waves generated by a moving source (e.g. earthquake, landslide) in a vertically stratified ocean.

There are only a few studies that focus on the generation of acoustic waves by submarine landslides. In [2], the combined analysis of field data and simulations underline the presence of an interference pattern in the acoustic waves' spectrogram. The interference pattern has a time-varying bandwidth, which is a signature of the submarine landslide dynamics. In a previous work [3], we used the model developed in [1] to reproduce the interference pattern for a static source.

Here we use the same model to simulate a submarine landslide in the 2D case. The simulations reproduce the time-varying bandwidth. They are then used to study the influence of two parameters on the acoustic spectrograms, namely landslide velocity and topography. Different velocity profiles available in the literature [4] are tested. For the topography, we use as reference the 2D case simulated in [1]. We also provide illustrations for the tsunami generation by the landslide.

[1] Dubois J, Imperiale S, Mangeney A, Bouchut F, Sainte-Marie J. Acoustic and gravity waves in the ocean: a new derivation of a linear model from the compressible Euler equation. Journal of Fluid Mechanics. 2023;970:A28. doi:10.1017/jfm.2023.595

[2] Caplan-Auerbach, J., Dziak, R. P., Bohnenstiehl, D. R., Chadwick, W. W., and Lau, T.-K. (2014), Hydroacoustic investigation of submarine landslides at West Mata volcano, Lau Basin, Geophys. Res. Lett.,  41,  5927 5934, doi:10.1002/2014GL060964.

[3] Dubois, J., Imperiale, S., Mangeney, A., and Sainte-Marie, J.: Simulation of the hydro-acoustic and gravity waves generated by a landslide, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15937, https://doi.org/10.5194/egusphere-egu23-15937, 2023.

[4] Farin, M., Mangeney, A., de Rosny, J., Toussaint, R., & Trinh, P.-T. (2019). Relations between the characteristics of granular column collapses and resultant high-frequency seismic signals. Journal of Geophysical Research: Earth Surface, 124, 2987–3021. https://doi.org/10.1029/2019JF005258

How to cite: Dubois, J., Imperiale, S., Mangeney, A., and Sainte-Marie, J.: Submarine landslides, tsunami and hydroacoustic waves: simulation and sensitivity analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11561, https://doi.org/10.5194/egusphere-egu24-11561, 2024.

The Himalayan belt includes the geologically unstable mountainous terrain of upper Uttarakhand, which is distributed throughout Sonprayag, Sitapur, Rampur, Barasu, Kalimath, Madhyamaheshwar, Chamoli, Birahi, Byasi, and Atali.

There are many more mountain ranges in the region. The rains that fall during the monsoon season are the most common cause of landslides in this mountain chain, whereas earthquakes and aftershocks are the least common cause. Hill slopes are becoming unstable as a result of human involvement in nature,

which includes activities such as cutting roads without following scientific principles, dumping garbage along roadsides, using landslide , deformation, and illegal mining operations, among other things. Once the prone regions have been identified and hazard zonation maps have been prepared, it will be possible to protect the different entitlements that are at risk due to the landslip threat.

The current investigation is an inventory-based technique that makes use of satellite data in order to determine the grey regions that exist within the region. The topo sheets of India, the geological maps that are already in existence, the data from remote sensing, the historical landslip data from 2010 to 2023, and the field inspection were all done. It is possible to construct primary topographic data with the use of a Digital Elevation Model (DEM), which includes aspects, slopes, curvatures, hill shades, mean curvatures, plan curvatures, relief, and drainage density respectively.  Afterwards, a Landslip Hazard Zonation (LHZ) Map is created by superimposing several theme layers. This is done in order to facilitate the process of making logical decisions and to facilitate the implementation of mitigation measures in advance of an occurrence. The observed landslip is mostly composed of rock and boulder falls as well as debris flow. Within this complex network of mountain ranges, there are significant dynamic sites that need the attention of scientists for further investigation. The findings will be disseminated to catastrophe authorities and governmental organizations in order to facilitate the development of contingency plans for dealing with future occurrences.

How to cite: Anand, A. and Bhardwaj, A.: Unmanned Aerial Vehicles and Terrestrial Laser Scanning are used to Monitor Kshetrapal landslides in the Chamoli Hazard Areaof Upper Himalayan Region in Uttarakhand, India., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11755, https://doi.org/10.5194/egusphere-egu24-11755, 2024.

EGU24-12607 | Orals | NH3.7

Investigating recent weather-induced landslides and the related weather characteristics in a test area in Campania Region (Italy) for warning purposes 

Guido Rianna, Gennaro Sequino, Gaetano Pecoraro, Alfredo Reder, and Michele Calvello

The municipalities of the Amalfi and Sorrento Coasts (Campania Region, southern Italy) have historically been affected by weather-induced slope instability phenomena causing casualties and heavy economic damages, often associated with transport interruptions limiting the crucial tourist activities in the area. Due to the considerable geomorphological complexity of the area, even the simple cataloguing of the events is often challenging. Furthermore, the significant differences between the dynamics affecting the slopes (rockslides, debris flows, flowslides in pyroclastic covers) result in substantial differences in the atmospheric patterns able to trigger such events: from short-duration (up to sub-hourly scale) heavy precipitation events up to long-lasting rainfalls anticipated by particularly wet periods. Despite the significant differences among the dynamics, the warning system current operational in the Region considers three reference durations for cumulative precipitation (24, 48, and 72 hours) and it is based on three alert levels simply associated with the return time of potentially triggering precipitation (2, 5 and 10 years).

This study wants to fill this knowledge gap by investigating the main recent weather-induced slope instability phenomena in the area in relation to the recorded characteristics of the associated weather events. The investigation aims at multiple objectives.

  • Comparing, over a common period, the records of different landslide catalogues available over the area - FraneItalia  (https://franeitalia.wordpress.com/), ITALICA (doi.org/10.5194/essd-15-2863-2023), Franceschini et al., 2022  (doi.org/10.1007/s10346-021-01799-y); Extreme Severe Weather Database (https://eswd.eu), Italian hydrological-geological Portal (https://idrogeo.isprambiente.it) - with the goal to verify consistency and to analyse the reasons leading to any discrepancies.
  • Verifying the performance of the currently operational warning system for a set of events assumed as reliable, as they are included in more than one catalogue, taking into account the seasonality of events and the triggering precipitation patterns.
  • Evaluating the capabilities of atmospheric reanalysis (ERA5land 10.24381/cds.e2161bac and CERRA 10.24381/cds.a7f3cd0be) made available by the Copernicus Climate Change Service to reconstruct the precipitation patterns that triggered the events (back-analysis). The topic is of great interest due to the high temporal resolution (1 hour) and spatial resolution (9 km for ERA5 land, 5.5 km for CERRA), which could therefore adequately cover areas where current sensor networks may be lacking or temporarily non-operational.
  • Assessing if and how the soil moisture content data returned by atmospheric reanalysis can support the back-analysis and/or the forecasting of landslide events (ERA5 is updated with a delay of only 5 days with respect of present time). Given the spatial resolution of the reanalysis, they are not expected to actually reproduce local in-situ conditions, but they rather should act as proxies to evaluate the average wetness status of the slopes and then the presence of conditions predisposing to landslide triggering.

The results discussed regarding the case study of the Amalfi and Sorrento Coasts can be readily extended to other geographical and geomorphological contexts, at national and continental scale.

How to cite: Rianna, G., Sequino, G., Pecoraro, G., Reder, A., and Calvello, M.: Investigating recent weather-induced landslides and the related weather characteristics in a test area in Campania Region (Italy) for warning purposes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12607, https://doi.org/10.5194/egusphere-egu24-12607, 2024.

EGU24-13149 | ECS | Posters on site | NH3.7

Optimizing operational efficiency in physically based landslide forecasting models: a multi-criterial parameterization approach in evaluating slope stability risk scenarios - a case study in Florence 

Greta Morreale, Nicola Nocentini, Elena Benedetta Masi, Ascanio Rosi, Samuele Segoni, and Veronica Tofani

Italy faces significant vulnerability to landslides, necessitating reliable forecasting models for effective property and population protection. These models must not only guarantee high accuracy but also facilitate easy integration into early warning systems for civil protection.

Physically based landslide forecasting models meticulously replicate the triggering mechanism of shallow landslides. These models employ numerous input parameters interconnected through complex mathematical relationships to assess the probability of landslide occurrences. Despite their precision, these techniques encounter challenges in spatializing geotechnical and hydrogeological parameters across extensive areas, restricting their application to slope-scale assessments. Additionally, the output of these models, presented as probability maps, lacks immediate utility for civil protection purposes, where a risk definition would be more operationally advantageous.

This study aims to address this gap by analyzing the optimal criterion for spatializing input data of physical models for regional-scale application. The goal is to develop a procedure that transforms model outcomes into readily usable risk scenarios. The study focuses on the Metropolitan City of Florence, leveraging a richly populated database of geotechnical and hydrogeological parameters. The selected model, HIRESSS (High-Resolution Slope Stability Simulator), simulates events occurring from January to March 2016, encompassing eight reported landslide events.

Through p-value analysis derived from statistical hypothesis testing, the study explores two criteria for parameterizing geotechnical and hydrological variables: a lithological criterion and one based on pedological-landscape units. This dual approach aims to consider both the lithological origin of soils and the impact of surface erosive processes on the spatial variability of input parameters. The study employs an innovative GIS-based procedure, integrating field surveys and morphometric parameters, to connect landslide probability maps with vulnerability and elements at risk, ultimately determining a risk scenario for the catchment area of the Cesto stream (southeast of Florence).

The analysis highlights the mixed criterion as the most supported spatialization approach, incorporating lithological factors for cohesion and friction angle and pedological-landscape criteria for hydraulic conductivity, soil unit weight, and porosity. Back-analysis validation reaffirms the model's high predictive capability with the adopted mixed-criterial parametrization. The results align with our understanding of landslide triggering mechanisms, particularly sensitive to cohesion and slope gradient.

The study concludes with a GIS-based risk analysis, providing impact scenarios for identified exposed elements. This final product proves instrumental for both prevention and emergency management. Once calibrated, the developed procedure holds potential for automation and replication in other study areas, offering a scalable solution for landslide risk assessment and mitigation.

How to cite: Morreale, G., Nocentini, N., Masi, E. B., Rosi, A., Segoni, S., and Tofani, V.: Optimizing operational efficiency in physically based landslide forecasting models: a multi-criterial parameterization approach in evaluating slope stability risk scenarios - a case study in Florence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13149, https://doi.org/10.5194/egusphere-egu24-13149, 2024.

EGU24-15046 | ECS | Orals | NH3.7

Spatiotemporal landslide forecasting through machine learning and perspectives of applications for early warning: a case study in Kvam, Norway 

Nicola Nocentini, Ascanio Rosi, Luca Piciullo, Zhongqiang Liu, and Samuele Segoni

The literature is rich with applications of machine learning techniques for assessing landslide susceptibility maps, which are limited to spatial prediction only. However, aspects related to extending the application framework to space-time landslides forecasting remain largely unexplored.

To fill this gap, this study introduces an innovative dynamic (i.e., time-dependent) application of the Random Forest (RF) algorithm. RF, among its advantages, allows the calculation of the Out-of-Bag Error (OOBE, which measures the error that would be committed if a given input variable is excluded from the RF classifier) and to visualize the Partial Dependence Plots (PDPs, depicting the relationship between each class of an input variable and the model outcome). These indices were discussed in this study to explore the algorithm's logic and verify its reliability.

The dynamic methodology proposed in this study involves using a spatially and temporally explicit landslide inventory as well as identifying non-landslide events over space and time. This procedure allows the inclusion of dynamic variables such as cumulative rainfall, snowmelt, and their seasonal variability, as model input. It also allows the inclusion of traditional static parameters such as lithology and geomorphologic attributes. Another key contribution of this study is that the RF model, once trained and tested using landslide and non-landslide events identified over space and time, produced a predictor that was subsequently applied to the entire study area before, during, and after specific landslide events. For each selected day, a specific and time-dependent landslide probability map was generated, simulating a real-time application in a warning system.

A case study in Kvam, Norway, was selected because of the availability of a comprehensive rainfall-induced landslide inventory, and the two major landslide events that occurred in June 2011 and May 2013 were selected for the simulations. Various model configurations involving the augmentation of non-landslide events were investigated to assess the model's sensitivity. The resulting pixel-based probability maps were validated using the Double Threshold Validation Tool (DTVT), a promising validation method based on the aggregation of pixels into catchment areas.

The reliability of the model was verified, and several benchmark configurations for the dynamic application of the RF model were provided. The generated landslide probability maps exhibit the ability to distinguish ordinary situations (low probability values where no critical rainfall was recorded, and no landslides occurred) from high-risk events (high probability values where highly intense rainfall triggered several landslides). The validation tool employed demonstrates the model's good performance and defines a criticality level suitable for early warning purposes. This study represents a step forward in comparison to traditional landslide susceptibility assessments and demonstrates the applicability of a novel method for spatiotemporal landslide probability mapping through machine learning, with perspectives of application to early warning systems.

Work supported by PRIN-ITALERT project (PRIN2022 call - grant number: 202248MN7N) funded by NextGenerationEU

How to cite: Nocentini, N., Rosi, A., Piciullo, L., Liu, Z., and Segoni, S.: Spatiotemporal landslide forecasting through machine learning and perspectives of applications for early warning: a case study in Kvam, Norway, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15046, https://doi.org/10.5194/egusphere-egu24-15046, 2024.

EGU24-15220 | Orals | NH3.7

A framework for the territorial landslide early warning system implementation: applications, lessons learnt and future challenges 

Mauro Rossi, Ivan Marchesini, Maria Teresa Brunetti, Silvia Peruccacci, Vinicio Balducci, and Fausto Guzzetti

As prioritized by the Sendai Framework, enhancing disaster preparedness is fundamental for the effective response, for taking actions in anticipation of events, and to ensure that the appropriate capacities are in place for effective response and recovery at all levels. Under this view early warning systems can be seen as irreplaceable tools to supporting the Civil Protection authorities in the preparedness and response phases. This is particularly relevant for the case of rainfall-induced slope failures that occur worldwide every year, claiming lives and causing severe economic disruption. Implementing early warning systems to forecast the occurrence of such geo-hydrological phenomena is difficult and challenging both from the scientific and technological side. Here we present a framework developed in Italy for the operational forecasting of rainfall induced landslides over large areas, which includes (i) models tools and technological supports for landslide prediction; (ii) algorithms for nowcasts and forecasts production using diversified inputs; (iii) operational early warning system procedures and technological supports for landslide forecasting; (iv) interfaces for the query and analysis of the early warning system outputs; (v) criteria, tools and technological supports for the validation of the early warning system outputs. The main lessons learned in the last two decades during the implementation of such framework are presented and discussed, highlighting the possible future challenges.

How to cite: Rossi, M., Marchesini, I., Brunetti, M. T., Peruccacci, S., Balducci, V., and Guzzetti, F.: A framework for the territorial landslide early warning system implementation: applications, lessons learnt and future challenges, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15220, https://doi.org/10.5194/egusphere-egu24-15220, 2024.

EGU24-15655 | ECS | Orals | NH3.7

Satellite derived Intensity- Duration (ID) thresholds for landslide forecast in Idukki, India 

Anamika Sekar and Srikrishnan Siva Subramanian

The Idukki district of Kerala experienced its worst disaster since 1924 in 2018 due to the excessive rain during the monsoon season from June to August. There were devastating landslides throughout the district accounting for the highest among the state which included debris flow, soil slides and rockfalls,  ever since making the area more susceptible to landslides. Thus, forging the impending need of an early warning system is crucial. Here, the study attempts to create a rainfall threshold to predict landslides through a satellite based precipitation product - GPM (Global Precipitation Mission Integrated Multi-satellitE Retrievals). The global coverage and the improved resolution of the data makes it more effective in mitigating landslide disaster risk.  Hourly precipitation data was obtained from GPM for the 23 grids within the district where there was an occurrence of debris flow. As the largest number of landslides happened during a second spell of intense rainfall that lasted from July 11 to August 19, 2018, the rainfall during this time was analyzed. A total of 4 days in these two months were identified with high amounts of rainfall with August 15th showing continuous rainfall for 24 hours. Using the rainfall and the landslide data for 2018 the overall regional threshold over the district was estimated to be I= 5.42D-0.16, where I is the rainfall intensity in mm/hr and D is the event duration. A more precise threshold could be obtained by considering grid-wise rainfall thresholds in a more detailed analysis. 

How to cite: Sekar, A. and Siva Subramanian, S.: Satellite derived Intensity- Duration (ID) thresholds for landslide forecast in Idukki, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15655, https://doi.org/10.5194/egusphere-egu24-15655, 2024.

EGU24-16641 | ECS | Posters on site | NH3.7

Slope surface deformation monitoring by close-range terrestrial photogrammetry 

Tianxin Lu and Peng Han

Landslide monitoring is an important means to prevent the landslide disaster. Among all elements of landslide monitoring, slope surface deformation is a piece of direct evidence to judge whether slope slips, which makes it indispensable in qualitative and quantitative analysis of slope stability. Current mainstream surface monitoring methods using GNSS are difficult to lay out densely on a large scale in a deformation region due to the high cost of equipment, leading to few surface points available for detection. With the rapid development of camera resolution and image processing, photogrammetry based on computer vision has great prospects in the application of slope real-time monitoring.

We introduce a low-cost landslide visual monitoring system using close-range terrestrial photogrammetry that deploys fixed cameras to capture the slope surface periodically and calculating the displacement of feature points from sequential slope images to generate the slope surface deformation network. A new machine learning framework is proposed to achieve image recognition, camera calibration and distance mapping altogether. We conduct indoor landslide experiments which verify the high precision, accuracy, and stability of our system.

How to cite: Lu, T. and Han, P.: Slope surface deformation monitoring by close-range terrestrial photogrammetry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16641, https://doi.org/10.5194/egusphere-egu24-16641, 2024.

EGU24-16859 | Posters on site | NH3.7 | Highlight

May and August 2023: the extreme landslide events in Slovenia, triggered by extreme rainfall 

Tina Peternel, Mateja Jemec Auflič, Ela Šegina, Domen Turk, Jernej Jež, and Miloš Bavec

In 2023, Slovenia experienced two major natural disasters caused by prolonged and intense rainfall event. The first occurred in May 2023 with over 2,000 shallow landslides triggered by prolonged heavy rainfall that lasted for about three weeks (from May 5 to May 23). This event mainly affected the north-east of Slovenia. The landslides caused major material damage to agricultural land and infrastructure, and at least 10 houses were evacuated.

The most notable event occurred in August 2023 and was estimated to be one of the largest in the history of independent Slovenia. In the period between August 3 and 6, 2023, precipitation with heavy storms and intense rainfall covered almost all of Slovenia. The extreme rainfall led to widespread flooding and triggered numerous landslides.

We estimate that there were around 10,000 landslides across Slovenia, with a particularly high density in some areas. Due to hydro-meteorological conditions (increased water flow and rising groundwater levels), a large portion of the landslides turned into mud or debris flows and were deposited a few to several hundred meters away from the source area. The main reason for the extreme landslide disasters was the heavy rainfall and high soil moisture as a result of the rainfall in July.

Due to the large scale of the landslide disaster in August, a detailed damage assessment is still being carried out. Preliminary estimates by the Geological Survey of Slovenia (GeoZS) indicate that around 10,000 landslides occurred (with an area of 1,000 to over 75,000 m2) and caused damage of more than €3 billion, of which around 40% had a direct impact on the built environment.

In both cases, the GeoZS emergency service provided residents and the relevant authorities with landslide forecasts and warnings using the existing national MASPREM system (Slovenian Landslide Forecast and Warning System). Although the Slovenian LEWS is operational, the performance of the forecasts has shown that about 15 to 25 % of the warnings were false, which we attribute to the short period of antecedent percipitations (the current calculation takes into account 3 days of antecedent percipitations)  and lack of soil and hydrological related parameters (e.g. effective percipitations, soil moisture, etc.).

Fundings:

This research was funded by the Slovenian Research And Innovation Agency through research projects J6-4628 and programme P1-0419. Additional financial support was provided by the Ministry of Natural Resources and Spatial Planning, Ministry of Defence (through project MASPREM) and project “Development of research infrastructure for the international competitiveness of the Slovenian RRI space – RI-SI-EPOS” (co-financed by the Republic of Slovenia, Ministry of Education, Science and Sport and the European Union from the European Regional Development Fund).

How to cite: Peternel, T., Jemec Auflič, M., Šegina, E., Turk, D., Jež, J., and Bavec, M.: May and August 2023: the extreme landslide events in Slovenia, triggered by extreme rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16859, https://doi.org/10.5194/egusphere-egu24-16859, 2024.

EGU24-18498 | ECS | Posters on site | NH3.7

Monitoring and forecasting subsurface geo-interfaces behavior of active slow-moving landslides using fiber optic nerve sensing system 

Xiao Ye, Hong-Hu Zhu, Bin Shi, and Filippo Catani

Monitoring evolution process of subsurface geo-interfaces in active slow-moving landslides can help understand landslide thermo-hydro-mechanical dynamics and predict potential landslide hazards. However, characterizing the behavior of these geo-interfaces and revealing their interactions remain challenging due to the general lack of high-resolution subsurface observations. To this end, we propose a novel fiber optic nerve sensing (FONS) system based on ultra-weak fiber Bragg grating (UWFBG) to sense the temperature, moisture and strain of geomaterials along a borehole in nearly real-time. The system is able to accurately locate and identify multiple potential slip surfaces and other critical geo-interface behaviors that may be relevant to landslide instability. The measurements confirm the foremost contribution of short-duration high-intensity extreme rainfall to accelerating landslide movement. We also attempted to employ machine learning algorithms based on classification principles to predict what hydrometeorological regimes would drive an accelerated deformation event. These subsurface data will allow us to investigate the multi-physical characteristics of geo-interfaces from daily to annual and even multi-annual scales and link cyclic thermo-hydro-mechanical external conditions to progressive failure. This work highlights the increasing impact of extreme weather events on landslide geohazards and the importance of multidisciplinary approaches for accurate prediction and early warning. Integrating FONS with remote sensing and ground-based technologies can create a comprehensive space-sky-ground-subsurface monitoring framework for landslides.

How to cite: Ye, X., Zhu, H.-H., Shi, B., and Catani, F.: Monitoring and forecasting subsurface geo-interfaces behavior of active slow-moving landslides using fiber optic nerve sensing system, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18498, https://doi.org/10.5194/egusphere-egu24-18498, 2024.

EGU24-19430 | ECS | Posters on site | NH3.7

Shallow landslide early warning in typhoon rainstorm area based on Slope Warning Model 

Liangxuan Yan, Kunlong Yin, and Lixia Chen

To carry out refined early warning for shallow landslides in typhoon rainstorm area, it is necessary to propose hourly precipitation warning criteria. The Slope Warning Model (SWM) of analyzing the correlation between landslides and rainfall process proposes short-term early warning criteria and rainfall duration. Individual slope warning framework is established based on regional average rainfall threshold and adjustment rainfall concerning specific geotechnical factors. The regional landslide rainfall threshold, counted by I-D model, is proposed as the regional average threshold. The geological environment of individual slope is investigated as geographical figures, geological structure, composition of soils, hydrological conditions and slope cutting. In terms of the simulation of infinite slope model, slope stability varies as geological factors changes due to rainfall infiltration, which may determine threshold adjustment values. Wenzhou City, Zhejiang Province of China, located in eastern coast area where is frequently impacted by typhoon, was taken as a study area. Quantitative threshold calculation formula has been proposed. Early warning criteria of different duration is proposed according to the geological factors of individual slope. This study proposed a short-term quantitative landslide meteorological warning model for individual slope. It may provide new ideas and references for "each-slope, each-threshold" of landslide early warning and risk management.

 Keywords: shallow landslide, early warning, typhoon rainstorm, individual slope, “each-slope. each-threshold”

How to cite: Yan, L., Yin, K., and Chen, L.: Shallow landslide early warning in typhoon rainstorm area based on Slope Warning Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19430, https://doi.org/10.5194/egusphere-egu24-19430, 2024.

EGU24-19871 | ECS | Orals | NH3.7 | Highlight

Impact-based Early Warning System for Debris flow in Malaysia: A Science-based and Localization Approach for Strengthening Disaster Resilience 

Liyana Hayatun Syamila Ramlee, Khamarrul Azahari Razak, Zamri Ramli, and Zakaria Mohamed

Malaysia is committed to accelerate the achievement of UN Sendai Framework for Disaster Risk Reduction 2015-2030, and support a newly launched agenda, “The Early Warning for All initiative, 2023-2027”. While investing into landslide risk reduction strategies through the National Slope Master Plan 2009-2023, landslides remained the major contributor to the highest number of human losses in Malaysia, and even so with new, emerging risk and compounding disaster as a result of local climate change impact. So far, landslide and debris flow occurred more than 25 times with 442 casualties in the last three decade. Amongst are the geological disaster debris flow in Jerai Geopark (Yan, Kedah) recorded on 18 August 2021 resulted in six fatalities, with more than RM75 million direct economic losses reported, and indirect cascading impact to local socio-economic activity and food security system. This study advances the people-center, end-to-end early warning system for debris flow in the tourism-dominated region in Kedah. It is worth mentioning that this Japanese-designated EWS is the first-ever system locally built in Malaysia, which was co-designed, co-developed and co-implemented driven by the local communities and multi-stakeholders in a tropical environment. Several unmanned assisted vehicles-based LiDAR missions were jointly conducted to quantitatively understand the possible remaining systemic risk for future debris flow in the upstream of the study area located in the vicinity of the Mount of Jerai. A complete system consists of wire-cable detection, vibration sensor, and siren system coupling with historical inventory analysis, hazard mapping, exposure assessment and systemic risk evaluation. The EWS development was carried out across sector, and carefully installed based on the detailed geological survey, geohazard mapping, vulnerability analysis, and risk assessment over several water catchments in the areas. A science-based knowledge coupled with the Local, Traditional, and Indigenous Knowledge (LTIK) was collectively explored and translated into series of Community-led Disaster Risk Reduction (CLDRR), an extended version of traditional Community-based Disaster Risk Management (CBDRM) that widely conducted at various implementation scales. The early warning system was later integrated with the public warning system to expand its dissemination scales and acceptance level. Interestingly, a local landslide risk reduction model was co-developed with several partnership modality (public-private-academia-NGO), namely as YAN DRR Model, to support the build-back-better agenda and rejuvenate the multi-scale eco-tourism and food security industry. An integrated EWS system was tested and demonstrated in the last two- commemoration years. Several innovations for improving local risk communication system are intelligently explored and strategically documented. As a conclusion, the study provides a new insight into locally-led and nationally-supported landslide disaster risk reduction strategy, by empowering an impact-based early warning system for debris flow and landslides, integrating with the innovated LTIK approach and strengthening local champions in the vulnerable regions. Remarkably, this study demonstrates regional benchmarking, national commitment, and local wisdom to reduce the number of human- and economic losses through an impact-based early warning system, led by vulnerable community and powered by humanizing technology for building societal resilience in a changing climate.

Keywords: Landslide Disaster, Debris Flow, Disaster Risk Management, People-centered EWS

How to cite: Ramlee, L. H. S., Razak, K. A., Ramli, Z., and Mohamed, Z.: Impact-based Early Warning System for Debris flow in Malaysia: A Science-based and Localization Approach for Strengthening Disaster Resilience, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19871, https://doi.org/10.5194/egusphere-egu24-19871, 2024.

EGU24-2467 | ECS | Posters on site | NH3.8

Landslide Inventory Mapping in Densely Populated and Forested Environments using UAV LiDAR Data: A Case Study in Zindisi, Surami District, Georgia 

David Bakhsoliani, Archil Magalashvili, and George Gaprindashvili

In the country of Georgia, the administrative territories of Surami (Khashuri municipality, Shida Kartli region) are particularly susceptible to the development of landslide processes. Among these areas, the Zindisi district stands out as a focal point for our research due to the occurrence of a significant landslide process in 2007, which remains active and poses periodic threats to residential houses and infrastructure. Zindisi district is characterized by dense forest cover and a high population density. Conducting a detailed landslide survey in such a challenging terrain using standard methods is difficult. Therefore, our research aims to overcome these challenges by employing lidar technology in a similar environment.

The research initiative commenced with the acquisition of high-density point cloud data utilizing UAV lidar surveys. A UAV (DJI- The Matrix 300 RTK) equipped with a lidar camera (DJI Zenmuse L-1), was deployed to scan the study area. This approach allowed for the capture of detailed topographical information crucial for understanding the landslide processes. The obtained dataset serves as the foundation for creating a precise Digital Elevation Model (DEM) with a spatial resolution of 1 meter. This DEM enabled the identification of landslide boundaries by leveraging lidar-derived high-resolution topographic information. Linear structures were mapped based on hillshade, aspect, slope, and other thematic maps, providing a comprehensive understanding of the terrain.

To validate the accuracy of our results, both aerial photos and on-site field investigations were utilized. The combination of lidar technology, high-resolution topographic data, and thorough validation techniques enhances the reliability of our landslide inventory in the Zindisi district. This research contributes valuable insights for effective land management and mitigation strategies in landslide-prone areas. Furthermore, the approach outlined in this research provides a method for landslide mapping in similar environments and demonstrate the potential of UAV LiDAR technology in enhancing landslide risk management in densely populated and forested regions.

How to cite: Bakhsoliani, D., Magalashvili, A., and Gaprindashvili, G.: Landslide Inventory Mapping in Densely Populated and Forested Environments using UAV LiDAR Data: A Case Study in Zindisi, Surami District, Georgia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2467, https://doi.org/10.5194/egusphere-egu24-2467, 2024.

EGU24-2523 | Posters on site | NH3.8

Advancing Landslide Monitoring in Tbilisi city and Imereti Region (Georgia): Integrating Tiltmeters, Piezometers, GPS and Geospatial Technologies 

Ramaz Koberidze, George Gaprindashvili, Zurab Rikadze, Otar Kurtsikidze, and Merab Gaprindashvili

This scientific exploration focuses on advancing landslide monitoring in the capital city of Tbilisi, Georgia and in Imereti Region village Gomi. By combining geotechnical monitoring systems, including tiltmeters and piezometers, with cutting-edge geospatial technologies such as digital elevation model (DEM) and aerial photography, our study aims to provide a comprehensive understanding of landslide dynamics in these diverse landscapes.

The integration of tiltmeters and piezometers facilitates real-time monitoring of ground movements and pore pressure changes, offering valuable insights into the evolving geotechnical conditions. A robotic S9 Trimble apparatus is installed in the capital city of Tbilisi, which gives accurate movements level, as well as directions. Coupled with the analysis of digital elevation model and aerial photos, research explores the topographical and morphological factors influencing landslide susceptibility.

The findings from Tbilisi and Gomi serve as case studies for urban and regional landslide hazard assessment. The study's strength lies in the integration of tiltmeters and piezometers, offering real-time monitoring of ground movement and groundwater fluctuations. Advanced geospatial technologies, such as satellite imagery and GIS, complement these measurements by providing a spatial context for landslide-prone areas. The combination of these methods enables a holistic approach to landslide risk assessment, considering the dynamic interplay of geological, climatic, and topographic factors.

In conclusion, this research makes a valuable contribution to landslide risk assessment in Tbilisi and Imereti Region Gomi. By addressing the geographic, geological, and climatic nuances of the region and integrating tiltmeters, piezometers, and advanced geospatial technologies, the study enhances our understanding of landslide dynamics and supports the development of targeted risk mitigation strategies tailored to the unique conditions of this area.

How to cite: Koberidze, R., Gaprindashvili, G., Rikadze, Z., Kurtsikidze, O., and Gaprindashvili, M.: Advancing Landslide Monitoring in Tbilisi city and Imereti Region (Georgia): Integrating Tiltmeters, Piezometers, GPS and Geospatial Technologies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2523, https://doi.org/10.5194/egusphere-egu24-2523, 2024.

EGU24-4974 | ECS | Posters on site | NH3.8 | Highlight

Integrative Analysis of Electrical Conductivity and Hydraulic Properties in Assessing Shallow Slope Stability 

Ya-Sin Yang, Hsin-Fu Yeh, Chien-Chung Ke, Lun-Wei Wei, and Nai-Chin Chen

This study integrated hydrological surveys with geophysical monitoring methods to obtain the geotechnical insights related to shallow landslides. The varied and complex conditions in subsurface pose difficulties in linking geophysical monitoring data to soil engineering properties. Therefore, we investigated the relationship between hydrological response and slope movement using real-time soil water and electrical conductivity data and displacement monitoring records. By integrating the relationship with the soil water characteristic curve (SWCC) and soil stress characteristic curves (SSCC) established from laboratory tests, we established specific curves that correlate electrical conductivity with soil water and stress. We also extended unsaturated soil shear strength model to relate the matric suction and electrical conductivity. We adopted finite element hydrodynamical model HYDRUS 2D and Slope Cube Module to assess the slope stability of shallow landslides triggered by rainfall. The local factor of safety obtained from numerical simulations were compared with the estimated shear strength values. The results showed that the changes in the shear strength estimated from the electrical conductivity is consistent with that of the local safety factor obtained from numerical simulations. This revealed that the shear strength model with electrical conductivity as a variable can reasonably evaluate slope stability, and is also suitable for analysis related to the hydraulic properties of unsaturated soils. This study can provide guidance for future field monitoring works and serve as a basis for shallow landslide early warning and slope stability assessment.

How to cite: Yang, Y.-S., Yeh, H.-F., Ke, C.-C., Wei, L.-W., and Chen, N.-C.: Integrative Analysis of Electrical Conductivity and Hydraulic Properties in Assessing Shallow Slope Stability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4974, https://doi.org/10.5194/egusphere-egu24-4974, 2024.

Landslides are serious natural hazards in the mountainous and hilly areas of New Zealand, where they frequently cause landscape changes and significant damage to people and infrastructure. Monitoring the evolution of landslides, associated landslide-dammed lakes, and their consequences is important for disaster risk management and can help to mitigate cascading hazards. The availability of time series satellite remote sensing data has facilitated more efficient mapping and monitoring of landslides and related hazard analysis.

By applying object-based image analysis (OBIA) and using Sentinel-2 satellite data from 2017 to 2021, complemented by PlanetScope data, we semi-automatically mapped the evolution of the Kaiwhata landslide and the associated landslide-dammed lake in the Wairarapa region in the south of New Zealand’s North Island (cf. Pooladsaz et al., 2023). We mainly used spectral indices, such as the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI), with the support of digital elevation model (DEM) data acquired from the Land Information New Zealand (LINZ) and its derivatives, to classify the landslide and landslide-dammed lake areas. The DEM data helped to remove false classifications, even though the DEM shows the pre-landslide status of the terrain. The segmentation parameters were determined based on expert trial-and-error and visual assessment of the resulting image objects. The classification rules and parameters were developed continuously from the first image to the subsequent ones, following the evolution of the landslide and landslide-dammed lake. The knowledge-based OBIA mapping workflow was designed to be transferable to all the images. When applying the workflow to the other images, only minor modifications concerning the used layers and thresholds were needed. The semi-automated OBIA results were compared with the results of visual interpretation to assess the mapping accuracy.

Despite challenges such as cloud coverage and shadow effects during certain seasons, the spatial resolution of Sentinel-2 images was sufficient to accurately capture the landslide and landslide-dammed lake. The mapping results, which were also visualised as interactive three-dimensional (3D) models, revealed a gradual increase in the landslide area, with two major changes in June 2019 and November 2020. These major changes were followed by the formation of temporary landslide-dammed lakes along the Kaiwhata River (cf. Morgenstern et al., 2021), because the landslide reached the riverbed and blocked the stream. The use of OBIA and time series satellite remote sensing data can provide valuable insights into the evolution of landslides and landslide-dammed lakes and allows for a more detailed assessment of their impacts.

 

Morgenstern, R., Massey, C., Rosser, B., Archibald, G., 2021. Landslide Dam Hazards: Assessing Their Formation, Failure Modes, Longevity and Downstream Impacts. In: Vilímek, V., Wang, F., Strom, A., Sassa, K., Bobrowsky, P.T., Takara, K. (eds), Understanding and Reducing Landslide Disaster Risk. WLF 2020. ICL Contribution to Landslide Disaster Risk Reduction. Springer, Cham, 117-123. https://doi.org/10.1007/978-3-030-60319-9_12

Pooladsaz, K., Hölbling, D., Brus, J., 2023. Monitoring the Evolution of the Kaiwhata Landslide in New Zealand Using Object-based Image Analysis and Sentinel-2 Time Series. GI_Forum, 11(2), 88-101. https://doi.org/10.1553/giscience2023_02_s88

How to cite: Hölbling, D. and Pooladsaz, K.: Mapping the evolution of the Kaiwhata landslide and landslide-dammed lake in New Zealand using satellite image time series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5077, https://doi.org/10.5194/egusphere-egu24-5077, 2024.

EGU24-5431 | Orals | NH3.8

Slope Stability Analysis and Mitigation of Mehla Landslide, District Chamba, Himachal Pradesh, India. 

Rajeshwar Singh Banshtu, Laxmi Devi Versain, and Abhay Pratap Singh

The Chamba Distirct is situated in the North Western part of the Himachal Pradesh State where presence of ancient monuments in the form of temples and holy lakes make this district a pilgrimage destination. Extensive damage to some of these monuments has been done due to occurrence of natural disasters. Himalayas represents a highly sensitive ecosystem vulnerable for natural disasters. Landslides are common phenomena in this geodynamically active terrain triggered by a wide variety of factors. The increased magnitude and frequency of Landslides is a cause of concern, since these interfere with human interest, causing immense loss to human life, infrastructure and natural resources. Extensive human activity in the region has further intensified erosion and triggered slope failures. The consequences are occurrence of large landslides, particularly in the zones of active faults and thrusts. The Chamba- Bharmaur highway has number of such active slide zones which causes obstruction for normal activities of the inhabitants. The area lies in seismically active region due to which occurrence of micro-earthquake at repeated intervals disturbs the already weathered rock mass. The initiation of Landslide near Mehla village on NH-153 can be attributed to the developmental activities ranging from farming on hill slopes to development of highways. Based upon geotechnical properties, numerical modeling of the landslide site using Geo5 software was conducted in order to calculate the factor of safety. The results of the numerical study can be used to ascertain the dependability of these slopes for future activities and suggesting mitigation measures to lower the frequency and severity of landslides in areas with similar geological conditions. This will further help in preserving the rich ancient heritage from occurrence of natural disasters in this region.

Keywords: natural disaster, ancient monuments, earthquake, hill slopes.

How to cite: Banshtu, R. S., Versain, L. D., and Singh, A. P.: Slope Stability Analysis and Mitigation of Mehla Landslide, District Chamba, Himachal Pradesh, India., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5431, https://doi.org/10.5194/egusphere-egu24-5431, 2024.

EGU24-6360 | ECS | Posters on site | NH3.8

Seismological analysis of the September 16, 2023 Greenland landslide triggering a 50 hours long monochromatic very long-period signal 

Angela Carrillo-Ponce, Gesa Petersen, Simone Cesca, Sebastian Heimann, Thomas R. Walter, and Torsten Dahm

On September 16, 2023, a landslide collapsed in the Dickson Fjord, a remote area of East Greenland. The collapse triggered a tsunami that hit Ella Island, which lies to the east of the fjord. The mass movement is identified in high resolution Planet Labs Dove mini-satellite imagery, and the generated seismic signals were recorded at both regional and teleseismic distances. The seismic records reveal a first strong transient signal (0.02-0.06 Hz) around 12:35:00 UTC, which we attribute to the landslide, followed by a long-lasting (~50 hours) monochromatic (~0.01 Hz) signal at teleseismic distances. We perform full waveform inversions using moment tensor and single force models to characterize the source of both signals. At regional distances, the first transient signal is well reproduced by single and double source models and is consistent with the landslide process. The long-lasting oscillation is modeled by a damped dipole oscillator, which is in agreement with the Love and Rayleigh waves radiation patterns observed at different azimuths. Using multiple different data and source models we are able to characterize the complex source process.

How to cite: Carrillo-Ponce, A., Petersen, G., Cesca, S., Heimann, S., Walter, T. R., and Dahm, T.: Seismological analysis of the September 16, 2023 Greenland landslide triggering a 50 hours long monochromatic very long-period signal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6360, https://doi.org/10.5194/egusphere-egu24-6360, 2024.

EGU24-6755 | ECS | Orals | NH3.8 | Highlight

Mapping and monitoring ground deformations: Insights from a Sentinel-1 Persistent Scatterer Interferometry study in Northeastern Italy 

Francesco Barbadori, Francesco Becattini, Silvia Bianchini, Francesco Caleca, Pierluigi Confuorto, Matteo Del Soldato, and Francesco Poggi

Persistent Scatterer Interferometry (PSI) is a valuable technique for investigating shallow ground displacement phenomena, such as slow landslides and subsidence. Its flexibility in time intervals and spatial scales allows to use PSI as an ideal tool for mapping and continuous monitoring over vast areas, ranging from regional to continental scales. In a four years collaboration (since 2019) between the University of Florence and the Veneto Region (Northeastern Italy), this study aims to enhance understanding of natural, gravity-induced phenomena while providing scientific support for geohazard management. The Veneto Region serves as an exemplary study site due to its complexity in terms of extent, geological setting, and geomorphological processes, challenging the PSI technique to prove its efficacy. For this work, ESA (European Space Agency) Sentinel-1 satellite constellation, with a revisiting time of 6 and 12 days (after the end of the operative life of Sentinel 1B in January 2022), were used. Radar data undergoes a set of different analysis: firstly, from Persistent Scatterer (PS)-derived deformation maps, clusters of high mean velocity were detected and classified using machine learning algorithms in order to mapping hotspot areas. Then, relevant displacement anomalies associated with periods of acceleration and deceleration of the deformation in the time series of each PS (Persistent Scatterer)  were identified and classified to recognize the cause of deformation (e.g. landslide or subsidence). Furthermore, a Principal Component Analysis (PCA) and a machine learning clustering were done on up-down and east-west InSAR components to identify specific time series patterns on regional scale. The implementation of this methodology revealed significant outcomes, particularly in the Belluno province where, in Cortina d’Ampezzo municipality, hotspot areas associated with known landslides were accurately identified and in the Lozzo di Cadore municipality, where the analysis detected high anomalous displacement rates within a narrow time frame. Notably, four anomalous PS points exhibited peak displacement rates ranging from 56 mm/yr to 78 mm/yr from February 2023 to October 2023, where no landslides were previously inventoried. The PCA and clustering procedure was successfully applied over the whole Region and, in particular, Lamosano village (Belluno province) where a known landslide movement was recognized.  This study underscores the efficacy of Sentinel-1 data for mapping and continuous, real-time ground displacement monitoring over wide areas. The cluster mapping and anomaly detection procedures proved to be crucial in identifying anomalies with high displacement rates, particularly in areas lacking prior landslide inventory. The Cortina d’Ampezzo, Lozzo di Cadore and Lamosano case studies exemplify how the PSI technique can contribute to risk mitigation strategies by suggesting updates to landslides inventories based on hotspot mapping and anomalies detection and classification. In conclusion, this work demonstrates the potential of PSI in advancing the understanding of ground displacement and contributing to proactive geohazard management.

How to cite: Barbadori, F., Becattini, F., Bianchini, S., Caleca, F., Confuorto, P., Del Soldato, M., and Poggi, F.: Mapping and monitoring ground deformations: Insights from a Sentinel-1 Persistent Scatterer Interferometry study in Northeastern Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6755, https://doi.org/10.5194/egusphere-egu24-6755, 2024.

EGU24-7787 | Posters on site | NH3.8 | Highlight

The November 2023 displacement of the Roncovetro Landslide (RE, Italy) as measured by a small wireless network of Ultra-WideBand (UWB) sensors 

Luca Nannipieri, Massimiliano Favalli, Pierfrancesco Burrato, Roberto Devoti, Giovanni Bertolini, Lorenzo Mucchi, and Alessandro Fornaciai

The Roncovetro landslide is a complex active earth flow located in the Enza Valley (Emilia-Romagna Region, Italy). It carves the southern flank of Monte Staffola from its summit to the riverbed of Tassobbio stream, with a total involved volume of ~ 3×106 m3. This ~ 2.5 km landslide has a maximum width of 300 m and a 30-40 m wide channel that separates the depletion zone from the accumulation zones. Since the clay fraction is largely dominant, the landslide mainly behaves like a fluid-viscous earthflow. capable of reaching maximum velocities of up to 10 m/day. The perennial activity of the Roncovetro landslide is characterized by phases during which the detachment is limited to deep creep, sliding, and flowing, as well as major events that result in the interruption of the white road between Roncovetro and Vedriano villages.

In recent years, the Roncovetro landslide has been selected as a test site for evaluating new monitoring technologies based on Ultra-Wide Band (UWB) wireless sensors. Currently, it has been designated as a study area for the "Land-slide Enhanced Monitoring Network (LEMON)" project funded by the INGV. As part of the LEMON project, a small network of UWB wireless sensors has been installed on the landslide body to monitor its movement. The technology used was previously described in Intrieri et al. (2018) and Mucchi et al. (2018). The installed network consists of five sensors, comprising one master node and four slave nodes. The master node and one slave node were placed outside the area recently affected by displacements, while three nodes were positioned inside the landslide body. The acquisition frequency was set at one acquisition every three hours, totaling eight acquisitions per day.

In November 2023, the Roncovetro landslide experienced a significant displacement that once again swept away the white road. This displacement was fully recorded by the UWB network. Additionally, an Unmanned Aerial System (UAS) survey was conducted before and after the displacement to offer a comprehensive view of the movement.

In this work, we first describe the technological improvements and updates made to the UWB wireless network compared to previous works. Second, we describe the November 2023 displacement of the Roncovetro landslide as recorded by the UWB network with a frequency of one acquisition every three hours. And finally, we compare the data provided by the UWB network with the changes in the landslide detected through the comparison of pre- and post-UAS-derived orthophotos.

How to cite: Nannipieri, L., Favalli, M., Burrato, P., Devoti, R., Bertolini, G., Mucchi, L., and Fornaciai, A.: The November 2023 displacement of the Roncovetro Landslide (RE, Italy) as measured by a small wireless network of Ultra-WideBand (UWB) sensors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7787, https://doi.org/10.5194/egusphere-egu24-7787, 2024.

EGU24-10833 | Orals | NH3.8 | Highlight

Geophysical survey for the estimation of geotechnical parameters and for the stability assessment of the Tehilly landslide (VdA, Italy) 

Veronica Pazzi, Agnese Innocenti, Elisa Gargini, Samuele Segoni, Ascanio Rosi, Elena Benedetta Masi, Veronica Tofani, and Nicola Casagli

An efficient stability analysis is closely linked to a good assignment of geotechnical parameters to the strata identified in the construction of the geological model. However, it is not always possible to determine the geotechnical parameters from direct tests, but there are indirect methods in the literature for determining the main geotechnical parameters of the ground using seismic parameters such as seismic velocities.

Numerous correlations exist in the literature between shear wave velocity (VS), and the N-SPT value derived from penetrometric tests.

This study presents the geotechnical model of the Theilly landslide (Western Alps, Italy) obtained by integrating the results of a multi-parameter geophysical survey (H/V seismic noise and ground-penetrating radar) with stratigraphic and geomorphologic observations, digital terrain model and field survey data. It is shown how VS values can be related to values obtained from direct tests such as N-SPT and, using the direct or estimated N-SPT value, it is possible to directly derive the friction angle value (φ'). Although, the indirect estimation of N-SPT is subject to a higher level of error, it could be very useful in the early stages of an emergency, when direct data are not available, and a preliminary forward and backward stability analysis could be performed to assess landslide evolution and civil protection actions.

Geophysical surveys were conducted on the landslide body and on nearby locations. The H/V survey identified the presence of 2 discontinuity surfaces and thus the presence of 3 seismo-layers. The GPR survey allowed the surface portion of the slope to be studied, identifying an extremely heterogeneous debris layer.

The H/V data allowed the interface depth to be related to the frequency of the identified peaks and the VS of the identified seismic layers. It was then possible to apply empirical equations to derive the value of N-SPT, and consequently φ', from the VS obtained through the H/V measurements.

The geotechnical parameters obtained from geophysical and direct tests were used to create a geotechnical model of the landslide to perform a reliable stability analysis. The analysis of the triggering conditions of the landslide was conducted through hydrologic-geotechnical modelling, evaluating the behaviour of the slope under different rainfall scenarios, and considering the stabilization interventions present on the slope.

The results of the filtration analyses showed a top-down saturation mechanism, which resulted in the generation of positive pore water pressure in the first few meters of soil and the formation of a saturated front with a maximum thickness of 5 m. Stability analyses conducted for the same events showed the development of a shallow landslide affecting the first few meters of saturated soil.

The geotechnical parameters estimated from the geophysical tests are in agreement with the data from the direct tests and have made it possible to create a geotechnical model that is faithful to reality.

The modelling results are compatible with the actual evolution of the phenomenon and have provided insight into the triggering mechanism, providing models to support future interventions.

How to cite: Pazzi, V., Innocenti, A., Gargini, E., Segoni, S., Rosi, A., Masi, E. B., Tofani, V., and Casagli, N.: Geophysical survey for the estimation of geotechnical parameters and for the stability assessment of the Tehilly landslide (VdA, Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10833, https://doi.org/10.5194/egusphere-egu24-10833, 2024.

EGU24-11217 | Posters on site | NH3.8

Varying weathering degree indicators within three paleosol layers 

Csilla Király, Juliet Keya Mondal, Gergely Jakab, Máté Karlik, György Falus, Dóra Cseresznyés, Péter Kónya, István Viczián, József Szeberényi, and Zoltán Szalai

Loess-paleosol layers are prevalent globally. One result of the urbanization, these layers often collapse on the buildings or if the buildings are the top of the bluff, houses can damage as a result of mass movements. Therefore, it is crucial to identify key parameters to predict the changes in the loess-paleosol layers stability. This study focused on three unaltered loess-paleosol profiles in Hungary (Bátaapáti, Nagymaros, Zebegény) where several vertical samples were taken. To assess the extent of weathering, X-ray fluorescence (XRF), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), and X-ray Diffraction (XRD) analyses were utilized. XRD provides detailed information about the crystallographic structure and chemical composition of minerals. Further details on the elemental composition of the three loess-paleosol systems were acquired through XRF analysis. Data from the Mastersizer 3000 analyzer were collected to examine particle size distribution, as the clay fraction (<2 µm) percentages elucidate the extent of weathering. Optical microscopic properties of the selected samples were investigated using the 2D image analyzer Morphologi G3-ID. The overall degree of weathering in Bátaapáti is lower, while a higher concentration of smectite in Nagymaros and Zebegény indicates more pronounced weathering activity. Considering paleoclimate and current meteorological conditions, a correlation between chemical weathering and particle size distribution was observed at the three sites. The precipitation of clay minerals affirms the ongoing pedogenesis in all of the locations. An increased proportion of fine particles (<2 µm) in deeper paleosol layers may suggest illuviation due to leaching. In Nagymaros, the illuvial horizon is situated between two loess deposit layers. Consequently, particle size, shape distributions, and chemical compositions indicate an elevated weathering status for Nagymaros, underscoring the advantages of concurrently employing multiple research methods. Support of the National Research, Development, and Innovation Office (Hungary) under contract FK128230 is gratefully acknowledged.

 

How to cite: Király, C., Mondal, J. K., Jakab, G., Karlik, M., Falus, G., Cseresznyés, D., Kónya, P., Viczián, I., Szeberényi, J., and Szalai, Z.: Varying weathering degree indicators within three paleosol layers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11217, https://doi.org/10.5194/egusphere-egu24-11217, 2024.

EGU24-11372 | Orals | NH3.8

Combined approach for hillslope hydrogeological assessment in rainfall-induced shallow landslides prone area. 

Valerio Vivaldi, Massimiliano Bordoni, Patrizio Torrese, and Claudia Meisina

In the last years extreme rainfall events and seasonal cumulated rainfall distribution variations occurred, increasing also the arise of slope instabilities, mostly in the more susceptible areas.

Heavy rainfall events are one of the main triggering factors in shallow landslides occurrence: therefore, a better understanding of the trigger processes is necessary, also for early warning systems development and improvement. The soil water content of the first 3-5 meters of soil becomes thus an important shallow landslide predisposing factor to monitor. At this purpose, the mainly employed technique for soil moisture monitoring is the in-situ measurement, through different types of soil probes directly installed in the first soil layers. However, despite being a very precise technique, this monitoring technique provides only for a punctual dataset.

An integrated method to extend the hydrological characterization from site-specific to a slope scale is presented, combining geotechnical analyses, field data monitoring and geophysical investigations, in particular the electrical resistivity tomography (ERT).

Geophysical models of the first subsoil were carried out through different geoelectrical investigations (2D-3D-4D) and were calibrated and interpreted based on soil monitoring data, stratigraphic logs and trenches carried out in the study areas.

Estimation of the test sites average bulk permeability was performed through time-lapse 3D-S surveys, carried out by simulating very intense precipitations through manual irrigation, that allowed to determine the resistivity variation from undisturbed to disturbed conditions.

Finally, resistivity variations were correlated to soil horizons geotechnical parameters to perform hydrogeological conceptual models of the first soil horizons.

This conference abstract is part of the project NODES which has received funding from the MUR – M4C2 1.5 of PNRR funded by the European Union - NextGenerationEU (Grant agreement no. ECS00000036).

How to cite: Vivaldi, V., Bordoni, M., Torrese, P., and Meisina, C.: Combined approach for hillslope hydrogeological assessment in rainfall-induced shallow landslides prone area., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11372, https://doi.org/10.5194/egusphere-egu24-11372, 2024.

EGU24-11428 | ECS | Orals | NH3.8

Satellite observations reveal the activity cycle of a giant irrigation-triggered landslide in southern Peru 

Chuang Song, Chen Yu, Zhenhong Li, and Jianbing Peng

Irrigation-triggered landslides have received much attention in recent years as they directly threaten the agricultural production and the lives of local communities. Although the triggering of such landslides has been well documented, their long-term post-triggering dynamics and complete activity history (important for landslide risk assessment) remain poorly understood. In this study, we focus on one of the largest irrigation-triggered landslides in Peru, i.e., the Punillo Sur landslide. Previous studies failed to observe and characterize the full cycle of landslide activity due to their inadequate monitoring capabilities, prompting us to combine satellite interferometric synthetic aperture radar (InSAR) and optical offset measurements to track its full 8.5-year kinematics from 2014 to 2023.

Our key findings include: (1) The landslide experienced three times of very large accelerations (i.e., three activity cycles) respectively in 2016, 2019 and 2022, with accumulated displacements of over 150 m; (2) These large accelerations, accompanied by headscarp retrogression, were all found to initiate from precursory/sudden movements of > 10 cm/yr (observed by InSAR) and were driven by long-term infiltration of irrigation water; (3) The southern portion of the landslide exhibited a greater magnitude of acceleration due to its thinner sliding layer that favors seepage-driven motion; (4) After the three large accelerations, the landslide invariably shifted to deceleration without catastrophic failures, which was found to be controlled by water evacuation and rate-strengthening friction.

These findings will serve as import materials for understanding the cycle of landslide activity and highlighting the prolonged effect of irrigation water on landslide dynamics. This will greatly increase our understanding of the long-term risk of irrigation-triggered landslides. Based on our findings, we also proposed critical disaster prevention/mitigation measures to support local communities in their disaster management efforts.

How to cite: Song, C., Yu, C., Li, Z., and Peng, J.: Satellite observations reveal the activity cycle of a giant irrigation-triggered landslide in southern Peru, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11428, https://doi.org/10.5194/egusphere-egu24-11428, 2024.

EGU24-12753 | ECS | Orals | NH3.8 | Highlight

Regional-scale monitoring of hillslope deformation through optical satellite imagery 

Maximillian Van Wyk de Vries, Katherine Arrell, Gopi Basyal, Simon Dadson, Alexander Densmore, Diego Di Martire, Alexandre Dunant, Mirko Francioni, Luigi Guerriero, Erin Harvey, Ganesh Jimee, Mark Kincey, Sihan Li, Alessandro Novellino, Dammar Pujara, Ram Shrestha, and Nick Rosser

Landslides are one of the most damaging disasters and have killed tens of thousands of people over the 21st century. Slow-moving landslides (i.e., those with surface velocities on the order of 10-2-101 m a-1) can be highly disruptive but are often overlooked in hazard inventories due to their subtle surface signatures and slow movement. Here, we discuss an approach to automatically map slow-moving landslides using feature tracking of freely- and globally-available Sentinel-2 optical satellite imagery.

We evaluate this method through case studies from different environments in the USA, Chile, Italy, and Nepal. Our workflow identifies both known landslides and previously unknown slow-moving landslides in these case studies across very different geographical environments. In particular, in a test case on the well-documented Slumgullion earthflow, our workflow successfully delineates the active portion of the earthflow with velocity magnitudes consistent with field measurements. In another test case on the margin of the Southern Patagonian Icefield, Chile, we identified a very large (>6 km2) composite landslide in the eastern lateral moraine of Glacier Occidental, part of which catastrophically collapsed onto the glacier in early 2023. Finally, we tested our tool to the Ponzano landslide in central Italy which failed catastrophically in 2017.

We are able to detect slow-moving landslides in complex environments using 10-m resolution globally available satellite imagery, all without any manual intervention. Taken together, this means that our workflow can be applied to any region on Earth, regardless of the availability of prior information. We leverage this workflow to conduct a preliminary national-scale survey of slow-moving landslides in Nepal, identifying over 10,000 deforming hillslopes across the country, many of which are populated. Improved mapping of the spatial distribution and surface displacement rates of slow-moving landslides will improve our understanding of their role in the multi-hazard chain and can direct detailed investigations into their dynamics.

Figure: Large slow-moving landslide complex in the lateral moraine of Glaciar Oriental, Chilean Patagonia detected using our workflow.

How to cite: Van Wyk de Vries, M., Arrell, K., Basyal, G., Dadson, S., Densmore, A., Di Martire, D., Dunant, A., Francioni, M., Guerriero, L., Harvey, E., Jimee, G., Kincey, M., Li, S., Novellino, A., Pujara, D., Shrestha, R., and Rosser, N.: Regional-scale monitoring of hillslope deformation through optical satellite imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12753, https://doi.org/10.5194/egusphere-egu24-12753, 2024.

EGU24-13082 | Orals | NH3.8

Integrated geophysical-geodetic-geotechnical systems for slope-scale landslide monitoring 

Jonathan Chambers, James Boyd, Paul Wilkinson, Philip Meldrum, Oliver Kuras, Harry Harrison, Adrian White, Russell Swift, Ben Dashwood, Alessandro Novellino, Matthew Kirkham, Edward Bruce, Shane Donohue, Arnaud Watlet, Jim Whiteley, Sebastian Uhlemann, and Andrew Binley

Moisture induced landslides in clay slopes are generally driven by heterogeneity in both saturation levels and material properties and their arising complex and dynamic interactions in the subsurface. The use of time-lapse geophysical imaging can illuminate four-dimensional subsurface moisture dynamics and geotechnical property changes at the slope-scale, thereby complementing conventional geotechnical point sampling and sensing, and geodetic observations of the ground surface. Here we consider: (1) the development of novel time-lapse geoelectrical, seismic and fibre-optic geophysical imaging technologies for landslide monitoring; (2) in-situ and laboratory derived petrophysical relationships to enable geotechnical information to be estimated from geophysical models; (3) surface topography determination and ground deformation tracking using geodetic observations; (4) coupled geophysical-hydrological modelling of slopes; (5) perspectives and recommendations for the incorporation of integrated geophysical-geodetic-geotechnical technologies into landslide early warning systems – illustrated using results from a number of long-term field observatories.

How to cite: Chambers, J., Boyd, J., Wilkinson, P., Meldrum, P., Kuras, O., Harrison, H., White, A., Swift, R., Dashwood, B., Novellino, A., Kirkham, M., Bruce, E., Donohue, S., Watlet, A., Whiteley, J., Uhlemann, S., and Binley, A.: Integrated geophysical-geodetic-geotechnical systems for slope-scale landslide monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13082, https://doi.org/10.5194/egusphere-egu24-13082, 2024.

EGU24-13537 | ECS | Posters on site | NH3.8

UAV-RFID landslide monitoring : centimetric precision with flying antennas 

Arthur Charléty, Mathieu Le Breton, Eric Larose, and Laurent Baillet

Radio-Frequency Identification (RFID) shows great potential for earth-sciences applications [1], notably for landslide surface monitoring at a high spatio-temporal resolution with long-term robustness to meteorological events (rain, fog, snow) [1,2]. The ability to localize RFID tags using Unmanned Aerial Vehicles (UAV) in a Synthetic Aperture Radar (SAR) approach, would offer new possibilites for monitoring inaccessible terrain, even under vegetation and snow [3].

To that end, an onboard measurement system was built that allows Global Positionning (GPS) tracking of an RFID reader antenna, in order to perform real-time SAR measurement acquisition. Three antenna tracking methods were compared.

In addition, Markov-Chain Monte-Carlo (MCMC) optimization was used to estimate tag position and characterize the solution, even in non-convex cost function scenarios. Two cost functions were compared, based on different RFID-phase processing approaches.

Real-time SAR-RFID localization yielded a centimeter accuracy in the horizontal plane, with lower resolution in the vertical direction. The Post-Processed Kinematics algorithm proved to best fit antenna tracking. The unwrapped-phase cost function provided more convex solutions, at the cost of a lower accuracy compared to the complex-phase cost function. MCMC is computationally efficient in SAR-RFID optimization, with enhanced results concerning the shape and orientation of the main localization errors.

    [1] Le Breton, Mathieu, et al. "Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring." Engineering geology 250 (2019): 1-10.

    [2] Charléty, Arthur, et al. "2D Phase-based RFID localization for on-site landslide monitoring." Remote Sensing 14.15 (2022): 3577.

    [3] Charléty, Arthur, et al. Towards centimeter precision UAV-RFID localization, in preparation.

How to cite: Charléty, A., Le Breton, M., Larose, E., and Baillet, L.: UAV-RFID landslide monitoring : centimetric precision with flying antennas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13537, https://doi.org/10.5194/egusphere-egu24-13537, 2024.

EGU24-14201 | ECS | Orals | NH3.8

Assessing instability of slow-moving landslides over Three Gorges area using InSAR techniques considering hydrogeological triggering factors 

Zhuge Xia, Mahdi Motagh, Wandi Wang, Tao Li, Mimi Peng, and Chao Zhou

Since the first impoundment in 2003 of the Three Gorges Reservoir (TGR), one of the largest reservoirs in the world, the issues of slope instability in the Three Gorges Area (TGA) have attracted significant worldwide attention. The operation of TGR, coupled with anthropogenic activities, has influenced slope instability and reactivation of plenty of landslides in the region. This study introduces a methodology to assess the slope instabilities over TGA using advanced integration of hydrological triggering factors with multi-temporal InSAR (MT-InSAR) techniques.

Our approach involves characterizing the transient deformation of reservoir bank slopes under the coupling effect of rainfall and reservoir water level (RWL) changes. To achieve this, we propose a methodology that uses MT-InSAR analysis and regression analysis to identify triggering factors, taking into account the periods when slope instability is influenced by the drainage/storage period of the reservoir and seasonal rainfall. Determining the optimal window size for the triggering factors involves iterative searching through wavelet analysis, considering the time-lag between rainfall and RWL data. To extract step-like kinematic features for slowing-moving landslides, we apply a constrained least-squares optimization to InSAR-derived displacement time series. We then use independent component analysis (ICA) to isolate and recover the dominant source features, facilitating unsupervised spatiotemporal clustering to elucidate slope kinematics.

This study utilized nearly 100 high-resolution Spotlight TerraSAR-X (TSX) and 50 medium-resolution Sentinel-1 (S1) SAR images captured between 2019 and 2021 to assess the slope instability. Here, we first test our proposed approaches for the single Huangtupo landslide in the TGA, which is one of China's largest reservoir-wading landslides along the Yangtze River; then, the approaches have been expanded to the whole study region near the Badong County. Overall, our proposed framework is transferable and can be applied to other local landslide or regional studies for monitoring slope instability and analyzing complicated cascading hazard chains.

How to cite: Xia, Z., Motagh, M., Wang, W., Li, T., Peng, M., and Zhou, C.: Assessing instability of slow-moving landslides over Three Gorges area using InSAR techniques considering hydrogeological triggering factors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14201, https://doi.org/10.5194/egusphere-egu24-14201, 2024.

EGU24-14904 | ECS | Orals | NH3.8

High-resolution 3D seismic characterization of an Alpine slope instability using a 1'000 node array 

Tjeerd Kiers, Cédric Schmelzbach, Hansruedi Maurer, Florian Amann, Pascal Edme, and Johan Robertsson

Slope instabilities, further destabilized by global warming and extreme weather conditions, pose increasing risks to life and property. Hence, understanding these potentially destructive phenomena is crucial to mitigate associated losses. Established approaches like remote sensing and radar-based observations yield important information on surface displacement. However, seismic imaging and monitoring techniques offer complementary insights into subsurface structures, physical properties and internal time-dependent processes that drive the slope instability evolution.

The ‘Cuolm da Vi’ slope near Sedrun in Central Switzerland is one of the largest mass movements in the Alps (100-200 million m3) and is moving by up to 20cm/year. Even though it currently does not pose an immediate threat, the surface displacement of the slope instability is closely monitored. Yet, knowledge about its internal structure is limited such as, for example, the vertical extent of the unstable section which is suspected to reach several hundred meters in depth. The main objective of our project is to gain new insights into the slope instability structure and evolution. Furthermore, we aim to extend this towards innovative seismic strategies for the characterization and monitoring of large-scale mass movements in general.

In summer 2022, we deployed an extensive seismic sensor network at Cuolm da Vi covering an area of approximately 0.6 km2. This network consisted of over 1'000 autonomous nodes arranged in a hexagonal grid pattern. In addition, we installed a 6-kilometer-long fiber-optic cable, targeted for long-term Distributed Acoustic Sensing (DAS) and Distributed Strain Sensing (DSS) measurements. This unique multi-sensor geophysical network enables us to investigate the unstable slope with an unprecedented level of spatial and temporal resolution, allowing us to monitor time-dependent changes over a broad spectrum of scales in space and time. During 2022 and 2023, we collected an extensive data set, including extended periods of continuous acquisition using the nodal, DAS, and DSS systems.

During the summer 2022 acquisition period, we conducted a controlled-source seismic experiment to characterize the 3D subsurface structure using seismic imaging techniques. Recordings of 163 dynamite shots by the 1’000 node array resulted in more than 30’000 P-wave first-arrival travel-time picks. Using 3D travel-time tomography, we established a first 3D subsurface P-wave velocity model of the Cuolm da Vi body. The resultant tomograms exhibit strong lateral and vertical velocity contrasts, which correlate at the surface with mapped tectonic features and identified instable sections. Furthermore, velocity anomalies within the slope instability volume indicate significant structural and/or geological variations in space. In combination with the other seismic and geotechnical information, the 3D seismic velocity model allows us to, for example, revise hazard scenarios.

How to cite: Kiers, T., Schmelzbach, C., Maurer, H., Amann, F., Edme, P., and Robertsson, J.: High-resolution 3D seismic characterization of an Alpine slope instability using a 1'000 node array, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14904, https://doi.org/10.5194/egusphere-egu24-14904, 2024.

EGU24-15408 | ECS | Orals | NH3.8 | Highlight

Integration of satellite SAR and optical acquisitions for the characterization of the Lake Sarez landslides in Tajikistan  

Olga Nardini, Pierluigi Confuorto, Emanuele Intrieri, Roberto Montalti, Thomas Montanaro, Javier Garcia Robles, and Federico Raspini

Around 1300 lakes make up Tajikistan, which is situated where the Euro-Asian and Indian tectonic plates intersect, and the majority of these were formed by rockfalls and collapsing moraine deposits. Moreover, the area is susceptible to powerful earthquakes due to its localisation. In 1911 a big earthquake in the area generated the Usoi dam, which consequently led to the creation of Lake Sarez, in the Easter side of the country. The region is dominated by high snow-covered mountains, and this complicated topography makes difficult to reach and work in it. So, due to this inaccessibility remote sensing plays an important role in risk assessment and monitoring of the region. The purpose of this work is to provide a detailed overview of ground deformation of the area of Lake Sarez using both the Interferometric Synthetic Aperture Radar (InSAR) technique and optical analysis, with a specific focus on both the right bank and left bank side landslides that affect and threaten the lake.

To study and analyse the two landslides, an integrated satellite analysis has been applied with the aim to collect as much information as possible about the slope instability phenomena of the area of interest. In particular, remote sensing practices such as InSAR using the Sentinel-1, processed through the SqueeSAR approach, and an optical image correlation using COSI-Corr technique applied to SPOT-6 and SPOT-7 acquisitions have been used. In this way, a synoptic and complete analysis of the ongoing displacements was retrieved, allowing to reconstruct the temporal evolution and to solve the spatial variability of the deformation affecting the Lake Sarez banks.

The InSAR data cover the period between 2016 and 2020, and the optical images have been chosen between 2015 and 2021. The two methods emphasize movement and displacement in both right-bank and left-bank landslide, and they concur on the definition of the broader kinematic picture of landslides that doesn't seem to have significant acceleration during the monitored period. The optical method shows the movement especially in the left-side bank landslide. In addition, since the volume of the right-bank landslide is still widely debated (estimated volume around 1.4·109 m3 and area 5.34km2), InSAR data have been also used to develop a model of the geometry and the depth of the sliding surface of a potential landslide that could occur and cause a huge wave that could top over the dam and create a destructive flood downstream. Data shows that most of the movement is located in the central part of the body.

The multi-perspective analysis performed has provided interesting results on the displacement and movement of the two landslides and it may represent a solid base and a starting point for modelling the mechanism of the landslides and also for the evaluation, reduction and mitigation of geohazard risks, especially in impervious areas.

How to cite: Nardini, O., Confuorto, P., Intrieri, E., Montalti, R., Montanaro, T., Robles, J. G., and Raspini, F.: Integration of satellite SAR and optical acquisitions for the characterization of the Lake Sarez landslides in Tajikistan , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15408, https://doi.org/10.5194/egusphere-egu24-15408, 2024.

EGU24-15434 | Posters on site | NH3.8 | Highlight

Machine Learning Assisted Analysis on Space-Borne Point Clouds for Detecting Landslide Affected Areas 

Fuan Tsai, Elisabeth Dippold, Chi-Chuan Lo, and Chien-Liang Liu

Landslide is one of the most frequently occurred and destructive natural hazards in Taiwan and many other places around the world. Using satellite images to help identify landslide affected regions can be an effective and economic alternative comparing to conventional ground-based measures. Our previous study developed a deep learning model to analyze bi-temporal satellite images for detecting landslide affected areas in mountainous areas. The deep learning model can successfully detect spatial (planar) changes of landslides from multi-temporal satellite images. However, in a long-term monitoring of landslide affected areas, it is common to observe existing landslides occurring repeatedly. In addition to planar expansions of existing landslides and increase the extents of landslide scars, it is also common that existing landslides collapse further and produce deeper craters. Therefore, it is necessary to detect and identify the volumetric changes of landslides for a better inventory. To address this issue, this research developed a systematic machine learning framework to analyze multi-temporal three-dimensional point clouds generated from stereo pairs of high-resolution satellite images. However, the lack of appropriate and adequate training data posed a great challenge. This study first modified existing high-resolution point clouds benchmark datasets to be more consistent with the relatively low-density space-borne point clouds for preliminary training. In addition, an integration of historical LiDAR point clouds and archived satellite images were also used to generate local training datasets for transfer learning. Experimental results indicate that the developed machine learning algorithms can be used to effectively analyze space-borne point clouds for detecting volumetric changes of landslides. The results not only can produce more accurate three-dimensional landslide inventories; they are also critical factors for hazard mitigation and policy decision support.

How to cite: Tsai, F., Dippold, E., Lo, C.-C., and Liu, C.-L.: Machine Learning Assisted Analysis on Space-Borne Point Clouds for Detecting Landslide Affected Areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15434, https://doi.org/10.5194/egusphere-egu24-15434, 2024.

EGU24-15817 | ECS | Posters on site | NH3.8 | Highlight

Assessing the Impact of Stabilization Measures on a Slow-Moving Landslide in Arcos de La Frontera town (SW Spain) using InSAR 

Guadalupe Bru, Pablo Ezquerro, Jose M. Azañón, Rosa M. Mateos, Meaza Tsige, Marta Béjar-Pizarro, and Carolina Guardiola-Albert

The town of Arcos de la Frontera is a historical heritage ensemble located in Andalusia (SW Spain), perched on a nearly vertical 100 m calcarenites cliff and surrounded by gentle slopes characterized by being composed of weathered clayey soil from the Guadalquivir Blue Marls formation. This formation, extensively present in the region, poses significant geotechnical challenges, particularly when weathered, exhibiting low strength parameters. Between the end of the 20th and the beginning of the 21st century, the town underwent significant urban expansion. New building blocks were constructed in the head of a complex slow-moving earth slide, whose activity had been producing documented damages to linear infrastructures and urban assets since the 1970s. The most affected structures in this area by slope movements belong to La Verbena neighbourhood, which started to deteriorate soon after their construction in 2007. By October 2009, severe structural damage prompted the evacuation of 22 families, and one of the buildings was officially declared derelict in March 2010 following intense precipitation. Although local authorities commissioned geotechnical investigations and stabilization measures, these initiatives did not approach the complex landslide as a holistic problem. Instead, the works were applied locally with the objective of stabilizing La Verbena neighbourhood. These measures included jet grouting of cement-based injections and drainage and were implemented intermittently in La Verbena from 2011 to 2021, incurring a cost of €4.1 million.

In this investigation, we employed a long-term motion InSAR analysis landslide activity using Sentinel-1 data acquired in both ascending and descending orbit from January 2016 to March 2023. The primary focus was to evaluate the efficacy of local stabilization efforts and compare our InSAR results to in-situ monitoring surveys. Our results indicate a clear deceleration of the landslide head post-mid-2018, providing evidence of the effectiveness of the local stabilization measures. Before this period, the Line-of-Sight (LOS) mean velocity of the entire landslide head in ascending and descending orbits was 2.2 cm/year and 1.3 cm/year, respectively, decreasing to 0.43 cm/year and 0.23 cm/year.

The findings of our study demostrate that the local stabilization works in La Verbena have influenced a significantly larger area, extending beyond the directly intervened zone and effectively stabilizing the entire head of the landslide. By providing data beyond the boundaries of the in-situ monitoring area, InSAR has enriched our insights into the effects of stabilization works, emphasizing the benefits of integrating InSAR techniques as a complementary tool to traditional geotechnical monitoring methods.

How to cite: Bru, G., Ezquerro, P., Azañón, J. M., Mateos, R. M., Tsige, M., Béjar-Pizarro, M., and Guardiola-Albert, C.: Assessing the Impact of Stabilization Measures on a Slow-Moving Landslide in Arcos de La Frontera town (SW Spain) using InSAR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15817, https://doi.org/10.5194/egusphere-egu24-15817, 2024.

EGU24-16395 | ECS | Orals | NH3.8

Monitoring landslides covered by vegetation using interferograms of different wavelengths 

Katarzyna Strząbała, Paweł Ćwiąkała, and Edyta Puniach

Detection of spatial and temporal deformations of landslides, along with the acquisition of precursor information, is crucial for hazard prediction and landslide risk management. Contemporary landslide monitoring systems based on remote sensing techniques (RST) play an important role in risk management and provide important support for Early Warning Systems. Research into the feasibility of using RST for monitoring different types of landslides also includes an analysis of the impact of radar wavelength on the obtained displacement results. The paper compares the time series results of landslide displacements obtained from satellite interferometric imaging in the C-band and L-band. The focus has been particularly on analyzing how the radar wavelength can impact the accuracy of the obtained displacement values and the ability to penetrate dense vegetation, especially under conditions of varying vegetation density. This poses a significant challenge for correct displacement detection. The obtained results are particularly relevant for geographical areas, such as Poland, where a large number of landslides occur in regions covered by dense vegetation. These are the conditions under which scientists encounter the greatest challenges in accurately monitoring these areas using radar systems. The final findings of the research are an important contribution to the development of landslide risk management strategies, crucial for the safety of people and infrastructure.

How to cite: Strząbała, K., Ćwiąkała, P., and Puniach, E.: Monitoring landslides covered by vegetation using interferograms of different wavelengths, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16395, https://doi.org/10.5194/egusphere-egu24-16395, 2024.

EGU24-17207 | Posters on site | NH3.8

FORMATION - Full cOveRage, Multi-scAle and multi-sensor geomorphological map: a practical tool for TerrItOrial planning and landslide analysis 

Federico Raspini, Pierluigi Confuorto, Francesco Barbadori, and Samuel Pelacani

The FORMATION project aims at fostering the implementation of new approaches for the description of geomorphological processes and representation of landforms, whose spatial distribution represents the most immediate tool to detect areas affected by geological risks, such as landslides.

The FORMATION project aims to fill this gap, integrating emerging remote sensing techniques into the new Italian guidelines for the geomorphological mapping provided by ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale in Italian, Italian Institute for the environmental protection and research). The main driver of the FORMATION project is the design of new paradigms for geomorphological mapping, where outcomes of traditional geomorphological survey and land degradation models, coupled with multi-band satellite analysis and multi-platform LiDAR and UAV data are convoyed within GIS (Geographic Information System) environment for the classification of landforms and the creation of a multi-scale, digital geomorphological map.

Databases, models, tools and methods will be presented and discussed with prototype implementations at pilot Italian cases in the Alps and Apennines, which share common pressing challenges on the environment, such as gravitational and running water-based processes causing several damages with a direct implication on human life and millions of euros spent in environmental remediation. Target basins have been selected to cover different geological, geomorphological and climatic settings and to demonstrate the effectiveness and replicability of the proposed methodology.

Here we present preliminary results for the Val d’Orcia, an area in Central Tuscany (Italy) with a long history of landslides and erosive processes. We exploited outputs provided by interferometric processing of Sentinel-1 data to create ground deformation maps used to scan wide areas, flag unstable zones and support the definition of priorities starting from the situations deemed to be most urgent. A database of active moving areas has been created to support further activities of the project, including field surveys, further investigation with landscape investigations and modeling.

Activities performed has been funded by MUR (Ministry of University in Italy) within the PRIN 2022 call Directive Decree n. 104 del 02/02/2022, Codice Progetto MUR 2022C2XPK7, “Full cOveRage, Multi-scAle and multi-sensor geomorphological map: a practical tool for TerrItOrial plaNning - FORMATION”- CUP B53D23007000006, that is included in within the activities funded by European Union (Next Generation EU).

How to cite: Raspini, F., Confuorto, P., Barbadori, F., and Pelacani, S.: FORMATION - Full cOveRage, Multi-scAle and multi-sensor geomorphological map: a practical tool for TerrItOrial planning and landslide analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17207, https://doi.org/10.5194/egusphere-egu24-17207, 2024.

EGU24-17951 | ECS | Orals | NH3.8

Combining ERT and an orthophoto time series to investigate thaw-related landslides in the Canadian Arctic 

Saskia Eppinger, Konrad Heidler, Hugues Lantuit, and Michael Krautblatter

Retrogressive thaw slumps (RTS) are a common permafrost related landslide type in the Arctic and provide a large amount of material to coastal nearshore zone, lakes and rivers. RTS are characterized by highly dynamic changes and rapid internal processes. Along the Canadian coastline there is an increasing number of RTS documented over the last century, acting sensitive to a warming climate.

The occurrence and behaviour of these landslides is strongly dependent on the presence of ground ice, including their likelihood for polycyclicity and reactivation. To detect and evaluate the ground ice content in different activity- and stabilization stages we used electrical resistivity tomography (ERT) on several RTS on Herschel Island in the Canadian Beaufort Sea. We combined ERT profiles remeasured 10 years apart, with orthophotos since 1952 to gain a detailed insight in their long-term behaviour, the availability of ground ice and the factors controlling polycyclicity.

This study demonstrates the capacity of ERT for detecting massive ice bodies and internal changes. Combining this with a time component and orthophoto analysis, provides a unique insight into the behaviour of retrogressive thaw slumps, but also shows the need to use complimentary techniques to correctly interpret geophysical measurements.

How to cite: Eppinger, S., Heidler, K., Lantuit, H., and Krautblatter, M.: Combining ERT and an orthophoto time series to investigate thaw-related landslides in the Canadian Arctic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17951, https://doi.org/10.5194/egusphere-egu24-17951, 2024.

EGU24-17961 | ECS | Posters on site | NH3.8

Determination of the potential shear plane of a clay-rich, deep-seated landslide using spectral induced polarization and geotechnical approaches: case study Brandstatt, Lower Austria 

Edoardo Carraro, Adrian Flores-Orozco, Jorge Monsalve Martinez, Philipp Marr, and Thomas Glade

Increasing knowledge about the landslide geometries is key to understand the factors driving the slope instability. Direct investigations can provide information about the soil properties or locate features that help to recognize the mechanism of the landslide failure. However, this information is punctual and requires the interpolation of the data, which may lead to uncertainties due to the complexity of the geological context. Geophysical methods offer the capability to broaden spatial information, covering extended depths, and do not require interpolation. In particular, the induced polarization (IP) method has proven to be a powerful technique for investigating the hydrogeological properties of landslides. This method offers advantages in discriminating between interfacial and electrolytic (electrical) conduction mechanisms, which is crucial for the accurate interpretation of imaging results in clay-rich landslides. This is attributed to the IP method's capability of extracting not only electrical conductive properties but also capacitive (i.e., polarization effect) properties of the subsurface and its frequency dependence.
In this work, we present the results of an ongoing investigation in the Brandstatt landslide (Lower Austria). This is characterized by a complex, slow-moving earth slides system, located in a geological transition zone between the Flysch and the Klippen Units and the Molasse zone, which is known to be a landslide-prone area. We applied a combination of different geotechnical methods, e.g., inclinometric measurements and dynamic probing (DP) tests, which have been carried out on the slope. We have conducted four IP profiles across the active area, each consisting of 32 electrodes with a spacing of 10 m. IP measurements were collected within frequency ranges of 0.25 to 225 Hz to discern the frequency dependence of the electrical properties and facilitate the quantification of hydraulic properties. The results of the investigations indicate different displacement rates and the presence of slip surfaces varying within the shallower layers. Additionally, IP imaging reveals the presence of high conductivity (50 mS/m) and polarization anomalies (20 µS/m) located in the first 40 meters, which are associated with the clay-rich area susceptible to movement. Furthermore, the contact with low conductivity values at depth indicates the geometry of the potential sliding plane. To potentially strengthen the correlation between the shallow information obtained by the geotechnical data and deep IP images, we examine the possibility of incorporating the results from surveys using electromagnetic methods. These results demonstrate that the combined application of direct and indirect methods allows us to gain better insight into large-scale subsurface variations that control small-scale changes in the surface and near-surface.

How to cite: Carraro, E., Flores-Orozco, A., Monsalve Martinez, J., Marr, P., and Glade, T.: Determination of the potential shear plane of a clay-rich, deep-seated landslide using spectral induced polarization and geotechnical approaches: case study Brandstatt, Lower Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17961, https://doi.org/10.5194/egusphere-egu24-17961, 2024.

EGU24-19353 | ECS | Orals | NH3.8

PlanetScope time series for the operational monitoring of large landslide terrain motion. 

Bastien Wirtz, Floriane Provost, Jean-Philippe Malet, and Ombeline Méric

PlanetScope imagery, with its high spatial resolution (3 m) and high revisit time (possibly 1 day, according to cloud cover) is a game changer for operational landslide monitoring especially for monitoring surface deformation using Optical Image Correlation (OIC) approaches. The high spatial resolution should allow to enhance both the sensitivity and the accuracy of the measurements with the possibility to obtain a theoretical deformation detection of 0.30 m. The high revisiting time ensures the completion of dense image time series, useful to increase the Signal-to-Noise ratio associated with multiple image pairing and to possibly construct deformation time series on daily temporal scales. These two aspects of PlanetScope imagery fill the gap of current optical constellations that usually offer either lower spatial resolution with regular and rather short revisit time (e.g. Sentinel-2, Landsat-8) or very high spatial resolution with irregular revisit time (e.g. Pléiades, Worldview). However, the specifications of the PlanetScope L3B data products do not meet the expected quality in terms of ortho-rectification and image time series co-registration and a specific workflow needs to be implemented. 

We propose a new workflow for -processing  PlanetScope L3B data products. The developed approach consists firstly in removing  clouds and water, using Fmask algorithm and PlanetScope Unusable Data Mask products delivered with the L3B products.

Secondly, we observe that the misalignment between scenes  can go up to 8 pixels of difference (24 m on ground), varying highly within the images and from one image to another. To correct such errors, a co-registration process in two steps is applied. At first, using the AROSICS library (Scheffler et al., 2017), the misalignment errors at a local scale are computed by image correlation in the frequency domain on overlapping subwindows pinned on a grid covering the whole image. These offsets are used to correct the local scale co-registration errors. After this step, a global shift is still observed between scenes, leading to the second step of co-registration at global scale. The global shift is corresponding to the mean offsets between image tie points, and is corrected by applying these offsets directly on the product. These developments have been integrated within the  GDM-OPT-Slide service and have been tested on two sites: La Valette (South East France) and Aiguilles (South East France) landslides to retrieve the mean velocity and the ground displacement time series for each pixel. We validate the proposed workflow by comparing the results of the processing chain and in-situ dataset (GNSS, Lidar and photogrammetry). We show that the proposed methodology allows envisaging the operational use of Planetscope imagery to document and monitor the displacement of large landslides with velocity larger than 0.3 m/year.

How to cite: Wirtz, B., Provost, F., Malet, J.-P., and Méric, O.: PlanetScope time series for the operational monitoring of large landslide terrain motion., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19353, https://doi.org/10.5194/egusphere-egu24-19353, 2024.

EGU24-19801 | ECS | Orals | NH3.8

Alternance of two reactivation regimes on Pont-Bourquin earthflow, highlighted by changes in seismic velocity and sensitivity to rainfall 

Mathieu Le Breton, Eric Larose, Florent Chatelain, Laurent Baillet, Alexandra Royer, and Antoine Guillemot

This study detects the regular alternation of two different reactivation regimes of the Pont-Bourquin Earthflow, occurring from 2010 to 2023, by combining the continuous monitoring of three indicators:
(1) seismic velocity, using ambient noise interferometry 1,2
(2) displacement rate, using extensometers and RFID tags 3–5
(3) sensitivity to rainfall and snowmelt, using dynamic impulse response deconvolution 6,7

The study confirms the hypothesis of a dual mechanism previously suggested on this landslide from the lag of hydrological and displacement response to precipitations 8,9, and goes further by detecting when these regime changes occur. In an early-warning system, this method might serve to discriminate different regimes during accelerations that are seemingly equivalent.

 

References related to this study:

1 Mainsant, G. et al. Ambient seismic noise monitoring of a clay landslide: Toward failure prediction. J. Geophys. Res. Earth Surf. 117, F01030 (2012).
2 Le Breton, M., Bontemps, N., Guillemot, A., Baillet, L. & Larose, É. Landslide monitoring using seismic ambient noise correlation: challenges and applications. Earth-Sci. Rev. 103518 (2021) doi:10.1016/j.earscirev.2021.103518.
3 Le Breton, M. et al. Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring. Eng. Geol. 250, 1–10 (2019).
4 Le Breton, M. et al. Dense and long-term monitoring of earth surface processes with passive RFID — a review. Earth-Sci. Rev. 234, 104225 (2022).
5 Charléty, A., Le Breton, M., Baillet, L. & Larose, E. RFID Landslide Monitoring: Long-Term Outdoor Signal Processing and Phase Unwrapping. IEEE J. Radio Freq. Identif. 7, 319–329 (2023).
6 Bernardie, S., Desramaut, N., Malet, J.-P., Gourlay, M. & Grandjean, G. Prediction of changes in landslide rates induced by rainfall. Landslides 12, 481–494 (2015).
7 Le Breton, M. Suivi temporel d’un glissement de terrain à l’aide d’étiquettes RFID passives, couplé à l’observation de pluviométrie et de bruit sismique ambiant. (Université Grenoble Alpes, 2019).
8 Bronnimann, C. S. Effect of Groundwater on Landslide Triggering. (École Polytechnique Fédérale de Lausanne, 2011).
9 Bièvre, G. et al. Influence of environmental parameters on the seismic velocity changes in a clayey mudflow (Pont-Bourquin Landslide, Switzerland). Eng. Geol. 245, 248–257 (2018).

How to cite: Le Breton, M., Larose, E., Chatelain, F., Baillet, L., Royer, A., and Guillemot, A.: Alternance of two reactivation regimes on Pont-Bourquin earthflow, highlighted by changes in seismic velocity and sensitivity to rainfall, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19801, https://doi.org/10.5194/egusphere-egu24-19801, 2024.

EGU24-20019 | ECS | Posters on site | NH3.8 | Highlight

Understanding the role of soil moisture in landslide research: Application of Cosmic Rays Neutron Sensing (CRNS) on a slow-moving landslide in Lower Austria 

Philipp Marr, Alejandra Jiménez Donato, Robert Kanta, Thomas Glade, Enrico Gazzola, Luca Morselli, Stefano Gianessi, and Federica Lorenzi

Soil moisture plays a crucial role in landslide research as it directly influences slope stability and the occurrence of landslides. The amount of water present in the soil significantly impacts its strength and cohesion. Excessive soil moisture, especially during periods of heavy rainfall, can reduce the frictional resistance within the soil, leading to a decrease in shear strength and an increased likelihood of landslides. The province of Lower Austria is situated in a region highly prone to landslides due to its specific geological characteristics. The prevailing geological formations consist mainly of the Flysch and the Klippen Zone, characterized by mechanically weak units comprising intercalated limestones and deeply weathered materials. These geological conditions, coupled with hydrological factors, changes in land use, and various anthropogenic influences, collectively contribute to the inherent instability of the region.

Monitoring and understanding soil moisture levels provide valuable insights into the predisposing and triggering factors, potentially enhancing the prediction and mitigation of these hazardous events. Advancements in technologies like Cosmic Rays Neutron Sensing (CRNS) enables to obtain spatially averaged soil moisture measurements, offering a more comprehensive understanding of moisture distribution across different scales. The defining characteristic of (CRNS) technology lies in its ability to directly measure water content, naturally averaged within a volume known as the footprint. This volume encompasses a horizontal extension with a radius spanning up to hundreds of meters and penetrates the soil to depths of tens of centimeters. This is widely acknowledged as the primary advantage of the CRNS probe compared to point-scale measurements, as it yields a valuable representative value for water availability in the designated area.  In this study, we apply CRNS at a slow-moving landslide in Lower Austria and explore its potential.

How to cite: Marr, P., Donato, A. J., Kanta, R., Glade, T., Gazzola, E., Morselli, L., Gianessi, S., and Lorenzi, F.: Understanding the role of soil moisture in landslide research: Application of Cosmic Rays Neutron Sensing (CRNS) on a slow-moving landslide in Lower Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20019, https://doi.org/10.5194/egusphere-egu24-20019, 2024.

Landslides are the most frequent type of natural hazard in the Azores Archipelago and are responsible for significant socio-economic consequences and nearly 40 casualties in the last three decades. Landslide monitoring is a mandatory step in landslide risk mitigation. Various techniques, such as remote sensing, geotechnics, geodetics, geophysics, and hydrologic, can be employed for monitoring landslides. These methods allow the collection of crucial data regarding landslide conditions, including the location of failure surfaces, areal extent, landslide kinematics, and hydrogeometeorological parameters.

In March 2010, a landslide triggered by rainfall, covering an area of approximately 18.500 m2, caused several damages on roads, houses and problems related with water and energy supply on Maia (Santa Maria Island). Since then, an Integrated Monitoring System (IMS) was designed and implemented to assess the kinematic behaviour and geometry of the unstable mass. This system incorporates a combination geodetic (total station), geotechnical (inclinometer), and meteorological monitoring technics. The IMS data is transmitted to the Centre for Information and Seismovolcanic Surveillance of the Azores (CIVISA), responsible for the permanent system management and data analysis. Periodic bulletins are issued by this entity, along with the dissemination of warnings and alerts to the Azores Regional Government.

The results of the geodetic network demonstrates a heterogeneous spatial deformation pattern in the unstable mass. The planimetric displacement and the subsidence pattern in the upstream sector of the road in the central part of the landslide, may be associated with the concave morphology of the terrain. This setting promotes the accumulation of water through surface runoff, that increase the effective load and shear stress in this sector. It is also worth noting that downstream of the road, both planimetric and altimetric displacements increase with proximity to the shoreline, with maximum accumulated displacement since 2012 of 0.054 m and 0.012 m, respectively. This observation is justified by the erosive action of the sea at the toe of the landslide, which enhances greater deformation of the destabilized mass in this sector.

Since the beginning of inclinometric monitoring in October 2017, the maximum cumulative displacement of the landslide at depth is 18.5 mm and 21.5 mm at depths of 7.0 m and 1.0 m in boreholes FSM1 and FSM2, respectively. Results obtained from the inclinometric monitoring network allowed the recognition of the rupture surface of the landslide between depths of 18.0 m and 18.5 m in borehole FSM1 and between depths of 15.5 m and 16.0 m in borehole FSM2. In general, the deformation velocity along the vertical profile of the terrain is uniform in borehole FSM1 and tends to decrease with depth in borehole FSM2. The behaviour of the kinematics of the landslide at depth is strongly determined by the higher or lower soil water content, as indicated by variations in the velocity of the displacement.

How to cite: Marques, R. and Silva, R. F.: Landslide monitoring based on an Integrated Monitoring System (IMS) using a combination of geodetic, geotechnical, and meteorological monitoring technics: a case study from Maia (Santa Maria Island, Azores), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20118, https://doi.org/10.5194/egusphere-egu24-20118, 2024.

EGU24-20621 | ECS | Posters on site | NH3.8

Long-term landslide ecological monitoring: the case of Pomezzana, Tuscany. 

Andrea Dani, Emanuele Giachi, Federico Preti, Marco Cabrucci, Martina Pollastrini, Agnese Bellabarba, Carlo Viti, Francesca Decorosi, and Yamuna Giambastiani

Land degradation and soil erosion due to increasingly frequent extreme hydro-meteorological events, has negative consequences on ecological processes, making the environment, particularly rural and mountain areas, more susceptible to biodiversity loss. Nowadays, the use of plants as a building material transfers the plant multifunctionality within engineering structures and meets the demand rising from society for more environmentally friendly approaches to structure design. EU strategies and regulations require the employment of Nature-Based Solutions, such as Soil and Water Bioengineering techniques (SWBE).  

 

Soil and Water Bioengineering techniques are applied worldwide, achieving great results for slope and streambank stabilization, water regulation, landslides restoration and for mitigation of environmental impacts. SWBE techniques manage natural hazard control using plants as living material in combination with inert natural material, achieving two main goals: on the one hand the technical function of stabilizing the soil on the other hand the mitigation of environmental damage, initiating natural ecological processes.

 

The research aims to evaluate the technical and ecological recovery effectiveness of a SWBE intervention for the restoration of a shallow landslide, occurred during Versilia flood in 1996. The project aims to monitor the evolution of vegetation and evaluate the composition of soil microorganisms by comparing the area restored by the intervention and surrounding areas. Field samplings and analysis will be conducted on two landslide bodies that occurred with the same extreme rainfall event: first site a landslide restored with SWBE techniques and the second site a naturally evolving landslide. A multi-approach methodology will be developed to evaluate differences and correlation between the ecological processes (vegetation and soil microorganism) and the technical efficiency of the landslide restoration intervention.

How to cite: Dani, A., Giachi, E., Preti, F., Cabrucci, M., Pollastrini, M., Bellabarba, A., Viti, C., Decorosi, F., and Giambastiani, Y.: Long-term landslide ecological monitoring: the case of Pomezzana, Tuscany., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20621, https://doi.org/10.5194/egusphere-egu24-20621, 2024.

EGU24-20709 | Posters on site | NH3.8

Temperature influence on relative seismic wave velocity measurements for landslide monitoring 

Etienne Rey, Alexandra Royer, Antoine Guillemot, Eric Larose, and Lucile Andre

Seismic interferometry is used as an innovant method since a tens of years to monitor landslides (LeBreton et al., 2021; Larose et al., 2022), especially since a sharp decrease of about 7 % in relative seismic velocity have been measured on the Pont-Bourquin clay landslide (Switzerland) a few days before a significative reactivation of the instable slope (Mainsant et al., 2012). However, if the relative variation of seismic wave velocity (dV/V) appears as a good precursory signal before a failure, indicating a  loss hydro-mechanical properties of the subsurface, the relative variation of seismic wave velocity (dV/V) within time generally show reversible variations due to environmental forcings. In the present work, we analyse more than two years of seismic data measured on a large clayey morainic landslide located in Valloire (Savoie, France), where seismic interferometry was coupled with other surface displacement monitoring involving RFID measurements and time-lapse photographies (Laigle et al., 2019).

On this site and during the stable considered period, dV/V appears well correlated with air temperature but in an unexpected way, since a decrease of temperature is correlated to a decrease of dV/V, instead of an expected increase of rigidity for soils. Considering the absence of water table in the ground due to high slope and permability, this correlation is observed at both daily and seasonal time scales, with a maximal amplitude of +/- 3%, and a very short response delay (several hours only). We precisely describe and quantify these correlations, towards in a second time being able to correct reversible temperature effects on dV/V and distinguish them from other possible processes precursor to failure. As temperature seems to have a stabilisation effect on slope due to an increase of the ground stiffness (dV/V) with temperature, our study paves the way to investigate more in details thermo-elastic processes on landslides as already done for rock columns (Guillemot et al., 2022).

 

Keywords: seismic interferometry, dV/V, temperature, landslide, monitoring

 

References

Mainsant G, Larose E, Brönnimann C, Jongmans D, Michoud C & Jaboyedoff M(2012). Ambient seismic noise 505 monitoring of a clay landslide: Toward failure prediction. J. Geophys. Res. 117, F01030. 506 https://doi.org/10.1029/2011JF002159

LeBreton M, Bontemps N, Guillemot A, Baillet L & Larose E (2021): Landslide Monitoring Using Seismic Ambient Noise Interferometry: Challenges and Applications, Earth Science Review 216, 103518

Larose E, Royer A, Guillemot A, LeBreton M, L. Baillet, E. Rey (2022). SOILSTAB: A seismic noise-based solution for near real-time monitoring of soil rigidity in the context of slow moving landslides (and beyond). Journées Aléas Gravitaires, Montpellier 2022.

Guillemot A, Baillet L, Larose L, Bottelin P (2022). Changes in resonance frequency of rock columns due to thermoelastic effects on a daily scale:  observations, modelling and insights to improve monitoring systems. Geophys. J. Int. 231, 894-906.

Laigle D., Jongmans D., Liebault F., Baillet L., Rey E., Fontaine F., Borgniet L., Bonnefoy-Demongeot M., Ousset F. (2019). Implementation of an integrated management strategy to deal with landslide triggered debris-flows : the Valloire case study (Savoie, France). 7th Int. Conf. on Debris-Flow Hazard Mitigation, June 10-13 2019, Golden, Colorado.

How to cite: Rey, E., Royer, A., Guillemot, A., Larose, E., and Andre, L.: Temperature influence on relative seismic wave velocity measurements for landslide monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20709, https://doi.org/10.5194/egusphere-egu24-20709, 2024.

EGU24-21116 | Orals | NH3.8

Automatic Photomonitoring Analyses for Rockfall Detection and Mapping at the Poggio Baldi Landslide, Italy 

Giacomo Santicchia, Antonio Cosentino, Giandomenico Mastrantoni, Antonio Molinari, and Paolo Mazzanti

In recent years, the monitoring of natural phenomena has become increasingly essential, with scientific innovations continuously enhancing its quality through more effective tools and efficient techniques. This study focuses on the synergistic utilization of two complementary monitoring techniques employed at the Poggio Baldi natural laboratory to monitor the active rock scarp: photomonitoring and laser surveys.

The Poggio Baldi landslide is one of the largest rock and debris landslide phenomena in the Emilia-Romagna Apennines, with an estimated volume of approximately 4 million cubic meters. Two documented episodes of activation occurred on March 25, 1914, and March 18, 2010, with ongoing rockfall phenomena on the scarp. To monitor the current rockfall phenomena on the landslide slope in 2021, the University La Sapienza inaugurated the Poggio Baldi natural laboratory. Over the past three years, a combination of monitoring techniques for rockfall has been employed at this site.

Utilizing affordable sensors such as optical cameras enable the daily monitoring of slopes. Through the implementation of automated acquisitions, images can be captured at an hourly frequency or even more frequently. This approach provides detailed information on rockfall occurrences, including their specific locations, affected surface areas, and the frequency magnitude relationships. To further validate rockfall occurrences, additional instruments like microphones and seismic devices can be integrated. The acquired images possess a lightweight quality, making photomonitoring a practical and cost-effective option for continuous surveillance. These images facilitate change detection analyses, allowing for the assessment of any alterations between successive images. The analytical process has been seamlessly automated to enhance efficiency.

The combined use of laser scanners and photomonitoring creates a comprehensive monitoring strategy. While laser scanners provide detailed volumetric data, photomonitoring enhances the understanding of individual events' frequency, size, and location. This combined approach leverages the strengths of each technique, mitigating the limitations of the individual methods. Relying only on periodic LiDAR acquisitions wouldn't enable us to assess whether portions of the landslide slope collapsed in a single event or multiple events, and if smaller rockfalls could be precursors to larger magnitude events. Moreover, employing this combination of permanently installing an optical instrument and conducting periodic LiDAR surveys proves advantageous both economically and in managing the volume of data.

The advantage of this combined method lies in its ability to provide both detailed, high-resolution data from laser surveys and near real-time information from photomonitoring. This approach allows for a better understanding of the ongoing dynamics of the landslide at Poggio Baldi, contributing valuable insights for hazard assessment and facilitating the development of more effective risk mitigation strategies.

How to cite: Santicchia, G., Cosentino, A., Mastrantoni, G., Molinari, A., and Mazzanti, P.: Automatic Photomonitoring Analyses for Rockfall Detection and Mapping at the Poggio Baldi Landslide, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21116, https://doi.org/10.5194/egusphere-egu24-21116, 2024.

EGU24-3526 | Posters on site | NH3.10

Sen12Landslides: A Multi-modal, Large-scale, Multi-temporal Benchmark Dataset for satellite-based Landslide Monitoring 

Paul Höhn, Konrad Heidler, Robert Behling, and Xiao Xiang Zhu

Landslides, with their devastating impact on communities and infrastructure, present a pressing challenge for accurate and timely detection. Effective monitoring is therefore essential, not only to understand the process of landslides, but also to provide comprehensive risk assessments for future planning and to mitigate the consequences of such events. In addition, timely mapping of these hazardous events is essential to gain an overview and coordinate rescue efforts, while also addressing the geoscientific component of how these processes evolve over space and time, including potential acceleration due to climate change. To address this critical need, our study presents a large-scale, multi-temporal dataset that uniquely combines time-series data from the Sentinel-1 and Sentinel-2 satellites to improve landslide monitoring. Our initiative aims to create a globally standardized dataset that will overcome the challenges of transferring existing algorithms and facilitate the development of more effective models. This innovative and still growing dataset, which already includes over 7500 landslides from 16 global regions, offers a unique opportunity to advance machine learning methods for landslide detection. Using time-series analysis of Sentinel-1 radar data, we have successfully identified the onset and end dates of landslide events. Complementing this, Sentinel-2 optical data analyzed by NDVI change provide detailed land cover information critical for accurate landslide labelling. Our methodological approach is rigorously validated by manual expert review to ensure the reliability and accuracy of our results. By incorporating temporal context and combining the cloud-penetrating capabilities of Sentinel-1 with the rich multispectral resolution of Sentinel-2, this research represents a significant advance in the use of satellite data for landslide monitoring and serves as an invaluable resource for both the remote sensing and machine learning communities. It supports both object-based landslide identification and granular pixel-level analysis through semantic segmentation, extending its versatility for various environmental research applications. In our initial benchmarks, we evaluated existing state-of-the-art models such as UNet3D, U-TAE, TSViT and U-ConvLSTM to better understand their individual advantages for landslide monitoring. This process highlights the potential of our dataset to provide a reliable benchmark for future developments in landslide detection research.

How to cite: Höhn, P., Heidler, K., Behling, R., and Zhu, X. X.: Sen12Landslides: A Multi-modal, Large-scale, Multi-temporal Benchmark Dataset for satellite-based Landslide Monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3526, https://doi.org/10.5194/egusphere-egu24-3526, 2024.

Due to the impact of climate change, the increasing frequency of extreme rainfall events, with concentrated rainfalls, commonly cause landslide hazard in the mountain areas of Taiwan. However, there are uncertainties for the predicted rainfall as well as the landslide susceptibility analysis.

This study employs machine learning approached, including the logistic regression method LR and deep learning method CNN, to analyze the landslide susceptibilities. Together with the predicted temporal rainfall, the predictive analysis of landslide susceptibility was performed in the adopted study area in Central Taiwan. The uncertainties within the rainfall prediction was firstly investigated before applied to the landslide susceptibility analysis. To assess the susceptibility of the landslides, logistic regression method LR and deep learning method CNN were applied. The results of predictive analysis, with the discussions on the accuracy and uncertainties, can be applied for a better landslide hazard management in the study area.

How to cite: Shou, K.-J.: On the Predictive Analysis of Landslide Susceptibility by ML Approached– for the Case in Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4938, https://doi.org/10.5194/egusphere-egu24-4938, 2024.

EGU24-9020 | ECS | Orals | NH3.10 | Highlight

A scalable workflow for shallow landslide inventory construction based on multitemporal LiDAR data with the explicit inclusion of landslides in forests 

 Lotte de Vugt, Shoujun Jia, Andreas Mayr, Barbara Schneider-Muntau, Thomas Zieher, Frank Perzl, Marc Adams, and Martin Rutzinger

For the development of accurate shallow landslide (translational debris and earth slides with a depth < 2 m) susceptibility assessments and further hazard or risk analyses, it is essential that complete and accurate landslide inventory data is available. Various methods are applied for the construction of shallow landslide inventories. However, it is known that the most used methods underreport landslides in forests, e.g. with visual interpretation of satellite/aerial imagery and manual mapping of landslides during field visits. To address this issue, several studies have instead used topographic Light Detection and Ranging (LiDAR) data to create their landslide inventories. These studies showed that landslides under forest cover can be mapped using topographic LiDAR, as LiDAR can penetrate the vegetation cover. The methods used in these studies can be divided into (1) methods using raster data derived from filtered LiDAR point-cloud data and (2) methods working directly on point-cloud datasets. The benefit of the raster-based methods is their computational speed and scalability, while point-cloud based methods are difficult to apply to larger areas, due to their high computational requirements, but have a greater measurement accuracy (e.g., landslide depth). This difference in accuracy is especially important for the mapping of shallow landslides, which often leave only limited traces in the landscape.

This study investigates how both methods can be combined to derive a semi-automatic workflow for mapping shallow landslides using LiDAR data that is accurate and scalable. The investigation focusses on mapping shallow landslides under forest, and on how the derived workflow for mapping landslides needs to be adapted to forested and non-forested areas. In a first step, potential landslide-prone areas are identified using the difference of pre- and post-event digital terrain models, an after-event digital terrain model and their related topographic derivatives such as the roughness coefficient and slope. In the next step, the identified areas are segmented and man-made topographic changes are removed, before they are further analyzed with a more accurate mapping technique using point-cloud data from the multiscale model-to-model cloud comparison (M3C2) algorithm. In addition to the M3C2 distances, the point-cloud based mapping will also make use of 3D shape features describing point location and orientation to increase the accuracy and robustness of the topographic change detection and estimation. The scalability of the workflow is tested by applying the workflow to several areas in the Tyrolean Alps (Austria).

First results, derived with a logistic regression model using the raster-based derivatives, show a distinct difference in the feature importance of the topographic derivatives when forested and non-forested areas are compared. In addition, the performance of the model also greatly benefits from a separate training in forested and non-forested areas, with an increase in the Area Under the Curve (AUC) value from 0.84 to 0.89 for, respectively, unseparated and separated training.

How to cite: de Vugt,  ., Jia, S., Mayr, A., Schneider-Muntau, B., Zieher, T., Perzl, F., Adams, M., and Rutzinger, M.: A scalable workflow for shallow landslide inventory construction based on multitemporal LiDAR data with the explicit inclusion of landslides in forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9020, https://doi.org/10.5194/egusphere-egu24-9020, 2024.

EGU24-10760 | ECS | Posters on site | NH3.10

Geographic Object-Based Image Analysis (GEOBIA) for inventory mapping of forest-covered landslides: a case study in Jena, Germany 

Ikram Zangana, Rainer Bell, Lucian Drăguţ, and Lothar Schrott

For assessing landslide susceptibility and hazard reliable landslide inventories are essential. Historic landslides might indicate periods of increased landslide activity compared to more recent decades. However, landslide features might have diminished over time especially due to human impact. Often features of historic landslides are well preserved under forest providing a valuable source for preparing or completing landslide inventories, but mapping them is challenging.

Analyzing Light Detection and Ranging (LiDAR) and its derivatives have become powerful tools in landslide research, particularly in the identification and mapping of landslides. In contrast to the expert-based analysis of LiDAR derivatives, there is a limited number of studies employing object-based approaches to (semi)automatically mapping landslides from LiDAR data. This study focuses on the use of Geographic Object-Based Image Analysis (GEOBIA) based solely on LiDAR derivatives (1 m resolution) to conduct inventory mapping of forest-covered landslides within a middle mountainous region in Germany.

The study centers on Jena and its surrounding areas in Germany, covering an approximate area of 150 km². As part of the Thuringia basin, the study area is dominated by two major geological formations. The Muschelkalk  (limestone) covers the majority of the upper parts of the slopes and the plateau areas. It is underlain by the Buntsandstein  (marls, claystone and sandstone). Large landslides are historic and covered by forest. The methodology incorporates an inventory map for the purposes of module training and validation. LiDAR derivatives, encompassing slope, plan curvature, Terrain Roughness Index (TRI), Terrain Position Index (TPI), and differential openness, are systematically applied across diverse scales to identify landslide scarps and bodies within distinct window sizes. This systematic approach is further complemented by multi-resolution segmentation at multiple levels, support vector machine (SVM), rule-based classification, GEOBIA-based refinements, and a rigorous accuracy assessment. Collectively, these components establish a comprehensive framework for the progression of landslide detection and mapping methodologies.

The results reveal that the proposed approach achieved an 80% detection rate compared to the expert-based inventory. Nevertheless, continuous efforts are being made to reduce the occurrence of false positive detections. While the module demonstrates proficiency in identifying and mapping historical forest-covered landslides, its current functionality is limited to recognizing and mapping large and medium-sized landslides [area > 0,5 ha]. The transferability of this module should be evaluated in other regions. We anticipate that globally landslides with clear geomorphological signatures in high-resolution Digital Terrain Models (DTMs) can be identified using this approach.

How to cite: Zangana, I., Bell, R., Drăguţ, L., and Schrott, L.: Geographic Object-Based Image Analysis (GEOBIA) for inventory mapping of forest-covered landslides: a case study in Jena, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10760, https://doi.org/10.5194/egusphere-egu24-10760, 2024.

The integration of Machine Learning (ML) into susceptibility mapping and hazard modelling has unveiled complex relationships between landslide predisposing factors and occurrence. However, understanding the practical implications of landslide susceptibility results still crucial. One concern is the conventional treatment of landslide inventory data, where various landslide types are uniformly addressed during model training, proving unrealistic given diverse geological and geomorphological conditions for distinct landslide types. Moreover, each landslide type requires a unique mitigation strategy, and valuable information is lost when treating all landslides uniformly. Another challenge is how susceptibility models typically present probabilities, while practical applications demand clear categories to avoid underestimation or overestimation of risks.

This study explores the practical application of landslide susceptibility to linear infrastructure, specifically railway design. The investigation centres on two established models, comparing each other: firstly, the classical statistical-based method, Weight of Evidence (WoE); and secondly, a ML method, the Generalized Additive Model (GAM). WoE was chosen for its clarity, while GAM accommodates continuous variables, offering a nuanced understanding of non-linear relationships. The study area encompasses a new 22.11 km railway stretch in the central Marche Region, Italy. We assessed the susceptibility to five landslide types, as classified in the Italian Landslide Inventory (IFFI). The models (WoE and GAM) are applied using different landslide types as distinct training datasets, resulting in unique susceptibility maps for each type. Additionally, the study evaluates the models using the Area Under the Receiver Operating Characteristic (AUROC) curve, providing insights into their performance. The rockfall susceptibility map demonstrates high reliability (AUROC of 0.942 with WoE and 0.978 with GAM), while slide-type landslides show more modest but fairly good results (AUROC of 0.696 with WoE and 0.784 with GAM).

To provide a comprehensive understanding of the study area, overall landslide susceptibility was calculated, corresponding to the probability of failure for any type of landslide. The overall probability was obtained by implementing a complementary probability approach for landslide probability analysis. A method is then proposed to classify the sensitivity of landslide types by considering the difference in their influences, facilitating a clearer understanding of their contributions to the overall susceptibility assessment.

The second practical concern involves the accurate definition of hazard classes, pivotal due to its direct impact on risk management, decision-making, and overall infrastructure resilience. The study introduces a novel approach, using mode calculation to consolidate results from various reclassification methods. This strategic use of mode calculation ensures a reliable representation of hazard classes, addressing the limitations of individual methodologies.

The results underscore the importance of considering multiple models and methodologies to obtain a comprehensive perspective in decision-making processes. Importantly, the study highlights the use of both classical statistical methods, exemplified by WoE, and ML methods like GAM, showcasing the benefits of a diverse analytical approach in landslide risk assessment for linear infrastructure.

How to cite: Rani, R., Sciarra, M., Rodani, S., and Berti, M.: Toward Pragmatic Landslide Susceptibility Mapping for Railway Planning: A Comparative Analysis of Statistical and Machine Learning Methods - The Case Study of the Marche Region, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10842, https://doi.org/10.5194/egusphere-egu24-10842, 2024.

EGU24-11385 | Orals | NH3.10

Landslide inventory following the May 2023 Romagna hydrometeorological event (Northern Italian Apennines): the unavoidable requirement for laborious manual mapping 

Matteo Berti, Alessandro Corsini, Marco Pizziolo, Simonelli Tommaso, Giuseppe Ciccarese, Vincenzo Critelli, Nicola Dal Seno, Cecilia Fabbiani, Mauro Generali, Elena Ioriatti, Francesco Lelli, Marco Mulas, Rodolfo Rani, Francesco Ronchetti, Michele Scaroni, Melissa Tondo, and Alessandro Zuccarini

Accurate and timely landslide inventory is crucial, particularly after large-scale disasters like earthquakes or heavy rainfalls. While remote sensing enhances mapping speed, accuracy is vital to avoid missing or falsely identifying landslides. Effective mapping depends on factors like immediate access to high-quality imagery and skilled surveyors for ground truth definition.

In May 2023, Italy's Emilia-Romagna region experienced a severe hydrogeological emergency, which triggered thousands of landslides. The landslide inventory, crucial for emergency management, faced challenges due to the high number of landslides. Initial efforts using Copernicus Emergency Management Service and national resources faced limitations in completeness and reliability. Ultimately, the official inventory was based on a detailed manual mapping from high-resolution aerial imagery.

This work presents the magnitude of the triggering event, the types of the landslides occurred with respect to the geological constraints and discusses the potential benefits and limitations of automated landslide mapping methods in such scenarios. Specifically, more than 50.000 landslides have so far been mapped over an area of around 1000 km2, which range from debris slides/avalanches to debris flows and rock block slides. The impact on infrastructures was significant especially on the road network. With respect to automatic mapping, two distinct techniques have been tested: the conventional NDVI (Normalized Difference Vegetation Index) method and the more sophisticated U-Net algorithm using different remote sensing images ranging in resolution from 10 to 0.2 m.

Results show that time-consuming creation of an extensive ground truth datasets is essential in order to evaluate the accuracy of automatic landslide mapping based on images of different resolution and quality, so to determine whether these methods can offer efficient alternatives to manual mapping in large-scale emergency situations.

How to cite: Berti, M., Corsini, A., Pizziolo, M., Tommaso, S., Ciccarese, G., Critelli, V., Dal Seno, N., Fabbiani, C., Generali, M., Ioriatti, E., Lelli, F., Mulas, M., Rani, R., Ronchetti, F., Scaroni, M., Tondo, M., and Zuccarini, A.: Landslide inventory following the May 2023 Romagna hydrometeorological event (Northern Italian Apennines): the unavoidable requirement for laborious manual mapping, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11385, https://doi.org/10.5194/egusphere-egu24-11385, 2024.

EGU24-15157 | Posters on site | NH3.10

An expert semi-quantitative evaluation approach to measure the quality of landslide inventories 

Michele Santangelo, Francesca Ardizzone, Francesco Bucci, Mauro Cardinali, and Federica Fiorucci

The quality of a landslide inventory depends on its accuracy and the type and certainty of information shown on the map. Defining the accuracy of a landslide inventory is not straightforward, and there are no standards. Accuracy depends on the completeness of the map and the geographic and thematic correctness of the information displayed on the map.

In this study, an expert, semi-quantitative evaluation approach was developed to assess mapping errors and consequently determine the quality of a geomorphological historical landslide inventory map for a 2,000 km2 area in the Southern Italian Apennines (Daunia, Puglia region) prepared through aerial photo-interpretation.

Quality control aims to quantify parameters, even in terms of binary choices. Whenever involving expert estimates, the assessment was carried out through a reference grid to limit inconsistencies. Furthermore, the expert evaluations were carried out by a team of evaluators working collegially, and who had not previously worked simultaneously on the same areas.

The general approach involves a systematic evaluation within 5 sample areas covering a total of 202 km2 deemed a choice enabling the identification of areas that are sufficiently extensive (i.e., 10% of the total area and 20% of the total number of landslides) and adequately represent the diverse morphological and litho-structural characteristics of the study area. The assumption of representativeness of these areas forms the basis for extrapolating error data to the entire investigated area.

Geographic accuracy gauges the degree of correspondence between morphological and photographic evidence of landslides and their portrayal on the map. This correspondence was decomposed in terms of position, shape, and size and was evaluated, for each landslide portrayed in the 5 sites, at the declared scale of the final map (1:5,000). Each component was considered acceptable if at least 2/3 of the landslide was mapped correctly, and the overall accuracy satisfactory if at least two components were sufficient.

To assess the completeness of the inventory, the authors of the map were preliminarily asked to state the minimum size of landslides consistently mapped (ACM) in the inventory. Then, within the sample areas, the ratio between the number of landslides exceeding ACM and not represented in the map and the number of the landslides mapped expresses the degree of completeness of the inventory for the declared ACM.

To evaluate the thematic accuracy, a percentage score was assigned representing the proportion of landslides with specific thematic errors within the inventory, considering the correct classification (type and relative age) of each landslide represented in the map and compared to its photographic and morphological evidence.

Considering the absence of qualitative standards in the scientific literature for landslide inventory maps, and, consequently, the lack of evaluative standards for the accuracy of such cartographic products, this work can be considered an attempt to define a procedure to evaluate the informative content of landslide inventory maps.

How to cite: Santangelo, M., Ardizzone, F., Bucci, F., Cardinali, M., and Fiorucci, F.: An expert semi-quantitative evaluation approach to measure the quality of landslide inventories, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15157, https://doi.org/10.5194/egusphere-egu24-15157, 2024.

The analysis of surface topography by using LiDAR (Light Detection and Ranging) technology proved to be effective in landslide inventory mapping during the last two decades. Among the leading methods is the visual interpretation of LiDAR Digital Terrain Model (DTM) derivatives, applied for the mapping of different landslide types along diverse environments. Landslides are usually first being searched for by interpreting the hillshade map, while the landslide delineation is commonly followed by interpretation of the slope and the contour line maps. Several studies have also demonstrated the curvature map and the topographic roughness map to be effective tools in landslide detection and mapping. However, the landslide features topography can be poorly or even barely observable on the hillshade map, so a certain amount of landslides may be omitted from the final inventory if other derivatives are not visually inspected in detail. Hence, the thematic accuracy of a landslide inventory map depends on the geomorphic expression of landslides on the hillshade map, while the geographical accuracy depends on the adopted mapping procedure and the type of derivatives used for landslide delineation. Despite the overall usefulness of the visual interpretation of LiDAR DTM derivatives in landslide studies, the effectiveness of particular LiDAR DTM derivatives for the identification and precise delineation of individual landslide features has not been tested yet. 

This study quantitatively ranks the airborne LiDAR datasets derived from the 1-m DTM, used for the production of the geomorphological landslide inventory map of the Vinodol Valley (65 km2) in Croatia, according to their effectiveness for identification and precise delineation of particular landslide features. Landslides are mapped by one and the same expert, by interpreting a total of nine DTM derivatives. Six steps were carried out in this study: (i) the creation of the landslide dataset, which consisted of 394 small debris slides; (ii) the classification of landslides according to their geomorphic expression on the hillshade map, distinguishing four classes; (iii) the grading of the each DTM derivative for its effectiveness in precise delineation of particular landslide feature (i.e., crown, right flank, left flank, foot, toe), by assigning the grade of 0, 1, or 2 to each map; (iv) the statistical analysis of a total of 15,760 grades using the Friedman test; (v) the ranking of DTM derivatives in total of eight ranks based on the post-hoc analysis; and (vi) the classification of the DTM derivatives according to their effectiveness in mapping small landslides, considering the geomorphic expression of a landslide on the hillshade map. Finally, two categories of LiDAR DTM derivatives are proposed: (i) the main LiDAR DTM derivative, i.e. the most effective one for the precise delineation of particular landslide feature of particular geomorphic expression on the hillshade map; and (ii) the secondary LiDAR DTM derivative, which is still considered to be effective for the precise delineation of particular landslide feature of particular geomorphic expression on the hillshade map, but should be visually interpreted coupled with other secondary map(s), or with the main DTM derivative.

How to cite: Jagodnik, P.: Evaluating the potential of visual interpretation of airborne LiDAR datasets for the identification and mapping of small landslides, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15211, https://doi.org/10.5194/egusphere-egu24-15211, 2024.

EGU24-16687 | ECS | Orals | NH3.10 | Highlight

The Use of Wavelet Transforms and Deep learning algorithms to identify risk caused by landslides from multitemporal satellite images 

Aadityan Sridharan, Remya Ajai A.S, and Sundararaman Gopalan

Landslide risk assessment is ineludible for communities in mountainous regions of the world. Life and habitat loss plague these communities due to rapid mass movements. Cloud burst conditions and strong earthquake tremors trigger thousands of landslides that can run amuck in the terrain. One way to assess the risk is by field investigations. Vast areas cannot be covered on foot and other limitations such as a lack of accessible roads. The next viable alternative is aerial photography and unmanned aerial vehicles (UAV). The range and accuracy of the deployed drones and aircraft also limit this method of earth observation. Overcoming these limitations, optical satellite images give us information for a vast area and can observe the surface daily, which is only limited by cloud cover. These satellites have advanced to give highly accurate images with a resolution of 3m/pixel.

Remote sensing image processing techniques are used to generate automated inventory of landslides. Most of the current algorithms use segmentation algorithms to map the landslide polygons but do not include the urban settlements that are vulnerable to these mass movements. Planet lab images (3m/pixel) and Google earth images (0.2m/pixel) can be acquired at a daily temporal scale. These images can be further processed to identify the scars caused by the landslides and the outlines of urban settlements. Sridharan et al 2020 and 2022 have looked at discrete wavelet transforms (DWT) and deep learning algorithms for assessing the proximity of these landslide scars to urban settlements.

In this work, we extend these algorithms with high-resolution satellite images and identify the risk caused by landslides to communities. We collected images for landslides from various parts of the world that are observed to be active and added them as one class of training dataset. From the urban settlements that are in steep terrain, we collect a second set of images as another training class. More than 3000 images are used for training and validation with a 70:30 train-test split. The models are then tested by classifying a set of images that contain both classes to assess their potential in identifying landslide risk to communities. Classic Support vector machine is used as a classifier after extracting features by DWT. Traditional deep learning algorithms such as AlexNET and ResNET are trained and tested on the satellite images. We observe both DWT and Deep learning algorithms  have good overall accuracy in extracting features and validating them while there are some accuracy differences in identifying the risk in mixed images that have both the classes. The models are rated based on the confusion matrix and AUC-ROC. While various DWT give an accuracy in range of 90 – 96%, the deep learning models have a range of 95 – 98%.

How to cite: Sridharan, A., Ajai A.S, R., and Gopalan, S.: The Use of Wavelet Transforms and Deep learning algorithms to identify risk caused by landslides from multitemporal satellite images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16687, https://doi.org/10.5194/egusphere-egu24-16687, 2024.

EGU24-16693 | Posters on site | NH3.10

Impact of Terrain Visibility on Field-Based Landslide Inventories and the Role of r.survey 

Txomin Bornaetxea, Ivan Marchesini, Michele Santangelo, Alessandro Mondini, and Federica Fiorucci

Landslide inventories form the backbone of numerous natural hazard studies, providing essential data for assessing susceptibility, hazard, and risk. However, the accuracy and comprehensiveness of these inventories are influenced by various factors, including the visibility of the terrain from observation points. This study delves into the critical relationship between terrain visibility and the quality of field-based landslide inventories, with a focus on the implications for hazard analysis.
Traditionally, the visibility of a territory has been an overlooked factor, often assumed to be uniform across inventories. However, our research, leveraging the r.survey tool in conjunction with digital elevation models, reveals that the density of landslide information is strongly correlated with visibility. In areas of high visibility, field-based inventories exhibit a higher density of landslide reports, whereas regions with poor visibility are often underrepresented. Conversely, inventories derived from satellite imagery, while consistent, may also lack detailed information, particularly regarding smaller landslides in potentially visible zones, such as areas near roads.
The introduction of r.survey, a GRASS GIS plugin, has allowed for an effective visibility assessments. It not only calculates the visibility from various observation points but also incorporates the concept of solid angles to account for the size and orientation of observed objects. This innovative approach enables the development of a 'Size-specific Effective Surveyed Area' (SsESA), refining our understanding of the actual terrain covered during field surveys.
Furthermore, our ongoing empirical studies aim to establish a minimum solid angle threshold to determine the visibility of landslides, crucial for improving the accuracy of landslide inventories. Such insights are invaluable for statistical modeling, as biases in inventory data directly influence hazard assessments. By enhancing our understanding of visibility-related biases, we can refine inventory methodologies, ensuring more robust and accurate landslide susceptibility models.
In conclusion, terrain visibility significantly impacts the quality and comprehensiveness of field-based landslide inventories. Through the continued development and application of tools like r.survey, we can mitigate visibility-related biases, fostering more reliable hazard assessments and better-informed mitigation strategies.

How to cite: Bornaetxea, T., Marchesini, I., Santangelo, M., Mondini, A., and Fiorucci, F.: Impact of Terrain Visibility on Field-Based Landslide Inventories and the Role of r.survey, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16693, https://doi.org/10.5194/egusphere-egu24-16693, 2024.

EGU24-17066 | Orals | NH3.10 | Highlight

Manual Landslide Maps are Surprisingly Inaccurate but Automated Detection Could Help 

David Milledge, Dino Bellugi, and Alexander Densmore

Efforts to understand the controls on landslides rely heavily on manually mapped landslide inventories, but these are costly and time-consuming to collect, and their reproducibility is not typically well constrained. To test the performance of manual mapping we compare two or more manually mapped inventories of landslides triggered by five recent earthquakes: Kashmir in 2005, Aysén in 2007, Wenchuan in 2008, Haiti in 2010, and Gorkha in 2015. We find surprisingly poor agreement between these maps (at worst 8 % overlap and at best 30 %). This has implications both for how future models and/or classifiers are tested and for the interpretations that are based on these inventories. We then test the ability of a new automated landslide detection index (ALDI) to recover landslide locations. In more than 50% of cases, ALDI more skilfully reproduces landslide locations from one inventory (treated as the ground truth) than a second inventory for the same site based on ROC curve analysis. Finally we examine the spatial pattern of landslides identified in the different maps and the patterns of their agreement and disagreement to show that: 1) much of the disagreement appears to be due to georeferencing rather than landslide identification; and 2) the ALDI map, which is quick and easy to produce, can be used to identify georeferencing errors and thus post-process and improve manual maps.

How to cite: Milledge, D., Bellugi, D., and Densmore, A.: Manual Landslide Maps are Surprisingly Inaccurate but Automated Detection Could Help, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17066, https://doi.org/10.5194/egusphere-egu24-17066, 2024.

EGU24-17519 | ECS | Orals | NH3.10 | Highlight

Spatiotemporal Modelling of Landslide Susceptibility Using Satellite Rainfall and Soil Moisture Products through Machine Learning Techniques 

Yaser Peiro, Luca Ciabatta, Evelina Volpe, and Elisabetta Cattoni

To mitigate the risk of landslides, building a model that can provide information on the spatial and temporal probabilities of landslides is essential yet challenging. Landslides are influenced by environmental factors, such as topography, geology, and mechanical properties of the soil, as well as triggering events like rainfall and earthquakes. This research leverages Random Forest algorithm for classification by creating multiple decision trees. Each tree is trained on a distinct, randomly selected subset of the dataset. The dataset includes specific static variables for each location, such as lithology, slope angle, aspect, curvature, and land use. Additionally, the study considers two dynamic variables for each location: high-resolution soil moisture data obtained from satellites to examine the impact of soil water content, and rainfall data.
By utilizing a unique rainfall-induced landslide database, which includes the location and time of landslide occurrences in the study area. The algorithm extracts the corresponding rainfall and soil moisture values preceding each landslide event and trains the model by adjusting both static and dynamic variables. The rainfall data is analyzed on two different time scales: short-term cumulative rainfall (1-72 hours before a landslide event) and medium-term cumulative rainfall (5-15 days before a landslide event). The outcomes are individual trees that determine the final class (landslide or non-landslide location) for each pixel based on the majority vote. The model's outputs, out-of-bag errors, and partial dependence plots provide insights into how each parameter influences the model's landslides predictions, and help to evaluate the impact of rainfall and soil saturation conditions on landslides occurrence both in space and in time.

How to cite: Peiro, Y., Ciabatta, L., Volpe, E., and Cattoni, E.: Spatiotemporal Modelling of Landslide Susceptibility Using Satellite Rainfall and Soil Moisture Products through Machine Learning Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17519, https://doi.org/10.5194/egusphere-egu24-17519, 2024.

EGU24-17851 | ECS | Orals | NH3.10

Statistical and geospatial approaches to evaluate the quality of earthquake-triggered landslide inventories 

Badal Pokharel, Massimiliano Alvioli, and Samsung Lim

Evaluating landslide inventories is crucial and the first step in assessing the extent of landslide event damage. Despite the several studies in landslide inventory preparation and assessment, there is a lack of standardised criteria for measuring their quality and completeness. This study aims to introduce an integrated approach for analysing different event inventories prepared by different geomorphologists. We considered five landslide inventories prepared by various authors following the 2015 Gorkha earthquake in Nepal [1-5]. We prepared susceptibility maps using multiple realisations of logistic regression, with slope units of the areas as a spatial basic unit for the analysis [6]. The goal was to analyse their differences or similarities and comprehend the influence of using them to prepare landslide susceptibility maps [7].

The key questions we explored were: How can the quality and reliability of landslide inventories be evaluated? And what are the similarities or differences in the landslide susceptibility maps generated using inventories from different research teams for the same event? To this end, we utilised three evaluation criteria: (i) an error index to check the discrepancies between inventories, (ii) statistical analysis to examine the inconsistencies in predisposing factors and susceptibility map performance, (iii) geospatial analysis to evaluate differences among inventories and their corresponding.

The study highlighted differences in landslide inventories and attributed them to differences in data collection methods and subjective judgments. It emphasised the need to address subjectivity for more accurate and consistent landslide mapping. The results from statistical analysis showed substantial differences in the areal extent and overlapping degree between inventories. The geospatial analysis, such as hot spots and cluster/outlier analysis, highlighted the distinctive differences in spatial patterns of landslide susceptibility maps corresponding to different inventories. The suggested geospatial methods offer investigators a viewpoint for quantitatively analysing earthquake-triggered landslide inventories and related susceptibility maps.

References

[1] Zhang et al., Journal of Mountain Science (2016). https://doi.org/10.1007/s11629-016-4017-0

[2] Gnyawali et al., Springer International Publishing (2017). https://doi.org/10.1007/978-3-319-53485-5_10

[3] Roback et al., US Geological Survey Data Release (2017). https://doi.org/10.5066/F7DZ06F9,   

[4] Kargel et al., Science (2016). https://doi.org/10.1126/science.aac8353

[5] Pokharel and Thapa, Journal of Nepal Geological Society (2019). https://doi.org/10.3126/jngs.v59i0.24992

[6] Alvioli et al., Journal of Maps (2022). https://doi.org/10.1080/17445647.2022.2052768

[7] Pokharel et al., Scientific Reports (2021). https://doi.org/10.1038/s41598-021-00780-y

 

How to cite: Pokharel, B., Alvioli, M., and Lim, S.: Statistical and geospatial approaches to evaluate the quality of earthquake-triggered landslide inventories, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17851, https://doi.org/10.5194/egusphere-egu24-17851, 2024.

EGU24-18374 | Posters on site | NH3.10 | Highlight

Landslide Identification in UAV Images Through Recognition of Landslide Boundaries and Ground Surface Cracks 

Zhan Cheng, michel Jaboyedoff, and wenping gong

Landslides represent one of the most pervasive and detrimental geohazards worldwide. Precise detection of potential landslides is imperative for effective landslide risk management. While the utilization of Unmanned Aerial Vehicles (UAVs) has seen a recent surge in landslide evaluation, the majority of contemporary UAV image-based identifications predominantly depend on visual inspections. This study introduces a sophisticated image analysis framework tailored for landslide identification in UAV-captured imagery. This framework not only discerns landslide boundaries but also detects ground surface fractures. Employing an object-oriented image analysis approach, potential landslide boundaries within UAV images are identified. Concurrently, an automated model, refined through a deep transfer learning methodology, recognizes ground surface fractures in these images. Subsequent to this, a fusion of identified landslide boundaries and ground fractures is achieved through Boolean operations, facilitating nuanced landslide detection within UAV imagery. To underscore the proficiency of our proposed framework, we selected the Heifangtai Terrace in Gansu, China, as a case study. The resultant identifications are cross-referenced with field survey data to confirm the validity.

How to cite: Cheng, Z., Jaboyedoff, M., and gong, W.: Landslide Identification in UAV Images Through Recognition of Landslide Boundaries and Ground Surface Cracks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18374, https://doi.org/10.5194/egusphere-egu24-18374, 2024.

EGU24-18897 | ECS | Posters on site | NH3.10

Comparative Assessment of Landslide Susceptibility Maps in the Alborz Mountain range by Tehran: Methodologies and Challenges 

Thomas Kreuzer, Christian Büdel, Peter Priesmeier, Alexander Fekete, and Birgit Terhorst

Tehran, the bustling capital of Iran, is internationally recognized as one of the urban areas most susceptible to natural hazards. Among the various threats, landslides constitute a significant danger to infrastructure, buildings and the inhabitants. The general exposure to hazards initiated the creation of multiple landslide susceptibility maps, especially for the mountainous terrain north of the city. These maps are pivotal for urban planning and disaster mitigation efforts.

Despite the high relevance of hazard and susceptibility maps in the study area, a systematic comparison of these susceptibility maps has not been undertaken so far, mainly due to the lack of accessible data. Primarily available maps exist in the form of published images, precluding detailed, pixel-level analyses that could reveal insights into their relative accuracy and effectiveness.

Addressing the data accessibility challenge, the current study introduces an innovative approach for extracting quantitative information from all published maps in the area of interest. The applied method leverages a modified k-means clustering algorithm, traditionally limited by its sensitivity to initial cluster centres and less suited for colour quantization. However, our proposed approach showcases reliability when applied to thematic maps characterized by monochromatic colour schemes.

Our research undertook a detailed comparison of 14 landslide susceptibility maps, all intersecting the northern area of Tehran, and encompassing various scales. The comparative analysis proved a significant discordance between the published maps. It can be observed that map performance is predominantly influenced by factors such as data resolution, methodological approaches, and parameter selection, rather than by the sheer number of parameters. Through this comparative assessment, we have identified critical parameters that greatly influence landslide susceptibility predictions.

A striking conclusion of the present study is the absence of a singularly superior methodology amongst the numerous scientific approaches assessed. Although all methods are established and reputable within the scientific community, our results demonstrate that they yield clear discrepancies when applied to the context of Tehran's landscape. In the context of landslide hazard evaluation, susceptibility mapping constitutes the foundational element within our Integrated Disaster Risk Management (IDRM) framework. Consequently, our findings highlight significant challenges concerning the practical implementation of these maps.

In conclusion, the present study points to complex problems of creating accurate landslide susceptibility maps and identified significant discrepancies that can arise from methodological variations. These findings demonstrate the urgent need for further research to deepen our understanding of landslide susceptibility mapping. It is mandatory that future studies continue to refine these techniques to enhance their predictive power, reduce uncertainties, and, ultimately, support the resilience of urban areas and societies. This is one of the main tasks in the project: “Geovisual analysis, evaluation and monitoring of geohazards and their related landforms” as part of the BMBF INCREASE research program (Förder-Nr. 01DK20101H).

How to cite: Kreuzer, T., Büdel, C., Priesmeier, P., Fekete, A., and Terhorst, B.: Comparative Assessment of Landslide Susceptibility Maps in the Alborz Mountain range by Tehran: Methodologies and Challenges, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18897, https://doi.org/10.5194/egusphere-egu24-18897, 2024.

EGU24-18951 | ECS | Orals | NH3.10 | Highlight

Adopting FAIR data management practices in mountain hazard research: Strategies for ensuring data quality for landslide susceptibility modeling 

Laura Waltersdorfer, Andrea Siposova, Matthias Schlögl, and Rudolf Mayer

Mountainous regions such as the Austrian Alps face a constant threat of natural hazards. Over time, this persistent danger has prompted a transition from heuristic hazard management strategies towards a more quantified risk culture. Since quantitative risk assessment heavily relies on understanding the occurrence frequency of the hazard processes under consideration, knowledge about past events and their characteristics becomes pivotal, thereby shaping the effectiveness and broader applicability of methodological workflows employed in this context.

We present challenges, and insights gleaned from the research project “gAia”, focusing on a data-driven susceptibility assessment for shallow landslides in Austria. The identified challenges mainly revolve around the quality of landslide inventories, which is influenced by factors like underreporting, inconsistent documentation, and lack of standardized data management practices. We thus recommend adopting FAIR (Findability, Accessibility, Interoperability, Reusability) principles and developing Data Management Plans to address these issues, and propose a general data management workflow:

  • Identify data sources and contents: Collect information about data sources and characteristics in a (machine-readable) DMP to obtain an overview of all data sources and most important characteristics (e.g. format, size, license, context, bias limitations). This should support the contextualization and ability to reuse this data.
  • Define processing activities: Explicitly define processing workflows to enhance reproducibility and transparency, using established standards such as Business Process Management (BPMN) or semantic web technologies to represent complex processes formally and make them more comparable and accessible to users.
  • Define (meta)-data and process activities trace templates: Provide metadata templates for datasets and trace processing activities to improve interoperability and reusability. Define domain-specific vocabularies and use concepts such as datasheets, model cards, ML experiment tracking and model registry tools as well as task orchestration platforms for data engineering pipelines to make results more traceable and reviewable. 
  • Monitoring processes for natural hazard event data: Implement processes to ensure adherence to quality metrics, with results published in machine-readable formats.

We detail the implementation of these steps using established concepts of traceability and provenance, and encourage to implement workflow tasks using common open source programming languages. In addition, we endorse the use of Git for version control and GitLab/GitHub as tools for facilitating collaboration and structuring technical tasks.

The benefits of the proposed data management strategies for enhancing quality and reliability of data as well as increasing overall transparency of processes are showcased in the gAia project. The project workflow, represented as a P-Plan, demonstrates the application of these strategies in different phases. Specifically, the importance of proper data management and adherence to FAIR principles for data-driven research and practical usability is highlighted using landslide inventories as a core example.

In summary, we provide insights into the complexities of geospatial data management in mountain hazard research and offer practical solutions to enhance the integrity and reliability of data for supporting effective risk assessment and disaster risk reduction.

gAia is funded through the KIRAS Security Research Program for Cooperative Research and Innovation Projects by the Austrian Research Promotion Agency (FFG) and the Federal Ministry of Finance, under grant agreement FO99988636910.

 

How to cite: Waltersdorfer, L., Siposova, A., Schlögl, M., and Mayer, R.: Adopting FAIR data management practices in mountain hazard research: Strategies for ensuring data quality for landslide susceptibility modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18951, https://doi.org/10.5194/egusphere-egu24-18951, 2024.

EGU24-19268 | ECS | Orals | NH3.10

Optimization of ML-based regression models applying metaheuristic algorithms to determine the landslide susceptibility 

Rajendran Shobha Ajin, Samuele Segoni, and Riccardo Fanti

A landslide susceptibility modelling has been carried out by applying two machine learning regression algorithms (SVR and CatBoost), and later two population-based optimization algorithms (metaheuristics) such as PSO and GWO were integrated to assess whether the integration improved the performance of the two regression algorithms. A total of 18 predisposing factors were selected for the study. After the multicollinearity assessment and feature selection applying the information gain (IG) method, four predisposing factors (three factors with collinearity issues and one irrelevant factor) were excluded. Hence, 14 predisposing factors were selected for the modelling. The landslide susceptibility maps were thus created by applying the CatBoost, CatBoost-PSO, CatBoost-GWO, SVR, SVR-PSO, and SVR-GWO models. The validation employing different techniques (MAE, MSE, RMSE, and R2) confirmed that the CatBoost model (MAE = 0.065 and 0.071, MSE = 0.027 and 0.032, RMSE = 0.165 and 0.180, and R2 = 0.890 and 0.869) is better than the SVR model (MAE = 0.179 and 0.181, MSE = 0.063 and 0.063, RMSE = 0.251 and 0.252, and R2 = 0.746 and 0.745). The integration of optimization algorithms improved the performance of these two regression models, and the GWO has the best performance when compared to the PSO algorithm. Also, CatBoost-GWO (AUC = 0.910) has the best performance, followed by CatBoost-PSO (AUC = 0.909), CatBoost (AUC = 0.899), SVR-GWO (AUC = 0.868), SVR-PSO (AUC = 0.858), and SVR (AUC = 0.840). The Friedman and Wilcoxon-signed rank tests confirmed that the models are significant. The feature importance assessment using the CatBoost confirmed elevation, slope, geomorphology, road, and soil bulk density as the top five important predisposing factors.

How to cite: Ajin, R. S., Segoni, S., and Fanti, R.: Optimization of ML-based regression models applying metaheuristic algorithms to determine the landslide susceptibility, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19268, https://doi.org/10.5194/egusphere-egu24-19268, 2024.

EGU24-19369 | ECS | Posters virtual | NH3.10

U-Net Deep Learning for Geospatial Landslide Inventory Mapping in Genting Highlands, Malaysia 

Siti Nuha Amisyah Sappe, Rabieahtul Abu Bakar, Khamarrul Azahari Razak, Zakaria Mohamad, Abdul Aziz Ab Rahman, Mohamad Abd Manap, and Tajul Anuar Jamaluddin

Genting Highland is predominantly the mode of landslides, especially prevalent during and post monsoon seasons. Globally, landslides encapsulates the widespread hydro-geological disaster elucidating their causes, risks, and impacts on infrastructure and human life. Attributed  from Malaysia natural undulated terrain, torrential rainfall, expanding urbanization contributed to the increasing landslide occurrences. Laying the groundwork for a more efficient landslide mapping over a vast area underscores the imperative need of Artificial Intelligence (AI). Landslide mapping to-date transitions from conventional delineation to employing U-Net, a deep learning architecture, to automate and expedite the process of identifying landslides from remote sensing data towards the emphasizes on rapid landslide mapping. This study is to create detailed landslide inventory maps by mapping new and old landslide footprint for Genting Highlands, with U-Net Deep Learning as a pivotal tool. Entail a systematic process, to identify landslide structures according to predefined categories, using high-resolution satellite imagery to train the U-Net model, and ultimately producing validated landslide maps for the region. The stages for integrating U-Net Deep Learning with geospatial analysis include data acquisition, pre-processing, DL training, analysis, and the final output of landslide mapping. Spot-7 imagery as input to the U-Net and  landslide semantic shapes that consist of crown, transportation body and foot, whereby pixel by pixel are classified when introduced. The anticipated results, showcasing the validity and precision of the model's landslide automated delineation on other imageries. Verification involves the comparison between U-Net's projected landslides to a manually delineated landslide inventory for Genting Highlands. Hence, this research provide precise and efficient tools for identifying and forecasting landslides in landslide-prone areas. 

How to cite: Sappe, S. N. A., Abu Bakar, R., Razak, K. A., Mohamad, Z., Ab Rahman, A. A., Abd Manap, M., and Jamaluddin, T. A.: U-Net Deep Learning for Geospatial Landslide Inventory Mapping in Genting Highlands, Malaysia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19369, https://doi.org/10.5194/egusphere-egu24-19369, 2024.

EGU24-2027 | ECS | Orals | NH3.13 | Highlight

Screening fungal species for soil-mycelia systems 

Alireza Fathollahi, Grainne El Mountassir, and Qi Zhang

Landslides induced by heavy rainfall and water infiltration into granular soils, pose a substantial challenge worldwide. As water infiltrates the soil, the degree of saturation increases and soil suction reduces with an associated reduction in soil shear strength, which can trigger the instability of these slopes. Landslides can have severe consequences, with 4,862 individual incidents resulting in more than 55,000 fatalities between 2004 and 2016 (Froude and Petley, 2018). Economically, landslides generate substantial financial burdens, for example in Europe, as much as 4.7 billion Euros each year (Haque et al., 2016) due to the cost of reconstruction and recovery efforts. Environmental consequences include the destruction of ecosystems, alteration of landscapes, and potential long-term impacts on soil quality.

Traditional strategies to mitigate slope failures rely on localised engineering interventions, including for example soil nailing, ground anchors, retaining walls, soil grouting, geotextiles, and drainage systems. Moreover, these solutions can have a high carbon footprint due to the reliance on the use of materials like cement and steel. Balancing the need for effective landslide prevention with minimising environmental impact and cost requires innovative, sustainable approaches. This research explores the potential of using filamentous fungi as a nature-based solution to mitigate landslides.

Filamentous fungi, through their unique structure composed of hyphae, create a vast network known as the mycelium. This mycelial network extends through the soil and binds particles together, enhancing soil stability (El Mountassir et al., 2018). Moreover, filamentous fungi also secrete hydrophobins, proteins that turn the surface they inhabit more hydrophobic (Salifu & El Mountassir, 2021). This induced hydrophobicity can delay and reduce soil water infiltration (Salifu et al., 2022) which could be beneficial in the context of slopes where failures are triggered by heavy rainfall and water infiltration.

This study explores various Basidiomycota fungal species, evaluating their potential to grow in diverse soil types under varying conditions, ranging from sterile to non-sterile environments. Growth patterns were monitored using time-lapse photography and image analysis techniques to determine the extent of growth over time within different soil compositions. Water Droplet Penetration Tests were conducted on specimens to evaluate how each fungal species influenced soil water repellency. Moreover, the impact of fungal growth on soil aggregation was evaluated using Soil-Aggregate Stability Tests. By correlating the growth patterns, water repellency, and soil aggregation outcomes, the most promising fungal species capable of enhancing soil stability and mitigating landslide risks in specific soil environments were identified.

References:

El Mountassir, G., et al. 2018. Applications of microbial processes in geotechnical engineering. Adv. Appl. Microbiol. doi: 10.1016/BS.AAMBS.2018.05.001

Froude, M. J. and Petley, D. N.: Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.

Haque, U., et al. 2016. Fatal Landslides in Europe, Landslides, doi: 10.1007/s10346-016-0689-3.

Salifu, E., El Mountassir, G. 2021. Fungal-induced water repellency in sand. Géotechnique. 71, 7. https://doi.org/10.1680/jgeot.19.P.341

Salifu, E., et al. 2022. Hydraulic behaviour of fungal treated sand, Geomechanics for Energy and the Environment, Volume 30.

How to cite: Fathollahi, A., El Mountassir, G., and Zhang, Q.: Screening fungal species for soil-mycelia systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2027, https://doi.org/10.5194/egusphere-egu24-2027, 2024.

EGU24-3627 | Posters on site | NH3.13

Utilizing new technologies and nature-based solutions for sustainable urban riparian area management 

George Zaimes, Valasia Iakovoglou, Paschalis Koutalakis, and Georgios Gkiatas

Citizens in urban areas face many pressures and the goal should be to develop plans and implement actions to improve their living environment by providing clean air, clean water but also recreation and relaxation areas. Urban riparian areas can support such services for its citizens; thus, efforts should be made to either establish new ones or conserve the already existing ones. The aim of this study was to utilize new technologies that should enhance the assessment of the current conditions of urban riparian areas. Such datasets should help land and water managers develop better plans to mitigate the anthropogenic pressures that these areas face. In addition, these datasets can showcase the main anthropogenic pressures of the study area and allow to recommend proper nature-based solutions and their optimal placement. The case study was the Agia Varvara Park of Drama city in Greece. The Park is a unique riparian area with litter one of the main problems in its water bodies. The innovative tools used were unmanned aerial vehicles with high resolution regular and thermal cameras, unmanned underwater vehicles. In addition, a GPS tracker, was also used to record the potential movement route of litter and a sonar device to develop cross-sections of Agia Varvara’s stream. The produced orthomosaics, digital surface models, cross-section and litter route showcased that litter traps could be a suitable nature-based solution. In addition, the optimal location for litter trap placement was determined. This simple measure could sustainably minimize litter pollution in the Park.

How to cite: Zaimes, G., Iakovoglou, V., Koutalakis, P., and Gkiatas, G.: Utilizing new technologies and nature-based solutions for sustainable urban riparian area management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3627, https://doi.org/10.5194/egusphere-egu24-3627, 2024.

EGU24-3879 | ECS | Posters on site | NH3.13

Literature review and empirical analysis of bend scour formulas. 

Natacha Fructus, Solange Leblois, Guillaume Piton, Alain Recking, and André Evette

Bank erosion is essential for the proper functioning of rivers and the preservation of their freedom space. However, when the assets are at risk, it is sometimes necessary to implement protective structures along the banks. Unlike civil engineering, soil and water bioengineering techniques offer the advantage of addressing various ecosystem services, thereby contributing to environmental preservation while protecting against erosion. Despite these advantages, the development of such techniques is hampered by a lack of understanding regarding their failure modes. Scour was identify as a factor of failure for 45% of cases of mechanical destruction on bioengineering structure. This is why accurate prediction of scour depths is a predominant factor for a successful design. In order to reduce the scope of the study, this work focuses on bend scour, where stresses on the outer bank are often significant. A review of existing literature was conducted to gain a deeper understanding of available methods for estimating this depth. Twelve empirical formulas for bend scour predication were identified and their domain of validity gathered. All these formulas were developed between 1930 and 2006 and some links between them were highlighted. Depending on the country in which they were developed, the news ones were often inspired from the old ones and used a part of the same dataset. Fifty natural bend were visited on ten lowland or piedmont rivers. Topographical and granulometric measurements were performed to compare the scour depths derived from literature formulas with field values. Some formulas appear to stand out due to their general tendency to overestimate depths or their precision under specific application conditions. Despite the limitations of the study, these results provide an initial overview of the trends for each formula, making it easier to understand the most appropriate conditions of application for each of them.

How to cite: Fructus, N., Leblois, S., Piton, G., Recking, A., and Evette, A.: Literature review and empirical analysis of bend scour formulas., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3879, https://doi.org/10.5194/egusphere-egu24-3879, 2024.

Our motivation is to explain how severe bank slides, such as those following natural disasters, can be sustainably reintegrated into the river ecosystem in a modern, contemporary manner through the application of NbS and combined techniques. Our purpose is to explain the needs of an integrated engineering approach to find out the causes of streambank slides before works start. We point out the workflow of NbS reconstruction process by determining an efficient analysing stage, a construction stage and a monitoring stage. We show three realized examples of steep bank reintegration situated in high flow regime. Our conclusions show that reintegration into the river landscape of violent bank slides near residential areas and infrastructure with NbS techniques is feasible. The prerequisites, however, are a sufficient root cause analysis by an integrated engineering approach, and good training and experience of the hired construction companies during construction stage. In addition, clients need to throw out some of their old ideas of exclusively mineral and similar attachment techniques. This presentation serves as a demonstration of the potential of sustainable NbS steep bank revegetation for infrastructure protection, based on geotechnical analysis using examples realized in France between 1999 and 2022.

How to cite: Peklo, K.: Nature based Solutions and combined techniques in the immediate vicinity of infrastructure and residential areas -  Case studies of steep bank stabilizations in the Garonne water catchment area in France realized between 1999 and 2022, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5718, https://doi.org/10.5194/egusphere-egu24-5718, 2024.

EGU24-7645 | ECS | Orals | NH3.13

Quantifying the resistance of protective mixed-forest against natural hazards in the Pyrenees 

Paula Gómez García, Jaime Madrigal-González, Francisco Arriaga, José Carlos Robredo, Ernesto Tejedor, and Juan Antonio Ballesteros-Cánovas

In mountain areas, extreme weather events can trigger hydrogeomorphological processes (HGEs), such as torrential floods, snow avalanches, landslides or rockfalls. To mitigate the risks associated with these natural hazards, ecosystem services based risk reduction (Eco-DRR) approaches can be applied. In an Eco-DRR scheme, vegetation plays an important role, not only in reducing the probability of occurrence, but also in minimizing its impact providing natural barriers that limit the propagation of flow and energy. Understanding how the vegetation resists such events within a given forest stand is relevant for designing better forestry practices and maximizing the protective role of the forest. Here we focus on quantifying the mechanical resistance of trees subjected to HGE processes considering two potential failure modes, namely tree overturning and stem breakage. To this end, we perform pulling tests on 53 trees of two main species (Abies alba Mill. and Fagus sylvatica L.) growing on two plots (Gourzy forest – France and Arañones Forest – Spain) in the Pyrenees. We also collected structural and neighborhood characteristics of trees and forest stands and carried out dendroecological studies on selected trees. Both areas have a similar soil type (sandy soil - dolomites and calcarenites) composed of limestone, marl, clay and sandstone, and are affected by recurrent snow avalanches and rockfalls. Using a structural equation model (SEM) statistical framework, we test whether mechanical capacity is determined by either functional traits (i.e. species, tree growth, diameter and height) or structural traits (i.e. tree density, tree structure and slenderness). Our results suggest that forest competition modifies the mechanical capacity of trees through two pathways involving both functional and structural traits. Overall, functional traits condition the individual stiffness parameter of trees, whereas structural traits are mostly related to changes in elastic modulus. These results shed light on the behavior and plasticity of both species in avalanche and rockfall events, revealing better adaptations depending on certain allometric and structural traits, and providing relevant information for foresight on management strategies of forests with a protective role against natural hazards in the face of climate change.

How to cite: Gómez García, P., Madrigal-González, J., Arriaga, F., Robredo, J. C., Tejedor, E., and Ballesteros-Cánovas, J. A.: Quantifying the resistance of protective mixed-forest against natural hazards in the Pyrenees, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7645, https://doi.org/10.5194/egusphere-egu24-7645, 2024.

EGU24-7680 | ECS | Orals | NH3.13

Which willows for Soil and Water Bioengineering structures on high-elevation streambank? Ex situ study of cutting capacity of three shrub species 

Juliette Rousset, Sarah Menoli, Adeline François, and André Evette

Soil and Water Bioengineering techniques are a sustainable alternative to civil engineering to prevent erosion processes that threaten streambank stability. These techniques are still poorly developed and documented in subalpine streams, where climatic and hydrological conditions are particularly challenging. It is well known that the success and integration of a SWBE technique is best achieved when it is possible to use indigenous plants and plant material. At the subalpine belt, shrub and tree willows are among the dominant woody species on streambanks. Even if a few past studies claimed that they could play a full role in stabilising the banks of high-elevation streams, their biotechnical characteristics are nearly unknown. The unique information available comes from empirical and not detailed results showing a low resprouting rate of cuttings. Still, no data or information on these capacities are known in the subalpine environment. We conducted an in situ experimental study to assess the cutting capacity of willow species at high elevations to improve SWBE on these streambanks.

Three species of subalpine shrub willow were chosen: S.caesia, S.foetida and S.hastata. These willows have no protected status in the French Alps, making them ideal for soil and water bioengineering. S.purpurea, known for its high resprouting ability in foothill streambanks, was used as a control species. The cuttings were placed in culture chambers for 4 months under controlled conditions of light, humidity, and temperature. We tested the effect of a growth hormone (indole-3-butyric acid), with the assumption that it would stimulate willow growth. 25 cuttings from each species were treated with the hormone while another 25 were not treated. At the end, we measured root diameter, primary root number, root biomass, cumulated stem length, stem number and, stem and leaves biomass. 

The recovery rate was high for all four species (>95%). No significant differences were found between the hormonal treatments. For each trait measured, there were significant differences for at least one of the species, reflecting significant differences in root and aerial morphology between species. S.hastata was distinguished by its very high biomass and S. purpurea by its very long structure. The results revealed significant differences between these species, in terms of morphology, resource allocation and therefore properties for soil and water bioengineering structures. All of the four species appeared to be suitable in SWBE structures. These findings have important implications for the effective installation of cuttings in SWBE structures in subalpine environments.

How to cite: Rousset, J., Menoli, S., François, A., and Evette, A.: Which willows for Soil and Water Bioengineering structures on high-elevation streambank? Ex situ study of cutting capacity of three shrub species, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7680, https://doi.org/10.5194/egusphere-egu24-7680, 2024.

EGU24-7925 | ECS | Orals | NH3.13

Willows root distribution on riverbanks through a descriptive approach 

Solange Leblois, Guillaume Piton, and André Evette

The use of Nature-based solutions for riverbank stabilization purposes in Western Europe is mainly based on willows implemented on engineered structures stabilizing riverbanks as they grow. Willows are ubiquitous and pioneer species capable of survival in submerged conditions when drowned a part of the year, therefore particularly well suited for soil and water bioengineering techniques. In the context of bend scour or of bed incision, bank toe bellow the line of brush growth is a weak point to control. This weaker zone presenting a low vegetation surface cover is in fact strongly subject to erosion leading to undermining and bank failure. This situation raised up the question: what is the effect on the soil stability of willows root reinforcement in this weak zone, knowing that their root system is allegdly able to develop in this part time drowned soil?  In order to understand the stabilizing function of these species bellow the brush line, willows root system implemented on riverbanks from two different alpine watersheds in France have been surveyed in autumn 2023. The root development is studied in regard of the ground water level and soil texture. Nine soil profiles with willows root systems are described in the study and the respective root area ratios have been estimated manually. Soil profiles were dug up to the last visible root and never exceeded 80 cm, corresponding to the ground water level of the low flows that were running during the measurements. The study describe three different species root system aged from 2 to 20 years: Salix purpurea, S. daphnoides and S. eleagnos.

How to cite: Leblois, S., Piton, G., and Evette, A.: Willows root distribution on riverbanks through a descriptive approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7925, https://doi.org/10.5194/egusphere-egu24-7925, 2024.

EGU24-8218 | ECS | Posters on site | NH3.13

Life Cycle Assessment of soil and water bioengineering structures 

Magdalena von der Thannen and Hans Peter Rauch

Nowadays there is a high demand on engineering solutions considering not only technical aspects but also ecological and aesthetic values. Soil and water bioengineering (SWB) is a construction technique that uses biological components for hydraulic and civil engineering solutions. In general it pursues the same objectives as conventional civil engineering structures. In this context SWB techniques are often used as standalone solutions or in combination with conventional engineering structures.

Currently, existing assessment methods for SWB structures are evaluating technical and economic aspects. In a modern engineering approach, additionally, environmental impacts should be considered. Therefore, the Institute of Soil Bioengineering and Landscape Construction aims at developing an Environmental Life Cycle Assessment (LCA) model for this special field of soil bioengineering and river restoration. Different studies were carried out to assess the carbon footprint of various SWB structures mainly with the popular impact category Global Warming Potential (GWP). The life cycle itself can be divided into four phases: the product phase, the construction phase, the use phase and the end of life phase. For the presented case studies the system boundary is defined as cradle to gate (until the construction is finished), except for one case study where the use phase is analysed (including the maintenance and conservation work as well as the potential positive effects resulting from the living plants).

The results show that SWB construction sites are able to perform better in terms of carbon emissions than conventional construction sites, but they even cause negative effects on the environment. Apart from that, SWB structures are able to compensate emissions from construction by absorbing carbon through growing vegetation in the use stage. Therefore, a holistic approach starting in the planning stage can help to optimize processes throughout the life cycle and to minimize the environmental burdens. The case studies show that the application of an LCA model is not only important in terms of engineering effects but also provides transparency for the responsible planners and stakeholders, by pointing out the total consumption of resources in all phases and components.

How to cite: von der Thannen, M. and Rauch, H. P.: Life Cycle Assessment of soil and water bioengineering structures, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8218, https://doi.org/10.5194/egusphere-egu24-8218, 2024.

Soletanche Bachy has developed and patented an innovative soil reinforcement method based on a natural biological process leading to the formation of calcite in situ, called Biocalcis®. This process is adapted for being applied in different soils and hydraulic conditions, including on hydraulic structures where continuous hydraulic flow is encountered. The mitigation of internal erosion is necessary to prevent damages on the infrastructure or the slope due to mechanical failures. Biocalcis treatment presents the advantage not to significantly change the overall permeability of the treated area and therefore avoid the risk of material sealing and waterproofing. Results obtained at sample scale during the frame of BOREAL project will be presented, during which four different erosion test devices have been used: Contact Erosion Test, Hole Erosion Test, Jet Erosion Test and Suffusion test. The resistance of untreated and treated soils will be detailed. The treated soils were obtained after injection of biocalcification in laboratory columns or inside large physical models using real site materials. All the test results indicate a strong increase of erosion resistance from a small percentage of added calcite (~2- 4%) that is easily achievable on real sites with the process. The presentation will also show examples of applications on real sites using different implementation methods. Environmental and durability aspects will also be addressed.

How to cite: Esnault Filet, A. and Sapin, L.: Biocalcification for slope reinforcement against internal erosion : results of experimental laboratory works and presentation of real case applications., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10728, https://doi.org/10.5194/egusphere-egu24-10728, 2024.

EGU24-15564 | Posters on site | NH3.13 | Highlight

Enhancing fascine techniques for slopes erosion control: A comprehensive technical guide 

Marie Didier, André Evette, Emma Schmitt, Solange Leblois, Delphine Jaymond, Jean-Baptiste Evette, Eleonore Mira, Pierre Raymond, Pierre-Andre Frossard, and Anne Vivier

Fascines are Soil and Water Bioengineering techniques for erosion control and slopes stabilisation. As Nature-based solutions, these age-old and highly adaptable techniques generally rely on the installation of living willow bundles fixed to either dead or living stakes. Fascines are the most widely used techniques to protect riverbanks toe in France; they are also implemented on slopes, and gullies making wide their possible use. They are often employed as part of a combination of techniques to meet specific local needs. Despite the common implementation of fascines, no guidelines cover the entire diversity of fascines. The technical guideline proposed describes the full scope of possibilities fascines offer, their advantages and disadvantages and technical details and specifications of implementation. Drawing on a foundation of technical literature, historical documentation, research experiments, and empirical knowledge, the guide delves into no fewer than 112 references. The objective is to enhance the use, success, and overall confidence in fascine-based techniques.

This guide presents comprehensive information on no fewer than 12 fascine techniques that have transcended through the ages, originating from structures dating back over 2,000 years in China and continuing to be relevant in the contemporary world.  Although fascines may seem simple and are known for their high mechanical strength, these techniques require high expertise to ensure lasting resistance and satisfactory plant growth. Several critical factors contribute to the success and durability of these structures, including the choice of plant species, the quality of planting materials, the nature of soil contact, and the positioning of the bundle relative to infiltration or groundwater levels. Application methods vary based on the specific technique and context: Fascines can be alive or inert; placed parallel or perpendicular to the slope; they come in different diameters with one or multiple bundles and can be used as barriers or drains. The most illustrative example is the implementation of fascines along the toe of the bank, which stands as the most widely used technique. For this approach, bundles should measure between 100 and 300 cm in length, with a diameter ranging from 15 to 50 cm. Branches should have a minimum diameter of 2 cm and a length of approximately one meter.

This technical support is intended for designers, river managers, technicians, and the general public, providing precise technical recommendations for the successful creation of fascines, from materials to maintenance, as well as implementation methods and environmental conditions appropriate to this type of structures.

How to cite: Didier, M., Evette, A., Schmitt, E., Leblois, S., Jaymond, D., Evette, J.-B., Mira, E., Raymond, P., Frossard, P.-A., and Vivier, A.: Enhancing fascine techniques for slopes erosion control: A comprehensive technical guide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15564, https://doi.org/10.5194/egusphere-egu24-15564, 2024.

EGU24-15726 | ECS | Posters virtual | NH3.13

A preliminary study on the possible effect of deforestation in debris flows deposits 

Andrea Lepri, Alessandro Fraccica, Corrado Cencetti, and Manuela Cecconi

The note focuses on a preliminary study of the effects of deforestation on the activation of debris flow. The area of interest is located in Nottoria, at the south of Norcia (Perugia, Italy). In 2012, after an intense thunderstorm, a debris flow occurred involving the village. The mobilized debris is mainly made of blocks of limestone channelling into the main road and then pouring into the valley lateral to the village. The debris reached in some point 1m of thickness while, in some areas, deep erosion due to water runout was significant. The debris consists of calcareous pebbles of varying sizes diffused in a marly-clayey matrix. Another debris flow was recorded in 2015. The main causes have been attributed to intense rainfalls involving valleys characterized by the outcrop of limestones intensely fractured. This information has been confirmed by the inspection of the Regional Geological Map (1:10000). The figure below shows the accumulation area, the propagation channel, and the source areas of the debris flow. Highly fractured side cliffs in which vegetation has grown were observed. Debris flow polygon has been imported from IdroGEO database (ISPRA).

A recent survey has revealed the presence of tall beeches and oaks. Furthermore, evidence of deforestation is clear in the area of possible triggering of debris. It is interesting to note that different deforestation parcels were generated between 2005 and 2011, while the debris flows occurred in 2012 and 2015. Moreover, from a recent survey, there appear to be potential source zones upstream of the phenomenon mapped in the official databases (IdroGeo, ISPRA).

A preliminary study has been undertaken to highlight the effects of deforestation occurring near the trigger zone. The research aims at investigating the role of vegetation in shallow slope stability or, from another point of view, the effect of deforestation in slope instability.  In-situ investigation has been planned, consisting of a geo-electric survey. Geophysical surveying techniques has been proved to be useful for predicting matric suction values through the relationships among soil porosity, saturation degree and electrical resistivity.

 

A laboratory investigation on physical properties of debris will be carried out in the geotechnical laboratories of ISPRA and University of Perugia. The need to set up specific in situ instrumentation to detect roots geometry, typology and depth is recognized, with the goal of quantifying the hydro-mechanical effects of roots on the material shear strength through in situ tests (e.g. direct shear apparatus, corkscrew, prospecting based on sound signal propagation).

There is no proof of debris re-activation after the seismic event of 30 October 2016 Mw 6.5 Norcia earthquake, 4 years later the occurrence of the first debris flow and 1 year later the second one. This point requires further investigation. The beneficial (or not) contribution of vegetation along the debris flow channel needs to be carefully modelled in order to design safe countermeasures for the mitigation of hydrogeological and seismic risk.

 

References

IdroGEO, https://idrogeo.isprambiente.it/ (website accessed on 09/01/2024).

Umbria Region, Geological Map (Carta geologica dell’Umbria - Dataset - Open Data Umbria regione.umbria.it).

Geological Survey of Umbria Region (https://www.regione.umbria.it/-/cartografia-geologica)

How to cite: Lepri, A., Fraccica, A., Cencetti, C., and Cecconi, M.: A preliminary study on the possible effect of deforestation in debris flows deposits, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15726, https://doi.org/10.5194/egusphere-egu24-15726, 2024.

EGU24-15976 | ECS | Posters on site | NH3.13

A method to derive spatially variable root cohesion maps from underground biomass maps for regional landslide susceptibility models 

Vittoria Capobianco, Rosa Palau Berastegui, Paul McLean, Elisabeth Hoffstad Reutz, Amanda DiBiagio, Luca Piciullo, and Graham Gilbert

In physics-based models for regional landslide susceptibility, the slope stability is most sensitive to the changes of both soil and root cohesion, thus a stochastic approach for these variables is preferred. Root cohesion (RC) is frequently oversimplified and assumed constant and uniform across the landscape. However, the assumption of a constant RC may be inappropriate because root distribution varies spatially with forest characteristics and temporally with tree growth.

Root biomass (RB) is a parameter used to partly quantify the amount of carbon sequestered in forest soils and therefore some empirically based functions (Marklund, 1988) exist to estimate RB from forest characteristics (size and species) in Norway. In turn, RB can be correlated to the reinforcement provided by roots, and can be included in slope stability models as an additional RC term.

This study presents an expeditious estimation of spatially variable RC from RB maps. The resulting maps can be used as input to shallow landslide susceptibility models at regional scale.

The method uses the formula proposed by Hwang et al. (2015), which derives the basal root cohesion from the original W&W model as proportional to the root biomass per ground area, and the density of the roots. The assumptions of the method are the following:

  • Basal RC is used to account for the role of forests on regional scale landslide susceptibility and hazard analysis.
  • RC increase is directly proportional to RB.
  • Only the roots with a diameter below 5 mm are concurring to the additional RC, thus only a percentage of the total root underground biomass as calculated for purposes of carbon sequestration is considered.

The method was applied for Norwegian forests consisting primarily of Pine (Pinus sylvestris), Spruce (Picea abies), and Birch (Betula pendula and pubescens) trees.

The RB maps were obtained by models produced by the Norwegian Institute of Bioeconomy Research (NIBIO), which use a mixture of airborne LIDAR and satellite imagery to characterise the above ground forest characteristics nationally (Astrup et al. 2019), then use the empirical functions to estimate RB. The surface resolution is 16 m2.

The study area is located in Sunnfjørd, precisely in Jølster, where several rainfall-induced landslides occurred in July 2019, causing damages to local infrastructure.

Estimates of RC from RB are compared with empirical data from the literature for similar species in forests outside Norway, showing reasonable consistency in the values ranges obtained. Further validation is needed with empirical data from Norwegian forests.

This study provides a simple yet computationally efficient estimation of root cohesion from RB maps, which can be used to supply parameters for models accounting for the effect of vegetation on landslide susceptibility at regional scale. In the future, it will be necessary to develop more precise relationships of fine root biomass to above ground forest characteristics with respect to changing soil properties.

References:

Astrup et al. (2019). https://doi.org/10.1080/02827581.2019.1588989

Hwang et al. (2015). https://doi.org/10.1002/2014JG002824

Marklund, L.G. (1988) Biomassafunktioner för tall, gran och björk i Sverige = Biomass functions for pine, spruce and birch in Sweden. Umeå: Sveriges lantbruksuniversitet, Institutionen för skogstaxering.

 

 

 

How to cite: Capobianco, V., Palau Berastegui, R., McLean, P., Hoffstad Reutz, E., DiBiagio, A., Piciullo, L., and Gilbert, G.: A method to derive spatially variable root cohesion maps from underground biomass maps for regional landslide susceptibility models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15976, https://doi.org/10.5194/egusphere-egu24-15976, 2024.

EGU24-16671 | Posters on site | NH3.13

Which willows for Soil and Water Bioengineering structures on high-elevation streambank? In situ study of cutting capacity of six species 

Adeline Francois, Juliette Rousset, Marie Didier, and André Evette

Soil and Water Bioengineering techniques are a sustainable alternative to civil engineering to prevent erosion processes that threaten streambank stability. These techniques are still poorly developed and documented in subalpine streams, where climatic and hydrological conditions are particularly challenging. It is well known that the success and integration of a SWBE technique is best achieved when it is possible to use indigenous plants and plant material. At the subalpine belt, shrub and tree willows are among the dominant woody species on streambanks. Even if a few past studies claimed that they could play a full role in stabilising the banks of high-elevation streams, their biotechnical characteristics are nearly unknown. The unique information available comes from empirical and not detailed results showing a low resprouting rate of cuttings. Still, no data or information on these capacities are known in the subalpine environment. We conducted an in situ experimental study to assess the cutting capacity of willow species at high elevations to improve SWBE on these streambanks.

Six willow species were selected: three subalpine shrub species (Salix caesia, S.foetida, S.hastata) and three tree species (S.daphnoides, S.myrsinifolia, S.purpurea) presents in both foothill and subalpine belt. The cuttings were planted in three different experimental sites with varied conditions: in Val Thorens at 1 800 m on subalpine grassland habitat and in Lautaret garden at 2 100 m on subalpine tall herb communities and on sand. For each site, 52 cuttings per species were planted in October 2022. In September 2023, at the end of the vegetative period, the recovery rate and the cuttings' aerial growth were assessed. Aerial growth was estimated by biomass dry weight and cumulative stem length.

All recovery rates were above 70%. In Val Thorens, S.purpurea had a recovery rate of 100%, S.hastata 80% and the other species between 88 and 96%. At the Lautaret garden on grassland, the recovery rates, ranged for all species from 71 (S.caesia) to 98% (S.purpurea). The recovery rates in the Lautaret garden on the sand were higher with 100% for S.caesia, S.foetida and S.purpurea and over 88% for the other three species. Despite differences in in situ conditions, all six species had excellent recovery rates for their use in SWBE structures. The willows growing on the sandy substrate at the Lautaret garden showed a higher growth rate. Within sites, there was no significant difference in growth between species. After the first year of growth, these six species seemed suitable for SWBE structures. Recovery rate and aerial growth will be re-estimated in autumn 2024, after the second growing season.

How to cite: Francois, A., Rousset, J., Didier, M., and Evette, A.: Which willows for Soil and Water Bioengineering structures on high-elevation streambank? In situ study of cutting capacity of six species, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16671, https://doi.org/10.5194/egusphere-egu24-16671, 2024.

EGU24-17275 | ECS | Posters on site | NH3.13

Nature-based Solutions in vineyards of Oltrepò Pavese (Northern Italy): state of the art and analysis of their effectiveness in shallow landslide mitigation  

Antonio Gambarani, Alberto Vercesi, Massimiliano Bordoni, Alessia Giarola, Valerio Vivaldi, and Claudia Meisina

Land degradation, e.g. shallow landslides, with correlated soil loss and nutrient loss, is a significant environmental problem for the agroecosystems, especially where farming is carried out on sloping soil (e.g. vineyards, olive groves, etc.).Due to climate change and consequent increase on extreme weather events, these processes are likely to become more widespread, thus leading to significant land abandonment.Another factor affecting land degradation concerns soil tillage by agricultural machinery, which, if uncontrolled, can accelerate the development of these processes.Land degradation is also dangerous for rural communities because of its rapidity of initiation and development and the lack of warning signs for its detection. It is therefore necessary to apply in agroecosystems effective solutions for disaster risk reduction (DRR) which, at the same time, are of low environmental impact and economically sustainable. Nature-based Solutions (NbS) can help address all these challenges as they are widely recognized by the scientific community and are often funded by countries or the union of countries, such as the European Union or the United Nations. However, NbS are still poorly applied by farmers and local governments, favoring gray infrastructure measures that are sometimes ineffective at achieving land degradation neutrality.

The aim of this work is to produce an inventory of the Nature-based Solutions applied in vineyards in an Apennine area of Northern Italy in order to verify, at the slope scale, their effectiveness in the mitigation of shallow landslides. The study area is represented by a sector of Oltrepò Pavese, one of the most important agricultural and viticultural regions in Italy.In the last 15 years, more than 2000 shallow landslides were triggered in consequence of intense rainfall events, with a density of distribution which reached more than 40% of the territory cultivated with grapevines. The work is carried out in the context of a PhD project, financed with PNRR (National Recovery and Resilience Plan) and cofounded by seven municipalities, stakeholders of the project. The final aim of the PhD projectis to identify the most suitable NbS for the studied area, in terms of technical and economical suitability. The scientific research results will be incorporated within the municipal planning tools and rural police regulation in order to prevent shallow landslides.

How to cite: Gambarani, A., Vercesi, A., Bordoni, M., Giarola, A., Vivaldi, V., and Meisina, C.: Nature-based Solutions in vineyards of Oltrepò Pavese (Northern Italy): state of the art and analysis of their effectiveness in shallow landslide mitigation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17275, https://doi.org/10.5194/egusphere-egu24-17275, 2024.

EGU24-18351 | Posters on site | NH3.13

From Parks to Banks: Aligning Nature-Based Urban Green Space Assessment with Erosion Protection Goals 

Michael Obriejetan and Theresa Krexner

The integration of urban green space management into erosion control for streambanks and embankments addresses essential environmental challenges by linking urban green spaces (UGS) with natural hazard (NH) mitigation. This strategic approach emphasizes comprehensive management that harmonizes seemingly different domains. At first glance, erosion stabilization measures and UGS appear distinct, yet they address similar processes from different perspectives. Central to this integration is vegetation assessment, vital for functions such as erosion control and urban ecosystem enhancement. Assessing vegetation through field evaluations and remote sensing is key for understanding how it interacts with soil, especially in terms of soil moisture, which is vital for slope stability and drought mitigation. This process is essential for evaluating the health and type of vegetation and its structural characteristics.

Decision-making in system selection and management for erosion control should adopt a lifecycle perspective, encompassing environmental and economic impacts. This includes considerations from material selection to maintenance and eventual decommissioning, aiming for sustainable, cost-effective approaches. Additionally, there is a wealth of knowledge in communal and city green space management that can potentially be adapted and transferred to meet the requirements of erosion control. The choice of vegetation is crucial for decisions in both urban areas and for slope stabilization measures. The role of evapotranspiration in enhancing soil cohesion and reducing erosion risk, especially in urban green spaces (UGS) and nature-based systems, is significant. These methods not only ensure slope stability but also offer urban benefits, like mitigating urban heat island (UHI) effects. In adapting to climate change for effective erosion protection strategies, the key distinction is found in the detailed assessment of specific parameters from UGS and their application to erosion control methods. This focused evaluation ensures that erosion control measures are not only effective but also congruent with the distinct ecological aspects of urban environments. By carefully analyzing factors like vegetation type, soil characteristics, and water management in UGS, these insights become invaluable in strengthening the resilience and adaptability of erosion control strategies. This strategy goes beyond mere soil erosion reduction; it plays a pivotal role in enriching ecosystem capacities. By fostering biodiversity and refining the utility of green spaces, it contributes to the development of landscapes that are both sustainable and better equipped to adapt to climate change. This holistic approach underlines the multi-faceted benefits of integrating green space management into broader environmental resilience planning.

How to cite: Obriejetan, M. and Krexner, T.: From Parks to Banks: Aligning Nature-Based Urban Green Space Assessment with Erosion Protection Goals, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18351, https://doi.org/10.5194/egusphere-egu24-18351, 2024.

EGU24-18452 | ECS | Posters on site | NH3.13

Innovations in Soil Water Bioengineering: A Stakeholder Perception Assessment 

Sara Pini and Federico Preti

Integrating Soil and Water Bioengineering (SWBE) and Nature-Based Solutions (NBS) represents a historical and advanced approach to addressing complex environmental issues. In particular, SWBE, as NBS, solutions aim to mitigate the occurrence and propagation of hydrogeological hazards. Techniques involving plants, and locally available materials, like timber and stone, have characterized land management since past times, guided by practical experience and necessity. In recent decades, we started rediscovering these techniques by including them in the definition of SWBE.

This study explores the current knowledge and perceptions of practitioners, such as engineers, architects, geologists, agronomists-foresters, and naturalists, regarding practices defined as SWBE by recent legislation and scientific literature. A questionnaire will be distributed through different communication channels to achieve this goal, mainly targeting the professional association of interest. The questionnaire consists of three sections: i) collecting the stakeholders’ biographical information, ii) investigating knowledge of the basic concepts and interpretation of SWBE and NBS techniques, and iii) discussing critical issues, possible improvements, and future perspectives in applying SWBE and NBS.

The results of this study provide a framework that leads to a deeper understanding of how SWBE and NBS are understood outside the academic environments, fostering more significant interaction between technical application and theoretical development. Analyzing similarities and divergences between the state of the art, current practices, and stakeholder perceptions is crucial, thus helping identify gaps and bringing out new frontiers of innovation within SWBE.

How to cite: Pini, S. and Preti, F.: Innovations in Soil Water Bioengineering: A Stakeholder Perception Assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18452, https://doi.org/10.5194/egusphere-egu24-18452, 2024.

EGU24-18576 | ECS | Orals | NH3.13

Impact of shrubby willows on seepage lines of flood protection dykes 

Helene Mueller, Elias Ferchl, Manuel Sokopp, and Hans Peter Rauch

Vegetation on flood protection dykes (FPD) is an ambivalent topic. It can provide multiple ecosystem services (e.g. erosion stability). Mostly herbaceous vegetation is used. Many rules, standards and technical codes ban woody vegetation from FPDs. While herbaceous vegetation leads to higher efforts regarding continuous maintenance work, it could be assumed that woody vegetation can provide additional benefits.  The spectrum reaches from less maintenance, impacts on biodiversity, shadowing effects that might counteract the drought stress of herbaceous vegetation under climate change aspects etc.. Nether the less effects of woody vegetation on FPDs reach from positive to negative influence, covering the spectrum of soil stabilization to tilling of the dyke matrix. Failure mechanisms of dyke stability with positive or negative influence of woody vegetation are surface erosion, subsurface erosion leading to ground failure, slope failure with deep sliding horizon and slope failure with shallow sliding horizon. A first step towards consideration of woody vegetation on FPDs is the prove of stability of dykes covered by woody vegetation. Up to now these issues were faced with individual expert opinions conducted for unique dyke situations and single tree individuals.
Focusing on the mechanism of ground failure, which is depending on the course of the seepage line through the dyke. The influence of the vegetation type covering the dyke surface on the seepage line has been analyzed over 15 years at an experimental dyke in Austria. Typical dyke related herbaceous vegetation communities were compared to woody vegetation implemented via soil bio-engineering techniques. Flooding experiments were carried out and the height of the seepage line in the dyke was measured cross-sectional at two to four points. The results represent newly built dykes considering the current state-of-the-art. The tested woody vegetation covers shrubby willows, implemented via cuttings and brush mattresses.  
Seven flooding experiments were conducted, covering durations from 5 to 49 days. Comparing the seepage lines of day 7 no clear patterns could be detected. For 42 % of measuring points the seepage line in the area of herbaceous vegetation is higher than in related areas with woody vegetation. For 37 % of measuring points the seepage line in the section covered by willows exceeds the height values related to herbaceous vegetation. 21 % of measuring points show almost the same heights for both vegetation types. Based on the conducted measurements no seepage section on the dyke surface could be assumed, dam stability appears not to be threatened by ground failure in both vegetation scenarios.
As first results it can be stated that continuously growing shrubby willows shows no negative effects on the seepage line of FPDs compared to herbaceous vegetation cover. Tough, this study shows some limitations: The results are only valid for dykes constructed under state-of-the-art standards and for shrubby species.

How to cite: Mueller, H., Ferchl, E., Sokopp, M., and Rauch, H. P.: Impact of shrubby willows on seepage lines of flood protection dykes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18576, https://doi.org/10.5194/egusphere-egu24-18576, 2024.

EGU24-18628 | ECS | Orals | NH3.13

Advancing Automated Detection in Neutron Scattering Imaging for Improved Root Structure Analysis of Rhizobox-Grown Salix Cuttings 

Yahel Eliyahu-Yakir, Mallory Wittwer, Anders Kaestner, Andrea Carminati, and Paolo Perona

Abstract:

In this work, we present a sequential procedure to analyze non-destructive neutron scattering imaging, which allows to improve the signal-to-noise ratio and maximize the identification of root structure architecture of plant cuttings grown in rhizoboxes containing humid sand sediment.

Plant cuttings play a pivotal role in water bioengineering applications, contributing significantly to enhancing waterway ecohydraulic processes, ecomorphodynamic mechanisms, flood protection strategies, and river restoration techniques. Despite their crucial role, various dynamics related to in-channel and bank vegetation responses to hydromechanical forces remain insufficiently understood. In this study, we conducted flume experiments to systematically examine the impact of hydrodynamic forces and subsurface flow on the root structure development of riparian plant cuttings (Salix species). Specifically, we addressed to role of such actions on triggering dynamotropism and hydropatterning mechanisms, which both lead to (upstream) asymmetrical plant root growth and spatially-variable soil reinforcement. The plant cuttings were cultivated in rhizoboxes filled with sand, which did undergo four different treatments aiming at single out which one better controls dynamotropism and hydropatterning. After a 6-week growth period, we employed a Neutron scanner to scan the boxes and detect the intricate root structures non-destructively. Analysis of the scans revealed significant challenges in distinguishing roots from the background due to factors such as the remaining water content at the pore level, sand texture, and variations in root dimensions. The high spatial variability of these parameters significantly influenced the accuracy of root detection. To address these challenges, we have developed a process utilizing advanced tools to enhance the probability of successfully detecting roots within the sand matrix. The automatization of such a procedure will allow to non-destructively analyse a large number of samples for statistically significant correlation analyses.

How to cite: Eliyahu-Yakir, Y., Wittwer, M., Kaestner, A., Carminati, A., and Perona, P.: Advancing Automated Detection in Neutron Scattering Imaging for Improved Root Structure Analysis of Rhizobox-Grown Salix Cuttings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18628, https://doi.org/10.5194/egusphere-egu24-18628, 2024.

EGU24-19131 | ECS | Orals | NH3.13

Soil and Water Bio Engineering (SWBE) techniques effects on Biodiversity, in Tuscany (Italy) 

Emanuele Giachi, Federico Preti, Martina Pollastrini, Marco Cabrucci, Carlo Viti, Agnese Bellabarba, Francesca Decorosi, and Andrea Dani

Monitoring, restoring and enhancing biodiversity is one of the most relevant issues in the transition towards more sustainable environmental solutions, but also to counter the effects of anthropogenic impacts and climate change. The development of new green jobs, together with the promotion of nature-based interventions, has increasingly pushed research to study NBS interventions, particularly those for restoring degraded areas, evaluating their effectiveness on ecological processes and the ecosystems.

The promotion of nature-based techniques (NBS) has seen a growing interest in the use of plants as building materials, as is done in Soil and Water Bioengineering (SWBE) techniques, that combine the technical function for natural hazard control and environmental function for ecological process restoration. With an interdisciplinary approach, a common feature of projects under the NBFC research centre, we seek to study the impact of the use of SWBE techniques on biodiversity and ecological processes from various perspectives.

Four main intervention sites have been identified where degraded areas have been or are to be restored with SWBE techniques. The study areas are in the locality of Pomezzana (LU), Torrente Sova (AR), Montisoni (FI) and Camaldoli (AR), all of which have been followed by the UNIFI DAGRI research group and carried out in different years, respectively: 25 years, 8 years, 3 years and to be carried out. We aim to assess the variation in biodiversity by comparing the areas restored with SWBE techniques to those with natural evolution adjacent to them, analysing various ecological parameters: vegetation, soil microorganisms, macroinvertebrates, and genetics of plant species.

During 2023, the first vegetation surveys (trees, shrub and herbaceous layer) were conducted, and pilot soil sampling was carried out to quantify the microorganisms present. Regarding the vegetation, Braun-Blanquet surveys were conducted for the herbaceous component, in transects of equal size both in the restored area and in the adjacent control areas; for the arboreal and shrub component, a standard-sized (depending on the site) sample area was made with a total plant stand (D>3 cm). For the soil samples, transects were drawn across the restored area following the level curve.

Initial data processing, on botanical survey of the plant species and the result of biodiversity indicators (Evenness, Shannon, etc.) revealed a difference in specific composition, and therefore environmental and microclimatic conditions, between the control plots and the restored area. The construction of the SWBE works, in timber and stone, and the use of rooted plants together with the sowing, create favourable conditions for the initiation of an ecological succession, even if it is not always in an excellent state compared to the control plots with 'natural' evolution. In the following elaborations we will try to understand the effect on soil microorganisms, and their relation within the vegetation composition, as well as to evaluate possible favourable conditions for the entry of alien and invasive species into the restored areas.

 

 

 

(1) Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali (DAGRI), Università degli Studi di Firenze

How to cite: Giachi, E., Preti, F., Pollastrini, M., Cabrucci, M., Viti, C., Bellabarba, A., Decorosi, F., and Dani, A.: Soil and Water Bio Engineering (SWBE) techniques effects on Biodiversity, in Tuscany (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19131, https://doi.org/10.5194/egusphere-egu24-19131, 2024.

EGU24-19887 | ECS | Posters on site | NH3.13

Exploring stress-paths and vegetation reinforcement mechanisms in a compacted soil 

Alessandro Fraccica, Enrique Romero, and Thierry Fourcaud

The use of vegetation is a sustainable technique to mitigate the risk of landslides and erosion phenomena. Literature agrees that roots improve soil shear strength properties. The reinforcement of roots on soils is complex and depends on their morphological and mechanical characteristics and the stresses that develop at the soil–root interface. In this regard, many models have been produced in literature to infer the increase in soil shear/tensile strength due to roots. Among them, soil hydraulic state was poorly considered.

Large cell triaxial consolidated drained compression tests and tensile tests were carried out to explore the mechanical effects of vegetation on a compacted soil at low confining stresses and at different hydraulic states (identified in terms of suction and degree of saturation). Root features were thoroughly assessed for each soil specimen and were correlated, jointly with soil hydro-mechanical states, to the two soil reinforcement mechanisms observed (roots breakage and slippage). Different stress-strain responses were observed during the mechanical tests, depending on soil initial suction. Strain spatial distributions during tensile tests were observed by an advanced imaging technique (Particle Image Velocimetry): roots contributed to redistribute the tensile stresses over larger soil volumes. A combination of two literature reinforcement models was adopted to interpret the results: one model to consider root tensile strength full exploitation and breakage, and the other to predict friction forces at the soil–root interface during root slippage. The correlation coefficients of these two models were calibrated based on this experimental campaign.

Fraccica, A., Romero Morales, E. E., & Fourcaud, T. (2019). Multi-scale effects on the hydraulic behaviour of a root-permeated and compacted soil. In IS-Glasgow 2019–7th International Symposium on Deformation Characteristics of Geomaterials (pp. 1-5). EDP Sciences.

Fraccica, A., Romero, E., & Fourcaud, T. (2022). Tensile strength of a compacted vegetated soil: Laboratory results and reinforcement interpretation. Geomechanics for Energy and the Environment30, 100303.

Fraccica, A., Romero, E., & Fourcaud, T. (2023). Large cell triaxial tests of a partially saturated soil with vegetation. In E3S Web of Conferences (Vol. 382, p. 05005). EDP Sciences.

Fraccica, A., Romero, E., & Fourcaud, T. (2024). Effects of vegetation growth on soil microstructure and hydro-mechanical behaviour. Géotechnique (accepted)

Oorthuis, R., Hürlimann, M., Fraccica, A., Lloret, A., Moya, J., Puig-Polo, C., & Vaunat, J. (2018). Monitoring of a full-scale embankment experiment regarding soil–vegetation–atmosphere interactions. Water10(6), 688.

How to cite: Fraccica, A., Romero, E., and Fourcaud, T.: Exploring stress-paths and vegetation reinforcement mechanisms in a compacted soil, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19887, https://doi.org/10.5194/egusphere-egu24-19887, 2024.

EGU24-20297 | ECS | Posters on site | NH3.13

Effect of brick sand on the soil water balance in permeable soils 

Andreas Mähr, Hans Peter Rauch, Josef Eitzinger, Philipp Weihs, and Stephan Hörbinger

In the course of climate change, the framework conditions for agricultural production will change significantly. The ability of the soil to absorb water quickly and efficiently while at the same time storing as much water as possible for plants to use is a prerequisite for maintaining future agricultural production potential.

The aim of this study was to investigate the application of recycled brick sand in agricultural soils with regard to its water absorption and storage capacity and thus to improve the efficiency of water utilisation. The influence of different precipitation intensities on the water storage capacity was analysed.

In order to determine the influence of brick sand on the soil water balance, an experiment was carried out with nine small lysimeter systems. The lysimeters were all filled with soil samples from a vineyard in eastern Austria, whose soil has a high sand fraction and low clay mineral content. Three lysimeters were used as a reference and contained no brick sand. In three others, a mixture of soil sample and 10 % brick sand was used and in three others a mixture of soil sample and 30 % brick sand was applied. A 3-phase test was then carried out. The first phase was used to set a volumetric water content that was as constant as possible in all samples. The second phase was the simulation of a 10-millimetre precipitation event, followed by the third phase, the simulation of a 20-millimetre precipitation event. During the precipitation simulation, the amount of water corresponding to the precipitation intensity was applied to the lysimeter systems and the volumetric water content of the samples was recorded. Control values were determined using soil moisture sensors.

The results showed that the addition of brick sand enabled the soil to store more water over time than the sample without brick sand. The simulations also showed that the amount of brick sand added made a difference in how the water storage capacity changed. Shortly after the rainfall simulation, the lysimeters with 30 % brick sand were able to store the water better. Towards the end of the precipitation simulation, the difference in stored water between the lysimeters with 30 % brick sand content and those with 10 % brick sand content became smaller, and in the 20 millimetre rainfall simulation, the lysimeters with 10 % brick sand content stored more water from halfway through the observation period. The results showed that the use of brick sand as a measure to improve the soil water balance has a high potential, however, the amount of brick sand applied must be adapted to the soil to be treated. These adjustments concern parameters such as grain size distribution and pore distribution, as these have a decisive influence on the water storage capacity.

How to cite: Mähr, A., Rauch, H. P., Eitzinger, J., Weihs, P., and Hörbinger, S.: Effect of brick sand on the soil water balance in permeable soils, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20297, https://doi.org/10.5194/egusphere-egu24-20297, 2024.

EGU24-20757 | Orals | NH3.13 | Highlight

Study on the durability of the biocementation treatment of a Portuguese motorway slope  

Rafaela Cardoso, Mário Oliveira, Miguel Cruz, Isabel Gonzalez, Ana Teresa Rodrigues, Leslie Sapin, and Annette Esnault-Filet

Biocementationconsists in using biological agents such as bacteria or enzymes to promote the precipitation of calcium carbonate. This environmentally sustainable technique was applied to treat an excavation slope in sandy soil on a Portuguese motorway, aiming to prevent erosion and the formation of ravines caused by water flow. The slope has been monitored for over one year as part of an ongoing project funded by FCT (ref. PTDC/ECI-EGC/1086/2021). The results of the first campaigns are presented, consisting in the time evolution of the amounts of calcium carbonate. The results confirm the durability of the treatment, also confirmed by laboratorial tests performed on samples of the same soil treated with the same protocol and after being submitted to 10 wetting and drying cycles.

How to cite: Cardoso, R., Oliveira, M., Cruz, M., Gonzalez, I., Rodrigues, A. T., Sapin, L., and Esnault-Filet, A.: Study on the durability of the biocementation treatment of a Portuguese motorway slope , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20757, https://doi.org/10.5194/egusphere-egu24-20757, 2024.

EGU24-21957 | ECS | Posters virtual | NH3.13

Can appropriate assessment drive hydraulic risk management towards nature-based solutions? A case study in a Natura 2000 site in central Italy. 

Riccardo Di Cintio, Simone Bollati, Carlo Maria Rossi, Giulia Luzi, Giuseppe Antonelli, Angela Antogiovanni, Francesco Forcina, Massimo Mancini, Simone De Simone, Armando Di Biasio, Antonio Nardone, Sandro Esposito, and Gianluca Sabatini

Flooding is a natural hazard stemming from heavy rainfall, with a growing global impact due to shifts in land use, particularly urbanization and climate change. Traditional flood damage control methods have predominantly relied on “grey” solutions, involving extensive use of concrete structures, either reinforced or not. The sustainability paradigm has prompted a shift towards solutions inspired by nature, where ecological approaches are integrated with engineering design to enhance risk management. In this context, striking a harmonious balance between the “security objective” and biodiversity preservation, especially in areas governed by the European Council Directive 92/43/EEC, emerges as paramount.
This case study focuses on the hydraulic-integrated environmental restoration of the Rio Santa Croce stream, partially encompassed within a Natura 2000 site (code IT6040024), located in Latina, Italy (Lat. 41.27°N, Long 13.71°E WGS 84). It serves as an illustrative example of how the Natura 2000 network, often perceived merely as a restriction by authorities, technicians and local communities, can be transformed into a valuable tool for steering hydraulic risk management towards nature-based solutions (NBSs). This transformation could be achieved through the appropriate assessment (AA) regulated by Article 3 of the European Council Directive 92/43/EEC.
A multidisciplinary team, comprising professional foresters from the Società Cooperativa Trifolium a.r.l., along with professional engineers and a professional geologist, on behalf of the Province of Latina, conceived a green gabion wall to stabilize the banks of a section of the Rio Santa Croce while creating habitats for aquatic vertebrates. These retaining structures are considered environmental-friendly, offering a more sustainable option compared to traditional earth-retaining walls. By integrating vegetation and implementing special technical measures during the assembly of the baskets, the gabion wall can be classified as NBSs, providing a favorable compromise in situations where the only alternative involves conventional grey solutions. 

How to cite: Di Cintio, R., Bollati, S., Rossi, C. M., Luzi, G., Antonelli, G., Antogiovanni, A., Forcina, F., Mancini, M., De Simone, S., Di Biasio, A., Nardone, A., Esposito, S., and Sabatini, G.: Can appropriate assessment drive hydraulic risk management towards nature-based solutions? A case study in a Natura 2000 site in central Italy., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21957, https://doi.org/10.5194/egusphere-egu24-21957, 2024.

EGU24-7008 | PICO | CR6.3

Research on avalanches caused by stability of snow cornices developed by blowing snow 

Satoru Yamaguchi, Yoichi Ito, Takahiro Tanabe, Koichi Nishimura, Satoru Adachi, Sojiro Sunako, Yoshihiko Saito, Tsubasa Okaze, Hirofumi Niiya, Kae Tsunematsu, and Hiraku Nishimori

Our research is aimed at improving the prediction accuracy of avalanches caused by the stability of snow cornices developed by blowing snow in the Niseko region, one of Japan's international ski resorts. For this purpose, several studies were conducted in cooperation with local authorities and ski resorts in the Niseko region. Specifically, a network of anemometers was installed and a system was developed to estimate areal wind conditions and snow redistribution over the entire mountain area from wind observation data. To validate the developed system, the snow cover distribution over the entire mountain area for two winters was obtained by laser survey using an aircraft. In addition, several portable ultrasonic anemometers were installed on the slopes where snow cornices develop to observe detailed wind conditions, and small LiDAR was used to continuously survey snow cornice development. We sampled snow in the developing snow cornice and analyzed its microstructure using X-ray computed tomography imaging. The presentation presents a first analysis.

 

 

How to cite: Yamaguchi, S., Ito, Y., Tanabe, T., Nishimura, K., Adachi, S., Sunako, S., Saito, Y., Okaze, T., Niiya, H., Tsunematsu, K., and Nishimori, H.: Research on avalanches caused by stability of snow cornices developed by blowing snow, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7008, https://doi.org/10.5194/egusphere-egu24-7008, 2024.

EGU24-9222 | ECS | PICO | CR6.3 | Highlight

Climate change impacts on large scale avalanche risk in alpine regions 

Gregor Ortner, Adrien Michel, Chahan M. Kropf, Yves Bühler, Marc Christen, Michael Bründl, and David N. Bresch

Observations in various regions worldwide document a decline in mean snow depth, spatial extent, and duration of snow cover, indicating a connection to climate change, especially at low elevations. Climate scenarios project further changes, but the exact consequences on future snow cover and avalanche patterns remain unknown. Our work investigates the influence of climate change on the snow cover, specifically focusing on its impact on avalanches and the associated risk to buildings. To compare the consequences of these potential changes on snow avalanche hazard and risk with the current situation, we have developed a framework to model avalanche risk on a large scale. We applied an algorithm to generate a protection forest layer, potential release areas, and conduct snow analysis for current climatic conditions. The RAMMS::LSHIM algorithm within the RAMMS avalanche model produces avalanche hazard indication maps. They are combined with the CLIMADA risk assessment platform, incorporating exposure and vulnerability data, to create spatially explicit risk maps under different avalanche return period scenarios.
To address climate change impacts, we have integrated the CH2018 climate scenario data including various model chains into avalanche hazard mapping, using the SNOWPACK snow cover model. Snow cover simulations cover the years from 1997 to 2100 and deliver three day snow accumulation data and layer temperatures for potential future avalanches. We used this data to run the RAMMS::EXTENDED avalanche model with modified snow and temperature parameters. This enabled us to create hazard indication maps considering climate change.
Results indicate a potential decrease in the spatial extent of avalanches, especially at lower altitudes, due to rising snowline, particularly in model chains with reduced snowfall. However, within CH2018, other climate model chains suggest increased snow accumulation, resulting in larger avalanches and increased pressure in high-altitude areas.
Applying the CLIMADA risk tool to climate change hazard analysis using an enhanced vulnerability curve and uncertainty analysis results in various risk outcomes. An average approach over all model chains suggests a decrease in risk, particularly in low-altitude side valleys. Single model chains with increased snowfall project higher risks despite a reduced affected area. The study underlines the need to incorporate climate change into practical avalanche hazard assessment and subsequently risk analysis.
Overall, this research, for the first time, quantifies the impact of climate change on the potential future spatial distribution of avalanches and associated changes in potential risk. The practical applicability of climate change avalanche hazard assessment was demonstrated, offering insights for stakeholders to assess future risks and consider climate change risk appraisal options. 

How to cite: Ortner, G., Michel, A., Kropf, C. M., Bühler, Y., Christen, M., Bründl, M., and Bresch, D. N.: Climate change impacts on large scale avalanche risk in alpine regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9222, https://doi.org/10.5194/egusphere-egu24-9222, 2024.

EGU24-10420 | PICO | CR6.3

Follow-up at the small scale during snow deformation. Microstructure evolution and local heterogeneities at various strain-rates. 

David Georges, Louis Védrine, Antoine Bernard, Mathilde Bonnetier, Maurine Montagnat, Pascal Hagenmuller, and Guillaume Chambon

Snow deforms naturally in a large range of strain rates covering ductile to brittle regimes. In all situations, snow deformation is characterized by complex mechanisms taking place at the microstructure scale, with interplay between metamorphism, sintering and grain rearrangements. Current modeling efforts require better understanding and formulation of the microstructure-scale complexity.
We performed compression experiments on snow samples in order to follow the microstructure evolution at various imposed displacement velocities. The resulting strain-rates varied between 10-2 s-1 and 10-7 s-1. Samples (15 mm height, 15 mm diameter) were made out of rounded grains with an initial density of about 250 kg m-3. Samples evolution was followed by means of micro-computed X-Ray tomography (microCT) with full 3D scans performed during the slower tests and simple radiographies at a high frequency for faster tests.
In this presentation we will focus on the various metrics used to analyse the microstructure evolution on one side, in particular specific surface area (SSA) and the minimum cut area. On the other side, we will present recent developments based on digital image and volume correlations (DIC and DVC) performed on the radiographies and the 3D microCT images with the open access SPAM software (https://hal.univ-grenoble-alpes.fr/hal-03020460), in order to follow the local strain field.
We will provide analyses of the interplay between metamorphism and strain in the microstructure evolution and of the impact of mechanisms at bonds in the various strain-rate regimes explored (ductile to brittle). Snow deformation localisations revealed by DIC and DVC observations will be presented. They can be inherited from initial sample heterogeneities or take the shape of compaction bands, depending on the strain rate.
All these data and analyses will be further interpreted regarding the understanding of the small scale mechanisms of metamorphism and deformation of snow and their modeling frame.

How to cite: Georges, D., Védrine, L., Bernard, A., Bonnetier, M., Montagnat, M., Hagenmuller, P., and Chambon, G.: Follow-up at the small scale during snow deformation. Microstructure evolution and local heterogeneities at various strain-rates., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10420, https://doi.org/10.5194/egusphere-egu24-10420, 2024.

EGU24-11202 | PICO | CR6.3

Toward automatic avalanche detection with Distributed-Acoustic-Sensing leveraging telecommunication infrastructure 

Pascal Edme, Patrick Paitz, Andreas Fichtner, Alec van Herwijnen, and Fabian Walter

Snow avalanches pose significant threats in alpine regions, leading to considerable human and economic losses. The ability to promptly identify the locations and timing of avalanche events is essential for effective prediction and risk mitigation. Conventional automatic avalanche detection systems typically rely on radars and/or seismo-acoustic sensors. While these systems operate successfully regardless of weather conditions, their coverage is often confined to a single slope or a small catchment (distances < 3 km).

In our study, we demonstrate the feasibility of detecting snow avalanches using Distributed Acoustic Sensing (DAS) through existing fiber-optic telecommunication cables. Our pilot experiment, conducted over the 2021/2022 winter, involved a 10km long fiber-optic dark cable running parallel to the Flüelapass road in the eastern Swiss Alps close to Davos. The DAS data reveal distinct evidence of numerous dry- and wet-snow avalanches, even when they do not reach the cable, as confirmed photographically. We show that avalanches can be distinguished from other signals (e.g., vehicle traffic) using a frequency-dependent STA/LTA attribute, enabling their detection with high spatiotemporal resolution. These findings pave the way for cost-effective and near-real-time avalanche monitoring over extensive distances, leveraging existing fiber-optic infrastructure.

How to cite: Edme, P., Paitz, P., Fichtner, A., van Herwijnen, A., and Walter, F.: Toward automatic avalanche detection with Distributed-Acoustic-Sensing leveraging telecommunication infrastructure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11202, https://doi.org/10.5194/egusphere-egu24-11202, 2024.

EGU24-12238 | ECS | PICO | CR6.3

Influence of snow microstructure on the compressive strength of weak layers 

Jakob Schöttner, Melin Walet, Valentin Adam, Florian Rheinschmidt, Philipp Rosendahl, Philipp Weißgraeber, Jürg Schweizer, and Alec van Herwijnen

Slab avalanches result from the failure of a weak snowpack layer buried underneath a cohesive slab. Determining the material properties of different weak layer morphologies is therefore necessary to better understand and model slab avalanche formation. Natural weak layers exhibit a variety of different microstructures and densities, and thus show different mechanical behavior. Up to now, mechanical properties of snow have been mainly evaluated based on bulk proxies such as snow density, while relevant microstructural characteristics have not been accounted for.

To establish a link between the microstructure of weak layers and their mechanical properties, we performed displacement-controlled laboratory experiments using a uniaxial testing machine. The compression experiments were recorded using a high-speed camera, allowing us to derive the strain within the weak layer. The microstructure of each batch of specimens was analyzed using micro-tomography to obtain density, specific surface area, anisotropy and correlation lengths. As testing a wide range of microstructural morphologies is difficult due to seasonal availability and the need to transport the fragile samples to the laboratory, we used both natural and artificially grown weak layers. We tested weak layers composed of facetted grains, depth hoar, surface hoar, precipitation particles and rounded grains.  

The compressive strength of more than 200 tested samples covered two orders of magnitude (0.5 kPa to 150 kPa) for weak layer densities ranging from 110 kg/m3 to 380 kg/m3. As expected, our results show a strong correlation between weak layer density and compressive strength, but also a dependence on other microstructural quantities. These results will help us improve our understanding of the mechanical properties of weak snowpack layers and will ultimately allow us to better forecast avalanche release probability.

How to cite: Schöttner, J., Walet, M., Adam, V., Rheinschmidt, F., Rosendahl, P., Weißgraeber, P., Schweizer, J., and van Herwijnen, A.: Influence of snow microstructure on the compressive strength of weak layers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12238, https://doi.org/10.5194/egusphere-egu24-12238, 2024.

EGU24-15088 | ECS | PICO | CR6.3

Snow depth distribution measurements using low cost LiDAR sensors 

Pia Ruttner-Jansen, Julia Glaus, Annelies Voordendag, Andreas Wieser, and Yves Bühler

Redistribution of snow by wind is an important factor influencing the avalanche danger. However, it is challenging to get detailed information on variations of snow depth in avalanche release areas with sufficiently high spatiotemporal resolution. We have developed a distributed measurement system containing two low cost LiDAR sensors, cameras and meteorological sensors. In autumn 2023 we have deployed this system at a first test site, in the area of a frequently released avalanche. Two stations equipped with the sensors cover an area of around 20'000 m² and provide the snow depth distribution once per hour with a spatial resolution on the cm to m-level. The (near) real time data transmission to a local server allows for an up-to-date assessment of the conditions in the slope. First analyses show the small temporal changes of average snow depth from epoch to epoch for small areas (1m²), including some local avalanche events. We will present first results obtained from the unique dataset resulting from acquisition at high spatio-temporal resolution over the entire winter season 2023/2024, focusing particularly on the snow depth variations before and after avalanche events. In the future, the newly built up snow depth database and the additionally recorded meteorological parameters will be used to model, predict and evaluate the snow depth redistribution on a slope scale level. The data collected directly within the release areas will improve the process understanding of avalanche formation and forecasting, and will thus contribute to better protection of people and infrastructure.

How to cite: Ruttner-Jansen, P., Glaus, J., Voordendag, A., Wieser, A., and Bühler, Y.: Snow depth distribution measurements using low cost LiDAR sensors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15088, https://doi.org/10.5194/egusphere-egu24-15088, 2024.

EGU24-16056 | PICO | CR6.3

Decennial infrasonic array analysis of snow-avalanche activity and its weather forcing in Pennine Alps: implications for forecasting 

Giacomo Belli, Duccio Gheri, Emanuele Marchetti, Paola Dellavedova, Nathalie Durand, and Eloise Bovet

Snow avalanches rank among the deadliest natural hazards in mountain environments worldwide. To date, forecasting is mostly based on measuring meteorological forcing, aiming at assessing the probability of event triggering in a certain area. To validate forecast models, information on avalanche occurrence is critical. However, real-time avalanche detection is still challenging and generally limited to radar or visual surveillance of one or a few known channels; here the need for novel monitoring solutions. In the last decades, infrasound has proven to be one of the most promising tools for real-time detection of avalanches. Indeed, snow avalanches, moving downhill, generate acoustic pressure waves in the air, which can be recorded with an array of infrasonic sensors that allows to detect and characterize the source. However, many difficulties still exist, mostly connected to the discrimination of the avalanche infrasound among the signals radiated by other natural or anthropic infrasonic sources active at the Earth's surface or in the atmosphere.

Here we present an analysis of >10 years of data recorded by a small-aperture infrasonic array deployed at an altitude of ~2000 m in Valle d'Aosta (Itay). To detect snow-avalanche events, we develop an algorithm aimed at identifying avalanche signals in the recorded infrasound dataset and calibrated on two avalanche crises occurred in the site. The identified avalanche-type infrasonic signals are then compared to local meteorological data and avalanche bulletins, to test the accuracy of our algorithm. Several clusters of avalanche-type infrasonic signals are identified on days with favourable weather conditions for the triggering of snow avalanches. Our study also allows us to investigate the meteorological forcing of snow avalanches in the Pennine Alps, showing that avalanche storms are induced preferentially as a result of the destabilisation of thick snow accumulations, but also highlighting the importance of weather patterns at seasonal scale.

This study was financially supported by the National Recovery and Resilience Plan, Mission 4 Component 2 - Investment 1.4 - NATIONAL CENTER FOR HPC, BIG DATA AND QUANTUM COMPUTING - funded by the European Union - NextGenerationEU - CUPB83C22002830001.

How to cite: Belli, G., Gheri, D., Marchetti, E., Dellavedova, P., Durand, N., and Bovet, E.: Decennial infrasonic array analysis of snow-avalanche activity and its weather forcing in Pennine Alps: implications for forecasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16056, https://doi.org/10.5194/egusphere-egu24-16056, 2024.

EGU24-16637 | ECS | PICO | CR6.3

The role of capillary forces in the formation of interfacial water layers in “cold” glide-snow avalanches 

Michael Lombardo, Amelie Fees, Peter Lehmann, Alec van Herwijnen, and Jürg Schweizer

Glide-snow avalanches are generally thought to come in two flavors: “cold” and “warm”. The main difference between them is the mechanism by which liquid water is generated and reaches the basal snowpack. For warm avalanches, the water comes from the snow surface via rain or surface melt. For cold avalanches, the water is thought to be generated by capillary suction or geothermal melting. Here, we focus on cold avalanches and address the role of capillary forces at the soil-snow interface. To do so, we combine theoretical considerations, snowpack simulations, and field data. Calculations based on basic principles show that the conditions necessary for capillary suction are unlikely for the representative soil types, because high soil saturation is required. Field data from the “Dorfberg” field site above Davos (eastern Swiss Alps) confirms that these saturated conditions rarely occur. Simulations of two “cold” glide-snow avalanches at the field site further confirm (i) the absence of capillary suction and (ii) the presence of geothermal melting. Thus, we suggest that in the absence of a distinct water source (e.g. spring), geothermal melting is likely responsible for the formation of liquid water in cold avalanches, while the capillary forces are responsible for the retention of this water within the basal snowpack layers.

How to cite: Lombardo, M., Fees, A., Lehmann, P., van Herwijnen, A., and Schweizer, J.: The role of capillary forces in the formation of interfacial water layers in “cold” glide-snow avalanches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16637, https://doi.org/10.5194/egusphere-egu24-16637, 2024.

EGU24-16711 | ECS | PICO | CR6.3

Assessing avalanche activity in seismic data with modern machine learning methods. 

Andri Simeon, Cristina Pérez-Guillén, Michele Volpi, Christine Seupel, and Alec van Herwijnen

Monitoring snow avalanche activity is essential for operational avalanche forecasting and the successful implementation of mitigation measures to ensure safety in mountain regions. To facilitate and automate the monitoring process, avalanche detection systems equipped with seismic sensors provide a cost-effective solution. Still, automatically differentiating avalanche signals from other sources in seismic data remains rather challenging. This is mainly due to the complexity of the seismic signals generated by avalanches, the relatively rare occurrence of avalanches and the presence of multiple sources in the continuous recordings.

To discriminate avalanches from other sources in the continuous seismic recordings, we test three random forest classifiers using two feature sets extracted with two autoencoders and a set of 57 statistical features. We extract these features from 10s windows of the seismograms recorded with an array of five seismometers installed in Davos, Switzerland. The statistical feature set includes waveform, spectral and spectrogram attributes. The first autoencoder is composed of convolutional layers and a long short-term memory unit. This neuronal network automatically extracts 64 features from the raw waveform signal. The second autoencoder applies a sequence of fully connected layers to extract the same number of features from the spectrum of the signals. We assess the performance of each classifier and compare the results. To improve the predictive performance of the seismic system, we employ different post-processing, e.g. adaption of classification thresholds and ensembling the predictions from the three classifiers. The final model is tested with the continuous seismic data of the last winter season to potentially be used as an operational, near-real-time detection system.

How to cite: Simeon, A., Pérez-Guillén, C., Volpi, M., Seupel, C., and van Herwijnen, A.: Assessing avalanche activity in seismic data with modern machine learning methods., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16711, https://doi.org/10.5194/egusphere-egu24-16711, 2024.

EGU24-17750 | PICO | CR6.3

ISeeSnow - initiating an avalanche simulation tool intercomparison 

Anna Wirbel, Felix Oesterle, Jan-Thomas Fischer, Guillaume Chambon, Thierry Faug, Johan Gaume, Julia Glaus, Stefan Hergarten, Dieter Issler, Alexander Jarosch, Tómas Jóhannesson, Marco Martini, Martin Mergili, Matthias Rauter, Joerg Robl, Giorgio Rosatti, Paula Spannring, Christian Tollinger, Hervé Vicari, and Daniel Zugliani

The ISeeSnow pilot-study aims at bringing together and starting a conversation among the different groups in the field of gravitational mass flow simulations, with a focus on snow avalanches. These simulation tools are an integral part of engineering practice, scientific development and academic education.

At its core, an objective comparison of simulation results is performed for three different test cases, based on a generic, idealized topography as well as a real-world simulation scenario. In this initial effort, we focus on thickness-integrated shallow water models using a simple Coulomb- or classical Voellmy rheology. In this manner, comparing simulation results for the test cases, prescribing the friction parameters, topography, release area and release thickness, allows us to analyze common features and differences stemming from the various implementations, i.e. formulation of model equations, choice of numerical methods and their implementation into computer code as well as geo-data handling (input/output). We also include simulation tools that rely on a different mathematical formulation and basic assumptions (e.g. 3D models or conceptual approaches) and perform a qualitative comparison for a specially designed test case. Furthermore, performing this pilot-study helps to identify common data needs, come up with standard result formats and discuss helpful visualization options. As a third outcome, we summarize ideas on what is needed to perform a more comprehensive model intercomparison study which also tackles model verification and validation tests, with respect to test designs, required input data as well as model configuration options. In this community-based contribution, we present the concept of the ISeeSnow pilot-study, show preliminary results of the simulation comparison and give an outlook on potential avenues for a future comprehensive model intercomparison project.

How to cite: Wirbel, A., Oesterle, F., Fischer, J.-T., Chambon, G., Faug, T., Gaume, J., Glaus, J., Hergarten, S., Issler, D., Jarosch, A., Jóhannesson, T., Martini, M., Mergili, M., Rauter, M., Robl, J., Rosatti, G., Spannring, P., Tollinger, C., Vicari, H., and Zugliani, D.: ISeeSnow - initiating an avalanche simulation tool intercomparison, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17750, https://doi.org/10.5194/egusphere-egu24-17750, 2024.

EGU24-18590 | ECS | PICO | CR6.3

Elastic snow properties for the optimization of weak layer fracture toughness estimates 

Melin Walet, Jakob Schöttner, Valentin Adam, Florian Rheinschmidt, Jürg Schweizer, Philipp Rosendahl, Philipp Weissgraeber, and Alec van Herwijnen

Dry-snow slab avalanches release due to crack propagation in a weak layer inside the snowpack. Understanding the fracture characteristics of the weak layer is essential for describing the onset of crack propagation and hence for predicting avalanche release. Avalanches release on steep slopes, thus crack propagation is a mixed mode fracture problem. Yet, thus far little is known about the mixed-mode fracture toughness of weak layers, a material property describing the resistance to crack growth under different loading conditions, from mode I normal to the crack faces to mode II parallel to the crack face.

Here, we present experiments that were conducted to derive a full range interaction between mode I and mode II fracture toughness of natural weak layers. Using a mechanical model, we derived fracture toughness values under different mixed-mode loading conditions. Crucial model variables are the elastic properties of the slab and the weak layer, which we retrieved from high-speed video recordings of the experiments and digital image correlation. These elastic properties allow for optimization of the estimates for weak layer fracture toughness values. Our results show that the specific fracture energy is larger in mode II than in mode II. This agrees with the behavior observed in other materials.

In future we will investigate the fracture properties of numerous weak layer microstructures. Since the snow microstructure most likely controls the mechanical properties, a characterization of the microstructure is essential. The connection between weak layer fracture and the microstructure of weak snowpack layers can be used to ultimately improve slab avalanche forecasting.

How to cite: Walet, M., Schöttner, J., Adam, V., Rheinschmidt, F., Schweizer, J., Rosendahl, P., Weissgraeber, P., and van Herwijnen, A.: Elastic snow properties for the optimization of weak layer fracture toughness estimates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18590, https://doi.org/10.5194/egusphere-egu24-18590, 2024.

Snow avalanches are one of the principal glacial threats, which are limited to high snow-covered alpine terrain. Mapping of Avalanche hazard and its modeling are useful in minimizing the fall risk. The current study assesses the utility of satellite imagery and GIS-based analytical hierarchical process (AHP) for mapping of possible avalanche locations for Draupadi ka Danda peak in Garhwal Himalaya, Uttarakhand. Various protruding terrain factors such as elevation, aspect, slope, curvature and land use land cover are used in this model and are derived from ALOS PALSAR DEM and Sentinel-2 images. Sensitivity analysis was performed on the chosen parameters and maximum weightage was set to slope, trailed by elevation, aspect, curvature and land use land cover. Using weighted overlay in ArcGIS avalanche susceptibility maps are formulated and distributed into five zones i.e. very low, low, moderate, high and very high zones and their validation was done by the listed avalanche occasions. Consecutively, Rapid Mass Movement Simulation (RAMMS) which is a three dimensional numerical model is used which generates parameters such as flow distance, height, velocity, pressure and momentum. The model requires a DEM of high resolution, release area of avalanche, friction parameter and was executed on the very high and high zones of avalanche susceptibility map.

How to cite: Mishra, N., Keshari, A. K., and Chahar, B. R.: Remote Sensing based mapping and modelling of potential avalanche zones in Draupadi ka Danda, Garhwal Himalayas, Uttarakhand, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19817, https://doi.org/10.5194/egusphere-egu24-19817, 2024.

EGU24-21128 | PICO | CR6.3

Quantification of reliability of roofs subjected to snow loadsdetermined by hydrological models 

Thomas Thiis, Iver Frimannslund, Hevi Nori, and Zhen Mustafa

Snow loads exert a significant influence on the structural integrity of buildings in the northern hemisphere, necessitating precise assessment methodologies to ensure the reliability of roofs under this environmental stressor. The determination of roof snow load is intricately linked to evaluating the weight of accumulated snow on the roof surface, a critical consideration in the design and construction of buildings. The reliability of a roof structure is conventionally gauged through the computation of the reliability index, denoted as beta. This index integrates the characteristic ground snow load and an estimation of the associated accuracy, forming a crucial metric for structural engineers. Traditionally, the characteristic ground snow load is determined by fitting a series of yearly maximum ground snow load data to a Gumbel distribution, enabling the extraction of the 50-year return period value. This process traditionally relies on data obtained from weather stations, where meticulous measurements of snow depth are conducted alongside either direct measurements or modeling of snow density. However, the landscape of snow load determination is evolving with the advent of more sophisticated hydrological models. In this context, the paper investigates the impact of transitioning from traditional station data to utilizing gridded simulation data for estimating the characteristic snow load on the ground. The hydrological model "SeNorge" serves as a pivotal tool in this investigation, offering simulated ground snow load data at a 1 km grid. The objective is to scrutinize whether this shift in methodology affects the reliability of buildings and infrastructure subjected to snow loads. The study extends its reach across various climatic zones in Norway, comparing results obtained from the hydrological model with measured data from diverse sources. The fundamental question is whether the adoption of simulated ground snow load data, as generated by advanced hydrological models, translates into a corresponding level of reliability when compared to the established paradigm of utilizing standardized ground snow load data. The results demonstrate a variable uncertainty in the quantification of the snow load depending on the climate region and elevation. When this uncertainty is applied to a reliability calculation a straightforward application of hydrological model may not maintain the same level of reliability as the traditional approach employing standardized ground snow load data. The shift in the structural reliability implies that the partial factors should be adjusted achieve the target reliability criteria when moving from measured to simulated snow load maps. This revelation holds substantial implications for the engineering community, urging a cautious approach to the adoption of newer methodologies in snow load assessments.

How to cite: Thiis, T., Frimannslund, I., Nori, H., and Mustafa, Z.: Quantification of reliability of roofs subjected to snow loadsdetermined by hydrological models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21128, https://doi.org/10.5194/egusphere-egu24-21128, 2024.

EGU24-1197 | ECS | Orals | EMRP1.3

A comparison of exfoliation joint formation mechanisms: what is the role of surface processes? 

Aislin Reynolds, Karl Lang, and Chloé Arson

The formation of granitic domes via exfoliation jointing produces some of the most celebrated and hazardous landforms on Earth. In 1904, G.K. Gilbert outlined three mechanisms to explain exfoliation jointing as: (1) related to the original cooling of the rock body, (2) related to decompression of the rock body as it is exhumed to the surface of the Earth, or (3) related to processes at Earth’s surface - a hypothesis recently supported by observations of thermal cycling in crack initiation and propagation. Despite more than a century of study, our understanding of the mechanisms driving exfoliation jointing remains incomplete. This research seeks to address the question: is the formation of exfoliation joints more sensitive to surface processes (e.g., biotite weathering, thermal cycling), topographic, or regional (i.e. tectonic) stresses? To test this hypothesis, we predicted the orientation of fractures subject to variable geologic conditions with a multi-scale weathering model of damage and fracture propagation implemented in the finite element method. We present predictions resulting from thermal contraction during cooling of the rock body, depressurization during rock exhumation, and regional tectonic compression. We then compare fractures generated under variable topographic stresses, surface weathering processes, and rock geochemistry (i.e., biotite fraction and orientation). By improving our understanding of how significantly pre-existing geologic conditions and rock fabrics influence fracturing, we can work towards disentangling this effect on observed fracture orientations and better interpret paleo-stresses for major tectonic events or potentially paleo-topography. Additionally, enhancing models for weathering mechanics and fracturing in granitic bodies may reveal sensitivities to changes in climate and critical zone evolution, with implications for the forecasting of rockfall hazards in relation to projected temperature and climatic changes.

How to cite: Reynolds, A., Lang, K., and Arson, C.: A comparison of exfoliation joint formation mechanisms: what is the role of surface processes?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1197, https://doi.org/10.5194/egusphere-egu24-1197, 2024.

EGU24-1670 | ECS | Posters on site | EMRP1.3

High-alpine rock slides controlled by pre-existing geological structures and brittle rock mass fracturing 

Reinhard Gerstner, Melina Frießenbichler, Michael Avian, Alexander Maschler, Christine Fey, Gerald Valentin, Markus Keuschnig, Volkmar Mair, Franz Goldschmidt, and Christian Zangerl

Deep-seated, high-alpine rock slides frequently occur in highly schistose, fractured, anisotropic rock masses. Many studies have shown that pre-existing geological structures are decisive for a rock slide’s initiation and kinematics, as they provide weakness zones that may be reactivated in the rock slide process. Besides this structural pre-disposition, internal deformation processes by brittle rock mass fracturing play an important role in the evolution of a rock slide. Nonetheless, the effect of multiscale rock mass fracturing due to the rock slide process is yet to be fully understood. Especially, as it is challenging to measure, characterize, and to numerically model these processes. In our contribution, we present three deep-seated rock slides located in the European Alps in heavily foliated, fractured rock masses with failure volumes above 500.000 m3 each. Focusing on these case studies, we investigate the internal deformation processes with a combined approach, comprising field mapping, laboratory testing, remote sensing, and numerical modelling.

During extensive geological field surveys, we mapped the geomorphological rock slide features and characterized the structural framework of each study site, yielding geometrical models of the rock slides. This provided the basis for our 2D distinct element modelling studies using UDEC, backed by lithological and rock mechanical laboratory investigations.

Whilst UDEC allows for modelling large displacement of blocks bounded by pre-existing discontinuities, it lacks the capability to simulate fracture initiation and propagation of new failure paths within intact blocks, thus neglecting brittle rock mass fracturing. We circumvent this constraint by tessellating the intact rock mass into random polygons – referred to as Voronoi elements. Here, we adapted the original Voronoi technique by assigning an asymmetry to the Voronoi elements, characterized by an elongated axis to consider rock mass anisotropy related to schistosity. By applying this approach, we modelled the fractured, anisotropic, metamorphic rock masses as a combination of pre-existing, field-related structures within a matrix of small, asymmetric Voronoi elements.

In order to confirm the model outputs, we used terrain and deformation data derived from various remote sensing techniques – e.g. satellite based synthetic aperture radar, terrestrial laser-scanning (Riegl VZ 4000) and several campaigns of unmanned aerial vehicle photogrammetry.

In our study, we were able to reproduce the failure mechanism and kinematics of all three rock slides in accordance with our remote sensing deformation data. Thereby, the asymmetric Voronoi tessellation proved to be feasible in reproducing the brittle rock mass fracturing processes in remarkable agreement with our observations in the field. Thus, our results show, how the formation and kinematics of deep-seated rock slides are controlled by the reactivation of pre-existing geological structures and brittle rock mass fracturing. In doing so, our integrated field, laboratory, and numerical modelling approach further contributes to a better understanding of rock slide initiation and kinematics in complex geological media.

How to cite: Gerstner, R., Frießenbichler, M., Avian, M., Maschler, A., Fey, C., Valentin, G., Keuschnig, M., Mair, V., Goldschmidt, F., and Zangerl, C.: High-alpine rock slides controlled by pre-existing geological structures and brittle rock mass fracturing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1670, https://doi.org/10.5194/egusphere-egu24-1670, 2024.

EGU24-3021 | ECS | Posters on site | EMRP1.3

Contribution of programming language to novel mine risk assessment project 

Pieride Mabe Fogang and Bingjie Huo

When excavating a tunnel, the stresses are distributed asymmetrically along the tunnel cross-section. Other factors, particularly slope friction force and excavation speed, can also contribute to the deformation and displacement of a tunnel. Despite this, several authors have used the complex potential method to predict the ground deformation surrounding the tunnel. However, their applicability to the ground response caused by the asymmetric stress distribution around the mine wall is analyzed in this context. This project, therefore, proposes an approximate solution on the slope to predict the mine cross-section deformation. The solution is based on the complex potential method to predict analytically and numerically the ground deformation around the tunnel. However, two variables called the “complex potential functions” for the Laurent series expansion are used for the stress redistribution to the tunnel boundary conditions. Data from the Datong mine case are used to justify the proposed analytical solutions. The solution is an essential guide for analyzing deformations in complex geological conditions and structures, such as steeper slopes.

How to cite: Mabe Fogang, P. and Huo, B.: Contribution of programming language to novel mine risk assessment project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3021, https://doi.org/10.5194/egusphere-egu24-3021, 2024.

Quantifying the changes in elastic properties of rocks during deformation is an important task. Effective Medium Theory (EMT), as formulated by Sayers & Kachanov (1995) relates the crack fabric (or damage) to the elastic properties. EMT has been successfully applied in the forward sense to predict the evolution of elasticity and related acoustic velocities in response to prescribed changes in crack density; and in the inverse sense to recover crack densities from laboratory measurements of acoustic velocities.  However, EMT fails to predict an important observation from laboratory studies of rock deformation: cyclic loading under uniaxial and conventional triaxial loads of rock samples can produce significant increases in Poisson’s ratio. These increases correlate with increasing number of cycles and with increasing crack density. This phenomenon has been known since the work of Walsh (1965), Brace et al. (1966) and Zoback & Byerlee (1975). More recent work by Heap & Faulkner (2008) and Heap et al. (2009; 2010) has extended the findings across a range of different lithologies.

Published EMT equations predict Poisson’s ratios that stay constant or decrease with increasing crack density. Resolving this discrepancy is important because Poisson’s ratio may play a key role in producing stress rotations in the damage zones of faults, thereby making them ‘weak’ and prone to slip even when the normal stress is high e.g. the San Andreas Fault (Faulkner et al., 2006; Healy, 2008). Building on the work of David et al. (2012 & 2020) incorporating the effects of crack closure, sliding on cracks (Kachanov, 1992) and grain boundaries (Sayers, 2018) during loading, and delayed back-sliding during unloading, closed form micromechanical equations have been derived to describe increases of Poisson’s ratio with increasing number of cycles. Critically, increases in Poisson’s ratio are predicted even without including the effects of new cracks. Examples are shown comparing the predicted changes in Poisson’s ratio using the newly derived equations to data from uniaxial and triaxial laboratory tests on cracked rocks.

How to cite: Healy, D.: Increases in Poisson’s ratio due to cyclic deformation in cracked rock, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3893, https://doi.org/10.5194/egusphere-egu24-3893, 2024.

EGU24-5440 | Posters on site | EMRP1.3

Using AE based Machine Learning Approaches to Forecast Rupture during Rock Deformation Laboratory Experiments 

Sergio Vinciguerra, Thomas King, and Philip Benson

Parametric analysis of laboratory Acoustic Emission (AE) during rock deformation laboratory experiments has revealed periodic trends and precursory behaviour of the rupture source, as crack damage nucleates, it grows and coalesces into a fault zone. Due to the heterogeneity of rocks and the different effective pressures, finding a full prediction of rupture mechanisms is still an open goal.

4x10cm cylindrical samples of Alzo granite were triaxially deformed at confining pressures of 5-40 MPa, while AE are recorded by an array of twelve 1MHz Piezo-Electric Transducers. We trained a Time Delay Neural Networks (TDNN) on key seismic attributes derived from AE, such: Event rate, i.e. the negative log time difference between successive events; Amplitude, i.e. the average max amplitude of all waveforms for each single event AE; Source mechanism estimated from first-motion polarity spheres (King et al., JGR, 2021); Seismic scattering, i.e the ratio between high and low frequency peak delays (King et al., GJI, 2022); Vp/Vs ratios from vertical P-wave velocities and horizontal S-wave velocities for individual AE (King et al., GJI, 2023).

These timeseries are then classified by the TDNN as variations in stress and strain (target parameters). TDNN require continuous, regularly sampled data but AE are discrete and irregular. To transform the training data for the TDNN, parameters are smoothed in a weighted moving window of 100 AE events, where weighting is given towards high amplitude events that occur close in space together. Data processing is applied to waveform data from all experimental condition. Despite the inherent complexity in the raw data, clear increasing or decreasing trends are repeated at different experimental conditions.

Hyperparameters for the neural network are optimised using a Genetic Algorithm (GA) by evaluating the misfit between training target (mechanical data) and model output. Each model is trained on the 10 MPa dataset and validated on the 40 MPa dataset. Roles are reversed and the results summed. This approach ensures consistent trends in the training data (waveform parameters) whilst reducing bias towards a particular dataset. We then investigate 120 configurations for the training data following a ‘leave-one-out’ strategy. E.g., a model is trained on 5, 10 and 20 MPa datasets whilst omitting the Event rate parameter. The model is then validated on the 40 MPa dataset.

Model output on validation datasets demonstrate that the TDNN can classify AE-derived parameters as increasing variations in stress and strain. 10 and 40 MPa demonstrate the best fit and are likely linked to the GA optimisation, highlighting biases driven by the training data. Forecasting results for strain and stress reveal notable over- and under-estimations of values. However, both 10 and 40 MPa are generally accurate to within 20% further highlighting the feasibility of using a TDNN for forecasting the development of new fracture under conventional triaxial conditions.

How to cite: Vinciguerra, S., King, T., and Benson, P.: Using AE based Machine Learning Approaches to Forecast Rupture during Rock Deformation Laboratory Experiments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5440, https://doi.org/10.5194/egusphere-egu24-5440, 2024.

EGU24-5553 | Orals | EMRP1.3

Progressive rock failure under different loading conditions – sound and vision 

Ian Main, Maria-Daphne Mangriotis, Alexis Cartwright-Taylor, Andrew Curtis, Ian Butler, Andrew Bell, and Florian Fusseis

Catastrophic failure is the end result of a progression of damage towards brittle failure on a variety of system scales in the Earth. However, the factors controlling this evolution, and the relationship between deformation and the resulting earthquake hazard, are not well constrained.  In particular, induced seismicity is a growing cause of concern in the engineering required for the net-zero carbon transition, including subsurface storage of carbon and geothermal energy production, and mining for critical metals. Here we address the question of how to optimize operational controls to minimize induced micro-seismicity in a ‘scale-model’ laboratory experiment where we can simultaneously image the underlying damage using acoustic emissions (sound) and x-rays (vision). We confirm that using continuous servo-control to maintain a constant acoustic emission event rate slows down deformation compared to standard constant strain rate loading, and demonstrate that it also suppresses micro-seismic events of all sizes, including extreme events, and reduces the proportion of seismic to total strain. We develop a new model to explain these observations, based on the observed evolution of microstructural damage and the fracture mechanics of subcritical crack growth.  The model is validated with high precision (r~99%) by comparison with the independently-observed stress history and acoustic emission statistics.

Qualitative inspection of comparable grey-scale x-ray volumes between the two experiments (peak stress and post-failure after unloading) showed that at peak stress microcrack damage accumulated initially, in both samples and in the same area of each sample, as localised pore collapse, pore-emanating and Hertzian tensile intra- and trans-granular cracks and pore-emanating shear and tensile inter-granular cracks. These features were mostly similar in length and aperture, although the sample loaded only under constant strain rate showed a few longer and more open cracks. Strain localisation was apparent at the same stage in both samples, but there was some evidence of earlier en-echelon microcrack localisation in the sample loaded under a constant strain rate. Post-failure, microcracks were longer and more open in the sample loaded under a constant strain rate than in the sample loaded under a constant AE event rate. The visible proportion of damaged rock was greater, with a broader shear zone around two to three grains wide (compared with <1-2 grains) and a greater degree of cataclasis throughout. Off-fault microcracking was limited, but there were some trans- and inter-granular microcracks that extended up to four to five grains long in both samples. These were more common in the sample loaded under constant strain rate and tended to be more open. Finally, branching of the fault zone appeared to be more pronounced in the sample loaded under a constant strain rate.

Our results explain the effectiveness of seismic event rate control on seismic hazard mitigation in mining settings, and imply that it may be more effective in managing the risk from induced seismicity in a pre-emptive way than the commonly-applied ‘traffic light’ system, which is based on reacting after the fact to extreme events.

How to cite: Main, I., Mangriotis, M.-D., Cartwright-Taylor, A., Curtis, A., Butler, I., Bell, A., and Fusseis, F.: Progressive rock failure under different loading conditions – sound and vision, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5553, https://doi.org/10.5194/egusphere-egu24-5553, 2024.

Macroscopic equilibrium statistical mechanics is first used to interpret and predict thermally driven microfracture in rock. Application of the theoretical framework to three heating and cooling experiments, performed on granite and reported between 1989 and 2017, provides strong evidence that the temperature-, pressure- and volume-dependent average microfracture population within a given rock volume can be treated as an equilibrium thermodynamic variable.  This observation, in turn, suggests that thermoelastic microfracture, in rock and similar granular solids, can be predicted and interpreted using standard, process- and history-independent equilibrium thermodynamics.  In order to place equilibrium rock fracture and healing in context, we then consider nonreversible, permanent, i.e., nonequilibrium fracture. Here, pictorial, physical, and quantitative analyses of several common, thermally driven rock fracture processes are presented, including: a) terrestrial thermal exfoliation of single grains from diurnally heated rock surfaces, b) non-terrestrial thermal exfoliation of thin, near surface rock layers, as recently observed, e.g., on Bennu, c) terrestrial and non-terrestrial thermally-driven through cracking, and d) initiation of c).  We show how the form of the continuum momentum and energy conservation equations for thermoelastic materials – here, rock- provides a powerful, intuitive framework for quickly visualizing and roughly predicting the fracture/weathering processes in a) through d).

How to cite: Keanini, R. and the US, Israel, UK, Japan, France Rock Fracture Collaboration: Equilibrium (reversible) and nonequilibrium (permanent) fracture in rock: equilibrium statistical mechanics theory and experiments, and physical/intuitive analysis of common nonequilibrium fracture modes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7023, https://doi.org/10.5194/egusphere-egu24-7023, 2024.

EGU24-8848 | ECS | Orals | EMRP1.3

Revealing the transition from brittle to ductile failure mode in Carrara marble through in-situ 4D X-ray imaging and acoustic emissions experiments 

Erina Prastyani, Benoît Cordonnier, Jessica McBeck, Lei Wang, Erik Rybacki, Georg Dresen, and François Renard

Rocks exhibit a brittle failure mode, leading to system-size failure through cataclastic faulting processes involving microfracture coalescence and frictional sliding, resulting in localized deformation. In contrast, the ductile failure mode can be described as a distributed deformation at the macroscopic scale, although there may be significant grain-scale heterogeneities. The transition between these two modes is an important research area because it is assumed to occur at the base of the seismogenic zone where large earthquakes may nucleate. Understanding strain evolution and partitioning between brittle and ductile failure modes may shed light on the preparation process for large earthquakes. To investigate the transition from brittle to ductile deformation, we performed two series of experiments on Carrara marble core samples: conventional triaxial experiments with acoustic emission recording at GFZ Potsdam, and dynamic in situ 4D X-ray imaging experiments on beamline BM18 at the European Synchrotron Radiation Facility.  Carrara marble is used as a rock model because this transition can be achieved at room temperature. We performed the experiments at room temperature and confining pressures between 5 and 100 MPa. For the synchrotron experiments, we segmented the images and implemented digital volume correlation (DVC) analyses between tomogram acquisitions to quantify the evolution of volumetric and shear strain components during the transition from the brittle to ductile regime. The results show that the transition is controlled by the dynamics of microfractures, even in the ductile regime. Below 40 MPa of confining pressure, deformation localizes along faults, particularly at 5 and 10 MPa. At 40 MPa, tomograms reveal the formation of a localized shear zone and macroscopically distributed deformation, resembling a semi-brittle regime. The DVC reveals the spatial extent of the strain directed into faults. A limited number of acoustic emissions recorded at this confining pressure revealed the prevalence of aseismic activity during deformation. Above 40 MPa, deformation shifts to a non-localized pattern at the core sample scale, involving the opening of microfractures, possibly due to the cataclastic flow mechanism accommodating this regime.

How to cite: Prastyani, E., Cordonnier, B., McBeck, J., Wang, L., Rybacki, E., Dresen, G., and Renard, F.: Revealing the transition from brittle to ductile failure mode in Carrara marble through in-situ 4D X-ray imaging and acoustic emissions experiments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8848, https://doi.org/10.5194/egusphere-egu24-8848, 2024.

EGU24-9339 | ECS | Orals | EMRP1.3

The role of grain fragmentation in understanding shear localization via DEM simulation 

Nathalie Casas, Guilhem Mollon, and Marco Maria Scuderi

Mature fault zones are formed by abrasive wear products, such as gouge, which results from the frictional sliding occurring in successive slip events. Shear localization in fault gouge is strongly dependent on, among others, fault mineralogical composition and grain size distribution, originating a wide variety of microstructural textures that may be related to different types of fault motion from aseismic creep, slow earthquakes to fast slip events. Within a quartz fault zone, one can encounter different stages of maturity, ranging from an incipient and poorly developed fault zone (i.e. discontinuous and thin gouge layer) to a mature fault zone that has experienced a lot of wear from previous sliding events (i.e. well-developed gouge layer). The localization of deformation within a mature gouge layer has been identified as possibly responsible for mechanical weakening and as an indicator of a change in stability within the fault.

However, to upscale the physics of shear deformation, we need to unveil the physical parameters and micro-mechanisms that govern shear localization. To gain insights on the role of dynamic changes in grain size (i.e. fragmentation), in slip behavior and fault rheology, we performed 2D numerical simulations of quartz fault gouges in a direct shear configuration using the Discrete Element Method (code MELODY). We can reproduce angular particles that can fragment during the simulation as the fault gouge accumulates strain. These experiments were performed to understand the micro-mechanical processes happening during fragmentation and shearing at a constant normal stress. Three mixtures of quartz were sheared to reproduce different initial grain size distributions within the fault (average grain sizes 100 μm, 10.5 μm, and a 50% mixture of both). The minimum grain size was set to 10 μm, meaning that all the coarser particles are subdivided into smaller ones (size 10 μm) that can fragment during the experiment.

Thanks to visual and data outputs, we can observe how particles behave during the compaction and shearing of the gouge. We use four main parameters to describe fault gouge evolution: the damage of coarse particles, the force chains, the change of porosity, and the kinetic energy linked to each particle breakage. Moreover, these numerical experiments were designed to reproduce and be directly compared with shear experiments realized on a double direct shear apparatus in the Laboratory (Casas et al., in prep). The fragmentation algorithm in the code can reproduce the shear localization observed within the real quartz microstructures and the progressive formation of Riedel bands. The connection between numerical and laboratory experiments gives important information on the connection between grain size distribution, shear localization, Acoustic Emissions, and the resulting fault slip behavior. In this context, the proportion between small/coarse particles within the fault plays an important role in controlling fault rheology.

How to cite: Casas, N., Mollon, G., and Scuderi, M. M.: The role of grain fragmentation in understanding shear localization via DEM simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9339, https://doi.org/10.5194/egusphere-egu24-9339, 2024.

EGU24-9811 | ECS | Posters on site | EMRP1.3

Multi-scale experimental deformation and damage initiation of clay-rich rocks  : Coupling ultrasonic wave propagation and  full field deformation measurements by digital image correlation (DIC) 

Matthieu Lusseyran, Alexandre Dimanov, Audrey Bonnelye, Jérôme Fortin, and Alexandre Tanguy

Understanding the damage processes in clay-bearing rocks is a decisive factor in geological engineering, and for instance considering nuclear waste deep geological repositories. But, more generally they may also contribute to localized deformation, and thus the rupture of fault gauges in seismic zones. However, owing to their complex mineralogy, multiscale microstructures and anisotropy, the mechanisms of clay-rich rock damage and their chronology are not yet well understood..

Here we focus on the impact of micro-damage on ultrasonic wave propagation velocity, which is confronted with the corresponding full deformation fields calculated by digital image correlation (DIC). 

The aim is to associate the acoustic signature with the active deformation mechanisms identified by DIC. To this end, an integrated experimental approach is proposed to  characterize localization and to identify the related deformation micro-mechanisms  during uniaxial compression of natural clayey rock samples (Tournemire shales) with two simultaneous measurements: 1) the evolution of P-wave velocity within the sample by active acoustics, 2) the development of the 2D mechanical full field by digital image correlation.

Both experimental techniques are well known, but the innovation of our approach is to combine simultaneously both measurements. Deformation localization is a multiscale problem, which obviously occurs at the sample scale, but also at the fines scales of the microstructure. Therefore, we developed two different experimental setups. On the one hand, during uniaxial compression with a standard MTS loading frame the macro-scale localization patterns are characterized by optical observations, which image resolution is well suited to the cm sample scale (sample diameter: 3.6 cm and double in length). On the other hand, in order to characterize the initiation of micro-damage at the microstructure scale of the composite type of rock, the same loading protocol is reproduced (while keeping the acoustic diagnosis) on smaller scale mm-sized specimens (sample diameter : 8 mm, double in length), using a home-designed miniature loading frame fit for an environmental scanning electron microscope (ESEM). The latter analysis is carried out under  controlled relative humidity  of RH = 80%, hence preventing the samples to dry out due to the high vacuum

A similar acoustic signature is identified at both scales of observation, in spite of the variations of experimental conditions imposed by the environmental SEM. We are therefore confident to be able to understand the fracturing process from micro-cracking initiation (microscale) to sample failure (macroscale), and to assess its impact on ultrasonic wave propagation.

How to cite: Lusseyran, M., Dimanov, A., Bonnelye, A., Fortin, J., and Tanguy, A.: Multi-scale experimental deformation and damage initiation of clay-rich rocks  : Coupling ultrasonic wave propagation and  full field deformation measurements by digital image correlation (DIC), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9811, https://doi.org/10.5194/egusphere-egu24-9811, 2024.

EGU24-9825 | Orals | EMRP1.3

Temperature “Memory” and Natural Rock Fracture at Earth’s Surface 

Martha-Cary Eppes, Christian David, Mike Heap, Patrick Baud, Thomas Bonami, Maxwell Dahlquist, Russell Keanini, Cyril Lacroix, Monica Rasmussen, Alex Rinehart, Youness El Alaoui, and Adrien Windenberger

Rock physics theory and experimental data suggest that fracture growth in rock proceeds not only as a function of synchronous stress and environmental conditions but also as a function of past fracture growth in response to those conditions. ‘Stress memory’ or ‘fatigue-limit’ fracture mechanics phenomena such as the Kaiser effect epitomize this idea. Many questions exist, however, as to if and how these phenomena impact the growth of fractures under natural environmental conditions. For example, to what extent does the orientation of past experienced stresses manifest in a rock’s response to stresses of the same magnitude?

Here we test for a memory of intergranular thermal stresses in two natural granite boulders of the same lithology for which we have 1 and 3 years of known temperature history, respectively. We hypothesize that cores extracted from the exterior portions of the boulders – that have necessarily experienced more and larger temperature fluctuations – will have more ‘memory’ of peak temperatures than those cores extracted from the boulder centers. In turn, we hypothesize that outer cores will crack less in response to temperature cycling than inner cores. For the first boulder, we measured P-wave velocities and connected porosities before and after 4 different oven heat treatments – heating up to 40, 45, 50 and 65 °C at a rate of at 20 °C/hr and cooling at an ambient rate over several cycles each. For two transects of cores extracted from the natural upward facing surface down, and the natural west-facing surface inward, we found that porosities increased after each subsequent heat treatment, but by larger amounts with distance away from the outer rock surface, as hypothesized. P-wave velocities, however, both increased and decreased with different heating cycles and positions. Therefore, for the second boulder, we extracted a top-down transect of 5 cores and, using a special-made rig, found that the samples exhibit significant P-wave velocity directional anisotropy. We subjected these cores to the same heat treatments as those of the first boulder, but this time orienting the samples identically in the oven with respect to their original positions in the boulder. Preliminary data show similar results as the first boulder, with the outermost core cracking the least (as interpreted from porosity changes) relative to the inner cores. Ongoing work will examine changes in P-wave velocity in different directions relative to measured anisotropy as a function of heat treatment cycles. This work has important implications for understanding if and how, with ongoing global warming, Earth’s rocks will respond to ‘new’ temperatures. 

How to cite: Eppes, M.-C., David, C., Heap, M., Baud, P., Bonami, T., Dahlquist, M., Keanini, R., Lacroix, C., Rasmussen, M., Rinehart, A., El Alaoui, Y., and Windenberger, A.: Temperature “Memory” and Natural Rock Fracture at Earth’s Surface, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9825, https://doi.org/10.5194/egusphere-egu24-9825, 2024.

EGU24-10099 | Posters on site | EMRP1.3

Multiscale experimental investigation of crystal plasticity and grain boundary sliding in rock salt using digital image correlation 

Xinjie Li, Alexandre Dimanov, Michel Bornert, Simon Hallais, and Hakim Gharbi

In the context of the global environmental crisis and the urgent need for energy transition and efficient energy storage solutions, salt caverns have gained attention as promising reservoirs for hydrogen. However, current literature predominantly focuses on deriving macroscopic constitutive relations, lacking crucial insights into the underlying physical mechanisms of deformation and damage active at various microscopic scales. This study addresses this gap by undertaking qualitative and quantitative investigations into the micro-mechanisms of rock salt, employing advanced micro-scale observation techniques. Natural rock salt from diverse mines and re-synthetic salts, produced through the cold compaction of grinded natural halite powder, are used to encompass a wide range of microstructural morphologies. Initial microstructure characterization involves SEM, EBSD, and CT, followed by classic uniaxial compressive tests coupled to optical microscopy monitoring. High-resolution images of the sample surface are continuously captured during testing, allowing for 2D full field measurements by subsequent application of digital image correlation techniques : the analysis of relative displacements of markers randomly distributed on the sample surface enables the retrieval of surface displacement fields and the calculation of the corresponding local strain fields over statistically representative domains. Segmentation of digital images and quantitative identification, specifically focusing on crystal slip plasticity and grain boundary sliding using an in-house computation program, reveal the complex local interactions of different micro-mechanisms. The estimation of the relative contributions of these mechanisms to global deformation all along the loading path, along with an analysis of the impact of salt grain size, provides insights into physically grounded micromechanical constitutive relations. These findings are essential for the safety assessment of industrial applications involving rock salt caverns with respect to short-term mechanical loading conditions relevant to daily hydrogen filling and withdrawal.

How to cite: Li, X., Dimanov, A., Bornert, M., Hallais, S., and Gharbi, H.: Multiscale experimental investigation of crystal plasticity and grain boundary sliding in rock salt using digital image correlation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10099, https://doi.org/10.5194/egusphere-egu24-10099, 2024.

EGU24-10753 | ECS | Orals | EMRP1.3

Non-linear softening and relaxation in rocks and geomaterials: a laboratory perspective 

Manuel Asnar, Christoph Sens-Schönfelder, Audrey Bonnelye, Georg Dresen, and Marco Bohnhoff

In rocks and other consolidated geomaterials, static or dynamic excitation leads to a fast softening of the material, followed by a slower healing process in which the material recovers all or part of its initial stiffness as a logarithmic function of time. This requires us to exit the framework of time-independent elastic properties, linear or not, and investigate non-classical, non-linear elastic behavior and its time dependency. Softening and healing phenomena can be observed during seismic events in affected infrastructure as well as in the subsurface. Since the transient material changes are not restricted to elastic parameters but also affect hydraulic and electric parameters as well as material strength – documented for instance by long lasting changes in landslide rates – it is of major interest to characterize the softening and recovery phases.

To characterize this behavior in a controlled environment, we perform experiments on Bentheim sandstone in a Materials Testing System triaxial cell with pore pressure and confining pressure control. Our sample is subjected to various static loading cycles in both dry and water-saturated conditions, while an active acoustic measurement setup allows us to monitor minute P-wave velocity changes, which can then be directly tied to dynamic elastic modulus changes.

Our transducer array allows us to observe the dynamic softening as well as the recovery processes in the sample during repeated loading phases of various time lengths. Observations indicate high spatial, frequency and lapse-time sensitivity of the observed velocity changes, indicating a rich landscape of concurrent effects and physical phenomena affecting our sample during these simple experiments.

To investigate the spatial and directional dependency of the velocity changes, we restrict the analysis to direct and reflected ballistic waves. Our observations indicate that, while stress-induced classical effects are clearly anisotropic as expected, the non-classical effects do not exhibit significant anisotropy. This allows us to rule out a number of physical phenomena as the cause for the non-classical effects. Most importantly, we conclude that the microscopic structures responsible for the reversible softening and healing processes are different from the cracks that induce the anisotropic acousto-elastic effect.

How to cite: Asnar, M., Sens-Schönfelder, C., Bonnelye, A., Dresen, G., and Bohnhoff, M.: Non-linear softening and relaxation in rocks and geomaterials: a laboratory perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10753, https://doi.org/10.5194/egusphere-egu24-10753, 2024.

EGU24-11304 | ECS | Orals | EMRP1.3

Frost damage in unsaturated porous media 

Romane Le Dizes Castell, Rosa Sinaasappel, Clémence Fontaine, Scott Smith, Paul Kolpakov, Daniel Bonn, and Noushine Shahidzadeh

Frost damage in porous materials is a weathering mechanism that can cause dangerous rockfalls or damage to built cultural heritage. The volume expansion of 9% when water freezes can be one of the cause of frost damage. This does not, however, explain why partially saturated porous stones also show damage despite the fact that ice should have room to grow. By performing experiments both at the scale of a single pore and in a real stone, we investigate the mechanism of frost damage at low water saturations at the pore scale and how it relates to macroscopic damage. We observe that the meniscus at an air-water interface confines the water in the pores. Because of this confinement, ice that forms will exert a pressure on the pore walls rather than growing into the pore. The amplitude of stress is found to be larger in small pores and when the meniscus has a larger contact angle with the walls. The contact angle is also observed to increase in the case of multiple freeze-thaw cycles, which increases the likelihood of damage. We find that cracks start first in the ice (being weaker than the confining material), followed by damage in the material itself. Remarkably, when multiple air-water interfaces are induced within limestone samples through a hydrophobic surface treatment, the stones are much more susceptible to frost damage than are uncoated stones, with cracks appearing preferentially at the hydrophilic-hydrophobic interface. This shows that indeed the meniscus confining the water during freezing and consequently the wetting properties are the relevant factors for frost damage in partially saturated porous stones

Reference: R. Le Dizès Castell, R. Sinaasappel, C. Fontaine, S. H. Smith, P. Kolpakov, D. Bonn, and N. Shahidzadeh, “Frost Damage in Unsaturated
Porous Media,” Physical Review Applied, vol. 20, p. 034025, Sept. 2023.

How to cite: Le Dizes Castell, R., Sinaasappel, R., Fontaine, C., Smith, S., Kolpakov, P., Bonn, D., and Shahidzadeh, N.: Frost damage in unsaturated porous media, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11304, https://doi.org/10.5194/egusphere-egu24-11304, 2024.

EGU24-13010 | ECS | Posters on site | EMRP1.3

The influence of fluid pressure on the phase transition of brittle faulting 

Hao Chen, Paul Selvadurai, Antonio Salazar, Patrick Bianchi, Sofia Michail, Markus Rast, Claudio Madonna, and Stefan Wiemer

Recent observations of large earthquakes document the progressive localization of rock damage around future rupture zones that is also coupled with the spatial migration of foreshock sequences (Kato & Ben-Zion, 2020). This implies that the precursory deformation may act as a potential tracer for preparatory process that result in large earthquakes. It has also been observed that self-organization of the localized damage regions can govern the eventual macroscopic brittle failure in geomaterials (Renard et al., 2019). How the presence of fluid controls the self-organized precursory deformation along localized damage zone remains an open question. In this study, we have performed two triaxial compression experiments on dry and water saturated Berea sandstone, using distributed strain sensing (DSS) technology to visualize the strain field on the sample surface (Salazar Vásquez et al., 2022) with high spatial resolution. By tracking components of the strain field, specifically the region on the sample that sustained the largest incremental change in strain, we tested the effect of fluid on the predictability of phase transition between intact and failed state, under the context of critical hypothesis. Strain was progressively localized around the eventual faulting region for both samples, while a slow faulting was observed in the wet sample accompanied by a diffuse deformation pattern and unstable crack nucleation at failure. The results showed that, the failure in the dry sample was preceded by a critical power law acceleration of the largest increment, thus the dynamic faulting occurred in a well-defined singularity. The strain distribution also provided evidence for a predictable evolution of precursors. In contrast, the wet test showed evidence for a first-order transition with an exponential increase in largest increment, leading to an abrupt failure with a transient increase of strain. We interpreted this abrupt transition to be due to the increasing dominance of fluid-driven subcritical crack growth in the faulting. In this process, the local stress at crack tips decreases with crack lengthening, hence impeding the crack interaction and leading to an abrupt development of fault network. Our observation unravels the mechanisms of precursory deformation with fluid-assisted subcritical cracking, which has important implication in forecasting large earthquakes in nature.

 

References:

Kato, A., & Ben-Zion, Y. (2020). The generation of large earthquakes. Nature Reviews Earth & Environment, 2(1), 26–39. https://doi.org/10.1038/s43017-020-00108-w

Renard, F., McBeck, J., Kandula, N., Cordonnier, B., Meakin, P., & Ben-Zion, Y. (2019). Volumetric and shear processes in crystalline rock approaching faulting. Proceedings of the National Academy of Sciences, 116(33), 16234–16239. https://doi.org/10.1073/pnas.1902994116

Salazar Vásquez, A., Rabaiotti, C., Germanovich, L. N., & Puzrin, A. M. (2022). Distributed Fiber Optics Measurements of Rock Deformation and Failure in Triaxial Tests. Journal of Geophysical Research: Solid Earth, 127(8). https://doi.org/10.1029/2022JB023997

How to cite: Chen, H., Selvadurai, P., Salazar, A., Bianchi, P., Michail, S., Rast, M., Madonna, C., and Wiemer, S.: The influence of fluid pressure on the phase transition of brittle faulting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13010, https://doi.org/10.5194/egusphere-egu24-13010, 2024.

EGU24-13669 | Orals | EMRP1.3

Laboratory measurement of subcritical crack growth and healing in calcite using Double-Torsion tests 

Seiji Nakagawa, Yida Zhang, Hooman Dadras, Zhao Hao, Anne Voigtländer, and Benjamin Gilbert

Subcritical crack growth accelerates weathering of rocks and minerals, reduces the strength of rock slope, and affects the stability of subsurface faults. Under special circumstances, the produced cracks can also heal spontaneously (Self healing) regaining a part of the original tensile strength.  These crack behaviors are a manifestation of molecular-scale surface forces acting between the surfaces near the crack tip. As a part of the effort to understand how these forces control the subcritical crack growth and healing of geological materials, we examine the tensile crack behavior of calcite single crystals. A miniature Double-Torsion (DT) test system was developed for testing small plate samples (40 mm x 20 mm x 1.5 mm) cut out of optical-quality calcite single crystals (Iceland Spar crystals). These samples are oriented in such a way that the induced crack is along the (1014) plane (the primary cleavage plane). The main output of the experiment is the crack velocity (vc) vs the magnitude of applied driving force (stress intensity factor K or strain energy release rate G), which is a typical way to summarize the rate-dependent crack behavior. From the experiment, we have learned that (1) calcite exhibits strong healing behavior compared to materials such as glass or (amorphous) quartz in humid air and water, (2) healing is time dependent (the strength of a healed crack increases over time), (3) liquid water (rather than vapor) introduces strong hysteresis in the recracking vs healing behavior.   The obtained laboratory data are used to develop a mechanistic model for predicting macroscale crack behavior in rock, particularly in a water and electrolyte-rich environment.

How to cite: Nakagawa, S., Zhang, Y., Dadras, H., Hao, Z., Voigtländer, A., and Gilbert, B.: Laboratory measurement of subcritical crack growth and healing in calcite using Double-Torsion tests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13669, https://doi.org/10.5194/egusphere-egu24-13669, 2024.

EGU24-13927 | Orals | EMRP1.3

Strain history of the Pioneer fault, Idaho, USA – progressive deformation and associated crystallographic alteration. 

Elizabeth Petrie, Bradford Burton, Kelly Bradbury, and Genna Baldassarre

In south-central Idaho, a segment of the Pioneer fault, exposed at Little Fall Creek, has accommodated large magnitude Mesozoic shortening overprinted by Paleogene extension. The resulting 30 m thick fault damage zone records a history of fault reactivation and associated deformation in quartz veins, graphite concentration on slip surfaces, polyphase contractional and extensional microstructures, and micro- to outcrop-scale corrugated, mineralized and polished slip surfaces. The gently west dipping (207°/14°) fault zone separates Ordovician argillite in the hanging wall from Mississippian argillite and quartzite in the footwall and accommodated east-northeast directed shortening. However, polished slip surfaces within the fault zone document top-to-the-west translation with a mean slip vector 15°/272°, consistent with extensional unroofing of the Pioneer Mountains core complex.

Argillite in the fault damage zone varies from proto- to ultra-cataclasite and provides evidence for overprinting of contractional fabrics by extensional fabrics. The fault damage zone is characterized by multiple anastomosing slip-surfaces which indicate a history of slip surface interactions, fault growth, and reactivation. Early deformation features include graphitic foliations and stylolites, SC foliations, and ptygmatic folds consistent with shortening. Quartz veins, mica fish, and slip surfaces coated with graphite, amorphous carbonaceous material, and amorphous quartz phases, overprint the early deformation features and are associated with west-directed extension. Hydrothermal quartz veins that show at least five phases of deformation indicate multiple strain episodes and high strain rates. Raman spectroscopy and scanning electron microscope textural analysis of the graphite in the fault damage zone show a loss of crystallinity toward the primary slip surface. We infer the late-stage meso- to micro-scale features record seismic slip and fluid-rock interactions in a gently dipping fault zone.

How to cite: Petrie, E., Burton, B., Bradbury, K., and Baldassarre, G.: Strain history of the Pioneer fault, Idaho, USA – progressive deformation and associated crystallographic alteration., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13927, https://doi.org/10.5194/egusphere-egu24-13927, 2024.

EGU24-14362 | Posters on site | EMRP1.3

Salt-driven Progressive Fracturing of Alluvial Boulders Along the Hyper-arid Shoreline of the Dead Sea  

Amit Mushkin, Ronen Boroda, Uri Malik, Nadav Lensky, Eyal Haggai, Boris Muravin, and Rivka Amit

Rock weathering is ubiquitously observed at or near Earth’s surface as a fundamental component in many landscape evolution process. In arid landscapes, where limited moisture availability restricts the rate and effectiveness of chemical and biological weathering – salt weathering (regarded herein as the physical disintegration of rocks in the presence of salts) is commonly acknowledged as an especially effective mechanism for progressive weathering of rocks. While volumetric expansion and contraction of salts in response to changes in ambient moisture conditions are broadly recognized as the primary drivers of salt weathering, our understanding of the environmental conditions that produce such moisture dynamics in otherwise extremely dry settings, such as hyper-arid deserts, remains largely unknown.

Here, we present preliminary results from field-based acoustic emission (AE) measurements for boulders with salt-laden cracks perched on abandoned shorelines of the hypersaline Dead Sea. Continuous measurements since April 2023 revealed daily fracturing activity displaying a bi-modal distribution with AE activity peaks during the early predawn and afternoon hours when T changes are minimal and RH fluctuations reach maximum or minimum values, respectively. Time-lapse photography revealed a recurring pattern of salts that crystalize along the rock cracks during the afternoon AE peak hours and subsequently disappear towards the predawn AE peak hours. The appearance of salt crystals during lowest RH conditions (warmest afternoon hours) and their disappearance during highest RH conditions (coldest predawn hours) suggests that stresses induced by repeated cycles of salt deliquescence/efflorescence in response to daily fluctuations in atmospheric RH are most likely responsible for the bi-modal distribution of daily fracturing activity. This suite of new field-based measurements of salt-weathering activity in natural hyper-arid settings suggests that atmospheric RH fluctuations and the volumetric changes they induce in hygroscopic salts can be key drivers of progressive rock fracturing in extremely dry and salt-rich environments on Earth and possibly Mars where other moisture sources are limited to effectively non-existent.

How to cite: Mushkin, A., Boroda, R., Malik, U., Lensky, N., Haggai, E., Muravin, B., and Amit, R.: Salt-driven Progressive Fracturing of Alluvial Boulders Along the Hyper-arid Shoreline of the Dead Sea , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14362, https://doi.org/10.5194/egusphere-egu24-14362, 2024.

EGU24-16652 | ECS | Posters on site | EMRP1.3

Time- and stress-dependent elastic properties in a concrete structure; spotting internal damage footprints 

Marco Dominguez-Bureos, Celine Hadziioannou, Ernst Niederleithinger, and Christoph Sens-Schönfelder

Time- and stress-dependency of elastic properties are features particularly observed in a variety of complex solids, ranging from steel, polymers, and cracked structures, to rocks and concrete. Recently, considerable effort has been made to understand the underlying physics of these phenomena commonly regarded as Nonlinear Mesoscopic Elasticity (NME) in laboratory setups.

As a result, various models have been suggested to explain a range of NME phenomena like hysteresis, dynamic softening, and slow dynamics, among others. Due to the high sensitivity of NME to the presence of imperfections or internal damage on solids, there is a growing interest in taking the current models and applying them to construction materials for damage assessment.

Intending to observe and incorporate these models into real-condition structures, we carried out a 1-day multifrequency vibration experiment in a 24-meter-long reinforced concrete test bridge equipped with a pretension system, to investigate the possible presence of internal damage with vibration-based methodologies.

We used the pretension system to subject the specimen to eight compression states in its longitudinal direction (forces of 400kN at the highest, and 280kN at the lowest). At every compression state, we struck the structure in the vertical direction three times on the north and south sides of the bridge with an impulse drop weight. Throughout the whole experiment, we recorded ambient seismic noise at different frequency bands with a 14-six-component sensor array to measure the acceleration in the conventional translational components and the angular velocity (rotation rate), a 14-geophone array of 4.5 Hz of natural frequency, and four pairs of embedded ultrasound transducers were used to estimate relative velocity changes (dv/v) by applying the Coda Wave Interferometry (CWI) stretching technique. internal temperature of the concrete was also recorded to correct our measurements by first-order thermal effects.

At the material scale (ultrasound regime) we observe stress-dependent dv/v at four different locations in the specimen and describe them by using the acoustoelastic effect concept regarded as a classical nonlinear phenomenon. We also analyze the relative velocity drop and the subsequent healing process in the concrete triggered by the action of the drop weight. We used the model of Snieder and Sens-Schönfelder (2017) to numerically describe the relaxation process happening at different time scales in the specimen through a deterministic inversion procedure. The north side of the structure showed to have a higher acoustoelastic effect and higher velocity drops, as well as longer relaxation times, it is important to mention that there is evidence of external cracking in this span of the bridge.

We present preliminary results in the seismic frequency band (structural scale), where we expect to observe the influence of the vertical beams that support the bridge on the spatial distribution of changes in dv/v. Changes in the fundamental frequency of the structure as a function of the stress level are also expected.

With this work, we point towards the development of new nondestructive testing methodologies highly sensitive to small cracks and imperfections using conventional and non-conventional seismic instruments, and linear and nonlinear wave propagation models.

How to cite: Dominguez-Bureos, M., Hadziioannou, C., Niederleithinger, E., and Sens-Schönfelder, C.: Time- and stress-dependent elastic properties in a concrete structure; spotting internal damage footprints, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16652, https://doi.org/10.5194/egusphere-egu24-16652, 2024.

EGU24-16840 | Posters on site | EMRP1.3

Are all lineaments the surface expression of faults and fractures? – A novel analysis using tunnel face mapping data from Norwegian road tunnels 

Espen Torgersen, Karoline Arctander, Thomas F. Redfield, Anne Kathrine Svendby, Anna Maria Dichiarante, and Mari Lie Arntsen

Lineaments are elongated elements in spatial data such as valleys and ridges on topographic maps, or linear lows and highs in aeromagnetic data. Topographic linear depressions (topolineaments) are generally considered as the morphological expressions of easily erodable, elongated rock bodies situated within a mechanically stronger rock mass. In most circumstances topolineaments are even directly interpreted as faults and fractures, which forms the basis for lineament analysis study to understand brittle deformation patterns. However, topolineaments may also be formed by other tectonic and non-tectonic causes, such as alternating layers, foliation traces, dikes etc., or river- and glacial erosion not controlled by any bedrock features. This mix of potential causes begs the question: “How robust is actually lineament analysis for characterizing and quantifying faults and fractures?”. Testing the topolineament vs. fracture-relationship is not straight forward since topolineaments are usually occupied by rivers or creeks and covered with colluvium, which prevents direct observation of rock types and bedrock structures.

Underground excavations allow for continuous logging of bedrock types, rock mass quality and fracture density and orientations, which is done routinely at tunnel face during tunnel construction. Here we make use of such underground data from a large dataset of Norwegian road tunnels to compare the position of topolineaments spatially and statistically with rock fracture density and orientations in the subsurface. The tunnel dataset comprises data from across Norway in areas with widely varying bedrock geology, tectonic evolution, and geomorphology (e.g. etched surface, alpine, lowlands), which allow for an evaluation of the robustness of lineament analysis in various settings. Topolineaments are acquired using a newly developed algorithm (OttoDetect) run on both 10x10m and 50x50m resolution digital elevation models. The algorithm ensures that tunnel data is compared to a homogeneous and reproducible lineament dataset without operator or hillshade illumination biases.

Preliminary results from tunnels in areas with etched geomorphology show that c. 75% of all topolineaments correspond to weakness zones in the bedrock (i.e. very high fracture densities/very low rock mass quality compared to the surroundings). Hit rate increases for longer lineaments, which generally correspond to thicker fault zones. At the same time, only up to c. 60% of all weakness zones mapped at tunnel face can be spatially associated to a topolineaments, which demonstrate that significant brittle deformation is not expressed as topolineaments. Further analysis will be carried out to build a statistically robust dataset on the validity of lineament analysis.

How to cite: Torgersen, E., Arctander, K., Redfield, T. F., Svendby, A. K., Dichiarante, A. M., and Arntsen, M. L.: Are all lineaments the surface expression of faults and fractures? – A novel analysis using tunnel face mapping data from Norwegian road tunnels, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16840, https://doi.org/10.5194/egusphere-egu24-16840, 2024.

NH4 – Earthquake Hazards

The Fracture-Induced Electromagnetic Radiation (FEMR) phenomenon has been substantially investigated as a prolific geophysical tool and provided a precursor to geohazards such as landslides, earthquakes, and rockburst hazards. Several lab-scale experiments on materials such as chalk, rocks, glass, ceramics, granite, etc., have been conducted to correlate between experimental observations and theoretical formulations of the physical parameters of FEMR generations such as crack dimensions, crack velocity, frequency of crack propagation, and finally draw an analogy with earthquake events. The FEMR working principle for Earth’s fracture detection is based on generating geogenic electromagnetic radiation from the brittle rock bodies subjected to differential stress in the near-surface of the Earth’s crust. When external stimuli, such as significant deviatoric stresses in thrust or shear zones due to active tectonic forces, induce stress on these rock bodies, microcracks form and propagate. The "Process zone" at the crack tip contains numerous microcracks and dipoles that emit FEMR waves in the kHz to MHz frequency range. As microcracks coalesce and lead to macro failure, the amplitude of FEMR pulses diminishes. FEMR pulses show less attenuation than seismic waves, making them a more efficient precursor to potential tectonic activities. They are an early warning sign for earthquakes a few hours or days before the event. The current study consisted of FEMR surveys along a segment of the active Dead Sea transform (DST) from Sodom to Jericho. This coincided with a 6.3 magnitude (Mw) aftershock earthquake (EQ) in the Turkey-Syrian region on February 20, 2023, where the last measurement was taken 2 hours before the EQ. Several FEMR parameters (e.g., Benioff strain release, frequency, rise time, hits or activity, and energy) along with their associated crack dimensions were analyzed after filtering the raw data and comprehending their trends leading up to the EQ. This study investigated the Benioff Strain plot and other parameters in three consecutive stages of earthquake nucleation leading to the EQ. In the first stage, there's an increase in FEMR hits and frequency, accompanied by a decrease in rise time (T') and crack dimensions. The second stage is characterized by a decline in FEMR hits and crack width while all continue to increase. Notably, the second stage accumulates the second highest energy, likely due to a high-stress drop. The third stage features a steady increase in FEMR hits and energy and an abnormal increase in crack dimensions, perhaps signifying an upcoming event of macro failure. The cyclic trend in FEMR hits suggests periods of high activity and silence, possibly related to stress changes during crack propagation. Because the measurements were taken a few hours before the earthquake, this survey provides valuable insights into the modulation of FEMR parameters before an earthquake. The results obtained from this analysis could bridge the gap between lab-scale and large-scale studies of stress-induced rock collapses and provide a befitting precursor to such disastrous natural calamities.

How to cite: Das, S. and Frid, V.: The Fracture Induced Electromagnetic Radiation (FEMR) induced along the Dead Sea Transform fault before the Syrian-Turkey earthquake (Mw-6.3) on 20.2.2023, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-360, https://doi.org/10.5194/egusphere-egu24-360, 2024.

This study investigates the early seismo-ionospheric signals preceding the 7.8 magnitude Turkey earthquake sequence on February 6, 2023. The main shock struck at 01:17:35 UTC in Şehitkamil, Gaziantep in southern Turkey near the northern border of Syria. About nine hours later, a strong 7.5 magnitude aftershock occurred to the northeast of the first main quake.

The present work is based on the analysis of the ionospheric behavior in response to these successive major earthquakes, using space-based GPS/GNSS (Global Positioning System/Global Navigation Satellite Systems) data. Employing geodetic data derived from both Turkish national (TUSAGA) and international (IGS) permanent receivers, we generated a local ionospheric map covering the seismogenic zone of southern Turkey. The aim is to reconstruct the time series of ionospheric Total Electron Content (TEC) and discern any potential anomalies in this signal. The diurnal variation of the ionospheric TEC shows homogeneity in the spatiotemporal pattern of the GNSS_TEC signal, except for January 12, 2023. At noon on this day, the ionospheric TEC reaches its maximum value (98.41 TECu), exceeding 250% of the mean value in the temporal series. This anomalous behavior prompted application of a robust statistical approach to exclude outliers, combined with wavelet transform analysis to capture the time-frequency characteristics of the ionospheric responses. These steps validated the results, indicating a potential seismic influence on the ionosphere approximately three weeks before the mainshock.

This research represents an important step to understanding seismo-ionospheric interactions, highlighting the complex relationship between crustal motions and ionospheric dynamics. Anomalies identified in the ionosphere prior to the major seismic event in Turkey suggest that the approach developed could be promising for predicting earthquakes. Further validation and collaboration are essential to refine these results and advance seismic risk assessment.

Keywords: 2023 Turkey earthquake, GPS/GNSS-TEC data, Pre-earthquake ionospheric anomaly, Crustal-Ionospheric Synergy.

How to cite: Tachema, A.: Exploring early seismo-ionospheric signs preceding the February 6, 2023, Turkey earthquake (Mw 7.8): Preliminary results, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2942, https://doi.org/10.5194/egusphere-egu24-2942, 2024.

EGU24-3264 | Orals | NH4.1 | Highlight

6 years results of EQ precursors research by using CSES-01 onboard and the following step of  IMCP  

Xuhui Shen, xuemin zhang, zhima Zeren, Shufan Zhao, Qinqin Liu, Roberto Battiston, Angelo De Santis, Tiger Liu, Valerio Tramutoli, Livio Conti, and Rui Yan
As the first geophysical field observation satellite mission in China, CSES-01 has been operating in orbit for six years and, based on its optimal performance, it will prolong its life after CSES-02's launch in orbit in order to partly overlap the two missions. In retrospect, CSES-01 acquired an amount of data such as geomagnetic field, low-frequency electromagnetic waves, in-situ plasma content, and temperature, charged particles as well ionospheric plasma, while more than 70 M7+  and 700 M6+  earthquakes  have been recorded in the globe, together with a series of space weather and volcano phenomena. 
The large amount of data collected has provided new ground for in depth exploration on statistical analysis of earthquake precursors as well as providing clear evidence for the feasibility of space-based co-seismic observation, helping the development of quantitative modeling of the Lithosphere-Atmosphere-Ionosphere Coupling mechanism focusing on its atmospheric and electromagnetic wave channel.
The following prospect plan, CSES-02, is under development by China-Italy joint team and is due to launch in 2024, which means that we will have two CSES satellites simultaneously in orbit from 2024. Such an increase in observational capabilities will strongly support the implementation of multi-parametric observation systems, both from the ground and from satellites, capable of significantly improving precision and reliability of earthquake forecasts. In addition, the new International Meridian Circle Project  (IMCP)   will be implemented as a ground-based observation network with its primary objectives of monitoring the geomagnetical field, space weather, and interaction among Lithosphere-Atmosphere-Ionosphere. The main tasks of IMCP are global data sharing, joint research on space weather and natural hazards, global change, and many other science fields. 

How to cite: Shen, X., zhang, X., Zeren, Z., Zhao, S., Liu, Q., Battiston, R., De Santis, A., Liu, T., Tramutoli, V., Conti, L., and Yan, R.: 6 years results of EQ precursors research by using CSES-01 onboard and the following step of  IMCP , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3264, https://doi.org/10.5194/egusphere-egu24-3264, 2024.

EGU24-6001 | Orals | NH4.1

Investigation of VLF/LF electric field variations related to magnitude Mw≥5.5 earthquakes in the Mediterranean region for the year 2023 

Hans Eichelberger, Mohammed Y. Boudjada, Konrad Schwingenschuh, Bruno P. Besser, Daniel Wolbang, Maria Solovieva, Pier F. Biagi, Patrick H. M. Galopeau, Ghulam Jaffer, Christoph Schirninger, Aleksandra Nina, Gordana Jovanovic, Giovanni Nico, Manfred Stachel, Özer Aydogar, Cosima Muck, Josef Wilfinger, Irmgard Jernej, and Werner Magnes

Strong natural hazards together with their societal impact are usually accompanied by multiple physical phenomena which can be an important information source about the underlying processes.  
In this study we statistically analyze the lithosphere–atmosphere–ionosphere couplings of magnitude Mw5.5+ earthquakes (EQs) in the year 2023 with the aid of sub-ionospheric VLF/LF radio links. The electric field amplitude and phase measurements with a temporal resolution of one second are from the seismo-electromagnetic receiver facility in Graz (GRZ), Austria (Galopeau et al., 2023), which is part of the INFREP network. The spatial extend of the study area has the range [-10°E ≤ longitude ≤ 40°E] and [20°N ≤ latitude ≤ 50°N], in total are 17 EQs according to the United States Geological Survey (USGS) data base, among them the Turkey–Syria EQs (main shocks Mw7.8 and Mw7.5) and the Morocco Mw6.8 EQ. We apply the night-time amplitude method (Hayakawa et al., 2010) for all available paths, of particular importance are the transmitter links TBB (26.70 kHz, Bafa, Turkey), ITS (45.90 kHz, Niscemi, Sicily, Italy), and ICV (20.27 kHz, Tavolara, Italy). Relevant crossings are determined by the size of the Dobrovolsky-Bowman relationship (Dobrovolsky et al., 1979; Bowman et al., 1998).
A major finding is the statistically significant electric field variation of the TBB-GRZ link related to the Turkey–Syria EQ sequence. A physical interpretation is based on atmospheric gravity waves (AGWs) which could alter the E-layer in the lower ionosphere during nighttime and modulate the height of the waveguide cavity.

References:

Galopeau et al., A VLF/LF facility network for preseismic electromagnetic investigations, Geosci. Instrum. Method. Data Syst., 12, 231–237, 2023, https://doi.org/10.5194/gi-12-231-2023
Dobrovolsky et al., Estimation of the size of earthquake preparation zones, PAGEOPH 117, 1025–1044, 1979, https://doi.org/10.1007/BF00876083
Bowman et al., An observational test of the critical earthquake concept, JGR Solid Earth, 103, B10, 24359-24372, 1998, https://doi.org/10.1029/98JB00792
Hayakawa et al., A statistical study on the correlation between lower ionospheric perturbations as seen by subionospheric VLF/LF propagation and earthquakes, JGR Space Physics, 115(A9), 09305, 2010, https://doi.org/10.1029/2009JA015143

How to cite: Eichelberger, H., Boudjada, M. Y., Schwingenschuh, K., Besser, B. P., Wolbang, D., Solovieva, M., Biagi, P. F., Galopeau, P. H. M., Jaffer, G., Schirninger, C., Nina, A., Jovanovic, G., Nico, G., Stachel, M., Aydogar, Ö., Muck, C., Wilfinger, J., Jernej, I., and Magnes, W.: Investigation of VLF/LF electric field variations related to magnitude Mw≥5.5 earthquakes in the Mediterranean region for the year 2023, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6001, https://doi.org/10.5194/egusphere-egu24-6001, 2024.

EGU24-6275 | Posters virtual | NH4.1

TEC variation over Europe during the intense tectonic activity in the area of SE Turkey on February of 2023. 

Michael E. Contadakis, Christos Pikridas, Styllianos Bitharis, and Emmanuel Scordilis

This paper is one of a series of papers dealing with the investigation of the Lower ionospheric variation on the occasion of an intense tectonic activity.In the present paper, we investigate the TEC variations during the intense seismic activity in the transition between the Dead Sea fault and the East Anatolian fault (SE Turkey) on February 6th, 2023. The Total Electron Content (TEC) data are been provided by the EUREF Network. These data were analysed using Discrete Fourier Analysis in order to investigate the TEC turbulence band content. The results of this investigation indicate that the High-Frequency limit fo of the ionospheric turbulence content, increases as aproaching the occurrence time of the earthquake, pointing to the earthquake epicenter, in accordane to our previous investigations. We conclude that the Lithosphere Atmosphere Ionosphere Coupling, LAIC, mechanism through acoustic or gravity waves could explain this phenomenology.

 

Keywords: Seismicity, Lower Ionosphere, Ionospheric Turbulence, Brownian Walk, East Anatolian Fault.

 

How to cite: Contadakis, M. E., Pikridas, C., Bitharis, S., and Scordilis, E.: TEC variation over Europe during the intense tectonic activity in the area of SE Turkey on February of 2023., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6275, https://doi.org/10.5194/egusphere-egu24-6275, 2024.

EGU24-6407 | Orals | NH4.1 | Highlight

 Multi-parameter study of the pre-earthquake phase associated with the Kahramanmaraş sequence in Türkiye on February 6th, 2023.  

Dimitar Ouzounov, Sedat Inan, Pavel Kalenda, Libor Neumann, Sergey Pulinets, Jann-Yenq Liu, Xuhui Shen, Rui Yan, Jana Rušajová, Menas C. Kafatos, and Patrick Taylor

We study critical lithosphere/atmosphere /ionosphere coupling processes that precede earthquake events. Soon after the M7.8 and M7.5 in Kahramanmaraş, Türkiye on Feb 6, 2023, Kahramanmaraş earthquakes, we started collecting and processing multi-parameter data from ground, atmosphere, and satellite observations, such as 1/ Vertical static pendulums data from the European network; 2/ Hydrogeochemical data for electrical conductivity and major ion contents from the spring water samples near Kahramanmaraş ; 3/ Outgoing long-wavelength radiation (OLR) obtained from satellites NPOESS; 4/ Ionospheric plasma observations from China/Italy Seismo-Electromagnetic Satellite (CSES1);5/Electron density variations in the ionosphere via GPS Total Electron Content (GPS/TEC) and 6/ Atmospheric chemical potential (ACP) obtained from NASA assimilation models. We have detected two temporal groups of pre-earthquake anomalies: A/few months in advance - hydrogeochemical anomalies lasting up to six months and vertical static pendulums lasting two months ahead of the seismic rupture and B/few days in advance -  OLR and ACP anomalies showed an abnormal increase on Jan 15-30, along with the plasma electron and oxygen ion density from the CSES1 satellite which is highly correlated with electron density variations in the ionosphere from GPS/TEC. Two groups of identified anomalies relate to different stages of Kahramanmaraş earthquake preparation processes. The first type was linked to the crustal deformation phase and was associated primarily with the coupling processes of the lithosphere-atmosphere. Based on the cross-event analysis of major seismicity in the regions, we found similarities in the pre-earthquake pattern occurrence between the M7.8/M7.5 2023 Kahramanmaraş sequence and the M7.2 Van Earthquake of 2011 and two other major events.

We show that we could extract new information about the different stages of earthquake preparation processes by combining ground and near-space data according to the physical concept of LAIC.

How to cite: Ouzounov, D., Inan, S., Kalenda, P., Neumann, L., Pulinets, S., Liu, J.-Y., Shen, X., Yan, R., Rušajová, J., Kafatos, M. C., and Taylor, P.:  Multi-parameter study of the pre-earthquake phase associated with the Kahramanmaraş sequence in Türkiye on February 6th, 2023. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6407, https://doi.org/10.5194/egusphere-egu24-6407, 2024.

EGU24-7299 | ECS | Orals | NH4.1

Groundwater geochemical anomalies in Mt. Conero area (central-eastern Italy) related to the pre- and post- 5.2 and 5.5 Mw Marche offshore seismic events (November 9, 2022) 

Lorenzo Chemeri, Marco Taussi, Davide Fronzi, Jacopo Cabassi, Alberto Tazioli, Alberto Renzulli, and Orlando Vaselli

It is well established in geosciences that Mw > 4 earthquakes are expected to produce changes in the geochemistry of the waters circulating close to epicentral area. Therefore, such modifications are commonly considered as precursory signals and strictly related to the earthquake preparation processes and seismic cycles. Since most of these changes are transitory and site-sensitive, the identification of possible and suitable seismic precursors represents one of the major challenges for geoscientists. Consequently, the development of multi-parametric water monitoring networks located in earthquake-prone areas is a fundamental step toward a better understanding of the relationship between the seismic cycle and the occurrence of possible tracers.

The northern offshore area of the Marche Region was hit by 5.2 and 5.5 Mw earthquakes (Lat. 43.9830, Long. 13.4240, 5 km depth) on November 9, 2022 during which no fatalities or serious damages were recorded. In this work we report the preliminary results obtained from a pre- and post-seismic monitoring focused on waters collected from three piezometers (with a depth ranging from 15 to 30 m) located in the Mt. Conero Area (central-eastern Italy): Monte Acuto (MAC), Vallemiano (VAL), and Betelico (BET), situated ca. 40-50 km from the epicenter. All waters were sampled within 48 hours from the mainshock and periodically (on a monthly or quarterly basis) collected for one year after the event. The water chemistry of BET sample was available from May to October 2022, i.e., up to six months before the event. While the water samples MAC and VAL did not show any relevant chemical and isotopic variations, those collected from BET displayed strikingly significant modifications. The geochemical facies, characterized by a calcium-bicarbonate and a TDS (Total Dissolved Solids) < 1000 mg/L, typical of shallow aquifers, indeed became sodium-chlorine with TDS > 3500 mg/L, since the end of June 2022, i.e., about four months before the mainshock. About a week after the main events, the water chemistry returned to be Ca-HCO3. Boron, Li, Sr and Rb concentrations also showed significant increments starting from June whereas those of Fe, Mn, Ni, Cu, Zn and Pb displayed overwhelming increases (up to 50 times their pre-seismic values) in those samples collected in the days following the mainshocks. Consequently, particular emphasis was placed on addressing the origin of these changes and evaluating their possible relation with the seismic event. We can hypothesize that a mixing process between shallow aquifer and Na-Cl connate (or thermal) waters occurred, the latter being widely reported in the Adriatic foredeep deposits. The observed chemical variations might likely be related to changes in the relative pressure between superimposed and separated aquifers triggered by modifications in the stress rates associated with the seismic cycle. Moreover, variations in the hydraulic heads resulting in a temporary connection between two distinct aquifers would also explain the transitory changes detected at BET. If confirmed, these variations would be among the most strikingly impressive geochemical evidences ever detected before a seismic event or, at least, ever reported in the literature.

 

 

How to cite: Chemeri, L., Taussi, M., Fronzi, D., Cabassi, J., Tazioli, A., Renzulli, A., and Vaselli, O.: Groundwater geochemical anomalies in Mt. Conero area (central-eastern Italy) related to the pre- and post- 5.2 and 5.5 Mw Marche offshore seismic events (November 9, 2022), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7299, https://doi.org/10.5194/egusphere-egu24-7299, 2024.

EGU24-8281 | Posters virtual | NH4.1

Potential earthquake precursory pattern of large Alpine- Himalayan earthquakes as seen by magnetic Swarm satellites 

Angelo De Santis, Homayon Alimorady, and Habib Rahimi

 Before the occurrence of an earthquake and when the lithosphere is in a state of critical stress accumulation, the lithosphere could react- with the so-called earthquake precursors. One of these precursors is the magnetic field, which, under proper conditions, may produce anomalies due to accumulated stress in the crust before an earthquake occurs. Since several years ago, it has been possible to observe the Earth's magnetic field through satellites. The Swarm satellite mission of the European Space Agency was launched at the end of 2013. It is composed of three identical specialized satellites for observing the Earth's magnetic field. Here, using the magnetic measurements provided by Swarm satellites, we investigate the possibility of identifying several anomalous magnetic signals before the occurrence of earthquakes, which are possibly related to lithosphere-atmosphere-ionosphere coupling. In this study, the earthquakes with a magnitude greater than 5.0 occurred from 2014 to 2023 in the Alpine-Himalayan belt under geomagnetically quiet conditions were examined. Using the algorithm applied to the data from 10 days before the earthquake, obvious anomalies in the components of the magnetic field are identified. Furthermore, a significant relationship between the length (duration) of the anomaly and the magnitude of the earthquake was observed and the empirical relationship between them was estimated. For instance, with the enhancement in the magnitude of the earthquake, the duration of the anomaly also increases.

In addition, significant relationships are also found between other parameters and the magnitude of the earthquake with an acceptable correlation.

We also performed a confutation analysis synthetizing a random catalogue of earthquakes and made again the correlation with the satellite anomalies: the results were far different from those obtained with real data, so confirming the validity of those results.

How to cite: De Santis, A., Alimorady, H., and Rahimi, H.: Potential earthquake precursory pattern of large Alpine- Himalayan earthquakes as seen by magnetic Swarm satellites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8281, https://doi.org/10.5194/egusphere-egu24-8281, 2024.

EGU24-8894 | Posters virtual | NH4.1

Attempts to include geomagnetic anomalies into the existing Romanian Operational Earthquake Forecast 

Iren Adelina Moldovan, Victorin Emilian Toader, Andrei Mihai, Alexandru Marmureanu, and Constantin Ionescu

Our study analyzes the possibility to include geophysical parameters in the existing OEF (Operational Earthquake Forecasting) application based on the geochemical detected anomalies correlated with short-term changes in seismicity rates and occurrence of medium sized intermediate depth earthquakes.

The study aims to decide which of the geomagnetic anomalous signals can be considered to be a reliable precursor of Vrancea, Romania moderate sized earthquakes that occurred in the last decade. The anomalies were observed using different processing methods: polarization, diurnal variation, differential analysis between two stations or simple visualization at only one station and the standard deviation from the mean value.

The existing OEF application for the Vrancea area based on geochemical parameters is using the standard deviation, time gradient, cross correlation, and linear regression customized for the geological specificity of the area under investigation. For anomaly detection is used the short-time-average through long-time-average trigger (STA/LTA) method on time-integral data. The daily–seasonal variation of parameters is correlated with atmospheric conditions and temperature in the borehole to avoid false decisions. The probability and epistemic uncertainty of the gas emissions act as input into a logical decision tree.

During the study period, in Vrancea seismogenic zone there have been recorded 25 earthquakes with moment magnitude Mw>4.5, at intermediate depth. The Geomagnetic data are obtained from Muntele Rosu (MLR) Seismological Observatory and Plostina (PLOR) of NIEP, situated inside Vrancea seismogenic zone as primary station, and from Surlari (SUA) National Geomagnetic Observatory, part of the International Real-time Magnetic Observatory (Intermagnet), as remote station, unaffected by medium size earthquake preparedness processes. We have assumed that the zone of effective manifestation of the precursor deformations is a circle with the radius taken from the equation of Dobrovolsky, 1979.  Geomagnetic indices taken from GFZ (https://www.gfz-potsdam.de/kp-index) were used to separate the global magnetic variation from possible local seismo-electromagnetic anomalies, that might appear in a seismic area like Vrancea zone and to ensure that observed geomagnetic fluctuations are not caused by solar-terrestrial effect.

Acknowledgments: This paper was carried out within AFROS Project PN-III-P4-ID-PCE-2020-1361, 119 PCE/2021, supported by UEFISCDI, Nucleu Program SOL4RISC, supported by MCI, project no PN23360201, and PNRR- DTEClimate Project nr. 760008/31.12.2023, Component Project Reactive, supported by Romania - National Recovery and Resilience Plan

How to cite: Moldovan, I. A., Toader, V. E., Mihai, A., Marmureanu, A., and Ionescu, C.: Attempts to include geomagnetic anomalies into the existing Romanian Operational Earthquake Forecast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8894, https://doi.org/10.5194/egusphere-egu24-8894, 2024.

EGU24-10341 | Orals | NH4.1

Study of VLF phase and amplitude variations before the Turkey Syria Mw 7.8 EQs 

Mohammed Y. Boudjada, Pier Francesco Biagi, Hans Ulrich Eichelberger, Patrick H.M. Galopeau, Konrad Schwingenschuh, Maria Solovieva, Giovanni Nico, Helmut Lammer, Wolfgang Voller, and Manfred Stachel

We investigate the recent earthquakes (EQs) that occurred on 06 February 2023 principally in the central southern part of Turkey and north western of Syria. The tectonic plate movements between Anatolian, Arabian and African plates are well known to be subject to EQs. The coordinate of the epicenter was 37.08°E and 37.17°N with depth in the order of 10 km and a magnitude Mw7.8. Beside aftershocks, a few hours later a strong Mw7.7 earthquake occurred in the same region . We consider in this analysis the Bafa VLF transmitter (TBB) signal emitting at frequency of 26.7 kHz and localized in the Anatolia region (Turkey) at longitude of 27.31°E and latitude of 37.40°N. TBB transmitter signal is daily monitored by the VLF Graz facility (Biagi et al., 2019; Galopeau et al., 2023) with a sufficient signal to noise ratio principally during night observations. We study the variations of the phase and amplitude of TBB signals, as detected by Graz facility (15.43°E, 47.06°N) few weeks before the earthquakes occurrence. It is essential to note that the geographical latitudes of the epicenter and the TBB transmitter are about 37°N, and the distance, in the order of 850 km, is found smaller than the radius of the earthquake preparation zone, as derived from Dobrovolsky et al. (1979), when considering the magnitude of the seismic event, i.e. Mw7.8. We have applied the terminator time (TT) method to make evident the presence of sunrise and sunset time shifts at terminators one week to ten days before EQs.  We discuss essentially the anomalies, in the phase and the amplitude of TBB transmitter, which are probably linked to the electron density variations at the formation and the destruction of the ionospheric D-E-layers.

 

References:

Biagi et al., The INFREP Network: Present Situation and Recent Results, Open J. Earth. Research, 8, 2019.

Dobrovolsky et al., Estimation of the size of earthquake preparation zones, Pageoph, 117, 1979.

Galopeau et al., A VLF/LF facility network for preseismic electromagnetic investigations, Geosci. Instrum. Method. Data Syst., 12, 2023.

How to cite: Boudjada, M. Y., Biagi, P. F., Eichelberger, H. U., Galopeau, P. H. M., Schwingenschuh, K., Solovieva, M., Nico, G., Lammer, H., Voller, W., and Stachel, M.: Study of VLF phase and amplitude variations before the Turkey Syria Mw 7.8 EQs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10341, https://doi.org/10.5194/egusphere-egu24-10341, 2024.

EGU24-11940 | Posters on site | NH4.1

Non-extensivity study of the seismicity along the Mexican Pacific coast based on the Tsallis q-statistical approach. 

Alejandro Ramírez-Rojas, Elsa Leticia Flores-Márquez, and Leonardo Di G. Sigalotti

The Mexican Pacific coast has presented significant seismic activity due to the tectonic processes that have generated it. This coast, from Baja California until Chiapas is matched with three tectonic settings, to the north, a dispersion zone is presented in Baja California and Cortes Sea, at the middle, conforming by Jalisco, Colima and Michoacan states, La Rivera Plate is the principal source of seismicity and, finally the seismic activity in Guerrero, Oaxaca and Chiapas is driven by the Cocos Plate subduction. According with the catalogues published by the SSN, the yearly number of earthquakes occurred is very different at each zone is very different being Cocos plate the subduction zone that has produced the major number of earthquakes. We analyzed the catalogues of six zones of the Mexican Pacific coast in the period between 2000 and 2023. Based on the Tsallis q-statistical approach it is possible to assess the temporal changes of the non-extensivity by fitting the cumulative number of earthquakes with the generalized Gutenberg-Richter. Our preliminary results show differences in the fitting of the q-values for the six studied regions. These results are consistent with a pervious analysis, where it was observed that the highest q-value was obtained in Jalisco zone, while Oaxaca region reported the lowest q-value.

How to cite: Ramírez-Rojas, A., Flores-Márquez, E. L., and Sigalotti, L. D. G.: Non-extensivity study of the seismicity along the Mexican Pacific coast based on the Tsallis q-statistical approach., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11940, https://doi.org/10.5194/egusphere-egu24-11940, 2024.

EGU24-12838 | Orals | NH4.1

Nicaragua seismicity study in terms of entropy fluctuations in natural time domain 

Elsa Leticia Flores-Marquez, Xochilt Esther Zambrana-Areas, and Alejandro Ramirez-Rojas

Nicaragua is located on the western margin of the Caribbean plate near its interaction with the Cocos plates. The Caribbean plate is surrounded by four major tectonic plates: Cocos at the southwest, Nazca at the south, the North American and South American to the north and southeast respectively. The Cocos plate subducts the Caribbean plate at rates of aproximately 70 to 90 mm/yr having a steeper dip around 75° and 80°. The Central American subduction zone is seismically active. The associated volcanic arc consists mainly of basaltic-andesitic quaternary volcanic rocks (predominantly pyroclastic and lava flows). The seismicity, although constant, has not exceeded earthquakes of Ms 7.3. We analyzed the period between 2000 and 2023 in terms of entropy in natural time domain. Our analysis in terms of Gutemberg-Richter law shows b-value fluctuation ranging between 0.53 and 1.03 by year. Regarding the analysis of entropy fluctuations, it indicates the correlations are short-range, so we consider that the seismic sequence behaves as a Markovian process.

How to cite: Flores-Marquez, E. L., Zambrana-Areas, X. E., and Ramirez-Rojas, A.: Nicaragua seismicity study in terms of entropy fluctuations in natural time domain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12838, https://doi.org/10.5194/egusphere-egu24-12838, 2024.

EGU24-13120 | Orals | NH4.1 | Highlight

Local Solid Earth Tides and Their potential use in assessing and forecasting the risk of seismic hazards 

Francesco Vespe, Jan Dousa, Carlo Doglioni, Eleonora Ficini, Olimpia Masci, Giovanni Nico, Jakub Nosek, Pavel Vaclavovic, Gianluca Sottili, Davide Zaccagnino, Luis Mendes, and Francisco Amarillo-Fernandez

This work presents some results achieved in the frame of TILDE project (Tidal Interplate Lithospheric Deformation of Earth). The main goal of TILDE project was the estimation of Local Solid Earth Tides (LSET); i.e. models which depends on the geographical position of the selected sites. The LSET models are built estimating Love and Shida numbers for each station and for each tidal constituents. The objectives were to investigate possible correlations between LSET and geological/geophysical events, such as tectonic plates movements, earthquakes and volcanic activities. GNSS data collected at 98 stations, split into global and regional networks have been used. The global network consists of 73 GNSS stations which have piled up a stack of data 20 years long. The regional networks consist of 25 stations, 7 located in New Zealand, 1 in Kamchatka, and 17 stations in Italy for which 3 year-long time series of data are available.

The LSET models have been achieved using GNSS coordinates expressed both in geocentric XYZ and local NEU references, estimated in Precise Post Processing mode, with a sampling rate in turn of 1 day and 3 hours.  Different GNSS solutions have been generated according the objectives of the project. The first one is the background solution in which the full IERS2010 tides model has been applied. The second solution is obtained by switching off the tides model. The third one is the solution in which only the Long-Periodic Tides (LPT) has been switched off. This last solution has been applied in order to lower the level of flickering of GNSS time series when Love and Shida numbers of LPT had to be estimated.

This analysis showed that there is a correlation between the latitude measured from the tectonic equator and Love numbers. This confirms the theory that moon tides contribute to trigger tectonic movements.

An interesting result, relevant for the assessment and potential precursiveness of the risk of seismic hazards, was the correlation found between the variation in time of Love numbers of diurnal (K1) and semi-diurnal (M2) tides and the occurrence of earthquakes nearby GNSS sites.  At this purpose we selected GNSS global stations which were at a distance <200 Km from the epicentre of EQ events. The investigation has outlined that almost the seismic events are got ahead by a downfall of Love numbers. It seems that each earthquake event cannot be characterized only by the type of slip occurred along faults: compressive (i.e., reverse fault), extensional (i.e., normal fault), strike slip or combination of them. This result could be explained with the rigidity of the crust/mantle which play a major role in triggering seismic events. For smaller values of Love number we have indeed a more rigid response of Earth to Tidal forcing.

How to cite: Vespe, F., Dousa, J., Doglioni, C., Ficini, E., Masci, O., Nico, G., Nosek, J., Vaclavovic, P., Sottili, G., Zaccagnino, D., Mendes, L., and Amarillo-Fernandez, F.: Local Solid Earth Tides and Their potential use in assessing and forecasting the risk of seismic hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13120, https://doi.org/10.5194/egusphere-egu24-13120, 2024.

EGU24-13277 | Orals | NH4.1

Study of ionospheric variations from a global network of VLF antennas 

Patrick Galopeau, Mohammed Boudjada, Hans Eichelberger, Ashanthi Maxworth, Pier Biagi, and Konrad Schwingenschuh

We present a system which records electromagnetic signals, in the Very Low Frequency (VLF: 3 kHz – 30 kHz) and Low Frequency (LF: 30 kHz – 300 kHz) range, 24 x 7 x 365, with the goal of identifying ionospheric variations. An individual system consists of a monopole antenna, a pre-amplifier, a power supply, a central computer, a GPS unit, and a recording device. Several receivers will be implemented around the globe in a network. The first implementation of the system was done in Graz (Austria), the second one will be in Guyancourt (France), a third one in Réunion (France) and a fourth one in Moratuwa (Sri Lanka). Each reception device will allow a continuous daily monitoring of transmitter signals in the VLF and LF frequency bands. This network will be devoted to the study of ionospheric variations, in particular, those linked to the solar activity, but also those associated with seismic activity with the purpose to identify electromagnetic earthquake precursors.

How to cite: Galopeau, P., Boudjada, M., Eichelberger, H., Maxworth, A., Biagi, P., and Schwingenschuh, K.: Study of ionospheric variations from a global network of VLF antennas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13277, https://doi.org/10.5194/egusphere-egu24-13277, 2024.

Among many precursors related with geology, geophysics and geochemistry field, the geomagnetic field is one of the most sensitive factors of seismic activity. Current works basically analyzed scalar values of multiple components separately or the ratio of vertical component and horizontal component to extract electromagnetic radiation anomalies in different frequency range. However, the relationship of induced magnetic horizontal vector (IMHV) and earthquake light generated by pressure-simulated rock current (PSRC) was initially proved in M7.3 Fukushima earthquake of 16 March 2022. The geomagnetic anomalies obtained by current methods originate from alternating electromagnetic fields instead of rock current, which lack the investigation of the direction information of seismic geomagnetic disturbance vector. 
By combining observational evidence from existing rock current experiments with the volumetric scaling effect, the intensity of current generated by the compressed crustal rock mass in seismogenic areas was estimated to be over 1 MA when the magnitude reaches 7 or above. Based on Biot-Savart's law, the magnetic field disturbance intensity generated by the rock current in three-dimensional space was simulated in this study. The simulation results indicate that magnetic field disturbances ranging from several nanotesla to tens of nanotesla can be generated at approximately 600 km from the rock current, which can be easily captured by the existing dense distribution of ground-based observatory networks (e.g., INTERMAGNET, MAGDAS).
This paper aims to propose an analysis method based on seismic geomagnetic disturbance vectors and validate it using the 2007 M7.3 Peru earthquake as a case study. In this method, two arbitrary geomagnetic stations around the seismogenic area are selected to obtain the magnetic variation of multiple geomagnetic component (e.g., declination horizontal, and vertical component), which are then synthesized into the disturbance vectors. Subsequently, the intersection line of the two vector planes of the magnetic field disturbances is determined based on the concept of forward intersection, allowing for an approximate estimation of the orientation of the rock current. Finally, the spatial relationship between multiple disturbance vectors and the rock current is assessed to determine if Biot-Savart's law is satisfied.
Taking the 2007 Peru earthquake as a research case, magnetic anomalies in both horizontal and vertical components were detected prior to the earthquake at two geomagnetic stations (i.e., the HUA station from INTERMAGNET and the ANC station from MAGDAS) located within 300 km from the epicenter. The method proposed in this study was utilized to further analyze the data, revealing that the rock currents obtained from the disturbance vectors were distributed around the seismogenic area. Besides, the combination of geological data and the positive holes theory also provided confirmation of the presence of rock types capable of generating current carriers in the seismogenic area. The method proposed in this study, to a certain extent, can effectively verify the spatiotemporal correlation between geomagnetic anomalies and seismic activities, which enables the localization of stress-locked regions and can serve as an effective approach for detecting seismic magnetic anomalies and short-term earthquake forecasting.

How to cite: Xie, B., Wu, L., and Mao, W.: New analysis method of seismic geomagnetic disturbance vector using ground-based observation: a case study of the 2007 Peru earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13546, https://doi.org/10.5194/egusphere-egu24-13546, 2024.

EGU24-14043 | Posters virtual | NH4.1

Lithosphere-atmosphere-ionosphere coupling processes for 2022 Luding Ms6.8 earthquake in China 

Xuemin Zhang, Angelo De Santis, Jing Liu, Saioa Campuzano, Na Yang, Serena D’Arcangelo, Xinyan Ouyang, Mariagrazia De Caro, Gianfranco Cianchini, Muping Yang, Cristiano Fidani, Xinyan Li, Martina Orlando, Hong Liu, Loredana Perrone, Lei Nie, Alessandro Piscini, Dario Sabbagh, and Maurizio Soldani

Due to the significant earthquake-related perturbations observed in the ionosphere by ground-based stations and space-borne satellites, scientists have increasingly focused on the studying the possible coupling mechanism among lithosphere, atmosphere and ionosphere. In this work, we contribute to this research, analyzing the phase of preparation of the 2022 Ms6.8 Luding (China) earthquake with a multi-parameter and multi-level approach from ground and satellite data taken in lithosphere, atmosphere and ionosphere, including the b value, earth resistivity, ELF magnetic field emissions, atmospheric electric field, surface temperature, foF2 from Ionosonde, GNSS TEC, magnetic field and electron density from CSES and Swarm satellites, etc. The results are encouraging confirming a chain of processes starting from ground and proceeding to the above atmosphere and ionosphere.

How to cite: Zhang, X., De Santis, A., Liu, J., Campuzano, S., Yang, N., D’Arcangelo, S., Ouyang, X., De Caro, M., Cianchini, G., Yang, M., Fidani, C., Li, X., Orlando, M., Liu, H., Perrone, L., Nie, L., Piscini, A., Sabbagh, D., and Soldani, M.: Lithosphere-atmosphere-ionosphere coupling processes for 2022 Luding Ms6.8 earthquake in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14043, https://doi.org/10.5194/egusphere-egu24-14043, 2024.

EGU24-18372 | ECS | Posters on site | NH4.1

Robust Satellite Techniques for seismic prone area monitoring: recent achievements and future perspective toward a multi-parametric t‐DASH system 

Roberto Colonna, Carolina Filizzola, Nicola Genzano, Mariano Lisi, Nicola Pergola, and Valerio Tramutoli

After more than 25 years of studies it is possible to draw a balance of the efforts, based on the application of Robust Satellite Techniques to long-term satellite TIR (Thermal InfraRed) radiances, to identify (isolating them from all the others possible sources) those anomalies (in the spatial/temporal domain) possibly associated to the occurrence of major earthquakes.

The results achieved by processing multi-annual (more than 10 years) time series of TIR satellite images collected in different continents and seismic regimes, showed that more than 67% of all identified (space-time persistent) anomalies occur in the pre-fixed space-time window around the occurrence time and location of earthquakes (M≥4), with a false positive rate smaller than 33%. Moreover, Molchan error diagram analysis gave a clear indication of non-casualty of such a correlation, in comparison with the random guess function.

Here, we will critically discuss the results up to now achieved by applying long-term RST analyses in different part of the world. Moreover, we will also discuss the common and/or peculiar elements of success/failure respect to the possibility to build and implement a multi-parametric system for a time‐Dependent Assessment of Seismic Hazard (t‐DASH).

How to cite: Colonna, R., Filizzola, C., Genzano, N., Lisi, M., Pergola, N., and Tramutoli, V.: Robust Satellite Techniques for seismic prone area monitoring: recent achievements and future perspective toward a multi-parametric t‐DASH system, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18372, https://doi.org/10.5194/egusphere-egu24-18372, 2024.

EGU24-20006 | Orals | NH4.1

Seismic LCAI Coupling Supported by Pressure Stimulated Rock Current: Multi-parameter Observations and Numerical Simulation 

Lixin Wu, Busheng Xie, Dingyi Wu, Xiao Wang, Ziqing Wang, Yifang Ding, Youyou Xu, and Wenfei Mao

Multiple parameters anomalies appeared before medium-strong earthquakes have long been observed and analyzed. The spatio-temporal relations of multiple anomalies were attributed to the coupling of lithosphere, coversphere, atmosphere and ionosphere (LCAI in brief) related with the seismogenious activity and final shocking. However, the mechanism of LCAI coupling is not yet clear and the process of LCAI coupling is much fuzzy, which hinders the scrutinizing of reported anomalies, and leads to great difficulty in discriminating the inconsistency for single parameter as well as the uncertainty among multiple parameters.

From laboratory experiments on rock specimens partly loaded to fracturing we discovered that there were pressure stimulated rock current (PSRC) developing with the applied pressure, and there was stepped increment of PSRC as well as sharp rise of PSRC appearing in the late phase of loading rock to failure. The measured PSRCs were measured in an amplitude of 2~8000na, which depending on rock-minerals and porewater of different rock specimen. The enhancement of surface infrared radiation and the reduction of surface rock dielectric, which lead subsequently to the enhancement of microwave brightness temperature (MBT), could be attributed the production of PSRC and its propagation to rock surface both in laboratory and seismogenious zone.

Ground observations in Luding, China, and Fukushima, Japan, showed that the arriving of PSRC from underground was able to disturb the near-surface electric field, and led further to the local atmospheric ionization and earthquake light near ground surface. Abnormal drop of atmospheric electric field and simultaneous rise of MBT were observed preceding the M6.8 Luding earthquake, 2022, and earthquake lighting and horizontal magnetic vector disturbance were observed accompanying with the M7.3 Fukushima earthquake, 2023.

The arrival of PSRC from seimogenious zone or hypocenter is to change the atmospheric electric field, which was believed being able to penetrate upward from ground surface to ionosphere. An atmospheric electric field penetration model was modified and used to simulated the ionospheric disturbance due to the seismic PSRC inhomogeneous appeared on ground surface. The ionospheric TEC disturbance related with the M8.0 Wenchuan earthquake in 2008, the M9.0 Tohoku earthquake in 2011, the M7.8 Nepal earthquake in 2015 and the M7.5 Turkey earthquake in 2022 were carefully simulated, respectively, according to the position of MBT anomalies or supposed PSRC occurrence. The simulation results were visualized in a 3D spheroid space and contrasted to the reported TEC anomalies retrieved from satellite or ground observations. Particularly for the great Nepal earthquake in 2015, we scrutinized the observed multiple anomalies, including TEC and VLF, possible related with the LCAI coupling, and rooted the seismic anomalies to the simulated underground high-stress accumulation regions on and above the subduction fault.

How to cite: Wu, L., Xie, B., Wu, D., Wang, X., Wang, Z., Ding, Y., Xu, Y., and Mao, W.: Seismic LCAI Coupling Supported by Pressure Stimulated Rock Current: Multi-parameter Observations and Numerical Simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20006, https://doi.org/10.5194/egusphere-egu24-20006, 2024.

Seismic hazard assessment involves quantitatively estimating ground shaking at site. There are two main approaches for estimating seismic hazard, Deterministic seismic hazard assessment (DSHA) and Probabilistic seismic hazard assessment (PSHA). In the present investigation DSHA is used, it relies on the worst-case scenario earthquake. The state of Kerala (9°N - 13°N and 75°E - 78°E) which lies in the seismic zone III, having a zone factor 0.16, has been considered to estimate seismic hazard in terms of PGA. Based on analyses of seismotectonics of the area, 26 seismogenic sources were identified and used for the PGA estimation. The peak horizontal accelerations (Ah) 0.2344g and peak vertical accelerations (Av) 0.1395g were computed for the city of Calicut. For other cities, Thiruvananthapuram, Kollam, Palakkad, Kochi, and Thrissur horizontal (Ah) and vertical accelerations (Av) were also estimated. However, the highest value was found to be at Calicut followed by Palakkad. In case of Palakkad, the values were influenced by cluster of faults located there while, at Calicut was caused by the Fault – 1 (source) which is in the Arabian Sea near the coast of the city. It has been observed that the seismic hazard assessment of Kerala advocate the PGA (Ah) falls in the range of 0.02g to 0.47g and PGA (Av) varies from 0.01g to 0.33g. These accelerations seem to be more realistic since they are based on consideration of many seismotectonic sources in the region that may rupture causing earthquakes. The ratio of Av/Ah was found to be in the range of 0.70 to 0.38. The prepared contour maps for the region show that larger peak ground accelerations are present in the region where there is a higher density of larger faults and vice versa. The findings highlight the need for further studies and enhanced preparedness measures in Kerala, aiming to mitigate potential seismic risks and ensure the safety of its residents in this seismically active region.

How to cite: Shanker, D. and Rafih AP, M.: Seismic Hazard in terms of Peak Ground Acceleration (PGA) for coast of Calicut, State of Kerala (INDIA), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-437, https://doi.org/10.5194/egusphere-egu24-437, 2024.

EGU24-882 | ECS | Orals | NH4.2

Hotspot analysis of critical infrastructure risk to debris flow hazard scenarios using Geo AI approach 

Shivam Priyadarshi, Somnath Bera, and Pritha Ghosh

The Indian Himalayas are facing rapid construction of critical infrastructure (CI) which is significant for the functioning of mountainous society. At the same time, these infrastructures are disrupted frequently during monsoon season particularly due to the onset of debris flows. It causes soaring economic losses and cutting off essential services like food, water, and health during disasters. In the background, mapping detailed CI and assessing their risk to debris flows is essential. However, one of the challenges of estimating debris flow is that it not only damages infrastructure at its source area but far beyond wherever it travels as run-out. The literature shows the risk of CI under such a run-out scenario is limited. Therefore, the study proposes a spatial framework for assessing CI risk to debris flow hazard scenarios. The frame is constituted in two parts, the first one focuses on developing a debris flow hazard model by integrating source and their runout areas. The second part concentrates on a systematic mapping of exposed CI and its risk-hotspot zonation. In the debris flow hazard modelling, an inventory database of sources and runouts are generated covering the year 2005 to 2022. The conditioning factors cover topographic, hydrological, geological, and environmental variables that are generated from multiple data sources such as DEM (ALOS PALSAR), Google Earth images, and high-resolution satellite images (Planet Scope). Next, the susceptibility of the debris flow source area is estimated by using Stacking Random Forest Model. Further, the runout area is simulated using the Flow R model in which susceptible debris flow source areas are considered as input. We generate two debris flow scenarios; one is considered normal rainfall-induced debris flows and another is a worst-case scenario that is developed considering extreme rainfall-induced debris flows. The models are validated using a confusion matrix and further, applied to CI risk analysis. In the second part of the paper, the detail of twelve category of CI is identified and mapped using GIS. These CI is treated as hard assets such as transportation, electricity, water lines, telecommunication, hospitals, schools, waste management, dam, recreation areas, hotels, helipads, and evacuation shelters. The spatial data of critical infrastructure are collected from multiple sources data such as Open Street Map, My Maps, Google Earth Images, Toposheet and various published reports. Then, the density of each CI at each village is generated and it is overlayed with the debris flow hazard scenarios for estimating risk. Finally, the hotspot of CI risk is analyzed using Global Moran's I method. The modelling framework is applied in the Sikkim Himalayas which is the one of sensitive debris flow regions of the world. We find a positive linearity with remoteness and debris flow hazard. However, a non-linearity exists with remoteness and CI risk. The findings and output map of the study can be used for financing and policy-making towards disaster-resilient infrastructure development.

Keywords: Critical infrastructure; Debris flow; Runout; Geo AI; Stacking Random Forest; Global Moran's I

How to cite: Priyadarshi, S., Bera, S., and Ghosh, P.: Hotspot analysis of critical infrastructure risk to debris flow hazard scenarios using Geo AI approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-882, https://doi.org/10.5194/egusphere-egu24-882, 2024.

This research aims to distribute b-value estimation spatially on the Mingachevir water reservoir area, a seismically active zone situated in Azerbaijani part of Kur depression. There are several researches proposing a relation between seismicity and b-value (Babayev G. et. al., 2020, Babayev T. et. al., 2023b, Telesca et. al., 2020). It is shown that, b-value is lower in the high-intensity zones, and higher in the low-intensity zones (Babayev T. et. al., 2023b). b-Value is an important parameter of a linear relation that is called Gutenberg-Richter law. Gutenberg-Richter law represents the earthquakes distribution with respect to the magnitude (Gutenberg and Richter, 1942). The relation below (1) presents Gutenberg-Richter law:

(1) log N = a - bM or N = 10a - bM,

where N is the number of earthquakes greater and equal than M, the magnitude of the earthquakes, a and b are the real constants.

 b-Value is the slope of this linear relation, in terms of mathematics. It is a parameter reflecting the relative size distribution of earthquakes (Babayev T. et. al., 2023a). Several ways were improved to estimate b-value (El-Isa, Eaton, 2014). We applied linear least-square fitting method to logarithmically binned data since it is preferred due to its instructivity (El-Isa, Eaton, 2014; Milojevic, 2010). In order to obtain spatial distribution of b-value the microzonation method of Babayev G. et. al., 2020 was applied. By use of this method, the area was divided to the grids of 10 km * 10 km. The seismic events in the Mingachevir catalog were clustered to each grid and b-value was estimated for each grid with the events. The microzonation of the study area was done on ArcGIS 10.7 (ESRI, 2018) software and the mapping of b-value spatial variation was done on SURFER software. According to the result of the research, we observe that mainly, in the study area the b-value has a low quantity, which is proposed to be related with higher seismic activity (Babayev G. et. al., 2020 and Babayev T. et. al., 2023b). Still, it varies through the study area and in the northern part of Mingachevir water reservoir, that is close to Southern Greater Caucasus and in the south-eastern part of the reservoir, that is close to Yevlakh region b-value is around 1. b-variations are impacted by tectonic stress (El-Isa, 2013). Wiemer and Wyss, 1997; Wiemer et. al., 1998; Zuniga and Wyss, 2001; Gerstenberger et. al., 2001; Wiemer and Wyss, 2002; Schorlemmer, 2004; Schorlemmer et. al., 2005; Wyss et. al., 2004; Wyss and Matsumura, 2006; Wyss and Stefansson, 2006 propose b-decrease with the increase of the tectonic stress. The studied area is a depression zone under compression between Lesser and Greater Caucasus mountains. The Kur depression forms a reverse fault or subduction zone by moving under the Greater Caucasus at a rate of 8 mm/year with the stress applied by Lesser Caucasus (Aktug et. al., 2009, 2013; Reilinger et. al., 2006). Therefore, lower b-values and high number of seismic events allow us to consider the relation among b-value, seismicity and tectonic factors.

How to cite: Babayev, T. and Babayev, G.: Spatial distribution of b-value on the Mingachevir water reservoir area for seismicity analysis applying the microzonation method of Babayev G. et. al., 2020., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1040, https://doi.org/10.5194/egusphere-egu24-1040, 2024.

EGU24-1228 | Posters on site | NH4.2

A novel artificial surface anomaly index (ASAI) based on post-disaster texture features using single-temporal and high-resolution imagery 

Shoujia Ren, Yaozhong Pan, Chuanwu Zhao, Yuan Gao, Gelilan Ma, Hanyi Wu, Yu Zhu, and Zhengyang Zhang

Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged or anomaly artificial surface area can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. In this study, we developed a method for near real-time, general and robustly identify anomaly artificial surfaces using 3DTF and ASAI. This method was designed to identify the impervious surface areas using single-temporal imagery without pre-disaster data. The features of the contrast, Gabor, and Con-Gabor features were used to construct 3DTF, which distinguish forest, bare land, shadows with artificial surface. And then it was then used with the K-means classifier to map the artificial surfaces area. Based on the different textures of normal and anomaly artificial surfaces, we constructed the ASAI using entropy and homogeneity, and used the index to detect anomalies in mapped artificial surface areas. The performance of the detecting anomalies method was developed at three different sites in Turkey Earthquake and the mapped results of artificial surface showed that the overall accuracies at sites A-C, and C were > 93%. Using The mapped artificial surface area and ASAI identified anomaly artificial surface. The results showed the overall accuracies were 93.76%, 91.4% and 90.07%. Given the promising and accurate outcomes of this study, further developments remain warranted to determine the robustness of the anomaly artificial surface detecting method in areas with complex artificial surface distribution.

How to cite: Ren, S., Pan, Y., Zhao, C., Gao, Y., Ma, G., Wu, H., Zhu, Y., and Zhang, Z.: A novel artificial surface anomaly index (ASAI) based on post-disaster texture features using single-temporal and high-resolution imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1228, https://doi.org/10.5194/egusphere-egu24-1228, 2024.

EGU24-1822 | Posters on site | NH4.2

Lessons learned developing a regionally-consistent exposure database for Central Asia 

Chiara Scaini, Alberto Tamaro, and Antonella Peresan

The Central Asia region encompasses a wide variety of climatic areas and geological settings. It is therefore prone to multiple hazards which can affect different parts of the region, including trans-boundary areas. Earthquakes, in particular, are a known threat for the region, and caused substantial damages and financial losses in the past. Here, we develop the first high-resolution regionally-consistent exposure database for Central Asia, encompassing multiple asset types including residential and non-residential buildings and transportation. The dataset was assembled using both global and regional-scale data and country-based information provided by local experts and authorities (e.g. building census, national statistics). This information includes also reconstruction costs, which are usually difficult to retrieve at country level, and images for different building typologies, which could serve as input for the development of image-based classification systems. Country-based data was collected interacting with local experts, and was supported by 5 workshops, one for each country, which fostered data sharing and knowledge transfer. Finally, the residential buildings exposure layer was used as a basis to estimate the projected exposure in 2080 under different Shared Socioeconomic Pathways. The lessons learned while developing the exposure database for Central Asia will be discussed in order to provide insights for developing similar datasets in other areas.

How to cite: Scaini, C., Tamaro, A., and Peresan, A.: Lessons learned developing a regionally-consistent exposure database for Central Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1822, https://doi.org/10.5194/egusphere-egu24-1822, 2024.

Purpose:

Strong earthquakes with greater magnitudes and longer durations can trigger numerous landslides. Several mechanisms have been proposed to explain the triggering process, such as seismic waves providing additional driving force, which increases the shear stress on the sliding plane. Earthquakes may also increase pore pressure, which reduces the effective normal stress on the sliding plane. However, the mechanisms that apply to both wet and dry conditions are not fully understood. Herein, we purposed to study the seismic response and triggering mechanisms through vibration experiments on granular materials.

Methods:

We used a ring shear apparatus to study the mechanical behavior of granular materials under cyclic loading. 0.2-0.4 mm glass spheres (SiO2) were placed in a ring shear box, and constant normal stress and constant shear stress were applied. Then, sinusoidal cyclic shear stress with different numbers of cycles were applied respectively. The frequency of cyclic loading was 1 Hz. We used dynamic triaxial-bender tests to monitor the evolution of the shear modulus of samples under cyclic loading. The confining pressure was 300 kPa and deviatoric stress was 380 kPa, and sinusoidal cyclic dynamic loads with amplitudes of 45 kPa, a frequency of 1 Hz and a cycle number of 200 were applied. All of the experiments were under dry conditions (room humidity).

Results:

The dynamic ring shear experiments show that the co-vibration and post-vibration shear displacements increased with an increase in the number of cycles, and the instability of granular materials can be triggered by a larger number of cycles while the shear stress returned to the initial value after the vibration ended. The stepwise increase curves of co-vibration shear displacement show platform segments and upward segments, the platform segments corresponded to trough segments of cyclic shear stress, and the upward segments to crest segments of cyclic shear stress. The shear displacement value of each upward segment increased with the increase in the number of vibration cycles (Fig. 1). The dynamic triaxial-bender test result shows that the specimen shear modulus decreased with the increase of the number of vibration cycles, while the density decreased slightly and the axial strain increased, roughly follow a logarithmic law during vibration (Fig. 2).

Conclusions:

Our dynamic ring shear experimental observations suggested that it is easier to trigger landslides with longer durations of vibration, and the triggering is closely related to the weakening of shear resistance. The results suggest that the reduction of shear modulus is an important mechanism for triggering failure of earthquake-triggered landslides. We infer that the earthquake-induced decrease in shear modulus was caused by structure changes, particle rearrangement, and slipping at the scale of micro-asperities.

How to cite: Luo, H., Hu, W., and Zhou, L.: Unraveling the Dynamic Weakening Mechanism of Earthquake-Triggered Landslides through Vibration-Induced Frictional Sliding Instability Experiments on Granular Materials, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2516, https://doi.org/10.5194/egusphere-egu24-2516, 2024.

The continuous functionality of critical infrastructure such as oil, gas, and water pipelines, as well as tunnels and bridges following an earthquake is important for the effective management of response actions and influences the seismic resilience of communities. Failure of such infrastructure may result in injuries and human fatalities, environmental pollution as well as significant direct and indirect economic losses. One of the most catastrophic earthquake-induced actions is the permanent fault displacements observed when fault ruptures propagate up to the ground surface in case of large magnitude earthquakes. Any structure but mostly pipelines, tunnels and bridges crossing active faults are prone to such permanent fault displacements as they develop excessive deformations as a result. The earthquake resistant design of pipelines, tunnels and bridges is based on reliable estimation of such excessive deformations.

6 February 2023 Kahramanmaras Turkiye Earthquake with Moment Magnitude 7.8 (United States Geological Survey, USGS) ruptured 3 consecutive segments of the East Anatolian Fault Zone: namely Amanos, Pazarcik and Erkenek segments. East Anatolian Fault Zone is one of the most active strike-slip faults in the world. The total observed surface rupture as a result of the Kahramanmaraş Earthquake exceeded 300km with measured permanent displacements reaching 5m near Kahramanmaras and diminishing to 0.5m towards South and North. In this study, by carrying out probabilistic fault displacement hazard assessment for these segments of the East Anatolian Fault Zone expected permanent fault displacements were computed as a function of return period. Influence of multi-segment rupture, selected earthquake recurrence model, adopted maximum magnitude value are studied on the computed permanent displacement results. Computed displacements are critically compared against the observed permanent displacements. Pipeline Systems and Liquid Storage Tanks Earthquake Code of Turkey (2021) and EN1998-4:2006 suggest the use of empirical fault rupture length-permanent fault displacement relationships in design of pipelines crossing active faults. prEN 1998-4:2022 however suggests an alternative methodology that allows approximate calculation of permanent fault displacements corresponding to any given return period based on fault mechanism, fault rupture length and fault productivity. These code-based estimates are compared with measured fault displacements and conducted probabilistic fault displacement hazard results.

How to cite: Cagnan, Z.: Comparison of probabilistic fault displacement hazard assessment results with observed permanent ground displacements in the aftermath of the 6 February 2023 Kahramanmaras Turkiye Earthquake., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2911, https://doi.org/10.5194/egusphere-egu24-2911, 2024.

EGU24-3744 | Posters on site | NH4.2

Quantifying Tsunami Hazard for the Northeastern Adriatic Coasts: A Multi-Scenario Approach 

Antonella Peresan and Hany M. Hassan

Significant earthquake-induced tsunamis in Northern Adriatic are rare and only a few historical events were reported in the literature, with sources mostly located along with central and southern parts of the Adriatic coasts. Recently, a tsunami alert system has been established for the whole Mediterranean area; however, a detailed description of the potential impact of tsunami waves on coastal areas is still missing for several sites. This study aims at modelling the hazard associated with possible tsunamis, generated by offshore earthquakes, with the purpose of contributing to tsunami risk assessment for selected urban areas located along the Northeastern Adriatic coasts. Tsunami modelling is performed by the NAMI DANCE software, which allows accounting for seismic source properties, variable bathymetry, and non-linear effects in wave’s propagation.

Preliminary hazard scenarios at the shoreline are developed for the coastal areas of Northeastern Italy and at selected cities (namely Trieste, Monfalcone, Lignano and Grado). A wide set of potential earthquake-induced tsunamis, located in three distance ranges (namely at Adriatic-wide, regional and local scales), are considered for the modelling; sources are defined according to available literature, which includes catalogues of historical tsunami and existing active faults databases. Accordingly, a preliminary set of tsunami-related parameters and maps are obtained (e.g. arrival times, maximum wave amplitude, synthetic mareograms), relevant towards planning emergency and mitigation actions at the selected sites.

In addition, a fully formalized operational procedure for time-dependent seismic hazard scenarios has been developed during the last two decades, which integrates earthquake forecasting information from pattern recognition analysis (CN algorithm), with the realistic modeling of seismic waves propagation by the neo-deterministic approach (NDSHA). For offshore large earthquakes, this integrated approach can be naturally extended to the definition of time-dependent tsunami scenarios, based on physical models of tsunami waves propagation. We review the outcomes from its applicaton for the recent events that occurred in the Adriatic region (namely: Durres, Albania 2019; Pesaro, Italy 2022), which support the possibility of developing time-dependent tsunamis scenarios, by integrating earthquake forecasts with the physical modelling of tsunami waves propagation.

How to cite: Peresan, A. and Hassan, H. M.: Quantifying Tsunami Hazard for the Northeastern Adriatic Coasts: A Multi-Scenario Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3744, https://doi.org/10.5194/egusphere-egu24-3744, 2024.

Taiwan situated on an active orogenic between the Eurasian plate and the Philippine Sea plate with an annual contraction rate of >8 cm, possesses therefore high seismicity and frequent geological hazards. Furthermore, many of the seismogenic faults pass across dense population areas and cause severe damages. In September 2022, several large earthquakes occurred in Longitudinal Valley, caused more than 100 casualties and damage roads, bridges and houses. However, exception of a few apparent surface cracks, the location, total length and actual deformation of the faults remain incomplete in most areas. In order to better constrain deformation and faulting behavior and potential threats, we focus on the Longitudinal Valley fault and Central Range fault in eastern Taiwan. To better estimate ground deformation around the active fault, large-area high-resolution geoinformatic datasets before and after the earthquake are critical. In this study, we use DMC aerial images, taken in April and September 2022, to produce DTM and orthomosaic images. Based on paired orthoimages before and after the earthquake, the particle image velocimetry (PIV) method was used to calculate the horizontal ground deformation. Vertical displacements near the fault were estimated from digital terrain models (DTM) of differences (DoD) pre- and post-earthquake. The results showed that the maximum horizontal displacement was greater than 2-3 meters and was been verified on field.

How to cite: Xu, J.-Y., Hsu, Y.-W., and Chang, K.-J.: Analysis of active fault morphotectonic behavior and seismic deformation during the September 2022 earthquakes in eastern Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3911, https://doi.org/10.5194/egusphere-egu24-3911, 2024.

EGU24-3915 | Posters on site | NH4.2

Assessment of landslide, Sediment Production and Disaster Prevention in in mountainous watersheds in Taiwan 

Yung-Wei Hsu, Jun-Yang Xu, and Kuo-Jen Chang

            Since the Chi-Chi earthquake in 1999 and the subsequent Typhoon Morakot in 2009, mass movements such as landslides have become a prominent focus of study. Particularly noteworthy are significant disasters like the Shiaolin Village debris flow and the Yushuishi debris flow in the Southern Cross-Island Highway, which have had a substantial impact on the environment and people's livelihoods. Consequently, the issue of sediment-related disasters has continued to gain attention and expand in recent years. However, estimating the volume of colluvium debris on the slope within the watershed, as well as understanding the transport and deposition of materials in the river channels, poses a challenging issue. This challenge arises from the complexity of geological factors and causes, the prolonged duration of these processes, and the difficulty of implementing engineering solutions. Therefore, effective estimation of the volume, transport, and deposition of sediment, especially in high-risk areas, along with the assessment of potential disaster risks, can be achieved with minimal human resources. This approach can provide effective early warning and reduce the impact of disasters, preventing them before they occur.

           The vigorous development of geospatial information technology has not only yielded positive results in land monitoring but has also gradually extended to other application fields. Hazard monitoring is one of its crucial applications. Geospatial information can be obtained through surveying and mapping technology, and through multi-temporal geospatial data, the production, migration, and accumulation of debris deposits can be quantitatively evaluated in a reasonable time and space within the catchment scale.

         For these purposes, this study focuses on the Laonongshi catchment, which has experienced past disasters and still retains a substantial amount of residual colluvium on its slopes. This study is dedicated in multi-temporal aerial photogrammetry and dataset generation. By combining surface geological investigations with various existing remote sensing images.Detailed DTMs and Orthomosaic images were established, since pre-Typhoon Morakot in 2009, and post events, including 2009, 2013, 2015, and 2018 with 2 meter resolution. The result reveals significant changes in the river channel and numerous reactivation of landslide debris accumulation.

How to cite: Hsu, Y.-W., Xu, J.-Y., and Chang, K.-J.: Assessment of landslide, Sediment Production and Disaster Prevention in in mountainous watersheds in Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3915, https://doi.org/10.5194/egusphere-egu24-3915, 2024.

EGU24-4914 | ECS | Posters on site | NH4.2

Application of topological filtering (DPS) algorithm for identifying linear seismogenic structures in the Lake Baikal region 

Anastasiia Agaian, Anastasia Nekrasova, and Shamil Bogoutdinov

The Topological Filtering Algorithm, Discrete Perfect Set (DPS) by Agayan et al. (2018), was developed within the framework of discrete mathematical analysis, which involves fuzzy models of discrete analogs of fundamental concepts of classical mathematical analysis. It is designed to select clusters of discrete observations according to a given criterion (classification of discrete observations belonging to one of the clusters) (Gordon, 1981). In this study, we applied the iterative S-DPS modification of the DPS algorithm (Agayan et al., 2022) for the sequential extraction of linear structures from an initial array of point objects. Specifically, we considered the catalogue data from the Baikal Division of the Geophysical Survey, Federal Research Center of the Russian Academy of Sciences, as the initial set of point objects. In each iteration, the densifications identified by S-DPS can be interpreted as discontinuous disturbances of various ranks. With each iteration, weaker yet significant concentrations are discerned. The identification of these discontinuous disturbances as linear structures, and their interpretation were conducted using an expert, non-automated approach.

Derived from expert analysis of a few sequential iterations of the S-DPS algorithm, this facilitated the identification of potential seismogenic structures for two selected territories in the Lake Baikal region. For both territories, the obtained structures were compared with the mapped active faults in the Lake Baikal region (Active Faults of Eurasia Database, Zelenin et al., 2022).

The iterative application of the S-DPS algorithm, combined with expert linear structures analysis, provides a nuanced approach to understanding the complexities of seismogenic features and their potential seismic implications. This methodology offers significant potential for analysing regional seismicity, aiming to discover new or adjust already mapped seismogenic structures.

References

Agayan SM, Bogoutdinov SR, Dzeboev, BA, Dzeranov BV, Kamaev DA, Osipov MO DPS Clustering: New Results. Appl. Sci. 2022, 12, 9335. https://doi.org/10.3390/app12189335

Zelenin E, Bachmanov D, Garipova S, Trifonov V, and Kozhurin A: The Active Faults of Eurasia Database (AFEAD): the ontology and design behind the continental-scale dataset, Earth Syst. Sci. Data, 2022, 14, 4489–4503, https://doi.org/10.5194/essd-14-4489-2022.

How to cite: Agaian, A., Nekrasova, A., and Bogoutdinov, S.: Application of topological filtering (DPS) algorithm for identifying linear seismogenic structures in the Lake Baikal region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4914, https://doi.org/10.5194/egusphere-egu24-4914, 2024.

EGU24-5603 | Posters on site | NH4.2

Spatiotemporal analysis of the background seismicity in Northern Algeria 

Elisa Varini, Amel Benali, Abdollah Jalilian, Sara Idrissou, and Antonella Peresan

This work has a twofold objective: to analyze for the first time the background seismicity of Northern Algeria and its vicinity and to apply a variety of statistical methods to identify its spatiotemporal features (Benali et al., Axioms, 2023).

The earthquake catalog of Northern Algeria and its vicinity includes events from 1950 to 2021 within the region between latitudes 32° and 38° and longitudes -2° and 10°. Based on the investigation of the frequency-magnitude for the overall catalog, the magnitude threshold for completeness is set at 3.7, so that the analyzed dataset includes 1561 earthquakes. The considered area comprises the largest and the most damaging earthquakes ever recorded in the Mediterranean region: the M7.3 earthquake at El Asnam in 1980, the M6.9 earthquake at Boumerdes in 2003, and the M6.7 earthquake at El Asnam in 1954.

The dataset is declustered by applying different methods, namely: the Gardner and Knopoff, Gruenthal, Uhrhammer, Reasenberg, Nearest Neighbour, and Stochastic Declustering methods. Each method identifies a different declustered catalog, that is a different subset of the earthquake catalog that represents the background seismicity, which is usually expected to be a realisation of a homogeneous Poisson process over time. A variety of statistical methods is applied to assess whether the background seismicity identified by each declustering method has the spatiotemporal properties typical of such a Poisson process. The main statistical tools of the analysis are the coefficient of variation, the Allan factor, the Markov-modulated Poisson process (also named switched Poisson process with multiple states), the Morisita index, and the L-function.

Summing up our findings, all declustering methods reduce the time of correlation structures in the background seismicity at small timescales, but temporal correlation still remains at intermediate and higher timescale ranges. In particular, Gruenthal and Stochastic Declustering methods turn out the most effective in removing the time clustering structures from this catalog. The spatial clustering structure is also significantly reduced, but it is not eliminated from the declustered catalogs, due to the natural clustering of seismicity along active fault systems.

How to cite: Varini, E., Benali, A., Jalilian, A., Idrissou, S., and Peresan, A.: Spatiotemporal analysis of the background seismicity in Northern Algeria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5603, https://doi.org/10.5194/egusphere-egu24-5603, 2024.

EGU24-7234 | ECS | Posters on site | NH4.2

Utilizing Various Geospatial Data for Debris Flow Geological Hazard Characterization and Mapping at Jerai Geopark, Malaysia 

Mohamad Rashidi Md.Razli, Mohamad Faruq Syahmi Md Aripin, Muhammad Afiq Ariff Mohd Hellmy, Muhammad Faris Qusyairi Hamat, Zakaria Mohamad, Abd Rasid Jaapar, Azizan Ali, and Mohamed Syahrizal Zakaria

Gunung Jerai, or Mount Jerai, is in northern Malaysia, a tropical forest where the intrusion of the granitic batholith and metasedimentary rocks controls the topographical condition. Due to the geological aesthetic and the socio-economic history, Gunung Jerai was gazetted as a National Geopark named Jerai Geopark. The geological disaster at Gunung Jerai on 18th August 2021 significantly impacted approximately 1000 families in the region, driven by a maximum cumulative rainfall of around 200mm per 3 hours. This study aims to determine the geological and geomorphological characteristics of the debris flow event on 18th August 2021, which affects mainly three catchments: Seri Perigi Catchment, Batu Hampar Catchment, and Titi Hayun Catchment by using geospatial technique. Three main remote sensing techniques were utilised to achieve the aim of the study, namely IfSAR, LiDAR, and photogrammetry. Aerial photogrammetry was conducted using fixed-wing UAVs with mounted camera sensors covering the catchment areas to visualise the current terrain condition after the debris flow event, which is utilised for the individual landslide inventory, debris flow path, formation of the natural temporary dam, and deposition of the debris flow materials. LiDAR was also employed separately using multi-rotor UAV to conduct detailed terrestrial mapping of selected major landslides to determine landslide classification such as landslide type, dimensions, activity, distribution, and causal factors. At the regional scale, DEM from IfSAR and field geological mapping is utilised for demarcation and delineation of geomorphological features and to generate morphometric data, including slope curvature, slope gradient, slope aspect, flow direction, and flow accumulation, which is derived from the DEM. This information is crucial for disaster management and mitigation efforts, aiding in better preparedness and response. These abstract aims to explain how each geospatial data is utilised and optimised to characterise the debris flow disaster event.

 

How to cite: Md.Razli, M. R., Md Aripin, M. F. S., Mohd Hellmy, M. A. A., Hamat, M. F. Q., Mohamad, Z., Jaapar, A. R., Ali, A., and Zakaria, M. S.: Utilizing Various Geospatial Data for Debris Flow Geological Hazard Characterization and Mapping at Jerai Geopark, Malaysia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7234, https://doi.org/10.5194/egusphere-egu24-7234, 2024.

EGU24-9166 | Orals | NH4.2 | Highlight

A comparison of the seismic risk assessment for the Lake Baikal railway system based on standard probabilistic and neo-deterministic approaches 

Anastasia Nekrasova, Vladimir Kossobokov, and Ekaterina Podolskaia

Seismic hazard assessment (SHA) and evaluation of seismic risks (SRs) require an adequate understanding of the actual distribution of earthquakes over magnitude, space, and time ranges. The standard probabilistic seismic hazard analysis (PSHA) has never been subjected to unbiased scrutiny before publication of the final maps, which are misleading to unacceptable human and economic losses; this has been proven on many occasions, including the most recent cases – 6 February 2023 (Turkey), 8 September 2023 (Morocco), and 1 January 2024 (Japan).  Neo-deterministic seismic hazard assessment (NDSHA) methodologies have been developed to improve the reliability and accuracy of reproducible seismic hazard maps. In the last decade, the application of NDSHA in many regions of the world has confirmed the availability of reliable and effective input for mitigating earthquake risks (Panza et al., 2021). NDSHA results have passed intensive testing by historical evidence and realistic modelling of scenario earthquakes.

We used two agents of the NDSHA synergy, i.e. Unified Scaling Law for Earthquakes (USLE) and anisotropic propagation of seismic effect, to evaluate SRs for the Lake Baikal regional railroad system on the basis of seismic hazard maps of maximum macroseismic intensity expected in 50 years with 10%, 5%, and 1% chance of exceedance. Specifically, we employed the regional layers from the widely used crowdsourced dataset, Open Street Map, which features global coverage. These layers include infrastructure elements such as tracks, bridges, and tunnels.

We have extended our analysis of seismic risk assessment for the Lake Baikal Region railway system presented earlier (Nekrasova et al., 2024) and compare our results with the SR evaluations based on the General Seismic Zonation 2016 and Global Earthquake Model 2018 final hazard maps at identical levels of probability of exceedance.

A comparison of PSHA and NDSHA approaches in application to the Lake Baikal railway system disclose significant overestimation of the reconstruction costs for expected state of extreme damage (Hazus state standard ds5 - Complete) due to earthquakes, if GSZ2016 or GEM2018 and not USLE modelling is used. In particular, the significant discrepancy in the area of expected ground shaking of macroseismic intensity VIII or higher that may damage the railroad tracks, bridges, and tunnels leads to a dramatic difference in the seismic risk values measured in arbitrary units of currency.

Our results are presented for academic purposes only. Evidently, more adequate though significantly more complex procedures involving more complicated procedures of convolution of seismic hazard, exposures, and their vulnerability are required when addressing realistic and practical assessment of seismic risks. Such assessments should involve experts in seismology, earthquake engineering, social sciences, and economics.

References

Nekrasova A, Kossobokov V, Podolskaia E (2024) Regional seismic risk assessment based on the Unified Scaling Law for Earthquakes: The Lake Baikal railway system. Soil Dynamics and Earthquake Engineering 177, 108402. https://doi.org/10.1016/j.soildyn.2023.108402

Panza G, Kossobokov V, De Vivo B, Laor E (Eds) (2021) Earthquakes and Sustainable Infrastructure: neo-deterministic (NDSHA) approach guarantees prevention rather than cure. Elsevier. Paperback ISBN: 9780128235034, eBook ISBN: 9780128235416, xxv, 672 p. https://doi.org/10.1016/C2020-0-00052-6

How to cite: Nekrasova, A., Kossobokov, V., and Podolskaia, E.: A comparison of the seismic risk assessment for the Lake Baikal railway system based on standard probabilistic and neo-deterministic approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9166, https://doi.org/10.5194/egusphere-egu24-9166, 2024.

EGU24-10711 | Orals | NH4.2

A scenario-based approach for immediate post-earthquake rockfall impact assessment and case study 

Massimiliano Alvioli, Antonella Peresan, Valerio Poggi, Chiara Scaini, Alberto Tamaro, and Fausto Guzzetti

Different approaches exist to describe the seismic triggering of rockfalls. Statistical approaches rely on the analysis of local terrain properties and their empirical correlation with observed rockfalls. Conversely, deterministic, or physically based approaches, rely on the modeling of individual trajectories of boulders set in motion by seismic shaking. They require different data and allow various interpretations and applications of their results. Here, we present a new method for earthquake-triggered rockfall scenario assessment making use of ground shaking estimates. Its key inputs are the locations of likely initiation points of rockfall trajectories, namely, rockfall sources, obtained by statistical analysis of digital topography [1,2,3].

In the approach proposed here [4], ground shaking maps corresponding to a specific earthquake are used to suppress the probability of activation of sources at locations with low ground shaking, while enhancing that in areas of high shaking close to the epicenter. Rockfall trajectories are calculated from the probabilistic source map by three-dimensional kinematic modeling using the software STONE [5,6]. Here, we apply the method to the 1976 MI = 6.5 Friuli earthquake, for which an accurate inventory of seismically-triggered rockfalls exists [7].

We suggest that using peak ground acceleration as a modulating parameter to suppress/enhance rockfall source probability the model reasonably reproduces observations. Calibration of the method is peculiar of the area, but it is expected to be valid for future earthquake-induced rockfalls in the same area, for similar seismic events. The method was previously applied at different scales and with different assumptions across Italy [8], in particular at national scale using maps of maximum expected ground shaking with different return times [9].

Results of this work [4] allow for a preliminary impact evaluation before field observations become available. We suggest that the framework may be suitable for rapid rockfall impact assessment as soon as ground-shaking estimates (from empirical ShakeMap [10] or from physical models of wave’s propagation) are available after a seismic event.

References

[1] Alvioli et al., Engineering Geology (2021). https://doi.org/10.1016/j.enggeo.2021.106301

[2] Alvioli et al., Geomatics, Natural Hazards and Risk (2022). https://doi.org/10.1080/19475705.2022.2131472

[3] Pokharel et al., Bulletin of Engineering Geology and the Environment (2023). https://doi.org/10.1007/s10064-023-03174-8

[4] Alvioli et al., Landslides (2023). https://doi.org/10.1007/s10346-023-02127-2

[5] Guzzetti et al., Computers & Geosciences (2002). https://doi.org/10.1016/S0098-3004(02)00025-0

[6] Valagussa et al., Engineering Geology (2014). https://doi.org/10.1016/j.enggeo.2014.07.009

[7] Govi, Bulletin Int. Assoc. Engineering Geology (1977). https://doi.org/10.1007/BF02592650

[8] https://frasi-project.irpi.cnr.it

[9] Alvioli et al., Geomorphology (2023). https://doi.org/10.1016/j.geomorph.2023.108652

[10] Worden et al., (2020). ShakeMap 4 Manual, USGS. https://doi.org/10.5066/F7D21VPQ

How to cite: Alvioli, M., Peresan, A., Poggi, V., Scaini, C., Tamaro, A., and Guzzetti, F.: A scenario-based approach for immediate post-earthquake rockfall impact assessment and case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10711, https://doi.org/10.5194/egusphere-egu24-10711, 2024.

EGU24-11144 | ECS | Posters on site | NH4.2

Monitoring seismic hazard with satellite geodesy in Italy: first steps for the integration of GNSS and European Ground Motion Service data 

Laura Giaccio, Roberta Ravanelli, Valeria Belloni, and Mattia Crespi

The potential role of satellite geodesy techniques for seismic hazard assessment, with particular focus on GNSS and InSAR, has been widely investigated in the last decades. These technologies can detect differences in ground velocity of less than one millimeter per year, and could therefore be suitable to highlight the accumulation of tectonic strain. While conventional strain field estimation is performed from a two-dimensional planimetric point of view, a novel approach was introduced by incorporating the independent a-priori tectonic knowledge of the study area to pre-select the directions along which strain accumulation signs should be searched [1, 2]. This method was applied to the earthquakes of Amatrice (2016) and Emilia (2012), analyzing the ground velocity estimated from GNSS station data along two transects of interest. Despite the promising results obtained, the spatial density of GNSS stations was too low to provide a detailed description of the velocity profile along the transects. In this sense, the combination  of GNSS and InSAR techniques could greatly improve these analyses. The recent European Ground Motion Service (EGMS) [3] constitutes an ideal dataset to pursue this objective. In the present work, we evaluated the suitability of EGMS data for seismic hazard assessment. To achieve this, we defined transects covering known high seismic hazard regions of Italy, following the scheme outlined in [2], but greatly improving both the spatial resolution along the transects and their inter-distance, leveraging the high spatial density of InSAR measurement points. We evaluated the velocity profile along the transects using the data provided by the EGMS service, and compared the results obtained with velocities measured from GNSS station data, both projecting GNSS data along the satellite line of sight and retrieving displacements eastward and upward considering SAR acquisitions from  ascending and descending orbits. Through this comparison we assessed whether the accuracy, the revisiting time and the covered temporal window of EGMS data are sufficient to ensure a correct velocity estimation, and took a first step in the direction of a future integration. Preliminary results obtained in the Irpinia region (Italy) suggested a good performance of EGMS data for the detailed description of the velocity profile and an excellent agreement with GNSS station data.

 

References

[1] Panza, G. F., Peresan, A., Sansò, F., Crespi, M., Mazzoni, A., & Nascetti, A. (2018). How geodesy can contribute to the understanding and prediction of earthquakes. Rendiconti Lincei. Scienze Fisiche e Naturali29, 81-93.

[2] Crespi, M., Kossobokov, V., Panza, G. F., & Peresan, A. (2020). Space-time precursory features within ground velocities and seismicity in North-Central Italy. Pure and Applied Geophysics177(1), 369-386.

[3] European Ground Motion Service. https://egms.land.copernicus.eu

How to cite: Giaccio, L., Ravanelli, R., Belloni, V., and Crespi, M.: Monitoring seismic hazard with satellite geodesy in Italy: first steps for the integration of GNSS and European Ground Motion Service data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11144, https://doi.org/10.5194/egusphere-egu24-11144, 2024.

EGU24-11974 | Orals | NH4.2 | Highlight

Why earthquakes cause disasters and how to counteract it? 

Alik Ismail-Zadeh

Scientific discoveries on earthquake occurrences integrated into hazard, vulnerability and exposure studies help in disaster risk assessment and its understanding. Research on the lithosphere dynamics, extreme seismic occurrences, and earthquake forecasting as well as seismic hazards assessments and early warning have significantly advanced during the last decades. Numerical earthquake simulations coupled with a seismic hazard analysis provide a better assessment of potential ground shaking due to future large earthquakes. Hazard analysis, modeling, and forecasting help in development of preventive measures aimed to reduce impacts of extreme events. Meanwhile, we cannot counteract disasters without the nexus between the scientific knowledge on seismic hazards, preparedness to large earthquakes and public awareness about disaster risks. Integrating natural, engineering, social and behavioral sciences and practices with policymaking should significantly improve measures to reduce disaster risks. To this end, a fundamental change in scientific approaches to disaster risk reduction is needed by shifting the current emphasis on individual hazard assessment (e.g., seismic hazard assessment only), which is dominant in the geoscientific community, to a transdisciplinary system analysis with action-oriented research on disaster risk co-produced with multiple stakeholders. This will allow for acquisition of policy-relevant knowledge and its immediate application to evidence-based policy and decisionmaking for risk reduction.

How to cite: Ismail-Zadeh, A.: Why earthquakes cause disasters and how to counteract it?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11974, https://doi.org/10.5194/egusphere-egu24-11974, 2024.

EGU24-12503 | Posters on site | NH4.2

TRACE: An approach to detect, track and monitor large floating marine litter in our seas 

Tobias Weiß and Mathias Bochow

Marine debris is a severe environmental problem. It originates from many sources and causes a wide spectrum of environmental, economic, safety, health and cultural impacts. Millions of tonnes enter the oceans every year and tackling the issue is gaining momentum at all levels.

Our project presents an approach to detect and track floating marine debris such as lost fishing nets, debris aggregations or patches based on high-resolution remote sensing time series, machine learning, and ocean current modeling. The goal is to obtain more reliable data regarding quantity, position, material properties and sources of litter as well as to address the lack of understanding of floating debris behavior in the open sea due to the limited monitoring capabilities (Garaba and Dierssen, 2018). In order to achieve this goal, a convolutional neural network was trained with a hand-labeled dataset of objects floating on the sea surface extracted from Planet satellite imagery, to learn the spatial characteristics of these objects. A software pipeline has been developed to automatically retrieve, process and analyze large amounts of satellite images and enable continuous monitoring. As identifying floating objects in the marine environment from space remains a challenging and difficult task and ground truthing is near to impossible, we further apply a mechanism to find matching objects on time series of satellite images using an ocean current model as well as different image processing techniques.

How to cite: Weiß, T. and Bochow, M.: TRACE: An approach to detect, track and monitor large floating marine litter in our seas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12503, https://doi.org/10.5194/egusphere-egu24-12503, 2024.

EGU24-12516 | Posters on site | NH4.2

Constraints on long-term seismic hazard from an intact, vulnerable stalagmite for the surroundings of Ördöglik (Čertova diera) part of Domica cave, Slovakia 

Katalin Gribovszki, Péter Mónus, Chuan-Chou Shen, Daniele Pinti, Bassam Ghaleb, Ernő Prácser, Marketa Lednická, Lili Czirok, Zoltan Jerg, Attila Novák, Tamás Bazsó, Gábor Brolly, and Sándor Szalai

To verify seismic hazard maps by independent observations that serves long-term information should be necessary. It requires studying vulnerable dripstones, since they survived all earthquakes that have occurred over thousands of years, depending on the age of them. Examination of an intact vulnerable stalagmite (IVSTM) in Ördöglik part of Domica cave (Slovakia) has been done. This IVSTM is suitable for estimating the upper limit of horizontal ground acceleration (HGA) generated by prehistoric earthquakes. This research is the continuation of our previous examination of IVSTMs in Baradla and Domica cave system, north-east Hungary.

               The density, the Young’s modulus and the tensile failure stress of the samples originating from broken speleothems have been measured in geo-mechanical laboratories, whereas the dimensions and natural frequency of the IVSTM was determined by different types of in situ observations. The value of HGA resulting in failure and the natural frequency of the IVSTM were assessed by theoretical calculations. The ages of the samples taken from a column next to the investigated IVSTM at different heights have been determined by MC-ICPMS analysis. The measured ages fall between about 7.6 and 2.4 kyr. The critical HGAvalues as a function of time going back into the past determined from the stalagmite that we investigated are presented. Our results show that all values of probabilistic seismic hazard maps, SHARE Map (Giardini et al. 2014) and PSHA Map (Tóth et al. 2006) at the location of Ördöglik part of Domica cave, are above the critical horizontal ground acceleration (CHGA) curve calculated by using the dimensions, geo-mechanical and elastic parameters of IVSTM, and the values of CHGA caves are lower than 0.05g since 2.7 kyr (0.05g was estimated by Szeidovitz et al. (2008) using another vulnerable stalagmite 4 km far from Ördöglik, in the Baradla cave.) All these means that the seismic hazard is overestimated at the territory of Ördöglik, Domica cave.

               This result have to be taken into account when calculating the seismic potential of faults near to Ördöglik part of Domica cave (e.g. Darnó and Rozsnyó lines).

How to cite: Gribovszki, K., Mónus, P., Shen, C.-C., Pinti, D., Ghaleb, B., Prácser, E., Lednická, M., Czirok, L., Jerg, Z., Novák, A., Bazsó, T., Brolly, G., and Szalai, S.: Constraints on long-term seismic hazard from an intact, vulnerable stalagmite for the surroundings of Ördöglik (Čertova diera) part of Domica cave, Slovakia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12516, https://doi.org/10.5194/egusphere-egu24-12516, 2024.

EGU24-13355 * | Posters virtual | NH4.2 | Highlight

Empowering Hazard and Disaster Informatics: Data Services at NASA GES DISC in the Earth System Observatory Era 

Binita Kc, Dave Meyer, Mahabal Hegde, Jennifer Wei, and Mohammad Khayat

NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC), a Distributed Active Archive Center (DAAC), is dedicated to archiving remotely-sensed and model observations from multiple disciplines. These datasets, stemming from NASA's Earth-observing satellites, field measurement programs, and collaborations with international partners such as the European Space Agency (ESA) ― including datasets from the TROPospheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor satellite and Radio Occultation data from Sentinel-6, are all publicly accessible. Operating as a multidisciplinary DAAC, GES DISC equips users with the ability to integrate datasets across multiple disciplines while ensuring data quality and provenance.

GES DISC offers comprehensive services, enabling users to map and monitor extreme weather and climate hazards, including tropical cyclones and floods, through high spatial and temporal resolution datasets in near real-time. Giovanni, a visualization and analytical tool designed for users with limited expertise, has been widely utilized in risk and post-disaster assessments, and natural hazards research. Additionally, API services such as Data Rods, offering a long-term time series of climate datasets, aid in monitoring the vulnerability of critical infrastructures to hydro-meteorological conditions.

In response to the increasing data volumes in the Earth System Observatory (ESO) era, GES DISC is currently migrating data and services to the Earthdata Cloud. This cloud migration not only advances hazard and disaster studies, but also empowers users to fully leverage the benefits of the cloud, such as improved accessibility, cost-efficiency, scalability, and collaboration.

How to cite: Kc, B., Meyer, D., Hegde, M., Wei, J., and Khayat, M.: Empowering Hazard and Disaster Informatics: Data Services at NASA GES DISC in the Earth System Observatory Era, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13355, https://doi.org/10.5194/egusphere-egu24-13355, 2024.

EGU24-19587 | Orals | NH4.2

A Robust Satellite Technique for monitoring landslides impact on electrical infrastructures 

Valerio Tramutoli, Mohammad Kazemi Garajeh, Annibale Guariglia, Parivash Paridad, Raffaele Santangelo, and Valeria Satriano

Natural disasters, in recent years, are increasinglyaffecting critical infrastructures and, particularly, electric and gas supply pipelineswhich play a vital role in modern society. In order to enable effectivedisaster response, ensure the safety of affected populations, and facilitatethe recovery and rebuilding process following sudden-onset disasters, it is crucialto have accurate and timely information on infrastructure damage. This studyimplements an advanced multi-temporal technique to detect even small landslideaffecting electrical poles.  Land-coverinformation obtained by the Multispectral Instrument (MSI) sensor aboard theCopernicus Sentinel-2 platforms are used to timely (within days/weeks) identifysuch events. To this end, long-term satellite data are processed in the GoogleEarth Engine (GEE) environment to preliminarily characterize unperturbed soilconditions before to implement the RST (Robust Satellite Techniques) foranomalous soil conditions identification. Our findings reveal that severalelectrical poles had been affected by landslides in Sicily from 2016-2023. Theresults of this study also confirmed the efficiency of an RST-likeapproach  for landslide detection.

How to cite: Tramutoli, V., Kazemi Garajeh, M., Guariglia, A., Paridad, P., Santangelo, R., and Satriano, V.: A Robust Satellite Technique for monitoring landslides impact on electrical infrastructures, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19587, https://doi.org/10.5194/egusphere-egu24-19587, 2024.

EGU24-19654 | ECS | Orals | NH4.2

Integratıng earth observatıons for enhancıng human health and ınfrastructure resılıence durıng desert dust storms 

Petros Mouzourides, Chrysoula Papathanasiou, Eleftheriou Andreas, Giorgos Nikolaidis, Marios Vlachos, Valantis Tsiakos, Georgios Tsimiklis, Chrysanthos Savvides, Emily Vasiliadou, Angelos Amditis, and Marina K-A Neophytou

As global climate change continues to exacerbate global warming and global warming moves into the future, desert ecosystems are expected to face a heightened vulnerability to its impacts, including rising temperatures, sea level rise and variations in intensity and frequency of precipitation. These conditions directly affect the structural integrity of desert ecosystems and their ability itself to function as ecosystems. The CiROCCO Project aims to address this critical issue by integrating a network of cost-effective sensing nodes with advanced remote and in-situ data fusion techniques1. This initiative intends to cover under-sampled desert areas and those profoundly impacted by Desert Dust Storms (DDS). The project focuses on four pilot areas, namely Egypt, Cyprus, Serbia, and Spain. Within the context of the Cyprus pilot study, CiROCCO aims to examine the nexus between the urban environment in the Municipality of Idalion and the consequences of DDS on air quality2 and public health3. As part of the project, an Early Warning System (EWS) for Air Quality will be put in place, with weather prediction models playing a significant role in the development of the EWS. The evaluation of the WRF-Chem model forms an integral part of the preliminary phase for establishing the Cyprus pilot. This assessment utilizes PM10 near-ground concentration obtained from a background monitoring station in Cyprus2, spanning the period from 2021 to 2023, predating the installation of the CIROCCO sensing node network. Future reevaluation of the WRF-Chem model aims to quantify the improvement in prediction accuracy resulting from the assimilation of model forecasts with in-situ datasets and earth observations facilitated by the CIROCCO infrastructure. Regulatory authorities plan to adopt the EWS, providing public access via a dedicated website and mobile app. The project contributes insights applicable to similar regions in Cyprus and Eastern Europe.

AKNOWLEDGMENTS

This research work is part of the CiROCCO Project. CiROCCO Project is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or REA. Neither the European Union nor the granting authority can be held responsible for them.

REFERENCES

1Papathanasiou C., Mouzourides P., Vlachos M., Neophytou M.K-A, Tsiakos V., Tsimiklis G., Amditis A. (2023). Enhancing in-situ environmental observation to support desert dust storm events monitoring, 10th Int. Conference on Civil Protection & New Technologies, SafeGreece2023, 25-27 September, Athens, Greece

2Kinni, P., Kouis, P., Dimitriou, H., Yarza, S., Papatheodorou, S.I., Kampriani, E., Charalambous, M., Middleton, N., Novack, V., Galanakis, E. and Yiallouros, P.K., (2021). Health effects of desert dust storm events in the south-eastern Mediterranean: perceptions and practices of local stakeholders. Eastern Mediterranean Health Journal, 27(11), pp.1092-1101.

3Achilleos, S., Mouzourides, P., Kalivitis, N., Katra I., Kloog, I., Kouis, P., Middleton, N., Mihalopoulos, N., Neophytou, M., Panayiotou, A., Papatheodorou, S., Savvides, C., Tymvios, F., Vasiliadou, E., Yiallouros, P. and Koutrakis, P. (2020).  Spatio-temporal variability of desert dust storms in Eastern Mediterranean (Crete, Cyprus, Israel) between 2006 and 2017 using a uniform methodology, Science of the Total Environment, 714, 136693

How to cite: Mouzourides, P., Papathanasiou, C., Andreas, E., Nikolaidis, G., Vlachos, M., Tsiakos, V., Tsimiklis, G., Savvides, C., Vasiliadou, E., Amditis, A., and Neophytou, M. K.-A.: Integratıng earth observatıons for enhancıng human health and ınfrastructure resılıence durıng desert dust storms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19654, https://doi.org/10.5194/egusphere-egu24-19654, 2024.

EGU24-19972 | ECS | Orals | NH4.2 | Highlight

Testing machine learning models for rapid building damage assessment at regional scale. 

Subash Ghimire and Philippe Guéguen

Assessing or forecasting seismic damage to buildings is crucial for earthquake disaster management. Several classical damage assessment methods are available for seismic damage assessment by combining hazard, exposure, and vulnerability. However, during emergencies, collecting all the necessary data for seismic damage assessment may not be feasible due to time and resource constraints, as this information may not be readily available.

In this context, machine learning methods can offer a paradigm shift by reasonably assessing damage by relying on readily available data cost-effectively. In this study, we aim to study the damage prediction efficacy of machine learning models for regional scale damage assessment. Machine learning models were trained and tested on the post-earthquake building damage database.

Results show that the readily available building features such as the number of stories, age, floor area, and height can result in a reasonable assessment of damage at a large scale, mainly when using a traffic-light-based (green, yellow, and red) damage classification framework.

The machine learning models trained on past earthquake building damage portfolios can reasonably estimate damage during the future earthquake for a different region with similar building portfolios.

How to cite: Ghimire, S. and Guéguen, P.: Testing machine learning models for rapid building damage assessment at regional scale., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19972, https://doi.org/10.5194/egusphere-egu24-19972, 2024.

EGU24-20837 | Posters virtual | NH4.2 | Highlight

Global Flood Alerting with an Ensemble of Models and Remotely Sensed Observations 

Margaret Glasscoe, Bandana Kar, Guy Schumann, Marina Mendoza, Doug Bausch, Jun Wang, and Greg Hampe

Flooding is one of the most frequent and costliest extreme weather events. The Model of Models (MoM) generates integrated products using ensembled hydrologic models and flood outputs derived from Earth observations. MoM provides global flood early warning and near-real time flood severity estimation. MoM results are shared via the Pacific Disaster Center’s (PDC) DisasterAWARE® multi-hazard alerting platform to the global community. Currently, DisasterAWARE incorporates Model of Models (MoM) outputs as flood “incidents,” visually depicting potential floods in the context of population and infrastructure that may become affected. Automated procedures categorize MoM outputs as DisasterAWARE “hazards,” allowing for their dissemination to users along with other flood products that assess potential impacts.

How to cite: Glasscoe, M., Kar, B., Schumann, G., Mendoza, M., Bausch, D., Wang, J., and Hampe, G.: Global Flood Alerting with an Ensemble of Models and Remotely Sensed Observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20837, https://doi.org/10.5194/egusphere-egu24-20837, 2024.

EGU24-20937 | Orals | NH4.2

Using rapid source characterisation to improve ShakeMaps and impact forecasts for large earthquakes (M6.5+) in New Zealand 

Anna Kaiser, Jen Andrews, Bill Fry, Nick Horspool, Biljana Lukovic, Chris Massey, Emily Warren-Smith, Calum Chamberlain, Tatiana Goded, Elisabetta D'Anastasio, Chris Zweck, and Florent Aden

The New Zealand R-CET Endeavour programme has been developing a suite of tools to characterize the earthquake source and its shaking in near real-time.  A key goal is to provide pathways to improve rapid earthquake impact forecasts.  

Small-to-moderate earthquakes can be reasonably represented by a ‘point source’.  This allows us to generate first shaking maps (GNS Shaking Layers; Horspool et al. 2023) automatically and robustly based on basic earthquake solutions (magnitude and hypocentre). These maps are now routinely available to the public within 10 – 20 minutes: https://www.geonet.org.nz/about/earthquake/shakinglayers#:~:text=What%20is%20Shaking%20Layers%3F,intensity%20anywhere%20in%20the%20country.

For very large earthquakes (M6.5+), a ‘point-source’ is a poor representation of the earthquake, which can rupture tens to hundreds of kilometres of the earth.  First shaking models based on ‘point sources’ could severely underestimate shaking in areas further from the epicentre, but close to the fault rupture. Rapid 3D characterization of the rupture area, even if approximate, has the potential to significantly improve shaking estimates, and allow meaningful first impact forecasts to be generated.

Here we present an overview of rapid source characterization tools implemented for New Zealand under the R-CET programme. These tools include FinDer (Andrews et al. 2023), w-phase (Fry et al. 2022), EQCorrScan (Chamberlain et al. 2017; Warren-Smith & Chamberlain 2022), G-FAST and others . We show examples of tool outputs for large (M6.5+) historical earthquakes in New Zealand and examine their potential to improve rapid shaking models, loss estimates and landslide forecasts. Our results show the importance of including rapid source characterization as a key component of our earthquake response systems, to underpin quality scientific advice for emergency responders.

How to cite: Kaiser, A., Andrews, J., Fry, B., Horspool, N., Lukovic, B., Massey, C., Warren-Smith, E., Chamberlain, C., Goded, T., D'Anastasio, E., Zweck, C., and Aden, F.: Using rapid source characterisation to improve ShakeMaps and impact forecasts for large earthquakes (M6.5+) in New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20937, https://doi.org/10.5194/egusphere-egu24-20937, 2024.

Earthquake catalogues, vital for understanding earthquake dynamics, often grapple with incompleteness across varying time scales. Our research pioneers an innovative strategy to seamlessly integrate time-varying incompleteness into the Epidemic-Type Aftershock Sequence (ETAS) model. Leveraging the Bayesian prowess of inlabru package in R programming language, which is based on the Integrated Nested Laplace Approximation (INLA) method, we not only capture uncertainties but also forge a robust bridge between short-term to long-term gaps in records of earthquakes.

Our methodology, a fusion of the ETAS model and inlabru, provides a comprehensive framework that adapts to diverse scales of incompleteness. We address the complex nature of seismic patterns by considering both short-term gaps in early aftershocks (minutes to a few days) and long-term irregularities (years to centuries) in historical earthquake data records. Technically, the short-term incompleteness period arises from seismic network saturation during periods of high activity, resulting in the underrecording of small events, while the long-term incompleteness originates from sparse network coverage and inability to detect events over extended time. Bayesian foundation of inlabru enriches the model with posterior distributions, empowering us to navigate uncertainties and refine seismic hazard assessments. By utilising a combination of simulated synthetic data and real earthquake catalogues, our results showcase the impact of this approach on the ETAS model, markedly improving its predictive accuracy across various temporal scales of incompleteness.

In this study, we present an initiative in seismicity modelling that bridges temporal gaps, allowing the ETAS model to evolve with the ever-changing landscape of earthquake data incompleteness. This research not only enriches our understanding of spatiotemporal seismicity patterns but also lays the groundwork for more resilient and adaptive aftershock forecasting, ultimately equipping decision-makers with more reliable information about seismic hazards, and enhancing community resilience in the face of earthquakes.

How to cite: Kamranzad, F., Naylor, M., and Lindgren, F.: Bridging time scales for comprehensive ETAS modelling to accommodate short-term to long-term incompleteness of seismicity catalogues, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-401, https://doi.org/10.5194/egusphere-egu24-401, 2024.

EGU24-634 | ECS | Posters on site | NH4.3

Mapping micro-seismicity around a nuclear power station in stable South Africa through machine learning 

Wade van Zyl, Diego Quiros, and Alastair Sloan

Ground motion caused by near-source seismic waves from shallow earthquakes can be dangerous to vital infrastructure such as nuclear power plants. South Africa is a stable continental region (SCR), however significant seismicity is known to occur. Nearby Cape Town, and the Koeberg Nuclear Power Station, historical sources record an earthquake with a potential magnitude of 6.5 in 1809. On September 29th, 1969 the magnitude 6.3 Ceres-Tulbagh earthquake affected an area less than 100 kilometers of the Koeberg Nuclear Power Station. These events emphasize the need to take the potential seismic hazard in this area seriously. Previous research has shown that the source zones of historic and even prehistoric SCR earthquakes are frequently related with enhanced microseismicity over hundreds or even thousands of years. This study seeks to investigate possible source zones for the 1809 event, and possible sources of future damaging earthquakes, by establishing whether earthquakes can be detected on regional structures. To accomplish these goals, we deployed 18 3-component seismographs over a 40-by-35-kilometer area near the Koeberg Nuclear Power Station. The network, which covered the Colenso fault zone, was also near the postulated Milnerton fault, the Ceres-Tulbagh region, and the Cape Town area. The network recorded for three months between August and October 2021. We looked for seismicity around known structures, like the Colenso fault, using supervised machine learning algorithms like PhaseNET, traditional STA/LTA algorithms, and manual inspection in addition to unsupervised machine learning algorithms such as Density-based spatial clustering of applications with noise (DBSCAN) and Bayesian Gaussian Mixture Models (BGMMs). We found 35 occurrences dispersed throughout our research area. These events appear to be organized into three broad groups, the first being an offshore cluster outside of the study region, and the second being a scattered cluster between the Colenso fault system and the postulated Milnerton Fault. The third concentrates on the Colenso Fault system, implying that it may be active. Additional results from our research show that traditional methods like STA/LTA are far less accurate at detecting micro-seismic events than manual inspection of waveform data and machine learning (i.e., where the unsupervised and supervised machine learning algorithms get combined to form an earthquake identification tool).

How to cite: van Zyl, W., Quiros, D., and Sloan, A.: Mapping micro-seismicity around a nuclear power station in stable South Africa through machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-634, https://doi.org/10.5194/egusphere-egu24-634, 2024.

EGU24-2615 | ECS | Orals | NH4.3

What do seismic clusters tell us about fault stability? 

Davide Zaccagnino, Filippos Vallianatos, Giorgios Michas, Luciano Telesca, and Carlo Doglioni

Seismic activity clusters in space and time due to stress accumulation and static and dynamic triggering. Therefore, both moderate and large magnitude events can be preceded by smaller events and also seismic swarms can occur without being succeeded by major shocks – which represents the vast majority of cases.

Unveiling if seismic activity can forewarn mainshocks, being somewhat distinguished by swarms, is an issue of crucial importance for the development of short-term seismic hazard. The analysis of thousand clusters of seismicity before mainshocks in Southern California and Italy highlights that the surface over which selected seismic activity spreads is positively correlated with the magnitude of the impending mainshock, as well as the cumulative seismic moment, the number of earthquakes, the variance of magnitude and its entropy, while no significant difference is observed in the duration, seismic rate, and trends of magnitudes and interevent times between foreshocks and swarms. Our interpretation is that crustal volumes and fault interfaces host more and more correlated seismicity as they become unstable, and some properties of seismic clusters may mark their state of stability. For this reason, large mainshocks tend to occur in more extended correlated regions and because of the scaling of maximum magnitudes with the size of unstable faults. Considering this, the recording of more numerous and energetic cluster activity before mainshocks than during swarms is also reasonable.

In recent years, our ability to track seismic clusters has improved outstandingly, so that their structural and statistical characterization can be performed almost in real time. Therefore, it may be possible to compare the current features of the active seismic cluster with the cumulative distribution functions of past seismicity. However, we would like to stress that foreshocks should not be considered as precursors in the sense that neither they forewarn mainshocks, nor they are physically different from swarms: the precursor is not in seismic activity itself, but in the development of mechanical instability within crustal volumes.

How to cite: Zaccagnino, D., Vallianatos, F., Michas, G., Telesca, L., and Doglioni, C.: What do seismic clusters tell us about fault stability?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2615, https://doi.org/10.5194/egusphere-egu24-2615, 2024.

From October to December 2019, the provinces of Cotabato and Davao del Sur in the Philippines experienced an earthquake sequence that involved five M~6 (Mw 6.4, 6.6, 5.9, 6.5, and 6.7) inland earthquakes. A deep-neural network-based phase picker, PhaseNet, was used to obtain the seismic phases of earthquake waveforms of stations within 200 km from the area of the events for 80 days from October 16 to December 31, 2019. The acquired seismic phases were initially associated and located using the Rapid Earthquake Association and Location (REAL). Subsequently, the initial hypocenter locations were adjusted through relocation utilizing VELEST, with further refinement achieved through a relative relocation technique hypoDD. By employing these methodologies, we successfully created an earthquake catalog that contains ~5,000 earthquakes for the corresponding period. The number of determined earthquakes through this method surpassed the ~3,000 event count reported in the original catalog by DOST-PHIVOLCS which depended solely on manually selected seismic phases. The spatial distribution of the relocated hypocenters reveals two seismic alignments: one trending in the SW-NE direction, parallel to the existing mapped active faults, and the other in the NW-SE direction. These lineaments intersect near the location of the Mw6.4 event, suggesting the presence of a conjugate fault or cross fault. The created earthquake catalog illuminates the spatial and temporal evolution of seismicity following each significant event, offering insights into the detailed patterns that characterize the clustering of aftershocks.

How to cite: Sawi, P., Kita, S., and Bürgmann, R.: Machine-Learning-based Relocation Analysis: Revealing the Spatiotemporal Changes in the 2019 Cotabato and Davao del Sur Earthquakes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3482, https://doi.org/10.5194/egusphere-egu24-3482, 2024.

EGU24-3569 | ECS | Posters on site | NH4.3

Testing the Potential of Deep Learning in Earthquake Forecasting 

Jonas Köhler, Wei Li, Johannes Faber, Georg Rümpker, and Nishtha Srivastava

Reliable earthquake forecasting methods have long been sought after, and so the rise of modern data science techniques raises a new question: does deep learning have the potential to learn this pattern? 
In this study, we leverage the large amount of earthquakes reported via good seismic station coverage in the subduction zone of Japan.  We pose earthquake forecasting as a classification problem and train a Deep Learning Network to decide, whether a timeseries of length ≥ 2 years will end in an earthquake on the following day with magnitude ≥ 5 or not.
 
Our method is based on spatiotemporal b value data, on which we train an autoencoder to learn the normal seismic behaviour. We then take the pixel by pixel reconstruction error as input for a Convolutional Dilated Network classifier, whose model output could serve for earthquake forecasting. We develop a special progressive training method for this model to mimic real life use. The trained network is then evaluated over the actual dataseries of Japan from 2002 to 2020 to simulate a real life application scenario. The overall accuracy of the model is 72.3%. The accuracy of this classification is significantly above the baseline and can likely be improved with more data in the future.

How to cite: Köhler, J., Li, W., Faber, J., Rümpker, G., and Srivastava, N.: Testing the Potential of Deep Learning in Earthquake Forecasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3569, https://doi.org/10.5194/egusphere-egu24-3569, 2024.

EGU24-3684 | Posters on site | NH4.3

Stress Shadows: Insights into Physical Models of Aftershock Triggering 

Jeanne Hardebeck and Ruth Harris

Why some aftershocks appear to occur in stress shadows, regions of Coulomb stress decrease due to a mainshock, is an open question with implications for physical and statistical aftershock models. New machine-learning focal mechanism catalogs make it possible to study the fault orientations of aftershocks occurring in the stress shadows, and test competing hypotheses about their origins. There are three main hypotheses: (1) Aftershocks appear in shadows because of inaccuracy in the computed stress change. (2) Aftershocks in the shadows occur on faults with different orientations than the model receiver faults, and these unexpected fault orientations experience increased Coulomb stress. (3) Aftershocks in the shadows are triggered by dynamic stress changes. We test these three hypotheses on the 2016 Kumamoto and 2019 Ridgecrest sequences. We test Hypothesis 1 through many realizations of the stress calculations with multiple mainshock models, multiple receiver fault orientations based on background events, and a range of coefficients of friction. We find that numerous aftershocks are consistently in the stress shadows. To test Hypothesis 2, we consider whether the individual event focal mechanisms receive an increase of Coulomb stress. Again, we perform many realizations of the stress calculation, this time with receiver fault orientations based on the focal mechanism and its uncertainty. Many of the aftershocks in the shadows consistently show a Coulomb stress decrease on the planes of their focal mechanisms. These results imply that aftershocks do occur in stress shadows, many on fault planes receiving a decrease in static Coulomb stress, contrary to Hypotheses 1 and 2. We test Hypothesis 3 by investigating the modeled dynamic stress changes on the individual event focal mechanisms. Preliminary results show that while the amplitude of the dynamic Coulomb stress change is generally lower on the aftershock nodal planes than on the planes of background events, the amplitude of the dynamic normal stress change is often 20%-100% higher. This suggests a dynamic triggering mechanism related to changing fault strength.

How to cite: Hardebeck, J. and Harris, R.: Stress Shadows: Insights into Physical Models of Aftershock Triggering, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3684, https://doi.org/10.5194/egusphere-egu24-3684, 2024.

With earthquake disasters inflicting immense devastation worldwide, advancing reliable prediction models utilizing diverse data paradigms offers new perspectives to unlock practicable prediction solutions. As reliable earthquake forecasting remains a grand challenge amidst complex fault dynamics, we employ combined finite-discrete element method (FDEM) simulations to generate abundant laboratory earthquake data. We propose a multimodal features fusion model that integrates temporal sensor data and wavelet-transformed visual kinetic energy to predict laboratory earthquakes. Comprehensive experiments under varied stress conditions confirm the superior prediction capability over single modal approaches by accurately capturing stick slip events and patterns. Furthermore, efficient adaptation to new experiments is achieved through fine-tuning of a lightweight adapter module, enabling generalization. We present a novel framework leveraging multimodal features and transfer learning for advancing physics-based, data-driven laboratory earthquake prediction. As increasing multi-source monitoring data becomes available, the established modeling strategies introduced here will facilitate the development of reliable real world earthquake analysis systems.

How to cite: Gao, K.: Laboratory earthquake prediction via multimodal features, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3745, https://doi.org/10.5194/egusphere-egu24-3745, 2024.

EGU24-4379 | ECS | Orals | NH4.3

Magnitude correlation exposes hidden short-term earthquake catalog incompleteness 

Paola Corrado, Marcus Herrmann, and Warner Marzocchi

Current models used for earthquake forecasting assume that the magnitude of an earthquake is independent of past earthquakes, i.e., the earthquake magnitudes are uncorrelated. Nevertheless, several studies have challenged this assumption by revealing correlations between the magnitude of subsequent earthquakes in a sequence. These findings could significantly improve earthquake forecasting and help in understanding the physics of the nucleation process.

We investigate this phenomenon for the foreshock sequence of the first 2019 Ridgecrest event (Mw6.4) using a high-resolution catalog; choosing this foreshock sequence has been guided by a low b-value (~0.68 ± 0.06 after converting local magnitudes to moment magnitudes) and a significant magnitude correlation, even when considering only earthquakes above the completeness level estimated with different methods. To disregard incomplete events in the b-value estimation, we apply the b-positive approach (van der Elst 2021), i.e., using only positive magnitude differences; those magnitude differences are uncorrelated and we obtain a markedly higher b-value (~0.9 ± 0.1). Apparently, the foreshock sequence contained substantial short-term aftershock incompleteness due to a Mw4.0 event.

We observe a similar behaviour for whole Southern California after stacking earthquake sequences. Finally, we generate synthetic catalogs and apply short-term incompleteness to demonstrate that common methods for estimating the completeness level still result in magnitude correlation, indicating hidden incompleteness.

Our findings highlight that (i) existing methods for estimating the completeness level have limited statistical power and the remaining incompleteness can significantly bias the b-value estimation; (ii) the magnitude correlation is the most powerful property to detect incompleteness, so it should supplement statistical analyses of earthquake catalogs.

How to cite: Corrado, P., Herrmann, M., and Marzocchi, W.: Magnitude correlation exposes hidden short-term earthquake catalog incompleteness, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4379, https://doi.org/10.5194/egusphere-egu24-4379, 2024.

EGU24-4958 | Posters on site | NH4.3

Unraveling the Preparatory Processes of the 2023 Kahramanmaraş MW7.8-7.6 Earthquake Doublet 

Fengling Yin and Changsheng Jiang

Within a span of 9 hours on February 6, 2023, two significant earthquakes, with magnitudes of Mw7.8 and Mw7.6, struck the southeastern part of Türkiye and the northern region of Syria, resulting in significant casualties and widespread economic losses. The occurrence of such intense earthquakes in rapid succession on adjacent faults, especially within a highly complex intraplate region with a multi-fault network, poses a rare phenomenon, presenting new challenges for seismic hazard analysis in such areas. In order to investigate whether the preparatory processes for the Mw7.8-7.6 earthquake doublet could be identified on a large spatial scale prior to the seismic events, we employed a data-driven approach for b-value calculation. The difference in b values from the background values (Δb) in a reference period were used as inputs, and the Cumulative Migration Pattern (CMP) method, quantitatively describing the migration of seismic activity, was utilized to calculate the corresponding probability distributions. The results indicate a widespread phenomenon of decreasing b-values in the study area over a decade before the occurrence of the earthquake doublet, revealing a significant enhancement of differential crustal stress over a large region. Additionally, despite not being the region with the most pronounced decrease in b-values, there is a distinct high probability distribution of CMP near the nucleation points of the earthquake doublet, indicating a spatial and temporal "focus" of increased crustal differential stress in the study area, unveiling the preparatory process of the earthquake doublet. This study reveals quantifiable migration patterns over a long-time scale and a large spatial extent, providing new insights into the evolution and occurrence processes of the 2023 Kahramanmaraş Mw7.8-7.6 earthquake doublet. Moreover, it offers potential clues for seismic hazard analysis in such intraplate regions with multiple fault systems.

How to cite: Yin, F. and Jiang, C.: Unraveling the Preparatory Processes of the 2023 Kahramanmaraş MW7.8-7.6 Earthquake Doublet, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4958, https://doi.org/10.5194/egusphere-egu24-4958, 2024.

EGU24-5516 | ECS | Posters on site | NH4.3

Asperity distribution and earthquake recurrence time based on patterns of forerunning earthquakes. 

Venkata Gangadhara Rao Kambala and Piotr Senatorski

Abstract. Due to the long recurrence time of the largest earthquakes and the short time covered by seismic catalogues, the potential for the strongest earthquakes in a given region should be estimated based both on combined seismological and geodetic observations, as well as on the developed seismicity models. At the same time, the asperity model, which is a general view of earthquake occurrence in seismic zones, still requires refinement and more solid empirical support.

In this study, we use new data science methods to analyze and interpret various data from selected subduction and collision zones, including Japan, Chile, and Himalaya-Nepal regions. First, we estimate the expected recurrence times of large earthquakes within a given magnitude range as functions of the Gutenberg-Richter’s b values, for  the assumed maximum magnitude and seismic moment deficit accumulation rate due to the tectonic plate movement. Second, we show seismicity patterns and underlying asperity structures using graphs representing the forerunning and afterrunning earthquakes, which are strictly defined based on the location of earthquakes in time and space, as well as their sizes.

In particular, we propose a method to estimate the rupture areas and magnitudes of possible megathrust earthquakes based on seismicity from the last few decades. We use the graph characteristics to distinguish among different seismicity patterns and scenarios. We also argue that changes in these features over time and space can be used to forecast seismicity forecasting.

 

Keywords: Earthquake forecasting, Gutenberg-Richter law, Recurrence time, Asperities, Forerunning earthquakes.

How to cite: Kambala, V. G. R. and Senatorski, P.: Asperity distribution and earthquake recurrence time based on patterns of forerunning earthquakes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5516, https://doi.org/10.5194/egusphere-egu24-5516, 2024.

EGU24-5878 | Posters on site | NH4.3

Forecasting Strong Subsequent Earthquakes in Japan Using NESTORE Machine Learning Algorithm: preliminary results  

Stefania Gentili, Giuseppe Davide Chiappetta, Giuseppe Petrillo, Piero Brondi, Jiancang Zhuang, and Rita Di Giovambattista

NESTORE (Next STrOng Related Earthquake) is a machine learning algorithm for forecasting strong aftershocks during ongoing earthquake clusters. It has already been successfully applied to Italian, Greek and Californian seismicity in the past. A free version of the software in MATLAB (NESTOREv1.0) is available on GitHub. The method is trained on the region under investigation using seismicity characteristics. The obtained region-specific parameters are used to provide the probability, for the ongoing clusters, that the strongest aftershock has a magnitude greater than or equal to that of the mainshock - 1. If this probability is greater than or equal to 0.5, the cluster is labeled as type A, otherwise as type B. The current version of the code is modular and the cluster identification method is based on a window approach, where the size of the spatio-temporal window can be adjusted according to the characteristics of the analyzed region.

In this study, we applied NESTORE to the seismicity of Japan using the Japan Meteorological Agency (JMA) catalogue from 1973 to 2022. To account for the highly complex seismicity of the region, we replaced the cluster identification module with software that uses a stochastic declustering approach based on the ETAS model.

The analysis is performed in increasing time intervals after the mainshock, starting a few hours later, to simulate the evolution of knowledge over time. The analysis showed a high prevalence of clusters where there are no strong earthquakes later than 3 hours after the mainshock, leading to an imbalance between type A and type B classes.

NESTORE was trained with data from 1973 to 2004 and tested from 2005 onwards. The large imbalance in the data was mitigated by carefully analyzing the training set and developing techniques to remove outliers. The cluster type forecasting was correct in 84% of cases.

 

Funded by a grant from the Italian Ministry of Foreign Affairs and International Cooperation and Co-funded within the RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan - NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005) and by the NEar real-tiME results of Physical and StatIstical Seismology for earthquakes observations, modeling and forecasting (NEMESIS) Project (INGV).

How to cite: Gentili, S., Chiappetta, G. D., Petrillo, G., Brondi, P., Zhuang, J., and Di Giovambattista, R.: Forecasting Strong Subsequent Earthquakes in Japan Using NESTORE Machine Learning Algorithm: preliminary results , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5878, https://doi.org/10.5194/egusphere-egu24-5878, 2024.

EGU24-6037 | Orals | NH4.3

Why is  b=1? 

Ian Main and Gina-Maria Geffers

The exponent b of the log-linear frequency-magnitude relation for natural seismicity commonly takes values that are statistically indistinguishable from b=1.  There are some exceptions, notably with respect to focal mechanism and for volcanic and induced seismicity, but it is possible these could be explained at least in part by variability in the dynamic range of measurements between the minimum magnitude of complete reporting and the maximum magnitude, especially where the dynamic range of the statistical sample is small.  However, in laboratory experiments and in discrete element simulations a wide range of b-values for acoustic emissions are consistent (after accounting for systematic differences in the transducer response) with systematic variations in the range  as the stress intensity factor increases from its minimum to its maximum, critical value.  The question remains: why is  an attractor stationary state for large-scale seismicity?  Previous attempts to answer this question have relied on a simple geometric ‘tiling’ argument that is inconsistent with the spatial distribution of earthquake locations, or a hierarchical ‘triple-junction’ model that has not been validated by observation.  Here, we derive a closed analytical solution for the maximum entropy -value, conditional on the assumption that earthquake magnitude scales linearly with the logarithm of rupture area. In the limit of infinite dynamic range, the solution is .  The maximum entropy -value converges to this value asymptotically from above as dynamic range increases for large systems at steady state.  This is in contrast to a previous maximum entropy solution based on analysing the spectrum in ‘natural time’ of earthquake catalogues, where larger samples with greater dynamic range lead to a divergence from .  The new theory is consistent with the trend in b-value convergence from above towards an asymptotic limit of in b=1.027±0.015 at 95% confidence from the global CMT earthquake frequency-moment catalogue for data since 1990.

How to cite: Main, I. and Geffers, G.-M.: Why is  b=1?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6037, https://doi.org/10.5194/egusphere-egu24-6037, 2024.

EGU24-6097 | Orals | NH4.3

The performance of the Foreshock Traffic Light System for the period 2016-2024 

Laura Gulia, Stefan Wiemer, Emanuele Biondini, Bogdan Enescu, and Gianfranco Vannucci

Strong earthquakes are followed by countless smaller events, whose number decays with time: a posteriori, we call them aftershocks. Sometimes, this sequence is interrupted by a larger event, and the “aftershocks” turn out to be foreshocks. In 2019, Gulia and Wiemer have proposed traffic light tool, named the Foreshock Traffic Light System (FTLS), that can discriminate between foreshocks and aftershocks, by monitoring the size distribution of events closely. The model successfully passed the first near real-time test (Gulia et al., 2020). A new version of the code, that can run in real-time, has been recently developed; since testing is the essence of the scientific method and is fundamentally important in seismicity forecast evaluation, we here show the performance of the new version of the FTLS through pseudo-prospective and, when possible, real-time tests on the available seismic sequences between 2016 and 2024.

How to cite: Gulia, L., Wiemer, S., Biondini, E., Enescu, B., and Vannucci, G.: The performance of the Foreshock Traffic Light System for the period 2016-2024, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6097, https://doi.org/10.5194/egusphere-egu24-6097, 2024.

EGU24-6346 | Posters on site | NH4.3

Characterizing clusters with strong subsequent events in Central Italy using RAMONES 

Piero Brondi, Stefania Gentili, Matteo Picozzi, Daniele Spallarossa, and Rita Di Giovambattista

Italy is a country affected by strong seismic activity due to the collision between the African and Euro-Asian plates. In such an area, it often happens that a first strong earthquake (FSE) is followed by a subsequent strong event (SSE) of similar magnitude. In recent years, several studies have attempted to analyze the correlation between the occurrence of a possible SSE in an area and the spatio-temporal distribution of the stress drop on the same area. In this work, we have investigated this relationship in Central Italy by using the Rapid Assessment of MOmeNt and Energy Service (RAMONES), which provides source parameters for events that have occurred in the area since 2007. Using 12900 ML≥2 events available in the RAMONES catalog and a window-based clustering method, we obtained 25 clusters between 2009 and 2017 with magnitude of the FSE greater or equal to 4. Among them are also the clusters corresponding to the L'Aquila earthquake (2009) and the Amatrice earthquake (2016). Looking at the magnitude difference between the FSE and the strongest SSE (DM), it is less than or equal to 1 in 64% of the cases and greater than 1 in 36%. In the first case, we labelled the cluster as type A, in the second case as type B. By analyzing the ratio between seismic energy and seismic moment provided by RAMONES over the entire duration of the cluster, we found that almost all A clusters correspond to a maximum change in apparent stress over time larger than the one of B clusters. To a first approximation, this observation also proves to be true when analyzing the seismicity before the strongest SSE or at the first SSE. These preliminary results are therefore encouraging for future use in forecasting SSEs in Central Italy.

Funded by the NEar real-tiME results of Physical and StatIstical Seismology for earthquakes observations, modeling and forecasting (NEMESIS) Project (INGV).

How to cite: Brondi, P., Gentili, S., Picozzi, M., Spallarossa, D., and Di Giovambattista, R.: Characterizing clusters with strong subsequent events in Central Italy using RAMONES, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6346, https://doi.org/10.5194/egusphere-egu24-6346, 2024.

Exploring the potential relationship between an earthquake’s onset and its final moment magnitude (Mw) is a fundamental question in earthquake physics. This has practical implications, as rapid and accurate magnitude estimation is essential for effective early warning systems.

This study employs a novel approach of a hybrid Convolutional Neural Network (CNN) - Recurrent Neural Network (RNN) models to estimate moment magnitude from just the first two seconds of source time functions (STFs), which is significantly shorter than the entire source duration. We use STFs of large earthquakes from the SCARDEC database, which applies a deconvolution method on teleseismic body waves, considering only events with a Mw > 7 and an initial STF value smaller than 1017 Nm/s to avoid potential bias. Additionally, we incorporate STFs from physics-based numerical simulations of earthquake cycles on nonplanar faults, varying in roughness levels and fault lengths. These simulations exhibit substantial variability in earthquake magnitude and slip behavior between events. The reported methodology uses the information contained in the initial characteristics of the STF, its temporal derivative, and the associated seismic moment, capturing the valuable insights present in the initial energy release about the final moment magnitude.

For the simulated data, the CNN-RNN model demonstrates a good correlation between the initial 2 seconds of the STF and the final event magnitude. Correlation coefficients close to 0.8 and root mean squared errors (RMSE) around 0.25 for magnitudes between 5 and 7.5 showcase the model’s ability to learn and generalize effectively from diverse earthquake scenarios. While results for natural earthquakes from the SCARDEC database remain promising (RMSE of 0.27), the correlation coefficient is lower (0.31), suggesting a weaker relationship than simulated data. This discrepancy might be attributed to the narrower band of magnitudes (7 to 7.5) within SCARDEC data used here, potentially limiting the model’s ability to discern subtle variations and establish a stronger correlation. Further, as an earthquake's fractional duration, 2 sec/source duration, increases, the model's error consistently decreases as expected. Finally, most predictions fall within a narrow range of 1% error, and nearly 90% of samples across diverse durations satisfy a set 5% error threshold. This consistent performance of the hybrid CNN-RNN model across varying source durations, magnitude ranges, and fault characteristics underscores the model's adaptability and robustness in handling diverse earthquake scenarios. While we mostly use here STFs from simulated earthquakes, continuous learning and refinement against reliable and diverse STFs obtained from teleseismic data, when available, are key to enhancing the potential of these CNN-RNN models for a better understanding of the onset-magnitude correlation in natural earthquakes.

How to cite: Rodda, G. K. and Tal, Y.: Analyzing Earthquake's Onset-Magnitude Correlation Using Machine Learning and Simulated and Seismic Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7459, https://doi.org/10.5194/egusphere-egu24-7459, 2024.

EGU24-8744 | ECS | Posters on site | NH4.3

Exploring the 2019 Ridgecrest seismic data with unsupervised deep learning  

Sarah Mouaoued, Michel Campillo, and Léonard Seydoux

We analyze the seismic data continuously recorded in the vicinity of the Mw7.4 2019 Ridgecrest earthquake with an unsupervised deep learning method proposed by Seydoux et al. (2020), in search of seismic signatures of physical signatures of the earthquake preparation phase. We downloaded data from the 3 different stations B918, with a 100 Hz sampling frequency, SRT and CLC with a 40 Hz sampling frequency. Using a scattering network combined with an independent component analysis, we define stable waveform features and cluster the continuous signals extracted from a sliding window before proposing cluster-based interpretations of the seismic signals. We also further discuss our results with external datasets such as independently-obtained seismicity catalogs in the area. We also investigate a manifold-learning-based representation (UMAP) of the data in 2D from the scattering network. According to our first results merged with a catalog analysis we are able to separate various events from the noise and identify several types of seismicity and noises. 

How to cite: Mouaoued, S., Campillo, M., and Seydoux, L.: Exploring the 2019 Ridgecrest seismic data with unsupervised deep learning , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8744, https://doi.org/10.5194/egusphere-egu24-8744, 2024.

EGU24-8786 | Orals | NH4.3

A Machine Learning-based Method for Identifying Segmented Fault Surfaces Through Hypocenter Clustering 

Ester Piegari, Giovanni Camanni, Martina Mercurio, and Warner Marzocchi

We present a method for automatically identifying segmented fault surfaces through the clustering of earthquake hypocenters without prior information. Our approach integrates density-based clustering algorithms (DBSCAN and OPTICS) with principal component analysis (PCA). Using the spatial distribution of earthquake hypocenters, DBSCAN detects primary clusters, which represent areas with the highest density of connected seismic events. Within each primary cluster, OPTICS identifies nested higher-order clusters, providing information on their quantity and size. PCA analysis is then applied to the primary and higher-order clusters to assess eigenvalues, enabling the differentiation of seismicity associated with planar features and distributed seismicity that remains uncategorized. The identified planes are subsequently characterized in terms of their location and orientation in space, as well as their length and height. By applying PCA analysis before and after OPTICS, a planar feature derived from a primary cluster can be interpreted as a fault surface, while planes derived from high-order clusters can be interpreted as fault segments within the fault surface. The consistency between the orientation of illuminated fault surfaces and fault segments, and that of the nodal planes of earthquake focal mechanisms calculated along the same faults, supports this interpretation. We show applications of the method to earthquake hypocenter distributions from various seismically active areas (Italy, Taiwan, California) associated with faults exhibiting diverse kinematics.

How to cite: Piegari, E., Camanni, G., Mercurio, M., and Marzocchi, W.: A Machine Learning-based Method for Identifying Segmented Fault Surfaces Through Hypocenter Clustering, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8786, https://doi.org/10.5194/egusphere-egu24-8786, 2024.

Seismic swarms are characterized by intense seismic activity strongly clustered in time and space and without the occurrence of a major event that can be considered as the mainshock. Such intense seismic activity is most commonly associated with external aseismic factors, as pore-fluid pressure diffusion, aseismic creep, or magmatic intrusion that can perturb the regional stresses locally triggering the observed seismicity. These factors can control the spatiotemporal evolution of seismic swarms, frequently exhibiting spatial expansion and migration of event hypocenters with time. This phenomenon, termed as earthquake diffusion, can be highly anisotropic and complex, with earthquakes occurring preferentially along fractures and zones of weakness within the heterogeneous crust, presenting anisotropic diffusivities that may locally vary over several orders of magnitude. The efficient modelling of the complex spatiotemporal evolution of seismic swarms, thus, represents a major challenge. Herein, we develop a stochastic framework based on the well-established Continuous Time Random Walk (CTRW) model, to map the spatiotemporal evolution of seismic swarms. Within this context, earthquake occurrence is considered as a point-process in space and time, with jump lengths and waiting times between successive earthquakes drawn from a joint probability density function. The spatiotemporal evolution of seismicity is then described with an appropriate master equation and the time-fractional diffusion equation (TFDE). The applicability of the model is demonstrated in the 2014 Long Valley Caldera (California) seismic swarm, which has been associated with a pore-fluid pressure triggering mechanism. Statistical analysis of the seismic swarm in the light of the CTRW model shows that the mean squared distance of event hypocenters grows slowly with time, with a diffusion exponent much lower than unity, as well as a broad waiting times distribution with asymptotic power law behavior. Such properties are intrinsic characteristics of anomalous earthquake diffusion and particularly subdiffusion. Furthermore, the asymptotic solution of the TFDE can successfully capture the main features of earthquake progression in time and space, showing a peak of event concentration close to the initial source of the stress perturbation and a stretched relaxation of seismicity with distance. Overall, the results demonstrate that the CTRW model and the TFDE can efficiently be used to decipher the complex spatiotemporal evolution of seismic swarms.

Acknowledgements

The research project was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (Project Number: 00256). 

How to cite: Michas, G. and Vallianatos, F.: Spatiotemporal Evolution of Seismic Swarms in the light of the Continuous Time Random Walk Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9184, https://doi.org/10.5194/egusphere-egu24-9184, 2024.

EGU24-9366 | ECS | Orals | NH4.3

Deep Learning for Higher-Order Aftershock Forecasting in Near-Real-Time 

Leila Mizrahi and Dario Jozinović

The use of machine learning (ML) methods for earthquake forecasting has recently emerged as a promising avenue, with several recent publications exploring the application of neural point processes. Such models, in contrast to those currently applied in practice, offer the flexibility to incorporate additional datasets alongside earthquake catalogs, indicating potential for enhanced earthquake forecasting capabilities in the future. However, with a forecasting performance that currently remains similar to that of the agreed-upon benchmark, the Epidemic-Type Aftershock Sequence (ETAS) model, the black-box nature of ML models poses a challenge in communicating forecasts to lay audiences. The ETAS model has stood the test of time and is relatively simple and comprehensively understood, with few empirically derived laws describing aftershock triggering behavior. A main drawback of ETAS is its reliance on large numbers of simulations of possible evolutions of ongoing earthquake sequences, which is typically associated with long computation times or resources required for parallelization.

In this study, we propose a deep learning approach to emulate the output of the well-established ETAS model, bridging the gap between traditional methodologies and the potential advantages offered by machine learning. By focusing on modeling the temporal behavior of higher-order aftershocks, our approach aims to combine the interpretability of the ETAS model with the computational efficiency intrinsic to deep learning.

Evaluated using commonly applied metrics of both the ML and earthquake forecasting communities, our approach and the traditional, simulation-based approach are shown to perform very similarly in describing synthetic datasets generated with the simulation-based approach. Our method has two major benefits over the traditional approach. It is faster by several orders of magnitude, and it is not susceptible to being influenced by the presence (or absence) of individual 'extreme' realizations of the process, and thus enables accurate earthquake forecasting in near-real-time.

How to cite: Mizrahi, L. and Jozinović, D.: Deep Learning for Higher-Order Aftershock Forecasting in Near-Real-Time, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9366, https://doi.org/10.5194/egusphere-egu24-9366, 2024.

EGU24-10426 | Posters on site | NH4.3

Unraveling the dynamics of the 2021 Arkalochori foreshock swarm: a fusion of machine-learning models and non-extensive statistical physics 

Filippos Vallianatos, Vasilis Kapetanidis, Andreas Karakonstantis, and Georgios Michas

On 27 September 2021, a significant Mw=6.0 earthquake struck near Arkalochori village in central Crete, Greece, about ~25 km south-southeast of Heraklion city. Remarkably, an extensive seismic swarm lasting nearly four months preceded the mainshock, activating structures near its hypocenter. In this work, we investigate the foreshock swarm by leveraging waveform data from seismological stations of the Hellenic Unified Seismic Network (HUSN) that were operational on Crete Island during its occurrence. Our approach involves the utilization of the EQ-Transformer machine-learning model, pre-trained with a diverse dataset comprising ~50,000 earthquakes sourced from the INGV bulletin (INSTANCE dataset). We employ a sophisticated methodology that incorporates a Bayesian Gaussian Mixture Model (GaMMA) to associate automatically picked P- and S-wave arrival times with event origins. Subsequently, the events are located using a local velocity model. Our findings reveal the detection and precise location (ERH < 1 km, RMS < 0.2 s) of over 3,400 events in the activated area between late May and 26 September 2021, showcasing a substantial increase compared to existing catalogs derived from routine analysis using conventional methods. The spatiotemporal distribution of the foreshock seismicity is examined to unveil migration patterns, potentially linked to fluid dynamics and pore-pressure diffusion. Furthermore, we explore the evolution of seismicity concerning different structures activated during the seismic swarm, with a particular focus on the final days leading up to the mainshock. Finally, our results are subjected to analysis through non-extensive statistical physics methods, providing a comprehensive understanding of the complex dynamics culminating in the Arkalochori earthquake sequence.

Acknowledgements

We would like to thank the personnel of the institutions participating to the Hellenic Unified Seismological Network (http://eida.gein.noa.gr/) for the installation, operation and management of the seismological stations used in this work. The present study is co-funded by the Special Account for Research Grants (S.A.R.G.) of the National and Kapodistrian University of Athens.

How to cite: Vallianatos, F., Kapetanidis, V., Karakonstantis, A., and Michas, G.: Unraveling the dynamics of the 2021 Arkalochori foreshock swarm: a fusion of machine-learning models and non-extensive statistical physics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10426, https://doi.org/10.5194/egusphere-egu24-10426, 2024.

Our research aims to investigate the three recent and powerful earthquakes in the Ionian Sea region which occurred on January 26, 2014, November 17, 2015, and October 25, 2018, of magnitude Mw 6.1, Mw 6.0, and Mw 6.6 respectively using the complexity theory and the non-extensive statistical physics (NESP).

The scaling properties that have been observed in the three aftershock sequences of the recent strong earthquakes that took place in the region of Ionian islands are presented. To analyze the evolution of three aftershock sequences, we plotted the cumulative number of aftershocks N(t) over time. Additionally, we used a modified version of Omori's law to study the temporal decay of aftershock activity.

Based on non-extensive statistical physics, the analysis of interevent times distribution suggests that the system is in an anomalous equilibrium, with a crossover from anomalous (q>1) to normal (q=1) statistical mechanics for large interevent times. The obtained values of q indicate that the system has either one or two degrees of freedom. Furthermore, the migration of aftershock zones can be scaled as a function of the logarithm of time. This scaling is discussed in terms of rate-strengthening rheology, which governs the evolution of the afterslip process.

Acknowledgements

The present study is co-funded by the Special Account for Research Grants (S.A.R.G.) of the National and Kapodistrian University of Athens.

How to cite: Pavlou, K., Vallianatos, F., and Michas, G.: Spatio-temporal evolution and scaling laws analysis of the recent three strongest earthquakes in the Ionian Sea region during the period 2014-2019., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11734, https://doi.org/10.5194/egusphere-egu24-11734, 2024.

EGU24-13405 | ECS | Posters on site | NH4.3

Pseudo-prospective earthquakes forecasting experiment in Italy based on temporal variation of the b-value of the Gutenberg-Richter law. 

Emanuele Biondini, Flavia D'Orazio, Barbara Lolli, and Paolo Gasperini

The analysis of space-time variations of the b-value of the frequency-magnitude distribution of earthquakes can be considered an important indicator in understanding the processes that precede strong earthquake events. Variations in b-value can provide valuable information on the stress state and probability of earthquake occurrence in a specific geographical region. By analyzing spatial variations in b-value, changes in local tectonic conditions can be identified, highlighting areas where seismic risk may increase. Similarly, the analysis of temporal variations in b-value can reveal patterns preceding seismic events, providing a possible precursor signal. Such variations could be the result of complex geological processes, such as the progressive accumulation of stress along active faults or the presence of underground fluids that influence fault dynamics. In fact, as it has been observed in many cases, the b-value tends to descend in the preparatory phases of a strong earthquake, and it increases suddenly after the mainshock occurrence.

To evaluate such a hypothesis, in this work, an alarm-based forecasting method that uses b-value space-time variations as a precursor signal is implemented. The forecasting method has been retrospectively calibrated and optimized for the period 1990-2011 to forecast Italian shallow earthquake (Z<50 km) of magnitude larger than 5.0.

The method has been than applied pseudo-prospectively over the period 2011-2022 and the forecasting skills have been assessed using specific test and statistics for alarm-based models. Such forecasting skills have been also compared with those of another alarm-based earthquake forecasting model that use the occurrence of potential foreshock as precursor signal.

How to cite: Biondini, E., D'Orazio, F., Lolli, B., and Gasperini, P.: Pseudo-prospective earthquakes forecasting experiment in Italy based on temporal variation of the b-value of the Gutenberg-Richter law., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13405, https://doi.org/10.5194/egusphere-egu24-13405, 2024.

EGU24-13573 | Posters on site | NH4.3

A Bayesian transdimensional approach to estimate temporal changes in the b-value distribution without truncating catalogs 

Marine Laporte, Stéphanie Durand, Blandine Gardonio, Thomas Bodin, and David Marsan

The frequency/magnitude distribution of earthquakes can be approximated by an exponential law whose exponent is the so-called b-value. The b-value is routinely used for probabilistic seismic hazard assessment. In this context we propose to estimate the temporal variations of the b-value together with its uncertainties. The b-value is commonly estimated using the frequentist approach of Aki (1965), but biases may arise from the choice of completeness magnitude (Mc), the magnitude below which the exponential law is no longer valid. Here we propose to describe the full frequency-magnitude distribution of earthquakes by the product of an exponential law with a detection law. The latter is characterized by two parameters, μ and σ, that we jointly estimate with b-value within a Bayesian framework. In this way, we use all the available data to recover the joint probability distribution for b-value, μ and σ. Then, we extend this approach for recovering temporal variations of the three parameters. To that aim, we randomly explore with a Markov chain Monte Carlo (McMC) method in a transdimensional framework a large number of time variation configurations of the 3 parameters. This provides posterior probability distributions of the temporal variations in b-value, μ and σ.  For an application to a seismic catalog of far-western Nepal, we show that the probability distribution of the b-value remains stable with larger uncertainties during the monsoon period when the detectability decreases significantly . This confirms that we can see variations in the b-value that are independent of variations in detectability. Our results can be compared with the results and interpretations obtained using the b-positive approach. We hope that further applications to real and experimental data can provide statistical constraints on the b-value variations and help to better understand the physical meaning behind these variations.

How to cite: Laporte, M., Durand, S., Gardonio, B., Bodin, T., and Marsan, D.: A Bayesian transdimensional approach to estimate temporal changes in the b-value distribution without truncating catalogs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13573, https://doi.org/10.5194/egusphere-egu24-13573, 2024.

EGU24-14304 | Posters on site | NH4.3

Comparative Analysis of Seismic Clustering: Deterministic Techniques vs. Probabilistic ETAS Model 

Giuseppe Falcone, Ilaria Spassiani, Stefania Gentili, Rodolfo Console, Maura Murru, and Matteo Taroni

Short-term seismic clustering, a crucial aspect of seismicity, has been extensively studied in literature. Existing techniques for cluster identification are predominantly deterministic, relying on specific constitutive equations to define spatiotemporal extents. Conversely, probabilistic models, such as the Epidemic Type Aftershock Sequence (ETAS) model, dominate short-term earthquake forecasting. The ETAS model, known for its stochastic nature, has been employed to decluster earthquake catalogs probabilistically. However, the challenge arises when selecting a probability threshold for cluster identification, potentially distorting the model's underlying hypothesis.
This study aims to assess the consistency between seismic clusters identified by deterministic window-based techniques specifically, Gardner-Knopoff and Uhrhammer-Lolli-Gasperini and the associated probabilities predicted by the ETAS model for events within these clusters. Both deterministic techniques are implemented in the NESTOREv1.0 package and applied to the Italian earthquake catalog spanning from 2005 to 2021.
The comparison involves evaluating, for each event within an identified cluster, both the probability of independence and the expected number of triggered events according to the ETAS model. Results demonstrate overall agreement between the two cluster identification methods, with identified clusters exhibiting consistency with corresponding ETAS probabilities. Any minor discrepancies observed can be attributed to the fundamentally different nature of the deterministic and probabilistic approaches.
This research is supported by a grant from the Italian Ministry of Foreign Affairs and International Cooperation.

How to cite: Falcone, G., Spassiani, I., Gentili, S., Console, R., Murru, M., and Taroni, M.: Comparative Analysis of Seismic Clustering: Deterministic Techniques vs. Probabilistic ETAS Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14304, https://doi.org/10.5194/egusphere-egu24-14304, 2024.

Challenges in Aftershock Forecasting

The probabilistic evaluation of aftershock activity relies on two empirical rules: the Gutenberg–Richter law (GR law) and the Modified Omori law (MO law). An important issue arises in aftershock observation, particularly when regarding the technical aspects of seismic monitoring, where smaller earthquakes are more challenging to detect than larger ones.  In cases where records of smaller seismic events are absent, the b value of the GR law and the K value of the MO law tend to be underestimated. This study was conducted to develop a model that corrects underestimation of these parameters based on main shock information.

 

Data and Methodology

Seismic source data from the Japan Meteorological Agency were used, including the main shock – aftershock sequence magnitudes, latitude and longitude of the epicenter, and occurrence times. Using data for the periods immediately after the main shock to 3 hours, 1 day, 30 days, and 90 days, calculations were performed on data to ascertain the K value of the MO law and the b value of the GR law. The objective was to investigate the relation between these parameters and the main shock magnitude (hereinafter, M0). Based on these relations, methodologies for correcting parameters were explored.

 

Results and Discussion

  • Relation between M0 and parameters

Significant negative correlation was found between the M0 and the b value, with larger M0 values associated with smaller b values. Furthermore, correlation was stronger for b values closer to the immediate aftermath of the main shock. This strong correlation suggests that larger M0 values are more likely to result in the omission of weaker seismic events from the data. The omission of earthquakes is particularly noticeable immediately following occurrence of the main shock. Similarly, a tendency was observed for the K value to be underestimated immediately after the main shock, when M0 is larger.

  • Parameter corrections

We introduce new parameters, b' and K', defined as shown below.

Larger values of b' and K' indicate underestimation of parameters at 3 hours after the main shock compared to 1 day after the main shock. Using these parameters, we perform linear regression analysis with M0 as the independent variable and b' and K' as dependent variables to estimate 1 day post-main-shock parameters from the 3 hours post-main-shock values.

The precisions of the estimated values are compared as shown in Figure 1.

Figure1:The precisions of the estimated values

Estimation of b shows superior accuracy compared to that obtained using earlier methodologies and conventional approaches used by the Japan Meteorological Agency. Estimated values of K show that systematic errors have been improved with the methodology used for this study. Using these corrected parameters, Figure 2 presents a comparison of the predicted aftershock numbers from 3 hours to 1 day after the main shock with the actual values. As the figure shows, on average, the methodology used for this provides favorable accuracy of predictions.

Figure2:The accuracy of Aftershock Predictions

How to cite: Hashimoto, R. and Kuzuha, Y.: Advancement of Aftershock Distribution Prediction Model Following a Main Shock – Examining Parameter Correction Methods for Predictive Formula Parameters Based on Main Shock Information –, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14398, https://doi.org/10.5194/egusphere-egu24-14398, 2024.

EGU24-15724 | Orals | NH4.3

Detect and characterize swarm-like seismicity 

Luigi Passarelli, Simone Cesca, Leila Mizrahi, and Gesa Petersen

Tectonic earthquake swarms exhibit a distinct temporal and spatial pattern compared to mainshock-aftershock sequences. Unlike the latter ones, where the earthquake sequence typically starts with the largest earthquake that triggers an Omori-Utsu temporal decay of aftershocks, earthquake swarms show a unique increase in seismic activity without a clear mainshock. The largest earthquake(s) in a swarm sequence often occur(s) later, and the sequence consists of multiple earthquake bursts showing spatial migration. This erratic clustering behavior of earthquake swarms arises from the interplay between the long-term accumulation of tectonic elastic strain and short-term transient forces. Detecting and investigating earthquake swarms challenges the community and ideally requires an unsupervised approach, which has led in recent decades to the emergence of numerous algorithms for earthquake swarm identification.

In a comprehensive review of commonly used techniques for detecting earthquake clusters, we applied a blend of declustering algorithms and machine learning clustering techniques to synthetic earthquake catalogs produced with a state-of-the-art ETAS model, with a time-dependent background rate mimicking realistic swarm-like sequences. This approach enabled the identification of boundaries in the statistical parameters commonly used to distinguish earthquake cluster types, i.e., mainshock-aftershock clusters versus earthquake swarms. The results obtained from synthetic data helped to have a more accurate classification of seismicity clusters in real earthquake catalogs, as it is the case for the 2010-2014 Pollino Range (Italy) seismic sequence, the Húsavík-Flatey transform fault seismicity (Iceland), and the regional catalog of Utah (USA). However, the classification obtained through automated application of these findings to real cases depends on the clustering algorithm utilized, the statistical completeness of catalogs, the spatial and temporal distribution of earthquakes, and benefits of a posteriori manual inspection. Nevertheless, the systematic assessment and comparison of commonly used methods - benchmarked in this work to synthetics catalogs and real seismicity – allows the community to have clear and thorough guidelines to identify swarm-like seismicity.

How to cite: Passarelli, L., Cesca, S., Mizrahi, L., and Petersen, G.: Detect and characterize swarm-like seismicity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15724, https://doi.org/10.5194/egusphere-egu24-15724, 2024.

Determining mainshocks from an ongoing seismic sequence poses a challenge for real-time hazard assessment. This study aims to address this issue by analyzing temporal variations in the b-value derived from the Gutenberg-Richter law, with a focus on moderate-to-large events in Yunnan province, southwest China. Yunnan is well known to experience frequent earthquakes due to the convergence of the Indian and Eurasian tectonic plates, along with its complex subsurface geological structure and active fault zones. Earthquake data were analyzed from the Unified National Catalog over the period from January 2000 through December 2022 and the magnitude of completeness is 1.4. We selected seismic sequences where the mainshock magnitudes were above 5. We employed a temporal b-value calculation approach, utilizing a minimum of 10 years of seismic data and including earthquakes within 20 km from the mainshock hypocenter. We used the long-term average b-value preceding the mainshock as the reference. Specifically, we compared the temporal b-value variation calculated for the one-month period following each mainshock to the reference b-value. In total, we investigated 23 sequences in the region. The b-value increased by 10% or more for 4 sequences and by <10% for 3 sequences. Three sequences showed b-value reduction. Insufficient data prevented analysis of 13 other sequences. To conclude, assessing temporal b-value variations is an active research topic to evaluate ongoing earthquake sequences. By testing the application in Yunnan, our b-value is able to help us identify a few mainshock-aftershock sequences. However, we also observe controversial cases. This limitation poses challenges to rapidly determine mainshocks in operational decision-making applications.

How to cite: Lau, T. L. and Yang, H.: Evaluating the Utility of b-Value for Discriminating Foreshocks and Mainshocks in Yunnan, southwest China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16739, https://doi.org/10.5194/egusphere-egu24-16739, 2024.

EGU24-17178 | ECS | Posters on site | NH4.3

Towards a Deep Learning Approach for Data-Driven Short-Term Spatiotemporal Earthquake Forecasting  

Foteini Dervisi, Margarita Segou, Brian Baptie, Ian Main, and Andrew Curtis

The development of novel deep learning-based earthquake monitoring workflows has led to a rapid increase in the availability of earthquake catalogue data. Earthquake catalogues are now being created by deep learning algorithms at significantly reduced processing times compared to catalogues built by human analysts and contain at least a factor of ten more earthquakes. The use of these rich catalogues has been shown to have led to improvements in the predictive power of statistical and physics-based forecasts. Combined with the increasing availability of computational power, which has greatly contributed to the recent breakthrough in the field of artificial intelligence, the use of rich datasets paired with machine learning workflows seems to be a promising approach to uncovering novel insights about earthquake sequences and discovering previously undetected relationships within earthquake catalogues.

Our focus is on employing deep learning architectures to produce high-quality earthquake forecasts. Our hypothesis is that deep neural networks are able to uncover underlying patterns within rich earthquake catalogue datasets and produce accurate forecasts of earthquakes, provided that a representative dataset that accurately reflects the properties of earthquake sequences is used for training. We use earthquake catalogue data from different geographical regions to build a time series of spatiotemporal maps of past seismicity. We then split this time series into training, validation, and test datasets in order to explore the ability of deep neural networks to capture patterns within sequences of seismicity maps and produce short-term spatiotemporal earthquake forecasts.

We assess the performance of the trained deep learning-based forecasting models by using metrics from the machine learning and time-series forecasting domains. We compare the trained models against a null hypothesis, the persistence model, which assumes no change between consecutive time steps and is commonly used as a baseline in various time series forecasting settings. The persistence null hypothesis has been proven to be a very effective model due to the fact that when only background seismicity is observed, there is very little change between consecutive time steps. We also evaluate the relative performance of different deep learning architectures and assess their suitability for dealing with our specific problem. We conclude that deep learning techniques are a promising alternative to disciplinary statistics and physics-based earthquake forecasting methods as, once trained, deep learning models have the potential of producing high-quality short-term earthquake forecasts within seconds. This realisation can influence the future of operational earthquake forecasting and earthquake predictability. 

How to cite: Dervisi, F., Segou, M., Baptie, B., Main, I., and Curtis, A.: Towards a Deep Learning Approach for Data-Driven Short-Term Spatiotemporal Earthquake Forecasting , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17178, https://doi.org/10.5194/egusphere-egu24-17178, 2024.

EGU24-17967 | Orals | NH4.3

The Effect of Data Limitations on Earthquake Forecasting Model Selection 

Marta Han, Leila Mizrahi, and Stefan Wiemer

In our recent study, we have developed an ETAS-based (Epidemic-Type Aftershock Sequence; Ogata, 1988) time-dependent earthquake forecasting model for Europe. Aside from inverting a basic set of parameters describing aftershock behaviour on a highly heterogeneous dataset, we have proposed several model variants, focusing on implementing the knowledge about spatial variations in the background rate inferred by ESHM20 already during the inversion of ETAS parameters, fixing the term dictating the productivity law to specific values to balance the more productive triggering by high-magnitude events (productivity law) with their much rarer occurrence (GR law), and using the b-positive method for the estimation of the b-value.

When testing the model variants, we apply the commonly used approach of performing retrospective tests on each model to check for self-consistency over long time periods and pseudo-prospective tests for comparison of models on one-day forecasting periods during seven years. While such pseudo-prospective tests reveal that some models indeed outperform others, for other model pairs, no significant performance difference was detected.

Here, we investigate in more detail the conditions under which performance differences of two competing models can be detected with statistical significance. Using synthetic tests, we investigate the effects of a catalog’s size and the magnitude range it covers on the significance of model performance difference. This will provide insight into whether recording many small events can, in this sense, replace having a large enough dataset of higher-magnitude events. Furthermore, due to the underrepresentation (or absence) of high-magnitude earthquakes in both training and testing data, both the models and tests are prone to overfitting to small events, potentially resulting in forecasts that underestimate both productivity of sequences with a high-magnitude main event and probabilities that a larger earthquake will follow such an event. We focus on defining metrics that highlight these properties as they are often of interest when applying time-dependent forecasting models to issuing operational earthquake forecasts.

How to cite: Han, M., Mizrahi, L., and Wiemer, S.: The Effect of Data Limitations on Earthquake Forecasting Model Selection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17967, https://doi.org/10.5194/egusphere-egu24-17967, 2024.

EGU24-20167 | ECS | Orals | NH4.3

Identification of Earthquakes and Anthropogenic Events in Madagascar 

Hoby N.T. Razafindrakoto and A. Tahina Rakotoarisoa

Earthquake catalog is a key element in seism hazards. However, it may be contaminated by non-natural earthquake sources. Hence,
This study aims to discriminate natural and non-natural earthquakes through machine learning techniques and spatio-temporal distribution of the events. 
First, we propose a Convolutional Neural Network based on spectrograms to perform the waveform classification. It is targeted to applications in Madagascar. The approach consists of three main steps: (1) generation of the time–frequency representation of ground-motion recordings (spectrogram); (2) training and validation of the model using spectrograms of ground shaking; (3) testing and prediction. To measure the compatibility between output predictions and given ground truth labels, we adopt the commonly used loss function and accuracy measure. Given that the spatial distribution of the seismic data in Madagascar is non-uniform, we perform two-step analyses. First, we adopt a supervised approach for 6051 known events in the central part of Madagascar. Then, we use the outcome for the second step of training and perform the prediction for non-categorized events throughout the country. The results show that our model has the potential to separate earthquakes from mining-related events. For the supervised approach, among the 20% used for testing, 97.48% and 2.52% of the events give correct and incorrect labels, respectively. These pre-trained data are subsequently used to perform predictions for unlabeled events throughout Madagascar. Our results show that the model could learn the features of the classes even for data coming from different parts of Madagascar.
From the analyses of the spatio-temporal patterns of seismicity, we also found evidence of induced earthquakes associated with the heavy-oil exploration in Tsimiroro, Madagascar with an increase in the rate of earthquake occurrence in 2022.

How to cite: Razafindrakoto, H. N. T. and Rakotoarisoa, A. T.: Identification of Earthquakes and Anthropogenic Events in Madagascar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20167, https://doi.org/10.5194/egusphere-egu24-20167, 2024.

EGU24-2337 | Orals | NH4.4

Under-Dip Toppling in the Outer Western Carpathians: Insight into Investigation of Slope Failures and Implication of Paleo-Seismic Activity 

Thanh-Tùng Nguyễn, Ivo Baroň, Jia-Jyun Dong, Rostislav Melichar, Filip Hartvich, Jan Klimeš, Jan Černý, Martin Šutjak, Lenka Kociánová, Václav Dušek, Matt Rowberry, Régis Braucher, Goslar Tomasz, Jyr-Ching Hu, Chia-Han Tseng, Yi-Chin Chen, and Cheng-Han Lin

The Outer Western Carpathians, situated in the central European segment of the Alpine-Himalayan orogenic zone, present an intriguing case of an accretionary wedge. This region is characterized by Mesozoic and Cenozoic flysch sedimentary rocks, comprising massive sandstone benches and intercalated clay layers. These formations have undergone significant deformation, including being thrust over the European foreland during the Paleogene and Neogene periods. The resulting hilly to mountainous terrain exhibits notable slope failures. Here we focused on the phenomenon of under-dip toppling –sandstone beds steeply dipping in the direction of the slope, which were locally overturned along systems of brittle fractures. Utilizing high-resolution LiDAR data, our study investigates the locations, geometrical characteristics, and tectonic settings of these toppling. In the Javorníky Mountains, these topples predominantly occur in SSE-dipping fold limbs, an orientation conducive to under-dip toppling. The mechanism of under-dip toppling, involving the lifting of the center of gravity of the toppled layers, presents a complex geomechanical challenge. Recent field investigations, including structural measurements on faults, electrical resistivity tomography (ERT) profiles, and 10Be dating, have identified active polyphase strike-slip surface ruptures in the region. These findings raise questions about the origins of toppling and their implications for understanding paleo-earthquakes in the area. Our preliminary analysis suggests a two-tiered approach to understanding toppling processes: firstly, exploring the deeper structural implications – could active tectonic faulting be the cause of the under-dip toppling? Secondly, we analyzed the mechanism of toppling near to the surface. By analyzing the geometry of near-surface persistent sandstone slabs and employing Pseudo-static analysis to assess seismic slope response, our results indicate that the layer while overturned may be attributed to strong paleo-seismic events. This study employs comprehensive site investigations and back analyses to understand a range of possible trigger and controlling mechanisms. It elucidates the geological conditions of slopes and performs a geomechanical analysis of under-dip toppling.

The research is part of the international bi-lateral project “Earthquake triggered landslides in recently active and stabilized accretionary wedges”, supported by the Czech Science Foundation (GAČR 22-24206J) and the Taiwanese Ministry of Science and Technology (NTSC 111-2923-M-008-006-MY3).

How to cite: Nguyễn, T.-T., Baroň, I., Dong, J.-J., Melichar, R., Hartvich, F., Klimeš, J., Černý, J., Šutjak, M., Kociánová, L., Dušek, V., Rowberry, M., Braucher, R., Tomasz, G., Hu, J.-C., Tseng, C.-H., Chen, Y.-C., and Lin, C.-H.: Under-Dip Toppling in the Outer Western Carpathians: Insight into Investigation of Slope Failures and Implication of Paleo-Seismic Activity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2337, https://doi.org/10.5194/egusphere-egu24-2337, 2024.

EGU24-3606 | ECS | Orals | NH4.4

A systematic analysis at stations of the Italian seismic network to test the role of local topographic effect. 

Mario Ariano, Pier Lorenzo Fantozzi, and Dario Albarello

The Italian seismic code (NTC18) provides indications about the expected effects of some morphological configurations on the expected ground motion during earthquakes. In particular, two main 2D morphologies are identified as reference: cliffs and crests. Based on numerical simulations, the value of St is assumed to depend on the steepness of the cliffs and aspect ratio of the crest. A critical aspect of these estimates is that the considered configurations are defined in terms of steepness angles and aspect ratios, without any scale indication. Moreover, the considered morphologies are very schematic, and this prevents their simple application in the natural context: in most case an expert judgement is necessary, and this makes the final estimates potentially controversial and difficult to validate on the basis of empirical observations. To face this problem, in the frame of the PRIN project “SERENA”, a procedure has been developed for the automatic identification of areas prone to morphological amplification effects by following NTC18 prescriptions,  based on the Digital Terrain Model. The proposed approach allows the full exploitation of topographical data at the maximum resolution available. After a first application to restricted areas, the proposed procedure has been applied at National scale at the seismometric and accelerometric sites managed by INGV. The aim is twofold: first comparing outcomes of the new approach with the ones proposed by other Authors at the same sites, second to provide a sound basis of a coherent and reproducible estimate of St values to be compared with possible empirical evidence. In the presentation, the results obtained about the first aim will be presented and discussed.

How to cite: Ariano, M., Fantozzi, P. L., and Albarello, D.: A systematic analysis at stations of the Italian seismic network to test the role of local topographic effect., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3606, https://doi.org/10.5194/egusphere-egu24-3606, 2024.

EGU24-3608 | ECS | Orals | NH4.4

Mapping seismostratigraphical amplification effects at regional scale from geological data 

Nicolò Carfagna, Pierluigi Pieruccini, Pier Lorenzo Fantozzi, and Dario Albarello

It is widely recognized that the amplification of ground motion during earthquakes is attributed to the interference of seismic waves trapped between the free surface and impedance contrasts in the shallow subsoil. Seismic Microzonation (SM) studies are devoted to evaluating these site effects, but their application in wider contexts is a hard and expensive task. To estimate seismic site effects at regional scale, the most viable approach is to utilize detailed geological and geomorphological data (1:10.000-1:50.000), which are available for large part of Italy.

In the frame of the national research project “SERENA”, in this study a procedure is proposed and tested to constrain entity of 1D seismostratigraphical ground motion amplification based on geological information at the most detailed scale available. In particular, amplification factors are estimated for Seismically Homogeneous Microzones (SHM) defined on the basis geological information. Each SHM is represented as a stack flat homogeneous layers each characterized in terms of engineering-geological units by following the seismic microzonation standards. Seismic properties of each layer (shear waves velocity, density, damping and G/G0 curves) and respective range of variability are determined on the basis of the most recent literature.

This information feeds a linear equivalent numerical approach and the Inverse Random Vibration Theory to compute the expected seismic response at each SHM. To account for the relevant uncertainty, 100 random profiles were generated for each SHM, which were compatible with available data. Outcomes of the relevant numerical simulations were considered to assess uncertainty affecting amplification estimates at each SHM.

Through this procedure, approximately 4000 SHM were identified, distributed across over 80,000 formation outcrops mapped on Geological map of Tuscany Region, selected by dedicated ArcgisPro TM/Arcpy TM scripts elaborated for this aim. The 50th percentile of the amplification factor distribution for each SHM was taken into consideration. This process aimed to create a new map of amplification factors for the entire territory of Tuscany, achieving an optimal spatial resolution of 1:10,000.

To assess the reliability of the results obtained from numerical simulations, and evaluate the possible presence of biases, outcomes of the numerical procedure here considered  were compared with those from second and third levels of Seismic Microzonation studies available in Tuscany. Approximately 1500 benchmark samples were identified, revealing distinct trends among various SHM, particularly between those with outcropping sedimentary covers and those with exposed geological bedrock.

In general, amplification estimates provided by the approach here proposed provide a slight overestimate of the ones provided by the detailed seismic microzonation studies (less than 10% on average). However, this overestimate is largely within the range of uncertainty affecting regional estimates and mostly concern SHMs where bedrock outcrops.

It is worth to note that by no way the proposed approach should be considered as substitute of detailed local studies. Anyway it could be considered to provide ex-ante evaluations to be used as a preliminary reference for large scale risk analysis and for a preliminary assessment of expected ground motion effects where more detailed studies are not available so far.

How to cite: Carfagna, N., Pieruccini, P., Fantozzi, P. L., and Albarello, D.: Mapping seismostratigraphical amplification effects at regional scale from geological data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3608, https://doi.org/10.5194/egusphere-egu24-3608, 2024.

The complexity of the geological setting of the Italian peninsula implies variable site conditions affecting seismic hazard. Their extensive mapping is needed for a reliable assessment of the induced risk on residential areas, industrial agglomerations, infrastructures, strategic sites, cultural heritage spread on the entire national territory. The research meets the need for a national reference map providing co-seismic ground deformation at the scale of interest of land use planning and bridging the information gap now existing among the urbanized areas covered by seismic microzonation studies. The project aims at defining a multidisciplinary procedure for a multiscale mapping of the local seismic hazard of Italy, exploiting the potentialities of having spatially extensive information for combining site-specific to regional estimates of site effects. The key elements are: i) full exploitation of geological/geomorphological data, ii) extensive numerical modelling, and iii) empirical testing of local hazard estimates. The study deals with the regional scale analysis and classification of the landscape and the geological-technical properties of the near-surface stratigraphic configurations (GeoMorpho-Stratigraphic Units, GMSUs), which affect seismic hazard.  The GMSUs are obtained by combining geomorphological analysis and automated landscape classification procedures, field-based lithostratigraphic constraints, instrumental signatures from geophysical investigations, and geotechnical parameters. Distinct parameterizations will be assessed for each GMSUs to feed simplified numerical models to quantify synthetic hazard indicators suitable for risk evaluations and land use planning. Outcomes will be managed through a coherent probabilistic approach to bound relevant uncertainty as a function of locally available data. Outcomes will be tested by considering site-specific analyses.

How to cite: Albarello, D.: Assessing seismic site effects at regional scale: the SERENA research project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3611, https://doi.org/10.5194/egusphere-egu24-3611, 2024.

EGU24-4649 | ECS | Posters on site | NH4.4

Seismic Site Effects Assessment at the Illinois Basin–Decatur Project (IBDP) site 

Yuliia Semenova and Victor Vilarrasa

Carbon capture and storage (CCS), is key to curtail carbon dioxide (CO2) atmospheric emissions and mitigate climate change. The complexities of carbon dioxide (CO2) storage are deeply intertwined with induced seismicity, a phenomenon set in motion by pore pressure, temperature and stress changes occurring during CO2 injection. If perceived, induced seismicity may negatively affect public perception of this carbon-removal technology. Here, we focus on assessing ground motion manifestations on the surface during hypothetical earthquakes with magnitudes ranging from 2 to 5, occurring at a depth of 2 km beneath the upper edge of the Precambrian basement rock of the Illinois Basin–Decatur Project (IBDP) site. The objective of this investigation is to analyze the seismic response of the IBDP site surface to earthquakes of specific magnitudes, considering their potential occurrence in connection with CO2 storage at the gigatonne scale.

The analysis of ground motion manifestations on the surface during various earthquake scenarios of different magnitudes at the IBDP site provides valuable insights into the seismic vulnerability of the location. It allows for a comprehensive assessment of both amplification and attenuation effects, revealing how the geological and geotechnical characteristics of the subsurface rock influence ground motion. Understanding how the site responds to seismic events allows for a more accurate assessment of potential risks and vulnerabilities.

Employing the equivalent linear approach of Ground Response Analysis, we computed the Fourier amplitude spectra of seismic motions on the surface of the IBDP site for earthquakes with magnitudes 2, 3, 4, and 5. These spectra are then compared with the Fourier amplitude spectra of input motions. The Fourier amplitude spectrum illuminates how ground motion amplitude is distributed across various frequencies. We also analyze the calculated Fourier Amplitude Ratio.

Through a thorough comparison of these spectra, we explore the shifts in amplitude-frequency composition as the magnitude increases. This analysis is instrumental in identifying frequencies that gain prominence or diminish, revealing resonant frequencies and their correlation with input wave amplitude. These findings are crucial for understanding the dynamics of seismic events across different magnitudes and their environmental repercussions at the IBDP study site. Moreover, they have the potential to contribute to the optimization of practices in CCS.

How to cite: Semenova, Y. and Vilarrasa, V.: Seismic Site Effects Assessment at the Illinois Basin–Decatur Project (IBDP) site, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4649, https://doi.org/10.5194/egusphere-egu24-4649, 2024.

EGU24-7351 | ECS | Posters on site | NH4.4

Temporal evolution of resonance frequencies as a proxy to monitor nonlinear site response: a case study using KiK-net data in Japan 

Ssu-Ting Lai, Alessandra Schibuola, Luis Fabian Bonilla, and Fabrice Cotton

The comprehension of earthquake ground motion amplification in soft sediments, influenced by the contrasting physical properties of rock and soil, faces challenges due to nonlinear site responses. Nonlinear effects, driven by distinct stress-strain behavior in soils under substantial loads, result in modified propagation velocity of the media, shifts in resonance frequencies, stronger damping, and reduced amplification. Identifying nonlinearity is particularly challenging, especially in the absence of a reference site. In addition, prevalent approaches in ground motion prediction studies often rely on empirical equations utilizing numerical computations that are difficult to validate, instead of incorporating the nonlinear effects present in the data.

In this study, we introduce a novel approach by constructing resonance curves derived from seismic waveforms recorded at the surface stations within the KiK-net network in Japan. These curves not only provide the resonance frequencies at a specific site but also serve as proxies for broadband site response, all while excluding site amplification. Our approach unveils the extent of frequency shifts in resonance frequencies, elucidating the interplay between events and sites across varying ground motion levels. Validation through borehole responses from the KiK-net network demonstrates the robustness of our methodology in characterizing the subsurface solely based on surface recordings. This contribution aims to identify both linear and nonlinear resonance frequencies using all available earthquake data at any site, which can help improve ground motion prediction studies, and more accurate seismic hazard assessments.

How to cite: Lai, S.-T., Schibuola, A., Bonilla, L. F., and Cotton, F.: Temporal evolution of resonance frequencies as a proxy to monitor nonlinear site response: a case study using KiK-net data in Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7351, https://doi.org/10.5194/egusphere-egu24-7351, 2024.

EGU24-7738 | Orals | NH4.4

Co-seismic landslide directions may help identifying earthquake fault ruptures 

Ivo Baroň, Kai-Ting Shen, Jia-Jyun Dong, Chia-Han Tseng, Che-Ming Yang, Janusz Wasowski, Jan Jelének, Jan Klimeš, Yi-Chin Chen, Chyi-Tyi Lee, and Jia-Qian Gao

Several studies have suggested that directions of earthquake-triggered landslides might be preferentially oriented according to the seismic waves’ characteristics.  Here we further address this issue by analyzing three landslide populations attributed to 1998 Ruei-Li Mw 6.5, 1999 Chi-Chi Mw 7.3 and 2022 Taitung Mw 6.9 earthquakes in Taiwan. In particular, we seek possible linkages between the patterns of co-seismic landsliding (predominant orientations) and the epicenter and fault rupture locations, by exploiting the assumption that surface waves with horizontal particle motions (Love waves) and horizontal shear waves, both characterized by transverse vibrations perpendicular to the direction of wave radiation from the source, are the major agents responsible for earthquake induced slope failures.

First, we take the aspect of each landslide source zone as representing the landslide directions. These directions are then statistically evaluated with respect to the epicentre and fault rupture positions for the characteristic segments of the landslide population. In the next step, we consider numerous possible pairs of the landslides to obtain intersections of the lines normal to their aspect directions using custom-designed Python code.

At each particular landslide population segment, the landslide displacement directions revealed slight preferential orientation with the maxima sub-perpendicular to the fault rupture. Symmetrically distributed and round landslide population of the Ruei-Li earthquake showed even better results than elongated landslide population of the Chi-Chi earthquake. In all three earthquake cases, the intersections maxima coincided with the maximum slip velocities and/or displacements along the fault ruptures, as revealed by GNSS. These promising results indicate that such an approach might be useful for identifying fault ruptures of old or even prehistoric earthquakes.   

The research was funded by the Grant Agency of the Czech Republic (GC22-24206J) and Taiwanese National Technological and Science Council (MOST/NTSC 111-2923-M-008-006-MY3).

How to cite: Baroň, I., Shen, K.-T., Dong, J.-J., Tseng, C.-H., Yang, C.-M., Wasowski, J., Jelének, J., Klimeš, J., Chen, Y.-C., Lee, C.-T., and Gao, J.-Q.: Co-seismic landslide directions may help identifying earthquake fault ruptures, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7738, https://doi.org/10.5194/egusphere-egu24-7738, 2024.

EGU24-9461 | Posters on site | NH4.4

Supervised and unsupervised machine learning techniques to map seismic site amplification 

Francesco Panzera, Paolo Bergamo, Paulina Janusz, Vincent Perron, and Donat Fäh

Switzerland experienced earthquakes mainly in the Basel area and within its Alpine region, with the Canton Valais standing out as one of the most active zones. The Rhone Valley, crossing the entire canton, is characterized by sediment deposits with a thickness reaching up to 800 meters. The valley’s topography and the significant contrast in seismic wave velocities between sediments and the surrounding rock, make it susceptible to 2D/3D effects, leading to significant site amplification phenomena. To develop local amplification models that integrate geological and geophysical data, specific areas – of relevance from the risk point of view - in the Rhone Valley were selected. One area is Sion, where geophysical data were acquired during the earthquake risk model for Switzerland project (ERM-CH). The dataset encompasses 313 single station noise measurements and seismic records from 10 seismic stations. The single station measurements were employed to compute horizontal to vertical spectral ratios (HVSR), while earthquake recordings were utilized to derive empirical spectral modelling amplification functions (ESM). Our approach involves the application of the canonical correlation (CC) statistical method, which explores the correlation between two sets of variables by identifying linear combinations that exhibit maximum correlation. Specifically, we conducted CC analysis between the sets of HVSR and ESM using as calibration dataset of 172 free-field and urban free-field stations run by the Swiss Seismological Service over the entire Swiss territory. Using canonical correlation, we developed a method to predict the ESM for a specific site based on its HVSR information. Additionally, we employed a correlation analysis based on the Pearson cross-correlation coefficient as an alternative method. This approach was utilized to group the Sion HVSR, with the seismic station HVSR, for which ESM is available, serving as the centroid. This grouping resulted in the assignment of each of the 313 HVSRs to one of the 10 amplification functions. Consequently, we extrapolated amplification values to various locations and employed kriging for interpolation to generate amplification maps at specific frequencies. The utilization of different amplification models at defined frequencies allows for the assessment and definition of epistemic uncertainties in our findings.

How to cite: Panzera, F., Bergamo, P., Janusz, P., Perron, V., and Fäh, D.: Supervised and unsupervised machine learning techniques to map seismic site amplification, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9461, https://doi.org/10.5194/egusphere-egu24-9461, 2024.

EGU24-9625 | ECS | Posters on site | NH4.4

Geophysical Imaging Of Shallow Geological Structures In Malta 

Peter Iregbeyen, Sebstiano D’Amico, Luciano Galone, Emanuele Colica, Fabio Villani, Salvatore Martino, Roberto Iannucci, and Isaac Aigbedion

 

ABSTRACT

 

There have been growing needs for scientists to search for efficiently high-resolution geophysical techniques to image the subsurface features, formations, and shallow geologic structures (e.g. faults, void, stratigraphy features). At shallow depths, an in-depth understanding of these features/structures could be  pivotal in in the management of the environment and crucial examination of hazardous terrains which are of growing threat to human safety. In the case of Malta, with a limited land space, their study could be relevant to the environmental planning agency in advocating for safe building sites for structural architecture as well as use of land. In this regard, this study will be investigating such features located in Malta, one in the Selmun Promontory, located in the north-eastern zone, and the second in the Mellieha valley located in the north-western zone of the Maltese archipelago. 

On the Selmun area ERTs arrays and passive seismic measurements were recorded both in the slope and on the plateau. Results are interpreted in terms of geological stratigraphy and whether zones on the plateau were identified, where rock falls and other slope processes are incipient.

In the Mellieha Area, ERTs arrays, GPR scans and ambient noise measurements indicate the presence of unmapped fault zones and sediment distribution, improving the understanding of the local geology. 

 

How to cite: Iregbeyen, P., D’Amico, S., Galone, L., Colica, E., Villani, F., Martino, S., Iannucci, R., and Aigbedion, I.: Geophysical Imaging Of Shallow Geological Structures In Malta, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9625, https://doi.org/10.5194/egusphere-egu24-9625, 2024.

EGU24-11911 | Posters on site | NH4.4

Seismic hazard evaluation and soil response analysis of Shamkir and Mingachevir hydroelectric power stations 

OLeksandr Kendzera, Yuliia Semenova, Oksana Topoliuk, Sergii Skurativskyi, Sergiy Mykulyak, Inna Skurativska, Olena Trypilska, and Viktoriia Drukarenko
In regions prone to seismic activity, assessing the seismic hazard of hydroelectric power stations is crucial for maintaining the dependability and robustness of critical infrastructure. In this study, we investigate and compare the seismic response of near-surface soil at the Shamkir and Mingachevir hydroelectric power stations in Azerbaijan when subjected to earthquakes of different magnitudes, utilizing numerical modeling techniques. This analysis not only enables a direct comparison of the sites but also facilitates the identification of underlying geological factors influencing their seismic vulnerability.
We particularly focus on the upper 30 meters of soil, exploring its substantial influence on the amplitude-frequency composition of motions and, consequently, its impact on the surface's seismic response. Examining the soil's characteristics, we assess its capacity to either amplify or attenuate seismic motions at specific frequencies. Additionally, this study explores the intricate effects of nonlinear soil deformation on the frequency selectivity of soil, elucidating its role in shaping the amplification patterns of seismic motions. These findings are not only relevant for advancing scientific knowledge but also hold practical significance in formulating effective strategies for enhancing the seismic resilience of critical infrastructure in earthquake-prone regions.

How to cite: Kendzera, O., Semenova, Y., Topoliuk, O., Skurativskyi, S., Mykulyak, S., Skurativska, I., Trypilska, O., and Drukarenko, V.: Seismic hazard evaluation and soil response analysis of Shamkir and Mingachevir hydroelectric power stations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11911, https://doi.org/10.5194/egusphere-egu24-11911, 2024.

EGU24-12861 | ECS | Orals | NH4.4

The i-FSC proxy for predicting near-source topographic site effects and studying earthquake-induced landslide distributions 

Aline Bou Nassif, Emeline Maufroy, Pascal Lacroix, Emmanuel Chaljub, Mathieu Causse, Odin Marc, and Pierre-Yves Bard

During earthquakes, a high degree of spatial variation in damage distribution, encompassing both structural damage to buildings and co-seismic landslides, is commonly observed in mountainous regions near the seismic source. Among other factors, this spatial variability can be partly attributed to the amplification of seismic waves caused by surface topography. Our study focuses on predicting ground-motion amplification due to topography in close proximity to earthquakes and examining its potential influence on co-seismic landslide distribution patterns.

To achieve this goal, we employ neural network analysis on previously available synthetic data from 3D finite-differences simulations of seismic wave propagation. The analysis aims at developing a physics-based estimator of topographic site effects in close distances to the source, referred to as the i-FSC proxy (Illuminated Frequency Scaled Curvature). This proxy depends on the S-wavelength, the curvature of the topographic surface, and a new parameter called the "normalized seismic illumination angle", which quantifies the slope's exposure to the incoming wavefield. The inclusion of the illumination parameter substantially decreases the uncertainties of the proxy by a factor of 2 compared to estimators that rely solely on curvature as a key parameter. The i-FSC proxy is a user-friendly tool that does not require high computational resources; it utilizes only a digital elevation map and the position of the seismic source to predict amplification factors at any point on the surface topography. This estimator allows exploring the spatial variations in topographic amplification caused by nearby seismic sources, representing a significant breakthrough as areas closest to the fault typically sustain the most damage during earthquakes.

Subsequently, the i-FSC proxy is used to investigate the correlation between ground-motion amplification and the spatial distribution of earthquake-induced landslides triggered by large events such as the 2015 Gorkha earthquake (MW 7.8). The results indicate that more than 71% of co-seismic landslides tend to be localized in amplified areas. Different physical controls on the landslide triggering at different frequencies have been identified. The results also highlight the crucial importance of considering the effect of topographic amplification, together with other classical factors such as slope steepness, for a better understanding of the complex mechanisms governing the spatial distribution of earthquake-induced landslides at local and regional scales. The obtained results could provide valuable insights for future researches, guiding efforts towards more effective risk assessment and mitigation strategies in mountainous regions.

How to cite: Bou Nassif, A., Maufroy, E., Lacroix, P., Chaljub, E., Causse, M., Marc, O., and Bard, P.-Y.: The i-FSC proxy for predicting near-source topographic site effects and studying earthquake-induced landslide distributions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12861, https://doi.org/10.5194/egusphere-egu24-12861, 2024.

EGU24-13036 | Orals | NH4.4

Evaluation of the triggering potential of seismic landslides in Italy 

Simone Barani, Sina Azhideh, Gabriele Ferretti, Giacomino Pepe, and Davide Scafidi

Landslides often occur as a consequence of natural hazards among which earthquakes are one of the main triggering factors. The effects of earthquake-induced ground shaking are often sufficient to cause the failure of slopes that were marginally to moderately stable before the earthquake. In this study, we define screening maps for Italy that classify sites in terms of their potentiality of triggering earthquake-induced landslides based on seismic hazard. To this end, we analyze seismic hazard maps and hazard disaggregation results on a national scale. First, as instabilities occur for acceleration values exceeding critical acceleration, we compare surface peak ground acceleration values derived from national hazard maps with critical acceleration thresholds proposed in the scientific literature. Then, magnitude-distance (M-R) scenarios from hazard disaggregation are analyzed in relation to upper-bound M-R curves for seismic landslide triggering. Landslide triggering can not be discounted if the value of the source-to-site distance R associated with magnitude M is lower than the reference upper-bound value and surface peak ground acceleration exceeds a given critical acceleration value.

Most of the work concerns the analysis of hazard disaggregation results to define the controlling M-R scenarios. First, joint probability mass functions (PMFs) of magnitude and distance are analyzed to identify all modal scenarios (i.e., local maxima). To this end, we treat each PMF as an image and apply morphological image processing techniques to find local maxima. Specifically, the maximum (dilation) filter operation is applied. Local maxima are detected by checking for element-wise equality between the original and filtered matrices. Then, for each computation node, mean and modal M-R scenarios are compared to upper-bound M-R curves for earthquake-induced landslides selected from the scientific literature and the preferred M-R pair is selected as follows:

  • if all M-R pairs stand above the reference upper-bound curve, then the triggering of earthquake-induced landslides can be neglected.
  • if at least one M-R pair is below the reference upper-bound curve, then the triggering of earthquake-induced landslides can not be discounted.
  • if more than one M-R pair lies below the reference upper-bound curve, then the triggering of earthquake-induced landslides can not be excluded and the M-R scenario that contributes the most to the hazard (i.e., the M-R pair with the largest PMF value) is selected as the preferred magnitude.

As sites respond at specific characteristic frequencies (depending on local geological characteristics) and disaggregation results may vary with response period (T), the previous procedure is repeated considering disaggregation results associated with different spectral periods (i.e., spectral acceleration for different response periods). This allows us to define the controlling M-R pair for each site in relation to geological conditions (through site classification).

The entire workflow is replicated for three types of landslides (disrupted slides and falls, coherent slides, and lateral spreads and flows), thus leading to three maps that show areas in Italy where the triggering of landslides due to seismic activity can not be excluded. The reliability of our results is finally checked by comparing them with observations of past seismic landslides in Italy.

How to cite: Barani, S., Azhideh, S., Ferretti, G., Pepe, G., and Scafidi, D.: Evaluation of the triggering potential of seismic landslides in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13036, https://doi.org/10.5194/egusphere-egu24-13036, 2024.

EGU24-15406 | ECS | Posters on site | NH4.4

Interactive GIS mapping of local site effects in Dalmatia region in Croatia 

Bruno Mravlja, Davor Stanko, Mario Gazdek, Iva Lončar, Lada Dvornik, Tvrtko Korbar, and Snježana Markušić

In order to produce an input for more accurate Ground motion prediction equations (GMPE) that will include site effects, an array of geophysical measurements was done in Dalmatia region in Croatia, as part of CRONOS Project – Investigation of seismically vulnerable areas in Croatia and seismic ground motion assessment. Research methods used were Horizontal/vertical spectral ratio (HVSR) and Multichannel analysis surface waves (MASW), measured at 21 locations with different site effects across this seismically active region. That included over 230 microtremor HVSR measurements, enabling local soil conditions characterization, alongside seismic microzonation mapping of town of Sinj. Around 40 MASW profiles were studied, providing site Vs30 estimation. Also, continuous borehole and surface accelerographs were installed at 14 locations to assemble strong motion database for the region.

Based on this research, an interactive and open access Geographic information system (GIS) map was constructed, showing locations of measurements and all related geophysical and geological data. The regional extent of map displays locations of all measurements, combining those that are close. The local map extent shows more detail about every measurement site, in form of a label, symbol classification or a pop-up window. Additionally, in case of dense measurement data at one location (e.g. microzonation of Sinj), interpolation map of area was created, offering a fast and visually intuitive way of understanding results. Adding geological layers to the map allowed for correlation with geological site conditions, which facilitated analyses results interpretation and detection of sites that required additional measurements.

How to cite: Mravlja, B., Stanko, D., Gazdek, M., Lončar, I., Dvornik, L., Korbar, T., and Markušić, S.: Interactive GIS mapping of local site effects in Dalmatia region in Croatia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15406, https://doi.org/10.5194/egusphere-egu24-15406, 2024.

EGU24-15852 | ECS | Orals | NH4.4

Examining Seismites using Anisotropy of magnetic susceptibility in and around the Kopili Fault Zone, Northeast India: A Characterization Study 

Mujahed Baba md., Lakshmi b.v., Rokade v.m., Deenadayalan k., Patil s.n., and Priyeshu s.

 

The North East Region (NER) of India is a Tectonically Active Zone with Noteworthy Intraplate Seismic Activity over the Past 200 Years. The tectonics and seismicity of large intraplate earthquakes in NER are poorly understood. As a result, the Kopili Fault (KF) has a complex tectonic setting with a history of past two large earthquakes of 1869 Cachar earthquake (Mw-7.4) and 1943 Hajoi earthquake (Mw-7.2) are being observed. Paleoseismological evidence reveals valuable insights into seismic hazard and the historical occurrence of earthquakes, as manifested in preserved liquefaction features. Field studies carried out by excavating trenches in five sites have uncovered secondary evidence of significant liquefaction-induced deformation features, known as seismites, occurring at a depth of approximately 2-3 meters below the surface. These features manifest as sand dykes and sills, exhibiting variations in colour, grain size, and sediment indurations across the sites. The findings from the excavated trenches have been summarized, incorporating multiple analyses to differentiate the seismites from depositional features. To aid in this distinction, the study utilized the Anisotropy of Magnetic Susceptibility (AMS) technique.

The stereographic projection and bootstrap plots for the host sediment at the NB site clearly depict a vertical orientation for Kmin, while Kint and Kmax are distributed around the horizontal plane, indicative of sediment formation through fluvial activity. In the doublet liquefaction dykes NBRD and NBLD, all three axes exhibit random scattering. Notably, Kmin is sub-vertical, and Kmax is sub-horizontal in the southeast direction. The Degree of Anisotropy (Pj), Lineation (L), and Shape parameter (T) plots for the host specimen fall within the oblate field, whereas liquefaction dykes exhibit a distribution ranging from prolate to triaxial. In our presentation, we delve into a detailed discussion on how Anisotropy of Magnetic Susceptibility (AMS) serves as a valuable tool for comprehending seismite behavior and their occurrences, particularly in relation to large to great earthquakes.

Understanding the tectonic and seismic characteristics of the Kopili Fault is crucial for assessing and managing earthquake risk in Northeastern India. Our studies will likely contribute to improved earthquake preparedness and resilience in the region for future prospecting.

How to cite: md., M. B., b.v., L., v.m., R., k., D., s.n., P., and s., P.: Examining Seismites using Anisotropy of magnetic susceptibility in and around the Kopili Fault Zone, Northeast India: A Characterization Study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15852, https://doi.org/10.5194/egusphere-egu24-15852, 2024.

EGU24-18376 | ECS | Orals | NH4.4

Probabilistic modelling of soil properties variability for local seismic response analysis in NaTech events 

Giorgia Berardo, Leonardo Maria Giannini, Alessandra Marino, and Gabriele Scarascia Mugnozza

NaTech events define the interaction between natural hazards and industrial accidents leading to major fires, explosions or toxic releases where hazardous substances are involved. Among NaTech events, earthquake is one of the most important, because it affects the entire plant and can cause simultaneous damage to different equipment. This study evaluates the local seismic response at the Bussi MHIP Chemical Company, located in Abruzzo region (Central Italy). It is a representative Major-Hazard Industrial Plant (MHIP) subject to Italian standard Decree (D.Lgs. 105/2015; Directive 2012/18/EC - Seveso III), which requires a multidisciplinary approach, given the high complexity of the problem and the numerous types of equipment. We focus on the EURECO plant, located inside the Bussi MHIP, which is featured by high seismicity with potential seismic amplification phenomena due to its complex geo-lithological setting. In the present framework, the influence of soil profile properties under the EURECO plant is investigated through a stochastic site response analysis. We aim to conduct a sensitivity analysis to assess the amplification factor (AF) variability with the randomness of soil properties and geological setting. The implementation of a geological reference model was supported by building a geo-database based on 125 collected boreholes stratigraphies, which identify the main lithological units and their spatial relationships. The limited availability of deep boreholes led to the adoption of other 110 virtual boreholes, where lithological column was extrapolated from stratigraphic sections, geological maps and information from the literature. This approach allowed us to integrate and combine actual with virtual subsurface data, through expert interpretation. Soil properties were collected from a review of relevant literature and previous Seismic Microzonation studies of geologically compatible areas. From this collection, we derived physical (e.g., g, Vs) and dynamic (e.g., shear modulus G/G0, damping D) properties for each soil type. In this study, the shear modulus and damping curves proposed by Darandeli (2001) and modified by Gaudiosi (2023) were applied to each soil type. The geotechnical properties and the variability associated with their distributions have a high impact on the seismic response of a site.  From the geological model, we defined the range of variability of the parameters associated with each seismic unit (e.g. Vs shear waves, bedrock depth, geomechanical properties). We assumed two scenarios in the ultimate conditions of the plant, the Safe Life State (SLV) and the Collapse Limit State (SLC) according to the National Building Code (NTC2018). The seismic inputs were selected using the Probabilistic Seismic Hazard Analysis (PSHA) approach. We performed numerical simulations of 1D – 1D stochastic -2D site response to take into account the influence of the variability of soil parameters and selected seismic input on amplification factor (AF). The development of a seismic response analysis for each simulation allowed us to calculate the AF for the EURECO plant within the estimated fundamental period of vibration of a specific H202 storage tank located inside it. The simulated seismic scenarios could involve the overturning of the storage tank, leading to fires or the release of toxic substances.

 

How to cite: Berardo, G., Giannini, L. M., Marino, A., and Scarascia Mugnozza, G.: Probabilistic modelling of soil properties variability for local seismic response analysis in NaTech events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18376, https://doi.org/10.5194/egusphere-egu24-18376, 2024.

EGU24-19704 | ECS | Posters virtual | NH4.4

Estimation of spectral amplification coefficients of seismic motion in Greece and comparison with the corresponding coefficients of  the “Eurocode 8”. 

Eirini Chatzianagnostou, Nikolaos Theodoulidis, Ioannis Grendas, Dimitris Hatzidimitriou, and Petros Triantafyllidis

In this study the critical role of spectral amplification factors (SAFs) in seismic hazard estimation is emphasized with respect to Seismic Regulations such as Eurocode 8. Thorough analysis is carried out of accelerogram recordings at six (6) selected  stations in Greece, identified as reference sites on “rock” formations. The primary focus is in developing Vsz profile models down to the seismological(H3000) and engineering bedrock (H800), based on single station ambient noise H/V spectral ratio and on the Diffuse Field Concept, by employing the respective “HV-inv” software tool (Garcia-Jerez et al. 2016). These profiles are compared with Vsz ones at the same sites as obtained by ambient noise array data using the Geopsy software tool.

Furthermore, all spectra from the data recorded at of the aforementioned reference stations have been corrected for the horizontal and vertical site amplification, among others due to shallow weathered layers, by considering as engineering bedrock the H800 soil-rock interface. After the
correction of spectra, a parametric Generalized Inversion Technique (GIT) is applied, to theoretically estimate properties of the factors influencing seismic-wave propagation (i.e.  source, path, and site factors). The site spectral amplification factors (SAFs) as estimated by GIT for more than 150 accelerometer stations in Greece, are grouped in site categories according to Eurocode 8. The SAFs estimated in this study, are compared with those proposed in Eurocode 8 and the results are presented and discussed in light of seismic hazard assessment in Greece.

How to cite: Chatzianagnostou, E., Theodoulidis, N., Grendas, I., Hatzidimitriou, D., and Triantafyllidis, P.: Estimation of spectral amplification coefficients of seismic motion in Greece and comparison with the corresponding coefficients of  the “Eurocode 8”., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19704, https://doi.org/10.5194/egusphere-egu24-19704, 2024.

EGU24-20010 | Posters on site | NH4.4

Earthquake-Induced reactivation of large landslides: Vera-Cruz Landslide, El Salvador 

Julio Garzón-Roca, Meaza Tsige, Martín Jesús Rodríguez-Peces, and José Jesús Martinez-Diaz

El Salvador has suffered several destructive earthquakes during the past 100 year, causing severe damage and a great social alarm fundamentally associated with induced-landslides. The losses by the landslides exceed that directly caused by the earthquake itself. For example, in January 13 and February 13, 2001, two earthquakes (Mw 7.6 and Mw 6.6 respectively) triggered at least 10000 landslides, killing more than 800 people, damaging many roads and burying villages. The triggered landslides were of different types, ranging from rockfalls and relatively shallow slides, to large deep-seated landslides, being the latter the most damaging. Most of the landslides in El Salvador are concentrated in the central part of the country where recent volcanic, unconsolidated pyroclastic deposits exist, those being prone to large seismic amplification due to their special geotechnical characteristics. Landslides generally occur during earthquakes or in a short time after the seismic event. Besides, the reactivation of large landslides which has been triggered by previous earthquakes is common. In this work, a very large paleo-landslide (Vera-Cruz landslide) located also in the highest landslide concentration area of El Salvador is identified and mapped. The objective is the study of the relationship between this paleo-landslide (triggering or reactivation) and four large earthquakes, occurred between 1982 and 2001, through Newmark coseismic displacement analyses. Geotechnical properties and static factor of safety were established by performing a limit equilibrium back-analysis for a non-circular failure surface. Then the critical acceleration is obtained, using the geometry of the slope prior to the landslide. The peak ground acceleration of the site was estimated using four ground motion prediction equations established for Central America, for both volcanic arc and subduction zone. Finally, the Newmark displacement considering the influence of local amplification effects is estimated using four different empirical relationships proposed for volcanic areas. The results of the study ​​indicate that the Vera-Cruz landslide could have been triggered first by the 1982 (Mw 7.3) earthquake and subsequently reactivated by the January 13, 2001 (Mw 7.7) and/or February 13, 2001 (Mw 6.6) earthquakes. The result of this work can help in refining the study and prediction of earthquakes triggering paleo-landslides in the area, being that useful for evaluation and mitigation of coseismic landslide hazard in the region.

How to cite: Garzón-Roca, J., Tsige, M., Rodríguez-Peces, M. J., and Martinez-Diaz, J. J.: Earthquake-Induced reactivation of large landslides: Vera-Cruz Landslide, El Salvador, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20010, https://doi.org/10.5194/egusphere-egu24-20010, 2024.

EGU24-20287 | Posters on site | NH4.4

Detecting Geophysical and Geological Signatures of an unknown Fault in Messina Historical Center (Sicily, Southern Italy) 

Sebastiano D’Amico, Paolo Pino, Scolaro Silvia, Antonino Torre, Giancarlo Neri, Debora Presti, Luciano Galone, and Barbara Orecchio

The analysis of seismic noise measurements indicates an evident shift in the Site Resonant Frequency along a NW-SE axis that crosses the historic center of Messina (Sicily, Southern Italy). This shift implies a clear lateral variation in sediment layers from the southwest to the northeast along the axis. Moreover, it suggests the existence of an unreported fault, differing from the widely accepted NNE-SSW primary structural system attributed to the M 7.1 earthquake of December 28, 1908, the strongest earthquake occurred in the Messina Straits area (southern Italy) in historical times.

Further evidence supporting this NW-SE fault is provided by surface geological investigations and comprehensive analyses of morphological and Digital Terrain Model data. While geological observations clearly suggest normal faulting, they do not explicitly reveal any potential strike-slip components. The activity of this NW-SE fault extends back to at least the Middle Pleistocene, as inferred from stratigraphic evidence and borehole data, possibly persisting into the Upper Pleistocene.

This newly detected fault warrants more extensive investigation in the near future to ascertain its precise spatial extent and contemporary dynamics, particularly regarding its potential for seismic activity.

How to cite: D’Amico, S., Pino, P., Silvia, S., Torre, A., Neri, G., Presti, D., Galone, L., and Orecchio, B.: Detecting Geophysical and Geological Signatures of an unknown Fault in Messina Historical Center (Sicily, Southern Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20287, https://doi.org/10.5194/egusphere-egu24-20287, 2024.

EGU24-1045 | ECS | Posters on site | TS3.5

Tectono-Geomorphic Studies along the Khetpurali Taksal Fault, Northwestern Himalayas 

Poorvi Narayana and Javed N Mailk

The Northwestern Himalayas have been host to many earthquakes, with the recent 1905 Kangra Mw 7.8. Studies suggest the seismic gap in the Northwestern Himalayas to be more than Mw 7.8 in general, and of about Mw 8.4 in the Nahan region of the Northwestern Himalayas. There are studies suggesting the rupture of the Himalayan Frontal Thrust (HFT) and hinterland subsidiary faults by the Earthquakes in the region. In this study, we focused the Khetpurali Taksal Fault (KTF), which is one of the corroboration. It is an out-of- sequence ~ 250 km long dextral strike-slip fault with an NNW-SSE trend. KTF, which is bounded to the west by the Nahan Salient, and in the east by the Dehradun re-entrant; marks the boundary between the Central Himalayas (convergence rate ~ 18 ± 1 mm/y and obliquity ~0°) and the Northwestern Himalayas (convergence rate ~13.6–14 ± 1 mm/yr and obliquity ~ 15°-30°), which runs through the ~ 100km locked width of the Main Himalayan Trust (MHT). The dextral strike-slip motion has caused the displacement of some quaternary deposits along the KTF. It plays a key role in the slip partitioning between the active thrust and the oblique faults with the HFT displaying the thrusting and oblique component in the Pinjore Garden fault, Jhajra fault, and Barsar fault of the same region in the Northwestern Himalayas. This study is focused on the active fault along the KTF. We prepared the geomorphic map and delineated the extent of the KTF using the high-resolution Cartosat-1 data. Our studies show the presence of displaced terraces, lateral offset of streams, sag ponds, and pressure ridges along the KTF. A displacement of 250m to 1350m has been observed. Samples from the displaced terraces are analyzed by OSL dating technique to find out the slip along the KTF. Understanding the slip along KTF will enhance the understanding of slip partitioning taking place in the Nahan Region as a whole, which will help understand the geodynamics of the region and thus in seismic hazard assessment.

How to cite: Narayana, P. and Mailk, J. N.: Tectono-Geomorphic Studies along the Khetpurali Taksal Fault, Northwestern Himalayas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1045, https://doi.org/10.5194/egusphere-egu24-1045, 2024.

EGU24-1056 | ECS | Posters on site | TS3.5

Active Fault and Paleoseismological studies in the hinterland region of NW Himalaya 

Rukhshar Husain and Javed N Malik

The Indian plate is currently underthrusting beneath the Tibetan plateau along the Main Himalayan Thrust (MHT). The strain is getting accumulated during the inter-seismic period on MHT due to this ongoing convergence. The accumulated strain energy is released in a stick-slip fashion on MHT causing destructive earthquakes. Several strong earthquakes within the Himalayan zone have been reported in previous studies such as 1897 at Shillong (Mw 8.2), 1905 at Kangra (Mw 7.8), 1934 at Bihar-Nepal (Mw 8.1), 1950 at Assam (Mw 8.4), 2005 at Muzaffarabad (Mw 7.6), 2015 at Gorkha (Mw 7.8), and 2015 in Afghanistan (Mw 7.6). Based on the distribution of recent and historic earthquake activity in the Himalayas, three seismic gaps can be distinguished from west to east: the Kashmir Seismic Gap (west of the 1905 Kangra earthquake), the Central Seismic Gap (between the 1905 and earthquakes), and the Assam Seismic Gap (between the 1897 and 1950 earthquakes). The major objective of this study is to investigate the hinterland region in the NW Himalaya, which is relatively less explored in terms of its Active Tectonics & Paleoseismology as compared to the deformation front along the Main Himalayan Thrust (MFT). The Nahan salient and Kangra re-entrant are characterised by a complicated pattern of fault distribution which has been proposed in previous studies to get activated, either individually or alongside the Main Frontal thrust, during past large to great-magnitude earthquakes. A detailed tectono-geomorphic map has been prepared using the Cartosat-1 dataset, and geomorphic markers suggestive of recent tectonic activity have been identified in the study region. An exhaustive fieldwork has been conducted, during which a total of 13 samples were collected for Optically Stimulated Luminescence (OSL) dating and Carbon dating to identify signatures of past earthquakes and assess the possibility and degree to which the 1905 earthquake has affected the region. Based on the detailed tectono-geomorphological and paleoseismological investigations, we will be able to assess regional seismic hazards.

(*Author RH aka Rukhshar)

How to cite: Husain, R. and Malik, J. N.: Active Fault and Paleoseismological studies in the hinterland region of NW Himalaya, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1056, https://doi.org/10.5194/egusphere-egu24-1056, 2024.

EGU24-2671 | ECS | Orals | TS3.5

Seismic risk microzonation mapping using microtremor recordings for an urban area in the vicinity of Lamni Fault, southern Kashmir Basin  

Falak Zahoor, Villayat Ali, Bashir Ahmad, and Inaam ul Haq Jeelani

A high-angle reverse fault was identified near the Aharbal Falls in the Shopian District of the southern Kashmir Basin and was subsequently named as Lamni Fault by Zahoor et al. (2023). The rise of the Pir Panjal range due to the higher tectonic activity in the southern part of Kashmir (Dar et al., 2014) has led to the overthrusting of the Early Permian Panjal Traps over the Pleistocene Fluvio-Glacial Deposits. The presence of the fault was experimentally validated through the conduction of single-station microtremor horizontal-to-vertical spectral ratio (MHVSR) method, supported by the results from multichannel simulation with one-receiver (MSOR) surface wave tests across the suspected fault zone in Shopian. The fault zone was demarcated at the location by identifying anomalously high H/V amplitudes (>8) at high frequencies (>4Hz) as opposed to the low values (2-3) in the surrounding host rock. As an extension of the work, we seek to conduct the microzonation of the region laced by the Lamni Fault in the Sedow area of Shopian, Kashmir, using the atypical HVSR amplitudes as the markers of high risk. The MHVSR method has been successfully employed for investigating buried and exposed faults like Erft-Sprung normal fault, Tremestieri normal fault, southern Crete of Greece, Longmen Shan fault zone, etc. (Hinzen, 2004; Lombardo and Rigano 2006; Moisidi et al., 2012; Zhang et al., 2019). The low-velocity fractured fault zone is known trap seismic waves and hence lead to large amplifications of the waves which is thus reflected in the HVSR curves as well as in earthquake recordings e.g., in San Andreas fault zone (Li et al., 2000) and San Jacinto fault zone (Roux et al., 2016). Utilising this behaviour of the fractured fault zones, microzonation of the Sedow locality which lies in the vicinity of the detected Lamni Fault was conducted by performing about 50-60 single-station MHVSR tests over an area of about 2 km x 2 km. The area has several residential buildings along with local government school buildings as well as a mosque, thus demanding serious consideration of the increased seismic hazard due to the presence of the fault. Zones of anomalous H/V amplitudes were found in the region surrounded by stable low estimates. This may have serious implications for the seismic hazard estimates in the region surrounding the fault zone also supported in earlier studies in other regions of the world (e.g., Spudich and Olsen, 2001; Donati et al., 2001; Rovelli et al., 2002). It is recommended that a zone be defined at a significant width around the fault zone in which constructions may be avoided or else special considerations for the increased seismic hazard be considered for the existing buildings. Such a buffer zone has been named the Alquist-Priolo zone, APZ in earlier studies (Spudich and Olsen, 2001; Bryant, 2010). The APZ is considered an important inclusion in seismic hazard and microzonation process to aid in urban planning and development in a region.

How to cite: Zahoor, F., Ali, V., Ahmad, B., and Jeelani, I. U. H.: Seismic risk microzonation mapping using microtremor recordings for an urban area in the vicinity of Lamni Fault, southern Kashmir Basin , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2671, https://doi.org/10.5194/egusphere-egu24-2671, 2024.

The January 10, 2022, MS 6.9 Menyuan, China, earthquake occurred caused by strike-slip faulting in the tectonically complex region of the northeastern Tibetan Plateau, and ten people were injured in Menyuan City. The September 8, 2023, MS 6.9 Morocco, earthquake occurred in the African Plate at shallow depth with oblique-reverse faulting. At least 2,900 people were killed and more than 5,000 injured in Morocco till to September 13, 2023. International media reports of such kind of disasters by the Morocco earthquake only resulted from poor building structure design and low-solidity housing, such as in Marrakech, southwest of the epicenter. The surface wave magnitude (MS) of the two earthquakes is the same, and the moment magnitude (MW) and energy magnitude (Me) of the Menyuan mainshock are slightly lower than those of the Morocco event. Although the scalar moment and radiated seismic energy from Morocco dynamic rupture are only 2~3 times of the Menyuan earthquake, the density of urban residents nearby and around the epicenter of the Morocco mainshock is at least more than a hundred times higher than that around the epicenter of the Menyuan even. For the Morocco sequence, the USGS reported the number of aftershocks higher than MW4.0 is only seven and the largest is 4.9. In contrast, there are two aftershocks higher than MS5.0 in the Menyuan sequence recorded by the China Earthquake Networks Center, 5.1 and 5.2, respectively. Normally, a similar magnitude does not reflect the equivalent seismic moment, release of radiated energy, and the occurrence of strong aftershocks. Meanwhile, devastating loss of life and injuries are not only due to the design of the building and the quality of the house.

Acknowledgment: This research is supported by the Spark Program of Earthquake Sciences (XH22012YC)

How to cite: Meng, L., Zang, Y., and Xie, M.: The Differential of Casualties, Energy Radiation, and Characteristics of Sequences from the Same MS: The Menyuan MS 6.9 2022 and Morocco MS 6.9 2023 Earthquakes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3159, https://doi.org/10.5194/egusphere-egu24-3159, 2024.

EGU24-5155 | Posters on site | TS3.5

Empirical scaling correlations between fault lengths and fault slip-rates in seismically-active extensional regions: The Calabria and Messina Strait region (southern Italy) as case study 

Marco Meschis, Gerald Roberts, Claudia Sgambato, Alessandro Maria Michetti, Franz Livio, Zoe Mildon, Joanna Faure Walker, Francesco Iezzi, Jennifer Robertson, Alessandro Gattuso, Marino Domenico Barberio, Paolo Randazzo, and Antonio Caracausi

In this study, we present scaling relationships between fault lengths, fault slip-rates and historical seismicity for an active normal fault system, seismically accommodating crustal extension within the upper plate of the Ionian subduction zone (southern Italy). This crustal extension is confirmed by historical seismicity and instrumental geodesy, with GNSS-derived values of horizonal deformation within a range of 2-3 mm/yr throughout Calabria and the Messina Strait region. We collated data for fault slip-rates, fault lengths and historical earthquakes for a given fault to explore whether fault slip-rates are correlated with fault size and their geometric moment.

We present new results showing a robust correlation between fault lengths and fault slip-rates, which supports the idea of a relationship for a given fault between fault slip-rates and the geometric moment.

We discuss our results in terms of how these correlations should be used if regional deformation is accommodated by localised strain on faults mostly arranged along strike rather than distributed strain on multiple faults across-strike. For instance, we compare our empirical correlation between fault lengths and fault throw-rates over the Middle-Late Pleistocene in Calabria and the Messina Strait with those from Central and Southern Apennines over the Holocene, characterized by strain distributed on multiple faults across-strike and strain localised on faults mostly arranged along-strike, respectively.

Tectonic and seismic hazard implications are discussed for future investigations based on fault slip-rates, fault size and historical seismicity.

How to cite: Meschis, M., Roberts, G., Sgambato, C., Michetti, A. M., Livio, F., Mildon, Z., Faure Walker, J., Iezzi, F., Robertson, J., Gattuso, A., Barberio, M. D., Randazzo, P., and Caracausi, A.: Empirical scaling correlations between fault lengths and fault slip-rates in seismically-active extensional regions: The Calabria and Messina Strait region (southern Italy) as case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5155, https://doi.org/10.5194/egusphere-egu24-5155, 2024.

EGU24-7698 | Posters on site | TS3.5

Exploring the uncertainties of the fault source parameters in the Alboran Sea for seismic hazard using earthquake rate modelling tools 

Hector Perea, Octavi Gómez-Novell, María José Jiménez, Mariano García, Lucía Lozano, Julián García-Mayordomo, José Luis Sánchez-Roldán, Ariadna Canari Bordoy, and Sara Martínez-Loriente

The Alboran Sea is one of the most seismically regions of Western Europe, accommodating an important part of the current NW-SE convergence between the African and Eurasian plates (4-5 mm/yr). Despite the Alboran Sea is considered as a region of relatively low tectonic deformation and diffuse seismicity, the major faults within have been responsible of large earthquakes (IEMS>IX) since historical times (e.g., 1522 Almería, 1790 Oran, 1804 Alboran, 1910 Adra or 2016 Al-Idrissi earthquakes). One of the main issues for the characterization of the seismic hazard in the Alboran Sea, common to many low-deformation regions, lies in accurately constraining the seismic parameters that define fault activity and their behavior (i.e., slip rates, earthquake recurrence and multi-fault rupture capability, among others). This issue is further aggravated by the fact that these faults are mostly located offshore, making their investigation more challenging. As a result, most faults in the Alboran Sea have poor slip and activity rate estimates, while their capability to interact and rupture in complex rupture patterns has not been explored yet. In this study, we compute several models of earthquake rupture rates for the Alboran Sea with the SHERIFS code and using a systematic parameter exploration tree to determine the parameters of each model. We base the exploration tree on the slip rate and multi-fault rupture scenarios, allowing us to investigate the epistemic uncertainty linked to these parameters. To check the feasibility of the computed earthquake rates of each model, we compare them with the observed seismicity rates in the region. As a result, this enables us to identify which parameter combinations best match the recorded seismicity, prioritizing those that perform better for the hazard assessment. In addition, these optimal values might be used as indicators for further studies focused on better constraining the fault parameters in some faults, as well as for preliminary fault-based seismic hazard assessments. By extension, the limitations of the modelling in terms of slip rate budget distribution and fault rupture scenarios can also be used to determine which areas should be prioritized for further research. We expect that the results of our work enhance discussion among researchers working in the area and motivate further investigations into fault dynamics.

How to cite: Perea, H., Gómez-Novell, O., Jiménez, M. J., García, M., Lozano, L., García-Mayordomo, J., Sánchez-Roldán, J. L., Canari Bordoy, A., and Martínez-Loriente, S.: Exploring the uncertainties of the fault source parameters in the Alboran Sea for seismic hazard using earthquake rate modelling tools, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7698, https://doi.org/10.5194/egusphere-egu24-7698, 2024.

EGU24-7956 | ECS | Posters on site | TS3.5

A Millennial Perspective on Coulomb Stress Transfer Impact in the seismicity of the Central Apennine Fault System 

Giorgio Valentini, Tiziano Volatili, Paolo Galli, and Emanuele Tondi

This research examines the influence of static Coulomb Stress Transfer (CST) in shaping the seismic cycles associated with the Central Apennine Fault System (CAFS), an active tectonic region that witnessed numerous destructive seismic events over the last millennium.

We selected 15 seismic events in the CAFS, dating from 1279 CE to the present, all exceeding Mw 6.0. Out of these, 9 events were specifically chosen for CST analysis, based on their spatial-temporal proximity to later activated faults. The study not only investigates static stress transfer for each event, but also considers the cumulative CST from recent earthquakes, providing a holistic view of the current stress environment. Following a novel approach, we utilized a three-dimensional fault modeling technique, with ellipses representing the 2D geometry of faults at depth. This approach accounts for strike variations and employs a variable strike three-dimensional elliptical model for enhanced precision in CST calculations.

Our case studies within the CAFS suggest that CST might have been a critical factor in either triggering or inhibiting fault activities. Instances of fault reactivation following high stress transfers and scenarios showing the dampening effects of stress shadows were observed. This intricate understanding of CST has practical implications, offering insights into potential future earthquake patterns and aiding in devising targeted risk mitigation strategies.

The complexity of CAFS reveals intricate stress patterns emerging from the interplay of different seismic episodes. These patterns of stress lobes interact in complex ways, influencing adjacent faults by amplifying, neutralizing, or diversifying their CST impacts. Through detailed analyses and cutting-edge modeling techniques, our study provides valuable insights for future research directions and practical approaches to seismic risk reduction. It underscores the strong impact of CST on shaping a region's seismic history and highlights the necessity of ongoing research in this vital area of geosciences.

How to cite: Valentini, G., Volatili, T., Galli, P., and Tondi, E.: A Millennial Perspective on Coulomb Stress Transfer Impact in the seismicity of the Central Apennine Fault System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7956, https://doi.org/10.5194/egusphere-egu24-7956, 2024.

EGU24-9870 | Orals | TS3.5

Characteristics of slip-rate variability and temporal earthquake clustering across a distributed network of active normal faults from in situ 36Cl cosmogenic dating of fault scarp exhumation. 

Gerald P. Roberts, Claudia Sgambato, Ioannis Papanikolaou, Zoe Mildon, Joakim Beck, Alessandro Michetti, Joanna Faure Walker, Sam Mitchell, Marco Meschis, Richard Shanks, Richard Phillips, Ken McCaffrey, Eutizio Vittori, Francesco Iezzi, Jennifer Robertson, Francesco Visini, and Maz Iqbal

We present an in situ 36Cl dataset recording the exhumation of 27 active normal fault planes by earthquake slip for the central Apennines, Italy. We do this to constrain the characteristics of earthquake clustering and anticlustering across the entire extending orogen, and in an attempt to constrain the reasons why clustering and anticlustering occurs. We show that duration and magnitude of clustering and anticlustering, and their characteristics, can be explained by a model where the transfer of differential stress between faults and their underlying shear-zones, and between neighbouring fault/shear-zone structures, produces changes in strain-rates on underlying viscous shear zones which drive periods of rapid or reduced slip-rate on their overlying faults. We suggest that stress increase on an underlying shear zone produced by coseismic slip on its overlying fault could be the mechanism that initiates an earthquake cluster. We suggest that stress reductions on shear-zones from coseismic slip located across strike could be the mechanism that initiates an earthquake anticluster. The durations of anticlusters are controlled by the summed stress decreases through time on shear zones, because although these shear zones are slipping relatively slowly, eventually they will load their overlying fault to failure initiating a new cluster, with anticlusters induced across strike. Thus, there is dynamic feedback both up and down dip between faults and their underlying shear zones and crucially across strike between neighbouring fault/shear-zone structures. If the dynamics producing clustering and anticlustering can be constrained, it may be that observations of these phenomena should be included in probabilistic seismic hazard assessments (PSHA) and also interpretations of regional deformation rates and crustal rheologies based on geodetic data. Multi-millennial clustering and anticlustering should become a subject for discussion in these scientific communities.

How to cite: Roberts, G. P., Sgambato, C., Papanikolaou, I., Mildon, Z., Beck, J., Michetti, A., Faure Walker, J., Mitchell, S., Meschis, M., Shanks, R., Phillips, R., McCaffrey, K., Vittori, E., Iezzi, F., Robertson, J., Visini, F., and Iqbal, M.: Characteristics of slip-rate variability and temporal earthquake clustering across a distributed network of active normal faults from in situ 36Cl cosmogenic dating of fault scarp exhumation., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9870, https://doi.org/10.5194/egusphere-egu24-9870, 2024.

We investigate the Coulomb stress changes due to 30 strong earthquakes occurring on normal faults since 1509 A.D. in Calabria, Italy, including the influence of both coseismic and interseismic loading in our modelling. We compare the results to existing studies of stress interaction from the Central and Southern Apennines, Italy. The three normal fault systems have different geometries and long-term slip-rates. The Central Apennines hosts a complex fault system, with many faults across strike, so that when an earthquake occurs, many of the surrounding faults experience a stress decrease. The Southern Apennines and Calabria have a simpler geometry, with fewer faults, and faults are located predominantly along strike, therefore when an earthquake occurs the dominant process on the neighbouring faults is stress increase. We investigate how stress transfer may influence the occurrence of future earthquakes and what factors may govern the variability in earthquake recurrence in different fault systems. Within the analysed time period, the Calabrian, Central Apennines, and Southern Apennines fault systems have 91%, 73% and 70% of faults with a mean positive cumulative Coulomb stress change, respectively; this is due to fewer faults across strike, more across strike stress reductions, and greater along-strike spacing in the three regions respectively. In regions with close along strike spacing or few faults across strike, such as Calabria and Southern Apennines, the stress loading history is mostly dominated by interseismic loading and most faults are positively stressed before an earthquake occur on them (96% of all faults that ruptured in Calabria; 94% of faults in the Southern Apennines), and some of the strongest earthquakes occur on faults with the highest mean cumulative stress of all faults prior to the earthquake. In the Central Apennines, where across strike interactions are the predominant process, 79% of the earthquakes occur on faults that are positively stressed. The results highlight that fault system geometry plays a central role in characterizing the stress evolution associated with earthquake recurrence, and can possibly influence the occurrence of propagating triggered earthquake sequences.

How to cite: Sgambato, C., Faure Walker, J. P., Roberts, G. P., Mildon, Z. K., and Meschis, M.: Influence of fault system geometry and slip rates on earthquake triggering and recurrence variability, insights from Coulomb stress interactions during historical earthquake sequences in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10100, https://doi.org/10.5194/egusphere-egu24-10100, 2024.

EGU24-10122 | ECS | Orals | TS3.5

Using fracture-scarp lineations as kinematic indicators on active normal fault scarps 

Billy Andrews, Zoë Mildon, Manuel Lukas Diercks, Sam Mitchell, Gerald Roberts, Constanza Rodriguez Piceda, and Jenni Robertson

To undertake fault-based seismic hazard assessment, we need to accurately identify source faults and assess their slip-rate and kinematics through pertinent data collection. For example, converging slip vectors may be used to deduce whether isolated fault strands are connected at depth. Kinematic (slip vector) data can be collected through offset piercing points or from striations preserved on fault scarps. However, striations are surficial features and may therefore be readily eroded and not preserved or visible on degraded scarps. Tensional fracture networks are ubiquitous on bedrock fault scarps and extend deeper into the scarp, and therefore have a greater preservation potential when compared to striations. In this work we characterise fracture-scarp (F-S) lineation patterns across eight faults in Italy (Central Apennines) and Greece (Perachora Peninsula) to explore how these patterns relate to fault plane geometry and slip-vector.

Various fracture-scarp (F-S) lineation patterns (including sinistral/dextral en-echelon arrays, slip-parallel/-perpendicular fractures, and conjugate sets) are recognised. These patterns show evidence of progressive growth during exhumation. This suggests F-S lineations formed near the surface as the footwall uplifts, with larger features becoming more connected and smaller ones remaining ‘isolated’. The orientations of F-S lineations align within a pure or Riedel shear geometry where the shear sense is related to the rake of the slip vector. We propose that the observed patterns are controlled by fault plane orientation relative to a 3D strain ellipsoid and the progressive reduction of effective normal stress during footwall exhumation. As fractures form under the same stress regime as striations, they can serve as a kinematic indicator even on highly degraded active fault scarps.

How to cite: Andrews, B., Mildon, Z., Lukas Diercks, M., Mitchell, S., Roberts, G., Rodriguez Piceda, C., and Robertson, J.: Using fracture-scarp lineations as kinematic indicators on active normal fault scarps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10122, https://doi.org/10.5194/egusphere-egu24-10122, 2024.

EGU24-10216 | ECS | Posters on site | TS3.5

Fault interactions and Coulomb stress-triggering in complex fault networks 

Manuel Diercks, Zoe Mildon, Sarah Boulton, Ekbal Hussain, Cihat Alçiçek, Tunahan Aykut, and Cengiz Yıldırım

Earthquakes on normal faults cause negative Coulomb stress transfer (CST) onto receiver faults located across-strike, which, in theory, delays or prevents rupture. Nevertheless, earthquakes on such across-strike faults are frequently observed. This study explores why, and how, large earthquakes can be triggered on faults repeatedly receiving negative coseismic CST. Two triggering mechanisms are hypothesised: (1) Positively stressed patches or segments of faults, resulting from heterogeneous stress transfer, act as triggers to rupture earthquakes on faults that are on average negatively stressed. (2) Negative coseismic CST is compensated by interseismic loading and other processes building up positive stress on the source faults. To test both hypotheses, a 400-year earthquake sequence is modelled, located in the fault network of the Western Anatolian Extensional Province (SW Türkiye). The fault network features multiple active faults located along-strike and across-strike of another, as well as faults in a variety of orientations, suitable to explore stress-triggering mechanisms in a structurally complex setting. Detailed information on fault location, geometry, and mechanism is compiled from field investigations, literature review, and geodetic data. Based on instrumental and historical earthquake catalogues, and the suitability of the source fault network, a sequence of earthquakes is determined to investigate the two hypotheses by comparing the effects of coseismic CST and interseismic loading.

Results show that, out of 28 modelled large (MW ≥6) earthquakes, 6 were triggered on faults receiving significant negative coseismic CST. For five of these, negative coseismic CST is compensated by processes increasing CST. Only for one studied example, highly stressed positive fault segments on an otherwise negatively stressed fault could have been the driving mechanism leading to rupture of a large earthquake. Given all model uncertainties, stress-heterogeneities cannot be validated as a probable triggering mechanism for faults in the stress shadow of neighbouring faults. In contrast, earthquakes on normal faults located across-strike of another can only delay, but in most cases not prevent failure, as interseismic loading usually exceeds negative coseismic CST.

To reinforce these results, the impact of the modelled fault geometry and slip rates, used to calculate interseismic loading, is evaluated. Models of strike- and dip-variable faults, following the actual surface fault traces, are compared with simplified, planar fault models. Simplified models feature exaggerated areas of positive and negative CST on source faults prior to earthquakes, essentially distorting the stress field and causing stress-heterogeneities that are less pronounced in more realistic models. This observation highlights the necessity of modelling fault geometry as realistic as possible, especially when models are used in fault-based SHA. The impact of slip rates on model results is less drastic, so long as slip rates are used that are determined on similar time scales as the model duration. For the studied fault network short-term (geodetic) and long-term (‘geologic’) slip rates vary from the ‘Holocene’ slip rates by an order of magnitude. If used for modelling interseismic loading, the stress state and recurrence intervals of faults would be drastically under- or overestimated.

How to cite: Diercks, M., Mildon, Z., Boulton, S., Hussain, E., Alçiçek, C., Aykut, T., and Yıldırım, C.: Fault interactions and Coulomb stress-triggering in complex fault networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10216, https://doi.org/10.5194/egusphere-egu24-10216, 2024.

Understanding earthquake initiation, propagation, and arrest is critical for mitigating seismic risks, yet these processes remain among the most complex natural phenomena to decipher. The ERC-Synergy project FEAR (Fault Activation and Earthquake Ruptures), conducted within the Bedretto Underground Laboratory for Geosciences and Geoenergy (BedrettoLab), offers a pioneering approach to investigate these intricate mechanics. Here, we highlight the unique challenges and opportunities presented by the FEAR project, with a particular focus on computational earthquake physics and its potential to enhance our understanding of fluid-induced seismic events on broadband seismic arrays. Located ~1.5 kilometers beneath the Swiss Alps, BedrettoLab provides an unparalleled setting for a detailed study of earthquake mechanics. The FEAR project utilizes this exceptional environment to induce and monitor small-scale seismic events. By employing hydraulic stimulation on selected faults near the BedrettoLab tunnel, the project aims to initiate and observe earthquakes of approximately magnitude ~1.0. These refined methods provide a controlled setting to study the intricate details of earthquake processes closely, offering a chance to push the boundaries of current understanding of earthquake physics.

Central to the FEAR project is the development and testing of hydro-mechanical computational methods capable of replicating various injection protocols. These methods systematically test a range of constitutive laws that govern the evolution of fault friction, integrating insights from laboratory experiments with fully inertial elastodynamic modeling of earthquake processes. This approach allows us to investigate the poroelastic response of the rock mass, examining how seismic and aseismic slip interact in space and time, and assessing the dynamic evolution of pore-fluid pressure due to processes such as shear-induced dilatancy and compaction. Furthermore, we employ 3D dynamic rupture simulations to explore conditions controlling either self-arresting or run-away rupture. These simulations provide critical insights into wave spectrum and attenuation near BedrettoLab, enabling us to predict the peak ground velocity (PGV) of anticipated magnitude ~1 earthquakes. This innovative modeling approach represents a significant opportunity to advance our understanding of fault mechanics and the influence of fluid interactions.

In conclusion, the FEAR project within BedrettoLab provides a unique and controlled environment to study the mechanics of earthquakes. The challenges posed by this research are matched by the significant opportunities it offers for advancing our understanding of seismic phenomena. By focusing on innovative modeling techniques and integrating multidisciplinary data, this project aims to shed light on the complex dynamics of fault activation and rupture, ultimately contributing to more accurate seismic hazard assessments and safer geoenergy practices.

How to cite: Dal Zilio, L. and the FEAR team: Modeling Earthquake Dynamics and Fault Poromechanics in the BedrettoLab FEAR Project: Opportunities & Challenges, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11726, https://doi.org/10.5194/egusphere-egu24-11726, 2024.

Himalayan seismicity exhibits a bimodal mechanism with great earthquakes (+M8) rupturing the upper locked segment of the Main Himalayan Thrust (MHT) and blind earthquakes (up to Mw ~ 7.8) rupturing the down-dip section of the decollement. However, few imbricate and out-of-sequence active structures have been overlooked with limited research in the hinterland regions with respect to active fault mapping and paleoseismological trench excavations. The present study focusses on the western section of the Trans-Yamuna Active Fault (TYAF) in northwestern Sub-Himalaya, hosting the Sirmurital Active Fault (SAF). The SAF exhibits a distinctive south-side up trace, obliquely cross-cutting the Main Boundary Thrust (MBT).

Satellite data, coupled with detailed field investigation confirms that the above fault dips 60˚ to the north, with a fault scarp of 40 m height. Minor strike-slip component is also confirmed with the presence of a subtle pressure ridge, and preliminary fluvial terrace mapping. Generation of a high-resolution Digital Elevation Model (DEM) from Cartosat-1 stereo pairs, and quantification with total station mapping of fault scarp further confirmed the terrace displacement. Subsequently, trench excavation (31 m in length) across the SAF at Sirmurital village provided compelling evidence of atleast two paleoearthquakes displacing and deforming Quaternary sediments along two identified fault strands. Soft-sediment deformation features complemented with injection features suggests its genetic link with paleoearthquakes. Radiocarbon dating analysis offers insights into the probable timing of the faulting events. Overall, the tectonic placement of the SAF provides a unique opportunity to document the occurrence of a normal fault in the hanging wall of a megathrust system and its potential to generate earthquakes in the highly populous mountainous belt of NW Sub-Himalaya. Therefore, the SAF along with the other associated faults, in the hinterland calls for detailed evaluation for a more comprehensive seismic hazard assessment.

 

Keywords: Out of sequence; Sirmurital Active Fault; Cartosat-1; Paleoearthquakes; Soft-sediment deformation; Seismic hazard 

 

How to cite: Ghosh, S., Philip, G., and Narayanapanicker, S.: Evidence of surface rupture associated with paleoearthquakes in the Trans Yamuna Segment of Northwestern Sub-Himalaya, India - Focus on the Sirmurital Active Fault , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12101, https://doi.org/10.5194/egusphere-egu24-12101, 2024.

EGU24-14251 | Orals | TS3.5

Palaeoseismology and tectonic geomorphology for detecting the seismic behaviour of the Pidima-Anthia Fault, south Greece 

Ioannis Koukouvelas, Athanassios Ganas, Vasiliki Zygouri, and Christina Tsimi

Geomorphologic analysis and data from paleoseismological sites across segmented active faults help the evaluation of past and future seismic faulting. The study of paleo-earthquakes on the Pidima-Anthia Fault provides an opportunity to unravel the seismic behaviour of the Eastern Messinia Fault Zone (EMFZ) that defines the western border of the N-S trending Taygetos Mtn range in Peloponnese (southern Greece). This fault zone is segmented and includes a complex system of primarily normal fault- segments dipping westwards, with a traceable length from 6-10 km. We applied geomorphological and palaeoseismological analysis across the Pidima-Anthia Fault segment. The palaeoseismological trench data provide evidence for five M >6.4 earthquakes and indicate an apparent slip rate of 0.23 mm/a. Geomorphologically, the modelling of a footwall series of triangular facets, attest to a slip-rate estimation in the order of 0.28-0.44 mm/a. These data highlight that the slip rate of the fault is remarkably stable for the Quaternary period but particularly over the last 17 ka period, as well as that this duration is enough for a morphogenic active fault to create seismic landscapes. The Holocene earthquake history of the Pidima-Anthia Fault allows its comparison with six other known active normal faults of southern Greece. The overall data indicate a pattern of earthquake clustering in the southern Greece faults ("Wallace-type" behaviour). In particular, the Pidima-Anthia Fault's seismic history resembles with time predictable earthquakes and clustering during the Holocene. However, the Pidima-Anthia Fault during the current period (i.e., post 1 Ka AD) does not display cluster time-predictable behaviour, and a strong earthquake can happen at any time.

How to cite: Koukouvelas, I., Ganas, A., Zygouri, V., and Tsimi, C.: Palaeoseismology and tectonic geomorphology for detecting the seismic behaviour of the Pidima-Anthia Fault, south Greece, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14251, https://doi.org/10.5194/egusphere-egu24-14251, 2024.

EGU24-15619 | ECS | Posters on site | TS3.5

Deciphering the recent activity of normal faults in the Hellenic Volcanic Arc from combined morpho-tectonics analysis and TCNs method dating (36Cl), Amorgos Island (Greece)  

Sylvain Palagonia, Frédérique Leclerc, Christophe Larroque, Lucilla Benedetti, Nathalie Feuillet, Paraskevi Nomikou, Maxime Henriquet, Valery Guillou, and Fabio Manta

The study of normal fault-generated landforms, such as fault scarps, is commonly performed to investigate fault evolution and the recurrence and magnitude of earthquakes. The Amorgos region (Cyclades, Greece), located in the central part of the Aegean Sea, is structured by ~70km large NE-SW normal faults accommodating the back-arc extension of the Hellenic arc and the Anatolian extrusion. These faults are able to generate large earthquakes such as the Amorgos event (Ms=7.8) on July 09, 1956, followed by a second shock (Ms=7.2) 12 minutes later. This destructive event was the largest Mediterranean earthquake of the 20th century and caused severe damage, especially on Santorini Island. It also triggered a tsunami with reported run-ups reaching locally 30m along the southern coast of Amorgos Island. The submarine Amorgos fault, structuring the island’s southern coast and cumulating a ~2 km high vertical offset, is suggested to be the source of the 1956 main shock and tsunami. However, the accurate position of the 1956 rupture and the magnitude of the slip at surface are unknown, as the fault outcrops at 700m below sea level, as well as the pace at which this fault breaks. Considering that normal faults frequently accommodate the deformation on multiple splays, and within their damage zone, we searched whether the onland faults found within the cumulative scarp of the Amorgos fault ruptured during the 1956 event. We first performed a morphological study of the Chozoviotissa fault segment with satellite imagery, Structure-from-motion modelling, and field observations. We found evidence of recent deformation along this fault, in particular a ~70 cm high fresh ribbon at the base of the fault scarp. To provide chronological constraints, we sampled along-dip the carbonate-rich fault scarp for TCNs (Terrestrial Cosmogenic Nuclides) dating using the chlorine-36 element. This paleoseismic approach provides new insights on the recent slip history of this secondary fault, which is important to better evaluate the activity of the Amorgos fault system and improve the hazard assessment of the archipelago.

How to cite: Palagonia, S., Leclerc, F., Larroque, C., Benedetti, L., Feuillet, N., Nomikou, P., Henriquet, M., Guillou, V., and Manta, F.: Deciphering the recent activity of normal faults in the Hellenic Volcanic Arc from combined morpho-tectonics analysis and TCNs method dating (36Cl), Amorgos Island (Greece) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15619, https://doi.org/10.5194/egusphere-egu24-15619, 2024.

EGU24-16169 | ECS | Posters on site | TS3.5

Analysis of active and fossil seismic structures: a multidisciplinary study for the seismic risk assessment in low-seismicity regions 

Michele Locatelli, Laura Crispini, Marco Scambelluri, Laura Federico, Daniele Spallarossa, Danilo Morelli, and Paola Cianfarra

Understanding the source processes and wave propagation in heterogeneous rock media is one of the most challenging frontiers to improve the seismic risk assessments in densely populated areas. In this framework, the sector of the Voltri Massif (NW Italian Alps) forming the hinterland of the city of Genoa is a natural laboratory to investigate (i) the interaction between rock faulting and fluid circulation during (potential) paleo-seismic activity and (ii) the detection, location, and source characterization of micro-earthquakes along tectonic lineaments developed inland and offshore the city area (i.e., in the Ligurian Sea). Our multi-scale and multidisciplinary study is part of the PNRR research program RETURN (“Multi-risk science for resilient communities under a changing climate”): it will include the structural and petrographic characterization of fault rocks (i.e., serpentinite breccias), the quantification of serpentinite carbonatization and its impact on the fault strength, and the analysis of the network of inland-offshore tectonic lineaments. This work, coupled with the analysis of historical seismic clusters, is crucial to identify suitable areas for the deployment of high-resolution seismometers and for tracing the spatial-temporal evolution of micro-earthquakes and their static and dynamic source parameters.

The detailed structural mapping of selected fault zones has revealed a complex, multi-stage deformation history, with older ductile structures (paragenesis: antigorite + ilmenite ± chlorite ± pyrite ± chalcopyrite, likely ascribed to the alpine-subduction and collision stages) cut by steeply dipping fault planes NNE-SSW striking. These latter are subparallel with the (low magnitude) seismic clusters detected in the area and develop multiple, anastomosed fault cores consisting of serpentinite-rich ultracataclasites, locally bound by chrysotile-rich shear bands. The faults damage zones textures (e.g., breccias and microbreccias), the paragenesis of newly formed shear bands and associated veins (chrysotile + chlorite) and the orientation of these faults (NNE-SSW striking, subparallel to the Miocene-age lineaments detected in the Gulf of Genoa) suggest recent tectonic reactivation at the regional scale.

Future developments of the research project will include more detailed, high-magnification microscopy of selected samples (e.g., raman, field emission SEM, EBSD and microprobe), regional scale morphotectonic characterization by satellite image analysis, and integration of field and seismic data. This will clarify the link between inland-offshore tectonic lineaments and the (low magnitude) seismicity of the area.

How to cite: Locatelli, M., Crispini, L., Scambelluri, M., Federico, L., Spallarossa, D., Morelli, D., and Cianfarra, P.: Analysis of active and fossil seismic structures: a multidisciplinary study for the seismic risk assessment in low-seismicity regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16169, https://doi.org/10.5194/egusphere-egu24-16169, 2024.

EGU24-16516 | ECS | Orals | TS3.5

Characterisation of strike-slip fault offsets using convolutional neural networks 

Sarah Visage, Léa Pousse, Sophie Giffard-Roisin, Margaux Mouchené, Laurence Audin, and Sarah Perrinel

The understanding of seismic recurrence relies on the chronology and magnitude of earthquake ruptures that have occurred in the past along a given fault. Knowledge of the rupture history of a fault provides valuable insights into its potential future behavior, aiding in the assessment of seismic hazard. Geomorphic evidence of faults is thus crucial for constraining models of seismic recurrence through surface rupture. The advent of remote sensing and other high-resolution datasets (such as Pleiades and SPOT satellite images) has improved tectono-geomorphological studies, promising to improve earthquake recurrence models. While manual or semi-automatic measurements of fault offsets using topographic markers like rivers have been conducted (Manighetti et al., 2015, 2020; Zielke et al., 2012), recent advances in artificial intelligence (AI) open new avenues for geoscientific applications (Ren et al., 2020) to handle the amount of high-resolution datasets.

This study takes on the challenge of measuring slip offsets of faults using a Convolutional Neural Network (CNN) applied to synthetic Digital Elevation Models (DEM). The methodology involves generating realistic synthetic landscape models (DEM) using the Landlab software (Hobley et al., 2017), simulating slip faults based on the method of Reitman et al. (2019). The approach includes creating synthetic DEMs with Landlab, incorporating fault effects such as erosion, slip rates, and variable fault zone widths. Preliminary work in this study involves automating the creation of synthetic DEMs for a 2D prototype with a variable slip fault. A regression CNN model (with three convolutional layers followed by max-pooling layers and fully connected layers) is trained on these synthetic datasets, achieving slip offsets of ±3 meters on validation data. The model is then tested on real data labeled by experts, yielding satisfactory preliminary results.

This study demonstrates the potential of CNNs for measuring slip offsets of faults using synthetic DEMs. The successful application of AI to geosciences paves the way for more efficient and automated analysis of fault activity in landscapes, thereby contributing to an enhanced assessment of seismic risks.

How to cite: Visage, S., Pousse, L., Giffard-Roisin, S., Mouchené, M., Audin, L., and Perrinel, S.: Characterisation of strike-slip fault offsets using convolutional neural networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16516, https://doi.org/10.5194/egusphere-egu24-16516, 2024.

EGU24-18480 | ECS | Posters on site | TS3.5

Evaluating probabilities of earthquake fault jumps from 2D numerical simulation of seismic cycles 

Sylvain Michel, Oona Scotti, Sebastien Hok, Harsha Bhat, Navid khairdast, Michelle Almakari, and Jinhui Cheng

The efficiency of an earthquake to cross a barrier can be evaluated based on geometric and frictional properties of faults, and specific seismic parameters such as the stress drop during an earthquake. Numerical modelling of seismic cycles allows to generate thousands of seismic events and to explore the effect of the physical properties with respect to a barrier effectiveness criteria. The probability of an event passing a barrier can thus be evaluated on the basis of this barrier effectiveness criteria. Such approach has been used for frictional barriers and fault bends. In this study we focuses on earthquake fault jumps which has been observed on multiple occasions such as the latest 2024 M7.5 earthquake in Japan. We use the quasi-dynamic algorithm VEGA, which numerically simulates seismic cycles of 2D fault networks and is based on rate and state friction. The problem is simplified to two planar faults separated by a gap. Among other parameters, we explore the effect of the overlap, distance and angle between the two faults. The loading of a fault network can be done in multiple ways. We thus explore the impact on the dynamics of sequences of earthquakes either from a far-field stress loading or from imposing a back slip rate loading on each fault. We also look at the effect of adding creeping - velocity strengthening - sections at the borders of the faults. We finally compare our results with the statistics of jump probabilities from published observed seismic events. Our study allows for a rapid assessment of thousands of earthquake scenarios and is a promising approach to facilitate the integration of earthquake physics into seismic hazard.

How to cite: Michel, S., Scotti, O., Hok, S., Bhat, H., khairdast, N., Almakari, M., and Cheng, J.: Evaluating probabilities of earthquake fault jumps from 2D numerical simulation of seismic cycles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18480, https://doi.org/10.5194/egusphere-egu24-18480, 2024.

EGU24-18523 | ECS | Posters on site | TS3.5

Review of methods that implement active faults characterization for PSHA in Southern Spain. Preliminary results of the application of the FAMS method. 

Adriana Fatima Ornelas-Agrela, Carlos Gamboa-Canté, María Belén Benito, Alicia Rivas-Medina, and Ligia Quirós-Hernandez

Incorporating faults as independent seismic sources in Probabilistic Seismic Hazard Assessment (PSHA) significantly influences the ground motion values when compared to classical zoning methods (CZM). This practice holds particular relevance for populations situated top or near active faults. Some hybrid methods (HM) and fault-based methods, implemented in Spain, show that Peak Ground Acceleration (PGA) values increase in the vicinity of the fault traces. In some cases the hazard levels may double, consistent with the PGA observed in recent earthquakes (Rivas-Medina, A., 2018; Gómez-Novell O., 2020). Despite the existence of methods that combine zones and faults in seismic sources characterization, there is a lack of allocation of seismic potential between these two types of sources. Additionally, there is an increasing use of geological data since seismic catalogs alone are insufficient to fully characterize the seismic potential of faults. This limitation becomes particularly evident in slow deformation zones, such as southeastern Spain, where the recurrence period of faults exceeds the temporal coverage of the seismic catalog.

The present investigation addresses two key aspects: how to quantify the geological information of the faults and transfer it to recurrence models, and how to distribute the seismic potential of the region between faults and zone. This research contemplates two steps. In the first step, four methods were applied: 1) Moment rate-based method, 2) Slip rate-based method, both proposed by Bungum (2007); 3) the hybrid method developed by Rivas-Medina et al. (2018), which considers both zone-type and fault-type sources; and 4) SHERIFS, a fault system-based assessment proposed by Cartier et al. (2019). In the second step, Faults and Area Moment Sharing (FAMS) (Ornelas-Agrela et al., 2022*) is applied. This new method enables characterizing the faults based on their associated seismicity, improving the distribution of seismic potential between faults and zones. The five methods were applied to multiple seismogenic zones within southeastern Spain, recognized as one of the most seismically active areas in the country. An analysis was conducted, highlighting the sensitivity of the results of PSHA implementation. The preliminary results of the FAMS method application are presented.

* first presented by Ornelas-Agrela, A. et al. at the Iberfault2022 congress in Teruel, Spain.

How to cite: Ornelas-Agrela, A. F., Gamboa-Canté, C., Benito, M. B., Rivas-Medina, A., and Quirós-Hernandez, L.: Review of methods that implement active faults characterization for PSHA in Southern Spain. Preliminary results of the application of the FAMS method., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18523, https://doi.org/10.5194/egusphere-egu24-18523, 2024.

EGU24-18876 | ECS | Orals | TS3.5

A simple yet effective method to rank the performance of physics-based earthquake simulations 

Octavi Gómez-Novell, Francesco Visini, Bruno Pace, José Antonio Álvarez-Gómez, and Paula Herrero-Barbero

The use of physics-based earthquake simulators is increasingly common in earthquake forecasting for seismic hazard. Their popularity is related to their ability to overcome completeness limitations of real seismicity catalogues, while reproducing complex earthquake rupture behavior and interaction patterns through the modelling of the physical processes involved in earthquake nucleation and rupture propagation. One common challenge when designing earthquake simulations is the selection of the input parameters that will produce the most feasible models in terms resemblance to natural earthquake processes and relationships, e.g., the rate-and-state frictional parameters – a, b – and the initial normal stress. The frequent lack of empirical data on such parameters, often bases their selection on non-systematic testing and qualitative model performance analysis, thus potentially reducing the objectivity of the modelling. We present a new quantitative approach to evaluate and rank the performance of multiple earthquake simulation models based on a workflow that scores each synthetic catalog according to their combined fit to objective seismological benchmarks. These benchmarks rely on widely used empirical earthquake data: 1) scaling relationships, 2) shape of the magnitude-frequency distribution and 3) rates of surface ruptures from paleoseismology. The approach permits an objective and effective approximation to model performance evaluation, allowing to easily identify which models (and input parameter combinations) simulate better natural earthquake relations and behavior. The algorithm-based approach also facilitates the exhaustive analysis of many input parameter combinations and allows the identification of systematic correlations between parameters and model performance. We validate the approach with earthquake simulations on a theoretical planar fault and with published simulations at the Eastern Betics Shear Zone (EBSZ) in southeastern Spain. In both cases, the method successfully ranks the models with better resemblance to natural catalogues, while avoiding self-correlation of the benchmark scores, i.e., the best model is not the best in all benchmarks but the better balanced across them. In the case of the EBSZ, our ranking analysis replicates the qualitative and manual analyses previously published, which reinforces the usefulness of the approach. We also identify very clear correlations between the model performance and the rate-and-state a and b parameters. In particular, we observe that larger differences between a and b tend to better model performance. Conversely, the initial normal stress does not correlate with the performance. Overall, we estimate that the approach can ease researchers on earthquake simulation design and building, and on better understanding the impact of selected input parameters into the physics-based models. Moreover, the model ranking results can be employed to drive further analysis such as weighting of earthquake forecast models in seismic hazard logic trees.

How to cite: Gómez-Novell, O., Visini, F., Pace, B., Álvarez-Gómez, J. A., and Herrero-Barbero, P.: A simple yet effective method to rank the performance of physics-based earthquake simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18876, https://doi.org/10.5194/egusphere-egu24-18876, 2024.

EGU24-179 | Posters on site | TS3.2

The 1928 – 1937 Oaxaca Earthquake Sequence (Mexico) 

Francisco J Nunez-Cornu and Diana Nunez

Oaxaca is the most seismically active region in Mexico and one of the most studied using different methodologies. This seismic activity is due to the subduction of the Cocos Plate beneath the North American Plate, which is considered an anomalous subduction zone since it is a truncated continental margin. Seventy-four earthquakes (M> 7.0) have been identified in the last 510 years, which is an average of one earthquake every 6.8 years. The seismic sequence occurred between 1928 and 1937 is the key to understand the regional seismotectonics. The locations of these nine events (M>7.0) reported by different authors differ by more than 100 km for the same earthquake. We relocated the aftershocks of these earthquakes using the seismograms from TAC (Tacubaya) and VCM (Veracruz) stations available at the Seismological Seismic Network (Mexico) archive reading pre-phases S-P.  To calibrate these readings, we relocate the seismicity in the region between 1950 and 1982 with the JHD Method using 1978, 1982, 1965 and 1968 earthquakes as Master Events. We look from this catalog the earthquakes registered in TAC and VCM in the period 1950 - 1982 and whose seismograms were in the archive were selected. The S-P prephases in TAC and VCM were read with the same criteria used previously. With these data we fitting a time-distance curve for each station. These curves were used to obtain more reliable aftershock area for each of the coastal earthquakes occurred during the 1928 – 1937 sequence.

How to cite: Nunez-Cornu, F. J. and Nunez, D.: The 1928 – 1937 Oaxaca Earthquake Sequence (Mexico), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-179, https://doi.org/10.5194/egusphere-egu24-179, 2024.

EGU24-1460 | ECS | Posters on site | TS3.2

Seismogenic structures and stress state of the Puysegur Subduction Zone (Fiordland, New Zealand) from detailed earthquake observations. 

Cédric De Meyer, Calum J. Chamberlain, and Martha K. Savage

The formation of new subduction zones, termed Subduction Zone Initiation (SZI), has a large influence on global plate tectonics. However, how stresses within the plate boundary region evolve throughout the evolution of nascent subduction zones remains unresolved. The Puysegur Subduction Zone in Fiordland, near the southern tip of New Zealand’s South Island, is a young, steeply dipping subduction zone and a key site for studying such incipient stages of subduction. Despite the global significance of the Puysegur Subduction Zone, it has received relatively little attention, mostly due to its remote location. Few passive seismic studies have been carried out in the region, and the continuous GeoNet network is too sparse to detect and accurately resolve seismicity around the Puysegur Subduction Zone. Because of this, the present-day structure and stress state of the Puysegur Subduction Zone remain poorly resolved.

We aim to study these two unresolved characteristics by using a combination of temporary seismic networks and the permanent GeoNet network to increase station coverage in the region. We have developed a Puysegur-appropriate workflow consisting of automated earthquake detection and association, manual event evaluation and P-wave polarity determination. Highly accurate earthquake locations are obtained using NonLinLoc and a 3D velocity model. Focal mechanism analyses and stress inversion are conducted using Bayesian approaches. Currently, we have obtained a preliminary catalogue for the period between 02/2018 and 10/2018, which shows that the developed methodology is capable of producing more complete earthquake catalogues compared to the national GeoNet catalogue. Preliminary precise hypocentral locations and well- constrained focal mechanisms for moderate-to-large magnitude events are used to constrain the region’s seismogenic structures, such as the subduction interface and major active faults, as well as provide preliminary constraints on the region’s stress state.

How to cite: De Meyer, C., Chamberlain, C. J., and Savage, M. K.: Seismogenic structures and stress state of the Puysegur Subduction Zone (Fiordland, New Zealand) from detailed earthquake observations., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1460, https://doi.org/10.5194/egusphere-egu24-1460, 2024.

EGU24-1542 | ECS | Posters on site | TS3.2

Neotectonics in southern Ontario: Pop-up structures and their implications for seismic hazards in intraplate settings 

Abigail Clark, Alexander Peace, Carolyn Eyles, and Ethan Davies

Intraplate neotectonism is generally not well documented and understood despite its significance for seismic hazards in areas such as eastern Canada. This study aims to provide an in-depth structural analysis of potential neotectonic pop-up structures in southern Ontario, Canada, leading to a more comprehensive definition of pop-up structures, and ultimately constrain the processes involved and extent to which neotectonism impacts the region. Three locations in Southern Ontario were documented using a combination of ground and drone-based structural analysis: 1) Fletcher Creek Ecological Preserve, 2) Wainfleet Wetlands, and 3) multiple sites on Manitoulin Island. Sites were chosen where previous work had documented neotectonic activity, and/or where initial geomorphic analyses indicated the possibility of pop-up structures. The locations are all located within the Ordovician to the Devonian Niagara Escarpment stratigraphy. Fracture patterns at each site were analyzed using ground-based measurements or drone-based photogrammetry (DJI Phantom 4 V2 and Phantom 4 Pro acquisition followed by analysis in Pix4D), where applicable. Orthomosaics were then analyzed using FracPaq to determine fracture statistics including orientation, intensity, and density. Where access permitted, ground-based structural measurements were also obtained on structures such as fractures and folds, in addition to RTK-DGPS (real time kinematic differential-global positioning system) profiles over potential pop-up structures. The analysis revealed inconsistencies in the definition of a "pop-up", prompting further inquiry into the definition of a pop-up versus stress relief features more generally. To address this ambiguity, a classification system was developed to differentiate between pop-ups and other tectonic stress relief features. It was concluded that pop-up structures exhibit a distinct geomorphic expression, manifesting as a linear elevated ridge. In southern Ontario, regardless of whether a feature is identified as a stress relief feature or a pop-up, it nonetheless demonstrates that the region is tectonically active despite often being characterized as a stable continental interior. This study adds to a growing body of work documenting neotectonic activity in southern Ontario, with the several stress-related structures documented for the first time in this study showing their prevalence over a wide area.

How to cite: Clark, A., Peace, A., Eyles, C., and Davies, E.: Neotectonics in southern Ontario: Pop-up structures and their implications for seismic hazards in intraplate settings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1542, https://doi.org/10.5194/egusphere-egu24-1542, 2024.

The characteristic stress drop of an earthquake is indicative of its slip to fault dimension. Its value is affected by fault strength, fault topography, the presence of fluids, and other properties. By estimating stress drops throughout an entire subduction zone, namely for the seismically highly active northernmost part of Chile, and combining it with mapped b-values and their corresponding magnitude distribution, this work aims to better constrain the conditions under which earthquakes of different provenances may nucleate.
Database is a recent seismicity catalog, containing over 180,000 events and covering 15 years of seismicity, for which more than 50,000 stress drop estimates were computed. Their class wise spatial average segments the subduction zone into different parts. This difference, however, is small compared to the natural scatter of stress drop values. 
By considering stress drop variations, b-value map, magnitude distribution, and thermal modeling, I describe a variety of mechanisms of earthquake nucleation which might explain the observed stress drop variation. This is done for 1) the plate interface in general; 2) local shallow interface features, i.e., asperities and creeping sections; 3) the highly active intermediate depth seismicity region. In all three cases, the combination of stress drop distribution and b-value mapping helps to better understand the differences in earthquake nucleation and to formulate hypotheses on the controlling factors of earthquake nucleation.

How to cite: Folesky, J.: From stress drop mapping to earthquake nucleation conditions in the northern Chilean subduction zone, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1741, https://doi.org/10.5194/egusphere-egu24-1741, 2024.

EGU24-2612 | ECS | Posters on site | TS3.2

Probabilistic Assessment of Slip Rates Over Time of OffshoreBuried Thrusts: A Case Study in the Central Adriatic Sea(Italy) 

Ada De Matteo, Daniel Barrera, Francesco Maesano, Giovanni Toscani, Silvio Seno, and Roberto Basili

Understanding the recent tectonic activity and seismotectonics of inaccessible buried faults requires the development of feasible and robust approaches. The foredeep deposits of the northern and central Apennines (an offshore area in the central Adriatic Sea, Italy) blanket the active buried frontal thrusts of the Apennines and the Dinarides orogens. Detecting recent-to-ongoing tectonic activity of these thrusts is particularly challenging because sedimentation rates easily exceed the very slow tectonic rates.
In this work, we combine seismic reflection profile interpretation, sediment decompaction, kinematic restoration and balancing to quantitatively analyse the Plio-Pleistocene tectonic activity of the Apennines and Dinarides buried thrusts in the central Adriatic Sea and calculate the slip rates of the major faults. The northern and central Apennines foredeep is filled by a thick Messinian to Quaternary sedimentary wedge, unconformably resting on a Meso- Cenozoic carbonatic and siliciclastic passive margin succession, which is in turn involved in the east-northeast propagation of the fold-and-thrust belt from onshore to offshore (Adriatic Sea). As suggested by previous studies, the region is in a substantial tectonic activity decrease, but local and qualitative observations on specific structures show evidence of recent tectonic activity. The frontal thrusts of both the Apennines and the Dinarides are active, as also demonstrated by the moderate seismic activity historically (few past centuries) recorded in the region and by the recent earthquakes, followed by rather rich aftershock sequences that occurred in this region and nearby (e.g. the Porto San Giorgio earthquake Ml 5.0 in 1987; the Jabuka earthquake Mw 5.5 in 2003, the Pesaro earthquake Ml 5.7 in 2022). We interpreted, depth converted, and restored two northeast-trending regional seismic reflection profiles, thus roughly orthogonal to the main strike of the buried thrusts. We then used the inverse trishear approach to determine the slip necessary to recover the residual tectonic deformation (after decompaction) of four stratigraphic horizons with well-constrained age determinations (Zanclean to Middle Pleistocene). We then calculated and reported the slip rates using probability density functions, considering the uncertainties associated with both horizon ages and the restoration process. All together, our results show a progressive reduction of slip rates over time, with a main slowdown around 1.5 Ma. Reporting slip rates with probabilistic distributions is useful for incorporating epistemic uncertainty on the total seismic moment release in earthquake hazard analyses.

How to cite: De Matteo, A., Barrera, D., Maesano, F., Toscani, G., Seno, S., and Basili, R.: Probabilistic Assessment of Slip Rates Over Time of OffshoreBuried Thrusts: A Case Study in the Central Adriatic Sea(Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2612, https://doi.org/10.5194/egusphere-egu24-2612, 2024.

EGU24-3071 | Posters on site | TS3.2

Virtual outcrop models of geological structures: problems and best practices related to extraction of 3D structural data 

Amerigo Corradetti, Stefano Tavani, Marco Mercuri, Lorenzo Bonini, and Thomas Seers

The advancement of computer vision–based photogrammetric image processing pipelines, particularly Structure from Motion–Multi-View Stereophotogrammetry (SfM-MVS), has rapidly evolved. This evolution, coupled with the accessibility of low-cost and portable acquisition tools such as DSLR and mirrorless cameras, Uncrewed Aerial Vehicles (UAVs) and smartphones, has transformed outcrop studies in structural geology, propelling traditional field geology into the digital era. Notably, this revolution has significantly impacted Virtual Outcrop Models (VOMs), elevating them from mere visualization media to fully interrogable quantitative objects. 

Among the various applications of VOMs in structural geology, the extraction of near-planar features, including fracture and bedding surfaces, stands out as crucial. Numerous procedures exist for this purpose, ranging from fully automated segmentation and best-fitting of point clouds to the manual picking of 3D traces on both point clouds and textured meshes.

In this work, we explore the advantages, disadvantages, best practices, and drawbacks associated with the principal procedures for extracting near-planar geological data from VOMs. While automated or supervised recognition and subsequent best-fitting of coplanar patches in point clouds have garnered significant attention, their application is generally limited to specific case studies. Geological outcrops commonly lack patches of sufficiently large near planar surfaces for robust best fitting, necessitating manual picking procedures based on visual and/or structural interpretation. In such cases, the use of textured meshes is preferred over point clouds, and consideration must be given to the accuracy of the textured mesh during digitization, as well as the intrinsic roughness of geological surfaces. 

The analysis of coplanarity and collinearity of picked point sets aids in identifying traces deviating from idealized configurations. However, commonly suggested threshold values often result in small datasets. Nevertheless, relying on the visual inspection of the best-fit plane and real-time computation of best-fit planes from picked point sets generally yields acceptable results, handling coplanarity and collinearity dynamically during the extraction process.

How to cite: Corradetti, A., Tavani, S., Mercuri, M., Bonini, L., and Seers, T.: Virtual outcrop models of geological structures: problems and best practices related to extraction of 3D structural data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3071, https://doi.org/10.5194/egusphere-egu24-3071, 2024.

EGU24-3277 | ECS | Posters on site | TS3.2

Impact of outer-rise slab hydration on the intermediate-depth seismicity: Evidence from near field OBS observation in the southernmost Mariana subduction zone 

Han Chen, Gauhua Zhu, Hongfeng Yang, Shaoping Lu, Chuanxu Chen, and Jian Lin

Intermediate-depth earthquakes (IDEs), i.e., earthquakes at depths of 70 to 300 km, have been observed in subduction zones globally and extensively investigated. However, the seismogenic mechanism of IDEs is still controversial, especially in the southern end of the Mariana Trench, where near-field observations are lacking. By using machine-learning-based methods in three sets of near-field Ocean Bottom Seismogram (OBS) network data, we detected and located more than 1,000 intraplate and interplate earthquakes. The seismogenic volumes in different regions of the subducted plate are different, showing the character of double seismogenic zones (DSZ) and single seismicity layer (SSZ). The seismicity features coincide well with the regional landform, development of outer-rise faults, and hydration scenarios, suggesting a dehydration-related mechanism for the generation of IDEs. The subducted slabs experience different degrees of slab hydration, leading to various seismic behaviors.

How to cite: Chen, H., Zhu, G., Yang, H., Lu, S., Chen, C., and Lin, J.: Impact of outer-rise slab hydration on the intermediate-depth seismicity: Evidence from near field OBS observation in the southernmost Mariana subduction zone, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3277, https://doi.org/10.5194/egusphere-egu24-3277, 2024.

EGU24-4320 | ECS | Orals | TS3.2

Relationships between seismicity and geological structures at the hanging-wall of a low-angle normal fault (Alto-Tiberina fault system, Northern Apennines of Italy). 

Federica Riva, Simone Marzorati, Nicola Piana Agostinetti, Elham Safarzadeh, Diana Latorre, Lauro Chiaraluce, and Massimiliano Rinaldo Barchi

One of the most seismically active areas in Central Italy is located within the Pre-Apennine Umbria region, between the Tiber Valley, the town of Gubbio and the main mountain ridge of the Umbria-Marche Apennines. The fault system that characterizes this region is dominated by a 60 km long low-angle normal fault (Alto Tiberina, ATF), active since the Late Pliocene-Early Pleistocene. This area is mainly monitored and studied though the Alto Tiberina Near Fault Observatory (TABOO-NFO), a multidisciplinary monitoring infrastructure composed of dense arrays of seismic, geodetic, strain , geochemical and electromagnetic sensors deployed both at the surface and on boreholes. This infrastructure is fundamental to investigate the principal geophysical and geochemical processes occurring in this complex geological area (https://www.ont.ingv.it/infrastrutture-di-ricerca/sismologia/taboo). Besides the high rate of micro-seismicity nucleating along the ATF (ML<3.0), there is also a considerable number of synthetic and antithetic faults (e.g., Gubbio Fault, GuF) located in the hanging-wall of the ATF that produced historical and most recent earthquakes of moderate magnitude (e.g., MW 5.1 1984 Gubbio earthquake).

Our study focuses on the most recent seismic sequences, occurred in this area between 2010 and 2023, that produced main shocks of magnitude > 3 (Mw= 3.6 - Pietralunga 2010, Mw= 3.6 - Città di Castello 2013, Mw = 3.9 - Gubbio 2021, Mw = 4.5 - Umbertide 2023).

These seismic events have been registered, located and published in the Database of the Central Eastern Italy by the INGV office in Ancona (https://doi.org/10.13127/resiico/eqs). From these data, all the considered sequences are characterised by dominant normal fault kinematics, coherent with the regional SW-NE active extension. Moreover, they occurred at relatively shallow depth (< 7 km), at the hanging-wall of the ATF, and their location cannot be directly referred to any extensional fault, mapped in the studied area. The aim of our work is to investigate the potential relationship between the cited 2010-2023 seismic sequences and the occurrence of still unknown causative minor faults, at the hanging-wall of ATF. To reach the goal, we propose a revised detailed interpretation of a set of 2D-seismic reflection profiles, calibrated by few deep boreholes, acquired in the 80s for hydrocarbon exploration purposes. Previous studies of these data have been focussed on the ATF and on its major antithetic splay, i.e. the SW-dipping Gubbio normal fault. In this study, we want to explore the presence of other, synthetic and/or antithetic splays, visible at the seismic scale and possibly connected with the 2010-2023 seismic sequences. In order to improve the comparison between the geological structure at depth and the seismicity distribution, we decided to relocate the 2010-2023 catalogue of seismicity for the study area, following two innovative strategies: a 3D velocity model created on purpose for the ATF area and a Markov chain Monte Carlo algorithm for events location.

By combining interpretation of active seismic data with innovative strategies of earthquake re-location, our study proposes as a pivotal experience for seismo-tectonic interpretation of low-magnitude seismic sequences.

How to cite: Riva, F., Marzorati, S., Piana Agostinetti, N., Safarzadeh, E., Latorre, D., Chiaraluce, L., and Barchi, M. R.: Relationships between seismicity and geological structures at the hanging-wall of a low-angle normal fault (Alto-Tiberina fault system, Northern Apennines of Italy)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4320, https://doi.org/10.5194/egusphere-egu24-4320, 2024.

EGU24-6030 | ECS | Orals | TS3.2

Geological and Seismotectonic Analysis of the area struck by the November 2022 Mw 5.5 Offshore Pesaro Earthquake (Northern Adriatic Sea Region, Italy).  

Elham Safarzadeh, Massimiliano Rinaldo Barchi, Assel Akimbekova, and Francesco Mirabella

On the 9th of November 2022, a Mw 5.5 earthquake occurred near the Northern Adriatic coast, between Ancona and Pesaro (Marche region, Italy), as part of a complex seismic sequence, including six M>4 events, with NW-SE striking thrust fault focal mechanisms. This study is aimed at reconstructing the subsurface geological setting of the area struck by the seismic sequence, focusing on the active thrusts responsible for the observed seismicity. We interpreted previously unpublished 2D seismic reflection profiles integrating with deep wells, covering approximately 1500 km2.

We analysed the stratigraphic and geophysical log data from eight deep wells. This analysis defined the local stratigraphy, comprising a Late Triassic-Paleogene multilayer of evaporites, carbonates and Tertiary marls, overlain by Pliocene-Quaternary syn-tectonic clastic sediments. Wells data were used to calibrate the strong reflections recognized along the 2D seismic profiles. These profiles include six cross-lines (i.e. SW-NE), connected by three strike-lines (i.e. NW-SE).

Five key-horizons were distinguished: Top Pleistocene unconformity, Base of Pliocene -Pleistocene unconformity, Top of Middle Pliocene, Top of Messinian, and Top of Oligocene. The Messinian's prominent reflection, specifically, played a pivotal role in interpreting and identifying these horizons. These stratigraphic markers are cut and displaced at depth by two major thrust-fault segments, affecting the Mesozoic-Cenozoic carbonate succession.  Along-strike geometry of these major, SW gently dipping thrusts has been identified across four seismic reflection profiles, along a distance of about 24 km. A set of more complex, shallower thrusts, affecting the Tertiary marls and the overlying, syn-tectonic clastic sediments, splays out from these major structures. Time to depth-converted structures were derived by establishing a proper velocity model based on both local and regional log data. The location and depth of the seismic events were plotted along the depth-converted seismic profiles, demonstrating a good correlation with the geometry and kinematics of the deep thrust-fault segments. The interpretation of the deformation observed in the overlying strata suggests a strong Pliocene-Pleistocene contractional phase, up to the end of the Early Pleistocene. In recent times, the increased sedimentation rate masks the continuing tectonic activity.

This study contributes to a deeper understanding of the location, geometry, and kinematics of potentially active buried faults, sheding light on the seismotectonic setting of the study area, leading to a better understanding of the geological structure of the active external thrust in the Northern Adriatic region. The study contributes not only to a better knowledge of the seismotectonic setting of the region, but also plays an important role in formulating effective strategies for seismic hazard assessment and regional seismic risk management.

How to cite: Safarzadeh, E., Barchi, M. R., Akimbekova, A., and Mirabella, F.: Geological and Seismotectonic Analysis of the area struck by the November 2022 Mw 5.5 Offshore Pesaro Earthquake (Northern Adriatic Sea Region, Italy). , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6030, https://doi.org/10.5194/egusphere-egu24-6030, 2024.

EGU24-7352 | Orals | TS3.2

Subduction thermal structure and megathrust earthquakes under the Mariana arc 

Yingfeng Ji, Rui Qu, and Weiling Zhu

Due to the steep subduction of a highly concave slab, researchers have characterized megathrusts under the Marianas as among the coldest and curviest plate coupling interfaces in various circum-Pacific subduction zones. Seismic tomography indicates that the heterogeneous underlying plate varies markedly in its subduction angle, velocity, and flexure along the strike and dip, while their effects on the thermal structure and intraslab earthquake occurrence remain enigmatic. By incorporating the 3-D MORVEL velocity and state-of-the-art slab geometry into thermomechanical modeling, we estimated the 3-D subduction thermal state and hydrothermal regime below the Marianas. We find that (1) the concave slab geometry and the complexity of the intraslab velocity variation in the Marianas are associated with a heterogeneous along-strike thermal regime and a cold mantle wedge beneath the central Marianas; (2) amphibolitization and eclogitization of subducted oceanic crust cause variations in fluid pressure and fluid release from the subduction interface, which may influence the distribution of interface seismicity in the Mariana system; (3) the concentration of active hydrothermal vents in the trench > 8 km deep is accompanied by a large temperature gradient and subsequent remarkable slab dehydration in the southern Marianas; and (4) slab dehydration (> 0.02 wt%/km) from 30 to 80 km indicates notable fluid release and potential fluid migration in subduction channels, which may correspond to the large water flux at depth beneath the Marianas.

How to cite: Ji, Y., Qu, R., and Zhu, W.: Subduction thermal structure and megathrust earthquakes under the Mariana arc, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7352, https://doi.org/10.5194/egusphere-egu24-7352, 2024.

EGU24-7886 | Posters on site | TS3.2

Predicting the fault beneath a newly-created earthquake-related landform: A case study of Leader Fault rupture during the 2016 Kaikōura Earthquake, New Zealand 

David Tanner, Christian Brandes, Andy Nicol, Jan Igel, Sumiko Tsukamoto, and Julia Rudmann

In outcrops, the hanging-wall and/or footwall structure around a fault are often exposed, while the underlying fault is poorly resolved. In these cases, it is desirable to estimate the location and shape of the fault at depth, especially if it belongs to an active fault system prone to large earthquakes. The Mw 7.8 Kaikōura earthquake occurred two minutes after midnight on 14th November 2016, causing at least 17 faults in the northeast South Island of New Zealand to rupture, including a number of faults that had not been previously mapped. One of these smaller new faults is the Leader Fault, which at the surface displaces Mesozoic interbedded greywacke and argillite. In outcrop, the fault rupture caused an over 3 m high, 20-30 m wide, and over 120 m long hanging-wall fold to appear at the surface.

In September 2022, we used a differential global navigation satellite system to map the topography of the fold. We collected a total of 1493 points over a map area of 4526 m², i.e. an average point density of ca. 1 point per 3 m². The data were meshed into a three-dimensional triangular surface, which was then sectioned into ten cross-sections, each 10 m apart and perpendicular to the fold axes. We present fault-prediction modelling of two of these sections. In the Movetm software (Petroleum Experts), we used two methods of fault prediction; constant heave and constant slip. Both methods require implicit information about the hanging-wall shape, the position of the fault at the surface and the “regional”, i.e. the position of the hanging wall before deformation. Before the modelling, all this information was known apriori; i.e. we mapped the shape of the ground surface, we knew the fault to outcrop at the break of slope at the front of the leading edge, and the regional is an extension of the undeformed footwall. Both modelling techniques require a seed, i.e., a small portion of fault at the surface with a certain angle of dip. We use a horizontal and a 60° dipping seed.

We can estimate the fault geometry down to a depth of 20-25 m. For both sections, we predict the fault is steep, greater than 60°. Using a flat seed gives a slightly listric fault geometry, but in any case, the fault is steep down to 20 m depth before flattening out slightly. Compared to a small (15 cm) outcrop of the fault plane (dipping 75° WNW) at the surface at the northern end of the outcrop, the best matches are given by modelling with constant slip. The steep fault geometry is governed by the basement rock that has steep bedding that also dips ca. 70° WNW.

How to cite: Tanner, D., Brandes, C., Nicol, A., Igel, J., Tsukamoto, S., and Rudmann, J.: Predicting the fault beneath a newly-created earthquake-related landform: A case study of Leader Fault rupture during the 2016 Kaikōura Earthquake, New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7886, https://doi.org/10.5194/egusphere-egu24-7886, 2024.

EGU24-9421 | ECS | Posters on site | TS3.2

Active deformation in Tunisia from GNSS measurements 

Hamza Kristou, Frédéric Masson, Néjib Bahrouni, Mustapha Meghraoui, and Patrice Ulrich

Tunisia lies at the centre of the East-West trending convergence zone between the Nubian and Eurasian plates, at the eastern end of the large tectonic structures of the Atlas and Tell mountains and to the west of the Pelagian block and Sicily. As a result, its complex tectonics along the plate boundary show N-S to NW-SE oblique convergence expressed by E-W- to WNW-ESE-trending right-lateral strike-slip faults associated with E-W- to NE-SW-trending thrust faults that affect the Neogene and Quaternary units of the Tell and Sahara Atlas of Tunisia.

Although this region is generally characterized by moderate seismicity, it is known for its historical and instrumental seismic activity that has resulted in human and materiel losses, such as in Utique 408 AD, Kairouan 859 AD, Tozer 1997 and recently in March 2018 an earthquake felt between Tunis and Bizerte and in April 2023 an earthquake felt in Metlaoui, both earthquakes registered (Mw 5).

A partnership between the National Office of Mines ONM-Tunisia and ITES-Strasbourg is being set up to develop spatial geodesy work using GNSS measurements to characterize and quantify the active deformation of Tunisia alongside previous tectonic and seismotectonic works.

A network of already existing 21 GNSS stations spread over the Tunisian territory is managed by OTC (Office of topography and cadaster) so in the framework of this project 6 days/year of records from 2012 to 2019 has been purchased.

To improve the resolution of the acquired data and fill the gaps between the OTC stations, a national network consisting of 24 mobile stations is set up and three campaigns of 3 days of records in 2019, 2021 and 2023 have already been carried out.

Between 2022 and 2023, five more permanent stations have been installed to provide a continuous flow of data.

Two target areas, Gafsa and Kairouan have been chosen to install regional networks consisting of 16 sites each around active faults. Three campaigns in 2021, 2022 and 2023 have been carried out and one more is planned in 2024 to detect the deformation in those areas.

All these data allowed the calculation of a precise velocity field of Tunisia based on GPS trends and the establishment of the strain rate distribution across continental Tunisia. These new data will be analyzed in the light of existing knowledge, in particular the recent seismotectonic and paleoseismological work carried out as part of our project.

How to cite: Kristou, H., Masson, F., Bahrouni, N., Meghraoui, M., and Ulrich, P.: Active deformation in Tunisia from GNSS measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9421, https://doi.org/10.5194/egusphere-egu24-9421, 2024.

The 2007 Mw8.4 southern Sumatra earthquake provides an opportunity to understand the rheological properties in the southern Sumatra, particularly in the Mentawai gap. In this study, we have derived the first 3-year GPS postseismic observations to study deformation processes based on a three-dimensional viscoelastic finite element model. In the model, a 2-km-thick shear zone attached to the fault is used to simulate the time-dependent and stress-driven afterslip. Model results indicate that a model with a heterogenous shear zone better fits the horizontal GPS observations than a model with a uniform shear zone. This heterogenous shear zone is divided into the southern shear zone and northern shear zone (Mentawai gap), which is separated by the southern edge of the Mentawai gap. The southern shear zone is further divided into an upper (depths of ≤ 20 km) and lower shear zone (depths of > 20 km). The viscosities in these three shear zones are determined to be 5 x 1017 Pa s, 1016 Pa s and 1018 Pa s, respectively. Model results indicate that a weakened mantle wedge is required to better explain the observed uplift in vicinities of the rupture area.

How to cite: Yang, S. and Yan, H.: Rheological structure beneath the southern Sumatra constrained from postseismic deformation of the 2007 Mw8.4 Sumatra earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11015, https://doi.org/10.5194/egusphere-egu24-11015, 2024.

EGU24-11125 | ECS | Orals | TS3.2

Seismological evidence for a multi-fault network at the Ecuadorian subduction interface 

Caroline Chalumeau, Hans Agurto-Detzel, Andreas Rietbrock, Michael Frietsch, Onno Oncken, Monica Segovia, and Audrey Galve

The simplified view of the subduction interface is that of a single plane along which seismic and aseismic deformation occurs. In reality, however, exhumed subduction zones and geophysical imaging have shown that the seismogenic plate interface is a deformed, 100m-1km thick tabular region. Within this region, we currently do not know if seismic slip is localized on a single fault or distributed over several active faults, and how this impacts seismogenesis and the timing of deformation. Here, we use high-resolution earthquake locations to shed light on these questions.

We focus on the aftershock sequence of the March 27th 2022, Mw 5.8 Esmeraldas earthquake which occurred at 19 km depth at the plate interface in Ecuador, and which was recorded by the dense temporary seismic network deployed during the HIPER2 marine campaign. We use machine learning to detect and pick over 1700 earthquakes (Mw 0-3), which we then locate using a double difference algorithm with cross-correlation times and a 3D velocity model. This allows us to obtain an exceptionally detailed image of the seismicity at the plate interface, which falls into a 200-400 m thick zone, comparable to plate interface thicknesses observed in exhumed subduction zones. Using a cross-correlation threshold of 0.75, we extract families of similar earthquakes, whose geometry we investigate using the 3-point method. These families generally occur on subparallel, sometimes superposed planes with a thickness of 0-40 m that is comparable to the thickness of individual fault zones observed within fossil subduction shear zones. These individual fault zones appear to form a network whose geometry impacts the aftershock expansion, itself controlled by afterslip rather than diffusive processes, thus demonstrating the importance of considering the 3D structure of the plate interface when modeling slip.

How to cite: Chalumeau, C., Agurto-Detzel, H., Rietbrock, A., Frietsch, M., Oncken, O., Segovia, M., and Galve, A.: Seismological evidence for a multi-fault network at the Ecuadorian subduction interface, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11125, https://doi.org/10.5194/egusphere-egu24-11125, 2024.

The Indo-Burma subduction zone (IBSZ) is an entirely subaerial plate boundary, where the Indian plate obliquely converges with the Burma microplate. Because the incoming plate includes the 16-20 km thick sediment of the Ganges-Brahmaputra Delta, the accretionary prism is over 250 km wide with numerous active splay thrust faults and strike slip faults. Accurately assessing the long- and short-term dynamics of this complex region is critical for determining its earthquake hazard.

However, due in part to insufficient geodetic observations in the region to constrain the 3D shape of the megathrust and upper plate deformation, the kinematics of this plate boundary zone remain controversial. Ongoing debates focus on how strain is partitioned between the megathrust and strike-slip and oblique faults, whether the subduction zone is locked, and whether the multiple anticlines of the accretionary prism foldbelt are locked or actively deforming aseismically.

In this study, we present the first large-scale Interferometric Synthetic Aperture Radar (InSAR) velocity field over the IBSZ. Considering the operational nature and radar characteristics of different satellites, we processed datasets of multiple satellites spanning from late 2014 to 2023, including Sentinel-1, ALOS-2, and the newly launched L-Band differential InSAR satellite of China, LuTan-1. This approach allows us to more accurately constrain deformation across such a heavily vegetated and topographically-varied region. We incorporated updated horizontal and vertical GNSS velocities from 60 sites obtained from 2003 to 2023 to derive a three-dimensional decomposed velocity field, and then we investigated faults activities by estimating interseismic strain rates across the IBSZ. Our preliminary results reveal how strain is distributed in the region, shedding light on seismic hazard across this densely populated area.

How to cite: Shen, L., Steckler, M., Lindsey, E., Oryan, B., and Chong, J. H.: Large-scale geodetic deformation measurements of the Indo-Burma Subduction Zone from multi-sensor InSAR and GNSS: implications for strain partitioning and earthquake hazard, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11641, https://doi.org/10.5194/egusphere-egu24-11641, 2024.

EGU24-12143 | ECS | Orals | TS3.2

Seismotectonics of the Southwestern Swiss Alps – Revisiting Faults, Earthquakes, and Crustal Stresses 

Sandro Truttmann, Tobias Diehl, Giovanni Luca Cardello, and Marco Herwegh

The Alps are a dynamic orogen, as evidenced by recent crustal uplift and seismic activity. Earthquakes are primarily occurring along the many pre-existing Neogene faults formed during the Alpine orogeny, making it challenging to predict which faults are being reactivated. Limited geophysical data, low strain rates, high erosion rates, and widespread faulting complicate the detection of active faults in low-strain regions. Currently there is a lack of knowledge about the abundance, architecture, and properties of active faults in the Alps, which is however critical for evaluating the regional seismic hazard.

This study adopts an interdisciplinary approach to identify and characterize active faults in the Rawil depression and surrounding areas north of the Rhône-Simplon fault system, located in the southwestern Swiss Alps. A comprehensive seismotectonic description of the region is achieved by combining information from recent high-precision earthquake catalogs derived from relative relocations covering about 40 years, new fault maps using remote sensing and field surveys, updated stress inversion from extended focal mechanism catalogs and paleostress inversion from fault slip data, as well as GNSS data. Results from 3D imaging of active faults at depth, based on the high-precision hypocenter catalogs, reveal that subvertical faults, striking E-W, host most of the present-day earthquakes in the region. This imaging also uncovers previously unknown NW-SE striking active faults potentially contributing to the overall strain distribution in this part of the Alps. Compared to principal stress orientations in the upper crust derived from focal mechanisms, faults striking in both E-W and NW-SE directions appear to be optimally oriented for reactivation in the current stress field. Recent crustal stresses, consistent with the results obtained from paleostress inversion indicating NE/SW-directed transtension, suggest a relatively constant stress regime over the last couple of million years. This implies similarities between exhumed and seismically active faults at depth. The agreement between fault geometries exhumed at the surface and reconstructions of active faults at depth, as determined by hypocenter-based 3D imaging of active faults, support these findings. In conclusion, our study demonstrates that such interdisciplinary studies provide valuable insights into the deformation processes in tectonically active regions, contributing to refined seismic hazard assessments.

How to cite: Truttmann, S., Diehl, T., Cardello, G. L., and Herwegh, M.: Seismotectonics of the Southwestern Swiss Alps – Revisiting Faults, Earthquakes, and Crustal Stresses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12143, https://doi.org/10.5194/egusphere-egu24-12143, 2024.

EGU24-12240 | ECS | Posters on site | TS3.2

Unveiling subduction-related seismicity: towards a new global database 

Silvia Brizzi, Arnauld Heuret, Claudia Piromallo, Fabio Corbi, Francesca Funiciello, and Serge Lallemand

Subduction zones host the world’s largest earthquakes. Recent studies suggest complex interactions between megathrust, upper plate and intraslab seismicity. Understanding the spatio-temporal relationships of seismicity within subduction zones is challenging, yet essential for accurate seismic hazard assessment. A prerequisite for conducting these analyses involves the availability of a reliable and readily updatable dataset that classifies subduction seismicity into the three categories above.

In this work, we compile a comprehensive global database of subduction-related earthquakes from 1976 to 2023, using the ISC-GEM catalog (Storchak et al., 2013; 2015; Di Giacomo et al., 2018) for events with magnitude Mw ≥ 5.5. Building on Heuret et al. (2011), we define 505 trench-normal transects across all active subduction zones, spaced at 1-degree intervals along the trench, partially overlapping and extending 120 km on both sides of a vertical plane. The seismicity in each transect is initially categorized into shallow (≤ 70 km) and deep (> 70 km) events. We then focus on the megathrust region, identifying earthquakes exhibiting a thrust focal mechanism with the  azimuth and dip of the focal planes aligning with the strike and dip of the megathrust along the transect. Subsequent steps involve categorizing the remaining earthquakes in the transect as either upper or subducting plate events. The classification uses the Slab 2.0 model (Hayes et al. 2018) when available, determining whether each earthquake occurs above or below the slab top surface.  In regions lacking Slab 2.0 data, geometric criteria are applied, considering the distance of the hypocenter to the trench. For each transect, this workflow yields three distinct seismicity classes: megathrust, upper plate, and intraslab earthquakes. Subsequently, seismicity from individual transects is merged into 62 broader segments (Heuret et al., 2011), ensuring the uniqueness of earthquakes in each segment.

This automated workflow ensures the application of objective classification criteria and facilitates efficient analyses with each update of the ISC-GEM catalog. We compare key seismic parameters (e.g., maximum magnitude, number of events, cumulated seismic moment, recurrence time) across the different categories and segments. Additionally, we evaluate the correlation with a wide range of geological, geophysical, and geodynamical factors. This process not only provides an overview of the global behavior of subduction-related seismicity but also allows for the statistical identification of the combination of factors influencing subduction seismicity.



How to cite: Brizzi, S., Heuret, A., Piromallo, C., Corbi, F., Funiciello, F., and Lallemand, S.: Unveiling subduction-related seismicity: towards a new global database, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12240, https://doi.org/10.5194/egusphere-egu24-12240, 2024.

EGU24-13263 | Posters on site | TS3.2

Fault pattern and kinematics at the Tyrrhenian-Ionian transition zone (northern Messina Strait) 

Alessia Conti, Marco Cuffaro, Eleonora Ficini, Patrizio Petricca, Andrea Billi, Alessandro Bosman, Valentina Ferrante, Filippo Muccini, Valentina Romano, Marco Ligi, Carlo Doglioni, and Sabina Bigi

The Messina Strait and surrounding areas are one of the most interesting regions of the western Mediterranean Sea, characterized by the complex interplay between the Mesozoic-Paleogene Ionian basin, where the Calabrian Arc accretionary prism extends towards the southeast, and the Neogene Tyrrhenian back-arc basin to the northwest.

Complex fault networks with different kinematics, running from the inner side of the Calabrian arc through the Messina Strait and the Ionian coast of Sicily, as far as the Hyblean Plateau, result from the coexistence of different geodynamic settings in the area. Some of these faults are responsible for several of the largest earthquakes occurred in southern Italy and the Mediterranean Sea in recent times. Different works aimed at establishing a relationship between seismogenic sources and mapped faults, defining the location and rupture mechanism of some of these fault lineaments. Even tough, many uncertainties still exist for earthquakes occurred in offshore areas, where the fault kinematics and geometry are in some cases still poorly constrained.

In this work, we focus on a group of offshore faults located between the northern sector of the Messina Strait and the Gioia Basin (southern Tyrrhenian Sea). We aim at understanding the kinematics and the style of deformation in this area, and to investigate the role played by the main fault networks in the framework of the regional complex geodynamic setting of the Ionian-Tyrrhenian transition zone. This study is based on the interpretation of a multichannel seismic dataset (TIR10 survey), combined with the analysis of morpho-bathymetric and geodetic data, and with numerical modeling. This multidisciplinary and multiscale approach can contribute to unravel the particular role of this region in the context of a stepwise migrating subduction system and provides new constrains for the study of this highly populated area characterized by severe seismic and tsunamigenic hazard.

How to cite: Conti, A., Cuffaro, M., Ficini, E., Petricca, P., Billi, A., Bosman, A., Ferrante, V., Muccini, F., Romano, V., Ligi, M., Doglioni, C., and Bigi, S.: Fault pattern and kinematics at the Tyrrhenian-Ionian transition zone (northern Messina Strait), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13263, https://doi.org/10.5194/egusphere-egu24-13263, 2024.

EGU24-13305 | Posters on site | TS3.2

Retracing the Africa-Eurasia convergent boundary in the western Mediterranean based on seismic, geodetic and tectonic data 

Marco Cuffaro, Andrea Billi, Barbara Orecchio, Mimmo Palano, Debora Presti, and Cristina Totaro

In the western Mediterranean, the subduction of the Tethyan ocean has progressively come to an end, following the intervening continent-continent collision. Compressional deformation connected with the ongoing Africa (AF) – Eurasia (EU) convergence has therefore progressively resumed mostly along the southern passive margins of the Mediterranean back-arc basins. The use of geodetic, seismological, and pre-existing tectonic data recorded between the Gulf of Cadiz and the Ionian Sea helps to trace this nascent AF-EU boundary and constrain its kinematics. Based on these data, this plate boundary is detected, kinematically defined, and compared with the previously identified boundaries in the same region. The nascent boundary is articulated and formed by variably oriented inherited structures. It is characterized by a discrepancy between the general motion of Africa with respect to Eurasia and the local contractional/compressive axes deduced from geodetic and seismic data. The oblique convergence along the nascent boundary matches that recorded in other instances of subduction initiation elsewhere, but the average convergence rate equal to 5 mm/yr in the Mediterranean seems currently too small for such a subduction initiation. Based on the assumption of a future northward tectonic vergence (i.e., Eurasian foreland), the Tyrrhenian, Algerian, and Betic salients, the Oran and Fès recesses, and the Ionian, Trans-Alboran, and Gibraltar transfer zones are identified along the nascent boundary. The latter zones connect salients and recesses through strike-slip displacements. The Algerian offshore hosts a long segment of the boundary characterized by locally increased seismic rate and actual northward vergence that would suggest this area being the first nucleus of subduction initiation in the western Mediterranean.

How to cite: Cuffaro, M., Billi, A., Orecchio, B., Palano, M., Presti, D., and Totaro, C.: Retracing the Africa-Eurasia convergent boundary in the western Mediterranean based on seismic, geodetic and tectonic data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13305, https://doi.org/10.5194/egusphere-egu24-13305, 2024.

EGU24-13308 | ECS | Posters on site | TS3.2

Present-day crustal deformation of the Caucasus and Northern Iran constrained by InSAR time series   

Zaur Bayramov, Renier Viltres, Cecile Doubre, Alessia Maggi, Frederic Masson, Behzad Zamani, and Marie-Pierre Doin

The Caucasus and Northern Iran lie within the central part of the Alpine-Himalayan belt, where the Arabian and Eurasian plates started colliding over 100 My ago and caused the building of mountain chains associated with complex tectonics, including transform faulting systems. The region contains many tectonic features including the EW-trending Greater Caucasus and the NW-trending Lesser Caucasus thrust belt separated by the Kura basin. In the southern part of the region, the tectonics are complicated by the Anatolia-Eurasia-Arabia triple junction and the northern end of the Talysh and Alborz thrust belts. There have been several destructive earthquakes in the region, including the Shamakhi earthquake sequences in 1667(8) and 1902 at the junction of the controversial and mostly a-seismic West-Caspian Fault and the Eastern Greater Caucasus and the 1721 and 1780 earthquakes on the North Tabriz fault in NW Iran. 

Investigations of the few publicly available seismic catalogs of the region have been insufficient to understand the seismo-tectonic behavior of the regional structures due to sparse existing seismic networks. To better characterize the active structures in the Caucasus and  Northern Iran we produced  regional-scale mean line-of-sight velocity maps and time-series of the surface displacement from the north-eastern Caucasus to northern Iran. To obtain this dataset we performed Synthetic Aperture Radar interferometry using the NSBAS processing (Doin et al., 2011) of Sentinel-1 images along both ascending and descending tracks for 9-years (2015 to 2023). Main processing steps (such as atmospheric correction, multilooking and filtering) were applied to counter biases and loss of coherence due to the snow and vegetation coverage in the Greater Caucasus mountains. We produced two regional-scale interseismic velocity maps that highlight crustal motions of the large-scale tectonic structures. Moreover, we have identified coseismic deformation due to the 5.2 ml Shamakhi earthquake in the SE Caucasus mountains (Feb. 2019), the 5.9 Mw Torkamanchay earthquake in the Bozgush mountains of NW Iran (Nov. 2019), and possible aseismic strike-slip along the West Caspian fault after the large seismic events in Türkiye in February, 2023. Our results can also be used to study the local deformation of mud volcanoes in the Eastern part of Azerbaijan.

How to cite: Bayramov, Z., Viltres, R., Doubre, C., Maggi, A., Masson, F., Zamani, B., and Doin, M.-P.: Present-day crustal deformation of the Caucasus and Northern Iran constrained by InSAR time series  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13308, https://doi.org/10.5194/egusphere-egu24-13308, 2024.

EGU24-14378 | Posters on site | TS3.2

Shallow geological structure by applying H/V method in volcanic area in northern Taiwan 

Chia-Han Tseng, Po-Yu Chu, Cheng-Feng Wu, and Ruei-Juin Rau

The Taiwan Island is the product of the orogeny resulting from the collision of the two tectonic plates, the Eurasia Continent Plate and the Philippine Sea Plate. The Philippine Sea Plate has subducted the Eurasia Continent Plate and formed Ryukyu Volcanic Arc in northern and northeastern Taiwan. The Datun Volcano Group (DVG) being located in northern Taiwan is the westernmost member of the Ryukyu Volcanic Arc and has the widest extent and largest eruption amount among the volcanic rock areas. About 1 Ma, compressional stress transformed into extensional stress in northern Taiwan, and magma from the depth erupted to form younger volcanoes (~20) in the same area. During this period, the Taipei Basin and the Jinshan Basin gradually formed as half grabens on a normal fault, namely the Shanjiao Fault.

The DVG and the Shanjiao Fault have been identified to be active for micro-earthquake activities and topographical features, respectively, revealed by dense and high-resolution surficial monitoring systems in the Datun Mountain area. However, owing to rugged landscape and dense vegetations, geological boreholes are few and shallow (10 to 20 meters) so that the underground geological structures in the Datun Mountain area are still unclear. In this study, microtremor cross the presumed fault trace of the Shanjiao Fault are recorded and analyzed by applying the horizontal-to-vertical (H/V) spectral ratio method, and the H/V spectrum is further decomposed into E-W and N-S components.

The H/V spectral ratio reveals different dominant frequency for different volcanic products. The results indicate that the stations on thin loose deposits (pyroclastic debris) underlying by lava flow (andesite) show the higher dominant frequency, and these stations are near crater, while the stations farther from the craters have lower dominant frequency with thick loose deposits. And these results are also consistent with the topography revealed by high-resolution digital terrain model of the Datun Mountain area.

Based on the results, the future work of this study will be describing spatial geometry of the Shanjiao Fault by distinguishing different dominant frequencies corresponding to the footwall and hanging wall.

How to cite: Tseng, C.-H., Chu, P.-Y., Wu, C.-F., and Rau, R.-J.: Shallow geological structure by applying H/V method in volcanic area in northern Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14378, https://doi.org/10.5194/egusphere-egu24-14378, 2024.

The seismicity in the back arc of the Mexican subduction zone is relatively low.  An exception to this is the seismic activity observed in the Isthmus of Tehuantepec, where shallow earthquakes take place mostly along the coast of the Gulf of Mexico.  The largest recorded earthquake occurred on 26 August 1959 (Mw 6.9).  Other moderate earthquakes are recorded also in the southeastern margin of the Gulf of Mexico with magnitudes ranging from 5.3 to 5.9.  Data from the VEOX experiment that registered seismic data continuously on a cross-section across the Isthmus of Tehuantepec were analyzed.  Shallow earthquakes were culled from the continuous records, eliminating events within the subducted slab.  A total of ~40 shallow earthquakes were identified.  The linear geometry of the VEOX array made it difficult to locate the earthquakes.  Thus, additional stations from the Seismological Service of Mexico were used in the analysis.  Hypocentral locations were improved using the double-difference hypocentral algorithm.  The focal mechanisms obtained show consistently reverse faulting, where the axes of maximum compression are oriented NE – SW, like the 1959 earthquake.  This indicates that the lithosphere is deformed by compressive stress oriented in the direction of relative plate motion.  The best-located earthquakes show focal depths ranging from 20 to 50 km.  The depth of the Moho in the Isthmus of Tehuantepec is well controlled by receiver function results.  Therefore, it is possible to identify where the earthquakes occur relative to the depth of the Moho.  Unlike most upper plate deformation in the back arc of the subduction zones, earthquakes in the Isthmus of Tehuantepec occur both in the crust and the upper mantle.    Rheological models suggest that shallow earthquakes occur mostly in the seismogenic part of the upper crust and the upper mantle.  Our observations clearly show that in this region earthquakes reflect lithospheric deformation involving the crust and the upper mantle.  We are currently exploring rheological models that may help explain earthquakes in both the crust and upper mantle. The focal mechanisms suggest that the deformation may be induced by the subduction of the aseismic Tehuantepec Ridge in the Mexican subduction zone.

How to cite: Suarez, G. and Aguilar, S.: Rheological Behaviour of  the Deformation of the Back Arc in the Isthmus of Tehuantepec in South-eastern Mexico, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14489, https://doi.org/10.5194/egusphere-egu24-14489, 2024.

EGU24-15223 | ECS | Posters on site | TS3.2

Local scale of ground deformation along faults in area and vicinity of one possible Einstein Telescope location 

Karolina Owczarz, Romy Schlögel, Anne Orban, and Hans-Balder Havenith

The Einstein Telescope area was a research site of a project called Ground Deformation from Meteorological, Seismic and Anthropogenic Changes Analyzed by Remote Sensing, Geomatic Experiments and Extended Reality (GERMANE), which aimed to analyze ground deformation hazards induced by meteorological changes and seismotectonic conditions in eastern Belgium, western Germany and the south-eastern Netherlands. Within the project we proposed and applied an approach based on various Synthetic Aperture Radar Interferometry (InSAR) processing methods to detect and measure ground motions in time series. We focused on the Persistent Scatterer Interferometry (PSI), Small Baseline Subset (SBAS)  and Parallel Small BAseline Subset (P-SBAS) methods. An important issue was that the current neotectonic activity in the target area was not well known, but through spatiotemporal analysis of ground deformation we investigated behavior along NW-SE trending normal faults, where karst also develops, as well as along Variscan  NE-SW trending thrust faults. Time series analyzes were performed along Gueule fault and Gulp fault, which cross the Einstein Telescope area in the Pays de Herve (Belgium) and Heerlerheide fault in the Roer Valley Graben (Germany). We calculated the relative double difference (RDD) of Line of Sight (LOS) displacements to estimate relative deformation of one point with respect to the other. Additionally, we detected regression lines with Bayesian information criterion (BIC) that enables to choose the model which represents better the set of data points corresponding to specific InSAR techniques in double difference. In results, annual velocity rates of the benchmarks extracted along the Gueule and Gulp faults were less than -2mm/yr – which are insignificant value. However, comparing the velocity values for the extracted benchmarks along the faults, it can be seen that the Gulp fault is characterized by slightly higher annual velocities than the Gueule fault. Our time series analyses results along the Heerlerheide fault indicated that its eastern face is uplifting with velocity rates of up to 8 mm/yr. The obtained InSAR results are very small and can be described as insignificant, therefore we cannot find increased seismic activity of the analysed faults, especially the Heerlerheide and Gueule ones, as old mining activity may be responsible for the observed deformation. In sum, the faults crossing the Einstein Telescope area do not show significant displacements, which confirms the initial hypothesis of their low seismotectonic activity. Therefore, we consider the possible Einstein Telescope location as being relatively stable.

How to cite: Owczarz, K., Schlögel, R., Orban, A., and Havenith, H.-B.: Local scale of ground deformation along faults in area and vicinity of one possible Einstein Telescope location, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15223, https://doi.org/10.5194/egusphere-egu24-15223, 2024.

EGU24-15633 | ECS | Orals | TS3.2

An integrated multi-proxy approach to characterize the southern part of the Al Idrissi strike-slip fault system, Alboran sea 

Léa Vidil, Elia d'Acremont, Sara Lafuerza, Laurent Emmanuel, Alain Rabaute, and Sylvie Leroy

In the Alboran Sea, oblique convergence between the African and Eurasian plates led to establishing the active Al Idrissi sinistral strike-slip fault system 1 Ma ago. Several moderate magnitude earthquakes (Mw > 6) have been recorded on different segments of this fault system.

The objective of this study is to analyse the dynamics of this nascent plate boundary by studying the seismic events recorded in sedimentary series. We focused on a key transtensive fault transect, namely the Bokkoya fault system, shifting the small Al Idrissi volcano. This fault has a lateral extent of 11km along strike. Sedimentation is strongly affected by the circulation of deep Mediterranean water masses resulting in contouritic deposits, and likely mass movement during seismic events.

We used a panel of geological, geophysical, geotechnical and geochemical tools acquired during the ALBACORE oceanographic campaign (R/V Pourquoi pas? 2021). This work is part of the ANR ALBANEO project, which aims to understand the dynamics of this new plate boundary and to assess the hazards in this area of the western Mediterranean Sea. The data analysed are derived from (i) 4 sediment calypso cores (ALB_CL26, ALB_CL54, ALB_CL53 and ALB_CL52) from 10m to 16m (analysed with a multi-sensor core logger – MSCL and X-Ray Fluorescence-XRF), (ii) piezocone tests (CPTU) with the Ifremer Penfeld as well as (iii) multibeam bathymetry data and (iv) seismic reflection/sub-bottom profiles. This multi-proxy dataset provided detailed lithological and geophysical stratigraphy, calibrated with the picked seismic horizons, and sediment cores dating along a transect perpendicular to the Bokkoya fault system.

Isotopic analysis of 3 cores provided 𝛿18O evolution curves, identifying a thermal anomaly in each of them, and in particular in the one penetrating the fault plane. Oxygen isotopic curves were calibrated using 14C radiocarbon analysis, enabling sedimentary series to be dated up to 40 ka. Accordingly dated, representing the first 16 m of sediment cores: the cold stadials, with the Younger Dryas; the Heinrich Stadials 1 and the Last Glacial Maximum. The sedimentation rate is about 30 cm/kyr in the depression zone whereas on either side of the contourite drift, it is about 20-25 cm/kyr.

The recognition of seismic events in the past is attempted by comparing sedimentary successions in different fault compartments. The active Bokkoya fault appears to offset the sedimentary series with a normal component and a vertical throw of 1 m, evaluated between the seabed and the dated YD reflector.

The results from the different datasets allow us to identify (1) syn-tectonic deposits that may be associated with past co-seismic events (2) intense erosional events that may be associated with localized water masses currents (3) a thermal anomaly whose origin is to be determined. This dataset highlights the complex interaction between tectonics and sedimentation/erosion along this segment of the Bokkoya fault over at least 60 ka.

How to cite: Vidil, L., d'Acremont, E., Lafuerza, S., Emmanuel, L., Rabaute, A., and Leroy, S.: An integrated multi-proxy approach to characterize the southern part of the Al Idrissi strike-slip fault system, Alboran sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15633, https://doi.org/10.5194/egusphere-egu24-15633, 2024.

EGU24-16945 | Orals | TS3.2

Interactions between deep seismicity and shallow deformation in the Japan trench and Chile subduction zones  

anne socquet, Audrey Chouli, Blandine Gardonio, Jorge Jara, Sophie Giffard Roisin, David Marsan, and Michel Bouchon

Recent great subduction earthquakes have been preceded by an accelerated rate of both interface seismicity along the megathrust and intermediate depth seismicity within the slab at ~100km depth (e.g. Bouchon et al., 2016, 2018), sometimes along with seismicity lineaments along dip over some hours (Bouchon et al., 2022, 2023). These may also be associated with large-scale gravity and mass changes in the subduction zone (Panet el al. 2018). Such interactions between deep and interface seismicity can last several years and can be associated with deformation within the upper plate (Durand et al., 2014; Jara et al. 2018, Rousset et al. 2023, Mitsui et al. 2021).

However such interactions between deep seismicity and shallow deformation have been observed only on rare occasions. In addition, assessing better how they relate to fluid transfer and slab force balance is key to improved understanding of the driving mechanisms of the plate interface destabilization.

Here we present some intriguing examples of interactions between intraslab seismicity and shallow deformation, and assess their statistical significance. We show that the occurrence of the Tohoku earthquake significantly changed the deep (>150km) seismicity rate, suggesting that this major megathrust event modified the slab equilibrium down to the lower mantle.

We also revisit the interactions between intermediate-depth and shallow seismicity in the Japan trench and the northern Chile subduction zone, during the decade preceding the Tohoku-oki (Mw 9.0, 2011) and Iquique (Mw 8.2, 2014) megathrust events. Cross correlations highlight different periods with significant interactions between intermediate-depth and shallow earthquakes, including the 8 months before the Tohoku-Oki megathrust in Japan, over which multiple bursts of ~7 days are synchronized. In Chile, the 4 months preceding the Iquique megathrust also show strong interactions, with successive bursts of ~4 days. Unlike some other periods, no stress transfer implied by Mw>6 earthquakes can explain the correlations observed before both megathrust events. Clustering of the seismicity allowed to identify along-dip lineament patterns. Their occurrence rate shows a significant increase when approaching the date of the megathrusts. If only a few are observed in Chile, the numerous lineaments downdip Tohoku highlight some structures along which lineaments concentrate. These elongated seismicity features seem to connect intermediate-depth and shallow seismicity and could be explained by fluid migrations.

How to cite: socquet, A., Chouli, A., Gardonio, B., Jara, J., Giffard Roisin, S., Marsan, D., and Bouchon, M.: Interactions between deep seismicity and shallow deformation in the Japan trench and Chile subduction zones , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16945, https://doi.org/10.5194/egusphere-egu24-16945, 2024.

EGU24-17556 | Posters on site | TS3.2

The active frontal sector of the offshore Northern Apennine thrust belt: insights from an interdisciplinary approach following the 2022 Mw 5.5 Costa Marchigiana Pesarese earthquake (Italy) 

Lorenzo Petracchini, Andrea Billi, Eugenio Carminati, Claudio Chiarabba, Alessia Conti, Roberto Devoti, Mimmo Palano, Giuseppe Pezzo, Laura Scognamiglio, Stefano Tavani, and Elisa Tinti

Identifying seismogenic faults in offshore regions presents significant challenges, particularly in achieving their precise geometry and kinematics. Geological data derived from deep-sea exploration and geophysical surveys are commonly used to characterize offshore active faults together with earthquake hypocentral locations. However, limitations may arise in the quantity and quality of geophysical available data, inhibiting the realization of accurate 3D models. Furthermore, the precise relocation of seismic events is demanding, especially in the depth domain, due to the limited azimuthal coverage and the minimum station-event distance that is well beyond the mean depth of the events. In this context, an interdisciplinary approach becomes imperative to mitigate over-interpretation and over-simplification in defining the seismogenic sources and establishing an all-encompassing rupture model.

By means of an interdisciplinary (geological, seismological, and geodetic) approach, we investigate the outermost Northern Apennines fold-and-thrust belt front in the Adriatic Sea (Italy) involved in the Costa Marchigiana Pesarese seismic sequence started with the 9 November 2022 Mw 5.5 mainshock. Given the proximity of the mainshock and the subsequent seismic sequence to the urbanized coastline, where several cities are situated, characterizing the activated faults and the related estimation of ground displacement becomes crucial for seismic risk assessment and the tsunamigenic potential.

We analysed the geological setting of the area by means of an accurate interpretation of numerous seismic reflection profiles and well data acquired over the past decades, which complemented the publicly available seismic data. The interpretation of this dataset, provided by oil companies, led to an accurate definition of the thrust systems highlighting both the geometry of the activated sector of the thrust front and its relation to potentially active adjacent faults. Moreover, the results show the strong influence of past paleogeography and paleomorphology on the evolution and geometry of this sector of the fold-and-thrust belt, including the buttressing effect of carbonate platforms and inherited highs.

The resulting 3D model was integrated with seismological data and geodetic observations allowing us to well highlight the activated portion of the fault plane: strong motion data and continuous GNSS stations hosted by onshore (storage centers) and offshore (seabed-anchored hydrocarbon platforms) infrastructures were jointly inverted to retrieve the Mw 5.5 coseismic rupture history.

How to cite: Petracchini, L., Billi, A., Carminati, E., Chiarabba, C., Conti, A., Devoti, R., Palano, M., Pezzo, G., Scognamiglio, L., Tavani, S., and Tinti, E.: The active frontal sector of the offshore Northern Apennine thrust belt: insights from an interdisciplinary approach following the 2022 Mw 5.5 Costa Marchigiana Pesarese earthquake (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17556, https://doi.org/10.5194/egusphere-egu24-17556, 2024.

EGU24-17839 | ECS | Orals | TS3.2

Insights into fault behaviour and seismic hazard from studying active and inactive faults over a range of timescales 

Zoe Mildon, Billy Andrews, Constanza Rodriguez Piceda, and Manuel Diercks

Tectonics and active faults are studied using a broad range of techniques and observations, and each of these datasets have both strengths and limitations. Ideally, a multidisciplinary approach should be used when studying active faults, to mitigate against gaps in data and knowledge, and to span the spatial scales of deformation. Furthermore different approaches can provide insights into how faults and fault networks behave over a wide range of timescales, from annual behaviour (e.g. geodesy, seismology) to millennia (e.g. paleoseismology) and millions of years (e.g. seismic reflection). By using a range of techniques to study fault behaviour over a range of timescales, we gain insights into how faults behave and interact, which ultimately can improve our understanding of the resultant seismic hazard.

For seismic hazard studies, it is important to quantify fault geometry, dimensions and connectivity as these factors influence the magnitude and propagation of earthquakes. However these are typically difficult to constrain from onshore continental faults where  sub-surface information is often limited. Another important aspect to consider for seismic hazard studies is the slip rate of faults, but an aspect that is rarely considered is how slip rates vary spatially and temporally. Using seismic reflection datasets of inactive normal faults, we can study how slip rates vary over far longer timescales than can be considered from field studies alone. While it is challenging to study onshore faults using the same approach, what our findings indicate is that slip rates can vary by more than an order of magnitude over the lifetime of a single fault. Additionally, faults are almost never a single isolated structure, and instead form fault networks, with variable spacing, orientation and lengths. Understanding how a fault network behaves and interacts over time is also important to gain insights into seismic hazard.

Ultimately to gain a comprehensive understanding of fault behaviour in time and space, a range of complementary studies, including observations and modelling, are needed to span the broad range spatial and temporal scales that need to be considered when assessing active faults.

 

How to cite: Mildon, Z., Andrews, B., Rodriguez Piceda, C., and Diercks, M.: Insights into fault behaviour and seismic hazard from studying active and inactive faults over a range of timescales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17839, https://doi.org/10.5194/egusphere-egu24-17839, 2024.

EGU24-19217 | Posters on site | TS3.2

The potential of high density seismic arrays to elucidate distributed deformation in the Dinarides and Hellenides 

Frederik Tilmann, Andreas Rietbrock, Bernd Schurr, Ben Heit, Michael Frietsch, Hans Agurto-Detzel, Ya-Jian Gao, Sofia-Katerina Kufner, Edmond Dushi, Besian Rama, Damiano Koxhaj, Dinko Sindija, Gesa Petersen, Efthimios Sokos, Claudio Faccenna, Thomas Meier, and Petr Kolinský

The eastern Adriatic margin with the Dinarides and Hellenides orogens is one of the most hazardous areas in Europe from an earthquake hazard perspective in spite of only moderate shortening rates (e.g. less than 0.5 cm/yr across the Dinarides), as exemplified by the recent highly damaging earthquakes in Durrës, Albania (2019, M6.4) and Petrinja, Croatia (2020, M6.4). Deformation is both fairly localised on shallowly NE dipping thrust faults near the coast, and distributed, with a transition to spatially extended extensional deformation in the southern Dinarides and Northern Hellenides. and a complex regime involving strike-slip and obblique mechanisms in the eastern part of the Northern Dinarides. Making sense of this distributed deformation requires highly accurate locations both horizontally and in depth, which can only be achieved with dense seismic observations.

This region is thus being explored with multi-scale dense seismic deployments. On one hand, the multi-national AdriaArray initiative has combined temporary and permanent broadband stations to achieve a nearly-uniform coverage with typical inter-station distances of 30-40 km. In Albania, where the transition of the Dinarides to the Hellenides is occurring, this regional coverage is complemented by a ultra-dense deployment of nearly 400 stations (mostly geophones with a few broadband sensors) with a nominal spacing of 5 km, which was later rearranged into three orogen-perpendicular profiles, and one along-strike profile with 1 km station spacing. Such large numbers of stations require automated processing approaches leveraging recently developed machine learning-based techniques. The presentation will review the tectonic context for these surveys and share some preliminary results from these deployments as well as an earlier more localised deployment in the area of the Durrës earthquake.

How to cite: Tilmann, F., Rietbrock, A., Schurr, B., Heit, B., Frietsch, M., Agurto-Detzel, H., Gao, Y.-J., Kufner, S.-K., Dushi, E., Rama, B., Koxhaj, D., Sindija, D., Petersen, G., Sokos, E., Faccenna, C., Meier, T., and Kolinský, P.: The potential of high density seismic arrays to elucidate distributed deformation in the Dinarides and Hellenides, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19217, https://doi.org/10.5194/egusphere-egu24-19217, 2024.

EGU24-19684 | ECS | Orals | TS3.2

DInSAR coseismic surface deformation of the 2023 Mw 6.8 Al Haouz earthquake(High Atlas Mountains, Morocco) 

Riccardo Lanari, Martina Occhipinti, and Massimiliano Porreca

On 8th September 2023, the Al Haouz province in Morocco was struck by a strong earthquake of 6.8 Mw. The mainshock was generated by a reverse fault with an ENE-WSW orientation, as suggested by the derived focal mechanism.  

To obtain preliminary information of a seismic event, and to characterize the associated seismotectonic framework, in the last decades, the combination of field geology with satellite observations is becoming gradually more frequent. In particular, the DInSAR technique can be a powerful method of analysis to have an initial detailed information on the deformation field produced by the earthquake.  

In the present study, to understand the deformation field induced by the event and the structures involved, the DInSAR technique has been applied to obtain displacement maps in LOS, vertical, and horizontal (E-W) directions. On these maps, the geological meaning of both the vertical and horizontal displacement components is interpreted in the framework of the known tectonic structures of the Western High Atlas Belt. The inferred coseismic deformation along its vertical component shows a wide antiform characterized by an overall E-W trend and a slight southward vergence. On the other side, the horizontal (E-W) component of the deformation seems to be affected by the flexuring of the antiform flanks.  

Integrating the retrieved DInSAR maps with published geological observations and preliminary seismological data, it is possible to demonstrate how the coseismic deformation pattern may be affected not only by a possible activity of the main Tizi n’test fault but also by the far western High Atlas frontal thrust and by possible blind faults, better oriented to the vertical deformation field. 

How to cite: Lanari, R., Occhipinti, M., and Porreca, M.: DInSAR coseismic surface deformation of the 2023 Mw 6.8 Al Haouz earthquake(High Atlas Mountains, Morocco), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19684, https://doi.org/10.5194/egusphere-egu24-19684, 2024.

EGU24-19788 | Posters on site | TS3.2

Land-sea mapping and deformation kinematics in the Cape Gris-Nez fault zone (Dover Strait, Eastern Channel)  

Dibousse Aboubacar, Olivier Averbuch, and Virginie Gaullier

The Dover Strait, at the transition between the Eastern English Channel and the North Sea, lies on a complex faulted bedrock, making it a potential seismic risk area. Resulting from recent periglacial processes, it cross-cuts the geological structures inherited from the major tectonic deformations that affected the West European margin at the Late Jurassic-Early Cretaceous (extension and subsidence due to the propagation of the opening of the North Atlantic Ocean) and during the Cenozoic (compression causing the inversion of basins linked to the African-Eurasian convergence). Cape Gris-Nez is one of the most striking features of the fault system bordering the inverted Weald-Boulonnais basin. The Sirène beach, which has been heavily cleared of sand over the past 20 years, reveals the complexity of the folded and faulted geological structures associated with the development of this deformation zone. Over the last few years, detailed structural surveys have been carried out on land, using GNSS layer-to-layer mapping, and at sea, using very high-resolution SPARKER seismic profiles, providing an overall land-sea map of this fault zone. This first-rate mapping was recently supplemented by photogrammetric surveys by drone at very high spatial resolution (5 cm) making it possible to obtain an ortho-mosaic and a digital terrain model of the foreshore and cliffs of Cap Gris Nez. The interpretation of these very high-resolution images, adopted in a new structural survey campaign, leads to an optimization of the mapping of structures and a better understanding of the geometry and kinematics of deformations at the fault zone preliminary data for a better definition of seismic risk in the sector.

How to cite: Aboubacar, D., Averbuch, O., and Gaullier, V.: Land-sea mapping and deformation kinematics in the Cape Gris-Nez fault zone (Dover Strait, Eastern Channel) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19788, https://doi.org/10.5194/egusphere-egu24-19788, 2024.

EGU24-19891 | ECS | Orals | TS3.2

Insights the transpressioanl deformation patterns in the western zone of Sulaiman Fold-and-Thrust belt from spaceborne geodesy 

Muhammad Tahir Javed, Sylvain Barbot, Farhan Javed, and Carla Braitenberg

Continental convergence of Indian and Eurasian plates produces Himalayas in the north, while tectonically complex transpressional zones of the Sulaiman Fold and Thrust (SFT), and Kirthar Fold and Thrust (KFT) belts in the East. Seismic hazards in the zones are very high and less understood due to complex tectonic settings, and lack of GPS network. Here, we take advantage of spaceborne SAR interferometry and use the Sentinel-1, and ALOS-2 ScanSAR satellite observations to estimate the coseismic deformation caused by the 2021 Mw 6.0 Harnai earthquake in the western zone of the SFT belt. We find the line-of-sight (LOS) displacement of ~80 and ~70 mm from Sentinel-1 descending and ascending interferograms respectively. We find the ~50 mm of LOS displacement from ALOS-2 descending interferogram, but it is majorly biased by lower and upper atmospheric noises even after the GACOS and ionosphere corrections. In order to avoid the major noise components in inversions that may affect the accuracy, we discarded the ALOS-2 LOS displacement and relied only on the ascending and descending interferograms of Sentinel-1data. The deformation has an oblique component, but mostly dominated by thrusting on the NW-SE trending Harnai fault. First, we invert the LOS displacement using geodetic Bayesian Inversions approach, and find two plausible fault plane the NW-SE trending, and the NE-SW trending solutions. The simplified fault parameters have a strike of 327° ± 12, a dip of 31° ± 9, the length of 8.3 ± 2.1 km, and the width of 2.5 ± 2.0 km, which fits well the ISC and USGS fault models. Then, we determine the finite slip distributions on both plausible faults.  The NW-SE trending fault shows the maximum slip is found to be 70 cm at around 8 km depth. The slip distribution along the down dip and strike of the fault shows that 85% of the slip is concentrated in an area of (9 × 9) = 81 km2 at a down dip distance of 3 - 12 km. Furthermore, the results show the earthquake is propagated equally along strike and dip. For the NE-SW trending fault the maximum slip is similar but has higher residuals and scattered slip along depth. Therefeore, we preferred the NW-SE trending fault plane solution because based on the compatibility with fault structures in the region, and higher accuracy in the inversions. We also determine postseismic movement using time series analysis of spaceborne Sentinel-1 SAR data, but no significant afterslip and viscoelastic relaxation signals is found on the fault after the earthquake.

How to cite: Javed, M. T., Barbot, S., Javed, F., and Braitenberg, C.: Insights the transpressioanl deformation patterns in the western zone of Sulaiman Fold-and-Thrust belt from spaceborne geodesy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19891, https://doi.org/10.5194/egusphere-egu24-19891, 2024.

EGU24-20437 | ECS | Posters on site | TS3.2

Direct dating of active faults using luminescence: A case of study in New Zealand 

Andrés Melo, Sumiko Tsukamoto, Margret Fuchs, David Tanner, Christian Brandes, Uwe Kroner, Andrew Nicol, and Richard Gloaguen

The Alpine Fault in New Zealand is one of the world’s major active crustal-scale faults. It builds the boundary between the Pacific and the Australian plate, and branches into strike-slip faults known as the Marlborough fault system. The northeastern region of the southern island of New Zealand has a historical record of large, shallow earthquakes with magnitude (Mw > 6.5) since the Nineteenth Century. The most recent event, the 2016 Kaikōura earthquake, with a magnitude (Mw) of 7.8, is among the strongest. The severe impact on society and landscape explain the importance of a better understanding of the Quaternary activity of these active faults. Recent investigations in other tectonically-active settings worldwide indicate the potential feasibility of applying luminescence dating to unravel the timing and hence, re-occurrence of fault activity as a source for earthquakes.

We aim to test the potential of luminescence dating to determine the relative activity of three active faults in New Zealand. To this end, we collected four dark-gray, fine to very fine grain-size samples classified as cataclasite and gouge from outcrops situated along the fault traces of the Alpine Fault, Hope Fault, and Hundalee Fault. Through sample processing, we obtained polymineral fine grains, ranging from 4 to 11 µm, to conduct post-infrared infrared stimulated luminescence (pIRIR225) dating. The method applied on faults is the signal-resetting event of the fault movement, and if the signal is not saturated in nature, this implies that frictional heating was enough to at least partially reset the system; for feldspar the closure temperature is 40-90 °C.

The growth curves of the pIRIR225 signals reveal that the gouge samples extracted from the Hope fault and Hundalee fault approach saturation levels with equivalent doses around 850 Gy and 900 Gy, respectively. In contrast, the equivalent dose of cataclasite samples from the Alpine Fault was clearly below saturation ranging from 220 Gy to 410 Gy. All assessment criteria, including recycling ratio and recuperation rate, meet the rejection criteria for all samples, indicating a reliable signal to dose relationship. These results suggest there were events, which thermally eroded the pIRIR225 signal at the Alpine Fault. The comparison of the equivalent doses from the three faults also indicates that the method is applicable to evaluate the relative fault activity; the Alpine Fault is more active than the Hope and Hundelee faults. However, micro-structural analysis also indicated differences in brittle deformation mechanisms, differences that also potentially influence the variations between the pIRIR225 signals of individual samples. Observed features comprise, for example, grain fracturing, frictional sliding, pressure solution, and twinning. The micro-structural variation suggest differences in deformation, stress and pressure-temperature (P-T) conditions experienced by the studied cataclasite and gouge samples.

This study presents the first findings of pIRIR225 dating on feldspar in active faults in New Zealand and points at the success of luminescence dating. However, we strongly emphasize the importance of combining luminescence analysis with microstructural and mineralogical data obtained through Scanning Electron Microscope (SEM)-Mineral Liberation Analysis (MLA) to better understand the P-T conditions and resulting degree of luminescence signal reset.

How to cite: Melo, A., Tsukamoto, S., Fuchs, M., Tanner, D., Brandes, C., Kroner, U., Nicol, A., and Gloaguen, R.: Direct dating of active faults using luminescence: A case of study in New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20437, https://doi.org/10.5194/egusphere-egu24-20437, 2024.

EGU24-20926 | Posters on site | TS3.2

Similarities and differences between natural and simulated slow earthquakes 

Adriano Gualandi, Luca Dal Zilio, Davide Faranda, and Gianmarco Mengaldo

Earthquakes are understood as frictional instabilities taking place in weak zones of the Earth crust called faults. On the one hand, the lengthy recurrence time of earthquakes makes numerical simulations an invaluable tool to study consecutive ruptures of a given fault. On the other hand, it makes a direct comparison with nature difficult, if not currently impossible. Slow earthquakes, exhibiting lower recurrence times, serve as a viable alternative for validating models against real-world observations. We investigate similarities and differences between natural and simulated slow earthquakes using nonlinear dynamical system tools. We focus on slow earthquakes derived from Global Navigation Satellite System (GNSS) position time series in Cascadia and numerical simulations intended to reproduce their pulse-like nature and scaling laws. We provide metrics to evaluate the accuracy of simulations in mimicking slow earthquake dynamics, and we investigate the influence of spatio-temporal coarsening as well as observational noise. Findings indicate that numerical simulations exhibit average properties akin to natural occurrences. In addition, despite the usage of many degrees of freedom in numerical simulations, we retrieve a low average dimension, like the one obtained for Cascadia slow earthquakes, suggesting that a reduced order model may be a viable representation of slow slip events. Time-dependent, instantaneous properties show strong dependence on the variable considered for the analysis for numerical simulations, but not for natural observations. Our exploration show a possible way to extract dynamic attributes from kinematic information, and enriches the picture that we have of natural-scale friction We propose to use the suggested metrics as an additional tool to narrow the divergence between slow earthquake observations and dynamical simulations.

How to cite: Gualandi, A., Dal Zilio, L., Faranda, D., and Mengaldo, G.: Similarities and differences between natural and simulated slow earthquakes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20926, https://doi.org/10.5194/egusphere-egu24-20926, 2024.

EGU24-21021 | Posters on site | TS3.2

Geophysical constraints on intraplate deformation in southern Africa 

Alastair Sloan, Beth Kahle, Robert Muir, Diego Quiros, Khumo Leseane, Shaakirah Adams, Timothy Jones, Anele Matsebula, Anzani Ramagadane, Guy Salomon, and Benjamin Whitehead

The hazard posed by large intraplate earthquakes is relatively well-known in the Global
North, but Sub-Saharan Africa is poorly represented in compilations of such events, and the
hazard they may pose in this region is not well understood. Much of southern Africa is an
unusual example of an intraplate region undergoing predominantly extensional
deformation, complicating comparisons with otherwise similar regions. Here we present the
locations of moderate magnitude instrumentally-recorded seismicity, as well as eight major
paleoseismic fault scarps across South Africa, Namibia and Botswana. We focus on regions
generally considered to be stable, and compare these data to available aeromagnetic and
seismic tomographic datasets. Major events are primarily focussed on either the boundaries
of the cratonic cores in the region, or in the vicinity of large igneous complexes, suggesting
that variations in large-scale lithosphere rheology provide a first-order control on their
occurrence. Aeromagnetic lineaments, associated with Jurassic-Cretaceous normal faults or
ancient shear zones within mobile belts, are associated with almost all of the major
paleoseismic ruptures, and appear to control fault bends and terminations. Significant
differences in strike over relatively short length-scales suggest the orientation of the faults
are controlled by crustal anisotropy rather than variations in stress orientation. Some of the
scarps are likely to be associated with M7+ events, suggesting that such events can occur in
stable regions experiencing extensional stresses. The association with major crustal
structures likely explains their great length, relative geometric simplicity and unexpectedly
large magnitudes, despite limited recent brittle offset. While intraplate events are relatively
poorly studied in southern Africa the excellent preservation potential of landscape, and the
rarity of extensional events in other comparably stable regions, mean that this region has
excellent potential to increase our understanding of these phenomena.

How to cite: Sloan, A., Kahle, B., Muir, R., Quiros, D., Leseane, K., Adams, S., Jones, T., Matsebula, A., Ramagadane, A., Salomon, G., and Whitehead, B.: Geophysical constraints on intraplate deformation in southern Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21021, https://doi.org/10.5194/egusphere-egu24-21021, 2024.

EGU24-21217 | ECS | Posters on site | TS3.2

Faults segmentation in active external extensional front: insights from seismicity in the Sant'Anna Pelago area, North Apennines 

Simone Lenci, Derek Keir, Giancarlo Molli, Paola Vannucchi, Chiara del Ventisette, and Carolina Pagli

The Neogene-to-Recent tectonic evolution of the Northern Apennines has been characterized by contraction in the foreland, accompanied by extension in the internal domain. While the architectural and kinematic aspects of these two distinct sectors are better-known, uncertainties persist regarding the transition between them. Understanding the tectonics is made more complex since the width of the internal extensional domain increases south-eastward as the Northern Apennines steps eastward across Italy.

The Sant'Anna Pelago area, located on the Tuscan-Emilian ridge between Alpe di Succiso (NW) and Monte Cimone (SE), exhibits pronounced instrumental seismicity with over a thousand recorded events over the last ~15 years, forming the focus of this study. Sant'Anna Pelago represents a critical zone as the extensional front is situated near the outermost out-of-sequence contractional front affecting the Tuscan Nappe. The region locates close to the orographic divide, and also where the width of the internal extension starts widening significantly eastward. Seismicity in Sant’Anna is expressed through three major seismic sequences over a 10-year period from 2012 to 2022, with events concentrated in 2013, 2018, and 2022. P and S arrival times from 56 evenly distributed stations within 130 km radius from the publicly available INGV database were utilized to perform a preliminary relocation of seismic clusters using NonLinLoc and a local velocity model. Subsequent precise relocations were conducted using differential arrival times through HypoDD.

The relocation revealed three primary deep clusters and several minor aligned ones. The 2013 sequence is 8-km-long, 10-17 km deep, strikes parallel (NW) with the Apenninic trend, and dips 50 degrees towards the SW. This structure aligns prominently with the southern tip of the Zola master fault, surfacing near Pieve Pelago. Earthquakes are particularly dense at the southern tip of this structure. The subsequent clusters are in the footwall of the 2013 sequence, and at similar depths. These show several discrete, sub-vertical structures oriented E-W, each approximately 3 km long. These clusters geometrically resemble synthetic en-echelon faults situated in the footwall of the Zola fault. The western tips of these structures align along a potential envelope segment linking them to the 2013 cluster, a transverse SW-NE structure orthogonal to the Apenninic structure and the Zola Fault. We interpret the 2013 sequence as normal slip on a reactivated NW striking Apenninic contractional structure, and the subsequent en-echelon sequences on E-W faults as mostly normal slip in a dextral stepping zone of local re-orientation of stress. The interpretations will however, be tested with earthquake focal mechanisms and field structural geology. 

How to cite: Lenci, S., Keir, D., Molli, G., Vannucchi, P., del Ventisette, C., and Pagli, C.: Faults segmentation in active external extensional front: insights from seismicity in the Sant'Anna Pelago area, North Apennines, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21217, https://doi.org/10.5194/egusphere-egu24-21217, 2024.

EGU24-22522 | Orals | SM1.3

Foreshock sequence prior to the 2024 M7.6 Noto-Hanto earthquake, Japan 

Aitaro Kato and Takuya Nishimura

A destructive M7.6 earthquake occurred on January 1st, 2024, at shallow depths along the northern coast of Noto Peninsula on the back-arc side of Central Japan. The earthquake rupture started from an area where an intensive seismic swarm has lasted for more than 3 years (from December 2020). The seismic swarm consisted of numerous small planar faults dipping toward the southeast. In May 2023, an M6.5 event, that was the largest event before the M7.6 rupture, emanated from the swarm area toward shallow depths, resulting in the subsequent increase in the seismicity in the swarm area (Kato 2024 GRL). Then, the seismicity had gradually decayed to a level before the 2023 M6.5 event. Here we have explored the seismic and geodetic data to revel the nucleation process of the M7.6 event. Approximately two weeks before the M7.6 event, seismic activity exhibited a weak localization around the point of rupture initiation. After that, a foreshock sequence commenced roughly one hour before the occurrence of the M7.6 event, concentrated in proximity to the epicenter (within a 1-kilometer epicentral distance). The tightly clustered foreshock sequence consisted of around 20 events, including an M5.5 event 4 minutes prior and an M3 class event 1 second before the onset of M7.6 event. The M7.6 rupture nucleated from the deep side of one of planar clusters that were dominantly dipping toward the southeast direction. The growth process of the rupture in the M7.6 event is characterized by a complicated nature.

How to cite: Kato, A. and Nishimura, T.: Foreshock sequence prior to the 2024 M7.6 Noto-Hanto earthquake, Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22522, https://doi.org/10.5194/egusphere-egu24-22522, 2024.

EGU24-22523 | Orals | SM1.3 | Highlight

The Impact of the 2024 Noto Peninsula Earthquake Tsunami 

Shunichi Koshimura, Bruno Adriano, Ayumu Mizutani, Erick Mas, Yusaku Ohta, Shohei Nagata, Yuriko Takeda, Ruben Vescovo, Sesa Wiguna, Takashi Abe, and Takayuki Suzuki

The tsunami generated by the Mw7.6 earthquake of Noto Peninsula, Japan left widespread impact. We analyzed multi-modal information and data to elucidate its impact.

We modeled the tsunami propagation and inundation with multiple tsunami source models based on GNSS-based crustal movement and tsunami waveform data to understand its propagation and inundation characteristics. The model results are verified by using post-tsunami field survey data. Preliminary tsunami modeling results implied that severe tsunami impacts were around Noto Peninsula (Shika to Nanao). Through the visualization of tsunami propagation model, we found that the remarkable tsunami refraction around the continental shelf of Noto Peninsula were responsible for high tsunamis in Suzu City. This distinctive sea bottom topography also affected the directivity of tsunami energy toward the Japan sea coasts, especially Joetsu city, Nigata Prefecture. Tsunami in Toyama bay had long duration of oscillation caused by multiple-reflection. The leading (negative) tsunami wave could not be explained by fault rupture and this implied the possibility of submarine landslides.

The post-tsunami field survey teams at Suzu City preliminarily found tsunami run-ups of 3 m or higher with flow depths of 2.5m or higher. Inside the tsunami inundation zone around Noto Peninsula, we found at least 648 houses out of 3398 were destroyed by both the strong ground motion and tsunami.

The cellphone-based population data (Mobile Spatial Statistics) were used to analyze the exposed population in the aftermath of the event. The hourly population estimates with 500m spatial resolution in the coastal communities implied how people reacted and were affected. Approximately 2500 population increase were found in the areas above 10 m after the major tsunami warning was issued.

How to cite: Koshimura, S., Adriano, B., Mizutani, A., Mas, E., Ohta, Y., Nagata, S., Takeda, Y., Vescovo, R., Wiguna, S., Abe, T., and Suzuki, T.: The Impact of the 2024 Noto Peninsula Earthquake Tsunami, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22523, https://doi.org/10.5194/egusphere-egu24-22523, 2024.

This presentation will report preliminary results of multifaceted analyses for the geomorphological aspects of the Mw 7.5 earthquake struck northern tip of the Noto Peninsula, Japan, at 16:10JST on January 1, 2024. The earthquake caused significant uplift of the northern coastal areas of the peninsula, accompanying a tsunami observed widely in the surrounding coastline, along with extensive tectonic deformations observed inland. Spatial extent of the crustal movements accords generally with the relief structures and distribution of marine terraces in the Noto Peninsula, implying the long-term tectonic forcing on the landscape evolution in this region. Numerous coseismic landslides occurred in steep mountainous terrains, which yield vast volume of sediment from hillslopes into fluvial channels. Inventory mapping revealed the localized distribution of the landslides, regulated most probably by geologic and topographic conditions. Areal density of the landslides can be explained by coupled factors of lithological susceptibility of the hillslopes to the seismic shaking and amplification of ground motion at the hilltops.

How to cite: Matsushi, Y.: Geomorphological consequences of the 2024 Noto Peninsula Earthquake: tectonic deformations, coseismic landslides, and their implications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22535, https://doi.org/10.5194/egusphere-egu24-22535, 2024.

Since November 30, 2020, an intense earthquake swarm with over 22,000 M≥1 earthquakes and transient deformation have been continuously observed in the Noto Peninsula, central Japan, which is a non-volcanic/geothermal area far from major plate boundaries. During the earthquake sequence, Mw6.2 and Mw7.5 earthquakes occurred on May 5, 2023, and January 1, 2024, respectively. We report the transient and coseismic deformation related to the earthquake sequence by a combined analysis of multiple Global Navigation Satellite System (GNSS) observation networks, including one operated by a private sector company (SoftBank Corp.), relocated earthquake hypocenters, and tectonic settings. The start of the transient deformation coincides with a burst-type activity of small earthquakes in late 2020. A total displacement pattern in the first two years shows horizontal inflation and uplift of up to ~60 mm around the source of the earthquake swarm. The overall deformation rate gradually decreased with time except for the coseismic displacement of the Mw 6.2 earthquake and its postseismic displacement. On January 1, 2024, the coseismic horizontal and vertical displacements reached ~2 m at several GNSS sites. The pattern of the postseismic displacement for the first three weeks is similar to that of the coseismic displacement, though spatial decay of the postseismic displacement from the epicentral area is much gentler than that of the coseismic displacement. Viscoelastic relaxation of the mantle and/or lower crust is probably an important factor in explaining the observed deformation. In order to explain the transient deformation before the Mw6.2 and Mw7.5 earthquakes, we assumed a southeast-dipping fault plane based on the observed seismicity and regional tectonics and estimated the distribution of both reverse-slip and tensile components on the fault plane. In the first three months, a significant tensile component with a small slip component was estimated around a depth of ~15 km. The estimated volumetric increase is ~1.4 x 107 m3. Over the next 15 months, the observed deformation was well reproduced by shear-tensile sources, which represent an aseismic reverse-type slip and the opening of the southeast-dipping fault zone at a depth of 14–16 km. These slips and openings of the fault are estimated mainly at the down-dip extension of the intense earthquakes. We suggest that the upwelling fluid spread at a depth of ~16 km through an existing shallow-dipping permeable fault zone and then diffused into the fault zone, triggering a long-lasting sub-meter aseismic slip below the seismogenic depth. The aseismic slip further triggered intense earthquake swarms including the Mw6.2 and Mw7.5 earthquakes at the updip.

Acknowledgments: We are grateful to SoftBank Corp., ALES Corp., and GSI for providing us with GNSS data.

How to cite: Nishimura, T., Hiramatsu, Y., and Ohta, Y.: Deformation of the 2020-2024 Noto Peninsula earthquake sequence revealed by combined analysis of multiple GNSS observation networks in central Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22539, https://doi.org/10.5194/egusphere-egu24-22539, 2024.

EGU24-22540 | Orals | SM1.3

Ground motions and geotechnical aspects of the Noto Peninsula earthquake, Japan 

Hiroyuki Goto, Ayaka Nakatsuji, Dongliang Huang, and Silvana Montoya-Noguera

The Noto Peninsula earthquake (MJ7.6, MW7.5) caused extensive damage to buildings and infrastructure in the Noto Peninsula located in the northern part of Ishikawa prefecture, Japan. The hypocenter was within the area of the earthquake swarm that started in 2020. However, the source fault bilaterally ruptured over a length of 150 km beyond this area. The main residential areas in Wajima, Suzu, and Anamizu are located almost above the western segment of the reverse fault. The geographical features of the Noto Peninsula pose significant challenges for aid and support, particularly due to embankment and soil failures that caused main road closure or limited access. This has led to increased traffic on the few accessible routes, further delaying the arrival of support. The situation has hindered the restoration of essential services such as water and sewage systems and has slowed down the process of demolishing buildings deemed dangerous.

Valuable strong motions were observed during this event. The maximum Peak Ground Acceleration (PGA) in the horizontal component reaching 2.78g was recorded at the K-NET ISK006 station, a location known for significant site amplification around 0.2s. This value aligns with the dominant period in the Spectral Acceleration (Sa), thus the extreme PGA was probably due to the enhanced short-period component in the shallow soil amplification. In addition, K-NET ISK002 and ISK005 recorded large PGVs of 1.31 m/s and 1.59 m/s, respectively, and observed the remarkable Sa with 1.3g and 2.2g at T=1.0s, respectively, which are similar to the damage-prone record in the 1995 Kobe earthquake (JR Takatori record).

In the main residential areas of Anamizu and Wajima, two seismic stations are operated. One is located on the stiff soil ground, and the other is located in zones where residential damage was most severe. In both Anamizu and Wajima, the records at the damage site were amplified in the periods of 1-4 s, suggesting that the residential damage is related to the site amplification. Since the spectral ratio of the weak motions shows the amplification at periods of less than 1s, the major reason for the amplification at periods of 1 to 4 seconds during the main event is due to the nonlinear response of the soil ground.

How to cite: Goto, H., Nakatsuji, A., Huang, D., and Montoya-Noguera, S.: Ground motions and geotechnical aspects of the Noto Peninsula earthquake, Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22540, https://doi.org/10.5194/egusphere-egu24-22540, 2024.

EGU24-22541 | Orals | SM1.3

Extensive liquefaction and building damage on the Niigata Plain due to the 1 January 2024 Noto Peninsula Earthquake: Geomorphological and geological aspects and land-use in coastal and lowland areas 

Kyoko Kataoka, Atsushi Urabe, Ryoko Nishii, Takane Matsumoto, Hirofumi Niiya, Naoki Watanabe, Katsuhisa Kawashima, Shun Watabe, Yasuhiro Takashimizu, Norie Fujibayashi, and Yasuo Miyabuchi

The Niigata (Echigo) Plain facing the Sea of Japan is located downstream of two large rivers (the Shinano-gawa River and the Agano-gawa River), and has three sand dune ridges which formed along the coastal areas during the Holocene. Niigata city, with a population of ~770,000, lies in the lower catchment of the alluvial-coastal system. Despite the city being approximately 160 km away from the epicenter of the January 1st 2024 Mw 7.6 Noto Peninsula Earthquake, extensive damage to houses, buildings, and infrastructure occurred throughout Niigata city due to pervasive liquefaction (resulting from the earthquake) in the coastal and lowland areas.

Our field investigation focuses on the Nishi-ku (west ward) of the city, where much of the liquefaction-induced building damage (~ 700 houses at the time of submission of the abstract) is concentrated. Although our “ground truth” fieldwork is still ongoing, we have manually mapped the distribution of damaged houses/buildings, road deformation, sand boiling (sand volcanoes), cracks, slides, groundwater springs and other related phenomena onto map sheets, before then digitising these data using GIS.  The distribution of damage is concordant with geomorphology—such as the Holocene sand dunes (and associated landforms) and buried meander loop of the Shinano-gawa River—as well as with subsurface geology (e.g. the location of the water table). Some damage areas are coincident with artificially modified landforms.

Liquefaction conspicuously occurred on natural (i.e. not artificially modified) gentle slopes of the Holocene coastal sand dunes and interdune swale/lowland. In particular, ground was liquefied in the lower parts of the landward slope of the sand dune (formed ~1800­–900 years ago) which has a lateral extension of ~7 km at the elevation of ~0–3 m above sea level. Sandy subsurface geology and high groundwater level of the Holocene sand dune, together with the force of gravity on the slopes, were probable contributors to liquefaction.

Evidence for liquefaction —including damage to houses—was observed in modern residential areas developed above the buried meander loops of the Shinano-gawa River, which have been historically filled in artificially with sandy material. Damage was also noted in houses built upon an artificially buried pond. However, there was no liquefaction on the natural levee along the abandoned meander loops where relatively old settlements are present.

Similar liquefaction occurred in Niigata city on the sand dune slopes and associated lowlands at the time of the M 7.5 Niigata Earthquake in 1964; the epicenter was in the Sea of Japan, approximately 60 km from the city.  Despite the Noto Peninsula Earthquake occurring remotely from Niigata, the aftermath of the earthquake indicates that certain geomorphologic and geological factors, coupled with particular seismic conditions, can result in repeated liquefaction. 

The field observation is still ongoing after the earthquake. Therefore this abstract is based on tentative results and analysis of our investigation so far. Further information on liquefaction related to the geomorphology and subsurface geology in this area will be available by the time of the 2024 EGU General Assembly.

How to cite: Kataoka, K., Urabe, A., Nishii, R., Matsumoto, T., Niiya, H., Watanabe, N., Kawashima, K., Watabe, S., Takashimizu, Y., Fujibayashi, N., and Miyabuchi, Y.: Extensive liquefaction and building damage on the Niigata Plain due to the 1 January 2024 Noto Peninsula Earthquake: Geomorphological and geological aspects and land-use in coastal and lowland areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22541, https://doi.org/10.5194/egusphere-egu24-22541, 2024.

EGU24-22563 | ECS | Orals | SM1.3

The 2024 Mw 7.5 Noto Earthquake, shallow rupture with a stagnant initiation in a fluid-rich immature fault zone 

Haipeng Luo, Zhangfeng Ma, Hongyu Zeng, and Shengji Wei

Seismic hazard evaluation at critical infrastructures, such as nuclear power plant, urges deeper understanding on the fundamental physics that govern the initiation, propagation and termination of damaging earthquakes. The 2024 moment magnitude (Mw) 7.5 Noto Peninsula earthquake produced great hazards and exhibited complex rupture process. We derive high-resolution 3D surface deformation of the event using dense space geodetic observations, which reveal two major deformation zones separated by ~40 km along the coast of the Peninsula. Two large (>10m) shallow slip asperities with over 10 MPa stress drop on the thrust faults explain excellently the geodetic observations. A calibrated back-projection using teleseismic array high-frequency data shows that the rupture was stagnant around the hypocentre for ~20s before it propagated bilaterally at the speed of 3.4 km/s and 2.8 km/s towards southwest and northeast, respectively. The slow start of the rupture coincides with the seismic swarm surged since 2020 due to lower crust fluid supply, suggesting low normal stress (high pore fluid pressure) at the bottom edge of the seismogenic zone slowed down the initial rupture. The first major asperity of the rupture was accompanied with intense high frequency seismic radiation, and such radiation is even stronger from the largest asperity located at the southern edge of the Peninsula where the Peak-Ground-Acceleration (PGA) exceeding 2.6G at a site that is less than 40km away from the nuclear power plant. Large stress accumulation together with rough fault geometry and/or friction are likely responsible for the exceedingly large high-frequency radiation, which is mostly responsible for devasting damages.

How to cite: Luo, H., Ma, Z., Zeng, H., and Wei, S.: The 2024 Mw 7.5 Noto Earthquake, shallow rupture with a stagnant initiation in a fluid-rich immature fault zone, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22563, https://doi.org/10.5194/egusphere-egu24-22563, 2024.

NH5 – Sea & Ocean Hazards

EGU24-60 | Posters on site | NH5.1

Tsunamis induced by round-shaped seabed deformations 

Chi-Min Liu

In this study, tsunamis which are induced by round-shaped seabed deformations and then propagate outwards in an axisymmetric form are analytically analyzed. The derivation of such an asymmetric wave is firstly reviewed, and followed by an introduction of a novel mathematical approach which is applied to decompose the Bessel function appearing in the wave solution. This approach not only provides an easier way to perform the calculation, but also addresses some physical understanding of axisymmetric tsunamis. A simplest scenario is simulated by the derived solution to observe the characteristics in the propagation phase. The major finding addresses that the first wave is not always the biggest one.

References

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  • C. M. Liu, Math. Prob. Eng., 2021 (2021), 1113733.
  • M. Abramowitz, I. A. Stegun, Handbook of mathematical functions with formulas, graphs, and mathematical tables(1964).
  • F. Maass, P. Martin, J. Olivares, Comput Appl Math., 39 (2020), 222.

How to cite: Liu, C.-M.: Tsunamis induced by round-shaped seabed deformations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-60, https://doi.org/10.5194/egusphere-egu24-60, 2024.

EGU24-212 | Posters on site | NH5.1

Mediterranean extreme wave sediments preserved in karst solution pockets in cliff-top sites on the island of Malta 

James Terry, Piero Bellanova, Lisa Feist, Margret Mathes-Schmidt, Aaron Micallef, Derek Mottershead, and Klaus Reicherter

The Mediterranean Sea has experienced extreme waves (including large tsunamis) in the past.  However, the pattern of timing, frequency and magnitudes of these events, and the relative importance of possible storm and tsunamigenic mechanisms (undersea earthquakes, volcanic eruptions, major landslides) are not so well understood.  The Maltese archipelago is uniquely situated for extreme wave  research in the Mediterranean Sea, since this group of small islands is exposed to waves approaching from any direction.  Previous studies in Malta investigating sediment deposits from Holocene palaeotsunamis have tended to focus on the hydrodynamic characteristics of large coastal boulders.  This study adopts an alternative approach.  In the Aħrax area on the northernmost peninsula of Malta Island, we examined ‘karst pockets’ (solution hollows) that pockmark the exposed limestone terrain at elevations of up to 10-12 m asl.  Deposited in the pockets are shelly marine sands.  Lined by insoluble terra rossa soils, the pockets act as sediment traps during inundation by wave flow and are excellent repositories from which the accumulated marine sands cannot easily be removed.

This presentation describes the sampling methods, some challenges and results of subsequent laboratory analysis.  Findings show the moderately-sorted sands contain a rich microfossil assemblage of mostly benthic species, comprising foraminifera, gastropods, echinoidea, serpulidae and bryozoa.  Wave-abraded forms occur alongside well-preserved forms.  Sediment stratigraphy within the karst pockets suggests various depositional episodes, contrasted by differing grain sizes, microfossil contents, colours and erosional contacts, while the cliff-top elevations of 10-12 m require consideration of the potential of both storm waves and tsunamis and their respective capabilities with regard to the exposed coastal geomorphology.

How to cite: Terry, J., Bellanova, P., Feist, L., Mathes-Schmidt, M., Micallef, A., Mottershead, D., and Reicherter, K.: Mediterranean extreme wave sediments preserved in karst solution pockets in cliff-top sites on the island of Malta, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-212, https://doi.org/10.5194/egusphere-egu24-212, 2024.

EGU24-479 | ECS | Orals | NH5.1

Improving Rapid Earthquake Characterization of Tsunami Early Warning for Aotearoa New Zealand and the Southwest Pacific 

Luce Lacoua, Bill Fry, Andrew Gorman, Yi-Wun Mika Liao, Laetitia Foundotos, Chris Zweck, and Anthony Jamelot

Aotearoa New Zealand, located in the Southwest Pacific Ocean, is vulnerable to tsunamis. The Rapid Characterization of Earthquakes and Tsunami (RCET) project, led by GNS Science (Geological and Nuclear Sciences), aims to improve rapid analysis of large local and regional earthquakes to determine their tsunamigenic potential. Within this project, we are focusing on a simple but rapid and robust estimation of the location and magnitude of an earthquake by refining automated moment tensor inversions. A method to estimate these parameters is the W-phase inversion. Unlike simpler automated magnitude determinations routinely used to analyze earthquakes in New Zealand, the W-phase does not saturate with magnitude, making it better at quantifying Mw for the largest earthquakes. It also provides the centroid, rather than the hypocentre of an earthquake, allowing better estimation of the spatial distribution of shaking impacts. For these reasons we are developing synthetic earthquake waveforms to refine W-phase inversions for Mw ~5+ earthquakes in New Zealand and Mw 6.5+ earthquakes in the southwest Pacific, including the Hikurangi-Kermadec subduction zone. The current tsunami early warning procedure calculates W-phase solutions within 20 minutes of earthquake origins and aims to reduce it to 5-10 minutes. 

With a large set of high-magnitude events adapted to New Zealand and Hikurangi-Kermadec context, we will refine our understanding of the limits regional W- phase inversion. We are focusing on the minimum magnitude we can accurately estimate, the minimal station coverage required and the complexity of the source that can be apprehended by the W-phase.

To improve W-phase solutions for New Zealand, we simulate earthquake waveforms using a catalogue of synthetic ruptures on the Hikurangi-Kermadec subduction zone, produced by RSQSim (Rate and State Earthquake Simulator) under the RNC2 (Resilience to Nature’s Challenge 2) project. To generate the waveforms, we use SPECFEM3D Globe, a finite element method-based software that simulates wave propagation through a global velocity model of the Earth. The simulated waveforms are then postprocessed and inverted to obtain a W-phase solution. Preliminary results define which minimum waveform resolution is required to observe a W-phase and that a simple centroid moment tensor source provides an adequate W-phase solution. 

How to cite: Lacoua, L., Fry, B., Gorman, A., Liao, Y.-W. M., Foundotos, L., Zweck, C., and Jamelot, A.: Improving Rapid Earthquake Characterization of Tsunami Early Warning for Aotearoa New Zealand and the Southwest Pacific, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-479, https://doi.org/10.5194/egusphere-egu24-479, 2024.

EGU24-799 | ECS | Posters on site | NH5.1

Exploration of a Time-dependent Forecast for Tsunami in New Zealand 

Emeline Wavelet, Bill Fry, Andrew Gorman, and Sarah-Jayne McCurrach

New Zealand’s (NZ) entire coastline is at risk of tsunami from local, regional, and distant sources. With more than 75% of New Zealanders living or working within 10 km of the coast, the tsunami risk is significant.

The Rapid Characterization of Earthquakes and Tsunamis (RCET) research programme is being undertaken to better understand, mitigate and respond to tsunami events in NZ. Within this project, my PhD focuses on improving the communication of tsunami threats to local stakeholders and the emergency response sector by creating a new concept: a time-dependent forecast for tsunami.

I have been using the software ComMIT (a tsunami model developed by the NOAA Center for Tsunami Research) to create a catalogue of synthetic tsunamis focusing on the cities of Tauranga and Whangarei, situated on the northeast coast of the North Island. These two cities have been selected due to their exposure to tsunamis: flat topography, densely populated, infrastructure-rich harbour, exposed coastline, proximity to the Kermadec-Tonga trench. 

Using Python, I have generated a diverse assembly of forecasts where the tsunami waves amplitude  measured on the coastline are linked to threat levels, resulting in the creation of the final product: a time-dependent forecast. I have also been engaging with stakeholders and various end user communities with the aim of adapting these models to their needs. We anticipate that this new tool will help them to respond to these threats more efficiently.

How to cite: Wavelet, E., Fry, B., Gorman, A., and McCurrach, S.-J.: Exploration of a Time-dependent Forecast for Tsunami in New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-799, https://doi.org/10.5194/egusphere-egu24-799, 2024.

EGU24-1142 | ECS | Posters on site | NH5.1

ML Surrogate for Tsunami Forecasting and Hazard Assessment in Eastern Sicily 

Naveen Ragu Ramalingam, Erlend Briseid Storrøsten, Steven Gibbons, Kendra Johnson, Gareth Davies, Stefano Lorito, Alice Abbate, Manuela Volpe, Fabrizio  Romano, Finn Løvholt, Marco Pagani, and Mario Martina

Addressing the challenges associated with the high computational cost of tsunami inundation simulation has been a persistent issue, particularly in capturing earthquake source uncertainty and solving the nonlinear shallow water equations on high-resolution grids. This study aims to alleviate this computational burden by leveraging machine learning surrogates. Further, evaluating these ML models is often hindered by their black-box nature and the limited size of training and testing datasets, posing challenges for practitioners. We propose an encoder-decoder neural network where offshore tsunami waveforms and local co-seismic deformation fields serve as the basis for predicting high-resolution inundation maps at 10m grids. The model is applied to the coastal region of Catania in Sicily, Italy, integrating diverse earthquake scenarios from a large simulation dataset of 53,550 tsunamigenic events in the Mediterranean Sea. We adopt a pretraining-fine-tuning approach for building the machine learning surrogate and address crucial questions regarding the efficient selection of training scenarios, model design, and training. Leveraging this large simulation dataset, we identify specific locations, scenarios and model conditions where the machine-learning surrogate demonstrates sufficient accuracy and reliability. This provides an efficient mechanism for long-term tsunami hazard assessment or urgent tsunami prediction in real-time situations.

How to cite: Ragu Ramalingam, N., Briseid Storrøsten, E., Gibbons, S., Johnson, K., Davies, G., Lorito, S., Abbate, A., Volpe, M., Romano, F., Løvholt, F., Pagani, M., and Martina, M.: ML Surrogate for Tsunami Forecasting and Hazard Assessment in Eastern Sicily, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1142, https://doi.org/10.5194/egusphere-egu24-1142, 2024.

EGU24-3037 | ECS | Orals | NH5.1 | Highlight

Towards Tsunami Early-Warning with Distributed Acoustic Sensing (DAS) 

Carlos Becerril, Pedro Vidal-Moreno, Anthony Sladen, Jean-Paul Ampuero, and Miguel Gonzalez-Herraez

Although Tsunami Early Warning Systems (TEWS) are in operation, they are yet to become the norm, mainly due to the high cost of installation and operation of offshore instrumentation with sufficient spatial coverage and spatial density of instruments. Tsunami observations are made mostly by coastal tide gauges, fixed moorings located offshore such as DART, or cabled observatories such as S-NET or NEPTUNE. While S-NET is capable of near-field warnings, many systems rely on seismic data, an effective TEWS should rely on direct measurements of the wave to avoid errors in the extrapolation of seismic information, and allow detection of tsunami from other sources (volcanic eruptions and submarine landslides).

To maximize evacuation time for coastal communities, tsunami warning systems should be based on sensors deployed as close as possible to the offshore source areas such as subduction earthquakes. With the advent of seafloor Distributed Acoustic Sensing (DAS), such deployments are becoming feasible at a relatively low cost and can deliver upon other key requirements for early-warning systems: Delivering real-time data from a dense array of strain sensors. DAS is capable of converting the already existing seafloor telecom fiber links into a dense linear array of strain sensors over spans of up to 100 km. With such attributes, DAS is becoming a sensor package to consider in the design of future TEWS, as a cost-effective means of deploying instrumentation directly at offshore locations such as active plate margins and subduction zones where the most destructive tsunamis are generated. Providing several measurements per tsunami wavelength, in real-time would allow faster forecasting of a tsunami.

Despite the aforementioned attributes, there are some aspects of DAS that need to be addressed towards integrating these sensors into future early-warning systems: 1) DAS measures 1D horizontal strain when vertical pressure is the usual means to detect tsunami, and 2) DAS usually has lower performance at long periods typical of a tsunami (a few 100s). In this work, we investigate both aspects. For the former, we present an analysis based on a 3-D full physics simulation which couple the dynamic rupture to the tsunami wave generation and propagation; upon which we estimate the expected strain observable on a submarine cable due to two effects induced by the hydrostatic pressure perturbations arising from tsunami waves: the Poisson’s effect of the submarine cable and the compliance effect of the seafloor. We also consider the effect of seafloor shear stresses induced by the horizontal fluid flow arising from tsunami waves. For the latter point, we review the low-frequency limit of DAS and present recently reported improvements in low-frequency sensitivity of a DAS system using linearly chirped pulses (cp-DAS); attained by suppressing the 1/f noise from the instrument. Tsunamis are expected to be observable with high signal-to-noise ratio, within a few minutes of the source onset, on seafloor cables located above or near the source area.

How to cite: Becerril, C., Vidal-Moreno, P., Sladen, A., Ampuero, J.-P., and Gonzalez-Herraez, M.: Towards Tsunami Early-Warning with Distributed Acoustic Sensing (DAS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3037, https://doi.org/10.5194/egusphere-egu24-3037, 2024.

EGU24-3383 | ECS | Orals | NH5.1

Multilayer HySEA granular flow and tsunami model improves results over single layer models: sensitivity analysis, benchmarking against flume experiments, and implications for field scale models. 

Maxwell M. W. Silver, Alexis Marboeuf, Anne Mangeney, Anne Le Friant, Enrique D. Fernandez Nieto, Amaury Belieres-Frendo, Alexis Bougouin, Olivier Roche, Raphael Paris, and Annabelle Moatty

     Granular avalanches that enter a body of water present a hazard to coastal communities via their ability to generate tsunami waves. By improving the accuracy of model estimates of tsunami severity and quantifying the error of said models, we can improve the accuracy of tsunami hazard assessments. Sensitivity analyses were performed of the hybrid finite-difference finite-element model HySEA to changes in the number of vertical layers used to discretize the water column (from a single layer up to 5 layers), non-hydrostatic vs hydrostatic fluid pressures, different friction rheological laws (Pouliquen and μ(I)), and various friction coefficients. Flume experiments with matching conditions were used to benchmark simulations. An improved fit between simulation and experiment wave heights and wave frequencies, as well as improved model stability was found with 3 to 5 vertical water discretization layers compared to using a single water layer. We also demonstrate an improved fit between simulation and experiment wave heights, speeds, and form with non-hydrostatic versus hydrostatic conditions, although most simulations performed here did not accurately estimate wave speeds. Only minor changes in fit were observed between the Pouliquen and μ(I) friction laws. We demonstrate that multilayer HySEA can reliably estimate tsunami wave heights with a reasonable certainty (< 38% error) without any fitting across different granular mass volumes, grain sizes, and slopes of flow and can reach errors < 2% with only limited fitting. Furthermore, we detail how to improve model fit using additional rheological information (e.g., grain size, slope, volume of mass) and friction coefficients.

How to cite: Silver, M. M. W., Marboeuf, A., Mangeney, A., Le Friant, A., Fernandez Nieto, E. D., Belieres-Frendo, A., Bougouin, A., Roche, O., Paris, R., and Moatty, A.: Multilayer HySEA granular flow and tsunami model improves results over single layer models: sensitivity analysis, benchmarking against flume experiments, and implications for field scale models., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3383, https://doi.org/10.5194/egusphere-egu24-3383, 2024.

EGU24-4024 | Orals | NH5.1

Global Science of Meteorological Tsunamis: From Planetary to Mesoscale Processes (GLOMETS) 

Ivica Vilibić, Gozde Guney Dogan, Iva Dominović Novković, Xun Huan, Gabriel Jordà, Petra Pranić, Iva Tojčić, Joan Villalonga, Ahmet Cevdet Yalciner, and Petra Zemunik Selak

Meteorological tsunamis - atmospheric ocean waves in the tsunami frequency band - and generally nonseismic sea level oscillations on tsunami timescales attracted a lot of attention in the recent decade due to the global availability of high-resolution sea level and ancillary measurements and advancement of both atmospheric and ocean models. This became even accentuated after the century-level event of the Hunga Tonga-Hunga Ha’apai explosive volcano eruption on 15 January 2022, which created global acoustic-gravity waves in the atmosphere and meteotsunamis in the ocean. In that spirit, the Global Science of Meteorological Tsunamis (GLOMETS) 4-year project has been proposed for funding to the Croatian Science Foundation and launched on New Year’s Eve of 2023 to tackle the following research topics: (1) global meteotsunami hazards from explosive volcanic eruptions and asteroid impacts, (2) meteotsunami hazards at the sub-kilometre scale from both weather- and explosive volcano-induced events, (3) reproducibility of meteotsunami hazard by climate models, for their eventual assessment in the future climate, (4) eventual optimization and improvement of the meteotsunami monitoring, and (5) developing stochastic techniques for meteotsunami uncertainty quantification. To achieve these objectives, state-of-the-art tools will be used, like (1) global quality-checked high-frequency sea level analyses, (2) coupled atmosphere-ocean global and (sub-)kilometre models, (3) climate simulations, reanalyses, and products, and (4) uncertainty quantification techniques and optimal experimental design methods. This presentation will overview state-of-the-art in the quoted topics, with planned work-to-do and research activities, hopefully to initiate fruitful discussions and new research directions and to establish new collaborations around the project.

How to cite: Vilibić, I., Dogan, G. G., Dominović Novković, I., Huan, X., Jordà, G., Pranić, P., Tojčić, I., Villalonga, J., Yalciner, A. C., and Zemunik Selak, P.: Global Science of Meteorological Tsunamis: From Planetary to Mesoscale Processes (GLOMETS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4024, https://doi.org/10.5194/egusphere-egu24-4024, 2024.

EGU24-4192 | Posters on site | NH5.1

The 2012 and 2023 Mw 7.6 tsunamigenic earthquakes at the Philippine trench and tsunami hazard implications 

Mohammad Heidarzadeh, Aditya Riadi Gusman, Iyan E. Mulia, and Anawat Suppasri

On 2nd December 2023, the eastern coasts of Philippines were struck by an M7.6 earthquake followed by a moderate tsunami measuring 0.5 m in height. The earthquake was the result of thrust faulting in the Philippine Trench (subduction zone) at the depth of 32.8 km according to the United States Geological Survey. Philippine Trench is the result of tectonic convergence between the Philippine Sea and Sunda plates. The December 2023 earthquake resulted in three deaths; however, no death or casualty was reported due to the tsunami. This event reminds another M7.6 tsunamigenic earthquake on 31st August 2012 in the outer-rise region of the Philippine Trench that occurred approximately 300 km from the 2023 epicenter causing one death (https://doi.org/10.1007/s00024-014-0790-2).

From historical records, two prominent events in the region are an M 8.0 – 8.3 tsunamigenic earthquakes in 1918, and an M 7.9 earthquake in August 1976. The latter event generated a locally destructive tsunami that killed 5,000 people. It appears the largest recorded event in the region is the 1918 earthquake with a magnitude in the range of M 8.0 – 8.3. Considering the relatively short span of recorded earthquake history, the 1918 event cannot conclusively be regarded as the largest possible event from the Philippine Trench. Recent insights from global earthquakes in various subduction zones suggest that the occurrence of M9 earthquakes is feasible in any subduction zone, provided that the zone's length is sufficient to accommodate such events. Therefore, it is important to study the hazards from M9 earthquakes and potential tsunamis in the Philippine Trench and investigate the risks to infrastructure. 

The purpose of this research is to study the tsunamigenic potential of the Philippine Trench by modeling the 2012 and 2023 events and comparing them, modelling potential worst-case tsunamigenic earthquakes in the region and investigating their hazards and risks to infrastructure. The methodology used in this research are waveform analyses, spectral and wavelet analysis, numerical modelling, and fault tree analysis (FTA). We develop a cascading risk model based on FTA for critical infrastructure in the region.

How to cite: Heidarzadeh, M., Gusman, A. R., Mulia, I. E., and Suppasri, A.: The 2012 and 2023 Mw 7.6 tsunamigenic earthquakes at the Philippine trench and tsunami hazard implications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4192, https://doi.org/10.5194/egusphere-egu24-4192, 2024.

EGU24-4815 | ECS | Posters on site | NH5.1

Propagation Process of Long Ocean Wave from the Yellow Sea to the Korea Strait in Spring 2019 

Kyungman Kwon, Sung-Gwan Myoung, Byoung-Ju Choi, and Kwang-Young Jeong

Meteotsunami, which cause fluctuations on the sea surface, occur due to atmospheric pressure jumps and atmospheric gravity waves. This is a long ocean wave with almost the same spatio-temporal scale as regular tsunamis, causing significant damage to coastal areas. To understand the relationship between meteotsunami and climate change in Korea, research on the genesis and development processes of meteotsunami is necessary. This study examines the generation and propagation process of a meteotsunami that occurred in the Korea Strait on April 7, 2019, using observational data and numerical models. Coastal tidal observation stations detected a meteotsunami in the Korea Strait, characterized by oceanic long waves with heights ranging from 0.2 to 0.9 meters and a period of about 60 minutes. Atmospheric pressure jumps, starting in the Yellow Sea and moving into the Korea Strait, propagated in succession, observed to range from 2 to 4 jumps with magnitudes of 1.5 to 3.9 hPa. Analysis of meteorological data showed that the isobars of the atmospheric pressure jumps were oriented eastward in a counterclockwise direction at angles of 75 to 83 degrees, moving at speeds of 26.5 to 31.0 m/s. The Regional Ocean Model System (ROMS) was used to reproduce this meteotsunami's generation and propagation process. Numerical model results indicated that long ocean waves were amplified in the southwestern part of the Yellow Sea with depths greater than 75 m due to Proudman resonance. This long ocean wave refracts towards the coast in shallow areas north of the Korea Strait, with refraction and reflection by offshore islands influencing the wave heights at the coast. In particular, the high maximum amplitude of long ocean wave in Masan Bay is mainly due to refraction and reflection by nearby islands, increasing the amplitude by approximately 72.7%. Sensitivity experiments were conducted to examine the relationship between the height changes of long ocean wave on the coast and the speed and angle of the atmospheric pressure jumps moving from west to east across the Korea Strait. In the numerical model experiments, atmospheric pressure jumps moving at angles of 80 to 118 degrees and speeds of 27 to 30 m/s significantly increased the amplitude of the ocean long waves. Regionally, Seogwipo and Goheung showed increased amplitudes at speeds of 24 to 30 m/s and were relatively less affected by the angle. In Masan, the maximum amplitude of sea surface oscillation occurred when the atmospheric pressure jump moved at angles of 85 to 100 degrees at a speed of 30 m/s.

How to cite: Kwon, K., Myoung, S.-G., Choi, B.-J., and Jeong, K.-Y.: Propagation Process of Long Ocean Wave from the Yellow Sea to the Korea Strait in Spring 2019, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4815, https://doi.org/10.5194/egusphere-egu24-4815, 2024.

EGU24-4947 | ECS | Orals | NH5.1

Volcanic meteo-tsunamis in Southeast Asia: A first-time assessment 

Andrea Verolino, Masashi Watanabe, Raquel Felix, Christopher Conway, and Adam Switzer

Volcanic meteo-tsunamis are rare and potentially devastating natural phenomena. In physical terms, they are comparable to meteorological tsunamis, where a relatively high atmospheric pressure disturbance leads to the formation of tsunami-like waves. A significant recorded example of volcanic meteo-tsunami is the one produced by the Hunga Tonga – Hunga Ha’apai (HT-HH) eruption in January 2022. Volcanic meteo-tsunamis have the peculiarity to generate waves that propagate beyond landmasses, due to the interaction between the air pressure wave and water, such as those observed in the Gulf of Mexico following the HT-HH eruption; they also move much faster than tsunamis generated by other mechanisms. These features increase the hazard potential of a given volcano, and expose countries that are generally protected by landmasses to tsunami waves. The South China Sea (SCS), for example, is relatively protected to the west and south from Indonesia, to the north from Taiwan, and to the east from the Philippines. However, volcanic meteo-tsunamis may be generated from a volcanic eruption from regions such as southern Japan, and affect the SCS and its surrounding coastlines. Southeast Asia (SEA) presents several records in the literature of volcano-induced tsunami events, including as source mechanisms landslides, Pyroclastic Density Currents, lava dome collapse, and underwater explosions. There are also two instances from Taal, Philippines, and Krakatau, Indonesia, where airwaves have been inferred as a possible tsunami source mechanism, with waves reported also across the Indian and Pacific Oceans, in the latter case. Here, we selected four potential candidates for a submarine or near-surface volcanic eruption, both outside (Kikai and Fukutoku-Oka-no-Ba, Japan) and inside the SCS (Banua Wuhu, Indonesia, and KW-23612, Vietnam), capable of generating volcanic meteo-tsunamis, with the aim to have a first-time assessment from such natural phenomena on SEA countries surrounding the SCS. At this stage, we focused on the general wave propagation in the region, based on the different source locations, and offshore wave maximum height (observed at 16 synthetic tide gauges placed around the SCS, at the 50-m water depth contour, to avoid shallow water complexities near coastlines that cannot be resolved through public bathymetry datasets). We modelled three potential scenarios for each selected seamount, with 100%, 66% and 33% of the HT-HH eruption intensity, respectively. This choice allows us to investigate a broad range of explosion intensities expressed through a perturbance of the atmospheric pressure field, following previous works. Initial results from this first assessment show that bathymetry has a strong control on tsunami wave propagation, being rather fast in deep waters (e.g. northern South China Sea) and much slower in shallow waters (e.g. Sunda Shelf). The higher waves are recorded at offshore stations 11 (Hong Kong) and 16 (West Philippines), with ~10 and 20 cm respectively, in both cases generated from within the SCS from seamount KW-23612. Work is ongoing to integrate higher resolution grids near these locations closer to coastlines, and also to assess the hazard at other areas on the Sunda Shelf where water depth is larger in proximity of coastlines (e.g. Singapore Strait).

How to cite: Verolino, A., Watanabe, M., Felix, R., Conway, C., and Switzer, A.: Volcanic meteo-tsunamis in Southeast Asia: A first-time assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4947, https://doi.org/10.5194/egusphere-egu24-4947, 2024.

EGU24-5650 | Orals | NH5.1

Uncertainty based amplification factors benchmarked by large ensembles of inundation simulations 

Finn Løvholt, Erlend Briseid Storrøsten, Sylfest Glimsdal, Ida Norderhaug Drøsdal, Steven J. Gibbons, Valentina Magni, Fabrizio Romano, Stefano Lorito, Manuela Volpe, and Beatriz Brizuela

Tsunami maximum inundation heights (MIH) are normally estimated by modelling the hydrodynamics of the overland flow over a limited area using high resolution long wave models. However, in situations where there one need to simulate inundation over large areas, we demand methods that are less resource intensive. The method of amplification factors represents one such simplified and resource efficient method. It is based on precomputed factors using linear shallow water models modelled over bathymetric transects to estimate the ratio of the offshore maximum surface elevation to that at the shoreline. It has been shown previously that we can get a relatively good estimate of the median value of the MIH at given coastline location using amplification factors. Yet, as this method is associated with considerably higher epistemic uncertainty than e.g. solving the nonlinear shallow water equations (due to the additional simplifications), there is need to include a measure of its uncertainty and bias. The main sources of uncertainty include among others the misfit of the method (towards data or more accurate methods) and local spatial variability of the inundation. Here, we present results from recent advancements of the amplification factor method emphasising a much more elaborate uncertainty analysis than employed previously. To this end, we use a unique set of synthetic data from several hundreds of thousands of massive scale nonlinear shallow simulations as a benchmark for estimating uncertainty concerned the amplification factors. The simulation dataset comprises ensembles of about 50 000 scenarios each for six different sites and includes sensitivity studies related to the Manning friction. When analysing the entire ensembles, we have revised the previous mathematical model for the uncertainty treatment (Glimsdal et al., 2019, PAGEOPH) by normalising the ensemble scenario outputs with the median MIH from each simulation. We further measure the bias of the amplification factor method by measuring its offset towards median MIH output from the shallow water simulations. The model provides input to the probabilistic tsunami hazard (PTHA) map for Italy, and we present related results of the amplification factor uncertainty analysis here. We will also discuss further and advocate the use of the method, both for long term hazard (PTHA) and for rapid post assessment following an event, e.g. through the ARISTOTLE framework. This work is supported by the European Union’s Horizon Europe Research and Innovation Program under grant agreement No 101058129 (DT-GEO, https://dtgeo.eu/). Computational resources were made available through PRACE grant number 2020225386, TsuHazAP.

How to cite: Løvholt, F., Briseid Storrøsten, E., Glimsdal, S., Norderhaug Drøsdal, I., Gibbons, S. J., Magni, V., Romano, F., Lorito, S., Volpe, M., and Brizuela, B.: Uncertainty based amplification factors benchmarked by large ensembles of inundation simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5650, https://doi.org/10.5194/egusphere-egu24-5650, 2024.

EGU24-5841 | Posters on site | NH5.1 | Highlight

Augmenting Tsunami Detection with a Ship-based GNSS Network 

James Foster, Todd Ericksen, Bruce Thomas, Jonathan Avery, Yuke Xie, and Robin Knogl

We demonstrated the potential for ship-based GNSS systems to contribute to tsunami warning with a pilot network of 10 ships – 8 commercial and 2 research vessels - equipped with a tsunami detection package that included a geodetic-grade GNSS antenna and receiver, and a satellite internet communication system. The ships we instrumented operated throughout the Pacific, and transmitted real-time precise positions to our shore server from 2015-2018. This data set is used to examine the performance that an operational system would be able to expect if employed for tsunami detection. The estimated accuracy for our real-time vertical position solutions is 5.6 cm, commensurate with the advertised accuracy of the positioning service we employed. This indicates it is plausible to expect to observe the sea surface perturbation of a potentially dangerous tsunami with open ocean wave amplitude of more than 10 cm.  Significant numbers of long period (10s of minutes) excursions, however, appear in the data in the absence of actual tsunami. The similarity of these excursions with the signals expected from a tsunami would result in a high rate of false positive detections if the ship data were used to independently identify tsunami events. A significant number of these were associated with ships changing speed as they were approaching or leaving port. A simple masking strategy based on the ship’s speed reduces the number of these artifacts by 48%. The rate of false positive detections can be reduced to negligible levels by treating the network as an ensemble detection system and examining the data from 4 or more ships together. The density of ships in the open oceans are shown to be well matched to the source regions of historical fatal tsunamis, confirming this approach could provide valuable additional data to tsunami warning centers. We suggest that a network of ships, equipped with geodetic GNSS packages, based on a voluntary participation model, and leveraging the results from our pilot project would provide a valuable low-cost augmentation to the current tsunami detection systems. Furthermore, extended tsunami detection capability from this proposed ship network is possible by leveraging the ability of dual frequency GNSS to detect ionospheric perturbations. Tracking perturbations in the total electron count along the ray paths between each ship and each GNSS satellite provides multiple additional time series that have demonstrated capability to detect the ionospheric signals induced by open ocean tsunamis.  Implementing these data streams would therefore expand the effective monitoring zone of each ship in the network from a single tide-gauge-like point to multiple observations within a circle with radius more than 500 km.

How to cite: Foster, J., Ericksen, T., Thomas, B., Avery, J., Xie, Y., and Knogl, R.: Augmenting Tsunami Detection with a Ship-based GNSS Network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5841, https://doi.org/10.5194/egusphere-egu24-5841, 2024.

The consensus in earlier studies was that the tsunami threat along the coast of south China primarily comes from destructive earthquakes occurring in the Manila subduction zone. However, two seismogenic structures on the continental shelf of the Northern South China Sea, namely the Littoral Fault Zone and the Slope Fault Zone, have been overlooked in these assessments. Both fault zones have a history of destructive earthquakes accompanied by tsunamis. In particular, the Slope Fault Zone, located in the shelf-slope bending zone, is prone to triggering submarine landslides after earthquakes, which can result in devastating tsunamis. This study aims to assess the potential threats posed by earthquake-submarine landslide-tsunami cascading events in the Qiongdongnan segment of the Slope Fault Zone to the coastal regions of Southern China.

To achieve this, we conducted a probabilistic seismic hazard analysis using the latest findings on the fault structure of the Qiongdongnan segment and the comprehensive regional seismic catalog. This analysis provides important information about the likelihood of earthquakes in the region. Based on the seismic hazard analysis results, we assessed the stability of gentle slope areas (submarine landslide gap) using high-resolution bathymetric data, multi-channel seismic profiles, and gravity core samples of seafloor sediments. Finally, we established a model for potential submarine landslide sources in these areas and evaluated the tsunami hazard resulting from earthquake-triggered landslides.

By comprehensively evaluating earthquake-submarine landslide-tsunami cascading events on the continental shelf fault zone of the Northern South China Sea, this study aims to provide a new perspective and understanding for earthquake and tsunami disaster prevention. Additionally, it seeks to establish the scientific foundations for the development of effective tsunami warning and risk management strategies.

How to cite: Du, P., Li, L., and Wang, D.: Hazard Assessment of Earthquake-Submarine Landslide-Tsunami Cascading Events on the Slope Fault Zone of Northern SCS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6087, https://doi.org/10.5194/egusphere-egu24-6087, 2024.

EGU24-6676 | Orals | NH5.1

A “cookbook” for probabilistic tsunami hazard and risk assessment 

Mathilde Sørensen, Jörn Behrens, Fatemeh Jalayer, Finn Løvholt, Stefano Lorito, Jacopo Selva, Mario Salgado, and Irina Rafliana

Probabilistic tsunami hazard and risk assessment methods (abbreviated PTHA and PTRA, respectively) have evolved quickly over the past 10 to 15 years. Given this rapidly evolving landscape, there is a need to establish best practices for PTHA and PTRA to improve reliability, comparability and reproducibility of studies applying such methods. The recently concluded Cost Action CA18109 AGITHAR (2019-2023) intended to improve the scientific foundation for PTHA and PTRA. To materialize the networking activities into guidelines and best practices, more than 50 tsunami scientists have joined forces to develop a so-called cookbook providing recommendations and workflows for both PTHA and PTRA. The cookbook will give an overview of existing methods, unify the descriptions of named workflows, make best practices examples available to a wider community, and provide background information to various stakeholder groups. We employ the analogy of a cookbook, because successful PTHA/PTRA workflows can be described by essential building blocks (ingredients) combined in specific ways (recipes) to serve the purpose of the analysis of actual application fields. In that regard, we first introduce the main ingredients in seven chapters describing e.g.  source models, tsunami models, vulnerability, exposure, as well as risk communication, and then present a series of recipes (25 in total) providing examples of how the ingredients can be combined in a workflow leading to a meaningful PTHA or PTRA. The cookbook can be used and read in different ways. On the one hand, and again in analogy to a usual cookbook, readers may browse through recipes, and access the ingredients chapters following the corresponding list of ingredients. The recipes all follow a similar organizational structure, so they can be accessed easily. On the other hand, the book can be read consecutively, starting with the study of ingredients, following the general workflow of PTHA and PTRA. By this, scholars will learn in a structured way how to build corresponding hazard and risk assessments. Finally, for the more experienced readers, the book may serve as a reference to the current state-of-the-art in this multidisciplinary research area. In this presentation, we will introduce the key ingredients described in the cookbook, as well as selected recipes. We will then summarize the main recommendations for future PTHA/PTRA studies, as provided in the book. The book is expected to be published in Autumn 2024.

How to cite: Sørensen, M., Behrens, J., Jalayer, F., Løvholt, F., Lorito, S., Selva, J., Salgado, M., and Rafliana, I.: A “cookbook” for probabilistic tsunami hazard and risk assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6676, https://doi.org/10.5194/egusphere-egu24-6676, 2024.

The Vanuatu Trench hosts tsunamigenic earthquakes exceeding magnitude 7. For these source locations, current tsunami early warning systems in Aotearoa - New Zealand are based on earthquake point-source parameters and as tsunamis propagate, initial forecasts are refined by DART (Deep-ocean Assessment and Reporting of Tsunamis) sea-level analysis. This study, which is part of the R-CET (The Rapid Characterization of Earthquakes and Tsunami) project led by GNS Science, aims to seismologically characterize the spatio-temporal behavior of the regional tsunamigenic ruptures in near real-time. This transition from basic point sources to 4-D rupture propagation could enhance the accuracy of initial tsunami threat maps and hazard response. A new array of broadband seismic stations, designated as the R-CET array, has been strategically deployed in New Zealand to support this analysis for events in the South Pacific.

In this proof-of-concept study, we applied a beamforming array seismological technique to analyze the R-CET array recordings from a recent tsunamigenic earthquake (Mw 7.7) in the Vanuatu region, the Loyalty Islands, on May 19, 2023. We use sliding window fk-analysis beamforming, which can simultaneously measure backazimuth and slowness. Incorporating the sliding window, in conjunction with the fk diagrams, helps to observe temporal azimuthal changes, which facilitates tracking the rupture length and direction over time. Preliminary results showed the azimuthal and temporal variation of the rupture is in alignment with post-processing estimates of the finite fault solution for this event reported by USGS. We test the utility of this analysis in tsunami forecasts by comparing threat maps generated from the beamforming source and initial response maps used in real-time response on the day. We further compare our results to actual measured coastal cancellation gauges (tide gauges) and DART observations. We show that this analysis has the potential to improve initial tsunami forecasts prior to the onset of tsunami waves at deep ocean tsunamimeters. We further present the technique as an enticing path to meet UN Ocean Decade tsunami warning goals within our framework of ensemble and time-dependent forecasting.

How to cite: Aghaee-Naeini, A., Fry, B., and D.Eccles, J.: Spatial-Temporal Rupture Characterization of Potential Tsunamigenic Earthquakes Using Beamforming: Faster and More Accurate Tsunami Early Warning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6824, https://doi.org/10.5194/egusphere-egu24-6824, 2024.

EGU24-8274 | ECS | Orals | NH5.1

Modeling optimal initial conditions for propagation of seismotectonic tsunamis: a database of smoothed unit sources based on an efficient and accurate numerical integration 

Alice Abbate, José Manuel González Vida, Manuel J. Castro Díaz, Fabrizio Romano, Hafize Başak Bayraktar, Andrey Babeyko, and Stefano Lorito

The initial conditions for the numerical simulation of a seismically-induced tsunami are modeled by transferring the impulse produced by the co-seismic seafloor deformation to the sea-surface. In this process, the water column acts as a hydraulic filter for the smaller wavelengths. The numerical simulation of this process is computationally demanding; this makes  the application of this filter unaffordable in studies that require a large number of simulations, such as the long-term probabilistic tsunami hazard assessment (PTHA). Here, we optimize the numerical modeling of the filter in the case of an instantaneous vertical seafloor deformation, given by an improper Fourier expansion integral in the wave number domain presented by Nosov and Kolesov (PAGEOPH, 2011); the contribution of elementary seafloor displacements can then be linearly combine to obtain a static tsunami initial condition. We first explore the convergence of the integral in one dimension, to identify the range of wavenumbers significantly contributing to the integral. We find that its support can be limited to , being H the sea-depth. We then compare several quadrature formulae, selecting the optimal one in terms of accuracy and efficiency. We grid the domain into cells of equal size and constant depth, and verify that the nonlinear effects are negligible when we recombine them to obtain the initial sea level displacement. In two dimensions, the integral is solved with the optimal quadrature and the results tested on the tsunamigenic Kuril doublet sequence - a megathrust and an outer-rise - occurred in the Central Kuril Islands in late 2006 to early 2007. We also consider the horizontal co-seismic deformation projected on a slope and a simple model of the inelastic deformation of the wedge, on a realistic bathymetry. The approach proposed results accurate and fast enough to be relevant for practical applications, taking a few seconds for solving a single cell, depending on the local depth, and ~3min to recombine ~91k elementary initial conditions. We finally build a database of elementary initial conditions, as a function of the local sea depth, which can be linearly combined to obtain a discretization of any sea floor displacement globally.

How to cite: Abbate, A., González Vida, J. M., Castro Díaz, M. J., Romano, F., Bayraktar, H. B., Babeyko, A., and Lorito, S.: Modeling optimal initial conditions for propagation of seismotectonic tsunamis: a database of smoothed unit sources based on an efficient and accurate numerical integration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8274, https://doi.org/10.5194/egusphere-egu24-8274, 2024.

EGU24-8317 | ECS | Orals | NH5.1

Meteotsunami-HySEA: A GPU accelerated code for simulating atmospherically-driven tsunamis on real bathymetries. Benchmark tests. 

Alex Gonzalez del Pino, Jorge Macías Sánchez, Manuel Castro Díaz, and Cléa Lumina Denamiel

Atmospherically-driven tsunamis or meteotsunamis are generated by atmospheric disturbances with steep gradients of pressure and/or wind. In recent years, meteotsunamis have received more attention from the tsunami modelling community. Although their destructive potential might be less severe than for earthquake or landslide triggered tsunamis, their frequency is much higher. The two main processes driving the most extreme meteotsunami events are the offshore amplification of the ocean long-waves due to Proudman or Greenspan resonances (i.e., when the atmospheric disturbance travels at the same speed than the long-waves) and, nearshore, the amplification factor of the shelfs, bays or inlets (i.e., resonance frequency associated to the nearshore geometry). As meteotsunamis have a high-dependence on the nearshore geometric characteristics, they often occur at known hotspot locations such as along the coastlines of Croatia, the Balearic Islands, Sicily, Malta, the Nagasaki Bay or the Baltic Sea. One of the most devastating meteotsunami events took place in Menorca (Balearic Islands) in 2006, where tsunami-like oscillations caused an economic loss of several tens millions of euros.

The EDANYA group from the university of Málaga is widely known for its GPU-accelerated tsunami simulation codes, such as Tsunami-HySEA (earthquake source) or Landslide-HySEA (landslide source). Here, we present our brand-new code for simulating meteotsunamis following the same philosophy as the previous codes. Meteotsunami-HySEA incorporates the atmospheric forcing together with additional terms such as Coriolis and the wind drag. The PDE system is written in spherical coordinates and implemented in CUDA. An additional feature related to preserving a linear version of the quasi-geostrophic equilibrium is added to the numerical scheme in order to preserve the structure of geostrophic flows, as large scale geophysical flow are often perturbations of this steady state.

To demonstrate the Meteotsunami-HySEA reliability, we first applied the code to some carefully-crafted benchmark tests, where Proudman resonance is exhibited and precisely capture, enabling accurate measures of the amplification gain due to the coupling of the propagation velocities. Then we followed the NTHMP’s guidelines for simulating a pilot study in the region of the Gulf of Mexico with a real topobathymetry. Further work will be focused on testing real scenarios, incorporating real atmospheric data and bathymetry for reliable forecast.

Acknowledgments: This contribution was supported by the EU project “A Digital Twin for Geophysical Extremes” (DT-GEO) (No: 101058129) and by the Center of Excellence for Exascale in Solid Earth (ChEESE-2P) funded by the European High Performance Computing Joint Undertaking (JU) under grant agreement No 101093038.

 

How to cite: Gonzalez del Pino, A., Macías Sánchez, J., Castro Díaz, M., and Lumina Denamiel, C.: Meteotsunami-HySEA: A GPU accelerated code for simulating atmospherically-driven tsunamis on real bathymetries. Benchmark tests., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8317, https://doi.org/10.5194/egusphere-egu24-8317, 2024.

EGU24-8319 | ECS | Orals | NH5.1

Optimizing Maximum Height Inferences through Neural Networks for the Spanish Tsunami Early Warning System 

Juan Francisco Rodríguez Gálvez, Jorge Macías Sánchez, Beatriz Gaite, Manuel Jesús Castro Díaz, Juan Vicente Cantavella, and Luis Carlos Puertas

Tsunami Early Warning Systems (TEWS) play a crucial role in minimizing the impact of tsunamis on coastal communities globally. In the NEAM region (North-East Atlantic, the Mediterranean, and connected Seas), historical approaches involve using Decision Matrices and precomputed databases due to the short time between tsunami generation and coastal impact. Overcoming real-time simulation challenges, the EDANYA group at the University of Málaga developed Tsunami-HySEA, a GPU code enabling Faster Than Real Time (FTRT) tsunami simulations. This code is successfully implemented and tested in TEWS of countries like Spain, Italy, and Chile, this code has undergone rigorous verification and validation processes.

In collaboration with the National Geographic Institute of Spain, we have extended the work previously done where we take advantage of the machine learning techniques and proposed a first approach to the use of neural networks (NN) to predict the maximum wave height and arrival time of tsunamis in the context of TEWS with very good results. This approach offers the advantage of minimal inference time and can be executed on any computer. It accommodates uncertain input data, delivering results within seconds.

As tsunamis are rare events, numerical simulations using the Tsunami-HySEA are used to train the NN model. This phase demands numerous simulations, necessitating substantial High-Performance Computing (HPC) resources. Approximately 300,000 simulations have been done to cover different faults in the Atlantic Ocean.

The goal is to develop neural network models for predicting the maximum wave height of such tsunamis at multiple coastal locations simultaneously.  To cover Huelva and Cádiz coast, 78 points in the coastline have been selected for their predictions. The main importance of this work is that the models developed will be implemented in the Spanish TEWS which will produce an estimation of the tsunami impact in seconds.

 

Acknowledgements

  • This project has received funding from the European High-Performance Computing Joint Undertaking (JU) through the projects eFlows4HPC (No 955558) and ChEESE-2P (No 101093038) and by the EU project DT-GEO (No: 101058129).
  • Spanish Network for Supercomputing (RES) grants AECT-2022-1-002, AECT-2022-3-0015 and AECT-2023-1-0028.

How to cite: Rodríguez Gálvez, J. F., Macías Sánchez, J., Gaite, B., Castro Díaz, M. J., Cantavella, J. V., and Puertas, L. C.: Optimizing Maximum Height Inferences through Neural Networks for the Spanish Tsunami Early Warning System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8319, https://doi.org/10.5194/egusphere-egu24-8319, 2024.

EGU24-8679 | Posters on site | NH5.1

Towards data assimilation in the Probabilistic Tsunami Forecasting digital twin 

Valentina Magni, Manuela Volpe, Louise Cordrie, Michel Bänsch, Finn Løvholt, Stefano Lorito, Fabrizio Romano, Roberto Tonini, Ida Drøsdal, Steven Gibbons, and Jörn Behrens

Probabilistic Tsunami Forecasting (PTF) uses the initial magnitude and location of a seismic event to forecast the tsunami intensity at coastal locations as a probability distribution (Selva et al., 2021). The PTF workflow can be summarized in the following steps: 1) select the ensemble of scenarios and the probability of a scenario coinciding with the actual earthquake; 2) for each scenario, compute a tsunami intensity measure (e.g., maximum inundation height) at coastal locations of interest – either by running shallow water tsunami propagation models with the code Tsunami-HySEA, or by retrieving it from a precomputed database of scenarios; 3) combine the intensity measure with scenario probabilities to compute hazard curves; 4) convert the probabilities into alert levels according to a predefined rule; and 5) visualise the results. More recently, developments in the context of the eFlows4HPC project have allowed for the possibility of updating the probabilities of the ensemble elements based on new data (focal mechanism and sea level data) to make the forecast more precise and/or reduce the uncertainties. Building on these new developments, we present the first results using an even more general PTF workflow here, implementing dynamically the assimilation of new data, such as new estimates of the earthquake magnitude and location, focal mechanism, GNSS displacements, and sea level data. In particular, new estimates of the source will be used to compute a new ensemble, new probabilities, and will trigger Tsunami-HySEA simulations of the new scenarios in the ensemble. If sea level and/or GNSS data are available, we compute the misfit between the data and the results of the simulations to further update the probabilities and reduce the overall uncertainty in the forecast. We use the 2020 Samos earthquake as a first test of the new workflow that includes data assimilation, but further testing will be done for other events in the Mediterranean Sea and Pacific Ocean. Implementing a continuous update of the results within the above outlined dynamic workflow triggered by the arrival of new data represents a crucial element in transforming the PTF into a digital twin.

This work is supported by the European Union’s Horizon Europe Research and Innovation Program under grant agreement No 101058129 (DT-GEO, https://dtgeo.eu/).

How to cite: Magni, V., Volpe, M., Cordrie, L., Bänsch, M., Løvholt, F., Lorito, S., Romano, F., Tonini, R., Drøsdal, I., Gibbons, S., and Behrens, J.: Towards data assimilation in the Probabilistic Tsunami Forecasting digital twin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8679, https://doi.org/10.5194/egusphere-egu24-8679, 2024.

The high-frequency (HF) ocean radar system is a shore-based remote sensing system that monitors sea surface currents, waves, and wind over large areas. It can measure tsunami-induced surface current velocity and provide information for tsunami early warning. An HF ocean radar system, installed by the Ministry of Land, Infrastructure, Transport, and Tourism in Japan, measured the tsunami velocity in the Kii Channel during the 2011 Tohoku earthquake. The Kii Channel is a strait that separates the Japanese island of Shikoku from the Kii Peninsula on the main island of Honshu. It connects the Osaka Bay with the Pacific Ocean.

We adopted the tsunami data assimilation approach to predict coastal tsunami waveforms. It is a method that reconstructs the tsunami wavefield using offshore data without the need for source information (Maeda et al., 2015). To process the HF radar data as the input, we initially converted the current velocity along the beam direction to into u, v directions (i.e., EW, NS directions). This process also involved the spatial interpolation of observational points from the beam of two HF radar land stations. In addition, recognizing the tradeoff between the sampling rate and velocity resolution, we applied a 10-min moving average to enhance data quality. The processed velocity data exhibited consistency with numerical simulations derived from the source model of Satake et al. (2013). The data assimilation started at 08:05 (UTC, hereafter) on March 11, 2011.

We predicted coastal tsunami waveform at Kobe, located in the Osaka Bay, and compared it with real observation recorded by the tide gauge. The forecast at 08:10 underestimated the tsunami amplitude, achieving an accuracy of 50.1% with a mean squared prediction error (MSPE) of 0.0101. However, the forecast at 08:20 matched well with the real observation, boasting an accuracy of 82.9% and a reduced MSPE of 0.0098. At 08:30, it continued to perform similarly, maintaining consistency between the predicted and observed waveforms. The accuracy was 81.3% and the MSPE further decreased to 0.0093. Given that the tsunami arrived in Kobe at 09:10, our approach can make an accurate prediction at least 50 min before its arrival.

To summarize, we demonstrated the effectiveness of the HF ocean radar system in tsunami early warning. The case study of the 2011 Tohoku tsunami yielded a remarkable accuracy of over 80% at Kobe station. In the future, we will investigate the relationship between the number and location of HF radar observational points and the forecast accuracy.

How to cite: Wang, Y. and Imai, K.: Tsunami early warning using high-frequency ocean radar system in the Kii Channel, Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9348, https://doi.org/10.5194/egusphere-egu24-9348, 2024.

EGU24-9919 | ECS | Orals | NH5.1

Experimental study of tsunami-driven transport of micro-plastic on sedimentary slope 

Pin-Tzu Su, Ira Didenkulova, and Atle Jensen

We study experimentally tsunami-induced transport of micro-plastic. The micro-plastic is modelled by spheres of different densities, some of which are lying on the bottom slope, while others are floating. The bottom slope is covered with the sand, which allows us to study micro-plastic interaction with sand of different sizes. The spheres are initially placed at different locations along the slope with respect to the wave breaking point. Experiments are performed in a small wave flume of the Hydrodynamics laboratory of the University of Oslo. It is 3 m long and 0.1 m wide. The water depth is 5 cm. The tsunami is modelled by breaking solitary-like waves with amplitude, normalized by the water depth 𝑎/ = 0.47. The waves propagate towards a sandy beach breaking on the slope, impact the floating and/or lying on the bottom spheres, and the spheres get displaced. Here we study the displacement of the spheres from their initial position with respect to their characteristics (densities), initial positions with respect to the wave breaking point, the number of consecutive waves and parameters of the sand.

How to cite: Su, P.-T., Didenkulova, I., and Jensen, A.: Experimental study of tsunami-driven transport of micro-plastic on sedimentary slope, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9919, https://doi.org/10.5194/egusphere-egu24-9919, 2024.

EGU24-10023 | Orals | NH5.1

Resurgence of Greenspan Resonance in Meteotsunami Dynamics 

Jihwan Kim and Rachid Omira

Originating from atmospheric pressure disturbances, meteotsunamis undergo amplification processes through resonances such as Proudman, Greenspan, and bay/harbor. While Greenspan resonance is often overlooked due to its moderately amplified waves, its recurrent nature makes it a crucial factor in meteotsunami magnification. We briefly review prior analytic studies using linearized shallow water equations on a constant slope with the propagation of Gaussian atmospheric pressure, providing insights into the background of our research. Additionally, we present two recent meteotsunami cases, the June 2009 event in the West coast of Korea, and the October 2018 event in the coast of Portugal, to emphasize the pivotal role of Greenspan resonance in enhancing meteotsunamis. Our study includes  data analysis, numerical simulations, and comparisons with analytical solutions. This work was supported by the project FAST (Development of new forecast skills for meteotsunamis on the Iberian shelf – ref. PTDC/CTA-MET/32004/2017), and by I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020-IDL, both funded by the Fundação para a Ciência e a Tecnologia (FCT), Portugal.

 

Keywords: meteotsunami, Greenspan resonance, numerical models, analytical solutions 

 

References

 

Greenspan, H. P. “The Generation of Edge Waves by Moving Pressure Distributions.” Journal of Fluid Mechanics, vol. 1, no. 06, 1956, p. 574, https://doi.org/10.1017/S002211205600038X.

Kim, Jihwan, et al. “On the Greenspan Resurgence of Meteotsunamis in the Yellow Sea—Insights from the Newly Discovered 11–12 June 2009 Event.” Natural Hazards, vol. 114, no. 2, 2022, pp. 1323–40, https://doi.org/10.1007/s11069-022-05427-3.

Kim, Jihwan, and Rachid Omira. “Combined Surge-Meteotsunami Dynamics: a numerical model for Hurricane Leslie on the coast of Portugal.” (submitted)

Niu, Xiaojing. “Conditions for the Occurrence of Notable Edge Waves Due to Atmospheric Disturbances.” Applied Ocean Research, vol. 101, 2020, p. 102255, https://doi.org/10.1016/j.apor.2020.102255.

Seo, Seung-Nam, and Philip L. F. Liu. “Edge Waves Generated by Atmospheric Pressure Disturbances Moving along a Shoreline on a Sloping Beach.” Coastal Engineering, vol. 85, 2014, pp. 43–59, https://doi.org/10.1016/j.coastaleng.2013.12.002.

Ursell, Fritz. “Edge Waves on a Sloping Beach.” Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, vol. 214, no. 1116, Aug. 1952, pp. 79–97, https://doi.org/10.1098/rspa.1952.0152.

How to cite: Kim, J. and Omira, R.: Resurgence of Greenspan Resonance in Meteotsunami Dynamics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10023, https://doi.org/10.5194/egusphere-egu24-10023, 2024.

EGU24-11223 | ECS | Posters on site | NH5.1

Sensitivity analysis of a shallow-water model for landslide-generated tsunamis in Mayotte 

Alexis Marboeuf, Pablo Poulain, Anne Mangeney, Anne Le Friant, Maxwell Silver, Enrique Fernandez Nieto, and Annabelle Moatty

Since May 2018, Mayotte Island has been experiencing seismo-volcanic activities which may trigger submarine landslides and tsunamis. Numerical models are a powerful tool to build tsunami hazard maps and to establish evacuation plans, improving early-warning systems. However, a lot of uncertainties still remain in model parameters making it difficult to reproduce the landslide dynamics and the generated waves. 

In this work, we perform a sensitivity analysis using the multilayer HySEA shallow water model [1, references therein]. HySEA simulates both a landslide and a generated tsunami. We focus on a scenario posing the greatest threat to the local community, involving a submarine landslide on the eastern side of Mayotte's lagoon at a shallow water depth [2]. Hydrostatic and non-hydrostatic results are compared and several numeric and physical parameters are investigated: grid resolution, number of water layers in the vertical direction, rheological laws, friction coefficients and grain sizes.

Our results show that using non-hydrostatic conditions, increasing the grid resolution and the number of water layers greatly impacts the computed waves. Increasing these parameters is worth the larger computational cost. Physical parameters related to the landslide also affect the dynamic and the final deposit of the granular mass. While the choice of the grain size, the used rheological law or the friction angles may lead to different results, almost no change was observed over an hour of simulation when the Manning coefficient is modified. In all our test cases, the differences appear mainly at the early stages of the simulations. Numerical gauges placed at locations of interest on Mayotte's coast allow a closer look at the numerical waves for a finer sensitivity analysis.

References

[1] J. Macìas, C. Escalante, M. J. Castro. Multilayer-HySEA model validation for landslide-generated tsunamis - Part 2: Granular slides. Natural Hazards and Earth System Sciences, Volume 21 (2021).
[2] A. Lemoine; R. Pedreros; A. Filippini. Scénarios d’impact des tsunamis pour Mayotte. BRGM Report BRGM/RP-69869-FR (April 2020).
 

 

How to cite: Marboeuf, A., Poulain, P., Mangeney, A., Le Friant, A., Silver, M., Fernandez Nieto, E., and Moatty, A.: Sensitivity analysis of a shallow-water model for landslide-generated tsunamis in Mayotte, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11223, https://doi.org/10.5194/egusphere-egu24-11223, 2024.

EGU24-11569 | ECS | Orals | NH5.1

Identification of the Storegga Tsunami offshore Shetland: implications for seabed infrastructure hazard risk assessment 

Jane Earland, James Scourse, Tobias Ehmen, and Sev Kender

The Shetland Islands (UK) are a seminal location for investigating palaeo-tsunami deposits. Onshore evidence suggests three tsunamis have occurred during the Holocene: the Storegga tsunami ca. 8175 cal yr BP, the Garth tsunami ca. 5500 cal yr BP and the Dury Voe tsunami ca. 1500 cal yr BP. However, to date no research has been published on the impact of tsunami on the subtidal shelf where a large amount of North Sea hydrocarbon infrastructure is located. During the SEACHANGE research cruise DY150 (2022), cores were recovered offshore east Shetland from the Fetlar Basin. The cores contained distinct sand and shell lenses within a Holocene mud sequence, indicating increases in bed shear stress. We test the hypothesis that these lenses represent the subtidal expression of North Sea tsunami. Radiocarbon dates bracketing the sand lenses overlap with the published dates for the Storegga tsunami, suggesting these sand lenses result from processes related to the Storegga tsunami. Dates within the deposit are older than the Storegga tsunami, indicating reworking and deposition of older sediments at the core site by the tsunami. Particle size analysis, ITRAX and MSCL data evidence increases in grain size, a reduction in sorting capacity, increased shell concentrations and peaks in associated elements (log(Ca/Fe), log(Ca/Ti) and Sr) and magnetic susceptibility. These attributes are typical of both palaeo and modern offshore tsunami deposits. No evidence was found within the cores for any later Holocene tsunami, due to either bioturbation, active currents, or lack of initial deposit. The data indicate that sediments in the Fetlar Basin were disturbed by the Storegga tsunami to palaeo-water depths of at least 88 m. This highlights the need to assess the potential impact of any future tsunami on existing or proposed hydrocarbon infrastructure.

How to cite: Earland, J., Scourse, J., Ehmen, T., and Kender, S.: Identification of the Storegga Tsunami offshore Shetland: implications for seabed infrastructure hazard risk assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11569, https://doi.org/10.5194/egusphere-egu24-11569, 2024.

Sandy tsunami deposits are essential stratigraphic markers to document the impact of tsunamis in the geologic record. Tsunami sands are also the only record of past tsunamis that can be interrogated to retrieve quantitative information about the causative tsunami event. Inversion of flow speed and flow depth from tsunami deposits is often employed to understand a tsunami event better and evaluate the impact of different tsunami events in the same stratigraphic sequence or geographic area. 

After deposition, like any other deposit, sandy tsunami deposits are exposed to a series of processes that alter the deposits, collectively called post-depositional processes. These post-depositional processes can change the characteristics significantly. If tsunami deposits are employed to gain quantitative insights into a past event, these post-depositional processes can potentially alter respective inversion results. The influence of post-depositional processes on the inversion of flow depths and speeds has been considered but remains understudied.

To gain more insight into the influence of flow speed and flow depth inversions, we present a new model to simulate different post-depositional processes, such as erosion, bioturbation, winnowing, compaction, and dissolution of minerals. We employ stochastic processes for all these sediment alteration possibilities on a grain-size distribution level. In this context, we use a large number of reference grains for each grain-size class in a given deposit and calculate an individual grain's fate depending on the post-depositional process. This new model allows us to consider different combinations of processes to simulate different sedimentary environments and to quantify the influence of different post-depositional processes with time. We employ the established TSUFLIND model to invert flow speed and depth from the altered grain-size distribution. 

Our results indicate how individual post-depositional processes have a more significant influence on inverted flow speeds and depths than others, but they also show how they can influence each other to have a more substantial impact on the sum than individually. Furthermore, our results shed light on potential uncertainties any inversion of the flow characteristics might have depending on the sedimentary environment in which the tsunami deposit was created. In turn, this contributes to a better understanding of uncertainties in tsunami hazard assessments that include tsunami deposits.

How to cite: Weiss, R. and Dura, T.: The impact of post-depositional processes on tsunami deposits - A quantitative analysis for tsunami hazard assessments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13527, https://doi.org/10.5194/egusphere-egu24-13527, 2024.

EGU24-13955 | ECS | Orals | NH5.1

Advancing User-Friendly Tsunami Hazard Mapping:  MATLAB-based Applications for FUNWAVE modelling 

Raquel Felix, Masashi Watanabe, Andrea Verolino, Elaine Tan, Jun Yu Puah, and Adam Switzer

Following the 2022 Hunga Tonga - Hunga Ha'apai tsunami, there is a renewed interest in assessing tsunami hazards related to tsunamis triggered by landslides, volcanic eruptions, and atmospheric disturbances. This increased interest suggests an expanding cohort of researchers delving into the assessment of tsunami hazards through numerical modelling. However, mastering a numerical model involving tasks such as input file preparation, simulation execution, and output data generation poses a challenge for inexperienced users. The learning process often demands a substantial time investment, potentially causing workflow delays that may prevent researchers from promptly initiating result analysis. To address this challenge, we introduce standalone applications designed to optimize the efficiency of both tsunami model preparation and post-processing stages. We present two MATLAB-based user-friendly applications designed to efficiently generate input files and output tsunami hazard maps. The applications were designed to align with the required input and expected output files of the Fully Nonlinear Boussinesq Wave (FUNWAVE) model. FUNWAVE is a well-established open-source model that has been extensively validated through analytical solutions and experimental investigations. It also offers options to set up initial conditions, such as landslides and meteotsunamis. To facilitate its useability, the applications incorporate tool tips and context menus that provide a comprehensive guide for users. Within the input-generator application, visual warnings pre-empt potential errors in tsunami simulations. Meanwhile, the output map generator application not only facilitates the creation of maps, but also offers users the convenience of converting these maps into raster files,  animations, KML, or shapefiles. This versatility ensures compatibility with various programming and Geographic Information System (GIS) platforms. We tested the functionality of the applications using the benchmark examples from the FUNWAVE model. Through the development of these applications, we aim to advance tsunami modelling research by enhancing technological accessibility, hence reducing the complexity, especially for individuals new to tsunami modelling.

 

How to cite: Felix, R., Watanabe, M., Verolino, A., Tan, E., Puah, J. Y., and Switzer, A.: Advancing User-Friendly Tsunami Hazard Mapping:  MATLAB-based Applications for FUNWAVE modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13955, https://doi.org/10.5194/egusphere-egu24-13955, 2024.

EGU24-14374 | ECS | Orals | NH5.1

Global investigation of the tsunamigenic dislocation of the seismic fault 

Ioanna Triantafyllou, Fumihiko Imamura, and Gerassimos Papadopoulos

Seismic tsunamis are produced from the sea floor dislocation (SFD) due to the earthquake rupture. The size of the SFD depends on the earthquake magnitude, depth and mechanism. The seismic moment, Mot, corresponding to the tsunamigenic SFD, is equal to k∗Mo, where Mo is the entire earthquake moment and k is a coefficient smaller than 1. For a first time, we estimated the coefficient k from published data collected for a set of tsunamigenic earthquakes that occurred in the global ocean from 1990 to 2023. The moment magnitude of these earthquakes ranges from 6.0 to 9.3. No default earthquake mechanism has been adopted. However, all the earthquakes considered are of dip-slip (thrust or normal) or oblique dip-slip types. It has been found that logk increases linearly with the earthquake moment Mo, which implies that the coefficient k increases exponentially with the Mo. For tsunami earthquakes it was found that k has a value larger than its value in regular tsunamis for the same Mo. These results provide a better understanding of the tsunami generation from earthquakes and may open possibilities for estimating the tsunami magnitude at the source.

How to cite: Triantafyllou, I., Imamura, F., and Papadopoulos, G.: Global investigation of the tsunamigenic dislocation of the seismic fault, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14374, https://doi.org/10.5194/egusphere-egu24-14374, 2024.

EGU24-14559 | Posters on site | NH5.1

The GTM global probabilistic tsunami hazard model 

Stefano Lorito, Fabrizio Romano, Manuela Volpe, Roberto Tonini, Valeria Cascone, Finn Løvholt, Steven Gibbons, Sylfest Glimsdal, Carl Harbitz, Micheal Bader, Alice Agnes Gabriel, Gareth Davies, Jorge Macias, Andrey Babeyko, Jörn Behrens, Kendra Johnson, Helen Crowley, Marco Pagani, and Piero Lanucara

The EU ChEESE-2P project (Centre of Excellence for Exascale in Solid Earth, second Phase, https://cheese2.eu/) aims to developing Pilot Demonstrators (PD) in different areas of Solid Earth (SE) addressing 12 SE Exascale Computational Challenges. 

One of these is a new Probabilistic Tsunami Hazard Assessment (PTHA) for earthquake-generated tsunamis at the global scale, in the framework of the GTM (Global Tsunami Model) initiative. The GTM PTHA model is meant to be an update of the previous one of its kind (Davies et al., 2018, Geological Society of London). The new model will present enhanced source variability (e.g. stochastic slip) and spatially higher resolution of the calculation points. 

“Capacity” simulations will involve on the order of several 100k unit sources, using grids with a 30 arc-sec resolution. The offshore simulations will require on the order of a few million GPU hrs. Inundation simulations for some pilot localities may need up to 5-10 million GPU hrs. They encompass tens of millions of global tsunami scenarios and create high-resolution inundation maps for 10-20 hotspot locations. The global and local models will be distributed through EPOS-TCS Tsunami, showcasing EuroHPC resource utilization for local hazard and risk analysis.

Further than representing a new global reference hazard model, some tools will be provided to allow to:

  • Take the global model as an input to perform local PTHA anywhere globally;
  • Recalculate the hazard using a custom source treatment, including probability, rates, fault data, and earthquake source models with dynamic and heterogeneous slip, using pre-calculated or on-the-fly HPC-based tsunami modelling with the Tsunami-HySEA GPU code;
  • Publish results via the EPOS-TCS Tsunami service delivery framework.

The GTM PTHA model and tools will be interoperable with the other seismic source models and risk calculation tools (e.g. OpenQuake), thus establishing a connection between the Global Tsunami Model (GTM) and Global Earthquake Model (GEM).

We will also seek to establish compatibility and potential coupling with the Digital Twins from different EU projects (DT-GEO, DT-Ocean) towards DestinE.

How to cite: Lorito, S., Romano, F., Volpe, M., Tonini, R., Cascone, V., Løvholt, F., Gibbons, S., Glimsdal, S., Harbitz, C., Bader, M., Gabriel, A. A., Davies, G., Macias, J., Babeyko, A., Behrens, J., Johnson, K., Crowley, H., Pagani, M., and Lanucara, P.: The GTM global probabilistic tsunami hazard model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14559, https://doi.org/10.5194/egusphere-egu24-14559, 2024.

EGU24-14623 | ECS | Orals | NH5.1

Building resilient coastlines: A comprehensive physics-based tsunami hazard model for Aotearoa New Zealand 

Aisling OKane, Bill Fry, Ciaran King, and Andy Nicol

Tsunamis have the potential to cause catastrophic damage to coastal communities. In Aotearoa New Zealand, where 3.5 million people reside within 5 km of the coast, the threat of experiencing a tsunami within their lifetime is a stark reality. Although these events are infrequent with recurrence intervals of hundreds of years, New Zealand faces an elevated risk due to its location within the tectonically active Pacific, where over 80% of the world's tsunamis occur. The region has experienced over seventy tsunamis in the past two-hundred years, with five of these causing devastating impacts to coastal communities and leaving an indelible mark on the landscape due to wave amplitudes surpassing 5 m at the coast. Recent studies, while crucial, have predominantly focused on assessing the tsunami hazard from local sources, recognising their immediate threat. However, to comprehensively assess the overall tsunami hazard to Aotearoa, we must fully account for the regional and distant sources also. This is informed by the harsh reality that some events, such as the 1877 Northern Chile and the 2004 Indian Ocean tsunamis, have inflicted staggering death tolls in distant locations, emphasising their paramount significance in our hazard assessment efforts.

 

In this talk, I will present our innovative hybrid tsunami hazard model designed for Aotearoa New Zealand. We use observations of accumulated earthquake slip on active faults in the Pacific alongside established earthquake laws to ensure that we capture a wide variability of seismogenic tsunami sources to complement the limited historical and instrumental records. Due to recent computational advancements, we can now calculate the seafloor deformation generated from hundreds of synthetic tsunami sources across twenty subduction zones and simulate the tsunami wave propagation to the coast of New Zealand. For each source, we can estimate the wave amplitudes and timing of potential tsunamis and use these metrics to calculate the hazard that these regional and distant sources pose over common return periods. Each part of the model, from the source characteristics to the wave propagation has been independently tested and benchmarked with recorded events to ensure the rigor of the research.

 

Our hybrid approach of blending observation-driven, physics-based, and probabilistic methodologies offers a comprehensive approach to assessing the full range of earthquakes that could cause a tsunami at the shores of New Zealand. Our work, alongside the recent research carried out on the local tsunami sources will accelerate Aotearoa New Zealand’s natural hazard resilience from Pacific earthquake-generated tsunami sources and will pave the way for other tsunami mechanisms to be incorporated into the model analysis, an urgent need given that these hazardous events do not occur independently. We look forward to having the opportunity to share our Aotearoa New Zealand tsunami hazard model with the wider tsunami community in Europe and discuss pathways that our combined research could follow to help build safer and more resilient coastal communities, globally. 

How to cite: OKane, A., Fry, B., King, C., and Nicol, A.: Building resilient coastlines: A comprehensive physics-based tsunami hazard model for Aotearoa New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14623, https://doi.org/10.5194/egusphere-egu24-14623, 2024.

EGU24-14625 | Posters on site | NH5.1

Tsunami databases in the eastern Mediterranean as new EPOS services 

Gerasimos Papadopoulos and Ioanna Triantafyllou

The European Plate Observing System (EPOS) provides research infrastructure, including data and services, in solid Earth science. Recently EPOS decided also to create a Tsunami Core Service (TCS). In addition to the existing databases, we contribute to the TCS initiative by providing two new tsunami databases in the eastern Mediterranean as new EPOS services. The first database compiles data on Tsunami Observation Points (TOPs) of past tsunamis.  For a specific tsunami event the TOPs DB includes the source epicenter, the TOPs names and the corresponding geographical coordinates, names of the localities and a characterization of the tsunami intensity level, K, in each TOP. The second database compiles data on the impact of past tsunamis. Depending on the data availability an effort has been made to introduce quantitative impact data to the extent it is possible (e.g., numbers of fatalities and injuries, numbers of buildings or vessels damaged, etc.). From the impact of a tsunami event the maximum tsunami intensity, K, has been estimated according to the 12-grade scale of Papadopoulos and Imamura (2001). The new service is of great importance since it may help in studies of several kinds such as understanding better of the tsunami source type, determination of the inundation area, verification of tsunami simulation results and tsunami risk assessment. 

 

How to cite: Papadopoulos, G. and Triantafyllou, I.: Tsunami databases in the eastern Mediterranean as new EPOS services, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14625, https://doi.org/10.5194/egusphere-egu24-14625, 2024.

EGU24-14673 | Orals | NH5.1 | Highlight

Tsunami Digital Twin – Concept, Progress, and Application to the 2024 Noto Peninsula Earthquake Tsunami Disaster, Japan 

Shunichi Koshimura, Bruno Adriano, Erick Mas, Shohei Nagata, and Yuriko Takeda

The digital twin is recognized as digital copies of the physical world's objects stored in digital(cyber) space and utilized to simulate the sequences and consequences of target phenomena. Users can fully view the target through real-time feedback by incorporating the physical world's data into the digital twin. Given the importance of the digital twin, the authors propose "Tsunami Digital Twin (TDT)" as a new paradigm in tsunami science and engineering to enhance tsunami disaster resilience.

The components of TDT are the transformation from "Data" to "Information" by integrating sensing, monitoring, and simulation; "Interpretation" of data and information; and "Inference" by using available data and information to draw conclusions and consequences and decide policies and responses for social resilience. Fusing these components is the key to gaining knowledge and insight for optimal solutions in the physical world.

In the session, the authors focus on two functionalities of TDT: Real-time tsunami modeling and forecast capability and Dynamic exposure estimation to verify through the 2024 Noto Peninsula Earthquake Tsunami Disaster.

The rapid tsunami hazard assessment by real-time tsunami modeling implied that severe impacts were expected around Noto Peninsula (Shika to Nanao), and the directivity of tsunami energy was also toward the Japan sea coasts, especially Joetsu city, Niigata Prefecture. We also found that the specific bathymetric features (continental shelf of Noto Peninsula) are responsible for high tsunamis in Suzu city.

The exposure analysis was performed using Mobile Spatial Statistics (the population estimates using mobile phone data) to elucidate population change after the earthquake by elevation (tsunami affected or not).

How to cite: Koshimura, S., Adriano, B., Mas, E., Nagata, S., and Takeda, Y.: Tsunami Digital Twin – Concept, Progress, and Application to the 2024 Noto Peninsula Earthquake Tsunami Disaster, Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14673, https://doi.org/10.5194/egusphere-egu24-14673, 2024.

EGU24-14855 | Posters on site | NH5.1

Synoptic conditions corresponding to the Adriatic meteorological tsunamis 

Jadranka Sepic, Nikola Metlicic, and Mirko Orlic

An online catalogue of meteorological tsunamis in the Adriatic Sea was recently published. The catalogue contains information on 36 meteorological tsunamis, all with a wave height of at least 1 m, which occurred between 1931 and 2021. During this period, there were 10 exceptionally strong events with observed tsunami wave heights of over 3 metres. The strongest event was characterised by tsunami waves of up to 6 m. For all 36 events, available sea level and air pressure measurements, atmospheric synoptic conditions (using ERA5 reanalysis) and satellite images were analysed. Based on the background sea level height (from the nearest tide gauge), the meteorological tsunamis were divided into three categories: (1) storm surge meteotsunamis, i.e. tsunamis that occur at the time of a storm surge; (2) ordinary meteotsunamis, i.e. tsunamis that occur when the background sea level is low; (3) transitional tsunamis. All three types were associated with a strong south-westerly to westerly jet stream in the middle and upper troposphere, which mainly led to the advection of warm air from the southern Mediterranean to the Adriatic Sea. Similarly, convective clouds were observed over the Adriatic Sea during most events before or at the time of the meteotsunamis.

At the surface, three types of events were distinguished from each other. Storm surge meteotsunamis (10 events in total) were associated with a mid-latitude cyclone, centred over the northern Adriatic or the Bay of Genoa, with the cyclone warm sector or advancing cold front over the area affected by the meteotsunami. The associated surface winds were strong and usually of a south-easterly direction (sirocco). The meteotsunamigenic air pressure disturbances were therefore probably generated in the areas of strong updrafts related to the advancing temperature fronts. Ordinary meteotsunamis (21 events) were associated with fair weather, i.e. with a gradient-free mean sea level pressure field over the Adriatic and very weak surface winds. In this type of event, the meteotsunamigenic atmospheric pressure disturbances were probably due to convective disturbances or the atmospheric gravity waves. Transitional events (5 of them) were associated with either a weak gradient of mean sea level pressure field over the Adriatic, with corresponding southeasterly winds of moderate strength, or with a closed shallow low over the Adriatic.

Stronger events were more likely to occur under fair weather conditions but were also observed under stormier weather. The analysis suggests that meteotsunamis in the Adriatic occur under variety of conditions, all of which should be considered when assessing the risk of meteotsunamis.

How to cite: Sepic, J., Metlicic, N., and Orlic, M.: Synoptic conditions corresponding to the Adriatic meteorological tsunamis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14855, https://doi.org/10.5194/egusphere-egu24-14855, 2024.

EGU24-14980 | ECS | Posters on site | NH5.1

Numerical modelling of the Montenegro tsunami of 15 April 1979 

Vedran Kapitanovic, Jadranka Sepic, Miroslava Pasaric, and Mohammad Heidarzadeh

On April 15, 1979, the coastal region of Montenegro was shaken by a devastating earthquake (M = 6.8, Modified Mercalli Intensity = IX-X). Towns and villages were severely damaged, numerous cultural heritage sites were destroyed and around 150 people were killed. The hypocenter was in the sea near the coast between Bar and Ulcinj at a depth of 13 km. The earthquake triggered a tsunami, which was registered by several tide gauges. The strongest waves with an initial height of 45 cm were registered in nearby Bar, where oscillations lasted for more than 24 hours. Tsunami waves of up to 10 cm in height were also recorded on the opposite Adriatic coast, at the Bari (Italy) tide gauge. According to newspaper reports, the tsunami had a strong impact along the Montenegrin coast, with waves reaching a height of up to 3 metres and one person drowning. The numerical model COMCOT (Cornell Multi-grid Coupled Tsunami model) was used to simulate the tsunami. Since various parameters for the earthquake source fault parameters are given in the literature, with varying values for the location of the epicentre, the depth, the earthquake magnitude, and the properties of the nodal plane, we carried out a series of simulations by considering a reasonable range for each parameter. The simulations differed in the parameters of the earthquake source - as given in the literature, as well as in the length and width of the fault plane. The simulation that best reproduced the waves recorded at the tide gauges was selected as representative and was further analysed to determine maximum heights, currents, inundation areas and tsunami propagation in the Adriatic Sea.

How to cite: Kapitanovic, V., Sepic, J., Pasaric, M., and Heidarzadeh, M.: Numerical modelling of the Montenegro tsunami of 15 April 1979, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14980, https://doi.org/10.5194/egusphere-egu24-14980, 2024.

EGU24-15140 | Orals | NH5.1

The 19 May 2023 tsunami near the Loyalty Islands captured by the new SWOT satellite 

Yannice Faugère, Jean Roger, Antoine Delepoulle, Gerald Dibarboure, and Helene Hebert

During the last decades, trans-oceanic tsunamis have been captured by satellite altimeters on several occasions. The largest event ever measured by an altimeter was the 2004 Indian Ocean tsunami, captured by Jason-1, Topex/Poseidon, GFO and Envisat altimetry missions flying at that time 

 

The new altimetry mission SWOT (Surface Water and Ocean Topography) developed by NASA and CNES, the US and French Space agency respectively, was launched in December 2022. SWOT embarks a novel instrument, a Ka-band Radar INterferometer (KaRIN), providing a 120 km wide swath Sea Level. On 19 May 2023, SWOT was able to measure the tsunami generated by the Mw 7.7 earthquake which occurred southeast of the Loyalty Islands (southwest Pacific Ocean) at 02:57:03 (UTC). SWOT flew over the region about 1 hour after the earthquake and captured the tsunami signature in several locations. For the first time, a 2D mapview image of the height of tsunami wavetrain was measured by a satellite.

 

The tsunami generation and propagation have been simulated using COMCOT model, using source parameters derived from seismic observations and empirical laws. Preliminary simulation results show that a simple fault plane with uniform coseismic slip allows to reproduce the regional coastal gauge and oceanic DART station records with a relatively good level of confidence, considering that the earthquake rupture was strongly not-double couple according to USGS. An array of virtual gauges was designed to cover the satellite pathway, allowing to extract the dynamic representation of the tsunami wavefield corresponding to the satellite propagation time (i.e., the sea surface deformation is observed over a period of time of several minutes, instead of being static at a given time). Comparison between the SWOT sea surface measurement and the simulation result is satisfactory, showing a good agreement between the location of the first wave peaks (propagating toward the southwest and the northeast, respectively), their amplitude and phase.

 

The objective of this study is first to present this unprecedented observation, and to analyze the level of consistency with simulations.

How to cite: Faugère, Y., Roger, J., Delepoulle, A., Dibarboure, G., and Hebert, H.: The 19 May 2023 tsunami near the Loyalty Islands captured by the new SWOT satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15140, https://doi.org/10.5194/egusphere-egu24-15140, 2024.

EGU24-15775 | ECS | Posters on site | NH5.1

High-Resolution Tsunami Simulations including Land Use-Dependent Variable Friction Along Puerto Rico's Coast 

Carlos Sánchez-Linares, Jorge Macías Sánchez, Hernán Porras, and Víctor Huérfano

This study integrates high-resolution tsunami simulations with land use-dependent variable friction across the entire coastal region of Puerto Rico. By using the Tsunami-HySEA model, developed by the EDANYA Research group at the University of Malaga, this research transcends traditional practices, exploring the interplay between terrain characteristics and tsunami dynamics through the incorporation of variable friction. The execution of high-resolution simulations covering the entire coast of Puerto Rico represents a computational and scientific challenge unprecedented in prior research, reinforcing the applicability of this study.

Computational topo-bathymetric grids are constructed to create a coherent model, smoothing irregularities in topo-bathymetric data. Provided by the Puerto Rico Seismic Network, these data have been processed for optimized numerical simulations. The study employs five sets of nested grids, corresponding to different regions (Northeast, Northwest, East, West, and South) of Puerto Rico, and within each configuration, four nested grids with resolutions ranging from 480 meters to 7.5 meters facilitate simulations with varying levels of detail. This strategy optimizes computational resources and ensures precise results in specific coastal areas. The high-resolution discretization, at 7.5 meter per pixel, spans the entire 1,100 km coastline of Puerto Rico. Additionally, simulations have been conducted for 29 distinct seismic sources, comparing this approach to the traditional constant friction approach with Manning coefficient set at 0.03.

The influence of the Manning coefficient is evident in its effects on velocities, momentum flux, and, on the inundation area extension. Understanding the different land uses is crucial for accurately analyzing the effects of a tsunami on the coast and predicting the magnitude of the resulting inundation. The topography, vegetation, and structures built in coastal areas can significantly modulate wave propagation and water depth inland. Identifying these variations in land uses allows for a more precise planning of tsunami mitigation and response measures, as well as a detailed assessment of vulnerable areas.

Acknowledges
This contribution was supported by the Center of Excellence for Exascale in Solid Earth (ChEESE-2P) funded by the European High Performance Computing Joint Undertaking (JU) under grant agreement No 101093038 and by the EU project “A Digital Twin for Geophysical Extremes” (DT-GEO) (No: 101058129). The authors thankfully acknowledges the computer resources at CTE-Power and the technical support provided by Barcelona Supercomputing Center (AECT-2023-3-0017 - Tsunami Hazard Assessment for Puerto Rico. A first study of variable friction coefficient with Tsunami-HySEA)

How to cite: Sánchez-Linares, C., Macías Sánchez, J., Porras, H., and Huérfano, V.: High-Resolution Tsunami Simulations including Land Use-Dependent Variable Friction Along Puerto Rico's Coast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15775, https://doi.org/10.5194/egusphere-egu24-15775, 2024.

EGU24-16049 | Posters on site | NH5.1

  Tsunami Simulation and Seismic Source Characterization: A Case Study of the March 18, 2021 Offshore Bejaia Earthquake (Mw 6.0) in the Western Mediterranean 

Philippe Heinrich, Aurélien Dupont, Marine Menager, Aurélie Trilla, Audrey Gailler, Bertrand Delouis, and Hélène Hebert

On March 18, 2021, a magnitude Mw 6.0 earthquake occurred offshore the Algerian coasts near Bejaia, resulting in a tsunami with offshore amplitudes smaller than a few millimeters that crossed the western Mediterranean Sea. This study pursues three primary objectives: firstly, to assess the ability of tsunami simulations to replicate tide-gauge observations; secondly, to ascertain the relevance of seismic sources calculated within the context of tsunami early warning systems, against tsunami generation and observations; and thirdly, to evaluate the sensitivity of simulations to grid resolutions and earthquake parameters.
Within the Mediterranean Sea, only a limited number of coastal tide gauges recorded the tsunami. Among these, select French tide gauge stations captured water waves with amplitudes smaller than a few centimeters and periods ranging from five to twenty minutes, often associated with harbor or bay resonances.
Numerical simulations of the tsunami were conducted utilizing the operational code Taitoko employing six distinct source fault models. Notably, two of these models provided rapid source detection and characterization within the framework of tsunami warning systems at CENALT (Centre National d’Alerte aux Tsunamis, France). The integrated code Taitoko employs a system of multiple nested grids. For this event, it solved standard Boussinesq equations within the Mediterranean grid, while employing nonlinear shallow water equations in coastal and harbor grids, each with resolutions of 25 and 5 meters, respectively. Regardless of the fault model employed, the model satisfactorily reproduced the observed time series of water heights in both phase and amplitude at Nice and Monaco, while some discrepancies are found and discussed for most of the other locations.

How to cite: Heinrich, P., Dupont, A., Menager, M., Trilla, A., Gailler, A., Delouis, B., and Hebert, H.:   Tsunami Simulation and Seismic Source Characterization: A Case Study of the March 18, 2021 Offshore Bejaia Earthquake (Mw 6.0) in the Western Mediterranean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16049, https://doi.org/10.5194/egusphere-egu24-16049, 2024.

EGU24-16257 | ECS | Orals | NH5.1

Influence of spatially correlated noise in the generation of meteotsunamis in Ciutadella 

Joan Villalonga, Patrick Marsaleix, Damià Gomis, and Gabriel Jordà

Meteotsunamis are sea waves with frequencies ranging from 2 minutes to 2 hours (the same frequency band than seismically generated tsunamis) that are generated by high frequency atmospheric perturbations. Extreme meteotsunamis can cause high frequency sea level oscillations of a few meters at the coast which are dangerous for coastal populations. The meteotsunami generation involves both the amplification of the inverse barometer response by Proudman resonance and also harbour resonance. For this reason, meteotsunami generation is highly dependent on the bathymetric and topographic characteristics of the basins, some of them being more suitable than others for the meteotsunamis occurrence. This is the case of the Ciutadella harbour, in the Balearic Islands (Western Mediterranean), where several meteotsunamis of >1 meter of amplitude (difference in the sea level elevation between consecutive maximum and minimum) occur every year. This hotspot for meteotsunamis has been studied for four decades and several forecasting systems have been implemented in the region. However, the accuracy of those systems, in particular in terms of predicting the amplitude at the coast, is still limited.

In a previous work (Villalonga et al., 2022), a new set of ultra dense atmospheric observations allowed a detailed characterization of the atmospheric disturbances generating meteotsunamis.  We found that these disturbances are highly heterogeneous both in time and space, and that heterogeneity is very difficult to reproduce with atmospheric models. With the aim of understanding what is the impact of that heterogeneity in the final meteotsunami amplitude, we have conducted several experiments with the SYMPHONIE model (Estournel et al., 2021). The model has been configured to cover the whole Balearic Islands with a variable spatial resolution reaching up to 5 meters inside Ciutadella harbour. It has been forced with different kinds of atmospheric disturbances, namely analytical functions and observed time series with tuneable propagation velocities over the model’s domain. Random noise with different spectral and spatial characteristics has also been added.

The model has been able to accurately reproduce the amplitude and spectra of real meteotsunamis events when forced with the observed atmospheric pressure time series. We have also tested the sensitivity of the model outputs to different model configurations by changing the friction parameters and comparing 2D to 3D simulations. The results suggest that 3D simulations provide a more realistic energy dissipation by friction, particularly in the higher frequencies. Finally, the experiments forcing the model with random spatially correlated noise have allowed understanding the impact of atmospheric spatial heterogeneities. In particular, the results show that the size of the random structures is a key parameter that determines the amplification of sea level oscillations. Namely,  the structures with a spatial scale of 10-30 km generate more signal amplification than larger structures.

All in all, these simulations have provided new results that will allow a better understanding of the generation of meteotsunamis in the Balearic Islands and the limits of their predictability.

 

How to cite: Villalonga, J., Marsaleix, P., Gomis, D., and Jordà, G.: Influence of spatially correlated noise in the generation of meteotsunamis in Ciutadella, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16257, https://doi.org/10.5194/egusphere-egu24-16257, 2024.

EGU24-16261 | Orals | NH5.1 | Highlight

A 21 km SMART Cable for earthquakes and tsunami detection operating in the Ionian Sea 

Giuditta Marinaro, Salvatore D'Amico, Davide Embriaco, Alessandra Giuntini, Francesco Simeone, John O'Neill, Bruce Nicholson, Neil Watkiss, and Federica Restelli

Continuous seismic and environmental monitoring at remote seabed sites always faced a major challenge due to technical, logistical and financial effort. Commercial Telecommunication submarine cables continuously expand the coverage of ocean seafloor following society's needs to increase connectivity between distant countries and remote sites. Cables over thousands of kilometres long are equipped with in-line repeaters which compensate for optical losses due to  such long distances. 

A Science Monitoring And Reliable Telecommunications (SMART) Subsea Cables, designed by a Joint Task Force (JTF) across the International Telecommunication Union, World Meteorological Organization, the UNESCO Intergovernmental Oceanographic Commission,  may host, inside repeaters, scientific sensors for seismic, ocean and climate monitoring and disaster risk reduction in cases of tsunamis. 

The recent successful deployment at the Western Ionian Sea, one of EMSO (European Multidisciplinary Seafloor and water column Observatory) Regional Facilities, of the InSEA Wet Demo SMART Cable displays a world first demonstrating the feasibility of such installation using standard cable-laying techniques to show proof of concept. Commercial viability for these systems relies on the cable being laid as if the scientific element did not exist, thereby minimising additional deployment costs and reducing barriers to cooperation with cable laying companies. Güralp Systems Ltd and INGV deployed three seismometer-accelerometer pairs housed in inline repeaters along the 21km cable long. Each repeater also provides temperature and pressure devices which respectivley enable the real time monitoring of sea environment state and of sea surface level for tsunami detection.

This pioneering installation demonstrates the feasibility of smart cable initiative which may lead to global coverage of ocean seafloor with a network of scientific sensors enabling the  real time monitoring of seismicity and tsunami events at remote locations thanks to a collaboration between scientific and commercial parties.

How to cite: Marinaro, G., D'Amico, S., Embriaco, D., Giuntini, A., Simeone, F., O'Neill, J., Nicholson, B., Watkiss, N., and Restelli, F.: A 21 km SMART Cable for earthquakes and tsunami detection operating in the Ionian Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16261, https://doi.org/10.5194/egusphere-egu24-16261, 2024.

 After the dense observation network for earthquakes and tsunamis along the Japan trench (S-net) was available, the tsunami data assimilation became a powerful technique to compute tsunamis in real-time. However, a problem exists for this technique to forecast tsunamis in real-time because the observation data near the source area are always unstable as shown in the 2016 Fukushima earthquake. Therefore, the data near the source area may not be available for real-time tsunami forecast.

 In this paper, we try to solve this problem by combining the tsunami data assimilation with the source estimation using real-time GNSS observation such as REGARD. We tested our method for two cases, the 2016 Fukushima earthquake case and the 1896 Sanriku earthquake case. We first computed the tsunamis from the source models estimated by Kubota et al. (2021) for the 2016 Fukushima case and that estimated by Satake et al. (2017) for the 1896 Sanriku earthquake case as reference tsunamis. We used those commuted data at stations of S-net as observation data without the stations near the source area. Then the tsunami data assimilations with and without the rectangular fault model are performed.

 The result of the 2016 Fukushima case shows that the tsunami data assimilation worked well although the quickly estimated rectangular fault model using the GNSS observation data was not acceptable for the tsunami simulation. The result of the 1896 Sanriku case shows that the tsunami data assimilation with the estimated rectangular fault forecast the acceptable tsunami waveforms along the coast about 20 minutes faster that that without the rectangular fault. This improvement is significant, so our method can be used as a real-time tsunami forecast technique even the tsunami data near the source area will not be available.  

References

Kubota, et al. (2021). Improving the constraint on the Mw 7.1 2016 off-fukushima shallow normal-faulting earthquake with the high azimuthal coverage tsunami data from the s-net wide and dense network: Implication for the stress regime in the tohoku overriding plate. Journal of Geophysical Research: Solid Earth126(10), 79. https://doi.org/10.1029/2021jb022223

Satake, K., Fujii, Y. & Yamaki, S. (2017) Different depths of near-trench slips of the 1896 Sanriku and 2011 Tohoku earthquakes. Geosci. Lett. 4, 33. https://doi.org/10.1186/s40562-017-0099-y

How to cite: Tanioka, Y. and Atobe, Y.: Rapid and Accurate Tsunami Forecast Method Using Tsunami Data Assimilation with Real-time Source Estimation., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17432, https://doi.org/10.5194/egusphere-egu24-17432, 2024.

EGU24-17621 | Orals | NH5.1

Scenario-based Probabilistic Tsunami Risk Analysis for Coquimbo Bay 

Fatemeh Jalayer, Hossein Ebrahimian, Patricio Catalan, Natalia Zamora, and Saeed Soltani

Scenario-based tsunami risk assessment provides valuable insights into the socio-economic consequences of a specific scenario. Although it is focused on a specific scenario or a range of scenarios, this type of analysis can still encompass uncertainty characterisation. 

Hazard: Focusing on Coquimbo Bay, which was affected by the 2015 Ilapel tsunami, we demonstrate how the uncertainties are quantified and propagated from the tsunami source level all the way towards risk metrics such as the economic losses.  We have chosen a range of near-field tsunami scenarios with moment magnitude between 8.6 <Mw <9.3 from a subduction interface zone on the Nazca–South American plate interface running parallel to the Chilean coastline. We have worked with a large set of stochastic scenarios generated compatible with the scaling laws, with variable slip distribution according to a prescribed correlation structure. We have estimated the seismicity rate through different sources: paleo seismic data, historical catalogue, and moment balancing and have combined the resulting probability distributions through a logic tree approach. The weights of the logic tree are assigned through a Bayesian model class selection procedure as related to the log-evidence calculated for each model. This will lead to scenario-based hazard curves with confidence intervals for different points of interest in the port city of Coquimbo.

Vulnerability: Based on the exposure model for Coquimbo, we have identified two different pre-dominant building categories in Coquimbo, namely the low-rise mixed (wood and masonry) building type and the high-rise residential buildings. For the first category, we have used empirical fragility curves for a similar building type in Dichato and damaged by the Chile 2010 and have characterised the epistemic uncertainty for these fragility curves. We have derived the vulnerability curves and their confidence band through convolution of the fragility curves and the consequence models. 

Risk: We demonstrate how hazard and vulnerability curves and their confidence intervals can be convolved to obtain loss curves for certain locations of interest and how this information can be processed to derive scenario-based risk maps for Coquimbo for different return periods. 

We conclude by demonstrating the importance of a thorough characterization of uncertainties and their propagation from the tsunami source towards the estimation of the economic losses. This provides important insights about the relative sensitivity of tsunami risk to different sources of uncertainty.

 

How to cite: Jalayer, F., Ebrahimian, H., Catalan, P., Zamora, N., and Soltani, S.: Scenario-based Probabilistic Tsunami Risk Analysis for Coquimbo Bay, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17621, https://doi.org/10.5194/egusphere-egu24-17621, 2024.

EGU24-18134 | Posters on site | NH5.1

An expert-based framework for susceptibility analysis for tsunamigenic landslides in Indonesia 

Anika Braun, Katrin Dohmen, and Tomas Manuel Fernandez-Steeger

Landslides can induce extremely high tsunami waves, reaching several tens of meters. These tsunamis typically impact only localized areas within about 100 km of the landslide. The most significant impact is generated in the immediate proximity to the landslide. Due to the short time between wave initiation and reaching the coast, early warning systems for these events have not yet been developed. This study aims to assess the exposure of particular regions to this specific form of tsunami with a focus on the Indonesian coastline. The approach not only evaluates the potential for the occurrence of landslides but also assesses whether there is a potential for the formation of particularly high tsunami waves, e.g. due to reflection or superposition of waves.

The limited number of known landslides that have triggered tsunamis in the past is not sufficient to enable a data-driven analysis. Hence, a heuristic approach is adopted in this study. It consists of the following 4 steps.

(1) Orientation workshop: A group of international scientists working on landslides and tsunamis discusses and selects parameters that might be relevant for the analysis.

(2) Online survey: The parameters selected in step (1) are ranked by a larger group of scientists.

(3) Result workshop: The survey results are discussed in another workshop.

(4) Susceptibility analysis: The parameter ratings from the online survey are transformed into a model for tsunamigenic landslide susceptibility evaluation and a susceptibility analysis for a pilot area in Indonesia is conducted.

During the orientation workshop, 37 parameters were selected to be considered for the susceptibility analysis. As part of the online survey, these were evaluated by a total of 25 scientists working on landslides and tsunamis. For landslide susceptibility in Indonesia, subaerial and submarine slope angle, presence of oversteeped slopes, landform, lithology, presence of lowly consolidated sediments, distance to active tectonic faults, depth and magnitude of historic earthquakes, precipitation, and pore water pressures were voted as crucial parameters. The work on this study is still ongoing and step (4) is planned to be conducted in the future.

The results of tsunamigenic landslide susceptibility mapping can aid local officials in elaborating mitigation measures for this type of tsunami. Even minor earthquakes in these areas could trigger landslides, creating waves despite not typically causing seismic tsunamis. Hence, it might be necessary to adapt land-use and evacuation plans in at-risk regions to account for both seismic and landslide-induced tsunamis. The limited availability of high-resolution data representing the submarine environment is the main obstacle, which hampers a deeper analysis of submarine landslide susceptibility and the potential for tsunami wave generation. Future efforts must be made to close this data gap and enable effective protection of coastal populations from landslide-induced tsunamis.

How to cite: Braun, A., Dohmen, K., and Fernandez-Steeger, T. M.: An expert-based framework for susceptibility analysis for tsunamigenic landslides in Indonesia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18134, https://doi.org/10.5194/egusphere-egu24-18134, 2024.

EGU24-18892 | Posters on site | NH5.1

Optimal positioning of two deep ocean bottom pressure gauges for tsunami wave detection in the western Ionian Sea 

Fabrizio Romano, Stefano Lorito, Alessio Piatanesi, Manuela Volpe, Hafize Basak Bayraktar, Nikos Kalligeris, and Alessandro Amato

Tsunami warning and forecasting largely benefit from using offshore bottom pressure gauges (OBPG); these sensors, installed far offshore and typically close to causative sources, can measure the tsunami waves before reaching the coasts to maximize the lead time for alerting. Most of these sensors are installed around the Pacific Ring of Fire (e.g., DART buoys, S-NET), which hosts ~90% of the global seismicity and most significant tsunamigenic earthquakes. Even though less frequent than in the Pacific Ocean, tsunamigenic earthquakes can also occur in the Mediterranean Sea (e.g., the M8+ 365 AD in Crete or the M7 2020 Samos earthquakes), in which the Ionian Sea is characterized by relatively high tsunami hazard (Basili et al., 2021). However, offshore sensors are not present in the Mediterranean Sea and the Tsunami Service Providers operating in the basin (CAT-INGV for Italy, NOA for Greece, KOERI for Türkiye, and CENALT for France) can rely for the tsunami monitoring activities only on the coastal tide gauges networks. One of the objectives of the Italian MEET project (MONITORING EARTH'S EVOLUTION AND TECTONICS), in the framework of the National Recovery and Resilience Plan (PNRR) funded by EU, is the deployment of two OBPGs offshore the Italian coasts. To maximize the lead time gain and due to the high cost of the instruments (including both the maintenance and installation), a careful analysis of the optimal locations where to deploy these instruments is required.

Here, we present the results of the study carried out to identify the more suitable locations to deploy two OBPGs offshore the Ionian coasts of southern Italy. The method proposed considers an ensemble composed of more than 150k scenarios selected from the NEAMTHM18 source model; these scenarios are the ones capable of causing at least a 20 cm tsunami height in front of the Ionian coasts of Italy. For each scenario, we compute i) the tsunami detection times for each point within a target area (i.e., more than 200 possible locations) where the OBPG deployment is envisaged, and ii) the tsunami detection times at all tide-gauges on the coasts of the Ionian Sea. The optimal location for the two OBPGs is established by minimizing a cost function which is a summation of the minimum travel times, for each potential tsunami source, to all available existing coastal gauges and all the potential pairs of OBPGs, weighted by the rate of occurrence of each individual source according to NEAMTHM18.

 

Basili et al. (2021). The Making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18). Front. Earth Sci. 8:616594, doi: 10.3389/feart.2020.616594

How to cite: Romano, F., Lorito, S., Piatanesi, A., Volpe, M., Bayraktar, H. B., Kalligeris, N., and Amato, A.: Optimal positioning of two deep ocean bottom pressure gauges for tsunami wave detection in the western Ionian Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18892, https://doi.org/10.5194/egusphere-egu24-18892, 2024.

EGU24-19130 | Posters on site | NH5.1

Tsunami source reconstructed from runup time-series 

Ira Didenkulova, Cesare Angeli, Alberto Armigliato, and Efim Pelinovsky

The study of long wave runup is a classical problem in fluid dynamics, in both linear and nonlinear formulations. However, little attention has been given to the inverse problem, i.e. the reconstruction of the initial condition from a known runup time history.

According to the piston model of tsunami generation, the problem can be modelled as an initial value problem with assigned initial water surface displacement and zero velocity. In this framework, the solution of the linear problem, i.e. the runup as a function of time, can be written as the convolution of the initial water surface with an Abel kernel. This solution can be analytically and uniquely inverted, obtaining the initial wave surface as a functional of the runup function.

In this work, this solution is applied to analytically generated runup time series and its properties are analyzed. In particular, the robustness of the solution to added noise is verified and the effect of nonlinearity is investigated through the use of a Riemann transform of the coordinates.

How to cite: Didenkulova, I., Angeli, C., Armigliato, A., and Pelinovsky, E.: Tsunami source reconstructed from runup time-series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19130, https://doi.org/10.5194/egusphere-egu24-19130, 2024.

EGU24-19260 | ECS | Orals | NH5.1

Modeling tsunami generation and propagation: Insights from sensitivity analysis of landslide parameters at Stromboli 

Matteo Trolese, Matteo Cerminara, Tomaso Esposti Ongaro, Mattia de' Michieli Vitturi, and Alessandro Tadini

Understanding the generation of tsunamis from landslides at volcanic islands is crucial due to their infrequent, yet potentially catastrophic, impact on coastal communities. We present a sensitivity analysis of the effects of different rheological and geometrical landslide parameters on the generation and propagation of tsunamis in the near field. In particular, we employed the MultiLayer-HySEA model to simulate tsunamis generated by landslides occurring along the northwestern flank of the Stromboli volcano, specifically in the area known as Sciara del Fuoco, which is considered most prone to instability. This shallow-water model implements a two-way coupling between a granular material layer representing the landslide and 3 fluid layers representing the water. The parameters investigated include the initial position, density, volume, and shape of the landslide, as well as its friction angles and water-landslide friction coefficients. We varied each landslide parameter to examine its effect on the tsunami wave height and energy at specific locations. We found that the principal parameters of the synthetic waveforms and the landslide volumes are logarithmically correlated when considering subaerial landslides, while they correlated linearly when considering submarine landslides. We than explored the effect of the other source parameters on such analytical relationships. Based on the variability observed in waveform characteristics, we suggest a ranking of importance for the source characteristics that contribute significantly to the uncertainty/variability of the model output. Our study aligns with previous predictions at Stromboli and offers a valuable tool for reconstructing the source parameters of tsunamis based on proximal sea-level measurements, enabling rapid forecasting of subsequent impacts around the volcanic island.

How to cite: Trolese, M., Cerminara, M., Esposti Ongaro, T., de' Michieli Vitturi, M., and Tadini, A.: Modeling tsunami generation and propagation: Insights from sensitivity analysis of landslide parameters at Stromboli, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19260, https://doi.org/10.5194/egusphere-egu24-19260, 2024.

EGU24-19584 | ECS | Posters on site | NH5.1

Effect of volcanic islands offshore morphology on the tsunami generation and hazard extent from coastal cliff-failures. 

Inês Ramalho, Rachid Omira, and Jihwan Kim

Mass-wasting events on volcano islands flanks are a recognized source of tsunami. Nonetheless, little is known about the failure mechanisms, dynamics that lead to the wave formation and the tsunami extent when the displaced material plunges into the sea and moves downslope. Owing to the lack of direct and instrumental observations, the main indicator of tsunamigenesis for mass-wasting events is the volume of the failure material, often inferred from mass transport deposits offshore and/or collapse scars onshore.

This work addresses the influence of islands offshore morphology on the formation and hazard extent of tsunamis triggered by coastal cliff-failures. Particularly, we explore two common coastal morphologies of ocean volcanic islands: a volcanic island with and without insular shelves. We seek to better understand how the presence of these shallow submarine platforms constrains the dynamics of the collapses and, consequently, the tsunami generation and its hazard extent. To this end, we performed numerical simulations using different morphologic configurations and landslide volumes and allowing to simulate and analyse the formed tsunami energy (both potential and kinetic). The results show that, for the same coastal cliff-failure volume, the islands offshore morphology highly influence the tsunami generation and hazard extent. We found that tsunamis forming on islands with insular shelves have initial solitary-like waveshape with relatively short wavelength, while those on islands without shelves show N-wave shape with longer wavelength. The latter have higher energy, both potential and kinetic, allowing the tsunami to travel away from the shore and cause larger hazard extent than those occurring on islands without shelves. Our results demonstrate that offshore island morphology is a particularly determining factor in the dynamics of collapsed sectors and, therefore, on their tsunamigenesis and hazard extent.

This work is supported by projects MAGICLAND (PTDC/CTA-GEO/30381/2017) and HAZARDOUS (PTDC/CTA-GEO/0798/2020) FCT-funded projects. This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020).

How to cite: Ramalho, I., Omira, R., and Kim, J.: Effect of volcanic islands offshore morphology on the tsunami generation and hazard extent from coastal cliff-failures., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19584, https://doi.org/10.5194/egusphere-egu24-19584, 2024.

EGU24-20633 | Orals | NH5.1

The Impact of Volcano-Generated Tsunamis on the Safety of Moored Vessels: The 2022 Tonga Incident. 

Sergio Padilla Álvarez, Iñigo Aniel Quiroga, Mauricio Gonzalez, Rachid Omira, Jihwan Kim, and Maria Ana Baptista

The atmospheric tsunami resulting from the eruption of the Tonga volcano on January 15, 2022 (Tonga22) marked an unprecedented occurrence, encompassing a Volcano-Meteorological Tsunami (VMT) with global ramifications. This study examines the comprehensive effects of Tonga22 on moored vessels, employing a spectral and hydrodynamic analytical framework. The aftermath of the event, including edge waves, resonance phenomena, and wave amplification in specific regions such as La Pampilla port in Peru, revealed substantial maritime challenges. Notably, a vessel in La Pampilla reported the rupture of mooring ropes, a remarkable incident occurring 10,000 kilometers away from the Tonga volcano, manifesting 15 hours post-eruption and resulting in the spillage of over 11,000 barrels of crude oil.

Our research aims to contribute to a nuanced understanding of the Tonga22 event by employing advanced spectral and hydrodynamic analyses. The primary focus lies in assessing its impact on mooring loads within the complex marine port environment. We postulate that atmospheric acoustic waves, a consequence of the volcanic eruption, pose hydrodynamic threats to vessels in port areas, potentially leading to mooring breakage.

Utilizing the Boussinesq model, validated at the local scale in Callao Bay, we establish a foundation for our mooring system model. This model, applied to a vessel analogous to the one docked at La Pampilla Port, aims to discern the nuanced influence of VMT on overstressing and mooring breakage during the Tonga22 event.

Our simulation results underscore the pivotal role of VMT in the displacement and loss of positioning of vessels. Moreover, atmospheric waves are revealed to significantly elevate mooring stresses, with a particular emphasis on the starboard quarter moorings in this specific case.

This research sheds light on a critical realization—the Tonga22 event highlights the inadequacies of existing tsunami early warning systems (TWC) in detecting and managing tsunamis induced by acoustic waves originating from volcanic sources. These findings contribute to the ongoing discourse on maritime safety and hazard preparedness.

How to cite: Padilla Álvarez, S., Quiroga, I. A., Gonzalez, M., Omira, R., Kim, J., and Baptista, M. A.: The Impact of Volcano-Generated Tsunamis on the Safety of Moored Vessels: The 2022 Tonga Incident., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20633, https://doi.org/10.5194/egusphere-egu24-20633, 2024.

Forecasting the impact of a tsunami on coastal areas requires accurate location of the source of the tsunami. This is particularly challenging because tsunamis often originate far from seismological and geodetic networks. However, tsunami waves often induce total electron content (TEC) perturbations in the ionosphere, which can be detected using Global Navigation Satellite Systems (GNSS). Tracking the source of these perturbations makes it possible to determine the tsunami source area. Previous studies have confirmed this approach. However, this is usually done by (1) using a "quasi-homogeneous" model to propagate the disturbances in the atmosphere and (2) arbitrarily fixing the height of the ionosphere. These approximations lead to relatively large uncertainties in the location of the tsunami source. Therefore, in this study we try to reduce these uncertainties by using a 1D model of the atmospheric structure and by including the search for the optimal height of the ionosp here in the inverse problem. To do this, we use a Bayesian approach to invert the onset times of the TEC disturbances. First, we test our method on synthetic data to determine the potential gain in accuracy between using a "quasi-homogeneous" and a 1D model of the atmosphere. We then apply our approach to study the 2010 M7.7 Mentawai tsunami earthquake and discuss the strength and limitations of the method as well as its usability for tsunami warning. We finally show preliminary results for the 2024 M7.5 Noto peninsula earthquake, and related tsunami offshore Japan.

How to cite: Twardzik, C., Rolland, L., Munaibari, E., and Mikesell, T. D.: Constraining the tsunami initiation area associated with the 2010 M7.7 Mentawai and 2024 M7.5 Noto peninsula earthquakes from first-arrival measurements on TEC data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21337, https://doi.org/10.5194/egusphere-egu24-21337, 2024.

EGU24-22502 * | Orals | NH5.1 | Highlight

Characteristics of the 2024 Noto Earthquake and Tsunami occurred in the Eastern Margin of the Japan Sea 

Yuichiro Tanioka and Yusuke Yamanaka

On January 1, 2024, a large earthquake (Mw7.6) occurred along the northern coast of the Noto Peninsula, Japan. Because the faults of the earthquakes were located beneath both land and sea, the large strong motion and tsunami were generated and caused severe disasters near the source area. More than 200 people were killed by the earthquake.

The earthquake occurred on the Eastern Margin of the Japan Sea where several great earthquakes and tsunamis occurred previously such as the 1993 Hokkaido Nansei-oki earthquake (Mw7.8), the 1983 Japan Sea earthquake (Mw7.7), and the 1964 Niigata earthquake (Mw7.6), The 2024 Noto earthquake also occurred on the same Eastern Margin of the Japan Sea where a large number of submarine active faults were identified by the undersea structure surveys and also the GNSS surveys indicted a convergence rate of approximately 1cm/year along the margin. 

The aftershock activity and the seismological analysis by the Japan Meteorological Agency (JMA) and the co-seismic deformation analysis using GNSS data by the Geospatial Information Authority of Japan (GSI) of the 2024 Noto earthquake showed that the fault length is about 150 km. Particularly, a northeast part of the fault was extended to the Japan Sea where the Noto peninsula was terminated. The co-seismic deformation due to the faulting generated a large tsunami observed at several tide gauges along the Japan Sea coast.

How to cite: Tanioka, Y. and Yamanaka, Y.: Characteristics of the 2024 Noto Earthquake and Tsunami occurred in the Eastern Margin of the Japan Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22502, https://doi.org/10.5194/egusphere-egu24-22502, 2024.

EGU24-22527 | Posters on site | NH5.1

The 2004 Noto Peninsula Earthquake Tsunami - It's Generation, Propagation, Inundation, and Impact 

Shunichi Koshimura, Bruno Adriano, Ayumu Mizutani, Erick Mas, Yusaku Ohta, Shohei Nagata, Yuriko Takeda, Ruben Vescovo, Sesa Wiguna, Takashi Abe, and Takayuki Suzuki

The tsunami was generated by the Mw7.6 Noto Peninsula Earthquake and left widespread impact. After the event occurred, we modeled the tsunami propagation and coastal inundation with various tsunami source models and discussed its propagation and inundation features.


Preliminary tsunami modeling results imply that the impacts were severe around Noto Peninsula (Shika to Nanao). Specific bathymetric features of the continental shelf of Noto Peninsula were responsible for high tsunamis in Suzu City. The directivity of tsunami energy was also toward the Japan Sea coasts, especially Joetsu City, Nigata Prefecture. Early tsunami arrival at Toyama City with the leading negative wave could not be explained by fault rupture. The post-tsunami field survey teams at Suzu City preliminarily found tsunami run-ups of 3 m or higher with flow depths of 2.5m or higher. Inside the tsunami inundation zone around Noto Peninsula, we found at least 648 houses were destroyed by both the strong ground motion and tsunami.

How to cite: Koshimura, S., Adriano, B., Mizutani, A., Mas, E., Ohta, Y., Nagata, S., Takeda, Y., Vescovo, R., Wiguna, S., Abe, T., and Suzuki, T.: The 2004 Noto Peninsula Earthquake Tsunami - It's Generation, Propagation, Inundation, and Impact, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22527, https://doi.org/10.5194/egusphere-egu24-22527, 2024.

The need to stabilise and protect beaches and coastlines is important due to the increasing recreational activities in the coastal zone. In Taiwan, the coastal area is hit by about four typhoons a year, and the large waves caused by the typhoons often lead to coastal disasters and beach erosion. The beach could also be the buffer zones against the large wave attack and coastal flooding and erosion. Although the gravel beaches have a great advantage over the sandy beaches in terms of energy absorption capacity, this advantage disappears under the strong wave attack during the typhoon season in Taiwan. The gravel is carried offshore, and it is difficult to return to the beach under the swell wave. During the extreme wave induced in typhoon conditions associated with storm surge, it causes gravel beach closer to the steep nearshore zone, which may then be irreversibly evacuated downslope. The extreme waves bring breaking waves high up on the beach, creating the step-reflecting berms. Energy reflection can thus contribute to further downslope transport of gravel to depths from which it can no longer be recovered by fair-weather waves. The gravel beach can be very steep, accompanied by a typically narrow surf zone and an energetic shore break.

The FuAng coast in the south of Taiwan has suffered severe beach erosion since the construction of breakwaters in 2015. The strong reflection creates partial standing waves that scour the sediment at the toe of the beach. In addition, the mixed sand and gravel beach is washed offshore during storms and cannot be brought back to the beach by the weak swell wave. The aim of this paper is to analyse the erosion problem using the shoreline evolution from the satellite images, the variation of the beach profile in several sections and the volumetric variation of the bathymetry. An integrated coastal protection countermeasure using submerged detached breakwaters with artificial beach nourishment is proposed to mitigate the beach erosion problem. Physical experiment and numerical simulation are used to verify the proposed countermeasure. The results show that the proposed method can effectively protect the coast, prevent the beach erosion and form a salient to be a good buffer zone to prevent the wave impact.

How to cite: Hsu, H.-C.: Morphological variation of the beach under the construction of submerged breakwaters-a case study in Pintung coastal area of Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-191, https://doi.org/10.5194/egusphere-egu24-191, 2024.

EGU24-1128 | ECS | Posters on site | NH5.3

Coastal vulnerability assessment in the central Mediterranean area: A case study of the Maltese coast 

Nabanita Sarkar, Angela Rizzo, Vittoria Vandelli, and Mauro Soldati

Coastal areas are primarily exposed to a range of coastal hazards, including both climate- and marine-related processes, due to their close proximity to the sea. In this context, the Maltese Islands, located in the centre of the Mediterranean Sea, are prone to be affected by various coastal risks in the form of erosion, flooding, landslides, storm surges and, on a longer-term, permanent inundation as a consequence of the ongoing sea level rise. These Islands have evolved over time from a complex interplay of marine, morphodynamic and tectonic processes resulting in highly diversified coastal landforms and scenic landscapes.

Considering primary and secondary data sources, this study investigates the coastal vulnerability of the north-west coast Malta with respect to a series of hazardous processes by applying an index-based approach supported by extensive field surveys. This stretch of coastal area attracts a large number of visitors each year, raising serious concerns about coastal vulnerability, thus, challenging sustainable management of coastal touristic assets.  In the first phase of this research, a set of indicators pertaining to the local land use, anthropogenic, and natural assets were used in order to estimate the level of coastal exposure. The following phase entailed the zonation of the areas exposed to rock falls, and storm surges, erosion and sea level rise, which enabled us to estimate the overall coastal vulnerability. The results show that the bay areas of the north-west coast of Malta dominated by tourist activities can be considered as the most vulnerable zones and targets of different climate- and marine-related impacts. These are the areas where it would be challenging to prevent future impacts if no adaptation and sustainable management strategies are taken into account.

How to cite: Sarkar, N., Rizzo, A., Vandelli, V., and Soldati, M.: Coastal vulnerability assessment in the central Mediterranean area: A case study of the Maltese coast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1128, https://doi.org/10.5194/egusphere-egu24-1128, 2024.

EGU24-1641 | ECS | Posters on site | NH5.3

Study on the influence of scour around tripod foundation for offshore wind turbine using Discrete Element Method 

Yu-wen Yang, Chia-Ming Lo, and Yu-Sen Lai

The seabed depth on the western coast of Taiwan is approximately between 20 to 50 meters, making it suitable for the installation of offshore wind turbines with a tripod foundation. Under the influence of water flow, the surrounding sand of the foundation can be eroded, forming scour holes and subsequently reducing the foundation's bearing capacity. The scour holes, influenced by the inherent angle of repose of the sand, undergo continuous erosion and collapse due to water flow, eventually reaching dynamic equilibrium. This study employs the Discrete Element Method (DEM) to conduct numerical simulations of scouring around the tripod foundation of offshore wind turbines. Different diameter particles are used to construct models of the offshore wind turbine tripod foundation and the sand. The dimensions of the seabed sand are 150 cm * 100 cm * 30 cm, with a particle diameter of 20 mm. This study observes the scouring of sand particles under different normal and shear stiffness conditions, resulting in various forms of scouring. The variations in scouring depth, length, and width under different normal and shear stiffness conditions will be discussed.

How to cite: Yang, Y., Lo, C.-M., and Lai, Y.-S.: Study on the influence of scour around tripod foundation for offshore wind turbine using Discrete Element Method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1641, https://doi.org/10.5194/egusphere-egu24-1641, 2024.

EGU24-2106 | ECS | Orals | NH5.3

Integrating incident and infragravity wave effects in a fast compound flood model 

Tim Leijnse, Ap van Dongeren, Maarten van Ormondt, Jeroen Aerts, and Sanne Muis

Coastal communities worldwide are under threat of flooding due to multiple hazards (Mousavi et al., 2011). In some coastal areas, waves are the dominant driver of extreme water levels (Parker et al., 2023). However, for regional to continental scales coastal flooding assessments, waves are often not or only crudely accounted for, due to the high computational expense of wave resolving numerical models (e.g., XBeach; Roelvink et al., 2009).

Recently, Leijnse et al. (2021) has shown that it is possible to model waves in a fast reduced-complexity compound flood model such as SFINCS. However, boundary conditions for SFINCS are still derived from a computationally expensive numerical model like XBeach or are generated using 1D based (meta) models (e.g., Bertoncelj et al., 2021), that do not (fully) account for alongshore varying 2D effects. To be able to include dynamic wave runup and overtopping in a 2D fast flooding model, we need to derive nearshore infragravity wave conditions also in a fast way.

To overcome this challenge, we introduce an integrated model approach, where we couple a fast stationary wave spectral model (SnapWave) to the fast compound flood model SFINCS. Besides incident waves, the SnapWave model can also efficiently estimates nearshore infragravity wave conditions (Leijnse et al. 2024, in review). Together with a nearshore wave generating boundary condition (van Ormondt et al., 2023), our new integrated wave-resolving approach internally drives the flood model SFINCS with waves and can therefore assess the effects of waves on coastal flooding. The performance is validated for several laboratory tests and against XBeach simulations of van Ormondt et al. (2021).

References

Bertoncelj, V., Leijnse, T., Roelvink, F., Pearson, S., Bricker, J., Tissier, M., and van Dongeren, A.: Efficient and accurate modeling of wave-driven flooding on coral reef-lined coasts: Case Study of Majuro Atoll, Republic of the Marshall Islands, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5418, https://doi.org/10.5194/egusphere-egu21-5418, 2021.

Leijnse, van Ormondt, Nederhoff, van Dongeren (2021). Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes. Coastal Engineering, 163, 103796. https://doi.org/10.1016/j.coastaleng.2020.103796

Leijnse, van Ormondt, van Dongeren, Aerts, Muis (2024, in review). Estimating nearshore infragravity wave conditions at large spatial scales. Frontiers in Marine Science.

Mousavi, Irish, Frey, Olivera, Edge (2011). Global warming and hurricanes: The potential impact of hurricane intensification and sea level rise on coastal flooding. Climatic Change, 104(3–4), 575–597. https://doi.org/10.1007/s10584-009-9790-0

Parker, Erikson, Thomas, Nederhoff, Barnard, Muis (2023). Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast. Natural Hazards. https://doi.org/10.1007/s11069-023-05939-6

Roelvink, Reniers, van Dongeren, van Thiel de Vries, McCall, Lescinski (2009). Modelling storm impacts on beaches, dunes and barrier islands. Coastal Engineering, 56(11–12), 1133–1152. https://doi.org/10.1016/j.coastaleng.2009.08.006

Van Ormondt, Roelvink, van Dongeren (2021). A Model-Derived Empirical Formulation for Wave Run-Up on Naturally Sloping Beaches. Journal of Marine Science and Engineering, 9(11), 1185. https://doi.org/10.3390/jmse9111185

Van Ormondt, Roelvink, van Dongeren (2023). Wave effects in a rapid compound flood model. 17th International Workshop on Wave Hindcasting and Forecasting.

How to cite: Leijnse, T., van Dongeren, A., van Ormondt, M., Aerts, J., and Muis, S.: Integrating incident and infragravity wave effects in a fast compound flood model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2106, https://doi.org/10.5194/egusphere-egu24-2106, 2024.

EGU24-4365 | ECS | Posters on site | NH5.3

Geological Records of Past Cyclones Preserved in the Beach Ridge Systems on the East Coast of India 

Rahul Kumar, Adam Switzer, Abang Nugraha, Raj Singh, Santanu Banerjee, Sunita Rath, Benjamin Horton, Siddharth Prizomwala, and Charles Bristow

The Bay of Bengal is a well-known hotspot for cyclone formation. Multiple recent cyclones, such as the Odisha Super Cyclone in 1999 and Cyclone Fani in 2019, along with a series of historical cyclones, have severely impacted the east coast of India, particularly the coastal regions of Odisha and West Bengal States. However, the existing cyclone record from the area is insufficient for multi-decadal recurrence analysis, rarely extending beyond last few decades. Hence, understanding and integrating historical, prehistorical, and geological cyclone records from the area can provide information on the social, economic, and environmental impacts of cyclones. This information will aid in planning response strategies and implementing policies to mitigate cyclone effects. This study investigates the geological record of cyclones buried in the prograded beach systems near Konark in Odisha over the past few hundred years. Shore-normal ground penetrating radar (GPR) reflection profiles were collected using the 250 and 500 MHz antennas of the pulseEKKO PRO GPR system. Sediment cores and excavated faces were analysed along the same GPR lines, and optically stimulated luminescence ages provide a chronological framework over the last 300 years. Processed GPR profiles exhibit a number of high-angle erosional surfaces. These surfaces were likely caused by erosion during severe cyclones in the region, spanning at least the last three centuries. Eight such erosional surfaces were identified from the GPR profile near Konark. Trench and core data from the swales also highlight several distinctive layers rich in heavy minerals, possibly the result of repetitive cyclones in the area. One prominent sand layer gives an interim age of 150 years, likely linked to a late 19th century washover event. The data presented in this study indicate that geological records can be used to build a long-term cyclone record for the area. Given the increasing population density in the region, a comprehensive cyclone record can provide valuable insights into the changes in frequency and intensity over the long term, which can be used to inform decision-making processes for coastal management and development.

How to cite: Kumar, R., Switzer, A., Nugraha, A., Singh, R., Banerjee, S., Rath, S., Horton, B., Prizomwala, S., and Bristow, C.: Geological Records of Past Cyclones Preserved in the Beach Ridge Systems on the East Coast of India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4365, https://doi.org/10.5194/egusphere-egu24-4365, 2024.

EGU24-4910 | Posters on site | NH5.3

Ground Penetrating Radar of a beach ridge system on Phra Thong Island, Thailand reveals repeat Late-Holocene tsunami events on a background of falling sea level 

Adam Switzer, Rahul Kumar, Chris Gouramanis, Charles Bristow, Timothy Shaw, Jankaew Kruawun, and Dominik Brill

This study examines ground penetrating radar (GPR) records of beach ridge stratigraphy as a proxy for reconstructing regional sea-level and tsunami histories in the tropics. We present topographically corrected GPR profiles on a prograded coast in Phra Thong Island, Thailand where we 1) identify downlap points marking the boundary between foreshore / beachface and upper shoreface facies and use this as past sea-level marker and 2) identify ‘cut and fill’ packages in the upper fill that we infer to be records of past erosion and recovery following repeated tsunami events. Optically Stimulated Luminescence (OSL) dates collected at locations slightly offset from the same profile line were incorporated to create the temporal record. The shore-normal GPR record shows ~0.82 m fall in the sea-level between 2659±139 years BP to 367±27 years BP that is consistent with other proxy based sea-level curves obtained in the region. The early part of the record (before ~2600 years) presents a period of rapid progradation and relatively stable sea level conditions. From ~2600 years BP to ~2200 years BP the record shows a steeper fall in sea level followed by a relatively stable to slightly falling phase between ~2200 years BP and ~550 years BP. Finally, for the seaward side, between ~550 years BP and ~350 years BP, the record indicates falling relative sea-level. The cut and fill packages suggest that Phra Thong has experienced 5 tsunami events in the last 2600 years including two events in close succession around 500 years ago that are recorded in the most landward part of the sequence.  This study confirms that the study of tropical beach ridge systems using GPR and OSL techniques can be highly effective for reconstructing regional sea-level trends and tsunami histories through the Common Era and beyond.

How to cite: Switzer, A., Kumar, R., Gouramanis, C., Bristow, C., Shaw, T., Kruawun, J., and Brill, D.: Ground Penetrating Radar of a beach ridge system on Phra Thong Island, Thailand reveals repeat Late-Holocene tsunami events on a background of falling sea level, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4910, https://doi.org/10.5194/egusphere-egu24-4910, 2024.

EGU24-6313 | ECS | Posters on site | NH5.3

Quantifying the impact of sea level and morphodynamics on shoreline changes with remote sensing observations 

Bene Aschenneller, Roelof Rietbroek, and Daphne van der Wal

Potential causes for shoreline retreat are diverse and very site-specific. These include inundation through absolute sea level rise or relative sea level changes caused by vertical land motions, as well as morphological processes (erosion or accretion). A widespread approximation to quantify and separate the influences of sea level changes and morphodynamics is to use the Bruun Rule. This simplified model has been interpreted in two ways, either by modelling the sediment redistribution along the beach profile, or by assuming a linear relationship where the ratio of sea level change and beach slope relates to the shoreline change. Here we show that the combination of several remote sensing observations from the last 20-30 years with sea level from radar altimetry, shorelines from optical satellite imagery and land elevation from LiDAR can be used to quantify the influence of sea level change and morphodynamics on shoreline changes.

In this case study for the barrier island of Terschelling (the Netherlands), we begin by assessing the uncertainties in the individual datasets. First, we compare ALES-retracked altimetry observations with two nearby tide gauges under different tidal corrections and estimate vertical land motion from GNSS height observations. For timeseries of cross-shore changes from satellite-derived shorelines, we show in a sensitivity analysis how different processing choices influence the outcome. Additionally, we intersect profiles of land elevation from a set of yearly coastal topobathymetry observations (JARKUS) with a horizontal plane at sea surface height in different combinations. We find that between 1992 and 2022 passive inundation accounts on average for -0.3 m/year of landward shoreline change at Terschelling, while the total estimated shoreline trend was on average -3.2 m/year. Finally, we will discuss possibilities and challenges to upscale the methodology to a global approach.

How to cite: Aschenneller, B., Rietbroek, R., and van der Wal, D.: Quantifying the impact of sea level and morphodynamics on shoreline changes with remote sensing observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6313, https://doi.org/10.5194/egusphere-egu24-6313, 2024.

Global climate change is expected to increase the proportion of intense tropical cyclones in the Northwest Pacific. This study focuses on how factors, especially extreme events, may affect disaster losses. To address this issue, an event-based multivariate tropical cyclone risk assessment model, which employs Copula, generalized additive model, and undersampling extreme gradient boosting decision tree techniques, is developed to enhance the accuracy of disaster loss prediction. The results suggest that on Hainan Island, the rate of the affected population is positively correlated with maximum wind speed and maximum daily rainfall but negatively correlated with gross domestic product and elevation. The study also shows that the tropical cyclone risk in the cities in Hainan increases as the return periods expand, and each return period scenario shows a unique geospatial distribution of the tropical cyclone risk on Hainan Island, with higher risks in coastal and eastern regions. These results emphasize the importance of implementing effective disaster management strategies to mitigate the impact of severe tropical cyclones in the region.

How to cite: Meng, C. and Xu, W.: Quantitative Assessment of Affected Population Risk by Tropical Cyclones Using the Hybrid Modeling Combining GAM and XGBoost: A Case Study of Hainan Province, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6922, https://doi.org/10.5194/egusphere-egu24-6922, 2024.

EGU24-7834 | ECS | Orals | NH5.3

Coastal boulders related to extreme marine events impacting the ABC islands (Aruba, Bonaire, Curacao islands, Leeward Antilles) 

Giovanni Scardino, Chiara Barile, Aruna Napayalage Nandasena, Tobia Lahbi, Enrico Muletto, Denovan Chauveau, Patrick Boyden, Sonia Bejarano, Alessio Rovere, Elisa Casella, Harold Kelly, Eric Mijts, and Giovanni Scicchitano

Extreme marine events determine different landform imprints, such as out-of-size deposits like coastal boulders with several tons in weight. These extreme marine events are usually connected to storms and tsunamis. Storms and tsunamis are characterized by a high-energy content, which is reflected in wave flow and wave height able to move the boulders. Several coastal boulders have been detected in Aruba, Bonaire, and Curacao (ABC) islands, overlying the marine terrace deposits that surround the seaward side of these islands. In this work, morpho-topographical surveys were performed on these coastal boulders in order to simulate the most probable events that caused their displacements. Unmanned Aerial Vehicle and close-range photogrammetry were used to reconstruct the volume and shape of boulders with their immersive scenario. Volume and shape of coastal boulders have been used to estimate the energy content able to determine their displacement. Furthermore, boulder samples were collected in order to assess their density and to obtain chronological constraints of the extreme marine events by applying U/Th and radiocarbon dating. Numerical models in Delft3D were applied to simulate the scenarios that could be responsible for the boulder movements. The results showed that the biggest boulders are located on Bonaire Island, located in the eastern part of the ABC archipelago, and were influenced by higher energy content than the Aruba and Curacao islands. This energy content could be related to three possible scenarios simulated in Delft3D: 1) a tsunami scenario connected to Venezuela earthquakes, 2) a Hurricane scenario impacting from the western side of the ABC archipelago, 3) a combination of multiple events (tsunami and storms) that caused differential boulders movement in the past.

How to cite: Scardino, G., Barile, C., Nandasena, A. N., Lahbi, T., Muletto, E., Chauveau, D., Boyden, P., Bejarano, S., Rovere, A., Casella, E., Kelly, H., Mijts, E., and Scicchitano, G.: Coastal boulders related to extreme marine events impacting the ABC islands (Aruba, Bonaire, Curacao islands, Leeward Antilles), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7834, https://doi.org/10.5194/egusphere-egu24-7834, 2024.

EGU24-8103 | Posters on site | NH5.3

A deep learning method to automatically measure tide and surge in coastal areas 

Gaetano Sabato, Giovanni Scardino, Alok Kushabaha, Giulia Casagrande, Marco Chirivì, Giorgio Fontolan, Saverio Fracaros, Antonio Luparelli, Sebastian Spadotto, and Giovanni Scicchitano

Advances in machine learning and deep learning approaches have drawn substantial interest across diverse research domains, including environmental studies. These innovative techniques have transformed the approaches to measuring marine parameters by facilitating automated and remote data collection. This study focuses on the implementation of a deep learning model to automatically assess tide and surge, aiming for precise outcomes through the analysis of surveillance camera imagery.

Utilizing the Inception v3 structure, the deep learning model was applied to predict tide and storm surge from surveillance cameras strategically positioned in two distinct coastal regions, namely Santa Lucia in southeastern Sicily and Lignano Sabbiadoro in Friuli Venezia Giulia, Italy. The deep learning model is based on classification methods to assign a value of water level to a given frame. This approach is particularly advantageous in scenarios where traditional tide sensors face inaccessibility or are distant from measurement points, especially during extreme events demanding accurate surge measurements. The dataset used for the training and validation of the deep learning model covers the entire tide values that could be observed in the study areas. Predictions of the deep learning model were compared with tide gauge values in order to assess the system accuracy.

The conducted experiments demonstrate the efficiency of the model in remotely and effectively measuring tide and surge, achieving an accuracy exceeding 90% while maintaining a loss value below 1 for the deep learning model. These findings underscore its potential to fill the data collection gap in challenging coastal environments, offering valuable insights for coastal management and hazard assessment. This study makes an important contribution to the rapidly growing field of remote sensing and machine learning applications in environmental monitoring, facilitating greater comprehension and decision-making in coastal areas.

How to cite: Sabato, G., Scardino, G., Kushabaha, A., Casagrande, G., Chirivì, M., Fontolan, G., Fracaros, S., Luparelli, A., Spadotto, S., and Scicchitano, G.: A deep learning method to automatically measure tide and surge in coastal areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8103, https://doi.org/10.5194/egusphere-egu24-8103, 2024.

EGU24-8125 | ECS | Posters on site | NH5.3

Integration of relational geodatabase in a web-GIS platform for Mapping the effects of Mediterranean Cyclone. 

Alok Kushabaha, Giovanni Scardino, Gaetano Sabato, Giovanni Scicchitano, and Alfio Marco Borzi

Several cyclogenesis processes affect the Mediterranean Sea, causing significant impacts along its coastline. This study focuses on mapping the effects of cyclones in the Mediterranean Sea, particularly Mediterranean hurricanes, which cause severe damage to coastal areas. Advanced remote sensing and Geographic Information System (GIS) techniques are used to analyse climatic data and observe geomorphological evidence, such as flooding, coastal erosion, landslides, alluvial flooding and debris flow. By integrating climate features and geomorphological evidence, this research establishes a connection with the occurrence of Mediterranean cyclones. The study specifically examines the south-eastern coasts of Sicily, where Mediterranean Hurricanes have caused extensive damages, including flooding, erosion, and storm surges. Pre and post-storm morpho-topographical surveys were conducted to assess coastal flooding and erosion through aerial photogrammetry and Terrestrial Laser Scanner surveys. The collected data were stored in a geodatabase, allowing for the display of climate features and geomorphological evidence. Additionally, the development of an open-source Web-GIS platform integrated with the geodatabase can facilitate the dissemination of geographic information to stakeholders and researchers, promoting collaboration and informed decision-making. This study contributes to a better understanding of Mediterranean cyclones, enabling the development of effective coastal management strategies to mitigate the challenges posed by Mediterranean Hurricanes.

How to cite: Kushabaha, A., Scardino, G., Sabato, G., Scicchitano, G., and Borzi, A. M.: Integration of relational geodatabase in a web-GIS platform for Mapping the effects of Mediterranean Cyclone., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8125, https://doi.org/10.5194/egusphere-egu24-8125, 2024.

EGU24-8336 | Orals | NH5.3

Impact of increasing storminess and decreasing sea ice cover on high-latitude beach erosion (Hornsund, Svalbard) 

Zuzanna Swirad, Agnieszka Herman, and Mateusz Moskalik

Observed and further predicted decreasing sea ice extent and increasing storminess over the North Atlantic are deemed to intensify coastal erosion along the shores of Western Svalbard. We investigate these relationships in Isbjornhamna, a bay with ~3 km shoreline located in north-western Hornsund fjord. The bay is delimited by Wilczekodden and Baranowskiodden headlands with 1.5 km opening to the main basin of the fjord where the depth is ~20-25 m. Mean significant wave height is 0.26 m and its 99th percentile is 1.5 m with highest values in autumn (mean of 0.4 m and 99th percentile of 1.91 m). A minor protrusion divides the bay into two basins. In the eastern part (Hansvika) a thick layer of glacier till deposits overlays metamorphic bedrock, while the western part (Krossvika) is cut in shists and paragneisses. Coastal cliffs are present at the outer parts of the bay, while gravel beach occupies its central 2 km section. There is an alongshore variability in beach morphology (width, slope) and grain size distribution. Glacier ice from calving Hansbreen often accumulates at the shore in summer and autumn months, while in winter/spring sea ice and ice foot are present. Polish Polar Station infrastructure is located on the shore which makes it directly exposed to storm waves.

We used repetitive Uncrewed Aerial Vehicle surveys combined with Structure-from-Motion photogrammetry to detect beach change over 5 years. In total 13 surveys were performed between July 2018 and August 2023 which allowed a separation of shorter- and longer-term changes in beach morphology. We observed processes such as formation and destruction of beach cusps, creation and disappearance of holes from melting growlers, shoreline retreat and across- and alongshore sediment transport. We calculated mean erosion rates, and analysed its spatial and temporal variability. Finally, the short-term measurements were compared to the decadal-scale erosion rates derived from orthophotographs. Relationships between beach erosion, wind wave conditions, and sea ice coverage were inspected to understand the role of changing climate on the rates of coastal change.

How to cite: Swirad, Z., Herman, A., and Moskalik, M.: Impact of increasing storminess and decreasing sea ice cover on high-latitude beach erosion (Hornsund, Svalbard), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8336, https://doi.org/10.5194/egusphere-egu24-8336, 2024.

EGU24-9395 | Posters on site | NH5.3

Tropical cyclone induced coastal flooding under current and future climates: A novel model framework for continental scale applications.  

Niall Quinn, Thomas Collings, Ignatius Pranantyo, Nicolas Bruneau, Hamish Wilkinson, Ivan Haigh, and Malcolm Haylock

Coastal flooding, often triggered by the convergence of high tides and intense storm surges and waves, poses a grave threat to global coastal communities, leading to widespread property damage and loss of life. Tropical cyclones (TCs) in particular have been responsible for the majority of the most devastating coastal flood events in the recent years, causing billions of dollars in damages over the last decade within the US alone. Further, the compounded impact of rising sea levels, fuelled by a warming climate, along with projected population growth and continued development in the flood zone, is widely expected to increase these risks to coastal communities in the future. 
It is essential to many end users, from environmental mangers to (re)insurers, to accurately characterize the risk of coastal flooding over large, often national scales, both under current and highly uncertain, future climate conditions. This poses a number of challenges. For instance, in many of the most heavily impacted regions of the world, the majority of the coastal flooding stems from severe TC induced storm surge events. The rarity of these events means that the historical record alone is insufficient to truly capture the current risk, let alone represent the vast range of potential future climate conditions and their subsequent impacts upon TC-induced flood risk. To provide the information required catastrophe model frameworks that can efficiently represent the full range of potential flooding events, from hazard generation through to financial impacts, and how their frequencies might change through time, are essential. 
This research introduces a comprehensive TC-induced storm surge catastrophe modelling framework. An extensive catalogue of synthetic TC wind and pressure fields, under current and future climate forcing, is utilised. The SCHISM model suite is used to numerically model surge and waves to generate boundary conditions to the reduced physical solver, SFINCS, which is used to model the nearshore and overland inundation processes. Using an example US implementation, novel approaches developed to enable the efficient representation of approximately 2.5 million unique TC events are discussed, and preliminary results presented. The proposed catastrophe model framework offers a valuable tool for those interested in coastal flooding, enabling a robust evaluation of TC-induced risk under any climate scenario, over extensive geographical domains.   

How to cite: Quinn, N., Collings, T., Pranantyo, I., Bruneau, N., Wilkinson, H., Haigh, I., and Haylock, M.: Tropical cyclone induced coastal flooding under current and future climates: A novel model framework for continental scale applications. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9395, https://doi.org/10.5194/egusphere-egu24-9395, 2024.

EGU24-9439 | ECS | Orals | NH5.3

Influence of different Total Water Level components on coastal flooding simulation: a case study “real-life” assessment 

Paulo Cabrita, Juan Montes Pérez, Enrico Duo, Riccardo Brunetta, and Paolo Ciavola

Extreme events can dramatically affect coastal areas, causing floods and shoreline erosion, consequently impacting infrastructures and, in the worst cases, resulting in life losses. These events are becoming frequent in regions along the northeastern Italian coastline, like the Emilia-Romagna region, significantly damaging the local economy. Here, regular coastal floods can impact infrastructures built on the beach or behind low-lying dunes, flooding through beach access paths. Therefore, predicting the impact of such extreme events and their appearance probability is important for coastal protection and the local economy.

Total Water Levels (TWLs) associated with extreme events can be characterised by different probability levels  (i.e. different return periods), influencing the flood extension. The definition of TWL in the literature depends on the chosen variables and the methods used to estimate it. In this work, to understand the influence of the different elements on TWL extreme values, combinations of different components, such as tide, wave set-up, run-up, calculated with Stockdon et al. (2006) equation (http://dx.doi.org/10.1016/j.coastaleng.2005.12.005), between others, and two methods for Extreme Value Analysis (EVA), were used. The two methods used for the EVA were (1) the analysis of the individual time series of each component, combining each extreme value to obtain a TWL, and (2) the combination of the different elements' time series to build the TWL time series and the application of the EVA. The dataset combines modelled data for the water level (SHYFEM) and waves (WW3 model) and predicted tide levels provided by the Pytides2 library. The EVA was done by selecting return periods between 1 and 500 years with a declustering factor of 24 hours. Those were divided into three categories: high [return period: 1-20 yrs], medium [30-50 yrs] and low-frequency events [100-500 yrs]. For each method and frequency, three values of the TWL were obtained, giving 72 TWL combinations for each beach slope category (three slopes were tested for the run-up). The highest TWL values were obtained by adding the extreme values of astronomical tide, non-tidal residual, run-up and setup. Meanwhile, the lowest TWL calculated corresponds to the EVA applied to the combination of all the components' time series, which does not include the run-up.

An evaluation of flood extension with Lisflood-FP model (Bates et al., 2005; https://doi.org/10.1016/j.coastaleng.2005.06.001) based on the different TWL values was made. The coast of Lido di Volano (Ferrara, Italy) was chosen as a case study site for a real-life assessment. For the flood model, storm events were reproduced assuming a triangular distribution for six hours, locating the starting and end points at the mean tide level. When compared with the real-life assessment, EVA method 1 demonstrated an overestimation for the same intensity of return period. EVA method 2 showed a good correlation, although an overestimation was observed when the run-up was included in the time series. Results demonstrated how the choice of EVA methods and water level contributions are crucial for predicting extreme events.

How to cite: Cabrita, P., Montes Pérez, J., Duo, E., Brunetta, R., and Ciavola, P.: Influence of different Total Water Level components on coastal flooding simulation: a case study “real-life” assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9439, https://doi.org/10.5194/egusphere-egu24-9439, 2024.

EGU24-9556 | ECS | Posters on site | NH5.3

Constructing an offshore tsunami event stratigraphy for the Shetland Islands 

Rikza Nahar, Pedro Costa, Maarten Van Daele, Sue Dawson, Max Engel, Juliane Scheder, Thomas Goovaerts, Vanessa Heyvaert, and Marc De Batist

Offshore tsunami deposits have received considerably less attention than their onshore counterparts, despite the fact that they have a higher likelihood of being preserved in the sedimentary record, especially in sufficiently deep marine environments, below the storm wave base. Here we provide the first results from our study of Holocene tsunami deposits offshore the Shetland Islands. The region is characterized by an irregular coastline with fjords and numerous embayments, and relatively deep waters (up to 100 meters in depth),  providing a sheltered environment, and by an extensively studied and well-documented onshore record of tsunami deposits, which should facilitate correlations between onshore and offshore event deposits. 
Within the NORSEAT Project (North Sea Tsunami Deposits Offshore Shetland Island), we aim to identify and trace tsunami deposits offshore, thoroughly study their characteristics and extent, and determine whether the offshore record holds evidence of events additional to those already known from the onshore record (i.e. the Storrega tsunami and two events at ca. 5500 yr and ca. 1500 yr BP), which would offer new insights into recurrence intervals. Two surveys with RV Belgica have already been conducted, during which high-resolution geophysical data (multibeam bathymetry and backscatter, geoacoustic and seismic data) were collected, along with several vibrocores, in three embayment areas around the Shetland Islands.
Bathymetric data and sub-bottom profiles reveal a complex geomorphology, including a.o. elevated features, like bedrock exposures, and isolated depressions that function as sub-basins. The sedimentary sequences infilling these sub-basins are characterized by a complex stratigraphy and comprise several different sedimentary units. Along the west and east fjords of Sullom Voe, three distinct sub-environments (inner, middle, and outer voe) exhibit a diverse and well-preserved stratigraphy, potentially including a significant event deposit. A set of prominent strong reflectors at a depth of 1-2 m below the seafloor is interpreted as dynamic shallow marine deposits, which is supported by the results of the vibrocores retrieved at these sites. Out of the total 31 sediment cores taken, many contain coarser-grained layers sandwiched between finer-grained deposits. These coarser layers, often with sharp basal contacts and normal grading patterns, suggest temporary interruptions of the steady-state sedimentary regime and are interpreted as possible event deposits based on their contrasting textural and lithological characteristics.
In the next phase of our analysis, we aim to obtain the exact timing and detailed information about the depositional setting based on radiocarbon dating, grain size analysis, geochemical analysis, mineral distribution patterns, and the distribution of microfossils within the sediment cores, which should help us to build a robust tsunami event stratigraphy for the region, combined with planned sea-level reconstructions, assess their run-up heights based on the onshore-offshore connection and the fundamental research on sedimentary signatures and facies patterns of offshore tsunami deposits.

How to cite: Nahar, R., Costa, P., Van Daele, M., Dawson, S., Engel, M., Scheder, J., Goovaerts, T., Heyvaert, V., and De Batist, M.: Constructing an offshore tsunami event stratigraphy for the Shetland Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9556, https://doi.org/10.5194/egusphere-egu24-9556, 2024.

EGU24-10979 | ECS | Posters on site | NH5.3

Measuring cliff top and cliff face retreat rates of a coastal drumlin using Structure-from-Motion in Galway Bay, Ireland 

Gregor Rink, Gordon Bromley, and Eugene Farrell

Sea cliffs comprise approximately 80% of the world’s coasts. Rapidly retreating cliffs are a widespread problem that threatens property, transport infrastructure and public safety. Cliff retreat rates depend on highly localised characteristics of the cliff itself, as well as on the land behind the cliff and the intertidal and marine environments in front of it. In addition to these physical properties, retreat rates are also influenced by the methodology applied. Traditionally, estimates of coastal cliff top retreat have been based on historic map and arial photograph (century scale) analyses that provide long-term rates but fail to provide information in short-term processes driving coastal evolution. Newer datasets from satellite imagery and uncrewed aerial vehicles (UAV’s) are being coupled with new techniques like Structure-from-Motion (SfM) to dismantle cliff top and cliff face dynamics at shorter timescales (weeks to months). It is now accepted that estimates of cliff retreat rates can differ substantially when calculated from cliff top versus cliff face analyses, usually finding that cliff-top retreat rates are higher than cliff-face retreat rates.

This study combines historical data (maps and aerial photographs 1842 – 2000) with contemporary UAV imagery (2019 – 2023) to analyse cliff top and cliff face dynamics of a 250 m wide coastal drumlin at Silverstrand in Galway Bay on the west coast of Ireland. The cliff top changes were analysed using the Digital Shoreline Analysis System (DSAS) in the ESRI ArcGIS Desktop platform. Cliff face change detection was done using a Multiscale Model to Model Cloud Comparison (M3C2) in CloudCompare. By using these different types of data and methods, we were able to calculate retreat rates of the cliff top and the cliff face independently. The average cliff top retreat rate between 1842 and 2023 (181 years) was estimated to be 0.14 +/- 0.02 m/year. The average cliff face retreat between 2019 and 2023 (4.45 years) was estimated to be 0.08 +/- 0.02 m/year. For both, cliff top and cliff face retreat rate, we found that the long-term retreat rates are lower than the short-term retreat rates and that the western part of the cliff experiences higher erosion than its eastern counterpart. This variability might reflect multiple erosional processes and differences in magnitude-frequencies of erosional events at the cliff top and cliff face, or even the application of various methods and datasets.

Our results are consistent with other soft rock cliffs in Ireland and globally in similar settings. Nonetheless, more detailed observations using shorter timescales and monitoring intervals are warranted to identify and quantify the rates, patterns, timing and magnitude- frequency of cliff retreat phenomena.

How to cite: Rink, G., Bromley, G., and Farrell, E.: Measuring cliff top and cliff face retreat rates of a coastal drumlin using Structure-from-Motion in Galway Bay, Ireland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10979, https://doi.org/10.5194/egusphere-egu24-10979, 2024.

EGU24-11851 | Posters on site | NH5.3

Analysis and modelling of compound hazards to the desalination plants on Gotland: The Hans Storm 2023 event 

Inga Monika Koszalka, Matteo Masini, Dimitrios Antivachis, Kristofer Döös, Agnes Karlsson, Bengt Karlsson, Lars Axell, and Lars Arneborg

The island of Gotland located in the middle of the Baltic Sea is Sweden's largest island, and also a county and municipality with the population of about 60,000, employed mainly in agriculture and tourist sectors. Gotland is a very popular domestic tourist destination for mainland Swedes, reaching nearly 2 million ferry and plane passengers per year. Gotland experiences limited capacity in groundwater reservoirs combined with increased demand during the warm season when tourists visits peak leading to recurring water stress. Desalination of drinking water from the Baltic Sea is a promising alternative to complement municipal water supply. The operation of the two major desalination treatment plants becomes however disturbed by compound hazards due to extreme sea weather events (marine heatwaves, strong upwelling events) and related hydro-sedimentary and biological processes (macro- and microalgae blooms) that are predicted to intensify under the climate change. Developing an apt forecasting system for this "multi-hazard" to inform sustainable management of Gotland's water resources becomes thus a priority and is of broader relevance to other regions in Sweden.

The ALGOTL project, funded by the Swedish research council for sustainable development (FORMAS), is a collaboration between Stockholm University, the Swedish Meteorological and Hydrological Institute (SMHI) and Region Gotland to develop a novel forecast framework for natural hazard impacts on management of water resources, both short term (early warning) and long term (climate scenarios). The project aims at development of Lagrangian- and risk modelling tools based on the operational ocean state forecast at SMHI. Our stakeholders on Gotland will provide input on adverse impacts, information required for management, and feedback on the forecast framework during the project.

This contribution will summarize results from observational and modelling analysis of the oceanographic, hydrological and biological conditions due to the Hans storm event in August 2023 that led to the disturbance in operation of the desalination plants on Gotland, located at the Herrvik (eastern side) and Kvarnåkershamn (western side of the island). The storm triggered an upwelling event leading to sea temperature changes of 10 K (prompting the change from summer to winter operational mode) and high vertical and horizontal velocities and associated excessive transport of sediment and biological (algae) material disrupting the filtering process. We will also show results from Lagrangian backtracking of the source waters reaching the desalination plants and present prospects for developing of a forecast system for related events in the future.

More information about the ALGOTL project: https://www.su.se/english/research/research-projects/algotl-forecast-framework-for-algae-blooms-to-secure-water-supply-on-gotland

How to cite: Koszalka, I. M., Masini, M., Antivachis, D., Döös, K., Karlsson, A., Karlsson, B., Axell, L., and Arneborg, L.: Analysis and modelling of compound hazards to the desalination plants on Gotland: The Hans Storm 2023 event, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11851, https://doi.org/10.5194/egusphere-egu24-11851, 2024.

EGU24-15411 | Posters on site | NH5.3

Linking sedimentary imprints of storms and tsunamis with numerical wave modeling: A case from a coastal lagoon in the Lesser Antilles (Saint Martin) 

Stefano C. Fabbri, Pierre Sabatier, Raphaël Paris, Simon Falvard, Nathalie Feuillet, Amélie Lothoz, Guillaume St-Onge, Audrey Gailler, Louise Cordrie, Fabien Arnaud, Maude Biguenet, Thibault Coulombier, Saptarshee Mitra, and Eric Chaumillon

We examined sedimentary records in a coastal lagoon on Saint Martin Island in the Lesser Antilles to identify and characterize extreme-wave events (EWEs), such as hurricanes and tsunamis. Employing a comprehensive approach involving sedimentological, geochemical, and radiocarbon dating analyses, complemented by X-ray computed microtomography (micro-CT) for examining sediment fabrics, we applied this multiproxy method to three oriented short sediment cores along a transect. This allowed us to identify sediment layers linked to both tsunami- and hurricane-induced EWEs. Five out of the seven EWEs were identified as paleo-tsunamis through their geochemical, sedimentary, and structural signatures. These five paleotsunamis were successfully dated over the last 3500 years, including the well-documented Pre-Columbian tsunami at approximately 1400 yrs CE and the transatlantic Lisbon tsunami at 1755 CE. This suggests a tentative local tsunami chronology of five well-documented events over the last 3500 years with a recurrence interval of 400 to 500 years.

However, the most recent EWE corresponded to the powerful Category 5 Hurricane Irma in 2017. Over the last 150 years, another 14 less intense hurricanes impacted the island, leaving no sediment imprints in the lagoon. This finding is in line with most recent publications showing that tropical storm intensification rates have already changed as anthropogenic greenhouse gas emissions have warmed the globe (Garner, 2023).

Furthermore, micro-CT-based sediment analysis provided a deeper understanding of the relationship between sediment fabric and tsunami wave dynamics. Therefore, we used the deposits of the Pre-Columbian tsunami and compared paleo-flow directions from micro-CT-derived fabric patterns to those from numerical tsunami models. The results that best explain the Pre-Columbian tsunami deposit emplacement are in line with a Mw 8.5–8.7 megathrust earthquake source located on the subduction interface at the Puerto Rico Trench, north of Anegada Island (Cordrie et al., 2022). Ultimately, integrating deposits of EWEs with numerical models is pivotal for devising effective hazard mitigation strategies tailored to vulnerable coastal communities.

Cordrie, L., Feuillet, N., Gailler, A., Biguenet, M., Chaumillon, E., Sabatier, P., 2022. A Megathrust earthquake as source of a Pre-Colombian tsunami in Lesser Antilles: Insight from sediment deposits and tsunami modeling. Earth Sci Rev 228, 104018. https://doi.org/10.1016/j.earscirev.2022.104018

Garner, A.J. Observed increases in North Atlantic tropical cyclone peak intensification rates. Sci Rep 13, 16299 (2023). https://doi.org/10.1038/s41598-023-42669-y

How to cite: Fabbri, S. C., Sabatier, P., Paris, R., Falvard, S., Feuillet, N., Lothoz, A., St-Onge, G., Gailler, A., Cordrie, L., Arnaud, F., Biguenet, M., Coulombier, T., Mitra, S., and Chaumillon, E.: Linking sedimentary imprints of storms and tsunamis with numerical wave modeling: A case from a coastal lagoon in the Lesser Antilles (Saint Martin), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15411, https://doi.org/10.5194/egusphere-egu24-15411, 2024.

EGU24-15450 | ECS | Orals | NH5.3 | Highlight

Factors of influence on flood risk perceptions related to Hurricane Dorian: an assessment of heuristics, time dynamics and accuracy of risk perceptions 

Laurine de Wolf, Peter Robinson, Wouter Botzen, Toon Haer, Jantsje Mol, and Jeffrey Czajkowski

Flood damage caused by hurricanes is expected to rise globally due to climate and socio-economic change. Enhanced flood preparedness among the coastal population is required to reverse this trend. The decisions and actions taken by individuals are thought to be influenced by risk perceptions. This study investigates the determinants that shape flood risk perceptions, as well as the factors that drive flood risk misperceptions of coastal residents. We conducted a survey among 871 residents in flood-prone areas in Florida during a five-day period in which the respondents were threatened to be flooded by Hurricane Dorian. This approach allows for assessing temporal dynamics in flood risk perceptions during an evolving hurricane threat. Among 255 of the same households, a follow-up survey was conducted to examine how flood risk perceptions vary after Hurricane Dorian failed to make landfall in Florida. Our results show that the flood experience and social norms have the most consistent relationship with flood risk perceptions. Furthermore, participants indicated that their level of worry regarding the dangers of flooding decreased after the near-miss of Hurricane Dorian, compared to their feelings of worry during the hurricane event. Based on our findings, we offer recommendations for improving flood risk communication policies

How to cite: de Wolf, L., Robinson, P., Botzen, W., Haer, T., Mol, J., and Czajkowski, J.: Factors of influence on flood risk perceptions related to Hurricane Dorian: an assessment of heuristics, time dynamics and accuracy of risk perceptions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15450, https://doi.org/10.5194/egusphere-egu24-15450, 2024.

EGU24-17053 | ECS | Posters on site | NH5.3

A combined modern training set from three salt marshes and tidal flats of Mainland, Shetland Islands, as a tool for local relative sea-level reconstruction 

Juliane Scheder, Sue Dawson, Thomas Goovaerts, Max Engel, Pedro Costa, Maarten Van Daele, Rikza Nahar, Marc De Batist, and Vanessa A.M. Heyvaert

High-resolution reconstructions of the relative sea-level (RSL) evolution are important for managing coastal-protection challenges and for hazard assessment. For the determination of palaeo-tsunami run-up heights in the Shetland Islands, United Kingdom, within the NORSEAT Project (Storegga and beyond – North Sea tsunami deposits offshore Shetland Islands), RSL reconstructions far beyond existing data are needed. Existing RSL data is limited to two time frames (ca. 7900–5990 cal BP and around 3500 cal BP) and include a large vertical error (approximately ±8 m around the time of the Storegga tsunami). More detailed Holocene RSL reconstructions shall be enabled by a combined modern training set of foraminifers and ostracods from three different voes of Shetlands largest island, Mainland. The training set serves as a basis for a RSL transfer function, which relates the elevation of surface samples to the modern microfaunal associations. This transfer function will be a valuable tool for high-resolution RSL reconstructions from the Holocene stratigraphic record around the Shetland Islands as shown by previous studies in Northern Germany.

Investigations of 44 surface samples, which were collected from three salt marshes and adjacent tidal flats (south Dales Voe, Dury Voe and north Dales Voe), are in progress. First results show highly diverse foraminifer and ostracod associations in the salt marsh and very low occurrence of microfauna in the very coarse parts of the tidal flat. Small areas of very muddy tidal flats suggest higher abundances than the latter. Aside from the investigation of the microfaunal distribution, analyses of environmental parameters like the grain-size distribution and the carbonate and organic matter content are still in progress. Multivariate statistics will determine the main influencing factor of the microfauna distribution between these environmental proxies and the elevation relative to mean sea level.

If the training set is feasible for a RSL transfer function, in a next step, it will be applied to Holocene deposits from offshore cores around Shetland that were conducted within the NORSEAT Project. The resulting new RSL reconstructions will enable more accurate determination of run ups of the currently identified palaeo-tsunamis (Storegga and two younger events). 

How to cite: Scheder, J., Dawson, S., Goovaerts, T., Engel, M., Costa, P., Van Daele, M., Nahar, R., De Batist, M., and Heyvaert, V. A. M.: A combined modern training set from three salt marshes and tidal flats of Mainland, Shetland Islands, as a tool for local relative sea-level reconstruction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17053, https://doi.org/10.5194/egusphere-egu24-17053, 2024.

Many river deltas and coastal lowlands in the world are densely populated and located in the Global South. Due to relative sea-level rise (rSLR), they face an increasing risk of drowning and flooding and thus require reliable impact and risk assessments of rSLR and flooding. As both sea-level rise (SLR) impact and flood inundation are closely related to land elevation, the quality of these assessments largely relies on vertical accuracy and proper datum referencing of the elevation data used. However, high-quality digital elevation models (DEMs) representing elevation at spatial resolutions and vertical accuracies at centimetre to decimetre scale are still not available or accessible for major parts of the Earth’s coasts, including densely populated Asian and African coastal lowlands or Small Island Development States. In these regions, global DEMs are often used even though they suffer from large vertical errors and artefacts, thereby impacting the quality of flood exposure assessments. While the accuracy of those global DEMs is extensively addressed both in their dataset documentation and literature, the relevance and proper vertical datum conversion from global geoid and ellipsoid models to local sea level is often still omitted in many applied studies; in part because the process is complicated in data-poor regions, where tide gauge records are often insufficient or outdated. Sea surface data based on satellite altimetry may serve as a substitute but the referencing of the land elevation and sea surface data to a common vertical datum includes several steps of datum conversion beforehand, which – if not performed properly – can introduce local errors of sea level to the land elevation up to several metres.

In this study, we test and present a workflow of globally consistent vertical datum conversion of elevation data to continuous local mean sea level by integrating globally available data on coastal elevation and sea surface. We apply our approach to recently published global DEMs and validate them for several key coastal lowlands such as the Ayeyarwady and Mekong Deltas, and show the improvement of the performance of global DEMs for impact assessments in data-poor regions. This proves the potential to improve impact assessments of SLR and flood exposure in coastal lowlands around the world where high-quality elevation information is not accessible.

How to cite: Seeger, K. and Minderhoud, P. S. J.: Accurate information on land elevation is key – Towards proper coastal flood risk assessment in data-sparse river deltas and coastal lowlands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17440, https://doi.org/10.5194/egusphere-egu24-17440, 2024.

EGU24-17794 | Orals | NH5.3 | Highlight

Exploring the wave storminess along the global coastlines 

Hector Lobeto, Alvaro Semedo, Melisa Menendez, Gil Lemos, Roshanka Ranasinghe, Ali Dastgheib, and Jean-Raymond Bidlot

Wave storms present a significant hazard to the coastal environment, particularly affecting the 10% of the population residing in low-lying coastal areas, as well as coastal zone infrastructure and developments. This study utilizes a ~40-year wave hindcast to conduct an analysis of wind-wave storminess along the worldwide coast (Lobeto et al., 2024). The main characteristics of wave storms, such as the associated wave height and direction, as well as the occurrence rate, duration and intensity, are analyzed. Additional climatic wave features including the relative importance of wind seas versus swells during wave storms are also explored. The combination of key storm features has led to a categorization of coastal regions based on their degree of wave storminess.

Results indicate Northwestern Europe and Southwestern South America to be the coastal regions experiencing the most severe storms, while the Yellow Sea, along with the South African and Namibian coastlines, are noted for their high frequency of storms. A global holistic analysis of the wave storminess reveals that, for example, the exposed shores of northwestern Europe experience over 10 storms annually, with mean significant wave heights exceeding 6 meters. A general latitudinal pattern in degree of wave storminess is observed, with the main exception of those coasts affected by wave storms generated by tropical cyclones. Accordingly, regions such as Iceland, Ireland, Scotland, Chile, and Australia exhibit the highest storminess levels, contrasting with lower levels observed in Indonesia, Papua-New Guinea, Malaysia, Cambodia, and Myanmar.

 

Lobeto, H, Semedo, A., Lemos, G., Dastgheib, A., Menendez, M., Ranasinghe, R., Bidlot, R. (2024). Global coastal wave storminess. Scientific Reports (in press).

How to cite: Lobeto, H., Semedo, A., Menendez, M., Lemos, G., Ranasinghe, R., Dastgheib, A., and Bidlot, J.-R.: Exploring the wave storminess along the global coastlines, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17794, https://doi.org/10.5194/egusphere-egu24-17794, 2024.

EGU24-19322 | ECS | Posters on site | NH5.3

Shallow water moment model for sediment transportation in coastal area 

Afroja Parvin, Julian Koellermeier, and Giovanni Samaey

Suspended and bedload sediment transport in shallow water environments is a critical factor influencing coastal morphology, ecosystem health, and infrastructure stability.  We present a new model for suspended and bedload sediment transport in shallow flows that takes into account vertically varying velocity profiles. We achieve this by using the recently developed shallow water moment model (SWME). The SWME employs a unified modeling framework that incorporates a polynomial expansion of the velocity profile in vertical direction, which represents a paradigm shift compared to the standard assumption of constant velocity profiles. The expansion coefficient equations constitute a hierarchical PDE system that improves accuracy when more equations are considered. The SWME model is then augmented by equations governing suspended sediment concentration and bedload transport. In this talk, we discuss the assumptions and general derivation of the 1D model, along with the theoretical analysis and the extension of this model to complex fluid phenomena.

 

How to cite: Parvin, A., Koellermeier, J., and Samaey, G.: Shallow water moment model for sediment transportation in coastal area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19322, https://doi.org/10.5194/egusphere-egu24-19322, 2024.

EGU24-19806 | ECS | Orals | NH5.3

Finding the potential height of storm surges in a changing climate using Bayesian optimization 

Simon Thomas, Dani Jones, Talea Mayo, John Taylor, Henry Moss, Dave Munday, and Ivan D. Haigh

Climate change is expected to increase the potential intensity and size of tropical cyclones, with implications for storm surges and other damaging effects associated with them. However, quantifying the maximum possible storm surge and the sensitivity of storm surges to the properties of a tropical cyclone remains computationally expensive and complex.

In this study, we use machine learning to find the upper bounds of storm surges, considering the coastline near New Orleans as a case study. To do this, we make use of the well-established potential intensity (Emanuel, 1986) and the recently introduced potential size (Wang et al., 2022) upper bounds for tropical cyclones. These encapsulate the physical constraints tropical cyclones will encounter in a changing climate. We use the max-value entropy search acquisition function from Bayesian optimization (Wang et al., 2017) to efficiently find the largest storm surge at each point along the coast given those constraints. The individual storm surge estimates are produced by forcing a barotropic ocean circulation model ADCIRC (Luettich, 1991) with a set of idealized tropical cyclones, the characteristics of which are determined by the Bayesian optimization procedure. To extrapolate these findings into the future, we replicate our experiment under a high emission CMIP scenario (SSP-585) for the year 2100, using potential intensity and potential size as constraints, evaluating potential differences and implications brought on by changing climate conditions.

Our study provides another way of understanding how climate change can influence storm surges. It aims to forge a pathway to more precise, computationally efficient storm surge predictions in the context of climate change, addressing a pressing issue for coastal regions globally. Our novel approach could easily be transferred to other coastlines around the world, influenced by tropical cyclones. 

 

References:

Emanuel, K.A., 1986. An air-sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. Journal of Atmospheric Sciences, 43(6), pp.585-605.

Wang, D., Lin, Y. and Chavas, D.R., 2022. Tropical cyclone potential size. Journal of the Atmospheric Sciences, 79(11), pp.3001-3025.

Wang, Z. and Jegelka, S., 2017, July. Max-value entropy search for efficient Bayesian optimization. In International Conference on Machine Learning (pp. 3627-3635). PMLR.

Luettich, R.A., R.H. Birkhahn and J.J. Westerink, 1991, Application of ADCIRC-2DDI to Masonboro Inlet, North Carolina: A brief numerical modeling study, Contractors Report to the US Army Engineer Waterways Experiment Station, August, 1991

How to cite: Thomas, S., Jones, D., Mayo, T., Taylor, J., Moss, H., Munday, D., and Haigh, I. D.: Finding the potential height of storm surges in a changing climate using Bayesian optimization, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19806, https://doi.org/10.5194/egusphere-egu24-19806, 2024.

EGU24-19910 | Orals | NH5.3

Assessing the impacts of coastal and riverine urban floods in the future climate, results from the SCORE project. 

Carlo Brandini, Michele Bendoni, Francesca Caparrini, Andrea Cucco, Stefano Taddei, Massimo Perna, Alberto Ortolani, Iulia Anton, Roberta Paranunzio, and Salem Gharbia

Assessing the local effects of climate change on coastal areas, and in particular on coastal cities and settlements, is one of the greatest challenges facing our society, aimed at finding innovative and sustainable solutions to increase the resilience of coastal communities to adverse climatic actions. In particular, the use of climate data is crucial for defining a downscaling strategy that starts with climate services on a global scale and goes on to define impacts on a local scale. A comprehensive 'global to local' approach is fundamental to envisage coastal flooding problems.

Estimating the effects of CC in coastal cities  requires increasing the resolution of urban-scale models to unprecedented levels, to simulate land and coastal flooding conditions for various scenarios and with different return periods, also allowing for the evaluation of financial resilience strategies or ecosystem solutions for adaptation, following a true multidisciplinary approach and fostering, through participatory approaches, the public engagement of citizens, scientists and policy-makers, to identify solutions technically and socially acceptable.

We present the results of a full “global to local” study, to estimate the effects of coastal and riverine floods associated with extreme events at three coastal cities located in the Mediterranean Sea (Massa - Italy and Villanova - Spain) and the Bay of Biscay (Oarsoaldea - Spain), for different climate projections. The present work is part of the H2020-SCORE project and the analyzed cities are organized in a network of Coastal City Living Labs (CCLLs). We implemented a relocatable modeling chain which uses the data from a Regional Circulation Model (RCM) provided by EuroCordex as atmospheric forcing to three different models: i) a WaveWatchIII model for the simulation of wave forcing, ii) a SHYFEM model for the simulation of storm surges and sea-level dynamics iii) a LISFLOOD model for river discharge. The wave and sea-level models are implemented on unstructured grids with increasing resolution at the target cities, whereas the river discharge is determined considering the basin located upstream of the city. The simulations are performed for the evaluation, historical, RCP45 and RCP85 datasets associated with the CMIP5 experiment. Time series of wave height and water level close to the coast, and river discharge are employed in an extreme value analysis procedure to obtain values associated to specific return periods (namely 25, 100, 200 years). These values are employed to simulate floods due to the effect of storm surge and peak river discharge, by means of a hydraulic model built on a high-resolution digital elevation model of the coastal city, including information on buildings, coastal bathymetry and river cross sections. Preliminary results from the calculated hazard maps (water depth associated with a return period event) show interesting differences in the three analyzed coastal cities based on different exposure to coastal or riverine floods.

How to cite: Brandini, C., Bendoni, M., Caparrini, F., Cucco, A., Taddei, S., Perna, M., Ortolani, A., Anton, I., Paranunzio, R., and Gharbia, S.: Assessing the impacts of coastal and riverine urban floods in the future climate, results from the SCORE project., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19910, https://doi.org/10.5194/egusphere-egu24-19910, 2024.

EGU24-2109 | ECS | Orals | OS2.4

Evaluating the numerical modeling of storm surges induced by hurricanes 

Alisée A. Chaigneau, Melisa Menéndez, Marta Ramírez-Pérez, and Alexandra Toimil

Coastal zones are increasingly threatened by extreme sea level (ESL) events. Storm surges (i.e. sea level variations due to meteorological drivers) are one of the most hazardous components of ESLs, especially in regions prone to tropical cyclones. This study aims to explore factors affecting the performance of numerical modeling in simulating storm surges induced by hurricanes. The focus is on the tropical Atlantic region, covering the Caribbean Sea and the Gulf of Mexico.

Several historical hurricanes causing severe coastal impacts are simulated. The skill of the simulations to reproduce the storm surge contribution to ESLs is evaluated against recorded values from tide-gauge stations. The modeled peak surge maxima and the hourly time series are analyzed during these extreme events.

The factors explored in this study encompass the numerical model, oceanic and atmospheric forcings, physical parameterizations, spatial resolution, and baroclinic/barotropic modes.

Two ocean models (ADCIRC and NEMO) are intercompared using a similar configuration: domain, spatial resolution (~9 km), bathymetry and barotropic mode. The sensitivity of the atmospheric forcings is assessed by comparing storm surges induced by ERA5 reanalysis data and parametric wind models usually applied for hurricanes (e.g. Dynamic Holland Model, Generalized Asymmetrical Holland Model). The effect on storm surge due to non-linear interactions with the astronomical tide and variations in mean sea level is also investigated, as well as the sensitivity to different wind stress schemes. In addition, the baroclinic contribution to ESLs is studied using a configuration with 75 vertical levels. Finally, the role of the spatial resolution on the modeled storm surges is evaluated with a high-resolution domain of about 500 m in coastal areas.

The analysis of the numerical experiments reveals some interesting insights. ADCIRC and NEMO can simulate storm surges due to tropical cyclones in a similar way compared to tide gauges. In general, the ERA5 forcing outperforms the various parametric wind models for storm surge modeling, in terms of maximum values, correlation, and duration of extreme events. Non-linear interactions of tides and mean sea level with storm surges have minimal contribution in the storm surges induced by hurricane events. However, the baroclinic response significantly improves the storm surge estimations in some coastal areas (e.g. along the southeastern Florida peninsula). 

All the authors would like to thank the Government of Cantabria through the FENIX Project GFLOOD.

How to cite: Chaigneau, A. A., Menéndez, M., Ramírez-Pérez, M., and Toimil, A.: Evaluating the numerical modeling of storm surges induced by hurricanes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2109, https://doi.org/10.5194/egusphere-egu24-2109, 2024.

EGU24-2825 | ECS | Posters on site | OS2.4 | Highlight

Global estimation of storm surge seasonality and the effect of interannual variability. 

Ayoola Apolola, Philip Ward, José Antolínez, and Sanne Muis

Extreme storm surges exhibit significant seasonal and interannual variability influenced by large-scale climate modes. The goal of our work is to investigate the seasonality of storm surge extremes and the influence of interannual climate variability at the global scale, which to date is not fully understood due to lack of observations with long-records.  

To achieve this goal, we use storm surge levels derived from the Global Tides and Surge Model (GTSM) forced with the extended ERA5 climate reanalysis data spanning 1950-2022. Our methodology consists of two main steps. First, we classify the dataset into four seasons (Winter-DJF, Spring-MAM, Summer-JJA, Autumn-SON) and compute the number of events per season. Next, we conduct extreme value analysis on selected thresholds and explore their connections with climate modes.

Preliminary findings indicate that extreme surge events are more frequent and pronounced at higher latitudes during SON, with notable peaks in DJF. This is particularly significant in the North Sea and funnel-shaped coastlines such as Rio de la Plata, Arafura Sea, and Hudson Bay. In contrast, regions like the South China Sea, the Bay of Bengal, the Yellow Sea, and southern Australia experience more frequent surge extremes from JJA to SON with variations in peak season.

Equatorial regions, especially around Africa, have negligible surge extremes except for occasional tropical cyclones from late DJF, with peaks in MAM in Mozambique and Madagascar. Similarly, there are occasional tropical cyclone events in parts of the Caribbean with peaks in JJA.

The study findings have broader implications for understanding the global distribution and spatio-temporal variation of extreme surge events, which could help to provide guidance on the impacts of climate change in the future. Overall, the preliminary findings underpin the need to further explore what the drivers of storm surge variability are. 

How to cite: Apolola, A., Ward, P., Antolínez, J., and Muis, S.: Global estimation of storm surge seasonality and the effect of interannual variability., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2825, https://doi.org/10.5194/egusphere-egu24-2825, 2024.

EGU24-6238 | Orals | OS2.4

What can we learn on internal tides with the 1-day phase of SWOT ? 

Loren Carrere, Michel Tchilibou, Florent Lyard, Clément Ubelmann, and Gérald Dibarboure

The Surface Water and Ocean Topography (SWOT) altimetry mission launched in 2022 makes 2D observations of sea surface height (SSH) using SAR radar interferometric techniques.  Compared to previous altimetry missions, SWOT extends SSH observations to 15-30 km and offers opportunities to understand better ocean dynamic processes such as mesoscale, sub mesoscale and internal tides (IT).

     This study based on SWOT observations during the Calval (1-day orbit, from mid-March to mid-July) period gives insight into the capability of SWOT to observe IT.  We analyzed the SWOT tracks crossing the Brazilian coast around the Amazon shelf.  The results show that SWOT IT observations in this region are made up of mode 1 and mode 2 but also of strong higher mode (50-2 km).  The M2 coherent IT model deduced from SWOT presents the same spatial distribution as the M2 model from Zaron et al., 2019.  Over this period, the rate of incoherent internal tidal is over 0.5 for modes 1 and 2 and almost 0.9 for higher modes.

How to cite: Carrere, L., Tchilibou, M., Lyard, F., Ubelmann, C., and Dibarboure, G.: What can we learn on internal tides with the 1-day phase of SWOT ?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6238, https://doi.org/10.5194/egusphere-egu24-6238, 2024.

EGU24-7151 | Posters on site | OS2.4

Sensitivity analysis of coastal storm surge forecasting using NEMO-based CTSM model 

Nary La and Pil-Hun Chang

The present study introduces a high-resolution Coastal Tide/Storm surge model (CTSM). Recently, the NIMS (National Institute of Meteorological Sciences) developed the CTSM, based on the NEMO ocean model to enhance forecasting capabilities for sea conditions and storm surges. The CTSM is constructed with a two-dimensional barotropic sigma coordinates and has a 1 km horizontal resolution. It consists of Tide/Surge model and Tide model, and their residual is used as surge forecasts. The surge forecasts are then added to the harmonically predicted tides to give forecasts of total water level at the 30 tidal stations around Korea Peninsula. Based on the sensitivity studies, the constant values of 0.0275 and 1024 hPa are adopted as the Charnock coefficient, bottom friction and reference pressure of the model, respectively.
In addition, this study investigated the effect of temporal and spatial variations of Charnock coefficient on the surge forecasts during Typhoon HINNAMNO, which caused substantial damage to the Korean Peninsula in 2022. For this, the 2-D Charnock coefficients derived from an operational Coastal wave model are added to the CTSM. It was found that the Charnock values generally exceeded the model’s constant value of 0.0275 during typhoon period. This alteration in Charnock coefficient impacts on the surge forecasts especially near the coastal regions, showing about 10% increase in the sea level.

How to cite: La, N. and Chang, P.-H.: Sensitivity analysis of coastal storm surge forecasting using NEMO-based CTSM model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7151, https://doi.org/10.5194/egusphere-egu24-7151, 2024.

EGU24-7830 | Posters on site | OS2.4

Developing Best Practices in Tidal Analysis 

Andrew Matthews and the IAPSO Tidal Analysis Best Practice Study Group

The tide is generally the dominant component of a sea level record in many parts of the world and its analysis has therefore been a central part of oceanography for hundreds of years. Methods to predict the tide have changed over time, but have largely converged on the classical harmonic method, which is based on the principle that a series of tidal observations may be decomposed into a finite number of sinusoidal functions, known as tidal constituents, with angular speeds related to known astronomical frequencies.

Classical harmonic analysis is usually carried out using one of a number of software packages made available by scientists and oceanographic institutions. These are exceptionally useful, but within them they encode a series of assumptions and decisions that need to be made in order to carry out an analysis, including:

  • What is an appropriate set of constituents to use in a location, given the data available and the hydrodynamics of the area?
  • How does the analysis account for variations of the tidal constituents over time, for example over the nodal cycle?
  • How will our results be affected by non-tidal influences?

Furthermore, other approaches will be more successful in particular environments, for example in shallow waters when the tidal curve can be highly non-symmetric.

Non-experts in tidal science are often unaware of the options available, and the consequence of making the wrong decision. Furthermore, this knowledge is developed as rules-of-thumb within organisations based on many years of experience, so is not readily accessible. As a result, there is a need for some internationally agreed recommendations.

We recently held a tidal analysis workshop to discuss these matters, funded by the International Association for the Physical Sciences of the Oceans (IAPSO) as one of their Best Practice Study Groups. Here we present some illustrations of the issues mentioned above, along with some of our suggested approaches.

The best practice document is currently being drafted based on discussions held at the workshop, and when completed will be submitted to the International Oceanographic Commission’s best practice system (https://www.oceanbestpractices.org/).

How to cite: Matthews, A. and the IAPSO Tidal Analysis Best Practice Study Group: Developing Best Practices in Tidal Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7830, https://doi.org/10.5194/egusphere-egu24-7830, 2024.

EGU24-9923 | Posters on site | OS2.4

Refinements to harmonic tidal predictions in estuaries and shallow water. 

Joanne Williams and Angela Hibbert
Harmonic analysis is used to predict tidal heights from observations or model data. The usual method is to fit tidal constituents, at frequencies informed by astronomical cycles. In most cases the higher harmonics of these frequencies are sufficient to provide a good model of the tide to within observational accuracy, and successfully predict tides for decades outside the observational period, even including double high and low water and seasonal variations.
In shallow bays or estuaries the propagation of the tidal wave slows, leading to very slow draining of the water and much faster rise. The tidal waveform is closer to a saw-tooth shape than sinusoidal. So least-square fit of harmonics leads to Gibbs ringing artefacts around the discontinuity in slope just before the tide rises. These are often several tens of cm in the macrotidal regime of the UK, and complicate the assessment of surge modelling.
Though the problem is not new, we are still seeking a consistent and universally applicable solution. In practice manual corrections are often applied at individual sites. Or with enough data, more harmonics can be fitted to minimise the false peaks, but at the risk of over-fitting. In this presentation we quantify the severity of this problem in UK estuarine sites, improvements using the response method, and the subsequent effect on total water level  for operational storm surge forecasting.

How to cite: Williams, J. and Hibbert, A.: Refinements to harmonic tidal predictions in estuaries and shallow water., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9923, https://doi.org/10.5194/egusphere-egu24-9923, 2024.

EGU24-10223 | ECS | Orals | OS2.4

Storm surge events and associated dynamics in the North Atlantic 

Simon Barbot, Lucia Pineau-Guillou, and Jean-Marc Delouis

Storm surges events are investigated using the ECHAR method, which identify and quantify the different dynamical structures of a typical storm surge event. In the North Atlantic, analysis of 65 tide gauges revealed that storm surge events display 2 majors and 2 minors structures, each of them corresponding to specific ocean dynamics. The 2 major structures refer to a slow-time Gaussian structure, lasting around 24 days, associated with the impact of the atmospheric pressure and a fast-time Laplace structure, lasting around 1.4 days, mainly wind-driven. The absence of the Gaussian structure along the North America coasts is explained by storms of smaller spatial extension, compared to Europe. Concerning the minor structures, a negative  surge of around 6 cm just after the peak surge is observed over North America only. Such a sudden drop of the sea level is explained by the turning winds during the storm event, favored by the smaller spatial extension of storms. Finally, high frequency oscillations, with amplitude typically of 3 cm and up to 25 cm, are observed at some tide gauges. These oscillations refer to tide-surge interactions they are often maximum at a specific phase of the tide and/or enhanced because of resonant basins.

How to cite: Barbot, S., Pineau-Guillou, L., and Delouis, J.-M.: Storm surge events and associated dynamics in the North Atlantic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10223, https://doi.org/10.5194/egusphere-egu24-10223, 2024.

EGU24-10307 | Posters on site | OS2.4 | Highlight

Storm surge warning for the German North Sea coast 

Ludwig Schenk and Marlies Methe

Storm surges along the German North Sea coast are tidal surges that reach a peak of 1.5 metres or more above mean high water (MHW). Severe and very severe storm surges exceed 2.5 and 3.5 metres above mean high water respectively. Storm surges along the German North Sea coast are triggered by westerly winds from approx. 7 to 8 Beaufort. At the Hamburg, St. Pauli gauge, the long-term average is 5 to 6 storm surges per year; less frequent are severe (2 in 3 years) and very severe storm surges (every 5 years). The period of occurrence is essentially limited to the winter half-year.

The Federal Maritime and Hydrographic Agency (BSH) is responsible for warning of storm surges along the Baltic and North Sea coasts and the tidal river sections of the Ems, Weser, Jade and Elbe. Warnings of storm surges are distributed in very different ways. Warnings have been broadcast on the radio for many decades. In Hamburg, firecrackers are set off by the police. In recent years, dissemination via the BSH website and a customisable telephone distribution system has become established. Since the 2021/22 storm surge season, warnings have been fed into warning apps such as NINA via the Modular Warning System (MoWaS) of the Federal Office of Civil Protection and Disaster Assistance (BBK) and thus reach more directly affected citizens.

The possibilities offered by new media make it necessary to further develop warning strategies. For example, we are currently working closely with the BBK on the automated provision of warnings via the NINA warning app. This leads to faster and more precise distribution of storm surge forecasts.

The warnings and forecasts described take place against the background of the mean sea level rise and the associated rise in mean high water level. It is also the responsibility of the Federal Maritime and Hydrographic Agency to monitor this and to provide and analyse it at tide gauges such as Cuxhaven Steubenhöft, where measurements have been taken for around 180 years.

When creating the forecasts, we set up the Flood Early Warning System (FEWS), which pools and helps to process the data and creates and publishes reports. With the help of our developed Model Output Statistics System (BSH-MOS), precise and individualised forecasts up to one week into the future are possible for up to 40 gauges. Among other things, MOS evaluates water level measurements, wind forecasts from the German Weather Service (DWD) and area-based modelled water level forecasts from the BSH model system.

How to cite: Schenk, L. and Methe, M.: Storm surge warning for the German North Sea coast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10307, https://doi.org/10.5194/egusphere-egu24-10307, 2024.

EGU24-10476 | ECS | Orals | OS2.4

Combination of Extreme Water Levels and Waves in a Semi-enclosed Sea: Reconstruction of the Baltic Sea 2023 Storm Surge (Babet) 

Anna Adell, Aart Kroon, Björn Almström, and Caroline Hallin

The October 2023 storm surge, denoted Babet, caused severe flooding and unprecedented damage along the southwestern Baltic Sea coasts. The beginning of October 2023 was dominated by several westerly low-pressure systems over the Baltic Sea region. The abundance of westerly winds pushed water into the Baltic Sea basin through the Danish straits resulting in elevated water levels of +50 cm above normal in the basin. Around the 18th of October the wind direction shifted from west to north and subsequently to east while also increasing in intensity, with mean wind speeds of 25 m/s and gusts exceeding 30 m/s. This gave strong wind setup in the southwestern part of the Baltic Sea and the strong winds generated large waves as well as increasing the water levels further. Notably, the area experienced the most extreme storm conditions in over a century with the storm peak was reached during the night between the 20th to 21st October.

We present a study with results of the numerical model simulation using SWAN set up for the southwestern part to the Baltic Sea basin. The simulation combines the wave conditions derived from wind forcing and observed water levels from a network of observation gauges. These levels are compared to historical event statistics from an existing long-term hindcast model of wave climate conditions for the region. Finally, the results of storm surge levels are assessed in relation to observed flooding and erosion impact on natural coastal areas and impact to existing coastal protection.

How to cite: Adell, A., Kroon, A., Almström, B., and Hallin, C.: Combination of Extreme Water Levels and Waves in a Semi-enclosed Sea: Reconstruction of the Baltic Sea 2023 Storm Surge (Babet), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10476, https://doi.org/10.5194/egusphere-egu24-10476, 2024.

EGU24-10636 | Posters on site | OS2.4

The impact of storm surges on ocean tides: insights from numerical simulations 

Sanne Muis, Michael Hart-Davis, Jelmer Veenstra, Martin Verlaan, Joanne Williams, and Denise Dettmering

The interaction between tides and storm surges can significantly affect shallow water regions with large tidal ranges. In modelling studies, including the atmospheric forcing, which drives the storm surge estimations within the model, can result in changes to the amplitudes and phases of the major tidal constituents. In certain regions, this can have severe impacts on the tidal predictions.

A standard product used to provide the atmospheric forcing is the ERA5 product developed at ECWMF. Previous studies have shown the presence of tidal constituents within the sea level pressure data provided by ERA5 used in various applications. For example, the commonly used Dynamic Atmospheric Correction derived from these data, which is used to correct satellite altimetry measurements for the atmospheric influence on the radar returns, has been shown to significantly impact the estimation of ocean tides from satellite altimetry. 

The Global Tide and Surge Model (GTSM), developed at Deltares, allows for the global estimation of ocean tides with and without atmospheric forcings. This presents the possibility of evaluating the influence of storm surges on the estimation of individual tidal constituents and the resultant prediction of tidal heights. In this poster, three model simulations are produced, which are as follows: an ocean tide-only version, a storm surge-only simulation and a tide plus storm surge version. The eight major tidal constituents are evaluated globally to assess the changes in their respective amplitudes and phases. Finally, several case studies are presented in regions with high influence on the individual constituents by evaluating the results of the tidal predictions with respect to in-situ measurements. 

How to cite: Muis, S., Hart-Davis, M., Veenstra, J., Verlaan, M., Williams, J., and Dettmering, D.: The impact of storm surges on ocean tides: insights from numerical simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10636, https://doi.org/10.5194/egusphere-egu24-10636, 2024.

EGU24-10850 | ECS | Posters on site | OS2.4

Estimation of time-varying tidal amplitudes using a state space model 

Koen Haakman, Cornelis Slobbe, and Martin Verlaan

Recently, global trends in tidal amplitudes have been estimated from satellite radar altimetry data by including several constituents with linearly changing amplitudes into the harmonic analysis least squares problem. However, changes in tidal amplitudes do not have to be linear. The assumption of linearity can potentially obscure the true time-varying evolution of tidal amplitudes. Revealing deviations from linearity could be useful for attribution of physical mechanisms responsible for changes in tidal amplitudes and may have implications for future projections.

To address this limitation, an algorithm that estimates time-varying amplitudes without making any assumptions about the temporal shape is desired. To that end, we propose to use a state space time series model, for which time-varying parameters are estimated using a Kalman filter. Unlike the conventional least squares problem, the state space approach allows the value of a parameter to vary at each time step, providing a more flexible representation of the dynamic nature of tidal amplitude changes.

We apply the model to global TOPEX/Poseidon and Jason altimetry data from 1993-2023 at satellite crossover locations, aiming to identify if and where tidal amplitude changes are deviating from linearity. Provisional results show that, in many locations, the M2 amplitude trend is close to linear during the considered timescale. Nevertheless, there are some regions where the estimated M2 amplitude trends are clearly deviating from linearity. However, these results should be interpreted with caution since the 95% confidence intervals around the estimated amplitudes are often of similar magnitude as the temporal variability of the amplitude. One potential strategy to mitigate this issue involves increasing the number of samples per time series by binning altimetry observations, as opposed to restricting the analysis solely to crossover locations. To fully understand whether the generated time-varying amplitudes are reliable, the state space model will be thoroughly tested with synthetic data.

How to cite: Haakman, K., Slobbe, C., and Verlaan, M.: Estimation of time-varying tidal amplitudes using a state space model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10850, https://doi.org/10.5194/egusphere-egu24-10850, 2024.

EGU24-10958 | Orals | OS2.4 | Highlight

The connection between coastal sea level and local ocean dynamics, and its relation to high-tide flooding along southern New England (U.S.)  

Carolina M.L. Camargo, Christopher G. Piecuch, and Britt Raubenheimer

According to NOAA’s Annual High Tide Flooding Outlook [1], the number of high-tide flooding days along the US East coast has increased  rapidly in recent years. High-tide flooding, also known as nuisance flooding, identifies floods that can occur in the absence of storms, for example, simply due to above-normal water levels.. Due to sea-level rise, it is predicted that, by 2050, coastal communities across the U.S. will experience high-tide flooding on average 45 to 85 days per year. Predicting the frequency of future coastal flooding is vital for the development and maintenance of coastal cities. Here we discuss the role of  local ocean dynamics to coastal flooding.

Along the Northeast US coast, an important driver of coastal sea-level variability is ocean dynamics, which includes large-scale circulation, such as the Gulf Stream, but also to smaller local ocean currents. An important circulation feature in this region is the Shelf break jet (SBJ). The SBJ flows equatorward from the Labrador Sea towards the Gulf Stream at Cape Hatteras following the shelf break along the Northeast US coast. We use velocity data from the Ocean Observatory Initiative (OOI) Coastal Pioneer Array and tide-gauge data during 2014-2022 to establish the connection between coastal sea level and local ocean circulation over the shelf and the slope. Located at the New England shelf break,  about 75 nautical miles south of Martha’s Vineyard, the Array is composed of seven site moorings, spread from the shelf to offshore of the shelf break. Each mooring contains, among other instruments, an upward-looking ADCP, which measures three-dimensional velocities throughout the water column. A spectral coherence and admittance analysis reveal that, after removing the effects of tides and the inverted barometer, about 30% of the coastal sea-level variance in the 1—15-day band in this region is related to the SBJ transport. This relationship has a clear spatial pattern: we find significant coherence between SBJ transport and coastal sea level from the South of New England to as far south as the Delaware coast, depending on frequency.

Since this frequency band coincides with the frequency variability of storm surges, we pose the question: “Are any of the flood events registered in this region related to SBJ variability”? To answer this question, we focus on 6 tide gauges stations along southern New England, which feature the highest coherence with SBJ transport in the 1—15-day band. When the jet-related variability is regressed off the tide-gauge sea level data over these frequencies, the number of minor flood days reduces. Thus, a fraction of coastal floods in these locations might be related to SBJ variability. This simple exercise highlights the importance of considering local ocean dynamics when projecting future coastal flooding.

 

Reference:

[1] https://tidesandcurrents.noaa.gov/high-tide-flooding/annual-outlook.html

How to cite: M.L. Camargo, C., G. Piecuch, C., and Raubenheimer, B.: The connection between coastal sea level and local ocean dynamics, and its relation to high-tide flooding along southern New England (U.S.) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10958, https://doi.org/10.5194/egusphere-egu24-10958, 2024.

EGU24-12341 | Orals | OS2.4

The effect of the 18.6-year lunar nodal cycle on steric sea level changes 

Dewi Le Bars, Sterre Bult, Ivan Haigh, and Theo Gerkema

We show that steric sea-level varies with a period of 18.6 years along the western European coast. We hypothesize that this variation originates from the modulation of semidiurnal tides by the lunar nodal cycle and associated changes in ocean mixing. Accounting for the steric sea level changes in the upper 400 m of the ocean solves the discrepancy between the nodal cycle in mean sea level observed by tide gauges and the theoretical equilibrium nodal tide. Namely, by combining the equilibrium tide with the nodal modulation of steric sea level, we close the gap with the observations. This result supports earlier findings that the observed phase and amplitude of the 18.6-year cycle do not always correspond to the equilibrium nodal tide. This finding allows to better filter natural variability when estimating the current rate of sea level rise along the European coast. Practical applications include the detection of an acceleration of sea level rise and the comparison between tide gauge and satellite observations with sea level projections.

How to cite: Le Bars, D., Bult, S., Haigh, I., and Gerkema, T.: The effect of the 18.6-year lunar nodal cycle on steric sea level changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12341, https://doi.org/10.5194/egusphere-egu24-12341, 2024.

EGU24-13233 | Posters on site | OS2.4 | Highlight

Twin storms and the performance of storm surge barriers 

Alexander Bakker and Dion Rovers

Early 2022, four severe storms (Corrie, Dudley, Eunice and Franklin) raged over the Netherlands, of which the latter three hit the Dutch coast in only four days. The question is how well the Dutch flood protection system can deal with such a series of storms. Will there be enough time to recover from the previous storm?

The Maeslant barrier is a storm surge barrier near Rotterdam that exists of two enormous floating sector doors. In rest, they are safely located in the dry docks along the shore. Yet, in case of the most severe storms the doors are floated to the middle of the river and submerged to retain storm surges from the sea. After the storm they are floated up again and moved back to the docks. During its operation the Maeslant barrier is likely to be more vulnerable for small damages, that may lead to the temporal unavailability of the surge retaining function.

This study investigates 1) the probability that the barrier needs to close shortly after a previous closure and 2) the flood risk as a result of failure of the second closure. Herewith, we distinguish two different phenomena. The two-top storm is a single storm during which the barrier needs to close twice and open in between as a result of the astronomical tide. The twin storm (or even triplet or multiple storm) is a cluster of severe storms that succeed each other shortly.

The probabilities of both phenomena are estimated from a data-analysis of a long record of sea level observations at Hoek van Holland, close to Rotterdam. The associated flood risk is estimated from a simple conceptual model of the failure probability of the Maeslant barrier.

How to cite: Bakker, A. and Rovers, D.: Twin storms and the performance of storm surge barriers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13233, https://doi.org/10.5194/egusphere-egu24-13233, 2024.

EGU24-14262 | ECS | Orals | OS2.4 | Highlight

Counting the contributions of tides and surges to changing coastal flooding 

Karen Palmer, Christopher Watson, Hannah Power, and John Hunter

Globally, the frequency of high tide exceedances is increasing with sea level rise. However, the rate of mean sea level (MSL) alone is not enough for estimating changes in coastal flooding. Understanding the drivers of changing exceedance frequency must also factor in additional contributions from tides and surges, accounting for the importance of local variability and interactions. Our novel Joint Probability of Maxima Method represents these complex processes nonparametrically, efficiently enabling the estimation of exceedance thresholds at user defined average recurrence intervals (ARIs). We compared exceedance levels between two recent 19-year epochs for 166 widely distributed coastal tide gauge sites, at 1, 5, and 10 year ARIs. We then quantified the specific contributions of MSL, tide, and skew surge components to the net changes in exceedance levels in metric terms, relating them directly to the height of coastal protections. Our approach demonstrates that high water exceedance levels are, on average, increasing more than MSL alone, and that changing exceedance frequency can depend significantly on local characteristics of sea level variability. On average, exceedance frequency doubled over the epochs assessed.

How to cite: Palmer, K., Watson, C., Power, H., and Hunter, J.: Counting the contributions of tides and surges to changing coastal flooding, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14262, https://doi.org/10.5194/egusphere-egu24-14262, 2024.

Severe storm tides are one of the main hazards for the German coast. Understanding the development of storm tides and the resulting water levels supports decision-making. We have used a hydrodynamic model to simulate several of the highest observed storm tide events for the locations Norderney, Cuxhaven and Husum (German Bight). The hydrodynamic model is forced by atmospheric (century) reanalysis data (20CR-ensembles, ERA5 and UERRA-HARMONIE) and FES-tides.  In general, the simulations of the severe storms with tracks over Scandinavia and a strong wind gradient over the North Sea show better peak water level results and lower variability compared with more southerly storms with storm tracks over the North Sea. However, the highest observed water level in the German Bight could not be simulated with any of the considered atmospheric forcings. The individual weather situations with the corresponding storm tracks are analysed in order to better understand their different effects on the peak storm tides, their variability and their predictability.

How to cite: Meyer, E. M. I. and Gaslikova, L.: How good are simulations of historical severe storm tides forced by atmospheric reanalysis products in the German Bight?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14664, https://doi.org/10.5194/egusphere-egu24-14664, 2024.

EGU24-15703 | ECS | Posters on site | OS2.4

Unravelling Spatial Variability of Sea Level Extremes in the Netherlands: Insights from Observational Data 

Mia Pupić Vurilj, Jose A. Alvarez Antolinez, Oswaldo Morales Napoles, Sanne Muis, and Fernando J. Mendez

Coastal regions in the Netherlands face persistent challenges from sea level extremes, prompting a comprehensive exploration of their spatial variability. Our study explores the nuances of extreme sea level events across the country, using the observed sea level data from the GESLA-3 (Global Extreme Sea Level Analysis) dataset. We analyse 16 stations with observational periods spanning from 38 to 68 years.

The total observed sea level is detrended and split into two components: (i) the tidal component, derived using harmonic analysis, and (ii) the non-tidal residual, calculated by subtracting the obtained tidal signal from the observed sea-level records. Extremes of both total sea level and non-tidal residual are then identified using the Peak over Threshold method, opting for a 70th percentile threshold. This choice allows us to examine less severe scenarios, suitable for risk assessments or planning purposes.

Our preliminary analysis of extreme event characteristics, such as the duration and intensity of an event, indicates significant spatial differences across stations. Correlation coefficients between stations, particularly for total extreme sea level characteristics and extreme non-tidal residual characteristics (duration and intensity), show a noticeable pattern that consistently reveals higher values between stations with similar latitudes across all variables. Moreover, the distributions of total extreme sea level characteristics exhibit noteworthy differences as well - for example, in southern regions, the distributions of intensity are more broadly dispersed and skewed to the right, signifying higher events than those in the northern counterparts. However, this distinction is less pronounced when focusing solely on the non-tidal residual, possibly since the total sea level is influenced by factors such as the river inflow, prevalent in the south, and tidal propagation behaviour in the North Sea.

As we progress with our analysis, we plan to apply a supervised learning method for classifying extreme events based on storm characteristics, and conduct a clustering analysis to reveal hidden spatial patterns of extreme events, for both total sea level and non-tidal residual. Furthermore, we aim to explore the interactions between surges and tides across different classes of extreme events, unravelling the underlying driving mechanisms of enhanced compound events.

In summary, our ongoing study of sea level extremes in the Netherlands, from spatial dynamics to event characteristics, will provide a solid foundation for understanding the driving mechanisms behind the extremes, gaining insights about their natural variability, and evaluating the impacts of changing climatic conditions.

How to cite: Pupić Vurilj, M., Alvarez Antolinez, J. A., Morales Napoles, O., Muis, S., and Mendez, F. J.: Unravelling Spatial Variability of Sea Level Extremes in the Netherlands: Insights from Observational Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15703, https://doi.org/10.5194/egusphere-egu24-15703, 2024.

EGU24-15861 | ECS | Orals | OS2.4

Optimized Prediction of Shallow-Water Tides with the Global Ocean Tide Model TiME 

Roman Sulzbach, Henryk Dobslaw, and Maik Thomas

Usually, the most accurate ocean tide atlases are produced by incorporating satellite altimetry observations into the modeling process. This strategy works best for large amplitude, i.e., major, ocean tides, which prominently appear in satellite observations. However, in the case of sparsely available observations or reduced observation precision (e.g., small-amplitude tides), purely numerical ocean tide models can provide valuable constraints for improving tidal predictions. For example, third-degree ocean tides, and several radiational tides were successfully predicted and identified in geodetic records by employing barotropic ocean models (e.g., Sulzbach et al. 2022; doi: 10.1007/s00190-022-01609-w), while they are hard to identify in altimetric records.

A further complex facet of ocean tidal dynamics is shallow-water tides (SWTs), which are not directly generated by celestial bodies, but through the non-linear interaction of ocean tides in shallow waters. While appearing relatively small in amplitude in the deep ocean, SWTs exhibit more prominent signals in shallow waters and are also relevant for the processing of geodetic satellite observations, e.g., altimetry and gravimetry. The responsible non-linear tide-generating processes depend on several spatially variable characteristics of the ocean, e.g., seafloor roughness and ocean depth, and the accurate incorporation of major tides into the ocean model. Therefore, their excitation mechanism is only approximately known in contrast to gravitationally-excited tides. This uncertainty poses an additional challenge to the numerical modeling process.

Here, we reapproach the simulation of shallow-water tides with the ocean tide model TiME by readressing the parameterization of potentially non-linear ocean-bottom friction. The barotropic ocean tide model has been refined to incorporate updated energy dissipation mechanisms by topographic wave drag and sea ice friction, possesses a truly global grid based on the rotation of the numerical poles, and operates at a relatively high resolution of 1/12°. Most importantly, the effect of Self-Attraction and Loading (SAL) is modeled based on fast decomposition into Spherical Harmonic Functions at each time step. Thus, the model does not rely on prior estimates of the SAL effect, which are only weakly constrained for the SWTs, but estimates SAL self-consistently in real-time.

The ocean tide model is optimized to simultaneously depict an accurate prediction of the major lunar tide M2, as well as its overtides in shallow waters (e.g., M4). Validation relies on geodetic data sets of complementary characteristics and focuses on a densely observed focus region: the European Shelf Sea. Based on multiple validation metrics, probing the sea surface height anomaly and the gravitational field of the SWTs, the effect of the improved bottom friction parameterization and the self-consistent effect of SAL are investigated. The simulations indicate that incorporating the self-consistent SAL effect for nonlinear tides significantly affects tidal propagation in the open ocean, similar to diurnal and semi-diurnal tides. Further, tuning of linear and nonlinear bottom friction effectively allows the reduction of the combined RMS for linear and nonlinear tides.

How to cite: Sulzbach, R., Dobslaw, H., and Thomas, M.: Optimized Prediction of Shallow-Water Tides with the Global Ocean Tide Model TiME, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15861, https://doi.org/10.5194/egusphere-egu24-15861, 2024.

EGU24-17298 | ECS | Posters on site | OS2.4

Unlocking Insights in Historic Tidal Records with Analysis Methods Tailored to High-Low Tidal Data 

Joris Beemster, Paul Torfs, and Ton Hoitink

Water-level measurements, sometimes spanning centuries, offer a valuable historical perspective. Although contemporary tidal data is collected digitally at high frequencies, historical records often merely consist of basic high and low water levels. Recognizing the value of these low-resolution tidal records, recent 'data rescue efforts' focus on digitizing and preserving them. Current tidal analysis methods, optimized for high-frequency data, fall short in exploiting the potential of high- and low-water observations.

Here, we introduce a specialized tidal analysis methodology tailored for high- and low-water observations. Leveraging equilibrium tide information and the unique characteristics of these observations, such as a derivative constraint, we enhance the analysis of historical records. Additionally, we explore interpolation methods for high- and low-water observations, aiming to address the possibilities and limitations associated with these data.

Our approach has the potential to offer valuable insights into century-scale water level changes, and to unravel the contributions by tides, river discharge, mean sea level, storm surges and interactions among those governing factors to water level variation. A key ambition we have is to reveal the hydrodynamic consequences of human interventions, which are difficult to distinguish from each other. We hope the new technique will encourage to continue digitization of historic high-low-tidal observations, and allow to demonstrate the role of intertidal areas in modulating water level extremes.

How to cite: Beemster, J., Torfs, P., and Hoitink, T.: Unlocking Insights in Historic Tidal Records with Analysis Methods Tailored to High-Low Tidal Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17298, https://doi.org/10.5194/egusphere-egu24-17298, 2024.

EGU24-17544 | ECS | Posters on site | OS2.4

Improving the temporal resolution of GNSS-IR water level monitoring using single-cycle periodogram 

Peng Feng, Rüdiger Haas, and Gunnar Elgered

GNSS-IR represents an innovative technique for monitoring water levels. By analyzing the frequency of interference patterns between the direct GNSS signals and the signals reflected off the water surface, GNSS-IR offers a robust alternative to traditional tide gauges. GNSS-IR provides various advantages, including cost savings, convenient implementation, and accurate separation of vertical land motion. Recently, commercial companies started to adopt GNSS-IR for operational water level monitoring campaigns. The Lomb-Scargle Periodogram (LSP) is widely used to determine the frequency of interference patterns in the GNSS signal-to-noise ratio (SNR) data. Subsequently, the frequency/period can be converted into reflector height and water level. The LSP retrieves only one dominant frequency for each satellite and each channel, ascending or descending, over a time period longer than 20 min. Consequently, the temporal resolution of GNSS-IR water level measurements with LSP is lower compared to traditional tide gauges. High-temporal-resolution water level data would be valuable for applications like coastal hydrodynamics and hurricane studies. To address the temporal resolution, we developed a Single-Cycle Periodogram (SCP) analysis. The SCP analysis uses the LSP retrieval as a priori value and determines the period for each SNR cycle by tracking the maximum/minimum point corresponding to constructive/destructive interferences. Due to the reduced data span, the SCP suffers from noise. To improve the data quality of the interference patterns, we installed a GNSS antenna 90 degree tilted, facing the horizon, taking advantage of the antenna gain characterises. Such an experimental installation exists at the Onsala Space Observatory, with a relative small reflector height of approximately 3 m. Usually a small reflector height GNSS-IR installation results in low temporal resolution due to few interference fringes. However, using the proposed SCP analysis, preliminary results from 26 days of data indicate a significant increase in the number of water level retrievals. The LSP method yields approximately 200 unevenly distributed results per day, with occasional gaps exceeding 30 min. The SCP method gives approximately 10 times more retrivals. Furthermore, using the nearby traditional tide gauge (in the Swedish observation network of sea level) as a reference, the SCP retrievals, averaged over 6 min, provide a higher accuracy compared to the unevenly distributed LSP results.

How to cite: Feng, P., Haas, R., and Elgered, G.: Improving the temporal resolution of GNSS-IR water level monitoring using single-cycle periodogram, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17544, https://doi.org/10.5194/egusphere-egu24-17544, 2024.

EGU24-19209 | ECS | Posters on site | OS2.4

A Stochastic Deep Learning Approach for Projecting Storm Surges in the Context of Climate Change 

Simon Treu, Matthias Mengel, and Katja Frieler

Projections of sea level rise are vital for assessing the impacts of climate change, especially in coastal regions. Present sea level rise projections are primarily focused on monthly water levels, but tend to underrepresent the critical role of storm surges. There are some studies that also provide projections of storm surges along global coastlines based on numerical models using meteorological forcing data from Global Climate Models (GCMs). However, those applications are limited by coarse meteorological inputs as well as the computational demands placed by running numerical models for an ensemble of different GCMs and climate change scenarios.

We propose a stochastic deep learning model trained on model output from numerical surge models. It is designed to capture the spatial and temporal dependencies that are characteristic of storm surge time series. Our approach generates potential storm surge scenarios that are consistent with GCM outputs but are not directly determined by those meteorological inputs. A second advantage is that the trained machine learning model has lower computational demands than traditional numerical models which makes it possible to explore different GCMs and climate change scenarios.

How to cite: Treu, S., Mengel, M., and Frieler, K.: A Stochastic Deep Learning Approach for Projecting Storm Surges in the Context of Climate Change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19209, https://doi.org/10.5194/egusphere-egu24-19209, 2024.

EGU24-19316 | Posters on site | OS2.4

Changes in ocean tides by the end of the 21st century in response to stronger stratification 

Leigh MacPherson, Lana Opel, Michael Schindelegger, Arne Arns, and Athanasios Vafeidis

Recent model results in combination with observations have provided a first coherent picture of secular changes in ocean tides since 1993. Strengthening of ocean stratification has been identified as an important driver of the observed secular trends, where the barotropic tide is primarily affected through enhanced tidal conversion at topography. These changes are responsible for open-ocean trends in the order of 0.1 mm yr-1 for the barotropic M2 tide, increasing to magnitudes comparable to the tidal response to sea level change (0.2—0.4 mm yr-1) in several coastal regions. This has ramifications for global projections of future extreme sea levels, which either neglect changes in tides or consider them solely as a function of sea level rise. In this study, we employ a global high-resolution (1/12°) internal-tide permitting numerical ocean model to quantify future changes in ocean tides until 2100 as a result of upper-ocean warming and the concomitant increase in stratification. We simulate the evolution of leading tidal constituents in 5-year average time slices and use EC-Earth3P HighResMIP density data to constrain the model’s background stratification. As the Representative Concentration Pathway (RCP) in the EC-Earth3P simulation is a high greenhouse gas emission scenario (RCP8.5), we also consider data from a CM2.6 coupled global climate model, which is more closely aligned with a medium stabilisation scenario (RCP6.0).

How to cite: MacPherson, L., Opel, L., Schindelegger, M., Arns, A., and Vafeidis, A.: Changes in ocean tides by the end of the 21st century in response to stronger stratification, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19316, https://doi.org/10.5194/egusphere-egu24-19316, 2024.

EGU24-19451 | ECS | Posters on site | OS2.4 | Highlight

Analysing extreme sea levels on the Finnish coast using Block Maxima and Peak Over Threshold approaches 

Ulpu Leijala, Milla Johansson, and Havu Pellikka

Melting of the land-based ice and warming of the oceans around the world has resulted in acceleration of the pace of global mean sea level rise. Higher mean sea level causes more frequent extreme sea levels. This forces coastal cities urgently to do major preparedness and adaptation measures.

In Finland, preparedness for coastal flooding hazards is relevant even though protection given by the post-glacial land uplift is helpful. This is especially true on the Finnish southern coast, where mean sea level rise is foreseen and increase of probability of high sea levels within the 21st century is expected (Pellikka et al., 2023, 2018). In the Finnish coastal area, the extreme sea level estimates are used e.g. to support infrastructure planning, flood maps and safe operation of nuclear power plants.

On a short timescale, sea level variations are driven on the Finnish coast by storm surges, wind induced oscillations within the bays, and tides (playing a minor role). On the long-term side, global mean sea level rise, land uplift and the water inflow and outflow in the Danish straits (which change the total amount of Baltic Sea water) are the main factors controlling the sea level behaviour.

In this presentation, a study aiming at improving extreme sea level estimates in Finland will be illustrated. Tentative results on how different sampling techniques and extrapolation approaches affect the probability estimates of coastal floods will be presented.

Altogether 90 years of observations from the 13 Finnish tide gauges are analysed. We apply two different well-known sampling methods (Block Maxima and Peak Over Threshold) to the high tail of the sea level distribution and investigate which extrapolation function belonging to the family of Generalized Extreme Value (GEV) distribution matches best to the Finnish tide gauge observations. The results will be grouped into four coastal regions in Finland: the Gulf of Finland and Archipelago Sea in the south, and the Bothnian Sea and Bay of Bothnia in the west.

 

Pellikka, H., Johansson, M. M., Nordman, M., and Ruosteenoja, K., 2023: Probabilistic projections and past trends of sea level rise in Finland, Nat. Hazards Earth Syst. Sci., 23, 1613–1630, https://doi.org/10.5194/nhess-23-1613-2023

Pellikka, H., Leijala, U., Johansson, M. M., Leinonen, K., Kahma, K. K., 2018: Future probabilities of coastal floods in Finland, Continental Shelf Research, 157, 32-42, https://doi.org/10.1016/j.csr.2018.02.006

How to cite: Leijala, U., Johansson, M., and Pellikka, H.: Analysing extreme sea levels on the Finnish coast using Block Maxima and Peak Over Threshold approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19451, https://doi.org/10.5194/egusphere-egu24-19451, 2024.

EGU24-19556 | Orals | OS2.4

Exploiting the wealth of satellite radar altimeter data to calibrate regional, high-resolution hydrodynamic models 

Cornelis Slobbe, Henrique Guarneri, and Martin Verlaan

To exploit the wealth of satellite radar altimeter data in calibrating the regional, high-resolution 2D tide-surge Dutch Continental Shelf Model version 7 (DCSM) model covering the northeast Atlantic including the North Sea and Wadden Sea requires an approach that can be applied to the separate water level variability contributors. In this study, we aim to improve DCSM's ability in representing the low-frequency water level variability by assimilating data acquired by the TOPEX/Poseidon and Jason (TPJ) satellites. This variability, caused by physical processes not included in the model’s governing equations or forcing terms, is a major source of errors in the operational forecasting of water levels. To validate the impact of the data assimilation, we used i) S3-derived water levels acquired over the southern North Sea and Wadden Sea that were produced in the context of ESA’s HYDROCOASTAL project, and ii) tide gauge records required at 149 locations throughout the DCSM model domain. The results show that the impact of the assimilation is substantial. At the tide gauge locations, the median SD of the residual monthly-mean water levels reduced from 6.2 cm to 2.8. The impact cannot be assessed from the HYDROCOASTAL data. The most likely explanation is the fact that these data are still impacted by the tidal errors in the DCSM-derived tide-surge water levels.

How to cite: Slobbe, C., Guarneri, H., and Verlaan, M.: Exploiting the wealth of satellite radar altimeter data to calibrate regional, high-resolution hydrodynamic models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19556, https://doi.org/10.5194/egusphere-egu24-19556, 2024.

EGU24-19736 | ECS | Posters on site | OS2.4

An exploration of the potential of using storm characteristics from long synthetic time series of wind and water levels for operational forecasting 

Paulina Kindermann, Oswaldo Morales Napoles, and José Antonlínez

The Dutch coast is characterized by dikes, dunes, and structural barriers with low-lying, densely populated hinterland, which makes the area very vulnerable to coastal flooding. Therefore, the reliability of flood forecasting models is of great importance: accurate short-term forecasts (up to 2 weeks lead time) are necessary for operational decision-making processes (e.g. closing the storm surge barriers on time), while mid-term forecasting (seasonal) is useful for the planning of maintenance, for example. However, the uncertainty of forecasts naturally increases with longer lead times, which means that the extent of a storm is often only known on short term, leaving little time to take safety measures (Pardowitz et al., 2016). With a changing climate, the uncertainty in forecasting might even increase. Improving our understanding of the characteristics of storm evolutions in present and future climate plays a fundamental role to reduce uncertainty in forecasting models.

In recent years, research into storms and resulting extreme sea levels along the Dutch coast has been boosted by the availability of long time series of meteorological data in the current climate, from the seasonal forecasting system (SEAS5) by the European Centre for Medium-Range Weather Forecasts (ECMWF) (ECMWF, 2021). For these synthetic time series of wind data, the Royal Dutch Meteorological Institute (KNMI) calculated corresponding sea levels (van den Brink, 2020). As a result, a period of 8,000 years of simulated meteorological and hydraulic data of the current climate have become available for many Dutch coastal locations. Compared to the limited availability of measurements from coastal stations (up to 50 or 100 years for a limited number of stations) these long time series are a great source of synthetic storm information.

The aim of this study is to explore the potential of using storm characteristics derived from these long synthetic time series of wind and corresponding water level for operational forecasting at the Dutch coast. First, physical and statistical properties of storm characteristics and their mutual correlations are analyzed. Storm characteristics consist of the temporal and spatial evolution of wind speed, wind direction and surge height, the duration of wind speed and storm surge above a certain threshold and the phase difference between the maximum storm surge and high tide. Mutual correlations between these characteristics are derived using copulas. Previous analyses result in strong correlations between wind speed and surge height, although it varies significantly depending on the location and combination of wind direction, duration and phase (Caspers & Kindermann, 2023). Still, this strong correlation suggests potential to be used for the forecasting of resulting storm surges from wind speed. Consequently, the correlations and other storm evolution properties found from these synthetic time series are compared to the observations of storms in recent years to investigate whether the findings from synthetic data agree with the characteristics of observed storm evolutions, in order to explore their potential for the short and mid-term forecasting of storm impact at the Dutch coast.

How to cite: Kindermann, P., Morales Napoles, O., and Antonlínez, J.: An exploration of the potential of using storm characteristics from long synthetic time series of wind and water levels for operational forecasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19736, https://doi.org/10.5194/egusphere-egu24-19736, 2024.

EGU24-22402 | Posters on site | OS2.4

Sedimentary record analysis of the geographic occurrences of storm surge events in response to climate change 

Shue Gao, Yang Yang, Liang Zhou, Yanan Li, and Jianhua Gao

The objective of this study is to establish a methodological framework for the study of the pattern changes in terms of geographic occurrences of storm surge events, caused by climate changes. The intensification of storms as a result of global warming may be true because of the enhanced energy level, but any specific situation depends on the geographic location. Due to the spherical shape of the earth and the distribution characteristics of the sea and land, climate zones are formulated, with variations with latitude and longitude. Thus, there are several possible combinations for storm intensity and frequency changes, but where do these different patterns occur and what are the control mechanisms? Here we carry out analyses of sedimentary records to answer these questions, by identifying the relationship between storm processes and the resultant product of deposition. We capture time series information on changes in intensity and frequency of Typhoons in Southeastern Asia and Hurricanes in the Atlantic, from sedimentary records within and near the storm event regions, and then compare them with other synchronous information on SST, ENSO, monsoon, ocean circulation, and atmospheric dust transport, to find clues for mechanism studies. We obtained the materials from the various marine environments, including tidal flats, coastal lagoons, beaches and coastal dunes, storm boulders on biological reefs and continental shelf regions, to identify the presence of storm event records, and obtain the information on the dynamic process that generates the record, in terms of the intensity and frequency of storms. sediment records, and studies of sediment records were carried out. Since the sedimentary records are distributed over low to middle latitudes, the zonation changes in the storm intensity/frequency can be compared with climate changes during the Holocene period. The data sets obtained so far reveal both patterns of synchronicity and asynchronicity of storm pattern changes in different geographical zones and during different climatic periods. The combined effects of the changes in the various factors, as mentioned above, may explain the complexity of the changing patterns. However, in order to quantify or establish a general model for the storm pattern and climate changes, the uncertainties of this study should be reduced, by enhancing the accuracy of storm intensity and frequency indicators, and improving the techniques to determine the spatial resolution of the sedimentary records of storm events.

 

How to cite: Gao, S., Yang, Y., Zhou, L., Li, Y., and Gao, J.: Sedimentary record analysis of the geographic occurrences of storm surge events in response to climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22402, https://doi.org/10.5194/egusphere-egu24-22402, 2024.

NH6 – Remote Sensing & Hazards

EGU24-354 | ECS | Orals | NH6.1

A Novelty Data Fusion Approach for Integrating Multi-Band/Multi-Sensor Persistent Scatterers 

Claudia Masciulli, Giorgia Berardo, Carlo Alberto Stefanini, Michele Gaeta, Santiago Giraldo Manrique, Niccolò Belcecchi, Francesca Bozzano, Gabriele Scarascia Mugnozza, and Paolo Mazzanti

The growing accessibility of multi-sensor Persistent Scatterer (PS) data in the advent of the European Ground Motion Service offers a well-established methodology for detecting and monitoring ground displacement over extended areas with sub-centimetric precision. The detection of ground deformation phenomena relies on the available PS density, which is influenced by the sensor resolution and specific site characteristics, such as the presence of stable natural and artificial reflectors. This study proposes a novel Data Fusion (DF) approach that integrates the displacement along the line of sight of PS products to unleash the full potential of multi-sensor combinations by synthesizing multi-band displacement information. The DF approach, developed by NHAZCA S.r.l. and the Research Center “CERI - Centro di Ricerca Previsione e Prevenzione dei Rischi Geologici” of the Sapienza University of Rome in the frame of the “MUSAR” project funded by ASI (Italian Space Agency), overcomes the limitations associated with individual sensor data, allowing for improved information content and data coverage.

The method based on the strain tensor approach combines data with different orbital geometries (i.e., ascending and descending) to obtain a comprehensive deformation map by extracting synthetic measurement points called Ground Deformation Markers. In our analysis, we applied, tested, and validated the fusion method in the Basilicata region of southern Italy, combining data extracted from the C-band Sentinel-1 Copernicus initiative and the COSMO-SkyMed constellation in X-band. We evaluated the DF performance within a test site characterized by homogeneous spatial and velocity PS data distribution. The method accuracy was assessed by comparing its interpolation capabilities to estimate the velocity of deformation at a specific location with those estimated by widely used traditional (i.e., linear interpolation, cubic spline interpolation, and inverse distance weighting) and advanced techniques (i.e., universal kriging and k-nearest neighbors). The predictions of interpolators were compared with randomly extracted ground truth datasets given by the observed PS velocities. The evaluation took into consideration several metrics, such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R-squared). After validating the DF application, we compared multi-sensor results with single-sensor PS to assess the capability of the method to improve spatial coverage and information content, enabling a more comprehensive understanding of ground displacements. The results verified the capabilities and robustness of the DF approach and underscored its efficacy in enhancing the accuracy and spatial coverage of ground deformation monitoring. The proposed study highlighted the DF approach as a valuable tool in geospatial analysis and satellite monitoring applications.

How to cite: Masciulli, C., Berardo, G., Stefanini, C. A., Gaeta, M., Giraldo Manrique, S., Belcecchi, N., Bozzano, F., Scarascia Mugnozza, G., and Mazzanti, P.: A Novelty Data Fusion Approach for Integrating Multi-Band/Multi-Sensor Persistent Scatterers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-354, https://doi.org/10.5194/egusphere-egu24-354, 2024.

EGU24-860 | Posters on site | NH6.1

Spatiotemporal variation in surface deformation of the North Anatolian Fault Zone in the Düzce Region by Geodetic and Geophysical techniques 

Çağkan Serhun Zoroğlu, Tülay Kaya Eken, Emre Havazlı, Quentin Bletery, and Haluk Özener

Abstract

Türkiye has a complex tectonic structure resulting from the northward movement of the African and Arabian plates towards the Anatolian plate relative to the Eurasian plate. Seismic energy is primarily released within the Anatolian plate by earthquakes along the North Anatolian Fault Zone (NAFZ), which is oriented east-west with a right-lateral strike-slip motion. Historical earthquake records suggest a westward migration of seismic energy release along this fault system through a series of earthquakes, beginning with the 1939 M7.9 Erzincan earthquake and culminating in the 1999 M>7 Izmit-Düzce ruptures. The 1999 Mw7.2 Düzce earthquake occurred three months after the 1999 Mw7.4 Izmit earthquake to the east leading to an eastward supershear rupture. We examine the potential correlation between crustal features, fault mechanisms, and inter-seismic loading parameters that impact surface deformation in Düzce. We analyzed spatio-temporal variation of the long-term surface deformation along the Düzce segment. We evaluated Sentinel-1 InSAR data for both ascending and descending orbits from 2014 to 2022, utilizing the InSAR Small Baseline Subset time series analysis technique to calculate horizontal and vertical displacements and the locking depth. Our findings indicate 25 mm/yr of slip rate on the Düzce Fault. We further utilize the previously estimated geoelectric characteristics of the crust by magnetotelluric data modeling that show strong resistivity variations from east to west on the Düzce rupture. Incorporating geodetic (e.g., InSAR-derived surface deformation) and geophysical (electrical resistivity, seismic velocity) constraints on the fault zone and its adjacent shed light on the impact of the physical characteristics of the crustal structure on the inter-seismic loading and surface creep parameters.  

This project is funded by the Bogazici University with the BAP Project No SUP-18161.

How to cite: Zoroğlu, Ç. S., Kaya Eken, T., Havazlı, E., Bletery, Q., and Özener, H.: Spatiotemporal variation in surface deformation of the North Anatolian Fault Zone in the Düzce Region by Geodetic and Geophysical techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-860, https://doi.org/10.5194/egusphere-egu24-860, 2024.

Coastal Subsidence is a complex phenomenon with large spatiotemporal variability to natural processes and anthropogenic activities, leading to the potential inundation risk of major coastal cities worldwide with the increase in relative sea level rise and shoreline sinking (Shirzaei et al., 2021). India’s coastal metro-politician cities are vulnerable to future inundation risk due to the rising sea level. Kerala, a southern state in India with about 590 km of coastline covering vast habitats of rich biodiversity and occupants, has faced the impacts of coastal subsidence for the past few decades. There is a wide scope of detail investigating Kerala’s coastal land subsidence and its impact due to the rise in sea level using geodetic techniques. In this context, we explored the data from Sentinel-1 of ESA acquired along the descending track (Path 63 and 165) with a VV polarization for monitoring subsidence. The Vertical Land Motion (VLM) is analyzed using the Small BAseline Subset (SBAS) based MT-InSAR technique along the entire coastline of Kerala which is spread across 590 km (Berardino et al., 2002). A total of 1443 interferograms were generated by co-registering 326 single-look complex images and applying a spatial baseline threshold of 85 m and a temporal baseline threshold of 65 days. The result shows that most regions in Kerala are subsiding at a rate of > 5mm/year, with the Kuttanad region of Alappuzha showing a maximum subsidence of > 20mm/year. The tide gauge station of Kochi Willingdon Island shows a relative sea level trend of 1.97±mm/year. NASA’s Intergovernmental Panel on Climate Change (IPCC) AR6 report has projected a future sea level change of 0.71 meters by 2100, considering the socioeconomic scenario SSP3-7.0. The InSAR-derived VLM, projection data of sea level from the IPCC-AR6 report, and the high spatial resolution of the Digital Elevation Model (DEM) have been incorporated to map the low-lying fast subsiding zones that are prone to future flood inundation due to relative sea level rise for all the 14 districts of Kerala. We further aim to incorporate a U-net-based deep learning model to efficiently handle these terabytes of data and develop more accurate inundation maps. This study will be helpful for policymakers to take precautionary measures to prevent future inundation hazards over the shoreline. 

 

References

Shirzaei, M., et al. (2021). "Measuring, modelling and projecting coastal land subsidence." Nature Reviews Earth, Environment 2(1): 40-58.

 

Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti, (2002). "A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms." IEEE Transactions on Geoscience and Remote Sensing 40 (11): 2375–83. https://doi.org/10.1109/TGRS.2002.803792.

 

How to cite: Raman, A. and Ojha, C.: Impact analysis of Relative Sea Level Rise in the entire Kerala Coast of India using MT-InSAR Technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1130, https://doi.org/10.5194/egusphere-egu24-1130, 2024.

EGU24-4400 | Orals | NH6.1

InSAR Norway: Advancing Geohazard Understanding through Wide-Area Analysis 

John F. Dehls, Marie Bredal, Ivanna Penna, Yngvar Larsen, Gökhan Aslan, Jacob Bendle, Martina Böhme, Reginald Hermanns, Vanja S. Haugsnes, and Francois Noel

Since its inception in 2018, InSAR Norway has emerged as a pivotal tool in addressing geological hazards and advancing scientific research in Norway. Utilizing the C-band data from Sentinel-1, it provides annual comprehensive ground movement updates crucial for understanding and mitigating natural disasters and ensuring infrastructure stability across Norway's complex terrain. The service's impact is particularly pronounced in landslide mapping and permafrost studies, areas of critical importance given Norway's climatic and geological vulnerability.


InSAR Norway has been instrumental in detecting and monitoring landslide-prone areas, providing data essential for early warning systems and risk assessment. Detailed morpho-kinematic inventories have been updated nationwide to include previously undetected movements. By classifying slope movements and providing velocity data, InSAR Norway has significantly contributed to understanding the kinematics of landslides, enabling more cost-effective monitoring solutions. A recent study leveraging InSAR Norway data has statistically explored the link between permafrost and displacement rates of large unstable rock slopes (LURSs), revealing that permafrost presence significantly influences these rates and that complete thawing of permafrost can reduce or halt displacement, indicating the nuanced role of permafrost in geological hazard scenarios.


InSAR Norway's data has also shed light on the dynamics of rock glaciers and permafrost creep. Studies utilizing this data have revealed the impact of permafrost thawing on rock glacier velocities and the broader implications for landscape stability and hydrology. By providing detailed movement profiles of rock glaciers in transition from active to relict stages, InSAR Norway has offered insights into the effects of climate change on cold region dynamics.


The service's free and open data policy has been central to its success, catalyzing a wide range of research and operational applications by providing unrestricted access to high-quality, high-resolution data. This policy has facilitated a collaborative environment where academics, government agencies, and industry can innovate and develop solutions to shared challenges.


With the impending integration of L-band data from the NISAR satellite mission, InSAR Norway is poised for significant enhancements. NISAR data will augment the service's ability to monitor ground movements, particularly in vegetated areas and through seasonal changes. This integration reflects our commitment to adopting cutting-edge technology to improve the accuracy, timeliness, and applicability of geohazard monitoring and research. By fusing the strengths of C-band and L-band data, InSAR Norway will provide a more comprehensive and nuanced understanding of ground deformation processes, supporting safer, more informed decision-making in the face of Norway's dynamic and often harsh environmental conditions. InSAR Norway will continue its legacy of pioneering satellite-based monitoring, safeguarding communities, and advancing scientific understanding of geohazards.

How to cite: Dehls, J. F., Bredal, M., Penna, I., Larsen, Y., Aslan, G., Bendle, J., Böhme, M., Hermanns, R., Haugsnes, V. S., and Noel, F.: InSAR Norway: Advancing Geohazard Understanding through Wide-Area Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4400, https://doi.org/10.5194/egusphere-egu24-4400, 2024.

EGU24-6112 | ECS | Posters on site | NH6.1 | Highlight

A remote-sensing-based framework to detect the rate of peat subsidence and associated CO2 emissions: A case study of the Biebrza Valley, Poland 

Pouya Ghezelayagh, Ryszard Oleszczuk, Marta Stachowicz, Mohammad Reza Eini, Piotr Banaszuk, Andrzej Kamocki, and Mateusz Grygoruk

Peatlands are vital ecosystems that provide essential ecological services, especially in carbon storage. Nevertheless, the decomposition of surface peat and subsequent carbon emission threaten to accelerate the pace of climate change. This study presents a framework designed to facilitate the estimation of peat subsidence and relevant CO2 emissions through the exclusive utilization of remote sensing techniques. In this study, the peatland subsidence in the Biebrza Valley, Poland, was estimated by using the Alaska Satellite Facility Interferometry Synthetic Aperture Radar on-demand cloud computing via a Small Baseline Set technique and seasonal-annual search approach covering the period from April 2015-April 2022. The amount of subsidence and associated carbon emission rates can be estimated by analyzing InSAR data from a selected period. The results reveal an annual peatland subsidence rate of 2.1 cm, verified through field surveys. An R2 value of 0.91, and an RMSE value of 0.23 cm indicate the reliability of this approach in estimating the subsidence. These findings unveil a troubling trend in the Biebrza National Park, with almost 88 MCM of its peatlands lost during the seven years from 2015-2022. Two different approaches were employed to estimate CO2 emissions associated with subsidence, each with three scenarios. Therefore, the estimation of annual peatland carbon dioxide loss, ranging from 3.24 to 5.36 tons per hectare through the remote sensing-based approach, compared to the broader range of 20.3 to 33.9 tons/ha/yr obtained from the common approach. It means that, based on the first approach, in the most optimistic scenario, the park is associated with a minimum of 1.35 million tons of carbon dioxide emissions during this period, potentially reaching as high as 2.26 million tons in the worst-case scenario. In contrast, the common approach indicates a wider range of emissions, ranging from 8.5 to 14.2 million tons over these years.

How to cite: Ghezelayagh, P., Oleszczuk, R., Stachowicz, M., Eini, M. R., Banaszuk, P., Kamocki, A., and Grygoruk, M.: A remote-sensing-based framework to detect the rate of peat subsidence and associated CO2 emissions: A case study of the Biebrza Valley, Poland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6112, https://doi.org/10.5194/egusphere-egu24-6112, 2024.

EGU24-6191 | Orals | NH6.1

Semi-automatic analysis of InSAR large datasets for landslide mapping and monitoring: the Great Britain case study 

Camilla Medici, Alessandro Novellino, Claire Dashwood, and Silvia Bianchini

In recent years, satellite-SAR interferometry has established itself as a widely used global monitoring technique, enabling timely detection, monitoring and mitigation of both natural disasters and human-induced ground movements. When dealing with large multi-temporal InSAR data, the ground deformation detection becomes a fundamental and complex task with the consequent pressing need to establish new approaches and tools for effectively analysing large interferometric datasets. The advanced capabilities of the satellite systems and the continuously updated processing techniques provide unprecedented amounts of data to analyse the ground deformation processes for large territories in reduced time frames. Within this context, the fast detection and characterization of the ground deformation processes constitute a milestone for what concerns the correct management and mitigation of their impact on vulnerable populations and infrastructures. As a result, the starting point for all ground deformation detection and monitoring techniques is to work with updated inventories, a fundamental yet often overlooked issue in most countries such as Great Britain. Despite the availability of a national landslide database, less than half of the landslides reported are mapped as polygons, and their state of activity is unknown. In this regard, in this work we updated the national landslide inventory by mapping new events or simply identifying their current condition of motions through the use of the data freely provided by the European Ground Motion Service (EGMS), which represents an unprecedented baseline for ground deformation applications at continental, national and local level with millimetre accuracy. The approach relies on a semi-automatic tool, recently developed at the Centre Tecnològic de Telecomunicacions de Catalunya to identify the Active Deformation Areas (ADAs). Following an initial analysis of the InSAR data, the tool allows the identification of unstable areas characterized by a minimum number of persistent scatterers with velocity values over a specific threshold. The results consist of two ADA maps corresponding to the two Sentinel-1 velocity components and, subsequently, the output can be combined with landcover and topographic maps. The study has been carried out by exploiting the horizontal and vertical velocity maps provided by the EGMS which has enabled a national-scale analysis. Subsequent steps involve the classification and temporal analysis of the identified ADAs, followed by the analysis of more relevant local case studies. 

How to cite: Medici, C., Novellino, A., Dashwood, C., and Bianchini, S.: Semi-automatic analysis of InSAR large datasets for landslide mapping and monitoring: the Great Britain case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6191, https://doi.org/10.5194/egusphere-egu24-6191, 2024.

EGU24-8369 | ECS | Posters on site | NH6.1

Automated classification of ground deformation processes in Spain: a machine learning approach using a novel national InSAR-based database 

Jhonatan Steven Rivera Rivera, Marta Béjar Pizarro, Héctor Aguilera Alonso, Pablo Ezquerro, Carolina Guardiola-Albert, and Oriol Monserrat

InSAR has been widely employed in terrain deformation analysis worldwide. Its significant utility in risk management has led to the development of extensive SAR databases, poised for exploration in land-use planning studies. However, this information still requires specific expertise, hindering its accessibility for non-expert users. In this work, we introduce MOVESAR, an SAR-based database designed for training Machine Learning (ML) classification models capable of providing precise information on the type of deformation process and its cause. MOVESAR is also planned to support the development of deformation time series forecasting models.

Each row in MOVESAR is spatiotemporally linked to a deformation time series (DTS) obtained through InSAR processing of SAR images from various satellites (SENTINEL 1, ENVISAT, ERS, COSMO-SkyMed, ALOS and TerraSAR-X), collected from previous studies conducted by the Geological Survey of Spain (IGME) and the Centre Tecnológic Telecomunicacions Catalunya (CTTC). Spatially, our database covers a substantial part of the Spanish territory, represented in 60 deformation polygons (with more than 300,000 measurement points or "MPs"), spanning from 1992 to 2020.

Each column in MOVESAR represents a covariate potentially related to the six deformation processes compiled in this initial version of the database: piezometric change-induced deformation, landslide in mining environments, soil landslide, constructive subsidence, subsidence in mining environments, and subsidence in dumps. Covariates include geological, morphometric, hydrological, and geotechnical information, as well as data associated with DTS, land use, land cover, and landslide, subsidence and expansive clays susceptibility/hazard. Dynamic variables, including precipitation and DTS, underwent transformation into static variables by extracting statistical measures such as mean, standard deviation, range, and slope.

In this study, we present preliminary results from nine ML models trained using MOVESAR: four single base models (nb, knn, lda, and lr), and five ensemble models (rf, gbc, xgboost, lightgbm, and catboost). We discuss the performance of the models and analyze the importance of covariates. Additionally, we evaluate the impact of applying techniques aimed at reducing noise, bias, and model complexity, such as threshold velocity filtering technique (TVF) for eliminating stables MPs, Recursive Feature Elimination (RFE) for covariate reduction, and Cost Sensitive Learning (CSL) for class balancing.

Our future work aims to expand the number of covariates, MPs, and classes using the European Ground Motion Service (EGMS) to enrich MOVESAR, establishing it as a nationally valuable database for forthcoming studies on geohazard management. Additionally, we plan to apply spatiotemporal Deep Learning (DL) models incorporating dynamic variables, providing reliable classifications for decision-making in urban planning and national land-use management.

This work has been developed thanks to the pre-doctoral grant for the Training of Research Personnel (PRE2021-100044) funded by MCIN/AEI/10.13039/501100011033 and by "FSE invests in your future" within the framework of the SARAI project "Towards a smart exploitation of land displacement data for the prevention and mitigation of geological-geotechnical risks" PID2020-116540RB-C22 funded by MCIN/AEI/10.13039/501100011033.

How to cite: Rivera Rivera, J. S., Béjar Pizarro, M., Aguilera Alonso, H., Ezquerro, P., Guardiola-Albert, C., and Monserrat, O.: Automated classification of ground deformation processes in Spain: a machine learning approach using a novel national InSAR-based database, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8369, https://doi.org/10.5194/egusphere-egu24-8369, 2024.

EGU24-8610 | ECS | Orals | NH6.1

EGMS insights into ground deformation patterns in Underground Gas Storage (UGS) activities 

Gabriele Fibbi, Tommaso Beni, Matteo Del Soldato, and Riccardo Fanti

The importance of natural gas in meeting human energy needs persists, even amid the ongoing global energy transition. Fossil fuels, including coal, oil, biomass, and natural gas, remain central for providing essential energy services such as cooking, heating, and electricity generation for homes and businesses. Despite the increasing emphasis on renewable energy sources, total reliance on electricity is not yet feasible, necessitating a transitional phase wherein natural gas will play a key role. Natural gas, particularly in the form of methane (CH4), remains an indispensable resource due to its efficiency and versatility. This is particularly evident during periods of increased energy demand, such as the winter season, when natural gas serves as a reliable source for heating and power generation. The importance of a steady and uninterrupted supply of natural gas is highlighted by the challenges posed by seasonal fluctuations in demand. In response to the dynamic energy landscape, Underground Gas Storage (UGS) facilities have gained prominence as a strategic solution. With 160 active projects in Europe at the end of 2021, UGS activities provide the flexibility to store and deliver natural gas continuously, adapting to daily and seasonal fluctuations. This adaptability is critical to maintain a stable energy supply, especially during peak demand periods. On the other hand, UGS cycles have the potential to induce three-dimensional deformations within the affected reservoir that are subsequently transmitted to the surface. These deformations should be monitored since they can compromise the integrity of wells and nearby infrastructure. In this context, Interferometric Synthetic Aperture Radar (InSAR) is emerging as a valuable tool for continuous monitoring ground displacement resulting from UGS activities. InSAR analysis can provide millimetre-precision measurement points, overcoming the spatial coverage of in-situ instruments. The Yela site exploits a fractured aquifer reservoir located in the Madrid Basin (Spain) currently employed for UGS activities by Enagás, the Spanish main Transmission System Operator. A correlation between long-term records of gas volume (2019-2022) with vertical and horizontal (E-W) ground displacement data (2015-2020) from the European Ground Motion Service (EGMS) and the UGS activity rates can be established. The temporal evolution of vertical ground displacement shows a clear sinusoidal signal aligned with the amplitude and periodicity of the load/discharge curve of natural gas in the reservoir. This result highlights the versatility of the InSAR approach for UGS monitoring, complementing in-situ data, enhancing safety and improving facility management. In addition, InSAR technology can allow continuous monitoring analysis for detecting changes in the UGS environment, for risk management purposes and calibration of geomechanical models useful for estimating maximum pressure values. This work introduces a replicable approach to investigate freely available ground movement data, presenting a comprehensive comparison of InSAR results for the Yela UGS site. Leveraging open-source and easily accessible data, the study offers insights into the volumetric variation model and it identifies a significant correlation between natural gas injection/withdrawal rates and InSAR ground displacement over time.

How to cite: Fibbi, G., Beni, T., Del Soldato, M., and Fanti, R.: EGMS insights into ground deformation patterns in Underground Gas Storage (UGS) activities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8610, https://doi.org/10.5194/egusphere-egu24-8610, 2024.

EGU24-8645 | Orals | NH6.1

Mapping Worldwide Ground Deformation in High-Strain Areas with SAR PS/DS Interferometry and Sentinel-1 Imagery 

Giorgio Gomba, Francesco De Zan, Ramon Brcic, and Michael Eineder

The motivation for this study is to help providing a better understanding of the behavior of the earth's crust in high strain areas. High strain areas are regions of the Earth's crust, associated with tectonic plate boundaries, where the rates of ground deformation are particularly high. These areas are characterized by high seismic activity, making them of significant concern. The ability to estimate ground deformation in these regions is critical for understanding the underlying geological processes and for assessing the potential risk of future seismic events. Interferometric Synthetic Aperture Radar (InSAR) has shown great promise in delivering millimetre-scale ground displacement information over long distances across plate boundaries. In this project, we aim to globally measure ground deformation using the InSAR Persistent and Distributed Scatterer (PS/DS) technique, focusing on the regions where the second invariant of the strain is higher than 3 nanostrain per year.

Due to the large amount of data that has to be processed, we use the high-performance data analytics platform made available within the framework of the Terra_Byte project, a cooperation between the German Aerospace Center (DLR) and the Leibniz Computer Centre (LRZ). This enables us to process large volumes of data efficiently. We use the IWAP processor to apply the PS/DS technique to time-series of seven years of SAR images acquired by the Sentinel-1 mission. To improve the accuracy of our analysis and reduce the influence of ionospheric variations we use CODE total electron contents maps. The impact of solid earth tides (SETs) is limited by using the IERS 2010 convention. We use ECMWF reanalysis data to correct for tropospheric delays, which are the biggest error source and limiting factor for the interferometric performance at large distances. The influence of soil moisture and vegetation growth on distributed scatterers is limited by the full covariance matrix approach used in the interferograms generation. Finally, we calibrate and compare our results with GNSS measurements to show a detailed picture of ground deformation.

The results of this project will be publicly available on a global scale, including: velocity maps, timeseries, line-of-sight projection vectors. The product palette will allow custom calibration or 2D decomposition by the user. Possible applications are: the large coverage and homogeneous processing characteristics of the data could serve as a baseline reference or comparison for other studies. Geoscientists will be able to use the deformation measurements to gain a better understanding of geological processes, with the dense PS/DS measurements filling in the gaps between existing GNSS survey data, contributing to the advancement of scientific knowledge in this field.

How to cite: Gomba, G., De Zan, F., Brcic, R., and Eineder, M.: Mapping Worldwide Ground Deformation in High-Strain Areas with SAR PS/DS Interferometry and Sentinel-1 Imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8645, https://doi.org/10.5194/egusphere-egu24-8645, 2024.

EGU24-9924 | ECS | Posters on site | NH6.1

Mapping the buildings stability at urban extent based on MT-InSAR and 3D rigid motion reconstruction method 

Francesca Grassi, Francesco Mancini, Veronica Dallari, Elisa Bassoli, and Loris Vincenzi

The recent and planned launch of high-resolution and short revisit time Synthetic Aperture Radar (SAR) satellite missions, along with the use of advanced multi-temporal interferometric techniques, has opened up new possibilities in the field of structure and infrastructure monitoring. The cited techniques are capable of providing displacement time series of stable targets at the ground with millimetre accuracy. They are particularly relevant for preventive conservation, maintenance, and health assessment of existing built heritage.
A method for reconstructing the 3D rigid motion of isolated buildings from a dual-orbit set of SAR data has recently been proposed by the authors. In that work, the assessment of the significance of the computed motion components has received particular attention due to the low entity of displacement that could potentially affect the buildings. The method was tested on COSMO-SkyMed SAR data processed using an open-source procedure. The results indicate that it is possible to detect displacements in the order of a few mm/yr and rotations in the order of mrad/yr with corresponding uncertainties that are one order of magnitude smaller than the associated parameters.
This work combines the proposed structural investigation method with a Geographic Information System (GIS) dataset to develop a methodology for assessing building stability at an urban extent. GIS layers were used to define the spatial relation between scatterer locations and building shape, detecting targets belonging to buildings and retrieving the precise heights of the scatterers. The 3D rigid motion analysis was conducted for all individual buildings in the area with relevant uncertainties assessment. The workflow is able to map the potential stability issues of single buildings, at urban extent, as starting point for further investigation.
The methodology has been tested on the city of Modena (Italy) and GIS layers representing the classification of building stability is presented.
Funding: The methodology adopted in the present research was partially developed in the frame of the Progetti di Rilevante Interesse Nazionale (PRIN) 2022 DAMAGE “Damage Analysis and Monitoring of Ancient structures interacting with Geotechnical Excavations”, contract E53D23002550006.

How to cite: Grassi, F., Mancini, F., Dallari, V., Bassoli, E., and Vincenzi, L.: Mapping the buildings stability at urban extent based on MT-InSAR and 3D rigid motion reconstruction method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9924, https://doi.org/10.5194/egusphere-egu24-9924, 2024.

EGU24-10088 | ECS | Posters on site | NH6.1

Inversion-based Time Series Analysis of PS-InSAR Data: Uncovering the Origins of Subsidence and Annual Fluctuations in Southern Hesse, Germany 

Michael Rudolf, Katrin Krzepek, Benjamin Homuth, Dorota Iwaszczuk, and Andreas Henk

The uplift and subsidence of the earth's surface can be attributed to many different processes. In urban regions in particular, it is important to understand which ground movements occur, whether they pose a risk to infrastructure and whether countermeasures can be taken. While events such as earthquakes, sinkholes and landslides have abrupt and visible effects, slow ground movements such as slope instabilities and tectonic movements are difficult to detect and it can take decades for visible damage to occur. Remote sensing, especially InSAR and Persistent Scatterer InSAR, provides high spatial and temporal coverage for monitoring these processes. The state of Hesse in central Germany is confronted with various ground movements, including former open-cast lignite mines, active salt mining and landslide-prone geological units. Our study aims to explore previously unknown ground movements in urban regions using remote sensing, analyse detected areas, determine causes, assess risks and anticipate future developments. We use Persistent Scatterer Interferometry (PS-InSAR) data from the Ground Motion Service Germany (BBD) to analyse ground motion patterns. With the help of a Ground Motion Analyser (GMA), time series analysis and external data, we identify regions with significant ground movements throughout the federal state. A case study in Frankfurt am Main, located on the northern edge of the Upper Rhine Graben, shows subsidence that was probably caused by groundwater extraction during the construction of buildings. Another case study in Crumstadt, in the centre of the northern Upper Rhine Graben, shows pronounced seasonal fluctuations, possibly related to temperature and activity in an underground gas reservoir. In both cases, an analysis of external data such as groundwater levels, climate data, construction activity, mining activities, hydrogeological and geological conditions must be taken into account. The ground movements caused by the various possible causes can sometimes be very similar, so a solid external database is particularly important. With the help of the results, the ground movements measured by remote sensing can be linked both qualitatively and quantitatively with the regional conditions. Our results thus contribute to understanding and mitigating the effects of ground movements and underline the importance of analysing both time-varying movements and linear velocities in parallel with external data.

How to cite: Rudolf, M., Krzepek, K., Homuth, B., Iwaszczuk, D., and Henk, A.: Inversion-based Time Series Analysis of PS-InSAR Data: Uncovering the Origins of Subsidence and Annual Fluctuations in Southern Hesse, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10088, https://doi.org/10.5194/egusphere-egu24-10088, 2024.

EGU24-13026 | ECS | Orals | NH6.1

The Role of Artificial Intelligence in Modeling and Predicting Ground Deformation Using Advanced InSAR Data 

Junaid Khan, Ascanio Rosi, Sansar raj Meena, and Mario Floris

Ground deformation, encompassing sudden and gradual shifts in the Earth's surface, poses significant global geohazard risks. These phenomena demand thorough investigation and monitoring and are influenced by a range of natural and anthropogenic factors such as mining, excessive groundwater extraction, seismic activities, structural loads, and subsurface geology. Our research is centered on the location in the Venetian-Friulian Plain (Veneto Region, NE Italy). This area is of interest because it represents a transitional zone where sedimentary deposits from both river systems (fluvial) and lagoon/coastal environments are found, marking the transition from the alluvial plain to the coastal plain. Ground displacement maps are generated using pre-event data from the Veneto Region Sentinel 1-PS data Service and the European Ground Motion Service (EGMS), allowing us to analyze the heightened susceptibility of areas undergoing deformation. Our approach integrates artificial intelligence techniques with InSAR-derived data to create comprehensive pre- and post-event multi-temporal deformation inventories and susceptibility maps. This fusion offers exceptional accuracy and timeliness in identifying, modeling, and predicting ground deformation events. Utilizing insights from InSAR data and AI techniques, we aim to project future trends and potential risks, contributing valuable insights to geohazard assessment and management within the study region.

How to cite: Khan, J., Rosi, A., Meena, S. R., and Floris, M.: The Role of Artificial Intelligence in Modeling and Predicting Ground Deformation Using Advanced InSAR Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13026, https://doi.org/10.5194/egusphere-egu24-13026, 2024.

EGU24-14387 | ECS | Posters on site | NH6.1

Active landslides inventory update based on EGMS data for slowing moving landslides in a hilly environment 

Nicușor Necula and Mihai Niculita

The European Ground Motion Service (EGMS) products expand the InSAR utility in geohazards investigation, including mapping and monitoring various surface processes such as land subsidence, volcanic activity, landslides, etc. Access to such data is crucial, particularly for urban areas needing continuous monitoring of structures and infrastructures affected by landslides. Landslide deformations have become a significant threat in the context of climate change and global urbanization nowadays. The EGMS products offer consistent and reliable InSAR measurements of ground deformations with millimeter accuracy, which can be accessed and downloaded from the platform. The measurements include GNSS-calibrated full-resolution velocity and displacement time series for the ascending and descending orbits and calculated displacement vectors in the vertical and E-W directions, resampled to a 100 x 100 m grid. We focus on the slow-moving landslides with typical velocities of 16 mm/year, specific to the Moldavian Plateau, Eastern Romania. We exploit the ascending and descending full-resolution data for the 2016 – 2022 interval to identify the active landslides. Based on an existing landslide inventory extracted from high-resolution LiDAR DEM, we analyze the moving landslide of the current inventory.

How to cite: Necula, N. and Niculita, M.: Active landslides inventory update based on EGMS data for slowing moving landslides in a hilly environment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14387, https://doi.org/10.5194/egusphere-egu24-14387, 2024.

EGU24-14488 | ECS | Posters on site | NH6.1

Caspian Sea Level Changes and Coastal Dynamics: A Case Study of the Gizil-Aghaj State Reserve Using Multi-Sensor Satellite Data 

Bahruz Ahadov, Fakhraddin Kadirov, and Eric Jameson Fielding

The decreasing sea level of the Caspian Sea is having a serious impact on coastal ecosystems and biodiversity. This study, conducted over a decade from 2014 to 2023, provides a comprehensive analysis of the coastal transformations in the Gizil-Aghaj State Reserve, Azerbaijan, using remote sensing technologies. By utilizing a combination of optical and radar satellite data, we mapped the evolving interplay between land and sea. Our research reveals a significant coastline shift, with the Caspian Sea receding to expose an additional 218 km2 of land. This significant change was most apparent in the northeastern area, corresponding with regions experiencing substantial land subsidence. As the Caspian Sea's level decreases and the land sinks simultaneously, it's reasonable to expect that the shoreline would remain stable. In contrast to areas with land subsidence, places where the land is uplifting, along with the Caspian Sea's decreasing level, are likely to experience noticeable changes in their shoreline, suggesting a more dynamic and changing coastal area. These findings are crucial for understanding the fluctuations in the Caspian Sea level, likely influenced by a combination of natural geological processes, human activities, and broader climatic trends. The subsidence observed in some areas may be due to tectonic movements or human activities such as resource extraction. In difference, the uplift seen in other areas, where there is evidence of building up over time, might be influenced by both anthropogenic factors and natural tectonic processes. Moreover, our study highlights the intricate relationship between coastal dynamics, vertical land movements, and environmental changes. It highlights the critical need for integrated and multi-dimensional monitoring approaches to address these complex interactions. These results not only contribute to a deeper understanding of the Gizil-Aghaj State Reserve's coastal ecosystem but also offer valuable perspectives on the Caspian Sea's response to climate change. Such insights are crucial for developing adaptive strategies for coastal management and conservation in an era marked by environmental uncertainties and changes.

How to cite: Ahadov, B., Kadirov, F., and Fielding, E. J.: Caspian Sea Level Changes and Coastal Dynamics: A Case Study of the Gizil-Aghaj State Reserve Using Multi-Sensor Satellite Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14488, https://doi.org/10.5194/egusphere-egu24-14488, 2024.

EGU24-14836 | Posters virtual | NH6.1

Multi-temporal InSAR for deformation study (MInDS): A software for deformation monitoring 

Avadh BIhari Narayan, Shouvik Bhattacharjee, and Ashutosh Tiwari

Multi-temporal SAR Interferometry (MT-InSAR) is one of the widely used modern geodetic techniques for monitoring the surface deformation. By using the spatio-temporal analysis of a stack of differential interferograms,  MT-InSAR measures the time series deformation pattern. The analysis separates the deformation component from decorrelation noise, atmospheric error, and inaccurately modelled nuisance parameters. In the initial phase of the development of MT-InSAR approach, only highly coherent pixels, called the persistent scatterers (PS), were used for deformation monitoring. Highly coherent pixels are mostly found either in the urban regions or on the slopes facing the satellite. To estimate the deformation pattern in other regions, moderately coherent pixels, called distributed scatterers (DS), are used. However, before applying spatio-temporal analysis to estimate deformation, the phase information of DS pixels needs to be optimized by the phase triangulation algorithm (PTA).

We have developed a software Multi-temporal InSAR for deformation study (MInDS), which uses a similar environment as stamps use.  The processing chain of the MInDS processing chain is based on Similar Time-series Interferometric Pixels (STIP), representing the number of neighborhood pixels with similar phase history. In this approach, PS selection and estimation of look angle error is improved by using STIP of the PS pixels. After the selection of PS, the PTA implemented by using complex least squares utilises the phase information of neighboring STIPs to improve the phase coherence of DS pixels. Finally, the deformation pattern of the PS and phase-optimized DS pixels are used for deformation estimation using spatio-temporal analysis.

How to cite: Narayan, A. B., Bhattacharjee, S., and Tiwari, A.: Multi-temporal InSAR for deformation study (MInDS): A software for deformation monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14836, https://doi.org/10.5194/egusphere-egu24-14836, 2024.

EGU24-14908 | Orals | NH6.1

Developing Machine Learning tools for the automatic interpretation of InSAR data 

Luke Bateson, Itahisa Gonzalez Alvarez, Raushan Arnhardt, Claire Fleming, Ekbal Hussain, Lee Jones, Alessandro Novellino, and Kay Smith

Hundreds of large cities worldwide are sinking; and this will get worse as by 2050 when almost 70% of the world’s population is set to live in megalopolises, the majority of these are in low lying coastal areas. At the same time sea levels are rising. According to the World Economic Forum, several of the globe’s cities, including New York, Dhaka, London and Bordeaux, could be partially or totally submerged by 2050-2100. As a city grows the environment is put under additional pressure and this often leads to subsidence. land less suitable for building upon is developed, in low lying coastal regions these areas are often poorly consolidated recent superficial deposits. Loading of such deposits causes consolidation which adds to subsidence resulting from increased groundwater abstraction required for industry and to support a growing population.

In order to mitigate against the effects of subsidence it is imperative to understand the subsidence; its location, magnitude, timing and crucially the underlying cause. InSAR offers the ability to understand the spatial extent, magnitude and timing and when integrated with in-situ data the cause can be determined. However, this interpretation process can take a significant amount of time. With the advent of continental scale InSAR data, such as the European Ground Motion Service, and automated online processing facilities such as COMETS LICSBAS system InSAR data is becoming far easier to access. This means huge volumes of data are generated and therefore automated methods are required to extract not only the areas of ground motion but also to indicate the underlying cause of the motion.

To this end we have been using integrated time series of optical and InSAR data for areas of rapid urban growth to understand the cause of subsidence. Combination of interpretations with expected patterns of subsidence derived from models of groundwater abstraction and ground loading allow us to separate subsidence signals from these causational factors. In turn this enables the generation of characteristic time series of subsidence that we would expect to see as a result of each process. Such characteristic time series form libraries that will be the basis for machine learning to automatically interpret the InSAR data.

We will present the creation of such subsidence libraries and illustrate the process with examples from Hanoi, Kuala Lumpur and Bandung. We will also present the machine learning method where a fully automated approach using Seasonal and Trend decomposition allows trends (such as stable, linear subsidence, non-linear subsidence and seasonal) within the InSAR time series to be identified and grouped into common trend behaviours. Metrics based on derived trends also allow the ‘strength’ of certain components (such as seasonal signals) to be automatically assessed.

How to cite: Bateson, L., Gonzalez Alvarez, I., Arnhardt, R., Fleming, C., Hussain, E., Jones, L., Novellino, A., and Smith, K.: Developing Machine Learning tools for the automatic interpretation of InSAR data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14908, https://doi.org/10.5194/egusphere-egu24-14908, 2024.

EGU24-16229 | ECS | Orals | NH6.1

A quantitative assessment of the SAOCOM-1 L-band DInSAR time-series retrieved through the P-SBAS approach in natural and anthropogenic hazard scenarios of the Italian territory 

Yenni Lorena Belen Roa, Claudio De Luca, Manuela Bonano, Francesco Casu, Marianna Franzese, Michele Manunta, Giovanni Onorato, Pasquale Striano, Muhammad Yasir, and Riccardo Lanari

Spaceborne Differential Synthetic Aperture Radar Interferometry (DInSAR) represents a well-established technique to accurately retrieving ground surface displacements over large areas of the Earth, in both natural and anthropogenic hazard scenarios, with limited costs and with a centimeter to millimeter accuracy. However, the DInSAR technique retrieval capability may be affected by the so-called “temporal decorrelation phenomena” due to possible temporal changes of the imaged scene electromagnetic response. In this regard, the low-frequency SAR sensors, as those operating at the L-band, characterized by a significantly larger wavelength (~23 cm) with respect to the X-band (~3 cm wavelength) and C-band (~5.6 cm wavelength) ones, are particularly suited to mitigate the above-mentioned decorrelation effects, thanks to their capacity of maintaining the interferometric coherence for a long period. Moreover, these L-band SAR systems also imply considerable robustness with respect to the possible occurrence of phase unwrapping errors. These peculiarities have pushed the worldwide space agencies to invest in the development of L-band spaceborne SAR sensors as, for instance, the NISAR mission, jointly developed by NASA and ISRO, the PALSAR-3 mission of JAXA and the ROSE-L mission developed by ESA, as well as the already operative SAOCOM-1 sensors of CONAE. In this work, we focus on the Argentinean SAOCOM-1 constellation which is composed of two twins, full-polarimetric L-band SAR sensors. This system guarantees, over a large part of Europe (with a priority given to the Italian territory coverage), a systematic, DInSAR-oriented acquisition plan of SAR images in the StripMap mode, with a revisit time varying among 16, 24 and 48 days, in order to avoid coverage gaps. Moreover, we largely exploit the Parallel Small BAseline Subset (P-SBAS) approach, which is an advanced DInSAR method that allows us to effectively and efficiently generate displacement time-series with sub-centimeter accuracy. The capability of the P-SBAS algorithm to retrieve C- and X-band DInSAR time-series, relevant to both natural and anthropogenic hazard scenarios has already been widely demonstrated, as well as its capacity to perform analyses at different spatial resolution scales. Accordingly, we present here the results of the L-band SAOCOM-1 P-SBAS analysis carried out at medium spatial resolution (about 30 m) in different ground deformation scenarios affecting the Italian territory. In particular, the presented results are relevant to a portion of the Tuscany region (central Italy), which is affected by significant landslide phenomena. Moreover, we also consider the volcanic contexts of the Campi Flegrei caldera, Mount Etna and Stromboli island, all located in southern Italy. In this case, we fully benefit from the availability of GNSS measurements to provide a quantitative assessment of the retrieved L-band deformation time-series.

Finally, some SAOCOM-1 results, achieved by applying the full resolution P-SBAS approach over the urban areas of Rome and Naples municipalities, are also presented. Such a full spatial resolution (about 5 m of pixel size) analysis allows us to investigate the potentialities of the L-band data to overcome some of the limitations of the current high resolution X-band SAR systems in urbanized scenarios.

How to cite: Roa, Y. L. B., De Luca, C., Bonano, M., Casu, F., Franzese, M., Manunta, M., Onorato, G., Striano, P., Yasir, M., and Lanari, R.: A quantitative assessment of the SAOCOM-1 L-band DInSAR time-series retrieved through the P-SBAS approach in natural and anthropogenic hazard scenarios of the Italian territory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16229, https://doi.org/10.5194/egusphere-egu24-16229, 2024.

EGU24-17444 | ECS | Posters on site | NH6.1

Advancing InSAR Applications in Detecting Land Movement and Sinkhole Precursors in Post-Mining Landscapes 

Artur Guzy, Magdalena Łucka, and Wojciech Witkowski

Mining, a critical global economic activity, disturbs the geomechanical and hydrogeological equilibrium of aquifer systems. This disturbance becomes particularly evident after mining operations cease. In post-mining areas, one of the most significant phenomena is the groundwater rebound. This process restores original groundwater levels in depleted mines, leading to land uplift and the formation of sinkholes. Such changes can be detrimental to infrastructure and pose a threat to public safety. These complex dynamics necessitate continuous monitoring of ground movements to mitigate potential hazards effectively. Interferometric Synthetic Aperture Radar (InSAR) technology has emerged as a valuable tool in this context, providing detailed insights into land movements. However, the complex geological, hydrogeological, and mining conditions in post-mining areas demand advanced InSAR data processing techniques to detect early signs of phenomena such as sinkholes, thereby enhancing our ability to respond to these geohazards.
Our study was conducted in the historical zinc and lead mining region near Olkusz, northeast of Krakow, Poland. This area, with a long history of underground mining, witnessed the conclusion of its mining operations in 2022. Since then, significant land surface deformations and sinkholes have been observed, impacting both rural and urbanized areas. To understand these land movements, our approach involved two primary methods: Persistent Scatterer Interferometric Synthetic Aperture Radar (PS InSAR) for long-term analysis and Differential InSAR (DInSAR) for short-term changes, employing ESA Copernicus Sentinel-1 data. For long-term land surface movement analysis, we analyzed 165 radar images from January 2020 to June 2023, captured using ascending orbital geometry. The data acquisition frequency varied due to changes in satellite operations. Short-term land surface movements were examined through 54 interferograms covering various time intervals (12-24-36 days) between July and December 2023, using both ascending and descending geometries.
We observed a complex pattern of land movement in the study area, with both subsidence and uplift. The average movement rates varied from -14.5 mm/year to +7.7 mm/year, with about 90% of the area experiencing changes within ±2.0 mm/year. The closed zinc and lead mine region showed significant uplift, reaching up to +7.7 mm/year, highlighting pronounced geomechanical changes. Seasonal movements, with amplitudes of ±15 mm, were dominated by winter-summer variations. A positive linear trend across a considerable portion of the study area suggests widespread land uplift since early 2022. The accuracy of the DInSAR method was approximately ±2 cm, while PSInSAR achieved finer resolution at ±0.5 cm. Short-term changes indicated potential ongoing terrain deformation, especially in shorter-time base interferograms. However, confirming these observations was challenging due to low signal quality in longer intervals. The impact of vegetation on DInSAR signal quality, particularly in forested areas, underscored the need for improved methodologies.
This study enhances our understanding of aquifer system deformation mechanisms in post-mining areas. The use of InSAR techniques, particularly in urbanized regions, is crucial for the effective monitoring of ground movements, highlighting the importance of ongoing research to refine interferometric calculation efficiency, especially in areas with dense vegetation and urban structures.

How to cite: Guzy, A., Łucka, M., and Witkowski, W.: Advancing InSAR Applications in Detecting Land Movement and Sinkhole Precursors in Post-Mining Landscapes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17444, https://doi.org/10.5194/egusphere-egu24-17444, 2024.

EGU24-18009 | ECS | Posters on site | NH6.1

Correlation between environmental variables and slope movements in the Ala Archa catchment, Kyrgyzstan 

Rainer Gardeweg, Tamara Mathys, Martin Hoelzle, and Simon Allen

In a time of increasing global warming and interconnected environmental changes, the assessment and detection of moving landforms are of growing importance for implementing successful adaptation and mitigation strategies concerning geohazards. Understanding the factors and processes governing slope movements, as well as their annual and seasonal variability, is of crucial significance. In recent years, advances in remote sensing applications and the availability of satellite data have been made, leading to an increased use of remotely sensed data for hazard monitoring and detection. Additionally, the use of machine learning enables the application of these methods to larger areas. Here, we concentrate on the Ala Archa catchment in Kyrgyzstan (Central Asia), located approximately 40 kilometres south of the capital city Bishkek, with a long history of glacier monitoring at Golubin Glacier.


This study aims to identify the predominant environmental factors influencing slope movements within the Ala Arch catchment and investigates the contribution of variations in environmental conditions to annual fluctuations in slope movement. We first present an average velocity map for the area of interest using InSAR (Interferometric Synthetic Aperture Radar) with Sentinel-1 data from both ascending and descending orbits between 2018 and 2023. The data is processed using ISCE (InSAR Scientific Computing Environment) and MintPy (Miami InSAR Time-series software in Python). Additionally, we use statistical modelling to estimate the influence of selected environmental variables such as relief, permafrost distribution, vegetation cover and landform classification. To determine the influence on seasonal/annual variations, we incorporate fluctuating variables like air temperature, precipitation and the duration of snow cover. In a final step, we examine how the identified relationships can be applied to generate an upscaled regional susceptibility map for slope movement.


In conclusion, our objective is to demonstrate the potential use of openly available satellite data for detecting hazardous or moving areas in regions where in-situ measurements are impractical or the necessary resources are unavailable.

How to cite: Gardeweg, R., Mathys, T., Hoelzle, M., and Allen, S.: Correlation between environmental variables and slope movements in the Ala Archa catchment, Kyrgyzstan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18009, https://doi.org/10.5194/egusphere-egu24-18009, 2024.

EGU24-19174 | ECS | Orals | NH6.1

A multivariate time series analysis of underground gas storage deformations using InSAR data 

Serena Rigamonti, Giuseppe Dattola, Matteo Oryem Ciantia, and Giovanni Battista Crosta

Underground gas storage (UGS) is of strategic importance both in terms of security of supply and to ensure the operational continuity of primary industrial basins. UGS reservoirs make it possible to guarantee the country a continuous and reliable supply of natural gas. It is well known that UGS activities can induce ground deformations, in response to gas injection and extraction cycles. The Lombardy region (Italy) has a predominant part in the Italian national policy of UGS in depleted reservoirs. In this work, five UGS reservoirs located in Lombardy and three additional ones in Italy, which differ in geometric and geo-lithological features, were considered.

In this context, the InSAR (Interferometric Synthetic Aperture Radar) technique plays a key role in monitoring ground deformations induced by UGS activities, providing precise measurements of ground displacement.

In this contribution, we present (i) an application of a multi-method approach for the analysis of trends and seasonal signals in the EGMS InSAR time series of ground displacements in the proximity of UGS reservoirs to recognise specific footprints and spatial-temporal patterns of ground deformation. For this purpose, large datasets of ground displacements covering the UGS area in Lombardy (25 km2) from 2015 to 2022 were analysed; and (ii) an interpretation of the possible causal relationship between displacement and gas injection and extraction time series using cross-correlation approach and wavelet tools in the time-frequency domain.

The multi-method approach involves the application and optimization of Principal Component (PCA) and Independent Component Analyses (ICA) in temporal (T-) and spatial (S-) modes on both ascending and descending InSAR time series, as well as on the vertical and horizontal ones, allowing for a spatial-temporal separation of the original data into a set of limited components. Among them, it is possible to isolate those related to the USG deformations, from other signals typical of the region. Subsequently, clustering analysis is performed to group the InSAR time series and identify characteristic ground deformation patterns, which could also be related to differences in grain size properties.

As a result, it was possible to recognize and separate a limited number of signal components, describing long-term displacement and seasonal fluctuations, and the derived maps allowed the characterization of the area of influence relative to each UGS reservoir. Finally, cross-correlation approach and wavelet tools made it possible to identify and interpret the time lag between the peaks and, consequently to improve the correlation between displacements and anthropogenic triggers.

To validate the deformation patterns resulting from the approach, numerical analyses were performed in which the gas injection and extraction time series were considered as input variables. 

How to cite: Rigamonti, S., Dattola, G., Ciantia, M. O., and Crosta, G. B.: A multivariate time series analysis of underground gas storage deformations using InSAR data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19174, https://doi.org/10.5194/egusphere-egu24-19174, 2024.

EGU24-1217 | ECS | PICO | NH6.2

Improving the detection accuracy of vegetation destruction events using bands sensitive to vegetation foliage, canopy and water content 

Chuanwu Zhao, Yaozhong Pan, Shoujia Ren, Gelilan Ma, Yuan Gao, Hanyi Wu, and Yu Zhu

Frequent climate changes and intense human activities increase the risk of vegetation destruction. Spectral index-based change detection can identify vegetation destruction from multi-temporal images, providing valuable insights for vegetation management and post-disaster recovery efforts. However, we still face the challenge of the spectral diversity of vegetation destruction and the complexity of the background environment. Existing spectral indices (VIs) often struggle to accurately detect vegetation destruction in complex scenarios. These VIs focus on specific aspects of vegetation, such as leaf, canopy or water content, limiting their effectiveness in capturing vegetation dynamics. In addition, they are susceptible to background environment changes. To overcome these challenges, this study proposes a new metric called Slope Vegetation Index (SVI) using bands that are sensitive vegetation leaf, canopy, and water content (i.e., green, near-infrared (NIR), and short-wave infrared (SWIR) bands). The performance of SVI was verified by the dual time-phase difference method, and five widely used VIs were selected for detailed comparison. In addition, the performance of SVI was evaluated using PROSAIL simulation data, various vegetation change scenarios, and real vegetation destruction cases. Moreover, we assessed the applicability of SVI to other multispectral sensors. The results showed that compared with existing VIs, SVI exhibited the highest sensitivity to vegetation changes under different chlorophyll and water content conditions. In various vegetation change scenarios and vegetation destruction cases, SVI consistently had the best performance, with Producer’s Accuracy (PA), User’s Accuracy (UA), and F1 scores all exceeding 0.90. In complex scenarios, SVI could better highlight vegetation changes while suppressing background environment changes. Additionally, SVI performed well on other Landsat-8/9 images, with an F1 score exceeding 0.89. This study confirms that SVI is valid for vegetation destruction detection and has potential for large-scale and high-frequency vegetation monitoring.

How to cite: Zhao, C., Pan, Y., Ren, S., Ma, G., Gao, Y., Wu, H., and Zhu, Y.: Improving the detection accuracy of vegetation destruction events using bands sensitive to vegetation foliage, canopy and water content, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1217, https://doi.org/10.5194/egusphere-egu24-1217, 2024.

On-orbit processing is an important way in the real-time remote sensing detection of earth's surface anomalies (ESSA). However, the existing methods cannot comprehensively utilize multidimensional remote sensing characteristics to detect multi-type ESSA in a unified manner. Meanwhile, it is also difficult to realize the comprehensive utilization of multidimensional remote sensing characteristics under the condition of limited storage and computing resources on satellites. Therefore, this study proposed a remote sensing method for detecting multi-type ESSA on orbit based on multidimensional feature space. The proposed method first selected the remote sensing characteristics reflecting the basic earth's surface elements to construct a multidimensional feature space and generated two comprehensive remote sensing characteristics. Then, the optimized storage content of the two comprehensive remote sensing characteristics were used to build a prior knowledge base reflecting the normal conditions of the earth's surfaces. Finally, through comparing the prior knowledge base and the real-time acquired data, this study completed the ESSA detection. The validation results indicated that the proposed method can effectively detect multi-type ESSA with a accuracy of over 85%. Meanwhile, the proposed method simplified the large and complex ESSA remote sensing characteristic system, which would be conducive to greatly reducing the complexity of ESSA detection methods and increasing the possibility of on-orbit processing.

How to cite: Wei, H., Jia, K., and Wang, Q.: A remote sensing detection method of the earth's surface anomalies based on multi-dimensional feature space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1626, https://doi.org/10.5194/egusphere-egu24-1626, 2024.

EGU24-2593 | ECS | PICO | NH6.2

Mid-Inclination Orbits for Small Satellite SAR Constellations and their Interferometric Exploitation: the IRIDE case study 

Federica Cotugno, Paolo Berardino, Manuela Bonano, Antonio Ciccolella, Gabriella Costa, Felipe Martin Crespo, Guido Levrini, Michele Manunta, Antonio Moccia, Alfredo Renga, and Riccardo Lanari

Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) plays nowadays a crucial role in studying ground deformations with centimeter-to-millimeter accuracy. Initially exploited to investigate individual deformation events, such as earthquakes and volcanic unrests, DInSAR has evolved in the last two decades thanks to the accessibility to large multi-temporal SAR data archives. This evolution has led to the development of advanced (also referred to as multi-temporal) DInSAR techniques, enabling to follow the temporal evolution of the detected surface displacements through the retrieval of deformation time series.

Despite the wide availability of spaceborne SAR systems with different characteristics (i.e., spatial coverage, spatial resolution, revisit time, orbital tube, etc.), the DInSAR community increasingly demands better coverage performance and improved imaging capabilities to address the latest emerging needs. For instance, short revisit time and high spatial coverage and resolution are usually needed to study fast deformation phenomena. Moreover, most SAR constellations exploit single plane, dawn-dusk, sun-synchronous orbits because this simplifies the satellite design across all subsystems, resulting in cost savings. However, in this traditional orbital design, the interferometric revisit time becomes considerable, thus representing a limiting factor. Furthermore, the poor sensitivity to the North-South deformation component that characterizes the sun-synchronous DInSAR systems represents a fundamental limitation in investigating the deformation phenomena.

In this scenario, the use of small SAR satellites is gaining traction, thanks to the simplified design and manufacturing processes. Additionally, the ability to launch multiple satellites, by using the same vehicle, enables the deployment of an entire constellation in a single mission. However, these systems, being smaller and lighter, have constraints on their imaging performance, potentially compromising coverage capabilities. Consequently, innovative mission configurations are necessary for their effective use.

This work focuses on a SAR component of the Italian IRIDE program, which will be implemented for the Italian government and completed by 2026 under the management of the European Space Agency, with the support of the Italian Space Agency. This SAR component, called NIMBUS, is expected to include, in its first batch and its preliminary design, 6 high-resolution X-band small satellites operating at altitudes between 490-550 km and in various operating modes including a StripMap one with a swath extension that is not designed to be extremely wide (25-30 km).

To cover the Italian territory with high spatial resolution and the shortest interferometric revisit time, we investigate a Mid Inclination Orbit solution that, through the DInSAR exploitation, can effectively measure the North-South deformation component, thus permitting us to investigate the three-dimensional behavior of the retrieved displacements.

Our simulations show that the analyzed IRIDE SAR component, through the preliminary setup in a 49° inclination orbit, permits covering nearly all the Italian territory with a 6-day revisit time in a right-looking acquisition mode. Moreover, we show that the simulated configuration would provide an excellent DInSAR retrieval capability for the North-South deformation component. Indeed, with such an orbital configuration, more than 40% of this component contributes to the SAR Line of sight projection, significantly better than what is typically achievable with sun-synchronous systems.

How to cite: Cotugno, F., Berardino, P., Bonano, M., Ciccolella, A., Costa, G., Crespo, F. M., Levrini, G., Manunta, M., Moccia, A., Renga, A., and Lanari, R.: Mid-Inclination Orbits for Small Satellite SAR Constellations and their Interferometric Exploitation: the IRIDE case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2593, https://doi.org/10.5194/egusphere-egu24-2593, 2024.

Wildfire hazard is a prominent issue in subtropical forests as climate change and extreme drought events increase in frequency. Stand-level fuel load and forest structure are determinants of forest fire occurrence and spread. However, the current fuel management often lacks the detailed vertical fuel distribution, limiting accurate fire risk assessment and effective fuel policy implementation. In this study, backpack laser scanning (BLS) is used to estimate several 3D structural parameters, including canopy height, crown base height, canopy volume, stand density, vegetation area index (VAI) and vegetation coverage, to characterize the fuel structure characteristics and the vertical density distribution variation in different stands of subtropical forests in China. Through standard measurement by BLS point cloud data, we found that canopy height, crown base height, stand density, and VAI in the lower and middle height strata differed significantly among stand types. Comapre to vegetation coverage, LiDAR derived VAI can better show significant stratified changes in fuel density in the vertical direction among stand types. Among the stand types, conifer-broadleaf mixed forest and C. lanceolata had higher VAI in surface strata than other stand types, while P. massoniana and conifer-broadleaf mixed forests were particularly unique in having higher VAI in the lower and middle height strata, corresponding to the higher surface fuel and ladder fuel in the stand respectively. To provide more informative support for forest fuel management, BLS LiDAR data combined with other remote sensing data was advocated to facilitates the visualization of fuel density distribution and the development of fire risk assessment. 

How to cite: Li, S., Wu, Z., and Huang, C.: Revealing 3D Variations in Forest Fuel Structures in Subtropical Forests through Backpack Laser Scanning , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2597, https://doi.org/10.5194/egusphere-egu24-2597, 2024.

Drought is a climate-related slow-onset hazard event and has a significant impact on agricultural production and ecosystem health. Mainland Southeast Asia is a tropical and subtropical region of major cropland and vegetation ecosystems, and this region is increasingly vulnerable to drought-related hazards. This study assessed space-time variability of vegetation dynamics and their drought impacts using satellite-based vegetation condition time series and multi-temporal drought indices from 2000 to 2022 over the MSEA region. Specifically, we examined the vegetation dynamics and their responses to multi-temporal (short-term and long-term) drought indices in consideration of different land cover types, land-use transitions, and elevation characteristics. We also used an explanable machine learning method to quantify the impacts of multi-faceted droughts on natural and undisturbed vegetation ecosystems. Our results revealed that vegetation in the MSEA region suffered from multi-year drought-induced stress, but overally nearly 70% of the region experienced a greening trend over the study period. Most declining vegetation areas are observed in forest and rainfed croplands in Cambodia and southern Laos whereas Vietnam witnessed a greening trend. Vegetation-drought analysis indicated that recent land-use transitions and lower altitude areas had higher responses of vegetation to droughts. In natural and undisturbed ecosystems, short-term drought disturbances had the largest impact on vegetation, accounting for nearly 93% of observed variations. The largest influential factors among the examined drought indices was identified as the SPEI-3 and TCI, accounting for around 35% and 20% of the observed changes in vegetation, respectively. Notably, the SPEI-3 highlights that favorable wet conditions can result in an enhancement of vegetation condition by up to 15%, while severe drought occurrences can lead to a significant reduction of up to 20% in vegetation condition.

How to cite: Ha Van, T., Uereyen, S., and Kuenzer, C.: Space-time variability of vegetation and their multi-faceted drought impacts in the tropical and subtropical regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7988, https://doi.org/10.5194/egusphere-egu24-7988, 2024.

EGU24-8452 | ECS | PICO | NH6.2

Operational soil moisture-based threshold for the assessment of landslide occurrence over Umbria region, central Italy 

Luca Ciabatta, Sara Galeazzi, Luca Brocca, and Francesco Ponziani

Landslides are one of the most dangerous natural hazards, causing every year fatalities, considerable damage and relevant economic losses. Early warning systems (EWS) for rainfall-induced landslides represent an useful tool for mitigating the impact of such hazard. The Umbria Regional Civil Protection Service developed a system able to take into account also the soil moisture conditions over the regional territory based on set of soil moisture-based thresholds. By identifying the soil saturation conditions before and after the rainfall event (obtained through a hydrological model), it has been seen that most of the activations occurred when the soil reached saturation. In this way, an alert can be issued when the amount of rainfall needed by the soil to reach saturation is observed. The amount of rainfall needed to reach saturation has been calculated through the definition of soil hydraulic parameters and the saturation degree at the start of the rainfall event. The obtained threshold is based on soil characteristics and it is independent by the input data (no need for recalibration or threshold adjustment). The proposed methodology is able to identify correctly most of the proposed events with a very limited amount of false alarms considering all the rainfall events occurred during the 1989-2022 period. Moreover, the use of high-resolution rainfall and soil moisture satellite-derived products has been tested for a limited time window to test whether these new sources of information can be used with benefit, even for operational purposes.

How to cite: Ciabatta, L., Galeazzi, S., Brocca, L., and Ponziani, F.: Operational soil moisture-based threshold for the assessment of landslide occurrence over Umbria region, central Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8452, https://doi.org/10.5194/egusphere-egu24-8452, 2024.

EGU24-9361 | ECS | PICO | NH6.2

Comparison of precipitation datasets for representing flood characteristics in Malaysia  

Sarath Muraleedharan, Kiran Kezhkepurath Gangadhara, and Bharath Raja

Reliable assessment of flood risk is very important for mitigating the disastrous impacts of floods. Since extreme precipitation is the most common cause of floods, accurate spatio-temporal precipitation data is crucial for flood risk assessment. Limited availability of gauge observations makes flood risk assessment challenging in Southeast Asian countries like Malaysia. In such cases, various gridded precipitation datasets developed using data sources such as satellite, reanalysis and gauge observations are of vital importance, however, the differences in the data sources and methods used to derive these datasets lead to significant uncertainty regarding the choice of dataset for a specific purpose. For flood risk quantification over a region where rainfall and streamflow data exhibit significant spatial dependence, it is important to ensure that the use of the chosen dataset results in an adequate representation of flood characteristics observed in the region. This is an important consideration in the development of flood catastrophe models widely used to quantify flood risk in terms of monetary losses in the insurance and reinsurance industry. 

At Impact Forecasting, Aon’s catastrophe model development team, the key undertaking in this study is to identify a suitable gridded daily precipitation dataset for modelling flood risk in the Southeast Asian region using Malaysia as a case study. Comparisons are made among six datasets (namely IMERG, CHIPRS, ERA5, ERA5-Land, CHELSA and APHRODITE) regarding their representation of the characteristics of historical flood events in Malaysia. While pluvial flood events are directly determined by the precipitation datasets, streamflow data is needed to represent fluvial flood events. However, observed streamflow data is available only at a few locations in Malaysia. In such situations, rainfall-runoff models can be forced with precipitation data to generate simulations of streamflow. For this purpose, we use the Impact Forecasting rainfall–runoff (IFRR) model, a spatially distributed (gridded) adaptation of the HBV model to generate daily streamflow simulations at 10kmx10km grids in Malaysia.  

We first compare the general characteristics of the precipitation datasets such as the total accumulated rainfall, number of wet days, length of wet spells and spatial correlation. The accuracy of the daily streamflow simulations at locations where observed streamflow data is available is evaluated using the Kling-Gupta Efficiency (KGE). Next, we apply an innovative clustering-based method to extract pluvial and fluvial flood events from the precipitation and simulated streamflow data respectively, and then merge dependent events. The resulting sets of flood events derived from each dataset are compared in terms of characteristics such as frequency, severity, duration, and spatial extent. The ability of the datasets to represent some of the severe flood events are evaluated using available data. 

How to cite: Muraleedharan, S., Kezhkepurath Gangadhara, K., and Raja, B.: Comparison of precipitation datasets for representing flood characteristics in Malaysia , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9361, https://doi.org/10.5194/egusphere-egu24-9361, 2024.

The geologically recent Himalayas, characterized by fragile slopes and active tectonics, are inherently susceptible to natural hazards, including frequent earthquakes and associated secondary hazards. Northwest Indian states like Jammu & Kashmir, Ladakh, Himachal Pradesh, and Uttarakhand experience these events with varying intensities, posing significant risks to infrastructure and livelihoods. Among these hazards are earthquakes-induced landslides (EIL), which often modify the landscapes and affect communities. While the existing inventory of EIL provides valuable insights, limitations require further refinement. For instance, the point-based inventory by Barnard et al. (2001) for the Chamoli region mapped 56 EIL within the 226 sq. km. of the region from the epicentre. The lack of landslide geometry in the inventory restricts detailed analysis and hampers robust landslide modelling and risk assessment. To bridge this gap, this study presents an approach to transition from the conventional point-based inventory to a more comprehensive polygon-based inventory for EILs triggered by the 1999 Chamoli earthquake (Mw 6.8). Utilizing pre- and post-event Landsat-5 imagery, the study employs multi-spectral analysis techniques like Pseudo Colour Transform (PCT), Normalized Difference Vegetation Index (NDVI), and image differencing. By integrating these analyses with visual interpretation (shape of the landslide), the study accurately delineates the spatial extent and geometry of EILs in the Chamoli and Rudraprayag districts of Uttarakhand, India. By providing detailed information and spatial distribution of landslides, this approach allows for enhanced risk assessment. Future research will utilize high-resolution (5m) IRS-1C/1D panchromatic imagery to (1) identify smaller-scale landslides, (2) monitor land-use/land-cover changes within existing landslide zones for a five-year period, and (3) analyze the resulting landscape dynamics in the aftermath of the Chamoli earthquake. This analysis will shed light on the intricate relationship between land-use modifications and post-seismic landscape evolution.

How to cite: Joshi, S. and Subramanian, S. S.: The Chamoli Earthquake (1999): Transitioning from Point-Based to Polygon-Based Landslide Inventory in Uttarakhand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9998, https://doi.org/10.5194/egusphere-egu24-9998, 2024.

EGU24-11256 | ECS | PICO | NH6.2

Satellite-based tracking of slow-moving landslides: challenges and perspectives 

Ariane Mueting and Bodo Bookhagen

Slow-moving landslides represent a significant hazard to local communities and infrastructure in mountainous regions worldwide. Given their challenging and often inaccessible terrain, satellite imagery holds great potential for monitoring landslides from space. In this study we use optical data from Sentinel-2 and PlanetScope satellites for tracing surface displacement across slow-moving landslides through image cross-correlation. Our work particularly focuses on the variables affecting measurement precision, including orthorectification errors and mismatches due to variable shading or seasonal snow cover. Erroneous measurements can be reduced when image pairs are carefully selected based on their view angles and sun positions. This practice, however, severely limits the number of potential image pairs, resulting in disconnected networks of displacement maps. This in turn poses problems when solving for a displacement time series using an inversion technique. Here, we evaluate the effect of network connectivity and measurement noise on inversion results using both synthetic and real-world data. Our findings support the extraction of accurate displacement estimates from remotely sensed data, advancing the detection potential of landslides and their dynamic behaviors. 

How to cite: Mueting, A. and Bookhagen, B.: Satellite-based tracking of slow-moving landslides: challenges and perspectives, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11256, https://doi.org/10.5194/egusphere-egu24-11256, 2024.

EGU24-12070 | ECS | PICO | NH6.2

Comparative Assessment of Sinkhole Susceptibility Mapping in Mexico City: Weight of Evidence versus Weighted Linear Summation 

Sergio A. García Cruzado, Nelly L. Ramírez Serrato, Graciela S. Herrera Zamarrón, Fabiola D, Yépez Rincón, and Samuel Villareal

Sinkholes are a geological phenomenon that appears as a closed funnel-shaped surface depression, where water can stagnate and drain into the subsoil. This phenomenon occurs mainly in karst environments, however it can also occur in multiple geological environments, generated by natural and anthropogenic processes, such as subsurface erosion, changes in groundwater levels and groundwater extraction, among others. The main distinctive feature of sinkholes is that their presence is not detectable until a sudden collapse of the surface layer of soil occurs, generating a significant risk for infrastructure and population in urban areas. Mexico City presents a critical situation due to the presence of sinkholes, since from 2017 to 2020 more than 500 sinkholes have been registered throughout the city, exposing to serious risks to the structures, roads and safety of the people who live and transit daily in the city. The aim of this study is to compare the sinkhole susceptibility maps of two methodologies: Weights of Evidence and Weighted Linear Sum. The accuracy of both methodologies will be obtained by comparing the values obtained using the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC). The maps were elaborated using a GIS database made up of 18 conditioning factors (groundwater depletion, land elevation, density of waterlogging, density of faults, density of fractures, density of leaks, density of mines, density of water wells, density of natural drainage, distance to faults, distance to fractures, distance to subway lines, distance to mines, distance to roads, sinking speed, slope, lithology and land use) and the record of damage caused by sinkholes in Mexico City. Both maps show a good identification of areas susceptible to the presence of sinkholes, with the central-northern and eastern parts of the city having the greatest potential for sinkhole formation. The convergence of the results underlines the importance of the conditioning factors that contribute to the formation of sinkholes, highlighting the factors of anthropogenic origin as the main forming factors. The findings emphasize the potential of both methods to generate good urban planning and elaborate adequate risk mitigation strategies in the identified areas.

How to cite: García Cruzado, S. A., Ramírez Serrato, N. L., Herrera Zamarrón, G. S., Yépez Rincón, F. D., and Villareal, S.: Comparative Assessment of Sinkhole Susceptibility Mapping in Mexico City: Weight of Evidence versus Weighted Linear Summation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12070, https://doi.org/10.5194/egusphere-egu24-12070, 2024.

EGU24-12315 | ECS | PICO | NH6.2

An insight into ALTRUIST: how to use GNSS Variometry for Natural Hazards Detecting and Monitoring 

Michela Ravanelli, Elvira Astafyeva, Pierre Sakic, Raphael Baucry, and Mattia Crespi

This work aims to present and to disseminate the ALTRUIST (totAL variomeTry foR tsUnamI hazard eStimaTion) project.

ALTRUIST is one of the eight projects selected worldwide for the Joint Call by the AXA Research Fund and the Intergovernmental Oceanographic Commission of UNESCO (IOC-UNESCO) on Coastal Livelihood within the framework of the United Nations Ocean Decade [1].

ALTRUIST’s main goal is to improve the reliability and accuracy of real-time tsunami warning systems leveraging the recent findings of Global Navigation Satellite System (GNSS) remote sensing. GNSS remote sensing employs the GNSS signal to infer information about atmosphere, oceans and ground.

In detail, ALTRUIST leverages the Total Variometric Approach (TVA) methodology [2]. GNSS Variometry is based on single time differences of suitable linear combinations of GNSS carrier-phase, allowing a GNSS receiver to provide valuable real-time information in a standalone operative mode. TVA jointly employs VADASE (Variometric Approach for Displacement Analysis Stand-alone Engine) and VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithms.

TVA allows for the simultaneous and real-time estimation of ground shaking, co-seismic displacements and ionospheric Total Electron Content (TEC) disturbances, using the same real-time GNSS data stream. The joint use of the information from the ground and ionosphere can be really beneficial.  Coseismic displacements can be used to retrieve important parameters about the seismic source and the seafloor displacement. The ionospheric observation, can, in turn, give information about the seismic source and, to some extents, about the ground motion.

These data are, hence, crucial in natural hazards management and can support traditional instruments to improve the quick estimation of the tsunami hazard.

ALTRUIST is currently being tested within the GNSS network of the Observatoire Volcanologique et Sismologique de Guadeloupe of Institut de Physique du Globe de Paris (IPGP), in the Caribbeans.

In detail, ALTRUIST is built to be a scalable and modular architecture that provides the first joint ground and ionosphere real-time solutions. In detail, it provides the real-time visualization on a dashboard and allows access to information and historical solutions through API.

These attributes embody a key point of the ALTRUIST project: sharing historical solutions foster discussion within the scientific community, whereas the interactive dashboard empowers local communities to access additional information on natural hazards.

Finally, ALTRUIST framework is versatile and can be easily applied to the monitoring of any kind of natural hazards events such as volcanic eruptions and explosions impacting ground and ionosphere geosphere.

This is the first feasibility demonstration of the ALTRUIST real-time capabilities.

References

[1] https://axa-research.org/funded-projects/climate-environment/mitigating-tsunamis-threats-and-destructive-impacts-through-enhanced-navigation-satellite-system

[2] Ravanelli, Michela, et al. "GNSS total variometric approach: first demonstration of a tool for real-time tsunami genesis estimation." Scientific Reports 11.1 (2021): 3114

How to cite: Ravanelli, M., Astafyeva, E., Sakic, P., Baucry, R., and Crespi, M.: An insight into ALTRUIST: how to use GNSS Variometry for Natural Hazards Detecting and Monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12315, https://doi.org/10.5194/egusphere-egu24-12315, 2024.

EGU24-12538 | ECS | PICO | NH6.2

Extreme weather threatening vineyards of North-East Italy: multi-temporal satellite analysis in Google Earth Engine  

Vincenzo Baldan, Eugenio Straffelini, Vincenzo D'Agostino, and Paolo Tarolli

The northern-east part of Italy is an important wine production area, which exports high-quality wine worldwide. The territory boasts of areas that are under the protection of FAO and UNESCO, thanks to the unique relationship between landscape and agriculture. In the last two decades, extreme weather events created criticalities, especially in steep slope territories.

Future climate trends could influence the frequency of heatwaves, drought and intense rainfalls, impacting on vineyards. Therefore, identifying trends helps to understand the risks to which vineyards are subjected.

The purpose of this study is to identify extreme weather trends in the area located in Veneto and Friuli-Venezia Giulia and discover areas that are more affected by increasing and decreasing trends. The workflow started with analyzing historical climate data in different datasets in Google Earth Engine. We implemented the Land Surface Temperature dataset of the Modis satellite for surface temperatures and the CHIRPS Daily dataset for historical precipitation data. Additionally, for 2-meter temperatures and cumulative rainfall, we considered weather station data.

Based on the initial findings, the summer of 2022 reported strong heatwaves and drought. Certain areas showed an increase in surface temperature of more than +20%, compared to the mean summer temperature during the 2000-2010 period. For precipitations, otherwise, the central-east part of the region reported a negative anomaly of around -50 % compared to the summer average of the last 30 years.

Future research activities will focus on intense rainfall and more about the frequency, duration and distribution of heatwaves and drought to detect future scenarios.

The results of this research may inspire the development of sustainable initiatives focused on improving water management, aiming to reduce run-off during intense precipitations and enhancing water storage during drought seasons, as well as on supporting the insurance companies to provide tailored risk coverages against increasing climatic risks in vineyard farms.

How to cite: Baldan, V., Straffelini, E., D'Agostino, V., and Tarolli, P.: Extreme weather threatening vineyards of North-East Italy: multi-temporal satellite analysis in Google Earth Engine , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12538, https://doi.org/10.5194/egusphere-egu24-12538, 2024.

EGU24-14506 | ECS | PICO | NH6.2

Assessment of Landslide Susceptibility Map in the Jaintia Hill District Using Remote Sensing and GIS 

Sachin Kumar, Mahendra kumar Choudhary, Thomas Thomas, and Shubhangi Umare

Landslides, a naturally occurring geological phenomenon, significantly threaten public safety, infrastructure, and the environment. Identifying the landslide-prone areas is essential for efficient risk mitigation and land-use planning. The main reason for concern about landslides is their potential to have disastrous effects, including property damage and casualties. Usually, landslides happen when a slope's stability fails due to natural or man-made causes like intense rain, earthquakes, etc. An area which are susceptible to landslide must be identified to prepare for disasters and take proactive mitigation measures. This study aims to use a Geographic Information System (GIS) and the weighted overlay method to create a landslip susceptibility map for the Jaintia Hills district. The main issue regarding landslide susceptibility involves three key factors: firstly, the inadequate knowledge of the geographic layout of areas vulnerable to landslides; secondly, the lack of a uniform strategy for evaluating landslide susceptibility; and thirdly, the immediate need for reliable resources to assist in land-use planning and development, to minimising the risk associated with landslides. The present study uses remote sensing and GIS techniques to address this challenge. It applies the Analytic Hierarchy Process (AHP) weighted overlay technique in GIS, incorporating eight thematic layers: elevation layer, drainage density (DD), land use/land cover (LULC), soil type, slope layer, aspect layer, geography, lineament density (LD), and geomorphology. The thematic layers are carefully selected to capture various factors influencing landslide occurrence, ensuring a robust and accurate susceptibility assessment. The AHP incorporates expert knowledge to allocate weights to each thematic layer using pairwise comparison. The overlay process combines these layers to generate a comprehensive map reflecting the potential zones of landslides in the Jaintia Hills district. The results reveal a detailed landslide susceptibility map for the Jaintia districts, highlighting areas prone to landslides. It reveals that approximately 11634 hectares are in the high landslide occurrence zone, and 52849 hectares are in the medium zone. The map compared with locations where the landslides occurred in the past and found that most of the points lie in the high-prone zone for landslides, which shows the significant accuracy of the prepared map. However, prepared map will provide valuable insights for land-use planning and risk mitigation strategies, aiding decision-makers in developing sustainable policies to safeguard both human lives and the environment in the Jaintia Hills region.

Keywords – Landslide Susceptibility, GIS, Remote sensing, Natural Hazards, AHP weighted overlay method

How to cite: Kumar, S., Choudhary, M. K., Thomas, T., and Umare, S.: Assessment of Landslide Susceptibility Map in the Jaintia Hill District Using Remote Sensing and GIS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14506, https://doi.org/10.5194/egusphere-egu24-14506, 2024.

EGU24-14888 | ECS | PICO | NH6.2 | Highlight

From Shelters to Skyscrapers: A Worldwide Exploration of Buildings and Building Types Using Volunteered Geographic Information and Earth Observation Datasets 

Laurens J.N. Oostwegel, Tara Evaz Zadeh, and Danijel Schorlemmer

The location and type of buildings are incredibly useful data in any phase of the disaster management cycle. During the prevention and preparedness phases, the exposure and vulnerability of the population to natural hazards can be identified, using building inventories. To get to know the extent of damage in the recovery phase, one needs to know the state of the buildings before the disaster. In the response phase, knowledge about the exact population distribution can prove crucial. This can be derived from the knowledge of building locations and how and when they are populated. The common spots for shelter, such as hospitals and schools, should be identified immediately after a disaster has struck. 
Humanitarian mapping has been a key support for disaster relief. Usually, the mapping is channeled through OpenStreetMap (OSM). By MapSwipe and automated completeness assessments  it can quickly become clear where data is lacking. Volunteers often map areas through Mapathons organized by the Humanitarian OpenStreetMap Team (HOT) or Missing Maps. It is partly per these endeavors that OSM contains almost 600 million buildings as of 1 January 2024.
Recently, datasets using AI methods, largely based on Earth Observation (EO) data have been created to identify the world’s buildings. The Google Open Buildings dataset, the Microsoft Global ML Building Footprints contain semi-automatically generated building footprints. Both are of near-global extent and they contain respectively 1.8 and 1.3 billion buildings, but neither is fully complete. 
Unfortunately, unlike OSM, these datasets lack building attributes. The Microsoft dataset does include height in some limited areas, such as the USA and parts of Europe. There are datasets that contain more information, but they span a much smaller area. For example the USA Structures dataset defines occupancy types of buildings based on land use. However, in an ideal situation the rich information structure found in OSM is combined with the extensiveness of building footprints from the EO-derived datasets. 
We investigated the wide range of features and attributes available from OSM, such as land use, amenities and points of interest and used these to classify all building footprints found in OSM itself and the EO-derived Google and Microsoft datasets. This resulted in three datasets of together 3.7 billion buildings. However, many of these buildings are overlapping. Therefore, a grid has been established on a resolution of roughly 100x100 meter. Each tile in the grid contains buildings exclusively from one of the three datasets, with the priorities from high to low: OSM, Google, Microsoft.
If we use the quantity of the EO-derived datasets with the elaborate OSM tagging scheme, we can make better data-informed decisions during all phases of the disaster management cycle: (1) A detailed high-resolution global building inventory leads to better risk forecasting models. (2) Knowing both location and type of buildings results in a broad understanding of the common shelter spots and better estimates of the population distribution at the time of the disaster. (3) post-disaster situations can be better analyzed in scenario-based damage assessments.

How to cite: Oostwegel, L. J. N., Evaz Zadeh, T., and Schorlemmer, D.: From Shelters to Skyscrapers: A Worldwide Exploration of Buildings and Building Types Using Volunteered Geographic Information and Earth Observation Datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14888, https://doi.org/10.5194/egusphere-egu24-14888, 2024.

EGU24-15272 | ECS | PICO | NH6.2

Using Google Earth Engine to map landslide hazard and exposure across Nepal 

Erin Harvey, Nick Rosser, Mark Kincey, Alexander Densmore, Ram Shrestha, Dammar Singh Pujara, Alexandre Dunant, Max Van Wyk de Vries, and Katherine Arrell

Nepal is one of the most susceptible countries to landsliding, with much of the country characterised by steep topography, annual monsoon rainfall and active tectonics. Current understanding of landslides in Nepal is predominantly based on static, catchment-scale landslide inventories or centred around data from specific events, such as the 2015 Gorkha earthquakes. Whilst static inventories provide a useful snapshot of past landslide characteristics, we cannot use these to infer how long landslides persist or how the hazard posed by landslides may evolve through time. In addition, the large number of small-scale inventories that currently exist cannot be readily compared, making it difficult to assess whether trends observed in specific catchments can be applied on a national scale. In this study, we aim to utilise advances in openly accessible remote sensing of large geospatial datasets, namely Google Earth Engine, to record the spatial and temporal evolution of landslides across the full extent of Nepal.

 

We build on an existing automated landslide detection algorithm in Google Earth Engine to compile a national scale landslide probability map, which is re-mapped annually. This allows us to capture changes in landslide hazard both spatially and temporally across the country. The algorithm uses NDVI differencing to identify possible new landslides. Our work seeks to refine this output by using landslide-specific information obtained from a series of existing manually mapped landslide inventories. This step includes applying spectral and object-based filters as well as using susceptibility metrics, such as topography, trained using manually mapped landslide inventories. By adding a landslide-specific filtering step, we aim to build on existing NDVI differencing approaches and improve per pixel landslide probability values. We present preliminary findings using this record of landslide hazard through time to better understand controls on slope failure evolution and persistence, to tackle questions such as whether new landslides evolve and runout from existing landslides, to consider how landslide mechanism changes through time, and how hazard translates into physical exposure through the use of metrics such as landslide proximity to roads and buildings.

How to cite: Harvey, E., Rosser, N., Kincey, M., Densmore, A., Shrestha, R., Singh Pujara, D., Dunant, A., Van Wyk de Vries, M., and Arrell, K.: Using Google Earth Engine to map landslide hazard and exposure across Nepal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15272, https://doi.org/10.5194/egusphere-egu24-15272, 2024.

EGU24-15430 | PICO | NH6.2

The environmental and health impact of salt dust aerosols from the dried Lake Urmia 

Mahshad Firouzeh and Mohammad Danesh-Yazdi

Lake Urmia (LU), a hypersaline lake in Iran and formerly recognized as the second-largest hypersaline lake worldwide, was desiccated to an area of less than 350 km2 in August 2023, facing almost a complete drying condition. This environmental catastrophe has resulted in the generation of extensive playas, potentially acting as sources of salt dust that, in turn, pose health and environmental risks to the nearby areas. In this study, we first identified the major environmental controls influencing salt dust generation in LU and developed a learning-based model to predict aerosol optical depth (AOD) using satellite data from 2017 to 2023. We then quantified the impact of salt dust aerosols diffused within a radius of 20 km around LU on the neighboring residential regions. The results demonstrated a significant correlation between AOD around LU and soil moisture (-0.66), soil temperature (0.70), wind speed (0.29), and precipitation (-0.53). We also found a significant correlation of 0.91 between the monthly averaged AOD in the East Azerbaijan and West Azerbaijan provinces and that observed in LU. Finally, the calibrated learning model could predict AOD with high accuracy, evidenced by R2 = 0.77 and RMSE = 0.147. The developed model can further be used to assess the impact of future climate-driven changes in the meteorological variables on the salt dust generation from LU.

How to cite: Firouzeh, M. and Danesh-Yazdi, M.: The environmental and health impact of salt dust aerosols from the dried Lake Urmia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15430, https://doi.org/10.5194/egusphere-egu24-15430, 2024.

With the increase of urbanization, the urban heat island phenomenon is becoming more noticeable and concerning. This effect occurs when the temperatures are higher in urbanized areas than in suburban and rural areas. The aim of this study is to analyze the influence of different land cover types on the land surface temperature (LST) and the surface urban heat island (SUHI) effect. The study was conducted on imagery acquired in September by Landsat 8 OLI TIRS satellite. The selected area was the city of Lucknow (India) and its surroundings. The climate is subtropical, seasons are clearly distinguishable - winters are cold, summers are hot and dry. Land cover types were determined using supervised classification and Normalized Difference Vegetation Index. Land surface temperature was calculated. The influence of different land cover on LST and SUHI phenomenon was analyzed by using visual analysis, comparing average temperatures of land cover classes, creating temperature profile and calculating Urban Thermal Field Variance Index to analyze the intensity of SUHI.

The type of land cover affects land surface temperature therefore has an impact on the SUHI phenomenon. Build-up areas show much higher land surface temperature than non-urban, vegetated areas. The spatial distribution of these forms of land cover, i.e. the cumulative built-up area forming the city and the green areas around the city, combined with the with their characteristic surface temperatures, result in an surface urban heat island effect. Average temperatures of non-natural surfaces are around 5°C higher than average temperatures of natural surfaces. UTFVI indicates that the intensity of SUHI phenomenon is the highest in build-up and bare soil land cover classes, and the lowest for vegetation and water areas. The intensity also varies within a single class, in urban areas UTVI is higher in the center and decreases toward the vegetation class. The LST values and temperature profile indicates that the higher temperature of non-natural land cover forms affects not only the increased temperature of the surface on which they are located but also the areas in the close neighborhood. Temperature within the same land cover class of agricultural areas and meadows areas is higher when measured in the vicinity of the urban class.

How to cite: Szrek, A.: Influence of different land cover types on land surface temperature - case study of the Lucknow city in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15756, https://doi.org/10.5194/egusphere-egu24-15756, 2024.

Slow-moving landslides (SML; mm year−1 to 100 m year−1) can be a ubiquitous geomorphic process in tropical mountain landscapes. Yet, answer to crucial questions such as what landscape characteristics exert the most important control on their spatial distribution (e.g., slope, connection to rivers, climate, lithology, tectonic setting, recent deforestation, degree of anthropogenic activity, etc.), or how does their dynamic behaviour responds to landscape changes (urbanisation, deforestation, etc.), remains elusive – and is typically relying on information collected on single or a few landslide(s). Intrinsically complex, obtaining large-scale datasets with dense surface displacement measurements is even more so in the tropics, where field access is typically difficult, and rapid vegetation changes and persistent cloud cover hamper the use of satellite remote sensing. In this work, we attempt to overcome these limitations by exploiting synergies between spaceborne sensors (i.e., radar and optical) and deformation measurement techniques (i.e., interferometry and sub-pixel image correlation), to obtain multi-year datasets of the activity of SML in the western branch of the East African Rift (wEAR). Characterised by a large natural landscape and climatic diversity, the wEAR is exemplative of many tropical mountain regions, i.e., i) affected by large-scale land use changes and ii) disproportionately high landslide impacts and iii) largely overlooked in landslide research.  We collected a spatio-temporal inventory containing characterised by varying level of activity and behaviours, and located in contrasting environments. This regional-scale dataset will form the foundation for untangling the intricate influences of climate, lithology, tectonics and man-made environmental changes on the occurrence and activity of SML. By investigating their interaction with river system, we also aim at estimating how they contribute to controls on river sediment budgets, regional erosion rates, channel network evolution and flooding patterns – key for our understanding of landscape evolution, sediment budgets and geo-hydrological hazards. Overall, this work aims at moving forward our understanding of a key geomorphic process in severely under-researched types of environments subject to rapid changes. This is not only essential for a better hazard assessment, but also for comprehending how (human-induced and/or natural) environmental changes affect these landscapes and the sediment dynamics.

How to cite: Dille, A., Smets, B., Vanmaercke, M., and Dewitte, O.: Combining radar and optical satellite data to gather a comprehensive regional-scale dataset of the activity of slow-moving landslides in diverse tropical landscapes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16249, https://doi.org/10.5194/egusphere-egu24-16249, 2024.

EGU24-16496 | ECS | PICO | NH6.2

Detection and mitigation of ionospheric artifacts in the azimuth ground displacements through the SAOCOM-1 L-band SAR data exploitation 

Marianna Franzese, Claudio De Luca, Augusto Aubry, Manuela Bonano, Francesco Casu, Michele Manunta, Giovanni Onorato, Yenni Lorena Belen Roa, Pasquale Striano, Antonio De Maio, and Riccardo Lanari

In a scenario where an increasing number of L-band Synthetic Aperture Radar (SAR) satellite systems is expected to be launched, such as the NISAR (NASA-ISRO), PALSAR-3 (JAXA) and ROSE-L (ESA) sensors, in addition to the already operative PALSAR-2 (JAXA) and SAOCOM-1 (CONAE) systems, an important challenge is represented by the development of innovative techniques to mitigate ionospheric effects on the generated SAR images and derived products. Indeed, widely used methods for ground displacement analysis, as for instance the Differential SAR Interferometry (DInSAR), the Multi Aperture Interferometry (MAI) and the Pixel Offset Tracking (POT) techniques, can suffer for the presence of such ionospheric effects, which can have a major impact on both the phase and the amplitude of the L-band SAR data. In this regard, it is well known that the propagation delay of the microwave signal induced by the variation of the Total Electron Content (TEC) in the ionosphere is inversely proportional to the frequency of the transmitted signal, in other words, the low-frequency signals experience more delay than the higher-frequency ones.

In the recent years, several methods have been proposed to estimate and mitigate ionospheric effects in the DInSAR measurements. Among them, we mention the Faraday rotation estimation, the azimuth shift and the range split-spectrum techniques. In particular, we underline that the range split-spectrum method will be exploited at system level as a solution for systematically correcting the ionospheric artifacts in the DInSAR products achieved through the NISAR mission. Indeed, the L-band NISAR sensor includes a 5-MHz sideband separated from the 20- or 40-MHz main band, allowing to mitigate the ionospheric and non-dispersive phase artifacts. However, it is also worth remembering that the mentioned range split-spectrum method fails if the ionospheric effects impact also the azimuth displacement component. The variations of the TEC along the azimuth direction causes the so-called “azimuth streaks” that reveals itself as an offset in the pixel azimuth position, thus affecting the SAR co-registration procedure and, consequently, the surface displacement measurements.

The aim of this work is firstly to investigate, in presence of ionospheric effects, the performance degradation of the MAI and POT techniques. Moreover, a solution technique is introduced that capitalizes on the large L-band data archives collected over the area of interest to effectively detect and mitigate the ionospheric artifacts. To this end, the StripMap L-band SAR images acquired by the SAOCOM-1 constellation are extensively exploited. In particular, results are presented based on the analyses carried out following the seismic events occurred on  February 2023 in South-East Türkiye near the border with Syria and the Litli-Hrútur volcano eruption in Iceland, which took place on  July 2023.

How to cite: Franzese, M., De Luca, C., Aubry, A., Bonano, M., Casu, F., Manunta, M., Onorato, G., Roa, Y. L. B., Striano, P., De Maio, A., and Lanari, R.: Detection and mitigation of ionospheric artifacts in the azimuth ground displacements through the SAOCOM-1 L-band SAR data exploitation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16496, https://doi.org/10.5194/egusphere-egu24-16496, 2024.

EGU24-17922 | ECS | PICO | NH6.2

Monitoring of La Palma 2021 volcanic eruption using Interferometric and Amplitude SAR data 

Pablo Ezquerro Martín, Guadalupe Brú Cruz, Ines Galindo, Oriol Monserrat, Juan Carlos López-Davalillo, Nieves Sánchez, Isabel Montoya, Riccardo Palamà, Rosa María Mateos, Raul Pérez-López, Elena González-Alonso, Raphaël Grandin, Carolina Guardiola-Albert, Juan López-Vinielles, José Antonio Fenández-Merodo, Gerardo Herrera, and Marta Béjar-Pizarro

Volcanic eruptions are a severe threat to approximately 800 million people living around 100 km from a volcano in 86 countries. For the eruptions affecting densely populated areas it is necessary to guarantee, during the emergency, the safety of the population, which requires a precise and reliable monitoring of the evolution of the volcano and the associated geological hazards.

This work shows the application of monitoring products during an emergency. Under those circumstances some requirements like the quick availability of the satellite data, the availability of experts to generate the needed products or the accessibility of the results for the decision-making authorities are of crucial importance.

During La Palma eruption in 2021, SAR data from 4 different satellites were used to generate three SAR-derived products to monitor the evolution of the morphology of the volcanic building, the extension of lava flows and ground deformation evolution in time. The availability of data from various satellites with different characteristics allows for their comparison, analyzing and identifying which is the optimal satellite and/or SAR dataset to generate each result.

This work is part of the Spanish Grant SARAI, PID2020-116540RB-C21, funded by MCIN/AEI/ 10.13039/501100011033.

How to cite: Ezquerro Martín, P., Brú Cruz, G., Galindo, I., Monserrat, O., López-Davalillo, J. C., Sánchez, N., Montoya, I., Palamà, R., Mateos, R. M., Pérez-López, R., González-Alonso, E., Grandin, R., Guardiola-Albert, C., López-Vinielles, J., Fenández-Merodo, J. A., Herrera, G., and Béjar-Pizarro, M.: Monitoring of La Palma 2021 volcanic eruption using Interferometric and Amplitude SAR data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17922, https://doi.org/10.5194/egusphere-egu24-17922, 2024.

EGU24-18788 | ECS | PICO | NH6.2

South Lhonak Glacial System: Cascade Investigation Using Satellite Remote Sensing 

Manmit Kumar Singh, Sandeep Kumar Mondal, and Rishikesh Bharti

In the Himalayas, the melting of glaciers leads to the creation of proglacial lakes. The expansion of these glacial lakes poses a significant risk of glacial lake outburst floods (GLOFs), a serious geomorphological hazard involving the sudden release of water from the glacial lake. The Teesta basin in the Sikkim Himalaya is home to numerous glacial lakes in the high-altitude glacierized region, including one of the largest and fastest-growing, South Lhonak Lake (SLL). The SLL is a moraine-dammed glacial lake in Sikkim's northern district (27˚54.741’ N and 88 ˚11.857’E). Situated at an elevation of 5200 msl (mean sea level), the lake is east-west elongated and located in the tongue of the South Lhonak glacier. The date of October 4, 2023, marks a significant event in the state of Sikkim. Investigation reports reveal a severe outburst flood triggered due to the breach of the moraine dam embankment around SLL. This wreaked havoc in the northeastern state, causing substantial damage and loss, especially along the Lachen and Chungthang regions downstream. The present study attempts to investigate the geometric changes in the lake between 2015 and 2023 using C-band Sentinel-1 Synthetic Aperture Radar (SAR) datasets. The glacial region is studied using the land surface temperature (LST) into a moisture index obtained from Landsat-8 Operational Land Imager (OLI) imagery. The lake’s geometric information (length and areal coverage) is acquired through a coupled automated manual delineation approach on the Google Earth engine platform. Analysing the backscatter information of Sentinel-1 datasets shows that the stretch of the lake has substantially increased by 575m (reaching up to 2.946 km) in 2023 before the outburst. Its average annual rate of expansion is observed to be 0.05 km² in the last 8 years (2015 to 2022). The lake volume is calculated using the well-established empirical equation for South Lhonak Lake using lake area. The average volume of water in the lake from 2015 till 2023 (before the GLOF) is observed to be 102.4 million m³, which is 55.59% more than the lake volume in 2014-2016 (65.8 million m³). After the event, there is approximately a 79.44% decrease in the lake volume, a 59% decrease in the lake area, and a 48.40% decrease in lake length. The largest change in the area of the lake is observed between 2020 and 2021. Apart from the geometric changes, the moisture index has shown a monotonous increment since 2018, suggesting enhanced melting of the South Lhonak glacier, which can be attributed as one of the important parameters for the formation of such a dangerous glacial lake. The application of geospatial technology in this research can offer valuable insights into the changes occurring in glacial systems in the Himalayas. Implementing such investigative protocols is crucial for comprehending the development patterns of moraine-dammed glacial lakes, thereby aiding in the formulation of effective mitigation strategies.

How to cite: Singh, M. K., Mondal, S. K., and Bharti, R.: South Lhonak Glacial System: Cascade Investigation Using Satellite Remote Sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18788, https://doi.org/10.5194/egusphere-egu24-18788, 2024.

EGU24-19476 | PICO | NH6.2

SAR and Optical Remote Sensing for Flood Mapping and Monitoring through GEE 

Francesca Giannone, Erik Guerrisi, Massimo Scaglione, and Silvia Di Francesco

The work explores the use of Synthetic Aperture Radar (SAR) and optical sensors on board the Sentinel-1 and Sentinel-2 satellites for mapping and monitoring the Earth's surface in response to flood events. The choice of SAR proves advantageous due to its ability to penetrate clouds, ensuring continuity in acquisitions even in adverse weather conditions.  

The Google Earth Engine (GEE) platform, which provides the opportunity to customize algorithms and scripts, is used to perform the analysis. The goal is to develop an integrated methodology for early warning and impact mitigation. Two case studies are here presented: the flood that affected Ravenna in May 2023 and  the Apollo hurricane in Sicily in 2021. The results confirm the effectiveness of the proposed approach in monitoring and discriminating water-covered surfaces. Despite challenges in data processing and calibration, the approach proves to be a valuable monitoring tool. The integration of SAR and optical data provides a comprehensive view of the flood situation, confirmed by the convergence of information from both satellites and news services.

How to cite: Giannone, F., Guerrisi, E., Scaglione, M., and Di Francesco, S.: SAR and Optical Remote Sensing for Flood Mapping and Monitoring through GEE, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19476, https://doi.org/10.5194/egusphere-egu24-19476, 2024.

EGU24-20230 | PICO | NH6.2

Enhancing disaster response through improved access to EO Data: EOTEC DevNet's Collaborative Approach 

Martyna A. Stelmaszczuk-Górska, Erin Martin, Yakov M. Moz, John J. Murray, Ganiy Agbaje, Jean Danumah, William Straka III, CM Bhatt, Luca Brocca, Terefe Hanchiso Sodango, Effiom Oku, Fabiola D. Yépez Rincón, Rishiraj Dutta, Mark Higgins, and Nancy D. Searby

The Earth Observation Training, Education, and Capacity Development Network (EOTEC DevNet) is a global network of networks in the forefront of integrating satellite Earth information into decision-making, especially in managing disasters. The Network focuses on fostering expert collaboration and knowledge sharing on the use of Earth Observations (EO) in improving disaster risk reduction efforts globally.

The primary goal is to enhance the accessibility of EO tools and training. The network aims to support a broad audience, ranging from local authorities to international agencies, in effectively utilising EO data for disaster management. The approach involves aligning existing EO solutions with the needs of those managing hazards such as floods and droughts. Additionally, the network seeks to bridge the gap by disseminating knowledge to partner institutions and the entities responsible for implementation, aiming to harness the strengths of both and address the requirements of disaster risk reduction.

Crucial to this initiative are the ‘Communities of Practice’ that form the backbone of EOTEC DevNet. These dynamic groups are the main drivers in the development of vital resources like the Flood Tools Tracker and the Drought Tools Matrix. These comprehensive guides assist users in selecting and utilising appropriate tools for varied disaster scenarios, showcasing commitment to enhancing stakeholder engagement with EO data across all disaster management stages. Beyond creating tools, this network of experts encourages learning through collaboration. Real-world cases of regional flooding and other disasters are analysed to show how EO tools can be used in practice. These studies/analysis highlights the impact of EO data in enhancing early warning systems and in the response and recovery from disasters. Lessons learned can be replicated elsewhere in the world as part of contribution to Disaster Risk Reduction.

EOTEC DevNet fosters an interactive online community where experts can share knowledge and resources. This platform is a hub for connecting people based on their areas of interest in EO and disaster risk reduction. It plays a key role in our efforts to build a stronger network of professionals to join in driving and delivering on the UN-WMO global assignment of “Early Warning for All (EW4All)”. While also enhancing global capacity in disaster management.

In summary, EOTEC DevNet is committed to improving disaster risk management through EO data. Our focus on collaboration, resource sharing, and practical application of EO tools is paving the way for more effective disaster management worldwide. The paper will present the operational structure of EOTEC DevNet; Establishment of; Meeting/Engagement Platform; a brief look at the Flood Tools Tracker and the Drought Tools Matrix; and other achievements that have been accomplished so far.

How to cite: Stelmaszczuk-Górska, M. A., Martin, E., Moz, Y. M., Murray, J. J., Agbaje, G., Danumah, J., Straka III, W., Bhatt, C., Brocca, L., Hanchiso Sodango, T., Oku, E., Yépez Rincón, F. D., Dutta, R., Higgins, M., and Searby, N. D.: Enhancing disaster response through improved access to EO Data: EOTEC DevNet's Collaborative Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20230, https://doi.org/10.5194/egusphere-egu24-20230, 2024.

At 07:10:39 (GMT ) on 1st January 2024, a devastating earthquake struck the west coast of Honshu, Japan. According to the Global Centroid Moment Tensor (CMT) Project, the magnitude and depth of the earthquake are respectively 7.5 Mw and 12 km; and the epicentre is located at Noto, Ishikawa Prefecture, Honshu (latitude: 37.490°N, longitude: 137.170°E). Two weeks after the earthquake (up to 15th January), the death toll had risen to 221. Besides heavy casualties, post-seismic ground deformation caused by the earthquake is intensively reported. In order to study the ground deformation caused by this large and shallow earthquake, the satellite geodetic technique, namely the synthetic aperture radar interferometry or interferometric
synthetic aperture radar, InSAR, will be adopted in this study. Moreover, Sentinel 1 Level 1 SLC product from the Copernicus Program will be utilized. An InSAR processing system based on the Generic Mapping Tools (GMT), or GMTSAR, for short, is used for data processing. Preliminary pre-seismic, co-seismic, and post-seismic results derived from GMTSAR will be shown together with the outcomes from the Sentinel Application Platform (SNAP) if applicable.

How to cite: Ng, S.-M.: Preliminary InSAR Results of t he 2024 Noto Japan Earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22244, https://doi.org/10.5194/egusphere-egu24-22244, 2024.

EGU24-889 | Posters on site | NH6.3

Surface deformation and Source Parameters of 2023 Hatay Earthquake inferred from the InSAR Data Analysis 

Merve Ercan, Tülay Kaya Eken, Çağkan Serhun Zoroğlu, Emre Havazlı, and Haluk Özener

Abstract

Tectonic features of Türkiye are mainly controlled by the relative northward movements of the Arabian and subducting African plates with respect to the Anatolian and Eurasian plates. Resultant extensional and collisional tectonics lead to a westward material extrusion accommodated along the right- and left-lateral strike-slip North Anatolian and East Anatolian Fault Zones (NAFZ and EAFZ), respectively. This lateral motion continues southward along the Dead Sea Fault Zone (DSFZ) at the southeastern of Türkiye. February 20, 2023, Mw 6.3 Hatay Earthquake occurred two weeks after the seismic energy release of the February 6, 2023, Kahramanmaraş earthquakes at the intersection of EAFZ, DSFZ, and the onshore extension of the Cyprus Arc. The N-S trending DSFZ starts from the south of the EAFZ and continues through Syria, Lebanon, and Israel. Although the broken segment in Hatay is not as active as the northern segments of the EAFZ, it has accumulated strain leading to significant seismic activity in the past in this region, i.e., the 1872 M7.2 earthquake occurred on the Karasu Fault. 2023 Kahramanmaraş and Hatay earthquakes caused severe damage in Hatay and the surrounding area. To determine the co-seismic deformation during the February 20, 2023, Hatay Earthquake, we applied the Interferometric Synthetic Aperture Radar (InSAR) technique on the Sentinel-1 data. Ascending and descending track SAR images before and after the Kahramanmaraş and Hatay earthquakes were analyzed using the TopsApp module of the InSAR Scientific Computing Environment (ISCE) software to obtain Interferograms of co-seismic deformation in and around Hatay region. Finally, we investigated source parameters by performing an inversion on geodetic constraints considering the Okada elastic dislocation model.

How to cite: Ercan, M., Kaya Eken, T., Zoroğlu, Ç. S., Havazlı, E., and Özener, H.: Surface deformation and Source Parameters of 2023 Hatay Earthquake inferred from the InSAR Data Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-889, https://doi.org/10.5194/egusphere-egu24-889, 2024.

EGU24-912 | ECS | Posters on site | NH6.3

Assessing the correlation of Time-Series Soil Moisture and Ground Deformation At Petacciato Landslide, Italy 

Divyeshkumar Rana, Prof. Paolo Mazzanti, and Prof. Francesca Bozzano

Soil moisture is an important parameter in many fields, including agriculture, climatology, hydrology, and geohazards. Accurate and high spatial resolution soil moisture estimation can improve our understanding of hydrological processes, and climatic interaction, and a more complete view of the domain. Soil moisture estimation can enhance our understanding of preparedness for natural hazards such as landslides, sinkholes, and subsidence. Single-dual polarimetric data is widely used for assessing and monitoring soil moisture due to the availability of datasets. This research proposes a synergized approach using the change detection method based on backscatter information using SAOCOM L-Band Synthetic Aperture Radar (SAR) datasets from 2021 to 2023 to estimate soil moisture and ground deformation using Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) using CosmoSkyMED X-Band datasets from 2011 to 2022. We present a case study of the Petacciato landslide, Molise Region, Italy. The Petacciato landslide is a coastal area in Europe highly prone to mass movements. It is in the northwestern sector of the Molise region (central Italy) in the outermost portion of the central-southern Apennine chain. Timeseries soil moisture results were further compared with the historical open-source meteorological datasets. Precipitation events lead to the most soil moisture that is observed between November to February months. The average ground deformation (LOS velocity) observed on unstable slopes ranged from -1 mm/year to -20 mm/year in the study area.

How to cite: Rana, D., Mazzanti, P. P., and Bozzano, P. F.: Assessing the correlation of Time-Series Soil Moisture and Ground Deformation At Petacciato Landslide, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-912, https://doi.org/10.5194/egusphere-egu24-912, 2024.

EGU24-1484 | Posters on site | NH6.3

InSAR points’ geolocation uncertainty estimation and geolocation improvement using LiDAR 

Jiacheng Xiong and Ling Chang

Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) technique can monitor displacement processes intarget areas with millimeter precision. However, limited by decimeter- or meter- level InSAR geolocation accuracy, directly associating InSAR points with actual ground targets merely based on InSAR-derived geolocation estimates is not always reliable. Especially for linear infrastructure like dams, poor-quality geolocation estimations can lead to deviations in the three- dimensional (3D) position of InSAR points, thereby failing to accurately link InSAR points with the specific structures of the dam. Here, we propose a method for 3D geolocation improvement of InSAR points based on the 3D error ellipsoid of InSAR positioning estimation and aided by Light Detection and Ranging (LiDAR) data (0.5 x 0.5 m). By establishing an error ellipsoid of every InSAR point and utilizing rotation and projection matrices for LiDAR datum transformation, we extract all LiDAR points located within the error ellipsoid and update InSAR point geolocation based on the extracted LiDAR values and their statistics. This process recalculates the 3-D geolocation of InSAR points and improves its accuracy. We applied this method to the Houtribdijk dam in the Netherlands, andimproved the InSAR points obtained with 152 and 148 Sentinel-1A IW SAR data (10 x 5m) in ascending and descending orbits acquired between 2018 and 2022, using the Actueel Hoogtebestand Nederland 3 (AHN3) LiDAR point cloud with centimeter-level accuracy. The results show that the InSAR points with 3D error ellipsoid properly link with structures over the entire dam compared with the points without concerning positioning uncertainty. For the SAR data in ascending and descending orbit, the Root Mean Square Errors (RMSE) of the heights between the LiDAR-based improved InSAR points and AHN3 LiDAR points are 0.4 m and 0.5 m, respectively. In contrast, the RMSE values for the InSAR points without LiDAR-based improvement are 1.4 m and 1.6 m, respectively. Furthermore, we compared the correlation of heights between all InSAR points on the dam and the AHN3-derived digital terrain model (DTM). The correlation of heights between the InSAR points without and with geolocation improvement and the AHN3 DTM is 0.14 and 0.95 with the RMSE values of 1.9 m and 0.5 m for ascending, 0.11 and 0.95 with the RMSE values of 1.2 m and 0.5 m for descending, respectively. All this demonstrates the efficacy of our method, and allows us to further precisely identify InSAR points from the slopes and top of the dam for the dam structures’ displacement assessment.

 

[1] Dheenathayalan P, Small D, Schubert A, et al. High-precision positioning of radar scatterers. Journal of Geodesy, 2016, 90(5): 403-422.

[2] Chang L, Sakpal N P, Elberink S O, et al. Railway infrastructure classification and instability identification using Sentinel-1 SAR and laser scanning data. Sensors, 2020, 20(24): 7108.

[3] Zhang, B., Chang, L., Stein, A., 2021. Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images. ISPRS Journal of Photogrammetry and Remote Sensing, 176.

How to cite: Xiong, J. and Chang, L.: InSAR points’ geolocation uncertainty estimation and geolocation improvement using LiDAR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1484, https://doi.org/10.5194/egusphere-egu24-1484, 2024.

EGU24-2017 | ECS | Orals | NH6.3

An operational way of SAR feature creation to facilitate machine learning analyses 

Xu Zhang, Ling Chang, and Alfred Stein

Satellite missions have delivered a wealth of SAR images for Earth monitoring applications since the 1990s. Due to the complex nature of SAR images and a limited amount of accessible SAR labeling data, these images remain underutilized in providing reference information for machine learning. In response to this gap, we designed a SAR feature creation workflow in an operational framework by releasing Jupyter tools to the public.  The workflow is developed upon Doris-5 and consists of two streams. The first stream utilizes SAR images to generate basic SAR and SAR interferometric and polarimetric features. The second stream capitalizes on other available geospatial datasets, such as optical images, cadastral and geological maps, to generate additional features for SAR data that can be treated as reference data. They are first radar-coded to align with the extracted SAR features and then geo-coded in geographic coordinates. All SAR features are concatenated as separate layers in the NetCDF data format, which contains STAC (spatio-temporal asset catalogs) for the data querying.

For the demonstration, an area in the province of Groningen, the Netherlands, was selected as the test site. Seven ascending Sentinel-1A images in VV and VH modes on track 15 between January and March 2022 were used, along with the topographic base map – TOP10NL dataset as a reference. The extracted features encompass VV amplitude, VH amplitude, VV interferometric phase, VV coherence, intensity summation, intensity difference, intensity ratio, cross-pol correlation coefficient, cross-pol cross product, entropy, buildings, roads, water and railways. The first ten features were created via the first stream, while the last four features via the second stream. By applying a random forest classifier to these fourteen SAR features, the model resulted into four types of classified SAR images: building, road, water and railway. The overall accuracy was 0.8558, 0.9939, 0.9065, and 0.8191, with corresponding F1-scores of 0.9191, 0.9669, 0.9490, and 0.9006, respectively.

We conclude that the created SAR features well facilitate machine learning, and that even a simple random forest classification can yield relatively high-accuracy results. In addition, our workflow to create SAR features is well suited to prepare labeled features for machine learning analyses that are even friendly to a user with limited knowledge of SAR.  

How to cite: Zhang, X., Chang, L., and Stein, A.: An operational way of SAR feature creation to facilitate machine learning analyses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2017, https://doi.org/10.5194/egusphere-egu24-2017, 2024.

EGU24-2419 | Posters on site | NH6.3

Mapping and monitoring different types of landslides through InSAR in the Northern Apennines of Italy 

Atif Ahmad, Alessandro Mercurio, Benedikt Bayer, Silvia Franceschini, and Alessandro Simoni

Landslides in mountainous regions are a major concern due to their potential impact on infrastructure and human lives. Many deep-seated slope movements alternate between phases of sustained movement to phases of dormancy. Detecting and monitoring active movements over large territories can effectively support risk mitigation efforts. Satellite radar interferometry is widely used for such purposes, despite its poor coverage in uninhabited rural areas. Our study aims to overcome such limitations by using conventional two-pass interferometry. We use interferometric stacking to improve the signal-to-noise ratio and carefully select interferogram duration and coherence to enhance the ability to detect active slow-moving landslides. The current study focuses on five large catchments of the Northern Apennines, Italy. In the first phase of the study, yearly stacks from 2016 to 2023 were used to identify InSAR Deformation Signals likely related to slope deformation processes. More than 80 signals were detected in the study area, showing sustained deformation in multiple interferometric stacks either in ascending and/or descending geometry. This provides strong evidence for the effectiveness of our approach. We compare our results with geomorphological and geological information, as well as the landslide inventory, illustrating how active landslides are favored by weak lithologies and pre-existing slope instability. The analysis of the evolution of selected signals over time, representative of the pattern of landsliding in our study area, shows distinct trends for landslides involving fine-grained materials and arenaceous bedrock. Earthslides and earthflows show sustained downslope motion with seasonal velocity changes, while rockslides are subject to short-duration acceleration episodes. Time series analysis show that surface displacements can be observed throughout most part of the year, with exceptions during periods of snow cover and the summer peak of vegetation. These findings highlight the potential of standard InSAR for mapping and monitoring active landslides. 

How to cite: Ahmad, A., Mercurio, A., Bayer, B., Franceschini, S., and Simoni, A.: Mapping and monitoring different types of landslides through InSAR in the Northern Apennines of Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2419, https://doi.org/10.5194/egusphere-egu24-2419, 2024.

Land subsidence has a great impact on coastal plains near sea level, leading to permanent inundation. The Shuguang oilfield, located in Liaohe River Delta (LRD), northeastern China, is one of the most significant subsidence areas as a direct consequence of oil production. We studied the production-induced deformation in the LRD region by Sentinel-1 radar images. Images from two ascending and two descending tracks are processed by an Interferometric Synthetic Aperture Radar (InSAR) time series analysis over the 2017 to 2021 period, providing deformation rate maps and time series in the radar line-of-sight (LOS) direction.

Previous researches carried out in this area assumed the oil production-induced deformation corresponds only to vertical deformation. Here, we proposed a method to retrieve the three-dimensional (3D) displacement field over the oilfield. We retrieved the vertical and east-west deformation components by combining the multiple InSAR geometries LOS observations and retrieved the north-south component based on the assumption of a physical relationship between the horizontal and vertical displacement.

The derived 3D displacement fields over Shuguang oilfield exhibit a circular subsidence bowl with a maximum subsiding rate reaching 212 mm/year, accompanied by a centripetal pattern of horizontal displacements with maximum rates up to 50-60 mm/year moving towards the subsidence center. The retrieved-3D displacements are in good agreement with predictions from the geomechanical modeling by assuming a disk-shaped reservoir subject to a uniform reduction in pore fluid pressure. Finally, we show the importance of knowing both the vertical and horizontal displacement in characterizing the lateral boundary of the subsurface reservoir.

The Liaohe River Delta region is often affected by heavy rainfall and storm surge in flood season, and flood disasters occur frequently in this low-lying coastal area. This deltaic region is vulnerable to floods not only from the extreme heavy rainfall, but also the land subsidence related to oil production. By spatial overlay analysis of the land subsidence distribution and the inundation extent of a flood event in August 2022, we reveal the impacts of land subsidence on flood inundation in this region. Our findings provide scientific support for oil production-related subsidence control and flood planning and designing in this deltaic region.

How to cite: Tang, W.: Three-dimensional deformation over Shuguang oilfield in Liaohe River Delta, China, from multi-track InSAR and its impacts on flood inundation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2842, https://doi.org/10.5194/egusphere-egu24-2842, 2024.

EGU24-2957 | ECS | Orals | NH6.3

Settlement and Landslide Risk Analysis of Temporary Soil Dump Based on InSAR and Continuous Medium Model 

Xiaoqiong Qin, Yuanjun Huang, Linfu Xie, Xuguo Shi, and Chisheng Wang

The planned soil dumping in Shenzhen has been insufficient for a long time, and improper disposal of excess soil would pose significant safety hazards such as soil settlement and landslides. Therefore, analyzing the causes and potential impacts of soil dumping disasters is crucial for effective risk prevention and control. Interferometry Synthetic Aperture Radar (InSAR) is an effective land surface deformation monitoring technology with unique advantages, including low costs, large-scale implementation potential, and a high coherence level in the settlement analysis of soil dumps without vegetation.

This study investigated a soil dump with the highest risk potential in the Shenzhen-Shanwei Special Cooperation Zone, processing 91 Sentinel-1 images from 2019 to 2022 for deformation monitoring. An improved Small Baseline Subset-InSAR (SBAS-InSAR) method was utilized to analyze the soil dump’s time-series deformation, and multi-source remote sensing data were used for auxiliary interpretation. The experimental results indicate that rainfall, high temperature, and construction vibrations may cause instability of the soil dump. When the monthly rainfall is 200 mm/month and the temperature is 30℃, the meteorological conditions significantly impact the soil dump’s stability. In addition, vegetation and drainage procedures can help resist the impact of high temperatures and rainfall. Activities such as slope excavation, earthwork filling, and gravel production are also the main causes of settlement fluctuation in the soil yard. However, with artificial excavation, unloading, and comprehensive management, the soil dump’s LOS velocity decreases by 10% to 45%.

The Chishi soil dump remains stable during the original period and does not show a subsidence trend until the soil dump is formed. The overall settlement rate is around -33.3mm/yr, and most severe settlement occurs near the north slope with a maximum deformation rate of about -51mm/yr. The closer to the landfill’s center, the greater the soil thickness and the more severe the settlement. Moreover, with similar soil thicknesses, the settlement rate on the slope is higher than that at the top of the soil dump.

The limit equilibrium analysis of the soil dump indicates a risk of instability under continuous heavy rainfall. Therefore, a depth-integrated continuous medium model was introduced to simulate the surface process and analyze the potential landslide risk. The landslide simulation results demonstrate that a landslide will likely occur, harm personnel, and damage the buildings on the north side of the soil dump when it is saturated (≥ 0.50). This research can provide case references for the analysis, interpretation, disaster prevention, and control evaluation of similar soil dumps.

 

How to cite: Qin, X., Huang, Y., Xie, L., Shi, X., and Wang, C.: Settlement and Landslide Risk Analysis of Temporary Soil Dump Based on InSAR and Continuous Medium Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2957, https://doi.org/10.5194/egusphere-egu24-2957, 2024.

EGU24-2972 | ECS | Posters on site | NH6.3

Unify Different Interferograms to Get the Unique InSAR Time Series 

Zhangfeng Ma, Yu Jiang, Chenglong Li, and Shengji Wei

“Long or short baseline interferogram” is a well-known concept in InSAR time series analysis. In different cases, scientists often choose interferograms with different baselines based on some specific criteria, such as the level of coherence, the degree of atmospheric delay, and the length of the spatiotemporal baseline to get the best results. However, a question behind the selection of interferograms still keeps intact, that is, why do different interferograms get different results? The recent case of deriving the postseismic deformation of 2021 Maduo Mw7.4 Earthquake illustrates just how important this question is, in which almost every team achieved different results. We highlight the roles of unwrapping error and fading signal in this case, which can explain why different interferograms can get different results. We also proposed a new method to correct these two error sources. After the correction, we unify the time series results from different interferograms. In addition, we also explored the relationship between fading signal and soil moisture, and successfully mapped the liquefaction related to earthquake using InSAR, which to our knowledge is the first time in the world.

How to cite: Ma, Z., Jiang, Y., Li, C., and Wei, S.: Unify Different Interferograms to Get the Unique InSAR Time Series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2972, https://doi.org/10.5194/egusphere-egu24-2972, 2024.

EGU24-4011 | ECS | Orals | NH6.3

InSAR Insights into the Massive Himalayan Leo Pargil Landslide 

Gökhan Aslan, Marcello de Michele, Tim Redfield, Mikis van-Boeckel, Reginald Hermanns, François Noël, and John Dehls

In the dynamic landscape of the northwest Indian Himalayas, the Leo Pargil Landslide stands as a monumental example of slope instability. This study marks the first detection of this giant landslide through Interferometric Synthetic Aperture Radar (InSAR) techniques. Spanning an impressive 55 km² and mobilizing approximately 25 km³ of rock material towards the Spiti River at a rate of 80 mm/year, it poses significant risks to several villages, towns, and the NH505 highway located atop and along its path.

Deep-Seated Gravitational Slope Deformations (DSGSDs), such as the Leo Pargil Landslide, are pivotal in shaping mountainous landscapes. These giant landslides significantly influence topographic evolution, particularly in regions marked by rapid rock uplift in steep terrain. Understanding these processes is crucial, given their geological significance and the natural hazards they pose to communities in tectonically active regions. However, their inherent unpredictability, influenced by factors like geology, geomorphology, climate, and seismic activities, makes evaluating landslide dynamics a challenging task.

The Leo Pargil Landslide, bounded by the northeast-trending Leo Pargil Shear Zone (LPSZ) and incorporating several brittle normal faults, is conditioned by at least three geological factors: steep slope terrain, the bedding structure of the rock formation, and deep river incision at the base of the landslide. Our study investigates the factors conditioning the landslide, the driving forces behind it, and its evolution, offering new insights into the underlying mechanisms of failure.

In this study, we utilized Sentinel 1A/B satellites, applying Persistent Scatterer (PS) InSAR processing techniques to analyze the active dynamics of the Leo Pargil landslide. By combining InSAR derived velocity field data with the local geology, geomorphological features of the slope and previously published geochronological data we tried to elucidate the possible mechanisms involved in the initiation and development this landslide.

The findings underscore the role of dome exhumation as a geomechanical driver of slope dynamics. The transition in stress fields, tectonic and structural influences, and the interplay between erosion, river incision, and monsoon precipitation anomalies are highlighted as significant factors in the landslide's development. This comprehensive understanding is vital for slope stability assessments and risk mitigation strategies in the Himalayan region.

In conclusion, the study links geomechanical, geochronological, and geomorphological analyses to unravel the complexities of the Leo Pargil Landslide. It emphasizes the significance of the Leo Pargil Dome, not merely as a backdrop but as an active contributor to landslide dynamics, highlighting the critical need to consider both local and broader tectonic contexts in understanding slope instability

How to cite: Aslan, G., de Michele, M., Redfield, T., van-Boeckel, M., Hermanns, R., Noël, F., and Dehls, J.: InSAR Insights into the Massive Himalayan Leo Pargil Landslide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4011, https://doi.org/10.5194/egusphere-egu24-4011, 2024.

EGU24-4398 | ECS | Posters virtual | NH6.3

Building Earthquake Damage Recognition Based on Frequency Domain Texture Features from PolSAR Data 

Wei Zhai, Jianqing Du, and Gangyu Yang

The collapse of buildings caused by destructive earthquakes often caused severe casualties and economic losses. After an earthquake, the assessment of building damage is one of the most important tasks in earthquake emergency response. Accurate assessment of building damage will be essential in making plans of emergency responses. Four-Polarimetric Synthetic Aperture Radar (PolSAR) data has the advantages of Synthetic Aperture Radar (SAR) imaging that is not occluded by sunlight and clouds, it also contains the most abundant information of four polarimetric channels. Due to the large amount of information in PolSAR data, only a single post-earthquake PolSAR image can be used to identify building damage of post-earthquake. It is easy to overestimate the number of collapsed buildings and the damage degree of earthquakes only using a traditional polarimetric decomposition method for PolSAR data. The layout of urban buildings can be diverse. Buildings can stand in parallel in typical SAR imaging with strong scattering features, there are also some oriented standing buildings with lower scattering intensity and with similar scattering characteristics of collapsed buildings, thus these oriented buildings are often misconstrued as collapsed buildings. The spatial frequency of SAR images can be clearly rendered in the frequency domain. In this study, we propose a new texture feature based on Fourier transform, namely the sector texture feature of the Fourier amplitude spectrum (STFFAS), to solve the overestimate of damage of buildings, which are caused by earthquakes. STFFAS can well describe the difference in texture between oriented buildings and collapsed buildings and accurately recognize the two types of buildings. The STFFAS index can be defined as follows:

             (1)

where ‘FFT’, ‘std’, ‘mean’ and ‘lg’ represent the function of 2D fast Fourier transform, standard deviation, mean values and logarithm to the base 10, respectively; ‘real’ and ‘imag’ represent the real parts and imaginary parts of complex numbers, respectively. Meanwhile, based on the Yamaguchi four-component decomposition method and the STFFAS texture feature parameter, we develop a solution to identify the damage of buildings only using a single post-earthquake PolSAR image. The Ms7.1 Yushu earthquake, which occurred in Yushu County of China on 14th April, 2010, is used as a study case to carry out the experiment with 75000 undamaged and damaged building samples. With the proposed method, the overall accuracy of correct building damage recognition with STFFAS is 81.30%. The Producer‘s Accuracy (PA) of damaged buildings, which is the correct recognition rate of collapsed buildings, is 81.06%; and the PA of undamaged buildings, which is the correct recognition rate of undamaged buildings, reaches 81.42%. Compared with the traditional polarimetric decomposition method, 70.18% standing buildings are successfully isolated from the mixture of collapsed buildings. Therefore this new method has greatly improved the accuracy and reliability of extracting damage information of buildings. This result well confirmed that the texture feature in frequency domain is effective for building damage recognition.

How to cite: Zhai, W., Du, J., and Yang, G.: Building Earthquake Damage Recognition Based on Frequency Domain Texture Features from PolSAR Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4398, https://doi.org/10.5194/egusphere-egu24-4398, 2024.

Over the past six decades, the groundwater became the main source of water following a serious shortage in surface water in the North China Plain (NCP). This resulted in a large area of groundwater level (GWL) depression and land subsidence cones. To address this crisis, the Chinese government implemented the largest water transfer project in human history—the South-to-North Water Transfer Project (SNWTP), the middle route of which was completed and put into operation in 2014. In this context, Tianjin, one of the main beneficiaries of this project, has been relieved from water shortages and begun to implement Groundwater Management Plans (GMP) such as water source conversion and ecological water replenishment for rivers and lakes since 2018, which undoubtedly have a significant effect on the groundwater recovery. Meanwhile, this provides a good case for studying the coupled process of ground settlement and groundwater dynamics, especially the soil deformation pattern driven by groundwater level (GWL) rebound. To analyze these issues in detail, field well data was collected to depict groundwater flow field. Moreover, geodetic data was also collated, including leveling, GPS, and InSAR, so that a vertical deformation field with high spatiotemporal resolution could be generated. The results reveal that the GWL of the third confined aquifer which is the main exploitation layer in Tianjin recovered significantly since 2018 with a rate of 2.1 m/yr. The area of GWL depression cones with a depth greater than 70 m has decreased by 85%. The dynamic deformation patterns indicate that the area of land subsidence cones in Tianjin has reduced significantly, accompanied by a sharply declining subsidence rate (decreased from -32.2 mm/yr to -4.5 mm/yr). Particularly, a significant poroelastic rebound has occurred in the Wuqing and Beichen districts since 2020, with the uplift rates in some areas exceeding 10 mm/yr. Furthermore, due to the delayed pore pressure dissipation in the aquitard, we find a time delay of 0.3–5.5 years between land subsidence and GWL time series, which is far less than that estimated by hydrogeological parameters, as the latter ignored the recharge and recovery capacity of the aquifer system. Finally, a evolution model in Tianjin was presented to illustrate interactive process among the deformation, pore pressure, and hydraulic head. In general, the SNWDP and the GMP has restored the pore pressure of aquifer, reduced the land subsidence, and alleviated the groundwater storage depletion of Tianjin, China.

How to cite: Su, G. and Xiong, C.: Coupled processes of groundwater dynamics and land subsidence in Tianjin, China after the South-to-North Water Transfer Project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4831, https://doi.org/10.5194/egusphere-egu24-4831, 2024.

The long-term over-extraction of groundwater in the North China Plain(NCP) has led to disasters such as ground subsidence, ground fissures, and seawater intrusion. These have posed serious threats to infrastructure, aquifer systems, and the ecological environment. By establishing a functional model of surface deformation and groundwater changes, we can enhance our understanding of the mechanisms behind ground subsidence and quantitatively assess how groundwater storage evolves under the dual influences of human activities and natural processes. InSAR (Interferometric Synthetic Aperture Radar) has proven to be the most effective tool for long-term、wide-area ground deformation monitoring and underground hydrological parameter inversion. Considering the characteristics of ground subsidence such as long-term, progressive, and wide distribution, in this study, eight stacks of 1496 Sentinel-1A/1B SAR scenes spanning from 2017 to 2023 were acquired in ascending mode along tracks T40 and T142. Through methods like (InSAR) time series analysis method、phase unwrapping correction and spatio-temporal smoothing fitting, we obtained a long-time-series high-precision LOS deformation field for the NCP. Secondly, by introducing the spatial domain network adjustment method, we can implement joint adjustment and correction of wide-area multi-map results to obtain a unified spatio-temporal reference for the NCP's wide-area InSAR vertical ground deformation field. Finally, we use the InSAR-VSM model based on elastic half-space and the one-dimensional poroelastic model considering elastic unloading to obtain independent quantitative estimates of groundwater loss in NCP. For the first time, we have reduced the spatial resolution of groundwater reserves inversion in the NCP from hundreds of kilometers to several kilometers, breaking through the bottleneck of insufficient spatial resolution in groundwater hydrological research. By integrating the South-to-North Water Diversion Project, groundwater extraction policies in the NCP, meteorological datasets, and groundwater level data, we have found that there are significant differences in the response mechanisms of groundwater and land subsidence between piedmont plains and flood plains in the NCP. Our data and results have enhanced our understanding of changes in groundwater storage in the North China Plain and provide scientific support for scientifically managing groundwater resources and carrying out related work on preventing and mitigating ground subsidence disasters.

How to cite: zhang, X. and hu, J.: Wide-area deformation surveying and Groundwater Volume Loss assessment in the North China Plain by Multi-track InSAR Observations and mechanical models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8212, https://doi.org/10.5194/egusphere-egu24-8212, 2024.

EGU24-8929 | ECS | Orals | NH6.3

Surface deformation along the Nile Delta, Egypt: From monitoring towards prediction 

Amira Zaki, Irene Manzella, Milan Lazecky, Andy Hooper, Ling Chang, Mark van der Meijde, and Islam Fadel

The Nile Delta represents the most critical part of Egypt, hosting more than 50% of the population and approximately two-thirds of the nation’s agricultural lands. During the last decades, the Nile Delta has suffered from significant surface deformation that has led to damage to transport networks and infrastructures, thus becoming a significant risk in the area. This deformation is mainly due to environmental changes and anthropogenic activities such as the over-extraction of groundwater for different purposes and the building of dams inside and outside Egypt along the river Nile. These activities have led to shortage of water inflow, changing the discharge rates, reduced sedimentation in the delta and changes in the water recharge rates of the Nile, the primary source of water for the Nile Delta aquifers. Regarding the environmental changes, the shifts in climate patterns, including variations in precipitation, rising temperatures, and rising sea levels, have all altered the hydrological balance of the Nile Delta, consequently leading to variations in surface deformation patterns. Many studies have studied the rate and patterns of land deformations in the Nile Delta based on geodetic tools such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR). But still, there is a gap in understanding the relationship between surface deformation rates and the causative factors. Such understanding could potentially enable the estimation of system response for future scenarios.

In this research, we present the results of a system that uses Sentinel-1 SAR data characterized by VV polarization, with ascending and descending orbital directions, acquired between 2015 and 2023 along the Nile Delta. We utilized open-source LiCSBAS tools to analyze the surface deformation rates from InSAR Sentinel-1 data. Then, we calculated the vertical deformation velocity over time by decomposing the ascending and descending LOS data. Then, we analyzed the surface deformation results obtained with the present methodology against the freely available geospatial data, which represents the possible causative factors (such as rainfall, water body change, total terrestrial water storage, land use-landcover, temperature, etc.), to understand their relations and their impact. By linking the surface deformation to its causative factors through machine learning techniques such as Random Forest, our research aims to provide a better understanding of the system dynamics and an appropriate model for prediction. This model can be utilized by decision-makers to consider and manage risks associated with severe surface deformation for possible future scenarios. The results should enable the design of future mitigation actions to protect Egyptian society and make it more resilient to the consequences of land deformation over the Nile Delta.

How to cite: Zaki, A., Manzella, I., Lazecky, M., Hooper, A., Chang, L., Meijde, M. V. D., and Fadel, I.: Surface deformation along the Nile Delta, Egypt: From monitoring towards prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8929, https://doi.org/10.5194/egusphere-egu24-8929, 2024.

EGU24-9076 | ECS | Posters virtual | NH6.3

Characterization of compound earthquake damage empowered by AI remote sensing 

Feng Lin, Yuqi Song, and Xie Hu

Rapid post-earthquake response remains a significant challenge for humanity. Emergency response to earthquakes requires accurate and timely information about the geographic locations of secondary hazards and the likely compound effects, such as landslides, liquefaction, and building damage. Current methods rely on data-driven approaches, and also start to consider the complex causal dependencies associated with earthquake-induced disasters. However, the accuracy of existing pipeline is limited due to factors like atmospheric noise contaminating satellite imagery.

To improve the accuracy of predicting multiple hazards and impacts, we introduce the principles of time-series Interferometric Synthetic Aperture Radar (InSAR) analysis to generate high-quality Damage Proxy Maps (DPM). Subsequently, we adopt a rapid seismic multi-hazard and impact estimation system leveraging advanced statistical causal inference and remote sensing techniques. This approach, by modeling causal dependencies from satellite images, infers multiple hazard scenarios on a regional scale at high accuracy and resolution.

Data we using include landslides, liquefaction, and building damage. We also created DPMs using SAR images from the Sentinel-1 satellite. Beides the accuracy, our approach’s results also reveal quantitative causal mechanisms among earthquake-triggered multi-hazard and impact events. Our system provides a new approach to InSAR data processing and offers a novel avenue for understanding the complex interactions of multiple hazards and impacts in seismic geological processes.

How to cite: Lin, F., Song, Y., and Hu, X.: Characterization of compound earthquake damage empowered by AI remote sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9076, https://doi.org/10.5194/egusphere-egu24-9076, 2024.

EGU24-9466 | ECS | Posters virtual | NH6.3

Ground Deformation Monitoring in Yan'an New District Using Time Series InSAR Method 

Jinghui Xiao and Xie Hu

Urban sprawl results in an increasing area of land being transferred into impervious layers. The city of Yan'an in Shaanxi Province in China, located in the hilly gully area of the Loess Plateau, has implemented the Mountain Excavation and City Construction project, aiming to transform the loess and gully area into an urbanized environment with an area of 78.5 km2. The increased flat land will be used to accommodate 400,000 people. The Mountain Excavation and City Construction project on the Loess Plateau is by far the largest geotechnical project in the loess area in the world. It is also an engineering trail to seek the balance between urbanization and sustainable development.

It is challenging to carry out such a large-scale construction in loess gullies where the hydrogeological and engineering conditions are complicated. The loess are naturally prone to deform. Our study applies time-series Interferometric Synthetic Aperture Radar (InSAR) analysis to measure the ground deformation in Yan'an New District. The reported deformation rates reach as large as 70 mm/yr, primarily in the filling areas. The main contributing factor to the deformation is sediment compaction. A stabilization of the new landform is anticipated in several years. Continuous monitoring plays an integral role in mitigating hazards in such loess environment.

How to cite: Xiao, J. and Hu, X.: Ground Deformation Monitoring in Yan'an New District Using Time Series InSAR Method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9466, https://doi.org/10.5194/egusphere-egu24-9466, 2024.

EGU24-9502 | Orals | NH6.3

An effective method to detect and measure earthflow displacements using a hybrid interferometric approach 

Matteo Mantovani, Angelo Ballaera, Giulia Bossi, Federica Ceccotto, Gianluca Marcato, and Alessandro Pasuto

This study presents a new application of the Sentinel-1 dataset for the detection and measurement of earthflow displacements. The proposed methodology utilizes a multi-baseline interferometric hybrid approach, leveraging the backscattered radiation from both point-like and distributed radar targets. The analysis takes into consideration eight datasets acquired between 2017 and 2020, both on ascending and descending orbits, but it is restricted to seven months of the yearly acquisitions, spanning from late March to the beginning of November, to mitigate temporal decorrelation and minimize the impact of snow cover. The investigated area is part of the Dolomites Unesco World heritage site (Eastern Italian Alps). The results so far obtained are then compared with those derived from the European Ground Motion Service (EGMS) and in-situ Global Navigation Satellite System (GNSS) monitoring networks. Preliminary findings reveal the promising reliability of this approach, demonstrating its efficacy and accuracy. Furthermore, this methodology offers a notable advantage in terms of spatial sampling, resulting in the enhancement of the capability to identify and characterize earthflows movement. Overall, this study underscores the potential of utilizing Sentinel-1 data for monitoring landslides distinguished by significantly high rates of displacement, by loosening some of the well-known constraints of the interferometric analyses. The findings highlight the importance of space-borne SAR missions in providing valuable insights in landslide risk mitigation and management.

How to cite: Mantovani, M., Ballaera, A., Bossi, G., Ceccotto, F., Marcato, G., and Pasuto, A.: An effective method to detect and measure earthflow displacements using a hybrid interferometric approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9502, https://doi.org/10.5194/egusphere-egu24-9502, 2024.

EGU24-10697 | ECS | Posters on site | NH6.3

Recent satellite-based radar and optical monitoring of the activity of a slow-moving landslide in Nepal during monsoon  

Florian Leder, Simon Daout, Jérôme Lavé, Nicolas d'Oreye de Lantremange, and Pascal Lacroix

The steep Himalayan slopes are highly exposed to landslides, primarily triggered by earthquakes and monsoon intense precipitation. Along the Himalayan southern slopes, a specific landslide type involves old slided hillslope, characterized by intense internal fracturing, and prone to rapid retrogressive erosion through deep gullies incision, ultimately leading to catastrophic collapse of secondary landslides. Anticipating such events requires understanding if subsiding slices at the edge of the deeply incised talweg exhibit signs of acceleration preceding their rapid collapse and establishing a potential relationship between triggering factors (such as rain) and displacement amplitude. While optical images are commonly used for rapid landslides (with displacements superior to 20 cm/yr), their effectiveness is hindered by cloud cover during monsoon period, limiting sampling frequency and impeding the identification of transient deformation signals.

In this study, we integrated satellite-based optical and radar remote sensing data with high spatial and temporal resolution to characterize the dynamics of a slow-moving landslide located in the Marsyandi valley (84.418° E ; 28.411° N ; 1900m a.s.l.) in Nepal, and to understand how it responds to monsoon rainfall. We developed a processing chain to apply sub-pixel image correlation to a data set comprising spotlight TerraSAR-X and PAZ radar images (1m spatial resolution), as well as medium resolution Sentinel-2 (10m), and high-resolution Pleiades (1m) amplitude optical images. We derived time series of ground displacements in range, azimuth, east-west, and north-south directions. Vertical displacements were additionally produced by comparing high-resolution Digital Surface Models (DSM) obtained from tri-stereo Pleiades images. 

The displacement time series revealed metric transient ground displacements in the upper part of the landslide at the end of the monsoon, along with linear displacements in downstream gullies. Field observations validated our satellite measurements, indicating that during the monsoon, the south-eastern part of the landslide remained relatively stable and revegetated, while the north-western part experienced downward sliding. By comparing these displacements with precipitation data, we characterized the response of the slow-moving landslide to seasonal forcing and gained insights into the mechanisms of collapsed hillslopes.

How to cite: Leder, F., Daout, S., Lavé, J., d'Oreye de Lantremange, N., and Lacroix, P.: Recent satellite-based radar and optical monitoring of the activity of a slow-moving landslide in Nepal during monsoon , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10697, https://doi.org/10.5194/egusphere-egu24-10697, 2024.

EGU24-11483 | Posters on site | NH6.3

Examination of Ground Deformation Information in Alpine Terrain - The Potential of EGMS 

Robert Siegmund, Paul Kotzerke, Jürgen Langenwalter, and Arnd Berns

Alpine terrain – in high and low altitudes - faces changes in stability due to climate change (permafrost and mass movements or landslides), effecting natural conditions and therefore human infrastructure. Those changes are mainly driven by changing atmospheric patterns leading to shifts in the temperature and precipitation regime. In high alpine terrain dwindling permafrost potentially results in an increasing instability. Recently several incidents of rockfalls and massive landslides were reported, e.g. the village of Brienz only narrowly escaped a fatal disaster. Especially low-lying areas or valleys are of special socioeconomic interest forming settlement areas with transport, tourism and human infrastructure. For example, an increasing number of land- and mudslide events along the “Brenner Highway” were reported by the Austrian motorway authority (ASFINAG). The highway and railway line act as a main and highly frequented transport route connecting Innsbruck (Austria) with Bolzano (Italy). Under a changing climate regime more of these incidents are expected in the near future. With the increased dynamics and probability of landslides the risk for human infrastructure and inhabitants of alpine regions could increase.

Consequently, the use of continuous and accurate ground deformation information becomes evident. EGMS, as a Pan-European service, provides validated and accurate data since 2021, therefore key information for ground deformation monitoring on a wide area basis. However, the utilisation of EGMS products in alpine terrain is not yet fully addressed due to technical plus natural constraints regarding alpine topography, climate, etc. versus the applied interferometric measurement approach.

Our analysis provides an assessment of ground deformation data on a wide area plus detail level in its temporal and spatial context and its applicability to changing permafrost and ground stability conditions. Based on EGMS products the distribution of deformation features is evaluated in correspondence to alpine permafrost index maps. An indication of potential hot spots is modelled by respective active areas and their relation to infrastructure elements and settlements. This includes the integration of auxiliary and reference data.

With this approach considerations of the distribution and temporal characteristics of deformation areas, in terms of mean velocities and deformation time series, are deduced together with spatial relations of measurement points to the objects of interest, e.g. settlements, road, railway or touristic infrastructure.

Finally, conclusions for a wide area utilisation of EGMS deformation information are drawn including the provision of an assessment of required reference and auxiliary information plus conceptualisation of an adapted and optimised monitoring approach addressing alpine geohazards.

How to cite: Siegmund, R., Kotzerke, P., Langenwalter, J., and Berns, A.: Examination of Ground Deformation Information in Alpine Terrain - The Potential of EGMS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11483, https://doi.org/10.5194/egusphere-egu24-11483, 2024.

EGU24-11830 | ECS | Orals | NH6.3

Kalman filter for sequential temporal coherence estimation for multi-temporal InSAR 

Mahmud Haghshenas Haghighi and Andreas Piter

Since the launch of the Sentinel-1 mission and with the upcoming NISAR mission, SAR data is continuously and freely available, which can be used for geodetic monitoring and assessing hazards related to infrastructure. Continous deformation monitoring requires a regular update of the displacement time series based on newly acquired images to assess the current structural health status of the observed infrastructure. Existing InSAR time series methods, in particular PSI methods, however, are designed for a fixed SAR stack size of a particular study period and unwrap the phase time series for pixels which exhibit a coherent signal over the whole study period. Therefore, before phase unwrapping, it is essential to assess if the pixels preserve phase coherence in the interferograms related to the new image.

Previous studies proposed an amplitude change detection which divides the study period into two subsets and tests whether the amplitude distributions of the subsets stem from different Rayleigh distributions and, hence, from different scatterers. All possible splits of the stack into two subsets are tested and the split with the highest test score is selected as the change point. This approach has the drawback that the changes can hardly be identified if one of the subsets contains only very few images, which would be the case for a sequential update for continuous monitoring purposes. Moreover, other studies demonstrated that the time of change in the amplitude might not coincide with the time of change in the coherence of the phase. Therefore, they suggested an unwrapping-based change point refinement to the amplitude-based method to identify the change point in the temporal coherence of the phase.

Here, we propose a new method for assessing the decorrelation in a sequential updating framework using a Kalman filter.
Our approach estimates the temporal coherence for the newly acquired image. We extend the Temporal Phase Coherence (TPC) approach from Zhao and Mallorqui (2019) which approximates the phase noise of a scatterer by subtracting the spatial low-pass filtered phase of the immediate neighbourhood of the scatterer in each interferogram. To assess the coherence of the new image, we connect the new image to all previous images within a fixed time of e.g. one year. We use the Kalman filter to predict and update the TPC for each new image and apply a threshold on the TPC to distinguish coherent from incoherent pixels. This approach comes with the advantage that neither amplitude analysis nor unwrapping of the phases is required to assess the coherence of a scatterer in the new image.

We perform a case study in Nordrhein-Westfalen, Germany, along the Sauerland-Autobahn to demonstrate the effectiveness of the proposed Kalman filter for sequential coherence estimation. Along the Sauerland-Autobahn, several highway bridges need to be rebuilt due to structural health problems arising from their ageing process. We coregister a stack of Sentinel-1 images using the InSAR Scientific Computing Environment (ISCE).
The dataset covers eight years of data from ascending and descending orbits. We compare our proposed phase-based coherence estimation with the results from amplitude-based change detection.

How to cite: Haghshenas Haghighi, M. and Piter, A.: Kalman filter for sequential temporal coherence estimation for multi-temporal InSAR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11830, https://doi.org/10.5194/egusphere-egu24-11830, 2024.

EGU24-11881 | ECS | Orals | NH6.3 | Highlight

Timing landslides and identifying reactivations during sequences of earthquakes and storms with Sentinel-1 amplitude and coherence 

Katy Burrows, Aadityan Sridharan, and Maria Francesca Ferrario

When shallow landslides are triggered by sequences of earthquakes or storms, we need to know when in the sequence they occurred and whether they were later reactivated in order to better understand and model the hazard. In tropical environments, cloud cover often obscures all or part of the optical imagery acquired during the sequence, so that it is necessary to use images acquired after the sequence of events to map the landslides. Because of this, we often cannot tell which earthquake or storm triggered a particular landslide. This limits our understanding of how landslide hazard and mass wasting evolve in space and time during such sequences.

Synthetic Aperture Radar (SAR) images can be acquired through cloud cover and since 2015, Sentinel-1 has acquired data globally every 6-12 days. Landslides alter the scattering properties of the Earth’s surface and so can be detected in SAR images. SAR amplitude time series can be used to constrain the timings of individual landslides. We apply these methods to three sequences of triggers in order to better understand how landsliding evolved during them: the 2018 Lombok, Indonesia earthquake sequence; the 2019 Cotabato – Davao del Sur earthquake and the earthquake-hurricane sequence that occurred in Haiti in 2021.

The 2018 Lombok earthquake sequence also offers an ideal opportunity to test new methods of using InSAR coherence (the level of noise in an interferogram) to detect multi-stage failure. High resolution cloud-free images were acquired halfway through this sequence of four Mw > 6.0 earthquakes and many landslides mapped after the first two earthquakes were then observed to have grown in size or changed shape by the end of the sequence. We demonstrate that for large, favourably oriented landslides, InSAR coherence can be sensitive to this reactivation and so could potentially be used in the future for cases where no cloud-free images are available.

How to cite: Burrows, K., Sridharan, A., and Ferrario, M. F.: Timing landslides and identifying reactivations during sequences of earthquakes and storms with Sentinel-1 amplitude and coherence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11881, https://doi.org/10.5194/egusphere-egu24-11881, 2024.

EGU24-12149 | Orals | NH6.3 | Highlight

New Open-Source Python libraries for Radar Interferometry Data Processing and Analysis 

Ou Ku, Fakhereh Alidoost, Pranav Chandramouli, Thijs van Lankveld, Francesco Nattino, Meiert Grootes, Freek van Leijen, and Ramon Hanssen

Modern satellite missions continuously generate extensive observation datasets for Interferometry Synthetic Aperture Radar (InSAR), which is a crucial technology for monitoring ground surface deformation. The efficient processing and analysis of these extensive InSAR datasets poses two computational challenges: 1) the growing volume of the datasets that needs to be incorporated into the data processing workflow, and 2) the integration of contextual information associated with the InSAR data to reveal the mechanisms driving deformation.   

To address these challenges, we present two open-source Python libraries: SARXarray [1] and STMTools [2]. They facilitate common InSAR data processing tasks and are developed as extensions of the open-source Python library, Xarray, which handles labelled multi-dimensional arrays and is well-suited to the space-time nature of InSAR data. SARXarray is designed to work with coregistered raster stacks, such as SLC or interferogram stacks, offering functionalities like multi-looking, coherence computation, and coherence scatterers selection. STMTools, on the other hand, focuses on large spatio-temporal datasets in the form of a Space-Time Matrix (STM) [3], for instance, coherent scatterers. It can query background contextual data, such as geospatial polygons, and add the attributes-of-interest to the corresponding STM. Furthermore, both SARXarray and STMTools support data chunking and lazy evaluation, enabling the scaling up of the data processing pipeline and parallel processing of larger-than-memory data across various computational infrastructures. 

[1] Ku, O., et al., sarxarray [Computer software]. github.com/MotionbyLearning/sarxarray 

[2] Ku, O., et al., stmtools [Computer software]. github.com/MotionbyLearning/stmtools 

[3] Bruna, M. F. D., van Leijen, F. J., & Hanssen, R. F. (2021). A Generic Storage Method for Coherent Scatterers and Their Contextual Attributes. 

How to cite: Ku, O., Alidoost, F., Chandramouli, P., van Lankveld, T., Nattino, F., Grootes, M., van Leijen, F., and Hanssen, R.: New Open-Source Python libraries for Radar Interferometry Data Processing and Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12149, https://doi.org/10.5194/egusphere-egu24-12149, 2024.

EGU24-12522 | ECS | Posters on site | NH6.3

Impact of Tropospheric Delay Correction on the Quality of Landslide Mapping in the Southern Central Andes, Northwestern Argentina 

Mohammad M.Aref, Bodo Bookhagen, and Manfred R. Strecker

Slow-moving landslides in high-mountain regions pose a significant natural hazard and are capable of delivering large sediment volumes to the fluvial system. Time series analysis of Interferometric Synthetic Aperture Radar (InSAR) allows us to identify unstable and potentially dangerous areas prone to landsliding, but this technique also helps quantify seasonal dynamics for predicting landslide behavior.

Our study in the Eastern Cordillera of the Argentine Andes focuses on enhancing InSAR's reliability for landslide mapping. This region is characterized by moisture changes along the topographic gradient across the orogen and seasonal variability associated with the South American Summer Monsoon. We extract InSAR time series data from Sentinel-1A/B's C-band (2014-2022) and ALOS1 PALSAR's L-band (2006-2011). Tropospheric delay is caused by atmospheric turbulence and vertical stratification changes. These delays can introduce significant errors in deformation measurements, thus impacting the quality of maps portraying landslide deformation rates. To address this problem, we apply various correction techniques, ranging from spatial and temporal filtering to water-vapor estimation from an atmospheric model. Fading signal noise, another challenge caused by multi-looking and short temporal baselines in the Small Baseline Subset (SBAS) technique, additionally compromises InSAR time series accuracy. We investigate the pattern and magnitude of fading signals in landslide areas using Small Baseline Subset (SBAS) with different neighboring connections and non-linear phase inversion methods, such as the Eigenvalue Decomposition-based Maximum Likelihood (EMI), Eigenvalue Decomposition (EVD), and the Phase Triangulation Algorithm (PTA).

Our research evaluates both statistical methods and Global Atmospheric Models for correcting tropospheric delays and fading signal noise. We explore statistical methods, such as double-difference filtering and corrections based on phase elevation, for different spatial windows, including individual catchments, moving windows, and adaptive window sizes. The efficiency of these methods varies with the environmental and topographic conditions in the orogen. Both stratified and turbulent components of the troposphere, along with fading signal noise, can significantly influence tropospheric delay and time series quality. In the context of the factors that influence deformation signals and the combined array of methods to obtain robust measurements, we can identify the spatial and temporal characteristics of slow-moving landslides and assess the different impacts on rate changes.

How to cite: M.Aref, M., Bookhagen, B., and R. Strecker, M.: Impact of Tropospheric Delay Correction on the Quality of Landslide Mapping in the Southern Central Andes, Northwestern Argentina, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12522, https://doi.org/10.5194/egusphere-egu24-12522, 2024.

Landslides cause significant socioeconomic impacts on people and national infrastructures like railways and roads and are considered one of the common geohazards that demand more attention. In Sweden, many areas are prone to landslides due to the presence of underlying quick-clay sediments, which may lead to minor to large slides. Ground deformation monitoring in such hazardous areas is important for a better understanding of the landslide processes and mitigation of hazards. Over the last decade, Interferometric Synthetic Aperture Radar (InSAR) time-series techniques, such as Persistent Scatterer Interferometry (PSI) and the Small Baseline Subset (SBAS), have become a crucial tool for ground surface deformation analysis. SBAS and PSI use SAR data to retrieve the time-series cumulative phase of the Persistent Scatters (PS). The main objective of this study was to demonstrate the advantage of using advanced InSAR time series analysis for a better understanding of surface deformation before a landslide event. We focused on the recent landslide on the E6 Sweden-Norway highway near Stenungsund in Southern Sweden, which occurred on 23 September 2023. Sentinel-1 SAR data was collected between 2018 and September 2023, with ascending flight direction to measure the pre-event deformation in the landslide zone. We used Alaska Facility (ASF) on-demand product processes based on Hybrid Pluggable Processing Pipeline (Hyp3) to search, process, and download time series Sentinel-1 data. We also used Miami INsar Time-series software in PYthon (Mintpy) to perform cloud-based SBAS processing using unwrapped interferograms stack derived from Sentinel-1 time series data. In addition, we employed Basic PSI products (ground motion in the Line-of-Sight (LOS) direction) provided by the European Ground Motion Service (EGMS). The initial SBAS results and EGMS Basic products for the same ascending orbit showed continuous deformation on the highway segment in the landslide zone over the last EGMS update period, 2018 to 2022 for the PSI results and 2018 to 2023  for the SBAS results. The first five-year period of the EGMS Basic and Ortho products, i.e., 2015-2021, was also checked and showed the same results over the longer period between 2015 and 2021. Both sets of PSI and SBAS results agree on the annual cm-level (10-15 mm/year) subsidence rate of the highway before the landslide, with SBAS analysis yielding more measurement points, especially in the vegetated and unbuilt areas. The initial results showed that the SBAS technique could provide more information within the hazardous zone; nevertheless, due to Sentinel-1 C-band data, the quality of the results can be degraded by coherence variations in the vegetated areas.  The comparison of preliminary results of InSAR data processing and available EGMS products provides insights into ground movements, facilitating a comprehensive understanding of evolving conditions before the landslide. Nevertheless, the results emphasize the importance of incorporating advanced time series InSAR techniques for continuously monitoring infrastructures such as railroads and highways to support sustainable development and natural hazard assessments.

How to cite: Dabiri, Z. and Nilfouroushan, F.: Enhancing Landslide Preparedness: Leveraging EGMS Products and SBAS-InSAR for Pre-Event Ground Deformation Monitoring along the E6 Highway near Stenungsund in Southern Sweden, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12802, https://doi.org/10.5194/egusphere-egu24-12802, 2024.

EGU24-13336 | Orals | NH6.3 | Highlight

Point Coherence Estimation (PCE) in SAR interferometry 

Mario Costantini, Federico Minati, Francesco Vecchioli, and Massimo Zavagli

Synthetic aperture radar (SAR) interferometry (InSAR) is a well-established technology for precise monitoring of ground motions (due to subsidence, landslides, volcanic and seismic phenomena) with millimeter accuracy from time series of satellite SAR images. A crucial aspect of this technology involves identifying points exhibiting interferometric phase coherence across acquisitions in an image stack, typically corresponding to man-made structures, rocks, or bare soil, irrespective of the scattering mechanism (point-like or distributed). Coherent point identification faces challenges, particularly due to atmospheric and other systematic disturbances affecting the phase. Various techniques have been presented in the scientific literature, relying on statistics of stack image amplitudes (such as amplitude dispersion and signal-to-clutter ratio) and/or phases in spatial and temporal domains.

This work presents a new algorithm we have recently developed, named Point Coherence Estimation (PCE), for identification of coherent points. The temporal coherence (related to phase noise) of each point is derived from the coherences between pairs of points, directly calculable, through an effective and clean procedure, without the need for spatial averages, amplitude/phase calibrations, or critical assumptions.

The algorithm begins by examining phase differences between neighboring points, within tens or hundreds of meters. As known, temporal coherences of these point pairs can be estimated exploiting the cancellation of spatially correlated components in phase differences (such as atmospheric and orbital artifacts, large scale motions) and determining temporally correlated components related to ground motion and elevation. The temporal coherence of each point pair primarily depends on the phase noises (temporal, spectral, geometric decorrelations, thermal noises) of the two points.

Assuming statistically independent phase noises in neighboring points (possibly excluding the nearest neighboring pixels if the images are oversampled), the expected value of temporal coherence for each pair is shown to be the product of the temporal coherence expected values for the two paired points. By taking the logarithm of these equations, an overdetermined system of linear equations is derived, which can be solved by minimizing the equation residuals according to the L1 or L2 norm, using existing efficient solvers such as linear or quadratic (LP or QP) programming solvers. The solution provides a reliable estimate of the temporal coherence for each point.

Importantly, the PCE method operates without assuming any probability distribution of phase noise. Moreover, the PCE algorithm can be applied to full-resolution data as well as to data with degraded resolution for a previous multi-look or distributed scattering processing. In addition, the algorithm provides consistent results if applied to preselected candidate coherent points to reduce computational time (however absolutely affordable even without point preselection).

Extensive testing, including stacks of Sentinel-1 interferometric SAR images over different scenarios, showcased the method effectiveness. PCE provided reliable measurements of temporal coherence and phase noise variance for each point, enabling detection of coherent points with minimal missing or false detections. The tested areas, affected by diverse displacement phenomena, showcased the algorithm applicability across different land cover types and geological features.

The PCE method will be made available to the geoscience community as software as a service (SaaS).

How to cite: Costantini, M., Minati, F., Vecchioli, F., and Zavagli, M.: Point Coherence Estimation (PCE) in SAR interferometry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13336, https://doi.org/10.5194/egusphere-egu24-13336, 2024.

EGU24-13793 * | Orals | NH6.3 | Highlight

Overview and Outcome of the NASA Marine Oil Spill Thickness (MOST) Project 

Cathleen Jones, Francis Monaldo, Benjamin DeChamps, Lisa Di Pinto, Oscar Garcia-Pineda, George Graettinger, Sean Helfrich, Benjamin Holt, Malin Johansson, Cornelius Quigley, Ellen Ramirez, Gordon Staples, and Dana Tulis

In 2018, NASA funded a project to develop and mature automated oil spill detection and thickness estimates from synthetic aperture radar (SAR) and optical imagery, based on focused field testing combined with in situ oil sampling and airborne imaging with the UAVSAR L-band SAR.  The goal was to implement these new algorithms and databases in a semi-automatic system that NOAA uses operationally to detect and assess oil spills and post-storm offshore damage and debris.  The study's field validation site was the Coal Oil Point seep field, an area of natural seep activity located in the Santa Barbara channel, California, which leaks approximately 100 barrels of crude oil per day.  There were three campaigns to collect calibration/validation data, in May 2021, October 2021, and June 2022, during which UAVSAR overflew boat crews collecting optical images from a drone and some water samples for thickness and viscosity analysis.  The data was combined with available satellite SAR and optical imagery collected around the same time and used to develop an algorithm for classifying oil by relative thickness based upon contrast with clean ocean.  One algorithm is tailored for Sentinel-1 data and uses Machine Learning (ML) methods, and the other is an analytical analysis that can be applied to any radar frequency's data.  The data acquired in June 2022 has been used additionally to evaluate differentiation of mineral oil slicks from low wind radar-dark areas using a series of rapid repeat SAR images. In this talk, the study, data collections, and developed algorithms and methods will be presented.

How to cite: Jones, C., Monaldo, F., DeChamps, B., Di Pinto, L., Garcia-Pineda, O., Graettinger, G., Helfrich, S., Holt, B., Johansson, M., Quigley, C., Ramirez, E., Staples, G., and Tulis, D.: Overview and Outcome of the NASA Marine Oil Spill Thickness (MOST) Project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13793, https://doi.org/10.5194/egusphere-egu24-13793, 2024.

EGU24-16066 | Posters on site | NH6.3

SBAS-InSAR Analysis and Assessment of Landslide deformation in the Loess Plateau, China 

Yan Yang, Mahdi Motagh, Mahmud Haghshenas Haghighi, and Andreas Piter

Landslide is a geological disaster with extremely destructive effects, resulting in huge casualties and economic losses in China. The Loess Plateau is widely covered by several to tens of meters of loess, and the underlying bedrock with good water barrier properties. Due to the frequent rains, the soil body is easy to flow or slide along weak structural surfaces. There are lots of typical loess landslides in the Loess Plateau and they seriously affect the lives of residents, so studying landslide deformation in Loess Plateau is of great significance for both society and geological expert. Interferometric Synthetic aperture radar (InSAR), with the advantages of wide monitoring range, high density, high accuracy, and not affected by weather conditions, has become the most effective technical means for regional surface deformation monitoring and landslide identification. In this paper we perform landslide deformation survey based on the small baseline Subset InSAR (SBAS-InSAR) method in Tianshui, which is located on the Loess Plateau, using 594 interferograms from the Sentinel-1 satellite ranging from January, 2017 to December, 2022. SBAS-InSAR time series analysis connects independent SAR images based on certain spatial baseline and time baseline thresholds, and finally gets time series and velocity of the Loess Plateau. The locations of landslides from National Geological Disaster Survey Database provided by China Geological Survey are compared with our results to verify the applicability of SBAS-InSAR technology in the Loess Plateau. The comparison results show that SBAS-InSAR technique using sentinel-1 dataset can effectively identify landslides in most areas except for the areas covered by forest. The results of velocity map and landslide maps can be used for landslide identify and assessment in the Loess Plateau.

How to cite: Yang, Y., Motagh, M., Haghshenas Haghighi, M., and Piter, A.: SBAS-InSAR Analysis and Assessment of Landslide deformation in the Loess Plateau, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16066, https://doi.org/10.5194/egusphere-egu24-16066, 2024.

Differential Synthetic Aperture Radar Interferometry (DInSAR) products are often contaminated by atmospheric contributions, frequently referred to as atmospheric artifacts or atmospheric phase screen (APS) signals [1]. Specifically, the velocity and, consequently, the path length of the radar signal propagating through the inhomogeneous atmosphere layers can vary among repeat-pass SAR acquisitions. Therefore, these variations can be erroneously interpreted as due to deformation signals. Accordingly, filtering out the APS component from DInSAR products, for correctly retrieving deformation measurements, represents a challenging issue.

In this work we present a statistical analysis to investigate the performance of the Sentinel-1 (S1) Extended Timing Annotation Dataset (ETAD) data for mitigating the APS component in both DInSAR interferograms and deformation time-series. The ETAD product consists of different correction layers that provide the azimuth and range timing shifts for each S1 burst to achieve a precise geolocation with centimetre accuracy [2]. It is worth noting that, although the ETAD dataset is not primarily designed for the interferometric phase filtering, some of its correction layers, specifically, the tropospheric, the ionospheric, and the solid Earth tidal displacement ones, may be effectively used to filter the APS signal component affecting the DInSAR measurements [2].

For the presented experimental analisys we used 104 S1 images acquired along ascending orbits over Central/Southern Italy, during the 2018-2020 time-span. The exploited DInSAR products have been generated at medium spatial resolution (about 40 m) and are represented by 278 interferograms and by the corresponding displacement time series retrieved through the P-SBAS processing chain [3].

To quantitively evaluate the ETAD APS correction performance, we analyzed first their impact on DInSAR interferograms. In particular, we considered the following statistical metrics for the entire dataset of unwrapped interferograms, before and after the application of the ETAD APS correction: i) standard deviation of the interferograms at different spatial scales and ii) empirical variograms of the unwrapped phase fitted with a parametric exponential model. Subsequently, to investigate the impact of the ETAD APS correction on the deformation time-series, we analyzed the behavior of their variance before and after the application of the ETAD correction.

The measured metrics results, although still preliminary, demonstrate the effectiveness of the ETAD APS corrections for both the DInSAR interferograms and the deformation time-series in more than 90% of the cases.

[1]  I. Zinno et al., "On The Exploitation of ETAD Data for the Atmospheric Phase Screen Filtering of Medium/High Resolution DInSAR Products," IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 7882-7885.

[2]  C. Gisinger et al., "The Extended Timing Annotation Dataset for Sentinel-1Product Description and First Evaluation Results,"  IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-22, 2022, Art no. 5232622

[3]  M. Manunta et al., "The parallel SBAS approach for Sentinel-1 interferometric wide swath deformation time-series generation: Algorithm description and products quality assessment," IEEE Transactions  on Geoscience and Remote Sensing, vol. 57, no. 9, pp. 6259-6281, 2019

How to cite: Casamento, F., Lanari, R., and Zinno, I.: On the exploitation of ETAD data to filter out atmospheric artifacts from Sentinel-1 medium-resolution DInSAR products: a performance evaluation analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16359, https://doi.org/10.5194/egusphere-egu24-16359, 2024.

In alpine regions, Deep-seated Gravitational Slope Deformations (DsGSDs) pose significant risks due to their continuous deformation rates, potentially leading to sudden and accelerated transformations that can cause unpredictable damage to local communities and infrastructure. Monitoring DsGSDs is crucial for effective risk assessment and land-use planning. Advances in remote sensing technologies, particularly InSAR (Interferometric Synthetic Aperture Radar), offer substantial advantages in monitoring and studying these widespread and slow processes. The European Ground Motion Service (EGMS), which provides Europe-wide ground motion data, emerges as a viable tool for detecting, monitoring, and characterizing DsGSDs. This study aimed to develop and evaluate an automated workflow for identifying and analyzing trends in DsGSDs in alpine areas using deformation time series datasets. The approach involves utilizing advanced statistical methods to characterize DsGSD phenomena in alpine regions. Focusing on the Carnic Alps area in the northern part of the Veneto Region and Friuli-Venezia Giulia Region (NE, Italy), our objective is to explore supervised machine learning (ML) and deep learning (DL) algorithms to automatically identify DsGSD areas and analyze the spatiotemporal behavior of long time series of ground deformations. The findings will be compared with data from the Italian Landslide Inventory (IFFI), serving to not only validate the newly extracted information but also assess the potential of integrating multi-source datasets. This work sets the foundation for further analyses on how transient climatic factors could influence DsGSDs regimes.

How to cite: Dong, Y., Floris, M., and Catani, F.: Deep-seated Gravitational Slope Deformations identification and trend analysis from ground deformation time series: A case study in the Italian Alps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16520, https://doi.org/10.5194/egusphere-egu24-16520, 2024.

Geohazards related to ground motion are widespread in mountainous regions. Time series of spaceborne SAR data are commonly used to retrieve maps of ground motion with extensive spatial coverage. However, there are situations where terrestrial radar systems are more suitable or even necessary for measuring ground motion. Such situations include slopes facing north or south, where the line of sight of current space-based SAR systems is nearly perpendicular to the prevalent direction of ground motion; slopes that lie in radar shadow or layover for current spaceborne SAR geometries; fast-moving landslides requiring shorter interferometric measurement intervals; and cases demanding higher spatial resolution or higher frequencies (e.g., Ku-band) with better sensitivity to line-of-sight motion.

Terrestrial stationary radar/SAR systems, typically operating at Ku- or X-band, have been employed for many years to address these challenges. However, their limited synthetic aperture (or antenna size in the case of real-aperture radars) result in a constant angular resolution in the azimuth direction, leading to a  reduced spatial azimuth resolution with increasing distance.

Monitoring a landslide from a moving car or a UAV with a longer synthetic aperture allows using lower frequencies such as L-band, offering good spatial resolution at the meter level. Aperture synthesis from a car or UAV at higher frequencies (e.g., Ku-band) with smaller radar antennas can significantly improve the azimuth resolution to sub-meter or even decimeter level compared to stationary terrestrial radar systems which typically have azimuth resolutions in the order of 10m and more at range distances of several kilometers.

In our previous work, we had demonstrated mobile mapping of ground motion using a compact repeat-pass L-band interferometric SAR system on a car and a UAV. Recently, a Ku-band SAR system (a modified version of the Gamma Portable Radar Interferometer (GPRI)) was added to the car-borne InSAR measurement setup. The new configuration allows simultaneous data acquisitions at both frequencies during repeat-pass SAR measurements while driving along a road.

Frequency diversity proves to be advantageous in mountainous areas with varying land cover and motion processes with different velocities and scales. In this contribution, we present recent results from car-borne mobile mapping campaigns in the Swiss Alps showcasing the dual-frequency car-borne SAR setup (Gamma L-band SAR and modified GPRI at Ku-band). In particular, we present ground motion measurements of the Brinzauls landslide in Switzerland taken in fall 2023 at both frequencies, Ku- and L-band, and at different time intervals. The case study strikingly shows the complementary properties of the two frequencies in terms of sensitivity to motion and temporal decorrelation. The unprecedented high-resolution SAR imagery and interferograms obtained with the car-borne Ku-band SAR (decimeter-level azimuth resolution) allows discriminating different bodies of the landslide moving at different velocities in detail.

How to cite: Frey, O., Werner, C., and Caduff, R.: Dual-frequency high-resolution mobile mapping of ground motion of the Brinzauls landslide in Switzerland with a car-based interferometric SAR system at L- and Ku-band, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17107, https://doi.org/10.5194/egusphere-egu24-17107, 2024.

EGU24-17912 | Orals | NH6.3

Quality assessment of Persistent Scatterer Interferometry time series using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling 

Mohammad Omidalizarandi, Kourosh Shahryarinia, Bahareh Mohammadivojdan, and Ingo Neumann

Large-scale, cost-effective, and reliable deformation monitoring of natural objects or man-made infrastructures is still challenging. Numerous past studies have employed the Persistent Scatterer Interferometry (PSI) technique, utilising open-source synthetic aperture radar (SAR) data from C-band of satellite Sentinel-1, for this purpose. However, a limited number of investigations have been performed to evaluate the quality of the Persistent Scatterer (PS) data points.

In this research, a comprehensive and sophisticated multi-step procedure is developed and implemented to perform quality assessment of the PS data points using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling. Firstly, the PS points are classified into buildings and ground types using LoD2 building models. Multivariate PSI time series analysis is then carried out to understand the temporal behaviours of groups of PS points in local geometric patches. This involves modelling and analysing PSI time series to estimate deterministic and stochastic parameters such as offset, velocity, standard deviation, and corresponding distributional parameters. A spatio-temporal modelling is employed within the local geometric patches of PS points using a mathematical surface approximation model. A 95% confidence interval is estimated for the approximated surfaces using a bootstrapping approach. Subsequently, an appropriate quality model for the PS points is derived from the above-mentioned temporal and spatial modelling.

The quality assessment and subsequent deformation analysis are carried out for areas of interest in the state of Lower Saxony, Germany. The PS data points for this study are extracted from the freely available online platform of the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany. For validation purposes, a time series of leveling and Global Navigation Satellite System (GNSS) measurements in the Hengstlage area, Germany, are considered, which provided by Landesamt für Geoinformation und Landesvermessung Niedersachsen (LGLN). In addition, cross-validation is performed for different local geometric patches. In the end, the results of the deformation analysis are compared with those obtained from the BGR. The outcomes of this study can be used to track earth surface displacements over time. This information could be valuable in understanding natural hazard processes such as landslides, earthquakes, and floods, and in improving the safety and resilience of communities and infrastructure.

How to cite: Omidalizarandi, M., Shahryarinia, K., Mohammadivojdan, B., and Neumann, I.: Quality assessment of Persistent Scatterer Interferometry time series using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17912, https://doi.org/10.5194/egusphere-egu24-17912, 2024.

EGU24-19329 | Posters on site | NH6.3 | Highlight

Environmental Players in the Lifespan of Landslides 

Xie Hu, Yuqi Song, and Yiling Lin

Landslides can move at divergent rates on the terrestrial planets. The occurrence and evolution of landslides are strongly affected by the stochastic nature of environment. Landslide activities are complicated by climate change and the attendant escalating number of extreme precipitation events. Here we use multi-source geodetic and remote sensing data (e.g., SAR and optical scenes, as well as climate reanalysis products) and skillsets (e.g., InSAR, pixel offset tracking, and AI) to disentangle the role of environmental players (e.g., water, wind, temperature, and tectonics) in the lifespan of landslides. The perpetual slow-moving landslide in Colorado Plateau will be exemplified to highlight the importance of pore fluid water from rainwater and snowmelt in regulating landslide speeds. An analog landslide to those on Mars will be exemplified to demonstrate an appropriate orientation and layout of topography may help promote eolian abrasion and landslide reactivation. The growth in the area and number of retrogressive thaw slumps in Qinghai-Tibet Plateau will be exemplified to unveil the tragedy of permafrost degradation due to warming temperature and ice-rich permafrost thaw. The spatial proximity of landslides to tectonic faults in California will be exemplified to show exacerbated landslide hazards by occasional dynamic shaking and prolonged weakening of materials.

How to cite: Hu, X., Song, Y., and Lin, Y.: Environmental Players in the Lifespan of Landslides, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19329, https://doi.org/10.5194/egusphere-egu24-19329, 2024.

EGU24-19890 | ECS | Posters on site | NH6.3

Ground Surface Deformation in the Niger-Delta Basin Caused by Hydrocarbon Exploration: First Results from Satellite InSAR Surveys 

Imeime Uyo, Mahdi Motagh, and Mahmud Haghshenas Haghighi

The Niger Delta basin located at the apex of the Gulf of Guinea on the west African coast has a vast deposit of hydrocarbon from which Nigeria’s oil and gas is derived. Although the export of oil and gas resources from this region has significantly improved the nation’s economy over the years, activities associated with hydrocarbon exploration have a significant impact on the land surface among other environmental detriments. If the benefits of hydrocarbon exploration and production must be realized in tandem with the environment, understanding the magnitude and nature of surface deformation within the production zones is crucial.

In this study, we present first results of InSAR-derived spatial and temporal variations in surface deformations over the oil production fields within the Niger Delta Basin. The mean deformation velocity maps and time-series of displacements for measurement points are used to assess rates of ground deformation.

Sentinel-1 C-band SAR data acquired between 2014 and 2023 are analyzed using both Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) InSAR techniques to assess deformation over oil and gas fields. We utilized the Stanford Method for Persistent Scatterer (StaMPS) technique for PSI processing and the MintPy package for SBAS analysis. Interferometric Synthetic Aperture Radar Scientific Environment (ISCE) developed by NASA's Jet Propulsion Laboratory is used to generate the interferograms. The findings of the study will reveal the rate of subsidence and uplift in the line-of-sight (LOS) direction over the active production oil/gas wells within the Niger Delta basin.

The findings of this study would be an invaluable input in decision-making for the benefit of affected communities and other stakeholders in the oil and gas industry. Monitoring subsidence helps to prevent hazards, ensures operational safety, and supports sustainable resource management in the affected areas.

How to cite: Uyo, I., Motagh, M., and Haghshenas Haghighi, M.: Ground Surface Deformation in the Niger-Delta Basin Caused by Hydrocarbon Exploration: First Results from Satellite InSAR Surveys, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19890, https://doi.org/10.5194/egusphere-egu24-19890, 2024.

Severe subsidence poses a significant threat to coastal river deltas, bringing substantial hazards. The Yellow River Delta, being the youngest of such deltas, is particularly vulnerable due to its unstable sedimentary structure. It has experienced significant subsidence as a result of frequent human activities. The InSAR technology facilitates large-area, long-term deformation monitoring of the Yellow River Delta region. Current research has identified that subsidence in the Yellow River Delta is primarily influenced by groundwater extraction and oil exploitation. However, there is a lack of comprehensive study on the spatiotemporal patterns of subsidence induced by different human activities. To acquire extensive and long-term surface subsidence information in the Yellow River Delta region and analyze its causes, this study utilizes 92 ascending Sentinel-1 satellite images and 79 descending Sentinel-1 satellite images. Applying the SBAS-DInSAR technique, the research investigates ground subsidence in the area from January 2019 to April 2022. The study includes an integration of interferometric fringes and DInSAR deformation monitoring results, along with ascending and descending orbit deformation rates for internal accuracy cross-checking. Additionally, it examines the spatiotemporal evolution characteristics and causes in different human-impacted areas. The results indicate that the deformation rates from ascending and descending orbits show high consistency, with a correlation coefficient exceeding 0.8. Significant subsidence areas in the Yellow River Delta are concentrated in the eastern coastal regions, with the maximum subsidence rate reaching approximately -255 mm/year. The primary human-induced factors contributing to subsidence include the extraction of underground brine, oil, and groundwater. Additionally, natural factors like temperature, precipitation, and evaporation also impact subsidence. Notably, the deformation rate changes induced by precipitation exhibit a delayed response. Human activities, with their varying types and intensities, impart distinct temporal characteristics to subsidence. In areas like wetlands, urban regions, and farmlands, deformation is influenced by changes in groundwater levels, resulting in smaller deformation magnitudes and fluctuating deformation rates affected by variations in rainfall, temperature, and evaporation. Oil extraction deformation exhibits long-term change characteristics, influenced by the volume of oil extracted and water injection; from January 2019 to July 2020, a subsidence trend was observed, followed by a slow rebound after July 2020. Subsidence induced by groundwater extraction is characterized by rapid and stable deformation rates. Temporally, significant linear rate subsidence occurred from January to August 2019, with varying degrees of rebound from June 2019 to March 2020, followed by a return to subsidence. Influenced by heavy rainfall, there is a minor rebound each year from July to August.

How to cite: Yu, B. and Ma, D.:  Spatiotemporal Patterns of Human-Induced Subsidence in the Yellow River Delta Region revealed by Ascending and Descending Orbit Time-Series InSAR , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20003, https://doi.org/10.5194/egusphere-egu24-20003, 2024.

The Vietnamese Mekong Delta (VMD) is facing several environmental challenges, including coastal erosion and land subsidence. Subsidence rates of up to several centimeters per year have been reported, which are an order larger than the regional sea level rise of about 3.3 mm/yr. The associated risks are an increased vulnerability to flooding, salinization of water resources and permanent inundation. Precise monitoring of land subsidence with high spatial and temporal resolution is essential to support the study of the associated causes and hazards as well as appropriate countermeasures.

Here, we present results of land subsidence monitoring between 2017 and 2022 in the VMD based on Sentinel-1 Persistent Scatterer Interferometry (PSI). We used Sentinel-1 scenes from ascending and descending orbits and applied an advanced PSI approach. The advancements of the algorithm include the integration of Temporary Persistent Scatterers to derive the best possible Persistent Scatterer network for long time series. Furthermore, we developed a method to optimally integrate reference pixels in order to suppress spatially correlated noise in the subsidence time series. Due to a lack of well distributed geodetic references, we made use of an infrastructural reference network consisting of large bridges with deep foundation depths, which are nearly unaffected by subsidence.

We present the derived subsidence rates and exemplary subsidence time series across the study area. Additionally, we highlight specific spatial and temporal features in the subsidence, which can be associated with land use characteristics and environmental influences.

How to cite: Dörr, N., Schenk, A., and Hinz, S.: Recent Land Subsidence in the Vietnamese Mekong Delta derived from Advanced Sentinel-1 SAR Interferometry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20069, https://doi.org/10.5194/egusphere-egu24-20069, 2024.

EGU24-20126 | Posters virtual | NH6.3

Monitoring the mining deformations by Time Series InSAR Integrating DT and SDFPT 

Deying Ma and Bing Yu

High-intensity mining leads to severe ground deformation and secondary geological disasters in coal mines. Persistent Scatters Synthetic Aperture Radar Interferometry (PSInSAR) has strong deformation monitoring capability, but cannot detect enough target points in the mining core and surrounding low-coherence areas. This paper attempts to combine Distributed Target (DT) and Slowly-decorrelating Filtered Phase Target (SDFPT) to improve the density and coverage of deformation monitoring points in mining areas. The Fast Statistically Homogenous Pixel Selection (FaSHPS) and the amplitude dispersion index method were used to select DT and SDFPT candidate points, respectively. Then phase optimization and stability analysis were carried out for the two types of points, and the qualified DT and SDFPT were screened out.  Both kinds of points were then fused, and three-dimensional phase unwrapping was performed. The phase time series were recovered. The spatiotemporal filtering was performed, and the deformation time series and the annual average deformation rate of the fused point set were finally obtained. The 60-scenario Sentinel-1 images covering the Buertai Coal Mine acquired from April 2018 to April 2020 were selected for deformation monitoring. The results show that the density and coverage of deformation points are significantly improved after the fusion of DT and SDFPT, and the maximum deformation level that can be monitored is also increased. There are 5 deformation funnels in the experimental area, and the maximum cumulative deformation reaches -309.76 mm. The influence range of deformation and the difference between time series deformation in different years are highly correlated to mining activities in mining areas.

How to cite: Ma, D. and Yu, B.: Monitoring the mining deformations by Time Series InSAR Integrating DT and SDFPT, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20126, https://doi.org/10.5194/egusphere-egu24-20126, 2024.

The Ridgecrest earthquake sequence occurred in July 2019 in the Eastern California Mojave Desert. The sequence included two large events with moment magnitude (Mw) 6.4 and 7.1 and thousands of aftershocks above lower magnitude cutoff Mw 3.2. There was severe damage to critical infrastructures, such as major cracks and pavement failures along roads and highways, and disruption to utility service due to surface displacements. These infrastructures were important for post-disaster response and recovery operations. Fault displacement hazard analysis serves as an essential tool for characterizing the fault rupture hazard at sites of interest. Advancements in remote sensing approaches provide opportunities to study earthquake ground deformation hazard by modeling fault rupture process and surface displacements more reliably.   

In the present study, a stochastic source-based fault displacement hazard analysis is conducted. The methodology of the present study is based on statistical scaling relationships of source parameters (e.g., fault length, fault width, mean slip, and maximum slip), and heterogeneous earthquake slip distributions are synthesized to generate various stochastic source models. The method uses ground-truth and remotely sensed data, such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR) data to search for the source model with a satisfactory match with the available data. The present study differs from conventional fault displacement assessment practices in utilizing stochastic source modeling, instead of empirical predictive relationships. The methodology can be applied to all faulting mechanisms and consider multi-segment fault rupture. The use of Okada’s equations facilitates the calculation of three translational displacements and provides physically consistent fault displacement modeling at two locations for a given earthquake scenario, thereby allowing the estimation of the differential fault displacement at two sites.

This study evaluates the effect of applying InSAR data to the stochastic source modeling approach for the 2019 Ridgecrest earthquakes which involved the complex interaction of multiple faults having different mechanisms. InSAR data provide useful information on the geometry and the extent of the rupture system and contributes to the hazard assessment efficiently. The capability of the method is evaluated in the framework of retrospective analyses by comparing the results with available data as well as existing studies and their associated model weighted errors. The performance of the models in earthquake source characterization is also analyzed considering InSAR data by the changes in model weighted errors for the cases of the surface displacement results with and without InSAR data. Based on the obtained results, InSAR data play an integral part in mainshock displacement analyses. Considering all the merits of applying ground truth and remote sensing data to the practice of stochastic source-based fault displacement hazard analysis, the obtained results characterize fault displacements more realistically and contribute to emergency management and disaster risk mitigation of critical facilities and infrastructure.

How to cite: Shoaeifar, P. and Goda, K.: Evaluation of stochastic source models for the fault displacement hazard analyses using InSAR data: 2019 Ridgecrest earthquakes , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20139, https://doi.org/10.5194/egusphere-egu24-20139, 2024.

EGU24-20708 | ECS | Orals | NH6.3

ADATools: free and user-friendly tools to semiautomatically extract and analyse wide PSI displacement maps. Applications to the European Ground Motion Service (EGMS).  

Anna Barra, María Cuevas-González, José Navarro, Marta Béjar-Pizarro, Pablo Ezquerro, Silvia Bianchini, Jose Luis Zezere, Camilla Medici, Matteo Del Soldato, Riccardo Palamà, Saeedeh Shahbazi, Rosa María Mateos, Eleftheria Poyiadji, David Alfonso Jorde, Michele Crosetto, and Oriol Monserrat

The availability of displacement maps across extensive regions, based on Multi-Temporal SAR satellite interferometry techniques (MT-InSAR), has notably increased in recent years. The launch of the Copernicus Sentinel-1 satellites in 2014, ensuring global and regular acquisitions under an open and free data distribution policy, marked a turning point in both exploitation and application. A significant outcome of this progress is the development of regional, national, and continental ground motion services, providing comprehensive displacement maps that offer highly detailed information regarding both human activities and natural phenomena. Since 2022, the European Ground Motion Service (EGMS) freely provides billions of displacement Measurements Points (MP) updated annually, covering nearly the entire European territory, characterized by high reliability and millimetric precision. Despite the full potential usefulness of these maps for territorial management and risk assessment, these data remain still underexploited. With the aim of improving the operational use of this extensive catalogue, there is a critical need for automated tools that can simplify and accelerate the extraction, analysis, and interpretation processes. The production of derived and simplified maps is crucial for the uptake of the EGMS products by both expert and non-expert InSAR users. In response to this need, projects such as the European RASTOOL (DG-HECHO, UCPM-PJG-101048474) and the Spanish SARAI (MCIN/AEI) have made concerted efforts to explore both artificial intelligence and deterministic approaches. In this context, we present the deterministic methodologies and the developed tools, called ADATools (i.e., Active Deformation Areas Tools). Designed to be flexible, adaptable, and user-friendly, these tools aim to support territorial and risk management, with specific attention given to compatibility with EGMS data formats. The first tool, ADAFinder, is an improvement of a previously consolidated tool developed in the frame of previous European projects. ADAFinder allows the automatic extraction and selection of most significant ADAs, a crucial initial step in transitioning from a multitude of individual MPs to a manageable number of polygons to be further analysed or used. Following the identification of moving areas or ADAs, the ADAClassifier permits a preliminary evaluation of the processes likely causing the displacement. Incorporating auxiliary data, each ADA receives a preliminary characterization, allowing to visualize associations with landslides, subsidence, sinkhole, construction settlements, or uplift. Furthermore, a temporal characterization based on the automatic analysis of the time series from all MPs within each ADA is provided. Both temporal and phenomena characterizations are then used for an initial ranking of ADAs, considering their potential impact on structures and infrastructures, using the ADAImpact. In this presentation, examples of results obtained by applying the ADATools to the EGMS data will be presented, emphasizing strengths, and outlining perspectives for future improvements. This work is part of the Spanish Grant SARAI, PID2020-116540RB-C21, funded by MCIN/AEI/ 10.13039/501100011033.

How to cite: Barra, A., Cuevas-González, M., Navarro, J., Béjar-Pizarro, M., Ezquerro, P., Bianchini, S., Zezere, J. L., Medici, C., Del Soldato, M., Palamà, R., Shahbazi, S., Mateos, R. M., Poyiadji, E., Alfonso Jorde, D., Crosetto, M., and Monserrat, O.: ADATools: free and user-friendly tools to semiautomatically extract and analyse wide PSI displacement maps. Applications to the European Ground Motion Service (EGMS). , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20708, https://doi.org/10.5194/egusphere-egu24-20708, 2024.

EGU24-21683 | Orals | NH6.3 | Highlight

Selecting optimal displacement models using an improved stochastic model in InSAR arc-based time series analysis 

Wietske Brouwer, Ling Chang, and Ramon Hanssen

In InSAR time series analysis for displacement studies, the essential parameter estimation part is performed on arcs between a reference point and an evaluation point. Usually, both points are scatterers that satisfy certain optimality conditions. The set of parameters to be estimated in the functional model can be different for each arc. Especially in the built environment, individual points may behave rather differently. Conventional approaches to estimate average displacement velocities for the entire time series length are therefore often sub-optimal. However, deviation from a single uniform parameterization for all arcs implies that for each arc the optimal model needs to be selected.

Chang and Hanssen (2016) proposed a method to select the optimal functional model, i.e. parameterization, for each arc using multiple hypothesis testing (MHT). The selection was based on rejecting the conventional null hypothesis of linear steady-state displacement, satisfying Newton’s first law, in favor of an alternative hypothesis that is chosen from a library of canonical models. This procedure required the a priori selection of a significance level (related to the impact of the erroneous rejection of the null hypothesis), the discriminatory power (related to the impact of erroneously sustaining the null hypothesis), and the stochastic model of the arc observations. For the latter, a conservative uniform approximation was chosen.

Recently, Brouwer and Hanssen (2023) developed a methodology to approximate the stochastic model for each scatterer in an InSAR time series analysis, based on amplitude behavior. By combining both approaches, i.e., applying the MHT approach for functional model selection using a point- and epoch-specific stochastic model, we significantly reduce both Type-1 and Type-2 errors, leading to the improved identification of dynamic mechanisms in a complex environment. We report on the mathematical background, the level of improvement in practical case studies as well as the numerical consequences of the approach.

References:

W.S. Brouwer, Y. Wang, F.J. van Leijen, and R.F. Hanssen. ”On the stochastic model for InSAR single arc point scatterer time series.” In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium, pp. 7902-7905. IEEE, 2023.

L. Chang and R.F. Hanssen, ”A Probabilistic Approach for InSAR Time-Series Postprocessing,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 421-430, Jan. 2016, doi: 10.1109/TGRS.2015.2459037.

How to cite: Brouwer, W., Chang, L., and Hanssen, R.: Selecting optimal displacement models using an improved stochastic model in InSAR arc-based time series analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21683, https://doi.org/10.5194/egusphere-egu24-21683, 2024.

EGU24-21827 | Orals | NH6.3 | Highlight

Geolocation accuracy and precision for InSAR point positioning; validation using the Dutch IGRS network 

Ramon Hanssen and Paolo Bazzocchi

Precise and accurate geolocation of (point) scatterers is crucial for the correct interpretation of InSAR time series in the built environment, since this allows the scatterers to be linked to physical objects. The precision and accuracy of the geolocation is dependent on orbit precision, sub-pixel scatterer localization within the SAR images, as well as a range of geophysical, SAR processor, and instrument-related corrections.

 

Focusing on the abundantly available Sentinel-1 SAR acquisitions, previous studies on 40 corner reflectors in  Australia, with 30 acquisitions aligned towards ascending orbits (Garthwaite et al., 2015), and georeferenced using annual GNSS campaigns, yielded a positioning dispersion (1sigma) of 6~cm in range and 26~cm in azimuth, and residual offsets of 3~cm (range) and 18~cm (azimuth) (Gisinger et al., 2021).  

 

Here we report on new results applied on the network of Integrated Geodetic Reference Stations (IGRS) in the Netherlands, which currently consists of 80 corner reflectors on 40 stations (i.e., ascending and descending) on the same physical construction, equipped with permanent GNSS stations.   The already developed end-to-end methodology for SAR geolocation is revised, and applied to Sentinel-1 interferometric wide swath (IW) data from 257 ascending and 263 descending acquisitions.  Our results confirm the validity of the applied corrections.

How to cite: Hanssen, R. and Bazzocchi, P.: Geolocation accuracy and precision for InSAR point positioning; validation using the Dutch IGRS network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21827, https://doi.org/10.5194/egusphere-egu24-21827, 2024.

Synthetic Aperture Radar (SAR) remote sensing has become indispensable for monitoring natural and anthropogenic hazards. Here we present a novel application of SAR technology in the ecological domain. Focusing on Zavodovski Island, home to the world's largest penguin colony, we address the challenges posed by limited optical satellite observations due to persistent cloud cover and rare ground surveys due to the extreme remoteness of the study site.

Our proposed approach involves the application of an AI-driven classification algorithm to high spatiotemporal resolution X-band radar interferometric coherence data. Despite the inherent limitations of optical observations, we showcase the potential of dual-polarimetric, high-resolution SpotLight SAR in measuring phenology and its effectiveness in detecting, mapping, and monitoring penguin colonies on Zavodovski Island. The study leverages temporally dense SAR data, utilizing the TerraSAR-X and PAZ satellite systems, and spatially high-resolution data gathered during two field campaigns in February and December 2023.

This research not only highlights the innovative use of SAR in ecological monitoring but also underscores the broader applicability of SAR technology in diverse domains. By contributing to the understanding of penguin colony dynamics, our study exemplifies the transformative impact of SAR remote sensing on ecological health indices. This contribution demonstrates the capabilities of SAR technology in addressing unique challenges and expanding its utility beyond traditional hazard applications.

How to cite: Richter, N., Schade, M., Cartus, O., and Hart, T.: AI-Driven Classification of X-band Radar Dual-Polarimetric Coherence Data for Mapping and Monitoring Penguin Colonies on Zavodovski Island, South Sandwich Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22189, https://doi.org/10.5194/egusphere-egu24-22189, 2024.

EGU24-308 | Posters on site | NH6.4

InSAR closure errors: temporal signatures and impact on deformation time series estimation 

Simon Zwieback and Rowan Biessel

Closure errors quantify the inconsistency of seemingly redundant interferograms. Systematic closure errors, associated with e.g. changes in soil moisture or vegetation, can bias estimated InSAR time series. Previous work has shown that the bias can be reduced by including interferograms spanning long temporal baselines. However, it is not clear how the bias reduction depends on the temporal signatures of the closure errors and in what circumstances including long-term interferograms improves or deteriorates the InSAR phase history and ultimately deformation estimates.

To identify how the temporal signatures relate to InSAR time series estimation, we introduce a mathematical framework that quantifies temporal closure signatures as a function of time and time scale. Technically speaking, we construct two complementary bases of the annihilator of the vector space of all temporally consistent phases, with each basis element extracting the closure error corresponding to the element's time and time scale. Applying this framework to Sentinel-1 observations, we find contrasting short-term, seasonal, and multi-annual closure signatures across land cover types. The inclusion of long-term interferograms is associated with characteristic changes in seasonal amplitudes and long-term trends in the InSAR phase history estimates. 

To determine when including long-term interferograms improves InSAR time series estimation, we formulate simple interferometric scattering models for seasonally variable soil moisture and vegetation conditions and sub-resolution deformation as is common in ice-rich permafrost. We find that including long-term interferograms improves the InSAR time series in simulation scenarios dominated by soil moisture wetting and dry down cycles. Conversely, including long-term interferograms can have a deleterious impact on InSAR time series estimates in scenarios with seasonal vegetation and sub-resolution deformation.

We conclude with simple diagnostics on how temporal closure signatures and expert knowledge can inform InSAR processing to maximize deformation time series quality for a range of geohazards, including lowland permafrost deformation, landslides, and sinkholes.

How to cite: Zwieback, S. and Biessel, R.: InSAR closure errors: temporal signatures and impact on deformation time series estimation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-308, https://doi.org/10.5194/egusphere-egu24-308, 2024.

EGU24-1129 | ECS | Posters on site | NH6.4

Exploring Sentinel-1 for Coastal subsidence monitoring along India’s Gujarat shore using MT-InSAR Technique 

Sona Sharma and Chandrakanta Ojha

India’s long 7500 km coastline covers vast habitats of rich biodiversity and occupants of about 26% of the country’s population in the coastal zone. By 2060, about 60 million of India’s coastal population will be exposed to a low-elevation coastal zone (LECZ) due to global mean sea level rise (GMSL) and its associated hazards (Neumann et al., 2015). However, the low-lying coastal zones are vulnerable to increasing sea levels and coastal subsidence, which threaten the region's socio-economic development (Shirzaei et al., 2021). The erosion assessment report depicts that 60% of the Gujarat shore covering 1600 km of extensive coastline in western India is undergoing erosion. This study investigates and analyzes the combined influence of coastal subsidence and SLR along the south of Gujarat shoreline. In that context, we explored the descending track (path 34) of C-band Sentinel-1 satellite data (92 SAR imageries) in interferometric wide swath mode (IW2 and IW3) of the European Space Agency (ESA) covering the study area from March 2020 to June 2023. The data sets were processed in an open-source GMTSAR software following an advanced Small BAseline Subset (SBAS) based Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique (Berardino et al., 2002). The results exhibit a deformation rate of  >5 mm/year in various parts of Gujarat's Surat, Bhavnagar, and Bharuch districts. Kododara region in Surat district shows a maximum deformation of >15 mm/year, Navamadhiya in Bhavnagar district is showing subsidence of >20 mm/year, and Chanchvel village in Bharuch is also showing subsidence of >15 mm/year. However, the precipitation data shows a total deviation of -3 % and -5 % in the monthly average compared to normal rainfall observed in Bharuch and Surat districts, respectively, from January 2000 to November 2023 (WRIS, India). Rapid urbanization, dependency on groundwater for basic needs and industrialization, and the impact of increasing sea levels could influence the coastal deformation and inundation hazard risk over the long shorelines and those coastal cities, which needs to be investigated in detail.

References

  • Berardino, P., G. Fornaro, R. Lanari, and E. Sansosti. 2002. "A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms." IEEE Transactions on Geoscience and Remote Sensing 40 (11): 2375–83. https://doi.org/10.1109/TGRS.2002.803792.
  • Neumann, B., et al. (2015). "Future coastal population growth and exposure to sea-level rise and coastal flooding-a global assessment." PloS one 10(3): e0118571.
  • Shirzaei, M., et al. (2021). "Measuring, modelling and projecting coastal land subsidence." Nature Reviews Earth, Environment 2(1): 40-58.

How to cite: Sharma, S. and Ojha, C.: Exploring Sentinel-1 for Coastal subsidence monitoring along India’s Gujarat shore using MT-InSAR Technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1129, https://doi.org/10.5194/egusphere-egu24-1129, 2024.

EGU24-2150 | Orals | NH6.4 | Highlight

Interferometric Digital Elevation Model Generation Using ICEYE Data 

Melanie Rankl, Valentyn Tolpekin, Qiaoping Zhang, and Michael Wollersheim

High resolution, digital representation of surface topography and surface features is key to understanding global changes of terrain due to natural phenomena but also due to manmade changes. Digital Elevation Models (DEMs) can be retrieved from various methods such as SAR Interferometry (InSAR), Photogrammetry or Lidar systems using satellite or aerial data . 

SAR data has the unique advantage that both amplitude and phase are recorded by the SAR antenna. The phase information, which determines the distance from the sensor to a target, is essential for interferometric DEM generation. In comparison to e.g. radargrammetric methods, more accurate DEM results can be derived. Hence, spaceborne SAR interferometry has developed as a key method to derive digital elevation models. The first near global dataset has been presented by the Shuttle Radar Topography Mission in 2000 and since then has been complemented by ESA’s global Copernicus DEM derived from the bistatic TanDEM-X mission . However, other currently commercially available spaceborne SAR systems are not suitable for interferometric DEM generation due to constraints arising from both  normal and temporal baselines between image acquisitions. 

ICEYE has launched 31 satellites up to date (as of December 2023) and operates the largest spaceborne SAR constellation currently available. The fleet of satellites allows for tasking of pursuit monostatic image pairs where both satellites fly in an identical satellite orbit with a short temporal separation. Both satellites individually transmit and receive their own radar pulse. Suitable imaging geometries , i.e., long enough normal baselines and short enough temporal baselines, allow for InSAR derived DEM generation. Pursuit monostatic image pairs with short temporal baselines are hardly affected by atmospheric delay, similarly to bistatic formations, however, as both satellites operate as individual systems, image acquisition and processing is simpler than for bistatic formation flying.

In this study we present 1) results from interferometric DEM generation using high resolution ICEYE SAR data and 2) a quality assessment of the derived pursuit monostatic DEMs. Resulting DEMs have been derived for different study sites using pursuit monostatic image pairs with short temporal baselines acquired in Strip or Spot imaging modes. The suitability of various baseline settings has been tested and limiting baselines determined. A vertical accuracy assessment has been performed against external datasets such as airborne LiDAR derived DEMs or NASA’s ICESat-2 ATL08 Terrain points  (https://nsidc.org/data/atl08/versions/6).

The results show high spatial detail of surface topography with a DEM resolution finer than 3 m for Spot and 5 m for Strip imaging modes. The vertical accuracy has proven to be better than 3 m RMSE in open and relatively flat areas (slopes less than 10 degrees) when compared to external datasets. Yet, interferometric processing has shown to be challenging when affected by temporal decorrelation between image acquisitions, vegetation coverage or steep terrain. 

How to cite: Rankl, M., Tolpekin, V., Zhang, Q., and Wollersheim, M.: Interferometric Digital Elevation Model Generation Using ICEYE Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2150, https://doi.org/10.5194/egusphere-egu24-2150, 2024.

EGU24-2863 | Orals | NH6.4 | Highlight

An InSAR-GNSS Velocity Field for Iran 

John Elliott, Andrew Watson, Milan Lazecky, Yasser Maghsoudi, Jack McGrath, and Jessica Payne

We present average ground-surface velocities and strain rates for the 1.7 million square km area of Iran, from the joint inversion of InSAR-derived displacements and GNSS data. We generate interferograms from seven years of Sentinel-1 radar acquisitions, correct for tropospheric noise using the GACOS system, estimate average velocities using LiCSBAS time-series analysis, tie this into a Eurasia-fixed reference frame, and perform a decomposition to estimate East and Vertical velocities at 500 m spacing. Our InSAR-GNSS velocity fields reveal predominantly diffuse crustal deformation, with localised interseismic strain accumulation along the North Tabriz, Main Kopet Dagh, Main Recent, Sharoud, and Doruneh faults. We observe signals associated with recent groundwater subsidence, co- and postseismic deformation, active salt diaprism, and sediment motion. We derive high-resolution strain rate estimates on a country- and fault-scale, and discuss the difficulties of mapping diffuse strain rates in areas with abundant non-tectonic and anthropogenic signals.

How to cite: Elliott, J., Watson, A., Lazecky, M., Maghsoudi, Y., McGrath, J., and Payne, J.: An InSAR-GNSS Velocity Field for Iran, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2863, https://doi.org/10.5194/egusphere-egu24-2863, 2024.

Climate change has led to increasingly serious flooding in many regions around the world, including Vietnam. The Kon and Ky Lo river basins in Binh Dinh and Phu Yen provinces, Vietnam, have experienced increasingly serious flooding in recent years, which has caused damage to property and people living in the area. This basin lacks the availability of historical flood maps; flood information is mainly in the form of statistical information on people's damage situations.

Floods in Vietnam often appear in the last months of the year, combined with storms and heavy rain, leading to more serious flooding. During such periods of heavy rain, measuring and monitoring the flood situation is very difficult. Currently, with the development of the European Space Agency's (ESA) radar Sentinel-1 remote sensing technology, flood monitoring has become more convenient compared to the use of optical remote sensing technology. Moreover, combined with Google Engine (GE) technology, mapping historical floods became easier.

In this study, we applied the Sentinel-1 satellite images on the GE platform combined with SRTM digital elevation model data to conduct flood mapping for the large floods of 2016 and 2021 along the Kon and Ky Lo rivers. These historical flood maps will be used on the basis of flood risk assessment and as a basis for assessing the accuracy of future hydrological-hydraulic flood simulation models. In addition, the study also delineated areas that are frequently flooded to help local authorities more easily manage disasters and have better response solutions in the future, in order to limit the risk of damage to people in areas affected by flooding.

How to cite: Van Phan, T., Anh Ngo, T., and Willems, P.: Historical Flood Mapping Combining Radar Remote Sensing and Google Engine Technologies for The Kon and Ky Lo River Basin, South Center Coast Vietnam, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4056, https://doi.org/10.5194/egusphere-egu24-4056, 2024.

Synthetic Aperture Radar (SAR) images are becoming increasingly important in a variety of remote sensing applications, leading to new missions with higher resolution and coverage, ultimately resulting in an ever-increasing volume of data. This burden on SAR data storage and transmission has established a serious interest in developing compression methods that can obtain higher compression ratios, while keeping complex SAR image quality to an acceptable level. In computer vision, neural network-based RGB image compression has exceeded traditional methods such as JPEG, JPEG2000 or BPG. The Mean-Scale Hyperprior network [1] is an auto-encoder based architecture exploiting the probabilistic structure in the latents to improve compression performance. Auto-encoders are architectures particularly suited for the inherent rate-distortion trade-off of data compression. They also offer an intuitive solution to the on-board image compression problem, as demonstrate for the Φ-Sat-2 mission [2].

In this work, we explore efficient SAR image compression, in this regard, we adapt the Mean-Scale Hyperprior architecture to SAR data. We use Sentinel-1 IW mode VV polarization SLC images to build a dataset of diverse scenes: urban areas, forests, mountains and water bodies in dry as well as snow/ice conditions. The central idea being to create an open-source and general dataset of SAR images, in order to compare the performance of the studied architecture with traditional codecs and baseline models, such as the work in [3]. We will experiment with latent sizes, patch size as well as different SAR data representations for the network.

References  
[1] D. Minnen, J. Ball ́e, and G. D. Toderici, “Joint Autoregressive and Hierarchical Priors for Learned Image Compression,” in Advances in Neural Information Processing Systems, vol. 31, Curran Associates, Inc., 2018.  
[2] G. Guerrisi, F. D. Frate, and G. Schiavon, “Artificial Intelligence Based On-Board Image Compression for the Φ-Sat-2 Mission,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 8063–8075, 2023.  
[3] C. Fu, B. Du, and L. Zhang, “SAR Image Compression Based on Multi-Resblock and Global Context,” IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1–5, 2023.

How to cite: Léonard, C.: Synthetic Aperture Radar SLC data compression using Mean-Scale Hyperprior architecture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5021, https://doi.org/10.5194/egusphere-egu24-5021, 2024.

On July 1, 2022, a doublet of earthquakes, with a magnitude of Mw6.0 and a Mw5.7 aftershock between them, occurred within a two-hour period in the southeastern part of the Zagros Mountains near the Persian Gulf in Iran. This doublet earthquake event provides a unique opportunity to study the geometric properties of geological faults and the frictional attributes of rocks in the southeastern of the Zagros Mountains, particularly in the vicinity of the Hormoz salt layer. Here, we acquired co-seismic and post-seismic InSAR ascending and descending observations to simultaneously determine fault geometry and slip distribution models for the doublet earthquakes based on Bayesian inference. The inversion results reveal that the doublet earthquakes occurred on two distinct faults with similar strike (101.93°, 93.7°) but notable differences in dip (56.2°, 31.3°), and the slip distribution of the mainshock 2 is shallower and more westward compared to the mainshock 1. Moreover, the reliability of the fault geometry and slip distribution was confirmed through detailed discussions on the distributions of post-seismic kinematic afterslip, the relocated aftershocks beyond five months after the mainshocks, and the changes in positive Coulomb stress triggered by co-seismic events. Additionally, our post-seismic deformation modeling elucidated that post-seismic deformation is predominantly driven by stress induced by co-seismic event, accompanied by the release of both afterslip and aftershocks. Afterslip is distributed both up- and down-dip of the coseismic region on the two faults, with the maximum afterslip concentrated in the shallow portions, reaching approximately 0.45 m. By comparing the temporal evolution characteristics of stress-driven afterslip distributions with those of kinematic afterslip, we observed significant inconsistencies in the frictional properties within the southeastern Zagros Mountains, particularly between the Hormoz salt layer and its upper region. Specifically, above the Hormoz salt layer, the friction is stronger, and the relaxation time of afterslip is shorter. Finally, we also discussed the triggering potential of the mainshock 1 and the Mw5.7 aftershocks on mainshock 2, and from the perspective of Coulomb stress transfer, we found that mainshock 1 and Mw5.7 aftershocks may have triggering effects on mainshock 2.

 

How to cite: zhao, X., dahm, T., and xu, C.: Fault Slip Distribution and Inhomogeneous Frictional Properties in the Southeastern Zagros Mountains of the 2022 Iran doublet Earthquakes Inferred from Bayesian Inference and InSAR observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6273, https://doi.org/10.5194/egusphere-egu24-6273, 2024.

EGU24-6699 | Orals | NH6.4 | Highlight

InSAR Phase Bias Correction Processor: Recent Developments 

Yasser Maghsoudi, Andrew Hooper, Tim Wright, Milan Lazecky, and Muriel Pinheiro

The Sentinel-1 satellite's short revisit time is advantageous for maintaining better coherence in interferograms over short intervals, resulting in more accurate assessments of rapid deformation. However, the use of shorter-interval, multilooked interferograms may introduce a bias, known as a "fading signal," in the interferometric phase, leading to unreliable velocity estimates.

In the first part of our research, funded by the European Space Agency (ESA), we explore characterizing phase bias, focusing on one of its primary indicators—the closure phase. We explore loop closure time-series across various datasets, considering different look directions (ascending and descending), evaluating the impact of filtering and multilooking on closure phases, investigating loop closures across diverse landcovers, and examining the polarization dependency of closure phases. Additionally, we establish correlations between the time series of phase closures and various environmental proxies.

In the second stage, we present our progress on developing a universally applicable phase bias correction. We previously developed an empirical mitigation strategy that corrects the phase bias based on the assumption that the change in strength of the bias in interferograms of different length has a constant ratio (Maghsoudi et al. 2022). In this presentation, we investigate the applicability of the proposed method across various scenarios and compare it with alternative approaches.

Correcting for the phase bias is particularly important for InSAR processing systems, such as the COMET LiCSAR system (Lazecký et al. 2020), which aims to study geohazards over large areas.

 

References

Maghsoudi, Y., Hooper, A.J., Wright, T.J., Lazecky, M., & Ansari, H. (2022). Characterizing and correcting phase biases in short-term, multilooked interferograms. Remote Sensing of Environment, 275, 113022

Lazecký, M., Spaans, K., González, P.J., Maghsoudi, Y., Morishita, Y., Albino, F., Elliott, J., Greenall, N., Hatton, E., Hooper, A., Juncu, D., McDougall, A., Walters, R.J., Watson, C.S., Weiss, J.R., & Wright, T.J. (2020). LiCSAR: An Automatic InSAR Tool for Measuring and Monitoring Tectonic and Volcanic Activity. Remote Sensing, 12

 

How to cite: Maghsoudi, Y., Hooper, A., Wright, T., Lazecky, M., and Pinheiro, M.: InSAR Phase Bias Correction Processor: Recent Developments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6699, https://doi.org/10.5194/egusphere-egu24-6699, 2024.

Interferometric synthetic aperture radar (InSAR) decorrelation that creates great challenges to phase unwrapping has been a critical issue for mapping large earthquake deformation. Some studies have proposed a “remove-and-return model” solution to tackle this problem, but it has not been fully validated yet, and therefore has rarely been applied to real earthquake scenarios. In this study, we use the 2023 Mw 7.8 and 7.6 earthquake doublet in Turkey and Syria as a case example to develop an iterative modeling method for InSAR-based coseismic mapping. We first derive surface deformation fields using Sentinel-1 offset tracking and Sentinel-2 optical image correlation, and invert them for an initial coseismic slip model, based on which we simulate InSAR coseismic phase measurements. We then remove the simulated phase from the actual Sentinel-1 phase and conduct unwrapping. The simulated phase is added back to the unwrapped phase to produce the final phase measurements. Comparing to the commonly-used unwrapping method, our proposed approach can significantly improve coherence and reduce phase gradients, enabling accurate InSAR measurements. Combining InSAR, offset tracking and optical image correlation, we implement a joint inversion to obtain an optimal coseismic slip model. Our model shows that slip on the Çardak Fault is concentrated on a ~100 km segment; to both ends, slip suddenly diminished. On the contrary, rupture on the East Anatolian Fault Zone propagated much longer as its geometry is fairly smooth. The iterative coseismic modeling method is proven efficient and can be easily applied to other continental earthquakes.

How to cite: Chen, J. and Zhou, Y.: Coseismic slip distribution of the 2023 earthquake doublet in Turkey and Syria from joint inversion of Sentinel-1 and Sentinel-2 data: An iterative modeling method for mapping large earthquake deformation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7005, https://doi.org/10.5194/egusphere-egu24-7005, 2024.

Concise and informative target feature descriptions are curial for accurate land cover classification of polarimetric synthetic aperture radar (PolSAR) images. Effective feature selection strategy significantly impacts both classification model design and final accuracy.

Ideally, target features should capture diverse polarization scattering characteristics and physical properties, the foundation for PolSAR image interpretation, and also require all these features satisfy the independent and identically distributed hypothesis, as directly using all these features can lead to sparse sample data in the multi-dimensional space, especially with limited samples, hindering model training.

To this end, existing research attempt to utilize multiple features manually or analyze specific scattering characteristics for classification scenarios. However, these studies mainly focus on manual feature selection or using traditional random forest importance-based feature selection strategy, adaptive feature selection tailored to individual situations remains less explored.

In order to address this gap, we propose a novel target-oriented feature selection framework leveraging multi-scale two-dimensional structural similarity measure (MTSSIM). This framework adaptively selects informative features from an initial PolSAR image feature set, encompassing commonly used polarization scattering features, spatial neighbor context features, and morphological features. The core principle lies in designing an efficient algorithm that selects features maximizing intra-class and minimizing inter-class structural similarity.

For enhanced robustness and practicality, the proposed framework incorporates two key modules: 1) Two-dimensional structural similarity representation: This module quantifies the structural similarity between two samples, and 2) Multi-scale feature structural similarity measurement: This module utilizes local feature images at multiple spatial neighborhood scales to assess the intra-class and inter-class structural similarity of each feature relative to the target category.

To validate the effectiveness of the proposed framework, we conducted classification experiments on two real PolSAR image datasets using identical classification methods and parameters for three feature sets: the manually chosen features that commonly used in PolSAR image classification task (Manual feature set), the random forest importance-based features (RF feature set), and MTSSIM-recommended features (MTSSIM feature set).

Experimental results demonstrate that the proposed MTSSIM feature set consistently outperforms traditional approaches, demonstrating significant improvements in classification accuracy. These benefits include: 1) Reduced misclassification rates: MTSSIM significantly decreases misclassified pixels, leading to more accurate and reliable land cover maps; 2) Enhanced homogeneity: MTSSIM-derived feature sets yield spatially consistent and less noisy classification results, facilitating easier interpretation and analysis. 3) Improved performance in small-sample scenarios: MTSSIM effectively utilizes limited data, enabling accurate classification even with limited training samples.

In conclusion, the MTSSIM framework offers a powerful and practical solution for optimizing feature selection in PolSAR image classification. By addressing feature redundancy and leveraging structural information, MTSSIM improves classification accuracy, making it a valuable tool for enhancing remote sensing applications in land cover mapping, environmental monitoring, and various other domains.

How to cite: Nie, W., Yang, J., Zhang, C., and Qi, Y.: A Target-oriented Feature Selection Framework for Polarimetric SAR Image Classification Based on Multi-scale Two-dimensional Structural Similarity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8174, https://doi.org/10.5194/egusphere-egu24-8174, 2024.

EGU24-8695 | ECS | Posters on site | NH6.4

Fault irregularity of recent large strike slip earthquakes revealed by satellite imagery 

Chen Yu, Bingquan Han, Chuang Song, Zhenhong Li, and Yosuke Aoki

The geometric complexity of strike-slip faults, such as stepovers, bends and branches, is a pivotal indicator of segmented fault rupture. These features act as barriers to the activity of strike-slip faults, leading to uneven stress distribution along the fault zone, thereby influencing the initiation, propagation, and termination of earthquake ruptures.

The East Anatolian Fault (EAF) is a significant sinistral strike-slip fault, connecting with the North Anatolian Fault (NAF) to the north and the Dead Sea Fault (DSF) to the south. Located in southeastern Turkey, it plays a crucial role in accommodating the relative motion between the northward-moving Arabian Plate and the westward-moving Anatolian Block. Despite the relative quietude of the EAF since the beginning of the 20th century, historical seismic activity indicates its potential to generate devastating earthquakes, as evidenced by a series of relatively large earthquakes occurring between 1822 and 1905. On January 24, 2020, the Pütürge segment at the northeastern end of the EAF experienced the Mw6.8 Elaziğ earthquake (2020 event). Subsequently, on February 6, 2023, the southwestern segment of the EAF witnessed the Turkey–Syria Earthquake Sequence (2023 event). The consecutive occurrence of these two seismic events has provided an opportunity to investigate the tectonic activity characteristics and seismic triggering relationships of the EAF.

In this study, we take the two events that occurred on the EAF in 2020 and 2023 as the time nodes and take the EAF as the research object. Utilizing InSAR technology, the research investigated the deformation during seismic cycles (interseismic, coseismic, and postseismic) based on Sentinel-1 radar data. We computed interseismic deformation velocities from 2015 to 2020 and displacement time series from February 2020 to February 2023, as well as from February 2023 to September 2023. Subsequently, this study extensively considered the geometric complexity of faults and established an elastic triangular dislocation model. Based on this model, we derived the interseismic fault slip distribution for the EAF from 2015 to 2020, as well as coseismic and postseismic fault slip distributions for the 2020 and 2023 events. The results indicate that: 1) The slip rate along the EAF exhibits a decreasing trend from the northeastern end (5 mm/yr) to the southwestern end (2 mm/yr); 2) The interseismic slip deficits of the EAF correlate well with the coseismic fault slip distribution of the 2020 and 2023 events; 3) The postseismic fault slip following the 2020 and 2023 events primarily occurs at coseismic slip deficit areas.

How to cite: Yu, C., Han, B., Song, C., Li, Z., and Aoki, Y.: Fault irregularity of recent large strike slip earthquakes revealed by satellite imagery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8695, https://doi.org/10.5194/egusphere-egu24-8695, 2024.

EGU24-10065 | ECS | Orals | NH6.4

Postseismic deformation of the 2021 Mw 7.4 Maduo earthquake, eastern Tibet: implications for fault friction 

Yuan Gao, Qi Ou, Kali Allison, Tim Wright, Jin Fang, and Manon Carpenter

Postseismic deformation occurs due to stress relaxation following large earthquakes and has been widely captured by space geodetic observations. For some earthquakes, afterslip has been inferred to take place in the fault barriers surrounding the areas of coseismic asperities. This phenomenon can be explained by the velocity-strengthening frictional behavior prevalent in the barriers and velocity-weakening frictional properties in the asperities. However, for some events, afterslip seems to exhibit spatial overlap with the coseimsic slip. Here we used postseismic deformation of the Maduo earthquake to investigate the afterslip pattern and fault friction properties. 

The 2021 Mw 7.4 Maduo earthquake ruptured ~150 km of the Jiangcuo fault, a previously-poorly known NWW-trending, sinistral strike-slip fault which lies within the Bayan Har block of the eastern Tibetan Plateau. Here we use ~2 years (between May 2021 and August 2023) of Sentinel-1 interferometric synthetic aperture radar (InSAR) data to study the postseismic deformation following the Maduo earthquake. Additionally, we use ~7 years (between October 2014 and May 2021) of InSAR data to obtain the interseismic velocity. We remove the interseismic components from postseismic data through transforming both datasets into Eurasian reference frame based on GPS velocities. Both descending and ascending postseismic data reveal notable localized postseismic deformation in the middle segment of the seismogenic fault, and diffused deformation in the far field. 

We apply a kinematic inversion to model the afterslip based on the cumulative postseismic displacement. We find that significant afterslip occurred on shallow (0–5 km) fault segments that also slipped coseismically . We then conduct dynamic earthquake cycle simulations incorporating vertical variations of frictional properties to understand the conditions where this can occur. We show that velocity-strengthening properties in the shallow region can rupture seismically and creep during postseismic period. Our dynamic model partially explains the overlapping slip of co- and postseismic slip of the Maduo earthquake. However, this model requires shallow interseismic creep, which is either not observed, or is obscured by noise in our data. 

Reference 

Lazecký, M., Spaans, K., González, P.J., et al. (2020). LiCSAR: An Automatic InSAR Tool for Measuring and Monitoring Tectonic and Volcanic Activity. Remote Sens., 12, 2430. 

Morishita, Y., Lazecky, M., Wright, T.J., et al. (2020). LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor. Remote Sens., 12, 424.  

Ou, Q., Daout, S., Weiss, J. R., et al. (2022). Large-scale interseismic strain mapping of the NE Tibetan Plateau from Sentinel-1 interferometry. J. Geophys. Res. Solid Earth, 127, e2022JB024176. 

Amey, R. M. J., Hooper, A., Walters, R. J. (2018). A Bayesian method for incorporating self‐similarity into earthquake slip inversions. J. Geophys. Res. Solid Earth, 123, 6052–6071. 

Allison, K. L., Dunham, E. M. (2018). Earthquake cycle simulations with rate-and-state friction and power-law viscoelasticity. Tectonophysics, 733, 232– 256.

How to cite: Gao, Y., Ou, Q., Allison, K., Wright, T., Fang, J., and Carpenter, M.: Postseismic deformation of the 2021 Mw 7.4 Maduo earthquake, eastern Tibet: implications for fault friction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10065, https://doi.org/10.5194/egusphere-egu24-10065, 2024.

EGU24-10416 | Orals | NH6.4 | Highlight

Tracking three-dimensional growth of magma-filled fractures by joint inversion of high-resolution geodetic and seismicity data 

Pablo J. Gonzalez, Yu Jiang, Maria Charco, Eugenio Sansoti, and Diego Reale

Magma-filled fracture propagation is the primary magma transport mechanism near the surface at ocean island basaltic volcanoes. Therefore, developing and implementing efficient workflows to track magmatic intrusions in the elastic-part of the oceanic lithosphere (<10-20 km depth, usually corresponding to shallower than the Moho) is of great importance for volcano hazard assessment. Here, we implement a kinematic three-dimensional magma-filled fracture geomechanical model capable of jointly inverting observations of surface deformation and seismic data. We combine the strengths of both datasets: first by constraining the magma-filled fracture geometry using satellite radar interferometry and/or GPS, and second by kinematic magma migration using seismic data. The final output is a refined spatio-temporal evolution model of the magma propagation process, parametrized by fracture opening and shear stress changes. We apply this method to simulated cases and also to gain insights on the magma migration process occurring during real volcanic unrests in Canary Islands volcanoes. Our work aims to contribute knowledge that will help hazard assessment and volcanic risk reduction.

Acknowledgements: We thank Spanish Agencia Estatal de Investigación projects PID2019-104571RA-I00 (COMPACT) funded by MCIN/AEI/10.13039/501100011033, and Project PID2022-139159NB-I00 (Volca-Motion) funded by MCIN/AEI/10.13039/501100011033 and “FEDER Una manera de hacer Europa”. Research activities of the CSIC staff during the 2021 La Palma eruption were funded by CSIC -CSIC-PIE project PIE20223PAL008. This work was also partially supported by project PTDC/CTA-GEO/2083/2021 GEMMA, funded by Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES. We thank INTA La Palma Announcement of Opportunity and Hisdesat for providing timely PAZ satellite radar data and also the Italian Space Agency (ASI) for providing Cosmo-SkyMed data within the CEOS Volcano Demonstrator. 

How to cite: Gonzalez, P. J., Jiang, Y., Charco, M., Sansoti, E., and Reale, D.: Tracking three-dimensional growth of magma-filled fractures by joint inversion of high-resolution geodetic and seismicity data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10416, https://doi.org/10.5194/egusphere-egu24-10416, 2024.

With an operating area of 4,380 ha producing approximately 40 million tons per year  of lignite , the Hambach mine is the largest open pit mine in Germany. To extract the lignite in open-cast mining, the groundwater level needs to be lowered down to below the deepest point of the open pit mine. This leads  to major changes in the aquifer conditions which may result in land subsidence that can affect the safety of built-up structures with significant socio-economic impacts.

In this study we perform a regional analysis of ground surface deformation in the Hambach mining area using interferometric observations from the Copernicus Sentinel-1 satellite. We present results from our validation investigation,  where results provided by German and European Ground Motion Services are compared with those obtained from our local surveys using high-resolution TerraSAR-X SAR data. We further investigate the correlation between InSAR measurement points, in-situ observations, and damages to infrastructures, and show evidence for several cases of fault reactivation and damages to infrastructures within the area undergoing mining related subsidence. Fault reactivation has resulted in the formation of fault scarps (offsets > 1 m), with detrimental impacts on existing structures. Finally, we integrate between results from InSAR measurement points with open source geospatial data to create maps that support hazard, exposure and risk assessment related to subsidence at regional scale in the Hambach region.

 

How to cite: Motagh, M., Haghshenas Haghighi, M., Piter, A., and Vassileva, M.: Mining-induced subsidence and fault reactivation due to open pit lignite mining in the Hambach region, North Rhine-Westphalia, Germany: Insights from Sentinel-1 based European Ground Motion Service (EGMS) and field surveys , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11866, https://doi.org/10.5194/egusphere-egu24-11866, 2024.

The fault structures of the 12 November 2017 Sarpol-e Zahab earthquake in Iran, as inferred from geodetic and geological data, exhibit significant distinctions, indicating intricate interactions between the crystalline basement and sedimentary cover. To further investigate this phenomenon, we employ interferometric synthetic aperture radar (InSAR) observations and 2-D Finite Element Models (FEM) with various fault geometries, such as planar, ramp-flat, and splay faults, to analyze mechanical (stress-driven) afterslip models for postseismic deformation. The kinematic coseismic slip model support a planar fault dipping at 15º, which is in good agreement with previously published results. Based on the coseismic model, we vary the fault geometries and explore the relationship between afterslip fault geometries and fault friction properties. We show that the planar frictional afterslip model fails to completely explain the long-wavelength postseismic deformation field. Instead, a ramp-flat fault model explains well the majority of the postseismic observations, with a maximum afterslip of approximately 1.0 m. The friction variations after fault strengthening are estimated to be about 0.001 and 0.0002 for the up-dip and down-dip portions, respectively. Expanding on the optimal ramp-flat fault model, we introduce an additional splay fault, which further improves the model fit, although the splay fault's frictional slip was limited to less than 0.2 m, and there is a trade-off between the splay fault geometries and their friction variations. Considering our results in conjunction with relocated aftershocks and geological cross-sections, we propose that a splay fault may have been weakly triggered after the mainshock, indicating more complex fault interactions than a simple decoupling layer between the basement and sedimentary cover.

How to cite: Guo, Z., Motagh, M., and Baes, M.: Structural Complexity Revealed by Frictional Afterslip Models and InSAR Observations Following the 2017 Mw 7.3 Sarpol- e Zahab (Iran-Iraq) Earthquake: Insights from Numerical Modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11944, https://doi.org/10.5194/egusphere-egu24-11944, 2024.

SAR and GNSS are two dominant techniques to measure the Earth's deformation. They have different characteristics in that InSAR has superior spatial resolution, and GNSS has superior temporal resolution. Also, GNSS has better precision than InSAR, and InSAR measurements have significant spatial correlation mainly because of the atmospheric disturbance. Therefore, if available, InSAR measurements will be more precise when combined with GNSS measurements. This study investigates the temporal evolution of land subsidence and slow slip transients in the Boso Peninsula, Japan, from InSAR and GNSS measurements. First, we generated interferograms of available ALOS-2 images. The generated interferograms are corrected to be consistent with GNSS measurements every 20 km or so. The correction assumes that the spatial variation of the noise in InSAR measurements is represented as a polynomial function, the degree of which is constrained adaptively. Then, the corrected interferograms are fed to the time-series analysis. The time series generated allows us to separate continuing subsidence of up to 20 mm/yr with a shorter wavelength and slow slip transients with a longer wavelength. 

How to cite: Aoki, Y.: Imaging land subsidence and slow slip transients by combining InSAR and GNSS , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14246, https://doi.org/10.5194/egusphere-egu24-14246, 2024.

EGU24-14887 | ECS | Posters on site | NH6.4

Ionospheric and Tropospheric Impact for InSAR Time Series Analysis in the Central Andes: A Case Study from Northwestern Argentina 

Sofia Viotto, Bodo Bookhagen, Guillermo Toyos, and Sandra Torrusio

The ionosphere, located 50 km above the Earth's surface is characterized by ionization processes that can significantly impact electromagnetic signals within the microwave wavelength range. The magnitude of the impact depends on the density of free electrons, which have daily and seasonal oscillations but are also tied to the 11-year solar activity cycles. Radar signals are delayed after interacting with free electrons and ions, and the magnitude of such delay is inversely proportional to the radar frequency. Thus, sensors operating in the longer wavelength L-band are more affected than those operating in the C-band. However, even C-band interferograms can be significantly affected if the region is close to the geomagnetic equator.

The Central Andes in Northwestern Argentina, being in proximity to the geomagnetic equator, offer an excellent setting to study the impact of the ionosphere on interferograms. Its low vegetation cover results in highly coherent interferograms, and predominantly dry conditions at high elevations lead to small tropospheric disturbances.

We employ the split spectrum technique extended to time series analysis to identify interferograms that are impacted by ionospheric contributions. Subsequently, we apply statistical methods to those time series to recognize acquisitions more likely to be contaminated by the ionosphere.  The magnitude of ionospheric contribution is compared to tropospheric delay. We demonstrate the impact of the high-solar activity on interferograms by correlating our time series of ionospheric delay to sunspot activity and total electron content maps. The analysis of Sentinel 1 C-band data from both ascending and descending tracks reveals a more significant contribution in ascending passes in response to the daily cycle of free electron density. These findings prove the relevance of the ionosphere as source of disturbance in interferograms from Sentinel C-band, particularly for studies at the regional scale.

How to cite: Viotto, S., Bookhagen, B., Toyos, G., and Torrusio, S.: Ionospheric and Tropospheric Impact for InSAR Time Series Analysis in the Central Andes: A Case Study from Northwestern Argentina, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14887, https://doi.org/10.5194/egusphere-egu24-14887, 2024.

EGU24-15424 | Orals | NH6.4 | Highlight

From meters of subsidence to millimeters of slow slip: monitoring deformation and associated uncertainties from InSAR 

Romain Jolivet, Manon Dalaison, Bryan Raimbault, Béatrice Pinel-Puysségur, Bertrand Rouet-Leduc, and Paul Dérand

Over the past two decades, InSAR evolved from the occasional processing of single interferograms over arid terrains to monitoring continuous time series of SAR acquisitions at the continental scale. Challenges, including atmospheric phase screen mitigation, automatic careful SAR image co-registration, ionospheric phase screen corrections, or discontinuous acquisition planning, were met through various technical and methodological advances by many research groups globally. The resulting methodologies now allow us to image a vast range of processes, from sudden large earthquakes to continuous subsidence involving metric to millimetric displacements. In addition to the ability to process datasets over continental scales, we can now measure natural signals of a few millimeters over distances lower than a kilometer.

In recent years, we proposed technical solutions to issues that were seriously impeding our ability to measure small, millimeter-scale displacements over natural terrains. First, I will discuss the early development of tropospheric corrections using numerical weather models and highlight some of the most recent tools and methods stemming from there. Second, I will illustrate our approach to tackle the issue of continuously incoming SAR acquisitions, which we addressed by developing a data assimilation-based method involving a Kalman filter. This tool allows the rapid update of pre-existing time series of deformation as new SAR images are available while carefully propagating forward some of the uncertainties associated with time series analysis. Third, I will show how we handle the automatic denoising of InSAR time series using a fully convolutional neural network, allowing us to detect sub-millimeter tectonic fault slip with no prior knowledge of the faults. Fourth, I will present some recent developments about the effect of fading signals and time-dependent coherence evolution over temperate regions, depending on land covers.

All these developments allowed us to image surface deformation processes, including several continuously creeping faults globally, transient tectonic slow slip events, intriguing post-seismic deformation signals, and strong subsidence patterns.

How to cite: Jolivet, R., Dalaison, M., Raimbault, B., Pinel-Puysségur, B., Rouet-Leduc, B., and Dérand, P.: From meters of subsidence to millimeters of slow slip: monitoring deformation and associated uncertainties from InSAR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15424, https://doi.org/10.5194/egusphere-egu24-15424, 2024.

Distributed scatter interferometric synthetic aperture radar (DS-InSAR) technology has been extensively employed for surface deformation monitoring, with phase optimization as a pivotal step. Currently, phase optimization techniques utilize the statistical intensity distribution of pixels to select homogeneous pixels. Pixels with low temporal intensity stability are excluded from consideration, avoiding their involvement in the phase optimization. However, it is noteworthy that distinguishing between homogeneous and heterogeneous pixels becomes more challenging in mountainous areas. Additionally, pixels with low stability are affected not only by thermal or environmental noise but also by the influence of local incidence angles, causing ground deformation beyond the Maximum Detectable Deformation Gradient (MDDG) of InSAR, resulting in geometric decorrelation. These pixels are often erroneously classified as noise and discarded. Nevertheless, these pixels contain rich and crucial deformation information, indicating disaster risks. Therefore, optimizing the phase of these pixels is essential.

This paper introduces a method for interferometric phase optimization of distributed scatterers in mountainous regions, considering geometric decorrelation (GD-DS). Using real InSAR differential interferometric phases as a basis, the study simulates interferometric phase datasets with rich spatiotemporal features, ensuring the correlation between simulated GD-DS phases and MDDG. Subsequently, K-means clustering is applied to segment the MDDG map, with resulting connected regions representing homogeneous pixels with similar local incidence angles. Convolutional denoising training is performed on homogeneous pixels using the generative adversarial network model (Pix2pix), and the trained model is then applied to real interferometric phase images. The proposed strategy and method are successfully applied to interferometric phase optimization in the Jishishan region of Gansu Province, China. Compared to traditional methods, the new approach demonstrates superior phase optimization performance, particularly in the case of GD-DS. Discussion and analysis of the spatial correlation between GD-DS and MDDG in the real experimental area confirm that introducing MDDG as a reference to optimize GD-DS is a key factor in improving phase optimization. Furthermore, the computational time of the new method is significantly reduced compared to traditional methods.

How to cite: Guo, A. and Sun, Q.: Interferometric Phase Optimization Method for Mountainous Regions Considering Geometric Decorrelation of Distributed Scatterers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15538, https://doi.org/10.5194/egusphere-egu24-15538, 2024.

EGU24-17181 | ECS | Posters on site | NH6.4

Assessing the Impact of Burst Overlap Interferogram of Sentinel-1 TOPS on Near-Fault 3D Displacement Modelling: A Case Study of the 6th February 2023 Mw7.8 and Mw7.5 Kahramanmaraş Earthquakes, Türkiye. 

Muhammet Nergizci, Qi Ou, Milan Lazecky, C. Scott Watson, Jin Fang, Andrew Hooper, and Tim J. Wright

On February 6, 2023, two devastating earthquakes, Mw7.8 and Mw7.5, struck the area surrounding Kahramanmaraş, Türkiye, resulting in extensive and complex surface deformations. The Mw7.8 event created a surface rupture over 310 km along the East Anatolian Fault, while the Mw7.5 earthquake resulted in a 150 km rupture along the Çardak-Sürgü Fault segment. Here we use Sentinel-1 Burst Overlap Interferometry (BOI) to improve 3D displacement mapping and in particular investigate near-fault deformation.In response to the earthquakes, previous studies have utilized various datasets, either separately or in combination. These include near and far-field seismic observations, continuous and campaign GNSS datasets, offset tracking from SAR satellites like Sentinel-1 and ALOS-2 and optical satellites such as Sentinel-2, and InSAR. These diverse data sources are vital for calculating the 3D displacement field. However, extracting information from standard interferograms, critical due to their high spatial resolution, is often challenging because of large phase gradients, particularly in the near field of fault ruptures.This issue frequently complicates the accurate determination of fault displacement and 3D decomposition in impacted areas. For Sentinel-1, with a range resolution of approximately 5 m, displacement in the range direction is usually determined with acceptable accuracy using range offset tracking. However, the azimuth resolution of about 20 m makes azimuth offset tracking less precise. This lower resolution frequently results in less reliable displacement constraints in the azimuth direction. To overcome this limitation, we produced Burst Overlap Interferograms (BOI) from four different tracks of Sentinel-1. These BOI results enabled more precise measurements of along-track displacement near the fault lines, which are theoretically proportional to the number of looks and the decorrelation noise.A key aspect of our methodology was the unwrapping process of the BOI, guided by azimuth offset tracking to handle large displacements exceeding ~1.5 m in the azimuth direction. For the 3D displacement field, we referenced all offset and BOI data to zero points away from the co-seismic ruptures and removed planar ramps. Uncertainties were empirically estimated as the mean absolute deviation in 4x4 pixel windows for offset data and 2x2 pixel windows for BOI. These uncertainties were then used to weight 3D motion inversion and decomposed displacements, providing a more reliable depiction of the earthquake impact. Our approach, combining east and north motion fields, allowed us to extract precise surface slip distributions and highlight surface ruptures through detailed strain analysis. In this study, we explored how to extract more accurate deformation in the north-south direction and reveal detailed deformation near faults by applying 3D decomposition with jointly inverted all datasets in together. We will discuss the implications of our findings for our understanding of earthquakes, and in particular for understanding distributed off-fault deformation that occurs near the fault rupture.

How to cite: Nergizci, M., Ou, Q., Lazecky, M., Watson, C. S., Fang, J., Hooper, A., and Wright, T. J.: Assessing the Impact of Burst Overlap Interferogram of Sentinel-1 TOPS on Near-Fault 3D Displacement Modelling: A Case Study of the 6th February 2023 Mw7.8 and Mw7.5 Kahramanmaraş Earthquakes, Türkiye., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17181, https://doi.org/10.5194/egusphere-egu24-17181, 2024.

EGU24-18703 | ECS | Posters on site | NH6.4

Service for automated processing and correction of DInSAR deformation maps 

Dominik Teodorczyk, Maya Ilieva, and Patryk Balak

One of the enduring facets within contemporary monitoring systems resides in the automation of data processing. This methodology ensures expeditious access to the most current and objectively derived results. Several systems for terrain monitoring have been realised in the last few years, with the leading role of the European Ground Motion Service (EGMS), part of the Copernicus program. Still most of these systems rely on the usage of the advanced Interferometric Synthetic Aperture Radar (InSAR) techniques which are not capable of exploring more dynamic and complex terrain change patterns as those related to underground mining works in Central Europe. A extensive study within the frames of the Polish realisation of the European Plate Observing System (EPOS) project, comprising long term monitoring between the years of 2016 and 2023 revealed the necessity of usage of the classical DIfferential InSAR (DInSAR) for more detailed study of the processes happening in the area of the Upper Silesian Coal Basin (USCB) in Poland. Within the project EPOS-PL+ we have developed an automated system for DInSAR processing of SAR data from Sentinel-1 satellite. The system also includes modules for processing of third party mission X-band data. 
This processing approach excels in managing significant deformations with reduced coherence, unlike methods relying on stable scatterers. The automated framework encompasses data retrieval, Line of Sight (LOS) deformation computation, trend elimination for atmospheric correction, and assessment of interferogram quality. The final step involves decomposing the LOS deformation into vertical and east-west components.
Upon initiation of the application, the user delineates parameters such as the region of interest by a shapefile, the period of study, and ascending and descending orbits. Subsequently, ingress into the Alaska Satellite Facility service repository, and data is procured for subsequent processing utilising the DInSAR method facilitated by the snappy library. This library enables script-based manipulation of the SNAP program using the Python language.
The subsequent phase involves detrending the data. Raw 1D deformation maps exhibit discernible trends, primarily attributable to atmospheric variations between successive acquisitions. To overcome this problem, a plane is fitted to the deformation data, and the estimated values are differentially subtracted from the original dataset. This estimation is implemented through two distinct methodologies. The more intricate approach include sthe identification of stable points based on nine coherence maps correlating with the deformation values, followed by the fitting of a plane. The simpler approach involves the fitting of a plane to the entire set of deformation data.
The quality check stage involves examining the dataset's pixels for coherence levels exceeding a set threshold (e.g., 0.2). Pixels failing coherence criteria are excluded, and linear interpolation is applied only to selected pixels. This approach minimizes phase unwrapping errors' propagation and effectively removes atmospheric effects in the final analysis. In instances of significant data gaps, the ensemble of adjacent images used for interpolation is expanded to reduce the impact of individual map errors. The enhanced DInSAR data are then projected into 2D components, namely the vertical and east-west (horizontal) dimensions.

How to cite: Teodorczyk, D., Ilieva, M., and Balak, P.: Service for automated processing and correction of DInSAR deformation maps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18703, https://doi.org/10.5194/egusphere-egu24-18703, 2024.

EGU24-18815 | ECS | Posters virtual | NH6.4

Assessment of Incoming Sediment with Flash Flood: A Case Study of the 2020 Flood in the Northeastern Part of Bangladesh using SAR Interferometry 

Kh. M. Anik Rahaman, Faizur Rahman Himel, Miftahul Zannat, Shampa Shampa, and Sonia Binte Murshed

Bangladesh, a riverine South Asian country with many Haor areas, is extremely vulnerable to flash flooding, which occurs primarily between the months of April and May (pre-monsoon). A Haor is a type of wetland ecosystem found in Bangladesh's northeastern region that is essentially a tectonically active shallow depression with a bowl or saucer shape where water flows from upstream basins. Floods and the resulting sediment have both positive and negative impacts on the affected Haor region, with broader implications for agricultural, water, fisheries, and other resource planning and management. However, till now there is no measurement or literature on the amount of sediment deposition caused by these flash flooding events. Threfore, the primary goal of this study was to determine the amount of incoming sediments associated with flash floods in Haor regions using remote sensing and to validate it in the field. The amount of incoming sediment associated with the flash flood that occurred in June 2020 was estimated for a selected region in the affected northeastern part of Bangladesh for this purpose. Using Sentinel-1 satellite images, interferometric techniques were used to create Digital Elevation Models (DEMs) of the pre and post-flood period of 2020. A total of eight Sentinel 1 A and Sentinel 1 B images covering the study area were collected from 22 July to 26 July 2019 to assess pre flood land conditions and from 21 July to 27 July 2020 to assess post flood land conditions. Our study revealed that the overall sediment deposition was found to be about 2.8 cm on average for the selected entire region. Furthermore, it has been observed that relatively less flashy areas gained sediment increase of about 7.3 cm on average within this one year interval, and relatively upstream areas with steep gradient gained 4.5 cm increase. Any anthropogenic interventions in this area should take into account the natural sediment distribution pattern and avoid impeding sediment spreading pathways, as sediment acts as a natural countermeasure to tectonic-subsidence of this area.

How to cite: Rahaman, Kh. M. A., Himel, F. R., Zannat, M., Shampa, S., and Murshed, S. B.: Assessment of Incoming Sediment with Flash Flood: A Case Study of the 2020 Flood in the Northeastern Part of Bangladesh using SAR Interferometry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18815, https://doi.org/10.5194/egusphere-egu24-18815, 2024.

EGU24-19176 | Orals | NH6.4

EPOS-PL+ project - infrastructure for long-term InSAR monitoring of mining induced deformations in Southern Poland 

Maya Ilieva, Kamila Pawłuszek-Filipiak, Dominik Teodorczyk, Natalia Wielgocka, Patryk Balak, Krzysztof Stasch, Mateusz Karpina, Paweł Bogusławski, and Przemysław Tymków

The second Polish realisation of the European Plate Observing System (EPOS), namely EPOS-PL+ project (2020-2023), comprised a dedicated task for development of an Infrastructure Centre for Satellite Data Research (CIBDS in Polish). The main task of the centre was to create a methodology for monitoring, modelling and prediction of the terrain deformations related with the extensive underground mining works taking place in the region of the Upper Silesian Coal Basin (USCB). This area is characterised with extremely dynamic surface changes consisting of small-scale deformation bowls (200-300m in radius) within short range from each other. The subsidence could reach between 0.6 up to 1.6 m per year, depending on the depth of the coal seams under explorations. The deposits are in depth between 400 and 1200 m, and are exploited in a multi-layer manner. The dynamics of the appearance of the subsidence patterns over time is closely related to the long-wall mining method used in this mining area. 

Within the CIBDS several modules for processing of Synthetic Aperture Radar (SAR) data have been developed. An automatic system for Differential Interferometric SAR (DInSAR) processing and postprocessing was developed based on the Alaska data facility repository of Sentinel-1 data, and the European Space Agency (ESA) tools SNAP and snappy. A new methodology was introduced for integration of lower quality but more detailed DInSAR terrain deformation maps with products created by the usage of Persistent scatterers (PSInSAR) technique, which have higher accuracy but lower coverage. The integrated deformation maps are validated with the results of campaign in-situ GNSS/levelling measurements.

A new methodology for modelling of the subsidence and 1-month prediction of the expected deformations have been designed on the basis of the Knothe-Budryk theory. FOr the purpose, artificial intelligence (AI) capabilities have been applied using the deformation maps generated by the DInSAR processing and external information about the rhythm and range of the mining works.

The newly developed system for terrain changes monitoring target the gaps that left in the commonly used platforms like European Ground Motion Service (EGMS) that cannot cover very extensive deformations and to support and upgrade the mining management and supervision. 

How to cite: Ilieva, M., Pawłuszek-Filipiak, K., Teodorczyk, D., Wielgocka, N., Balak, P., Stasch, K., Karpina, M., Bogusławski, P., and Tymków, P.: EPOS-PL+ project - infrastructure for long-term InSAR monitoring of mining induced deformations in Southern Poland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19176, https://doi.org/10.5194/egusphere-egu24-19176, 2024.

Earthquakes with large magnitude induce massive post-seismic deformation lasting for months to years. Modeling the post-seismic deformation gains invaluable insights to understanding the physics of fault zone and the lower crustal rheology. However, the observed post-seismic deformation is originated from sources with variant mechanisms, including afterslip, poroelastic rebound, and viscoelastic relaxation, which occur at different spatial and temporal scales. Decomposing and interpreting deformation resulted from deep afterslip and viscoelastic relaxation especially remains challenging. The 2021 Mw 7.4 Maduo earthquake, which occurred on a secondary fault ~80 km south of the previously identified major block boundaries, east Kunlun fault, has generated clear afterslip signal reported by several studies. However, the interpretations regarding viscoelastic models remained debated in two aspects: 1) How can we quantify the contribution from deep afterslip and viscoelastic relaxation during the early post-seismic phase? 2) Does the lower crust exhibit the same rheological property across the ruptured Jiangcuo fault and east Kunlun fault? In this context, acquiring high-resolution and extensive coverage of post-seismic deformation data becomes critically important.

Here, we derived a high-resolution post-seismic deofrmation extending over ~1000 kilometers for 2.5 years, using 6 tracks of Sentinel-1 SAR images and 32 continuous GNSS stations. Far-field deformations showed a smooth decay, ranging from 2 cm/year at the fault to 200 kilometers away on both sides of the fault rupture, extending over 500 kilometers along the strike. Notably, no discontinuity was observed along the east Kunlun fault, indicating that the boundary fault kept silent following the Maduo earthquake. We constrained the spatial pattern of post-seismic deformation with high-resolution InSAR observations, offering significant constrains into the depth and viscoelastic structure. Additionally, we utilized GPS time-series data to accurately ascertain the viscosity magnitude. By extracting the contribution of shallow afterslip from the initial observations, we explored the trade-off between deep afterslip and viscoelastic relaxation.

We firstly used a three-layer Maxwell and Burgers model for far-field deformation (100-200 km) and then incorporated deep afterslip and viscoelastic relaxation for mid-field observations (10-100 km). Our best-fit results reveal that deep afterslip dominates in mid-field areas, while viscoelastic relaxation significantly impacts far-field deformation. The optimal model presents an upper crust depth of 20 km, with transient and steady-state viscosities in the lower crust at 10^18 and 4*10^19 Pa·s, respectively, and a steady-state upper mantle viscosity of 10^20 Pa·s. As with the preliminary results, the model did not require a strong variant viscosity to explain the data. Disregarding deep afterslip could lead to overestimating viscosity by 1-1.5 orders of magnitude. Our results imply that the ruptured secondary fault can continue to ~20 km and kept slip after earthquakes. However, for the deeper lower crust and upper mantle, the material keeps the same strength across the northeastern boundary of Bayankara block.

How to cite: Li, Z., Xiong, W., Zhao, Z., and Wang, T.: Deep fault structure and lower crust rheology beneath the northeastern Bayankara block revealed by post-seismic deformation following the 2021 Mw 7.4 Maduo Earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20075, https://doi.org/10.5194/egusphere-egu24-20075, 2024.

EGU24-1664 | Orals | NH6.6 | Highlight

The Increasing Impact of Climate Change on coastal-fluvial Extremes and Severity of Compound Flood Events in UK Estuaries 

Pete Robins, Charlotte Lyddon, Chien Nguyen, Grigorios Vasilopoulos, Mirko Barada, Andrew Barkwith, Gemma Coxon, Laura Devitt, and Thomas Coulthard

Estuarine flooding is driven by extreme sea-levels and river discharge, either occurring independently or at the same time, or in close succession to exacerbate the hazard, known as compound events. Understanding compound flooding in the face of climate change is crucial for anticipating and mitigating heightened risks. Rising sea levels, increased storm intensity, and changing precipitation patterns can amplify the simultaneous occurrence of extreme storm surges and river flows. It is necessary to assess changing patterns of timing and intensity in extreme storm-driven compound events to inform future incident and hazard management strategies. Understanding whether these events will intensify or diminish is crucial for adapting and developing effective mitigation measures.

 

This research represents the first time that projections of future sea-level, storm surge, and river discharge to assess changes in the magnitude and timing of storm-driven compound events in an estuary particularly vulnerable to compound flooding (Dyfi, west Wales). Sub-daily projections of river discharge from a hydrological model and sea level and residual surge from a shelf sea model are assessed independently to identify changes in their magnitude and return periods. Projections are then assessed in combination to identify future extreme dependence and timing of compound events. The analysis provides forcing conditions representative of a 1 in 20-year and 1 in 50-year event to simulate the impacts of future return periods in the Dyfi Estuary.

 

The research shows that more extreme river discharge and storm surges will occur up to 2100, and the severity of a 1 in 1-year to a 1 in 5-year event will become more severe into the future. There is a stronger likelihood of an extreme river discharge occurring at the same time as an extreme skew surge in the future, more often per storm season, and with greater dependence. Further to this, as storm-driven compound events become more prevalent in the future, the associated flood impacts are anticipated extend over larger areas and occur with increased severity.

 

This research presents a scalable methodology for comprehensive assessment and analysis of the future likelihood and impacts of storm-driven compound events, that can be applied worldwide where sub-daily river and sea level projection forced by the same global climate model are available.

How to cite: Robins, P., Lyddon, C., Nguyen, C., Vasilopoulos, G., Barada, M., Barkwith, A., Coxon, G., Devitt, L., and Coulthard, T.: The Increasing Impact of Climate Change on coastal-fluvial Extremes and Severity of Compound Flood Events in UK Estuaries, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1664, https://doi.org/10.5194/egusphere-egu24-1664, 2024.

EGU24-1860 | ECS | Posters on site | NH6.6

Site-Specific Thresholds for Storm-Driven Compound Flooding in UK Estuaries 

Charlotte Lyddon, Nguyen Chien, Grigorios Vasilopoulos, Michael Ridgill, Sogol Moradian, Indiana Olbert, Thomas Coulthard, Andrew Barkwith, and Peter Robins

Estuarine flooding is driven by extreme sea-levels and river discharge, either occurring independently or at the same time, or in close succession to exacerbate the hazard, known as compound events. Estuaries have their own dynamics, and different behavior means flooding will occur under different conditions. Recent UK storms, including Storm Desmond (2015) and Ciara (2020), have highlighted the vulnerability of mountainous Atlantic-facing catchments to the impacts of compound flooding including risk to life and short- and long-term socioeconomic damages. There is a need to identify site-specific thresholds for flooding in estuaries, which represent the magnitude of key drivers over which flooding occurs, to improve prediction and early-warning of compound flooding.

In this study, observational data and numerical modelling were used to reconstruct the historic flood record of an estuary particularly vulnerable to compound flooding (Conwy, North Wales). The record was used to develop a method for identifying combined sea level and river discharge thresholds for flooding using idealised simulations and joint-probability analyses. Only 6 records of known flooding are identified in the official record. The key limitation of using historic records of flooding is that not all flooding events have been documented, and there are gaps in the record. Therefore, this research also identified the top 50 extreme sea-level and river discharge events in the historic gauge measurements in the estuary, and cross-checked these against online sources using web scraping to establish if these additional 100 extreme events also led to flooding. A more comprehensive historic record of flooding allows more accurate thresholds for flooding to set in each estuary.

Caesar-LISFLOOD, a hydrodynamic flow and morphological evolution model, is used in a sensitivity test to simulate inundation under different idealized sea-level and river discharge conditions to further isolate accurate thresholds. The variation in flooded area from a baseline scenario is used to capture flood magnitude associated with each scenario. The results show how flooding extent responds to increasing total water level and river discharge, with notable amplification in flood extent due to the compounding drivers in some circumstances, and sensitivity due to a 3-hour time-lag between the drivers. Joint probability analysis is important for establishing compound flood risk behaviour. Elsewhere in the estuary, either sea state (lower-estuary) or river flow (upper-estuary) dominated the hazard, and single value probability analysis is sufficient. These methods can be applied to estuaries worldwide to identify site-specific thresholds for flooding to support emergency response and long-term coastal management plans.

How to cite: Lyddon, C., Chien, N., Vasilopoulos, G., Ridgill, M., Moradian, S., Olbert, I., Coulthard, T., Barkwith, A., and Robins, P.: Site-Specific Thresholds for Storm-Driven Compound Flooding in UK Estuaries, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1860, https://doi.org/10.5194/egusphere-egu24-1860, 2024.

EGU24-2010 | ECS | Posters on site | NH6.6

EU-Funded LIFE Projects Influence in Land Use/Land Cover Changes in Insular Ecosystems: The Case-Study of São Miguel Island (Azores) 

Rafaela Tiengo, Silvia Merino-De-Miguel, Alicia Palacios-Orueta, Jéssica Uchôa, and Artur Gil

Small oceanic islands, like São Miguel Island (Azores), show high vulnerability to climate change impacts, biological invasions, and land-use/land-cover changes that threaten their biodiversity and affect their ecosystem functions and services. Organized and long-term nature conservation actions and projects such as those funded by the EU LIFE Programme have been fundamental to mitigating biodiversity loss in the eastern part of São Miguel Island since 2003. The use of remote sensing-based approaches may constitute a cost-effective way to support the management, monitoring, and control of these LIFE projects. In this work, a land-use/land-cover change detection approach focusing on the 2003-2022 LIFE Projects intervention areas was applied by using the RAO’s Q diversity index, which holds significant potential for monitoring the proliferation of invasive plant species and alterations in land use patterns. Using the ASTER, Landsat 8, and Sentinel-2 images from the Google Earth Engine on Google Colab and Python as the programming language, the average distribution of RAO’s Q diversity index values in the intervention areas was analyzed. The Normalized Difference Vegetation Index was calculated for the different years within the LIFE projects. The Classic Rao was calculated, giving the ability of this methodology to identify and evaluate diversity, making it possible to determine areas in which changes occurred in the project areas and the period in which these areas underwent interventions. By evaluating the effectiveness of conservation initiatives on small oceanic islands and archipelagos, we can gain insights into the ecological responses and long-term sustainability of these projects. This knowledge can inform future conservation strategies, contribute to the broader field of island conservation, and enhance our understanding of the unique dynamics and challenges associated with protecting biodiversity in insular environments.

How to cite: Tiengo, R., Merino-De-Miguel, S., Palacios-Orueta, A., Uchôa, J., and Gil, A.: EU-Funded LIFE Projects Influence in Land Use/Land Cover Changes in Insular Ecosystems: The Case-Study of São Miguel Island (Azores), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2010, https://doi.org/10.5194/egusphere-egu24-2010, 2024.

EGU24-2112 | Posters on site | NH6.6

Reasons of changes sediment movement near the Rioni river estuary 

Manoni Kodua, Ivane Saghinadze, and Mari Tebidze

Rioni river, which joins the Black Sea in the territory of Western Georgia, has undergone hydrological changes many times as a result of artificial intervention. Close to its estuary to the south is the port of the city of Poti, whose breakwater was extended by 1.8 km and approached closer to the estuary of the river Rioni.

The article discusses the influence of the construction of a breakwater at the mouth of the northern channel of the river Rioni on the movement of sediments along the shore.

The constancy of sediment mass balance condition was used to study the sediment transport rates in the coastal zone and the change in the topography of the seabed, based on this the equation of water depth change was obtained. The finite element method and Crank-Nicolson schemes are used to solve the developed equations. The seacoast near the Rioni Nabada delta is taken as the research area.

Based on the resulting equations, the numerical experiments are conducted using the values of the known hydrological and hydrometric parameters of the Rioni river and the sea coast.

The overbank and bank-directed sediment transport rates are determined. The amount of beach-forming sediment imported by the Rioni river is about 4 million m3 per year.

Numerical analysis shows that after the construction of the new port breakwater, the impact of southwesterly waves will be weakened to the north, the movement of sediment in the southern direction will be completely blocked, and 0.85 mln m3 volume of solid sediment will begin to settle in the north of the new Breakwater. In the case of the current hydrological and hydrometric parameters of the Rioni River, the accumulation of a large amount of sediment over time will lead to the blocking of the southern branch of the Nabada channel. Accordingly, the total flow of water from the channel will be shifted to the northern branch and the formation of a new delta will begin there.

All movement of fine sediments in this direction will be stopped, and solid sediments will begin to settle to the north of the new breakwater after the new breakwater is built. Ultimately, this will lead to the blocking of the southern branch of the Nabada channel. The entire flow of water from the Nabada channel will be diverted to the northern arm, and the formation of a new delta will begin there. The canyon is currently in equilibrium. A reduction in the supply of sediment may cause it to move towards the shore, which will interfere with the normal operation of the harbor.

How to cite: Kodua, M., Saghinadze, I., and Tebidze, M.: Reasons of changes sediment movement near the Rioni river estuary, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2112, https://doi.org/10.5194/egusphere-egu24-2112, 2024.

EGU24-3136 | ECS | Orals | NH6.6

Influence of groundwater in compound flooding in UK estuaries.  

Ankita Bhattacharya, Andrew Barkwith, and Peter Robins

Low-lying estuaries, deltas, and bays are especially prone to flooding from multiple sources of high river discharge, coastal flooding from waves and storm surges, and pluvial flooding from intense rainfall – with groundwater levels a lesser researched flood driver. When these drivers occur simultaneously or sequentially, they create a greater impact, and are referred to as Compound Flooding. Recent compound events such as Hurricane Katrina (New Orleans in 2005), Cyclone Nargis (Myanmar in 2008) or Storm Xynthia (French Atlantic coast in 2010) have been shown to result in significant loss of lives and properties in coastal lowlands. Globally, 2.15 billion people reside in near-coastal areas, with 898 million in low-elevation coastal zones.

The UK has a long history of estuarine flooding from compound events. UK climate projections indicate that there will be hotter and drier summers and prolonged wet winter periods, with an increase in the frequency and intensity of extreme storm surge and rainfall events that are also more likely to co-occur. Climate projections also indicate sea level rise at most locations around the UK which will make the coastal areas increasingly vulnerable. Groundwater is an important and dynamic component of the coastal environment. Coastal aquifers are vital fresh groundwater resources that are frequently subjected to coastal flooding due to increased runoff, storm surge and sea-level rise. Despite its lesser volumetric contribution in comparison with fluvial inputs, recent studies have found the presence and movement of groundwater may be both volumetrically and chemically important in river dominated coastal environments and requires future attention in view of climate change. Through our study we aim to investigate the different drivers influencing compound flooding in UK estuaries.

Our focus is on the Conwy estuary in North Wales, which is a flashy catchment that floods several times per season. A serious recent compound flood event was due to Storm Ciara (February 2020) where river gauges hit record levels and combined with intense rainfall and high storm tide, impacting 172 properties. River Conwy drains a catchment of nearly 600 km2 and includes large mountains with high annual precipitation of around 1700mm per year and a baseflow contribution of 27%. Baseflow, which is the contribution of groundwater to surface water components, is notably influenced by topography, geology, vegetation, land use, and climatic factors. In this study we will develop a coupled catchment and groundwater model in Caesar Lisflood to understand how groundwater processes in the form of the baseflow can influence compound flood events in the estuary. Model simulations are calibrated against past fluvial and tidal flows to show how the river discharge, groundwater and associated drivers are likely to influence the magnitude, behaviour, and timings of compound flooding in the future.

How to cite: Bhattacharya, A., Barkwith, A., and Robins, P.: Influence of groundwater in compound flooding in UK estuaries. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3136, https://doi.org/10.5194/egusphere-egu24-3136, 2024.

EGU24-4146 | ECS | Posters on site | NH6.6

Mapping Tidal Flat Changes and Determining Drivers in China's Coastal Zones: An Efficient and Reproducible Remote Sensing Method 

Yuekai Hu, Lin Yuan, Huifang Fan, Yuwen Pang, Yao Li, Qiannan Ding, Juntian Liu, Bo Tian, and Yunxuan Zhou

The dynamic coastal zones, marked by rich biodiversity and rapid transformations due to human activities, present a challenging environment for monitoring and management. Tidal flats, a key natural feature of these zones, are increasingly subjected to anthropogenic stress, rising sea levels, and various environmental pressures. This study addresses the critical need for a robust, large-scale remote sensing approach to monitor these changes over time, particularly under fluctuating tides and evolving coastal landscapes. Using the three decades of Landsat 5 and Landsat 8 data (1990-2020), we developed an innovative approach for the automatic acquisition of low-tide imagery. Our method, which incorporates knowledge-based of tidal flat extraction, achieved a classification accuracy of over 95%. This technique effectively mitigates the impact of clouds, fog, and waves on image analysis, enabling precise and rapid delineation of large-scale intertidal zones. As a result, we produced the most extensive dataset on tidal flat areas in China's coastal zone, updated at three-year intervals. The spatial analysis results showed the primary distribution of tidal flats in Liaoning, Shandong, Jiangsu, Zhejiang, and Guangxi, which collectively account for over 70% of China's tidal flat areas. We observed distinct patterns of tidal flat evolution, with rapid changes in regions like the Liaohe River Delta, Yellow River Delta, Yangtze River Delta, and the Jiangsu Coast. These changes are closely linked to increased reclamation activities and salt marsh vegetation expansion. In contrast, coastal areas like Tianjin and Zhejiang showed a swift expansion of intertidal zones initially, followed by a stabilization post-2010, constrained by limited development space. Our study's approach to rapid tidal flat extraction has shown promising applications in other global river deltas. The comprehensive tidal flat mapping and data generation presented here offer valuable insights and support for the monitoring, management, and sustainable development of coastal wetlands.

How to cite: Hu, Y., Yuan, L., Fan, H., Pang, Y., Li, Y., Ding, Q., Liu, J., Tian, B., and Zhou, Y.: Mapping Tidal Flat Changes and Determining Drivers in China's Coastal Zones: An Efficient and Reproducible Remote Sensing Method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4146, https://doi.org/10.5194/egusphere-egu24-4146, 2024.

EGU24-6436 | ECS | Orals | NH6.6

Alternative nature-based solutions for flood protection in a macrotidal estuary under a changing climate. 

Marta Payo Payo, Constantinos Matsoukis, Xiaorong Li, Elina Apine, Amani Becker, Sara Kaffashi, Marta Meschini, Francisco Calafat, Claire Evans, Kenisha Garnett, Stephen Jay, Simon Jude, Andy Plater, Leonie Robinson, Joana Zawadzka, Richard Dunning, Anil Graves, Tim Stojanovic, Jenny Brown, and Laurent Amoudry

Estuaries are complex and dynamic systems where physical and biological processes overlap with social and economic activities. Increasing coastal hazards and human pressure threaten the fragile equilibrium of these ecosystems. The combination of fluvial and coastal processes increases the probability of flooding in estuaries. Expanding urban development in these low-lying areas increases their exposure (i.e. the population, and the number and value of the coastal assets), which impacts the vulnerability of coastal communities and businesses. Traditionally, hard-engineered structures (i.e. grey defences) have been used to protect the coast from flooding risk. Nature-based solutions (i.e. green solutions) are now increasingly promoted to help remediate the growing costs and long-lasting impacts of grey defences, and to address the need for solutions that can balance the benefits for both nature and society and bridge social and economic interests. These green solutions have the potential to deliver both flood risk reduction, and other co-benefits such as habitat provision, spaces for recreation, or climate regulation. However, the shift towards green solutions is hindered by social and political resistance, by the difficulty to assess the co-benefits they offer, and by knowledge gaps in the level of flood protection they can provide under a changing climate.

Here, we explore management options that can mitigate or worsen flood hazards both now and in the future for the Ribble estuary, a macrotidal estuary in North West England. The Ribble estuary includes Hesketh Out Marsh, one of England’s most important estuarine bird habitats and one of the biggest (322ha) completed managed realignment schemes in the UK. We will present coastal inundation modelling results using the SFINCS (Super-Fast Inundation of CoastS, Deltares) model under a series of ‘what-if’ scenarios including alternative interventions, and future sea level rise. We tailored the experimental design by considering the coupled human-environment estuarine system. The chosen scenarios encompass a range of plausible interventions focusing on the managed realignment site of Hesketh Bank (e.g. no intervention vs managed realignment alternatives). We reviewed historic events with strong local narrative and legacy (e.g. near-miss event for storm Desmond in 2015). We chose the events so that they cover a range of compound fluvial and coastal hazards. We built on these historic events to explore mid to long term flooding risk under changing climate. For each scenario, we propagated nearshore the offshore conditions with the Delft3d model (Deltares). We then used the Delft3d outputs as inputs to the SFINCS model. The outcome is a library of flood maps, which can be overlapped with vulnerability or exposure data. This evidence can support coastal managers both on present day coastal management and on adaptation planning for environmental resilience.

How to cite: Payo Payo, M., Matsoukis, C., Li, X., Apine, E., Becker, A., Kaffashi, S., Meschini, M., Calafat, F., Evans, C., Garnett, K., Jay, S., Jude, S., Plater, A., Robinson, L., Zawadzka, J., Dunning, R., Graves, A., Stojanovic, T., Brown, J., and Amoudry, L.: Alternative nature-based solutions for flood protection in a macrotidal estuary under a changing climate., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6436, https://doi.org/10.5194/egusphere-egu24-6436, 2024.

EGU24-6937 | ECS | Posters on site | NH6.6

Spatial-temporal variation of estuarine acidification in the southeastern Yellow Sea, Korea 

Yujeong Choi, Hyebin Kim Kim, and Tae-Hoon Kim

Geographically, an estuary is a transition zone where river water and seawater mix. In estuaries, where river water and sea water meet, acidification can occur due to carbon dioxide (CO2) changes due to strong horizontal stratification, long residence time, eutrophication, and weak acid-base buffering capacity.

Despite the potential consequences, studies on acidification in Korean estuaries are notably scarce. This research focuses on the seasonal variations in aragonite saturation in the Han River estuary (an open estuary), and the Geum River and Yeongsan River estuaries (constrained by estuary dams) to assess the status of estuary acidification.

Seasonal changes in aragonite saturation (Ωarg) recorded values of 1.5±0.5, 1.8±0.8, and 2.1±0.4 at the mouths of the Han River (HRE), Geum River (GRE), and Yeongsan River estuaries (YRE), respectively. Acidification was weak at the YRE, where dissolved inorganic carbon and total alkalinity were high. Conversely, acidification was pronounced at the HRE, where dissolved inorganic carbon (DIC) and total alkalinity (ALK) were low. Remarkably, downstream areas of the estuary, particularly those near large cities like Seoul, exhibited heightened vulnerability to acidification.

In all three estuaries, aragonite saturation was lower in the upper reaches, influenced by river water with weaker acid-base buffering capacity than in the lower reaches. This underscores the potential for estuarine acidification to either worsen or alleviate based on future changes in the river's carbonate system, nutrient supply rates, and biological communities.

Should estuary acidification intensify, the buffering capacity of estuaries will be compromised, potentially leading to the transfer of acidification to the ocean. This research sheds light on the intricate dynamics of estuarine acidification and emphasizes the need for continued monitoring and understanding of these crucial ecosystems.

How to cite: Choi, Y., Kim, H. K., and Kim, T.-H.: Spatial-temporal variation of estuarine acidification in the southeastern Yellow Sea, Korea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6937, https://doi.org/10.5194/egusphere-egu24-6937, 2024.

EGU24-9306 | ECS | Posters on site | NH6.6

Predicting Coastal Flooding in the Mediterranean with Remote Sensing and Machine Learning 

Alice Re, Lorenzo Minola, Alessandro Pezzoli, and Gustau Camps-Valls

Due to its historically low tidal variations, the Mediterranean Sea basin has seen significant coastal urbanisation, exemplified in the densely populated Italian region Liguria. However, the region faces increased vulnerability to extreme sea level changes and coastal flooding due to potential climate change-induced storminess.

Machine learning has recently received increased attention in the literature as regards the ability of data-driven approaches to solve flood-related problems, including the identification of areas potentially susceptible to inundation in support of risk preparedness and resilience in coastal cities. This work explores the application of machine learning using widely available remote sensing datasets to predict the inundation extent for a modelled 100-year return period coastal flooding event in Liguria. Numerical simulations produced by local administrations in the context of the EU Floods Directive serve as ground truth due to the absence of post-event inundation maps. Various pre-processed remote sensing datasets are employed as predictors, including land cover data, spectral indices and high-resolution DEM.

The results highlight challenges in integrating diverse timescales and data types and can be used to assess the influence of predictors on coastal resilience. The study also addresses the benefits and drawbacks of different machine learning algorithms in evaluating coastal resilience within this approach.

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References

Woznicki, S. A., Baynes, J., Panlasigui, S., Mehaffey, M. and Anne Neale. “Development of a spatially complete floodplain map of the conterminous United States using random forest.” Science of the Total Environment 647 (2019): 942-953.

Ireland, Gareth, Michele Volpi, and George P. Petropoulos. "Examining the capability of supervised machine learning classifiers in extracting flooded areas from Landsat TM imagery: a case study from a Mediterranean flood." Remote sensing 7.3 (2015): 3372-3399.

Fogarin, S., et al. "Combining remote sensing analysis with machine learning to evaluate short-term coastal evolution trend in the shoreline of Venice." Science of The Total Environment 859 (2023): 160293.

Tsiakos, Chrysovalantis-Antonios D., and Christos Chalkias. "Use of Machine Learning and Remote Sensing Techniques for Shoreline Monitoring: A Review of Recent Literature." Applied Sciences 13.5 (2023): 3268.

Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., & Prabhat, F. (2019). Deep learning and process understanding for data-driven Earth system science. Nature, 566(7743), 195-204.

Camps-Valls, Gustau, et al., eds. Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences. John Wiley & Sons, 2021.

How to cite: Re, A., Minola, L., Pezzoli, A., and Camps-Valls, G.: Predicting Coastal Flooding in the Mediterranean with Remote Sensing and Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9306, https://doi.org/10.5194/egusphere-egu24-9306, 2024.

EGU24-9879 | Posters on site | NH6.6

Enhancing Coastal Infrastructure Resilience: three decades of InSAR Analysis of Nice Côte d’Azur Airport Subsidence 

Olivier Cavalié, Frédéric Cappa, and Béatrice Pinel-Puysségur

Coastal areas can be tremendously biodiverse and host a substantial part of the world’s population and critical infrastructure. However, there are often fragile environments that face various hazards such as flooding, coastal erosion, land salinization or pollution, earthquake-induced land motion, or anthropogenic processes. In this article, we investigate the stability of the Nice Côte d’Azur Airport, which has been built on reclaimed land in the Var River delta (French Riviera, France). This infrastructure, as well as the ongoing subsidence of the airport runways, has been a permanent concern since the partial collapse of the platform in 1979. Moreover, using InSAR data between 2003 and 2011, Cavalié et al. (2015) showed that parts of the airport platform were subsiding up to 10 mm/yr.

Understanding the mechanism and thus the evolution of sediment compaction is essential to evaluate the danger caused by the coastal subsidence. Therefore, in this study, we extended the observation period of InSAR measurements to better analyze the temporal evolution of the ground displacement on the Nice Côte d’Azur Airport platform in the hope of capturing the non-linear component of the deformation. Indeed, the relatively short period of observation (2003-2011) of the previous study (Cavalié et al., 2015) impeded the accurate detection of non-linearity in the surface displacement and thus to understand its dynamic. So, we used here the complete archive of SAR images acquired by ESA over a much longer period of time (28 years from 1992 to 2020).

Extending the observation window to study the long-term subsidence leads to substantial improvements in the understanding of the ongoing mechanisms along this coastal area. Indeed, the new analysis reveals a notable deceleration in the maximum downward motion rate, decreasing from 16 mm/yr in the 1990s to 8 mm/yr in the present day (for the fastest subsidence area).  We then used a simple analytical Burgers creep model to constrain the mechanisms and rheology at play. The data are properly explained by the phases of primary and secondary creep, highlighting a slow viscoelastic deformation at multiyear timescales.  Our study thus proves that the long-term InSAR data can improve our understanding of the surface processes and the subsurface material properties. Although the subsidence rate decelerates, at least for 28 years, our results show that the compaction of the sediment is still active and its future evolution is uncertain and still at stake. Indeed, if compaction bands are developing under the airport platform, creep processes could potentially lead accumulated material damage to failure.

This study underscores the critical role of remote monitoring in comprehending coastal land motion. We show here that employing advanced InSAR techniques offers a better understanding of actual hazards posed by the airport built on reclaimed lands. The findings advocate for ongoing monitoring initiatives to mitigate risks and enhance the resilience of coastal infrastructure.

How to cite: Cavalié, O., Cappa, F., and Pinel-Puysségur, B.: Enhancing Coastal Infrastructure Resilience: three decades of InSAR Analysis of Nice Côte d’Azur Airport Subsidence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9879, https://doi.org/10.5194/egusphere-egu24-9879, 2024.

EGU24-11728 | ECS | Posters on site | NH6.6

Dynamics of Coastal Extremes: Unravelling Estuarine Processes through Numerical Modelling 

Aaron Furnish, Peter Robins, and Simon Neill

Exploring the intricate relationships between land and marine processes is essential for a comprehensive understanding of climate dynamics. While contemporary coupled climate models have made significant progress in capturing various interactions, the explicit resolution of estuarine and intertidal processes remains a challenge. Building upon the foundation laid by the UKC3 UK national climate model, we present a novel perspective by incorporating a high-resolution (<20 m) flexible mesh model, Delft-3D, to specifically address intertidal and estuary regions.

Our study focuses on the dynamic eastern Irish Sea, marked by hyper-tidal conditions and hosting eight estuaries alongside a significant intertidal zone. Employing a comprehensive comparison between the Delft model and the UKC3 model, we emphasize the simulation of extreme water heights during the winter storm season of 2013-2014. The outcomes provide valuable insights into the capabilities of both models in capturing high-water levels, paving the way for future investigations.

Looking ahead, our research extends to incorporate the latest UKCP18 climate scenarios into the refined Delft model. This expansion allows us to explore potential variations in climate patterns and their implications for estuarine and coastal regions. The anticipated analysis aims to offer valuable insights into the impact of future climate change on these vital areas.

As a final objective, I plan to parameterize estuarine processes within the UKC3 coupled system using an estuarine box model. This simplified approach holds promise in resolving coastal extremes and fluxes for impact studies, marking a crucial step towards enhancing the overall accuracy of climate models in portraying estuarine dynamics.

How to cite: Furnish, A., Robins, P., and Neill, S.: Dynamics of Coastal Extremes: Unravelling Estuarine Processes through Numerical Modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11728, https://doi.org/10.5194/egusphere-egu24-11728, 2024.

EGU24-11761 | ECS | Posters on site | NH6.6

Statistical properties of water level extremes along the St. Lawrence fluvial estuary 

Silvia Innocenti, Pascal Matte, Remi Gosselin, Mouna Doghri, Caroline Sevigny, Olivier Champoux, and Jean Morin

The governmental Flood Hazard Identification and Mapping Program (FHIMP) seeks to update standards for flood mapping and risk area definition in Canada. Within this initiative, Environment and Climate Change Canada (ECCC) has been mandated to provide 2D simulations of water levels in the St. Lawrence fluvial estuary to estimate return periods of extreme water levels under historical and future conditions. Long-term fine-scale hydrodynamic simulations are necessary to reproduce accurately the complex interplay of hydrological, meteorological and tidal processes responsible for extreme water levels in this system. However, the substantial computational resources and time needed to run the hydrodynamic numerical models constrain the feasibility of producing numerous long-term simulations with a wide range of potential flood-generating conditions. Consequently, this study considers a complementary statistical framework to assess the extreme characteristics and drivers from historical data to prepare input scenarios for climatic projections. 

Event-based analyses of water level records are conducted at 18 stations across the St. Lawrence system using univariate and multivariate techniques to characterize the observed extreme dynamics and flood events. Specifically, univariate frequency analysis is applied at each station to quantify local flood risk based on approximately 400 extreme events observed in the Estuary between 1972 and 2022. Multivariate investigations based on a non-stationary tidal harmonic regression tool (NS Tide) are then used to study the system dynamics involved in major observed events and reconstruct the extreme water level series using a set of hydrological, meteorological, and astronomical covariates. Finally, multivariate spatial analyses are performed on the identified extreme events and NS Tide continuous reconstructions. The goal is to assess the characteristics of high water-level events (e.g., duration, seasonality, and probability distribution) and extreme drivers at the local and regional scales.

How to cite: Innocenti, S., Matte, P., Gosselin, R., Doghri, M., Sevigny, C., Champoux, O., and Morin, J.: Statistical properties of water level extremes along the St. Lawrence fluvial estuary, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11761, https://doi.org/10.5194/egusphere-egu24-11761, 2024.

EGU24-12667 | Orals | NH6.6

Satellite optical imagery: towards fully integrated measurements of the coastal zone. 

Erwin Bergsma, Stephanie Artigues, Rafael Almar, Adrien Klotz, and Thierry Garlan

Space-based coastal observations are emerging as satellite imagery becomes more freely available through large-scale programs such as Landsat and Copernicus. Remote sensing techniques enable large-scale, even global, studies with sufficient spatio-temporal resolution, given that, for example, optical satellite imagery from the Sentinel-2 program has a global coastal coverage of up to 20 km offshore and a revisit of 2 to 5 days. The availability of data combined with accessible tools has enabled an explosion in space-based observations, even if these observations now go beyond the research phase alone and can support large-scale decision-making (see, for example, the Space Climate Observatory). However, most spaceborne applications for the coastal zone focus on useful but indirect proxy indicators such as waterline estimation. Submerged bathymetry and emergent topography are often not taken into account, even though they are essential for the usage and forecasting with of process-based models. Here, we present current work by the French Space Agency in collaboration with LEGOS and Shom on the future of space-based coastal observations: total, fully integrated monitoring of the coastal zone from space. This includes simultaneous measurements of bathymetry, coastline and topography at multiple spatial and temporal scales. Sentinel-2's large-scale bathymetry estimation and coastline detection, complemented by 3D topography using very high-resolution Pleiades images, offer a solution for monitoring the coastal zone from space over large regional scales. All these components of coastal monitoring are open-source, such as the CNES CARS routines for DEM 3D topography estimation, the CNES-IRD-SHOM S2SHORES bathymetry estimation. While focusing on current capabilities, we will also present prospects for future Earth observation missions, such as CO3D, and new capabilities for obtaining fully integrated measurements in a single satellite pass.

How to cite: Bergsma, E., Artigues, S., Almar, R., Klotz, A., and Garlan, T.: Satellite optical imagery: towards fully integrated measurements of the coastal zone., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12667, https://doi.org/10.5194/egusphere-egu24-12667, 2024.

EGU24-13318 | ECS | Posters on site | NH6.6

Use of Sentinel-1 SAR data in assessing the accuracy of LISFLOOD-FP in modelling (compound) flooding in estuaries 

Mirko Barada, Peter Robins, Martin Skov, and Matthew Lewis

Estuaries are among most vulnerable parts of our planet in terms of flood risk because they are constantly exposed to flood sources from at least two directions. While different flood modelling tools are helping us to be better prepared for flood events, state-of-the-art space technologies are providing useful high resolution (temporal and spatial) data to quantify and monitor real flood impacts and consequences, regardless of night and cloudiness.

In this study we are: a) applying LISFLOOD-FP hydrodynamic model for modelling compound flood event in the Dyfi estuary, Wales (UK) and b) using Sentinel-1 SAR data to map flood event from the same period and to validate flood inundation model. The selected flood event (> 300 m3/s and around 70 cm surge) caused large flooding along the estuary, particularly in the upper parts. Modelled results are shown as water surface elevation and water depth classified raster maps, which are used later for comparison with the SAR image.

Raw Sentinel-1 SAR (GRD) image downloaded from Copernicus Browser had to be pre-processed in ArcGIS PRO (The Synthetic Aperture Radar toolset) to remove unwanted noise and correct distortions. Further, RGB color composite was produced from the calibrated SAR image and used for extracting water bodies/flooded areas. It was achieved by applying deep learning tools integrated in ArcGIS PRO which classify pixels (wet/dry) based on a previously trained sample. Resulting raster was then compared with the modelled flood extent, quantifying the differences. Matching was very good in the upper parts where major flooding was recorded (> 80 % agreement), while the model was slightly less accurate in the lower estuary and along the salt marsh zone due to larger DEM uncertainty in those areas. However, when selected shallow areas (e.g. 0-1 cm or 0-2 cm class) were removed from the model, matching between modelled and observed flood extent was higher.

How to cite: Barada, M., Robins, P., Skov, M., and Lewis, M.: Use of Sentinel-1 SAR data in assessing the accuracy of LISFLOOD-FP in modelling (compound) flooding in estuaries, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13318, https://doi.org/10.5194/egusphere-egu24-13318, 2024.

EGU24-17509 | ECS | Orals | NH6.6

Assessing Coastal Resilience from Space 

Arjen Luijendijk, Etienne Kras, and Floris Calkoen

Satellite imagery proves to be a promising data source to gain insights in historic shoreline behavior over the last 4 decades on a global scale. To enable the use of such a large amount of satellite data, image processing techniques are introduced to interpret such large datasets. Furthermore, Machine Learning (ML) algorithms allow for an extra in-depth understanding of the shoreline dynamics, while growing computational power and standardization of ML packages, opens possibilities for studying shoreline dynamics and their drivers on a global scale.

In this way, human drivers, such as nourishments, ports, coastal structures, and natural drivers, such as relative sea level rise, inlet systems, and storms, can be identified across the globe. The high spatial and temporal resolution of this information yields more comprehensive understanding of our coasts and their resilience to cope with a changing climate. This is not only of great added value in data-poor environments, but it will also allow for more cost-effective coastal monitoring in data rich environments as the necessity of in-situ measurements will reduce in future. Furthermore, information on the governing drivers for local coastal change is one of the key elements required for shoreline predictions.

Providing such a prediction for future shoreline positions is just one example of a climate service. To prepare coastal zones for a changing climate in the future, coastal managers are demanding various other climate services to efficiently access and use state-of-the-art data on projections related to flooding, erosion, subsidence, vulnerability of assets and adaptation measures. The CoCliCo platform will be presented that fulfils the stakeholder needs by providing climate services at a pan-European scale.

How to cite: Luijendijk, A., Kras, E., and Calkoen, F.: Assessing Coastal Resilience from Space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17509, https://doi.org/10.5194/egusphere-egu24-17509, 2024.

EGU24-17702 | ECS | Posters virtual | NH6.6

Assessing Shoreline Dynamics under Macro to Meso-tidal Conditions through Integrative low-cost Remote Sensing Technique 

khurram riaz, Marion McAfee, and Salem Gharbia

Coastal erosion, a critical issue in shoreline management, arises from a combination of natural dynamics and anthropogenic influences. In macro to meso-tidal regions, this phenomenon is particularly pronounced due to the interplay of sea level fluctuations, erosive wave action, and sediment displacement. Significantly, this erosion poses a direct threat to the stability and integrity of coastal dunes, which are vital for protecting inland areas and maintaining ecological balance on these beaches. This study addresses this issue by analysing shoreline changes over the past decade at three unmanaged Northwest beaches of Ireland: Enniscrone, Streedagh, and Dunmoran. Utilising open-source satellite imagery, the research employed the CoastSat and DSAS tools to extract data on shoreline movement to tackle coastal erosion or accretion. Acknowledging the errors in satellite-derived shoreline data due to high tidal variations, the study further validates its findings with field data. This validation was performed using two contrasting technological approaches: a high-cost LiDAR-equipped drone (DJI Terra drone and DJI Zenmuse L2 Lidar) and a low-cost DJI Phantom 4 RTK drone with a standard camera. The comparison of data from these diverse sources reveals crucial insights. Firstly, the study validated shoreline changes detected by satellite imagery, ensuring the consistency and reliability of observed trends across different remote sensing platforms. Additionally, the comparison between high-cost and low-cost drone data was instrumental in assessing their respective efficacies in capturing coastal topography. The high-resolution LiDAR data offered detailed 3D models of the coastal landscape, allowing for precise measurements of dune morphology and erosion patterns. In contrast, the standard camera on the low-cost drone provided broader, less detailed views but was surprisingly effective in identifying larger-scale changes and erosion hotspots. The study highlights the potential of integrating various remote sensing techniques for coastal monitoring, which provides a cost-effective and accurate way of assessing the coastal erosion in Macro to Meso-tidal beaches.

How to cite: riaz, K., McAfee, M., and Gharbia, S.: Assessing Shoreline Dynamics under Macro to Meso-tidal Conditions through Integrative low-cost Remote Sensing Technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17702, https://doi.org/10.5194/egusphere-egu24-17702, 2024.

EGU24-17886 | ECS | Orals | NH6.6

Unlocking the potential of observations in shoreline modelling through data assimilation 

Moisés Álvarez-Cuesta, Alexandra Toimil, and Iñigo Losada

Analyzing the coastal response is a complex problem that usually requires the use of numerical modelling in combination with observations (Alvarez-Cuesta et al., 2023). To this end, data assimilation is a useful tool to blend observational data and models to produce more accurate forecasts.

Here, the performance of different data assimilation algorithms in predicting multiscale shoreline dynamics is studied. Two statistical algorithms based on the Kalman filter (Alvarez-Cuesta et al., 2021) and one variational algorithm named 4DVar (LeDimet, F-X. & Talagrand, O., 1986) are employed together with an equilibrium cross-shore model and a one-line longshore model. A twin experiments procedure is performed to obtain the observation requirements for the different assimilation algorithms in terms of accuracy, length of the data collection campaign and sampling frequency. Similarly, the initial system knowledge needs and the ability of the different assimilation methods to track the system non-stationarity are evaluated under synthetic scenarios.

 With noisy observations, the Kalman filter variants outperform the 4DVar. However, the 4DVar is less restrictive in terms of initial system knowledge and tracks nonstationary parametrizations more accurately for cross-shore processes. Results are demonstrated at two real beaches governed by different processes with different data sources used for calibration and stress the need for assimilating shoreline observations to produce robust forecasts.

REFERENCES

Alvarez-Cuesta, M., Losada, I. J. & Toimil, A. (2023). A nearshore evolution model for sandy coasts: IH-LANSloc. Environmental Modelling and Software, 169, 105827

Alvarez-Cuesta, M., Toimil, A., & Losada, I. J. (2021). Modelling long-term shoreline evolution in highly anthropized coastal areas. Part 1: Model description and validation. Coastal Engineering, 169(July), 103960.

LeDimet, F-X. & Talagrand, O. (1986). Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus a 38.2: 97-110.

How to cite: Álvarez-Cuesta, M., Toimil, A., and Losada, I.: Unlocking the potential of observations in shoreline modelling through data assimilation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17886, https://doi.org/10.5194/egusphere-egu24-17886, 2024.

EGU24-18225 | Posters on site | NH6.6

CoastSnap community beach monitoring: new innovations in smartphone-based monitoring of the coast 

Mitchell Harley, Fred Chaaya, and Michael Kinsela

CoastSnap is a low-cost citizen science beach monitoring program that empowers local communities to collect quantitative measurements of coastline change using their smartphones. Underpinning CoastSnap is a stainless-steel smartphone cradle that is installed overlooking a beach in a location easily accessible to the public. Using the cradle for image positioning, passers-by simply take a photo of the coast and upload it to a centralized database, which in turn provides a crowd-sourced record of coastline change over time.

Behind this simple idea are advanced image processing algorithms that then enable the shoreline position (and other relevant coastal features) to be mapped from these community snapshots in a scientifically rigorous manner. First established in Sydney, Australia in May 2017, the network of CoastSnap stations has grown rapidly over the past seven years to now encompass over 350 monitoring locations in 31 countries. This growth of this global network now means that the CoastSnap project comprises the largest coordinated network of coastal monitoring worldwide.

The poster will provide a general overview of this unique global citizen science program to date and present latest developments regarding enhanced automation using AI, participation and new research outcomes.

How to cite: Harley, M., Chaaya, F., and Kinsela, M.: CoastSnap community beach monitoring: new innovations in smartphone-based monitoring of the coast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18225, https://doi.org/10.5194/egusphere-egu24-18225, 2024.

Estuaries are known as transition zones which modulate the freshwater inputs into the sea, with ocean salt water entering the river mouth and merging with the zero-salinity river streamflow. Understanding their dynamics is important for several purposes including the estimate of the salinization of inland waters and the effects in the thermohaline variability of the shelf to the open sea. The Copernicus Service Evolution Project EstuarIO proposes a low-to-high complexity modeling of the estuaries by  merging 1D box and 3D unstructured modeling approaches. The final aim is to better represent the river release (in terms of runoff, temperature and salinity) within the Copernicus forecasting Centres over the Southern European Seas. A source of uncertainty is that most estuaries are poorly monitored, river discharge measurements are taken far from river outlets, and salinity and temperature at the river mouths are mostly unknown. One of the EstuarIO objectives is to strengthen the calibration and validation of the estuarine models applied to target sites (Rhone, Po, Ebre and Danube deltas), using water temperature and salinity data derived from EO satellites. Landsat 8 and 9, along with other data sources such as MODIS are used as preliminary data sources for the riverine and coastal surface temperature (ST). The Landsat scenes used in the study were the L1TP (calibrated top-of-atmosphere reflectance and brightness temperature) data, with a combined repeat coverage of 8 days and spatial resolution of 30 m for the Operational Land Imager (OLI) multispectral bands and 100 m resampled to 30 m for the Thermal Infrared Sensors (TIRS) bands. Atmospheric correction and cloud masking were applied before retrieving the ST values. Current results suggest that the Landsat 8 and 9 imageries can be utilized to obtain high-resolution riverine and coastal ST data. A multilayer perceptron neural network based (MPNN) model is under testing in the target estuaries to estimate SSS values with in situ observations as benchmark to judge this innovative approach. Preliminary results on SSS extraction will be presented as well.

How to cite: Faelga, R. A., Verri, G., and Silvestri, S.: Water surface temperature and salinity estimation from EO satellites for estuarine dynamics assessment in the Mediterranean and Black Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19590, https://doi.org/10.5194/egusphere-egu24-19590, 2024.

EGU24-19824 | ECS | Orals | NH6.6

Advanced Insights into Coastal and Estuarine Environments: Key Fine Targets Analysis through Automated 2D and 3D Techniques 

Jianru Yang, Kai Tan, Shuai Liu, Ruotong Zhou, Yuekai Hu, and Weiguo Zhang

Coastal inshore areas, recognized as invaluable yet vulnerable, are experiencing shifts between various states due to gradual environmental changes and artificial disturbance. These transitions, however, are often imperceptible with large-scale mapping or through on regional in situ surveying when using traditional techniques. Advanced 2D and 3D technologies, particularly high-resolution remote sensing (HRRS) and LiDAR, offer novel perspectives that unveil fine details and precise vertical 3D structure of coastal ingredients. These technologies enable early, rapid, and accurate identification of significant transient or persistent patterns. Additionally, machine learning (ML), encompassing parametrized algorithms, ensemble learning (EL), and deep learning (DL), provides a unique advantage for automated observation.

 

This work aims to advance the observation of key fine components in coastal inshore areas by designing automated methods and frameworks. It considers both natural and human-made sources as targets. with the focus of Poaceae and marine debris.

 

First, an automated 3D recognition of stalks and leaves for Poaceae in coastal mudflats. Poaceae species (Giant reed and reed) in coastal mudflats hold ecological importance and serve as indicators. However, obtaining their phenotypic parameters like stalks and leaves is challenging. Our new automated, parametrized algorithm recognizes stalks and leaves of individual Poaceae plants in coastal wetlands using terrestrial LiDAR point clouds, leveraging radiometric and geometric features.

                                                                                   

Second, a new framework for comprehensive surveying of coastal Fairy Circles (FCs). FCs, predominantly formed by Poaceae, are self-organized patterns linked to recovery processes and salt-marsh resilience. Our new framework aims for automated surveying of coastal FCs, utilizing ML methods (which includes state-of-the-art foundation model, EL, and DL methods) on 2D and 3D data (satellite-borne and airborne). It is grounded in clear principles of FCs' definition and dynamics, potentially revolutionizing our understanding of coastal FCs behavior.

 

Third, an automated method for 2D and 3D recognition of marine debris across complex scenarios. Marine debris in coastal environments poses significant ecological and environmental issues and has garnered widespread concern. Our new method detects and extracts marine debris from terrestrial LiDAR point clouds or UAV HRRS imagery, combining calibrated radiometric data with geometric features.

                         

Fourth, we have developed a series of mathematical models for instrumentation and data processing to achieve these goals. We proposed generalized rigorous model to mathematically correct the density variation in terrestrial LiDAR point clouds, the novel distribution pattern features, and a model to eliminate the specular effect on UAV LiDAR point cloud intensity.

                                                                                 

How to cite: Yang, J., Tan, K., Liu, S., Zhou, R., Hu, Y., and Zhang, W.: Advanced Insights into Coastal and Estuarine Environments: Key Fine Targets Analysis through Automated 2D and 3D Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19824, https://doi.org/10.5194/egusphere-egu24-19824, 2024.

The escalating threats of climate change, compounded by seismicity along the ring of fire, pose significant challenges to the Pacific Island Countries (PICs), making them particularly susceptible to the impacts of natural hazards. This commentary explores the potential of Artificial Intelligence (AI) and satellite technology in enhancing resilience, focusing on their application in early warning systems and response/recovery for these vulnerable regions. The integration of these digital technologies can revolutionize the way PICs predict, respond to, and recover from climate- and seismic-induced catastrophes, thereby strengthening their resilience. It also discusses the future prospects for AI and satellite technology in PICs and concludes by highlighting the importance of international cooperation to ensure that PICs can benefit from these technologies.

How to cite: Kim, J. and Shm fakhruddin, B.: Empowering Pacific Island Countries against Climate Change: The Role of AI and Satellite Technology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16, https://doi.org/10.5194/egusphere-egu24-16, 2024.

EGU24-1408 | ECS | Orals | NH6.7 | Highlight

The Need for Utilizing AI in Locating Trapped Victims Following Earthquakes and Floods 

Ronnen Avny and Menachem Friedman

The present article delves into the necessity of employing artificial intelligence (AI) in locating individuals trapped during natural disasters such as earthquakes and floods. By utilizing unmanned equipment for reconnaissance and support tasks during search and rescue missions, lives can be saved, and the process expedited. Natural disasters have resulted in significant financial losses and loss of human lives, making it imperative to develop efficient and effective methods for rescue operations. The article emphasizes the benefits of using Trapped Victims Location (TVL) systems, including improved response times, increased accuracy, enhanced situational awareness, and improved safety for first responders. Furthermore, the article discusses the current TVL technologies available, such as visual cameras, acoustic sensors, thermal imaging cameras, radar sensors, GPRS, Cellular receivers, and more. The article also highlights the operational gaps within first responders' systems for locating trapped victims and discusses the specific operational needs for various scenarios. This work serves as a basis for further scientific and engineering projects that can overcome existing gaps and enhance the operational process of locating victims during emergencies, significantly improving accuracy and the likelihood of locating live individuals while expediting the entire procedure.

How to cite: Avny, R. and Friedman, M.: The Need for Utilizing AI in Locating Trapped Victims Following Earthquakes and Floods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1408, https://doi.org/10.5194/egusphere-egu24-1408, 2024.

Xiaojin County, Sichuan Province, China was selected as the study area of this paper, and twelve conditioning factors were determined according to the literature review. The spatial correlation between landslide and conditioning factors is analyzed using the weights-of-evidence (WoE) model, and the landslide susceptibility in Xiaojin county is predicted. The landslide susceptibility in this region was mainly assessment by WoE based random forest (RF) model. The radial basis function network (RBFNetwork) model was also exploited to map landslide susceptibility with the identical datasets. Finally, the landslide susceptibility maps were produced, and the comprehensive performance of the three models was quantitatively evaluated and compared by the receiver operating characteristic (ROC) curves and area under curve (AUC) values. The results show that the three models are suitable for landslide susceptibility evaluation in the study area, and the evaluation effect of the WoE model is better than that of the RF and RBF network models. More concretely, the goodness-of-fit values of the WoE, RF and RBFNetwork models in the training dataset are 0.899, 0.880 and 0.866, respectively. In terms of prediction accuracy, AUC values are 0.892, 0.874 and 0.863 respectively. Additionally, mean decrease accuracy (MDA) and means decrease Gini (MDG) are used to quantify the importance of landslide conditioning factors. Elevation, soil, distance to roads and distance to rivers are considered as the most important conditioning factors in landslide susceptibility modeling. Consequently, the study achievements in this paper have reference significance on the development and exploitation of land resources in Xiaojin County.

How to cite: Zhao, X. and Chen, W.: Landslide susceptibility modeling using data-driven weights-of-evidence based random forest and radial basis function network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7006, https://doi.org/10.5194/egusphere-egu24-7006, 2024.

The world has experienced the profound and devastating consequences of floods on human life, prompting a shift from mere academic examination to a critical socio-political imperative. To initiate effective flood risk management, many nations are working on creating user-friendly tools to identify flood-prone areas across extensive watersheds. Recently, Geomorphic Flood Descriptors (GFDs), which rely on the characteristics of the river drainage and are computationally less demanding, have been used as an efficient alternative to complex hydraulic models. However, validating the flood inundation maps from GFDs remains a major challenge, especially for ungauged watersheds that limit the adoption of data-intensive hydraulic modeling. In addition, as weather patterns and climate variations incur significant heterogeneity in flood patterns over large watersheds, we need to find error-free benchmark maps to validate the GFDs. The present study explores the suitability of Ensemble Machine Learning (ML) models to represent flooding at high resolution over large ungauged watersheds, thus paving the major research gap of authenticating the GFD-derived flood map with ground truth in ungauged basins. A suite of about 25 flood-influencing factors incorporating geomorphological, climatological, and soil parameters such as the Geomorphic Flood Index (GFI), Topographic Wetness Index (TWI), Height Above the Nearest Drainage (HAND), Slope, Stream Power Index (SPI), rainfall, soil type, and horizontal distance from the stream, etc., were derived from a high-resolution DEM (CartoDEM, resolution~30m). The two most prominent tree-based machine learning (ML) techniques, Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were employed to simulate flood inundation at a fine scale of 30m in the severely flood-prone Mahanadi basin. An ensemble of linear model, random forest, and support vector machine models were further tested for geographical extrapolation which quantified the flood hazard in an ungauged basin, which was lagged by tree-based models. These ML models were trained using a flood inundation map derived from LISFLOOD-FP using the ERA5 reanalysis dataset. The performance of the GFD-derived flood map is tested against the LISFLOOD-FP flood map through a set of performance statistics. The performance of the model developed was evaluated using Area Under the receiver operating characteristics curve (AUC), kappa coefficient, precision, recall, and F1 score, while RMSE and KGE were used for regression models. The ambiguous nature of ML models was also estimated using SHAP values to justify the degree of influence of each GFD on flood depth. The ongoing research also inspires to the development of a global flood inundation atlas using RCMs, which can be used to compare and validate inundation over large regions through geomorphic analysis. Any uncertainty in flood inundation estimates may amplify largely while quantifying flood risk, including vulnerability and exposure dimensions.

Keywords: Flood hazard, Geomorphic Flood Descriptors, LISFLOOD-FP, Machine Learning, SHAP

How to cite: Mohanty, M. and Tripathi, V.: Can Catchment attributes coupled with an Ensemble of Machine Learning improve Flood Hazard mapping over large data-scarce catchments?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9063, https://doi.org/10.5194/egusphere-egu24-9063, 2024.

EGU24-9683 | ECS | Posters virtual | NH6.7

Integrating XBoost and SHAP for Enhanced Interpretability in Landslide Susceptibility Assessment: A Case Study in North-western Peloponnese, Greece. 

Maria Sotiria Frousiou, Ioanna Ilia, Dimitrios Kasmas, and Ioanna Petropoulou

Landslide phenomena, acknowledged as significant geohazards affecting both human infrastructure and the natural environment, have been the
subject of intensive research aimed at pinpointing areas at risk of instability. This task involves the complex modelling of variables related to landslides, which requires both knowledge-based and data-driven methodologies. The challenge is heightened by the often intricate and obscure processes that trigger landslides be they natural or anthropogenic. Over the past two decades, the application of artificial intelligence, specifically machine learning algorithms, has brought a transformative approach to landslide susceptibility evaluations. These advanced methodologies, encompassing fuzzy logic, decision trees, artificial neural networks, ensemble methods, and evolutionary algorithms, have demonstrated notable accuracy and dependability. A significant recent development in this field is the incorporation of eXplainable AI (XAI) techniques into landslide susceptibility models. XAI tools, such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), offer a window into the previously opaque decision-making processes of AI models, thus demystifying the "black box" aspect of conventional AI systems.

The primary aim of this study was to employ the XBoost algorithm and integrate SHAP methods for an in-depth landslide susceptibility assessment. The methodology was methodically divided into five distinct phases: (i)the creation of the inventory map, (ii)the selection, classification, and weighting of landslide-influencing variables, (iii)conducting multicollinearity analysis, (iv)applying and testing the developed model, and (v)evaluating the predictive performance of various models and analyzing the results.

The computational work was performed using coding languages R and Python, while ArcGIS 10.5 was instrumental in compiling data and producing detailed landslide susceptibility maps. This study's efficiency was tested in the North-western Peloponnese region of Greece, known for its frequent landslide occurrences. Nine specific variables were considered: elevation, slope angle, aspect, plan and profile curvature, distance to faults, distance to river networks, lithology and hydrolithology cover and landslide locations, all contributing to the generation of training and test datasets. The Frequency Ratio method was applied to discern the correlation among these variables and assign weight values to each class. Multi-collinearity analysis further helped in identifying any collinearity among the variables.

SHAP values were utilized to rank features according to their importance, offering a transparent view of variable contributions. The evaluation phase involved calculating the model's predictive power using metrics like classification accuracy, sensitivity, specificity, and the area under the success and predictive rate curves (AUC). This comprehensive approach combining XBoost and SHAP methods presents a refined model for understanding and predicting landslide susceptibility, aiming for more accurate and interpretable hazard assessments. The results highlight the high performance of the XBoost algorithm, in terms of accuracy, sensitivity, specificity and AUC values. SHAP method indicates that slope angle was the most important feature in this model for landslide susceptibility. Other features such as elevation, distance to river network, and lithology cover also contribute to the model's predictions, though to a lesser extent and with more mixed effects. Aspect, profile curvature, plan curvature, distance to fault, and hydrolithology cover appear to have a more moderate or minimal impact on the model’s predictions. 

How to cite: Frousiou, M. S., Ilia, I., Kasmas, D., and Petropoulou, I.: Integrating XBoost and SHAP for Enhanced Interpretability in Landslide Susceptibility Assessment: A Case Study in North-western Peloponnese, Greece., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9683, https://doi.org/10.5194/egusphere-egu24-9683, 2024.

EGU24-11739 | ECS | Posters virtual | NH6.7

Leveraging Near Real-Time Remote Sensing and Explainable AI for Rapid Landslide Detection: A Case Study in Greece 

Aikaterini-Alexandra Chrysafi, Paraskevas Tsangaratos, and Ioanna Ilia

Landslides, triggered by severe rainfall events, pose significant risks to both life and infrastructure. Timely and accurate detection of such landslides is crucial for effective disaster management and mitigation. This study presents an innovative approach combining near real-time remote sensing data with advanced machine learning techniques to rapidly identify landslide occurrences following severe rainfall events, specifically focusing on a recent case in Greece.
Our methodology harnesses the capabilities of pre and post-event satellite imagery to capture the landscape's transformation due to landslides. We compute remote sensing indices, including the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI), among others, to detect changes indicative of potential landslide areas. This approach leverages the temporal resolution and wide-area coverage of satellite data, enabling a swift and comprehensive assessment immediately after a triggering rainfall event.
To enhance the accuracy of our detection model and reduce false positives, we incorporate a landslide susceptibility map generated via a Weight of Evidence (WoE) model. This map is based on historical landslide occurrences and helps to exclude areas with very low to low susceptibility, thereby refining our detection process.
Central to our study is the implementation of an eXplainable AI (XAI) framework. This aspect is particularly crucial, as it provides insights into the influence of various landslide-related factors on the model's predictions. The factors considered include elevation, slope angle, aspect, plan and profile curvature, distance to faults and river networks, lithology, and hydrolithology cover. By employing XAI techniques, we unravel the complex interactions between these variables and their relative importance in predicting landslide occurrences. This not only enhances the trustworthiness and transparency of our model but also aids in understanding the underlying geophysical processes leading to landslides.
The model's architecture is built upon advanced machine learning algorithms capable of processing large datasets efficiently. This setup is particularly suited to handle the high-dimensional and multi-temporal nature of remote sensing data. Furthermore, the model's ability to rapidly process and analyze data aligns well with the urgency required in disaster response scenarios.
Our case study in Greece demonstrates the model's efficacy in rapidly identifying landslide-prone areas post-severe rainfall events. The results show a significant improvement over traditional methods in terms of speed and accuracy. Moreover, the inclusion of XAI provides valuable insights for local authorities and disaster management teams, enabling them to make informed decisions for emergency response and long-term land-use planning.
This research contributes to the evolving field of rapid landslide detection by integrating cutting-edge remote sensing technologies with the latest advancements in machine learning and AI interpretability. It offers a novel, efficient, and transparent approach to landslide detection, which is vital for enhancing disaster preparedness and resilience in landslide-prone regions.

How to cite: Chrysafi, A.-A., Tsangaratos, P., and Ilia, I.: Leveraging Near Real-Time Remote Sensing and Explainable AI for Rapid Landslide Detection: A Case Study in Greece, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11739, https://doi.org/10.5194/egusphere-egu24-11739, 2024.

EGU24-12368 | Orals | NH6.7

The deployment of an integrated suite for wildfire prediction, near real-time fire monitoring and post-event mapping over Attica region, Greece. 

Nikolaos S. Bartsotas, Stella Girtsou, Alexis Apostolakis, Themistocles Herekakis, and Charalampos Kontoes

In a changing climate, the growing frequency and intensity of wildfires requires innovative services in order to efficiently remediate against their catastrophic socioeconomic threat. Under the framework of MedEWSa project, we capitalise upon the reliability of the FireHub platform to further enhance its capability and features along the full spectrum of pre-event to post-event time scales, catering: (i) prevention and preparedness, (ii) detection and response, as well as (iii) restoration and inducement of cascading effects.

During the pre-event stage, the fire risk over Attica Region is denoted on a daily basis in 5 risk levels over a detailed 500m grid spacing through a combination of high resolution numerical weather predictions, advanced ML models that utilize historic wildfire record analysis as well as a number of associated atmospheric parameters (temperature, wind speed and direction, precipitation, dew point) and datasets (DEM, land use / land cover) from 2010 onwards. During the event, continuous monitoring is provided through MSG/SEVIRI image acquisitions every 5 minutes from NOA’s in-house antenna, while the spatiotemporal fire-spread information is simulated through a dynamic modelling of the evolving fire. This feature is currently being further developed in order to be capable of performing “hot” starts along the incident and re-estimate based upon new hotspot retrievals from VIIRS imagery. Finally, the procedure of post-event burnt-scar mapping is currently being automated, to provide rapid footprints of the affected areas by utilising MODIS, VIIRS and Sentinel imagery and examine potential cascading effects through hazard assessment maps on landslides, soil erosion and floods. The whole suite will be hosted on a brand new fully responsive user interface that will provide detailed yet straightforward and easy to adopt information in order to enhance the decision making of policy makers and public bodies.

How to cite: Bartsotas, N. S., Girtsou, S., Apostolakis, A., Herekakis, T., and Kontoes, C.: The deployment of an integrated suite for wildfire prediction, near real-time fire monitoring and post-event mapping over Attica region, Greece., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12368, https://doi.org/10.5194/egusphere-egu24-12368, 2024.

EGU24-15738 | ECS | Orals | NH6.7 | Highlight

Digital Twins for Early Warning Systems: Intricacies and Solutions 

Saman Ghaffarian, Fakhereh Alidoost, Umut Lagap, Pranav Chandramouli, Yifat Dzigan, Meiert Grootes, Fatemeh Jalayer, and Ilan Kelman

In the ubiquitous dynamic landscape of social changes and technological advancements, the utilization of innovative solutions for disaster early warning systems (and for other forms of warning) has become paramount. This study explores the incorporation of Digital Twins (DT), dynamic digital replicas of physical entities, into disaster warning. Drawing from insights obtained through a comprehensive literature review and perspectives gleaned from a workshop, we investigate the technical challenges and needs of the research communities engaged in developing DTs for disaster risk management. Additionally, we propose a novel framework for employing DTs in early (and beyond) warning systems.

The implementation of DTs for early warning involves several intricacies and challenges. For instance, achieving seamless data fusion is crucial for enhancing the accuracy and timeliness of early warnings.  However, the real-time integration of diverse and large data sources, including geospatial data, environmental sensors, social media feeds, and demographic and census data is not straightforward task. Another intricacy involves the need for robust predictive modelling within the DT framework. Overcoming this challenge requires the development of dynamic models that can adapt to evolving disaster scenarios. Machine Learning plays a pivotal role in this context, enabling the DT to continuously learn and improve its predictive capabilities. Privacy concerns and ethical considerations are paramount in the use of DTs for early warning, especially when leveraging data from various sources and to ensure trust and credibility. Solutions include the development of privacy-preserving methods and transparent communication strategies to gain public trust and ensure responsible model development and data usage. Furthermore, user interaction and community involvement are essential aspects of a successful DT-based early warning system. Tailoring communication strategies to diverse audiences and fostering community engagement through user-friendly interfaces contribute to the effectiveness of early warnings.

Accordingly, we propose solutions and strategies for addressing these challenges. For instance, leveraging edge computing capabilities for real-time data processing, integrating explainable artificial intelligence (AI) techniques to enhance model interpretability and transparency, and adopting decentralized data governance frameworks like Blockchain address key challenges in DT implementation for early warning systems.

This study provides valuable insights into the current state of DT integration for disaster early warning, highlighting intricacies and offering examples of solutions. By understanding the challenges and proposing a new integration framework, we pave the way for the realization of the full potential of Digital Twins in advancing disaster resilience, early warning capabilities, and contributing to the United Nations’ initiative ‘Early Warnings for All’.

How to cite: Ghaffarian, S., Alidoost, F., Lagap, U., Chandramouli, P., Dzigan, Y., Grootes, M., Jalayer, F., and Kelman, I.: Digital Twins for Early Warning Systems: Intricacies and Solutions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15738, https://doi.org/10.5194/egusphere-egu24-15738, 2024.

EGU24-16038 | ECS | Posters virtual | NH6.7

Automatic regional identification of active and inactive landslides using satellite image analysis 

Ploutarchos Tzampoglou, Dimitrios Loukidis, Paraskevas Tsangaratos, Aristodemos Anastasiades, Elena Valari, and Konstantinos Karalis

Over the past decades, landslides have significantly affected extensive areas worldwide due to changing environmental conditions and human activities, causing major problems in the built environment and infrastructure and resulting in the loss of human lives and significant financial damages. The island of Cyprus and especially its southwestern part (which constitutes the study area) have experienced the severe impact of landslides due to the unfavorable geological/geotechnical conditions and mountainous geomorphology. According to the data obtained from the Geological Survey Department of Cyprus (GSD), 1842 landslides (active and inactive) of various types have been identified in an area covering 40% (546km2) of the Paphos District (3.4 landslides per km2).

Knowledge of the location and extent of existing landslides plays crucial role in the landslide susceptibility and hazard assessment. The primary aim of this research is to develop an algorithm for the automatic detection of landslides at regional scale. This is achieved through application of image recognition technology utilizing the cascade method on the hillshade of a region as produced by ArcGIS. The database of recorded landslides of the GSD was split in a algorithm training dataset and a validation dataset. The study also explores the effect of the resolution of terrain data, expressed by the size of the grid cells. To comprehensively assess landslides, the morphology is classified into three types: active, dormant, and relict. The use of hillshade instead of a raster image of the elevation map was chosen because the latter usually results in relatively minor color variations between adjacent pixels, thus hindering the most striking geomorphological features of landslides, which are the main scarp and the enveloping streams.

The results obtained suggest that a hillshade produced using a high-resolution Digital Elevation Model (DEM), i.e. based on elevation contour interval of 1m and a cell size 1 x 1 m (obtained from the Department of Land and Surveys of the Republic of Cyprus), yields better results for landslides with gentle geomorphology (relict). Nonetheless, analysis based on such a high-resolution DEM requires substantial computational resources and time. On the contrary, landslides associated with steeper geomorphologies (active) exhibited optimal performance with a cell size of 2 x 2 m, achieving success rates (80%), for DEMs based on contour intervals of 1m and 5m. In this case, the computational time is significantly reduced.  Depending on the specific landslide types investigated in a particular area, the appropriate processing model can be selected, ultimately leading to significant time savings.

This research was funded by the European Commission (Marie Sklodowska-Curie Actions, Hybland-Society and Enterprise panel, Project No.: 101027880).

How to cite: Tzampoglou, P., Loukidis, D., Tsangaratos, P., Anastasiades, A., Valari, E., and Karalis, K.: Automatic regional identification of active and inactive landslides using satellite image analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16038, https://doi.org/10.5194/egusphere-egu24-16038, 2024.

With the increasing frequency of global extreme weather events and urbanization accelerates, the probability of urban flooding has significantly increased, posing a grave threat to both property and lives. Creating accurate flood maps is a critical component of effective emergency management for urban floods. However, current research primarily focuses on the extent of urban flood, with little consideration given to its type. Different types of floods often have varying water components and sediments, necessitating the identification of flood types during mapping to provide targeted relief. This paper proposes a method using multiple Convolutional Neural Networks (CNNs) that combines U-Net and ResNet architectures for urban flood extent extraction and type classification. The proposed method achieved 97.1% accuracy in flood extent extraction and 91% accuracy in flood type classification, demonstrating its accuracy in urban flood mapping. Furthermore, the research was validated using a global dataset, covering six continents and 20 countries, encompassing samples with diverse dimensions and geographical features, showcasing the robustness and practicality of the model in various regions.

Keywords: Urban flood mapping, Flood type, Deep learning, CNN, Classification

How to cite: Wang, Z. and Zhang, C.: Urban Flood Extent Extraction and Type Recognition Based on Multiple Convolutional Neural Networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16528, https://doi.org/10.5194/egusphere-egu24-16528, 2024.

The presented study implements existing deep learning (DL) algorithms, an artificial intelligence approach, to extract geotechnical properties about unconsolidated material from photographs. The ultimate goal of this approach lies in facilitating, aiding and simplifying the collection of often missing data about unconsolidated bedrock cover relevant in regional landslide susceptibility studies.  Current research aims at answering, if existing DL algorithms (e. g. Buscombe’s (2020) Sedinet algorithm), developed for granular, often well-sorted sediments, can also perform well with poorly-sorted sediments. It also inquires, if, which and how well geotechnical properties, as described in soil classification standards like ISO 14688-1:2017-12 (EU) and ASTM D2487-17e1 (USA), can be directly or indirectly obtained through DL analysis of photographs. The study approaches these questions by initially building a DL model based on several thousand photographs of 240 samples of unconsolidated material plus their several hundred laboratory sieve residue samples. In a previous project, the 240 samples of mostly alluvial, colluvial, eolian and glacial sediments had been collected from different geological environments within the state of Styria, Austria. Grain size distribution (GSD) and other soil classification parameters, obtained through field and laboratory testing, exist for these samples and have been provided as courtesy by the Land Steiermark (State of Styria).  In the current study this knowledge about geotechnical properties of the samples allows attribution of this information to each of the several thousand photographs, which were taken with three different cameras under controlled conditions. The DL model uses several hundred of these photographs with their associated attributes as training and test data to build a prediction model. The validation of thus derived model in regard to its performance is achieved with selected photographs, not yet used in the training and testing. Results of this approach allow a discussion about applicability, emerging limitations and possible improvements in regard to predicting geotechnical parameters, particularly GSD, for unconsolidated material using existing DL algorithms. As a consequence the results and drawn conclusions also warrant an outlook and contemplation on how, if and in what way the method can aid and simplify field mapping and the collection of relevant input data for regional landslide susceptibility studies.  

How to cite: Kurka, M.: Performance of deep learning algorithms on obtaining geotechnical properties of unconsolidated material to improve input data for regional landslide susceptibility studies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16620, https://doi.org/10.5194/egusphere-egu24-16620, 2024.

EGU24-17169 | Posters virtual | NH6.7

Utilizing Geographic Information Systems to Identify and Map Climate Hazards in Greece: A Regional Analysis 

Kleoniki Valvi, Constantinos Cartalis, Kostas Philippopoulos, Athina-Kyriaki Zazani, and Ilias Agathangelidis

The aim of the present study is the identification of the prevailing climate hazards (e.g., extreme heat, forest fires, drought, floods) and their changes, in terms of frequency, intensity, and trends during multiple 30-year climate reference periods in Greece. The analysis involves the identification of climate hazards using a plethora of extreme event indices along with the application of the extreme value theory (EVT). Changes in extremes over a period are often examined under two different perspectives, one that detects changes in the frequency of the extremes and the other in their intensity. For this purpose, high-resolution reanalyses data (ERA5-Land) are used, with a horizontal resolution of 0.1o x 0.1o. The sensitivity of diverse regions was determined through the analysis of Earth Observation data and products, alongside with the examination of their geomorphological features. In the final stage of the work, all of the above were incorporated using Geographic Information Systems, and GIS tools were developed for the synthesis of the climate hazards. This analysis focuses on the understanding of how climate change may be impacting Greece and can provide valuable insights for policymakers, researchers, and the general public to adapt to and mitigate the effects of climate hazards on a regional scale.

How to cite: Valvi, K., Cartalis, C., Philippopoulos, K., Zazani, A.-K., and Agathangelidis, I.: Utilizing Geographic Information Systems to Identify and Map Climate Hazards in Greece: A Regional Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17169, https://doi.org/10.5194/egusphere-egu24-17169, 2024.

EGU24-18310 | ECS | Posters on site | NH6.7 | Highlight

ClarifAI: Interactive XAI Methods for Geosciences 

Yulia Grushetskaya, Mike Sips, Reyko Schachtschneider, and Mohammadmehdi Saberioon

In geosciences, machine learning (ML) has become essential for solving complex problems, such as predicting natural disasters or analysing the impact of extreme temperatures on mortality rates. However, the integration of ML into geoscience scenarios faces significant challenges, especially in explaining the influence of hyperparameters (HP) on model performance and model behaviour in specific scenarios. The Explainable Artificial Intelligence (XAI) system ClarifAI developed at GFZ addresses these challenges by combining XAI concepts with interactive visualisation. 

ClarifAI currently provides users with two interactive XAI methods: HyperParameter Explorer (HPExplorer) and Hypothetical Scenario Explorer (HSExplorer). 

HPExplorer allows interactive exploration of the HP space by computing an interactive tour through stable regions of the HP space. We define a stable region in HP space as a subspace of HP space in which ML models show similar model performance. We also employ HP importance analysis to deepen the understanding of the impact of separate HPs on model performance.The Hypothetical Scenarios Explorer (HSExplorer) helps users explore model behaviour by allowing them to test how changes in input data affect the model's response. 

In our presentation, we will demonstrate how HSExplorer helps users understand the impact of individual HPs on model performance. As ClarifAI is an important research area in our lab, we are interested in discussing relevant XAI challenges with the XAI community in ESSI.

 Our goal is to create a comprehensive set of tools that explain the mechanics of ML models and allow practitioners to apply ML to a wide range of geoscience applications.

How to cite: Grushetskaya, Y., Sips, M., Schachtschneider, R., and Saberioon, M.: ClarifAI: Interactive XAI Methods for Geosciences, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18310, https://doi.org/10.5194/egusphere-egu24-18310, 2024.

EGU24-18870 | Posters virtual | NH6.7

Spatial correlation between landslides and geotechnical factors using Random Forest and SHAP 

Ploutarchos Tzampoglou, Dimitrios Loukidis, Konstantinos karalis, Aristodemos Anastasiades, and Paraskevas Tsangaratos

The activation as well as the consequences of landslides are difficult to predict, as they depend on factors characterized by large variability and uncertainties. The aim of this study is to establish a correlation between geological, geotechnical and geomorgpohlogical characteristics and the spatial distribution of recorded landslides.

The study area is located in the southwestern (SW) part of the island of Cyprus, covering an area of 552km2. During the past years, more than 1800 landslides, active and inactive (dormant and relict), have been recorded within this area through detailed mapping based on field observations, rendering the area an ideal test bed. At the beginning of this research study, all recorded landslides were digitized in raster format. Consequently, the study area was partitioned into 15 x 15m size cells having three classes: no landslides, inactive landslides and active landslides. Additionally, regarding the geological aspect, polygons encompassing 100% rock mass formations within recorded landslides were categorized as rock mass landslides, while the rest were characterized as landslides in argillaceous (soft rock and soil) materials. A series of correlation analyses were conducted using the Random Forest and SHAP (Shapley Additive explanation) methods.

Considering the outcomes of the Random Forest method in argillaceous materials, it turns out that the most important factors for both active and inactive landslides are the Plasticity Index (PI) and the clay fraction (CF), followed by the factors associated with the geomorphology and the bedding structure (e.g. slope angle and bedding dip). The ranking results for inactive and active landslides in rock mass show that the most important factor is the Uniaxial Compressive Strength (UCS), followed by the Geological Strength Index (GSI). Furthermore, the orientation (azimuth) difference between slope and bedding dip (dip direction difference) appears to be more important than the slope angle.

Similar ranking results were obtained using the SHAP method for argillaceous materials. Regarding the contribution of each factor in the inactive landslides, it appears that the PI and the slope angle increase proportionally to the possibility of landslide occurrence, while the CF does not exhibit a specific trend. Regarding the dip direction difference, small values contribute more to the occurrence of landslides. The active landslides show a similar picture, but with the CF exhibiting a stronger correlation than in the case of inactive landslides. According to the SHAP analysis for rock mass, the parameters of importance in both inactive and active landslides are UCS and GSI, followed by the slope angle and the dip direction difference.

This research was funded by the European Commission (Marie Sklodowska-Curie Actions, Hybland-Society and Enterprise panel, Project No.: 101027880).

How to cite: Tzampoglou, P., Loukidis, D., karalis, K., Anastasiades, A., and Tsangaratos, P.: Spatial correlation between landslides and geotechnical factors using Random Forest and SHAP, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18870, https://doi.org/10.5194/egusphere-egu24-18870, 2024.

EGU24-20051 | Posters virtual | NH6.7

Resilient Data Harvesting: A Low-Cost IoT Paradigm for Robust Measurement Collection in Challenging Environments 

Marios Vlachos, Chrysoula Papathanasiou, Valantis Tsiakos, Georgios Tsimiklis, and Angelos Amditis

Desert ecosystems are particularly vulnerable to global climate change, characterized by increased temperatures, variable intensity and frequency in precipitation and increased atmospheric CO2 levels. Under such conditions, substantial alterations in their structure and functioning of desert ecosystems is expected. This climate shift poses a serious threat to species adapted to deserts, especially endemic plants, which are susceptible to the potential loss of suitable habitats. Further to that, neighboring populated areas are also exposed to adverse conditions characterized by poor air quality, with direct impacts on human health, the economy and the environment overall. To address these challenges, the CiROCCO Project aims to implement a robust yet cost-effective Internet of Things (IoT) system for environmental measurements in harsh desert environments. Such a system not only enhances data accuracy but also enables continuous monitoring, reduces costs, and supports critical research and conservation efforts considering climate change and ecosystem challenges. The proposed IoT system primarily relies on a network of distributed low-cost Wireless Sensor Nodes (WSNs) that have the capability to monitor the surrounding environment and measure various crucial meteorological and air quality parameters, including inter alia air and sand/soil temperature, solar radiation, Ozone, PM2.5, PM10, with accuracy comparable to commercial high-end nodes offering similar measurements. Additionally, communication gateways are employed to collect measurements from the distributed WSNs using low-power consumption protocols such as Bluetooth Low Energy (BLE) and LoRaWAN. The collected measurements are then standardized into JSON messages, including the unique identifier of the device, timestamp, and parameter values. Subsequently, the data are transmitted wirelessly to the cloud using the most suitable method based on network connectivity. If there is an available Wi-Fi network in the field, the data is prioritized for transmission through this network. Alternatively, the system utilizes the 4G or 5G network in the area. In cases where none of these networks is accessible, the data is transmitted to the cloud through satellite communications. This method involves an additional satellite device connected to the gateway, where the formatted messages are loaded through serial communications. The satellite device awaits the next pass of the nanosatellite, for uploading the measurements. The nanosatellite continues its journey until it passes by a base station, at which point the data are downloaded, stored in the base station portal, and made available to third-party applications through the portal API. In conclusion, the scientific approach outlined in this work addresses the imposing challenges of collecting valuable in-situ data for monitoring climatic conditions in hard-to-reach under-sampled environments. The development of low-cost devices, including WSNs and gateways with IoT capabilities, is crucial for advancing research and conservation efforts in the context of climate change and considering the unique challenges posed on desert ecosystems.

AKNOWLEDGMENTS

This research work is part of the CiROCCO Project. CiROCCO Project is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or REA. Neither the European Union nor the granting authority can be held responsible for them.

How to cite: Vlachos, M., Papathanasiou, C., Tsiakos, V., Tsimiklis, G., and Amditis, A.: Resilient Data Harvesting: A Low-Cost IoT Paradigm for Robust Measurement Collection in Challenging Environments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20051, https://doi.org/10.5194/egusphere-egu24-20051, 2024.

EGU24-20549 * | Posters on site | NH6.7 | Highlight

The Use of Digital Twins for the Management of Cultural Heritage Sites 

Kyriacos Themistocleous and Dante Abate

There is a need for the use of digital twins of cultural heritage sites, especially for those that are affected by natural hazards, for documentation, monitoring and management. This study examines the use of digital twins through the EXCELSIOR and TRIQUETRA project for the use of 3D digital volumentric reporesentation model and Augmented Reality applications by creating a digital twin for monitoring natural hazards in archaeological settings. The EXCELSIOR H2020 Widespread Teaming project under Grant Agreement No 857510 and the TRIQUETRA project Horizon Europe, Grant Agreement No. 101094818 will study the effects of climate change and natural hazards on cultural heritage and remediation using state-of-the-art techniques.  Through the TRIQUETRA project, Choirokoitia, Cyprus is used as one of the pilot studies using these techniques. Choirokoitia is a UNESCO World Heritage Site and is one of the best-preserved Neolithic sites in the Mediterranean. The project will also examine the potential risk of rockfall at the Choirokoitia site, as the topology of the site is vulnerable to movements as a result of extreme climate change as well as of daily/seasonal stressing actions. Rockfall poses a significant danger to visitor safety as well as damage to cultural heritage sites.

Digital twins provide a dynamic visualization of the site and can also be used to monitor any changes resulting from natural hazards. A digital twin model can also be shared with visitors in order to provide an alternative approach and a visualization experience for viewing the site.

How to cite: Themistocleous, K. and Abate, D.: The Use of Digital Twins for the Management of Cultural Heritage Sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20549, https://doi.org/10.5194/egusphere-egu24-20549, 2024.

EGU24-22176 | Orals | NH6.7

Machine Learning Approach for Next-Day Wildfire Prediction: Challenges, Solutions, andInsights 

Stella Girtsou, Alexis Apostolakis, Konstantinos Alexis, Mariza Kaskara, Giorgos Giannopoulos, and Charalampos Kontoes

Next-day wildfire prediction is a critical research problem with significant implications for the environment, society, and economy. This study addresses the challenges associated with accurately predicting fire occurrences and presents a machine learning methodology designed to achieve high sensitivity and specificity in predicting wildfires at a country-wide scale with high spatial granularity. The unique aspects of the problem, including extreme data imbalance, massive scale, heterogeneity, and absence of fire, are thoroughly examined.

The proposed methodology focuses on three key components:

  • Feature Set Enhancement: An extended set of fire driving factors, encompassing topography, meteorology, Earth Observation data, and historical fire occurrence information, is utilized. This comprehensive feature set provides a holistic view of the factors influencing fire risk.
  • State-of-the-Art Classification Algorithms: A set of well-established classification algorithms, including Random Forest, Extremely Randomized Trees, XGBoost, and shallow Neural Networks, for benchmarking is employed. These algorithms are carefully tuned and optimized to strike a balance between sensitivity and specificity. Furthermore, state-of-the-art Deep Learning Methodologies like Semantic Segmentation and Metric Learning are employed and tuned for this specific task.
  • Effective Cross-Validation and Model Selection: Two alternative cross-validation schemes and custom validation measures are introduced to ensure optimal training of classification models. This allows for the selection of diverse models based on the desired trade-off between sensitivity and specificity.

The paper addresses specific challenges, such as extreme data imbalance, massive scale of data, heterogeneity, and absence of fire. The scale of the dataset, with over 830 million instances covering a 500m grid cell resolution for the entire Greek territory, necessitates careful undersampling for model training. Heterogeneity and concept drifts in different months are acknowledged, and the absence of fire instances is discussed in the context of unpredictable factors.

The study explores pitfalls, best practices, and directions for further investigation, providing valuable insights into the complexities of next-day wildfire prediction. The impact of class_weights hyperparameter in compensating for data imbalance is highlighted, emphasizing its significance in cost-sensitive learning.

In conclusion, the proposed machine learning methodology demonstrates effectiveness and efficiency in next-day fire prediction, aligning with real-world fire prediction system requirements. Further, our proposed methods achieve adequately high effectiveness scores (sensitivity > 90%, specificity > 80%) and are realized within a pre-operational environment that is continuously assessed on real-world conditions and also improved based on the feedback of the Greek Fire Service.  The study contributes insights that can guide future research in addressing the challenges associated with wildfire prediction, paving the way for more accurate and reliable models in the field.

Acknowledgement: "This work has been supported by the national research project PREFERRED, which is co-funded by Greece and the European Union through the Regional Operational Programme of Attiki, under the call "Research and Innovation Synergies in the Region of Attica” (Project code: ΑΤΤΡ4-0340489)"

How to cite: Girtsou, S., Apostolakis, A., Alexis, K., Kaskara, M., Giannopoulos, G., and Kontoes, C.: Machine Learning Approach for Next-Day Wildfire Prediction: Challenges, Solutions, andInsights, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22176, https://doi.org/10.5194/egusphere-egu24-22176, 2024.

The exponential increase in flood intensity that causes loss of life and economic and structural
damage to their connected environment calls for strategic rescue and response solutions for
risk mitigation. This study focuses on flood mapping using satellite imagery combined with
machine learning (ML) and deep learning (DL) techniques. Remote sensing and Geographic
Information Systems (GIS) serve as vital tools in this process, enabling the effective utilization
of satellite data.
While academics consistently contribute to novel flood mapping approaches, a research gap
that requires a discussion about the comparative performances of these ML and DL
techniques exists, which this paper aims to address. This comparison is crucial as it highlights
the strengths and limitations of each method, contributing valuable insights to the literature on
flood risk management. The study focuses on the Ernakulam District of Kerala, chosen due to
its frequent flooding and the availability of diverse datasets.
The methodology involves the use of satellite imagery for flood analysis, employing an array
of techniques: a thresholding method recommended by the UN-SPIDER Office for Outer
Space Affairs, and statistical ML methods including Random Forest, Support Vector
Classification (SVC), Real AdaBoost, alongside a deep learning semantic segmentation
method, UNet. Modelled using JavaScript and Python languages, the models and the
packages are completely reusable. The dataset comprises two before and after floods satellite
images: the thresholding method uses Sentinel-1 SAR images, and the ML and DL method
uses Sentinel-2 MSI Level 1C, a digital elevation model image from SRTM for feature
engineering, processed to identify flood-affected areas. The data is normalized and cleaned
to account for cloud and missing data before the analysis. Alongside, we sourced the labelled
flood data from the Kerala State Disaster Management Authority (KSDMA) and filtered and
rasterized it on QGIS.
The results emphasize the varied effectiveness of these methods, with Random Forest
outperforming others with a 96.61% accuracy rate. At the same time, the UNet-Linear Model
lags at 75% accuracy, indicating the significant impact of hyperparameter tuning and dataset
size on model performance. This comparative analysis not only delineates the strengths and
weaknesses of traditional and advanced techniques but also sets a precedent for future
studies to build upon an understanding of flood risk management and rapid response
strategies.

How to cite: Menon, N., Parastoo, S., and Adriaensen, R.: Flood Inundation Mapping of the 2018 Kerala Floods: A ComparativeStudy of Traditional Remote Sensing, Machine Learning, and Deep Learning Methods. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22400, https://doi.org/10.5194/egusphere-egu24-22400, 2024.

Detailed information on the exposure of critical infrastructure (CI), such as power assets, is a necessity to establish accurate risk assessment from natural and human-made hazards. Currently, large-scale risk assessment mostly relies on Volunteered Geographic Information to establish the exposure of CI causing limited reliability due to inherent information gaps. Deep Learning offers the possibility to fill such gaps through the extraction of CI from remote sensing imagery.

Here we present a comprehensive high-resolution geospatial database encompassing key elements of the power grid, namely power towers, electrical substations, and power plants. The dataset is derived from a workflow using Worldview-2 0.4-meter resolution satellite imagery for the most populated urban areas along the European coastlines.

The method extracts infrastructure location from OpenStreetMap to create annotations. Subsequently, the satellite imagery raster and annotations undergo processing to constitute training data. Data augmentation is employed on the raster tiles to enhance the training dataset. The method then trains a Mask R-CNN model to automate the detection of CI. Additionally, saliency maps are generated to validate the proper functioning of the model.

Performance metrics, specifically mean Average Precision and F-scores of the tile classification, are presented to evaluate the model's ability to correctly identify and classify power infrastructure. Furthermore, to assess the completeness of the geospatial database, a comparative analysis is conducted with OpenStreetMap on “unseen” locations. This comparative study sheds light on potential gaps and discrepancies, offering insights into the overall reliability and comprehensiveness of the dataset.

How to cite: De Plaen, J., Koks, E., and Ward, P.: A Coastal European Dataset of Critical Infrastructure:  Leveraging Deep Learning to Enhance Power Infrastructure Exposure Information for Disaster Risk Assessment., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22456, https://doi.org/10.5194/egusphere-egu24-22456, 2024.

NH7 – Wildfire Hazards

EGU24-614 | ECS | Orals | NH7.1

Spatiotemporal analysis and projections of wildfire risk across Pakistan under different climate change scenarios 

Zarmina Zahoor, Jonathan Eden, Matthew Blackett, and Yung-Fang Chen
 

Wildfires are becoming more intense and frequent, with record-breaking fire seasons witnessed across the world in recent years. Amid rising global temperatures, the challenge to understand, communicate and ultimately reduce wildfire risk is critical. A recent report published by the United Nations Environment Programme noted a particular increase in fire prevalence across regions that were not previously considered fire-prone, including the Indian subcontinent. In Pakistan, wildfire has gradually emerged as a significant environmental and societal threat. However, it is unclear how such threats will evolve under climate change, and to what extent Pakistan’s ongoing afforestation projects, such as the Ten Billion Tree Tsunami, take changes in risk into account. 

Here, we explore how meteorological conditions conducive to wildfire are likely to respond to a changing climate throughout Pakistan. Following an initial spatiotemporal analysis of wildfire occurrence based on satellite-derived data between 2001 and 2020, we identity hotspots of fire activity across the forested regions of the Baluchistan, Kashmir, Khyber Pakhtunkhwa and Punjab provinces. Using the fire weather index (FWI) derived from the simulations of 14 global climate model ensembles from the 6th phase of the Coupled Model Intercomparison Project (CMIP6), we then quantify changes in fire danger throughout the 21st century under four climate change scenarios defined by the Shared Socioeconomic Pathways (SSPs). We show that the magnitude of seasonal mean FWI is projected to increase by as much as 10% by the end of the century under the highest emissions scenario, with up to 20 additional days of extreme fire weather projected per year.  

Our conclusions advise on how forest management strategies and afforestation projects across Pakistan should account for potential changes in wildfire risk associated with a changing climate. We introduce a prototype online portal as a mechanism to disseminate results and communicate future risk to a range of potential stakeholders. Further work will focus on the resilience of wildfire forecasting and early warning systems in a changing climate.  

 

How to cite: Zahoor, Z., Eden, J., Blackett, M., and Chen, Y.-F.: Spatiotemporal analysis and projections of wildfire risk across Pakistan under different climate change scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-614, https://doi.org/10.5194/egusphere-egu24-614, 2024.

EGU24-708 | ECS | Posters on site | NH7.1

High-Resolution Simulation of the Extreme Fire Event in Central Portugal, Pedrogão Grande (2017) 

Luana Santos, Miguel M. Lima, Pedro M. M. Soares, Ricardo M. Trigo, and Rita M. Cardoso

Wildland fire spread and behaviour are complex phenomena owing to both the number of involved Physicochemical factors and the non-linear relationship between variables. In Portugal, one of the European countries most affected by wildfires, forest and bushfires occur every summer and are often exacerbated when extremely dry weather sets along with high temperatures. On the 17th of June 2017, an extreme heatwave associated with a severe drought and compounded by unusual levels of atmospheric instability led to a multiplicity of wildfires with many active fronts, and the formation of pyro-cumulus with explosive fire behaviour. All these factors contributed to the catastrophic fires that occurred in Pedrogão Grande on that day, with more than 100 fatalities and heavy impacts on livelihoods and assets.

The June 2017 extreme fire event in Pedrogão Grande is simulated with the WRF- Fire and Sfire model using a nested framework with increasing spatial resolution, including high-resolution regional scale (2km), local (0.4km) and Large Eddy Simulation (0.08km) resolutions. In this simulation 68 hybrid vertical levels are used, the model top is fixed as 20hPa, the first level is set at approximately 15m from the ground. Initial and boundary conditions for the outer domain were extracted from the ECMWF operational analyses, at 6-hourly intervals. Three microphysics schemes and three boundary layer parameterisations were employed to evaluate the best combination that suits robust reproduction of this complex event. The fire module is a simple 2D model of a surface fire, where the fire spreads through fuels on the ground. In every time step, the fire model inputs surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. Among the different unusual features, we were particularly interested in assessing the model’s ability to reproduce a series of downbursts that occurred prior to and during the event and that have contributed decisively to atmospheric instability.

It was found that WRF can simulate those features, as well as the pyro-cumulus formation, yet their development is highly dependent on the interaction between the chosen microphysics and the boundary layer schemes. As in the observed event, the fire spread is accelerated westwards in association with the pyrocumulus. The initial simulated fire spread is faster than the observed in all simulations while the extent of the pyro-cumulus is shorter. The FWI (Fire Weather Index), the CHI (Continuous Haines Index) and the FWIe index (blending of FWI and CHI) were high prior and during the fire, observed in all domains, indicating extreme fire hazard and the presence of large instability conditions that can enhance fires that might become out of control, and with erratic behaviour.

Acknowledgements: This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020. L.C. Santos is supported by the EarthSystems Doctoral School, at University of Lisbon, supported by FCT project UIDP/50019/2020-2023, University of Lisbon. M.M. Lima was supported through the PhD FCT programme grant PRT/BD/154680/2023.

How to cite: Santos, L., M. Lima, M., M. M. Soares, P., M. Trigo, R., and M. Cardoso, R.: High-Resolution Simulation of the Extreme Fire Event in Central Portugal, Pedrogão Grande (2017), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-708, https://doi.org/10.5194/egusphere-egu24-708, 2024.

EGU24-769 | ECS | Posters on site | NH7.1

A multidecadal satellite-derived burn severity atlas for Portugal (1984 – 2022) 

Dina Jahanianfard, Joana Parente, Oscar González-Pelayo, and Akli Ait Benali

Wildfires have been known as one of the most disturbing phenomena in Portugal during last decades with increasing frequency, annual number of ignition and affected area. However, the extent of wildfire-induced changes on soil and vegetation, or burn severity, of these historical wildfires is unclear. To contribute to a better knowledge of post-fire impacts, this study presents a long-term burn severity atlas of historical wildfires in Portugal from 1984 to 2022 using satellite data.

Burn perimeters and start/end dates for large wildfires (>=100ha) were gathered and necessary corrections were manually applied on them. Due to the availability of satellite images, different imagery from Landsat sensors were used for different years: Landsat-5 (TM) for 1984 to 2011, Landsat-7 (ETM+) for 2002, and Landsat8 (OLI) for 2013 to 2022. The time lag between wildfire occurrence and satellite image acquisition dates was quantified and used to determine the suitability of each satellite image to estimate burn severity. Then, using Google Earth Engine API (JavaScript) and through a semi-automated process, the burn severity of each wildfire was calculated via difference normalized burn ratio (dNBR) derived indices (dNBR, relative dNBR (RdNBR), Relativized Burn Ratio (RBR), dNBR – Enhanced Vegetation index (dNBR-EVI)). These maps were created by the application of a pair of pre- and post-fire images with the highest suitability values.

The analysis performed on the time lag quantification showed a decrease in dNBR accuracy with the increase of both pre- and post-fire time lags. Over 3.7 million ha of land burned in Portugal from 1984 to 2022 in all vegetation types, around 3.2 million were associated with wildfires equal or larger than 100ha with known start and end dates (86.2%). Among these wildfires, 3.1 million ha had dNBR estimates (83.72% of all wildfires and 97.05% of wildfires>=100ha).

To the best of our knowledge, a long-term burn severity atlas has never been developed for an entire European country before. Another noteworthy advancement provided by this atlas is that the imageries from Landsat family of sensors were utilized for development of burn severity maps, offering the resolution of 30m over the manually corrected historical wildfire data (perimeters, locations, and dates). Also, a semi-automated process has been provided, equipped with the capacity to develop burn severity atlas for historical wildfires of any other region in the world with the prerequisite of wildfire data. Such datasets can be used by both scientific and management communities to improve current knowledge on post-fire impacts and develop better pre- and post-fire management plans to mitigate wildfire impacts. Moreover, this multidecadal burn severity dataset can be used by other research communities in the fields related to water, soil, and air quality which are potentially at risk due to wildfire occurrences.

Acknowledgements

We acknowledge CESAM by the Portuguese Foundation for Science and Technology FCT/MCTES (UIDP/50017/2020+UIDB/50017/2020+LA/P/0094/2020). D. Jahanianfard is supported by the Portuguese Foundation for Science and Technology (FCT-Fundação para a Ciência e Tecnologia) with a PhD grant reference (2021.08094.BD). O. Gonzalez-Pelayo further acknowledges FCT for the funding of FRISCO (PCIF/MPG/0044/2018) and SOILCOMBAT (PTDC/EAM-AMB/0474/2020) projects.

How to cite: Jahanianfard, D., Parente, J., González-Pelayo, O., and Ait Benali, A.: A multidecadal satellite-derived burn severity atlas for Portugal (1984 – 2022), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-769, https://doi.org/10.5194/egusphere-egu24-769, 2024.

EGU24-795 | ECS | Orals | NH7.1

Assessing meteorological fire danger over Europe based on a statistical model of satellite-derived fire radiative power 

Mariana Ponte Oliveira, Sílvia A. Nunes, Carlos C. DaCamara, Ricardo M. Trigo, and Isabel F. Trigo

The Satellite Application Facility for Land Surface Analysis (LSA SAF), that is part of EUMETSAT’s ground segment, operationally disseminates daily forecasts of meteorological fire danger over Mediterranean Europe. The so-called Fire Risk Map (FRM) product relies on estimates of the probability of exceedance of predefined thresholds of daily released energy by active fires as derived from a Generalized Pareto model that uses FWI as covariate for the scale parameter; FWI, the Fire Weather Index (FWI), is part of the Canadian Fire Weather Index System and has proven to be very suitable to rate fire danger over Europe.

The aim of this study is to extend the procedure to Northern and Central Europe making use of a statistical model of Fire Radiative Power (FRP) as derived from MODIS observations over Europe covering the period 2000-2022. Following the approach developed by DaCamara et al. (2023), the statistical model consists of an 8 parameter, doubly truncated lognormal body distribution with generalized Pareto tails, using FWI as a covariate of its parameters.

First, Europe is divided into eight regions according to the recorded number of hotspots and to the averaged FRP over the study period. Each one of those regions is then stratified into three subregions according to the dominant land cover type, i.e., forest, shrub, or agriculture. For each of the subregions, a statistical model is fitted to the sample of historical records of FRP together with the associated sample of FWI values obtained from the Copernicus Emergency Management Service.

The fitted models are then applied to Europe to generate monthly climatological values of probability of exceedance of prescribed thresholds of FRP. This information is used to define appropriate limits for classes of fire danger (i.e. low, moderate, high, very high and extreme) for each subregion of Europe. Finally, these classes are validated by analyzing the distribution of recorded FRP among the classes and by examining maps for extreme fire events.

 

This work was supported by EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF) and by Instituto Dom Luiz (IDL), a research unit financed with national funds (PIDDAC) by FCT (UIDB/50019/2020).

 

References:

DaCamara, C. C., Libonati, R., Nunes, S. A., de Zea Bermudez, P., & Pereira, J. M. C. (2023). Global-scale statistical modelling of the radiative power released by vegetation fires using a doubly truncated lognormal body distribution with generalized Pareto tails. Physica A: Statistical Mechanics and Its Applications, 625. https://doi.org/10.1016/j.physa.2023.129049

How to cite: Ponte Oliveira, M., A. Nunes, S., C. DaCamara, C., M. Trigo, R., and F. Trigo, I.: Assessing meteorological fire danger over Europe based on a statistical model of satellite-derived fire radiative power, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-795, https://doi.org/10.5194/egusphere-egu24-795, 2024.

EGU24-885 | ECS | Posters on site | NH7.1

The fire, burned areas and charcoal - charcoal-data modelling of burned areas, cross-validation of the fires and charcoal signal 

Krzysztof Szewczyk, Dominika Łuców, Boris Vanniere, Milena Obremska, and Michał Słowiński

Fire is one of the fundamental factors that governs and shapes the functioning of many ecosystems and directly influences changes in vegetation, biodiversity and ancient societies. Recent decades have shown how wildfires and their associated global relationships contribute to accelerate climate change through changes in vegetation, permafrost conditions, and the release of residues, greenhouse gases and aerosols. The last IPCC report shows that the European region is characterized by an increase in fires directly caused by current climate change. In addition, forecasts for the next century indicate a continuous increase in air temperature, which could lead to an increase in the frequency and intensity of wildfire events. In this regard, the questions arise: What are the social and environmental impacts of future unexpected climate events? And how could an increase in wildfires accelerate climate change?

During a fire, smoke, particles and various chemical compounds are released into the atmosphere, which can have a harmful effect on human health. Because of these consequences, it is important to understand what affects the occurrence and severity of fires. Paleofire reconstructions are useful for studying the effects of climate change and vegetation on fires at a time when human influence was less than today. Archived charcoal particles  in peat and lake sediments have been successfully used as geographic patterns in changing fire conditions. However, as many publications show, charcoal data can only provide partial estimates of changes in biomass burning. Therefore, the aim of the project is to indicate and verify the relationship between fire and its record in peat and lake sediments. To do this, burned areas within 40 km of 10 test sites (lakes and peatlands) are identified, and the intensity of each fire is estimated using fire data (i.e. fire type: ground, surface or crown), fire indicators (burnt area, weather conditions, wind speed and direction), fuel information (ecosystem type, forest age and species structure), obtained from the State Forests. Past fires and regional vegetation will be reconstructed using cores collected from lakes and peatlands based on pollen and charcoal analysis  with morphotypes in six fractions (100, 150, 200, 300, 400, 500 μm) with a high sampling resolution (0.5-1 cm). μ-XRF scanning will also be utilised to detect erosion and redeposition processes. The chronology will based on radiocarbon dating (AMS) and cesium-137 dating. Finally, the model of the spread of charcoal from the burnt area will be created. We assume that the amount of carbon accumulated on the lake and marsh surface is directly proportional to fire distance, burned area, and fire intensity. In this project, we want to advance the interpretation of reconstructed fires. This study could be the next step to better understand the fire signals preserved in our archives and improve the interpretation of paleo fires. This research is funded by the Polish National Science (No. 2023/49/N/ST10/04035).

How to cite: Szewczyk, K., Łuców, D., Vanniere, B., Obremska, M., and Słowiński, M.: The fire, burned areas and charcoal - charcoal-data modelling of burned areas, cross-validation of the fires and charcoal signal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-885, https://doi.org/10.5194/egusphere-egu24-885, 2024.

EGU24-1324 | Orals | NH7.1

Automated Selection of Sentinel-2 Spectral Bands for Fire Detection 

Octavian Dumitru, Gottfried Schwarz, and Chandrabali Karmakar

This work investigates the occurrence, parameters, and consequences of fires in satellite images that can be directly exploited by several combinations of different multispectral image bands.

When we want to understand the semantics of a recorded digital image, we can cut it into smaller-size image patches and routinely classify these image patches via common unsupervised or supervised image classification techniques. In addition, when we include some clever interactive learning steps to attach semantic labels to the hitherto mathematically classified image patches, this should allow for a highly automated and powerful image understanding procedure.

On the other hand, starting with simple examples, the application-oriented analysis and exploitation of Sentinel-2 images can combine and display selected colour bands and their combinations. This has already been discussed in many (mostly GIS-oriented) publications ranging from the straightforward assignment of directly available pseudo-RGB colour bands up to advanced machine learning approaches for the extraction of content-related information (such as image feature descriptors or indices) [1-4]. Further, we will also refer to a few recently published advanced information extraction tools [5-10].

As an alternative to these (mostly conventional) image classifications, we describe a powerful semantic image classification technique that starts with the generation of topics (instead of classes) that was originally described by [11].Here, the resulting topic maps can be further combined and be used for colour band displays and their interpretation. When we combine the properties and capabilities of Sentinel-2 images with topic interpretation techniques, the most interesting question is whether a semantic interpretation based on topic maps outperforms common feature-based approaches.

To this end, we selected several Sentinel-2 multi-band images comprising different geographical areas affected by fires. This presentation shows the actual impact of various band combinations of Sentinel-2 channels and illustrates the band-dependent appearance of Fires, Smoke, Clouds, and other specific categories linked to the investigated continental areas. The basic algorithm being used for this investigation is Latent Dirichlet Allocation that has been applied as a data mining tool to discover patterns in the data, combined with automated band selection approaches.

The combination of automated image classification and multi-colour visualization seems to be an interesting alternative to Deep Learning.

[1] https://gisgeograpy,com/sentinel-2-bands-combinations

[2] https://worldofittech.com/sentinel2-bands-and-combinations

[3] https://giscrack.com/list-of-band-combinations-in-sentinel-2a

[4] https://eo4geocourses/github.io/IGIK_Sentinel2-Data-and-Vegetation-Indices

[5] A. Revill et al., The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development, Remote Sensing, 11(17), 2018.

[6] K. Kowalski et al., A generalized framework for drought monitoring across Central European grassland gradients with Sentinel-2 time series, Remote Sensing of Environment, 286, 2023.

[7] M.K. Vanderhoof et al., High-frequency Time Series Comparison of Sentinel-1 and Sentinel-2 Satellites for Mapping Open and Vegetated Water Across the United States, Remote Sensing of Environment, 288, 2023.

[8] E.C. Rodriguez-Garlito et al., Mapping Invasive Aquatic Plants in Sentinel-2 Images Using Convolutional Neural Networks Trained with Spectral Indices, JSTARS, 16, pp.2889-2899, 2023

[9] Z. Chen, et al., Mapping Mangrove Using a Red-Edge Mangrove Index (REMI) Based on Sentinel-2 Multispectral Images, TGRS, 61, pp.1-11, 2023.

[10] A. Temenos, Interpretable Deep Learning, GRSL, 20, pp.1-5, 2023.

[11] D.M. Blei, et al., Latent Dirichlet Allocation, Journal of Machine Learning Research, 3, pp.993-1022, 2003.

How to cite: Dumitru, O., Schwarz, G., and Karmakar, C.: Automated Selection of Sentinel-2 Spectral Bands for Fire Detection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1324, https://doi.org/10.5194/egusphere-egu24-1324, 2024.

Wildfire risk prediction is a critical component of disaster prevention and mitigation, often closely associated with local human activities in most regions. Recent studies demonstrate that employing joint modeling techniques using diverse datasets alongside Convolutional Neural Networks-Long Short-Term Memory Networks (CNN-LSTM) produces favorable predictive results. This approach effectively tackles certain drawbacks of fire weather indices (FWI), notably the insufficient consideration of surface coverage and coarse resolution. However, previous research inadequately explored variations in the impact of influencing factors across different categories and spatial orientations, neglecting the internal structural features within the samples. This study focuses on the six eastern provinces of China, utilizing a multi-source dataset comprising satellite-monitored wildfire products from 2012 to 2022, along with terrestrial ecology, terrain, and simulated meteorological elements. By introducing channel and spatial attention mechanisms, high-resolution imagery, and visual transformer model, this research optimizes the CNN-LSTM wildfire prediction model. Results indicate a noteworthy enhancement, elevating accuracy, Kappa coefficient, and AUC of ROC curves from 91.15%, 80.87%, and 97.01% to 93.30%, 85.63%, and 98.15%, respectively. This refined model not only refines high-risk prevention areas highlighted by FWI but also enhances understanding of mountain trails in hilly terrains. Consequently, it reduces false alarms in regions such as non-harvesting agricultural fields, reinforcing predictive risk assessment concerning potential human activities within forested areas. Sensitivity analysis reveals that while the impact of internal sample structural features on wildfire risk prediction is lower than meteorological elements, it surpasses the influence of terrain and terrestrial ecology elements. Thus, this study has developed a methodology integrating multiple attention mechanisms and sample structural features, furnishing high-precision daily kilometer-level wildfire risk prediction products. This approach holds substantial promise for the precise prevention and control of regional wildfires.

How to cite: Fan, G. and He, Z.: Deep Learning Modeling of Human Activity Affected Wildfire Risk by Incorporating Structural Features: A Case Study in Eastern China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1627, https://doi.org/10.5194/egusphere-egu24-1627, 2024.

EGU24-2647 | Orals | NH7.1

 A comprehensive wind-fire-smoke simulation tool based on physical models and geospatial information. 

María Isabel Asensio, José Manuel Cascón, and José Manuel Iglesias

We present a comprehensive simulation toolset for the analysis and prediction of wind fields, wildfire spread, and the propagation of their resulting smoke. It is composed of three physical simulation models that work together: HDWind, PhyFire and PhyNX.

The wind field simulation model, HDWind, is a mass consistent vertical diffusion wind field model based on an asymptotic approximation of the Navier-Stokes equations, providing a 3D wind field (which satisfies the incompressibility condition in the air layer) governed by a 2D equation that id adjusted to meteorological data obtained in a small number of points by solving an optimal control problem. PhyFire is a simplified 2D one-phase fire spread simulation model based on the principles of mass and energy conservation and that considers the radiation and convection (i.e., driven by wind and terrain slope) means of propagation, featuring the most relevant 3D effects, the influence of humidity, ambient temperature, wind, and the fuel types as well as their moisture content. The atmospheric dispersion model PhyNX is an urban scale Eulerian non-reactive multilayer air pollution model, able to describe convection, turbulent diffusion, and emission, considering the 3D wind field provided by the HDWind, and the smoke emission provided by PhyFire. The three models are solved using mainly the finite element method and some numerical and computational procedures to reduce the computational cost.

The required data to feed the simulation models such as cartographic and meteorological information are obtained from online geospatial information systems (GIS) in an automated way with little user intervention, thanks to the integration of the models with the geospatial library GDAL/OGR, which enables easy interpolation with most used standard GIS formats and services. An integration of this toolset into an easy-to-use webgis platform for their exploitation for professionals in the field of wildfire prevention will be demonstrated.

How to cite: Asensio, M. I., Cascón, J. M., and Iglesias, J. M.:  A comprehensive wind-fire-smoke simulation tool based on physical models and geospatial information., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2647, https://doi.org/10.5194/egusphere-egu24-2647, 2024.

EGU24-3221 | ECS | Orals | NH7.1

Standard Precipitation Index (SPI) applied to Socioeconomic Pathway Scenarios (SSPs) as a tool to map the distribution of droughts and potential fire hazard areas in Brazil in the face of climate change 

Aimée Guida Barroso, Gean Paulo Michel, Franciele Zanandrea, Márcio Vinicius Aguiar Soares, Gabriel Ferreira Subtil de Almeida, Marcio Cataldi, Priscila Esposte Coutinho, and Livia Sancho

Wildfires represent a significant threat to natural ecosystems, biodiversity, and communities worldwide. Disruption in precipitation regimes and temperature rise caused by climate change are key factors that worsen and increase wildfire incidents. In Brazil, recent studies have shown the majority of fire incidents are initiated by anthropogenic action, as a consequence of agricultural expansion, deforestation and land disputes. Although the human use of fire as an illegal tool is difficult to predict, the occurrence of dry meteorological conditions, prone to uncontrolled spreading of fires, can be studied employing climate modeling, providing a useful instrument to aid authorities in preventive measures and improved responses to mitigate these impacts, contributing to more efficient and sustainable management of fire-related risks. The Standardized Precipitation Index (SPI) is a useful tool for assessing precipitation variability, allowing the analysis of drought period duration, distribution, and severity. The SPI uses precipitation data to standardize the deviation of accumulated precipitation from the historical average in each location. This process yields negative or positive values, which correspond to water deficits or surpluses, respectively. Aiming to identify areas in Brazil where predicted disruption in rainfall patterns, in face of climate change, may create drier conditions and increase vulnerability to fire incidents, we evaluated precipitation trends, comparing historical simulations from the 6th phase of the Model for Interdisciplinary Research on Climate (MIROC6) and future scenarios data from the Intergovernmental Panel on Climate Change (IPCC). We focused our analysis on 3 climate change scenarios, referred to as Shared Socioeconomic Pathways: SSP2-4.5, SSP3-7.0, and SSP5-8.5. These scenarios encompass anticipated global socioeconomic transformations up to the year 2100, based on different projections of greenhouse gas emissions, and offer an assessment of the climate outlook for current society. Thus, we calculated SPI indexes for the time spans 1960-1990 and 2020-2050, examining the variations in rainfall patterns across the country during both periods. Using SPI derived from MIROC6 climatological data, it is possible to identify past patterns that are the basis for understanding future changes' impact. The results from SPI climatological data are consistent with the climate and seasonal rainfall patterns historically observed in Brazil, where Northeast and Central Brazil exhibit greater water deficits. The scenarios employed suggested that the historical patterns of droughts would be worsened in severity in central Brazil and the areas of influence would be extrapolated, creating drier meteorological conditions to the Southern and East portions of Amazonia and the Southeast of Brazil. The SPI indexes calculated to the projected scenarios reinforce the understanding of the impacts of climate change, suggesting the pathway SSP55-8.5, with higher emission of CO2, implicates in increased occurrences of extreme events, particularly prolonged and severe droughts in regions that suffer from wildfires. Identifying regions with an increased likelihood of prolonged drought events in the projected future is a valuable instrument for examining fire hazard and mitigation plans within a country such as Brazil, which encompasses diverse climates and biomes across its territory with resources of significant conservation value.

How to cite: Guida Barroso, A., Michel, G. P., Zanandrea, F., Vinicius Aguiar Soares, M., Ferreira Subtil de Almeida, G., Cataldi, M., Esposte Coutinho, P., and Sancho, L.: Standard Precipitation Index (SPI) applied to Socioeconomic Pathway Scenarios (SSPs) as a tool to map the distribution of droughts and potential fire hazard areas in Brazil in the face of climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3221, https://doi.org/10.5194/egusphere-egu24-3221, 2024.

EGU24-3838 | ECS | Orals | NH7.1

Burned area detection based on Planet imagery using virtual SWIR band 

Byeongcheol Kim and Seonyoung Park

Forest fires pose significant threats to both human safety and the natural ecosystem. Detecting and accurately estimating the extent of the burned area is crucial for effective response planning. Remote sensing emerges as a valuable solution for estimating the burned area, with various satellites employed in previous studies. Unlike these satellites, microsatellites offer a promising alternative with higher spatiotemporal resolution. In this study, we utilized PlanetScope imagery and implemented the U-Net model. PlanetScope provides images at a 3m spatial resolution and revisits the same area every day, offering a distinct advantage in accurately estimating burned areas across different scales of fire events. However, PlanetScope lacks a Shortwave Infrared (SWIR) band commonly used in forest fire studies. To address this limitation, a virtual SWIR band was introduced in this study. To enhance accuracy in specific regions, a virtual SWIR band was created using machine learning techniques using the SWIR images from Landsat and Sentinel-2. Our approaches were tested in four study regions. The U-Net model was employed to generate burned area prediction maps, and each model's performance was evaluated using several metrics, including intersection-over-union (IoU), mean IoU, recall, precision, F1-Score, and the Kappa coefficient. In this study, we not only validated the effectiveness of our proposed methods but also identified the potential to enhance the accuracy of burned area estimations, particularly for microsatellites lacking a SWIR band.

How to cite: Kim, B. and Park, S.: Burned area detection based on Planet imagery using virtual SWIR band, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3838, https://doi.org/10.5194/egusphere-egu24-3838, 2024.

Over the last decades, the frequency and magnitude of wildfires increased worldwide, posing a risk not only for people and infrastructure, but also for the environment. To enable preventive and protective measures it is crucial to monitor and forecast wildfire hazards. Existing systems derive wildfire indices from meteorological data or include remote-sensing-based observations, such as soil moisture anomalies and the state of vegetation health. However, their ability to forecast wildfire hazards into the future is very limited.

Therefore, we here suggest utilizing the potential of a global hydrological model to not only monitor, but also provide seasonal forecasts of wildfire hazards globally. To do so, we force the global water resources and use model WaterGAP by meteorological data from ERA5 reanalysis and SEAS5 seasonal ensemble forecasts. Model output, including for example soil moisture anomalies, are combined with meteorological data to derive indicators for wildfire hazards at a global scale. We assess the capability of such indicators to reflect spatio-temporal pattern of wildfire hazards during the year 2018 by performing a regional analysis.

Eventually, derived wildfire hazard indicators can be made available for stakeholders via the operational multi-sectoral global drought monitoring and seasonal forecasting system (OUTLAST) on WMO’s HydroSOS web portal.

How to cite: Trautmann, T. and Doell, P.: Towards global monitoring and seasonal forecasting of wildfire hazards based on a global hydrological model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4332, https://doi.org/10.5194/egusphere-egu24-4332, 2024.

EGU24-5196 * | Posters on site | NH7.1 | Highlight

A new publically available dataset of global seasonal prediction of fire danger 

Francesca Di Giuseppe

The European Centre for Medium range weather forecast (ECMWF) on behalf of the Copernicus Emergency Management Service (CEMS) has recently widened the fire danger data offering in the Climate Data Store (CDS) to include a set of fire danger forecasts with lead times up to 7 months. The dataset incorporates fire danger indices for three different models developed in Canada, United States and Australia. The indices are calculated using ECMWF Seasonal Forecasting System 5 (SEAS5) and verified against the relevant reanalysis of fire danger based on the ECMWF Re-Analysis (ERA5). The data set is made openly available for the period 1981 to 2023 and will be updated regularly providing a resource to assess the  predictability of fire weather at the seasonal time scale. The data set complements the availability of seasonal forecast provided by the Copernicus Emergency Management Service in real time. 

A preliminary analysis shows that globally anomalous conditions for fire weather can be predicted with confidence 1 month ahead. In some regions the prediction can extend to 2 months ahead. In most situations beyond this horizon, forecasts do not show more skill than climatology. However an extended predictability window, up to 6-7 months ahead is possible when anomalous fire weather is the results of large scale phenomena such as the El Ni\~no Southern Oscillation and the Indian Ocean Dipole, often conducive of extensive fire burning in regions such as Indonesia and Australia.

How to cite: Di Giuseppe, F.: A new publically available dataset of global seasonal prediction of fire danger, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5196, https://doi.org/10.5194/egusphere-egu24-5196, 2024.

EGU24-5375 | ECS | Orals | NH7.1 | Highlight

Global patterns of Mediterranean ecosystems recovery from recurrent fires 

Tiago Ermitão, Célia Gouveia, Ana Bastos, and Ana Russo

Over the past two decades wildfires have been increasingly disturbing many ecosystems worldwide. Among them, the Mediterranean-like climate regions have been strongly affected by recurrent events, as widely seen during the fire seasons of 2003, 2005, 2017 and 2022 in Portugal and northern Spain, as well as in Greece and southern Italy in 2007, 2021 and 2023. Additionally, Chile experienced significant fire seasons in 2015 and 2017, California faced destructive wildfires in 2018, 2020 and 2021, and Australia was affected by severe wildfires during 2019-2020.

Even though there is an observed increase of fire frequency over fire-prone regions, the Mediterranean ecosystems are in general well adapted to fire through several mechanisms to tolerate exposure to extreme conditions and recover from fire. However, climate change has been exacerbating the frequency and severity of climate extreme events, so that the pace of recovery of ecosystems from fires may be impaired, enhancing the potential of irreversible changes in vegetation communities. 

Here we assess the recovery of global Mediterranean vegetation after recurrent fires over the past two decades based on Enhanced Vegetation Index (EVI) retrieved from the MODIS sensor. To do so, we apply a statistical model to assess the recovery rate of vegetation repeatedly burned across different land cover types. Moreover, we study how fire severity, pre-fire state of vegetation and post-fire climate conditions modulate the recovery rates. Our results show a significant influence of fire severity on vegetation recovery rates globally across all Mediterranean regions, suggesting that higher severity levels may trigger the activation of the ecosystem's recovery mechanisms. Nevertheless, we also find a modulating effect of post-fire climate conditions, particularly air temperature and precipitation, on the recovery rates of burned vegetation, which highlights how compounding effects of changing disturbance regimes and climate change might destabilize ecosystems.

This study was supported by the doctoral Grant PRT/BD/154296/2022 financed by FCT under the MIT Portugal Program and was performed under the framework of DHEFEUS project, funded by Portuguese Fundação para a Ciência e a Tecnologia (FCT) (https://doi.org/10.54499/2022.09185.PTDC). The work was also funded by the FCT I.P./MCTES through national funds (PIDDAC) UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). A.R. is supported by the FCT through national funds from the MCTES within the Faculty of Sciences of University of Lisbon, through https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006.

How to cite: Ermitão, T., Gouveia, C., Bastos, A., and Russo, A.: Global patterns of Mediterranean ecosystems recovery from recurrent fires, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5375, https://doi.org/10.5194/egusphere-egu24-5375, 2024.

EGU24-5991 | Orals | NH7.1

Towards a better understanding of pyroconvective clouds using Meso-NH/ForeFire coupled model 

Flavio T. Couto, Cátia Campos, Jean-Baptiste Filippi, Roberta Baggio, Carolina Purificação, Filippe L. M. Santos, and Rui Salgado

In 2017, Portugal was affected by several mega-fire episodes, which led the convective clouds formation, i.e., pyroCumulus (pyroCu) or pyroCumulonimbus (pyroCb). The pyroCb plays a crucial role in the fire front evolution through feedback processes between the atmosphere and the fire, including increased burn and spread rates by surface wind speed and direction variations. In order to investigate the pyro-convective activity during mega-fire events, numerical simulations were performed with the Meso-NH atmospheric model coupled to the ForeFire fire propagation model. The present study considers the mega-fires occurred in Pedrógão Grande and Góis on June 17, 2017, and in Quiaios on October 15, 2017. The experiments were configured into three nested domains with horizontal resolution of 2000 m (600 km × 600 km), 400 m (120 km × 120 km) and 80 m (24 km × 24 km) for the innermost model. The vertical resolution is the same for all the nested domains, with 50 levels and a first level above the ground at 30 m height. Initial and lateral boundary conditions for the outer domain were provided by ECMWF analysis, with updates every 6 h. Heat and water vapour were emitted into the atmosphere using the ForeFire model. In this case, the fire front evolution is directly imposed from a pre-defined time of arrival map (one-way coupling) and obtained from official reports. The results from the simulation of 80 m horizontal resolution showed that in the Pedrógão Grande mega-fire, the violent fire-driven convection manifested as a pyroCb cloud. The convective column penetrated the upper troposphere, and an intense outflow originated from the pyroCb cloud. In Quiaios mega-fire, the simulation also well represented the pyro-convection phenomenon, characterised by a northward-oriented smoke plume and the development of a pyroCu cloud. This study has provided important insights into the numerical modelling of pyroconvective clouds using Meso-NH/ForeFire simulations. This study was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Ref. PCIF/MPG/0175/2019).

How to cite: Couto, F. T., Campos, C., Filippi, J.-B., Baggio, R., Purificação, C., Santos, F. L. M., and Salgado, R.: Towards a better understanding of pyroconvective clouds using Meso-NH/ForeFire coupled model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5991, https://doi.org/10.5194/egusphere-egu24-5991, 2024.

EGU24-6004 | Orals | NH7.1

Meteorological environments leading to two large fires in Southern Portugal 

Carolina Purificação, Cátia Campos, Alice Henkes, Stergios Kartsios, and Flavio T. Couto

The study is a step forward in the characterization of meteorological environments that favour the evolution of large and extreme fires in Southern Portugal. The region has some fire-prone areas which are recognized by the mega fires occurred in 2003, 2005, and 2018. Two numerical simulations were performed using the Meso-NH non-hydrostatic research model and used to investigate in detail the atmospheric environments of two large fires that occurred on 18th July 2012 and 19th June 2020. The simulations were configured using two nested domains with a 375 km × 375 km grid domain (D1) at 2.5 km horizontal resolution and a 150 km × 150 km domain (D2) at 500 m resolution added before the start of the fires. The vertical grid was configured with 50 stretched levels following the terrain. The initial and boundary conditions are provided by the 6-hourly operational ECMWF analyses. The large-scale circulation has been characterised using data obtained from the ECMWF's Meteorological Archival and Retrieval System. In addition to the large-scale circulation, namely the positioning of the Azores anticyclone and the thermal low development over the Iberian Peninsula, the results have shown the important role played by regional orography in creating favourable fire weather conditions. For instance, the high-resolution simulations showed the high daytime temperatures and sometimes overnight, low humidity, and strong wind gusts that favour fire spread. In July 2012, the typical sea breeze circulation affected the fire evolution, whereas the intense downslope winds favoured the fire spread in June 2020. The study brings useful guidelines for interpreting the impact of different mesoscale environments that may produce large fires, namely the orographic effects that can increase the fire susceptibility and vulnerability of some regions. This study was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Ref. PCIF/MPG/0175/2019).

How to cite: Purificação, C., Campos, C., Henkes, A., Kartsios, S., and Couto, F. T.: Meteorological environments leading to two large fires in Southern Portugal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6004, https://doi.org/10.5194/egusphere-egu24-6004, 2024.

EGU24-6060 | Orals | NH7.1

The research landscape of wildfire vulnerability in Austria 

Sven Fuchs, Pia Echtler, David Hausharter, Matthias Schlögl, and Maria Papathoma-Köhle

Changes in temperature and precipitation in Austria due to climate change are expected to increase the days of fire weather in the near future. Extreme wildfire events are not common in Austria, nevertheless, given climate change and an increase in the number of events in the last years, authorities and decision-makers require tools to identify vulnerable hotspots and to reduce the upcoming risk in the Wildland Urban Interface. A number of projects ran by the University of Natural Resources and Life Sciences in Vienna focus on the assessment of vulnerability at different levels (national and local) and different elements at risk (industrial and residential buildings, free spaces and infrastructure). We present herein the current research landscape on the field in Austria and more specifically the projects PHLoX (StartClim), REVEAL (Waldfonds), and FIREPRIME (DG ECHO). Each project is based on expert knowledge and data-driven approaches and deals with different elements at risk and vulnerability indicators emphasising the need for participatory methods for wildfire risk management. We demonstrate how these projects can serve as a blueprint for increased wildfire resilience in Europe and beyond.

How to cite: Fuchs, S., Echtler, P., Hausharter, D., Schlögl, M., and Papathoma-Köhle, M.: The research landscape of wildfire vulnerability in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6060, https://doi.org/10.5194/egusphere-egu24-6060, 2024.

EGU24-6108 | Orals | NH7.1

Assessing ECMWF Lightning Forecast in Portugal during fire seasons 

Cátia Campos, Flavio T. Couto, Filippe L.M. Santos, João Rio, Teresa Ferreira, Carolina Purificação, and Rui Salgado

Portugal is one of the European countries that faces significant challenges with wildfires. While lightning-triggered natural fires constitute a minority compared to anthropogenic ones, accurate forecasting of lightning occurrences is crucial for effective prevention. The study assesses the ECMWF model's capability to predict lightning in Portugal over four fire seasons [2019-2022]. Observed lightning data was obtained from the national lightning detector network, aggregated into 0.5° and 1° resolutions over 3-hour periods. The evaluation employs statistical indices from a contingency table to analyze the model's performance. Results indicate an overestimation of lightning occurrences by the ECMWF model, with a Bias greater than 1. The success rate for lightning prediction was 57.7% for a horizontal resolution of 1° and 49% for 0.5°. Additionally, the temporal analysis reveals a time lag between both data, with the model starting to predict lighting before its occurrence and finishing the prediction earlier. These findings are complemented by analyzing the spatial lightning distribution, which led us to identify some weather patterns associated with lightning activity during the study period. For instance, lightning activity was associated with the Iberian thermal low development overlapped by an Upper Level Low and the passage of large-scale features, such as frontal systems. The insights gained from this study have implications for the ECMWF lightning forecast applicability in the context of forecasting natural forest fires in Portugal. The research was funded by the European Union through the CILIFO project (0753-CILIFO-5-E) and also by national funds through FCT Foundation for Science and Technology, I.P. under the PyroC.pt project (PCIF/MPG/0175/2019).

How to cite: Campos, C., Couto, F. T., Santos, F. L. M., Rio, J., Ferreira, T., Purificação, C., and Salgado, R.: Assessing ECMWF Lightning Forecast in Portugal during fire seasons, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6108, https://doi.org/10.5194/egusphere-egu24-6108, 2024.

EGU24-6133 | Posters on site | NH7.1

Nearly all of the increase in summer forest fires in California since 2001 is directly attributable to human-caused climate change 

Marco Turco, John T. Abatzoglou, Sixto Herrera, Yizhou Zhuang, Sonia Jerez, Donal D. Lucas, Amir AghaKouchak, and Ivana Cvijanovich

This study delves into the increasing extension of summer forest fires in California, primarily driven by anthropogenic climate change (Turco et al. 2023). Historical data indicate a fivefold increase in summer burned area (BA) in forests in northern and central California from 1996 to 2021 relative to 1971 to 1995. Using the latest simulations developed for climate change attribution and detection studies and accounting for the uncertainties arising from the data-driven climate-fire model, climate models, and internal climate variability, we have investigated the impact of anthropogenic climate change on the observed increase in BA in California’s forests. We detect the signal of combined natural and anthropogenic forcing on the observed BA starting in 2001 while finding the observed BA changes to be inconsistent with internal variability or natural forcing alone. We estimate that climate simulations that included both human and natural forcings yield 172% more BA from 1971 to 2021 than models without anthropogenic forcing, with a remarkable +320% increase from 1996 to 2021. Considering the significance of anthropogenic climate change for the rise in forest BA in California, we pose a crucial question: what will the future of fires look like with ongoing climate changes? Addressing this, we evaluate how fuel limitations resulting from fire-fuel feedbacks might alter future fire trajectories under the influence of anthropogenic climate change. Dynamic models incorporating various feedback strengths suggest an expected further increase in annual average forest BA, ranging from 3 to 52% compared to the mean of the last two decades (2001-2021), which also marks the highest 20-year records since 1971. This highlights the imperative for proactive adaptation strategies. Our findings underscore the urgent need to address the impacts of climate change within fire management and policymaking.

How to cite: Turco, M., Abatzoglou, J. T., Herrera, S., Zhuang, Y., Jerez, S., Lucas, D. D., AghaKouchak, A., and Cvijanovich, I.: Nearly all of the increase in summer forest fires in California since 2001 is directly attributable to human-caused climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6133, https://doi.org/10.5194/egusphere-egu24-6133, 2024.

EGU24-6456 | Orals | NH7.1 | Highlight

The FISC-Cerrado near-real time web-system for predicting fire spread 

Ubirajara Oliveira and Britaldo Soares-Filho

Firefighting has become increasingly difficult and costly due to climate change. In response, new tools, including online platforms, are emerging to help prevent and promptly combat ever more destructive wildfires. While those initiatives only provide maps of fire risk based on environmental and climatic conditions, which in general have a medium predictive capability, fire propagation models, although successful in predicting fire behavior and spread, particularly at local scale, can become impractical during emergency situations, since they require lots of spatial data that must be obtained, processed and input by the user. To overcome these limitations, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires in South America. The system, named as FISC-Cerrado, automatically uploads hot pixels and satellite data to calculate maps of fuels loads, vegetation moisture, and post-probability of burning for simulating fire spread thrice a day for the entire Cerrado at 25 ha and for nine conservation units at 0.09 ha spatial resolution. Unlike the requirements to operate fire spread models, the user-friendly interface of FISC-Cerrado, alongside the automatization of the entire chain of tasks, allows its use by practitioners who do not have technical skills, such as GIS knowledge. Model results together with ancillary data, e.g., historical burned areas and annual CO2 emissions from fires, are available on an interactive web-platform (https://csr.ufmg.br/fipcerrado/en/), which is being used for daily operations by the fire brigades of the selected conservations units. 

How to cite: Oliveira, U. and Soares-Filho, B.: The FISC-Cerrado near-real time web-system for predicting fire spread, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6456, https://doi.org/10.5194/egusphere-egu24-6456, 2024.

EGU24-6539 | Orals | NH7.1

Assessing Wildfire Vulnerability in the absence of empirical data: the REVEAL Project 

Maria Papathoma-Koehle, Pia Echtler, Sven Fuchs, Matthias Schlögl, Mortimer Müller, and Harald Vacik

Changes in temperature and precipitation in the European Alps are reflected in an increasing number of wildfire events and burnt areas. Therefore, apart from conducting research on the behaviour of wildfires in regions with high fire danger, it is important to analyse the vulnerability of settlements, buildings, and infrastructure also in areas with less experience with the impacts of an increasing wildfire hazard. Studies focusing on the vulnerability of the built environment do exist, but they are mostly limited to the interaction of buildings with fire, rather than offering a tool to measure this vulnerability for planning and conducting risk reduction measures. We attempt to close this gap by assessing the physical vulnerability of elements at risk located at the Wildland Urban Interface (WUI) in several case study areas in the Austrian Alps. In the absence of empirical data and by using a co-creation approach, we engage experts from various domains (firefighters, managers, planners, and government officials) to develop a tool for wildfire risk management. The tool is based on indicators to assess the vulnerability of different characteristics of elements at risk, including residential buildings, hotels, industry, critical infrastructure, and cultural heritage. Applications in each case study area are designed to demonstrate the usability of the tool in various disaster risk reduction activities and different contexts with a high or low wildfire danger. A final workshop is planned to ensure the dissemination of the results in the entire wildfire community. The resulting REVEAL decision support tool should be applicable not only in other regions of Austria, but also in other European regions that do not have experience and empirical data related to the impacts of wildfire events on infrastructure.

How to cite: Papathoma-Koehle, M., Echtler, P., Fuchs, S., Schlögl, M., Müller, M., and Vacik, H.: Assessing Wildfire Vulnerability in the absence of empirical data: the REVEAL Project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6539, https://doi.org/10.5194/egusphere-egu24-6539, 2024.

EGU24-6775 | ECS | Orals | NH7.1

Canada’s Wildfire Susceptibility Assessment Using Statistical Data-Driven Models 

Khabat Khosravi and Aitazaz Farooque

Abstract

Wildfire Susceptibility Assessment (WSA) is one of the critical approaches to wildfire risk management. In this study, we employed a hybrid approach by integrating two distinct statistical models, namely Frequency Ratio (FR), Weight of Evidence (WoE), with Shannon Entropy (SE) (i.e., FR-SE and WoE-SE) for WSA. To meet the aim, 18538 historical wildfire data were collected and separated into two sections for model development and validation. Next, 13 wildfire-influencing parameters, including slope degree, aspect, topographic wetness index, elevation, evapotranspiration, land use/land cover, normalized differences vegetation index, distance from the lake, precipitation, distance from the rivers, distance from the roads, soil moisture, and mean annual maximum temperature were prepared and feed the models. Finally, model performance were evaluated using the validation data set and receiver operating characteristic (ROC) curve technique. Findings shows that the integration of models has improved the modeling performance, as WOE-SE model has the highest performance (96.5%), followed by WoE (96.3%), SE-RF (95.9%) and RF (95.2%) model respectively. Result of SE model showed that mean annual maximum temperature has the highest impact on the wildfire occurrence across Canada, while topographic wetness index is the lowest effective parameter.

Keywords: Wildfire, statistical models, Canada, Shannon Entropy, Frequency ratio, Weight of Evidence.

How to cite: Khosravi, K. and Farooque, A.: Canada’s Wildfire Susceptibility Assessment Using Statistical Data-Driven Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6775, https://doi.org/10.5194/egusphere-egu24-6775, 2024.

EGU24-7211 | ECS | Posters on site | NH7.1

Development of wildfire detection and trajectory tracking system using scanning LiDAR 

Dasom Lee, Kwanchul Kim, Seong-min Kim, Jeong-Min Park, Gahye Lee, and Young J. Kim

Recently, several huge wildfires in South Korea caused record-breaking damage and casualties. In addition, wildfire occurrence and the amount of damages showed an increasing trend from the 1970s to the 2020s. Moreover, wildfires have become a major concern for the public and key ministries. Thus, the Korean government has been operating various wildfire observation systems using watch towers, CCTV, sensors, observers, etc. However, these systems have spatiotemporal and technical limitations such as short effective distances and discontinuous monitoring. Despite remarkable advances in wildfire detection, it remains challenging to early detect rapidly long-range wildfire events. Here, we developed equipment for early wildfire detection based on scanning Light Detection and Ranging (LiDAR) as a proof of concept to fill that void. Existing scanning LiDAR is used to track and monitor aerosol plumes providing multi-dimensional views of atmospheric layers. An early wildfire detection system using scanning LiDAR has improved for detection of wildfire smoke within 15 minutes with an enhanced spatial distance over a 10km radius and contained both eye safety function and trajectory tracking for point of ignition using HYSPLIT-based Emissions Inverse Modeling System for wildfires (HEIMS-fire).  We showed that the enhanced system continuously detected fire and smoke in rural areas during the day and night. The developed scanning LiDAR system can likely be used for early wildfire detection to prevent large-scale disasters.

Acknowledgement: This research was supported by a grant (2023-MOIS-20024324) of Ministry-Cooperation R&D Program of Disaster-Safety funded by Ministry of Interior and Safety (MOIS, Korea).

How to cite: Lee, D., Kim, K., Kim, S., Park, J.-M., Lee, G., and Kim, Y. J.: Development of wildfire detection and trajectory tracking system using scanning LiDAR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7211, https://doi.org/10.5194/egusphere-egu24-7211, 2024.

EGU24-7851 | Orals | NH7.1

Investigating fuels, fuel moisture and fire severity in the Bohemian-Saxon Switzerland region (Czech Republic/Germany): the need for dynamic fire risk assessment and management  

Christopher Marrs, Kristina Beetz, Johanna Kranz, Konrad Bauer, Evripidis Avouris, Markéta Poděbradská, Daniel Kinalczyk, and Matthias Forkel

Until recently, forest fires were considered a rare phenomenon in the temperate forests of Central Europe due to the moderate summer temperatures and the humid climate. However, many of those forests (e.g. monocultures of Picea abies, Norway Spruce) were affected by bark beetle infestations in the past years and recent fires such as in the Bohemian-Saxon Switzerland in 2022 raised widespread debates about the effects of forest mortality on fuel accumulation and hence fire occurrence and severity. Here we mapped and investigated fuel types, fire severity and started to continuously monitor fuel moisture in the Bohemian-Saxon Switzerland. We enhanced a European fuel type classification with a class for dead and dying spruce and mapped fuel types. Satellite observations from VIIRS, Sentinel-2 and Landsat were used to map fire intensity and severity of the fire from 2022.

We found the highest fire intensities at sites with dead spruce forests and single beech trees. Burn severity was moderate with high variability across all fuel types but highest severities occurred in dead spruce stands. Fire severity derived from satellite observation correlated positively with char height and torched trees, especially seen in dead spruce stands, which was likely caused by the high amount of dry fine woody debris and the initial natural regeneration. Our results demonstrate that surface fuel accumulation from past bark beetle disturbances resulted in more intense fires and higher burn severity. The results demonstrate that the recent rapid changes in Central European temperate forests cause a need for a dynamic mapping and monitoring of fuel types and fuel moisture for fire risk assessment and for cross-border fire risk management in landscapes previously not considered as fire-prone.

How to cite: Marrs, C., Beetz, K., Kranz, J., Bauer, K., Avouris, E., Poděbradská, M., Kinalczyk, D., and Forkel, M.: Investigating fuels, fuel moisture and fire severity in the Bohemian-Saxon Switzerland region (Czech Republic/Germany): the need for dynamic fire risk assessment and management , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7851, https://doi.org/10.5194/egusphere-egu24-7851, 2024.

EGU24-8266 | Orals | NH7.1 | Highlight

Spatio-temporal patters of fire in humid-Atlantic Europe: is vegetation phenology rather than fire weather the key driver?  

Stefan Doerr, Tadas Nikonovas, Cristina Santin, Gareth Clay, Claire Belcher, and Nicholas Kettridge

Fire weather indices are used widely as predictors for landscape fire potential. However, for the United Kingdom (UK: England, N-Ireland, Scotland and Wales) and comparable regions of humid-Atlantic Europe, they do not correlate well with fire occurrence. Here we explore the role of vegetation phenology as a key driver for fire occurrence in the UK.

We mapped satellite-derived fire occurrence and phenology climatology for 2012-2023 onto main fire-affected vegetation cover types within distinct precipitation regions for the UK. This enabled fire occurrence for fuels in different phenological phases to be explored across distinct ‘fuel’ types and regions.

Semi-natural grassland and dwarf shrub-dominated land emerged as the prominent fire affected ecosystems across much of the UK. We found that, critically, fire occurrence for vegetation at its maximum greenness were reduced by a factor of five to six compared to dormant vegetation, despite higher fire weather indices being typically associated with the former.

In contrast to most regions of the world that exhibit more extreme fire weather, fire activity in the UK’s humid Atlantic climate therefore seems strongly governed by vegetation phenology. This suggests that incorporating vegetation phenology is la critical step in the development of robust fire risk and behaviour prediction systems for regions with similar climate. It should be noted, however, that we also found evidence of that this fire-suppressing phenology barrier can be broken during extreme summer heat/drought events, which are likely to increase in frequency and severity under changing climate.  Hence fire weather indices remain critical predictors during the currently still rare extreme summer heat/drought events.

How to cite: Doerr, S., Nikonovas, T., Santin, C., Clay, G., Belcher, C., and Kettridge, N.: Spatio-temporal patters of fire in humid-Atlantic Europe: is vegetation phenology rather than fire weather the key driver? , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8266, https://doi.org/10.5194/egusphere-egu24-8266, 2024.

EGU24-8496 | ECS | Posters on site | NH7.1 | Highlight

ONFIRE Dataset: Harmonizing Decades of Wildland Fire Data 

Andrina Gincheva and the ONFIRE group

We present the ONFIRE Dataset (Gincheva et al., 2023), a gridded monthly burned area (BA) data product with national wildland data from several regions: Australia (since 1950), Canada (since 1959), Chile (since 1985), Europe (since 1980) and the United States (since 1984), covering up to the year 2021. This database is organised on a uniform 1° × 1° grid, providing a consistent spatial resolution for global analysis. Records from different sources and regions have been extracted and harmonised using open and reproducible methods. The data remapping and validation process ensures consistency and comparability between different regions. This dataset complements existing remotely sensed databases, offering users the opportunity to explore and analyse changes in fire regimes. The ONFIRE Dataset is accessible on Zenodo (https://zenodo.org/records/8289245; Gincheva  & Turco,  2023).

References

Gincheva, A., Pausas, J. G., Edwards, A., Provenzale, A., Cerdà, A., Hanes, C., ... & Turco, M. (2023). A monthly gridded burned area database of national wildland fire data (ONFIRE).

Gincheva, A., & Turco, M. (2023). ONFIRE dataset: Monthly Gridded Burned Area data (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8289245

Acknowledgements

A.G. thanks to the Ministerio de Ciencia, Innovación y Universidades of Spain for Ph.D. contract FPU19/06536. M.T. acknowledges funding by the Spanish Ministry of Science, Innovation, and Universities through the Ramón y Cajal Grant Reference RYC2019-027115-I and through the project ONFIRE, grant PID2021-123193OB-I00, funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”. S.J. acknowledges funding by the MCI/AEI Ramón y Cajal Grant Reference RYC2020-029993-I. M.B., A.P., and M.M. acknowledge the support of the European Union - NextGenerationEU in the framework of the National Biodiversity Future Center of Italy; A.P. and M.M. acknowledge the support of the EU project FireEUrisk, grant no. 101003890. M.E.G acknowledges research support provided by ANID/FONDECYT N° 1231573 and ANID/FONDAP 15110009; COD 1522A0001. R.L. was supported by FAPERJ (Grant E-26/200.329/2023) and CNPQ (Grant 311487/2021-1). M.M.B. acknowledges funding from the New South Wales Government (NSW Bushfire and Natural Hazards Research Centre) and the Australian Research Council (DP 220100795). F.M. and E.C. were supported by the European Space Agency FireCCI project. 

How to cite: Gincheva, A. and the ONFIRE group: ONFIRE Dataset: Harmonizing Decades of Wildland Fire Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8496, https://doi.org/10.5194/egusphere-egu24-8496, 2024.

EGU24-8971 | ECS | Orals | NH7.1 | Highlight

Projected impacts of climate change in forest fires and wind damage in Fennoscandia 

Outi Kinnunen, Leif Backman, Juha Aalto, and Tiina Markkanen

Climate change alters boreal forest dynamics. The risk of boreal forest disturbances are expected to increase by the end of the century compared to the current state. However, projecting the future impacts of climate change on forest disturbances inherently contains uncertainties related to the global climate models.

Here, we study the impact of climate change on forest fires and wind damage using ecosystem model (JSBACH) simulations from 1951 to 2100. The simulations are driven by output from three global climate driver models that have been bias-corrected and downscaled (CORDEX EUR-44 domain). The global models from CMIP5 were run under two forcing scenarios, RCP 4.5 and RCP 8.5. To tackle the uncertainty of climate change projections, we use six climate projections.

In our simulations the fire season in Fennosscandia is projected to extend in both spring and autumn. The fire season is estimated to lengthen by 20-52 days, starting 10-23 days earlier and ending 10-30 days later, by the end of the century. In general, it is expected that the number of fires and burnt area are projected to increase from the reference period (1981-2010) to the end of the century (2071-2100) due to rising temperatures, despite increases in precipitation. However, the amount and direction of change varies significantly between climate projections and locations.

Our preliminary results implicate that the risk for wind damage may change and affect to the number of fires. Wind damage affects the size of litter pools that change the amount of fuel available for fires. Finally, our aim is to study the interaction between forest fires and wind damage in boreal forests.

How to cite: Kinnunen, O., Backman, L., Aalto, J., and Markkanen, T.: Projected impacts of climate change in forest fires and wind damage in Fennoscandia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8971, https://doi.org/10.5194/egusphere-egu24-8971, 2024.

EGU24-9001 | ECS | Posters on site | NH7.1 | Highlight

Unveiling RISICO 2024: Enhancing Wildfire Forecasting through Cutting-Edge Updates 

Nicolò Perello, Andrea Trucchia, Giorgio Meschi, Mirko D'Andrea, Silvia Degli Esposti, and Paolo Fiorucci

The socio-economic changes over recent decades, marked by rural abandonment and fuel accumulation, coupled with the impact of climate change altering spatio-temporal weather patterns, have created conditions conducive to potential extreme wildfire events. Numerous wildfire management systems have thus faced significant challenges, leading to an additional push to develop or improve decision-support tools. Forest Fire Danger Rating models have been widely used by wildfire management systems in recent decades, aiding in daily operations planning and the production of fire bulletins.

Since the year 2000, independent research programs conducted by the Liguria Region in Italy, and subsequently by the Italian Civil Protection, have led to the creation of the Forest Fire Danger Rating system known as RISICO. The system incorporates meteorological observations and forecasts from Limited Area Models, utilizing vegetation cover and topography as additional inputs to enhance its capabilities. The system is currently adopted at the national level in Italy by the Civil Protection system (Dipartimento della Protezione Civile), supporting the production of the national daily fire danger bulletin, and by several regional authorities.

Over the past year, significant efforts have been made to upgrade the model. Specifically, a new fuel map based on fire susceptibility obtained through Machine Learning techniques has been proposed. This new approach allows for the structured integration of wildfire susceptibility information within the assessment of wildfire danger. Given the importance RISICO places on information about fuel classes, this approach allows a focus on fuel conditions that, when combined with specific meteorological conditions, can lead to extreme wildfire events. Furthermore, the Fine Fuel Moisture component of RISICO has been modified in its dynamics and calibrated using observed data from fuel sticks. This modification aims to better identify prolonged conditions of dry fuel that facilitate the ignition and spread of fires. Finally, the Rate of Spread model has been enhanced through the integration of the PROPAGATOR wildfire spread model's approach, with the goal of providing a more accurate description of the interaction between wind and topography.

The updated model was subsequently validated using fires that occurred in Italy from 2007 to 2022 and compared with the model's performance before the modifications. The results demonstrate an improvement in the model's ability to identify situations particularly dangerous for fire ignition and spread. The updated model, therefore, enhances the prediction of wildfire danger, providing scientific support in the decision-making process and promoting effective wildfire management.

How to cite: Perello, N., Trucchia, A., Meschi, G., D'Andrea, M., Degli Esposti, S., and Fiorucci, P.: Unveiling RISICO 2024: Enhancing Wildfire Forecasting through Cutting-Edge Updates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9001, https://doi.org/10.5194/egusphere-egu24-9001, 2024.

EGU24-9132 | Posters on site | NH7.1 | Highlight

Local feature importance of predisposing variables to explain the spatial heterogeneity of wildfires density in the Mediterranean area  

Marj Tonini, Giorgio Meschi, Andrea Trucchia, and Paolo Fiorucci

In the southern European countries, the combination of climate change, substantial shifts in land use/land cover, and socio-economic factors acting over the last decades are anticipated to increase the frequency, scale, and intensity of wildfires unless enhanced prevention and control strategies are implemented. Statistical and data-driven approaches are widely used by researchers to evaluate the main variables controlling wildfires occurrences and spreading. Lately machine learning proved to be highly performant due to its flexible and non-linear nature, capable of capturing the complexity of the wildfire process. Nevertheless, conventional classification and regression methods like Support Vector Machine, pixel-based Neural Network, and Random Forest (RF), are global modelers, not calibrated to deal with the spatial heterogeneity of the investigated area. Thus, these algorithms turn out to be incapable of adequately addressing the spatially varying underlying relationship between wildfires pattern distribution and the predisposing variables.

While many studies seek to assess the importance of the predictor variables both at regional [1, 2] and at supranational level [3], up to now there is a lack of studies attempting to account for the spatial heterogeneity (i.e. non-stationarity) when modeling wildfires spatial patterns as function of geographical features.  To fill this gap, the present work explores the local feature importance of geographical independent predisposing variables on the spatial distribution of burned area density in the Mediterranean area. To this end, we have used the last development of Geographical Random Forest (GRF) [4], which integrates a parallelizable RF function, a procedure for the bandwidth optimization, and an option to spatially weight the local observations. As dependent variables we considered the percentage of burned pixels per map unit. Both geo-environmental features (i.e., variables providing information on the topography and land cover) and anthropogenic features (e.g., distances to urban areas and road network) have been select as predictors. The importance of these independent variables has been assessed by evaluating the Mean Decrease Accuracy (MDA) by using the Out of Bag samples available in RF: higher values mean that the model strongly benefits from the given variable when performing predictions. The spatial variation of each predisposing factor was illustrated by mapping the corresponding MDA values over the geographical space. Finally, the implemented model has been validated by using the root mean squared error computed over an independent testing dataset.   

[1] Trucchia A, Izadgoshasb H, Isnardi S, Fiorucci P, Tonini M, 2022. Machine-Learning Applications in Geosciences: Comparison of Different Algorithms and Vegetation Classes' Importance Ranking in Wildfire Susceptibility. Geosciences, 12 (11) p. 424. 

[2] Bustillo Sánchez M, Tonini M, Mapelli A, Fiorucci P, 2021. Spatial Assessment of Wildfires Susceptibility in Santa Cruz (Bolivia) Using Random Forest. Geosciences, 11 (5) p. 224. 

[3] Trucchia A, Meschi G, Fiorucci P, Provenzale A, Tonini M, Pernice U, 2023. Wildfire hazard mapping in the eastern Mediterranean landscape. International Journal of Wildland Fire. 32, 417-434. 

[4] Georganos S, Kalogirou S, 2022. A Forest of Forests: A Spatially Weighted and Computationally Efficient Formulation of Geographical Random Forests. ISPRS Int. J. Geo-Inf. 2022, 11, 471. 

How to cite: Tonini, M., Meschi, G., Trucchia, A., and Fiorucci, P.: Local feature importance of predisposing variables to explain the spatial heterogeneity of wildfires density in the Mediterranean area , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9132, https://doi.org/10.5194/egusphere-egu24-9132, 2024.

As socio-natural hazards, future extreme wildfires across Europe are exacerbated by two main drivers: climate change and socioeconomic dynamics. While modelling studies account for changes in fire danger and area burned under different climate scenarios, they largely disregard the impacts of land use change, or the interaction with adaptation through changes in vegetation management. This creates uncertainties regarding the role of anthropogenic processes and the reliability of projections under various policy scenarios. Next to the interaction with wildfire hazard, socioeconomic processes are shaping all dimensions of wildfire risk. Building on the IPCC notion that risk arises at the intersection of hazard, exposure and vulnerability, we screen the relevant empirical literature to identify key socioeconomic drivers of wildfire risk in a European context and bring this together with the Shared Socioeconomic Pathways (SSP) perspectives on plausible socioeconomic futures. The resulting wildfire risk scenario space serves two main purposes: (i) providing a qualitative navigator for incorporating socioeconomic uncertainty in model-based wildfire risk assessments and (ii) establishing boundary conditions for evaluating the feasibility of management strategies. Applying the SSP framework for envisioning plausible development trajectories, we systematically investigate the role of socioeconomic dynamics in determining future wildfire risk. Sustainable land use practices and profitable agricultural value chains reduce hazard (e.g. SSP1), while factors like poor environmental regulation (e.g. SSP5) and increasing pressure on land abandonment as competitive value chains disappear (e.g. SSP4), increase this dimension of wildfire risk. Exposure remains high across scenarios for different reasons. Ineffective land use planning contributes to the expansion of human settlements in areas dominated by unmanaged flammable vegetation (e.g. SSP3, SSP5), with a further escalation of livelihood exposure on poorly managed agricultural land (e.g. SSP4). Vulnerability becomes a distinctive driver of wildfire risk in scenarios with low rates of economic development and poor investment in human capital (e.g. SSP3, SSP4). While increased socioeconomic welfare may enhance coping capacities in the context of wildfires (e.g. SSP1, SSP5), the prioritization of business-related objectives in institutional risk management (e.g. SSP5) poses a risk of neglecting other critical aspects. As wildfires transition from a climate hazard into a potential disaster at the intersection with exposure and differential vulnerabilities, we emphasize the importance of addressing all three dimensions of risk. By expanding the view of future wildfire risk, we show that challenges to wildfire risk management differ significantly between scenarios. Social, economic and socioecological challenges may lead to paradoxical situations in managing wildfire risk. In scenarios, where vulnerability reduction has maximum leverage in reducing risk, socioeconomic challenges hinder the feasibility of implementing the measures necessary to achieve it. Similar dilemmas may arise in the context of hazard and exposure. By considering multiple plausible futures, this work stresses the importance of considering socioeconomic dynamics in shaping wildfire risk and keeping the design of risk management strategies open and flexible to adapt to changing circumstances.  

 

How to cite: Preinfalk, E. and Handmer, J.: Fuelling the fires - An exploration of the drivers and the scope for management of European wildfire risk under the Shared Socioeconomic Pathways , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10384, https://doi.org/10.5194/egusphere-egu24-10384, 2024.

EGU24-10974 | Orals | NH7.1

The exceptionality of the 2022 fire season over Central Europe 

Célia M. Gouveia, Alexandre M. Ramos, Mafalda C. Silva, Rita Durão, A. Serkan Bayar, and Joaquim G. Pinto

The frequency and intensity of temperature extremes have increased worldwide in the past couple of decades. The year 2018 was characterized by record-breaking temperatures in many parts of Europe during spring and summer, which lead to unusual and severe wildfires in central and northern Europe. For example, devastating fires destroyed large areas of intact forests, not only in countries with a long tradition of wildfires but also in countries, such as Sweden, Norway, Finland, and Latvia.  In 2022, Europe was characterized   by a prolonged spring drought, several summer heatwaves and fire activity without precedents for several European countries. In particular, a high number of fires occurred in Germany, Austria, Chechia, Hungary, Slovenia and Romania during the summer months, highlighting the increase of fire-prone conditions in the region linked with an increase of hot and dry conditions.

This work analyses the exceptionality of the 2022 fire season over central Europe. Fire Radiate Power (FRP) from MODIS, burned area and number of fires from EFFIS were used to characterize fire occurrence in 2022. We used ERA5 meteorological parameters, such as the maximum and minimum air 2m temperature, minimum relative humidity, and wind speed to evaluate the severity of the heat extremes from April to August. SPEI for the time scales of 6 and 12 months were computed using ERA5 data to evaluate the drought conditions in spring and summer over the central European region. The Canadian Fire Weather Index (FWI) and sub-indices available from ERA5 data, were used to assess the exceptionality of meteorological fire danger over the region in the summer of 2022.  Moreover, possible FWI trends and sub-indices were also analysed for the period from 1979 to 2022. The impact of drought on vegetation productivity during the spring and summer of 2022 was also evaluated. Results highlight the new fire dynamics in Europe in recent years, with new emergent hot spots, in central and northern European countries. It is thus extremely important to assess of trends of fire danger and changes in fire activity over this region to better define the related activities of fire monitoring, as well as the definition of planning activities and suppression measures towards climate mitigation and adaptation.

Acknowledgements: This study is partially supported by the European Union’s Horizon 2020 research project FirEUrisk (Grant Agreement no. 101003890) and by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020- IDL and DHEFEUS - 2022.09185.PTDC.

How to cite: Gouveia, C. M., Ramos, A. M., Silva, M. C., Durão, R., Bayar, A. S., and Pinto, J. G.: The exceptionality of the 2022 fire season over Central Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10974, https://doi.org/10.5194/egusphere-egu24-10974, 2024.

EGU24-10990 | Orals | NH7.1 | Highlight

Global warming increases population exposure to wildfires  

Luiz Galizia, Christelle Castet, and Apostolos Voulgarakis

Wildfires are expected to increase under warmer and drier conditions, yet little is known about their potential effects on population at global scale. Here, we developed a novel framework based on statistical wildfire model and spatial demographic data to better understand how global warming alters population exposure to wildfires throughout the world. We sought to model annual burn rate with relevant explanatory variables, such as climate, land cover, and topography to simulate historical and future wildfire frequency at global scale. To do so, we used a Generalized Additive Model combined with historical climate data and an ensemble of CMIP6 climate projections under the SSP5-8.5 scenario. We then analysed population exposure to wildfires combining population count across the wildland–urban interfaces with the simulated historical and future wildfire frequency. Our results indicate that in the present day the highest population exposure to wildfires is in southeast Asia, parts of South America and Africa, due to the large number of people living in wildland–urban interfaces with a high wildfire frequency. All other things being equal, global warming was found to increase population exposure, with an expansion of the regions with high wildfire frequency in east and south Europe, southeastern Asia, parts of North and South America. The estimated increase in population exposure may also imply potential impacts on the built environment and human health in the absence of mitigation or adaptation measures.

How to cite: Galizia, L., Castet, C., and Voulgarakis, A.: Global warming increases population exposure to wildfires , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10990, https://doi.org/10.5194/egusphere-egu24-10990, 2024.

EGU24-11261 | ECS | Posters on site | NH7.1

Forests on fire: Effects of input data resolution on forest fire behaviour modelling – A case study from Lower Austria 

Katrin Kuhnen, Maria Isabel Asensio, José Manuel Cascón, José Manuel Iglesias, Mariana Silva Andrade, Tatiana Klisho, Herbert Formayer, and Harald Vacik

Forest fires are becoming an important hazard in the mountain forests of European alpine areas due to changing environmental and socio-economic conditions. Understanding the fire behaviour is critical for all phases within the disaster management cycle – from prevention and preparedness to response and recovery. PhyFire is a simplified physical model which simulates the fire propagation and allows considering fire suppression measurements to see their effect on the fire behaviour. The model has been used for Mediterranean countries so far but has been now adapted to central European alpine mountain forests within this case study. The model requires the following input data: a digital height model, fuel data, and meteorological data. Besides the adaption process itself the effect of different qualities of input data in terms of temporal and spatial manner were investigated. In this contribution we show the challenges of the adaption process of the PhyFire model to the characteristics of the Austrian case study area and analyse the effect of different resolutions of input data resolution on the overall quality of the fire propagation simulation.

How to cite: Kuhnen, K., Asensio, M. I., Cascón, J. M., Iglesias, J. M., Andrade, M. S., Klisho, T., Formayer, H., and Vacik, H.: Forests on fire: Effects of input data resolution on forest fire behaviour modelling – A case study from Lower Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11261, https://doi.org/10.5194/egusphere-egu24-11261, 2024.

EGU24-11570 | ECS | Orals | NH7.1

Persistent positive anomalies in geopotential height drive enhanced wildfire activity across Europe 

Kerryn Little, Dante Castellanos-Acuna, Piyush Jain, Laura Graham, Nicholas Kettridge, and Mike Flannigan

Persistent positive anomalies in 500 hPa geopotential height (PPAs) are upper-air circulation patterns associated with surface heatwaves, drought, and consequently fuel aridity, elevated fire weather, and active wildfires. We examined the association between PPA events and surface fire weather and burned area at a pan-European level. Europe-wide, extreme fire weather and wildfires were on average 3.5 and 2.3 times more likely to occur concurrently with a PPA, respectively. PPAs were associated with 43% of pan-European area burned between March and October 2001–2021, and there was a latitudinal increase in the percentage of area burned during PPAs up to 60% over Northern Europe. Burned area was highest in the three days following PPA presence, and fuel moisture indices from the Canadian Fire Weather Index System lagged behind peak PPA strength, demonstrating the role of PPAs in pre-drying fuels. PPAs have been associated with significant wildfire events experienced across Europe, including the 2017 Portugal wildfires, the 2018 UK, Sweden, and Finland wildfires, and the 2021 Greece wildfires. Our findings demonstrate opportunities for developing early warning systems of wildfire danger, having implications for wildfire awareness and preparedness, informing policy, and wildfire management decisions like early mobilisation and resource sharing initiatives within and across Europe.

How to cite: Little, K., Castellanos-Acuna, D., Jain, P., Graham, L., Kettridge, N., and Flannigan, M.: Persistent positive anomalies in geopotential height drive enhanced wildfire activity across Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11570, https://doi.org/10.5194/egusphere-egu24-11570, 2024.

EGU24-11983 | ECS | Orals | NH7.1

Relation between the distribution of fuel types and forest fires in Austria 

Mariana Silva Andrade, Mortimer M. Müller, Katrin Kuhnen, and Harald Vacik

The altering climate patterns contribute to variations in precipitation, temperature and overall ecosystem conditions, influencing the composition and combustibility of forest fuels in the alpine regions. Changes in vegetation patterns, with shifts in species distribution and the prevalence of dry, flammable materials, increases the risk through wildfires. Rising temperatures and prolonged periods of drought enhance the likelihood of ignition and intensify fire behavior. Thus, this research aims to carry out a comprehensive vegetation analysis to characterize the different fuel types in Austria and to provide the scientific basis for developing a detailed forest fuel map, considering various types of vegetation, topography and land cover. We use statistical models to predict fuel characteristics based on vegetation type and empirical data collected during field surveys in the recent years. The spatial distribution of fuel types will be related to an analysis of the location of historical fire data for the time period 2001-2023. A statistical analysis is done to identify clusters, patterns, and relationships for different fuel types. This integrated methodology not only enriches our understanding of the complex interconnection between vegetation fire ignition and behavior, but also provides the scientific basis for developing targeted strategies in forest fire management and improving prevention measures in Austria.

How to cite: Silva Andrade, M., M. Müller, M., Kuhnen, K., and Vacik, H.: Relation between the distribution of fuel types and forest fires in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11983, https://doi.org/10.5194/egusphere-egu24-11983, 2024.

EGU24-12598 | ECS | Posters on site | NH7.1 | Highlight

Impact of burn severity of the July 2022 forest fire on soil hydrophobicity in the Elbe Sandstone temperate forest 

Linda Emily Weis, Michael Dietze, Anette Eltner, Daniel Schwindt, Kristina Beetz, Daniel Wolf, Annika Busse, and Elisabeth Dietze

Soil water repellency is a common phenomenon often associated with wild fires, which leads to a temporal change of forest ecosystems, for example, by enhanced overland flow, soil erosion and limited plant growth. Forest fires are expected to play an increasingly larger role due to climate change, resulting in more frequent droughts, higher temperatures, heatwaves, and landcover changes in temperate latitudes. Despite that importance, only a few studies have been published concerning soil water repellency in temperate European forests, and relatively little is known about soil hydrophobicity associated with so far rare forest fires in Central European spruce and beech forests.

In this study, we examine the impact of different burn severities on soil hydrophobicity down to 15 cm below the surface in the National Park “Sächsische Schweiz” after the forest fire in summer 2022, using the Water Drop Penetration Time (WDPT) test. Measurements were limited to the conductivity or non-conductivity of the water, with the test terminated at a time of 900 s. Various parameters, that could control water conductivity were examined, including burn severity from drone data, ground vegetation, duff layer, slope angle, slope aspect, and elevation of the site. In addition, soil properties such as soil type, carbon and nitrogen contents were analysed. We find a high spatial variability of hydrophobic plots in the studied area. The most hydrophobic plots were found in low severity sites rather than in moderate-high to high severity sites. Plots lacking a duff layer were more likely to exhibit hydrophobic layers. Soil water repellency was also found in unburnt sites. No distinct correlation was found between slope angle, slope aspect, elevation and the occurrence of hydrophobic plots. Plots located in coniferous forests exhibited higher frequencies of hydrophobicity compared to deciduous forests. That large variability and non-agreement with typically formulated relationships argue for a need to rethink the transferability of assumptions from traditional fire regions such as the Mediterranean or the boreal zone to the emerging fire regimes of temperate forests under climate change, requiring more empirical data.

How to cite: Weis, L. E., Dietze, M., Eltner, A., Schwindt, D., Beetz, K., Wolf, D., Busse, A., and Dietze, E.: Impact of burn severity of the July 2022 forest fire on soil hydrophobicity in the Elbe Sandstone temperate forest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12598, https://doi.org/10.5194/egusphere-egu24-12598, 2024.

EGU24-14409 | Posters on site | NH7.1

Development of early wildfire detecting system using scanning lidar and image processing 

Kwanchul Kim, Dasom Lee, Seong-min Kim, Gahye Lee, Jeong-Min Park, Youngmin Noh, Young J. Kim, Kwon-ho Lee, Sungchul Choi, Changgi Choi, Woosuk Choi, and Chunsang Hong

Wildfires are increasing globally due to climate change. Wildfires can spread rapidly in a short period of time, early detection is important. A CCTV and thermal imaging camera are used for early detection and prevention of wildfires and improved using camera analysis method and AI technology. However, the wildfire detection distance is still shortened depending on weather conditions and air quality, and image processing performance deteriorates due to low light at night. A satellite remote sensing technology is difficult to monitor wild fires in real time and affected by cloud mask, low spatial and temporal resolution. A Drone is also limited in flight time by communication, weather conditions, battery capacity, and payload. In the case of lidar-based long-distanced wildfire monitoring, advanced remote sensing monitoring that can monitor wildfires is possible by classifying the type of aerosol particles and the amount of light backscattered by smoke particles. Our recently developed wildfire scanning lidar technology uses light sources of two wavelengths (532 nm and 1064 nm) and developed a system capable of 360° observation within 30 minutes with an angular resolution of less than 1° in the horizontal direction. In addition, it is the wildfire scanning lidar capable of detectiong a wildfire in the atmosphere using the backscattering coefficient and aerosol optical properties calculated at two wavelengths. A depolarization of smoke aerosol in the air can be used to improve the accuracy of wildfire smoke detection using characterization of particles. Presently wildfire monitoring lidar technology under development is producing commercial products that protect eyesight and monitor forest fire smoke within a radius of 10 km through long-wavelength laser and object analysis.

 Acknowledgement: This research was supported by a grant (2023-MOIS-20024324) of Ministry-Cooperation R&D Program of Disaster-Safety funded by Ministry of Interior and Safety (MOIS, Korea).

How to cite: Kim, K., Lee, D., Kim, S., Lee, G., Park, J.-M., Noh, Y., Kim, Y. J., Lee, K., Choi, S., Choi, C., Choi, W., and Hong, C.: Development of early wildfire detecting system using scanning lidar and image processing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14409, https://doi.org/10.5194/egusphere-egu24-14409, 2024.

EGU24-14466 | ECS | Orals | NH7.1

Indicator-based measurement of resilience and analysis of spatial trend in resilience to forest fire in Uttarakhand, India 

Aryalakshmi Madhukumar, Jayaluxmi Indu, and Lanka Karthikeyan

Wildfires are becoming increasingly frequent and devastating in many tropical forests. In India, nearly 6% of forest cover is highly fire-prone, and 36% is prone to frequent fires. These frequent wildfires have compound impacts on forests, which include changes in biodiversity and, forest functionality. In the short term, the burnt ecosystem cannot have the same functionality as that of a pre-fire situation. Understanding forest ecosystem health status after a fire event can help increase our ability to manage the fire seasons. 
In the current study, time series data from optical remote sensing is used to assess the forest ecosystem resilience. The study area chosen is the forest region in Uttarakhand, India, including Jim Corbett National Park, that witnessed a severe forest fire in 2016. The active fire pixels during the 2016 fire event in the area were identified, and resilience over the identified pixels was measured based on the concept of engineering resilience.  Results are presented as resilience quantified for all burnt pixels based on three different indices which represent resistance and recovery namely, time taken for recovery, maximum impact of fire event, and cumulative impact. Further, we identified how resilience differs with the type of forest cover in the study area and how well each type of forest recovers from the fire event. The findings suggest that in the Indian scenario, deciduous broadleaf forests have a longer recovery followed by evergreen broadleaf and evergreen needleleaf, while grasslands and broadleaf cropland have shorter recovery times and impacts. From this work, we aim to study forest resilience in the Indian scenario and how well this can be compared with other areas where similar climatic conditions exist. The current work has potential applications in risk governance, ecosystem management, etc. and in evaluating the post-fire processes and primary factors driving the processes. Extensive data feeds available from current satellite platforms enable the post-fire dynamics study to be more accurate, thus more informed, and faster choices by stakeholders.

How to cite: Madhukumar, A., Indu, J., and Karthikeyan, L.: Indicator-based measurement of resilience and analysis of spatial trend in resilience to forest fire in Uttarakhand, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14466, https://doi.org/10.5194/egusphere-egu24-14466, 2024.

EGU24-14686 | ECS | Orals | NH7.1 | Highlight

Machine learning based fire danger assessment framework for Indian forests  

Anasuya Barik and Somnath Baidya Roy

We developed a comprehensive fire risk assessment framework for Indian forests, divided into five distinct forest zones (Himalayan, Northeast, Central India, Deccan, and Western Ghats) characterized by diverse climatic conditions and forest types. This framework focused on three primary triggering factors: weather, fuel availability, and anthropogenic ignition.

For the weather factor, we considered the Fire Weather Index (FWI) module of the Canadian Forest Fire Danger Rating System with ECMWF's ERA5 reanalysis as meteorological inputs over the period 2003-2021. As fire weather is a dominant factor in causing fires, we developed a robust system to predict fire weather danger. We evaluated the simulated FWI against MODIS active fire data and observed that FWI was a good enough metric for fire weather danger assessment. FWI was categorized into five danger classes through an ensemble approach based on logistic regression, FWI percentiles, percentage of fires, and K-means clustering. We introduced machine learning techniques to reduce the subjective decisions in these methods. This increased the efficiency of the danger rating system to detect fire probability well by 30-50%. A rigorous evaluation of the danger classes revealed that there was no overlap of central tendencies between different methods in the ensemble. The defined danger classes demonstrated coherent values for evaluative parameters, with a consistently high hit rate, low hits due to chance, moderate correct rejections, and an acceptable false alarm ratio.

Addressing fuel availability, we used vegetation indices (MODIS normalized difference and enhanced vegetation indices) and topographic features (aspect, elevation and slope from FLDAS land surface model). The anthropogenic ignition factor consisted of population density and land use information. In India, fragmented forests cohabitate with human settlements and agricultural lands. To quantify the impact of anthropogenic ignition on fire occurrences, we computed the percentage of built-up and agricultural area within each grid cell. We used machine learning predictive algorithms such as multiple linear regression with interactions, support vector machines, decision trees and neural networks to integrate these triggering factors with fire count as the target variable, We selected the highest-performing system as the risk assessment framework.

This country-scale fire risk assessment provides insights into regional exposure variations and serves as a foundational step towards establishing an operational fire risk assessment system for India. This framework will be of help to operational fire management agencies, enabling enhanced prediction of fire danger and informed decision-making.

How to cite: Barik, A. and Baidya Roy, S.: Machine learning based fire danger assessment framework for Indian forests , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14686, https://doi.org/10.5194/egusphere-egu24-14686, 2024.

EGU24-15304 | ECS | Orals | NH7.1 | Highlight

Modelling and Analysis of Lightning-Induced Wildfires in Australia  

Li Zhao and Marta Yebra

Lightning-induced wildfires lead to significant loss of life and extensive property damage worldwide. This issue is especially critical in southeast Australia, where such wildfires account for 80-90% of the total area burned, emphasising the need for a comprehensive understanding of the contributing factors and mechanisms that drive these events. This study aims to investigate the complex interactions between climate, topography, lightning activity, and fire events in New South Wales (NSW), Australia. By analysing comprehensive datasets from 2017-2021, including ignition records, meteorological data, topographical information, and fuel characteristics, this research seeks to identify the key factors influencing lightning-attributed wildfires and predict the probability of lightning-caused fire occurrence. A Random Forest model is trained and tested to estimate the probability of fires caused by lightning strikes. Model performance was assessed through the Receiver Operating Characteristic, with an Area Under the Curve (AUC) around 0.7 in the validation datasets, indicating a good agreement between the estimated probabilities and the reported lightning-caused fires. The identified key factors that influence lightning fire ignitions include humidity, elevation, temperature, rainfall, soil moisture, and fuel moisture, highlighting the dominant influence of weather variables on wildfire ignitions. The preliminary results demonstrate a potential link between the geographic distribution of lightning-induced fires and the temperate climate zones, possibly due to the presence of dense vegetation and seasonal weather patterns. Our ongoing efforts focus on further refining the predictive model and conducting a more extensive analysis of the data to enhance our understanding of the dynamics of lightning-induced wildfires. Ultimately the study will provide insights for effective risk management and mitigation of lightning-caused wildfires in the regions prone to wildfires.

How to cite: Zhao, L. and Yebra, M.: Modelling and Analysis of Lightning-Induced Wildfires in Australia , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15304, https://doi.org/10.5194/egusphere-egu24-15304, 2024.

EGU24-15610 | ECS | Orals | NH7.1

Spatially Consistent Fire Weather Index Predictions using Convolutional Neural Networks in Diverse Iberian Locations 

Oscar Mirones, Jorge Baño-Medina, Joaquín Bedia, Swen Brands, and Mario Santa Cruz

The accurate prediction of the Fire Weather Index (FWI) is vital for effective wildfire management and climate-resilient planning. Multisite fire hazard forecasts are crucial for resource allocation, early intervention in high-risk areas, and identifying potential “megafire” threats from multiple simultaneous fire spots. Therefore, it is very important to account for the spatial consistency of these forecasts. This study examines the performance of Convolutional Neural Networks (CNNs) as a Statistical Downscaling (SD) technique for predicting FWI in different locations in the Iberian Peninsula. We contrast CNNs with two conventional SD methods: Generalized Linear Models and analogs. Using daily observed FWI data as predictands and ERA-Interim fields as predictors under a cross-validation setup, we discover that the CNN-Multi-Site-Multi-Gaussian (CNN-MSMG) model outperforms in daily FWI forecasting. This model integrates the covariance structure of the predictands into the CNN design, producing spatially consistent FWI forecasts. Furthermore, CNN-MSMG shows desirable features for estimating fire hazard in the climate change scenario, such as strong spatial consistency of extreme events and the capacity to generalize to new climate situations. These findings have important implications for improving FWI forecast accuracy and strengthening wildfire risk evaluation under climate change.

How to cite: Mirones, O., Baño-Medina, J., Bedia, J., Brands, S., and Santa Cruz, M.: Spatially Consistent Fire Weather Index Predictions using Convolutional Neural Networks in Diverse Iberian Locations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15610, https://doi.org/10.5194/egusphere-egu24-15610, 2024.

EGU24-16369 | ECS | Posters on site | NH7.1 | Highlight

Modeling Wildfire Dynamics in Latin America Using the FLAM Framework 

Johanna San Pedro, Andrey Krasovskiy, Shelby Corning, Pavel Kiparisov, and Florian Kraxner

The increasing frequency of wildfires caused by climate change poses a significant threat globally, particularly in Latin America – a region known for its critical ecosystems. Its vulnerability to climate change-induced wildfire threats, resulting from increasing temperatures and changing precipitation patterns, is uncertain, highlighting the need for comprehensive strategies such as incorporating advanced modeling and proactive measures to understand, manage, and conserve its ecological state  in the face of  threats posed by climate change, such as wildfires. This study utilizes the wildFire cLimate impacts and Adaptation Model (FLAM) by IIASA to provide a comprehensive analysis of past and projected wildfire dynamics in Latin America. FLAM is a process-based fire parameterization algorithm used to assess the impacts of climate, fuel availability, topography, and anthropogenic factors on wildfire characteristics. It is highly adjustable and adaptable, making it suitable to analyze past and future wildfire trends in diverse regions such as Latin America. We analyzed spatial and temporal wildfire patterns using MODIS satellite data alongside historical climate and anthropogenic data to calibrate FLAM. We generated projections of burned areas until 2100 under 3 RCP scenarios for Latin American as a whole, as well as for distinct sub-regions to better assess regional wildfire dynamics and climate change impacts. Moreover, we developed a scenario to explore the impacts of increased fire suppression efficiency on projected burned area and highlight the impacts of focusing mitigation and management efforts on areas identified as hotspots (high risk of wildfire).

The study shows FLAM’s effectiveness in modeling historical wildfires and its sensitivity to the RCP scenarios in predicting wildfire trends in Latin America. Our analysis and results show how FLAM helps in evaluating the potential future changes in wildfire intensity, and geographic spread under various climatic scenarios.  FLAM projected a dramatic rise in burned area until the end of the century across Latin America in line with observed trends, especially under severe climate change scenarios. Regions with the highest temperature rises are also prone to reduced precipitation, which further increase  wildfire risks. The spatially-explicit projections highlight  areas at higher risk of wildfire, enabling targeted and efficient fire management and mitigation strategies. Our study further showed the potential impact of adaptive measures, such as enhanced fire suppression efficiency in identified hotspots, in reducing annual mean burned area. Overall, this study provides critical insights into the relationship between climate change and wildfire dynamics using a state of the art model. It sets the foundation for further research on fires in Latin America and efficient management strategies which can be modelled by FLAM.

How to cite: San Pedro, J., Krasovskiy, A., Corning, S., Kiparisov, P., and Kraxner, F.: Modeling Wildfire Dynamics in Latin America Using the FLAM Framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16369, https://doi.org/10.5194/egusphere-egu24-16369, 2024.

EGU24-16436 | ECS | Orals | NH7.1 | Highlight

Advanced Wildfire Risk Mapping: A Novel Global Approach Using AI and Socio-Ecological Data 

Alba Marquez Torres and Diego Bengochea Paz

In an era of increasing wildfire incidents worldwide, fire risk mapping has emerged as a crucial tool for ecosystem management and environmental safeguarding against the significant loss of socio-ecological value. Our research introduces a novel daily global fire risk model, combining the probability of fire ignition as a fire hazard model with an analysis of exposure and vulnerability. This model was calculated with over 4 million historical fire and non-fire ignitions recorded between 2000 and 2020 and tested with more than 24 million ignition points. It integrates key explanatory variables encompassing climatic conditions, agro-environmental factors, terrain, and social drivers at the time of fire ignition, processed through advanced machine learning techniques, such as the XBoost Random Forest algorithm.

Further enhancing our model's robustness, we incorporate a suite of socio-ecological models, previously developed using machine reasoning, an AI algorithm based on semantics, through the k.LAB platform. These models cover critical areas such as vegetation carbon mass, pollination, outdoor recreation, and soil retention, enabling us to identify regions where humans and nature are most vulnerable to fire hazards.

Adhering to FAIR principles, our approach ensures that our data and models are findable, accessible, interoperable, and reusable. This commitment not only advances scientific research but also promotes broader application and collaboration. The global fire risk model provides temporally and spatially explicit results on a daily basis, offering a dynamic and precise tool for understanding and preventing fire risks.

This research has significant implications for policymaking and emergency response planning. By offering a detailed and dynamic understanding of fire risks, stakeholders can make informed decisions that can mitigate the impact of wildfires. The combination of diverse datasets, advanced analytical techniques, and a focus on practical applications makes this model a valuable resource in the global effort to address the increasing challenges of wildfires.

How to cite: Marquez Torres, A. and Bengochea Paz, D.: Advanced Wildfire Risk Mapping: A Novel Global Approach Using AI and Socio-Ecological Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16436, https://doi.org/10.5194/egusphere-egu24-16436, 2024.

EGU24-16616 | ECS | Posters on site | NH7.1 | Highlight

Forest fire risk under a changing climate in Croatia 

Mislav Anić, Maša Zorana Ostrogović Sever, Doroteja Bitunjac, and Hrvoje Marjanović

Fire represents one of the major disturbances in natural ecosystems around the planet. By burning ecosystems, fire has a significant role in shaping global biome distribution and influences biogeochemical cycles such as the carbon cycle. Particularly in the coastal part of Croatia during the summer months, wildfires often escalate to catastrophic levels, posing serious threats to human lives, infrastructure, and the natural environment.

Our study aims to estimate the changes in forest fire danger in Croatia between 1981 and 2020 based on the Fire Weather Index (FWI) and seasonal severity rating (SSR) calculated using data from the National Meteorological Observation Network. To estimate the risk of forest fires in this region, the study utilizes the Canadian Forest Fire Weather Index System. The original system consists of six components that solely depend on meteorological conditions. The calculated FWI represents the potential fire intensity and is a very good indicator of fire danger. The initial equations are calibrated for Canadian boreal forests, characterized by distinct differences in vegetation and climate features when compared to forests of the Mediterranean regions. Despite these differences, researches have revealed a noteworthy correlation between the components of the FWI system and fire activity in Spain, Portugal, France, Italy, and Greece.

Measurements of air temperature, wind speed, and relative humidity taken at 14h, along with daily precipitation records from 83 meteorological and 119 rain gauge stations were used in the analysis. Daily severity ratings were calculated from FWI values and averaged over the fire season, spanning from June to September, to obtain SSR. The station-based SSR were spatially interpolated using regression kriging and a 1 x 1 km horizontal grid, resulting in 40 raster maps (one for each year). Results from a trend analysis, aimed at identifying areas with the highest increase in fire risk during the period 1981-2020, indicate an overall increase in SSR across a significant portion of the country. The observed trends align well with the positive trends identified in maximum air temperature and the lengthening of dry periods.

Additionally, to evaluate changes in fire weather extremes in Croatia the seasonal count of days with FWI > 30 (FWI30) and the seasonal 90th percentile of FWI (FWIp90) indices were calculated. A comparison of these indices between the periods 1981-2000 and 2001-2020 revealed an increase both in FWI30 and FWIp90 across a substantial portion of the country. These trends highlight a concerning escalation in fire risk for Croatia.

Keywords: forest fire risk, fire weather index, extreme fire weather, climate change, trends

How to cite: Anić, M., Ostrogović Sever, M. Z., Bitunjac, D., and Marjanović, H.: Forest fire risk under a changing climate in Croatia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16616, https://doi.org/10.5194/egusphere-egu24-16616, 2024.

EGU24-17032 | Posters on site | NH7.1

On the definition of an Exceptional fire danger rating over Mediterranean Countries 

Mafalda Canelas da Silva, Catarina Alonso, Rita Durão, and Célia M. Gouveia

The Mediterranean countries are largely affected by wildfires, and appropriate monitoring of daily fire danger is crucial to contribute to quick decision-making and mitigate destructive wildfire disturbances. In operational wildfire monitoring, the Canadian Forest Fire Weather Index System (CFFWIS) is one of the most used fire danger indices, particularly over the  Mediterranean region, which rates relative danger of wildfire occurrence by combining six components: three fire behavior indices and three fuel moisture codes.

Since FWI results from all components, it is evident that the short and long-term variations of meteorological variables will be reflected and the components will have different influences on FWI values. The main purpose of this work is to contribute to the definition of a new class associated with Exceptional fire weather danger, based on a statistical analysis of FWI, FFMC, and ISI indices for different Mediterranean countries, and for the months between June and October of 2010-2023 period and information of Fire Radiative Power, from the Land Surface Analysis Satellite Applications Facility project (LSA-SAF).

Results show, on one hand, that the extreme values of FWI (given by the 99th percentile) of the Mediterranean region are higher in Italy and Greece, in contrast with Portugal and Spain. On the other hand, regarding FFMC and ISI values, higher values can be seen in North African regions for FFMC, and in Italy and Greece for ISI. This is clear evidence of the variations in fire activity in the different Mediterranean regions. A new Exceptional class of fire danger is defined based on the extreme classes of FWI, FFMC, and ISI, jointly based on the occurrence of the recent Megafires in the Mediterranean region, such as the fires in Portugal in 2018 and Greece in 2023. The new approach to define the Exceptional class revealed to be an extremely important tool for fire danger assessment and for the definition of planning activities and suppression measures in the present context of climate warming.

Acknowledgements: This study is partially supported by the European Union’s Horizon 2020 research project FirEUrisk (Grant Agreement no. 101003890) and by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020- IDL and DHEFEUS - 2022.09185.PTDC.

How to cite: Canelas da Silva, M., Alonso, C., Durão, R., and M. Gouveia, C.: On the definition of an Exceptional fire danger rating over Mediterranean Countries, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17032, https://doi.org/10.5194/egusphere-egu24-17032, 2024.

EGU24-17121 | Orals | NH7.1 | Highlight

Early warning meteorological fire danger over Central Europe 

Carlos C. DaCamara, Mariana Ponte Oliveira, Sílvia A. Nunes, Ricardo M. Trigo, and Isabel F. Trigo

Meteorological fire danger has been steadily increasing over Europe in the last decades, not only over the Mediterranean South that is recurrently affected by extreme fire weather and where the largest fire events take place, but also over Central, Eastern and Northern countries that are facing more and more events. The two most recent examples are the devastating fires in Rhodes and northern Greece in 2023, and those in France, Spain, Portugal, Slovenia and Czechia in 2022 when the total of burnt area almost reached the record value of 2017. The increase in severity of fire events is of major concern for all European countries, but special attention should be devoted to Central Europe where large fires, usually driven by the compound effect of droughts and heatwaves (e.g., 2018, 2022), are posing new challenges at the levels of fire management and fire forecasting.

We present a statistical model of energy released by wildfires that allows calibrating the Canadian Fire Weather Index (FWI) over three major land cover types (forest, shrub, and agriculture) covering an area encompassing Central Europe (3.5º-17ºE and 45º-62ºN). The model consists of a doubly truncated lognormal body distribution with generalized Pareto tails (DaCamara et al., 2023) that incorporates FWI as a covariate of its parameters. For each land cover type, the model is fitted to the set of observed values (from 2001 to 2022) of the logarithm of Fire Radiative Power associated to hotspots as detected by the MODIS instrument on-board Terra and Aqua platforms. For each model, goodness of fit is evaluated by using the Anderson-Darling test to assess the strength of the evidence against the null hypothesis that the sample follows the distribution.

The fitted models allow estimating for each land cover type the probability of exceedance of a predefined threshold of log(FRP) for each day and grid point. Five classes of fire danger (low, moderate, high, very high, and extreme) for each land cover type are then defined by analyzing the spatial and temporal variability of the distribution of pixels among classes as well as the distribution among classes of FRP associated to hotspots, such that classes of higher fire danger tend to concentrate in the fire season, and fires with high values of FRP occur in pixels classified in the classes of high, very high and extreme danger. The procedure is further validated by examining several case studies that were chosen because of unusually intense fire events or because of the high number of occurrences.

 

This work was supported by EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF) and by Instituto Dom Luiz (IDL), a research unit financed with national funds (PIDDAC) by FCT (UIDB/50019/2020).

 

References:

 

DaCamara, C. C., Libonati, R., Nunes, S. A., de Zea Bermudez, P., & Pereira, J. M. C. (2023). Global-scale statistical modelling of the radiative power released by vegetation fires using a doubly truncated lognormal body distribution with generalized Pareto tails. Physica A: Statistical Mechanics and Its Applications, 625. https://doi.org/10.1016/j.physa.2023.129049

How to cite: DaCamara, C. C., Oliveira, M. P., Nunes, S. A., Trigo, R. M., and Trigo, I. F.: Early warning meteorological fire danger over Central Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17121, https://doi.org/10.5194/egusphere-egu24-17121, 2024.

EGU24-18048 | ECS | Orals | NH7.1

Effect of climate change on lightning induced forest fires in Austria 

Johannes Laimighofer, Mariana Silva Andrade, Pia Echtler, Sven Fuchs, Mortimer Müller, Maria Papathoma-Köhle, Harald Vacik, and Herbert Formayer

Increasing temperatures, due to climate change lead to more evapotranspiration which increases the possibility of severe drought periods. These trends enhance the risk of wildfire hazards even in humid regions like the Alps. Further, possible changes in the occurrence of thunderstorms can modify the ignition danger of lightning induced wildfires. This study aims to investigate the effect of climate change on the probability of wildfires ignited by lightnings including possible shifts in lightning probability for Austria.

The full analysis is performed on a 1x1 km grid over Austria. Fire ignition danger and drought periods are approached by computing the Fine Fuel Moisture Code (FFMC). Noon temperature and windspeed for the FFMC are estimated by a spatio-temporal GAM (generalized additive model) with a geographic varying cyclic B-spline. The occurrence of lightnings is approached by the Showalter Index, which is validated with data from the Austrian Lightning Detection and Information System (ALDIS) for the period 2011 to 2020. For the historical weather conditions the Spartacus dataset is used for the period 1981-2022. Regarding the future development, five different climate projections are compared.

The historical period showed on average no trend for days with high FFMC values (> 91) for Austria, but already 13% of the study area have a significant positive trend (tested by Mann-Kendall trend test). The trend is even more evident for the climate projections, which show a significant increase in days with FFMC values > 91 for 99% of the study area, with a sharp increase starting about 2050. Possible alterations in thunderstorm activity will strengthen the danger of forest fire ignitions of wildfires in Austria and are posing an increasing threat for forest management and society.

 

How to cite: Laimighofer, J., Andrade, M. S., Echtler, P., Fuchs, S., Müller, M., Papathoma-Köhle, M., Vacik, H., and Formayer, H.: Effect of climate change on lightning induced forest fires in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18048, https://doi.org/10.5194/egusphere-egu24-18048, 2024.

EGU24-18220 | ECS | Posters on site | NH7.1

High-resolution fire weather projections for effective forest management and restoration across the Mediterranean region  

Carolina Gallo, Jonathan Eden, Bastien Dieppois, Peter Fulé, Jesús San-Miguel-Ayanz, Valentina Bacciu, Christophe Besacier, and Matthew Blackett

The Mediterranean region has historically been prone to wildfire activity. However, many Mediterranean countries have been particularly impacted in recent years by an increase in fire intensity and fire season length, with hundreds of thousands of hectares burned both north and south of the basin. Larger and more frequent fires are anticipated across the Mediterranean region in the future, a key driver of which is the projected increase in so-called fire weather (the meteorological conditions conducive to fire ignition and spread) associated with a warming world. In view of the loss or degradation of forest areas due to wildfires, and in the context of the ongoing UN Decade on Ecosystem Restoration (2021-2030), Mediterranean countries are actively engaging in post-fire restoration actions. Developing new insights into the evolution of fire weather across Mediterranean ecosystems is crucial for effective forest management and restoration planning.  

For the Mediterranean, fire weather projections under climate change have typically been extrapolated from global-scale studies or otherwise focused predominantly on Southern European countries. By contrast, far less attention has been given to countries in North Africa and the Middle East. Here, we generate high-resolution fire weather projections for the entire Mediterranean region, using the latest generation of global climate models. We calculate the Canadian Fire Weather Index (FWI) following a multivariate bias correction and downscaling of the FWI’s underpinning meteorological variables (namely, maximum daily temperature, minimum daily relative humidity, mean daily wind speed and daily precipitation). 

Results show changes in the magnitude of FWI seasonal means, maxima and fire season length in different scenarios and areas of the Mediterranean region where fire danger is projected to increase in the forthcoming decades. We discuss potential implications for future land management and restoration activities, as current preventive and restorative strategies should consider these future scenarios to ensure their success. The high-resolution fire weather projections generated here will help to better target areas of intervention and types of measures to be implemented.

How to cite: Gallo, C., Eden, J., Dieppois, B., Fulé, P., San-Miguel-Ayanz, J., Bacciu, V., Besacier, C., and Blackett, M.: High-resolution fire weather projections for effective forest management and restoration across the Mediterranean region , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18220, https://doi.org/10.5194/egusphere-egu24-18220, 2024.

EGU24-18455 | ECS | Orals | NH7.1

Projections of the Fire Weather Danger over Central Europe using EURO-CORDEX simulations 

A. Serkan Bayar, Alexandre M. Ramos, Célia Gouveia, and Joaquim G. Pinto

Increasing temperatures and harsher drought conditions in recent decades have enhanced the risk of wildfire in many regions across the globe. Recent fire activity in Central Europe raised concerns about the possible expansion of the fire weather danger conditions under climate change outside the present-day fire-prone regions, such as the Mediterranean Basin. Here, we employ the widely used Canadian Fire Weather Index (FWI) system to assess the historical and future trends in the fire weather danger for Central Europe. Calculation of the originally proposed FWI requires utilizing noon-time temperature, relative humidity, wind, and accumulated precipitation. Using the ERA5 reanalysis dataset, we make sensitivity analyses with different combinations of alternative input data for noon-time meteorological parameters and estimate their biases.

This study uses an ensemble of regional climate models (RCM) from the EURO-CORDEX domain. We first compare the results from ERA5 with the RCM ensemble for the historical period. Then, we analyze future projections for Central Europe under different global warming levels (+2 K and +3 K). Results indicate that the fire-prone areas consistently increase under warmer climate conditions, including emerging fire-prone regions in Central and Northern Europe.

How to cite: Bayar, A. S., Ramos, A. M., Gouveia, C., and Pinto, J. G.: Projections of the Fire Weather Danger over Central Europe using EURO-CORDEX simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18455, https://doi.org/10.5194/egusphere-egu24-18455, 2024.

EGU24-19064 | ECS | Posters on site | NH7.1

Forecasting Forest Fires in South Korea Using a Diagnostic Forest Fire Model 

Minwoo Roh, Sujong Lee, and Woo-kyun Lee

Forest fires exert a significant impact on Earth's ecological systems, resulting in consequences such as deforestation, habitat degradation, and adverse effects on environmental, economic, and social domains. The restoration of areas affected by forest fires demands substantial time and effort to return them to their original state. Proactive identification of areas prone to forest fires is crucial for minimizing the damage caused by such incidents. In this study, a forest fire diagnostic model was developed to enhance the precision of forest fire risk predictions. The model utilized remote sensing data and human activity maps. To gauge the dryness of the land surface, the Vegetation Temperature Condition Index (VTCI) was employed, and density maps of roads, buildings, and cropland were incorporated for the human activity maps. The algorithm of the model was based on the Random Forest classifier, and it was trained on forest fire occurrence data from 2016 to 2020 across South Korea. To assess the actual performance of forest fire forecasting, short-term forecasts for a 3-day period were conducted from February to May 2023. The model successfully predicted 80% of forest fires during this evaluation period.

How to cite: Roh, M., Lee, S., and Lee, W.: Forecasting Forest Fires in South Korea Using a Diagnostic Forest Fire Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19064, https://doi.org/10.5194/egusphere-egu24-19064, 2024.

EGU24-19169 | ECS | Posters on site | NH7.1 | Highlight

Quantifying post-fire effects and recovery in a disturbed landscape: Quesenbank fire, Harz National Park 

Robert Jackisch, Birgitta Putzenlechner, Simon Drollinger, and Elisabeth Dietze

Anthropogenic climate change increases the risk of forest fire following drought periods in temperate forests of Central Europe. Areas with an increased proportion of standing deadwood are often considered to be at risk. Especially in national parks, deadwood is not removed, forming an essential part of the local ecosystem.

In the Harz National Park, we aim at a comprehensive impact assessment following a fire in a spruce forest that was already disturbed after a massive bark beetle infection to understand deadwood breakdown, vegetation succession, surface erosion and changes in soil properties. The Quesenbank fire of August 2022 burned an area of approx. 13 ha within four days. We scanned 10 ha of burned compared to unburned areas using unoccupied aerial vehicles (UAVs) equipped with multispectral, thermal, high-resolution RGB and light-detection and ranging (LiDAR) sensors. Derived orthoimages, 3D point clouds and canopy height models (CHM) are employed to estimate standing deadwood, fractional cover and succession indicators, thermal ground regime alterations and small-scale morphological changes. To capture the gradual breakdown of deadwood, we collected ground truth on vegetation biophysical parameters, such as fractional cover, plant area index (PAI) and fraction of absorbed photosynthetically active radiation (FAPAR) from upward-directed digital hemispherical photos. The surveys were conducted 2, 9, 11 and 12 months post-fire together with the UAV campaigns in diffuse or near-dusk light conditions.

The analysis of the digital CHM and ground models reveal a decline in the detection rate of tree crowns (tree height ≥ 2 m) by 15 %, crown area by 74 %, and a corresponding loss of surface material affecting at least 0.9 ha between October 2022 and October 2023, respectively.

The ground reference data confirmed considerably lower fractional cover on burned areas. PAI and FAPAR in burned standing deadwood was lower in unburned stands, altering light, soil moisture and temperature regimes. This is reflected in the occurrence of typical post-fire and light-demanding species such as Epilobium spec. on burned areas, though in lower coverage compared to an unburned, logged site. As the variation in reference data was relatively low over the observation period, we suggest that the main dynamics of the breakdown of standing deadwood had already happened several weeks after the fire. Interestingly, we found a very heterogeneous microtopography due to granite boulders, with subsurface tunneling and unstable ground, influencing post-fire recovery. Upcoming analysis will include analyses of fire-influenced soil properties, morphodynamics and biogeochemical cycling in a region that still shows traces of past land use associated with the mining history of the Harz.


We acknowledge the collaboration with the Harz National Park Authority. A preliminary data set from two months after the fire can be accessed via Zenodo: Jackisch, R., Putzenlechner, B., & Dietze, E. (2023). UAV data of post fire dynamics, Quesenbank, Harz, 2022 (orthomosaics, topography, point clouds) (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7554598

How to cite: Jackisch, R., Putzenlechner, B., Drollinger, S., and Dietze, E.: Quantifying post-fire effects and recovery in a disturbed landscape: Quesenbank fire, Harz National Park, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19169, https://doi.org/10.5194/egusphere-egu24-19169, 2024.

EGU24-20768 | ECS | Orals | NH7.1

VQ-VAE generative model of spatial-temporal wildfire propagation 

Sibo Cheng and Rossella Arcucci

The growing frequency of wildfires globally has highlighted the importance of immediate fire forecasting. Traditional high-accuracy fire spread simulations, like cellular automata and computational fluid dynamics, are detailed but require extensive computational resources and time. Consequently, there has been a significant push towards developing machine learning-based fire prediction models. These models, while effective, tend to be specific to certain regions and demand a large volume of simulation data for training, leading to considerable computational demands across various ecoregions.

In response, this study introduces a generative approach using three-dimensional Vector-Quantized Variational Autoencoders. This method is designed to create spatial-temporal sequences predicting the progression of future wildfires in specific ecoregions. The effectiveness of this model was evaluated in the context of the Chimney fire, a notable recent wildfire in California. The results demonstrate that the model effectively produces realistic and structured fire scenarios, incorporating influential geophysical factors like vegetation and terrain slope. Additionally, the data generated by this model were used to develop and train a surrogate model for wildfire spread prediction. This surrogate model was successfully validated using both simulated data and actual data from the Chimney fire incident.

How to cite: Cheng, S. and Arcucci, R.: VQ-VAE generative model of spatial-temporal wildfire propagation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20768, https://doi.org/10.5194/egusphere-egu24-20768, 2024.

EGU24-20928 | Orals | NH7.1

Modeling Post-Wildfire Rainfall Events in the Santa Cruz Creek Watershed using HEC-HMS and GSSHA 

Avery Walters, Nawa Raj Pradhan, Ian Floyd, and Venkataraman Lakshmi

The 2007 Zaca Fire burned about 240,000 acres of land north of Lake Cachuma, which supplies water to Santa Barbara, CA. USGS Streamgage 11124500 was able to record pre and post-fire stream discharge for the affected Santa Cruz Creek Watershed, of which 67% was burned. 80% of this burn was severe, which raises concern for extreme flood events following the wildfire. It has been observed that the extreme temperatures in wildfires not only damage vegetation but soils as well -- wildfires much more so than comparatively mild prescribed burns. Our research proposes analyzing precipitation and stream discharge data from the affected Santa Cruz Creek Watershed to quantify the effects of such widespread and severe wildfire. This study uses the Hydrologic Modeling System (HEC-HMS) from the Army Corps of Engineers (ACE) to perform event-based, lumped modeling. It also uses Gridded Surface Subsurface Hydrologic Analysis (GSSHA) to perform physics-based modeling of the same watershed. Doing so should deepen our understanding of the effects of increasingly common and severe wildfires on watershed characteristics like infiltration and streamflow.

How to cite: Walters, A., Pradhan, N. R., Floyd, I., and Lakshmi, V.: Modeling Post-Wildfire Rainfall Events in the Santa Cruz Creek Watershed using HEC-HMS and GSSHA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20928, https://doi.org/10.5194/egusphere-egu24-20928, 2024.

EGU24-21377 | Orals | NH7.1

Integrating Multi-Sensor Remote Sensing Data for Comprehensive spatio-temporal WildfireAssessment In Campania Provinces – Italy 

Hanieh Dadkhah, Divyeshkumar Rana, Ebrahim Ghaderpour, and Paolo Mazzanti

Wildfires present substantial threats to ecosystems and human settlements which increase the importance of monitoring for timely detection and assessment. This study was performed on the Campania provinces—Salerno, Avellino, Benevento, Caserta, and Napoli in Italy—employing a multi-sensor remote sensing approach to elevate wildfire analysis. The first objective is identifying fire patches through Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2001 to 2020. Although, generating Difference Normalized Burn Ratio (DNBR) and Difference Normalized Difference Vegetation Index (DNDVI) maps from Sentinel-2 images. Integration of MODIS and Sentinel-2 outcomes enhances pinpointing fire-affected areas. Subsequently, Incorporating Landsat 9 images for Land Surface Temperature (LST) and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) for precipitation trends in five provinces from 2001 to 2020 in Hotspot Polygons generated via First Order Contiguity edges corners algorithm. Pearson correlation coefficients between burnt area, LST, and precipitation are computed. A high correlation coefficient was observed between the mentioned parameters. Wildfire analysis reveals peak burnt areas in 2001, 2007, and 2017 in Avellino and Salerno Province. Change detection maps illustrate significant land cover changes from Forest to Savannas and Shrubland to grasslands in 2001. Avellino province reveals a decreasing trend in Grassland and an increase in Savannas, as the same as observations in Salerno Province. This study considers the analysis of wildfires, connecting burnt areas, climate variables, and land cover changes across the Campania provinces.

Keywords: Wildfire, Fire and Vegetation Indices, Land Cover Changes, Climate Change

How to cite: Dadkhah, H., Rana, D., Ghaderpour, E., and Mazzanti, P.: Integrating Multi-Sensor Remote Sensing Data for Comprehensive spatio-temporal WildfireAssessment In Campania Provinces – Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21377, https://doi.org/10.5194/egusphere-egu24-21377, 2024.

EGU24-22445 | Posters on site | NH7.1

Creation of data cube for the analysis of wildfires in Cyprus using open access data  

Maria Prodromou, Stella Girtsou, George Leventis, Dimitris Koumoulidis, Marios Tzouvaras, Christodoulos Mettas, Alexis Apostolakis, Mariza Kaskara, Haris Kontoes, and Diofantos Hadjimitsis

This study presents the actions that are currently been conducted through a demonstration project in the framework of the EXCELSIOR funded project, entitled “Capitalizing on the ERATOSTHENES Data Cube to support the development of the Fire Risk Prediction Model” between the ERATOSTHENES Centre of Excellence and the National Observatory of Athens. Wildfires detection is a major issue for authorities. There are various causes of fire events with the most common being human influence. A fire risk prediction model through the analysis of geo-environmental and climate data is important for early warning and fire management. An effective wildfire risk prediction and management depend on the up-to-date, spatial explicit representation of the environment, mainly focusing on the biomass and characteristics of live and dead vegetation, which is the primary factor influencing fire behaviour and risk. In this work, a dataset from multiple modalities, including road density, travellers, forest-agriculture interface, burned areas from historical fire events, metrological data, land cover, vegetation indices from data cube, is generated. These factors are selected based on their potential correlation with the unique characteristics of the area investigated, the historical fire events, and the availability of relevant data. Artificial intelligence and machine learning models can use this multimodal dataset to improve forest fire management. Specifically, the combination of data cubes, machine learning, and geospatial ontology-based data access (OBDA) technologies, allows for effective harmonization of diverse data sources, enhancing the accuracy and efficiency of fire risk computations.


ACKNOWLEDGEMENT
The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

How to cite: Prodromou, M., Girtsou, S., Leventis, G., Koumoulidis, D., Tzouvaras, M., Mettas, C., Apostolakis, A., Kaskara, M., Kontoes, H., and Hadjimitsis, D.: Creation of data cube for the analysis of wildfires in Cyprus using open access data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22445, https://doi.org/10.5194/egusphere-egu24-22445, 2024.

EGU24-763 | ECS | Posters on site | BG1.1

The influence of pyrolysis time, moisture, and plant species on carbon bridgehead fraction of charcoal 

Vinothan Sivapalan and William Hockaday

Paleofire reconstructions are a challenging endeavor primarily due to the numerous factors involved in wildfire frequency, behavior, and regimes. These factors include, but are not limited to fuel composition, moisture, soil types, climate/weather conditions, and topographical features. Therefore, development of robust wildfire proxies requires vigorous experimental testing for multiple variables. Here, we explore the influence of pyrolysis time, moisture, and plant species on a novel proxy for fire intensity—carbon bridgehead fraction of charcoal. Experimentally, we have produced charcoals from three native Texas plants: live oak (Quercus sp.), Ashe juniper (Juniperus ashei), and broomsedge bluestem (Andropogon virginicus) under a range of temperature (300-700°C), moisture (0-100% moisture capacity), and time (0-1 hr) conditions in a tube furnace. Samples were analyzed using solid-state C-13 nuclear magnetic resonance (NMR) spectroscopy with two experiments to calculate carbon bridgehead fraction: cross polarization – magic angle spinning (CP-MAS) to quantify total aromatic carbon and dipolar dephasing (DD) to quantify aromatic bridgehead carbon. Results reveal significant differences between vegetation types, with moisture delaying or slowing the rate of carbon bridgehead formation. Relationship between carbon bridgehead fraction and time are less clear and may be influenced by the formation of pyrolysis byproducts (such as pyroligneous acids and free radicals) and/or signal losses in the cross-polarization spectra. To assess the influence of these factors on carbon bridgehead fraction we plan to conduct additional analyses on our experimental charcoals, including electron paramagnetic resonance (EPR) spectroscopy to quantify the free radicals in samples and C elemental analysis to assess carbon observability by NMR. Future work involves ground truthing the proxy to modern wildfires and subsequently applying it to paleorecords.

How to cite: Sivapalan, V. and Hockaday, W.: The influence of pyrolysis time, moisture, and plant species on carbon bridgehead fraction of charcoal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-763, https://doi.org/10.5194/egusphere-egu24-763, 2024.

EGU24-1123 | ECS | Orals | BG1.1

Assessment of ecohydrological response of Himalayan Forest ecosystems to  forest fires 

Nagashree Ge and Ashutosh Sharma

Himalayan forests boast an incredible biodiversity, harboring a wide range of flora and fauna and playing a significant role in regulating water resources. Forest fires are one of the disturbances which constitute a major force influencing, even determining, the structure and functions of ecological components-populations, communities, and ecosystems. The ability to withstand disturbance is defined as resistance whereas resilience is the capacity to recover from disturbance. These two terms define the ecohydrological response to forest fire. This study insights on how remote sensing technique can be utilized for the measurement of ecohydrological response of a large extent of region subjected to forest fire based on resistance-resilience framework and how further implementation of these measures would help to know the changes in the interaction been vegetation and water cycle. Normalized burn ratio (NBR) is used to quantify the response.  The outcome of the study reveals that deciduous needled leaf forests are subjected frequently to forest fires compared to other classes of forests during 2002-2022. The regions considered for study showed moderate to high range of resistance but low resilience, signifying the region has gained and lost vegetations in the post-fire. There was a variation in rainfall and run-off occurred during the post-fire year for different burn severities. The present approach has the potential to quantify the response of ecosystems to the forest fire and related effects on hydrology of the region.

How to cite: Ge, N. and Sharma, A.: Assessment of ecohydrological response of Himalayan Forest ecosystems to  forest fires, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1123, https://doi.org/10.5194/egusphere-egu24-1123, 2024.

From March to April, widespread forest fires and agro-residue burning frequently occur in Southeast Asia, which release large amounts of gas species and aerosols and impact air quality over the wide source and downwind regions. In this study, we investigated the impact of biomass burning (BB) over Southeast Asia on particulate matter concentrations and aerosol properties in downwind areas of the low-latitude plateau from 1 March to 30 April 2019, with a focus on a typical pollution event in Kunming (KM), the capital of Yunnan Province, by using a wide variety of observations from the Chenggong ground monitoring station in Yunnan University, an air quality network in China, satellite retrievals and ERA-5 reanalysis data and numerical simulation. A regional pollution event contributed by BB pollutants from Southeast Asia and the India-Myanmar trough occurred in Yunnan Province on 31 March to 1 April 2019, which was the only typical pollution event that pollution transmission ran through central Yunnan Province from south to north since 2013, when the Airborne Pollution Action Plan was unveiled by China government. The daily mean PM2.5, PM1, and black carbon concentrations increased by 73.3 μg m−3 (78%), 70.5 μg m−3 (80%), and 7.7 μg m−3 (83%), respectively, and the scattering and absorbing coefficients increased by 471.6 Mm−1 and 63.5 Mm−1 , respectively, at the Chenggong station. The southwest winds exceeding 2 km vertically thick appeared in front of the India-Myanmar trough over the fire regions, pushing BB plumes northward into Yunnan Province. The model results show that 59.5% of PM2.5 mass produced by BB in Yunnan Province was sourced from the Myanmar-Thailand border, and 29.3% was from western Myanmar at a lower altitude (<4.9 km), which indicated that BB in the Myanmar-Thailand border was the dominant contributor.

How to cite: Fan, W., Li, J., Han, Z., and Wu, J.: Impacts of biomass burning in Southeast Asia on aerosols over the low-latitude plateau in China: an analysis of a typical pollution event, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1471, https://doi.org/10.5194/egusphere-egu24-1471, 2024.

EGU24-1756 | ECS | Orals | BG1.1

Direct Estimation of Carbon Emissions from High Latitude Fires: The Adapted FREM Approach 

Will Maslanka and Martin Wooster

Landscape fires are a widespread natural phenomenon that directly influences carbon cycling through the combustion of organic material. Space-based remote sensing, including Active Fire (AF), remains the only way to estimate wildfire activity accurately on the regional-to-global scale. Fire emission inventories generally fall into two categories. “Bottom-up” methodologies rely on observations of AF counts, Fire Radiative Power (FRP), or burned area to estimate the amount of biomass burned, or “Top-down” methodologies, which directly relate observations of FRP to landscape fire emission estimates. Bottom-up methods tend to have a reliance on uncertain parameters, such as pre-fire fuel load and combustion completeness, or a conversion factor between FRP and fuel consumption rate. The Fire Radiative Energy Emission (or FREM) approach is one such top-down methodology that has removed such a reliance, by directly relating FRP to observed rates of emissions, such as CO or aerosols, but has so far been used with geostationary FRP data only. Whilst very effective at lower latitudes, due to the poor spatial resolution and extreme viewing geometry of geostationary data at higher latitudes, the approach is not applicable for fires in this region in its current format. However, by using polar orbiting FRP data and making use of the high latitude orbital convergence, this study looks to adapt the FREM approach to deliver direct estimation of carbon emissions for high latitude (>60°N) landscape fires. We use direct observations of FRP, from Suomi-NPP, NOAA-20 and MODIS, along with observations of Total Column Carbon Monoxide from TROPOMI onboard Sentinel-5P. A series of cloud-free plumes and associated FRP data were identified in Deciduous and Evergreen Needleleaf biomes in North America and Russia in the summers of 2019 – 2023. The resulting emission coefficients and emission totals were compared to pre-existing top-down and bottom-up emission coefficients and totals from the FEER, GFAS, and GFED inventories for high latitude fires between 2018-2023. This adapted FREM approach is shown to provide direct emission estimates without recourse to significant assumptions and can do so in real time – opening up a new avenue for real-time fire emission estimation at high latitudes.

How to cite: Maslanka, W. and Wooster, M.: Direct Estimation of Carbon Emissions from High Latitude Fires: The Adapted FREM Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1756, https://doi.org/10.5194/egusphere-egu24-1756, 2024.

EGU24-2099 | ECS | Orals | BG1.1

Exploring the effect of vegetation photosynthesis phenology on wildfire dynamics 

Gengke Lai, Jialing Li, Jun Wang, Chaoyang Wu, Yongguang Zhang, Constantin M. Zohner, and Josep Peñuelas

2023 has witnessed a record-breaking extreme wildfire season in Canada from coast to coast, following closely to the unprecedented wildfire outbreaks in 2019/20 Australia and 2021 Siberia, causing far-reaching threats on terrestrial carbon stock, air quality, and human society. The heightened wildfire activity in specific regions prompts us to rethink the underlying factors driving the global wildfire dynamics. Climate change has been recognized as an important factor in amplifying wildfire risk, mainly through increasing temperature and reducing relative humidity. However, the role of vegetation productivity and phenology on wildfire dynamics remains elusive, even though which can exacerbate or mitigate the climate-induced fire risk. Importantly, changes in vegetation phenology can cause biophysical feedback to the climate system and land surface by modulating the exchanges of water and energy between land and the atmosphere. Considering the climate feedback of vegetation phenology, we hypothesize that peak photosynthesis timing (PPT) can contribute to wildfire activity. To explore it, we provide comprehensive analyses using multiple satellite-based photosynthesis observations from solar-induced chlorophyll fluorescence (SIF), and wildfire activity from national fire perimeters and MODIS global burned area records from 2001 to 2018, as well as diverse methodologies and models. In response to changes in various biological and climatic factors, we find PPT has advanced 1.10 ± 0.57 days per decade at a global scale. This earlier PPT acts to expand the extent of wildfires, with an increase in the global average burned fraction by 0.021% (~2.20 Mha) for every additional day of PPT advancement. Satellite observations and the Earth system modeling consistently reveal that this expansion is attributed to the intensified drought conditions during the potential fire season, induced by the earlier PPT that can modulate the global patterns of temperature, precipitation, and surface soil moisture. Furthermore, current fire-vegetation models participating in the FireMIP project underestimate the sensitivity of burned area to PPT, despite reproducing their negative correlation. Our findings highlight the importance of climate-vegetation-fire feedback loops in future prediction of wildfire dynamics and the strategy of climate change adaptation and mitigation.

How to cite: Lai, G., Li, J., Wang, J., Wu, C., Zhang, Y., Zohner, C. M., and Peñuelas, J.: Exploring the effect of vegetation photosynthesis phenology on wildfire dynamics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2099, https://doi.org/10.5194/egusphere-egu24-2099, 2024.

EGU24-4071 | ECS | Posters on site | BG1.1 | Highlight

The Influence of Climate Teleconnections on Global Burned Area 

Yuquan Qu, Harry Vereecken, Sander Veraverbeke, and Carsten Montzka

Wildfires are known to be controlled by fuels and weather. Climate teleconnections may influence wildfires by altering fuel availability and fire weather. In this study, we used the random forest approach to systematically detect relationships between teleconnection climate indices (CIs) and burned area while accounting for different lag times. Results indicate that burned area is especially modulated by climate teleconnections in Africa and Australia. The Tropical Northern Atlantic (TNA) pattern was the most influential CI for the global burned area, followed by the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Pacific–North American (PNA) pattern. To study pathways of how teleconnections affect the burned area, we distinguished two classes of fire drivers: bottom-up fuel availability and top-down weather conditions. Bottom-up fuel drivers showed higher correlation with CIs than top-down weather drivers and served as mediators between teleconnections and wildfires. The mediating effect of top-down weather drivers was only apparent in specific seasons. Our study highlights that in teleconnection-wildfire hotspot regions, knowledge of the relation between CIs and drivers of wildfires could improve long-term wildfire predictability. We recommend that bottom-up fuel drivers should also be integrated into wildfire predictive frameworks as they play an important mediating role in linking teleconnections and wildfires.

How to cite: Qu, Y., Vereecken, H., Veraverbeke, S., and Montzka, C.: The Influence of Climate Teleconnections on Global Burned Area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4071, https://doi.org/10.5194/egusphere-egu24-4071, 2024.

EGU24-5191 | ECS | Orals | BG1.1 | Highlight

Impacts of land use change and interannual climate variability on biomass burning emissions, air quality and public health in Amazon 

Tsin Hung Leo Ng, Amos P. K. Tai, Stephen Sitch, Luiz Aragao, and Shixian Zhai

Biomass burning in Amazon Basin has a significant impact on regional climate and deteriorates regional air quality, which poses a threat to human and ecosystem health. The fire-induced pollution worsens during dry season (Jul to Nov) and shows a strong seasonal variation. Past research has demonstrated that the occurrence of wildfires in Amazon is not only influenced by deforestation, but also interannual climate variability, particularly droughts. Here we estimate the impacts of deforestation and droughts on fire emissions and regional air quality between 2010 to 2015 by using Global Fire Emission Database Version 4 (GFED v4) to drive a global 3-D atmospheric chemical transport model GEOS-Chem High Performance (GCHP) and further examine the effect of PM2.5 and O3 on premature mortality across the region. By comparing the “fire-on” and “fire-off” scenarios, we find that biomass burning alone in normal years (2011 and 2013) contributes 5.7 μg m-3 (47.6% of the total concentration) PM2.5, 0.08 ppm (46.3%) CO, 0.03 ppb (85.0%) NOx, and 9.5 ppb (41.2%) O3; and these numbers during drought years (2010, 2012, 2014 and 2015) increase to 19.6 μg m-3 (74.7%) for PM2.5, 0.20 ppm (67.0%) for CO, 0.19 ppb (97.4%) for NOx, and 15.6 ppb (52.0%) for O3. We find that these pollutants from wildfires mainly concentrate in the south-eastern Amazon and then transport southward, thus strongly impacting public health in the downwind regions. We estimate that premature mortality due to long-term exposure to particulate matter and ozone by applying the simulated concentration to the concentration-response functions from the European Environment Agency. We find that ~8,500 and ~10,400 deaths per year are attributable to PM2.5 and O3 exposure for 2010-2015 respectively. During drought years, we discover there are 2.8% and 3.4% more deaths than normal years for PM2.5 and O3 exposure. Our study shows the significance of biomass burning emissions in shaping the air quality in the Amazon region, and highlights the impact of drought events on enhancing biomass emissions, worsening regional air quality and causing public health issues. Therefore, it is important to address the underlying causes of biomass burning in the Amazon, such as deforestation and land use change, and droughts, to protect the region's ecosystems and mitigate the impacts of climate change.

How to cite: Ng, T. H. L., Tai, A. P. K., Sitch, S., Aragao, L., and Zhai, S.: Impacts of land use change and interannual climate variability on biomass burning emissions, air quality and public health in Amazon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5191, https://doi.org/10.5194/egusphere-egu24-5191, 2024.

EGU24-5236 | ECS | Posters on site | BG1.1 | Highlight

Are there lightning Fires in the Amazon Rainforest? 

Cunhui Zhang, Thomas Janssen, Matt Jones, and Sander Veraverbeke

Tropical rainforests have exceptionally high biodiversity and store large amounts of carbon in biomass. However, large and frequent fires across tropical rainforests in the last decades threaten the ecosystem integrity of these ecosystems. The general belief is that fires in the Amazon rainforest are all human-ignited and that lightning fires do not occur in rainforests due to the predominant wet conditions. However, recent research indicates the possibility of lightning fires in tropical rainforests. Here, we aim to investigate the occurrence of lightning-ignited fires in the Amazon rainforest, a topic that has been largely overlooked in the current understanding of fire dynamics in this biome. We collected and analyzed data on lightning strikes, fire occurrences, and weather patterns derived from satellite imagery and climate datasets. The objective is to detect, quantify, and characterize lightning fires in the Brazilian Amazon rainforests, thereby providing new insights into the natural fire regime of this crucial ecosystem.

How to cite: Zhang, C., Janssen, T., Jones, M., and Veraverbeke, S.: Are there lightning Fires in the Amazon Rainforest?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5236, https://doi.org/10.5194/egusphere-egu24-5236, 2024.

EGU24-5348 | Posters on site | BG1.1

Wetlands in monoculture forests – how fire activity and different forest management strategies impact Sphagnum-dominated peatlands 

Katarzyna Marcisz, Mariusz Bąk, Mariusz Lamentowicz, Piotr Kołaczek, Thomas Theurer, Paweł Matulewski, and Dmitri Mauquoy

Monoculture forests are now a dominant forest type in Europe. Created for easier management and increased timber production, they are now witnessing many disturbances due to climate change, such as more frequent windthrows, droughts, fires or insect outbreaks. The functioning of forests impacts other elements of the landscape, including peatlands, which also have been affected by various natural and anthropogenic disturbances (e.g., drainage) that make them more vulnerable to drying and burning. We aim to recognize how peatland functioning has changed along with changing forest management strategies. For this we studied a Sphagnum-dominated peatland located in the Tuchola Pinewoods – one of the largest Scots pine (Pinus sylvestris) monoculture forest in Poland. We used high-resolution multi-proxy palaeoecology including pollen, plant macrofossils and testate amoebae, additionally focusing on a wide range of charcoal analyses: charcoal counts, charcoal morphological types, and Raman spectroscopy. Our results show that the studied peatland experienced several critical transitions in vegetation composition and hydrology over the last 600 years when new forest management techniques were introduced. A reduction in fire activity led to a dominance of Sphagnum and increased peat accumulation rates. Establishment of a monoculture forest further impacted the site and stabilized Sphagnum growth and acidity levels. We believe that these results can be helpful for the improvement of conservation planning for peatlands located in forested areas, especially in monoculture forests.

The study is funded by the National Science Centre, Poland (2020/39/D/ST10/00641).

How to cite: Marcisz, K., Bąk, M., Lamentowicz, M., Kołaczek, P., Theurer, T., Matulewski, P., and Mauquoy, D.: Wetlands in monoculture forests – how fire activity and different forest management strategies impact Sphagnum-dominated peatlands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5348, https://doi.org/10.5194/egusphere-egu24-5348, 2024.

EGU24-5494 | ECS | Orals | BG1.1 | Highlight

Half of global burned area is due to managed anthropogenic fire: findings from a coupled socio-ecological modelling approach  

Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Tamsin Edwards, and James Millington

Globally, vegetation fires are a key component of many ecosystems and have substantial impacts on carbon emissions. Yet humans also use and manage fires for a huge range of purposes around the world, dependent on numerous social and biophysical factors. Existing representations of anthropogenic fire in dynamic global vegetation models (DGVMs) have been highly simplified, with readily available global variables (e.g. population density) used to estimate numbers of anthropogenic ignitions. Here, we present results from a novel coupled socio-ecological modelling approach to improve understanding of how human and biophysical factors combine to drive the spatio-temporal distribution of global fire regimes. Specifically, we present the integration of two process-based models. The first is the Wildfire Human Agency Model (WHAM!1), which draws on agent-based approaches to represent anthropogenic fire use and management. The second model is JULES-INFERNO2, a fire-enabled DGVM, which takes a physically-grounded approach to the representation of vegetation-fire dynamics.

The new WHAM-INFERNO model ensemble suggests that as much as half of all global burned area is generated by managed anthropogenic fires - typically small fires that are lit and spread according to specific land use objectives (such as crop residue burning). Furthermore, we demonstrate that including representation of managed anthropogenic fires in a coupled socio-ecological simulation can improve understanding of the biophysical drivers of unmanaged wildfires, by allowing clearer recognition of the role of anthropogenic land management in global fire regimes. Hence, WHAM-INFERNO is applied to understand how landscape fragmentation, wider land use change, and changes in human fire management have together led to observed recent declines in global burned area despite the warming climate. Overall, findings presented here have substantial implications for understanding of present and future fire regimes, indicating that changes to socio-economic systems are at least as important a consideration as climate change.  

1. Perkins, O., Kasoar, M., Voulgarakis, A., Smith, C., Mistry, J., and Millington, J. (2023). A global behavioural model of human fire use and management: WHAM! v1.0. EGUsphere, 1–42. 10.5194/egusphere-2023-2162.

2. Mangeon, S., Voulgarakis, A., Gilham, R., Harper, A., Sitch, S., and Folberth, G. (2016). INFERNO: a fire and emissions scheme for the UK Met Office’s Unified Model. Geosci. Model Dev. 9, 2685–2700. 10.5194/gmd-9-2685-2016.

How to cite: Perkins, O., Kasoar, M., Voulgarakis, A., Edwards, T., and Millington, J.: Half of global burned area is due to managed anthropogenic fire: findings from a coupled socio-ecological modelling approach , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5494, https://doi.org/10.5194/egusphere-egu24-5494, 2024.

EGU24-6077 | ECS | Orals | BG1.1

Updated Exposure Estimate for Indonesian Peatland Fire Smoke using Network of Low-cost Purple Air PM2.5 sensors 

Ailish M Graham, James B McQuaid, Thomas E L Smith, Hanun Nurrahmawati, Devina Ayona, Hasyim Mulawarman, Chaidir Adam, Dominick V Spracklen, Richard Rigby, and Shofwan A B Choiruzzad

Air pollutant emissions from wildfires on Indonesian peatlands lead to poor regional air quality across south-east Asia. Fine particulate matter (PM2.5) emissions are particularly high for peat fires leading to substantial population exposure to PM2.5. Despite this, air quality monitoring is limited in regions close to peat fires meaning the impacts of peatland fires on air quality is poorly understood and it is difficult to evaluate predictions from atmospheric chemistry models. To address this, we deployed a network of low-cost (Purple Air) PM2.5 sensors at 8 locations across Central Kalimantan, where peat fires are frequent. The sensors measured indoor and outdoor PM2.5 concentrations during August to December 2023. During the haze season (September 1st to October 31st), daily mean outdoor concentrations were 120 mg m-3 but peaked at >400 mg m-3. Indoor PM2.5 concentrations were only ~10% lower (mean 110 mg m-3), indicating that is difficult for the population to reduce their exposure to PM2.5 from fires. The reduction in mean PM2.5 concentrations between outdoor and indoor environments was larger in urban locations (-11%) compared with rural locations (-3%), suggesting urban housing may provide better protection from outdoor air pollution. To generate an updated assessment for the population’s exposure to peatland fire PM2.5 we combine the information from monitoring both indoor and outdoor PM2.5 concentrations with modelled ambient (outdoor) PM2.5 concentrations from the WRF-Chem atmospheric chemistry transport model. Our updated exposure assessment accounts for the population’s personal exposure to peatland fire PM2.5 for the first time.

How to cite: Graham, A. M., McQuaid, J. B., Smith, T. E. L., Nurrahmawati, H., Ayona, D., Mulawarman, H., Adam, C., Spracklen, D. V., Rigby, R., and Choiruzzad, S. A. B.: Updated Exposure Estimate for Indonesian Peatland Fire Smoke using Network of Low-cost Purple Air PM2.5 sensors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6077, https://doi.org/10.5194/egusphere-egu24-6077, 2024.

EGU24-6624 | ECS | Orals | BG1.1

Excessive fire occurrence in Romania from 2001 to 2022: Trends and drivers across ecoregions and land cover classes 

Till Mattes, Irene Marzolff, and Angelica Feurdean

Wildfire is an integral part of temperate ecosystems, but human activities have significantly altered fire regimes, including frequency, size, intensity and seasonality. Romania, located in central-eastern Europe, recently exhibited the highest biomass burning in Europe. However, little is known of the trends and determinants of fire recurrence, apart from the common use of fire to clear crop residues on arable land. This study utilizes satellite-based fire data (FIRMS) from 2001 to 2022 and land cover maps (CORINE) to investigate temporal trends in fire occurrence across ecoregions and land cover types in Romania and identify those most susceptible to fire.

Over 2001-2022, Romania witnessed a total of 0.44 fires/ km² averaging 0.02 fires/km²/yr. Our analysis revealed a declining trend in fire occurrence along an elevation gradient, from plains to hills, plateaus and mountains, aligning with the prevalence of the dominant land cover classes and climatic gradients. Agricultural land cover types demonstrated the highest fire incidence, with arable land exhibiting the highest rate (0.04 fires/km²/yr) and forests the lowest (below 0.01 fires/km²/yr). Following the accession of Romania to the EU in 2007 and the prohibition of agricultural fires, a reduction in burning on arable land (crop residues) can be observed, while the use of fire in other agricultural classes persisted or even increased, indicating a more complex effect of socio-economic developments on fire pattern. Specifically, areas more marginal for agriculture, such as complex agricultural fields interspaced with housing and natural vegetation continued to employ fire as a management tool.

Natural land cover classes, such as wetlands principally occupying the Danube Delta (0.06 fires/km²/yr) and natural grasslands (0.01 fires/km²/yr), also experienced substantial fire occurrences and an intensification in more recent periods. Given the rarity of naturally ignited fires (lightning) in Romania, the intentional use of fire to clear dry reed biomass for land regeneration appears to be prevalent also in moist areas. Remarkably, broadleaved and mixed forests burned more frequently than coniferous forests despite the latter having traits to convey high flammability and burn with high frequency. This feature suggests that fires in broadleaved forests, predominant at low and mid elevations, likely expanded from neighbouring agricultural lands.

Crucially, our analysis highlights that years with elevated fire occurrence coincide with extreme droughts and heatwaves (e.g., 2012, 2015), emphasizing the influence of extreme climate conditions in accelerating fire episodes and the spread of fires initiated in agricultural areas into natural and semi-natural habitats. Given the substantial occurrence of fires in agricultural land but also in natural habitats, such as wetlands and grasslands in Romania, research investigating the risks and vulnerability of these habitats to fire should be prioritized.

How to cite: Mattes, T., Marzolff, I., and Feurdean, A.: Excessive fire occurrence in Romania from 2001 to 2022: Trends and drivers across ecoregions and land cover classes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6624, https://doi.org/10.5194/egusphere-egu24-6624, 2024.

Wildfires have become more prevalent in recent years because of climate change. Meanwhile wildfires, as a major type of biomass burning, could emit a large amount of black carbon (BC) and brown carbon (BrC) to the atmosphere. Since BC and BrC play important roles in climate change, air pollution and human health issues, it is necessary to research their physicochemical properties to evaluate their impacts on urban areas. Here we present BC mass concentration and absorption coefficients measured by aethalometer (AE43), combing with the chemical constitutions acquired by GC-MS, during the record-breaking 2023 wildfire season in Canada. The back-trajectory analysis indicated that the smoke mainly came from north Quebec where the wildfires took place. We demonstrated how BC and BrC emitted by wildfires could affect urban regions after long-range transport.

How to cite: Li, H. and Ariya, P.: Measurement of Physicochemical Properties of Black Carbon and Brown Carbon and the Impacts of Canada Record-Breaking Wildfires in Summer 2023 , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6761, https://doi.org/10.5194/egusphere-egu24-6761, 2024.

EGU24-7467 | ECS | Posters on site | BG1.1

The Impact of Wildfires on Atmospheric Nitrogen Deposition in the United States: A Multiple Linear Regression-based Analysis 

Jiangshan Mu, Yingnan Zhang, Chenliang Tao, Zhou Liu, Yu Zhao, Lei Zhang, Yuqiang Zhang, and Likun Xue

Nitrogen deposition can exert a significant impact on global ecosystems. The increased occurrence of natural factors such as wildfires are becoming more important in atmospheric deposition especially with the continued decreases of the anthropogenic emissions in developed countries. In this study, we investigate the mechanisms by which the increasingly frequent wildfires affect nitrogen deposition in the United States using comprehensive datasets and multiple linear regression (MLR) methods. We found a downward trend in nitrogen deposition in the U.S. (-0.09 kgN ha yr-1), mainly due to the decreases in oxidative nitrogen deposition (-0.1 kgN ha yr-1). In contrast, reduced nitrogen deposition showed a slight increase (0.02 kgN ha yr-1). Our preliminary results show that wildfires contributed ~10% to the U.S. domestic deposition overall, but the magnitudes and signs of impact vary geographically, depending on the frequency and intensity of wildfires and the dominant deposition types. On average across the U.S., wildfires predominantly negatively contribute to wet deposition, while their contributions to dry deposition is smaller or slightly positive. Specifically, wildfires enhance dry deposition in the western U.S. while inhibiting wet deposition in the southeastern U.S. Wildfires exert a suppressive effect on both oxidized and reduced forms of nitrogen deposition in the southeastern U.S. Our study highlights the significant influence of wildfires on nitrogen deposition, underscoring the need to consider wildfire events in environmental management and policy-making.

How to cite: Mu, J., Zhang, Y., Tao, C., Liu, Z., Zhao, Y., Zhang, L., Zhang, Y., and Xue, L.: The Impact of Wildfires on Atmospheric Nitrogen Deposition in the United States: A Multiple Linear Regression-based Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7467, https://doi.org/10.5194/egusphere-egu24-7467, 2024.

EGU24-7895 | ECS | Posters on site | BG1.1

Vegetation types influence fine-scale drought impact on land surface cooling and burn patterns in the Siberian coastal tundra 

Nils Rietze, Jakob Assmann, and Gabriela Schapeman-Strub

In 2020, the Northeastern Siberian lowland tundra faced an extreme drought and unprecedented wildfires. The burning of carbon-rich soils in this region can release large amounts of carbon, worsening climate change and Arctic warming.  However, we know little about of how droughts impact vegetation and how this vegetation might become fuel for large fires in the typically wet landscapes of the Northeastern Siberian lowland tundra. We studied the impact of the extreme summer drought in 2020 on the tundra vegetation and the resulting burn patterns in the Indigirka lowlands using a combination of in-situ, thermal, and multispectral remote sensing data from drone and high-resolution satellite imagery. The fine-scale vegetation types revealed increased landscape-wide drought susceptibility indicated by an overall loss of land surface cooling. This suggests a shift towards an energy budget dominated by sensible heat flux, which may feed back and intensify the heatwave.  Further, we found that mostly dry vegetation types were affected by fire in the NE Siberian coastal tundra, while wetter vegetation types did not burn, leading to a fine-scale heterogeneous burn pattern. Our results indicate that the enhanced drought susceptibility of vegetation types may have led to higher fire fuel connectivity of the tundra landscape. Consequently, this may have resulted in the large burn extents observed in 2019 and 2020. Our analysis is an effort toward the prediction of fire fuel connectivity and fire management in remote Arctic areas.

How to cite: Rietze, N., Assmann, J., and Schapeman-Strub, G.: Vegetation types influence fine-scale drought impact on land surface cooling and burn patterns in the Siberian coastal tundra, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7895, https://doi.org/10.5194/egusphere-egu24-7895, 2024.

EGU24-8017 | ECS | Posters on site | BG1.1

Combining stand-level and remote sensing data to model post-fire recovery of Mediterranean tree-forest communities – A case study in Spain. 

Raul Hoffren, Juan de la Riva, Darío Domingo, María Teresa Lamelas, Paloma Ibarra, Alberto García-Martín, and Marcos Rodrigues

Mediterranean forests are recurrently affected by wildfires. Fire activity is expected to accelerate in the future due to landscape homogenization, fuel accumulation, and climate warming. A key aspect to prevent and mitigate the negative impacts of wildfires on ecosystems is to understand the factors that govern the recovery of forest communities. This study analyzes the post-fire recovery potential of four representative Mediterranean tree-communities (Pinus halepensis, Pinus nigra, Pinus pinaster, and Quercus ilex) affected by large wildfires (> 500 ha) during the summer of 1994 in Spain. For this purpose, information collected in the field 25 years after the fires in 203 forest plots (131 burned and 72 unburned control plots) was coupled with remote sensing, geospatial, and forest inventory data, to build an empirical model capable of assessing recovery. Remote sensing data provided a proxy for burn severity, through the Composite Burn Index, and allowed modelling the local topography (slope and aspect) of the terrain. The geospatial data included climatic information on temperature and precipitation trends. These data were entered into the model, calibrated using Random Forest, to provide information on the degree of recovery, inferred from the similarity (in terms of vegetation height, aboveground biomass, species diversity) between the burned and unburned control plots. Results showed that only the 25% of the burned plots can be considered as recovered. The burn severity had a significant effect on the recovery albeit strongly modulated by local topography. Overall, the key features of the recovered plots were a low-to-moderate burn severity and a favorable topographical setting, especially the shading effect of steep northwestern slopes. Furthermore, a warmer and more humid climate improved the capacity of recovery. These results constitute a valuable tool for improving forest management and preserving ecosystem services.

How to cite: Hoffren, R., de la Riva, J., Domingo, D., Lamelas, M. T., Ibarra, P., García-Martín, A., and Rodrigues, M.: Combining stand-level and remote sensing data to model post-fire recovery of Mediterranean tree-forest communities – A case study in Spain., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8017, https://doi.org/10.5194/egusphere-egu24-8017, 2024.

Wildfires pose an increasing threat to boreal forest and tundra ecosystems in boreal North America (Alaska and northwestern Canada), as their frequencies rise under global warming. These fires exhibit strong interannual variability that is influenced by regional atmospheric circulation. However, potential impacts of remote boundary forcings on regional fires and the underlying mechanisms remain unclear. This study provides a comprehensive analysis on the impacts of spring sea surface temperature (SST) and sea ice on interannual variability of burned area in this region during fire season (summer) from 1997 to 2020 using GFED5 burned area, SST and sea ice concentration data from the Met Office Hadley Centre, and ERA5 reanalysis data. Results show that in spring a warmer SST in the East Pacific and reduction of sea ice in the northern Chukchi Sea lead independently to an increase in burned area in boreal North America. The correlation coefficients between the SST and sea ice factors with the burned area in boreal North America are 0.43 and –0.44 respectively. The SST-fire relationships can be explained as follows: A warm SST anomaly in the East Pacific triggers a northeastward-propagated Rossby wave, inducing a high-pressure anomaly over boreal North America in spring. Consequently, this circulation anomaly causes a higher surface temperature and thus vegetation growth or drying. As temperatures rise and lightning activity intensifies in summer, burned area increases. On the other hand, the process of sea ice affecting burned area is different. A reduction in sea ice coverage in the northern Chukchi Sea leads to a decrease in surface albedo, resulting in an increase in heat flux. The heat release persists from spring to summer and causes a high-pressure circulation anomaly in boreal North America in summer, which suppresses regional water vapor convergence and precipitation, reducing soil moisture and surface air humidity and increasing vapor pressure deficit (VPD) thereby promoting fuel flammability.

How to cite: Zhao, Z., Lin, Z., and Li, F.: Impacts of Spring East Pacific SST and Arctic Sea Ice on Interannual Variability of Summer Burned Area in boreal North America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8303, https://doi.org/10.5194/egusphere-egu24-8303, 2024.

EGU24-8506 | Orals | BG1.1

Anticipating future extreme wildfire events by coupling ignition and success of initial attack models 

Pere Joan Gelabert Vadillo, Adrian Jiménez Ruano, Fellice Catelo, and Marcos Rodrigues Mimbrero

In recent years, the EU Commission has enacted various firefighting policies to combat and diminish the adverse effects of wildfires. The Mediterranean area has experienced an observable extension of its wildfire season, coupled with rapid shifts in fire-weather dynamics, resulting in exceptionally severe wildfire occurrences. As of 2022, the EU has recorded an approximate total burned area of 792,902 hectares, with forests accounting for 66% of this figure (Rodrigues et al., 2023).

The main objective of this study is to anticipate extreme wildfire conditions by providing a synthetic product depicting the chances of a fire event starting and escaping containment. To do so, we combined empirical models of ignition likelihood and effectiveness of the initial attack stage. We employed machine learning techniques to calibrate binary regression models using historical wildfire ignition data and geospatial layer depicting the main drivers of ignition and containment, namely: accessibility, human pressure on wildlands, fuel moisture and availability. We illustrate our approach along the Mediterranean coastal region of Spain. Our approach enables us to predict wildfire contention capacity under diverse population growth and climate warming scenarios. This strategy aims to improve disaster risk reduction by pointing wildfire management zones and prioritizing intervention in high-risk areas.

Results indicate a high predictive ability to model human-caused wildfire ignition (AUC>0.80) but a modest capability to capture the containment capability (AUC≈0.70). Accessibility by road largely controls the spatial pattern of ignition and containment, with dead fuel moisture content modulating the temporal pattern of probability. We further illustrate the approach by providing insights into future SSP (Shared Socieconomic Pathways) scenarios by synthesizing both products into comprehensive management zones (Rodrigues et al., 2022).

 

References

Rodrigues, M., Camprubí, À.C., Balaguer-Romano, R., Megía, C.J.C., Castañares, F., Ruffault, J., Fernandes, P.M., Dios, V.R. de, 2023. Drivers and implications of the extreme 2022 wildfire season in Southwest Europe. Science of The Total Environment 859, 160320. https://doi.org/10.1016/j.scitotenv.2022.160320

Rodrigues, M., Zúñiga-Antón, M., Alcasena, F., Gelabert, P., Vega-Garcia, C., 2022. Integrating geospatial wildfire models to delineate landscape management zones and inform decision-making in Mediterranean areas. Safety Science 147, 105616. https://doi.org/10.1016/j.ssci.2021.105616

How to cite: Gelabert Vadillo, P. J., Jiménez Ruano, A., Catelo, F., and Rodrigues Mimbrero, M.: Anticipating future extreme wildfire events by coupling ignition and success of initial attack models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8506, https://doi.org/10.5194/egusphere-egu24-8506, 2024.

EGU24-8507 | ECS | Posters on site | BG1.1

Unravelling Variability: Discrepancies in Amazonian Biomass Burning Emissions Under Different Emission Factor Scenarios  

Guilherme Mataveli, Matthew W. Jones, Gabriel Pereira, Saulo R. Freitas, Valter Oliveira, Esther Brambleby, and Luiz E.O. C. Aragão

Biomass burning (BB) plays a key role in the biosphere–atmosphere interaction. It is a major source of trace gases and aerosols that alters the atmosphere and the water cycle. Additionally, these emissions are often related to other detrimental impacts including biodiversity loss in fire-sensitive biomes, increase of respiratory diseases, and massive economic losses. BB emissions are used as inputs in models that estimate air quality and the effect of fires on Earth’s climate. Hence, an accurate estimation of BB emissions is paramount. While BB emissions spread over most of the global vegetated areas, the integration of orbital remote sensing and modelling is the most effective approach to estimate them from regional to global scales. BB emission estimation follows the relationship between burned biomass and the emission factor (EF - mass emitted of a given species, for example carbon dioxide, per mass of dry matter burned). The burned biomass can be estimated using two approaches: (i) based on the relationship among burned area, above-ground biomass, and combustion completeness; or (ii) based on fire radiative power (FRP), a quantitative measurement that is directly related to the rate of burned biomass and is estimated to each active fire detected by several orbital sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. EF values, which are Land Use and Land Cover (LULC) based, are required to estimate BB emissions independently on the approach adopted to estimate the burned biomass. Although novel approaches to improve the accuracy of BB emissions have been developed, the impact of EF values on the final estimated emissions remains uncertain. We have evaluated the impact of the EFs on the final estimate of fine particulate matter (PM2.5) emitted from BB in the Brazilian Amazon during a nineteen years’ time series (2002-2020) by running the PREP-CHEM-SRC emissions preprocessor tool under four EF scenarios: the tool original EF values based on the work of Andreae and Merlet (2001), the average EF values recently updated by Andreae (2019), and the minimum and maximum EF values also proposed by this author. The minimum (maximum) EF values were defined as the average EF value for each LULC class minus (plus) one standard deviation. The PM2.5 emissions were estimated at the spatial resolution of 0.1º using the FRP approach implemented on PREP-CHEM-SRC (3BEM_FRP model) having MODIS active fires as input, since this approach requires fewer inputs and the impact of the EFs over the emissions would be more evident. Our results showed that the annual average PM2.5 emission in the Amazon varied by 163% between the four EF scenarios (from1,426 Gg and 3,747 Gg), while the scenario based on the average values was the closest to the one based on PREP-CHEM-SRC original EF values (2,582 Gg and 2,213 Gg, respectively – an increase of 17%). These results contribute to the better understanding of how this single parameter impacts on the estimation of BB emissions.

How to cite: Mataveli, G., W. Jones, M., Pereira, G., R. Freitas, S., Oliveira, V., Brambleby, E., and E.O. C. Aragão, L.: Unravelling Variability: Discrepancies in Amazonian Biomass Burning Emissions Under Different Emission Factor Scenarios , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8507, https://doi.org/10.5194/egusphere-egu24-8507, 2024.

EGU24-8668 | ECS | Posters on site | BG1.1

Effect of long-range transported fire emissions on aerosol and cloud properties at high latitudes: In situ measurements and satellite observations 

Snehitha M. Kommula, Angela Buchholz, Yvette Gramlich, Tero Mielonen, Liqing Hao, Iida Pullinen, Lejish Vettikkat, Jorma Joutsensaari, Siegfried schobesberger, Petri Tiitta, Ari Leskinen, Dominic Heslin Rees, Sophie Haslett, Karolina Siegel, Chris Lunder, Paul Zieger, Radovan Krejci, Sami Romakkaniemi, Claudia Mohr, and Annele Virtanen

Global warming and climate change-induced rise in Earth’s temperature have increased the frequency of forest/wildfires over the past decade. Therefore, understanding the effect of fire emissions on aerosol-cloud interactions is crucial for improving Earth system models.

         We present observations from in-situ measurements of aerosol properties at the Puijo SMEAR IV station in eastern Finland and the Zeppelin Observatory in Ny-Ålesund, High Arctic. Both stations are frequently inside low-level clouds due to their topographic prominence. During the autumn of 2020, fire emissions from the same active fire region in south-eastern (SE) Europe reached both stations after ~2 - 8 days of atmospheric aging. This enabled us to investigate the changes in aerosol and cloud properties for clouds formed under the influence of aged fire emissions (referred to as the ‘fire’ period) and under cleaner conditions with no fire emission influence at these stations (‘non-fire’ period). The aerosol hygroscopicity parameter (κchem) was derived from the chemical composition data obtained from online aerosol mass spectrometers and was used to derive the number concentration of cloud condensation nuclei (NCCN) from the measured particle size distributions.

         At both stations, the aerosol number concentration in the accumulation mode and the cloud condensation nuclei concentration (NCCN) were higher during the fire period than during non-fire times. However, the aerosol hygroscopicity increased at Puijo but decreased a Zeppelin from the non-fire to fire period. At Puijo, in-situ measured cloud droplet number concentration (CDNC) was by a factor of ~7 higher when comparing fire to non-fire periods. This was in good agreement with the satellite observations (MODIS, Terra). At Puijo, the higher CCN concentrations during the fire period cause a depletion of the water vapor available for cloud droplet activation leading to larger observed activation diameters during cloud events despite the higher hygroscopicity of the aerosol particles.

         These observations show the importance of SE European fires for enhancing the CCN activity in Finland and the high Arctic. Results from this study emphasize the complex interplay between particle size and chemical composition, and how fires even from sources far away can have strong impacts in these remote regions.

How to cite: Kommula, S. M., Buchholz, A., Gramlich, Y., Mielonen, T., Hao, L., Pullinen, I., Vettikkat, L., Joutsensaari, J., schobesberger, S., Tiitta, P., Leskinen, A., Rees, D. H., Haslett, S., Siegel, K., Lunder, C., Zieger, P., Krejci, R., Romakkaniemi, S., Mohr, C., and Virtanen, A.: Effect of long-range transported fire emissions on aerosol and cloud properties at high latitudes: In situ measurements and satellite observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8668, https://doi.org/10.5194/egusphere-egu24-8668, 2024.

EGU24-9225 | ECS | Orals | BG1.1 | Highlight

Warming and cooling influences of North American boreal fires 

Max van Gerrevink, Sander Veraverbeke, Sol Cooperdock, Stefano Potter, Qirui Zhong, Michael Moubarak, Scott J. Goetz, Michelle C. Mack, James T. Randerson, Merritt R. Turetsky, Guido van der Werf, and Brendan M. Rogers

The Arctic-boreal region is warming rapidly, with consequences for northern ecosystems and global climate. Fires across the Arctic-boreal region are a major natural disturbance mechanism that initiate climate warming (positive) and cooling (negative) feedbacks. Understanding the net forcing effect from boreal fire on climate is crucial in managing and mitigating climate change impacts of boreal fires. Here we report radiative forcing estimates from boreal forest fires across Alaska and Western Canada (Arctic Boreal Vulnerability Experiment-domain). Our results integrate the effect of greenhouse gas emissions (warming) and aerosols emission (net cooling) have through direct combustion, post-fire vegetation recovery sequestering carbon (cooling), fire-induced permafrost degradation emitting CO2 and CH4 (warming), and changes in surface albedo (cooling). Alaskan fires are on average climate warming (1.34±2.95 W/m2 per burned area) – uncertainty given as spatial standard deviation, while Canadian fires show on average a climate cooling (‑2.26±2.48 W/m2 per burned area) effect. The emissions from the combustion of organic soils and post-fire permafrost thaw dominate the positive feedback for Alaskan fires, whereas the cooling effect of post-fire changes in surface albedo because of prolonged spring snow cover dominate for the western Canadian fires. Our work demonstrates large-scale spatial variability in the climate feedbacks from North American boreal forest fires. Such fine-scale spatial information on the warming and cooling influences of forest fires could be useful in designing forest management and fire suppression activities informed by climate impacts.

How to cite: van Gerrevink, M., Veraverbeke, S., Cooperdock, S., Potter, S., Zhong, Q., Moubarak, M., Goetz, S. J., Mack, M. C., Randerson, J. T., Turetsky, M. R., van der Werf, G., and Rogers, B. M.: Warming and cooling influences of North American boreal fires, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9225, https://doi.org/10.5194/egusphere-egu24-9225, 2024.

EGU24-9270 | ECS | Orals | BG1.1

What limits the growth of lightning fires in the remote northeast Siberian taiga? 

Thomas Janssen and Sander Veraverbeke

In recent years, boreal forests have experienced unprecedented fire activity. These fires have contributed substantially to carbon emissions and posed hazards to human health. In the remote northeast Siberian taiga, the vast majority of fires are ignited by lightning strikes and not by human activity. Furthermore, active fire suppression is largely absent in these remote areas, resulting in uncontrolled fire growth. Here, we present a detailed look at the places and times where these lightning fires do finally stop spreading and aim to identify the causes. We employ various remote sensing and geo-spatial datasets including fire weather as well as landscape variables such as the presence of surface water, road networks, woody fuel load, fire history, elevation and landcover, to pinpoint the limitations to fire growth along fire perimeters recorded between 2012 and 2022 at a 300-meter spatial resolution. We were able to attribute 87% of all fire perimeter locations to a statistically significant (p < 0.01) change in one or more of these fire limitations over either time (fire weather) or space (landscape). The analysis reveals that fire growth is mainly limited by a change in the vegetation (fuel type and fuel load) as well as a change to less favourable weather for fire spread, although there are clear regional differences in the importance of specific limitations. Overall, fire weather seems to be the most important limitation to fire growth in the north of the Siberian taiga where continuous permafrost is present. With a rising frequency of lightning strikes, droughts, and heatwaves in boreal regions, uncontrolled lightning fires have the potential to expand even further in the future, leading to significant implications for vulnerable permafrost landscapes and, consequently, the global carbon cycle.

How to cite: Janssen, T. and Veraverbeke, S.: What limits the growth of lightning fires in the remote northeast Siberian taiga?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9270, https://doi.org/10.5194/egusphere-egu24-9270, 2024.

EGU24-10145 | ECS | Posters on site | BG1.1

Burned area and climate extremes in different land covers in southeastern Australia 

Patrícia Páscoa, Ana Russo, Andreia Ribeiro, and Célia Gouveia

Large burned areas (BA) in southeastern Australia were regularly registered during hot and dry years, such as the Black Saturday (2009) and the Black Summer (2019-2020) extreme bushfires. These types of extreme climate conditions are expected to become more frequent, leading to an increased risk of large BA in this region.

In this work, the influence of drought conditions and hot events on the BA in southeastern Australia was assessed, using correlation and copula functions. Bivariate copula functions were fitted, and conditional probabilities of large BA given climate extremes were computed. Three classes of drought intensity were studied, namely moderate, severe, and extreme, as well as three thresholds for temperature extremes, namely the 80th, 90th, and 95th percentiles. Monthly BA were computed as the sum of the burned pixels in the fire season (from October to March), using data from the MODIS Burned Area product. The analysis was performed on forests, grasslands, and savannas separately. Drought conditions were assessed with SPEI at several time scales, computed with data from the CRU TS4.07 dataset. Maximum and minimum daily temperature were retrieved from the ERA5 dataset.

Results showed that the correlation between BA and SPEI was high in the current and previous 1 month for all land covers, being highest in savannas and lowest in grasslands. Short time scales of SPEI had the highest correlation on grasslands, and the opposite was observed in forests and savannas. The correlation with maximum temperature increased until 10-15 days before the fire event and surpassed 0.6 over forests. Minimum temperature presented much lower correlations and there was not a pronounced increase in the previous days, as observed with the maximum temperature.

The conditional probability of large BA increased with the intensity of the drought on all land covers, and it reached almost 100% probability of exceeding the 50th percentile of BA under extreme droughts on forests and savannas. For the case of the 80th percentile of BA, the probability was lower, but the difference given drought and non-drought conditions was larger than for the 50th percentile. On savannas and forests, the conditional probability was still high when considering SPEI in the previous 2 and 3 months.

Maximum temperature yielded a higher probability of BA for the two highest percentiles. Savannas presented the lowest probability of BA given hot events, and forests the highest. The probability increased up to 10 days before the fire. Overall, the probabilities obtained given drought conditions are higher than given hot events, particularly for larger fires. Moreover, high probabilities obtained with large time scales and longer lead times are indicative of the importance of drought conditions before the fire season and may help predict the occurrence of large BA.

 

Acknowledgments: This study was partially supported by FCT (Fundação para a Ciência e Tecnologia, Portugal) through national funds (PIDDAC) – UIDB/50019/2020, by project Floresta Limpa (PCIF/MOG/0161/2019), and by project 2021 FirEUrisk, funded by European Union’s Horizon 2020 research and innovation programme under the Grant Agreement no. 101003890). A.R. was supported by FCT through https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006. 

How to cite: Páscoa, P., Russo, A., Ribeiro, A., and Gouveia, C.: Burned area and climate extremes in different land covers in southeastern Australia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10145, https://doi.org/10.5194/egusphere-egu24-10145, 2024.

EGU24-10377 | ECS | Posters on site | BG1.1

Human land occupation regulates the effect of the climate on the burned area of the Cerrado biome 

Carlota Segura-Garcia, David Bauman, Vera L. S. Arruda, Ane Alencar, and Imma Oliveras Menor

The Brazilian Cerrado is a heterogeneous biome formed by a mosaic of savannas, grasslands, and smaller patches of denser woody forms. In this biome, fire is a natural disturbance agent that contributes to maintaining its open ecosystems and rich biodiversity. However, modern human activities and climate change are altering its fire regimes. In tropical savannas, land-use expansion is usually associated to a decrease in burned area primarily through land fragmentation, but also through active fire suppression. Meanwhile, climate change is fostering fire weather conditions, exacerbating fire activity. Hence, the two main drivers of fire could be pushing burned area in opposite directions, both with important ecological consequences for the Cerrado. However, it remains unclear how these two drivers interact, which is essential to devise effective fire management policies and conservation plans.

In this study, we use a causal inference framework to quantify the interaction between anthropic area percentage – as a proxy of human presence and fragmentation – and various climatic variables on their effects on Cerrado’s burned area. As well, we explore the spatial structure of temporal trends in burned area, anthropic expansion and climate change, and quantify the causal effect of the last two on the former.

We use geospatial data from different sources on a 0.2o grid over the Cerrado for the period 1985 to 2020. We use burned area and land use data from the MapBiomas project, and climate re-analysis data from ERA5 Land, CHIRPS and TerraClimate. We design our models using Directed Acyclic Graphs, a graphic representation of the causal relations between the predictors and burned area that informs variable selection for causal inference. Hence, based on these DAGs, we build multilevel Bayesian regression models to quantify the effects of the predictors and their interactions.

We find that a larger presence of land-use activities keeps burned area low and, importantly, hinders the effects of the climate. That is, while in landscapes composed mostly of native vegetation hotter and drier conditions increase burned area as expected; in anthropic landscapes, humans completely limit burned area responsiveness to climate. We also find spatially heterogeneous increasing and decreasing trends in burned area over the period, but concentrated in those areas of the Cerrado that were mostly natural in 1985. In these areas, a large anthropic expansion brought about a decrease in burned area, while we observe an increase in burned area in relation to climate change only in the areas that remained intact throughout the study period.

In conclusion, burned area in the Cerrado is shaped primarily by the extent of human presence in the landscape, even limiting the effects of the climate, while climatic effects become relevant in areas with larger tracts of native vegetation, suggesting that these areas may be more vulnerable to climate change.

How to cite: Segura-Garcia, C., Bauman, D., S. Arruda, V. L., Alencar, A., and Oliveras Menor, I.: Human land occupation regulates the effect of the climate on the burned area of the Cerrado biome, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10377, https://doi.org/10.5194/egusphere-egu24-10377, 2024.

EGU24-10606 | ECS | Orals | BG1.1

Characterizing lightning-ignited wildfire occurrences at sub-grid scales in orography-aware NOAA/GFDL land model LM4.2 

Rui Wang, Enrico Zorzetto, Sergey Malyshev, and Elena Shevliakova

Lightning ignitions are the dominant causes of wildfires in many regions, responsible for 80% of burned areas at high latitudes and about 70% of fires in the Amazon rainforest. With global wildfire activities and extreme fire events (e.g., intensity, duration, and size) increasing under the changing climate conditions, understanding the interactions between lighting, landscape characteristics, and wildfires is crucial for predicting and mitigating the impacts of climate change. Cloud-to-ground lightning activities are driven by a combination of large- and local-scale factors, e.g., local atmospheric circulations and convection and topography. Furthermore, the number of lightning strikes is predicted to increase by 10 – 30 % per degree warming. Decadal satellite observations have revealed Earth’s lightning hotspots at very high resolution, however, there is a paucity of fine-scale lightning strikes and lightning-ignited wildfires (LIW) in the Earth system and climate models. Currently, many climate and ESM  models do not include fires at all or simulate them with meteorological inputs and grid-average lightning at the scale of atmospheric models (25 to 100 km), introducing large uncertainties of LIW due to the lack of information at the scales relevant to fire dynamics.  Lack of information about lightning trends and variability hinders the prediction and projection of fires and their contribution to carbon and other atmospheric tracers and global warming. For example, in the US National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL) ESM4.1 model, the fire model uses a climatology of lightning strikes from preindustrial to 2100.

In this presentation, we will demonstrate the implications of capturing subgrid lightning distributions in the GFDL land model LM4.2 for the global simulations of wildfire dynamics over the available records (1998-2013) and provide insights into future projections. LM4.2 captures sub-grid heterogeneity of land cover and use, soil geomorphology, and topography, facilitating the understanding of LIW distribution across global to regional and sub-grid scales. In this study, we leverage 0.1° × 0.1° lightning observations from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) in the GFDL LM4-HB to characterize fine-scale lightning strike distribution and associated LIW.

How to cite: Wang, R., Zorzetto, E., Malyshev, S., and Shevliakova, E.: Characterizing lightning-ignited wildfire occurrences at sub-grid scales in orography-aware NOAA/GFDL land model LM4.2, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10606, https://doi.org/10.5194/egusphere-egu24-10606, 2024.

EGU24-10793 | ECS | Posters on site | BG1.1

A Decision Support System for Forest Fire Danger Notices in Ireland  

Padraig Flattery, Klara Finkele, Paul Downes, Alan Hally, and Ciaran Nugent

Since 2006 the Canadian Forest Fire Weather Index System (FWI) has been employed operationally at Met Éireann to predict the risk of forest fires in Ireland. Around 11% or 770,000 ha of the total land area of Ireland is afforested, but there are also large areas of open mountain and peatlands covered in grasses, dwarf-shrub and larger woody shrub type vegetation which can provide fuel for spring wildfires under suitable conditions. After winter, vegetation can be dead or have a very low live moisture content, and the flammability of this vegetation can be readily influenced by prevailing weather, especially following prolonged dry periods.

Different decision support tools are available to different sectors, namely:

  • The General Public: who have access to fire weather index meteograms on Met Éireann’s public website.
  • Local Authorities, who have access to the ANYWHERE multi-hazard warning system, which provides multiple sources of information about fire danger and propagation.
  • The Department of Agriculture, Food and Marine (DAFM), who are provided with information and additional support from National and European partners and networks.

DAFM is the Forest Protection authority in Ireland responsible for issuing Forest Fire Danger Notices which improve preparedness for fire responses and are based on a range of factors including information provided by Met Éireann who calculate the FWI and FWI components using observation data at synoptic stations, and the predicted FWI for the next five days ahead based on numerical weather prediction data. This allows fire responders to build resilience and prepare for impending fires.

The FWI is determined based on the types of forest fuel and how quickly they dry out/get rewetted, and components of fire behaviour. The FWI represents the fire intensity as the rate of energy per unit length of fire front (kW/m). The components which provide the most accurate indication of risk under Irish conditions are the Fine Fuel Moisture Code and Initial Spread Index, based on the fuels involved and ignition patterns observed to date. Since 2022 Met Eireann provide the FWI as well as the individual components Fine Fuel Moisture Content and Initial Spread Index via the public website for synoptic stations. These indices are based on observations and a seven-day forecast into the future using ECMWF predictions. This allows all county councils responsible for wildfire preparedness to access this information swiftly and directly.

Met Éireann also use the ANYWHERE multi-hazard warning tool which allows for visualisation of multiple fire-related risk factors and warning indices to be viewed simultaneously. The ANYWHERE system, in combination with our station-based forecast and antecedent conditions, provide fire managers and response teams with excellent information with which to make decisions.

How to cite: Flattery, P., Finkele, K., Downes, P., Hally, A., and Nugent, C.: A Decision Support System for Forest Fire Danger Notices in Ireland , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10793, https://doi.org/10.5194/egusphere-egu24-10793, 2024.

EGU24-10920 | ECS | Posters on site | BG1.1

Reconstructing 20th century burned area by combining global fire model input, satellite observations and machine learning 

Seppe Lampe, Lukas Gudmundsson, Vincent Humphrey, Inne Vanderkelen, Bertrand Le Saux, and Wim Thiery

The temporal coverage (∼2000 to present) of global burned area satellite observations limits many aspects of fire research e.g., long-term trend analysis, disentangling the effect of various drivers on fire behaviour and detection and attribution of changes to climate change. As a result, global fire models are more frequently being called upon to answer questions about past and future fire behaviour. Unfortunately, the limited temporal coverage of the observations also hinders the development and evaluation of these fire models. The current generation of global fire models from ISIMIP are able to simulate well some characteristics of regional fire behaviour such as mean state and seasonality. However, the performance of these models differs greatly from region to region, and aspects such as extreme fire behaviour are not well represented yet. Here, we explore the possibility of using machine learning algorithms to model burned area from the same input parameters that are passed to global climate models. Once trained, this data-driven model can be evaluated against regional proxies for past fire behaviour e.g., tree rings and charcoal records. Hopefully, this data-driven reconstruction can provide valuable insights on the 20th century burned area, and can help improve and evaluate fire models.

How to cite: Lampe, S., Gudmundsson, L., Humphrey, V., Vanderkelen, I., Le Saux, B., and Thiery, W.: Reconstructing 20th century burned area by combining global fire model input, satellite observations and machine learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10920, https://doi.org/10.5194/egusphere-egu24-10920, 2024.

EGU24-10947 | Orals | BG1.1 | Highlight

Burned area and fire emissions according to the fifth version of the Global Fire Emissions Database (GFED) 

Guido van der Werf, James Randerson, Dave van Wees, Yang Chen, Roland Vernooij, Louis Giglio, Joanne Hall, Douglas Morton, Kelley Barsanti, and Bob Yokelson

Quantifying burned area and associated fire emissions is paramount to understand how changing fire patterns affect radiative forcing and air quality. It is now well established that many fires are too small to be detected by coarse resolution satellite burned area products on which the Global Fire Emissions Database (GFED) relied. In the fifth version of GFED (GFED5) we therefore combine burned area derived from mapped coarse-resolution burned area from the MODIS sensor -which excels in detecting larger fires- with small-fire burned area. The latter is derived from MODIS active fire detections scaled to burned area using ratios constrained by higher-resolution burned area datasets from Landsat and Sentinel-2 for selected regions. Burned area in cropland regions was based on the Global Cropland Area Burned (GloCAB) dataset. Total global burned area is 61% higher than in GFED4s. We converted burned area to emissions using a simplified version of the CASA model used in previous GFED versions, but which now runs at a 500 m spatial resolution. This allows for better constrained modeled fuel loads based on field measurements. Although GFED5 emissions are aggregated to a 0.25 degree grid due to the statistical nature of deriving our burned area, we can now account for heterogeneity in fire processes within these large pixels. Emissions (3 Pg carbon per year) are roughly 50% higher than in GFED4 and we show how diverging trends in grassland versus forest ecosystems impact trends in total emissions. Finally, we show how converting fire carbon losses to trace gas and aerosol emissions is now better constrained due to the addition of several new emission factor measurement campaigns. In the savanna biome we now account for spatial and temporal variability in emission factors.

How to cite: van der Werf, G., Randerson, J., van Wees, D., Chen, Y., Vernooij, R., Giglio, L., Hall, J., Morton, D., Barsanti, K., and Yokelson, B.: Burned area and fire emissions according to the fifth version of the Global Fire Emissions Database (GFED), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10947, https://doi.org/10.5194/egusphere-egu24-10947, 2024.

EGU24-11206 | ECS | Posters on site | BG1.1 | Highlight

Global cloud-to-ground lightning data to inform wildfire ignition patterns 

Esther Brambleby, Sander Veraverbeke, Guilherme Mataveli, Manoj Joshi, and Matthew Jones

Lightning is recognised as a crucial wildfire ignition source worldwide, especially in remote regions including boreal and temperate forests where large carbon stocks are held. The societal consequences of these wildfires, as well as their contribution to climate change, can be immense. The occurrence of lightning is projected to increase in these areas under climate change, however robust assessments of lightning contribution to wildfire risk have been restricted to selected regions due to the narrow spatial extent of cloud-to-ground lightning records. Consequently, evaluations of lightning-fire relationships using existing global lightning observational datasets have been limited to considering the total amount of lightning. Only cloud-to-ground lightning can ignite a wildfire, therefore when considering impacts on wildfire risk it is essential to distinguish between lightning types.

Using Vaisala’s unique Global Lightning Dataset (GLD360), which discriminates between cloud lightning and cloud-to-ground lightning strikes, we present our preliminary analyses of the spatial patterns and seasonality of cloud-to-ground lightning. Here, we show the regional variation in the lightning frequency and the cloud-to-ground fraction, as well as the strength (current) and polarity of cloud-to-ground lightning strikes.

By considering cloud-to-ground lightning strikes only, we characterise the spatial and seasonal variation in lightning events with the potential to ignite wildfires. Combining global observations of lightning strikes with observations of individual fires and coincident meteorology will advance our mechanistic understanding of wildfire ignition potential in a range of weather conditions, improve the process representation of the ignition process in global models, and refine projections of changing wildfire risks under climate change.

How to cite: Brambleby, E., Veraverbeke, S., Mataveli, G., Joshi, M., and Jones, M.: Global cloud-to-ground lightning data to inform wildfire ignition patterns, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11206, https://doi.org/10.5194/egusphere-egu24-11206, 2024.

This research delves into the dynamics of forest fires across various Indian regions, particularly during the unique COVID-19 lockdown period. The study's core focus is on the interaction between forest fires, climatic factors, and vegetation indices in a scenario of reduced human activity. It employs a multidimensional methodology, integrating satellite imagery and climatic data from periods before, during, and post-lockdown. The lockdown provides a critical opportunity to assess the impact of decreased human interference on forest fire patterns. Advanced statistical techniques are used to analyze the relationship between vegetation indices, fire occurrences, and meteorological conditions. This approach aims to uncover the underlying mechanisms driving these relationships, moving beyond simple trend identification. The research offers a nuanced perspective by differentiating natural factors from human influences. This distinction is vital in understanding the environmental dynamics during the lockdown. The findings have significant implications, offering insights for policymakers and environmentalists in enhancing forest fire management strategies. Emphasizing the need for a comprehensive understanding of environmental interactions, this study contributes to forming more informed and sustainable approaches to natural disaster management in the face of global challenges like climate change and pandemics.

How to cite: Kate, R. and Bhattacharya, J.: Forest Fires during COVID-19: Assessing Environmental Interactions and Fire Dynamics Amidst Reduced Human Intervention in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11291, https://doi.org/10.5194/egusphere-egu24-11291, 2024.

EGU24-11432 | ECS | Posters on site | BG1.1 | Highlight

Northern high latitude peat fires: from lab to modelling  

Dimitra Tarasi, Eirini Boleti, Katie Blackford, Matthew Kasoar, Emmanouil Grillakis, Guillermo Rein, Hafizha Mulyasih, and Apostolos Voulgarakis

Climate warming is occurring most rapidly at high latitudes, heightening the vulnerability of carbon-rich peatlands to fire. Northern peatlands comprise the largest terrestrial carbon store, and exert a net cooling effect on the climate. Warmer and drier conditions due to the anticipated climate change are expected to contribute substantially to increased fire severity and frequency in the northern high latitudes, potentially shifting peatlands from being carbon sinks to being greenhouse gas emission sources. Therefore, peat fires, which are considered the largest and most persistent fires on Earth, can significantly impact the global carbon cycle, atmospheric composition, climate, air quality, and human health. Representing peatland fire feedbacks to climate in Earth system models is essential for accurately predicting the future of the climate system. Here, we present the first steps of an effort to distill lab results on peat burning and emissions into global fire modelling. Since peat moisture content and the depth of burn have been experimentally proved to be critical for the representation of peat fires, we aim to incorporate those mechanisms into a global model functionality. More specifically, we aim to represent the mechanistic understanding of the ignition and spread of peat fires in INFERNO-peat, the peat module of the JULES-INFERNO global fire model. To assess the added value of our updated model, we compare the simulated burnt area and carbon emissions with observation-based products. As boreal regions remain a big mystery for the future of our planet, our improved model representation of peat fires in northern high latitudes contributes to a better understanding of future atmospheric composition, radiative forcing and climate. 

How to cite: Tarasi, D., Boleti, E., Blackford, K., Kasoar, M., Grillakis, E., Rein, G., Mulyasih, H., and Voulgarakis, A.: Northern high latitude peat fires: from lab to modelling , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11432, https://doi.org/10.5194/egusphere-egu24-11432, 2024.

EGU24-11599 | ECS | Orals | BG1.1

Comparison and validation of state-of-the-art fire emissions models for the Amazon 

Dave van Wees, Vincent Huijnen, Matthias Forkel, Jos de Laat, Niels Andela, and Christine Wessollek

Amazon forest conservation is critical for reaching net-zero carbon emissions and protecting regional biodiversity but these efforts are at risk from deforestation, fire and drought. In particular, accurate quantification of carbon losses from forest and deforestation fires are required to understand long-term impacts of fire on the carbon cycle and inform management strategies. Recent developments in the detection of burned area, near-real time tracking of fire patch metrics, and higher-resolution fire emissions models allow for improved estimates of carbon losses from fire. Nevertheless, independent validation of these novel approaches often remains elusive, leading to large disagreement between different emissions inventories.

Here, we compare carbon emissions estimates from several state-of-the-art fire emissions models, including a 500-m resolution GFED version, GFAS, and the Sense4Fire project, in a case-study for the Amazon region. Where necessary, we have updated the models to extend to 2022 and to include the most recent version of model input data from MODIS (Collection 6.1). We analysed the added years of data to elucidate recent trends in fire-related carbon emissions across the Amazon and adjacent biomes. For validation, we ingested the CO emissions from the considered fire emissions models into an atmospheric transfer simulation (IFS-COMPO) and compared those to column CO observations from Sentinel-5P TROPOMI. Finally, we propose an optimization methodology for matching modelled CO concentrations to observations with the objective of constraining regional carbon losses from fire. Results provide novel insights into carbon losses from fire across different fire types and land use practices, and can be extended to global scale for improved estimates of global fire emissions.

How to cite: van Wees, D., Huijnen, V., Forkel, M., de Laat, J., Andela, N., and Wessollek, C.: Comparison and validation of state-of-the-art fire emissions models for the Amazon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11599, https://doi.org/10.5194/egusphere-egu24-11599, 2024.

EGU24-11809 | ECS | Posters on site | BG1.1

Analysing the effects of postfire oak afforestation on the provision of ecosystem services 

Luis Filipe Lopes, Erika S. Santos, Leónia Nunes, Paulo M. Fernandes, and Vanda Acácio

Forests play a substantial role in generating externalities and supporting services essential for maintaining key ecosystem functions and processes. Fire has long been a natural element of forest dynamics, contributing to model the structure, composition, and diversity of vegetation. However, changes in fire regimes in recent decades in Europe (e.g., more frequent and severe fires) have led to negative ecological, social, and economic impacts, particularly marked by a decline in the provision of ecosystem services. Mediterranean Europe, being a region highly prone to wildfires and currently experiencing a change in fire regimes, exemplifies this situation.

In this study, we aim to understand the effects of postfire oak afforestation on the provision of ecosystem services (ES). We analysed 15 afforestation projects with the deciduous Pyrenean oak (Quercus pyrenaica) carried out in 1994-2006 in similar soil type (Cambisols) in the North and Center of Portugal, including seven pure and eight mixed oak stands. For each project area, we identified an adjacent control area affected by the same fire event but without oak afforestation or evident management. In 2021-2022, for each project and control areas, we collected field data on: site conditions, stand characteristics, forest biometry, understory vegetation (height and cover), floristic richness and diversity, oak natural regeneration and litter. At the moment of data collection, the majority of projects (10) were 12 to 17 years old, with the remaining projects (5) having been implemented 21 to 25 years ago. Collected data was used to quantify provisioning ecosystem services (wood volume) and regulation and maintenance services (forest and litter carbon, fire protection, maintenance of nursery populations, habitats, and seed dispersal).

Afforested areas supplied more provisioning services (higher wood volume), as a consequence of a higher tree density when compared to non-afforested areas. Total carbon content and litter carbon were not significantly different between afforested and control areas. Nevertheless, afforested and control areas exhibited distinct patterns concerning carbon in the different forest layers: carbon in the tree layer was significantly higher in afforested areas, while carbon in the understory layer was significantly higher in control areas. Afforested areas also showed a significantly higher fire protection service, as a consequence of lower fuel load from regular understory shrub management. Lastly, we found no significant differences in services related to maintenance of nursery populations and habitats (estimated with floristic species and diversity), and seed dispersal (estimated with oak natural regeneration), although afforested areas presented a higher number of oak seedlings.

Our study shows that postfire afforestation in oak forests may have a positive, null or negative impact on ES, depending on the service under analysis, highlighting the existence of trade-offs among multiple ES. We emphasize the importance of a comprehensive understanding of the impacts of postfire afforestation on ES to guide postfire management, aiming to enhance forest resilience in the face of predicted climate change.

How to cite: Lopes, L. F., Santos, E. S., Nunes, L., Fernandes, P. M., and Acácio, V.: Analysing the effects of postfire oak afforestation on the provision of ecosystem services, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11809, https://doi.org/10.5194/egusphere-egu24-11809, 2024.

EGU24-11962 | Orals | BG1.1

The Great Fuel Moisture Survey: developing fundamental wildfire science and sustainable community owned agency in traditionally non-fire prone societies 

Nicholas Kettridge, Katy Ivison, Alistair Crawford, Gareth Clay, Claire Belcher, Laura Graham, and Kerryn Little

New fire vulnerable communities are emerging in traditionally non-fire prone regions of the world. But these communities are often largely unaware of the developing threat and do not hold the core wildfire knowledge to galvanise collective community-based action to mitigate the risk. Furthermore, we urgently require knowledge of fuel moisture dynamics and flammability of fuels in such regions to provide accurate assessments of fire danger at the national scale. Here we characterise the moisture content and flammability of heather through engaged environmental science, demonstrating the potential of the approach to develop a public consciousness and knowledge of wildfire within communities. Fuel sampling kits were sent to 150 samplers who collected ~1000 vegetation samples across the UK (from Land’s End to John O’Groats) over a period of two days during a single period of high fire danger. The validity of the volunteer approach for collecting high quality fuel moisture data was also assessed from the analysis of a separate ~1500 samples collected by 17 samplers in a single test plot. The approach provides a simple nationally available entry point for residents traditionally unaware of both the wildfire risk and the management of their community for wildfire mitigation. Empowering samplers offers potential future opportunity to create meaningful local datasets, to build communities, and in doing so give a strong voice to residents in regional and national policy discussions.

How to cite: Kettridge, N., Ivison, K., Crawford, A., Clay, G., Belcher, C., Graham, L., and Little, K.: The Great Fuel Moisture Survey: developing fundamental wildfire science and sustainable community owned agency in traditionally non-fire prone societies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11962, https://doi.org/10.5194/egusphere-egu24-11962, 2024.

EGU24-11965 | ECS | Posters on site | BG1.1

Effects of 2018 wildfire on soil properties in a peatland within the Peak District National Park (central England) 

Luigi Marfella, Mark A. Ashby, Georgia Hennessy, Rossana Marzaioli, Flora A. Rutigliano, and Helen C. Glanville

Peatland soil is a valuable component of natural capital by constituting the largest terrestrial carbon sink (~30% of the global soil carbon) and an essential freshwater source. Despite covering only ~3% of the Earth’s surface, peatlands provide crucial ecosystem services i.e. water-quality improvement and climate regulation by storing carbon in peat. However, peat degradation due to anthropogenic activities (e.g. drainage) as well as global climate change exposes this ecosystem to fire risk.
This study assessed the medium-term (~5 years) impacts of the 10 August 2018 wildfire within The Roaches Nature Reserve. This area spans the southeastern sector of the Peak District National Park and Special Area of Conservation (SAC-UK0030280). According to the Staffordshire Wildlife Trust (responsible authority for Reserve management), the human-caused fire broke out in a wooded area and aided by wind, spread to the peatland. Here, we integrated soil analyses and vegetation surveys of a burnt and unburnt area i) to assess possible correlations between soil biogeochemical properties and vegetation cover with ii) remote sensing to collect data on fire severity exploring temporal and spatial wildfire impacts.
Processing of satellite imagery highlighted a high-severity fire impact within the perimeter of the burned area, which predicts alteration of soil characteristics. Preliminary outcomes on the soil indicated deacidification and reduced water content in the burned peat remains 5 years post-fire.
Given that global peatland conservation is an important tool for addressing climate-change, this research appears necessary to develop effective management strategies, including rewetting of peatlands postfire.

How to cite: Marfella, L., Ashby, M. A., Hennessy, G., Marzaioli, R., Rutigliano, F. A., and Glanville, H. C.: Effects of 2018 wildfire on soil properties in a peatland within the Peak District National Park (central England), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11965, https://doi.org/10.5194/egusphere-egu24-11965, 2024.

The ignition, spread, and severity of wildfires are driven largely by weather conditions (Jain et al. 2020: https://doi.org/10.1139/er-2020-0019; Liu et al. 2013: https://doi.org/10.1371/journal.pone.0055618).  The main tool for weather prediction across the globe is a set of physical, coupled atmosphere/ocean models, called numerical weather prediction (NWP).  Despite rapid improvements in the last few decades, NWP alone is not sufficient for wildfire prediction, because it does not resolve every process related to wildfire.  One solution is to post-process NWP with statistical models, which correct the NWP model towards better resolving processes related to the phenomenon of interest (here, wildfire).  This post-processing is called model-output statistics (MOS) and typically involves linear regression.  However, recent work has advanced MOS by incorporating more powerful statistical models from deep learning (DL).  We use DL to predict extreme fire weather and behaviour at multi-day lead times throughout the United States.

 

For fire weather, we have trained U-nets -- a type of deep neural network -- to predict at lead times of 3-240 hours over the United States.  The output (target) variables are seven indices from the Canadian Fire Weather Index System (CFWIS), computed from the ECMWF Reanalysis version 5 (ERA5).  These seven indices include the fine-fuel moisture code (FFMC), initial-spread index (ISI), overall fire-weather index (FWI), etc.  Meanwhile, the input (predictor) variables come from five sources.  The first is a forecast time series of atmospheric state variables (height, temperature, humidity, and wind) from the Global Forecast System (GFS) NWP model.  The second is a forecast time series of surface and subsurface moisture (soil moisture, accumulated precipitation, and snow depth) from the GFS.  The third is a set of constant fields (terrain height/slope/aspect, land-sea mask, etc.) describing the underlying terrain.  The fourth is a lagged time series of CFWIS over the past several days, i.e., past target values.  The fifth is a forecast time series of CFWIS indices, computed by applying the CFWIS functions directly to GFS-forecast weather variables.  These are the uncorrected (GFS-only) CFWIS forecasts, to be corrected by the U-net.

 

For fire behaviour, we have trained random forests -- ensembles of decision trees -- to predict fire radiative power (FRP) at lead times of 1-48 hours over the United States.  The labels (correct answers) for FRP are obtained from the Regional ABI and VIIRS Emissions (RAVE) merged satellite product.  Predictors for the random forest include the first three sources listed for the U-net above, plus a lagged time series of FRP over the past 24 hours, i.e., past target values.

 

Both models -- the U-net for fire weather and the random forest for fire behaviour -- are trained with built-in uncertainty quantification.  Thus, at every lead time and grid point, both models provide an expected value and an estimate of their own uncertainty.  We will present objective evaluation results (for both the mean forecast and uncertainty) and explainable artificial intelligence (XAI) to understand what the models have learned, e.g., which spatiotemporal weather patterns in a given area are most conducive to extreme fire weather/behaviour.

How to cite: Lagerquist, R. and Kumler, C.: Using deep learning to improve multi-day forecasts of extreme fire weather and behaviour throughout the United States, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12223, https://doi.org/10.5194/egusphere-egu24-12223, 2024.

EGU24-12320 | ECS | Orals | BG1.1

Integrating Human Domain Knowledge into Artificial Intelligence for Hybrid Forest Fire Prediction: Case Studies from South Korea and Italy 

Hyun-Woo Jo, Shelby Corning, Pavel Kiparisov, Johanna San Pedro, Andrey Krasovskiy, Florian Kraxner, and Woo-Kyun Lee

Forest fires pose a growing global threat, exacerbated by climate change-induced heat waves. The intricate interplay between changing climate, biophysical, and anthropogenic factors emphasizes the urgent need for sophisticated predictive models. Existing models, whether process-based for interpretability or machine learning-based for automatic feature identification, have distinct strengths and weaknesses. This study addresses these gaps by integrating human domain knowledge, crucial for interpreting forest fire dynamics, into a machine learning framework. We introduce FLAM-Net, a neural network derived from IIASA's wildfire Climate impacts and Adaptation Model (FLAM), melding process-based insights of FLAM with machine learning capabilities. In optimizing FLAM-Net for South Korea, new algorithms interpret national-specific forest fire patterns, and multi-scale applications, facilitated by U-Net-based deep neural networks (DN-FLAM), yield downscaled predictions. Successfully tailored to South Korea's context, FLAM-Net and DN-FLAM reveal spatial concentration near metropolitan areas and the east coastal region, with temporal concentration in spring. Performance evaluation yields Pearson's r values of 0.943, 0.840, and 0.641 for temporal, spatial, and spatio-temporal dimensions. Projections based on Shared Socioeconomic Pathways (SSP) indicate an increasing trend in forest fires until 2050, followed by a decrease due to increased precipitation. During the optimization process of FLAM-Net for Italy, optimal parameters for sub-areas are identified. This involves considering biophysical and anthropogenic factors at each grid, contributing to improved localized projection optimization by utilizing various sets of optimal parameters. There by, this process illuminates the intricate connections between environmental factors and their interpretation in the dynamics of forest fires. This study demonstrates the advantages of hybrid models like FLAM-Net and DN-FLAM, seamlessly combining process-based insights and artificial intelligence for interpretability, accuracy, and efficient optimization. The findings contribute scientific evidence for developing context-specific climate resilience strategies, with global applicability to enhance climate resilience.

How to cite: Jo, H.-W., Corning, S., Kiparisov, P., San Pedro, J., Krasovskiy, A., Kraxner, F., and Lee, W.-K.: Integrating Human Domain Knowledge into Artificial Intelligence for Hybrid Forest Fire Prediction: Case Studies from South Korea and Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12320, https://doi.org/10.5194/egusphere-egu24-12320, 2024.

EGU24-12529 | ECS | Orals | BG1.1 | Highlight

GlobalRx: A global assemblage of regional prescribed fire records for use in assessments of climate change impacts 

Alice Hsu, Jane Thurgood, Adam Smith, Liana Anderson, Hamish Clarke, Stefan Doerr, Paulo Fernandes, Crystal Kolden, Cristina Santín, Tercia Strydom, and Matthew Jones and the GlobalRx Consortium

Prescribed (Rx) and controlled fires are an important land management tool used globally for a variety of reasons, including the reduction of hazardous fuel loads, ecological conservation, agriculture, and natural resource management. Its use has important implications for wildfire risk, biodiversity, and carbon storage. However, the use of Rx and controlled fires is highly dependent upon weather conditions, requiring a weather window during which a careful balance of temperature, moisture, and wind ensure that the burns achieve their objectives while minimizing ecological damage or risk to human lives or assets. The planning and execution of Rx burns must also consider how these weather conditions interact with the local vegetation and ecology. As fire weather is projected to grow more extreme under the impacts of climate change, there is a growing need to monitor this effect on the ability to carry out Rx burning.

Here, we introduce a new dataset, GlobalRx, which includes around 140,000 records of Rx and other controlled fires from 16 countries, encompassing 207 ecoregions and 13 biomes around the world. For each record, we have geolocated values of various metrics of fire weather and fire danger (e.g. fire weather indices, vapour pressure deficit) from the ERA5 meteorological reanalysis, as well as the biome, ecoregion, fuelbed type, and protected area status from global thematic layers. We demonstrate the usefulness of this dataset for analyzing viable meteorological windows under which Rx fires may be conducted across diverse environmental settings in the present climate, as well as how these Rx burning windows may shift under the threats of climate change. This dataset has potential to shed light on how Rx burning windows may shift under future climate change, as well as opportunities to understand other drivers and effects of Rx burning.

This project has been supported by valuable contributions from non-public data from a consortium of data providers: Parks Canada, South Africa National Parks, Brazilian Institute of the Environment and Renewable Natural Resources, East-Pyrenees Prescribed Burning Team, Institute for Nature Conservation and Forests (Portugal), Regional Forest Fire Service (Italy), Russian Federal Forestry Agency, H2020 LifeTaiga Project, Government of the Principality of Asturias, Council of Andalucía, Council of Galicia, Forestry England, National Forestry Commission of Mexico, ZEBRIS Geo-IT GmbH, Hokkaido University, Pau Costa Foundation, Asian Forest Cooperation Organization.

How to cite: Hsu, A., Thurgood, J., Smith, A., Anderson, L., Clarke, H., Doerr, S., Fernandes, P., Kolden, C., Santín, C., Strydom, T., and Jones, M. and the GlobalRx Consortium: GlobalRx: A global assemblage of regional prescribed fire records for use in assessments of climate change impacts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12529, https://doi.org/10.5194/egusphere-egu24-12529, 2024.

EGU24-13237 | Posters on site | BG1.1

The role of fire radiative power to estimate fire-related smoke pollution. 

Rita Durao, Catarina Alonso, Ana Russo, and Célia Gouveia

The intensity of a wildfire can be assessed based on its released energy, obtained through remote measurements of the fire's radiative power. Since the Fire Radiative Power (FRP) is proportional to the amount of burned biomass and therefore to smoke production. Higher FRP values are associated with more severe fires, suggesting higher levels of smoke production and, consequently, higher emissions of particulate matter and other pollutants. The specific composition of smoke emissions can vary depending on factors such as the type of vegetation burned, the temperature of the fire, and the combustion conditions. In general, fire smoke is composed of a variety of air pollutants, including gases (NOx, CO, VOCs, O3, PAHs, etc) and particulate matter (PM). The objective of this work is to evaluate the ability of FRP, to be used as an indicator of fire smoke pollution. Particulate matter (PMx) and carbon monoxide (CO) concentrations emitted during recent wildfires in Portugal are analyzed to assess the link between pollution concentration levels and fire intensity over the affected areas, taking into account the spatial and temporal characteristics of each event. For this purpose, two particularly severe fires with significant impacts on air quality in central and southern Portugal were analyzed namely the ones taking place in October 2017 and August 2018. Concentrations of PMx and CO were evaluated through CAMS data, and the radiative power through the FRP product of the SEVIRI/MSG disseminated by LSA-SAFThe results show that the emitted pollutant concentrations significantly exceeded the established daily target limit values (air quality and public health guidelines). The fire intensity, based on the emitted Radiative Energy (FRE) derived from FRP, aligns with the known severity of these events, consistent with the observed concentrations of air pollutants, being demonstrated that the FRP can be associated with smoke production, especially PMx emissions during a fire. Thus, the proposed methodology using FRP can be a valuable tool for assessing the impact of wildfires on air quality and understanding the potential for smoke dispersion over fire-affected regions. The role of FRP as an indicator of air pollution highlights the potential use of FRP in assisting in management activities, operational planning, and emergency intervention during ongoing fires. 

Acknowledgments: This study is partially supported by the European Union’s Horizon 2020 research project FirEUrisk (Grant Agreement no. 101003890); and by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES on behalf of DHEFEUS -2022.09185.PTDC and the project FAIR- 2022.01660.PTDC).

How to cite: Durao, R., Alonso, C., Russo, A., and Gouveia, C.: The role of fire radiative power to estimate fire-related smoke pollution., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13237, https://doi.org/10.5194/egusphere-egu24-13237, 2024.

EGU24-13416 | ECS | Posters on site | BG1.1

Two decades of fire-induced albedo change and associated radiative effect over sub-Saharan Africa 

Michaela Flegrova and Helen Brindley

Fire is an important, widespread Earth-system process, influencing local ecosystems and climate around the globe. Over half of global burned area occurs in Africa, with over 10% of the continent affected by fire every year. Fire temporarily alters the surface properties, including surface albedo, causing long-lasting changes to the surface radiation budget.

We present the analysis of 20 years of fire and albedo data in Africa, using the MODIS product suite. We show that fire causes an average immediate albedo decrease, recovering exponentially with a time constant of several weeks. While the magnitude of albedo changes shows large spatial and temporal variations and a strong land cover type (LCT) dependency, exponential recovery is observed in the majority of LCTs. We show that fires cause long-term brightening, observing on average a small positive albedo change 10 months after a fire, but we find this is driven almost exclusively by slow vegetation recovery in the Kalahari region.

Using downward surface shortwave flux estimates we calculate the fire-induced surface radiative forcing (RF), peaking at 5±2 Wm−2 in the burn areas, albeit with a significantly smaller effect when averaged temporally and spatially. We find that the average long-term RF is negative because of the brightening observed.

Our temporal analysis does not indicate a decrease in overall fire-induced RF, despite a well-documented reduction in burning in Africa in the recent decades, suggesting that the RF of individual fires is increasing because of higher levels of downward surface shortwave flux. We hypothesise this may be due to lower levels of smoke aerosols in the atmosphere.

How to cite: Flegrova, M. and Brindley, H.: Two decades of fire-induced albedo change and associated radiative effect over sub-Saharan Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13416, https://doi.org/10.5194/egusphere-egu24-13416, 2024.

EGU24-14202 | Posters on site | BG1.1 | Highlight

Evaluation of global fire simulations in CMIP6 Earth system models 

Fang Li, Xiang Song, Sandy Harrison, and Zhongda Lin

       Fire is the primary form of terrestrial ecosystem disturbance globally and a critical Earth system process. So far, most Earth system models (ESMs) have incorporated fire modeling, with 19 out of them submitted fire simulations to the CMIP6. Transitioning from CMIP5 to CMIP6, much more models submitted fire simulations and the dominant fire scheme has evolved from GlobFIRM to the Li scheme. However, it remains unknown how well CMIP6 ESMs perform in fire simulations. This study provides the first comprehensive evaluation of CMIP6 fire simulations, through comparisons with multiple satellite-based datasets and the Reading Paleofire Database of global charcoal records (RPD).

        Our results show that most CMIP6 models simulate the global amounts of present-day burned area and fire carbon emissions within the range of satellite-based products, and reproduce observed major features of spatial pattern and seasonal cycle as well as the relationships of fires with precipitation and population density, except for models employing the GlobFIRM fire scheme. Additionally, most CMIP6 models can reproduce the response of interannual variability of tropical fires to ENSO, except for some models incorporating the SPITFIRE fire scheme. From 1850 to 2015, CMIP6 models generally agree with RPD, with some discrepancies in southern South America before 1920 and in temperate and eastern boreal North America, Europe, and boreal Asia after 1990. Compared with CMIP5, CMIP6 has solved the serious issues of CMIP5 which simulates the global burned area less than half of observations, fails to capture the high burned area fraction in Africa, and underestimates seasonal variability. CMIP6 fire carbon emissions simulations are also closer to RPD. However, CMIP6 models still fail to capture the present-day significant decline in observed global burned area and fire carbon emissions partly due to underestimation in anthropogenic fire suppression, and fail to reproduce the spring peak in NH mid-latitudes mainly due to an underestimation of crop fires. Based on our findings, we identify potential biases in fire and carbon projection based on CMIP6 models. We also provide suggestions for the fire scheme development, and bias correction methods when generating multi-source merged fire products.

How to cite: Li, F., Song, X., Harrison, S., and Lin, Z.: Evaluation of global fire simulations in CMIP6 Earth system models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14202, https://doi.org/10.5194/egusphere-egu24-14202, 2024.

EGU24-14446 | ECS | Posters on site | BG1.1

Wildland Fire Smoke and Emissions Tradeoff Decision Support 

Laurel Sindewald, Shawn Urbanski, Karin Riley, Christopher Eckerson, Alex Dye, and Rachel Houtmann

In 2023, 6,551 wildfires across Canada burned 184,961 km2 of the landscape—about 5% of Canadian forests—emitting nearly 480 megatonnes of carbon, with emissions leading to air quality warnings as far away as Washington DC, USA. In early June, the air quality index in New York City was over 400, and by mid-June, smoke plumes passed above Europe. As wildland fires of increasing severity occur with increasing frequency, driven by global climate change and decades of fire suppression, societies near and far from high-risk ecosystems face increased exposure to wildfire emissions that may have both acute and long-term health impacts. Prescribed fire interventions show promise for reducing the risk of large wildfires in fire-prone ecosystems, but implementing prescribed fire can be difficult, in part due to concerns about the potential health impacts of prescribed fire smoke on nearby communities. To provide decision support for land managers aiming to reduce wildfire risk with prescribed fire treatments, we will produce a geospatial database of daily pollutant emissions and fire intensity from simulations of prescribed and wildland fires over a 20-year period for: 1) a baseline scenario of no management actions, 2) one or more scenarios of prescribed fire locations and timing based on interaction with tribes and Okanogan-Wenatchee National Forest (OWNF) managers, and 3) scenarios of prescribed fire locations and timing based on fire paths, locations of highly valued resources, areas available and suitable for treatment, determined by the research team. We can accomplish this by iterating between FSim, the Large Fire Simulator, which stochastically simulates large wildfire ignition and spread across a LANDFIRE fuels landscape, and FFE-FVS, the Forest Vegetation Simulator with the Fire and Fuels Extension, which simulates post-fire regeneration, forest growth, management actions including prescribed fire, fuel dynamics, and fuel consumption and pollutant emissions from prescribed fires and wildfires. Because FSim takes a Monte Carlo approach, simulating fires over 10,000 or more hypothetical fire seasons comprised of daily weather sequences, we will be able to estimate the probability of each landscape pixel burning in a wildfire and the conditional probability of that pixel burning at different flame lengths, allowing us to provide emissions estimates within a risk-assessment framework for managers. The framework will allow land managers to quantify the likelihood that smoke impacts from near-term prescribed fire treatments will be offset by reductions in severe smoke events from future wildfires. Additionally, the smoke event geospatial datasets may provide input into atmospheric transport models which could be used to simulate regional to national scale smoke impacts. We will pilot the project in Okanogan-Wenatchee National Forest, Washington, USA, working with the forest’s managers to design fuel treatment scenarios that will yield realistic fire occurrence trajectories and emission estimates to inform near-term prescribed fire operations. As a U.S. Federal Bipartisan Infrastructure Law Research & Development “proof of concept” project, the Wildland Fire Smoke and Emissions Tradeoff Decision Support project will inform U.S. Forest Service management policy and strategy around the use of prescribed fire in other National Forests in the U.S.

How to cite: Sindewald, L., Urbanski, S., Riley, K., Eckerson, C., Dye, A., and Houtmann, R.: Wildland Fire Smoke and Emissions Tradeoff Decision Support, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14446, https://doi.org/10.5194/egusphere-egu24-14446, 2024.

EGU24-14748 | ECS | Posters virtual | BG1.1

Reconstructing human-fire-vegetation inter-relationships in a protected dry tropical forest, Mudumalai National Park, southern India 

Prabhakaran Ramya Bala, Nithin Kumar, Diptimayee Behera, Anoop Ambili, and Raman Sukumar

Tropical dry forests are recognized globally as the first frontier of human land-use change, due to multiple factors that make them amenable to human occupation, especially with the use of fire. However, in southern India, biodiversity ‘hotspots’ with human habitation are not uncommon with a long-term co-existence of humans in pristine environments. This points to the need for more accurate evidence-based (using charcoal, pollen, phytoliths) understanding of if, when and how land use and land cover changes impact regional vegetation-fire relationships. We reconstruct the environmental history for Mudumalai National Park, a fire-prone dry forest with >30% of the park subject to annual fires and a west-to-east rainfall-vegetation gradient. We examined a 150 cm sediment profile from an excavation in a seasonal wetland in the wettest part. The record spans 1200 years in time (bracketing radiocarbon dates) with very low macrocharcoal counts (mean - 4), with highest numbers in the surface and near-surface layers. Molecular fire proxies Polycyclic Aromatic Hydrocarbons (PAHs) were also found present - Phenanthrene (Phe), Anthracene (Ant), Fluoranthene (Fl), Pyrene (Py), Benzo[ghi]fluoranthene (Bghi), Benz[a]anthracene (BaA), Chrysene (Chr), Benzo(b)fluoranthene (BbF), Benzo(k)fluoranthene (BkF), Benzo[e]pyrene (BeP), Benzo[a]pyrene (BaP), and Perylene (Pry). Notably, Fl, Py, Bghi, BbF, BaA,and BeP constituted 90% of the total concentrations. Diagnostic ratios of PAHs for source determination pointed at a pyrogenic source consistently across all samples. Paleovegetation proxies n-alkanes (C14-C33) were analyzed and the average chain length (ACL) showed a transition towards higher chain lengths towards the surface indicating a change towards grass sources (C31, C33) in addition to woody biomass-derived compounds (C27, C29). Further analysis to characterize the human-fire-vegetation relationships is underway and to our knowledge, as the first report from a protected forest in India, our study offers critical insights for forest fire management in forested landscapes.

How to cite: Ramya Bala, P., Kumar, N., Behera, D., Ambili, A., and Sukumar, R.: Reconstructing human-fire-vegetation inter-relationships in a protected dry tropical forest, Mudumalai National Park, southern India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14748, https://doi.org/10.5194/egusphere-egu24-14748, 2024.

EGU24-14762 | Orals | BG1.1

Climate change has increased fire PM2.5 and its associated health burden 

Chaeyeon Park, Kiyoshi Takahashi, Shinichiro Fujimori, Thanapat Jansakoo, Chantelle Burton, Huilin Huang, Sian Kou-Giesbrecht, Christopher Reyer, Matthias Mengel, and Eleanor Burke

Climate change has influenced fire activities, altering the fire risk associated with air pollution and human health. However, the specific contribution of climate change to fire risks on air pollution and health burden has not yet been discovered. In this study, three fire-vegetation models were employed to simulate fire aerosol emissions under two simulations over the past six decades: an observation climate scenario and a counterfactual scenario where the long-term climate change trend is removed. Combining fire aerosol emissions with a chemical transport model and an avoidable mortality risk model, we calculated global fire PM2.5 and its associated mortality. By comparing the results under the two simulations, we demonstrated the climate change has increased the fire PM2.5 and its mortality. The findings indicated an increase in fire mortality over the six decades: 46,401 in the 1960s and 98,748 in the 2010s, with 3-8% attributed to climate change. Clear relationships were observed between the contribution of climate change to fire mortality and relative humidity or air temperature in some regions. This suggests that fire risks in these regions are sensitive to climate change and necessitate the development of adaptation strategies to mitigate risks in the future.  

How to cite: Park, C., Takahashi, K., Fujimori, S., Jansakoo, T., Burton, C., Huang, H., Kou-Giesbrecht, S., Reyer, C., Mengel, M., and Burke, E.: Climate change has increased fire PM2.5 and its associated health burden, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14762, https://doi.org/10.5194/egusphere-egu24-14762, 2024.

EGU24-14891 | Orals | BG1.1

Fire hazard trajectories under climate change and management scenarios 

Marcos Rodrigues, Pere Gelabert, Teresa Lamelas, Raúl Hoffrén, Juan de la Riva, Darío Domingo, Cristina Vega-García, Paloma Ibarra, Aitor Ameztegui, and Lluís Coll

In this work we showcase the in-progress results from the FirePATHS project (PID2020-116556RA-I00). The project aims to assess the evolution of fire danger under different emission and forest management scenarios through the explicit interaction of the climate-vegetation-fire system. For this purpose, a methodological framework combining different simulation models of the elements of this system is proposed. The core of the process lies in the modeling of vegetation dynamics at stand scale according to different trajectories of climatic evolution to characterize the state and typology of fuels and the subsequent simulation of potential fire behavior during the 21st century.

We analyzed a set of 114 Pinus halepensis plots, surveyed in the field during 2017;  68 plots burned during the summer of 1994 and 46 unburned control stands. We used the medfate model to simulate forest functioning and dynamics, which provides the necessary fuel model parameters to be entered into fire behavior models (Fuel Characteristics Classification System, implemented in medfate as well). The combination of these two approaches provides time-varying estimates of fire behavior metrics (e.g., flame length or rate of spread). The simulation was conducted under SSP climate scenarios (SSP 126, 245, 370 and 585) depicting different levels of climate warming, vegetation dynamics and, hence, fire danger. Likewise, we devised a set of forest management prescriptions aimed at reducing climate vulnerability of tree communities and reducing extreme wildfire potentials. A baseline scenario with no management was also assessed.

We observed very contrasting trajectories between burned and control stands, with the first leading to increasing fuel loads, except in SSP 585. Fire potentials depicted a significant increase in surface fire behavior, with adaptive and mitigation management being able to mitigate it to some extent.

How to cite: Rodrigues, M., Gelabert, P., Lamelas, T., Hoffrén, R., de la Riva, J., Domingo, D., Vega-García, C., Ibarra, P., Ameztegui, A., and Coll, L.: Fire hazard trajectories under climate change and management scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14891, https://doi.org/10.5194/egusphere-egu24-14891, 2024.

EGU24-15398 | Posters on site | BG1.1

Effects of recent increase in anomalous fires and smokes at high latitude regions on regional atmosphere 

Kwon-Ho Lee, Kwanchul Kim, and Dasom Lee

Spatiotemporal patterns and trends of atmospheric aerosols in high latitude region have been analyzed. Aerosol observation data from 2000-2022 acquired from the earth observing satellites including the Moderate Resolution Imaging Spectroradiometer (MODIS), the Ozone Monitoring Instrument (OMI), or geostationary satellites such as the Geostationary Korea Multi-Purpose Satellite-2A (GK-2A) . Results showed that Aerosol Optical Thickness (AOT) over the high latitude region has gradually decreased before 2016. However, AOT has increased significantly over the past 8 years. This increase was clearly shown in North America and North Asia, and was associated with an increase with fire activities. Smoke plumes originated from fire active fires transported eastward with meteorology, but occasionally moved toward the Arctic region. The occurrence of fires and the production and transport of aerosols will be a consequence or factor of the recent rapid climate change.

Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2019R1I1A3A01062804).

 

How to cite: Lee, K.-H., Kim, K., and Lee, D.: Effects of recent increase in anomalous fires and smokes at high latitude regions on regional atmosphere, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15398, https://doi.org/10.5194/egusphere-egu24-15398, 2024.

EGU24-15436 | ECS | Posters on site | BG1.1

Investigation of spatiotemporal variability in South American wildfire emissions and its impacts on CO concentrations 

Maria Paula Velasquez Garcia, Richard Pope, Steven Turnock, and Martyn Chipperfield

Wildfires in South America are a significant concern, causing high emissions and deforestation rates. They affect air quality, radiation balance, and sensitive ecosystems like the Amazon rainforest. Wildfires are expected to intensify with future land use and climate changes, making it crucial to enhance decision-making tools. Models of atmospheric composition, combined with wildfire emissions inventories, support decision-making by simulating events and their impacts on air quality. There are currently a range of wildfire/biomass burning emission inventories, which all use different approaches. This can lead to substantial differences in estimated emissions and thus impacts on atmospheric composition estimation.  This study aims to assess four inventories (2004-2022) in South America: Global Fire Emissions Database (GFED), Fire INventory from NCAR (FINN), Global Fire Assimilation System (GFAS) and Brazilian Biomass Burning Emission Model (3BEM-FRP), focussing on carbon monoxide (CO) given its relatively large emission and complementary satellite missions retrieving atmospheric CO. Our results analyse the temporal consistency in the emission seasonal cycles from the inventories and quantify the spatial agreement/differences between them. We also exploit the Measurements Of Pollution In The Troposphere (MOPITT) retrieved CO to assess the links between emission inventory tendencies with that of the atmospheric temporal evolution. Finally, we use an offline version of the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO) model, within the Joint UK Land Environment Simulator (JULES) framework to investigate simulated skill of emissions of CO against the observational constraints above as INFERNO is the fire model of choice in the UK Earth System Model (UKESM).

How to cite: Velasquez Garcia, M. P., Pope, R., Turnock, S., and Chipperfield, M.: Investigation of spatiotemporal variability in South American wildfire emissions and its impacts on CO concentrations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15436, https://doi.org/10.5194/egusphere-egu24-15436, 2024.

EGU24-15518 | Posters on site | BG1.1

Integrating stakeholders’ opinion in land management to build climate resilience in the context of fire risk 

Valentina Bacciu, José Costa Saura, Grazia Pellizzaro, Bachisio Arca, Pierpaolo Duce, Donatella Spano, and Costantino Sirca

The Mediterranean region, already a climate change hotspot, is experiencing milder winters, hotter and drier summers, and increased extreme weather events, leading to longer fire seasons and increasing fire impacts. The socio-economic consequences of wildfires are significant, including the loss of human lives, infrastructure, and economic activity. Additionally, wildfires contribute significantly to climate change, accounting for up to 20% of global greenhouse gas emissions annually. Climate change is expected to worsen these conditions in the near future.

Given these circumstances, it is necessary to accelerate the transition towards the implementation of integrated and holistic fire management approaches aligned with future hazards. In the framework of The HUT project (The Human-Tech Nexus - Building a Safe Haven to cope with Climate Extremes), financed by the Horizon Europe program, the "Ogliastra-DEM8" case study (located in Sardinia, Italy) is aimed at responding to this necessity.

In particular, the main objective of The HUT is to mitigate the effects of climate-related events, by integrating and leveraging best practices and successful multi-disciplinary experiences and focusing on the prevention and preparedness phases of the disaster risk management cycle. In this context, the specific aim of the "Ogliastra-DEM8" case study is to provide the scientific/knowledge base needed to help policymakers and decision-makers defining adaptation and mitigation strategies that are effective in reducing fire impacts and associated costs in the short to medium-term under a changing climate. Towards this end, innovative tools (e.g., fire simulators, catastrophe insurance products, nature-based solutions) and stakeholder engagement, including participatory methods, will be developed.

This work presents the first phase of the work aimed at evaluating enablers and barriers to multi-hazard/systemic risk reduction by (i) reviewing the literature from other projects based in Sardinia, (ii) mapping and engaging stakeholders during an initial round of workshops, and (iii) debating fire-smart land management and adaptation options. Preliminary results indicate key barriers such as stakeholder conflicts, administrative silos, lack of political will, and funding complexities. All these elements contributed to varying degrees to the lack of a comprehensive approach towards integrated and sustainable management of the entire territory. On the other hand, enablers include stakeholder engagement, evidence of performance and co-benefits, and community awareness.

Further work will integrate stakeholder opinions into fire exposure and risk mapping under climate change conditions, with the goal of selecting and co-designing with them which fire-smart land management and adaptation options can be applied and where to protect the most important and vulnerable communities and ecosystems.

How to cite: Bacciu, V., Costa Saura, J., Pellizzaro, G., Arca, B., Duce, P., Spano, D., and Sirca, C.: Integrating stakeholders’ opinion in land management to build climate resilience in the context of fire risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15518, https://doi.org/10.5194/egusphere-egu24-15518, 2024.

EGU24-16087 | Posters on site | BG1.1

Assessing post-fire soil erosion and water contamination risk in European fire-affected catchmentswith WEPPcloud-EU WATAR watershed model 

Jonay Neris, Carmen Sánchez-García, Marta Basso, Roger Lew, Anurag Srivastava, Mariana Dobre, Pete Robichaud, Erin Brooks, Cristina Santin, and Stefan Doerr

Soil and ash are key sources of sediment, carbon, nitrogen, and associated pollutant movement following a wildfire. Their transport into freshwater systems can pose severe environmental and socio-economic implications including impacts to water quality and aquatic ecosystems, disruptions to drinking water supply and high remediation costs, as well as the depletion of carbon and nutrients from areas affected by erosion. We assessed the risk of soil erosion, ash and contaminant transport, and water contamination in three burned European catchments in Central Europe (Germany and the Czech Republic), Portugal and Spain using the European Water Erosion Prediction Project cloud interface with the Wildfire Ash Transport and Risk (WEPPcloud-EU WATAR) watershed model. The watersheds varied in size from 100 to 22,000 ha and represent distinct climatic conditions. To our knowledge, this is the first application of this model in European post-fire scenarios. We calibrated and validated the model using catchment runoff data (where available) and nearby streamflow data from both pre- and post-fire periods when runoff data was unavailable. Additionally, we used sediment transport data (where available) along with ash contaminant content data to calibrate and validate erosion and ash transport rates. Model performance was assessed using statistics like Nash-Sutcliffe Efficiency (NSE), coefficient of determination (R2) and percent bias (PBias (%)). Once the model was calibrated and validated, we estimated the post-fire risk of soil erosion, ash transport, and ash pollutant concentrations in the affected areas. The simulations provided the probabilities of occurrence and return periods for severe erosion events, as well as for ash and contaminant transport events. Based on these simulations, we identified hillslopes that were the main sources of runoff, erosion, ash and contaminant transport. This information is important to managers who can prioritize the application of mitigation treatments and prevention plans. Given the projected increase in fire weather in many regions in Europe, our findings suggest that the WEPPcloud-EU WATAR model is an increasingly useful tool in predicting and mitigating soil erosion and water contamination impacts of European burnt catchments.

How to cite: Neris, J., Sánchez-García, C., Basso, M., Lew, R., Srivastava, A., Dobre, M., Robichaud, P., Brooks, E., Santin, C., and Doerr, S.: Assessing post-fire soil erosion and water contamination risk in European fire-affected catchmentswith WEPPcloud-EU WATAR watershed model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16087, https://doi.org/10.5194/egusphere-egu24-16087, 2024.

EGU24-16263 | ECS | Orals | BG1.1

Fire, permafrost, and people: Late Holocene fire regimes and their impacts on lake systems in Yakutia, Siberia 

Ramesh Glückler, Elisabeth Dietze, Stefan Kruse, Andrei Andreev, Boris K. Biskaborn, Evgenii S. Zakharov, Izabella Baisheva, Amelie Stieg, Shiro Tsuyuzaki, Kathleen Stoof-Leichsenring, Luidmila A. Pestryakova, and Ulrike Herzschuh

The Republic of Sakha (Yakutia), the coldest permanently inhabited region on Earth, is characterized by unique ecological relationships between larch forest, permafrost, and wildfires. Together, they can stabilize each other, preserving the larch-dominated biome. Abundant lakes have important cultural and subsistence-related functions and are dynamically connected to warming permafrost processes. Recently intensified wildfire seasons, however, raised questions regarding the causes and impacts of long-term (centennial to millennial) fire regime changes. Despite recent progress, eastern Siberia is still sparsely covered by reconstructions of long-term fire history. This also limits any evaluation of fire regime impacts on permafrost lake development and catchment erosion. Past studies have shown the benefit of combining paleoecological fire reconstructions with geochemical data to shed light on fire regime changes and their impacts on lake catchments, as well as traces of potential human land use.

We present nine new records of Late Holocene wildfire activity, based on macroscopic charcoal in lake sediments (including information on charcoal particle sizes, morphologies, and length to width ratios), accompanied by sediment geochemistry data from high-resolution XRF core scanning. The studied lakes are located in the Lena-Amga interfluve of the Central Yakutian Lowlands, the Verkhoyansk Mountains, and the Oymyakon Highlands. The new data cover both thermokarst and glacial lakes, and a range from remote to rural settings and low to high elevations. Charcoal concentration in the lowland lakes is on average three times as high as in the highland lakes. Contrary to our hypothesis, charcoal concentration in most lakes is negatively correlated to many XRF-derived lithogenic elements indicating detrital input from catchment erosion (e.g., Ti, K). Reminiscent of earlier findings [1], multiple lowland sites share a signal of sharply decreasing biomass burning around 1300 CE. This coincides with the initial settlement of the Sakha people and increased catchment erosion. The new fire reconstructions allow for the evaluation of potential human impacts on past fire regime changes in Yakutia, while improving the region’s representation in global synthesis studies.

[1]  Glückler R. et al. (2021): Wildfire history of the boreal forest of south-western Yakutia (Siberia) over the last two millennia documented by a lake-sediment charcoal record. Biogeosciences 18 (13): 4185–4209. https://doi.org/10.5194/bg-18-4185-2021.

How to cite: Glückler, R., Dietze, E., Kruse, S., Andreev, A., Biskaborn, B. K., Zakharov, E. S., Baisheva, I., Stieg, A., Tsuyuzaki, S., Stoof-Leichsenring, K., Pestryakova, L. A., and Herzschuh, U.: Fire, permafrost, and people: Late Holocene fire regimes and their impacts on lake systems in Yakutia, Siberia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16263, https://doi.org/10.5194/egusphere-egu24-16263, 2024.

EGU24-16293 | ECS | Posters on site | BG1.1 | Highlight

Global atmospheric impacts of aerosols emitted from the 2023 Canadian wildfires 

Iulian-Alin Rosu, Matt Kasoar, Eirini Boletti, Mark Parrington, and Apostolos Voulgarakis

Wildfires are a central but relatively unexplored component of the Earth system. Severe wildfire events can lead to intense destruction of both nature and property, as was the case during the anomalously intense 2023 Canadian wildfire event. Last year, approximately 5% of the total forest area of Canada burned [1] [2], which is the highest wildfire damage Canada has ever sustained [1].

Conditions pertaining to climate change and modifications in atmospheric conditions are considered to be responsible for this record series of wildfires [3]. Increasing mean temperatures and decreasing humidity in the region has exacerbated wildfire risk. Carbon emissions from the 2023 Canadian wildfires have been the highest on record [4], including large amounts of carbonaceous aerosol which can exert substantial atmospheric radiative forcing. Also, Canadian fire emissions contributed around 20% of global emissions from vegetation fires. Thus, beyond the well-known health risks of wildfire emission compounds, it is important to also study the consequences of these emissions on large-scale atmospheric composition and meteorological behavior.

In this work, the global and regional atmospheric impact of the previously mentioned series of wildfires is investigated using the EC-Earth3 and UKESM1 earth system models. Simulated atmospheric conditions with and without the wildfire emissions, as provided by the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS), are compared through atmospheric modelling in the context of the Canadian 2023 fire season. The investigation reveals the connections between the emissions produced by this series of wildfires and atmospheric phenomena of importance, such as large-scale circulation, temperature patterns, and precipitation.

[1] "Fire Statistics". Canadian Interagency Forest Fire Centre. Retrieved January 4, 2024.

[2] The State of Canada’s Forests: Annual Report 2022. Canadian Minister of Natural Resources.

[3] Barnes, Clair, et al. "Climate change more than doubled the likelihood of extreme fire weather conditions in eastern Canada." (2023).

[4] “Copernicus: Emissions from Canadian wildfires the highest on record – smoke plume reaches Europe”. Atmosphere Monitoring Service, Copernicus. Retrieved January 4, 2024.

How to cite: Rosu, I.-A., Kasoar, M., Boletti, E., Parrington, M., and Voulgarakis, A.: Global atmospheric impacts of aerosols emitted from the 2023 Canadian wildfires, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16293, https://doi.org/10.5194/egusphere-egu24-16293, 2024.

EGU24-16592 | ECS | Posters on site | BG1.1 | Highlight

Exploring the role of post-fire erosion as a carbon sink mechanism 

Antonio Girona-García, Diana Vieira, Stefan Doerr, and Cristina Santín

Wildfires release approximately 2.1 Pg C to the atmosphere each year. The impact of wildfires on the carbon cycle, however, extends well beyond direct emissions, involving complex interactions among various source and sink processes. One such process, the enhanced post-fire soil organic carbon (SOC) erosion, remains unquantified as a potential C sink mechanism. Post-fire SOC erosion functions as a C sink when the subsequent burial and stabilization of eroded C offsite, coupled with the recovery of net primary production and SOC content onsite, outweigh the C losses to the atmosphere during post-fire transport of SOC. In this work, we synthesize published data on post-fire SOC erosion and evaluate its overall potential to act as C sink. In addition, we estimate its magnitude at continental scale following the 2017 wildfire season in Europe, showing that SOC erosion can indeed play a quantitatively significant role in the overall C balance of wildfires. 

How to cite: Girona-García, A., Vieira, D., Doerr, S., and Santín, C.: Exploring the role of post-fire erosion as a carbon sink mechanism, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16592, https://doi.org/10.5194/egusphere-egu24-16592, 2024.

EGU24-16676 | ECS | Orals | BG1.1

Study of greenhouse gases emitted by biomass burnings with a decade of infrared observation of CO2 and CH4 by IASI 

Victor Bon, Cyril Crevoisier, and Virginie Capelle

Biomass burnings are one of the major sources of greenhouse gases in the atmosphere, impacting air quality, public health, climate, ecosystem dynamics, and land-atmosphere exchanges. In the tropics, South America represents about 10 % of the tropical emissions and present a large diversity of biomes and fire conditions. Over the last two decades, satellite observations have provided crucial information, notably via active fires detection, Fire Radiative Power (FRP) estimates and burned area (BA) measurements from imagers such as Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). Global inventories (e.g., GFED, GFAS, FEER, QFED, etc.) heavily rely on these satellite-derived indicators to estimate emissions from biomass burnings. However, emissions derived from these various models can significantly differ among them and large uncertainties persist regarding fire emissions, their variability, and their links with several drivers (e.g., type of combustion, vegetation, transport, etc.).

In this context, we propose a novel approach to estimate emissions from biomass burnings by directly using greenhouse gas concentrations in the atmosphere derived from spaceborne observations. Leveraging a decade of observations from the Infrared Atmospheric Sounding Radiometer (IASI) on-board the three Metop satellites, we have access to an unprecedented spatial coverage of global mid-tropospheric CO2 and CH4 concentrations twice a day (9:30 AM/PM LT). From this dataset, we developed the Daily Tropospheric Excess (DTE) method, which is based on the use of the diurnal cycle of biomass burnings and the vertical transport of their emissions to link the observed diurnal variations of the mid-tropospheric CO2 and CH4 concentrations to burnings activities.

We will demonstrate the relevance of the DTE for analyzing CO2 and CH4 emissions from various type of burnings, biomes, and human activities across South America. This will be achieved by comparing DTE with existing indices of fire characteristics such as FRP and BA from MODIS/SUOMI satellite observations, alongside global emissions databases like GFED and GFAS. Globally, we will show that their spatial distribution, seasonal intensity, and interannual variability are consistent with each other, even if some differences have been found and will be discussed. Additionally, geostationary data from GOES-R, MSG, and Himawari-8 satellites will be used to analyze the impact of observation times on the differences observed between the various datasets and the DTE.

How to cite: Bon, V., Crevoisier, C., and Capelle, V.: Study of greenhouse gases emitted by biomass burnings with a decade of infrared observation of CO2 and CH4 by IASI, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16676, https://doi.org/10.5194/egusphere-egu24-16676, 2024.

EGU24-17593 | Orals | BG1.1

Effect of combustion conditions on aerosol particle emissions from savanna and grassland fires 

Ville Vakkari, Angela Buchholz, Liqing Hao, Mika Ihalainen, Kerneels Jaars, Kajar Köster, Viet Le, Pasi Miettinen, Arya Mukherjee, Saara Peltokorpi, Iida Pullinen, Stefan J. Siebert, Olli Sippula, Markus Somero, Lejish Vettikkat, Annele Virtanen, Pasi Yli-Pirilä, Arttu Ylisirniö, and Pieter G. van Zyl

Fire is an integral part of savanna and grassland biomes and globally approximately half of landscape fire emissions originate from savannas and grasslands. Emissions of trace gases and aerosol particles from landscape fires are characterised by emission factors (EFs), which denote the amount of emitted substance per mass of combusted biomass. EFs vary depending on both the biomass that is consumed in the fire and the combustion characteristics of the fire, i.e. the ratio of flaming to smouldering combustion. However, emission inventories tend to use only one average EF for each biome.

Here, we use a set of 27 laboratory experiments to characterise the effect of combustion characteristics on submicron aerosol EFs from savanna and grassland biomass acquired from South Africa as well as boreal forest floor samples from Finland. Combustion experiments were carried out at the ILMARI facility in Kuopio, Finland from May to June 2022 under an open stack mimicking natural burning and dilution. Sample was injected into a 29 m3 environmental chamber for ageing studies. Chemical and physical properties of both fresh and aged smoke were observed with a host of instruments including e.g. AMS, FIGAERO-CIMS, VOCUS, SP2 and SMPS. The ratio of flaming to smouldering combustion was characterised by modified combustion efficiency (MCE), i.e. CO2/(CO2+CO).

The increase of organic aerosol EF with increasing smouldering fraction (i.e. decreasing MCE) was very similar for both the grassland and savanna combustion experiments. Surprisingly, also the boreal forest floor EFs closely follow the same trend, where smouldering-dominated combustion EFs are more than 10 times higher than EFs for flaming combustion. We observed also that the submicron aerosol particle size distribution shifts towards larger sized particles with increasing smouldering fraction. Furthermore, both the number and the mass of the size distribution cannot be fully characterised with a single log-normal size distribution, which needs to be considered when converting mass emissions into number size distribution in simulations.

How to cite: Vakkari, V., Buchholz, A., Hao, L., Ihalainen, M., Jaars, K., Köster, K., Le, V., Miettinen, P., Mukherjee, A., Peltokorpi, S., Pullinen, I., Siebert, S. J., Sippula, O., Somero, M., Vettikkat, L., Virtanen, A., Yli-Pirilä, P., Ylisirniö, A., and van Zyl, P. G.: Effect of combustion conditions on aerosol particle emissions from savanna and grassland fires, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17593, https://doi.org/10.5194/egusphere-egu24-17593, 2024.

EGU24-17935 | Posters on site | BG1.1

The FLARE Workshop perspective on Fire’s Role in the Carbon Cycle 

Chantelle Burton, Stephen Plummer, Noah Liguori-Bills, Morgane Perron, Douglas Kelley, Miriam Morrill, Boris Vannière, Joanne Hall, Stijn Hantson, Matthias Forkel, Christoph Völker, Kebonye Dintwe, Cristina Santin, Jessie Thoreson, Benjamin Poulter, Matthew Jones, and Douglas Hamilton

Fire substantially influences and modulates the global carbon cycle through numerous processes, interactions, and feedbacks. Fires are also strongly intertwined with human activities; people act both as drivers of change through ignitions, suppression, land-cover change, prescribed burning, and climate change, and are affected in return by changes in fire regimes. 

Despite fire’s many complex interactions throughout the Earth System, it is often viewed only as a destructive process, and one that solely acts as a source of atmospheric carbon. In terms of fire’s carbon budget, the release of carbon only represents the very initial stages of the process, missing the drivers and complex ways in which fire shapes plant species evolution and ecosystem trajectories, nutrient cycling and redistribution, carbon allocation, deposition and sequestration over different spatiotemporal scales. Therefore, there is a clear need to fully understand the role of fire in the Earth System holistically. However, different aspects of fire’s role in the carbon cycle are often studied by different communities and disciplines, hindering this much-needed integrated understanding. 

Through the Fire Learning AcRoss the Earth Systems (FLARE) workshop (September 2023) we brought together fire scientists across multiple disciplines to facilitate transdisciplinary discussion. We propose that the visualization of fire processes as carbon colours across the Earth System can be a thematic tool for unifying disciplines. It explores all aspects of fire and smoke implications for living systems and opens questions about fire’s role in carbon budgets, afforestation, and climate change and related mitigation strategies. We also identified several scientific challenges for the community where, by working together, we can address some fundamental questions for fire’s role in the carbon cycle, such as: What is the contribution of fire and of individual fire events to the global carbon cycle? How do changes in fire regimes influence ecosystem stability across different timescales? How do future changes in fire regimes influence global climate, allowable emissions and carbon budgets, and temperature mitigation ambitions? In this presentation, we explore how we can bring a more interdisciplinary approach to fire science to address these fundamental questions.

How to cite: Burton, C., Plummer, S., Liguori-Bills, N., Perron, M., Kelley, D., Morrill, M., Vannière, B., Hall, J., Hantson, S., Forkel, M., Völker, C., Dintwe, K., Santin, C., Thoreson, J., Poulter, B., Jones, M., and Hamilton, D.: The FLARE Workshop perspective on Fire’s Role in the Carbon Cycle, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17935, https://doi.org/10.5194/egusphere-egu24-17935, 2024.

EGU24-18169 | ECS | Posters on site | BG1.1 | Highlight

What makes a fire grow extremely large? 

Rebecca Scholten, Tirtha Banerjee, Yang Chen, Ajinkya Desai, Tianjia Liu, Douglas Morton, Sander Veraverbeke, and James Randerson

Wildfires are an important disturbance in global ecosystems and are a critical driver of trends in the land carbon budget. Fire is an extreme phenomenon, with the largest burned area often occurring during extreme fire seasons generating large fires. Days with fire conditions conducive to fire ignition and spread are increasing in a warming climate in many regions of the world, contributing to increases in fire occurrence and annual burned area. However, the climate, fuel, and weather conditions that lead to extremely large fires in different biomes are poorly understood.

Here, we explore the temporal evolution of extremely large fires in temperate and boreal regions using new satellite-derived fire event tracking datasets optimized to match higher resolution time series of fire progression from aircraft and other sources. We aimed to understand the specific environmental conditions required for the development of a large fire. Our analysis revealed a disproportionate impact of multiple fire ignitions in creating large fires through merging. Our findings suggest that the largest fires in both biomes may be commonly created through multiple fires growing together. We hypothesize that a combination of physical and anthropogenic factors may accelerate merging, making these fires extremely difficult to contain and more robust to environmental controls regulating extinction. In our analysis, we use the Fire Events Database, the Arctic-boreal Fire Atlas, and GOFER, which enable attribution of ignition sources. Our analysis may contribute to an improved understanding of the influence of large-scale lightning storms in creating extremely large and destructive fire events.

How to cite: Scholten, R., Banerjee, T., Chen, Y., Desai, A., Liu, T., Morton, D., Veraverbeke, S., and Randerson, J.: What makes a fire grow extremely large?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18169, https://doi.org/10.5194/egusphere-egu24-18169, 2024.

EGU24-18811 | Posters virtual | BG1.1

Taking advantage of satellite data, large datasets of fire records and cloud computing for modelling potential fire severity useful for better assess fire risk 

José Maria Costa Saura, Valentina Bacciu, Donatella Spano, and Costantino Sirca

Fire risk analyses, usually focused on fire hazard (i.e. the probability of fire occurrence), often neglect an important issue such as the sensitivity/vulnerability (i.e., the degree of potential damage, sensus IPCC) of different locations within the area of interest.  Such lack of consideration comes from past data processing constrains that limited fire severity studies to analyse only single or few fire events. Nowadays, online data repositories and processing platforms (e.g. Google Earth Engine) allow to easily integrate and process a vast amount of data from multiple sources that might prove useful for developing tailored tools for decision making. Here, we present an example for predicting potential fire severity based on the analysis of more than 1 000 fire events from southern France and western Italy which integrates climate, topographical and remote sensing variables. Furthermore, we assessed if the model “used” the explanatory variables under a meaningful biophysical sense.   Using the random forest algorithm and the relativized difference of the Normalized Burn Ratio (rdNBR) as proxy of fire severity, we reach to explain up to 75% of the variability in the data with most of the variables showing a clear and interpretable effect. Our results suggests that this type of approach might prove useful for better address fire risk assessments.

How to cite: Costa Saura, J. M., Bacciu, V., Spano, D., and Sirca, C.: Taking advantage of satellite data, large datasets of fire records and cloud computing for modelling potential fire severity useful for better assess fire risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18811, https://doi.org/10.5194/egusphere-egu24-18811, 2024.

EGU24-18894 | ECS | Posters virtual | BG1.1

Mapping open burning of agricultural residues from Earth Observations 

Eduardo Oliveira, João Gata, Diogo Lopes, Leonardo Disperati, Carla Gama, and Bárbara Silva

Agricultural residue burning is a common practice in various regions of the world, which may have several environmental impacts, including on air quality, and the potential for triggering wildfires. In Portugal, this practice is particularly prevalent during the wet season, spanning from October to April. It involves open field burning of pruning residues and extensive burning to clear shrubbery, creating pastures for livestock. This research, conducted within the framework of the PRUNING project - Mapping open burning of agricultural residues from Earth Observations and modelling of air quality impacts- aims to explore the potential for detecting such events through satellite remote sensing.

The primary focus of this study is to assess the limitations of satellite remote sensing detection, with the overarching aim of integrating these findings into a systematic monitoring framework for open burning of agricultural residues. Additionally, the study aims to predict pollutant emissions and assess their impacts on air quality, providing valuable insights for environmental management and sustainable agricultural practices.

To achieve this goal, an in-depth analysis of known burning events was conducted using infrared thermal sensors. Multiple products, including Fire Radiative Power and fire masks from various sensors (e.g., MODIS, VIIRS, and Sentinel 3), were employed to characterize these known open field burning events. The results of this work allow verifying the tradeoffs effects associated with spatial, spectral, and temporal resolutions for each sensor, elucidating their impacts on the precision and accuracy of event detections. In parallel, this study evaluated the accuracy of the MINDED-FBA method in characterizing these known events. This automatic detection method, allows incorporating data from higher spatial resolution sensors (e.g., Sentinel-1, Sentinel-2, Landsat), for determining the extent of burned areas through multiple multispectral indices. In this context, the MINDED-FBA method may also be used to validate thermal anomalies detection products. Finally, the results of this work have also been compared to a national level register database of open burning, provided by the ICNF (Institute for Nature Conservation and Forests).

How to cite: Oliveira, E., Gata, J., Lopes, D., Disperati, L., Gama, C., and Silva, B.: Mapping open burning of agricultural residues from Earth Observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18894, https://doi.org/10.5194/egusphere-egu24-18894, 2024.

EGU24-18941 | Orals | BG1.1

Arctic peat fire emissions estimated from satellite observations of fire radiative power 

Johannes Kaiser, Kerstin Stebel, Philipp Schneider, and Vincent Huijnen

Exceptional wildfire activity occurred in the Arctic during the last years due to pronounced heat episodes. The Arctic has an abundance of peat and soils with organic content. When peat is burnt, the carbon flux into the atmosphere is virtually irreversible and this process may become of global significance for Arctic fires. Furthermore, smoke from smoldering fires (below-ground, peat) has a different chemical composition than smoke from flaming fires. It is therefore important to distinguish peat fires and above-ground, potentially flaming fires in fire emission estimation.

The operational Copernicus Atmosphere Monitoring Service (CAMS) is tracking global fire activity and emissions with its Global Fire Assimilation System (GFAS) as a near-real time service. GFAS uses satellite-based observations of fire radiative power (FRP), which links observed thermal radiation directly to the biomass combustion rate, i.e. amount of biomass burnt and corresponding emission of carbon into the atmosphere, based on satellite retrievals from MODIS and VIIRS. 

Here, we present a partitioning of the Arctic fire activity represented in GFAS into smoldering below-ground and potentially flaming above-ground fires using two approaches: (1) masking the fire activity maps with published peat maps and (2) analysing the observed diurnal cycles of the fire activity at all locations. We subsequently apply adapted emission factors and compare the resulting emission estimates to the standard values produced by CAMS for carbon, carbon monoxide, nitrogen dioxide and aerosols.

Furthermore, we may confront the fire emission estimates with independent atmospheric smoke observations by feeding them into IFS-COMPO, which is used to generate hindcasts of atmospheric composition, including tropospheric columns of CO and NO2. This allows an evaluation of the estimated trace gas emissions, by comparing the model simulations to satellite retrievals of carbon monoxide and nitrogen dioxide. It thus provides an independent assessment of the estimated fire emissions, and, in turn, carbon flux.

How to cite: Kaiser, J., Stebel, K., Schneider, P., and Huijnen, V.: Arctic peat fire emissions estimated from satellite observations of fire radiative power, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18941, https://doi.org/10.5194/egusphere-egu24-18941, 2024.

EGU24-18977 | Orals | BG1.1 | Highlight

Global seasonality of small-scale livelihood fire 

Matthew Kasoar, Cathy Smith, Ol Perkins, James Millington, and Jayalaxshmi Mistry

Landscape fires are increasingly represented in dynamic global vegetation models to understand impacts on carbon emissions and climate. Deliberate human fire use and management influence landscape fire characteristics, varying in space and time depending on social, economic, and ecological factors. For example, fire is used variously in rural livelihoods involving e.g., agriculture, hunting, gathering, and for other cultural practices, often depending on the time of year. Yet existing global fire models typically represent human fire use as a constant function of gridded datasets such as population density or gross domestic product.

Recently, initiatives have begun to draw together available data on global fire use from across multiple disciplines and disparate sources into coherent databases. We draw on information from one of these databases, the Livelihood Fire Database (LIFE), which includes case studies in 587 locations worldwide, to assess the availability of data on seasonality of anthropogenic fires associated with small-scale rural livelihoods. By defining seasonal cycles relative to the local variation of precipitation and evapotranspiration at each case study location, we look for patterns in the spatiotemporal nature of anthropogenic fires associated with different fire-use purposes - such as clearing vegetation for agriculture, maintaining pasture for livestock, or driving game when hunting - and consider the potential for this analysis to inform fire models.

For many fire types, especially those related to hunting, gathering, human wellbeing, and social signalling, there are limited quantitative data available, but it is possible to draw qualitative insights from case studies. Where quantitative data are available, we find some correspondence between fire seasonality and the intended fire-use purpose, suggesting that distinguishing between distinct fire-use purposes could improve the representation of human fire use in fire models, and consequently the seasonal cycle of fire emissions. Case studies demonstrate that environmental and social conditions drive variation in fire use for the same purpose, reiterating that a wide range of factors influence human behaviour and that assumptions of uniform drivers of anthropogenic fire may be misleading. Many of the fires now being revealed in global burned area data by new fine-scale remote sensing products are likely human-set; continued collection, collation, and analyses of data on human fire use globally is important to ensure appropriate anthropogenic representation in fire models.

How to cite: Kasoar, M., Smith, C., Perkins, O., Millington, J., and Mistry, J.: Global seasonality of small-scale livelihood fire, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18977, https://doi.org/10.5194/egusphere-egu24-18977, 2024.

EGU24-19223 | ECS | Posters virtual | BG1.1

Monitoring wildfires from satellite, integration in Copernicus services and characterizing atmospheric impacts from the regional to the global scales 

Dominika Leskow-Czyżewska, Stephan Bojinski, Julien Chimot, Andrea Meraner, Mark Parrington, and Federico Fierli

Satellite-borne observations offer the possibility to monitor wildfires and their impact worldwide. In addition, satellite products are increasingly used in early warning and forecasting systems for fire management. Europe is implementing a long-term and reliable observational programme and, within this frame, EUMETSAT, the European meteorological satellite operator, provides numerous observational products ranging from near-real-time wildfire identification (e.g. fire radiative power) to atmospheric impacts (e.g. major pollutants and smoke). 

Our presentation will focus on the satellite data value chain, e.g. the integration in the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS). To do that, we will firstly present datasets addressing wildfires (e.g. Fire Radiative Power, atmospheric composition, and smoke) currently generated at EUMETSAT and its Satellite Applications Facility (SAF). We will also introduce upcoming (based on the Flexible Combined Imager on-board the Meteosat Third Generation) and future products (Sentinel-4 and 5), with an example of potential joint use for a past intense fire case in the Mediterranean (Greece, August 2023).  

We will then show the entire value chain, including how the data is used in the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS), with an example on the recent intense and anomalous fire season in Canada (spring to summer 2023). This will show how distinct phases of wildfires management – from early warnings up to the impacts on yearly emissions – can be monitored with the synergy of satellite data and Copernicus forecast and analysis. Finally, we will touch also on the user support activities within EUMETSAT in this area. 

How to cite: Leskow-Czyżewska, D., Bojinski, S., Chimot, J., Meraner, A., Parrington, M., and Fierli, F.: Monitoring wildfires from satellite, integration in Copernicus services and characterizing atmospheric impacts from the regional to the global scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19223, https://doi.org/10.5194/egusphere-egu24-19223, 2024.

EGU24-19330 | Orals | BG1.1

Burned Area Mapping with Sentinel-2 based on reflectance modelling and deep learning – preliminary global calibration and validation 

Marc Padilla, Ruben Ramo, Sergio Sierra, Bernardo Mota, Roselyne Lacaze, and Kevin Tansey

Current global burned area products are available at coarse spatial resolutions (300-500 m), what leads to large amounts of errors, hindering an accurate understanding of fire-related processes. This study proposes a global calibration method for a sensor-independent burned area algorithm, previously used with 300 m Sentinel-3 Synergy data, and here implemented with 20 m Sentinel-2 MSI imagery. A binomial model that combines reflectance-based burned area predictions constrained by spatio-temporal densities derived from VIIRS active fires is calibrated using a reference dataset generated from Landsat imagery at a sample of 34 units across the globe. Preliminary leave-one-out cross-validation analyses show promisingly high accuracies (Dice of coefficient of 84.8%, commission error ratio of 13.2%, omission error ratio of 17.1% and relative bias of -4.5%), especially taking into account the mismatch of acquisition dates between reference and algorithm input data, what introduces apparent errors on the validation results.

How to cite: Padilla, M., Ramo, R., Sierra, S., Mota, B., Lacaze, R., and Tansey, K.: Burned Area Mapping with Sentinel-2 based on reflectance modelling and deep learning – preliminary global calibration and validation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19330, https://doi.org/10.5194/egusphere-egu24-19330, 2024.

EGU24-19716 | ECS | Posters on site | BG1.1

"Fire impacts in the Cerrado: Integrating LiDAR and field data to monitor vegetation structure and post-fire recovery." 

Manoela Machado, Wesley da Cruz, Maria Antonia Carniello, Emily Sturdivant, Francisco Navarro-Rosales, Marcia Macedo, Wayne Walker, and Imma Oliveras Menor

Fire is a natural disturbance capable of altering plant distributions and community assemblages, influencing species evolution through the selection of traits and strategies, and affecting biogeochemical cycles. This powerful tool of landscape transformation can negatively impact even a fire-dependent ecosystem when natural fire regimes are altered. In recent times, interactions between human activities in the Cerrado (e.g., deforestation and intentional fires used to clear land), and a hotter and drier climate (due to climate change), have altered natural fire regimes causing more frequent and intense fire events, negatively impacting biodiversity, human health, and the regional climate. These fire-disturbed areas are widespread and highly vulnerable to future degradation from compounding disturbances, but they still harbour valuable biodiversity and carbon stocks that deserve protection and restoration. Monitoring the impacts of fire disturbance on vegetation structure and the potential pathways of recovery is critical to understand and protect resilient ecosystems under a rapidly changing climate. Robust monitoring requires the integration of modelled and field-based data tools and techniques. Field inventories alone are insufficient to capture the spatiotemporal variability of impacts of fire on native vegetation and should be coupled with remotely sensed data, among which, LiDAR (light detection and ranging) is unparalleled in characterising 3-D vegetation structure. Thus, the combination of LiDAR and forest inventory data is ideally suited for scaling the impacts of fire on forest vegetation and associated carbon stocks. In this study, we are assessing key metrics of vegetation structure derived from a combination of LiDAR and field data collected at the Experimental Station Serra das Araras, Mato Grosso state, Brazil. This field site comprises Cerrado vegetation that has been subject to three experimental fire treatments: every year, every two years, and every three years beginning in 2017, as well as fire suppression for over three decades. We are investigating whether key vegetation structural metrics can capture different fire treatments and identify spatial patterns of disturbance. We are also assessing if these patterns are different when comparing LiDAR data collected with a handheld scanner versus an airborne drone. This study aims to refine our methods and improve our understanding of vegetation structure responses across a gradient of fire disturbance regimes and potential post-fire recovery trajectories, which are key not only for ecological studies but also for emerging carbon markets – one of several mechanisms aimed at achieving climate change mitigation, conservation, and sustainable development outcomes. We hope to improve the process of carbon stock mapping in disturbed ecosystems and use the outputs to drive scenarios modelling at larger scales, providing a more comprehensive assessment of what future Cerrado carbon dynamics might look like under a range of possible disturbance/recovery dynamics.

How to cite: Machado, M., da Cruz, W., Carniello, M. A., Sturdivant, E., Navarro-Rosales, F., Macedo, M., Walker, W., and Oliveras Menor, I.: "Fire impacts in the Cerrado: Integrating LiDAR and field data to monitor vegetation structure and post-fire recovery.", EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19716, https://doi.org/10.5194/egusphere-egu24-19716, 2024.

EGU24-20564 | ECS | Orals | BG1.1 | Highlight

Future global wildfire regimes under high and low climate mitigation efforts  

Olivia Haas, Colin Prentice, and Sandy P. Harrison

There is growing concern over future trajectories of burning on Earth. One the one hand, some regions have seen the emergence of large and novel wildfires, whilst satellite observations continue to show declining burnt area globally, most notably in the tropics. Quantifying the response of global wildfire regimes to future changes in especially challenging given that wildfires are driven by climate, vegetation, and human activities, and that these different factors may have contrasting and opposing effects.

Using global empirical models of burnt area, fire size and fire intensity we explore the trajectory of future fire regimes under high and low climate change mitigation efforts. The models are driven by lightning ignitions, climate, vegetation properties, topography, and human factors. Making use of a set of sensitivity analysis, we show a global shift in wildfire patterns by the end of the 21st century even with warming kept below 1.5°. Burning will generally be reduced in tropical regions but larger and more intense wildfires will occur in extra-tropical regions. Under low mitigation, increases in burnt area worldwide overwhelm the human-driven decline, with up to a 60% increase in burnt area by the end of the century. However, fire size and intensity will be increasingly limited by dryness and vegetation fragmentation.

These results suggest that even under high climate change mitigation, fire management strategies must urgently be revised as current fire-suppression policies will no longer be effective in much of the world. Regional-level fire management, led by local stakeholders, should be encouraged. Wildfire risk and management must also be incorporated into mitigation scenarios that rely on extending forest area if these mitigation scenarios want to remain realistic.

How to cite: Haas, O., Prentice, C., and Harrison, S. P.: Future global wildfire regimes under high and low climate mitigation efforts , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20564, https://doi.org/10.5194/egusphere-egu24-20564, 2024.

EGU24-774 | ECS | Orals | BG8.7

Health impacts of long-range transported air pollution in South America: compound events, cascading hazards and the Pantanal 2020 fire crisis. 

Djacinto Monteiro dos Santos, Aline M. de Oliveira, Ediclê S. F. Duarte, Julia A. Rodrigues, Lucas S. Menezes, Ronaldo Albuquerque, Fabio de O. Roque, Leonardo F. Peres, Judith J. Hoelzemann, and Renata Libonati

Human-induced climate changes have increased the frequency of simultaneous hot–dry events. In 2020, the occurrence of compound droughts and heat waves (CDHW) conditions in the Pantanal (the largest continuous tropical wetland located in central-western Brazil) exacerbated fire risk, leading to unusual amounts of burned area (BA). Despite the well-documented local impacts on the ecosystem and economy, besides regional effects that included black sky episodes in South and Southeastern Brazil, the number of studies investigating the long-range impacts associated with Pantanal fires is still limited, compared to Amazon and Cerrado biomes. Here, we analyzed the long-range transport of smoke from the Pantanal during the 2020 mega fires to the São Paulo state (SPS) and the cascading impacts on air quality and human health statewide, integrating observational, satellite-based, and reanalysis data and atmospheric dispersion models. Three main episodes of transport of smoke-related to peaks of fire events in the Pantanal were identified through air mass trajectories simulated with HYSPLIT, leading to a substantial enhancement in PM2.5 levels over SPS, surpassing World Health Organization guidelines by over 70%-600% in different regions of the state. The EURAD-modeled PM2.5 concentrations during the fire episode aligned with those observed from air quality monitoring stations. Model results highlighted the key role of the South American Low-Level Jet (SALLJ) in the redistribution of smoke plumes in South America, as previously observed in central Brazil and the Amazon basin. Two smoke-induced air pollution episodes coincided with heat waves observed in the SPS, contributing to worsening air quality and amplifying health risks. Thus, the period between October 1st and October 14th was marked by excess mortality of 2,150 (2,095 - 2,206) over 14 days, representing a 21% (17-24%) mortality increase. The impact on mortality was higher in the northwestern SPS, regions more affected by the transported smoke. Our findings reinforce the need to implement public policies associated with fire control and management in the Pantanal, considering the country's large-scale interactions among different regions and biomes, besides adaptation strategies to concurrent and cascading extreme events expected to increase under any future global warming scenarios.

How to cite: Monteiro dos Santos, D., M. de Oliveira, A., S. F. Duarte, E., A. Rodrigues, J., S. Menezes, L., Albuquerque, R., de O. Roque, F., F. Peres, L., J. Hoelzemann, J., and Libonati, R.: Health impacts of long-range transported air pollution in South America: compound events, cascading hazards and the Pantanal 2020 fire crisis., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-774, https://doi.org/10.5194/egusphere-egu24-774, 2024.

EGU24-1092 | ECS | Posters on site | BG8.7

Temporal patterns of burned area in the Brazilian biomes 

Thaís Pereira de Medeiros, Débora Joana Dutra, Poliana Domingos Ferro, Henrique Alves Leão, Deila da Silva Magalhães, Celso H. L. Silva-Junior, Swanni Tatiana Alvarado Romero, Maria Isabel Sobral Escada, Luiz Eduardo Oliveira e Cruz de Aragão, and Liana Oighenstein Anderson

Fire, a dual-edged phenomenon, holds the potential for both harm and benefit to individuals and ecosystems contingent on its location, timing, and manner of occurrence. The expansion of human civilization has positioned it as the main source of fire ignitions on the Earth, fundamentally altering natural fire regimes. Ecosystems exhibit different responses and susceptibilities to fire, with impacts varying based on specific ecosystem characteristics. Across the  Brazilian landscapes, distinct biomes such as Cerrado, Pampa, and Pantanal are classified as fire-dependent. In contrast, forest-dominated biomes like the Atlantic Forest and Amazon are deemed fire-sensitive, while the Caatinga, despite limited research on its historical fire relationship, is tentatively categorized as fire-independent.

Brazil has witnessed unprecedented wildfires in recent decades, with natural fire regimes undergoing modification due to human activities, frequently tied to land-use and its changes practices or exacerbated by climate extremes associated with global warming. In this context, our goal was to characterize the temporal patterns of fires in Brazilian biomes, using a burned area dataset obtained from the Global Fire Atlas (2003-2018). This dataset tracks the daily dynamics of individual fires, and our analysis focused on the burned area extent.

In Brazil, over the time series (2003-2018), the peak years regarding the extent of burned areas were 2010, 2007 and 2012, totalling 392,057 km², 382,163 km², and 249,596 km², respectively. 2010 and 2007 presented an increase of ~240% above the mean, while 2012 an increase of ~150% above the mean.

Regarding the intra-annual fire patterns, observations revealed that Fire-sensitive biomes, in the Amazon and Atlantic Forest, the fire season was well-defined in two months, specifically August and September, representing, on average, 55% (4,058 km²) and 40% (1,027 km²) of the total burned area, respectively. In the Fire-independent biome, Caatinga, the fire season was prominent in September and October, constituting 67% (436 km²) of the total burned area. In relation to Fire-dependent biomes, Cerrado and Pantanal exhibited a concentrated fire season in August and September, accounting for 57% (10,283 km²) in Cerrado and 68% (900 km²) in Pantanal. Finally, Pampa's fire season displayed a heterogeneous configuration over time, making it impossible to extract a specific pattern of fire season.

In general, August and September of 2010 were the months that presented the greatest extent of burned area in the time series, in almost all biomes, except Pantanal and Pampa. The occurrence of fires, often caused by human actions, also can be associated with mega-droughts and ocean circulations such as the El Niño-Southern Oscillation (ENSO) event. The widespread occurrence of fires in 2010 can be attributed to the severe and unique drought that occurred as a consequence of the ENSO, affecting mainly Cerrado and Amazon.

In summary, the intensification of extreme events and the increase of fire source ignitions, even in fire-dependent environments, is affecting the Brazilian ecosystems, which presents distincts behavior and resilience in relation to fire events. Therefore, understanding the period of fire season is essential to develop command-and-control approaches and to fire prevention.

How to cite: Pereira de Medeiros, T., Joana Dutra, D., Domingos Ferro, P., Alves Leão, H., da Silva Magalhães, D., H. L. Silva-Junior, C., Tatiana Alvarado Romero, S., Sobral Escada, M. I., Oliveira e Cruz de Aragão, L. E., and Oighenstein Anderson, L.: Temporal patterns of burned area in the Brazilian biomes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1092, https://doi.org/10.5194/egusphere-egu24-1092, 2024.

EGU24-1158 | ECS | Posters on site | BG8.7

Estimation of aboveground biomass recovery through chronosequence in forests degraded by fire in the Legal Amazon 

Henrique Leão, Debora Dutra, Thaís Medeiros, Celso Silva-Junior, Swanni Alvarado, Vinicius Peripato, Marcus Silveira, Ana Larissa De Freitas, Luiz Aragão, and Liana Anderson

The Amazon biome is under constant pressure from deforestation and fire occurrence, one of the most active forest degradation processes. The advance of deforestation leads to the increase of forest edge effects. Thus, agricultural management based on slash-and-burn practices can lead to fire escaping into native vegetation, leading to forest degradation, impacting biodiversity, forest structure, carbon stocks and emissions. 

Maranhão state, located in northeastern Brazil and part of the Legal Amazon, encompasses a  transition from the Amazon rainforest to Cerrado. Attention to this region is urgent due to growing pressures related to fire and deforestation mainly within Protected Areas (PA), threatening the conservation and functioning of this unique ecosystem. An up-to-date spatial explicit diagnostic of disturbances such as fire, deforestation and edge effects is important for formulating protective measures for these areas.

Methodologies for quantifying Greenhouse Gas (GHG) emissions and removals, analyzing trends, attributing sources and sinks are key to support the establishment and reporting of national GHG inventories. Brazil has legal tools, like the National Climate Change Policy, aligned with Paris Agreement goals, emphasizing the Reduction of Emissions from Deforestation and Degradation (REDD+). Quantifying carbon losses from degradation is challenging due to uncertainties in estimating degraded forest areas and disturbance impacts. About 61% of carbon removals occur in protected native vegetation, yet estimates may be overestimated due to unaccounted forest degradation processes, like burn emissions from non-deforested native vegetation, untracked in National Inventories. These uncertainties, however, can be reduced by combining field measurements with an ever-increasing range of datasets and remote sensing methods. This study aims to enhance understanding of post-fire biomass growth dynamics and recovery potential, emphasizing the pivotal role of carbon removal by vegetation.

Our analysis covers the heterogeneous spatial and temporal patterns of vegetation growth in fire-degraded forests, where we combined a satellite dataset tracking fire disturbances with the fusion of 3 products widely used in other studies (MCD64A1, Fire_CCI and Mapbiomas Collection 2, fusion product with 30 m resolution), with a global above-ground biomass (AGB) product (Biomass_CCI, 100 m resolution) in a space-for-time substitution approach to model accumulated AGB as a function of the Years Since the Last Fire Disturbance (YSLF). 

Over 20 years of recovery (2001 - 2020), regeneration rates in areas degraded by forest fires ranged from 2 to 12% per year, totalling up to 80% biomass recovery, compared to old forests that were never burned. Degraded forests are most severely disturbed after the first YSLF, where AGB is reduced to 58% of the median AGB of old-growth forests (113.86 Mg/ha), resulting in a 42% loss of biomass. In 2016, fires breached Maranhão's protected areas for the first time in two decades. Even after a single fire event, the areas did not fully recover in terms of biomass, indicating a potential reduction in carbon storage capacity.

Extreme fire events amplify these occurrences, affecting protected areas and decreasing the carbon storage potential of forests. Urgent measures are needed to protect and restore these areas, recognizing the lasting impacts of forest fires on biodiversity, forest structure and carbon emissions.

How to cite: Leão, H., Dutra, D., Medeiros, T., Silva-Junior, C., Alvarado, S., Peripato, V., Silveira, M., De Freitas, A. L., Aragão, L., and Anderson, L.: Estimation of aboveground biomass recovery through chronosequence in forests degraded by fire in the Legal Amazon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1158, https://doi.org/10.5194/egusphere-egu24-1158, 2024.

EGU24-3376 | ECS | Orals | BG8.7

Inferring extreme fire theory from land surface models: from imperfect proxies to predictive power. 

Simon Bowring, Wei Li, Florent Mouillot, Thais Rosan, and Philippe Ciais

Wildfire cause, effect and severity are driven by interactions between an array of climatic, biotic, and anthropogenic factors at multiple spatio-temporal scales.  While a broad theory of fire causation has been unveiled by a vast body of in vivo, in vitro and satellite studies, this complexity and wildfire’s destructive nature have precluded large-scale experimentation of remaining unresolved drivers and mechanics. This hampers theoretical advances for fire prediction at scale, acutely so where global climate and anthropogenic change amplifies hitherto minor or only-hypothesised processes.  Here, we show that where process representation is task-sufficient and appropriate, global land surface models can step in to infer and resolve these theoretical gaps.  This is possible precisely because these models currently fail to reproduce observed burned area and/or fire intensity patterns in a substantive number of space-time and biome-level configurations, despite reasonable performance at global and annual scales.  These in turn provide clues towards the primary theoretical deficiencies in contemporary fire ecology, as well as a platform for resolving them.

 

We present two studies that achieve this, which suggest that appropriate construction of model protocols enables hypothesis testing that can reject the null where simulation outcomes simultaneously meet both alternative hypothesis criteria and expected simulation improvements with respect to observed patterns, paving the way for improved theoretical understanding and predictive capacity.

 

The first study constructs a simplified yet powerful proxy for anthropogenic land fragmentation’s effects on fire activity at global scale.  Including this complex interaction of increased human ignition potential, fire size constriction, wind infiltration and land surface desiccation drives fire decreases in temperate and cold areas of moderate to high population density, while causing substantial increases in tropical areas subject to high levels of fragmentation.  In aggregate, including fragmentation effects decreased simulated global burned area by -6% and increased it by +5% (-1% net), while 7% of grid cells’ fire activity was affected by >25%.  These results were consistent with both global and regional (e.g. Brazil, Indonesia) -scale statistical and fire-fragmentation relationships.  

The second study provides a solution for representing the critical bifurcation of fire phenomena and severity between boreal Eurasia and North America, previously unachievable in global land surface models. Our solution results in wide-ranging improvements to the simulated space-time patterns of boreal burned area, fire intensity and their divergence.  The initial theoretical gap was addressed by hypothesizing that a previously described (Rogers et al., 2015) vegetation -and hence fire -ecology split between the two continents could be fundamentally defined by a top-down (climatic) signal, rather than the bottom-up (vegetation) driver identified by that study, which cascaded into ground/crown fire probability, fire spread and combustion dynamics. 

Process-based theoretical inference, in combination with high resolution machine learning techniques, may pave the way for future advances in global-scale fire ecology.

How to cite: Bowring, S., Li, W., Mouillot, F., Rosan, T., and Ciais, P.: Inferring extreme fire theory from land surface models: from imperfect proxies to predictive power., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3376, https://doi.org/10.5194/egusphere-egu24-3376, 2024.

EGU24-5700 | ECS | Posters on site | BG8.7

Optimizing Fire Preparedness: A Forward-looking Analysis for 2030 in Boca do Acre Region, Brazilian Amazon 

Débora Dutra, Marcelo Santos Junior, Igor Ferreira, Beatriz Cabral, Philip Fearnside, Paulo Graça, Aurora Yanai, Ricardo Dalagnol, Daniel Braga, Chris Jones, Chantelle Burton, Richard Betts, Henrique Leão, Thaís Medeiros, Guilherme Mataveli, Luiz Aragão, and Liana Anderson

The Amazon Rainforest, crucial for climate regulation, carbon and water cycles, and biodiversity preservation, faces escalating threats from heightened forest degradation, including disturbances from fire and logging. In 2020, Brazil was responsible for a concerning 70% of the active fire hotspots detected in the Amazon, signaling a notable 60% increase compared to 2019. This surge has pushed the region into an extreme fire situation. Urgent and effective interventions are imperative to mitigate these extremes, ensuring the preservation of the Amazon and global climate stability. The study focuses on the Boca do Acre region in the southwest Amazon, one of the most recent hotspots of deforestation and forest degradation in the Amazon. We project the suitability of fire for 2030, following the timeframe set by the United Nations for the implementation of actions aimed at creating a better world for all peoples and nations through the Agenda 2030. Using the MAXENT algorithm within the R software, we conducted a detailed analysis exclusively within the non-forest land-use class on a 5 km x 5 km grid. Burned area data from products Fire CCI (250m), MapBiomas Fire (30m), and MODIS MCD64 (500m) were used to study fire occurrence across the study area. The chosen baseline year is 2014, representing the last year of historical data before the influence of different Shared Socioeconomic Pathways (SSPs) on IPCC models (1-2.6 and 3-7.0). The statistic involves the use of specifically selected variables, determined by their performance in correlation tests and principal component analysis. These variables encompass the percentage of forested areas, agriculture, pasture, and a 1000 m buffer along the region's roads. Additionally, factors such as the percentage of conservation unit occupancy, indigenous lands, and medium-sized properties (400-1000 ha) in the Rural Environmental Registry (CAR), along with precipitation values during dry months, are taken into account. Model validation incorporates AUC analysis, where the model must exhibit performance greater than 0.7, background analysis with the same curve behavior, false positive rate (FPR), accuracy evaluation, and sensitivity analysis. Following this process, we project the feasibility of fire for 2030. Results consistently demonstrate high performance, with AUC values surpassing 0.7 and pixel-to-pixel accuracy ranging from 60% to 90%, lower FRP values, and higher sensitivity values. Projected results indicate an increased susceptibility to fires that spread in the region, especially under less sustainable scenarios, emphasizing the urgency of preventive measures before 2030. Projections reveal an advancement in fire suitability, particularly in the SSP 3-7.0 scenario, with a significant increase in non-forest areas. However, as the scenario worsens, areas prone to fires that spread decrease due to the advancement of agricultural and pasture areas, underscoring the need for more sustainable practices. In conclusion, this study holds promise as a management tool for decision-makers, offering valuable insights for the development of mitigation and adaptation measures to climate change in the Boca do Acre region. These contributions are essential for preserving this vital ecosystem, highlighting the importance of implementing effective strategies.

How to cite: Dutra, D., Santos Junior, M., Ferreira, I., Cabral, B., Fearnside, P., Graça, P., Yanai, A., Dalagnol, R., Braga, D., Jones, C., Burton, C., Betts, R., Leão, H., Medeiros, T., Mataveli, G., Aragão, L., and Anderson, L.: Optimizing Fire Preparedness: A Forward-looking Analysis for 2030 in Boca do Acre Region, Brazilian Amazon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5700, https://doi.org/10.5194/egusphere-egu24-5700, 2024.

EGU24-6369 | Posters on site | BG8.7

Prediction of forest degradation as a subsidy for mitigating actions to preventing fires and wildfires in a new Amazonian frontier 

Liana Anderson, Débora Dutra, Chris Jones, Guilherme Mataveli, Igor Ferreira, Henrique Leão, Beatriz Cabral, Philip Fearnside, Paulo Graça, Aurora Yanai, Celso Silva Junior, Thaís Medeiros, Ricardo Dalagnol, Daniel Braga, Vinícius Peripato, Chantelle Burton, Richard Betts, and Luiz Aragão

Anthropogenic disturbances stand as the primary driver of degradation in the remaining Amazon forests, posing a significant threat to their future. Notable among these disturbances are edge effects, timber extraction, fire, extreme droughts and temperatures, which have been intensified by human-induced climate change. A pilot study aiming to integrate forest fire occurrence, timber extraction and climate change scenarios was developed for a new deforestation frontier in southwestern Amazonia. We integrated a series of remote sensing fire products, spatialized land tenure information, selective logging mapping techniques and Global Climate Models (GCMs) simulated projections of three SSPs (SSP climate forcing scenarios) for 2015–2100 period. The results showed that the increased deforestation trend occurred between 2003 and 2019 predominantly on public lands, following the implementation of the new forest code.  This surge contributed to a spike in fires, escalating from 66% to 84% in 2019. Over the period from 2007 and 2019, 2.4% of the primary forest was logged. By 2022, precipitation values aligned closely with SSP 5-8.5, and temperature values neared SSP 3-7.0. Projections for 2100 indicated an alarming increase of 5.19 ºC in overall temperature and a reduction of 55 mm in annual precipitation compared to 2003 baseline. The results indicate that the study region is already heading towards a less sustainable future. Logging activities, as well as agricultural production, are threatened by both increase in economic losses by fires and temperatures, and rainfall reduction. Implementing mitigation measures, such as fire-free land management, traceability controls for all wood production from logged forests, and addressing issues of land tenure and regulation are pivotal in steering the current development pathway towards a more sustainable pathway.

How to cite: Anderson, L., Dutra, D., Jones, C., Mataveli, G., Ferreira, I., Leão, H., Cabral, B., Fearnside, P., Graça, P., Yanai, A., Silva Junior, C., Medeiros, T., Dalagnol, R., Braga, D., Peripato, V., Burton, C., Betts, R., and Aragão, L.: Prediction of forest degradation as a subsidy for mitigating actions to preventing fires and wildfires in a new Amazonian frontier, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6369, https://doi.org/10.5194/egusphere-egu24-6369, 2024.

EGU24-8126 | ECS | Orals | BG8.7

Overlapping US-Australia fire seasons reduce the window of opportunity for firefighting cooperation 

Andreia F. S. Ribeiro, Doug Richardson, Yann Quilcaille, Fulden Batibeniz, Andrew Pitman, and Jakob Zscheischler

Wildfires are a growing global challenge. In addition to becoming more widespread and intense due to climate change, the fire seasons in many regions are becoming longer. The lengthening of fire seasons reduces the window of opportunity for preparedness (e.g. prescribed burning of dry fuels before fire season onset) and increases the likelihood of spatially compounding fire risks due to overlapping fire weather seasons. These increased risks demand efficient global cooperation in sharing firefighting resources (e.g. helicopters, planes, firefighters), and of major concern, is how well-established international arrangements may be compromised or disrupted in the near future.

Here we investigate increasing fire season lengths across two distanced fire-prone regions with typically distinct fire seasons and a long-term collaboration in sharing firefighting resources, Eastern Australia (EAU) and Western North America (WNA). We aim to test the hypothesis that spatially compounding fire weather events occur due to overlapping fire weather seasons, based on the Canadian Fire Weather Index (FWI). To robustly characterize the potential overlap, we make use of CMIP6 single model initial-condition large ensembles (SMILEs) for historical and future periods, and the ERA5 reanalysis. We define Fire Weather Days (FWD) as when the FWI exceeds a climatological threshold specific to each region, and we then estimate the total number of overlapping FWD per year for different time periods.

We show that these distanced regions are becoming more likely to experience periods of overlapping FWD, which can compromise the human response in terms of firefighting. Most of the overlap occurs during boreal Autumn months, coinciding with the end of the fire season in WNA and the beginning of the fire season in EAU. Correlations between the number of overlapping FWD and the length of the regional fire season suggest that the main driver of the overlapping is the increasing early start of the fire season in EAU, rather than the late offset of the fire season in WNA. Additionally, we find that overlapping FWD is expected to increase in the future in a warming climate. As fire seasons overlap, the existing international collaborations will be increasingly constrained, and the window of opportunity for firefighting will shorten. 

How to cite: Ribeiro, A. F. S., Richardson, D., Quilcaille, Y., Batibeniz, F., Pitman, A., and Zscheischler, J.: Overlapping US-Australia fire seasons reduce the window of opportunity for firefighting cooperation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8126, https://doi.org/10.5194/egusphere-egu24-8126, 2024.

EGU24-8559 | Posters on site | BG8.7

Effects of wildfires on water quantity and quality in southern Chile 

Alejandra Stehr, Nicole Vyhmeister, Vicente Saenger, Pablo Villegas, and Efrain Duarte

Wildfires are a global and catastrophic phenomenon, generating major impacts on soil characteristics, erosion, water flow and water quality at the watershed scale, among others. Such effects depend on the severity of the fire, a metric that depends on the intensity of the fire and the nature of the vegetation that is burning. During the last 60 years the average annual area burned in Chile due to wildfires has been approximately 65,000 hectares per year. This figure has been greatly surpassed in the last 5 years, averaging approximately 155,000 hectares per year. Although worldwide, especially in the United States and Europe, there is evidence of impacts on the quantity and quality of water from wildfires, this is not the case in Chile. Given the above, the objective of this work is to analyze the effects on water quantity and quality in burned and unburned watersheds in the Andes and Coastal Cordillera in southern Chile. Two native forest basins and two exotic plantation basins were studied, one burned and one unburned in each class. The native forest basins correspond to the Allipén River and Quepe River basins, located in the Andes Mountain range, while the exotic plantation basins are found in the Carampangue River basin, located in the Coastal Mountain range. The results indicate differences in nutrients (phosphorus and nitrogen) present in the water between burned and unburned watersheds during the rainy season.

How to cite: Stehr, A., Vyhmeister, N., Saenger, V., Villegas, P., and Duarte, E.: Effects of wildfires on water quantity and quality in southern Chile, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8559, https://doi.org/10.5194/egusphere-egu24-8559, 2024.

EGU24-9387 | Orals | BG8.7

An Operational Global Probability-of-Fire (PoF) Forecast : Can we predict extreme events? 

Joe McNorton and Francesca Di Giuseppe

Wildfires have widespread effects on local ecosystems, communities, air quality, and global atmospheric conditions. Accurate wildfire forecasts can be used by local communities and agencies to manage and respond to wildfires effectively. As such, it is essential these predictions are not only accurate but are accessible in real-time and provide sufficient advanced notice to ensure successful actions can be taken. Existing systems typically use fire danger indices to predict landscape flammability, based on meteorological forecasts alone, often using little or no direct information on land surface or vegetation state. Here, we use a vegetation characteristic model, weather forecasts and a data-driven machine learning approach to construct a global daily ~9 km resolution Probability of Fire (PoF) model operating at multiple lead times. The PoF model outperforms existing indices, providing accurate forecasts of fire activity up to 10 days in advance, and in some cases up to 30 days and has been deployed operationally at the European Centre for Medium-Range Weather Forecasts (ECMWF). The model can also be used to investigate historical shifts in regional fire patterns. Furthermore, the underlying data driven approach allows PoF to be used for fire attribution, isolating key variables for specific fire events or for looking at the relationships between variables and fire occurrence. The 2023 Canadian wildfire season is used as a test case to assess model performance at predicting extreme wildfire events.

How to cite: McNorton, J. and Di Giuseppe, F.: An Operational Global Probability-of-Fire (PoF) Forecast : Can we predict extreme events?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9387, https://doi.org/10.5194/egusphere-egu24-9387, 2024.

EGU24-10020 | ECS | Orals | BG8.7

A globally-consistent modelling approach to assess socio-economic wildfire risks 

Carmen B. Steinmann, Jonathan Koh, Samuel Lüthi, Samuel Gübeli, Tanja N. Dallafior, Benoît P. Guillod, Chahan M. Kropf, Stijn Hantson, David N. Bresch, and Dahyann Araya

Wildfires cause extensive damage to physical assets exposed to them. So far, assessing the risk of these events remains an understudied area of global disaster risk assessment. Probabilistic risk estimates covering the range and likelihood of devastating events are crucial for various applications such as prioritising adaptation measures and determining insurance pricing. Quantifying tail risks such as a one-in-a-hundred-year impact has important implications for disaster risk management, including the pricing of insurance. However, short observational time series render modelling efforts indispensable for risk assessments on a global scale.
In parallel, increasing data availability allows for the use of machine learning techniques to predict wildfire behaviour. In this context, an open-source wildfire risk model based on globally available data would facilitate the accessibility of such analysis to stakeholders from both the public and private sector. Here, we present such a machine learning model that estimates wildfire probabilities and we integrate these within a global socio-economic risk framework. 

We determine burning probabilities based on MODIS burnt area, a set of predictors and a country-and-biome specific machine learning model. The chosen predictors include weather variables, land use covariates and population density. We enhance the model with spatial and temporal feature-engineered covariates, such as the count of neighbouring burnt cells and time since the last fire in each cell. The model employs XGBoost, a tree boosting system, tailored for each country and biome. The model generates stochastic, counterfactual historic wildfire seasons by leveraging the inherent randomness in its predictions, further influenced by temporal and spatial covariates.

Secondly, we compute socio-economic impacts as the combination of the newly developed wildfire hazard, an exposure representing physical assets; and a vulnerability that was calibrated on historic fire damage data. We compute wildfire risks by combining the resulting impacts with their respective probabilities. This renders a globally consistent modelling approach of wildfire risk to physical assets. Our model's stochastic representation of wildfire hazards enables the analysis of extreme events with return periods extending beyond available observational data, enhancing our understanding of potential high-impact scenarios.  

How to cite: Steinmann, C. B., Koh, J., Lüthi, S., Gübeli, S., Dallafior, T. N., Guillod, B. P., Kropf, C. M., Hantson, S., Bresch, D. N., and Araya, D.: A globally-consistent modelling approach to assess socio-economic wildfire risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10020, https://doi.org/10.5194/egusphere-egu24-10020, 2024.

Wildfires are phenomena that affect large areas of land worldwide, causing substantial economic and human losses every year. Ecuador is a country with important geology and archaeological heritage, recognized by several authors historically and awarded by UNESCO in 2019. On the other hand, agriculture widely distributed all along the country constitutes one of the major economic activities that supports the gross domestic product. Both resources are susceptible to the manifestation of forest fires, becoming a major problem in the country.  

In 2023, the months of August and September showed the highest recurrence of fires at national level. One of the most damaged regions was Imbabura UNESCO Global Geopark that covers the total surface of Imbabura province (4712,37 Km2) here the fires burned about 1600 hectares of land. Fires in Ecuador are usually caused by a combination of factors including inadequate human practices, highly flammable dry vegetation, and meteorological conditions. Thus, this research focuses on the estimation of the severity of damage during forest fires, also considering the forest-urban interface it was possible to estimate the impact to settlements in the geopark. The processing of satellite data was performed by applying the algorithm in Google Earth Engine (GEE), from the ImageCollection package that contains information on burned surface to Sentinel-2 satellite images based on key indices, such as Normalized Difference Vegetation Index (NDVI), Normalized Burned Area Ratio (NBR) and shortwave infrared (SWIR) (UN-SPIDER).   

The geopark embraces 12 geosites, including the “Yachay Archaeological Sites” located on the grounds of the City of Knowledge Yachay, in Urcuquí, being one of the most important cultural heritage, which importance stems from its inclusion of bone remains, malacological, ceramic, lithic, and monumental structures. It holds particular significance for the descendants of the Caranqui population that inhabits the entire area of influence; therefore, preserving it for future generations is crucial. The monuments (Tolas, Pucarás, and Pirámides), distributed aleatory in the geosite, were highly affected. Sentinel 2 has a resolution of 30 m, and some monuments are less than 5m, for this reason it was necessary to use high-resolution images captured with unmanned aerial equipment to evaluate the impact. The final analysis reveals that, for the geosite "Yachay Archaeological Sites," 127 hectares were affected, with a considerable harm in several levels that 29 out of the 37 monumental structures, this represents the 78% of the total structures were potentially damaged.  

Key words: Severity, Forest Fires, GEE, Geosites, Imbabura Geopark, Archaeological Sites Yachay, Tolas  

Reference:  

UN-SPIDER Knowledge Portal. Paso a paso: Mapeo de la severidad de incendios forestales en Google Earth Engine https://www.un-spider.org/es/asesoria/practicas-recomendadas/practica- recomendada-mapeo-gravedad-quemaduras/paso-a-paso/google-earth-engine

How to cite: Vásquez, S., Carrión, B., Torres, R., and Vázquez, Y.: Forest fire severity estimation in 2023 in UNESCO Global Geopark Imbabura with the impact review at the archaeological heritage in the geosite “Yachay Archaeological Sites”   , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12036, https://doi.org/10.5194/egusphere-egu24-12036, 2024.

EGU24-12209 | Orals | BG8.7

Monitoring wildfire smoke plumes and clouds with portable weather radar to nowcast hazards associated with extreme wildfires 

Adrien Guyot, Kathryn Turner, Jordan Brook, Joshua Soderholm, Nicholas McCarthy, Alain Protat, and Hamish McGowan

Extreme and megafires demonstrate a significant interplay between fire dynamics and the surrounding atmosphere, resulting in erratic fire behavior, rapid fire spread, long-range transport of burning embers, and pyro-convective activity that leads to the formation of pyrocumulus and/or pyrocumulonimbus clouds.

These fire-induced clouds play a crucial role, generating strong updrafts and downdrafts, causing plume collapse, and carrying particles like firebrands downwind while also lifting smoke particles into the stratosphere. Monitoring these clouds poses challenges; satellites offer limited resolution and passive sensing, while ground-based weather radars provide the best means to track their entire lifecycle, especially portable systems deployed at proximity of the fire and offering better resolution and accuracy. These systems are capable of identifying specific features and phenomena, such as rotors and vorticity, pyrometeors and the formation of condensation.

Our study presents observations from portable weather radars captured from various Australian wildfires. We introduce machine learning-based techniques to process radar data, aiming to provide actionable intelligence on wildfire-related hazards.

How to cite: Guyot, A., Turner, K., Brook, J., Soderholm, J., McCarthy, N., Protat, A., and McGowan, H.: Monitoring wildfire smoke plumes and clouds with portable weather radar to nowcast hazards associated with extreme wildfires, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12209, https://doi.org/10.5194/egusphere-egu24-12209, 2024.

Natural ecosystems are fundamental to biodiversity and reaching net-zero, but are at increasing risk from disturbance events like drought and fire. Across many landscapes, fire responds non-linearly to drought and temperature changes, obscuring evolving fire risk until critical thresholds are breached. In particular, in the absence of natural or human-made barriers, growing fire perimeters result in non-linear increases of daily burned area over the lifetime of any individual fire. Fuel conditions and structure further determine the velocity at which fires can spread across the landscape. Predicting fire extremes remains notoriously difficult due to these non-linear responses and complex interactions of natural and managed landscapes, short observational time-series from satellites, and rapid regional trends in climate and human activity. 

 

One potential new avenue of exploring fire extremes is through the use of novel object-based fire inventories, like the Global Fire Atlas or Amazon Dashboard. Here we use these novel approaches to assess several recently unfolding fire extremes, with special attention to South America. We find that fire extremes can both unfold within a single season or drought year, as well as over the course of multiple years with continued heightened fire activity across a particular landscape. Further characterization of fire types, based on unique characteristics of each fire object, helps better separate climate and land-use driven variability and change in fire extremes. Our results provide novel insights in the underlying mechanisms driving exceptional fire activity, which can inform estimates of future change and land management strategies.

How to cite: Andela, N.: New insights on global fire extremes from object-based fire inventories, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12734, https://doi.org/10.5194/egusphere-egu24-12734, 2024.

EGU24-12769 | Posters virtual | BG8.7

Impact of Canadian Wildfires 2023 on North Atlantic’s Region Air Quality: An Analysis Using ASDC Data 

Hazem Mahmoud, Ingrid Garcia-Solera, Daniel Kaufman, Alexander Radkevich, and Walter Baskin

The escalating threat of wildfires in North America raises significant concerns regarding their adverse effects on air quality and public health, as recent wildfires have resulted in widespread smoke plumes that transcend international borders. This study focuses on the exposure of the North Atlantic region to smoke from Canadian wildfires, underscoring the profound implications for public health and environmental well-being. To assess the air quality impact, we analyze satellite data obtained from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, in conjunction with ground-based measurements and atmospheric modeling outputs. Specifically, we investigate  concentrations of atmospheric aerosols, notably PM2.5 particulate matter originating from Canadian wildfires, dispersion patterns, and the duration and intensity of smoke events affecting the North Atlantic. Utilizing data from multiple instruments — including those from the Earth Polychromatic Imaging Camera (EPIC), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP Lidar), and Measurement of Pollution in the Troposphere (MOPITT) — strengthens the conclusions drawn from the impact assessment and estimation of aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes.

The study's findings enhance understanding of the repercussions of Canadian wildfires on air quality in the North Atlantic region, underscoring the necessity of monitoring and prediction of transboundary smoke events through the integration of data from diverse sources, such as those provided by the ASDC. This information is pivotal for policymakers, public health officials, and residents in affected areas to formulate effective strategies in mitigating health risks associated with wildfire smoke and improving air quality during wildfire seasons. The study emphasizes the critical role of atmospheric remote sensing, particularly the use of ASDC data, in addressing the challenges posed by wildfires and their consequences on regional scales.

How to cite: Mahmoud, H., Garcia-Solera, I., Kaufman, D., Radkevich, A., and Baskin, W.: Impact of Canadian Wildfires 2023 on North Atlantic’s Region Air Quality: An Analysis Using ASDC Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12769, https://doi.org/10.5194/egusphere-egu24-12769, 2024.

EGU24-12863 | ECS | Posters on site | BG8.7

The FLARE Workshop's Future Directions for Defining Extreme Fire 

Noah Liguori-Bills, Morgane Perron, Stephen Plummer, Christoph Voelker, Boris Vannière, Joanne Hall, Matthias Forkel, Kebonye Dintwe, Cristina Santin, Miriam Morrill, Jessie Thoreson, Benjamin Poulter, Matthew Jones, Douglas Kelley, Chantelle Burton, Stijn Hantson, and Douglas Hamilton

In September 2023, the Fire Learning AcRoss the Earth Systems (FLARE) workshop brought together fire scientists across a wide range of disciplines, including physical and social scientists and representatives of fire-prone communities, with the aim to facilitate a transdisciplinary discussion.

 

The FLARE community identified characterizing “fire and extreme events” as a research priority. In recent years, there has been a rise in extreme weather events worldwide. Both in science and in the media, the word “extreme” is increasingly used to describe the impact of natural phenomena on ecosystems, human health, the carbon cycle, and economies. However, the severity associated with recent changes in fire activity is not well defined. Assessing the cause(s) and consequences of a fire event on a global scale is complex, this leads to different definitions and assessment techniques/methods being used in the range of disciplines that study fire, including ecology, biology, hydrology, atmospheric science, marine science, Earth science, or public health. Additionally, it is hard to disentangle human land management and climate change induced changes in fire regimes.

 

Using examples from the 2023 Boreal fires, this presentation discusses future directions for defining extreme fires. Fires are also part of the broader interconnected Earth System and influenced by droughts, heat waves, and altered landscapes. In turn, post-fire effects such as erosion, landslides, and floods create cascade events that impact both human societies and natural ecosystems. We discuss this broader view of including fire extremes as part of compound extreme events in order to fully assess their impact. We finish by providing recommendations for the fire science community to tackle this challenge. Some of which may include more proactive modeling, observation and communication tools aimed at providing relevant and timely information.

 

https://futureearth.org/2023/12/13/reflections-from-the-fire-science-learning-across-the-earth-system-flare-workshop/

How to cite: Liguori-Bills, N., Perron, M., Plummer, S., Voelker, C., Vannière, B., Hall, J., Forkel, M., Dintwe, K., Santin, C., Morrill, M., Thoreson, J., Poulter, B., Jones, M., Kelley, D., Burton, C., Hantson, S., and Hamilton, D.: The FLARE Workshop's Future Directions for Defining Extreme Fire, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12863, https://doi.org/10.5194/egusphere-egu24-12863, 2024.

EGU24-13017 | Posters on site | BG8.7

Global Extremes in Burnt Area 

Stijn Hantson, Laura Obando Cabrera, and Matthew Forrest

In recent years, the world has witnessed a surge in "extreme" fire events, with notable occurrences in regions like California and Australia, where their disproportionate impacts have been evident. However, the term "extreme fire" lacks a standardized definition, leading to a diverse and ambiguous usage. To address this, we utilize the MODIS burnt area record spanning 2002-2022 to systematically identify extreme fire years across diverse ecoregions worldwide. Our analysis detects most of the reported events in developed regions, but also additional extreme fire occurrences in less developed areas.

While global fire models are commonly employed to estimate the overall impact of fires on a global scale, their ability to accurately represent extreme events remains uncertain. To assess this, we compare extreme events identified in the MODIS time series with simulations from six global fire models participating in FireMIP. The results reveal variations in model performance, with some models accurately simulating extreme events in burnt area while others exhibit limitations.

Our findings highlight biases in reporting on extreme events and underscore the importance of a quantitative identification framework. Additionally, our analysis suggests that certain global fire models hold promise for studying extreme fire events. This research contributes to a more comprehensive understanding of global fire dynamics and impacts.

How to cite: Hantson, S., Obando Cabrera, L., and Forrest, M.: Global Extremes in Burnt Area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13017, https://doi.org/10.5194/egusphere-egu24-13017, 2024.

EGU24-13319 | ECS | Orals | BG8.7

Probabilistic assessment of extreme fire risk under the impact of climate change 

Zhongwei Liu, Jonathan Eden, Bastien Dieppois, Igor Drobyshev, Stefaan Conradie, Carolina Gallo, Matthew Blackett, and Robert Parker

As major natural hazards, wildfires pose a significant risk to many parts of the world. The occurrence of extensive fires in both hemispheres in recent years has raised important questions about the extent to which the changing nature of such incidents can be attributed to human-induced climate change. Offering reliable answers to these questions is essential for communicating risk and increasing resilience to major wildfires. However, the scarcity of wildfire attribution studies, combined with limited observational records and the complexity of representing fires by different models, poses a challenge in establishing robust and unified conclusions to better inform future forest management strategies.

Here, a globally applicable framework is developed to better understand and quantify how wildfire risk is responding to a changing climate. The framework is based on an empirical-statistical methodology, facilitating its application to ’fire weather’ extremes from both observational records and the latest generation of global climate model ensembles (e.g. from CMIP/UKESM). Particular attention is given to the sensitivity of the eventual findings to the spatial scale of the event, the chosen event definition and the climate model(s) used in the analysis. As part of a global analysis, a series of maps are constructed detailing the change in likelihood of fire weather extremes, defined by both intensity and duration, throughout the world’s fire-prone regions as a result of rising global temperatures. Both observation- and model-based analyses reveal an increase in likelihood of at least twofold across many parts of the world, with considerable regional and inter-model variation. The value of the framework is demonstrated by combining results from a series of case studies of recent high-impact wildfires that differ by scale, duration and location. The conclusions drawn from this work provide a platform to guide future analysis of fire weather events and facilitate reliable recommendations for responding to the hazards associated with wildfires, and enhancing resilience in the face of climate change.

How to cite: Liu, Z., Eden, J., Dieppois, B., Drobyshev, I., Conradie, S., Gallo, C., Blackett, M., and Parker, R.: Probabilistic assessment of extreme fire risk under the impact of climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13319, https://doi.org/10.5194/egusphere-egu24-13319, 2024.

EGU24-13497 | Orals | BG8.7

Prescribed burning as a mechanism to mitigate emissions of extreme fire events: a case study from the Brazilian Cerrado 

Renata Moura da Veiga, Celso von Randow, Manoel Cardoso, Eddy Robertson, Eleanor Burke, Maria Lucia Barbosa, Chantelle Burton, Douglas Kelley, and Fabiano Morelli

The risk of fire occurrence and the frequency of extreme fire events have been increasing globally due to climate change. As a result, greenhouse gas (GHG) emissions are higher worldwide, including in the Brazilian Cerrado. Cerrado is a fire-prone Biome in central Brazil, where fire is essential for maintaining the Biome diversity and integrity. Cerrado presents distinct rainy and dry seasons. In the dry season, the accumulated biomass available for burning becomes highly flammable and fire can rapidly spread from grasslands and savannas to forests. In fire-prone ecosystems globally, prescribed burning prevents intense and frequent wildfires in the drier months by intentionally applying fire under controlled conditions at the end of the rainy season and/or the beginning of the dry season. In Cerrado, prescribed burning is applied in the early dry season (EDS; April-June) to avoid severe wildfires in the late dry season (LDS; August-October), but so far there have been no documented estimates of the effect of prescribed burning on carbon emissions. In this study, we evaluate the potential of prescribed burning to mitigate emissions from extreme fire events in the Brazilian Cerrado region. We modelled fire emissions in Cerrado with JULES-INFERNO over a 30-year period (1990-2019), using the ISIMIP3a simulations. We adjust JULES-INFERNO to represent Cerrado, and then simulate prescribed burning by setting an additional ignition to C4 grass during EDS. We analyse years with large burned areas, including El Niño years, to represent years with intense fire events. Over the 30 years, prescribed burning resulted in reduced fire emissions in the LDS, especially in years when there was high burned area. This indicates that prescribed burning can be used in the Cerrado to reduce the impacts of uncontrolled fires in the drier months. We also observe that the effectiveness of prescribed burning in reducing emissions depends on the C4 grass recovery rate. Further investigation is needed to better understand the model’s performance, including analysis of modelled parameters such as the C4 grass post-fire recovery.

How to cite: Moura da Veiga, R., von Randow, C., Cardoso, M., Robertson, E., Burke, E., Barbosa, M. L., Burton, C., Kelley, D., and Morelli, F.: Prescribed burning as a mechanism to mitigate emissions of extreme fire events: a case study from the Brazilian Cerrado, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13497, https://doi.org/10.5194/egusphere-egu24-13497, 2024.

EGU24-15606 | Posters on site | BG8.7

Community input for a how-to guide for using fire models. 

Douglas I Kelley, Chantelle Burton, Stacey New, Inika Taylor, Camilla Mathison, João Teixeira, Seppe Lampe, Anna Bradley, Eddy Robertson, Robert Parker, Stijn Hantson, Maria Lucia Ferreira Barbosa, Gerd Folberth, Eleanor Burke, Chris D. Jones, Jacquelyn Shuman, Adrianna Foster, and Matthew Forrest

We, the fire science community (and friends), are increasingly asked to provide information about drivers and the impact of fire and make fire projections under future climate and land use change. While the current generation of fire models has skill at modelling certain aspects of global fire regimes, many uncertainties remain. Most models struggle to represent extreme fires and often disagree over future changes in burning. We are collating information on good practices of fire model applications that consider or robustly reduce these uncertainties. These include single or multi-global fire model output, and new and novel modelling and statistical techniques, either in isolated studies or larger projects that contain multiple studies.

The aim is to provide a guide to using fire models for science and policy and a roadmap for development pathways. Thereby moving the community forward to help answer some of the urgent fire-related questions in our changing world. We aim to highlight the fantastic work of many in the community at designing and implementing robust scientific integrity in their analysis. Excellent work already identified often involves tailored modelling and evaluation techniques for specific questions, developing ways to quantify uncertainty, and statistical methods to extract relevant information from models based on historical performance. But there is certainly more we don’t know about!

Can you tell us how and when fire model evaluation has helped inform or adapt a research question? How do you account for fire model uncertainties? We especially want to hear from you if you're unsure or don't think your research is entirely relevant. Maybe we've missed that vital aspect of fire science!? 

To contribute, fill out the questionnaire, jam board, or request an interview at https://forms.gle/NJPEShq6V1ky3Dbv5. Or come talk to us at EGU and fill out our interactive poster!

 

 

How to cite: Kelley, D. I., Burton, C., New, S., Taylor, I., Mathison, C., Teixeira, J., Lampe, S., Bradley, A., Robertson, E., Parker, R., Hantson, S., Barbosa, M. L. F., Folberth, G., Burke, E., Jones, C. D., Shuman, J., Foster, A., and Forrest, M.: Community input for a how-to guide for using fire models., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15606, https://doi.org/10.5194/egusphere-egu24-15606, 2024.

EGU24-16612 | Posters on site | BG8.7

Understanding the impact of large fires in air quality in a Mediterranean area 

Grazia Pellizzaro, Valentina Bacciu, Carla Scarpa, Bachisio Arca, Michele Salis, Marcello Casula, and Annalisa Canu

Fires have been a natural component of Mediterranean ecosystems for centuries, contributing to their ecological balance. However, they also release significant amounts of smoke and various pollutants like carbon monoxide, methane, nitrous oxide, nitrogen oxides, volatile organic compounds, and particulate matter (PM). The emissions not only compromise air quality but also pose a threat to human health, particularly for those with chronic heart and lung diseases. These impacts have been largely studied in the United States and in neighboring countries, while in the Euro-Mediterranean continent the studies available on the patterns of wildfires and fire emissions are more limited. However, the increase in the frequency of large fires recorded in recent years, especially in southern Europe and often close to inhabited centers, urges the scientific community to investigate on the impact of these events on air quality and human health at European level as well.

This study examines six large fires (>2000 ha) in Sardinia, Italy, over the past fifteen years, with the main aims to (i) characterize the six forest fires in term of size, fuel, and weather conditions; (ii) estimate the contribution of the six forest fires to environmental PM levels.

Meteorological conditions at synoptic scale have been investigated through NCEP Climate Forecast System Reanalysis (CFSR) data with a spatial resolution of 0.5° x 0.5° and maps of 850 hPa temperature and airmasses from WetterZentrale (https://www.wetterzentrale.de/). The impacts on particulate matter on air quality has been evaluated through data obtained from the monitoring stations of the Air quality control network of the Regional Environment Protection Agency of Sardinia (ARPAS).  To further investigate the impacts of the fire plumes, the study employs the HYSPLIT (hybrid single-particle Lagrangian integrated trajectory) model developed by NOAA’s Air Resources Laboratory to compute the forward trajectories of air masses. Finally, for selected recent fires, the plume spatial distribution has been investigated and verified using Modis satellite images on board the Aqua satellite as well as the visible Infrared Imaging Radiometer Suite (VIIRS) Corrected Reflectance imagery on board the joint NASA/NOAA Suomi National Polar orbiting Partnership (Suomi NPP) satellite.

Preliminary findings reveal varying degrees of correlation between air quality and fire events in the six examined cases. This variability could be attributed to different fuel types, atmospheric conditions, and, to a significant extent, the location and density of air monitoring stations.

How to cite: Pellizzaro, G., Bacciu, V., Scarpa, C., Arca, B., Salis, M., Casula, M., and Canu, A.: Understanding the impact of large fires in air quality in a Mediterranean area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16612, https://doi.org/10.5194/egusphere-egu24-16612, 2024.

EGU24-17187 | ECS | Posters on site | BG8.7

Comparative assessment of evacuation capacity of selected fire prone areas in Attica region, Greece 

Michail-Christos Tsoutsos, Nikolaos Stasinos, Melpomeni Zoka, Martha Kokkalidou, Stella Girtsou, Nikolaos Stathopoulos, and Charalampos Kontoes

During the last decades, Greece has experienced a range of natural hazards, with three significant events occurring in the wider Attica region. Notably, these include the Athens earthquake that took place on September 7, 1999, the flash flood of Mandra that unfolded on November 15, 2017, and the wildfires that happened on July 23, 2018, in Mati. Among these, wildfires stand out as particularly detrimental disasters provoking numerous fatalities, which have an intense presence within the Attica region according to the FireHub Web Service provided by the Operational Unit “BEYOND” Centre of the National Observatory of Athens. This stems from a persistent urban sprawl over the years throughout the region that leads to an unwavering invasion of urban and suburban infrastructures into wildland areas containing typical Mediterranean vegetation, and as a result, heightens the vulnerability of human lives and properties to a fire-prone environment. Furthermore, most of the suburban areas in the broader Attica region are characterized by uncontrollable urban planning, numerous dead ends, inaccessible seafronts, insufficient installation of firefighting equipment, accumulation of fuels in both private properties and public spaces, and in most cases poor road network quality. This precarious combination of factors exacerbates the risk and impact of wildfires, posing serious challenges to the safety and well-being of the community and underscores the urgent need for comprehensive and strategic protection measures. Considering the necessity to efficiently prevent any loss in human and built environments due to the aforementioned destructive hazards and the region’s characteristics, the Region of Attica funded a research project where fire, seismic, and flood risk was estimated. Within the context of fire risk assessment, evacuation plans were created given the fact to inhibit any fatalities in the likelihood of a forest fire event. The evacuation plans are based on extensive field investigations which brought about insights related to human and physical geographical elements (e.g. topography, land use/land cover, road network density) of each area of interest. The research identified the total number of dead ends, the vehicle escape routes, points of traffic congestion, and polygons representing the order of areas to be evacuated, taking into account the incoming direction of a possible fire front. Moreover, the main routes of evacuation for pedestrians were traced in conjunction with the points of public gathering. Lastly, a variety of recommendations are provided in light of the hotspots that need immediate intervention in order to counter a severe fire event. The primary objective of this research is to present and evaluate the proposed evacuation risk management plans in selected municipalities, as well as, to highlight the most vulnerable areas in terms of capacity through maps.

Acknowledgments

This research work was developed under the national research project “Seismic, Fire and Flood Risk Assessment in Attica Region, Greece”, funded by the Region of Attica, led and coordinated by the Operational Unit “BEYOND Centre of Earth Observation Research and Satellite Remote Sensing” of the Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, of the National Observatory of Athens, Greece.

How to cite: Tsoutsos, M.-C., Stasinos, N., Zoka, M., Kokkalidou, M., Girtsou, S., Stathopoulos, N., and Kontoes, C.: Comparative assessment of evacuation capacity of selected fire prone areas in Attica region, Greece, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17187, https://doi.org/10.5194/egusphere-egu24-17187, 2024.

EGU24-19850 | Posters on site | BG8.7

A Tenfold Increase in Extreme Fires  expected in Europe under a warming climate   

Fredrik Wetterhall, Siham El Garroussi, and Francesca Di Giuseppe

Extreme wildfires have a disastrous impact on society and the natural environment. Wildfires are prone in areas with fuel built up and desiccated over time. A warmer and drier climate will lead to an increase in the risk of extreme fires. 
    This study quantifies how the risk of extreme fires is conditioned on potential temperature and precipitation changes. Our results indicate that large areas of southern Europe could experience a tenfold increase in the probability of catastrophic fires occurring any given year under a moderate CMIP6 scenario. If global temperatures reach the +2 C threshold, central and northern Europe will also become more susceptible to wildfires during droughts. The increasing probability of fire extremes in a warming climate, in combination with an average one-week extension of the fire season across most countries, is expected to strain Europe's ability to cope in the forthcoming decades.

How to cite: Wetterhall, F., El Garroussi, S., and Di Giuseppe, F.: A Tenfold Increase in Extreme Fires  expected in Europe under a warming climate  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19850, https://doi.org/10.5194/egusphere-egu24-19850, 2024.

EGU24-20348 | Orals | BG8.7

Projected Increases in fire weather days even when the Paris Agreement targets are met: an exploration of fire risk uncertainty with a perturbed physics ensemble of climate models  

Inika Taylor, Douglas Kelley, Camilla Mathison, Karina Williams, Andy Hartley, Richard Betts, and Chantelle Burton

Large destructive fires can cause extensive damage to ecosystems, and infrastructure, and loss of life. Understanding how these ‘wildfires’ are likely to change as the world warms is vital for effective fire management planning. This study provides information on likely future change and associated uncertainty in fire weather, relevant for fire management planning, including periods and extent of extreme fire weather and length of control burn season. 

We use the McArthur Forest Fire Danger Index (FFDI) to investigate the effect of human-caused climate change on fire weather. We use a large, perturbed physics ensemble to explore the uncertainty at three Global Warming Levels (GWLs); 1.5°C, 2.0°C and 4.0°C above pre-industrial temperatures, for two emissions scenarios, RCP2.6 (a mitigation scenario), and RCP8.5, (a high-end scenario). We look globally, and focus on three regions: Australia, Brazil and the USA.  The frequency and severity of fire weather increases at all GWLs. The amount of land with more fire weather days increases with GWL, as does the uncertainty. Limiting warming to 1.5°C limits increases in future fire weather. However, even at 1.5°C, there is still a 31% (25% – 36%) increase in the land surface with more fire weather. 

Our analysis shows a substantial increase in fire weather and shortened control burn season even under the best-case scenario of meeting the 1.5°C Paris Agreement temperature target. However, exceeding the Paris Agreement target will see a much more substantial increase in both the fire season length and the amount of the land surface exposed to a greater risk of wildfires. These potential changes in fire weather have important implications for planning appropriate responses, such as the controlled burning season length, resourcing and training of fire managers and first responders, and the development of fire management plans. 

How to cite: Taylor, I., Kelley, D., Mathison, C., Williams, K., Hartley, A., Betts, R., and Burton, C.: Projected Increases in fire weather days even when the Paris Agreement targets are met: an exploration of fire risk uncertainty with a perturbed physics ensemble of climate models , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20348, https://doi.org/10.5194/egusphere-egu24-20348, 2024.

In Latin America, social media platforms are the main source of information updates for the population with internet access. On social networks, information from quick videos, photographs and digital narratives are sources of learning exchanges, updates and lessons.  Thus in this, using the social networks to scientific dissemination with the aim of increase awareness and engagement about the occurrence of forest fires, risks of disasters and the impact of forest fires in Latin America. The digital social platforms used here were Youtube, Facebook and Instagram in Portuguese, English and Spanish. Metrics such as reach, reactions, comments, number of likes, impressions per post, number of followers and automatic evaluations of participation and engagement were collected as a positive strategy for monitoring and social participation of populations with digital access and interest in the topics.

How to cite: Maia, M. and Anderson, L. O.: Scientific communication on social media as a tool for Increase awareness on fire occurrence , risk reduction and environmental disasters associated with forest fires., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20820, https://doi.org/10.5194/egusphere-egu24-20820, 2024.

NH8 – Environmental, Biological & Natech Hazards

EGU24-1803 | PICO | NH8.1

Environmental Monitoring with Q8 datalogger and Quanterra Mesh Extension (QME) 

Arvind Parapuzha, Lani Oncescu, and Mathias Frank

The versatile Q8 datalogger is telemetry ready, but using very low power (~300mW) is suitable for portable applications, such as On-Site-Inspections or seismo-acoustic arrays. Q8 features six or seven high resolution channels, plus an internal +/-2g accelerometer with additional three high resolution channels. The new Quanterra Mesh Extension (QME) allows for simplified integration of up to 16 one-sample-per-second environmental sensors, analog and digital. QME uses a modern IEEE wireless protocol, eliminating the management of multiple cables, ground loops, conduits, trenching, while adding freedom in sensors positioning. QME improves environmental data quality, lowers installation costs and time, and does not require specialized software. The environmental sensors tested so far were for temperature, relative humidity, barometric pressure, wind speed and direction, tilt, strain, external voltage, and intrusion.

How to cite: Parapuzha, A., Oncescu, L., and Frank, M.: Environmental Monitoring with Q8 datalogger and Quanterra Mesh Extension (QME), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1803, https://doi.org/10.5194/egusphere-egu24-1803, 2024.

EGU24-3075 | PICO | NH8.1

Estimation of unknown source term based on radioxenon observations with the presence of background signal 

Ondřej Tichý, Václav Šmídl, Václav Mácha, Jolanta Kuśmierczyk-Michulec, Wolfgang Sommerer, and Anne Tipka

The identification of a sample associated with a nuclear test is a challenging task for the CTBTO because of the presence of a noble gas background in the constant evolving atmosphere. This background is caused by nuclear power plants, nuclear research reactors, and medical isotope production facilities and contributes to samples collected by the noble gas systems of the International Monitoring Stations (IMS). Because of that background, standard linear inverse model applied to Xe-133 measurements is prone to substantial errors. To address this problem, we investigate possible methods for separation of the background signal and any signal from a nuclear explosion, which is further processed for estimation of the Xe-133 source term.

We assume that the observed unknown point release of Xe-133 can be modeled as a linear model y=Mx, where y is the vector of observations, M is source-receptor sensitivity (SRS) matrix, and x is the temporal profile of the unknown release from a nuclear explosion, i.e. its source term. Since the signal in the observation vector is most probably mixed with civilian emitters, we test methods for separation of the contributions from the unknown signal and the background. We compare various approaches, ranging from simple model calibration, to simulated background term and their combinations with anomaly detection.

The results are demonstrated on the data from the 1st Nuclear Explosion Signal Screening Open Inter-Comparison Exercise 2021 where advantages and disadvantages of studied methods are discussed and results are evaluated with the use of ground truth information on temporal and spatial location of the Xe-133 source.

Acknowledgment: This research has been supported by the Czech Science Foundation (grant no. GA24-10400S). The work was performed under the CTBTO awarded contract for ”Provision of Software Engineering Services for the Scientific Development of a Source Term Estimator Tool (STE)” under funding from the European Union Council Decision VIII.

How to cite: Tichý, O., Šmídl, V., Mácha, V., Kuśmierczyk-Michulec, J., Sommerer, W., and Tipka, A.: Estimation of unknown source term based on radioxenon observations with the presence of background signal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3075, https://doi.org/10.5194/egusphere-egu24-3075, 2024.

At least since 1998, we know that the main nuclear weapons states are using computer simulations aimed at having the capability of designing new nuclear weapons without conducting any nuclear test, among other relevant jobs in which computer simulations are used. Currently, three important developments have increased the power of computer simulations: a) the development of new supercomputers with a tremendous capacity for processing and realising complex jobs; b) the accumulation of billions of data useful for simulations considering the number of nuclear tests conducted in the past and the results of computer simulations, and c) the recent developments of powerful AI foundation models with billions of parameters that can be used in nuclear weapon design very successful. The dominant thesis, since 2002, is that experiments “using simulants to replace nuclear materials are permitted under the Comprehensive Test Ban Treaty (CTBT)”. What this means is that states can develop new nuclear weapons complying with the CTBT, but this, I consider, is contrary to the goal of the CTBT and CTBTO. Nuclear proliferation was expected during the first two decades of the 21st century.  However, in the current global geopolitical situation, where other forms of nuclear proliferation are observed, these computer simulations pose challenges to the CTBT and CTBTO.

How to cite: Vargas, C.: Computer Simulations and the Need for Nuclear Weapon Testing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7049, https://doi.org/10.5194/egusphere-egu24-7049, 2024.

EGU24-7502 | PICO | NH8.1

Identifying rocket launches for space missions using infrasound detections across the IMS 

Christoph Pilger, Patrick Hupe, and Peter Gaebler

During the last 20 years, an increasing number of rocket launches for space missions per year was conducted from various space ports all around the world. These missions were mainly launched to place satellites in Earth’s orbit, but also for space station flights and the exploration of the Moon and other bodies in the solar system.  

Rocket launches can be detected at infrasound arrays in thousands of kilometers distance. We use infrasound data from stations of the International Monitoring System (IMS) for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) to identify and characterize rocket launches all over the world.

We present selected cases of interest, including the latest NASA Artemis 1 Space Launch System and SpaceX Starship launches as well as airborne rocket starts and small-lift launches by different companies. Furthermore, we highlight a systematic analysis of infrasound recorded from multiple and regularly launched vehicles like Ariane 5, Falcon 9, and various Soyuz and Long March rocket types.

 

 

How to cite: Pilger, C., Hupe, P., and Gaebler, P.: Identifying rocket launches for space missions using infrasound detections across the IMS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7502, https://doi.org/10.5194/egusphere-egu24-7502, 2024.

EGU24-7649 | PICO | NH8.1 | Highlight

Underwater explosions recorded at IMS hydroacoustic stations from well-defined experiments 

Tiago Oliveira, Mark Prior, Ying-Tsong Lin, and David Dall’Osto

This study analyzes signals recorded by the CTBT-IMS hydroacoustic network from well-defined underwater explosions in the Atlantic Ocean, and looks at the relationships between yield, location, and detectability. The events analyzed are detonations of TNT charges and are used here to assess the ability of the CTBT-IMS hydroacoustic network to detect H-phases, which are signals from in-water explosions. The locations of the explosions ranged between the continental shelf, shelf break, and deep waters, and their yields were between 0.8 and 18,000 kg TNT. For high-yield explosions, T-stations (coastal seismometers) and Hydrophone stations effectively detected the explosions. For distant low-yield events, the ability of the network to detect the explosions depends heavily on the location of the source. Distant shallow events on the continental shelf can be more detectable than closer deep-water events. This is because the sound from the former events propagates off the shelf and skips off the shelf edge into the SOFAR channel, while events in deep water, depending on their depth, can have more difficulty coupling into the SOFAR channel. Similarly, explosions near the shelf break can have a favourable SOFAR channel coupling mechanism due to reflections from the shelf into the channel.

How to cite: Oliveira, T., Prior, M., Lin, Y.-T., and Dall’Osto, D.: Underwater explosions recorded at IMS hydroacoustic stations from well-defined experiments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7649, https://doi.org/10.5194/egusphere-egu24-7649, 2024.

The International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization was designed so that, when fully deployed, it could detect with high confidence and accurately locate nuclear explosions with a yield of about 1 kt TNT equivalent in the absence of special efforts at evasion [1]. Also, an indicative metric for event location precision is that the confidence ellipse area around the estimated event location should not exceed 1000 km2, the maximum area for an on-site inspection request in case of a suspected Treaty violation, specified in the Treaty. The IDC, therefore, needs to meet standards for both event detection and location precision. The event detection standard is most of the time easily met during automatic processing for energetic events thanks to the sufficient number of time-defining detected phases (i.e., phases whose arrival time isused for locating an event), however for events with few detecting stations, azimuth- and slowness-defining phases play a significant role. Furthermore, the more the defining features used in event location, the higher the location precision, i.e. the smaller the confidence ellipse, is. Therefore, accurate arrival directional information slowness and azimuth values can be very important, especially for small, weak events.  

About 25 years ago, after the first few years of operation, systematic biases of measured slowness and azimuth (deviations of measurements from predicted values) of the stations that comprised the IMS at the time were observed. They were attributed largely to lateral heterogeneity and slowness and azimuth station corrections were calculated to mitigate them [2]. Since then, some of these stations have been relocated, had their instruments re-calibrated or replaced and in some cases had their orientation modified. Also, new stations, for which no corrections have ever been calculated, have been installed. There is therefore a need to calculate or in some cases update these corrections. To do so we have considered good quality events (events with body wave magnitude ≥ 4, at least four detecting stations and azimuthal gap < 180°) reviewed by IDC analysts. We analyse time-defining phases with slowness and azimuth measurements and calculate corrections for prespecified slowness and azimuth bins. We also calculate station-specific trends to use as default corrections for bins for which the number of observations is insufficient to draw statistical conclusions. Finally, we calculate bin-specific and default uncertainties (modelling errors) as the spread of the residuals for bins. We compare the new corrections for some stations to the ones calculated previously and discuss differences and similarities. We also assess the effect these corrections would have on event definition, phase type identification and few-station event location.  

 

[1] National Academy of Sciences (2002), Technical Issues Related to the Comprehensive Nuclear Test Ban Treaty. The National Academies Press. https://doi.org/10.17226/10471 

[2] Bondar, I., North, R. G., Beal G. (1999), Teleseismic slowness-azimuth station corrections for the International Monitoring System Seismic Network, Bulletin of the Seismological Society of America, 89, pp.989-1003, https://doi.org/10.1785/BSSA0890040989  

How to cite: Saragiotis, C.: Calculation of slowness-azimuth station corrections for the IMS seismological networks , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12096, https://doi.org/10.5194/egusphere-egu24-12096, 2024.

EGU24-12634 | PICO | NH8.1 | Highlight

Detection of underwater volcanic activity at stations belonging to the International Monitoring System - case of Izu Islands sequence 

Paulina Bittner, Sherif Mohamed Ali, Ehsan Qorbani, Ali Kasmi, Marcela Villarroel, and Gerard Rambolamana

In October 2023, a sequence of shallow seismo-acoustic events occurred in Izu Islands archipelago, south of Honshu, Japan’s main island. The sequence started on October 1, and within a span of 8 days, approximately 70 events with magnitudes of 4.0 (International Data Centre mb) or higher were reported in the Reviewed Events Bulletin (REB) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). An unusual tsunami of up to 60 cm was reported on October 09 by the Japan Meteorological Agency. The authorities suggested that it was triggered by a relatively small magnitude earthquake, however, other related phenomena were also considered. An underwater volcano eruption or quake-triggered seabed landslide could have caused the tsunami. In this work, we show features of signals recorded at the hydrophone stations of the International Monitoring System (IMS), which indicate that the tsunami might have originated from volcanic activity. In addition, hydroacoustic signals were also observed at island seismic stations. This presentation demonstrates how IMS data may contribute to the identification of underwater events, such as volcanic activity, which may result in catastrophic phenomena. Even though the IMS was built to detect nuclear explosion tests, the data are available for civil applications and are distributed to tsunami warning centres.

How to cite: Bittner, P., Ali, S. M., Qorbani, E., Kasmi, A., Villarroel, M., and Rambolamana, G.: Detection of underwater volcanic activity at stations belonging to the International Monitoring System - case of Izu Islands sequence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12634, https://doi.org/10.5194/egusphere-egu24-12634, 2024.

EGU24-15475 | PICO | NH8.1

Seismic Data Archive in the United Kingdom to support Nuclear Test Monitoring 

Sheila Peacock and Peter Bartholomew and the Forensic Seismology Team

In 1961, AWE Blacknest became the home of Forensic Seismology in the UK, with the aim of developing and maintaining a capability to provide seismological advice to the UK government. During the 1960s the group set up a seismometer array in Scotland and worked with host countries to set up arrays in Canada, Australia (now both IMS stations), India and Brazil. AWE Blacknest has continuous data archives from these sites dating back to 1961 on a mix of paper helicorder records (seismic and infrasound traces), analogue FM-encoded tape and digital tape. From 2006-15 Blacknest developed and ran an extensive programme to overcome the ageing issues presented by vintage magnetic media condition and formats, and recovered and digitised the tapes, putting the continuous data on to modern computer storage systems. Since the 1990s data have been directly recorded to digital storage systems. Historically only events of interest, including data recorded from suspected nuclear explosions, were extracted, and Blacknest is running a programme of analysing these events and preparing the data and analysis in a form for public release. I will present on the work undertaken to develop the programme, data recovery and digitization methods from magnetic media, and the modern storage systems Blacknest use for serving seismic data. This will also include analysis work and the data inventories that Blacknest is making available.
UK Ministry of Defence © Crown Owned Copyright 2024/AWE

How to cite: Peacock, S. and Bartholomew, P. and the Forensic Seismology Team: Seismic Data Archive in the United Kingdom to support Nuclear Test Monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15475, https://doi.org/10.5194/egusphere-egu24-15475, 2024.

EGU24-17018 | ECS | PICO | NH8.1 | Highlight

Why do field seismometers need to be calibrated? Benefits through traceably calibrated seismometers from the laboratory to the field 

Michaela Schwardt, Thomas Bruns, and Christoph Pilger

As part of the EU-funded joint research project "Metrology for low-frequency sound and vibration - 19ENV03 Infra-AUV" laboratory calibration methods for seismometers in the low frequency range down to 0.01 Hz have been developed. The reliable knowledge of the full complex sensor response and its associated measurement uncertainty for both, magnitude and phase, improve data quality and reliability by correctly estimating estimating signal amplitude and phase information. Using newly developed on-site calibration approaches, full-frequency responses are estimated for, and the traceability can be transferred to station seismometers of the Comprehensive Nuclear-Test-Ban Treaty Organization’s (CTBTO) International Monitoring System (IMS) during operation without disturbing their regular measurements.

With the on-site methodologies in place for co-located sensors, we show how precisely determined full-frequency response information effects seismogram interpretation and the determination of key parameters such as amplitudes and subsequently magnitudes, as well as first motion polarity or event localisation. For that purpose, we use data from on-site calibration tests performed at IMS station PS19 in Germany with both short-period and broadband seismometers calibrated in the laboratories at PTB.

Furthermore, the possibility of an array-wide calibration of seismometers with a number of temporary and stationary reference sensors is assessed using suitable excitation signals and station-wide similarity measures. The primary focus is to estimate the required quantity, spacing, and distribution of reference sensors throughout the array.

How to cite: Schwardt, M., Bruns, T., and Pilger, C.: Why do field seismometers need to be calibrated? Benefits through traceably calibrated seismometers from the laboratory to the field, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17018, https://doi.org/10.5194/egusphere-egu24-17018, 2024.

Within the International Monitoring System Infrasound Stations, Wind Noise reduction Systems (WNRS) help to improve the infrasound signal quality and analysis by eliminating local atmospheric noise. A standardized system has been designed for the monitoring of nuclear explosions, with a frequency range of interest of 0.1Hz to 10Hz.

This standardized system, a pipe-array rosette, has many options for adaptation with different pipe length, material, and geometry. The type of air inlet and the use or not of primary manifolds will change WNRS characteristics.  All these options of adaptation, give the possibilities to turn the WNRS into tailor-made flexible systems which can be further customized according to their use.

Other types of WNRS have been developed and tested. Enviroearth offers to compare and assess their particular performances : considering their different characteristics, those distinct WNRS model could be practical and optimal for specific applications. By modifying the geometry and characteristics of a WNRS, frequency at which maximum noise reduction is reached can be changed. Therefore, adapted WNRS can be used in measurement stations to monitor natural events (Seismic, Storm, hurricane …) which data can be used for early warning and/or climate change adaptation systems.

How to cite: Lucas, J. and Bednarowicz, C.: Wind Noise Reduction System models state of the art assessment and study of their respective optimal field of application, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17139, https://doi.org/10.5194/egusphere-egu24-17139, 2024.

Part of the International Monitoring System (IMS) for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) is  a network of highly sensitive radionuclide stations sniffing for tiny traces of fission and activation products in the atmosphere.  All IMS radionuclide stations have a high volume sampler for the detection of particulate radionuclides, some are equipped with noble gas systems for the measurement of radioxenon. The specific radioactive xenon isotopes are more likely to escape from underground nuclear explosions and have less complex features in atmospheric transport. There are also radioxenon background emissions from legitimate nuclear facilities. Isotopic ratio analysis allows to a certain extend for source characterization and timing. Atmospheric Transport Modelling (ATM) in backward and forward mode is applied to connect the measurements in space and time with potential releases.  

Noble gas systems at IMS radionuclide stations used to operate with 24 or 12 hours sampling time. The next generation noble gas systems utilize shorter sampling periods. At station RN33 on Mount Schauinsland, Germany, a SPALAX system with 24 hours sampling is operated by BfS. In the phase II testing a  “Xenon International” system with six hours sampling time and better sensitivity to Xe-135, Xe-133m and Xe-131m was installed in parallel from July 2021 to April 2022. The main contributing emitter to elevated xenon activity concentrations at RN33 is the medical isotope production facility at Fleurus, Belgium.

We investigated how the increase in time resolution in sampling and ATM changes the location capability of backward ATM. For that, the Lagrangian Particle Dispersion model HYSPLIT (NOAA-ARL) is applied driven by GFS meteorological data for all samples of the test phase. Calculation of expected Xe-133 contributions from Fleurus derived by ATM backward sensitivities and emission data show generally good agreement. As the Xenon International system also allows for additional detections particularly of Xe-135 and isomers Xe-133m and Xe-131m, the sensitivity to unknown additional sources is potentially improved and analysed. A coincidence analysis of repeating or in respect to isotopic composition remarkable detections which could not be well explained by emissions from Fleurus show several other potential source regions pointing to several  Nuclear Power Plants and research reactors.

How to cite: Ross, J. O. and Brander, S.: Source localization by backward atmospheric transport modelling for radioxenon detections at Mount Schauinsland with six hours sampling duration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19291, https://doi.org/10.5194/egusphere-egu24-19291, 2024.

EGU24-20403 | PICO | NH8.1

Performance variability of the Hydroacoustic and Infrasound IMS stations 

Ehsan Qorbani Chegeni, Paulina Bittner, David Applbaum, and Gerard Rambolamanana

Seismic, hydroacoustic, infrasound, and radionuclide are the four complementary monitoring technologies of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). The International Monitoring System (IMS) of the CTBTO consists of, when complete, 50 primary and 120 auxiliary seismic stations, 11 hydroacoustic stations, 60 infrasound stations, 80 radionuclide stations and 16 radionuclide laboratories. Hydroacoustic and Infrasound stations of IMS are designed to detect events of any kind in and underwater, and in the atmosphere respectively. Hydroacoustic stations have been in operation since 1999; 11 stations, of which 6 hydrophones and 5 T-phase, have been sending data since the completion of the network in 2016. Infrasound data was introduced to routine data analysis in 2010 after improvements in automatic processing to reduce the number of false detections. Currently, 54 (out of 60) infrasound stations are being processed.

Both hydroacoustic and infrasound technologies have had significant contributions to detecting and to improving event location at the International Data Centre (IDC). This presentation assesses the data quality and performance of the hydroacoustic and infrasound stations in the data analysis aspect. We focus on signal and event detection rate and in turn the contribution of the data from hydroacoustic and infrasound stations to the data analysis. We show how the station performance changes temporally and discuss the results.

How to cite: Qorbani Chegeni, E., Bittner, P., Applbaum, D., and Rambolamanana, G.: Performance variability of the Hydroacoustic and Infrasound IMS stations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20403, https://doi.org/10.5194/egusphere-egu24-20403, 2024.

EGU24-21035 | PICO | NH8.1

Suppressing Coda Events with a Bayesian Model of Global Scale Seismology 

Aleksandr Shashkin, Nimar S. Arora, Sherif Mohamed Ali, Urtnasan Khukhuudei, Vera Miljanovic Tamarit, and Gerard Rambolamanana

NET-VISA stands for NETwork processing - Vertically Integrated Seismic Analysis. The package comprises a physics-based, probabilistic model and a heuristic inference algorithm to find the most probable set of seismic events to explain a series of arrivals detected by a global seismic network. It has been extended to find events in any of three mediums – rock, air, and water- and supports seismic, hydro-acoustic, and infrasound sensors.

Large seismic events often trigger a wave train of slow decaying energy known as the coda that can mislead signal detectors into forming coda detections that look like regular phase detections. These coda detections can confuse event formation algorithms into building false events known as coda events. Naive solutions to this problem by dropping any detection that looks like coda detection can have the negative consequence of missing real events. 

We propose to address this issue by extending an existing Bayesian Approach, designed to build event bulletins using a generative model of global-scale seismology. Our extensions significantly boost to the existing work by reducing the total number of false events and virtually eliminating coda events at the cost of a very small drop in the number of real events.

How to cite: Shashkin, A., Arora, N. S., Mohamed Ali, S., Khukhuudei, U., Miljanovic Tamarit, V., and Rambolamanana, G.: Suppressing Coda Events with a Bayesian Model of Global Scale Seismology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21035, https://doi.org/10.5194/egusphere-egu24-21035, 2024.

NH9 – Natural Hazards & Society

EGU24-12 | ECS | Posters on site | NH9.1 | Highlight

Understanding fatal landslides on a global scale: insights from topographic, climatic, and anthropogenic perspectives 

Seckin Fidan, Hakan Tanyas, Abdullah Akbas, Luigi Lombardo, David N. Petley, and Tolga Gorum

Landslides are a common global geohazard that lead to substantial loss of life and socio-economic damage annually. Landslides are becoming more common due to climate change and anthropogenic disturbance, threatening sustainable development in vulnerable areas. Previous studies on fatal landslides have focussed on inventory development; spatial and temporal distributions; the role of precipitation and/or seismic forcing; and human impacts. However, their climatological, topographic, and anthropogenic characterization on a global scale has been neglected. Here, we present the association of natural and anthropogenically induced landslides in the Global Fatal Landslide Database (GFLD) with topographic, climatic, and anthropogenic factors, focusing on their persistent spatial patterns. The majority of natural (69.3%) and anthropogenic (44.1%) landslides occur in mountainous areas in tropical and temperate regions, which are also characterized by the highest casualty rates per group (66.7% and 43.0%, respectively). However, they significantly differ in terms of their morphometric footprint. Fatal landslides triggered by natural variables occur mostly in the highest portions of the topographic profile, where human disturbance is minimal. As for their anthropogenic counterpart, these failures cluster at much lower altitudes, where slopes are gentler, but human intervention is greater due to a higher population density. Our results demonstrate that fatal landslides have a heterogeneous distribution on different macro landforms characterized by different topographic, climatic, and population conditions. Our observations also point towards land cover changes being a critical factor in landscape dynamics, stressing human pressure as a discriminant cause/effect term for natural vs. human-induced landslide fatalities.

How to cite: Fidan, S., Tanyas, H., Akbas, A., Lombardo, L., Petley, D. N., and Gorum, T.: Understanding fatal landslides on a global scale: insights from topographic, climatic, and anthropogenic perspectives, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12, https://doi.org/10.5194/egusphere-egu24-12, 2024.

EGU24-1451 | ECS | Posters on site | NH9.1

A vulnerability framework for a global flood catastrophe model 

Conor Lamb, Izzy Probyn, Oliver Wing, James Daniel, Florian Elmer, and Malcolm Haylock

In recent years the precision and skill of global flood hazard models has increased dramatically. This, alongside developments allowing for hazard model conversion to stochastic event sets and the open-sourcing of catastrophe modeling software, have opened up the possibilities of developing detailed and skillful global flood catastrophe models; assessing not just average risk but also the possible impacts of major flood events and the probability distribution of annual losses. In order to realize these possibilities, it is necessary to develop a global vulnerability framework that appropriately represents the state of the art in vulnerability modeling whilst being flexible to user inputs and faithfully representing uncertainties. 

Here, we present a framework for implementing a flexible vulnerability module within a global flood catastrophe model. Vulnerability curves are derived for a variety of occupancies (residential, commercial, industrial), for both building and contents losses. The mean loss ratio curves are derived from literature and commercial datasets before being normalized and fit to a family of logarithmic functions of depth, which can be adjusted for varying property characteristics. Uncertainty distributions are parameterised using a 4 parameter beta model and derived from a large insurance claims dataset (~2 million claims). 

Finally, using the same large claims dataset, we explore the event-level correlation of the quantiles sampled within our uncertainty distribution. Specifically, we evaluate the extent to which the quantiles sampled of the uncertainty distribution, in a Monte Carlo approach, should be clustered for each event. This is vital for correctly estimating the losses from rare, high-impact events and allows for a realistic representation of vulnerability uncertainty in aggregate loss estimates. 

How to cite: Lamb, C., Probyn, I., Wing, O., Daniel, J., Elmer, F., and Haylock, M.: A vulnerability framework for a global flood catastrophe model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1451, https://doi.org/10.5194/egusphere-egu24-1451, 2024.

EGU24-1669 | ECS | Posters on site | NH9.1

A Comprehensive Review of Coastal Compound Flooding Literature 

Joshua Green, Ivan Haigh, Niall Quinn, Jeff Neal, Thomas Wahl, Melissa Wood, Dirk Eilander, Marleen de Ruiter, Philip Ward, and Paula Camus

Compound flooding, where the combination or successive occurrence of two or more flood drivers leads to an extreme impact, can greatly exacerbate the adverse consequences associated with flooding in coastal regions. This paper reviews the practices and trends in coastal compound flood research methodologies and applications, as well as synthesizes key findings at regional and global scales. Systematic review is employed to construct a literature database of 271 studies relevant to compound flood hazards in a coastal context. This review explores the types of compound flood events, their mechanistic processes, and synthesizes the definitions and terms exhibited throughout the literature. Considered in the review are six flood drivers (fluvial, pluvial, coastal, groundwater, damming/dam failure, and tsunami) and five precursor events and environmental conditions (soil moisture, snow, temp/heat, fire, and drought). Furthermore, this review summarizes the trends in research methodology, examines the wide range of study applications, and considers the influences of climate change and urban environments. Finally, this review highlights the knowledge gaps in compound flood research and discusses the implications of review findings on future practices. Our five recommendations for future compound flood research are to: 1) adopt consistent definitions, terminology, and approaches; 2) expand the geographic coverage of research; 3) pursue more inter-comparison projects; 4) develop modelling frameworks that better couple dynamic earth systems; and 5) design urban and coastal infrastructure with compound flooding in mind. We hope this review will help to enhance understanding of compound flooding, guide areas for future research focus, and close knowledge gaps.

How to cite: Green, J., Haigh, I., Quinn, N., Neal, J., Wahl, T., Wood, M., Eilander, D., de Ruiter, M., Ward, P., and Camus, P.: A Comprehensive Review of Coastal Compound Flooding Literature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1669, https://doi.org/10.5194/egusphere-egu24-1669, 2024.

Translation of geoscience research into tangible changes, such as modified decisions, processes or policy in the wider world is an important yet notably difficult process. Co-RISK is an accessible (i.e. open access, paper-based, zero cost) ‘toolkit’ for use by stakeholder groups within workshops, which is intended to aid this translation process. It is given a robust basis by incorporating paradox theory from organisation studies, which deals with navigating the genuine tensions between industry and research organizations that stem from their differing roles. Specifically designed to ameliorate the organizational paradox, a Co-RISK workshop draws up ‘Maps’ including key stakeholders (e.g. regulator, insurer, university) and their positionality (e.g. barriers, concerns, motivations), and identifies exactly the points where science might modify actions. Ultimately a Co-RISK workshop drafts simple and tailored project-specific frameworks that span from climate to hazard, to risk, to implications of that risk (e.g. solvency). The action research approach used to design Co-RISK (with Bank of England, Aon, Verisk), its implementation in a trial session for the insurance sector and its intellectual contribution are described and evaluated. The initial Co-RISK workshop was well received, so application is envisaged to other sectors (i.e. transport infrastructure, utilities, government).  Joint endeavours enabled by Co-RISK could fulfil the genuine need to quickly convert the latest insights from environmental research into real-world climate change adaptation strategies. 

 

https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1251/

How to cite: Hillier, J. K. and van Meeteren, M.: Co-RISK: A tool to co-create impactful university-industry projects for natural hazard risk mitigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1684, https://doi.org/10.5194/egusphere-egu24-1684, 2024.

EGU24-2009 | ECS | Orals | NH9.1

Considering aftershock-induced damage accumulation in seismic loss assessments 

Corentin Gouache and Adélaïde Allemand

This work outlines a methodology developed for considering aftershock-induced damage accumulation in seismic loss assessments. In particular, it adapts this methodology to the case of reinforced concrete (RC) frames in mainland France and incorporates it to an already-developed seismic loss assessment model.

The methodology consists in dividing the RC buildings into sub-categories of buildings, depending on parameters influencing the vulnerability of the structures. For each category, a set of discrete damage states is defined. For each state Di, fragility functions are derived, enabling to compute the probability of transitioning to another damage state Di+1, knowing the intensity of the ground motion. Therefore, this methodology allows to estimate the final damage state reached by a structure submitted to a series of ground motions.

In order to do so, the pool of French RC buildings is analysed so as to create realistic and general models of RC frames. Ground motions are selected from an open database, following some criteria. Fragility functions are then derived (for each type of building) by applying numerous ground motions to the models and assessing the probabilities of reaching each damage state. The methods for constructing those fragility functions are evaluated from the literature. The choice of relevant parameters measuring damage and measuring ground motion intensity is also scrutinized.

How to cite: Gouache, C. and Allemand, A.: Considering aftershock-induced damage accumulation in seismic loss assessments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2009, https://doi.org/10.5194/egusphere-egu24-2009, 2024.

EGU24-5951 | ECS | Posters on site | NH9.1

Three-dimensional analysis of air temperature of the Hualien M6.9 earthquake based on the tidal forces 

Xian Lu, Weiyu Ma, and Zhengyi Yuan

The Hualien M6.9 earthquake on September 18, 2022 was calculated based on the additional tectonic stress caused by celestial tidal-generating forces (ATSCTF) model. The period of celestial tidal-generating forces was the time background of the air temperature calculation, and the air temperature variation of three-dimensional layered before and after the Hualien earthquake was studied combined with the air temperature data from the National Center for Environmental Prediction (NCEP) of United States. According to the changes of ATSCTF, the Hualien earthquake occurred within the Period B among the three periods: Period A, Period B, and Period C. The air temperature stratification changes during these three periods were calculated separately, and the results showed that on September 12 in Period B, a temperature increase phenomenon began to occur near the epicenter of the Hualien earthquake. On September 13, the air temperature increase anomaly was significant, and the amplitude and area of the temperature enhancement anomaly increased. On September 14th and 15th, the anomaly gradually weakened and disappeared, and the change of the air temperature anomaly followed the seismic thermal anomaly law caused by tectonic movement: the air temperature closer to the land’s surface had a greater anomaly amplitude and a wider anomaly range; as the altitude increases, the air temperature gradually decreases, and the range of anomalies gradually reduces until it disappears. Meanwhile, there were also high temperature anomalies on September 4 and 5 in the Period A, as well as October 1 to October 4 in the Period C. However, the amplitude and area of the warming anomalies in the upper atmosphere were larger than those near the land surface, which did not conform to the seismic thermal anomaly law caused by tectonic movements and did not belong to the seismic thermal anomalies. In addition, the solar geomagnetic KP index in the study area was relatively low during Period B, indicating that it was in a calm period of solar geomagnetic.

How to cite: Lu, X., Ma, W., and Yuan, Z.: Three-dimensional analysis of air temperature of the Hualien M6.9 earthquake based on the tidal forces, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5951, https://doi.org/10.5194/egusphere-egu24-5951, 2024.

EGU24-7652 | ECS | Posters on site | NH9.1

A semi-automatic natural language tool to minimize systematic biases in geo-hydrological disaster datasets in tropical Africa 

Bram Valkenborg, Olivier Dewitte, and Benoît Smets

The high susceptibility to geo-hydrological hazards in tropical Africa and their impacts remain poorly documented in existing disaster databases. Only impactful events with high attention are manually reported, creating systematic biases. Natural Language Processing has the potential to automate the documentation of geo-hydrological disasters. This research focuses on developing a semi-automated tool to extract information from online press and social media posts. Fine-tuned Large Language Models perform a series of tasks, such as question-answering, zero-shot classification, and near-entity recognition, to extract information from these online sources. A three-step approach is proposed for the detection of events: (1) filtering posts or articles on their relevancy, (2) extracting information on the location, timing, and impact and (3) merging and sorting information to document identified events into a structured disaster database. Shortcomings compared to a manual approach remain. These mainly relate to the complexity of the text or toponymic ambiguity when geocoding events. The tool is therefore complementary to other information-gathering approaches. These new sources of information will improve our understanding of the distribution of disasters related to geo-hydrological hazards, especially in data scarce context. Future work will combine this semi-automated tool with remote sensing and citizen science data, to further reduce systematic biases in disaster datasets.

How to cite: Valkenborg, B., Dewitte, O., and Smets, B.: A semi-automatic natural language tool to minimize systematic biases in geo-hydrological disaster datasets in tropical Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7652, https://doi.org/10.5194/egusphere-egu24-7652, 2024.

EGU24-7875 | ECS | Orals | NH9.1

Advancing drought detection and management using ML enhanced impact-based drought indexes 

Martina Merlo, Matteo Giuliani, Yiheng Du, Ilias Pechlivanidis, and Andrea Castelletti

Drought is a slowly developing natural phenomenon that can occur in all climatic zones and propagates through the entire hydrological cycle with long-term socio-economic and environmental impacts. Intensified by anthropogenic climate change, drought has become one of the most significant natural hazards in Europe. Different definitions of drought exist, i.e. meteorological, hydrological, and agricultural droughts, which vary according to the time horizon and the variables considered. Just as there is no single definition of drought, there is no single index that accounts for all types of droughts. Consequently, capturing the evolution of drought dynamics and associated impacts across different temporal and spatial scales remains a critical challenge.

In this work, we first analyze different state-of-the-art standardized drought indexes in terms of their ability in detecting drought events at the pan-European scale, using hydro-meteorological variables from the E-HYPE hydrological model and forced with the HydroGFD v2.0 reanalysis dataset over the period 1993-2018. The findings suggest the need of adjusting the formulation of traditional drought indexes to better capture and represent drought-related impacts. Specifically, here we use the FRamework for Index-based Drought Analysis (FRIDA), a Machine Learning approach that allows the design of site-specific indexes to reproduce a surrogate of the drought impacts in the considered area, here represented by the Fraction of Absorbed Photosynthetically Active Radiation Anomaly (FAPAN). FRIDA builds a novel impact-based drought index combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm.

Our results reveal a general pattern among different indexes, that Southern England, Northern France, and Northern Italy are the regions with the highest number of drought events, whereas the areas experiencing longest drought durations are instead the Baltic Sea region and Normandy. Clustering the 35,408 European basins according to dominant hydrologic processes reveals that the variables mainly controlling the drought process vary across clusters. Similarly, we obtain diverse correlation between standardized drought indexes and the FAPAN in different clusters. Numerical results also show that, in one of the worst cases (cluster 10), the FRIDA index increases the correlation with FAPAN from 0.16 to 0.69. Lastly, the FRIDA indexes are computed for different climatic projections to investigate future trends in drought impacts.  Results show divergence with respect to the trends of the standardized drought indexes, with correlation values below 0.30. In conclusion, these findings can contribute in advancing drought-related climate services by enabling the analysis of projected drought impacts.

 

How to cite: Merlo, M., Giuliani, M., Du, Y., Pechlivanidis, I., and Castelletti, A.: Advancing drought detection and management using ML enhanced impact-based drought indexes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7875, https://doi.org/10.5194/egusphere-egu24-7875, 2024.

EGU24-8660 | ECS | Orals | NH9.1 | Highlight

Assessing landslide risk on a Pan-European scale 

Francesco Caleca, Luigi Lombardo, Stefan Steger, Ashok Dahal, Hakan Tanyas, Federico Raspini, and Veronica Tofani

Assessing landslide risk is a fundamental step in planning prevention and mitigation actions in mountainous landscapes. To date, most landslide risk analyses address this topic at the scale of a slope or catchment. Whenever the scale involves regions, nations, or continents, the landslide risk analysis is hardly implemented. To test this theoretical framework, we present a practical case study, represented by the European landscape. In this contribution, we take the main Pan-European mountain ranges and provide an example of risk assessment at a continental scale. We consider challenges like cross-national variations landslide mapping and digital data storage. A two-stepped protocol is developed to identify areas more prone to failure. With this initial information, we then model the possible economic consequences, particularly in terms of human settlements and agricultural areas, as well as the exposed population. The analytical protocol firstly results in an unbiased landslide susceptibility map, which is combined with economic and population data. The landslide risk is presented in both the spatial distribution of possible economic losses and the identification of risk hotspots. The latters are defined through a bivariate classification scheme by combining the landslide susceptibility and exposure of human settlements. Ultimately, the exposed population is represented during the two sub-daily cycles across the study area.

How to cite: Caleca, F., Lombardo, L., Steger, S., Dahal, A., Tanyas, H., Raspini, F., and Tofani, V.: Assessing landslide risk on a Pan-European scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8660, https://doi.org/10.5194/egusphere-egu24-8660, 2024.

EGU24-9197 | Orals | NH9.1 | Highlight

A global stochastic flood risk model for any climate scenario 

Oliver Wing, Niall Quinn, Malcolm Haylock, Conor Lamb, Rhianwen Davies, Nick Sampson, Izzy Probyn, James Daniell, Florian Elmer, Johannes Brand, and Paul Bates

Modelling flood hazards at large scales – both uniform frequency hazard maps and event simulations whose frequency varies in space – is a relatively new scientific endeavour. Data and computation constraints have historically necessitated either a more local focus to modelling efforts, or the building of proof-of-concept global-scale models whose fidelity inhibits most practical applications.

Here, we present a global climate-conditioned flood catastrophe model; the culmination of decades of research into scaling inundation modelling, the incorporation of climate change, and synthetic event generation. 30 m resolution global maps representing fluvial, pluvial, and coastal flooding for given return periods were simulated using a hydrodynamic model with sub-grid channels whose inputs were defined using regional flood frequency analyses. Change factors from climate model cascades were flexibly used to perturb the local flood frequency a given flood map represents. Separately, a 10,000-year-long set of synthetic events were simulated using a conditional multivariate statistical model fitted to global fluvial-pluvial-coastal reanalysis data. The empirical return period of a given event is used to sample the corresponding flood map return period in order to build a long synthetic series of floods.

With a global exposure model built using a top-down approach – downscaling capital stock models to high-resolution satellite-derived land-use and building height data – and a global vulnerability model derived from an extensive review of modelling and engineering literature, we demonstrate the calibration and validation of the global risk model. We also show the software challenges overcome to run this model, as well as to enable end-users to flexibly calculate the flood risk of their own exposures in the Oasis Loss Modelling Framework.

How to cite: Wing, O., Quinn, N., Haylock, M., Lamb, C., Davies, R., Sampson, N., Probyn, I., Daniell, J., Elmer, F., Brand, J., and Bates, P.: A global stochastic flood risk model for any climate scenario, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9197, https://doi.org/10.5194/egusphere-egu24-9197, 2024.

EGU24-9533 | Posters on site | NH9.1

Modeling inland flooding caused by tropical cyclones in the US using AI-based synthetic events 

Nans Addor, Natalie Lord, Balaji Mani, Thomas Loridan, Naoki Mizukami, Jannis Hoch, and Malcolm Haylock

Tropical cyclones (TCs) are a key driver of flooding in the US. Here we present a modeling approach to simulate their associated inundation footprint under present and future climate and generate the hazard data necessary to run a CAT model. 

We developed an AI-based model called RainCyc that learns from the TC rainfall fields dynamically generated by the WRF model as well as from observations. RainCyc is orders of magnitudes faster than WRF, meaning that orders of magnitude more events can be simulated for the same computational cost. This is essential to capture the tail of the distribution, i.e., to generate synthetic events over a period longer than the longest return period of interest. Future boundary conditions for RainCyc are provided by the CESM2-LENS ensemble, which covers the 21st century under SSP370 levels of warming using 50 model realizations started from slightly perturbed initial conditions.

The rainfall fields produced by RainCyc are used to simulate inland flooding, i.e., pluvial and fluvial. The inundation footprint for each event is generated by sampling from flood hazard maps simulated by the LISFLOOD hydraulic model. The sampling for pluvial is informed by RainCyc precipitation, while for fluvial, it relies on hydrological simulations driven by the FUSE and mizuRoute models. FUSE is a frugal rainfall-runoff model that is run at 10km over a domain encompassing each event to generate its associated runoff. This runoff is then provided to the vector-based routing model mizuRoute to generate flow time series from which peak flow is extracted and used to sample fluvial hazard maps.

We present this modeling framework and test it for thousands of years of synthetic events under present and future climate. We benchmark the hydrological simulations for historical events using runs from other models, including GloFAS. We also test the ability of the framework to generate synthetic events spanning the intensities covered by hazard maps for a wide range of return periods.

How to cite: Addor, N., Lord, N., Mani, B., Loridan, T., Mizukami, N., Hoch, J., and Haylock, M.: Modeling inland flooding caused by tropical cyclones in the US using AI-based synthetic events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9533, https://doi.org/10.5194/egusphere-egu24-9533, 2024.

Understanding the relationship between extreme temperature events and health outcomes necessitates integration of hazard and impact data. International databases of societal impacts from disasters serve as an important data source for empirical cross-country analyses. Yet, detailed and precise estimations of the hazard magnitude of these impact records are often lacking. Physical metrics play a pivotal role in, for instance, statistical analyses and exposure assessments.

In bridging this gap, our work leverages recent advancements in geocoding of disaster records alongside high-resolution meteorological datasets to construct an inventory of a diverse range of health-related climate metrics. Our global analysis spans over 200 records of extreme temperature disasters from the past fifty years. By doing so, we unveil insights into the properties of these disastrous heat- and cold-waves. We furthermore explore differences across space, time, metrics, and data sources. This work highlights the potential of utilizing this integrated approach to extract meaningful information from historical disaster records in global databases, aiding climate resilience and public health strategies.

How to cite: Lindersson, S. and Messori, G.: Quantifying health-related climate metrics of extreme temperature disasters: An international analysis over five decades, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9798, https://doi.org/10.5194/egusphere-egu24-9798, 2024.

EGU24-10060 | ECS | Posters on site | NH9.1

The Impact of El Niño-Southern Oscillation on Tropical Cyclone Risks 

Juner Liu, Simona Meiler, David N. Bresch, and Carmen B. Steinmann

The El Niño-Southern Oscillation (ENSO) is the most important inter-annual signal of climate variability on the planet. It affects many natural hazards including tropical cyclones (TCs), known for causing severe economic losses and many fatalities. Although research efforts have examined ENSO’s influence on TC characteristics including frequency and intensity in different basins, the transfer of these findings to global TC risk assessments has yet to be undertaken. This covers aspects such as damage to physical assets and the number of people affected. However, this is complicated by many uncertainties, such as landfall location (heterogeneous distribution of exposures) and vulnerability definitions. To bridge this gap, we assess TC risks on physical assets and affected people under ENSO’s influence and quantify related sources of uncertainty on a global scale.

We analyze TC risks during El Niño and La Niña years, using three types of TC datasets: the International Best Track Archive for Climate Stewardship (IBTrACS), probabilistic tracks generated by a random walk algorithm (IBTrACS_p), and synthetic TCs generated by a statistical-dynamical TC model (MIT). Furthermore, we quantify the sensitivity of input variables, such as the ENSO threshold, and assess uncertainties arising from TC landfall location using uniform exposure values. The outcomes regarding ENSO-conditioned TC risks can potentially improve seasonal TC risk prediction, thus benefiting policymakers and the insurance industry alike. Additionally, the results contribute to more balanced and diversified (multi-)hazard risk portfolios by accounting for ENSO as an important common modulator of spatially compounding hazards.

How to cite: Liu, J., Meiler, S., Bresch, D. N., and Steinmann, C. B.: The Impact of El Niño-Southern Oscillation on Tropical Cyclone Risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10060, https://doi.org/10.5194/egusphere-egu24-10060, 2024.

EGU24-10905 | ECS | Posters on site | NH9.1

Flooding Under Climate Change in Small Island Developing States 

Leanne Archer, Jeffrey Neal, Paul Bates, Natalie Lord, and Laurence Hawker

Small Island Developing States are a group of 57 island nations and territories which are some of the most at-risk places to the impacts of climate change globally, particularly from changes in hydrometeorological hazards such as flooding. Despite this, little research has quantified present day flood hazard and population exposure in small islands, let alone how this may change as global temperatures continue to rise. Until now, this was due to the insufficient data to produce high-resolution flood hazard and population exposure estimates for a wide range of possible scenarios at such a large scale. Following the release of Fathom’s Global Flood Model 3.0, in this work we combine global flood hazard estimates for coastal, fluvial, and pluvial flood hazard at ~30m flood model resolution to estimate present day population exposure to flooding across all 57 small islands. We also investigate how flood hazard and population exposure changes under three climate scenarios: two plausible climate change scenarios (SSP1-2.6 and SSP2-4.5), and a plausible worst-case climate scenario (SSP5-8.5). We assess how present day flood hazard and exposure differs across the island typologies, and how these are projected to change under the different climate change scenarios. We also compare population exposure with vulnerability metrics to explore how population exposure to flooding and vulnerability interact. The results of this analysis aim to improve understanding regarding the range of plausible estimates of current and future population exposure to flooding in Small Island Developing States. These results will help inform adaptation to more extreme flood risk in Small Island Developing States under current and future climate change.

How to cite: Archer, L., Neal, J., Bates, P., Lord, N., and Hawker, L.: Flooding Under Climate Change in Small Island Developing States, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10905, https://doi.org/10.5194/egusphere-egu24-10905, 2024.

EGU24-13847 | Posters on site | NH9.1

Development of a Comprehensive Exposure-at-Risk Map for Europe: Integrating Coinciding Natural Hazards and Exposure Metrics 

James Daniell, Andreas Schaefer, Judith Claassen, Johannes Brand, Timothy Tiggeloven, Bijan Khazai, Trevor Girard, Annika Maier, Benjamin Blanz, Nikita Strelkovskii, Jaroslav Mysiak, Marleen de Ruiter, Wiebke Jaeger, and Philip Ward

The development of an Exposure-at-risk map for Europe that encompasses multiple coinciding natural hazards builds upon many previous attempts and existing portals such as TIGRA, TEMRAP, ESPON, JRC DRMKC, and GIRI to name a few, which have primarily focused on examining a few single hazards and limited exposure.
The novelty of this approach lies in its integration of a myriad of hazards into a single, cohesive framework. The European Hazard Map is constructed using data from various sources, covering geophysical hazards (earthquakes, volcanoes, landslides), meteorological hazards (winds, convective storms, storms), hydrological hazards (river/pluvial floods), climatic overlaps (bushfires, droughts), and biological hazards. These hazards are modelled using both stochastic and probabilistic methods as well as historical reanalysis, offering a robust and comprehensive view of potential risks.
The exposure component of this map is constructed around a handful of key Europe-wide metrics, encompassing aspects crucial to the European multi-sector context. These include tourism-based metrics such as domestic and international expenditure, hotel statistics, employment figures, as well as broader economic indicators like capital stock (particularly focusing on buildings), GDP, and critical infrastructure related to transport and energy. Additionally, agricultural production and seasonal population variations are factored in. These metrics are pivotal in assessing the potential impact of various hazards, including but not limited to earthquakes, tsunamis, winds, floods, landslides, tornadoes, hail, droughts, and bushfires.
This map has been developed as part of the MYRIAD-EU project, a multi-hazard initiative, and is built using open data sources and risk analytics within the project. A significant feature of this map is its ability to demonstrate temporal and spatial overlaps. This capability allows for the visualization of combined events or the combined impact of different exposure-hazard overlaps, depending on whether the output is stochastic or probabilistic. The interface of this map serves as a crucial gateway to the MYRIAD-EU multi-hazard software scorecard approach. It also plays a pivotal role in identifying overlapping hazards within the EU, enabling better preparedness and response strategies.
In summary, this Exposure-at-risk map for Europe is a significant advancement in the field of hazard assessment and risk management. It integrates a multitude of hazards and exposure metrics, offering a comprehensive and detailed view of potential risks across Europe. This map is not only a tool for current risk assessment but also a foundation for future research and development in this critical area of study.

How to cite: Daniell, J., Schaefer, A., Claassen, J., Brand, J., Tiggeloven, T., Khazai, B., Girard, T., Maier, A., Blanz, B., Strelkovskii, N., Mysiak, J., de Ruiter, M., Jaeger, W., and Ward, P.: Development of a Comprehensive Exposure-at-Risk Map for Europe: Integrating Coinciding Natural Hazards and Exposure Metrics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13847, https://doi.org/10.5194/egusphere-egu24-13847, 2024.

EGU24-13864 | Orals | NH9.1

Connecting the dots: teleconnection of global floods and their association with climate variability 

Yixin Yang, Long Yang, Qiang Wang, and Gabriele Villarini

A fundamental question in global hydrology is how global floods behaved in the past and are expected to behave in the future. Previous site-specific analyses might offer locally relevant insights, but little is known about how floods are connected in space and time as well as their synchronous responses to climate variability at the global scale. Here we carry out empirical analyses based on a comprehensive dataset of annual maximum flood peak series from 4407 stream gaging stations. We establish the link between any two stream gages if their annual maximum flood peak discharges are significantly correlated and the dates of their occurrences are sufficiently close (using event synchronization and complex network). Our results identify notable remote links of annual flood peak series over western Canada/US (e.g., upper Missouri River basin), northern Europe (e.g., Kemijoki River basin), southern China (e.g., middle Yangtze River basin), and northern South America (e.g., Amazon River basin). Annual flood peak series are linked to their local neighbors (within a distance of 4500 km) over eastern United States, central Europe, and eastern Australia. Remote links highlight the spatial dependence of riverine floods at the global scale. These links are dictated by the oscillation of dominant climate modes over the Pacific Ocean (e.g., El Niño Southern Oscillation, Pacific Decadal Oscillation) and their resultant anomalous atmospheric circulation patterns. Local flood clusters are more responsive to region-specific atmospheric forcings. The complex flood network plays an important role in regulating the dynamic behaviors of flood hazards. Our results offer new insights into global flood hydrology and their connections with large-scale climate forcings.

How to cite: Yang, Y., Yang, L., Wang, Q., and Villarini, G.: Connecting the dots: teleconnection of global floods and their association with climate variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13864, https://doi.org/10.5194/egusphere-egu24-13864, 2024.

Floods constantly occur in San Miguel de Ibarra's urban setting each year. Situated on the slopes of the Imbabura volcano, an integral component of the UNESCO Global Geopark Imbabura, this Ecuadorian city boasts an invaluable cultural and natural heritage. However, it has experienced multiple adverse impacts due to the overflow of rivers and streams. In 2022, an inventory of floods was compiled for the Geopark, revealing the persistent recurrence of this phenomenon within the city. Consequently, it became imperative to gather historical and contemporary data from diverse sources such as public institutions (GAD Ibarra 2023), digital newspapers, social networks, and aerial imagery (IGM 2014) to discern patterns and establish correlations related to these occurrences (SNGRE 2023).

In this way, the acquired information spanning the period from 1965 to the present, insights were gained into the distribution of flood-prone zones and their correlation with paleochannels. Additionally, discernment was achieved regarding alterations in land-use planning attributable to urban expansion in the city, which, in turn, contributes to the heightened susceptibility to floods. This meticulous analysis unveiled specific areas within the city consistently affected by such hazards, elucidating these events' characteristics and the ensuing damage to both public and private properties. The current publication presents preliminary findings utilized in the estimation of flood risk.

Keywords: Paleochannels, floods, Ibarra, Imbabura, Imbabura UNESCO Geopark

References:

GAD Ibarra (2023) Cartography of Ibarra canton at several scales

IGM (2014) Cartography of Ibarra canton 1:5.000

IGM (2023) Historical imagery of flights in Ecuador at several scales

SNGRE (2023) Data Base Events SNGRE. Period 2010 to 2023

How to cite: Torres-Ramírez, R.: Paleochannels and their correspondence with floods in the 21st century. Case study of Ibarra city, Imbabura, Ecuador., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14423, https://doi.org/10.5194/egusphere-egu24-14423, 2024.

Abstract: The incidences of earthquakes in the north Indian state of Uttarkhand are broadly associated with the presence of active fault viz. Main Central Thrust and Alaknanda Fault in the north, Moradabad Fault and Himalayan Frontal Thrust in the southern margin, Martoli Thrust and Indus Suture in the eastern, Mahendragarh Dehrdun Fault in the west. Uttarakhand falls under Seismic Zone IV and V and has been struck by several devastating earthquakes viz. 1905 Kangra earthquake of MW 7.8, 1991 Uttarkashi earthquake of MW 6.8 and 1999 Chamoli earthquake of MW 6.5 with maximum MM Intensity of IX observed in near-source region causing widespread damage and destruction in the study region. Uttarakhand region has undergone unprecedented development and population growth, emphasizing the importance of analysis of Seismic Hazard to ensure safe and secure progress in this seismically vulnerable region. Consideration of seismicity patterns, fault networks and similarity in the style of focal mechanisms yielded 10 areal seismogenic sources with additional active tectonic features in 0-25km, 25-70km, and 70-180km hypocentral depth ranges, along with 15 Ground Motion Prediction Equations for the tectonic provinces of Uttarakhand region yielding Probabilistic Peak Ground Acceleration (PGA) at engineering bedrock  seen to vary from 0.36g to 0.63g for 475years of return period which places the region in the moderate to high hazard zone necessitating a case study for site-specific seismic characterization of the region. Seismic site classification has been done based on an enriched geophysical, in-situ downhole, geotechnical database and surface geoscience attributes comprising of Geology, Geomorphology, Landform and Topographic Gradient derived shear wave velocity categorizes the region into Site Classes E, D4, D3, D2, D1, C4, C3, C2, C1, B and A. Using the input ground motion at bedrock level obtained from stochastic simulation for the near-source earthquakes, nonlinear site response analyses have been performed using PLAXIS-2D software package wherein site amplification has been mapped which is seen to vary in the range of 1.02 to 2.86. Surface-consistent probabilistic seismic hazard in terms of Peak Ground Acceleration (PGA) for a return period of 475 years has been assessed for the study region by convolving site amplification with bedrock hazard thus predicting a variation of PGA in the range of 0.51-1.61g. Additionally, assessment of liquefaction potential of the terrain and seismic hazard microzonation have been done for Dehradun city to identify areas with varying level of ground shaking and its associated liquefaction phenomenon during earthquakes, enabling the development of site-specific building codes and land-use regulations. The results of this investigation are expected to play vital roles in the earthquake–related disaster mitigation and management of the region.

How to cite: Bind, A. P. and Nath, S. K.: Site-specific Seismic Hazard Assessment of Uttarakhand, India with special emphasis on Liquefaction Potential  modelling of the terrain and Seismic Hazard Microzonation of Dehradun City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14677, https://doi.org/10.5194/egusphere-egu24-14677, 2024.

EGU24-16095 | ECS | Posters on site | NH9.1

Do catchment characteristics drive extreme discharge tail behavior in the Meuse catchment? Insights from 1,040 years of synthetic discharge data.  

Anais Couasnon, Laurène Bouaziz, Ruben Imhoff, Hessel Winsemius, Mark Hegnauer, Niek van der Sleen, Robert Slomp, Leon van Voorst, and Henk van den Brink

Understanding extreme discharge behavior is of importance for flood design and risk management. For example, estimates of large extreme discharge return periods such as the 100-year return period or higher are often needed as a basis for flood hazard maps or dike design. Yet, frequency analysis based on decade-long discharge records show a large uncertainty for these frequencies, among others due to the statistical uncertainty from the distribution parameters.  This is not the case for the shape parameter, a key parameter that describes the upward or downward curvature of the tail of the distribution and thus an indicator of extreme discharge behavior. 

This study provides robust estimates of the shape parameter by using the 1,040 years of synthetic daily discharge generated for the Meuse catchment as part of the EMfloodResilience project from the Interreg Euregio Meuse-Rhine program. The spatially-distributed hydrological model wflow_sbm, calibrated and validated for the Meuse catchment, is forced with 16 synthetic climate ensembles of 65 years representative for the current climate from the physically-based KNMI regional climate model RACMO climate model at a daily and hourly time step. The annual maxima (AM) from hydrological years (Oct-Sep) are retrieved from these continuous time series, and a GEV distribution is fit to the AM. We observe a clear spatial pattern of the shape parameter across the Meuse catchment. Using this large dataset of shape parameters, we also review the possible reasons for the different tail behavior obtained with respect to rainfall statistics, catchment characteristics and river systems following the In doing so, we aim to bridge the extreme value statistical modelling with our current understanding of the extreme hydrological signatures present in the catchment.

How to cite: Couasnon, A., Bouaziz, L., Imhoff, R., Winsemius, H., Hegnauer, M., van der Sleen, N., Slomp, R., van Voorst, L., and van den Brink, H.: Do catchment characteristics drive extreme discharge tail behavior in the Meuse catchment? Insights from 1,040 years of synthetic discharge data. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16095, https://doi.org/10.5194/egusphere-egu24-16095, 2024.

EGU24-16556 | ECS | Posters on site | NH9.1

Coastal flood risks in Europe in the context of sea-level rise: methods and preliminary results from the CoCliCo project 

Vincent Bascoul, Rémi Thiéblemont, Jeremy Rohmer, Elco Koks, Joël De Plaen, Daniel Lincke, Hedda Bonatz, and Goneri Le Cozannet

Present days and future coastal flooding is a key concern for Europe due to sea-level rise, storm surges and the importance of infrastructure at risk in low-lying areas. To support adaptation, information on future risks such as people exposed and economic damages are required. The CoCliCo project aims to contribute responding to this need by informing users about coastal risks via an open-source web platform. This platform aspires to improve decision-making on coastal risk management and adaptation in Europe.

Here, we present the methods used in CoCliCo to compute risks and provide early results of risk calculations at the European scale. The results take the form of costs calculated for different flooding scenarios on different infrastructures (residential buildings, roads...) as a function of flood water levels. Flood water levels are determined for each infrastructure based on flood modelling. Then, using vulnerability curves, a damage associated with the type of infrastructure as a function of the water level is assigned. The damage ratio then is used to calculate the cost of flooding. Coastal risk can also be presented in social terms, by assessing the number of people potentially affected by flooding. The results are illustrated for two case studies: Dieppe and Hyère in France using detailed flood modelling and complemented by preliminary results for Europe. Our results are compared results from with previous studies.

Finally, flood risk projections will be presented for several return periods at different scales and for different integrated scenarios considering climate change and associated socio-economic pathways as well as different adaptation options. These results will be made available on the CoCliCo platform.

How to cite: Bascoul, V., Thiéblemont, R., Rohmer, J., Koks, E., De Plaen, J., Lincke, D., Bonatz, H., and Le Cozannet, G.: Coastal flood risks in Europe in the context of sea-level rise: methods and preliminary results from the CoCliCo project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16556, https://doi.org/10.5194/egusphere-egu24-16556, 2024.

Tropical cyclones are events responsible for the costliest meteorological catastrophes. On average per year over the last decade, they have affected 20 million people, with estimated economic losses US$51.5 billion (Krichene et al., 2023). These consequences reduce the economic growth of the affected countries (Berlemann & Wenzel, 2018). Take Jamaica, for instance, where annual damages caused by tropical cyclones are estimated at 0.5%, reaching up to 10% of the Gross Domestic Product (Adam & Bevan, 2020).

The climatology of tropical cyclone, defined as characteristics averaged over years, controls parameters like tracks, intensification, number of storms, all crucial for induced hazards (winds, precipitation, storm surge and waves). In recent years, anomalous tropical cyclones have impacted the coasts worldwide. In 2023, hurricane Otis, without precedent, rapidly intensified off the coast of the coast of Acapulco (Mexico), resulting in at least 52 deaths and estimated damage exceeding 10 billion USD. The track of tropical cyclone Kenneth struck areas of Mozambique where no previous tropical cyclone had impacted before, resulting in 45 casualties and $100 million in damage (Mawren et al., 2020). The future of tropical cyclones is impregnated with uncertainty and is a matter of concern, which have motivated the recent advance in this topic. Several authors asseverate an increase in intensity, reduce in frequency (Bloemendaal, et al., 2022; T. Knutson et al., 2020; T. R. Knutson et al., 2010), and their poleward displacement (Studholme et al., 2022). However, the global study of the displacement of tropical cyclones and their characteristics due to the migration of storms has not been integrated into large-scale adaptation planning.

This study identifies regions affected by the displacement of storms in the North Atlantic at the municipal administration level. Analysing characteristics under two climatology periods—a baseline climate (1980-2017) and a future high-emission climate scenario, Shared Socioeconomic Pathway SSP8.5 (2015-2050)—we used synthetic tracks (Bloemendaal, et al., 2022) generated with a model based on STORM  (Bloemendaal et al., 2020). Four Global Climate Models (CMCC, CNRM, EC-Earth, and HadGEM3) were examined to evaluate uncertainty, focusing on frequency, intensity, and critical parameters such as size, translation speed, track complexity, residence time in front of the coast, and relative direction to the shoreline.

This study identifies hotspots where tropical cyclone characteristics are spatially displaced, increasing the exposure to tropical cyclones in these regions. For example, the Canary Islands in Spain show that hurricanes of category 1, in present conditions, have a return period of 215 years, reducing to 62 years in the SSP8.5 scenario. This is in line with the recent records, the Hermine storm in 2022 almost impacted their coasts. The results raise questions about our public policies for future adaptation. In areas historically unaffected and unprepared for tropical cyclones, the corresponding government may lack and require prevention systems for tropical cyclones, such as warning alarms, reducing subsidies for coastal development or implementing disaster relief policies. 

How to cite: Odériz, I. and Losada, I.: Implications of the displacement of tropical cyclones for public policies in the North Atlantic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17338, https://doi.org/10.5194/egusphere-egu24-17338, 2024.

EGU24-17738 | ECS | Orals | NH9.1

Complex emergencies: drivers of the humanitarian impacts of climate-related disasters 

Ellen Berntell, Nina von Uexkull, Tanushree Rao, Frida Bender, and Lisa Dellmuth

Climate-related disasters such as floods, droughts and storms often pose significant threats to human livelihoods, especially in developing countries. The extreme weather events often lead to destroying of shelter, harming of crops and livestock as well as fueling of conflicts, and the threat to human livelihoods are likely to increase due to climate change. While we know that climate change and conflict interact and reinforce each other, less is known in the context of natural disasters and disaster aid. In this paper we address this gap by studying how hazard severity, disaster exposure and drivers of vulnerability interact to produce humanitarian impacts, and if the delivery of emergency disaster aid alleviates these impacts. We do this by generating meteorological hazard severity measurements based on the reanalysis dataset ERA5, comparable across different climate-related disaster types, allowing us to study drivers of vulnerability to climate-related hazards. Secondarily, we study the role of aid allocation on limiting disaster mortality and displacement, with the results having broad implications for the understanding of disaster impacts and aid effectiveness.

How to cite: Berntell, E., von Uexkull, N., Rao, T., Bender, F., and Dellmuth, L.: Complex emergencies: drivers of the humanitarian impacts of climate-related disasters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17738, https://doi.org/10.5194/egusphere-egu24-17738, 2024.

EGU24-17751 | ECS | Orals | NH9.1 | Highlight

A New Method to Compile Global Multi-Hazard Event Sets 

Judith Claassen, Elco E. Koks, Timothy Tiggeloven, and Marleen C. de Ruiter

This study presents a new method, the MYRIAD-Hazard Event Sets Algorithm (MYRIAD-HESA), that compiles historically-based multi-hazard event sets. MYRIAD-HESA is a fully open-access method that can create multi-hazard event sets from any hazard events that occur on varying time, space, and intensity scales. In the past, multi-hazards have predominately been studied on a local or continental scale, or have been limited to specific hazard combinations, such as the combination between droughts and heatwaves. Therefore, we exemplify our approach by compiling a global multi-hazard event set database, spanning from 2004 to 2017, which includes eleven hazards from varying hazard classes (e.g. meteorological, geophysical, hydrological and climatological). This global database provides new scientific insights on the frequency of different multi-hazard events and their hotspots. Additionally, we explicitly incorporate a temporal dimension in MYRIAD-HESA, the time-lag. The time-lag, or time between the occurrence of hazards, is used to determine potentially impactful events that occurred in close succession. Varying time-lags have been tested in MYRIAD-HESA, and are analysed using North America as a case study. Alongside the MYRIAD-HESA, the multi-hazard event sets, MYRIAD-HES, is openly available to further increase the understanding of multi-hazard events in the disaster risk community. The open-source nature of MYRIAD-HESA provides flexibility to conduct multi-risk assessments by, for example, incorporating higher resolution data for an area of interest.

How to cite: Claassen, J., Koks, E. E., Tiggeloven, T., and de Ruiter, M. C.: A New Method to Compile Global Multi-Hazard Event Sets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17751, https://doi.org/10.5194/egusphere-egu24-17751, 2024.

EGU24-17874 | ECS | Orals | NH9.1

An evaluation of the use of regional climate model data applied to extreme precipitation in the Meuse basin 

Leon van Voorst, Henk van den Brink, and Anais Couasnon

Understanding of hydrological and meteorological extremes is essential for flood risk management and flood protection. A primary focus in these professions is adequate estimation of extreme events that correspond to large return periods. Hydrological and meteorological observations only go back several decades, complicating frequency analysis of these large extremes. Capturing the tail behaviour of extremes is particularly challenging with such short records, resulting in high uncertainty of large precipitation and discharge extreme estimates.

This study proposes an alternative strategy for hydrological and meteorological frequency analysis. Long timeseries obtained from regional climate models are used to replace short observational datasets, leading to a substantial reduction of the statistical uncertainty of meteorological and hydrological extreme estimates. The approach was tested in the Meuse basin as part of the EMFloodresilience project, evaluating meteorological extremes from 16 synthetic ensembles of 65 years from the RACMO regional climate model (forced by the EC-EARTH global climate model). Hydrological extremes are analysed in a subsequent study from Rijkswaterstaat and Deltares, by forcing the wflow discharge model with the RACMO climate model dataset.

The study results reveal that bias-corrected model data is climatologically comparable to observational averages and extremes, exhibiting similar GEV location and scale parameters. Revealing a previously unexamined range of extremes, the model data offers a more plausible method to estimate the tails of annual extremes and likely provides a better estimate of the corresponding GEV shape parameter. Spatially, the model-derived parameter shows greater consistency across different sub-catchments of the Meuse basin compared to observations, suggesting a more robust insight in the tail behaviour of extremes. Additionally, a distinct separation between GEV distributions of summer and winter events is observed, indicating a transition in magnitude dominance from winter to summer maxima and possibly the presence of a double population. The existence of such a double population is difficult to obtain from observations, but can have an enormous impact on the return values of summer extremes. This emphasizes the need for further research on this area for adequate flood management.

How to cite: van Voorst, L., van den Brink, H., and Couasnon, A.: An evaluation of the use of regional climate model data applied to extreme precipitation in the Meuse basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17874, https://doi.org/10.5194/egusphere-egu24-17874, 2024.

EGU24-18718 | ECS | Orals | NH9.1

When one becomes many: Including complex channel systems in large scale flood models 

Laurence Hawker, Jeffrey Neal, Michel Wortmann, Louise Slater, Yinxue Liu, Solomon H. Gebrechorkos, Julian Leyland, Philip J. Ashworth, Ellie Vahidi, Andrew Nicholas, Georgina Bennett, Richard Boothroyd, Hannah Cloke, Helen Griffith, Pauline Delorme, Stuart McLelland, Andrew J. Tatem, Daniel Parsons, and Stephen E. Darby

Over 70% of flood events recorded in the past two decades in the Global Flood Database and WorldFloods dataset have occurred in locations where complex channel systems occur. Here we define complex channel systems as parts of the river network that diverge, such as bifurcations, multi-threaded channels, canals and deltas. Yet, large scale flood models have, until now, used only single-threaded networks due to the lack of a river network that reflects complex channel systems . Therefore, these large-scale models fundamentally misrepresent the physical processes in these often highly populated areas, leading to sub-optimal estimates of flood risk.

Using the new Global River Topology (GRIT) dataset, a global bifurcation and multi-directional river network (Wortmann et al. 2023), we extend the river channel bathymetry estimation routine of Neal et al. (2021) to model multi-channels with LISFLOOD-FP. We compare the multi-thread model results to observations and to previous versions of LISFLOOD-FP using a single-threaded river network in the Indus, Mekong and Niger rivers at 1 arc second (~30m). By using GRIT, we find marked improvements in model results, observing better connectivity to areas of the floodplain that are far from the main channel and more channel floodplain interactions in wetlands. This work paves the way to further our understanding of global flood risk and to finally consider the diverse, evolving nature of geomorphologically active river networks. As this work progresses, we will continue to model a typology of bifurcations and multi-directional rivers to help further our understanding of the significance of complex river systems.

Neal, J., Hawker, L., Savage, J., Durand, M., Bates, P., & Sampson, C. (2021). Estimating river channel bathymetry in large scale flood inundation models. Water Resources Research57(5), e2020WR028301.

Wortmann, M., Slater, L., Hawker, L., Liu, Y., & Neal, J. (2023). Global River Topology (GRIT) (0.4) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7629908

How to cite: Hawker, L., Neal, J., Wortmann, M., Slater, L., Liu, Y., Gebrechorkos, S. H., Leyland, J., Ashworth, P. J., Vahidi, E., Nicholas, A., Bennett, G., Boothroyd, R., Cloke, H., Griffith, H., Delorme, P., McLelland, S., Tatem, A. J., Parsons, D., and Darby, S. E.: When one becomes many: Including complex channel systems in large scale flood models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18718, https://doi.org/10.5194/egusphere-egu24-18718, 2024.

EGU24-20386 | ECS | Orals | NH9.1

Slow-moving landslide exposure increases with population pressure 

Joaquin Vicente Ferrer and Oliver Korup

Slow-moving landslides can cause damage to structures and infrastructure and result in thousands of casualties, if they fail catastrophically. Landslide motion may accelerate after prolonged rainfall, and with alterations to their surface hydrology caused by urbanization. As populations grow in mountainous regions, there will be more direct interactions between communities expanding onto landslides. Yet, the lack of systematic data has precluded a global overview of exposure. We address this by compiling a global database of 7,764 large landslides (>0.1 km2 in area) reported to be slow-moving. Here, we assess the presence of human settlements in 2015 and estimate exposure across IPCC regions with projected landslide risk. We estimate that 9% of landslides in a given basin are occupied by human settlements. On 1195 km2 slow-moving landslides, settlement footprints total 55 km2 and cover an average of 12%, relative to the landslide area. We show regional influences of exposure to floods, average steepness, and urbanization on exposure across basins. Our estimates of exposure in East Asia (EAS) show the most credibility across regions facing growing landslide and flood risk by the IPCC. Apart from Central Asia, we find that urbanization in a basin increases the relative number of landslides inhabited. Furthermore, we find that regions with mountain risks projected to increase have highest uncertainty in our assessment.

How to cite: Ferrer, J. V. and Korup, O.: Slow-moving landslide exposure increases with population pressure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20386, https://doi.org/10.5194/egusphere-egu24-20386, 2024.

EGU24-20522 | ECS | Orals | NH9.1

Global assessment of human exposure to sea-level rise to 2300 

Jack Heslop, Robert Nicholls, Caridad Ballesteros Martinez, Daniel Linke, and Jochen Hinkel

The PROTECT project [1] includes a probabilistic integrated assessment of global population exposure to coastal flood hazard under climate-induced sea-level rise (SLR) over the next three centuries (to 2300). The assessment synthesises present-day datasets on population distribution [2], low lying coastal elevations [3] and extreme tides [4] with probabilistic projection datasets of population [5] and sea level [6] to 2300. For the scenarios considered (SSP1-2.6 & SSP2-4.5) and at a global scale, the median human exposure to coastal flood hazards grows substantially but then peaks in the early 2200s and subsequently slowly declines by 2300, despite continued rise in sea level.

Previous assessments have primarily focussed on shorter timeframes [2], typically to 2100, while it is widely acknowledged that even if temperatures are stabilised, sea levels are almost certain to continue to rise for many centuries [7][8][9]. Stakeholder workshops carried out with practitioners under the umbrella of PROTECT [10] and literature reviews [11][12] highlight the importance of extending sea-level rise information beyond 2100, to support strategic coastal adaptation and management, land-use planning, and critical infrastructure design.

Recent advancements in long term socio-economic modelling [13][5] now provide projections of global population and GDP at country level to 2300. These have already been applied to long-term risk assessments for other climate sectors [13][5][14].

For this assessment, the global coastline was split into ~29,000 segments, each assigned an extreme tide curve (from the COAST-RP dataset [4]) and a hypsometric curve, generated from a global terrain model [3] and present-day population distribution [2]. The hypsometric curves aggregate the total land-area and population at each elevation, including consideration of hydraulic connectivity to the coastline. This gives the land area and population that would be exposed at a given coastal flood level (up to 20mAMSL) for each coastal segment.

When sea-level scenarios [6] (SSP1-2.6 & SSP2-4.5) and socio-economic data [5] are combined, the human exposure and land area exposure to coastal flood hazard under a chosen extreme tide return period (or the annual average based on the event-exposure curve) is calculated.

This approach facilitates efficient computations, sampling across probabilistic data, and providing robust statistics at a high spatial resolution compared to traditional methods. The outputs at each coastal segment can be aggregated to sub-national, national, or the global scale.

In this analysis, it is found that the median exposure of people to coastal flood hazards increases fivefold to a peak in the early 2200s and subsequently slowly declines to 2300 in both SSPs, despite the continued rise in sea level. For the 80th percentile population exposure grows even more (10- to 11-fold) but then stabilises rather than declines. These results reflect the interplay of sea level and demography with fall in global population in the latter half of the assessment period and are contrary to conventional wisdom. This analysis shows that in addition to sea-level rise, it is important to consider demographic trends when considering coastal futures.

Figure 1. Probabilistic annual average global population exposure to coastal flood hazard

References exceed the word limit so not included

How to cite: Heslop, J., Nicholls, R., Ballesteros Martinez, C., Linke, D., and Hinkel, J.: Global assessment of human exposure to sea-level rise to 2300, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20522, https://doi.org/10.5194/egusphere-egu24-20522, 2024.

EGU24-21315 | Orals | NH9.1

Wildfire Risk Assessment under present and future climate at national scale: a pan european approach 

Farzad Ghasemiazma, Giorgio Meschi, Andrea Trucchia, and Paolo Fiorucci

The authors present a framework designed to model wildfire risk and the future projection of wildfire risk patterns, also in view of climate change scenarios. The adopted modeling framework is inherently multi scale, giving results at national scale, after a data gathering process developed at regional / supranational scale. The risk assessment comprises the computation of susceptibility, hazard, exposures, and damage layers. Machine learning techniques are used to assess the wildfire susceptibility and hazard at regional level, analogously to [1, 2]. To this end, a two-models approach has been adopted. The first model, based on the Random Forest Classifier, is trained at pan-European level to capture the climate variability of the European continent and related fire regimes. Building upon the outcome of this model, a wildfire susceptibility map representative for the historical
conditions at pan-European level is produced and used in input of a second machine learning model, to provide results at national level. The strength of this model lies in using high-resolution downscaled climate data and annual temporal resolution, with the objective of computing a high resolution annual susceptibility map for the specific region. This approach facilitates the generation of annual outcomes for both historical and future conditions, using the climate projections available in the ISIMIP framework. The result of five different climate models and three climate change scenarios have been used to estimate the average annual losses due to wildfires. The wildfire hazard has been evaluated through empirical approaches, building a wildfire hazard classes map combining fuel type/severity maps with wildfire susceptibility. Then, a burning probability is estimated for each hazard class: a statistical analysis on historical wildfires at pan-European level has been performed in order to retrieve the annual relative burned area per hazard class. The method allows to estimate the average annual probability to be affected by a fire given a wildfire event. Several exposed elements were used to estimate the losses ranging from infrastructure to forest and roads: Global Earthquake Model [3] provides a dataset featuring economic values under both present and future conditions across five categories of infrastructures at European level. JRC, OpenStreeMap, and Copernicus provide information on the presence of roads and forests. Empirical vulnerability functions establish a link between severity maps, the presence of exposed elements, and their economic value, leading to the estimation of potential damage maps. The assessment of average annual losses involves coupling spatial information on average annual probability with potential damage maps. This approach allows for the evaluation of average values across various future timeframes associating a variance accounting for both the year to year and climate models’ variability. Results have been produced at national level for several countries characterized by different wildfire regimes, land cover and climate, such as Croatia, Romania and Bulgaria.

How to cite: Ghasemiazma, F., Meschi, G., Trucchia, A., and Fiorucci, P.: Wildfire Risk Assessment under present and future climate at national scale: a pan european approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21315, https://doi.org/10.5194/egusphere-egu24-21315, 2024.

EGU24-226 | ECS | Posters on site | NH9.2

Propagation of climate extremes across global value chains 

Serine Guichoud, Laurent Li, and Patrice Dumas

This paper presents a theoretical frame relying on the graph theory for assessing extreme weather events relative damage to global value chains. 
The approach is defined in three steps: the first part of the paper presents the intuition inspiring the defined model and associated theory , the second part is focused on a scenario analysis declining extreme events relative severity by countries, the third part leverages on the graph theory to translate the damages associated to these events into macro-sectorial value chains disruptions. A numerical application is then run by estimating drought global damages.
We consider damage as a score based on extreme events occurrence, calibrated in this article with historical data. Using the graph theory, we incorporate these damages to a network of countries moving from a stationary state of constant flows before a distribution of extreme events, to a modified state considering the extreme events occurrence. The spread of these production damages is modeled as a contagion applied to a network representing intermediate consumption financial flows, to assess the cumulative effect of a damage to value chains. 

How to cite: Guichoud, S., Li, L., and Dumas, P.: Propagation of climate extremes across global value chains, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-226, https://doi.org/10.5194/egusphere-egu24-226, 2024.

EGU24-681 | ECS | Orals | NH9.2

Windstorm risk assessment in the Netherlands: Evaluation of statistical dependencies between hazard and damage data 

Maria del Socorro Fonseca Cerda, Toon Haer, Hans de Moel, Jeroen Aerts, Wouter Botzen, Elco Koks, and Daan van Ederen

Extreme windstorms pose significant societal and economic challenges, ranking among the costliest natural disasters in Europe. This study addresses the complex task of quantifying windstorm impacts, with a specific focus on the Netherlands. Despite their substantial economic cost, windstorm risks in the Netherlands have been underexplored in dedicated regional studies. Existing large-scale investigations often rely on hazard-loss relationships derived from data from other European countries. We aim to enhance the accuracy of windstorm risk assessment by utilizing not only higher-resolution hazard data but also higher-resolution Dutch damage data. Our methodology involves analyzing high-resolution data to identify hazard variables that best correlate with losses. This is done by leveraging post-disaster loss data from a private Dutch insurance company. In particular, we use the aggregated losses per postal code 4 area, which delivers a nuanced understanding of the spatial distribution of losses. Simultaneously, we account for hazard intensities using the wind climatology data from KNMI North Sea Wind (KNW). This data is derived from 40 years (1979-2019) of ERA-Interim re-analyzed data and downscaled to a higher resolution (2.5 x 2.5 km) tailored specifically for the Netherlands. Through statistical analysis, the study aims to determine the most suitable hazard components for a regional windstorm damage assessment model. This approach aims to move beyond the conventional use of daily maxima wind speed or gust speed by evaluating the appropriateness of hazard variables concerning observed losses. This meticulous integration of proprietary loss records and refined wind climatology enables developing new spatial windstorm hazard maps and a high-resolution windstorm risk database, which provide a solid basis for risk assessment.

How to cite: Fonseca Cerda, M. S., Haer, T., de Moel, H., Aerts, J., Botzen, W., Koks, E., and van Ederen, D.: Windstorm risk assessment in the Netherlands: Evaluation of statistical dependencies between hazard and damage data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-681, https://doi.org/10.5194/egusphere-egu24-681, 2024.

EGU24-3045 | Posters on site | NH9.2

Applying Mobile Phone Data on Seismic Disaster Reduction 

Sheu-Yien Liu and Ming-Wey Huang

To grasp specific population distribution information is crucial for accurate impact assessments and preparedness planning on natural disasters. With the high popularization of mobile phones, it is possible to know the distribution trend of the people movement in different regions. The mobile phone data from Chunghwa Telecom (the telecommunications company with largest market share in Taiwan) displayed in 500m×500m grids gives the spatiotemporal distribution of people around the Taiwan area on the geographic information system (GIS). Combined with immediate reception of earthquake intensity distribution map, not only can the number of people at risk be more accurately estimated, but also the abnormal flow of people can be highlighted in areas, and then provide real-time warning messages. Except for the real-time crowd data, the historical data from one year of 2018, which is converted into weekly crowd data, are also provided for the purpose of seismic disaster scenarios to improve the precision of relief needs by the grid-base earthquake impact assessment technology of TERIA (Taiwan Earthquake Impact Research and Information Application Platform, established by NCDR) for enhancing the disaster resilience against future major earthquakes.

How to cite: Liu, S.-Y. and Huang, M.-W.: Applying Mobile Phone Data on Seismic Disaster Reduction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3045, https://doi.org/10.5194/egusphere-egu24-3045, 2024.

EGU24-3851 | ECS | Posters on site | NH9.2

Development of the Methodology to Identify Potential Modes of Dam Failure and to Estimate Structural Health of Water Management Dams 

Mateja Klun, Žiga Begelj, and Andrej Kryžanowski

Here we present the project activities of an ongoing project aiming at the identification of potential failure modes of dams and the development of the methodology to be applied on water management dams in Slovenia. Water is the most important natural resource for human existence, while changes in hydrological conditions have an impact on the water balance and require innovative approaches in water management. There are currently 68 registered infrastructure facilities in Slovenia, 42 of which meet the criteria of large dams or are subject to a special regime for operational safety as critical infrastructure. According to the Slovenian National Committee for Large Dams the average age of our dams is already more than 45 years.

Objectives of the project proposal, which will last 24 months, are the following: the analysis of the current state of the practice in the field of dam surveillance in Slovenia, provision of a summary document with a set of potential failure mechanisms for each type of dams, and development of a methodology for identifying failure mechanisms and monitoring the condition of dams. Monitoring of dams is regularly carried out in Slovenia, at least in the form of technical monitoring of the structures. However, we must note that professional knowledge of the operational safety of dams has advanced considerably since the time when most of the dams in Slovenia were built. In particular, the understanding of dam safety has changed and is now understood in a broader sense, encompassing the safety of the dam and auxiliary structures under all conditions throughout its life cycle, as well as the safety of the population and the environment in the dams' impact area. The lifetime of dams is very long, and sound structural management improves their structural health of dams and extends their service life.

The main output of the project is the development of the methodology for identification of potential failure modes. The steps of the methodology will also be implemented on at least 3 pilot cases and will be presented to the professional public and to institutions working in the field of dams and dam engineering. The project addresses both the World Declaration on Dam Safety, (Porto, 2019), and the World Declaration Water Storage for Sustainable Development, from (Kyoto, 2012). The authors acknowledge that the research is financially supported by the Slovenian Research and Innovation Agency research project No. V2-2340 and by the Ministry of Natural Resources and Spatial Planning.

How to cite: Klun, M., Begelj, Ž., and Kryžanowski, A.: Development of the Methodology to Identify Potential Modes of Dam Failure and to Estimate Structural Health of Water Management Dams, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3851, https://doi.org/10.5194/egusphere-egu24-3851, 2024.

EGU24-5387 | ECS | Orals | NH9.2 | Highlight

High-resolution Downscaling of Disposable Income in Europe using Open-source Data 

Mehdi Mikou, Améline Vallet, Céline Guivarch, and David Makowski

Poverty maps have been extensively used for identifying populations vulnerable to global changes. The frequency and intensity of extreme events are likely to increase in coming years as a result of climate change. In this context, several studies have hypothesized that the economic and social impact of extreme events depends on income. However, to rigorously test this hypothesis, it is necessary to have income data on a fine spatial scale, compatible with the analysis of extreme climatic events. In order to produce reliable high-resolution income data, we have developed an innovative machine learning framework, based on random forests, that we applied to produce a 1 km-gridded dataset of disposable income for 2015 in Europe. This dataset was generated by downscaling disposable income data available for more than 120,000 administrative units. Our learning framework showed high accuracy levels, and outperformed other existing approaches used in the literature for downscaling income. Using SHAP values, we explored the contribution of the model input factors to income predictions and found that, in addition to geographic inputs (country, latitude, longitude), distance to public transport or nighttime light intensity were key drivers of income predictions. Finally, we illustrated how this new dataset can help identifying poverty areas in Europe. More broadly, this dataset offers an opportunity to explore the relationships between economic inequality and environmental degradation in health, adaptation or urban planning sectors. It can also facilitate the development of future income maps that align with the Shared Socioeconomic Pathways, and ultimately enable the assessment of future climate risks.

How to cite: Mikou, M., Vallet, A., Guivarch, C., and Makowski, D.: High-resolution Downscaling of Disposable Income in Europe using Open-source Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5387, https://doi.org/10.5194/egusphere-egu24-5387, 2024.

EGU24-8752 | ECS | Orals | NH9.2 | Highlight

Identifying global biases in hydro-hazard research by mining the scientific literature 

Lina Stein, S. Karthik Mukkavilli, Birgit M. Pfitzmann, Peter W. J. Staar, Ugur Ozturk, Cesar Berrospi, Thomas Brunschwiler, and Thorsten Wagener

Floods, droughts, and rainfall-induced landslides are hydro-geomorphic hazards that affect millions of people every year. These hazards are therefore heavily researched topics with several hundred thousand articles published. The large number of published articles means identifying existing gaps is a challenge, especially regarding research specific to local risk conditions and impacts. How well does hydro-geomorphic hazard research cover heavily impacted regions, different hydro-climatic processes, or relevant socio-economic aspects? In this work, we use natural language processing to search a database of 100 million abstracts for mentions of floods, droughts, and landslides. We annotate all hazards and location mentions and geolocate each study via Nominatim. We use this information to create global gridded research densities for the three hazards based on all study locations from 293,156 abstracts. We then compare research density to environmental, socio-economic, and disaster impact data. The global distribution of research is heavily influenced by human activity, national wealth, data availability, and population distribution. Countries that have been heavily impacted by hydro-geomorphic hazards in the past have a higher research density. However, this relationship strongly depends on country wealth. In low-income countries 100 times more people need to be affected before a comparable research density to high-income countries is reached. This disparity needs to be addressed to reduce disaster impact and adapt to changing conditions in the future. We here give guidance for which regions and hydro-climatic conditions an increased research focus on hydro-geomorphic hazards is most urgent.

How to cite: Stein, L., Mukkavilli, S. K., Pfitzmann, B. M., Staar, P. W. J., Ozturk, U., Berrospi, C., Brunschwiler, T., and Wagener, T.: Identifying global biases in hydro-hazard research by mining the scientific literature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8752, https://doi.org/10.5194/egusphere-egu24-8752, 2024.

The Central American Dry Corridor (CADC) spans Guatemala, Honduras, El Salvador, Costa Rica, and Nicaragua. Over half of the population in this region is engaged in agricultural activities, with more than 73% of the rural population living in poverty, and 7.1 million people experiencing severe food insecurity. The increasingly frequent droughts exacerbate the challenges faced by agricultural production in this area. Long-term series of agricultural drought mapping can assist agricultural planners in minimizing the impact of drought on production. Based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) spanning from 2001 to 2021, this study will utilize the Vegetation Health Index to map agricultural drought in CADC at monthly, seasonal, and interannual scales. Multi-temporal agricultural drought mapping will reveal the spatiotemporal distribution patterns of agricultural drought in CADC over the past 20 years. Additionally, the study will employ the Mann-Kendall test and Sens' slope estimator to simulate the changing trends of agricultural drought, aiming to identify regions where agricultural drought is worsening.

How to cite: Qiu, J. and Tarolli, P.: Long-term agricultural drought monitoring in the Central America Dry Corridor using Vegetation Health Index, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9901, https://doi.org/10.5194/egusphere-egu24-9901, 2024.

EGU24-10678 | ECS | Orals | NH9.2

Leveraging Multi-Sector Needs Assessments to Assess Dynamic Social Vulnerability: A Methodological Exploration 

Jean-Baptiste Bove, Silvia De Angeli, Lorenzo Massucchielli, and Davide Miozzo

In the context of escalating climate change impacts, conflicts, urbanization, and the complex interplay between ecological, physical, human, and technological systems, this research explores an innovative methodology for the assessment of dynamic social vulnerability for disaster risk assessment and management by exploiting Multi-Sector Needs Assessments (MSNA) data. Current frameworks for assessing social vulnerability frequently exhibit a hazard-specific focus and are not often generalizable because of differences in methodologies or limits in data availability. Moreover, they often fail to incorporate the dynamic nature of vulnerability, and neglect the inclusion of critical context-specific elements. The proposed research addresses these limitations by exploring the innovative application of MSNAs conducted by humanitarian organizations for assessing dynamic social vulnerability. MSNAs, by providing data across various sectors and geospatial scales, offer an underutilized resource for understanding the multi-dimensional and dynamic aspects of vulnerability in crisis-affected contexts. The use of MSNA data, which includes repeated assessments over time and disaggregation by different population groups and geographic levels, presents new opportunities to understand how and why social vulnerability can change over time. This research aims to address the methodological challenges of data accessibility,  standardization, comparability, and representation of socio-economic factors by proposing an innovative way of constructing a social vulnerability index based on MSNA data and indicators that can capture and reflect changes in social vulnerability over time. This approach will be demonstrated through a case study, providing a practical illustration of how dynamic social vulnerability can be effectively measured and analyzed using MSNA data. The research will also highlight how the methodology can be replicated to any other country for which MSNA data is available. By bridging the gap between crisis-driven needs assessments and long-term social vulnerability analysis, this study contributes to more informed, context-specific, and timely strategies in disaster risk management, humanitarian response and policy-making. The findings are expected to enhance the understanding of social vulnerability in varied contexts, highlighting the dynamic nature of vulnerability from a multi-risk and multi-hazard perspective.

How to cite: Bove, J.-B., De Angeli, S., Massucchielli, L., and Miozzo, D.: Leveraging Multi-Sector Needs Assessments to Assess Dynamic Social Vulnerability: A Methodological Exploration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10678, https://doi.org/10.5194/egusphere-egu24-10678, 2024.

EGU24-12391 | ECS | Orals | NH9.2

Developing a micro-scale population exposure model: insights from the Italian context 

Sara Rrokaj, Daniela Molinari, Francesco Ballio, Alice Gallazzi, Stefano Annis, Maria Grazia Badas, Anna Rita Scorzini, and Marco Zazzeri

The increasing impacts of climate change and urbanization underscore the critical importance of micro-scale population data for enhancing natural risk management and emergency preparedness. Access to high resolution population information enables better correlation with the spatial variability of hazards, leading to more accurate damage estimations. However, such data are typically available at macro and meso-scales. In the case of Italy, for example, population data from the National Institute of Statistics (ISTAT) is provided at the census tract scale (meso-scale) for the entire country, despite the uneven distribution of residents within these areas. This study focuses on developing an exposure model for resident population in Italy at a finer spatial resolution than the currently available data. The model uses point data of resident population in the Emilia Romagna region, relating this information to residential building footprint area and volume, as well as land use features. The analysis reveals a notable portion of vacant residential buildings, with approximately 30% of Italian residential buildings reported as uninhabited by ISTAT. The study suggests that incorporating information on the type of residential buildings (main, secondary, or vacant) could significantly enhance the model's performance, especially in tourist-centric cities characterized by a high share of holiday houses. Additionally, the results of this study highlight the need for public entities to invest efforts in the development of a reliable and comprehensive spatial database that includes information on permanently inhabited properties.

How to cite: Rrokaj, S., Molinari, D., Ballio, F., Gallazzi, A., Annis, S., Badas, M. G., Scorzini, A. R., and Zazzeri, M.: Developing a micro-scale population exposure model: insights from the Italian context, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12391, https://doi.org/10.5194/egusphere-egu24-12391, 2024.

EGU24-12963 | ECS | Orals | NH9.2

Systemic human-biosphere-atmosphere monitoring and diagnostics 

Wantong Li, Gregory Duveiller, Fabian Gans, Dorothea Frank, and Markus Reichstein

Here we propose a planetary health diagnostic framework, which aims to track, understand, and characterize the Earth system during the onset and progression of both chronic change (such as climate change) and abrupt disruptions (stemming from climate extremes and socio-economic shocks). However, monitoring a single component of the Earth system to guide policy, but ignoring other essential components, could lead to misleading diagnostics and maladaptation. To gain insights into the integration of climate, biosphere, and society, we apply an interactive dimensionality reduction to the annual variability of multi-stream global data from 2003-2022, including data representing the biosphere and climate combined with national socio-economic indicators.

We find that the interactions between biosphere, atmosphere and socio-economy can be captured by three principal axes, which cumulatively explain 17.3%, 22.8% and 24.5% of the variability condensed by non-interactive dimensionality reduction in each individual domain, respectively. First principal components are related to long-term trends in global warming, land surface dimming, and socio-technical development, while the second and third components are related to changes of other processes under climate and biospheric extremes and socioeconomic shocks. These processes include vegetation dynamics, land surface and atmospheric water demand, life and environmental inequality. We find distinct trajectories across countries with the most distinct cluster is Middle East and North Africa that exhibit climate extremes in 2010 and 2016, socio-financial shocks between 2010-2012 and COVID-19 in 2020. This study advocates for a data-driven paradigm to jointly monitor the recent trajectories of the biosphere, atmosphere, and society that could provide a better understanding and early warning of the state of the Earth system for human well-being.

How to cite: Li, W., Duveiller, G., Gans, F., Frank, D., and Reichstein, M.: Systemic human-biosphere-atmosphere monitoring and diagnostics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12963, https://doi.org/10.5194/egusphere-egu24-12963, 2024.

EGU24-13968 | Posters virtual | NH9.2

Flood Severity, Socio-Economic Impacts, and Elevation Strategy Effectiveness in a Subset of Louisiana Post-Hurricanes Katrina and Rita 

Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland, and Fuad Hasan

FEMA's Hazard Mitigation Grant Program (HMGP) assisted survivors of Hurricanes Katrina and Rita, necessitating a 25% homeowner contribution for post-disaster home elevation. The federal Community Development Block Grant Disaster Recovery (CDBG-DR) program allocated $13.4 billion to Louisiana, offering $30K grants per home, aligning with HMGP needs. This study focused on elevated residential homes in a subset of Louisiana's housing data, aiming to understand the intersection of flood risk when disaggregated by frequency, vulnerable populations, and mitigation costs.

The analysis investigating the correlation between flood frequency/severity and variables such as race and ethnicity, and socioeconomic status, exploring their interconnections. Subsequently, we explored how flood risk changed both pre- and post-implementation of elevation strategies across various return periods, aiming to determine the proportional attribution of the total AAL to these different periods. Additionally, it examined the comparative flood risk before and after elevation strategies across diverse socioeconomic statuses. Finally, it analyzed the absolute benefits of elevation strategies, particularly the avoided AAL, compared with investment values and socioeconomic statuses.

The result of this study indicates that Poverty levels remain consistent across different return periods, a notable increase in Non-white population percentages with longer return periods, and a peak in Renters' percentage at floods with a return period of ≥200 years. It’s demonstrated that a substantial percentage of the total AAL is attributed to less frequent but more severe events—those occurring with return periods between 100 and 500 years, as well as those with return periods greater than 500-year. The results show inconsistencies in the Avoided AAL values across different investment levels suggest that the relationship between investment in elevation costs and Avoided AAL is not directly proportional.

The study results provide multifaceted insights, aiding in the identification of vulnerable communities and offering guidance for resource allocation decisions, and demonstrating the impact of elevation strategies. The economic analysis enhances understanding of federal mitigation investments' cost-effectiveness across diverse socio-economic statuses.

 

How to cite: Al Assi, A., Mostafiz, R. B., Friedland, C. J., and Hasan, F.: Flood Severity, Socio-Economic Impacts, and Elevation Strategy Effectiveness in a Subset of Louisiana Post-Hurricanes Katrina and Rita, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13968, https://doi.org/10.5194/egusphere-egu24-13968, 2024.

EGU24-14637 | Posters on site | NH9.2

A systems approach for holistic resilience building 

Alison Sneddon

Resilience for Social Systems (R4S) is an approach to analyse the resilience of socioeconomic systems. Societies are made up of socio-economic systems which service the needs of their populations, and addressing recurrent crises and effectively building resilience requires an integrated systems approach. Where these systems are fragile and large portions of the population are socially or economically marginalized, communities are highly susceptible to external shocks and stresses; coordination among stakeholders to strengthen these systems will ultimately improve resilience and lead to resilient and inclusive development.

The R4S approach to resilience helps to understand how various system components (stakeholders, resources, regulations) interact and interconnect, as well as assessing the potential impacts from risk scenarios. In other words, when applying the R4S Approach to build resilience, the user can anticipate better how natural hazards can trigger economic shocks, how conflicts can leave people more exposed to additional shocks or stresses (e.g., an outbreak of cholera can be triggered when water, sanitation and hygiene systems are destroyed or become inaccessible), and how long-term stresses such as environmental degradation can lower agricultural productivity, weakening food security and income levels, and impacting a household’s ability to pay for health care or education.

Understanding these dynamics is critical to deliver better programming that addresses root causes of constraints rather than symptoms alone. The R4S Approach is based on best practice in Systems Thinking, Network Theory, Scenario Thinking, Social and Behaviour Change, Inclusion and Resilience approaches and provides a logical step by step process for assessing resilience of socio-economic systems.

This presentation will provide an overview of the R4S, the innovations in the assessment of complex and interlinked vulnerabilities it provides, and practical examples drawn from GOAL’s experience of conducting the assessment and implementing resilience-building strategies based on the needs and opportunities identified.

How to cite: Sneddon, A.: A systems approach for holistic resilience building, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14637, https://doi.org/10.5194/egusphere-egu24-14637, 2024.

EGU24-15543 | ECS | Orals | NH9.2 | Highlight

Collection, Standardization and Attribution of Robust Disaster Event Information — A Demonstrator of a National Event-Based Loss and Damage Database in Austria 

Dominik Imgrüth, Katharina Enigl, Matthias Themessl, and Stefan Kienberger

Loss and damage databases are essential tools for disaster risk management in order to make informed decisions. However, even in data-rich countries such as Austria, there has been no consistent and curated multi-hazard database to date. Based on the demands of the United Nations, the European Union and national requirements for monitoring and managing the effects of disasters, the CESARE project (funded by KIRAS/FFG; project end 02/2022) designed and developed a demonstrator for a consistent national event-based damage database. This demonstrator enables event identification, loss and damage monitoring and assessment according to international standards and offers the possibility of disaster forensics. The CESARE system is based on existing data collected by administrations as well as federal authorities which are consolidated according to a common data model. By this means, the primary data and the data collection procedures are not affected and a sustainable exchange of data is made possible. The demonstrator currently focuses on two Austrian federal states, three hazard types - floods, storms and mass movements - and the period between 2005 and 2018. By analysing over 140,000 individual event descriptions, we demonstrated that - despite some limitations in retrospective data harmonisation - the implementation of an event-based national damage database is feasible and offers considerable added value compared to the use of individual data records. The demonstrator will in future substantially support quantitative analysis in the context of the national risk assessment, national UNDRR-Sendai monitoring and disaster risk management at federal level by providing the best possible harmonised damage information, tailored indicators and statistics as well as maps on the impact of hazards at municipal level. The CESARE system is currently being rolled out operationally as well as extended to other hazard categories and the remaining provinces of Austria. With its final implementation, CESARE will provide the most complete event and damage database in Austria.

How to cite: Imgrüth, D., Enigl, K., Themessl, M., and Kienberger, S.: Collection, Standardization and Attribution of Robust Disaster Event Information — A Demonstrator of a National Event-Based Loss and Damage Database in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15543, https://doi.org/10.5194/egusphere-egu24-15543, 2024.

EGU24-18132 | Posters on site | NH9.2

Revealing Environmental Threats: Harmonizing Indigenous Narratives with Geomorphic Hazard Thematic Maps for Community Awareness 

Sheng-Chi Lin, Su-Min Shen, Sendo Wang, Mu-Ti Yua, Si-Chin Lin, and Chih-Hsin Chang

From the perspective of natural disaster prevention, larger-scale and higher-intensity geomorphic events often have longer recurrence intervals. The impact of these events on a region is frequently underestimated unless residents have experienced them firsthand. Consequently, the success of promoting self-reliant disaster-prepared communities by the government heavily relies on the experiences of the affected population. In this context, our study integrates government cartographic data and interprets the geomorphic evidence preserved in the landscape.

We conducted in-depth interviews with elders from indigenous tribes, leveraging their rich storytelling tradition and local residents' experiences to collect observations of environmental changes, past disaster experiences, and ancestral stories. The spirit of storytelling is incorporated into the map user manual, emphasizing a place-based approach. Using the devastating impact of Typhoon Morakot in 2009 on the Tjalja'avus Tribe in southern Taiwan as a case study, we produced a geomorphological hazard thematic map of the tribe. This map utilized national environmental mapping imagery, including landslide records, large-scale landslide-prone areas, potential debris flow streams, and high-resolution digital elevation models created by unmanned aerial vehicles LiDAR.

Through a combination of multi-temporal data visuals, we highlighted recent (within the last five years) highly active landslide locations, emphasizing dynamic geomorphic features. In the context of environmental awareness and risk communication between the government and local communities, we structured the map user manual to revolve around the narrative axis of visible terrain features in the tribal landscape and experiences or stories related to soil and rock disasters. This approach allows individuals to comprehend the geomorphic influences leading to disasters in their communities, facilitating collaboration between the government and community builders. Ultimately, our initiative aims to achieve environmental management and disaster prevention goals within indigenous communities.

How to cite: Lin, S.-C., Shen, S.-M., Wang, S., Yua, M.-T., Lin, S.-C., and Chang, C.-H.: Revealing Environmental Threats: Harmonizing Indigenous Narratives with Geomorphic Hazard Thematic Maps for Community Awareness, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18132, https://doi.org/10.5194/egusphere-egu24-18132, 2024.

EGU24-18238 | ECS | Orals | NH9.2 | Highlight

Risk Tipping Points in an Interconnected World 

Caitlyn Eberle, Jack O'Connor, Liliana Narvaez, Melisa Mena-Benavides, and Zita Sebesvari

The convergence of multiple societal and ecological challenges threatens to push us into an uncertain, risky future. Our critical life-supporting systems, such as the human climate niche, hydrological cycles, natural ecosystems, food production, knowledge systems, and risk management tools, are all fundamentally challenged. While these systems have been continually reshaped throughout human history, the speed of change and the simultaneous changes occurring today are unprecedented. Our research shows how we are teetering on the precipice of multiple tipping points that can trigger abrupt and often irreversible changes to the systems we rely upon.

Our research provides a conceptual definition of risk tipping points as a new way to think about the risks we face and illustrates examples of how the concept can be applied. While climate tipping points refer to tipping elements of Earth systems, such as hydrological cycles or climate patterns, risk tipping points concern the socioecological systems dependent on them and when they stop being able to buffer risk and provide their expected functions. We discuss six prominent examples of risks facing these socioecological systems, such as groundwater depletion and space debris, and identify conceptual tipping points for each of them.

Furthermore, our research discusses each of these risk tipping points within a context of interconnectivity. We analyze how similar human behaviors and values are at the root of multiple risk tipping points, putting pressure on multiple systems simultaneously. Since none of these systems are isolated from each other, when one system passes a risk tipping point, it increases the overall risk across systems and may actually accelerate tipping in another system. Feedback loops between systems can amplify the impacts of risks and can create self-reinforcing dynamics that increase the speed of change. The effects of these manifesting risks may accumulate over time, causing multiple risk tipping points to overlap and increase risk even further.

Finally, our research demonstrates that any attempt to reduce risk in these systems must acknowledge and understand these underlying pressures and their interconnectivity. Actions that affect one system will likely have consequences on another, so integrated and informed solutions are necessary to avoid negative consequences. This also means that interconnectivity can be used as an advantage through solutions that provide co-benefits to address risk tipping points in multiple systems at once. Interconnected risks require interconnected solutions to ensure a safe and sustainable future for all.

How to cite: Eberle, C., O'Connor, J., Narvaez, L., Mena-Benavides, M., and Sebesvari, Z.: Risk Tipping Points in an Interconnected World, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18238, https://doi.org/10.5194/egusphere-egu24-18238, 2024.

EGU24-18933 | ECS | Posters on site | NH9.2

A holistic examination of Disaster Risk Management in the context of volcanic risk in the Canary Islands 

María García-Vaquero, Sara García-González, Noemi Padrón-Fumero, Julia Crummy, Tamara Febles-Arévalo, and Jaime Díaz_Pacheco

Understanding the complexity of past chain events in depth and learning from them to improve
decision-making in a dynamic context can be challenging. Although efforts have been made to
address these challenges, further research is needed. Storylines have proven to be a valuable
qualitative tool not only for describing multi-hazard scenarios, understanding the system and
the interrelationships between different elements, but also for improving resilience by taking
into account lessons learned throughout the process.


The 2021 La Palma volcanic eruption, with its enduring aftermath characterised by atmospheric
gas emissions in one of the island's prime tourist locales, exemplifies the intricate challenges in
decision-making for planning, procedural execution, and organisational management. This
event highlights the extensive and profound impacts of such dynamic risks, underscoring the
need for adaptable and robust strategies in risk management and response. Our study aims to
provide a comprehensive understanding of the whole volcanic disaster in detail by integrating
the different dimensions (multi-hazard, multi-risk and systemic impacts) into the disaster risk
reduction cycle (prevention and preparedness, response and recovery). This approach provides
a holistic and proactive approach and allows for an assessment of the impact and
consequences of the decision making process in the Canary Islands at each stage over time. For
this purpose, a 20-year timeline will be used, starting in 2004 when the first seismic swarm
indicated a possible volcanic eruption in the island of Tenerife.


This research uncovers a significant shortfall in risk planning across all stages of the disaster
reduction cycle on the islands, noting a disproportionate emphasis on administrative
coordination during emergencies. The absence of preemptive measures in land-use planning,
especially in areas highly vulnerable to exposure, exacerbates the complexity of post-eruption
recovery. By thoroughly examining the decision-making processes, planning strategies, and
organisational procedures, this study aims to distil key lessons from recent experiences. Such
an endeavour enhances our comprehension of the complex interplay between decisions and
risks, providing critical insights for bolstering resilience against volcanic disasters.

How to cite: García-Vaquero, M., García-González, S., Padrón-Fumero, N., Crummy, J., Febles-Arévalo, T., and Díaz_Pacheco, J.: A holistic examination of Disaster Risk Management in the context of volcanic risk in the Canary Islands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18933, https://doi.org/10.5194/egusphere-egu24-18933, 2024.

EGU24-19054 | ECS | Posters on site | NH9.2

Agricultural Drought Case Study in South Korea: Selection of Rural Specialization Districts based on Principal Component Analysis 

Hyochan Kim, Hoyoung Cha, Jongjin Baik, Kihong Park, and Changhyun Jun

Recently, the frequency and severity of droughts have gradually increased due to extreme weather events and global warming. As the demand for drought management increases, field surveys and water supply are actively conducted in many countries. Given that such drought assessment and support require the consumption of labor and financial resources, the prioritization of essential agricultural areas has become a major topic for efficient decision-making in drought relief. In this study, we proposed a Principal Component Analysis (PCA) for selecting rural specialization districts across the 162 administrative regions of South Korea. Additionally, we aimed to investigate real cases of agricultural drought occurred in these regions by utilizing the survey of water supply measures derived from Ministry of Agriculture, Food and Rural Affairs. The research data comprised seven agricultural specialization factors, exemplified by agricultural workforce and infrastructure. First, we implemented singular decomposition method included in PCA process to represent the comprehensive trends of the agricultural specialization factors with maximum reflection. High value of principal component scores (PCS) estimated from PCA was interpreted as regions with high agricultural relevance. Lastly, the PCS were classified into different levels, defining top-ranking regions as rural specialization districts. Based on agricultural drought case studies from 2018 to 2021, it is expected that finding relative damage-prone areas and establishing appropriate drought responses will be feasible.

Keywords: Principal Component Analysis, Rural Specialization Districts, Agricultural Specialization Factors, Principal Components Score

Acknowledgement

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00250239) and this research was supported by Korea Environment Industry & Technology Institute (KEITI) through Water Management Innovation Program for Drought (RS-2022-KE002032) funded by Korea Ministry of Environment.

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No.NRF-2022R1A4A3032838).

How to cite: Kim, H., Cha, H., Baik, J., Park, K., and Jun, C.: Agricultural Drought Case Study in South Korea: Selection of Rural Specialization Districts based on Principal Component Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19054, https://doi.org/10.5194/egusphere-egu24-19054, 2024.

EGU24-19940 * | ECS | Orals | NH9.2 | Highlight

A global database of natural hazards impacts reported in the scientific literature 

Taís Maria Nunes Carvalho, Jakob Zscheischler, Christian Kuhlicke, and Mariana Madruga de Brito

The increased frequency and magnitude of natural hazards might significantly increase social, economic, and health impacts on society in the next decades. Existing studies and databases of natural hazard impacts have several limitations, such as (1) a low level of detail on how people were affected; (2) an underestimation of the impacts; (3) a limited geographical range; and (4) a lack of information on the source of the data. However, scientific publications, reports, and handbooks compose a large data repository that can provide valuable and trustworthy information on natural hazards. We are building a global database on the impacts of natural hazards that have been documented since 1950 in the scientific literature. We mapped global research on climatological, hydrological, and meteorological extremes, such as heatwaves and floods. We retrieved over 40 thousand full-text open-access papers from ScienceDirect and Pubmed. Documents were coded according to (i) relevance: if the study describes impacts from a natural hazard, (ii) hazard class: single or multiple hazards, and (iii) event assessment: specific or multiple climate-related events. A randomly selected sample of the documents was manually labeled and a classification model was trained to classify the remaining papers. We further developed an annotation scheme for marking information on climate-related hazards in scientific publications, such as the date and location of hazard and their impacts. The inter-annotator agreement analysis shows the complexity of this task and the high annotation quality in our corpus. This work fills a critical gap in information extraction tasks within the natural hazards research domain, providing a robust foundation for future studies and analysis.

How to cite: Nunes Carvalho, T. M., Zscheischler, J., Kuhlicke, C., and Madruga de Brito, M.: A global database of natural hazards impacts reported in the scientific literature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19940, https://doi.org/10.5194/egusphere-egu24-19940, 2024.

Landslides cause severe impacts on society, infrastructure, and the environment globally, and their occurrence in some regions is expected to rise due to climate change. Although the cumulative impacts of landslides do not reach the level of earthquakes or floods, their disperse occurrence in space and difficult prediction pose a fundamental challenge for landslide disaster risk reduction effort. Clearly, accurate information is needed both for understanding spatiotemporal occurrence of landslides and their social impacts and responses held by societies. Documentary data are among the key sources that enable compilation of regional landslide databases, allow to quantify the landslide impacts and describe both quantitatively and qualitatively causal chains leading to increased landslide risk and the societal responses to landslide events. In this respect, the documentary data fill the time gap between the landslide occurrence in the past environments studied by proxy data, and the present-day landslides, for which different monitoring and mapping techniques may be used. Over the last decades, important progress has been made in employing various documentary data for landslide research, and extending empirical evidence about advantages and limitations is available thanks to case studies from different environmental and institutional settings. The synthesis of this progress that would guide further research is missing though. The overall goal of this paper is to broaden the perspective on the use of documentary data in historical landslide research, which has so far too much concentrated around the landslide inventories. To do so, we present a scoping literature review with three main objectives. First, we present a classification of both quantitative and qualitative approaches and related research questions in historical landslide research, linking them to key challenges in landslide disaster risk reduction. Second, we review the types and content of available documentary data sources with special attention paid to sources that have been underresearched so far. Finally, we review the quantitative and qualitative methods used to analyse the content of documentary data. While doing so, we draw also from comparative evidence in historical climatology and hydrology in order to point to methods that may hold a potential, but have not been validated in landslide research yet. The paper concludes with identifying challenges and pathways for future research.  

How to cite: Raška, P.: Recent progress in the use of documentary data in landslide research: a review of approaches, sources, and methods , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20289, https://doi.org/10.5194/egusphere-egu24-20289, 2024.

EGU24-188 | ECS | Posters virtual | NH9.3

Resilience for Landslide Geohazards and Promoting Strategies in the Three Gorges Reservoir Area 

Yuanyue Huang, Haixiang Guo, and Jing Yu

Resilience is increasingly used as a concept for understanding natural disaster systems. Some countries have developed resilient city plans based on theoretical research and applied practice. Landslide is one of the most frequent geohazards in the Three Gorges Reservoir Area (TGRA). However, it is difficult to measure local disaster resilience, because of the special geographical location. Current approaches to disaster resilience evaluation are usually limited either by the qualitative method or properties of different disaster. Therefore, there is a great need to explore effective disaster resilience measurement methodologies. In this study, we developed an indicator system to evaluate landslides’ disaster resilience in the TGRE at the county level. It includes two properties of inherent geological stress and external social response, which are summarized into physical stress (Ps) and social forces (Sf). The evaluated disaster resilience can be simulated for promoting strategies with fuzzy cognitive map (FCM). The results show that: (1) The overall disaster resilience in the Three Gorges Reservoir Area was relatively low. (2) The resilience of the TGRA has spatial auto-correlation, that is, the areas with similar resilience are gathered in geographical location. (3) Proper policy guideline is essential to promote the disaster resilience. Policy promotes the system from all aspects in the TGRA.

How to cite: Huang, Y., Guo, H., and Yu, J.: Resilience for Landslide Geohazards and Promoting Strategies in the Three Gorges Reservoir Area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-188, https://doi.org/10.5194/egusphere-egu24-188, 2024.

EGU24-1179 | ECS | Posters on site | NH9.3 | Highlight

A Multi-dimensional Framework for Assessing Disaster Recovery Pathways: Lessons and Experiences from Germany and Nigeria  

Olasunkanmi Okunola and Saskia Werners

The recent increase in the frequency of extreme events worldwide highlights the urgent need for comprehensive and coordinated efforts to achieve sustainable recovery and resilience. However, the recovery process following such events has often been prolonged and uneven, and it is frequently overlooked in global disaster management policies. This study aims to address this gap by providing a comprehensive assessment of disaster recovery pathways after extreme flood events, by developing a multidimensional framework.

The research questions guiding this study are: What are the key elements of disaster recovery? What factors act as barriers or facilitators to recovery pathways after disasters? How do these factors contribute to building back better? To answer these questions, the study combines conceptual and empirical insights, including a literature review and an assessment of recovery pathways from recent extreme flood events in Germany and Nigeria.

A multi-methods approach was utilized, encompassing in-depth interviews with representatives from government, NGOs, the private sector, community members, and disaster recovery experts. A total of thirty-eight in-depth interviews were conducted with stakeholders from both countries. Additionally, grey literature and policy documents were analyzed. Qualitative content analysis was employed to analyze the data derived from the in-depth interviews and policy documents.

The findings highlight the significant role of relief organizations in driving recovery efforts, with a particular focus on humanitarian aspects. Moreover, sustainable changes have been observed, such as the implementation of communal heating systems and the use of sustainable materials in building reconstruction. Religious organizations have played a crucial role in providing social and psychological support during the recovery process.

Despite these positive developments, the study underscores a lack of concerted efforts to truly "build back better" during the recovery process, primarily due to political, financial, and institutional constraints. This observation holds across different cases, including the Ahr and Erftstadt in Germany and Lagos in Nigeria. These themes have been explored within the broader scope of the Sendai Framework for Disaster Risk Reduction 2015 - 2030.

How to cite: Okunola, O. and Werners, S.: A Multi-dimensional Framework for Assessing Disaster Recovery Pathways: Lessons and Experiences from Germany and Nigeria , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1179, https://doi.org/10.5194/egusphere-egu24-1179, 2024.

Despite traditional measures to prevent disasters, climate change and urbanization increase flood risk. Thus, flood resilience has attracted increased global concern. Understanding the commonalities and differences between flood resilience and risk is arguably important for flood risk reduction. However, these factors have been seldom reported in previous studies, and discussions on the role of flood resilience in flood risk analysis, assessment, and management are lacking. In this study, the association between flood resilience and risk is discussed using a case study in the Pearl River Delta. Flood resilience is quantified using a pressure-state-response (PSR) model, while flood risk is assessed based on the hazard-vulnerability framework and the extension catastrophe progression method. The implications of considering flood resilience in flood risk analysis, assessment, and management are proposed. The results suggest that the overall flood resilience (risk) in the study area is greater (lower) than that in the highly urbanized areas, and areas with low (high) flood resilience (risk) are mainly concentrated within the highly urbanized areas. Indices extracted from human society and highly related to human activities have the same attributes in both frameworks, while indices associated with climate and geography contribute to the two con- cepts differently. Flood resilience supplements the concept of flood risk, and can be incorporated into risk assessment as an index. Moreover, pre-disruption (post-disaster) measures should follow flood risk (resilience) assessment, and strategies that foster flood resilience should be included in flood risk management. This study provides references for flood resilience improvement and risk mitigation.

How to cite: Zheng, J. and Huang, G.: Towards flood risk reduction: Commonalities and differences between urban flood resilience and risk based on a case study in the Pearl River Delta, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2259, https://doi.org/10.5194/egusphere-egu24-2259, 2024.

EGU24-2987 | ECS | Posters virtual | NH9.3

Community resilience in China in the context of disaster management 

Jie Liu and Alexander Los

In recent years, the frequent occurrence of natural disasters due to global climate change has brought devastating impacts on many countries’ economies, societies, resources, and environment. How decision makers and practitioners respond before, during, and after a disaster occurs is critical to reducing disaster impacts, restoring system functionality, and improving the adaptive capacity for future events, that is, enhancing CR. Currently, there is a lack of empirical data and process-based approaches to assess the dynamic characteristics of CR and to understand what contributes to CR evolution during the disaster management process (i.e., early warning, emergency response, recovery and adaptation). This research is based on the 7.20 heavy rainstorms that happened in Zhengzhou City. To quantify CR, a Dynamic Community Resilience Assessment Framework (DCRAF) is firstly developed. Then, the disaster management meta-network (DMMN), hazard evolution, and disaster management background are identified as the influencing factors of the dynamics of CR. In the next stage, an analytical model is built to explore the quantitative relationship between the dynamics of CR with its influencing factors, and based on this, propose CR enhancement strategies for different phases of future events. Furthermore, the analytical model is expected to have the ability for CR prediction, whereby decision-makers could adjust actions accordingly to mitigate disaster impacts and recover quickly. This presentation will (1) explain the indicators of the DCRAF in the infrastructure domain (including communication, transportation, water, power, municipal infrastructure, and protection works) and the approach to quantify and integrate them to get CR evolutions; (2) use the empirical data to explain how the DMMN, hazard evolution, and disaster management background influence CR at different stages of disaster management; (3) elaborate on the structure of the analytical model, the approach of extracting CR enhancement strategies, and the approach of CR prediction.

How to cite: Liu, J. and Los, A.: Community resilience in China in the context of disaster management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2987, https://doi.org/10.5194/egusphere-egu24-2987, 2024.

EGU24-3895 | ECS | Orals | NH9.3

The Multiple Resilience Dividends Framework: Rethinking Adaptation Decision-Making as a Transformative Approach for Sustainable Development 

Oscar Higuera Roa, Michaela Bachmann, Reinhard Mechler, and Robert Sakic Trogrlic

Climate Change Adaptation (CCA) is crucial for the sustainable development of communities, sectors, and regions as the risks and impacts of climate-related disasters continue to increase. Informed decision-making is essential for effective CCA, but building its business case is challenging, especially when decision-makers have to deal with competing priorities on limited budgets. Accordingly, decision-makers seek innovative ways to assess and prioritize adaptation options to make CCA more appealing as an investment.

The "resilience dividend" is a key concept in the literature, referring to the net benefits of investing in resilience, even in the absence of a climate-related disaster. It evaluates the differential impact of CCA measures, considering benefits, co-benefits, costs, and co-harms. Aligned with this concept, the Multiple Resilience Dividend (MRD) approach interprets resilience as the system's capacity to achieve development goals while managing climate risks proactively. It departs from the conventional "bouncing back" understanding and adopts a "bouncing forward" perspective, offering a holistic view of CCA benefits beyond disaster risk management. 

In this session, we present a framework incorporating the MRD approach into the decision-making, aiming to enhance the impact of adaptation decisions and support the case for resilience investment. Developed in three stages, the framework is built upon (i) findings from the literature related to resilience dividends, co-benefits assessment, and adaptation decision-making, (ii) Systems Thinking, and (iii) multi-disciplinary expert feedback.

The MRD framework is adaptable to varying degrees of local capabilities and context-specificities, enabling a systematic and flexible approach to analyzing the wide impact of adaptation measures, including benefits, synergies, adverse effects, and trade-offs. By doing that, it offers decision-makers a nuanced understanding of the effectiveness and performance of adaptation measures in line with local conditions and priorities. 

Under the MRD framework, adaptation responses can deliver multiple benefits in a continuum, explained by three aspects: (1) benefits that unfold at different periods [realization time], (2) intervention benefits cascade across sectors, scales, and space [interconnectivity], and (3) a benefit is valued differently depending on the receptor [receptor-specificity]. The framework considers adaptation responses as interventions that impact various sectors in different domains (e.g., social, economic, cultural, environmental, institutional, political, and technological). For example, an adaptation measure can improve the quality of life, foster energy, food and water security, support ecosystem functioning and health, or have other benefits that extend beyond the targeted system or community. This means that the MRD framework considers adaptation responses as a cross-cutting developmental aspect going beyond the scope of disaster risk management and reframes CCA investments as drivers of progress across the system (e.g., region, city, sector). Thus allowing decision-makers to identify adaptation options that build systemic resilience to climate change more effectively by encouraging cross-sectoral, long-term, and transformational adaptation processes. 

As part of the Pathways2Resilience program, which will be deployed across 100 European regions over the next 4 years, the MRD Framework intends to shift the narrative in the CCA field from problem-centred to opportunities-oriented, supporting decision-makers in planning adaptation strategies with more positive, sustainable, and long-lasting impacts.

How to cite: Higuera Roa, O., Bachmann, M., Mechler, R., and Sakic Trogrlic, R.: The Multiple Resilience Dividends Framework: Rethinking Adaptation Decision-Making as a Transformative Approach for Sustainable Development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3895, https://doi.org/10.5194/egusphere-egu24-3895, 2024.

EGU24-4099 | ECS | Posters on site | NH9.3

Comparing the distribution and development of Urban Green Spaces in the two Vietnamese delta cities Hanoi and Ho Chi Minh City 

Leon Scheiber, Vera Zühlsdorff, Ngo Than Son, Nong Huu Duong, Nguyen Hong Quan, Matthias Garschagen, and Andrea Reimuth

Promoting public access to Urban Green Spaces is a central objective in sustainable city planning. Urban Green Spaces can play a vital role in enhancing various aspects of public life, including human recreation, local climate regulation and rainwater infiltration. However, in most metropolitan areas, especially in developing countries and emerging economies, Urban Green Spaces face competition with strong economic interests leading to their deterioration over the last decades. Our study critically examines this assumption for two Vietnamese delta cities, namely Hanoi and Ho Chi Minh City. In particular, we use multi-spectral satellite imagery from the Sentinel-2 mission to create seasonal maps of the Normalized Difference Vegetation Index in order to estimate the local proportion of densely vegetated areas. By blending these maps with population data from the National Census of 2019, we determine the spatial distribution of Urban Green Spaces per capita in both cities and interpret these findings against the background of recent spatial planning efforts. Spanning seven dry seasons in total (Dec 2016 – Jan 2023), the satellite data furthermore allow us to compare the temporal development of Urban Green Spaces and tentatively extrapolate these trends into the near future. Our preliminary results suggest that districts with particularly high percentages of Urban Green Spaces in Hanoi generally encompass the historic city core, while the greenest districts of HCMC are located in the newly established city-within-city Thu Duc east of the Saigon River. Moreover, the Urban Green Space per capita in Hanoi is nearly twice as high as in Ho Chi Minh City amounting to 11.6 and 6.8 square meters, respectively. Judging from the NDVI time series, these figures seem relatively stable with variations in the order of 1 square kilometre per year. Yet, ongoing urbanization trends will put stress on both the proportion of Urban Green Spaces and the number of inhabitants benefitting. Even though the stability of the Normalized Difference Vegetation Index is subjected to atmospheric and climatic boundary conditions, we can report that measurement-inherent variations in our study only accounted for standard deviations below 0.1 at selected locations with constant land cover. Consequently, the applied methodology is considered a valid instrument for documenting spatial distributions and temporal developments in order to support and advocate the advantages of Urban Green Spaces in future spatial planning.

How to cite: Scheiber, L., Zühlsdorff, V., Son, N. T., Duong, N. H., Quan, N. H., Garschagen, M., and Reimuth, A.: Comparing the distribution and development of Urban Green Spaces in the two Vietnamese delta cities Hanoi and Ho Chi Minh City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4099, https://doi.org/10.5194/egusphere-egu24-4099, 2024.

EGU24-6568 | ECS | Posters on site | NH9.3

Adapting coastal airports to climate change challenges 

Asimina Voskaki, Thomas Budd, and Keith Mason

Rising sea levels and changes in the frequency and intensity of storms can have physical, operational and business implications for coastal airports worldwide. Employing appropriate risk reduction measures is essential, and airports demonstrating higher adaptive capacity are generally expected to be better equipped to respond and recover quickly after a disruptive event. While a growing body of research investigates the impact of rising sea levels on coastal infrastructure systems, limited studies discuss how coastal airports can measure their adaptive performance considering the main climate extremes occurring in the coastal zone. This study presents an approach to measure coastal airports' adaptability to hazards such as rising sea levels, extreme precipitation, and storminess. The developed framework uses indicators identified in adaptation and risk assessment literature to reflect prevention, response and institutional actions to reduce climate risk. By examining the key challenges coastal airports face and best-applied practices to respond, this contribution provides insights into the drivers for action, the efficiency of existing practices to address climate challenges and qualities that coastal airports need to demonstrate to strengthen their capacity and shift towards a more informed risk management culture. 

How to cite: Voskaki, A., Budd, T., and Mason, K.: Adapting coastal airports to climate change challenges, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6568, https://doi.org/10.5194/egusphere-egu24-6568, 2024.

EGU24-7358 | Orals | NH9.3 | Highlight

Flood Risk Governance in Greece in the Aftermath of Storm Daniel 

Ioannis Kougkoulos, Stella Apostolaki, Simon J. Cook, and Miltiadis D. Lytras

In this study, we assess the impacts of Storm Daniel, which emerged as a low-pressure system on September 4, 2023, and dissipated by September 12. This storm significantly impacted Libya, Greece, Bulgaria, Turkey, Egypt, and Israel, causing widespread flooding. Greece was particularly affected, with 17 deaths and over two billion euros in damages, making it the country's most expensive storm. On September 5, Zagora in Mount Pelion, Greece, recorded an unprecedented 754 mm of rainfall in a single day, leading to extensive flooding in central Greece. A prosecutor's investigation into local authorities' preventive measures followed, aiming to evaluate if further actions could have lessened the storm's effects. This event highlights the need to consider the effects of global warming, which is expected to intensify the hydrological cycle, increasing the likelihood of severe precipitation events and flooding risks. Our paper has two objectives: (a) to analyze the response of the existing Greek Flood Risk Governance (FRG) framework to Storm Daniel, and (b) to recommend improvements of the Greek FRG framework using Multi-Criteria Decision Analysis (MCDA). The initial phase involves analyzing documents related to the flood risk governance cycle, including prevention mapping, emergency response protocols, and national natural disaster insurance frameworks. This analysis uncovers several shortcomings, notably a lack of effective government action in disaster prevention, despite the existence of Flood Risk Management (FRM) plans by the Ministry of the Environment in 2018. Additionally, the Greek natural disaster insurance framework could benefit from strategic improvements. For the second objective, we employ MCDA, specifically Multi-Attribute Utility Theory (MAUT), to evaluate FRG frameworks from various EU countries, identifying the most suitable model for Greece. MAUT is chosen for its ability to incorporate both quantitative and qualitative criteria effectively, ideal for decision-making involving subjective judgments. The feasibility of conducting sensitivity analysis by altering criteria weights, utility scores, and creating best- and worst-case scenarios makes MAUT well-suited for policy decision-making. We assess criteria such as effectiveness, cost, adaptability, resilience, stakeholder engagement, and environmental impact, considering different flood scenarios, including Mediterranean storms and catastrophic flooding. Next, we intend to integrate Machine Learning (ML) techniques to perform a sensitivity analysis on our Multi-Criteria Decision Analysis (MCDA) method for storm disaster management. This approach will enhance our understanding of how different variables impact our decision-making process, thereby improving its accuracy and effectiveness in storm-related scenarios. In summary, this study aims to deliver a thorough and critical evaluation of the Flood Risk Governance (FRG) in Greece. It also seeks to offer well-informed recommendations for enhancing the Greek FRG system, particularly in the context of escalating flood risks driven by climate change. This comprehensive assessment not only scrutinizes the current state of flood risk management but also considers the future challenges posed by environmental changes, aiming to bolster Greece's resilience and adaptive capacity against such natural hazards.

How to cite: Kougkoulos, I., Apostolaki, S., Cook, S. J., and Lytras, M. D.: Flood Risk Governance in Greece in the Aftermath of Storm Daniel, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7358, https://doi.org/10.5194/egusphere-egu24-7358, 2024.

EGU24-7903 | ECS | Orals | NH9.3

Strategizing Building Resilience: A Big Data Driven Approach to Flood Risk Assessment and Management 

Han Kyul Heo, Youngjin Cho, Taehwan Hyeon, Yumi Song, and Ho gul Kim

The increased prevalence and intensity of flooding, exacerbated by climate change, pose significant risks to the structural integrity of buildings. A pertinent example of this was the 2022 flooding of Gangnam Station in South Korea, resulting in loss of life and amplifying concerns over flood-related damages. It is imperative to proactively assess the flood vulnerability of individual buildings to enhance public safety. This susceptibility is influenced by the building's unique characteristics and geographical location, necessitating their incorporation into flood mitigation strategies. This study endeavors to: (1) ascertain the flood risk of individual building units, and (2) suggest a management strategy to augment the flood resilience of buildings.

Our analysis encompassed 27,438 instances of flood damage in Seoul from 2016 to 2022, correlating this data with detailed building registry information. We categorized buildings into two risk groups—low and high—based on a damage threshold of 3 million won. Employing a range of variables, our study developed a flood risk analysis model utilizing the TabNet classifier, achieving an impressive predictive accuracy of 88%. Key factors in assessing flood risk included the building's function, structural design, height, and floor area ratio, with smaller buildings identified as particularly vulnerable.

The research revealed that flood hazard maps and flood risk maps display differing patterns. In certain areas, high flood probability coincides with low potential damage. This observation has two key implications: First, individuals in high flood probability but low damage areas might be exempt from stringent governmental oversight. Second, there are regions with low flood likelihood outside of government regulation that could still incur significant damage in the event of a flood.

Leveraging the power of machine learning and deep learning, increasingly applied across various fields, this study integrates building attribute data with a plethora of spatial and socio-environmental factors. This integration has facilitated the creation of a comprehensive list of buildings particularly prone to flooding, utilizing public datasets and advanced deep learning techniques. Most identified high-risk buildings are small-scale structures, already under the purview of mandatory inspections by several legislations including the Building Management Act and others related to safety and fire protection. However, buildings classified as safety-vulnerable are not subject to regular inspections under current laws. Given the anticipated increase in flood events due to climate change, it is crucial to establish safety management standards tailored to specific building characteristics to effectively reduce flood-related damages.

How to cite: Heo, H. K., Cho, Y., Hyeon, T., Song, Y., and Kim, H. G.: Strategizing Building Resilience: A Big Data Driven Approach to Flood Risk Assessment and Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7903, https://doi.org/10.5194/egusphere-egu24-7903, 2024.

EGU24-8172 | Posters on site | NH9.3

Identifying future challenges for adaptation to climate change through insights from participatory scenario-downscaling in Mumbai 

Jan Petzold, Matthias Garschagen, Ravinder Dhiman, Deepal Doshi, Alexandre Pereira Santos, and Devanathan Parthasarathy

Populations in many coastal urban areas are increasingly exposed to climate-related hazards, such as rising sea levels, increasing intensities and frequencies of tropical cyclones, and extreme weather events. At the same time, the number of people in coastal cities is growing and, especially in the Global South, these cities are characterised by rapid and often unplanned urbanisation and a high degree of social inequality. Hence, coastal cities are also hotspots of social vulnerability. That coastal cities are climate risk hotspots has been widely acknowledged, and adaptation is happening, especially in terms of planning and reactive responses. However, the current adaptation progress lacks implementation, evidence of effective risk reduction, and long-term pathway perspectives. A global future-oriented approach for a better understanding of the socioeconomic developments shaping challenges to adaptation is the Shared-Socioeconomic Pathway (SSP) framework. Our research uses the case study of Mumbai, one of the world’s most vulnerable cities, to apply a participatory scenario approach, downscaling the SSP narratives to the local level with bottom-up input from diverse local stakeholder groups. Our specific research question is: How do future socioeconomic urban developments affect Mumbai’s social vulnerability and challenges for adaptation? Our results provide three distinct scenario narratives for Mumbai’s socioeconomic development until 2050, including “Wider sustainability transitions”, “Partial exploitation of existing potential and current trends”, and “Increasing barriers through inequality and fragmentation”. The scenario narratives stress the relevance of addressing social inequality in urban change and development processes across different sectors, including labour, housing, transport, and health. A further prominent cross-cutting aspect resulting from the co-development of the scenario narratives with local stakeholders deals with streamlining urban planning across different governance scales (i.e., local and regional) and sectors (e.g., transportation and spatial planning). The SSP downscaling approach also sheds light on several conceptual and methodological challenges. For example, data availability guiding the drafting of plausible scenario assumptions varies significantly across different elements of the scenario narratives. Moreover, the framework is limited in considering local development pathways switching from one scenario track to another and the effects of unforeseen transformations or shocks. In conclusion, our study proves the value of developing globally nested regional scenarios to understand challenges for adaptation, consistent with research on global socioeconomic developments, and the importance of a transdisciplinary approach to guarantee plausibility, consistency and relevance for local contexts. The results of our study are relevant for a holistic understanding of future climate risk and challenges and opportunities for adaptation planning at the local scale. 

How to cite: Petzold, J., Garschagen, M., Dhiman, R., Doshi, D., Pereira Santos, A., and Parthasarathy, D.: Identifying future challenges for adaptation to climate change through insights from participatory scenario-downscaling in Mumbai, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8172, https://doi.org/10.5194/egusphere-egu24-8172, 2024.

EGU24-9458 | ECS | Orals | NH9.3

Progress and gaps in climate change adaptation in coastal cities across the globe 

Mia Wannewitz, Matthias Garschagen, and Jan Petzold

In the realm of adaptation to climate change, coastal cities deserve special attention as they are faced with an abundance of climate impacts while also being engines of economic development, trade, innovation and culture with, in theory, high adaptation potential. While there is eclectic evidence for urban adaptation, we are lacking a global overview of the extent to which coastal cities are on track to prepare for and adapt to climate risks. Building on and complementing highly relevant findings from the Global Adaptation Mapping Initiative (GAMI), this paper presents findings from a global review of empirical evidence for adaptation in coastal cities. We systematically analysed adaptation actions reported in the scientific literature for 199 coastal cities across the globe with the aim to provide the first stocktake of empirical evidence of adaptation in coastal cities. To do so, the paper addresses four key questions: (1) How is evidence for coastal urban adaptation spread across the globe? (2) Which hazards and trends of exposure and vulnerability are reported? (3) Which responses are reported and which actors are involved in their implementation? And (4) What is the speed, scope, depth and evidence of risk reduction due to adaptation? Using the World Bank’s income groups and city sizes as cross-cutting lines of analysis, our findings show that there is comparatively little published knowledge on coastal urban adaptation in low and middle income economies.  Reported adaptation measures are predominantly designed based on past and current, rather than future, patterns in hazards, exposure, and vulnerability. The results unravel that city governments, particularly in high-income countries, are more likely to be reported as implementers of institutional and infrastructural responses, while coastal cities in lower-middle income countries are often reported to rely on households to implement behavioral adaptation. Finally, the assessed evidence mostly presents coastal urban adaptation that is rather slow, of narrow scope, and not transformative. In sum, the paper provides a nuanced picture of the current state of adaptation in coastal cities. It highlights fields of progress as well as key gaps to be tackled in the future.

How to cite: Wannewitz, M., Garschagen, M., and Petzold, J.: Progress and gaps in climate change adaptation in coastal cities across the globe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9458, https://doi.org/10.5194/egusphere-egu24-9458, 2024.

In disaster science, the discussions predominantly stem from the various notions of risk and associated concepts. While understanding risk is an undeniable necessity to comprehend disasters, it is inadequate. This is because, risk only provides an understanding of what is, but it doesn’t describe what could be done and what should be done. As such, there are additional parameters that needs to be included to fully capture the complexities of disaster risk reduction. To this end, it is argued that disasters need to be framed through additional lens of law and ethics that interact with the concepts of risk. A framework, termed Ethics for 4Rs (E4Rs) where 4Rs represent the 4 phases of disaster cycle (reduction, readiness, response, and recovery), is proposed where the three main concepts: risk, ethics, and law interact continuously. Additionally, this framework emphasizes the need to explicitly express the importance of our values, i.e., ethics as disasters are fraught with difficult decisions. This theoretical framework was derived based on understanding gained through studies on the use of post-earthquake cordons as a response and recovery strategy following major disasters in three countries: Aotearoa New Zealand (Christchurch earthquake 2011), Italy (L’Aquila earthquake 2009), and Nepal (Gorkha earthquake 2015). For the case studies, a qualitative research methodology was used for data collection, where 44 experts from varying backgrounds such as politicians, emergency managers, city council members, police, community leaders among others were interviewed. The development of this framework has also been supported through review of ethical concepts from health sciences, in particular public health sciences. This is because discussions on ethics in relation to disasters are limited in literature where as they have been developed more thoroughly in public health sciences. Although, there are differences in disasters due to natural hazards and public health events such as a pandemic, the complexity, urgency, scale and the need to make difficult decisions remain the same and are comparable. Finally, it is suggested that this framework will bring about discussion on disasters and ethics where a significant gap remains in the current disaster science discourse.

How to cite: Shrestha, S. R.: Risk, Ethics, and Law: A framework (E4Rs) to understand disasters, learned through response to earthquake disasters in Aotearoa New Zealand, Italy, and Nepal. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10224, https://doi.org/10.5194/egusphere-egu24-10224, 2024.

EGU24-13097 | ECS | Posters on site | NH9.3

Dynamic Adaptive Policy Pathways for Flood Adaptation in Shanghai under Deep Uncertainty 

Xinmeng Shan, Jeroen C.J.H Aerts, Jun Wang, Jiahong Wen, Jie Yin, Yuhan Yang, Fengyue Qiu, and Paolo Scussolini

Decisions on coastal cities flood adaptation are complicated by deep uncertainty about sea level rise, subsidence and socioeconomic trends, increasing the chance of under- or over-investment. Frameworks have been proposed to plan coastal adaptation in urban settings. In this study, we expand those frameworks to include elements critical to rational decision-making in coastal cities under deep uncertainty. Our framework, trained on the city of Shanghai, includes compound flood modeling, flood risk analysis, design and quantitative simulation of adaptation strategies, cost-benefit analysis, trade-off analysis and formulation of dynamic adaptive policy pathways (DAPP). We include land subsidence in modeling flood scenarios; we compute a diverse set of flood impacts on multiple sectors; we evaluate several techniques of cost-benefit analysis; and we include multiple adaptive strategies against compound flooding (i.e., pluvial, fluvial, coastal). We show that the hard adaptation strategies (e.g., storm-surge barriers and storage tank) can successfully reduce future increase in risk generated by sea level rise, land subsidence and socioeconomic development, by 58%~94%. In contrast, soft adaptation only generate considerable benefits when integrated with hard adaptation into hybrid strategies. A hybrid strategy that combines storm-surge barrier and wetland creation most effectively reduces flood damages and casualties, and yields promising co-benefits. We formulate DAPP for robust and flexible decision-making over time for the coming decades, which open up the decision-making space and help overcome policy paralysis due to deep uncertainty.

How to cite: Shan, X., Aerts, J. C. J. H., Wang, J., Wen, J., Yin, J., Yang, Y., Qiu, F., and Scussolini, P.: Dynamic Adaptive Policy Pathways for Flood Adaptation in Shanghai under Deep Uncertainty, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13097, https://doi.org/10.5194/egusphere-egu24-13097, 2024.

EGU24-13553 | ECS | Posters virtual | NH9.3

HawardAware: A Comprehensive Flood and Wind Risk Assessment and Mitigation Tool for Enhancing Resilience in Gulf of Mexico Coastal Communities 

Rubayet Bin Mostafiz, Ayat Al Assi, Md Adilur Rahim, and Carol Friedland

Understanding natural hazard risk is critical for fostering the development of resilient residential communities. Existing web-based tools, while valuable for decision-making, often fall short of providing comprehensive information at a regional level. This research introduces the Flood and Wind Risk and Mitigation Calculation Tool (FWRMCT), an integral component within the "HazardAware" platform tailored for 196 Gulf of Mexico coastal counties in the United States. Current tools predominantly focus on general property information, creating a gap in accurate and region-specific natural hazard risk assessments. FWRMCT addresses this void by offering a comprehensive address-based risk assessment tool that aids decision-making at both individual and regional levels. By incorporating flood and wind risk assessment capabilities, the tool empowers users to make informed decisions regarding long-term mitigation options. Additionally, FWRMCT features toolsets that not only assess risk accurately but also illustrate the economic costs and benefits associated with mitigation measures such as elevating homes, installing storm shutters, reinforcing garage doors, and implementing Insurance Institute for Business & Home Safety (IBHS) certified FORTIFIEDTM roof. This renders FWRMCT a valuable asset in promoting the development of flood and wind-resilient residential communities. The research outlines the comprehensive framework of FWRMCT, elucidating its features, methodology, and the economic savings associated with mitigation actions. The goal is to ensure the tool's accessibility and usability for various stakeholders, including researchers, scientists, and homeowners. Through educational resources, the research enhances user understanding, empowering them to actively contribute to the development of resilient residential communities. Moreover, FWRMCT improves the flood and wind Average Annual Loss (AAL) assessment, catering to diverse users based on building types and spatial locations. FWRMCT's unique ability to differentiate between owner/occupant types, such as homeowners and renters, offers recommendations based not only on financial considerations but also on feasibility. This customization provides both tenants and homeowners access to tailored information, assisting them in making well-informed decisions about mitigating flood and wind hazards. Additionally, HazardAware provides a rich repository of educational resources related to flood, wind, and other natural hazards, along with mitigation techniques and associated benefits. By comprehending potential risks and benefits, home occupants enhance their awareness of local risk profiles, enabling them to take proactive measures to safeguard their homes and protect their families and investments. As more residents make risk-informed housing decisions, community resilience increases. FWRMCT within HazardAware excels over other web tools in the hazard risk space by utilizing address-specific calculations that consider building type, attributes, and area. This approach provides more comprehensive information for generating accurate risk assessments. FWRMCT also offers actionable information, including calculated mitigation benefits, costs, and payback periods. Its ability to showcase how risk, costs, and benefits change under different scenarios further sets it apart, making it a versatile tool for users concerned with various home information, building characteristics, and owner/occupant types. This research introduces FWRMCT as a powerful tool within HazardAware, aiming to raise awareness and improve understanding among researchers, stakeholders, communities, and citizens about the significance of addressing natural hazard risk for the development of resilient residential communities.

How to cite: Mostafiz, R. B., Al Assi, A., Rahim, M. A., and Friedland, C.: HawardAware: A Comprehensive Flood and Wind Risk Assessment and Mitigation Tool for Enhancing Resilience in Gulf of Mexico Coastal Communities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13553, https://doi.org/10.5194/egusphere-egu24-13553, 2024.

EGU24-14544 | ECS | Posters on site | NH9.3

Who is responsible for addressing climate risks in coastal cities? Insights from a policy document analysis of Metro Manila 

Lena C. Grobusch, Bethany M. Liss, and Matthias Garschagen

Metro Manila is the Philippines’ largest metropolitan region. It is highly urbanized, densely populated, and situated on the coast where it is highly exposed to natural disasters and rising sea levels. Therefore, a significant question for Metro Manila concerns how to adapt to such current and future climate hazards. To address this urgent need to adapt to climate change while simultaneously tackling pronounced urban and sustainable development challenges, a multitude of policy and planning documents have been formulated within the Philippines across varying scales. These documents represent a suitable means of analyzing the legal-institutional dimension of adaptation governance in Metro Manila. One pressing question in the field of adaptation governance, which remains understudied, is who is actually responsible for adaptation. Hence, this research aims to answer how, in the documents, roles and responsibilities for adaptation are divided amongst the different actors who are parties to the ‘social contract’ on adaptation. The research questions are as follows: 1) What is the discourse on roles and responsibilities in the policy and planning documents? 2) Which actors are described as being responsible for implementing adaptation strategies, and who should benefit from these actions? 3) Are these actors’ roles and responsibilities clearly defined in the documents, and which types of responsibilities are defined? A qualitative methodology was utilized to answer these questions. First, existing literature was reviewed to synthesize a framework for assessing different types of roles and responsibilities (such as financial, legal, and moral) as well as evaluation criteria (such as accountability, responsiveness, and transparency). Then, the framework was applied to 39 policy and planning documents from the national to the local level by means of a qualitative content analysis in MAXQDA. The findings show that responsibilities are more commonly referred to than roles, and that clearly defined responsibilities throughout the adaptation policy cycle are increasingly considered to be an important aspect for effective implementation. The documents vary in the extent to which they clearly define responsibilities for different actors, but the roles and responsibilities of governmental actors are defined most clearly. However, the adaptation stakeholder landscape is quite complex and stretches beyond governmental actors to incorporate academia, citizens, civil society and non-governmental organizations, international organizations and foreign actors, future generations, and the private sector. The latter is often called upon to aid the government in fulfilling financial responsibilities and infrastructure construction. Lastly, the analysis shows that cooperative and participatory processes, as mechanisms for influencing social contracts for adaptation, are playing progressively important roles. Future research will thus conduct interviews to explore how, in collaborative efforts and participatory processes, questions around social acceptability and political responsibilities are discussed and where the disparities lie between the legal-institutional responsibilities captured in the documents, and practiced and expected responsibilities. This is key for making some of the implicit developments more explicit in the timely discussion about who is responsible for doing what in adaptation, and which actors benefit or lose out.

How to cite: Grobusch, L. C., Liss, B. M., and Garschagen, M.: Who is responsible for addressing climate risks in coastal cities? Insights from a policy document analysis of Metro Manila, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14544, https://doi.org/10.5194/egusphere-egu24-14544, 2024.

EGU24-14632 | ECS | Posters on site | NH9.3 | Highlight

Mainstreaming climate change adaptation into local land use planning in Metro Manila: lessons learned and potential for knowledge transfer 

Bethany M. Liss, Lena C. Grobusch, and Matthias Garschagen

As recent IPCC reports have highlighted, urban areas are now home to most of the world’s population. The majority of such urban growth continues to occur in less developed regions and is expected to persist, specifically in Asia. Due to extensive anthropogenic change along coastal zones, as well as their inherent exposure to natural hazards such as sea level rise, erosion, and tropical storms, coastal cities are especially at risk to the adverse impacts of climate change. Having consistently ranked as one of the countries most at risk to the negative impacts of anthropogenic climate change, the Philippines has undertaken significant efforts to integrate climate change adaptation into various policies and planning documents. This research reflects on the specific practice of mainstreaming climate change adaptation (CCA), as well as disaster risk reduction (DRR) measures, into local land use planning in Metro Manila as a means of reducing the region's present and future risk. Effective land use planning represents a proactive and economical approach to managing both current and future climate change related risks, especially when taking into consideration the significant expenses necessary to remedy issues caused by poorly or unplanned development, which often most negatively impacts a community’s most vulnerable members. Specifically, the aim of this research is to take stock of what progress has been made toward mainstreaming climate change adaptation and disaster risk reduction strategies into local land use planning in Metro Manila and to understand how this impacts those who are most vulnerable to climate change. The analysis also strives to comprehend how the knowledge gained from the Metro Manila case study can be transferred to other cities in Southeast Asia facing similar challenges. Methodologically, the software MAXQDA was utilized to conduct a qualitative data analysis of 39 policy and planning documents, ranging from the national to the local level. This analysis demonstrates that policy and planning documents at all levels integrate future-oriented climate change adaptation and disaster risk reduction strategies to a certain extent. However, despite the consistent and comprehensive integration of such strategies into documents across scales, numerous documents cite significant challenges in implementing CCA and DRR strategies, especially at the local level. Poor and/or inconsistent coordination between government offices, in addition to other stakeholders, limited or poorly prioritized and difficult-to-access financing, as well as a lack of continuity in personnel due to political election cycles, particularly at the local level, were frequently referenced as representing significant barriers to proper implementation of CCA and DRR strategies. Future research will be conducted in the form of expert interviews, which will help to better understand the current issues regarding the local implementation of these strategies and in what ways these can be improved or altogether remedied.

How to cite: Liss, B. M., Grobusch, L. C., and Garschagen, M.: Mainstreaming climate change adaptation into local land use planning in Metro Manila: lessons learned and potential for knowledge transfer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14632, https://doi.org/10.5194/egusphere-egu24-14632, 2024.

Severe storm events are one of Central Europe's most damaging natural hazards, thereby under particular focus on disaster risk management. One key element for risk reduction is vulnerability. Risk assessments often assume vulnerability as constant, leading to an overestimation of risk in the future. This work aims to quantify the temporal dynamics of vulnerability to assess future risks more precisely. An essential factor for the dynamics of vulnerability is the hazard itself. Extreme events destroy the most vulnerable elements, which are rebuilt or repaired in a less vulnerable way. Therefore, the intensity of the previous events and the resulting damage is a decisive factor in reducing vulnerability. A second important factor is the period between events. If the next event occurs during the reconstruction phase, vulnerability is higher than when the reconstruction phase is completed.

We analyze the impact of previous storm events on the vulnerability of residential buildings. For this purpose, generalized additive models are implemented to estimate vulnerability curves, which are set as a function of the intensity of the previous event and the duration between the events. The damage is extracted from a 23-year-long data set of the daily storm and hail damages for insured residential buildings in Germany on the county level provided by the German Insurance Association, and the hazard component is described by the daily maximum wind load calculated from the ERA5 reanalysis. The results show a negative relationship between the previous event's intensity and the current event's damage. The duration between two events shows a significant reduction of the damage for events occurring one or more winter seasons ago compared to events occurring within the same season. On a daily scale, the first seven days are especially crucial for vulnerability reduction.

How to cite: Trojand, A., Rust, H., and Ulbrich, U.: Temporal dynamic vulnerability - Impact of antecedent events on residential building losses to wind storm events in Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14810, https://doi.org/10.5194/egusphere-egu24-14810, 2024.

EGU24-15338 | ECS | Posters virtual | NH9.3

Land-use scenarios for assessing climate risk as a tool for spatial planning: a case study of the Stuttgart Region, Germany 

Joanna M. McMillan, Franziska Göttsche, Hendrik Janssen, Holger Hoppe, and Jörn Birkmann

Spatial development, particularly the rapid expansion of urban areas, is increasing disaster risk in city-regions around the world. The planning region of Stuttgart is a growing polycentric region with a high demand for housing and commercial space, and at the same time faced with increasing risk of pluvial flooding and heatwaves. Spatial planning that controls and coordinates urban development is an important tool for ex-ante disaster risk reduction. However, planners face a complex task to weigh up a myriad of development goals of which risk reduction is just one. Decision-making tools for planning practitioners and the public that quantify resilience factors spatially can support the integration of resilience and risk considerations into planning processes. In our research, we investigate the use of land-use scenarios as a way to measure the relevance of land to the hazards of pluvial flooding and the urban heat island effect and thus to risk reduction. We do so with a particular focus on operationalizing such a quantitative assessment for the regional planning level, whose task it is to coordinate the spatial development of the municipalities. Such coordination is particularly important in the context of disaster resilience in urban regions such as Stuttgart, because, for example, the development of land in one municipality can increase water runoff or decrease cooling airflows in a neighboring municipality.

In our contribution to this session, we share our insights from a combined effort by research, modelling and planning practitioners to operationalize land-use scenarios as a way to quantify the effect of urban development on risk. A central aim of our approach was relevance to regional and local planning processes. The land that we considered as potential for urban development was thus based on the current planning law. We constructed two land-use scenarios, in which all land in the region with potential for development was fictitiously used for building housing but in two different ways – one with a building density and height and level of soil sealing typical to the local setting, and the second with a more compact urban form with more green and less impervious surfaces. The aim was, firstly, to measure the effect of urban expansion on hazard exposure and, secondly, to determine if through a compact and climate-sensitive urban form the needs for more housing could be met without increasing hazard exposure. The pluvial flood hazard model and an urban climate model of the two scenarios provided useful results for the first aim, but less so for the second. In our contribution, we will share the methodological challenges of translating the scenarios for two different types of models, and discuss the results and their potential as a tool for use in spatial planning processes.

How to cite: McMillan, J. M., Göttsche, F., Janssen, H., Hoppe, H., and Birkmann, J.: Land-use scenarios for assessing climate risk as a tool for spatial planning: a case study of the Stuttgart Region, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15338, https://doi.org/10.5194/egusphere-egu24-15338, 2024.

EGU24-15967 | Orals | NH9.3

An operational framework for improving the resilience of inland waterways and floodplains to the impacts of flood-induced dike breach hazard 

Benjamin Dewals, Joris Hardy, Davide Mastricci, Vincent Schmitz, Alexis Melitsiotis, Michel Pirotton, Sébastien Erpicum, and Pierre Archambeau

Early warning is critical to enhance the resilience of communities and infrastructures towards a wide range of natural and human-caused hazards. As a part of a broader initiative aiming at improving the resilience of waterways to multi-hazards risk (earthquake, fog, wind, low flow …), we present here components of an operational hazard assessment tool focusing on the impact of dike breaching. The system is developed and showcased on a study site located in Belgium, involving major waterways such as a stretch of river Meuse, a parallel navigation channel and tributaries.

The modelling strategy builds on three steps. Step one is a machine-learning-based hydrological model which provides quick estimates of flow rate at the upstream ends of the domain. The model was trained based on observed flow rates and precipitation data at rain gauges distributed across the catchments.

Step 2 consists in a detailed hydrodynamic modelling reproducing the flow in the navigation channels and simulating breach development, flow through the breach, as well as in the floodplains. This approach is accurate and detailed; but too slow for rea-time prediction, i.e., operational use. Therefore, Step 3 consists in combining a quick and efficient simplified dike breach model to estimate breach hydrograph and produce inundation maps in the floodplains by spatial interpolation in a collection of pre-computed results of the detailed hydrodynamic model (Step 2).

The model structure will be detailed, and results will be presented and discussed.

This research is co-funded by the European Union’s Horizon Europe Innovation Actions under grant agreement No. 101069941 (PLOTO project: https://ploto-project.eu/). 

How to cite: Dewals, B., Hardy, J., Mastricci, D., Schmitz, V., Melitsiotis, A., Pirotton, M., Erpicum, S., and Archambeau, P.: An operational framework for improving the resilience of inland waterways and floodplains to the impacts of flood-induced dike breach hazard, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15967, https://doi.org/10.5194/egusphere-egu24-15967, 2024.

EGU24-16180 | Orals | NH9.3

Operationalising ecological resilience 

Ronald Corstanje, Nikolaos Toumasis, Marko Stojanovic, Daniel Simms, JIm Harris, and John White

Given the increasing pressures and perturbations on ecosystem due to climatic variability, there has been a developing interest in determining the resilience of ecosystems, particularly given the potential of abrupt and possibly irreversible shifts between alternative ecosystem states. There are numerous conceptual definitions of resilience in environmental systems and, even when resilience is clearly described for a particular ecosystem, it can challenging to quantify a priori to a state change in the ecosystem of interest. Ecosystems that approach transition exhibit generic changes in dynamical behaviour that can be used to signal the approach of a critical transition. When an ecosystem approaches a critical transition, its dynamics “slowdown”, and start exhibiting properties associated to the process critical slowing down (CSD), such as increased recovery time, variance, and autocorrelation. Here we develop a set of analytical methods based on measures of variance and autocorrelation to determine the current state of ecosystem and their likelihood to be at CSD, so to demonstrate how to operationalise what to date has been developed as a theoretical framework. We use wavelets as a measure of identifying changes in the variance term, and autocorrelation was modelled using an Bayesian dynamic linear model. We illustrate this on three case studies; i) on an experimental soil system subjected to dry wet cycles; ii) on an intensely managed ecological system in the Everglades and iii) on extensively managed grassland systems in the UK. We illustrate that although any of the resilience characteristics can be used to define resilience, the identified properties of a resilient response must be described for different contexts.

How to cite: Corstanje, R., Toumasis, N., Stojanovic, M., Simms, D., Harris, J., and White, J.: Operationalising ecological resilience, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16180, https://doi.org/10.5194/egusphere-egu24-16180, 2024.

EGU24-16498 | Posters on site | NH9.3

Exploring the relationship between urban morphology types and household-level flood vulnerability profiles in Ho Chi Minh City 

Jiachang Tu, Andrea Reimuth, and Matthias Garschagen

There is rising discussion focused on the ways in which urban growth and expansion, often into flood-prone areas, takes effect on the exposure and vulnerability profiles of the respective households. In order to drive city-wide and regional analysis, remotely sensed urban structure types are increasingly being used as a proxy for socio-economic characteristics. However, whether and how urban structure types in fact match the nuanced realities of socio-economic exposure and vulnerability to floods remains largely unclear. Resolving this question is of particular relevance for improving flood risk assessments in rapidly growing coastal cities with a high hazard exposure. We therefore use Ho Chi Minh City in Vietnam as a case study to develop a detailed composite indicator index for measuring the exposure and vulnerability at household level in flood-affected parts of the city, based on household survey data. We then correlate this index to urban structure types to see whether morphology characteristics map against socio-economic vulnerability and exposure profiles. In order to allow for an assessment of temporal trends, data from a repeated survey (two years after the first) is used to examine dynamics in exposure, vulnerability and urban development.

Our research yields a number of key results (Tu et al., forthcoming): First, household vulnerability is not necessarily correlated to flood exposure. Second, the vulnerability and flood exposure levels of households are differ along an urban, peri-urban and rural gradient. Third, the exposure and vulnerability profiles only partly correlate with the urban structure types, but a certain mapping can be done with a reasonable uncertainty bandwidth in order to drive future modeling forward. These findings not only shed light onto spatial vulnerability patterns in HCMC but also on methodological advances in the field of city-wide risk and adaptation modeling. These lessons and their transferability to other coastal cities with similar adaptation pressures but different morphology and vulnerability profiling will be discussed.

How to cite: Tu, J., Reimuth, A., and Garschagen, M.: Exploring the relationship between urban morphology types and household-level flood vulnerability profiles in Ho Chi Minh City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16498, https://doi.org/10.5194/egusphere-egu24-16498, 2024.

EGU24-18567 | ECS | Orals | NH9.3

Assessing disaster risk governance effectiveness: a document-based analysis using the READ approach in Thua Thien Hue province, Central Vietnam 

Thanh Bien Vu, Olabisi S.Obaitor, Lena C. Grobusch, Ulrike Schinkel, Dominic Sett, Michael Hagenlocher, and Matthias Garschagen

Although substantial research has been conducted on the subject of good governance, our comprehension of effective disaster governance and its criteria remains inadequate.

Drawing from a comprehensive literature review, six criteria of good disaster risk governance were selected to assess the effectiveness of disaster risk governance in Thua Thien Hue province, a region prone to natural and climate-induced hazards. These criteria include accountability, responsiveness and flexibility, transparency, collaboration, decentralization and autonomy, information sharing. Insights into these six characteristics were extracted from an analysis of 106 legal documents, utilizing the READ approach (Dalglish et al., 2020). These insights were then categorized based on the four phases of disaster risk management: prevention, preparedness, response, and recovery. To enhance the robustness of the findings from the document-based analysis and delve deeper into the efficacy of policy implementation, the research incorporates perspectives from 606 citizens, collected in a standardized household survey. Through ordinal logistic regressions, the study explores the factors influencing citizens’ perceptions regarding the effectiveness of flood risk governance.

The results obtained through the READ approach reveal distinct emphases in various phases of disaster risk government. In the prevention phase, legal documents underscore the importance of responsiveness and flexibility, achieved through the integration of climate change adaptation scenarios into diverse plans such as socio-economic development and spatial planning. However, these legal documents only addressed the integration of climate change scenarios without including vulnerability scenarios that consider changes in the socio-economic and environmental aspects. During the preparedness phase, emphasis is placed on inter-agency coordination to ensure accountability for financing the disaster prevention fund. In the response phase, critical emphasis is placed on information sharing which helps authorities, and organizations make informed decisions, allocate resources efficiently, and save lives during disasters. Transparency in the allocation of subsidies following disasters takes center stage during the recovery phase.

Findings from the household survey indicate that about 70% of citizens perceive flood risk management as effective. Yet, approximately one-quarter of respondents indicated that they perceive the government's handling of flood risk as either low or not effective at all. Explaining citizens' perceptions of the effectiveness of flood risk governance involves considering five influencing factors: location, age, individual responsibility, income, and past flood experiences. Specifically, individuals with greater self-assigned responsibilities in flood control, older age, those residing outside core urban areas, and households with less exposure to flood impacts over the past decade are more likely to express higher effectiveness. Interestingly, lower-income households perceive government flood management as effective, possibly due to prioritization in response and recovery, as indicated by document analysis.

Although the legal framework for risk management in Thua Thien Hue is relatively comprehensive, supplementing it with additional components currently lacking, such as vulnerability scenarios, would promote the risk management transition from the 'response and recovery' phase to the 'prevention and preparedness' phase, a trend that has been proven to be more effective in disaster risk governance (PU & UNDRR, 2021; Khan et al., 2022; WB 2023).

How to cite: Vu, T. B., S.Obaitor, O., C. Grobusch, L., Schinkel, U., Sett, D., Hagenlocher, M., and Garschagen, M.: Assessing disaster risk governance effectiveness: a document-based analysis using the READ approach in Thua Thien Hue province, Central Vietnam, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18567, https://doi.org/10.5194/egusphere-egu24-18567, 2024.

EGU24-18696 | ECS | Orals | NH9.3

The Future of Urban Climate Vulnerability in Southeast Asia: Linking downscaled shared socioeconomic pathways to the drivers of urbanisation in Mumbai, Manila and Jakarta 

Alexandre Pereira Santos, Olabisi Obaitor, Jan Petzold, Mia Wannewitz, Veronika Zwiglmaier, Gusti Ayu Ketut Surtiari, Ravinder Dhiman, and Matthias Garschagen

Reducing future climate vulnerability at the local level depends on consistent policies and setting clear roles and responsibilities. Unfortunately, these are often missing in developing countries, given that different agencies and actor groups develop local adaptation and urbanisation policies with little streamlining and integration. More fundamentally, research combining local adaptation and urbanisation is rare, especially that which provides future-oriented, long-term pathways. This policy and research gap clouds decision-making, fuels potential maladaptation, and saps policy effectiveness, especially in the highly vulnerable coastal Southeast-Asian cities. To shed light on this problem, this research asks: How do three shared socioeconomic pathways (SSP) shape the future drivers of urbanisation for Mumbai, Manila and Jakarta? We approach this question by combining mixed qualitative narratives and quantitative estimates of urbanisation drivers from the regional SSPs developed by Petzold and colleagues (in press). Petzold et al. downscaled three SSPs (matching SSP 1, 2, and 3) to the metropolitan areas of Mumbai and Jakarta in a participatory scenario approach that yielded narratives on themes like population, labour, health, and migration. We applied this method to Manila and extracted the significant factors driving urbanisation from the three regions, forging integrated urbanisation and adaptation pathways. The results include region-specific qualitative narratives of future development and quantitative estimates of the urbanisation drivers with their associated levels of uncertainty. We present these results across the themes of population growth, urban structure types at the metropolitan cores, inner and outer peripheries, urban planning, infrastructure, informality, and inequality, among others. Stakeholder engagement supported validating the research assumptions and narratives and developing the estimates through a hierarchical analytical process. This mixed methods approach sheds light on the relationship between urban development and risks in highly urbanised and at-risk cities in Southeast Asia, considering the social drivers of vulnerability and the physical drivers of exposure. Its limitations include data and research scarcity, despite which it bridges the gap between urbanisation and adaptation policy and research. It also provides a globally nested approach to future development built on transdisciplinary research and validated with local knowledge. It presents methods suitable to other cities in the region, as well as insights for the future development and risk assessment of Mumbai, Manila, and Jakarta. Future work includes checking the narratives against ongoing processes and future urban growth simulations to provide critical insight for local decision-makers into their adaptation agendas.

How to cite: Pereira Santos, A., Obaitor, O., Petzold, J., Wannewitz, M., Zwiglmaier, V., Ketut Surtiari, G. A., Dhiman, R., and Garschagen, M.: The Future of Urban Climate Vulnerability in Southeast Asia: Linking downscaled shared socioeconomic pathways to the drivers of urbanisation in Mumbai, Manila and Jakarta, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18696, https://doi.org/10.5194/egusphere-egu24-18696, 2024.

The last 2023 IPCC report draws attention to the change in the occurrence and frequency of weather extremes and natural hazards (Lee et al., 2023). It emphasizes the urgent need for climate change mitigation and adaptation to counteract the risks to life, nature, values, and societies. A recent study by Köhler et al. (2023) provides insight into the fact that frequent flood experiences increase the willingness to undertake protective actions at the individual level but simultaneously lead to decreased self-reported resilience. Still, there is a gap in understanding why frequent flood experiences influence protective motivation and what other factors play a role. Building upon this, this study explores the role of frequent experience in protective motivation and why more experienced people are more likely to adapt. Also, we introduce a measure for control experience, the individual's perceived efficacy in managing past flood situations, to understand the role of perceived resistance in affecting protective motivation.

To meet this aim, we apply Protection Motivation Theory (PMT) from the field of psychology to understand how frequent flood events and control experiences influence coping and threat appraisal, two factors that have been shown to impact people's motivation to change behavior. Structural equation Modeling is used to detect processes and interactions between several variables in one model. The data comes from a survey in Saxony (Germany) in 2020.

We find that both the frequency of experienced floods and the control experience increase threat appraisal but decrease coping appraisal. Threat appraisal could, therefore, be a channel through which flood experience positively influences protective motivation. The negative influences of flood experience on coping appraisal could limit this positive impact, at least to some extent. Our findings carry profound implications in understanding better the protective behavior of people who have undergone multiple flood events. We deliver crucial insights into how the frequency of experienced floods, perceived efficacy in managing past flood events, and individual protective behavior are related.

 

Citations:

Lee, H., Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P., ... & Park, Y. (2023). IPCC, 2023: Climate Change 2023: Synthesis Report, Summary for Policymakers. Contribution of Working Groups I, II and    III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing  Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland.

Köhler, L., Masson, T., Köhler, S., & Kuhlicke, C. (2023). Better prepared but less resilient : the paradoxical impact of frequent flood experience on adaptive behavior and resilience. Natural Hazards and Earth System Sciences, 23(8), 2787–2806.

How to cite: Köhler, L. and Han, S.: The leverage effect of experience: how flood frequency and perceived loss of control influence individual protective motivation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18999, https://doi.org/10.5194/egusphere-egu24-18999, 2024.

EGU24-20204 * | ECS | Orals | NH9.3 | Highlight

Flood Risk Management and Health Consequences: a case-study of the 2021 floods in Germany 

Nivedita Sairam, Domenica Michelle Jaramillo Sanchez, and Heidi Kreibich

Owing to changing climate and growing urban cities, the frequency and intensity of extreme flood events are rising. Often, the impacts of flooding on the economic front is the focus of science and policy. On the other hand, floods adversely affect the health and well-being of exposed populations which are difficult to quantify through conventional risk assessment frameworks.

There is currently a lack of a comprehensive understanding of the Flood–Human-health system. In specific, understanding and quantification of the drivers and feedback-effects leading to health-related consequences is crucial for developing inclusive flood risk management strategies.

Focusing on the 2021 flooding in Germany, we aim to identify and elucidate the drivers and processes that led to health consequences with a focus on aspects of flood risk management – mitigation, preparedness, response and recovery. Our study employs data-driven approaches, utilizing a substantial sample of empirical household surveys on flood characteristics, consequences and risk management aspects. The presentation of key findings will shed light on the pathways leading to consequences on human health, encompassing elements of risk management

How to cite: Sairam, N., Jaramillo Sanchez, D. M., and Kreibich, H.: Flood Risk Management and Health Consequences: a case-study of the 2021 floods in Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20204, https://doi.org/10.5194/egusphere-egu24-20204, 2024.

EGU24-21664 | ECS | Posters on site | NH9.3

Extracting socioeconomic information with the help of urban structure types indata-scarce environments 

Charlotta Mirbach, Alexandre Pereira Santos, Matthias Garschagen, Volker Hochschild, and Gebhard Warth

Linking socio-economic and spatial structural data is a key research gap in the assessment of urban climate risk. Urban populations are increasingly exposed to adverse effects of climate change, particularly in coastal urban areas in the Global South, where information is scarce. Researchers often rely on survey results, which deliver highly detailed micro-level point data but those are costly and lack spatial coverage. Conversely, Earth observation
(EO) data offers greater spatial coverage but provides limited insights into socio-economic factors. Hence, there is a gap in integrating urban morphology data derived from EO and micro-scale survey data. We aim to address this gap by linking socio-economic and morphological data using a novel machine learning-based approach and testing whether and to what extent urban structure types (UST) can function as spatial predictors for
socio-economic profiles.
To do so, we implement a two-stage process based on k-means and random forest (RF) algorithms in two case studies. First, we employ a k-means clustering algorithm to delineate socio-economic profiles based on household survey variables relating to education, household size and composition, and asset ownership. We then used an RF classification algorithm that used USTs as predictors to extend the survey socio-economic profiles into
morphologically similar areas in two case study cities: Mumbai (India) and Ho Chi Minh City (Vietnam). In Mumbai, current socio-economic data is severely outdated (i.e., the last census was in 2011), while in Ho Chi Minh City it is only available in coarse spatial units (i.e., at the commune level). These conditions hinder research on assessing flooding vulnerability, as population growth and the mismatch between administrative units and flood hotspots introduce severe bias and uncertainty in the available data. To overcome this situation, we implemented household surveys (n=1240 and 751, respectively) in flood hotspots that cover a variety of urban structure types (e.g., compact low-rise, open mid-rise, or lightweight low-rise).
In our study, morphological information functions as a proxy for socio-economic profiles, thus providing a cost-effective and spatially explicit novel approach to assessing social vulnerability in data-scarce conditions. By starting from the household-level survey data, we avoid the most critical problems from reductionist approaches (e.g., social determinism) and recognize the limitations of data triangulation. To this end, we measure the uncertainty of the association in each step and validate the assumptions and results with local stakeholders. Our novel approach aims to use the available EO data to improve the identification of high-vulnerability areas. Albeit experimental, the spatially explicit identification provided in
this study provides crucial insights for targeted climate adaptation policy and research. By studying two rapidly evolving coastal cities, we provide a comprehensive and reproducible method to assess the challenges urban populations face under climate change.

How to cite: Mirbach, C., Pereira Santos, A., Garschagen, M., Hochschild, V., and Warth, G.: Extracting socioeconomic information with the help of urban structure types indata-scarce environments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21664, https://doi.org/10.5194/egusphere-egu24-21664, 2024.

EGU24-31 | ECS | Posters on site | NH9.6 | Highlight

Estimating the carbon footprint of post-flood urban road network restoration: A case study in Carlisle 

Weichen Zhong, Guy Howard, and Jeffrey Neal

Climate change and urbanization are expected to increase the risk of flood disasters in vulnerable areas. Urban road infrastructure can be affected by flooding, and subsequent restoration creates an additional carbon emission burden. These emissions are likely to compromise local decarbonization efforts, but there remains a lack of tools for quantifying the environmental impact of reconstruction projects after disasters. This study aims to develop an assessment framework to reveal the carbon footprint of post-flood road network restoration projects. The model integrates flood simulation, pavement damage evaluation, and carbon footprint calculation modules. This paper introduces nine flood scenarios ranging from 2-year to 1000-year events and a case study in Carlisle, UK, to test the integrated model. Results of the scenario simulation indicate that the carbon emissions from restoring per unit length of pavement as the flood magnitude increases for both main roads (10.46-19.21 kgCO2e) and low-volume roads (5.34-10.17 kgCO2e). Moreover, the case study indicates that the urban road network layout may significantly influence the general carbon footprint of post-flood pavement restoration. The carbon emissions from only restoring the main body of damaged pavements after this 70-hour disaster are estimated to offset almost 1% of the local decarbonization achievement for a month. Indirect carbon footprints from material production (67%) and delivery (29%) are much higher than direct emissions from on-site tasks (4%). Measures such as optimizing pavement materials, reusing wastes, rationalizing delivery routes, and improving the city layout help alleviate the burden of recovery. This study reflects on the environmental costs of disaster recovery processes, with a view to supporting improved mitigation strategies. The integrated modeling framework can also be applied to cities in different contexts to enrich reference for decision-making.

How to cite: Zhong, W., Howard, G., and Neal, J.: Estimating the carbon footprint of post-flood urban road network restoration: A case study in Carlisle, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-31, https://doi.org/10.5194/egusphere-egu24-31, 2024.

Seismic safety assessment of existing buildings is very important because their design and construction are made according to lower standards. The buildings designed with lower standards and without standards are susceptible to earthquake-induced damage. The vulnerability of existing buildings to seismic events has been vividly highlighted by recent earthquakes, such as the Türkiye–Syria earthquake on February 6, 2023, the Herat Afghanistan earthquake on October 11, 2023, and the Marrakesh-Safi Morocco earthquake on September 9, 2023. In the Turkey-Syria earthquake alone, over 50,000 people lost their lives [1], over 100,000 sustained injuries [2], and the economic toll amounted to approximately 110 million dollars [3]. Building damage from seismic events poses risks to lives and causes substantial financial losses, necessitating the determination of each building's fragility and the implementation of appropriate precautions before an impending devastating earthquake. Rapid Visual Screening (RVS) methods are employed for assessing building inventory, given the computational and cost constraints of in-depth vulnerability assessment methods. While conventional RVS methods are widely used and high efforts are given to enhance them, their reliability is limited for accurately assessing a building inventory [4–6]. Therefore, this study leverages post-earthquake building inspection data from the 2015 Gorkha, Nepal earthquake to develop a RVS method using artificial intelligence algorithms, encompassing fuzzy logic, machine learning, and neural networks. The integration of advanced feature engineering techniques introduces sophisticated parameters like fundamental structural period, spectral acceleration, and distance to the earthquake source, enhancing the RVS method's assessment capabilities across diverse seismically vulnerable areas. The developed RVS method demonstrates a correlation between observed building post-earthquake damage states and the predicted ones. When compared to conventional RVS methods, a noteworthy test accuracy of 44% is achieved, surpassing conventional methods in accurately classifying building damage states. Notably, in contrast to RVS methods solely developed using machine learning and neural networks, the developed method exhibits transparency and the capability to be adapted to different regions.

Keywords:

Seismic vulnerability assessment; Earthquake-induced damage; Rapid Visual Screening (RVS); Artificial intelligence algorithms; Fuzzy logic; Machine learning; Neural networks

 

References: 

[1]        UN says at least 50,000 killed in Turkey and Syria quakes, AP News. (2023). https://apnews.com/article/turkey-syria-earthquakeunited-nations-44c2b736108ccb37130cf64e9e5fa7ca (accessed December 1, 2023).

[2]        Turkey and Syria earthquake: latest news, British Red Cross. (n.d.). https://www.redcross.org.uk/stories/disasters-and-emergencies/world/turkey-syria-earthquake (accessed December 1, 2023).

[3]        M. Ozturk, M.H. Arslan, H.H. Korkmaz, Effect on RC buildings of 6 February 2023 Turkey earthquake doublets and new doctrines for seismic design, Engineering Failure Analysis. 153 (2023) 107521. https://doi.org/10.1016/j.engfailanal.2023.107521.

[4]        N. Bektaş, F. Lilik, O. Kegyes-Brassai, Development of a fuzzy inference system based rapid visual screening method for seismic assessment of buildings presented on a case study of URM buildings, Sustainability. 14 (2022) 27.

[5]        N. Bektaş, O. Kegyes-Brassai, Development in Machine Learning Based Rapid Visual Screening Method for Masonry Buildings, in: M.P. Limongelli, P.F. Giordano, S. Quqa, C. Gentile, A. Cigada (Eds.), Experimental Vibration Analysis for Civil Engineering Structures, Springer Nature Switzerland, Cham, 2023: pp. 411–421. 

[6]        E. Harirchian, T. Lahmer, Developing a hierarchical type-2 fuzzy logic model to improve rapid evaluation of earthquake hazard safety of existing buildings, Applied Sciences (Switzerland). 10 (2020) 1384–1399.

How to cite: Bektaş, N.: Enhancing Seismic Safety Assessment Through Development of a Transparent and Adaptive Rapid Visual Screening Method Employing Artificial Intelligence Algorithms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1012, https://doi.org/10.5194/egusphere-egu24-1012, 2024.

EGU24-1041 | ECS | Orals | NH9.6 | Highlight

AI based assessment of flash flood damages to company 

Apoorva Singh, Nivedita Sairam, Kasra Rafiezadeh Shahi, Anna Buch, Chandrika Thulaseedharan Dhanya, and Heidi Kreibich

Flash floods like the flood in 2021 in the west of Germany result in particularly large numbers of fatalities and heavy asset damages. Among the several flood-exposed sectors, companies are severely affected by floods and constitute a significant component of overall flood damages. However, understanding and modeling the underlying processes influencing flash flood losses for companies is specifically challenging due to (1) heterogeneity in terms of sectors, building size and type, number of employees, and equipment, and (2) scarcity of company-specific flood loss data. In comparison to fluvial floods, the influence of flood characteristics and hydro-dynamic processes on damage is different in the case of flash floods.  To tackle this challenge, multi-variate probabilistic flash flood loss models are developed based on feature selection using empirical data from detailed surveys conducted with companies after the flash floods of 2002, 2016, and 2021 in Germany. The machine learning ensemble-based approach of feature selection revealed the significance of the following hazard variables (water depth, flow velocity, contamination), exposure variables (sector, number of employees, size of premise), and vulnerability variables (implementation of precautionary measures, early warning time, flood experience) in determining flood losses. The Bayesian Networks-based flood loss models developed in this study provide probability distributions of estimated losses and as such inherently quantify uncertainties.

How to cite: Singh, A., Sairam, N., Shahi, K. R., Buch, A., Dhanya, C. T., and Kreibich, H.: AI based assessment of flash flood damages to company, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1041, https://doi.org/10.5194/egusphere-egu24-1041, 2024.

EGU24-2761 | ECS | Posters on site | NH9.6

The islanding effect of river basin city-regions under climate changes: vulnerability and resilience 

Chi-Tung Hung, Wen-Yen Lin, and Chun-Fang Liu

This study focusing on the vulnerability and resilience in the downstream areas of the Da-an river basin (Dajia district and Houli district) centeral Taiwan. The study addresses the urban governance on compound disaster in the upstream Da-an river basin, including Taian township and Jhunan township in Miaoli county, Zhuolan township, and the Heping district in Taichung city. The research also explores how these townships adapt to extreme weather impacts and post-pandemic industrial adaptation. Our research employs various methods such as field surveys, in-depth interviews, literature reviews, and statistical data analysis: (1) By investigating and analyzing tourism camping areas in the aforementioned townships, we examine the environmental vulnerability of their industries and land use. This includes environmentally sensitive areas and agricultural and pastoral lands in indigenous areas, as well as issues related to vulnerable policies; (2) Agricultural production and marketing and government responses to different stages of impacts from extreme climates and diseases are being reviewed regarding the adaptive planning of local governments; (3) A vulnerability assessment framework applicable to settlements in islanding areas of the upper Da-an river is constructed by utilizing the Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) for overlay analysis to discuss the relevant assessment influencing factors in camping areas. The research aims to clarify how watershed townships, under the influence of climate change, transform based on local tourism characteristics and agricultural industries post-pandemic. Particularly, it explores the mitigation measures demonstrated by local governments and private operators in the face of climate change and land exposure, showcasing the resilience of governance at different levels of government and private entities. Two aspects are found on this research: (1).The tourism vulnerability of townships in the upper Da-an river basin, particularly the crisis of camping tourism sites and land exposure, along with the island effect of their settlements. (2). Adaptive mechanisms of industrial resilience in watershed townships under the impact of the pandemic.

Keywords: river basin, extreme weather, islanding effect, city resilience, urban disaster, city vulnerability.

How to cite: Hung, C.-T., Lin, W.-Y., and Liu, C.-F.: The islanding effect of river basin city-regions under climate changes: vulnerability and resilience, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2761, https://doi.org/10.5194/egusphere-egu24-2761, 2024.

EGU24-4495 | ECS | Posters on site | NH9.6

Changes in Flood Risk to Cultural Assets Under Climate Change - A Case Study of  Kinmen 

Shou-Chi Chen, Kuo-Chen Ma, Mo-Hsiung Chuang, and Wen-Yen Lin

Amidst global climate change, extreme weather events are becoming increasingly common. The international community has established 'preventive conservation' of cultural assets as a core strategy. Nations are actively devising measures to counter the potential impacts of climate change on cultural assets and developing related adaptive strategies. Particularly noteworthy is the often-overlooked potential risk of natural disasters to cultural assets, which poses a severe threat to these irreplaceable assets.

This study focuses on the Kinmen area of Taiwan and utilizes data provided by the Taiwan Climate Change Projection and Adaptation Knowledge Platform (TCCIP). Employing flood risk maps as the primary analytical tool, it delves into the changing risks faced by cultural assets under climate change and explores how to implement preventive conservation strategies.

The research reveals that during the baseline period (1980-2015), Kinmen had 287 cultural assets, with 4 facing the risk of flooding. According to the extreme weather scenario AR5 (RCP 8.5) provided by TCCIP, it is predicted that various regions will experience more intense rainfall conditions in the mid-21st century (2041-2065), increasing the risk of flooding and leading to more cultural assets (18 in total) being threatened. Therefore, through meteorological data projection and disaster risk assessment, this study advocates for early preventive conservation measures for high-risk cultural assets, aiming to mitigate the potential impact of climate change on these valuable assets.

How to cite: Chen, S.-C., Ma, K.-C., Chuang, M.-H., and Lin, W.-Y.: Changes in Flood Risk to Cultural Assets Under Climate Change - A Case Study of  Kinmen, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4495, https://doi.org/10.5194/egusphere-egu24-4495, 2024.

EGU24-6859 | Posters on site | NH9.6

Study on the impact and adaptation strategies of climate change on infrastructure in coastal communities. 

Mo-Hsiung Chuang, Shyue-Yen Lin, Kuo-Chen Ma, and Cheng-Yu Ku

This study aims to explore the assessment of landslide hazards and adaptation faced by coastal communities under the impact of climate change. Considering the influence of climate change leading to increased frequency of extreme weather events, particularly heavy rainfall, which significantly affects the stability of hill slopes, this research will establish a shallow landslide susceptibility model for extreme rainfall events. This model can comprehensively solve the unsaturated transient Richard's equation and utilize the resultant pore water pressure along with the formula for the safety factor of unsaturated slope stability to construct a comprehensive regional landslide susceptibility analysis module. The module will generate distribution maps depicting the potential for slope collapses during extreme rainfall events. Through this analysis module, the study intends to predict collapse grids influenced by climate change and use Geographic Information Systems to create collapse susceptibility maps. We will overlay these maps with key infrastructure of coastal communities, including emergency response units, to understand the impact of landslide disasters on the infrastructure, emergency response capabilities during disasters, and post-disaster recovery capabilities of coastal communities. Furthermore, the study will explore the impact and adaptation strategies of climate change on infrastructure in coastal communities.

How to cite: Chuang, M.-H., Lin, S.-Y., Ma, K.-C., and Ku, C.-Y.: Study on the impact and adaptation strategies of climate change on infrastructure in coastal communities., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6859, https://doi.org/10.5194/egusphere-egu24-6859, 2024.

EGU24-7335 | ECS | Posters on site | NH9.6

Evaluating Flood Adaptation Effectiveness through Economic Analysis: A Case Study of Surat, India 

Ashish Kumar and Udit Bhatia

Floods are among the most costly natural disasters globally and are projected to increase in frequency and magnitude with a warming climate. To confront increasing flood risks, flood managers need the most cost-effective adaptation actions to reduce economic damage to floodplain infrastructures. Recent research advancements have explored the physical aspects of flood adaptation strategies such as levees, diversions, and barrages. However, implementing adaptation actions requires comprehensive economic analysis before execution due to the substantial capital investment involved. Here, we develop a 1D-2D coupled hydrodynamic flood model in the MIKE+ platform, considering river flow to generate flood inundation maps for various hydraulic inland scenarios. We generate inundation maps for 10-, 50-, 100-, and 200-year return periods of design discharge, considering flood adaptation strategies. Subsequently, we utilize available flood depth-damage functions to calculate expected flood damage and conduct a cost-benefit analysis of the proposed adaptation strategies. We demonstrated the proposed framework for the coastal city of Surat, India. Our results provide the decision matrix to select adaptation strategies based on design standard objectives. The initial assessment highlights that a combination of levee and barrage is more effective than individual levee, barrage, and diversion strategies, particularly in terms of cost-effectiveness in reducing flood damage. Our framework would be beneficial in selecting effective planning strategies for reducing flood damage.

How to cite: Kumar, A. and Bhatia, U.: Evaluating Flood Adaptation Effectiveness through Economic Analysis: A Case Study of Surat, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7335, https://doi.org/10.5194/egusphere-egu24-7335, 2024.

EGU24-10164 | Posters virtual | NH9.6 | Highlight

Debris Management in the Area Affected by the 6 February 2023 Turkey Earthquakes: Detecting Challenges, Hazards and Responses aiming to Effective Disaster Risk Reduction 

Maria Mavrouli, Spyridon Mavroulis, Emmanuel Vassilakis, Ioannis Argyropoulos, Panayotis Carydis, and Efthymios Lekkas

Disasters arising from geophysical hazards have the potential to trigger extensive structural damage upon the built environment within the impacted area. A substantial proportion of debris generated from earthquakes is a consequence of structural collapse during the ground motion, coupled with the urgent demolition of severely damaged and unstable structures in the course of emergency response and recovery. Among the foremost and pivotal measures undertaken during disaster management is the effective management of the generated debris. This task stands as one of the paramount challenges faced by those involved, given its inherent hazards to both the natural environment and public health. These hazards emanate from the presence of hazardous materials within debris from collapses and demolitions.

Numerous challenges and associated hazards emerged in southeastern Turkey after two devastating earthquakes on 6 February 2023 with Mw=7.8 and Mw=7.5 respectively. These seismic events affected a densely populated region encompassing 11 provinces, which included numerous sizable urban centers, such as large cities and towns, along with extensive rural areas comprising countless villages.

The convergence of intense ground motion, accompanied by the occurrence of widespread primary effects, such as coseismic surface ruptures, and the triggering of secondary effects, including mainly but not limited to liquefaction and landslides, culminated in the total or partial collapse of tens of thousands of structures and the extensive leveling of residential areas. This fact gave rise to a debris volume deemed the largest since the 1994 Northridge earthquake and challenging to manage, even within well-organized nations.

In the course of post-event field surveys conducted by the authors within the earthquake-stricken area, various disposal sites established in the most severely affected provinces were identified and assessed for suitability. The field surveys included the utilization of Unmanned Aircraft Systems (UAS) in the disaster-affected areas, complemented by the examination of satellite imagery in the laboratory to evaluate the characteristics of the sites and their immediate surroundings and to monitor the ongoing debris management activities.

The findings indicate that none of the identified sites possessed attributes qualifying them as safe for the treatment and disposal of earthquake debris. Primarily, this inadequacy is attributed to their close proximity to areas densely populated with thousands of residents who engage in daily activities. Furthermore, from the environmental viewpoint, these sites operated either within or in close proximity to surface water bodies. This situation reveals a rush for rapid debris removal and recovery resulting in serious omissions in the preparation of disaster management plans and concessions in their implementation. Consequently, recommendations for effective debris management measures are also proposed in the context of this research based on existing scientific knowledge and operational expertise.

How to cite: Mavrouli, M., Mavroulis, S., Vassilakis, E., Argyropoulos, I., Carydis, P., and Lekkas, E.: Debris Management in the Area Affected by the 6 February 2023 Turkey Earthquakes: Detecting Challenges, Hazards and Responses aiming to Effective Disaster Risk Reduction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10164, https://doi.org/10.5194/egusphere-egu24-10164, 2024.

EGU24-10267 | Orals | NH9.6

Catastrophic (CAT) Bond as Sustainable Finance Instruments: Understanding from Cross-Country Perspectives 

Nandini Suresh, Trupti Mishra, and Devanathan Parthasarathy

Disasters have significant environmental, human, social, economic, and financial impacts. These effects are potentially long-lasting and have multi-generational consequences. Due to climate change, disasters have cascading and compound effects, heightening the financial risks. However, the number of countries issuing CAT Bonds as a financial instrument for tackling the financial burden of disasters is less than 5% as of 2023. This study explores the need to use CAT Bonds as a risk transfer mechanism that allows governments and insurers to spread their climate change risk across capital markets. It presents a comprehensive cross-country level analysis of the potential drivers that influence the CAT bond issuance at a sovereign level for 131 countries from 2016 to 2021 to understand their significance for issuers and non-issuers of CAT Bonds. These potential drivers were filtered after an exploratory factor analysis. Nonetheless, the imbalance between the number of issuers and non-issuers has resulted in poor classification accuracy results and bias. Hence, this study employs Logistic Regression with Synthetic Minority Over-sampling Technique (SMOTE) and without SMOTE. Further, a comparison study between the effective CAT Bond issuance in the Philippines against non-issuance in India was conducted to determine the obstacles in the Indian setting. The result from the study indicates that a country’s exposure to hazards, population growth, investment freedom, regulatory quality, gross budget balance, stock traded and rule of law have statistically significant impact on the issue of CAT Bond. Highlighting the Indian context, the major challenges the country faces in issuing CAT Bonds are its stringent rule of law, regulatory inferiority, economic uncertainty, and less stock traded.

How to cite: Suresh, N., Mishra, T., and Parthasarathy, D.: Catastrophic (CAT) Bond as Sustainable Finance Instruments: Understanding from Cross-Country Perspectives, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10267, https://doi.org/10.5194/egusphere-egu24-10267, 2024.

EGU24-10438 | Posters on site | NH9.6

Decision systems for nature based solutions to mitigate floods 

Maria Bostenaru Dan

In the 20th century often the solution to mitigate floods was putting a corset of reinforced concrete to rivers. An example is one of the case studies in our project which we will detail, the Vidraru dam on Arges river, where a neighbourhood was built after the 1940 floods. In the 21st century however the approach is different. Several years ago a communication session was dedicated to achieving more flood resilience through floodplains on the Danube, and also several years ago a doctorate was concluded on landscape architecture solutions to mitigate floods on the Rhine. The geographic areas are different, and so are the localities and the early 20th century constructions which might be affected by floods and their relationship to the city - ex. peripheral Siedlung in Germany. Today one can look more systematically. A recent course of the European Commission offered insights to natural disaster mitigation through nature based solutions across the globe. We also reviewed literature in a nice part of this: decision systems to prioritise interventions based on cost-benefit to mitigate floods. On this basis, identifying gaps - the papers cover some of the aspects of this issue at once, not all of them - we elaborated a decision tree and its taxonomy according to criteria related to the building and the river landscape. The indices to quantify these criteria will be shown. This will be exemplified in case studies comprising Bucharest, Rome and Lisbon. It can be converted into an ontology for software planning, as in numerous European projects related to protection of architectural and archaeological heritage protected from climate change with IT support which go even further, towards Internet of Things. The context of future possible projects will be shown in the discussion.

How to cite: Bostenaru Dan, M.: Decision systems for nature based solutions to mitigate floods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10438, https://doi.org/10.5194/egusphere-egu24-10438, 2024.

EGU24-10972 | Posters on site | NH9.6

A new revetment system based on high-strength steel-wire mesh filled with rock for coastal erosion control 

Mohammad Heidarzadeh, Mahan Sheibani, and Roberto J. Luis-Fonseca

Recent years have seen a rise in both the intensity and frequency of storms, resulting in damage to coastal protection systems across the UK and globally. As a result, these systems have demanded substantial maintenance. For example, the gabion protection at Chesil Beach (Portland, UK) was severely damaged during the storms of February 2014, necessitating restoration costing at least £600 million. Similarly, the rock armor protection at Beesands (Devon, UK) also suffered damage in the same storm. These incidents highlight the urgent need to develop more resilient and innovative coastal defense systems. This fact gains further significance considering the UK's extensive coastal defense sector, necessitated by its vast coastlines with a length of approximately 30,000 km. According to various sources, approximately 18% of UK coastlines are protected with defense systems.

Here, we introduce an innovative coastal defense system comprising high-strength steel-wire mesh filled with rock. The system is securely fastened using tension rod ensuring its long-term integrity and stability. The diamond mesh in this system features units measuring 8.3 cm in width and 14.3 cm in height. These units are filled with uniformly-sized rock units, typically ranging in diameter from 15 cm to 25 cm. The high-tensile stainless-steel mesh, referred to as 'Tecco Cell’, is supplied by Geobrugg Inc. Therefore, we name this system as Tecco Cell (TC) revetment hereafter. The TC revetment carries the advantages of both gabion and rock revetments and minimizes their drawbacks. Gabion baskets or mattresses are susceptible to a significant weakness: their wire baskets can be damaged or broken by the force of strong waves. For rock armor, the rock units are displaced by strong waves resulting in the collapse of the defense system. The TC revetment systems alleviate both drawbacks; their high-strength mesh resists waves, while the tension rods, combined with the mesh, stabilize the system even against the strongest waves. The TC revetment was installed along a 120-meter stretch of the coast in Beesands (Devon, UK) in 2016. Over the past seven years, it has effectively defended the coast with minimal maintenance needs. Despite encountering several winter storms since its installation in 2016, the TC system in Beesands has remained resilient.

The purpose of this research is to report the results of two phases of laboratory tests on a 1/10 scaled model of a TC revetment. In Phase 1, eight tests were delivered on three types of revetments: gabion (two tests), rock armor (two tests) and TC revetments (four tests). In Phase 2, we conducted 32 tests comparing TC (16 tests) and rock armor (16 tests) revetments. It was found that the TC revetment consistently outperformed rock armor in terms of run up control and wave oscillations with an average runup reduction of 15%. We developed empirical equations for wave runup.

Thanks to the successful implementation of the TC revetment in Beesnads (UK), there is now consideration for applying this new coastal defense system in Ritoque (Chile) and along the northwestern coast of Italy.

How to cite: Heidarzadeh, M., Sheibani, M., and Luis-Fonseca, R. J.: A new revetment system based on high-strength steel-wire mesh filled with rock for coastal erosion control, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10972, https://doi.org/10.5194/egusphere-egu24-10972, 2024.

EGU24-11615 | ECS | Posters on site | NH9.6 | Highlight

Flood risk to cultural heritage: a voyage through scales 

Claudia De Lucia, Fabio Castelli, and Chiara Arrighi

Floods are among the most frequent and damaging events worldwide, affecting population and residence buildings, economic activities, agriculture but also cultural heritage (hereinafter CH). Flood impacts to CH are very challenging to evaluate, due to their intangible values (e.g., spiritual, social, aesthetic) and difficulty in replacing unique objects. These aspects make the evaluation of CH exposure and vulnerability complex, also depending on the scale of analysis adopted.

This work aims at illustrating the differences in risk evaluations, as the scale of analysis varies. It highlights the information usually available for flood risk analysis of CH when moving from a large scale, e.g. regional/national level, to building scale, with different stakeholders’ perspectives, and demonstrates a very detailed approach for hazard modelling inside the CH building. The regional/national scale considers CH often as a point feature and usually aims at identifying geographic damage hotspots, i.e., river basin authority perspective. Few information is available at this scale, mostly hazard classification (low to high probability of occurrence) and often a tailored taxonomy for exposed assets has to be developed.

The site/city scale usually considers cultural heritage as a polygon feature with a better description of flood depths and of building characteristics such as the building type (e.g., religious or rural), the presence of underground floors or the presence of artworks. It identifies risk priorities and potential damage, i.e. it adopts a mayors’ perspective.

The building scale analysis, i.e., heritage manager perspective, requires moving towards a 3D geometric description of the cultural building by incorporating elevations of features with respect to the terrain to better understand actual inundation depths and their effects. On-site inspections are required to measure specific characteristics of the structure such as the location and the height of the openings, which let floodwater enter inside the building. Such information allows for a downscaling of a city inundation model, that provides the hydrograph to assign as boundary condition to the building.

The method is applied to the Florence area (central Italy) and to a museum inside the city center. The 2D inundation model at building scale shows the inundation inside the basement of the museum, formerly a crypt, where a part of the permanent art collection is exhibited. The museum model reveals the flow and the quantity of water within different part of the building. A comparison with the historical records of the 1966 flood in the Museum, confirms the findings of the simulation.

Acknowledgments. This work received co-funding by (i) Regione Toscana, Fondo per lo Sviluppo e la Coesione 2014-2020, Project “GiovaniSì” and by (ii) the RETURN Extended Partnership, European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005)

How to cite: De Lucia, C., Castelli, F., and Arrighi, C.: Flood risk to cultural heritage: a voyage through scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11615, https://doi.org/10.5194/egusphere-egu24-11615, 2024.

EGU24-12992 | ECS | Orals | NH9.6 | Highlight

Quantifying the Economic Impact of Floods on Businesses with a Network Analysis 

Elisa Grazia Lucia Nobile, Marcello Arosio, Alessandro Caiani, Jlenia Di Noia, and Mario Lloyd Virgilio Martina

Climate change and urbanization are intensifying economic losses from natural hazards, particularly floods, making robust risk assessment crucial. However, traditional risk assessment frameworks fall short in representing the full costs of natural hazards, as they typically focus only on direct damages, like property damages, neglecting the indirect tangible damages. One of the key objectives of this research is to quantify the indirect economic impacts resulting from business interruption (i.e. reduction in production due to physical damages in areas directly affected by the hazard) and contingent business interruption (i.e. production losses of suppliers and customers of companies directly affected by the hazard), and the associated macroeconomic impact. This study addresses this gap by employing a multidisciplinary approach, integrating network theory with traditional Input-Output (I-O) economic models. This integration not only enhances the representation of the interconnectedness inherent in socio-economic systems but also aids in quantifying the often-overlooked indirect effects of floods. The methodology integrates high-resolution input-output tables, geolocalized firms and spatial information on critical infrastructures, like the transportation network. This comprehensive approach not only provides a detailed view of the cascading economic effects, but it could also enhance traditional I-O models by incorporating information on geographical substitutability. The detailed understanding of economic dependencies and network vulnerabilities is crucial in assessing the full costs of floods. Applied to a significant Italian region recently struck by a severe flood, the approach allows for the mapping of the region's economic structure as an interconnected network of economic sectors. Network theory measures and tools are then employed to identify central and vulnerable nodes, enabling a detailed analysis of shock propagation within supply chains. The findings of this research are not only critical for policy-makers and urban planners in adopting more effective flood risk management strategies but also offer valuable insights for the insurance sector in terms of understanding and mitigating collective risk. In conclusion, this study advocates for a shift from traditional risk assessment models towards a more holistic, systemic approach, thereby enhancing societal resilience to the multifaceted impacts of natural hazards.

How to cite: Nobile, E. G. L., Arosio, M., Caiani, A., Di Noia, J., and Martina, M. L. V.: Quantifying the Economic Impact of Floods on Businesses with a Network Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12992, https://doi.org/10.5194/egusphere-egu24-12992, 2024.

EGU24-15873 | ECS | Posters on site | NH9.6

Machine-learning based feature selection for a regional flood damage model 

Daniela Rodriguez Castro, Kasra Rafiezadeh Shahi, Nivedita Sairam, Melanie Fischer, Guilherme Samprogna Mohor, Annegret Thieken, Benjamin Dewals, and Heidi Kreibich

After the 2021 floods in Europe, independent data collection initiatives were undertaken in the impacted areas of Belgium and Germany. The resulting datasets at residential building level contain valuable information on hazard characteristics, vulnerability of exposed assets, socio-economic factors and coping capacity of the inhabitants and the emergency services (i.e., emergency and precautionary measures). A transnational analysis of these datasets enhances our understanding of flood damage mechanisms.

The data analysed resulted from 420, and 609 standardized surveys with private households affected by the 2021 floods in Belgium and Germany, respectively. Of these, 277 correspond to the area of Rhineland-Palatinate, and 332 were from North Rhine-Westphalia in Germany. A set of 64 potential damage influencing variables were harmonized across the datasets. The initial phase involved conducting descriptive statistics of the selected variables in three regions: the Vesdre valley in Belgium, the Ahr valley in Rhineland-Palatinate (Germany) and affected regions in North Rhine-Westphalia (Germany).

In a second step, the most influential variables for predicting flood damage to residential buildings were identified by means of feature selection. This was conducted using the linear approaches multilinear with k-best predictors, and Elastic net regression as well as the non-linear techniques Random Forest and Conditional Inference Trees. Total building loss and the total content loss were used as target values. Based on different evaluation metrics, the most important variables describing absolute building damage and absolute contents damage in the three analyzed areas, were identified.

Commonalities and differences in flood characteristics and damage in the three regions will be presented and interpreted in detail.

How to cite: Rodriguez Castro, D., Rafiezadeh Shahi, K., Sairam, N., Fischer, M., Samprogna Mohor, G., Thieken, A., Dewals, B., and Kreibich, H.: Machine-learning based feature selection for a regional flood damage model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15873, https://doi.org/10.5194/egusphere-egu24-15873, 2024.

EGU24-17113 | ECS | Orals | NH9.6

New tools for the estimation of direct and indirect impacts to Italian economic activities 

Marta Ballocci, Daniela Molinari, Francesco Ballio, Giovanni Marin, Alice Gallazzi, and Panagiotis Asadiris

Flood-related damage has increased dramatically in recent decades with direct and indirect economic impacts accounting for a large share of gross national products. Therefore, there is an urgent need to acquire more quantitative knowledge about flood damage to mitigate economic losses and reduce exposure to flood risk.

Firms are especially affected in case of flood. Still, flood direct damage assessment to businesses is hindered by the paucity of available data to characterize the enterprises, the lack of high-quality damage data to derive new models or validate existing ones, and the high variability of activity types which hampers generalization. On the indirect damage side, the existing literature predominantly focus on estimating damage at the macro scale, leaving a gap in understanding the specific impact on individual firms.

This study contributes at improving knowledge about types and extent of damage of flood events on economic activities through the analysis of empirical data, focusing on direct and indirect damage at the micro-scale, with specific reference to the Italian context. The investigated data derive from observed direct damage records collected after six flood events in Italy. The information on the surface of the building, the typology of the affected firms (i.e., NACE category) as well as on local water depth levels and the classification in damage components (building, equipment, and stock) permitted to develop an econometric model to forecast the direct damage and to analyze the mechanisms of flood damage across the economic sectors. The original dataset was then enriched with information included in the financial statement of flooded activities that has been used to investigate indirect damage.

Despite characterized by significant uncertainty, obtained results supply first tools for the prediction of flood direct damage and for the quantification of indirect damages to firms for the Italian context, in the support of more effective risk mitigation actions. In fact, the model identifies the more vulnerable elements within the business sectors orienting modelers and decision-makers choices.

How to cite: Ballocci, M., Molinari, D., Ballio, F., Marin, G., Gallazzi, A., and Asadiris, P.: New tools for the estimation of direct and indirect impacts to Italian economic activities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17113, https://doi.org/10.5194/egusphere-egu24-17113, 2024.

EGU24-17388 | ECS | Posters on site | NH9.6

Mapping of Active Deformation Areas using Multi-Temporal InSAR data. 

Enrico Ciracì, Carmine Frascella, Filippo Santarelli, Emanuela Valerio, Stefano Scancella, and Andrea Chessa
In this study, We use data from the European Space Agency Sentinel-1 mission to map areas affected by active deformation processes over the Italian territory. To achieve this goal, we use data acquired by the satellite mission between 2018 and 2023, and we generate ground deformation products using a multi-temporal interferometric approach (Persistent Scatterer Interferometry - PS).
We automatically delimitate areas characterized by homogeneous deformation by employing a novel spatial clustering algorithm that analyzes the PS average annual displacement rate over the considered temporal period. For each cluster, we determine its boundaries and average deformation statistics.
Here, we present the algorithm implementation details and discuss the results obtained by applying the methodology to deformation observations acquired from ascending and descending geometries and projected 2D East-West and Vertical deformation products. We use the algorithm to process observations acquired over two validation sites, and we determine its performance over large spatial scales and in proximity to critical national infrastructures.
Our results allow us to generate a complete, nationwide dataset of active deformation areas, highlighting how adopting automatic strategies to handle large volumes of data is crucial nowadays.

How to cite: Ciracì, E., Frascella, C., Santarelli, F., Valerio, E., Scancella, S., and Chessa, A.: Mapping of Active Deformation Areas using Multi-Temporal InSAR data., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17388, https://doi.org/10.5194/egusphere-egu24-17388, 2024.

Disaster preparedness and risk reduction is one of the most valuable research topics from both seismological and societal aspects to save lives. Scenario loss assessments help disaster managers to conceive an idea about what to expect and how to best prepare for the disaster. Prior to providing such scenario loss estimates, it is imperative to conduct an evaluation of the utilized program and its method. In the absence of information regarding the reliability of the assessments, an evaluation of potential future losses becomes challenging and even unreliable.

There are multiple tools available for rapid earthquake loss estimation purposes. 'Quake Loss Assessment for Response and Mitigation' (QLARM) is one of the few established programs, existing since 2002. It is a computer program used by the International Centre for Earth Simulation in Geneva, Switzerland, to issue timely reports on both building damage and human losses for potentially damaging earthquakes. QLARM uses 2013 population information for approximately 2 million settlements world-wide along with the building information initially taken from the World Housing Encyclopedia. These settlements are then classified into distributions of building vulnerabilities according to the six classes in EMS98 and seismic intensity fields are estimated for each earthquake to compute the expected losses. 'Loss-Calculator' on the other hand, is a new Python program that employs a different approach than QLARM. It uses detailed building-by-building information along with the population assigned to each building based on the buildings’ size and types. The buildings in the Loss-Calculator are classified into numerous classes, following the taxonomy of the Global Earthquake Model. Losses are computed based on ground-motion fields using standard intensity measures like peak ground acceleration (PGA) or spectral accelerations (SA).

We first evaluate the accuracy of both tools for several destructive past earthquakes to explore the uncertainty range of results and identify potentially necessary calibration or improvements in the input data, e.g. the earthquake shaking, population numbers, settlement and building locations. To focus on relevant events with a high death toll, we selected earthquakes in Iran, such as the Rudbar-Manjil (Mw=7.4) and the Qayen (Mw=7.3) earthquakes with fatalities of around 40,000 and 1,500, respectively. This comparison includes not only the absolute value of the losses, but also their detailed spatial distribution. We also compare the loss assessments using different possible inputs, such as different building information and intensity measure fields to achieve the goals.

Furthermore, we estimate losses expected to occur in possible future earthquakes by computing probable earthquake scenarios. These scenarios prove the need for serious disaster preparation and highlight the likely locations of largest losses or most affected people. We introduce high-resolution spatial distributions of losses for improved disaster preparedness planning and show how the detailed knowledge of building locations can improve loss assessments.

How to cite: Evaz Zadeh, T., Wyss, M., and Schorlemmer, D.: Earthquake loss assessments methods - Comparison and new developments shown on past and future earthquake scenarios for Iran, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18163, https://doi.org/10.5194/egusphere-egu24-18163, 2024.

EGU24-18463 | Orals | NH9.6

Assessing subsidence-induced damage on heritage: an integrated remote sensing and structural modelling approach 

Giorgia Giardina, Elpida Georgiou, Raymond Brouwers, Dominika Malinowska, Max Hendriks, and Pietro Milillo

Cultural heritage sites all over the world are increasingly threatened by regional-scale subsidence. Addressing this issue necessitates a deep understanding of how ground settlements impact structural integrity. Traditional approaches, primarily reliant on in-situ investigations, are not only costly but also constrained by their installation in anticipated vulnerable structures. Recent advances in satellite technologies, historically used in geophysical studies of natural phenomena like glaciers and earthquakes, have shown potential in detecting structural deformations. In particular, Interferometric Synthetic Aperture Radar (InSAR) techniques have the capability to measure ground subsidence and building displacements with millimetric precision, they are independent from weather and light conditions, and can provide frequent, weekly updates over extensive areas. Furthermore, the availability of historical data enables retrospective monitoring, eliminating the requirement for pre-installed in-situ monitoring systems. Nevertheless, the interpretation of InSAR data in isolation falls short without correlating it to structural damage.

This study aimed to bridge the existing gap by integrating InSAR monitoring with Finite Element Method (FEM) modelling, specifically applied to a historic church in Poland affected by mining-induced ground settlements. The objective was to predict the structural damage over time caused by subsidence at this heritage site. InSAR data for a reference region, including the area around the church, was acquired and processed using Multi-Temporal InSAR techniques. This was complemented by regional-scale interpolation to address data gaps near the church. These displacement measurements were then incorporated into a computational model of the church, to estimate the level of structural damage. The FEM model, informed by InSAR-derived displacements, was used to assess the impact of various factors on the church's structural response. These factors included settlement profiles and soil-structure interaction characteristics. Through the proposed integration, we aimed to gain critical insights into the resilience of cultural heritage sites and develop novel, practical tools for analysing structures at risk.

How to cite: Giardina, G., Georgiou, E., Brouwers, R., Malinowska, D., Hendriks, M., and Milillo, P.: Assessing subsidence-induced damage on heritage: an integrated remote sensing and structural modelling approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18463, https://doi.org/10.5194/egusphere-egu24-18463, 2024.

EGU24-18643 | Posters on site | NH9.6 | Highlight

Geospatial and remote sensing analysis for earthquake risk management: The case study of Ancient Olympia archaeological site.  

Stavroula Alatza, Nikolaos Stasinos, Nikolaos Stathopoulos, Marietta Papakonstantinou, Michail-Christos Tsoutsos, and Charalampos Kontoes

The Western Greece is one of the most tectonically active regions in the Mediterranean Sea, due to the subduction of the African plate underneath the Eurasian plate. The past years, major earthquakes occurred in Western Greece, causing destructions and casualties. Ancient Olympia, located in the North West of the Peloponnese in Western Greece, combines a great cultural background with natural beauty and is also associated with the Olympic Games. It is among the most visited archaeological sites in Greece, as it combines cultural tourism, eco-tourism and sports tourism. However, the complex tectonic field of Western Greece, including the broader area around Ancient Olympia, raises awareness and dictates the adoption of preventive and recovery measures in case of an earthquake risk in Western Peloponnese. Therefore, we propose an emergency and recovery plan for an earthquake risk scenario, that will be implemented in the broader area around the archaeological site of Ancient Olympia. Satellite and geospatial data are processed to extract all necessary thematic information. Additionally, multi-temporal InSAR analysis of Sentinel-1 images, is performed to identify areas exposed to ground deformation phenomena, therefore vulnerable during an earthquake. Detailed thematic information layers, combined with the identification of ground instabilities in the wider area around Ancient Olympia, will contribute to an efficient evacuation and reconstruction plan. Since cultural heritage sites are often exposed to various hazards, including geohazards, preparedness, risk assessment and emergency management near cultural heritage sites, is of great importance for their protection and preservation.

 

Acknowledgements

The research was funded by the Working Programme 2021 under the Caroline Herschel Framework Partnership Agreement on Copernicus User Uptake.

How to cite: Alatza, S., Stasinos, N., Stathopoulos, N., Papakonstantinou, M., Tsoutsos, M.-C., and Kontoes, C.: Geospatial and remote sensing analysis for earthquake risk management: The case study of Ancient Olympia archaeological site. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18643, https://doi.org/10.5194/egusphere-egu24-18643, 2024.

EGU24-18789 | ECS | Orals | NH9.6

Developing structural-financial flood damage curves for residential buildings 

Guilherme Samprogna Mohor and Annegret Thieken

The documentation and quantification of flood impacts is required by multiple actors, such as public administrators, insurers and scientists, for multiple reasons, such as planning, mitigating, projecting or even forecasting. Collecting and analysing impact data is however not systematically undertaken. Direct flood impacts can be documented as structural (or physical) or financial damage. Structural damage is described as an ordered classification with five grades, from moist and dirt, to wall cracking, up to complete collapse. The financial damage is rather documented as absolute or relative damage, i.e. the ratio between repair costs and the building value, which allows for an easier comparability. Both structural and financial damage are at times documented and numerical models have been developed for both types. Models are frequently used to estimate damage of undocumented cases and make projections. Yet, large uncertainties remain and each model has different data requirements, making them sometimes inapplicable for a certain area or after a certain flooding event. In a joint work, we have shown that the documentation of structural damage need not be undertaken on site, but can be accomplished for large areas through remote sensing, when quality aerial data is available. Here, we also explore the relationship between the two impact types, structural and financial damage, to allow for a conversion from structural to financial damage, complementing the data gathering obviating the labour- and time-intensive on-site surveys. The work is based on survey data gathered after eight flood events in Germany. The data can be regarded representative and transferable to Europe as most buildings are of masonry and have a cellar.

How to cite: Samprogna Mohor, G. and Thieken, A.: Developing structural-financial flood damage curves for residential buildings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18789, https://doi.org/10.5194/egusphere-egu24-18789, 2024.

EGU24-19185 | ECS | Orals | NH9.6

Contribution of coupling hydraulic and economic models at the building scale for assessing flood adaptation 

David Nortes Martínez, Frédéric Grelot, Pascal Finaud-Guyot, Marie Arragon, and Freddy Vinet
In France, adaptation to floods has been the subject of a clearly identified public policy, at least since the first versions of the action programs for flood prevention launched in 2002. Axis 5 of these action programs aims to reduce the vulnerability of people and property by implementing flood adaptation measures at the "individual" level, i.e. dwellings, economic or agricultural activities.

In the specific case of dwellings, flood adaptation can have two objectives: to increase human safety and to reduce material damage. Neither of these objectives has an established method for measuring the effectiveness of the recommended measures. In fact, although it has been identified as a priority, the evaluation of the effectiveness of proposed measures remains underdeveloped and, as a consequence, professionals, especially those performing vulnerability assessments, lack the tools to assess the validity of their recommendations.
Furthermore, a number of studies show that effectiveness assessment can call into question the very validity of programs that are designed on the basis of broad principles but applied to specific areas.

This work presents an original spatially explicit, process-based (synthetic) 3D model at the building level, combining hydraulic and economic modules, and we show how it can respond to this need for assessing the effectiveness of flood adaptation measures. This model relies on the characterization of the vulnerability of spatially explicit (xyz) elementary building components based on expert knowledge and on the classical weir law to determine the water flow exchange between the exterior and interior of a building and between rooms. The combination of these elements allows us to i) simulate the hydraulic behavior of the building using flood duration and exterior flood depth as the main flood parameters; ii) estimate the flood damage caused by a flood event; and iii) dynamically evaluate the danger of the path(s) to safety inside the building based on pedestrian stability studies.
Real case buildings are used to test the model. The selected buildings benefited from a French vulnerability reduction program called "Alabri". This program offers vulnerability diagnostics of buildings to voluntary owners and, based on the diagnostics, recommendations for vulnerability reduction. Field work and interviews show that the most frequently proposed measures are aimed at preventing water infiltration inside buildings (with temporary barrier systems) and creating refuge areas for people. The hypothesis is that the combination of both measures is sufficient to reduce flood damage and ensure the safety of the occupants of a dwelling. We also use specific hydraulic conditions to test these measures and their combination.

This approach allows us to perform contextual analyses and provide insights into the effectiveness of the recommended measures and their combination. This approach also allows us to analyze the extent to which the methodology we propose is consistent with the approach chosen by the professionals who carried out the diagnoses. Finally, it allows us to explore the potential of synthetic models for the ex ante analysis of mitigation policies.

How to cite: Nortes Martínez, D., Grelot, F., Finaud-Guyot, P., Arragon, M., and Vinet, F.: Contribution of coupling hydraulic and economic models at the building scale for assessing flood adaptation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19185, https://doi.org/10.5194/egusphere-egu24-19185, 2024.

EGU24-19500 | ECS | Posters on site | NH9.6

Analysis of the spatial distribution of perceived flood damage in Italy 

Federica Zambrini, Giovanni Menduni, and Sara D'Alessandro

Being able to quantify the possible flood damage in a territory is a pivotal matter while designing strategies to mitigate risk. In this context, data driven quick assessment can be an useful tool to better understand the territory needs and to establish priorities.

With our work we have been working on the spatial distribution of perceived flood damage in Italy, analyzing data coming from more than 45000 citizens’ declarations registered after events occurred in Italy between 2013 and 2021. We focused on events which required the national state of emergency, which activated the procedure of claims' collection carried out by regions. Working on such material, we’ve been able to identify the subset of data which are specifically associated to flood events and to geolocalize them. Once the definitive dataset was ready we had a framework of the perceived damage at square meter in the country, which has been analyzed at different spatial scales. The work highlighted a great variability and inhomogeinity within different areas in the country. A further step of the analysis tried to link the perceived damage to the characteristic of the society and the territory, explaining what drives the perception of damage.

How to cite: Zambrini, F., Menduni, G., and D'Alessandro, S.: Analysis of the spatial distribution of perceived flood damage in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19500, https://doi.org/10.5194/egusphere-egu24-19500, 2024.

Three major earthquake disasters occurred during 2023: Turkey M7.8, February 6, Morocco M6.8 August 9, Afghanistan M6.5 November 10. The final cost in lives reported were 59500, 2946 and 1482 fatalities, respectively. QLARM (Quake Loss Alerts for Recovery and Mitigation) is a computer tool used to estimate damage, fatalities and injured for potentially fatal earthquakes worldwide. Using QLARM (e. g. Wyss 2014, 2023), my estimates were the only red alerts for these earthquakes issued within minutes. Red alerts are the highest level of urgency that can be given. The fatality estimates were 2000-6000 for Turkey, 100 to 1000 for Morocco, and a total of 500 to 2000 for the Afghanistan earthquake swarm (three messages within 4 days). These alerts were distributed by SMS to anyone who signed up to receive the QLARM alerts (signup link given below) free of charge. These three red alerts were received by subscribers within 30, 31, and 18 minutes, respectively. The USGS hypocenter and magnitude estimates arrived within 29, 24 and 30 minutes, respectively. The QLARM fatality estimates were based on the first information on source parameters for these three earthquakes available worldwide, which came from GFZ (Geophysicalisches ForschungsZentrum, Potsdam) after 7, 8 and 7 minutes, respectively.

The purpose of the QLARM alerts is to activate first responders and government in case of earthquake disasters, and also to furnish quantitative information for the many large magnitude earthquakes that were not likely to have killed many and therefore for which an international response was not needed. During the year 2023, QLARM issued a total of 60 alerts with a median delay of 22 minutes.

The chief reason for the initial fatality underestimates for the Turkey and Morocco disasters was that the source was assumed to be a point, which was appropriate only for the Afghanistan sequence, where the fatality estimate was correct. The information on the lengths, direction and endpoints of the rupture became available only later for the Turkey and Morocco cases. Using line sources for the Turkey and Morocco earthquakes brings the fatality estimates closer to the reported ones, but they are still lower than what was reported, most likely due to the construction of buildings in these two regions, which are apparently weaker than assumed in the QLARM data set. The most important means of improving near-real-time estimates of earthquake losses is to implement rapid estimates of rupture lengths and azimuths.

References:

International Centre for Earth Simulation (ICES). QLARM sign-up. https://www.icesfoundation.org/Pages/CustomPage.aspx?ID=122, Retrieved January 09, 2024.

Wyss, M. (2014). Ten years of real-time earthquake loss alerts. In Earthquake hazard, risk and disasters (pp. 143-165). Academic Press.

Wyss, M. (2023). Quantitative Earthquake Loss Estimates the New Frontier. Seismological Research Letters, 94(6), 2569-2574.

How to cite: Wyss, M.: Estimates of the number of fatalities within minutes for the three great earthquake disasters in 2023, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22242, https://doi.org/10.5194/egusphere-egu24-22242, 2024.

With frequent extreme heat events (EHEs), rapid urbanization, and uneven social development, the impact of EHEs on health has attracted increasing attention. Comprehensive assessment of heat-related health risks is important for tolerating hot weather. To address the limitations of previous assessment methods in regard to the appropriateness of indicators and the fineness of mapping scales, in this paper, we proposed a quantitative method for assessing heat-related health risks at the grid scale. A combination of multisource remote sensing data and demographic-socioeconomic data was utilized to develop an integrated heat health risk index (HRI) that considers the three dimensions of heat hazards, human exposure, and vulnerability in the Yangtze River Delta (YRD). Compensating for the limitations of land surface temperature (LST) and meteorological station data, daily maximum and minimum air temperatures were retrieved to characterize heat hazards and subsequently calculate the hazard index. Gridded population density data were also developed based on nighttime light data to calculate the exposure index. Multidimensional indicators were derived to describe vulnerability, including demographic characteristics, socioeconomic conditions, infrastructure status, governance, and medical resources. By combining the hazard, exposure, and vulnerability indices, an HRI map of the YRD was developed. Furthermore, the spatial heterogeneity and the dominant factors of the heat health risk were examined. The high-risk areas were predominantly concentrated in southern Jiangsu, the Shanghai-Hangzhou Bay urban agglomeration, and the central urban area of prefecture-level cities. This phenomenon suggests synergy between increased human exposure and heat hazards in these metropolitan areas. Due to a low economic development level, the resilience against heat risks in underdeveloped regions such as northern Anhui is low. This study contributes to the identification of areas vulnerable to heat stress, which can help decision-makers optimize local urban heat risk management strategies.

How to cite: Wu, H., Pan, Y., Zhao, C., and Zhu, Y.: Spatially explicit assessment of heat health risk in the Yangtze River Delta, China using multi-source remote sensing and socio-economic data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2194, https://doi.org/10.5194/egusphere-egu24-2194, 2024.

EGU24-4281 | Posters on site | NH9.8

Risk Mapping and Evacuation Analysis of Vulnerable Population under Climate Change - a Case Study in New Taipei City, Taiwan. 

Kai Yuan Ke, Hsiang Kuan Chang, Ching Ling Li, and Yu Fen Cheng

The objective of this study is to investigate the flooding effect on the evacuation safety of vulnerable populations in the context of disaster response and climate change impact. The case study of New Taipei City, Taiwan, is introduced. Initially, we establish an urban flood drainage model, NTU-2DFIM, which includes a watershed rainfall-runoff model, a one-dimensional hydraulic model for regional drainage and stormwater sewers, and a two-dimensional surface flood model. After calibration and validation, the IPCC AR6 RCP8.5 climate change scenario is applied to simulate the flooding. Regarding vulnerable groups, which include the elderly (65 years and above), children (5 years and below), low to middle-income households, people with disabilities, solitary elderly individuals, and individuals with no formal education, a spatial autocorrelation analysis is conducted using the Basic Statistical Area to identify hotspots of vulnerable populations. Subsequently, in these hotspot areas, together with nearby evacuation shelters, service coverage analysis is performed. Additionally, road network analysis is conducted by considering flood-induced obstacles to determine optimal evacuation routes. With the above risk mapping process, the results can guide individuals in formulating emergency response plans for household and community, as well as providing public authorities with insights for adjusting shelter locations and planning transportation for the evacuation of vulnerable groups.

How to cite: Ke, K. Y., Chang, H. K., Li, C. L., and Cheng, Y. F.: Risk Mapping and Evacuation Analysis of Vulnerable Population under Climate Change - a Case Study in New Taipei City, Taiwan., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4281, https://doi.org/10.5194/egusphere-egu24-4281, 2024.

EGU24-5529 | ECS | Orals | NH9.8 | Highlight

Flood impacts and adaption for transportation 

Weiping Wang

The adverse effect of climate change continues to expand, and the risks of flooding are increasing. The transport system is crucial for daily life and threatened heavily by floods. Despite advances in emergency management for transportation, we still lack an integrated framework to examine the impact of transport system under floods. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The framework has three parts: (1) a simulation model to represent traffic, heterogeneous user demand, and route choice in a transportation network; (2) a flood simulator using future runoff scenarios generated from global climate models and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the traffic simulation system, and quantifies the flood impact on a transportation system. This framework is illustrated with different cases studies including the Chinese highway network, urban transportation networks in 40 cities in China and road traffic system in the Guangdong-Hong Kong-Macao Greater Bay Area. Because of climate change, adaptation strategies are critical for mitigating future flood damage. Our approach provides a quantitative assessment tool to evaluate the effectiveness of adaptation measures. The results show that for different global climate models, the associated flood damage to a transportation system is not linearly correlated with the forcing levels, or with future years and floods in different years have variable impacts on regional connectivity. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.

How to cite: Wang, W.: Flood impacts and adaption for transportation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5529, https://doi.org/10.5194/egusphere-egu24-5529, 2024.

EGU24-8977 | Posters virtual | NH9.8

Deformation Time-series Analysis and Disaster Potentiality Inversion by Short Baseline Interferometry Measurement 

Wang Xiaoqing, Wu Junli, Zhang Peng, Sun Zhanyi, Wang Yongshang, Zhang Qinglan, and Liang Shenghao

Synthetic aperture radar interferometry (InSAR) measurement technology is a new remote sensing technology that can effectively monitor slight land deformation. Compared with traditional monitoring technology, InSAR technology has the advantages of wide coverage, all-weather and low cost, providing a technical means of high-resolution, high-precision and low-cost for hidden geological hazard identification and deformation monitoring along pipelines. For purpose of this paper, considering the complex terrains of research area, SBAS-InSAR technology was adopted for deformation information extraction. This technology performs better in identifying fast deformation by controlling temporal and perpendicular baseline thresholds, which is able to prevent temporal de-coherence caused by fast deformation. In this paper, we performed deformation time-series comprehensive processing and analysis on gas pipeline based on Sentinel-1 image data through short baseline data processing, obtained deformation results in terms of time series by calculating linear deformation rate and nonlinear deformation phase based on residual phase separation nonlinear deformation phase and atmospheric effect phase, and then conduct parameter calculation, linear deformation rate calibration, accumulative deformation quantity calculation, etc. Finally, we extracted pipeline deformation quantities from 2020 to 2022. The result showed that, the land deformation rate of the ascending track data during this period ranges from -43 mm/year to 25 mm/year, and that of the descending track data from -66 mm/year to 33 mm/year. The results show that the area along the gas pipeline is in stable condition on the whole, deformation mainly occurred along a section in the northwest of Haidian District, and a large quantity of deformation occurred since January of 2020 until December of 2021, with the maximum deformation quantity of -70mm, This result provided a reliable reference for safety monitoring and repair & maintenance of the gas pipeline.Further more, The possible causes of the deformations mainly include surface subsidence, groundwater mining and such factors. Precautionary measures need to be enhanced for the area at potential risk of surface subsidence, to get rid of the threat of sudden geological disasters and resulting losses particularly in extreme weather conditions. At the same time, terrains and geographical realities should be considered to further determine whether there exists any hidden geological hazard like unstable slope, surface subsidence or landslide and decide the potential risk the pipeline is faced in combination with actual conditions.

How to cite: Xiaoqing, W., Junli, W., Peng, Z., Zhanyi, S., Yongshang, W., Qinglan, Z., and Shenghao, L.: Deformation Time-series Analysis and Disaster Potentiality Inversion by Short Baseline Interferometry Measurement, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8977, https://doi.org/10.5194/egusphere-egu24-8977, 2024.

Urban water management highly relies on a large number of related technical infrastructures. However, urban water management faces a severe challenge due to climate extremes' increased frequency and severity. Recent phenomena, such as droughts, heatwaves, storms, rising aquifers, or sea level rise, threaten the balance of water resources and cause potentially a functional degradation of water-related infrastructures. To understand how to act, more and more researchers suggest understanding the resilience mechanisms of these infrastructures. Unlike the concept of "vulnerability", which focuses on protecting infrastructure from hazards, "resilience" considers mainly the recovery of infrastructure functionality. It accepts hazards and transforms them into non-risk factors.

Even though “resilience” today in the literature has a wide range of meanings, studies on the resilience of infrastructures aim to the development of more effective and sustainable actions for the cities under risk. The choice of possible actions for optimising resilience is varied and multidimensional. In applying a case study in Lyon, France, this study aims to identify potential actions for improving the resilience of urban water infrastructures under multi-risk scenarios. Among the related theories and methods, the “Behind the Barriers” model is chosen as the foundation of this study. This model is considered a theory that allows effective and comprehensive analysis of urban infrastructure resilience. In the model, urban systems are conceptualised as complex systems, and long-term impacts and connections with the external environment are considered to overcome the barriers of temporal, geographic, and dimensional limits. The results show that, under different risk scenarios, the resilience of water-related infrastructures could be optimised by improving cognitive, functional, correlative, and organisational capacities.

How to cite: Yang, Z.: Resilience Optimisation of Urban Water-Related Infrastructures under Multi-Risk Scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9740, https://doi.org/10.5194/egusphere-egu24-9740, 2024.

As the European Union (EU) progresses towards an energy transition to mitigate climate change, the concept of decentralization has attained increasing prominence as a potential pathway. This study conducts a systematic comparative analysis of decentralization conceptualizations within the pivotal National Energy and Climate Plans (NECPs) for 2030 and Long-Term Strategies (LTSs) out to 2050. Textual analysis of 28 NECP and 24 LTS documents surfaces 313 mentions of “decentralization”, revealing multiplicity across member states’ outlooks regarding strategic decentralization prioritizations and definitions.

While technical dimensions of localized renewables and distributed infrastructure predominate, particular member states delineate decentralization’s transformative breadth more expansively—entailing substantial disruptions to conventional centralized paradigms across social, political and economic dimensions. Appreciable divergence also emerges regarding motivations, spanning improved resilience, efficiency and environmental performance. Inter-temporal comparisons expose profound integration of governance and participation considerations in LTSs, contrasting NECPs’ emphases on technical and financial aspects.

Notably, France's 2023 NECP draft indicates a potential reversal towards re-centralization - lowering renewable targets and contemplating extended nuclear reliance. Such outliers highlight complex interplays between national circumstances and priorities amidst the bloc’s overarching decentralizing course.

As ascending decentralization restructures Europe’s energy paradigm, these findings furnish insights into member states’ transitional outlooks, trends and intricacies. This informs governance to facilitate coherent, cooperative decarbonization aligned with decentralization’s multifaceted essence and diverse national manifestations.

How to cite: Ozhan, S.: Decentralising Europe's Energy Systems: Diverse Perspectives in National Roadmaps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10329, https://doi.org/10.5194/egusphere-egu24-10329, 2024.

EGU24-11276 | ECS | Posters on site | NH9.8

Multi-hazard conditions in urban settlements: a framework for heatwave and flooding integrated impacts assessment to support climate-oriented design 

Sara Verde, Maria Fabrizia Clemente, Valeria D'Ambrosio, and Mario Losasso

The co-presence and the simultaneous occurrence of multi-hazard conditions can trigger the attainment of tipping points, potentially responsible for undermining the balance of urban settlements. In recent years, there has been a growing awareness of the need to know, investigate and to manage multiple risks involving impacts on assets, resources and people. The analysis of potential impacts can be based on a spatial approach that considers a base area and the hazards that may occur within this area (including cascade, compound, effects, etc.).

In relation to multi-hazard conditions – which may vary both temporally and spatially – urban hot spots can be identified as areas where the consequences of the combination of vulnerability, exposure and hazard are condensed as transition factors from risk conditions to impacts.  

In this scenario, the contribution aims to test a decision support framework – based on a systemic approach - for climate adaptation and mitigation design strategies and solutions under multi-hazard conditions.

The methodological approach is based on the identification of urban hotspots based on climate-related impacts. The proposed process identifies urban hotspots evaluating the impacts resulting from heat wave and pluvial flooding, assuming as exposed value the total population potentially subject to suffer the negative impacts of extreme climatic events.

The evaluation of an integrated impact indicator considers the intrinsic features of the urban system and the hazardous phenomena to understand the complex effects that emerge from the coexistence of multiple risk on the same area and the same exposed assets. The areas where the impact values of heat wave and pluvial flooding are higher and, therefore the integrated impact value is increased, represent urban hotspot. The criticality, thus assessed, is based on a complex data set that includes both exposure, i.e. the population that is likely to be affected, and vulnerability, determined by the physical characteristics of the urban system considered.

Based on the knowledge phase, it is then possible to operate simulations of adaptation and mitigation strategies and solutions, supporting decision-makers in evaluating design alternatives for increasing resilience and reduce urban risks.

The framework, developed in a GIS environment, serves as a simplified tool for assessing the resilience of project proposals – through the application of the Proof of Concept (PoC) process – aimed at counteracting impacts under multi-hazard climate conditions, contributing to guide the development of policies, plans and projects. The use of the PoC methodological approach allowed the introduction of some innovative elements that contribute to the usefulness of the proposed decision-making model. A testing case in the city of Naples is proposed; where the PoC plays a significant role to identify and address the challenges and limitations that may arise in the early stages of developing an idea or project.

The contribution is developed within the research Partenariato Esteso PE3, RETURN project (multi-Risk sciEnce for resilienT commUnities undeR a changiNg climate) (Codice Progetto MUR: PE00000005), in the framework of the Spoke TS1 - Urban and metropolitan settlements activities.

How to cite: Verde, S., Clemente, M. F., D'Ambrosio, V., and Losasso, M.: Multi-hazard conditions in urban settlements: a framework for heatwave and flooding integrated impacts assessment to support climate-oriented design, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11276, https://doi.org/10.5194/egusphere-egu24-11276, 2024.

In 2015, with the publication of the UN Agenda, sport has been recognized as instrumental for sustainable development. The Agenda consists of guidelines for the future and is in line with the recommendations of the 2020 Olympic Agenda: in fact, the International Olympic Committee (IOC) believes that sports and the Olympics can help develop the majority of the Agenda goals.

The next Olympics will be held in Paris in 2024 and will be the first organized according to the sustainability principles set up by the Agenda. This case is supposed to mark a turning point in the history of the Olympics. However, these objectives remain fairly vague in that they are not defined by concrete criteria.

Here we develop a method that starting from the analysis of the Agenda goals provides a series of requirements to discretise and evaluate quantitatively the long-term sustainability of the event. This study investigates, with particular focus on the urban and architectural aspects, the relations between the event and the host city, between people and context and between event and environment. Much importance is given to public infrastructures, the wellbeing of visitors and athletes and the needs of the host city. We study the Olympic venues, assessing how many of them already exist, are temporary, or have been built for the event, as well as which materials were used in the realization [fig.1]. We pay attention to the legacy of the event, which implies planning from the beginning the future of the city after the Games. In fact, the Olympics in Paris are part of a wider process of expansion of the city: the construction of a large infrastructure network, the Grand Paris Express, and the redevelopment of the suburban district of Seine Saint-Denis [fig.2].

With this method, we can easily analyse results of studies and field research, like visits to the building site, and evaluate the impact of the event. This study is the beginning of a process that allows us to analyse and compare different Olympic editions within a single coherent framework.

How to cite: D'Ercoli, C.: From the UN Agenda 2030 to the organisation of a mega sustainable event: the case study of Paris 2024 Olympics., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13167, https://doi.org/10.5194/egusphere-egu24-13167, 2024.

EGU24-15592 | ECS | Posters on site | NH9.8

System dynamics for water management in coastal cities under multi-risk scenarios 

Marion Perney, Mauro Moreno, Francesco Giannino, and Mattia Federico Leone

In the context of global warming, extreme weather events are rising in frequency and severity. Urban communities prosperity heavily depend on the balance of environmental and socio-technical systems to access to fundamental resources and services, making them more susceptible to the impacts of climate change. Coastal cities, in particular, are characterized by a high degree of vulnerability to climate variations, potentially leading to critical impacts if resilient and sustainable water management strategies and measures are not in place. To assess the significance of territorial adaptation and mitigation measures in a dynamic and holistic approach, the use of System Dynamics tools aims to study the effects and interactions of various sectors, examining the risks associated with flood management in coastal cities.

This approach incorporates multidisciplinary, multi-scalar, and multi-operational dimensions, supporting stakeholders in identifying potential measures for building resilient pathways. By identifying interactions within the various interconnected sub-systems that influence the dynamic behaviour of the overall system, stock and flow models enable complex systems to be analysed through interdependent components that influence each other over time. It can be used to support decision-makers in getting insights about the potential effects of different policies and strategies.

The model presented is a conceptual framework able to represent the impact of compound coastal flood (combination of pluvial, river and coastal flood) on sectors (transport, energy, landuse, etc.) and explores adaptation and mitigation measures (Nature Based, architectural and engineering solutions) to contrast coastal risks using dynamic tools and methods for assessing their relevance in urban coastal areas. The different types of water storage and flows/processes have been identified, namely: coastal flow, surface water, river/ponds, soil water, groundwater table, city drainage system. These are used to simulate different scenarios and study the interlinks among technical solutions, urban features, and coastal flood water management.

The presentation explores SD thinking and tools for dialogue and decision-making on complex and interdisciplinary issues linked to Climate Change Adaptation and Disaster Risk Reduction actions. The quantitative developed stock and flow model contributes to study the climate impacts on coastal cities under a cross-sectorial approach.

How to cite: Perney, M., Moreno, M., Giannino, F., and Leone, M. F.: System dynamics for water management in coastal cities under multi-risk scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15592, https://doi.org/10.5194/egusphere-egu24-15592, 2024.

Climate change is leading to more frequent and intense heat waves, exposing urban populations to extreme heat conditions, and posing significant health risks. Many cities are adopting nature-based solutions (NbS) to mitigate urban heat, with green roofs emerging as a universal NbS. They are advantageous as they can be easily implemented in dense urban areas without requiring extra land and are generally effective in cooling. Although numerous green roof projects are implemented on a small scale, research on the effectiveness of small-scale green roofs in heat reduction is limited. Consequently, we assess the cooling potential of small-scale green roofs, identifying the traits of successful implementations and how these differ from green roofs that result in maladaptation. We utilized a quasi-experimental design methodology to improve causal inference, effectively isolating the impact of individual green roofs from background climate changes using publicly available green roof data and longitudinal satellite imagery. In our study of 11 green roof projects in Seoul, we noted that intensive-type green roofs had a cooling effect. In contrast, projects that experienced temperature increases typically featured extensive vegetation and structural elements that increased albedo. This evidence can assist decision-makers in reducing risks of maladaptation and enhancing effective adaptation practices. This method is expected to support governments, especially those with limited budgets, in efficiently managing urban heat, reducing trial and error. Ultimately, our research holds the potential to significantly contribute to the sustainability of society and the environment.

How to cite: Kim, S. and Park, C.: Investigation of Urban Heat Mitigation and Thermal Maladaptation Potential from Small-Scale Green Roofs: A Case Study in Seoul, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15922, https://doi.org/10.5194/egusphere-egu24-15922, 2024.

The energy crisis in Europe, triggered by growing demand for fossil fuels and exacerbated by recent health emergencies and geopolitical tensions, is putting additional pressure on an environmental context already made fragile by the increased frequency and intensity of extreme weather events caused by climate change. These events have significant consequences on both natural and anthropogenic systems. In addition, the exponential increase in population, concentrated mainly in urban areas, amplifies dependence on external primary resources. In fact, contemporary settlement patterns, combined with lifestyles characterized by high consumption of resources such as food, water, and energy, accentuate socioeconomic and/or environmental impacts resulting from climate change.

Interrelated and overlapped crisis conditions represent a new field of investigation for the experimentation of approaches, strategies, and technical solutions in response not only to climate adaptation and mitigation objectives but also to the satisfaction of needs, expression of emergent habitat complex conditions.

In this context, the Food-Energy-Water (FEW) nexus approach emerges as a key response to understanding and managing the interconnectedness of resources, external drivers of climatic, geopolitical, demographic, and/or socioeconomic nature, and the impacts on affected communities. 
This integrated system approach emphasizes how the three dimensions - food, energy, and water - are closely interdependent and mutually affect each other. The nexus approach aims to consider these resources synergistically, recognizing that decisions and actions developed for one of the considered topics, can significantly impact the others.  Addressing challenges in these three dimensions in a coordinated way can help reduce environmental impacts and promote more efficient and sustainable use of global resources.

The FEW nexus integrated approach examines the complex dynamics associated with the development of innovative strategies and technologies. This approach allows to realize an assessment of alternatives of technological solutions and build a coherent set of indexes to make a qualitative and quantitative evaluation of performances and benefits of integrated food and energy production systems at different scales.

Among complex systems, Agrivoltaic systems represent a challenging case study to test the FEW nexus integrated approach, being integrated systems capable of dual exploitation of the soil both as a productive green area for food cultivation and energy generation from renewable sources. Such systems, both in open spaces and combined in the built environment, emerge as potential examples of convergent innovation and represent a model of integration between innovative technologies and sustainable strategies, addressing complex contemporary issues in a systemic way.

The goal is to promote self-production and resource management in the urban context, preserving ecosystem services and generating co-benefits that can have widespread positive spillovers in terms of environmental and social benefits and economic opportunities.
The implementation of integrated systems and the application of systems approaches such as the FEW nexus form the basis for pursuing sustainable and resilient solutions for urban systems in response to the pressing challenges imposed by the climate and energy crises and the resource scarcity they entail.

How to cite: Marandino, F., Santomartino, G., and Tersigni, E.: Photovoltaic-Green Systems for Urban Transition. An Integrated Approach for the Assessment of Food-Energy-Water mutual benefits in the Emergent Habitat , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17669, https://doi.org/10.5194/egusphere-egu24-17669, 2024.

Soil artificialisation due to urban sprawl, infrastructure development and concreting is one of the causes of the loss of urban biodiversity. In addition, the rise in global temperatures as a direct consequence of climate change has become a major challenge for urban planning. The urban heat island, which is mainly the result of the waterproofing of soils to encourage surface reflection (Aldebo), contributes to global warming. The Urban Digital Twin, a design tool that can simulate, predict and monitor through the implementation of data, enables urban resilience strategies to be put in place.

This proposal aims to discuss the relationship between the "Zero Net Artificialization (ZNA) by 2050" objective (the ban on artificialization over a " defined period ") of the 2021 French "Climate and Resilience" legislation and the "Urban Digital Twin" in view of building models for planning cities that are more resilient to heat islands.
The first part of this presentation is devoted to the development of a methodology for selecting data (type of land use, topography, albedo of materials, etc.) and implementing them in numerical models in order to obtain "urban and climate Digital Twins".
The second part of this document is devoted to the methodology for evaluating the various strategic models developed in the first part of the document at different scales, from the block to the territory, but also over different temporalities in line with the ZNA objective (currently conditional on the renaturation of an equal proportion of artificialised spaces over a specific timeframe) and further research into the fight against heat islands.

By using the Urban Digital Twin to meet the ZNA objective, this proposal focuses on developing predictive models for controlling heat islands in an attempt to guide urban planning towards sustainable and resilient environments.

How to cite: Josse, F.: The connection between the "Zero Net Artificialisation 2050" objective and the "Urban Digital Twin" tool, a methodology for assessing strategies to reduce the risk of urban heat islands using data., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17811, https://doi.org/10.5194/egusphere-egu24-17811, 2024.

EGU24-17931 | ECS | Posters on site | NH9.8

The use of Local Urban Plan to limit the effect of heat waves 

Valentin Clémence, Bruno Barroca, Anne Ruas, Jean-François Girres, Elodie Nourrigat, Mathieu Delorme, and Loic Quéru

Heatwaves are meteorological events characterized by prolonged periods of intense heat. They present a growing challenge for societies. Indeed, since 2003 France has faced exceptional heatwaves, with significant implications for public health. These climatic phenomena, exacerbated by global climate change, are generating increased concern at both local and national levels.

The presentation will focus on the Freshway project aims to deepen our understanding of the mechanisms, challenges, and strategies inherent in the implementation of cooling solutions at local level. Through a comprehensive analysis, the Freshway project seeks to identify institutional and technological barriers that may hinder the realization of such initiatives. Concurrently, Freshway endeavors to map and detail the adaptation trajectories adopted by communities in response to climate challenges, thereby providing valuable insights for more resilient and sustainable urbanization. The project included several study sites, including Paris, Montreuil, Pontault-Combault, and Sarcelles in the Ile-de-France region, as well as Montpellier, Castelnau-le-Lez, and Beziers in the Occitanie region. Among the different results of the project, this paper focuses on the use of local planning document to limit the effect of heat waves.  

Methods : This study presents a multidimensional approach to understanding urban trajectory for planning and acting against heat waves. Through in-depth individual interviews with key stakeholders from local authorities, valuable insights were gathered on the challenges and issues encountered in urban planning and management. Concurrently, a detailed description of emblematic achievements provides a tangible overview of innovative land-use practices in response to heatwaves.

Moreover, our research incorporates a rigorous analysis of geographical data, examining trends and transformations across various temporal scales, including the evolution of urban minerality versus the evolution of urban vegetation. Special attention is devoted to a detailed examination of the PLU (Local Urban Plan, the French land use regulation document), offering an in-depth perspective on the strategic and regulatory directions shaping urban development.

Findings : Montreuil, located in the inner suburbs of Paris, demonstrates a strong political commitment to urban cooling initiatives, while simultaneously facing intense land pressure due to high urban densification, in alignment with regional objectives. Recent modifications to the PLU have strengthened regulatory constraints, notably through the full-ground coefficient (CPT), construction coefficients (CES), and the establishment of protected landscaped areas (EPP). Since 2020, the number of EPPs has significantly increased, rising from 51 to 163, with particular attention given to targeted smaller spaces, sometimes of a private nature. This evolution reflects a proactive approach aimed at reconciling urban development with environmental preservation.

Conclusion : The Freshway project focuses on understanding and implementing cooling solutions in response to climate challenges, analyzing community adaptation trajectories. Utilizing interviews, documents analysis and geographical data, the study investigates urban dynamics, such as in Montreuil, where a strong political commitment to urban cooling coexists with challenges related to densification and local regulations.

Funding : Freshway Project, 2022-2025 , funded by ADEME – PACT program

How to cite: Clémence, V., Barroca, B., Ruas, A., Girres, J.-F., Nourrigat, E., Delorme, M., and Quéru, L.: The use of Local Urban Plan to limit the effect of heat waves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17931, https://doi.org/10.5194/egusphere-egu24-17931, 2024.

EGU24-18465 | ECS | Orals | NH9.8

From critical urban context to heatwave-related hotspot. An exposure-based application for a study case in the metropolitan area of Naples 

Antonio Sferratore, Sara Verde, Federica Dell'Acqua, and Mario Losasso

KEYWORDS: climate risk, climate resilient design, urban settlements

INTRODUCTION. Urban areas face environmental multi-risk conditions involving biophysical and socioeconomic subsystems, leading to complex interactions. Recent research focuses on compound risks resulting from hazard interactions, posing challenges in defining impacted exposed urban systems by multiple events.

Nevertheless, several enhancements about the methodologies are to be addressed, to identify urban areas with the highest compound risk impacts.

Therefore, to provide an overview of the risk arising from climate change a multidisciplinary approach to assess climate-related disaster risks is needed, considering all aspects contributing to increase hazards, exposure, and vulnerability.

Within this thematic framework, it is important to identify factors defining an urban context as environmentally critical. Such urban contexts represent areas where single or interconnected hazards, along with exposure and vulnerability conditions, determine higher risks. These higher-risk areas are hotspots where to take action with climate-resilient strategies to reduce vulnerability.

 

OBJECTIVES. The goal of the contribution is to develop a conceptual framework for modelling multi-risk conditions in urban and metropolitan areas throughout a taxonomic knowledge of critical urban contexts. Specifically, the contribution aims to identify heatwave-related hotspots as locations where there are additive effects of hazards and overlapping impacts.

 

MATERIALS AND METHODS. The methodology for urban settlements’ analysis integrates soft, hard, and demographic systems, separating physical and functional-service aspects.

The physical part includes Green, Grey and Population subsystems with different features: built-up areas (Grey), natural services and green systems (Green).

The methodology has been applied in the study case of Nola city, in the metropolitan area of Naples.

The thematic maps, resulting from the analysis of these sub-systems, has been overlapped with environmental, technological, functional-spatial elements and exposure factors like population distribution. The relationship between urban critical context assets (built-up features, road traces, geomorphologic conditions, natural and green elements, socio-economic conditions, etc.) and key environmental factors identifies hotspots.

This knowledge model evaluates the inherent vulnerability of physical subsystems using indicators such as phase shift, attenuation, albedo and NDVI for built-up system (buildings and outdoor spaces).

Exposure is only related to the population.

RESULTS AND CONCLUSIONS. The results show that the built-up system behaves inadequately to heat waves. The impermeable surfaces are 26% and located in the historic centre. About 12% of the population, children and old people, are weaker to heatwaves negative effects.

The experimentation allows to develop a knowledge model for the identification of the hotspots, and to support climate-resilient design choices for the reduction of the vulnerability to heatwave, based on the exposed population.

The contribution is developed within the research Partenariato Esteso PE3, RETURN project (multi-Risk sciEnce for resilienT commUnities undeR a changiNg climate) (MUR Project Number: PE00000005), in the framework of the Spoke TS1 - Urban and metropolitan settlements activities, and within Programma PON R&I 2014-2020 - Asse IV “Istruzione e ricerca per il recupero - 840 REACT-EU”, Codice Unico di Progetto (CUP) 65F21003090003.

How to cite: Sferratore, A., Verde, S., Dell'Acqua, F., and Losasso, M.: From critical urban context to heatwave-related hotspot. An exposure-based application for a study case in the metropolitan area of Naples, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18465, https://doi.org/10.5194/egusphere-egu24-18465, 2024.

In the process of transitioning into resilient urban areas, cities face a wide variety of challenges in relation to adaptation, mitigation and sustainable development. Commonly these challenges are addressed in a merely isolated fashion, or only two out of the three objectives are tackled simultaneously. It is pivotal to take a systemic approach over time in order to maximise synergies and minimise trade-offs between these different policy objectives. Climate Resilient Development Pathways (CRDPs) aim to integrate adaptation, mitigation and sustainable development into flexible pathways over time, while considering (deep) uncertainties regarding climate change, as well as other sources of uncertainty. Climate resilient development pathways seek to support integrated planning and implementation of climate action. Currently no comprehensive framework exists for operationalising CRDPs. There is a need to develop a methodology for the practical pursuit of climate resilient development pathways. 

This research presents a novel approach to operationalise climate resilient development pathways, using the well-established method for adaptation pathways, so-called “dynamic adaptation policy pathways (DAPP)”, as a starting point. The CRDP process starts by envisioning multiple desirable futures and understanding the decision context and current policy objectives and actions for adaptation, mitigation and development. Thereafter the synergies and trade-offs are assessed between the different climate actions, as well as tipping points are identified – meaning points in time when new actions will be required. Consequently, alternative actions are co-developed for the future to pursue desirable pathways. The final outcome is a pathways map, as well as an implementation and monitoring plan. An urban case-study to demonstrate the applicability of climate resilient development pathways is presented for the city of Cork in Ireland. 

CRDPs can be created for different climate-related impacts such as flood and heat, as well as for a wide variety of development issues. The main target groups of the approach are decision makers and/or (urban) planners, although a wider engagement is recommended for different steps during the co-creation process of the pathways. Climate resilient development pathways support integrated climate action planning, interlacing adaptation, mitigation and sustainable development through designing flexible pathways over time that provide insights into the range of options to achieve resilient urban futures.  

How to cite: Langendijk, G., McEvoy, S., Jeuken, A., and Haasnoot, M.: Urban resilience through integrating adaptation, mitigation and sustainable development - a novel approach to operationalise climate resilient development pathways , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18661, https://doi.org/10.5194/egusphere-egu24-18661, 2024.

EGU24-19387 | ECS | Orals | NH9.8

Mapping the opportunities of Nature-Based Solutions for Climate Adaptation: bottom-up approach in the Louisiana Watershed Initiative case study 

Martina Di Palma, Marina Rigillo, Gabriella Esposito De Vita, and Mattia Federico Leone

In line with the IPCC's recommendations, managing the risks associated with extreme climate events requires a holistic approach covering both structural and non-structural measures for the project of climate adaptation. The former involves the implementation of green infrastructures and the integration of hybrid systems into conventional gray infrastructure through low-impact development (LID) systems and Nature-Based Solutions (NBS). The second involves the investment of economic resources in governance programs aimed at prioritizing adaptation and mitigation actions, the adoption of innovative technologies for ecosystem mapping and monitoring, and the implementation of climate risk prediction information models.

NBS are sustainable technological systems capable of responding to current climate challenges by tapping into the natural capacities of ecosystems to provide regulating ecosystem services. Implementation in the urban system of NBS aims to harness and preserve the natural functions of ecosystems, providing multiple benefits such as managing weather flows, reducing the heat island effect, improving air and water quality, preserving biodiversity, and improving the quality of life and health.

The integration of these types of solutions into increasingly complex urban systems requires integrated data-driven systems to support technology choices and decision-making processes to maximize their achievable benefits and co-benefits for local communities. The current challenge requires the use of enabling technologies that can identify and localize urban regeneration opportunities while reducing the risk of uncertainty and error.

The goal of such an approach is to optimize processes toward practices, policies, and solutions that know how to derive the greatest benefit in terms of resilience. This approach is very common in territories affected by major environmental disasters that need a fast and effective response to climate risks. The study aims to examine the best practices stemming from the interstate “Louisiana Watershed Initiative” (LWI) to deepen the integration of NBS in climate adaptation projects. 
In particular, through the analysis and critical use of the "NBS Explorer "tool,  the model of "Opportunity Maps" is explored in its products "Restoration Opportunity Map" and "Preservation Opportunity Map”.

The results emphasize the use of an information model based on multi-criteria assessment, which, through the overlay mapping technique, identifies the optimal areas for the implementation of NBS. Furthermore, the LWI takes a bottom-up approach through a decision-making platform that facilitates interaction between policymakers, funders, local communities, and planners. This platform, by providing data and support tools, fosters a multi-directional and synergistic dialogue between stakeholders, playing an integrative role in the decision-making process and implementation of NBS.

Thanks to the involvement of different users, NBS can be selected and prioritized, taking into consideration quantifiable and comparable benefits and co-benefits in different design scenarios. The proposed approach implies that data collection is guided by a clear objective and specific knowledge needs. Data selection begins with a detailed understanding of the questions and objectives, avoiding an indiscriminate approach to information collection.
The key element lies in leveraging data effectively across various phases of climate adaptation projects, enabling informed decision-making and the implementation of targeted NBS.

How to cite: Di Palma, M., Rigillo, M., Esposito De Vita, G., and Leone, M. F.: Mapping the opportunities of Nature-Based Solutions for Climate Adaptation: bottom-up approach in the Louisiana Watershed Initiative case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19387, https://doi.org/10.5194/egusphere-egu24-19387, 2024.

EGU24-19867 | ECS | Posters on site | NH9.8 | Highlight

Climate change and risk management in shopping centers and other commercial structures in urban areas. 

Rita Akiki, Bruno Barroca, and Emilie Sampson

The disruption of temperatures at a global and local level directly impacts the city and the users and more particularly vulnerable people such as children and the elderly at any time of the day and during all seasons.

The architecture of the city and the quality of its spaces influence the intensity of the effects of heat islands and can, in the case of strong heat such as the heat wave of 2003 in France, cause material and human damage. For example, severe heat waves accompanied by heat island effects can affect urban transport networks and cause engine failures and fires due to overheating. Similarly, the mortality rate of vulnerable people such as children and the elderly is higher in cities during heat waves than in the countryside. 2022 has been the hottest year ever noted with 33 days of heat waves and 11000 deaths due to heat in France. We’ve had 17 heat waves between 1947 and 2000 and 27 heat waves since the year 2000, and it is expected to double till 2050. (L’atelier de la transition - Halte à la surchauffe urbaine - Aupa Agence d'urbanisme Pays d'Aix - Durance)

Shopping centers in dense urban or peri-urban areas today represent major potential for transformation and densification. Faced with issues of climate change and adaptation as well as new laws and regulations, cities can no longer look away from these areas.

The city, being a global system composed of different microsystems, cannot therefore function and adapt without considering all its components, notably shopping centers. These shopping centers have long been criticized for their sparse urban form favoring the use of cars and their large asphalt parking spaces. Faced with current and future climate issues, as well as the dynamics of densification and restructuring and the needs and demands of customers, shopping centers must review their operating models.

Some shopping centers have managed to move beyond their primary uses and become main areas participating in natural and/or climate crisis management. For instance, Walmart in the United States during Hurricane Sandy which devastated the northwest, and other chains such as Home Depot and Lowe's have set up recharging stations and stock distribution areas directly after the disaster, to provide electricity, water and food for those who have been affected.

In this study the focus is on analyzing different responses to natural hazards with a multidimensional approach to understand what can be done and how can it be done in places such as shopping centers. We will be focusing on the representation of the classic mode of operation of these commercial centers that constitutes a system functioning on its own but still linked to the city at the same time. Therefore, this work aims to identify how, in the event of a crisis or a climate risk, this system can be called upon and reused beyond its primary function.

 

Keywords: shopping mall redevelopment, New Urbanism, metropolitan area, sustainable development, risk management, crisis management center, climate refuge, system planning, climate change.

How to cite: Akiki, R., Barroca, B., and Sampson, E.: Climate change and risk management in shopping centers and other commercial structures in urban areas., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19867, https://doi.org/10.5194/egusphere-egu24-19867, 2024.

EGU24-20428 | Orals | NH9.8

Decoding the urban geo-puzzle: navigating geological issues and global challenges through the lens of the Urban Geo-climate Footprint  

Francesco La Vigna, Azzurra Lentini, Jorge Pedro Galve, Beatriz Benjumea-Moreno, Stephanie Bricker, Xavier Devleeschouwer, Paolo Maria Guarino, Timothy Kearsey, Gabriele Leoni, Saverio Romeo, and Guri Venvik

At present, worldwide population and economic expansion boosts the demand for environmental resources and urban development. According to the 2022 United Nations World Population Prospect, the global population may reach up to 9.7 billion people by 2050 of which nearly 70% will be residing in urban areas. As a result, the urban setting will become increasingly complex and with more geological and climate negative effects exacerbated by the increasing population, the unequal distribution of economic and energy resources, and the over-exploitation of the environment.

To face these worldwide issues, a global approach to knowledge is required with concerted actions by all countries and cities. One possible solution addressing this need could be achieved firstly by classifying cities throughout the world as complex systems defined by geological, subsoil-related climate impact, environmental, and anthropic factors considered in a more holistic way.

To achieve this objective, the Urban Geo-climate Footprint (UGF) project, aimed to define a new methodology to classify and cluster cities by geological and climatic point of view.

The basic assumption of the UGF approach is that cities with similar geological-geographical settings should have similar challenges to manage, due to both common geological issues and climate change subsoil-related effects. Following this approach, a holistic tool consisting in a complex spreadsheet has been developed and applied to several European cities, in collaboration with several Geological Surveys of Europe.

It is demonstrated as the Urban Geo-climate Footprint tool is currently capable of providing a semi-quantitative quick representation of the pressures driven by geological and climatic complexity in the analysed cities, providing for the first time such classification for the urban environment.

Through the wide application of this methodology several benefits could be reached as the general awareness increase of non-experts and the enhanced reading-the-landscape capacity of decision makers about the link between geological setting and the increase in pressures due to climate change and anthropogenic activity.

Furthermore, the UGF approach would facilitate the possibility to exchange best practices among similar cities for planning purposes, and it would support the decision processes to define and differentiate policies and actions, also supporting policy and cooperative geoscience and climate justice.

How to cite: La Vigna, F., Lentini, A., Galve, J. P., Benjumea-Moreno, B., Bricker, S., Devleeschouwer, X., Guarino, P. M., Kearsey, T., Leoni, G., Romeo, S., and Venvik, G.: Decoding the urban geo-puzzle: navigating geological issues and global challenges through the lens of the Urban Geo-climate Footprint , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20428, https://doi.org/10.5194/egusphere-egu24-20428, 2024.

EGU24-1636 | Posters on site | NH9.10

Assessing drought induced subsidence risk in France under current and future climate 

Mathis Joffrain and Nicolas Bruneau

Subsidence risk induced by drought produced widespread damages to low- rise buildings in France in 2022, and has become of increasing concern for insurers. Companies expect greater average annual costs in the near future, and modeling solutions are scare to model the impacts by extreme events. In this poster, we present a stochastic model designed to calculate the full distribution of annual losses over an home insurance portfolio. It generates a stochastic set of SSWI footprints based on ERA Land data and at each location, evaluates both the claim propensity and the insured damage. Results will show (i) how damage rates for drought induced subsidence risk compare to other perils in France and (ii) how the risk changes between current and future climate.

How to cite: Joffrain, M. and Bruneau, N.: Assessing drought induced subsidence risk in France under current and future climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1636, https://doi.org/10.5194/egusphere-egu24-1636, 2024.

EGU24-1646 | ECS | Orals | NH9.10

Agricultural Drought in Sweden: Assessment of Hazard and Impacts 

Claudia Canedo Rosso, Lars Nyberg, and Ilias Pechlivanidis

Sweden is known for its abundance of water resources, while future climatic projections indicate a rise in precipitation and temperature rates. However, droughts had severe effects on the environment, society, and agriculture in 2016, 2017 and 2018, highlighting the need for improved drought monitoring and management. The agricultural sector, in particular, suffered significantly during the 2018, 2021, and 2023 droughts, inquiring the need for enhancements in climate adaptation and preparedness. This study aims to assess the agricultural drought in Sweden with a focus on hazard assessment and its associated impacts. Firstly, we unfold the lessons learnt from continental observatories and national services by evaluating the reliability of the derived information and identifying the added value for local decision making. For this, we compare the simulated soil moisture derived from the LISFLOOD and S-HYPE hydrological models, and we evaluate the modelled simulations against earth observation-based soil moisture from the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). Based on the LISFLOOD model, we used anomalies of the soil moisture index and the combined drought index at a 10-day average and at a 5 km spatial resolution. Daily runoff and soil moisture data were also used from the S-HYPE model at about 13 km2 spatial resolution. Secondly, the spatiotemporal drought hazard is assessed using drought indicators to identify drought frequency and intensity. Here, drought indicators such as Standardized Precipitation Index (SPI), Soil Moisture Anomaly (SMA), and Combined Drought Index (CDI) are computed using S-HYPE model outputs. Finally, we evaluate the utility of integrating data from drought indices (SPI-1, SPI-3, SMA and CDI) and crop yield of wheat and potato to improve the understanding of the links between impacts and statistical indices. The relationships between drought onset and yield response are evaluated for different aggregation of time periods and lags (i.e., monthly). The study outputs are used to assess alternative ways to improve decision-making regarding adaptation strategies to reduce agricultural vulnerability and the capability of addressing the challenges posed by a changing climate.

How to cite: Canedo Rosso, C., Nyberg, L., and Pechlivanidis, I.: Agricultural Drought in Sweden: Assessment of Hazard and Impacts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1646, https://doi.org/10.5194/egusphere-egu24-1646, 2024.

EGU24-1704 | ECS | Posters virtual | NH9.10

Monitoring of water area in the dry season of East Dongting Lake Wetland from 2022 to 2023 based on Google Earth Engine 

Leishi Chen, Jianbo Deng, Qinzhe Han, and Bing Sui

Wetlands have functions such as hydrological regulation, water purification, and climate regulation. However, under the dual influence of global climate change and human activities, the frequency and intensity of wetland ecological droughts are increasing, leading to shrinkage of wetland area and decline in ecological service functions, seriously threatening wetland ecological security. The East Dongting Lake Wetland is located in Hunan, China. According to the observation results of the Chenglingji Water Level Station, from August 2, 2022 to June 5, 2023, it entered an abnormal dry period of 305 days, which is the longest dry period since observation records began. Our goal is to understand the changes in water distribution in East Dongting Lake during this period based on satellite images.

We used the Sentinel-1 GRD data provided on Google Earth Engine and developed a water area monitoring module based on the OTSU method, which provided us with water distribution data of the East Dongting Lake wetland during the target period. There are 44 available Sentinel-1 GRD images in these 305 days. The average water area in the dry season calculated from the 44 images is 230.75 square kilometers. In contrast, there were 49 available images in the same period of the previous year, and the average water area was 486.32 square kilometers. The average water area in the same period of the previous year was even larger than the maximum water area of 369.06 square kilometers during the target period. This reflects the continued impact of the severe drought in China's Yangtze River Basin in the second half of 2022 on the East Dongting Lake wetland.

We analyzed the water distribution results on August 20, 2022, when the drought was severe. The results showed that contiguous exposed lake beds were exposed in the north and south of the main lake body of East Dongting Lake, and the main flood channel even experienced drying out. Drought has affected the core area of the East Dongting Lake Wetland, causing the water level to drop rapidly into the dry season, resulting in rapid changes in the spatial distribution of the Dongting Lake Wetland's shoals and water bodies. The advance of the dry season mainly affects the seasonal growth of wetland vegetation, including submersed plants (Echinacea, etc.), floating-leaf plants (Rhombus, etc.), emergent plants (Reeds, Typha, etc.), swampy meadows (Carex etc.) and swamp grasses (Nandi, etc.). The drought has even affected the habitat of elk and has had a complex impact on wetland ecology.

How to cite: Chen, L., Deng, J., Han, Q., and Sui, B.: Monitoring of water area in the dry season of East Dongting Lake Wetland from 2022 to 2023 based on Google Earth Engine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1704, https://doi.org/10.5194/egusphere-egu24-1704, 2024.

EGU24-2705 | Orals | NH9.10

A daily evapotranspiration-based drought indicator in characterizing spatiotemporal evolution of flash droughts 

Xia Zhang, Jianping Duan, Francesco Cherubini, and Zhuguo Ma

Droughts cause multiple ecological and social damages. Reliable drought monitoring and forecasting can benefit various sectors by allowing adequate lead times for drought mitigation efforts. Drought indices are key tools to quantify drought severity, but they are currently limited to timescales of monthly or longer. However, shorter-timescale (e.g., daily) drought indices enable more accurate identification of drought characteristics (e.g., onset and cessation time), especially for flash droughts. Here, we propose a daily drought index named daily evapotranspiration deficit index (DEDI) that is constructed based on actual and potential evapotranspiration data. Through comparisons with multiple reference indices and observations, DEDI can well characterize the spatiotemporal evolution of regional drought events that occurred in North China, Southwest China, eastern Northwest China, and Northeast China in the spring and summer of 2019. We have publicly shared the DEDI dataset with a high spatial resolution (0.25°) and a long time series (1979–2022) covering global land areas, available at https://doi.org/10.5281/zenodo.7768534. The dataset has also been validated to have the capability to capture dry and wet variations and to detect ecology- or agriculture-related droughts at a global scale. Overall, the DEDI indicator could be regarded as a practical solution to facilitate flash drought monitoring and early warning.

How to cite: Zhang, X., Duan, J., Cherubini, F., and Ma, Z.: A daily evapotranspiration-based drought indicator in characterizing spatiotemporal evolution of flash droughts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2705, https://doi.org/10.5194/egusphere-egu24-2705, 2024.

EGU24-3057 | ECS | Orals | NH9.10

Relative contributions of atmospheric circulation and evaporation to the faster onset of flash droughts 

Qiqi Gou, Akash Koppa, Diego Miralles, and Huiling Yuan

Flash droughts are characterized by their abrupt onset and rapid intensification. Identifying and quantifying the factors that trigger and accelerate the onset of flash droughts is crucial for establishing reliable early warning systems, and thus alleviate their detrimental impacts on agriculture, ecosystems, and water resources. Recent findings indicate that the combined influence of soil moisture depletion and atmospheric aridity contributes to the faster onset of flash droughts. However, the understanding of the dynamic and thermodynamic processes that expedite this rapid onset still remains limited. In this study, we utilized a drought index derived by a state-of-the-art generation of land evaporation model (the fourth version of the Global Land Evaporation Amsterdam Model; GLEAM v4.0), to investigate the spatial distribution and trends in flash drought onset speeds from 1980 to 2023. Our goal was to quantify the relative contributions of atmospheric circulation and evaporation to the trends in onset speed. Our results reveal that the transition from evaporation being energy-limited to water-limited serves as a sufficient condition for flash drought onset in humid and semi-humid regions. The onset speed of flash droughts has exhibited a significant increase since 1980, with intensified atmospheric circulation identified as a key driver for the increasing onset rates. Additionally, elevated evaporation, resulting from increased soil moisture and evaporative demand in the preceding period, emerges as the primary thermodynamic and dynamic factor expediting flash drought onset. This study enhances our understanding of the dynamic and thermodynamic drivers underlying flash droughts, contributing to the advancement of the flash drought onset mechanism. Moreover, the insights gained from this research provide valuable information for predicting flash droughts and developing strategies for effective mitigation.

How to cite: Gou, Q., Koppa, A., Miralles, D., and Yuan, H.: Relative contributions of atmospheric circulation and evaporation to the faster onset of flash droughts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3057, https://doi.org/10.5194/egusphere-egu24-3057, 2024.

In Taiwan, water storage grapples with challenges from steep slopes, fast-flowing streams, limited land size, and a dense population, intensifying constraints on water resources. Climate-sensitive agriculture, especially vulnerable to drought, faces threats to Taiwan’s food supply, particularly in the Jhuoshuei River Alluvial Plain, crucial for rice cultivation. To investigate the drought-rice yield relationship there, this study focused on Changhua County, chosen for its comprehensive meteorological data, encompassing maximum and minimum temperatures, precipitation, wind speed, relative humidity, and solar radiation. Given the geographical features of Changhua County, where farmers heavily rely on groundwater, drought events may induce land subsidence due to excessive groundwater pumping. Utilizing AquaCrop, a crop-water productivity model developed by the Food and Agriculture Organization of the United Nations, we simulated historical rice yields from the first crop between 2016 to 2021, configuring model parameters with soil properties, groundwater, water quality, and meteorological data. Rice growth conditions were determined by the growth degree days method, and irrigation was modeled with the first two transplanting stages having a 3 cm ponding depth, followed by a third stage with weekly draining and drying, a nutrient phase with 5 cm water, and final drainage before harvesting. For drought assessment, we calculated consecutive drought days and standardized precipitation index (SPI) to evaluate rice yields risk. A sensitivity analysis of temperature, precipitation, additional irrigation, and harvesting time was conducted to comprehend potential effects on rice yield under drought conditions. Despite drought events in 2017, 2019, and 2021 (SPI≦-1), records showed no reduction in rice yields. AquaCrop simulations revealed a rice yield range of 4.02 to 8.51 (t/ha) with a root mean square error (RMSE) of 2.40 (t/ ha) and mean absolute percentage error (MAPE) of 22.66%. Farmers may have mitigated drought impacts by pumping groundwater. Assessing irrigation water by pumping, adding 1 to 3 irrigation events brought simulations closest to rice production records, with an RMSE of 0.06 t/ha and MAPE of 0.65%. The Sensitivity analysis results showed a strong correlation (R2=0.97) between precipitation change and yield. While no clear linear relationship existed between temperature change and yield, reductions in temperature could increase production. Additional irrigation, up to four times during drought, resulted in the highest yield improvement (2.06 t/ha). Beyond the fifth irrigation, yield slightly decreased to 2.05 t/ha, with no further improvements. Lastly, changes in the harvest period exhibited a high correlation with yield (R2=0.99). These findings provide a valuable reference for developing agricultural policies to ensure food supply and farmers’ livelihoods. Future research will explore the relationship between drought and rice yield under climate change scenarios to understand potential agricultural risks better.

How to cite: Huang, S.-H. and Cheng, S.-T.: Assessing the Risk of Rice Production under Drought Conditions in the Jhuoshuei River Alluvial Plain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3717, https://doi.org/10.5194/egusphere-egu24-3717, 2024.

EGU24-3793 | ECS | Posters on site | NH9.10

Predicting Flash Droughts Using Transformers: Understanding Surface and Root Zone  

Roberto Chang-Silva and Seonyoung Park

Flash droughts, characterized by their rapid onset and devastating agricultural and ecological impacts, pose a growing threat in a changing climate. Accurate and timely predictions are crucial for implementing mitigation strategies and minimizing their widespread consequences. This research presents a novel transformer-based forecasting system designed to predict soil moisture with a focus on detecting the early warning signs of flash droughts in North America. This study integrates the concepts of the two main soil moisture zones, surface and root zones, to provide a comprehensive understanding of drought dynamics. The research leverages the NLDAS (North American Land Data Assimilation System) simulation dataset, offering high-resolution spatiotemporal information crucial for accurate modeling. The transformer-based architecture is employed to capture complex temporal dependencies and non-linear relationships inherent in soil moisture variations. The architecture captures long-range dependencies and complex interrelations within the data, enabling accurate predictions of both surface and root zone moisture content. This approach enables the development of a robust forecasting model capable of capturing sudden and intense decreases in soil moisture characteristic of flash droughts. The system considers the relationship between surface and root zone soil moisture, acknowledging their distinct roles in impacting vegetation health, water availability, and overall ecosystem resilience. By incorporating this dual-zone perspective, the forecasting system enhances the accuracy of flash drought predictions, providing valuable insights for early intervention and adaptive management. Through rigorous evaluations and comparisons with existing forecasting methods, we assess the system's performance in capturing spatiotemporal variability and providing lead time for proactive mitigation strategies. Our findings shed light on the transformative potential of deep learning for flash drought prediction, highlighting the crucial role of understanding the interplay between surface and root zone moisture dynamics in this context.

How to cite: Chang-Silva, R. and Park, S.: Predicting Flash Droughts Using Transformers: Understanding Surface and Root Zone , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3793, https://doi.org/10.5194/egusphere-egu24-3793, 2024.

Droughts can affect a variety of sectors, such as water resources, agricultural yield, and energy security. Moreover, their impacts can cascade or propagate to other regions due to the physical or socioeconomic linkages. Though drought impacts on energy (e.g., hydropower generation) have been well explored, their effects, in tandem with other extremes, such as heatwaves (or compound droughts and hot extremes), across different regions have been less explored. In this study, we demonstrated the compounding risk of droughts in Southwest China and hot extremes in East China (with hydropower transmission from Southwest China), which collectively presents challenges to energy security in East China. We then explore the changes in the characteristics of such spatial compounding of droughts and hot extremes across different regions in historical periods. Finally, future risks of such extremes are also explored based on simulations from Coupled Model Intercomparison Project Phase 6 (CMIP6). This study can be useful for understanding compounding risks with impacts transmitted to remote locations through physical or socio-economical pathways.

How to cite: Hao, Z.: Compounding risks from droughts and hot extremes across different regions due to energy linkages , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4546, https://doi.org/10.5194/egusphere-egu24-4546, 2024.

EGU24-4690 | Orals | NH9.10 | Highlight

Understanding and managing growing drought risks – the need for a systemic perspective 

Michael Hagenlocher, Gustavo Naumann, Isabel Meza, Veit Blauhut, Davide Cotti, Petra Döll, Katrin Ehlert, Franziska Gaupp, Anne F. Van Loon, Jose A. Marengo, Lauro Rossi, Anne-Sophie Sabino Siemons, Stefan Siebert, Abebe Tadege Tsehayu, Andrea Toreti, Daniel Tsegai, Carolina Vera, Jürgen Vogt, and Marthe Wens

In the last few years, the world has experienced numerous extreme droughts with adverse impacts on coupled human and natural systems. While agriculture is the most affected sector, the lack of water due to droughts in our highly interconnected world also affects ecosystems, public water supply, power generation, tourism, water-borne transport and buildings, often with non-linear cascading and systemic impacts. Moreover, droughts also interact with other hazards in complex ways, for example leading to compound heat-drought events, wildfires or aggravated impacts when concurring with other non-climatic hazards and shocks, such as the COVID-19 pandemic. At the same time, responses to droughts can also lead to response risks, for example when the establishment of reservoirs in response to droughts leads to overreliance on these reservoirs and in turn increases the vulnerability of communities, sectors and systems to droughts. Combined, these characteristics pose a serious challenge to our ability to grasp the complexities of drought risks and to manage them in a comprehensive way. To avoid ineffective risk management and maladaptation, a paradigm shift in how we look at, assess and manage drought risks is urgently needed – from a siloed, single-risk (e.g. drought risks for agriculture, energy, transport) to a systemic perspective.  

However, despite more frequent and severe events, systemic drought risk assessment is still incipient compared to that of other meteorological and climate hazards. This is mainly due to the outlined complexity of drought, the high level of uncertainties in its analysis, and the lack of community agreement on a common framework to tackle the problem. Addressing this gap, we propose a novel drought risk framework that highlights the systemic nature of drought risks, and show its operationalization using the example of the 2022 drought in Europe. Our research emphasizes that solutions to tackle growing drought risks should not only consider the underlying drivers of drought risks for different sectors, systems or regions, but also be based on an understanding of sector/system interdependencies, feedbacks, dynamics, compounding and concurring hazards, as well as possible tipping points and globally and/or regionally networked risks.

How to cite: Hagenlocher, M., Naumann, G., Meza, I., Blauhut, V., Cotti, D., Döll, P., Ehlert, K., Gaupp, F., Van Loon, A. F., Marengo, J. A., Rossi, L., Sabino Siemons, A.-S., Siebert, S., Tadege Tsehayu, A., Toreti, A., Tsegai, D., Vera, C., Vogt, J., and Wens, M.: Understanding and managing growing drought risks – the need for a systemic perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4690, https://doi.org/10.5194/egusphere-egu24-4690, 2024.

EGU24-5881 | ECS | Orals | NH9.10

An analytical framework to understand flash drought mechanisms 

Vishal Singh and Tushar Apurv

Understanding the physical mechanisms which contribute towards the rapid intensification of flash droughts is crucial for improving their forecasts. These mechanisms are difficult to elucidate using statistical techniques due to the complex interactions between land surface and atmospheric processes. In order to overcome this limitation, we use a slab model to model the coupled energy and water balance of the land and atmosphere. We develop an analytical framework to disentangle the influence of external forcings and system response driven by the state variables using the energy and water balance equations of the model. We apply the model to six locations selected from different climate regions of India to identify the physical mechanisms of flash droughts. We find that most flash droughts in India happen during the monsoon season, with higher frequency in humid regions of Northeast India and southern peninsular India. We find that all flash droughts occur during periods of deficient rainfall and the drying is predominantly driven by net shortwave radiation. However, the flash droughts differ in terms of contribution of winds towards drying, based on which we classify the flash drought mechanisms into three types: (a) Category 1: flash droughts with wind-driven intensification due to land-atmospheric feedback (b) Category 2: flash droughts with minimal contribution of winds towards drying and (c) Category 3: flash droughts with wind-driven intensification due to advected heat. We also show that although the enhanced vapor pressure deficit is a frequently recurring feature of flash droughts, it is not necessarily the most relevant contributor in their development.  

How to cite: Singh, V. and Apurv, T.: An analytical framework to understand flash drought mechanisms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5881, https://doi.org/10.5194/egusphere-egu24-5881, 2024.

EGU24-6334 | ECS | Posters on site | NH9.10

Global characterisation of land-atmosphere interactions during flash droughts using satellite observations 

Bethan Harris, Christopher Taylor, Darren Ghent, and Wouter Dorigo

Land-atmosphere interactions are known to be important for the development of flash droughts, and improving the representation of these interactions in subseasonal-to-seasonal (S2S) forecasting models would provide a potential source of skill for predicting these events. However, understanding the land-atmosphere coupling processes involved in flash drought development globally is hindered by the fact that key variables such as root-zone soil moisture and surface latent and sensible heat fluxes cannot be directly observed from satellites. In this study, we use a definition of flash droughts based on ESA CCI soil moisture to explore the composite behaviour of land-atmosphere variables around flash drought onset dates. We exploit satellite-observed land surface temperature (LST) data from ESA CCI to diagnose the balance between latent and sensible surface heat fluxes by computing the difference between LST and 2m air temperature (T2m) from ERA5 reanalysis. Since the standardised anomaly of the sensible heat flux is approximately equal to the standardised anomaly of LST-T2m, this method allows us to identify increases in sensible heat flux anomalies during flash droughts. When radiation conditions remain approximately constant, this is associated with the onset of a water-limited evaporative regime. We explore the spatial variation in the sensitivity of both LST-T2m and Vegetation Optical Depth (VOD) to flash drought events, to understand where the surface energy budget changes most strongly and where impacts on vegetation are most severe. Additionally, we consider which satellite-observable variables are most promising for providing information that can improve the S2S prediction of flash droughts.

How to cite: Harris, B., Taylor, C., Ghent, D., and Dorigo, W.: Global characterisation of land-atmosphere interactions during flash droughts using satellite observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6334, https://doi.org/10.5194/egusphere-egu24-6334, 2024.

EGU24-7553 | ECS | Orals | NH9.10

Data-driven assessment of drought impacts – exploring sectoral impacts at a subnational scale: a case study for Romania. 

Dor Fridman, Reetik Sahu, Emilio Politti, Peter Burek, Barbara Willaarts, Marthe Wens, Natalia Limones Rodriguez, and Taher Kahil

Drought hazards have intensified in many world regions during the recent century, exposing multiple environmental and socio-economic systems to increased risks. Nevertheless, estimating drought risk is still challenging due to the complex links between drought hazards and their potentially disastrous impacts. The recently published JRC European drought risk atlas, an outcome of the European Drought Observatory for Resilience and Adaptation (EDORA) project, has utilized a data-driven approach, linking drought’s hazard, vulnerability, and exposure with observed sectoral impacts. This project links theoretical causal impact chains and quantitative outcome-oriented drought risk assessment, resulting in a high-resolution assessment of drought-driven sectoral impacts, which can support drought management, and adaptation policies and actions.

At the European level, long time series of observed impacts may be limited in terms of spatial or sectoral coverage, relevance, or granularity. However, specific countries often collect and compile sub-national resolution impact data relevant to drought risk assessment that can inform management and adaptation policies and actions. Implementation at a subnational scale using customized country specific data can be a valuable tool to assess drought risk and impact. However, ensuring valid and reliable results would require following a standard procedure. We explore this potential and delve one step deeper by conducting a national data-driven drought risk assessment in Romania.

We use data from various Romanian government agencies to examine drought-associated impacts on water supply, hydroelectricity energy production, and cultivated crop production. These spatially explicit national data provide larger coverage (cultivated crops), higher spatial resolution (hydroelectricity generation), and country-relevant data (drinking water supply to households) as compared to using Eurostat data for a Europe-wide approach. Data is not restricted only to these sectors; instead, it allows extending the sectoral coverage beyond that of the European drought risk atlas and exploring drought impacts on livestock productivity, water-dependent tourism, and forestry productivity, which are sectors of specific interest to the country. A preliminary assessment suggests a range of sectoral impacts associated with droughts in Romania. The livestock productivity suffers an average annual loss (AAL) of 1 -2%, the forestry sector presents 3% of AAL, and the tourism sector has the highest AAL, at around 6%.

This proposed talk will focus on the potential of applying the Pan-European data-driven drought risk assessment method with nationally derived and diverse datasets, highlighting its flexibility in incorporating additional sectors. Specifically, we will present results for sectors not accounted for before. Finally, we will provide insights into the opportunities and limitations of standardizing the data-driven approach to conduct country-specific, sub-national drought risk assessments.

How to cite: Fridman, D., Sahu, R., Politti, E., Burek, P., Willaarts, B., Wens, M., Limones Rodriguez, N., and Kahil, T.: Data-driven assessment of drought impacts – exploring sectoral impacts at a subnational scale: a case study for Romania., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7553, https://doi.org/10.5194/egusphere-egu24-7553, 2024.

EGU24-8665 | Orals | NH9.10

Drought risk perception and adaptive measures of livestock farmers in NE Romania 

Mihai Ciprian Margarint, Andra-Cosmina Albulescu, Mihai Niculita, Jianshuang Wu, and Paolo Tarolli

Droughts represent the main climatic hazard in NE Romania, affecting all agricultural activities to different extents, depending on their timing and intensity. This work investigates the drought risk perception of livestock farmers, together with their coping strategies, through a downscaled approach. Extensive fieldwork complemented by interviews and a survey was carried out during the summers of 2022 and 2023, with the main goal of gathering data from the most drought-sensitive and impacted farmer typology: livestock farmers that practice grazing, depending entirely on the amounts of precipitation and their distribution during the grazing period.

The questionnaire was applied to 185 farmers with different farm settings. This included 64 questions (with response types grouped in 5-point Likert scale, dichotomic, multiple choice, or open items), structured as: (i) the risk perception of the farmers regarding climate-related hazards (awareness, perceived trends of climate hazards, impacts on water and feed supply, animal health, pasture quality, preparedness, trust in authorities); (ii) farm settings (type, size, water supply, restrictive factors, production specificity, animal breed, partnership status, perspectives), and (iii) farmer profile (age, education level, experience, implication, place of living, heat vulnerability, satisfaction level). The statistical analysis was performed in R (univariate, bivariate, and multivariate analysis).

The results include a broad range of correlations and insights, from which we selected an initial subset statistically significant. Respondents considered droughts the most impactful climatic hazard, followed by heat waves, both in the last and the next 10 years. Also, about 75% of the farmers reported an increase in drought intensity and frequency in the last 10 years. In terms of preparedness, 58% of the participants reported that they implemented drought preparedness measures, although they estimate their preparedness level as medium (2.82 mean, 1.1 std). Medium to low levels were also reported by farmers when talking about trusting authorities at county (1.85 mean, 0.82 std), national (2.29 mean, 1.15 std) or European (2.34 mean, 1.26 std) scales to reduce the impact of droughts.

As drought risk perception is a prominent factor to be acknowledged and integrated into drought mitigation strategies, these findings can inform decision-making at regional and local scales. This study marks the start of drought risk perception research in Romania, being the first to address this topic in the country of reference and one of the few and most detailed in Europe.

How to cite: Margarint, M. C., Albulescu, A.-C., Niculita, M., Wu, J., and Tarolli, P.: Drought risk perception and adaptive measures of livestock farmers in NE Romania, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8665, https://doi.org/10.5194/egusphere-egu24-8665, 2024.

EGU24-8923 | ECS | Orals | NH9.10

Enhanced drought impact monitoring: integrating automated search, translations, and text analysis into online media report scraping 

Monika Bláhová, Veit Blauhut, Mirko D’Andrea, Lauro Rossi, Kerstin Stahl, and Kathrin Szillat

Droughts are among the most destructive natural disasters affecting millions worldwide, profoundly impacting society and ecosystems. The demand for effective drought impact monitoring and reporting systems was proven to be crucial for timely mitigation and response. Traditionally, drought impact monitoring systems rely heavily on manual processing analysis and validation of physical and online reports or costly clipping databases, often lacking real-time information. The manual processing of drought impact reports is not only time-consuming but also prone to inconsistencies and delays in the long term. The sheer volume of data generated daily demands significant human resources, often leading to escalated costs and low viability of the final drought impact databases. These challenges underscore the need for more efficient, cost-effective, and reliable methods to process and analyze drought-related data. Recent advancements in large language models (LLM) and artificial intelligence (AI) tools have opened new pathways for enhancing drought impact monitoring systems. The recent EDORA (The European Drought Observatory for Resilience and Adaptation) project enabled us to employ these novel methods, facilitating the task of populating the European Drought Impact Database (EDID). The specific methodology and workflow we tested involved three steps: (1) automated searching for drought impact-related online media posts, (2) automated text translations, and (3) automated text content analysis. Step (1) of the workflow involved employing Google News Archive Search for EU countries in 2000-2022 to scrape relevant online media reports automatically. Searching was based upon predefined search queries translated into all official EU languages. The media report's content was acquired using the trafilatura Python package. A large number of reports found this way were then, in Step (2), translated to the English language using Amazon AWS Translation service. In order to support a correct selection and classification of the drought impact database’s structure, Step (3) was necessary. The translated reports were further analyzed and classified using the GPT 3.5 API, extracting structured data from unstructured text. Thanks to this semi-automated workflow, we analyzed over 60000 online reports and included over 700 additional entries to the EDID. The difference in these numbers shows that the multi-step workflow is necessary to select only those reports that comply with the drought impact definitions of EDID. The contribution will illustrate the difficulties and successes in each step with specific examples. In conclusion, integrating LLM and AI tools into drought impact monitoring systems presents a significant leap forward in our ability to process vast amounts of data quickly and accurately. While some expert decisions are still necessary in our workflow, this innovation reduces the reliance on manual labor and associated costs.  From an operational risk management perspective, it enhances the responsiveness and effectiveness of drought impact reporting. As we continue to refine and expand these technologies, we anticipate a future where real-time, accurate drought impact monitoring is not just a possibility but a reality.

How to cite: Bláhová, M., Blauhut, V., D’Andrea, M., Rossi, L., Stahl, K., and Szillat, K.: Enhanced drought impact monitoring: integrating automated search, translations, and text analysis into online media report scraping, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8923, https://doi.org/10.5194/egusphere-egu24-8923, 2024.

EGU24-9666 | Orals | NH9.10 | Highlight

Insights from the European Drought Risk Atlas 

Lauro Rossi, Marthe Wens, Hans De Moel, Davide Cotti, Anne-Sophie Sabino Siemons, Michael Hagenlocher, Anne Van Loon, Willem Maetens, Dario Masante, Andrea Toreti, Gustavo Naumann, Roberto Rudari, Michele Meroni, Francesco Avanzi, Tatiana Ghizzoni, and Paulo Barbosa

In the past decades, and notably the last few years, droughts have severely impacted various interconnected socio-economic sectors and ecosystems across the EU. These impacts encompass, among others, extensive losses in both rain-fed and irrigated agriculture, challenges and constraints in public water supply, disruptions in inland shipping, diminished production of hydropower and thermoelectric energy, impaired functioning of terrestrial and freshwater ecosystems, and implications for the tourism industry. In order to better prepare for future drought events in Europe, knowledge on the drivers, spatial patterns and dynamics of drought risks is urgently needed. 

The European Drought Risk Atlas responds to that need by mapping hotspots and risk drivers across diverse systems and regions within the EU. Combining conceptual risk models (impact chains) and a data-driven quantitative drought risk assessment based on machine learning, this Atlas represents a significant stride toward impact-driven drought risk analysis in present and projected global warming levels (+1.5°C, +2.0°C, +3.0°C). It provides a detailed and disaggregated perspective on the risks posed by droughts to societies and ecosystems, with a particular focus on agriculture, public water supply, energy, river transportation, freshwater, and terrestrial ecosystems.

The data-driven analysis reveals that current levels of drought risk in the EU are already notable, with average annual losses presenting economic and environmental threats in nearly all regions. As expected, the Mediterranean region, particularly the Iberian Peninsula, faces high drought risk under both current and projected climate conditions, driven by the escalating dry conditions associated with global warming. However, while drought risk of certain sectors in Europe follows a north-south gradient of overall mean drying (south) and wetting (north) under climate change, the analysis underscores that each sector reacts distinctly to current and projected hazard conditions, exhibiting sector-specific sensitivity. Eastern and Western Europe may experience complex dynamics due to the interplay between drying and wetting patterns and precipitation variability, resulting in different risk conditions depending on the considered sector. While the analysis may still be refined as new data (observations and future climate simulations) become available, this Atlas represents a unique tool of unparalleled value that can shape future EU preparedness and adaptation policies.

How to cite: Rossi, L., Wens, M., De Moel, H., Cotti, D., Sabino Siemons, A.-S., Hagenlocher, M., Van Loon, A., Maetens, W., Masante, D., Toreti, A., Naumann, G., Rudari, R., Meroni, M., Avanzi, F., Ghizzoni, T., and Barbosa, P.: Insights from the European Drought Risk Atlas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9666, https://doi.org/10.5194/egusphere-egu24-9666, 2024.

EGU24-9744 | ECS | Posters on site | NH9.10

Framing co-production in socio-hydrological modelling for drought impact assessment and mitigation 

Luigi Piemontese, Silvia De Angeli, Giulio Castelli, Lorenzo Villani, Giorgio Boni, and Elena Bresci

Drought is an increasingly widespread and impactful disaster across the world, causing serious impacts on health, agriculture, societies and the environment. For its complex nature, assessing the present and future impacts of droughts is a prominent challenge. Droughts can be defined differently according to the sectoral, disciplinary, and socio-economic domains, making drought impact assessment often ill-defined or incomplete. For example, droughts may or may not occur after a period of scarce precipitation, depending on local water access and use. Drought impacts are increasingly understood to be socially-influenced processes instead of mere hydro-climatic events. Transdisciplinary approaches to co-producing drought impact assessments and co-defining drought mitigation strategies are therefore particularly needed, while presenting specific challenges and differences compared to participatory approaches traditionally used for other natural hazards. Drawing from a diverse body of literature on participatory modelling research in the fields of transdisciplinary sustainability science, integrated water resources management, socio-hydrology and hydrosocial studies, we introduce a comprehensive framework for guiding participatory socio-hydrological modelling oriented to problem solving and real case applications. The framework is composed of two parts. The first part sets up a collaborative space by defining 1) a fitting drought governance space, 2)  potential shared definitions of drought impact; while the second part provides a practical guidance on 3) the biophysical as well as perceived features contributing to drought impact, 4) how and in which phase of the workflow to promote a proactive stakeholders involvement and 5) the potential pitfalls and uncertainty analysis to assess the equity and sustainability of the identified solutions. We further illustrate how such a framework can capture the different dimensions of participation throughout the modelling phases in some case studies to elucidate the applicability of the proposed approach in advancing research and action on drought impact assessment and mitigation.

How to cite: Piemontese, L., De Angeli, S., Castelli, G., Villani, L., Boni, G., and Bresci, E.: Framing co-production in socio-hydrological modelling for drought impact assessment and mitigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9744, https://doi.org/10.5194/egusphere-egu24-9744, 2024.

EGU24-10657 | ECS | Posters on site | NH9.10

An historical flash drought analysis in Sicily based on ERA5 Reanalysis evapotranspiration and soil moisture data 

Tagele Mossie Aschale, Gaetano Buonacera, Nunziarita Palazzolo, Antonino Cancelliere, and David. J Peres

Sicily copes periodically with the challenge of drought events, impacting water resources management, as well as agricultural and environmental landscapes. While the area is well studied regarding traditional slow-evolving droughts, studies on flash droughts are lacking. This study delves into the historical analysis of flash drought events in Sicily, characterized by their abrupt onset and severity.  Specifically, we carry out our analysis based on ERA5-Land Reanalysis daily evapotranspiration and soil moisture data, covering the period 1950-2023. First, a comparison of ERA5-Land Reanalysis evapotranspiration with reference evapotranspiration computed from observational series is carried out. Then the Evaporative Demand Drought Index (EDDI) is computed from the Reanalysis evapotranspiration series, at various temporal scales. The EDDI index is then analysed in combination with soil moisture series at various soil depths, to corroborate the identification of the onset of past historical flash drought events. A specific focus in devoted to a heat wave occurring during July 2023, showing the severity of this event. The study provides preliminary insights for a clearer development of criteria for flash drought identification in the Mediterranean area.  

How to cite: Aschale, T. M., Buonacera, G., Palazzolo, N., Cancelliere, A., and Peres, D. J.: An historical flash drought analysis in Sicily based on ERA5 Reanalysis evapotranspiration and soil moisture data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10657, https://doi.org/10.5194/egusphere-egu24-10657, 2024.

EGU24-10992 | ECS | Posters on site | NH9.10

Constructing a Social Media-Based Index to Capture the Socio-Economic Impacts of Droughts 

Jingxian Wang, Barbara Pernici, Matteo Giuliani, and Andrea Castelletti

Droughts, unlike other natural disasters, have complex and multifaceted consequences that spread over vast regions and extended durations. Several indices, including the Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI), were designed to measure and quantify droughts. However, they predominantly focus on the meteorological and hydrological aspects of drought events, often overlooking the social and economic impacts. On the other hand, existing impact databases like the European Drought Impact Report Inventory (EDII) and the European Drought Impact Database (EDID) are usually constrained by temporal and spatial resolution due to the limitations of available data sources. Given this context, social media, bolstered by the rapid evolution of technology, offers a unique perspective. Users on social media can share their firsthand experiences and perceived impacts of droughts, providing a rich source of indirect socio-economic impact information that is often missed by traditional methods.

The objective of this study is to develop an ad-hoc drought index that reflects the socio-economic impacts of droughts using information gathered from social media, and compare the ad-hoc drought index to physical drought indices to evaluate the usefulness and accuracy of the state-of-the-art method. While current literature underscores the importance of integrating social media as a complementary data source to improve drought detection and response, most studies focus on classifying the impacts of droughts into different categories based on text mining. To the best of our knowledge, none have transformed these text-derived impacts from social media into a single numeric index to help decision-makers grasp the drought situation quickly and efficiently. Thus, we aim to address this gap and, ultimately, inform dynamic and adaptive drought management strategies.

While the goal is to capture the impacts of drought at a Pan-European scale, Italy was selected for preliminary studies, due to a significant drought event that occurred in 2022. This event drew attention from various sectors and offered a snapshot of socio-economic impacts on local communities. Notably, the number of tweets containing the keywords “siccità” or “siccita” (drought) increased more than tenfold in 2022 compared to 2020 and 2021. We conducted location extraction, topical modelling, and classification to filter out irrelevant tweets, identify the regions where information is shared, and categorise the sectors in which impacts are perceived by local residents. Each tweet is scored based on the positivity or negativity of its narrative through sentiment analysis, which indicates the gravity of its impact. Subsequently, this score is combined with a manual evaluation of the intensity for constructing the ad-hoc drought index. Once established, the ad-hoc drought index is compared to physical drought indices. We do expect the ad-hoc drought index to reveal patterns that were not previously seen with physical drought indices, providing a broader and deeper understanding of the impacts of droughts on societies and economies.

How to cite: Wang, J., Pernici, B., Giuliani, M., and Castelletti, A.: Constructing a Social Media-Based Index to Capture the Socio-Economic Impacts of Droughts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10992, https://doi.org/10.5194/egusphere-egu24-10992, 2024.

EGU24-11009 | ECS | Orals | NH9.10

The Italian Alpine Drought Impact Inventory through an automatic text analysis of newspaper articles: the case of 2022-2023 drought 

Stefano Terzi, Luigi Piemontese, Stefan Schneiderbauer, and Massimiliano Pittore

Droughts in mountains are expected to increase in the future with consequences downstream and beyond mountain ranges. While these conditions are internationally recognized, quantitative data on drought effects and impacts are still lacking or not available. This gap hampers a clear understanding and modelling of drought conditions for future adaptation. For these reasons, unconventional data types (such as newspaper articles) have been recently explored to fill this gap with information on drought extension, duration and impacts. In particular, the 2022-2023 drought in the North of Italy was one of the most impactful events in the modern history of the country causing severe damages for a long period on multiple sectors. However, data on its impacts is not available.

For these reasons, this study aims to create an automatic and open near-real time drought impact inventory from newspaper articles for the Italian Alps focusing on the 2022-2023 event. By doing so, the database allows to investigate drought impacts looking at their dynamics in space, time and across multiple sectors. Building on concepts and classifications from the European Drought Impact Inventory, the Italian Alpine Drought Impact Inventory includes an automatic identification of newspaper article, harvesting and classification of information on drought impacts according to the: geographical area (e.g., municipality, river basins and province), the affected sectors (e.g., agriculture, energy, urban and tourism) and temporal duration of events occurred in the Italian Alps. Information is sourced and categorized from newspaper articles from 2022 on a weekly basis through an automated text analysis of Google News query results which are processed using Natural Language Processing methods of tagging and classification. The resulting inventory provides an open-source database of drought information making data available for further research on droughts.

Preliminary analyses of the Italian Alpine Drought Impact Inventory show the largest number of news reported during the July-2023 period covering multiple sectors, mainly agriculture and water supply. A high number of news can also be observed in March 2022, capturing the early signals of snow drought conditions in the Alps that led to extended impacts during summer and autumn. Overall, the open dataset has the potential to advance the understanding of drought impacts in the Italian Alps towards a better informed implementation of prevention strategies and future climate change adaptation.

How to cite: Terzi, S., Piemontese, L., Schneiderbauer, S., and Pittore, M.: The Italian Alpine Drought Impact Inventory through an automatic text analysis of newspaper articles: the case of 2022-2023 drought, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11009, https://doi.org/10.5194/egusphere-egu24-11009, 2024.

EGU24-11123 | ECS | Posters on site | NH9.10

In sync or apart: A downscaled approach to drought vulnerability and self-reported preparedness among livestock farmers in NE Romania 

Andra-Cosmina Albulescu, Mihai Ciprian Mărgărint, Mihai Niculiță, Jianshuang Wu, and Paolo Tarolli

In recent years, there has been a growing emphasis on drought vulnerability within the broader context of drought risk assessments, which can be primarily attributed to the pivotal role that vulnerability plays in determining the potential impacts of drought and in shaping drought management. Nevertheless, effective drought mitigation efforts should not solely focus on a thorough examination of drought vulnerability but should also factor in preparedness, if they are to gain a broader perspective and produce meaningful change for the human communities and systems impacted by droughts. This holds significant implications for the farming sector and, at a deeper level, for small or medium farmers, who stand at the forefront in terms of vulnerability to drought and also face significant challenges in withstanding its impacts.

This study investigates the convergences and divergences between drought vulnerability and self-reported preparedness, with a specific focus on 1) the spatial patterns of vulnerability and preparedness, and 2) the relationships between these key elements, local landforms, and farm settings. The selected farming community, namely the livestock farmers in the Northeast of Romania, stands out as one of the most representative, year-long exposed to drought. The analysis focuses on agricultural drought within the last decade, and it relies on a downscaled, index-based approach.

In order to compare the vulnerability and preparedness levels, two indexes are computed under an intuitive additive approach based on the data gathered from a survey conducted in situ on 141 livestock farmers in May-July 2023. Drought vulnerability is examined in terms of access to water resources, basic infrastructure, availability of reserves, networking level, farming education background and experience of farmers, and diversity of farming activities. Self-reported drought preparedness is conceptualised under a dichotomic approach that integrates proxies of both objective and subjective preparedness.

Ranging from 0 to 1, the values of the Drought Vulnerability Index and Drought Preparedness Index are divided into equal-interval levels (i.e., very low, low, medium, high, and very high). Drought vulnerability levels are mapped against those of self-reported preparedness to discern spatial patterns within the study area. Further on, statistical tests (e.g., t-test, Spearman correlation) are conducted to explore significant relationships between drought vulnerability, preparedness, local landforms, and farm settings.

Under the presented methodological framework, a negative correlation emerged between drought vulnerability and self-reported preparedness. Cross-correlations point out that the farming educational background, availability of fodder and financial reserves, basic infrastructure, and access to water play prominent roles in shaping both drought vulnerability and preparedness. Although there are no evident spatial patterns in drought preparedness levels, drought vulnerability shows a northward increase in the study area. In addition, there is a significant variation in both drought vulnerability and preparedness between different farm sizes, revealing that smaller farms have higher vulnerability and lower preparedness.

This paper significantly contributes to the understanding of drought vulnerability in Europe, specifically in an area still underexplored in this regard. The findings serve as a roadmap for developing contextually relevant drought management plans, and the cross-correlations reveal the key components of vulnerability or preparedness.

How to cite: Albulescu, A.-C., Mărgărint, M. C., Niculiță, M., Wu, J., and Tarolli, P.: In sync or apart: A downscaled approach to drought vulnerability and self-reported preparedness among livestock farmers in NE Romania, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11123, https://doi.org/10.5194/egusphere-egu24-11123, 2024.

EGU24-11341 | ECS | Orals | NH9.10

Impact perception as driver for extreme event definition, identification and monitoring 

Pedro Henrique Lima Alencar, Trenton Wayne Ford, and Eva Nora Paton

The current approach to defining (flash) droughts in climate and hydrology typically relies on standardized indexes like SPI, SMI, and SPEI, combined with specific thresholds to determine the onset and conclusion of these events. However, this methodology often overlooks a crucial aspect – the impacts that communities experience during these events, such as plant mortality, well drying, or heat stress. We propose a novel framework that integrates the community's perception of extreme events, considering both the impact and risk tolerance of these communities. Our approach involves actively engaging with communities and stakeholders to understand their perception of extreme events, their associated impacts, and their levels of resilience and risk acceptance. By leveraging hydrological and crop models alongside historical and projected climate data, we can analyse conditions associated with specific impacts and the severity of these impacts for each community or user group. Additionally, we can develop local definitions of droughts and other related extreme events that align more closely with community perceptions and relevant impacts. This tailored approach aims to enhance communication and resilience within these communities. We tested this new framework in the farming communities of Illinois (USA), Brandenburg (Germany) and Ceará (Brazil), where we identified varying perceptions of drought impacts. Using these insights, we formulated distinct definitions of flash droughts for different regions, considering local climate conditions and community perspectives. This approach resulted in improved event identification and definition, facilitating more effective communication and empowering community actions.

 

How to cite: Lima Alencar, P. H., Ford, T. W., and Paton, E. N.: Impact perception as driver for extreme event definition, identification and monitoring, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11341, https://doi.org/10.5194/egusphere-egu24-11341, 2024.

EGU24-11625 * | Orals | NH9.10 | Highlight

The European Drought Impact Database (EDID) - from Research to Operation 

Kerstin Stahl, Kathrin Szillat, Monika Blahova, Veit Blauhut, Lauro Rossi, Dario Masante, Willem Maetens, and Andrea Toreti

Drought impact data play a crucial role in assessing drought risk, aiding in the determination and validation of warning levels, and predicting potential impacts. Although there is a growing consensus on the operational use of monitored physical drought hazard indices, there is currently no universally accepted convention for drought impact data. This contribution delves into the methodology, development, and content filling of the European Drought Impact Database (EDID), illustrating the challenges involved in transitioning from initial research databases to a database tailored for operational purposes, specifically within the framework of the Copernicus European Drought Observatory. Drawing on previous experience with text-based drought impact reports and regional sector-specific operational impact monitoring, EDID addresses the need for common, yet impact-specific, and information-specific solutions. The conceptual data model for coding text into usable data attributes, such as the impacted system, time, and location of the impact, needed to balance between parsimony and flexibility. The model developed allows for future expansion of sources and links; linked attribute tables enable the storage of source and sector-specific data. The implementation of a new severity score applicable across all nine impacted systems highlights this challenge of finding a balance between commonality and specificity. 

To test the method's applicability, diverse existing databases, including the European Drought Impact Report Inventory (EDII) and regional or national inventories, such as the Czech Intersucho data, were integrated into the new EDID. Additional content was gathered through a semi-automated webcrawl+translation+classification procedure to fill gaps using media reports. The development and content-building of EDID mark significant progress towards a Europe-wide and more consistent collection and archiving of drought impact data. However, challenges persist for the real-time operational use of EDID as an indicator of the situation and for certain future analyses. Drought impact reports often lack sufficiently accurate geographical or time references and other key attributes. The spatial differences in the current EDID database's impact data records content highlight the need for more effective sharing of regional experience and knowledge, serving as examples across larger regions, as well as a  systematic approach to impact data collection. Despite these challenges, the EDID represents a substantial step forward in enhancing our understanding of drought impacts on a broader scale.

This work was part of the project EDORA - European Drought Observatory for Resilience and Adaptation (The European Commisssion DG Environment and Joint Research Centre; https://edo.jrc.ec.europa.eu/edora/)

How to cite: Stahl, K., Szillat, K., Blahova, M., Blauhut, V., Rossi, L., Masante, D., Maetens, W., and Toreti, A.: The European Drought Impact Database (EDID) - from Research to Operation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11625, https://doi.org/10.5194/egusphere-egu24-11625, 2024.

EGU24-16262 | ECS | Posters on site | NH9.10

Drought Vulnerability Concepts and User-Endorsed Factors in Forested Ecoregions in Cold and Continental Climates 

Elin Stenfors, Malgorzata Blicharska, Thomas Grabs, and Claudia Teutschbein

In a changing climate, the assessments of drought risk and vulnerability are becoming increasingly important. Responding to the global call for a proactive approach to drought risk management, there is now a growing emphasis on drought vulnerability assessments within the drought research community. Since the manifestation of drought vulnerability depends on the social, ecological, and hydroclimatic context in which it unfolds, recognizing vulnerability factors specific to particular climatological and ecological regions could enhance the accuracy and reliability of vulnerability assessments. However, a holistic overview of factors affecting vulnerability in polar and cold climates is currently lacking, although these regions accommodate extensive socio-hydrological systems, encompassing urban areas, energy infrastructures, agricultural practices, and vast boreal forests. Through an interdisciplinary and systematic exploration of existing literature, we identified the manifestation and conceptualization of drought vulnerability for forested ecoregions in the Köppen–Geiger D and E climates. Factors contributing to vulnerability, as delineated by several scientific disciplines, were identified and synthesized into a novel conceptual framework that categorizes vulnerability factors by their location in a socio-hydrological system, and their relation to blue or green water sources (Stenfors et al., 2023). To further assess their relative importance in cold and continental climates, a survey with more than 100 respondents from various sectors (e.g., agriculture, forestry, energy, water supply, environment, etc.) and different governance levels was conducted to validate and rank the identified factors and measurable indicators. Thus, we provide a list of user-endorsed drought vulnerability factors and corresponding indicators, which allows for identification of systemic vulnerability patterns, providing new insights into regional differences in drought vulnerability and a base for stakeholders performing proactive drought risk assessments in the study region.

Reference:

Stenfors E, Blicharska M, Grabs T, Teutschbein C. 2023. Droughts in forested ecoregions in cold and continental climates: A review of vulnerability concepts and factors in socio-hydrological systems. WIREs Water: e1692 DOI: https://doi.org/10.1002/wat2.1692

How to cite: Stenfors, E., Blicharska, M., Grabs, T., and Teutschbein, C.: Drought Vulnerability Concepts and User-Endorsed Factors in Forested Ecoregions in Cold and Continental Climates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16262, https://doi.org/10.5194/egusphere-egu24-16262, 2024.

EGU24-17075 | ECS | Orals | NH9.10

Dynamic spatiotemporal migration of cross-sectoral cascading drought events across climate zones  

Lu Tian, Jingshui Huang, and Markus Disse

Anthropogenic global warming is exacerbating the frequency and severity of extreme droughts, reinforcing cascading effects across sectors and increasing the urgency of research on the systematic risks associated with droughts. Current research on cascading droughts is predominantly constrained to examining the temporal delay response of cross-sectoral droughts within single characterized regions or climate zones. The dynamic spatio-temporal migration of cross-system cascading drought chains across multiple climate zones remains unexplored. In this study, we rely on the highly precise event-by-event link between multiple types of droughts and make the first attempt to investigate the dynamic spatio-temporal migration trajectory of cross-system cascading droughts across multiple climate zones in Central Asia, including arid desert (AD), arid steppe (AS), temperate (T), cold (C) and alpine (Alp). The results capture for the first time the apparent spatial aggregation state of cascading drought events in the three climate zone combinations AD+AS, AD+AS+C+Alp, and AD+AS+Alp. The transition zone, from the alpine to the arid desert (AD+AS+C+Alp), represents a climate zone combination with the highest systematic drought risk zone, marked by the highest occurrence of the four-system cascading drought event involving droughts of precipitation, evaporation, runoff, and soil moisture. The typical cascading drought pattern shows that the hotspot gradually moves away from the Alp and C to AD and AS climate zones, implying the effect of the interplay between different climate zones on drought evolution. Our findings recommend that early warnings of systematic drought risk should not be limited to temporal links alone but should include both spatial and temporal aspects.

How to cite: Tian, L., Huang, J., and Disse, M.: Dynamic spatiotemporal migration of cross-sectoral cascading drought events across climate zones , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17075, https://doi.org/10.5194/egusphere-egu24-17075, 2024.

EGU24-18709 | ECS | Orals | NH9.10

Understanding drought risks for European ecosystems through conceptual risk models 

Anne-Sophie Sabino Siemons, Davide Cotti, Marthe Wens, Hans de Moel, Lauro Rossi, Yvonne Walz, and Michael Hagenlocher

Ecosystems in Europe are increasingly faced with more frequent and more intense drought events. The impacts of droughts do not only undermine ecosystem health and the provision of ecosystem services, but can lead to the deterioration of the system’s long-term resilience to droughts. In order to effectively assess, reduce, and manage the risks posed by droughts on ecosystems, it is first necessary to gain a thorough understanding of how droughts affect a particular ecosystem, what the underlying risk drivers and root causes are, and how these interact to produce that risk. 

Addressing this need, we have developed conceptual models of drought risks for two highly-relevant European ecosystem types, forest and freshwater ecosystems. The conceptual models were developed and visualized using the impact chain methodology, building on extensive literature review and expert consultations, and validated in a series of expert workshops. Following this process, the risks of decreased primary production, forest die-off, and soil degradation and desertification were identified for forest ecosystems, and the risk of disruption of environmental flow for freshwater ecosystems.

The resulting impact chains provide insights into how different climatic, ecological, and societal risk drivers interact to produce drought risks for ecosystems, with some drivers being specific to a certain risk (e.g. forest composition), and others shared across them (e.g. societal water demand and abstractions). While some of these drivers relate to purely ecological features (e.g. plant physiology or soil conditions), many relate to how ecosystems are managed, and to the influence of other sectors/systems upon them (e.g. hydropower, river transportation or intensive agriculture and their adverse effects on freshwater ecosystems). Moreover, the impact chains also highlight some of the root causes (e.g. increased demand for energy, farmers' lack of awareness about agriculture's impacts on freshwater ecosystems, or incentives to enhance navigability) behind these drivers, indicating potential entry points for risk reduction and adaptation. 

The visualization in impact chains is useful to enhance the understanding and at the same time break down the complexity of the risks for these systems, which can support data-driven risk assessment, as well as the identification of entry points for risk management and adaptation. 

While in this work the risks posed by droughts for forests and freshwater ecosystems were assessed on European level, the impact chain approach presented here can be used at different scales and transferred to different ecosystems at risk from droughts. Moreover, it can be used to identify common risk drivers between ecosystems that could be addressed jointly, contributing to a more systemic drought risk management. 

How to cite: Sabino Siemons, A.-S., Cotti, D., Wens, M., de Moel, H., Rossi, L., Walz, Y., and Hagenlocher, M.: Understanding drought risks for European ecosystems through conceptual risk models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18709, https://doi.org/10.5194/egusphere-egu24-18709, 2024.

The accessibility of water resource, encompassing both water quantity and quality, is pivotal for public health and aquatic ecosystem. It has been recognized by water related Sustainable Development Goals (SDGs) such as life on land and below water. This study underscores the importance of integrating these goals in the context of water resource accessibility. We develop water scarcity assessment that accounts for water demands of human activities by further introducing water quantity and quality requirements for different aquatic life uses. This is applied in a case study for Nooksack watershed that featured diverse anadromous fish habitats. In this study, local data including hydrological flows modelled using regional records, local water quality data, and water withdrawal reports are applied for enhancing the geographical specificity of our analysis. Using different geographical scales including management areas, drainages, and NHD stream reaches, along with annual and monthly temporal scales, this study presents a comprehensive view of water scarcity. Our findings reveal different levels of water scarcity across tributaries with residential distributions and the downstream region of the Nooksack River, with the most severe level observed in agriculture intensified area (Lower Nooksack) and moderately to highly developed urban coastal region (Lummi Bay Watershed). Impaired water quality contributes to exacerbated scarcity, especially during summer, peaking in August. The detailed water scarcity examination at stream reach level specifically identifies the border streams located in the Fishtrap drainage of Lower Nooksack as critically affected by both quantity and quality induced water scarcity. It highlights the need of effective management of border watersheds. It is noteworthy that water quality induced deficiencies of instream flow required by aquatic life uses distribute at mostly first level tributaries overlapping with those most affected drainages, but do not surge at some specific locations. The This study offers a novel framework for assessing water resources accessibility at watershed scale, advocating the downscaled application of water scarcity assessment results to the NHD reach level, thereby providing more intuitive and granular insights. 

How to cite: Li, Y., Faustman, E., and Norton, C.: Integrative Assessment of Water Scarcity: A Case Study in the Nooksack Watershed Addressing Human and Aquatic Life Needs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20107, https://doi.org/10.5194/egusphere-egu24-20107, 2024.

EGU24-20347 | ECS | Orals | NH9.10

The 2022 European Drought Needs to be a Turning Point for Drought Risk Management: An Overview from Drivers to Impact and Management 

Riccardo Biella, Anastasiya Shyrokaya, and Monica Ionita and the Drought in the Anthropocene (DitA) working group - Panta Rhei/HELPING

The summer of 2022 marked a turning point for Europe as the largest drought in centuries unfolded, with dire consequences for livelihoods and ecosystems all across the continent. High temperatures and prolonged record-low precipitation underscored the event. The ensuing heatwaves in May, June, and July intensified water uptake, exacerbating conditions all across the continent, and causing secondary hazards, such as wildfires and landslides.

This research offers a comprehensive overview of the 2022 European drought, reconnecting the physical drivers of the drought, to its societal and ecological impacts, and the drought risk management measures implemented by water managers across the continent. To do so, this study relies on a survey submitted to water managers all across the continent. The survey gathered 487 responses from 30 European countries, predominantly from public and governmental organizations, making it one of the largest datasets on response to this event to date. The study shows that while Southwestern Europe bore the initial brunt, the whole continent endured protracted effects. Water managers across Europe almost unanimously acknowledged that the risk of drought is increasing and that its management is becoming more crucial year after year.

Based on the collected data we identified a correlation between increased awareness and improved preparedness post 2018-2019 drought. Yet, while awareness of drought risk is growing rapidly, preparedness lags. Additionally, despite the upward trajectory of drought preparedness, challenges persist in managing large-scale events. Differences among countries are significant, underscoring the need for European-wide coordination.

The type of measures taken varied by region and sector. In particular, water managers in Southern Europe, where agriculture is more prevalent, focussed on water supply-side measures, showing an imperative to preserve business-as-usual operations even in the face of water scarcity. On the other hand, water demand management was more common in Central and Western Europe. Long-term and transformative measures and ecosystem-based measures remain underused, underscoring how drought risk management remains largely responsive and event-focused. As droughts transcend borders, pan-European coordination is paramount to ensure effective drought risk management and address disparities in capacity across countries.

How to cite: Biella, R., Shyrokaya, A., and Ionita, M. and the Drought in the Anthropocene (DitA) working group - Panta Rhei/HELPING: The 2022 European Drought Needs to be a Turning Point for Drought Risk Management: An Overview from Drivers to Impact and Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20347, https://doi.org/10.5194/egusphere-egu24-20347, 2024.

EGU24-22325 | Orals | NH9.10

NextGen Drought Index Dashboard - Designing and piloting a new satellite data platform to strengthen drought risk financing in the Horn of Africa 

Bertrand Richaud, Jannik Anthonj, Ole Larsen, Markus Enenkel, and John Luke Plevin

One of the biggest strengths of parametric drought insurance products is that they can trigger payouts independently from observed losses (and expensive loss assessments), potentially increasing the speed of payouts and lowering premiums. To support low-income countries in formulating policies and developing instruments aimed at enhancing their financial resilience against drought, the World Bank’s Crisis and Disaster Risk Finance (CDRF) team and DHI are developing a novel drought risk finance dashboard. The overarching objective is to improve the transparency and accountability related to the development of drought risk financing instruments to strengthen national decision-making and risk ownership in low-income countries. The NextGen Drought Index (NGDI) dashboard is being piloted in Ethiopia, Kenya, and Somalia, with the vision to be implemented across Africa, and ultimately, on a global scale. The new tool allows users to access, visualize, and analyze historical and current drought conditions alongside socio-economic data, such as food insecurity. This enables users to close the critical gap between drought hazard, drought impact, and the performance of financial products. The dashboard optimizes the use of satellite-derived climate datasets, such as estimates of precipitation, soil moisture and vegetation greenness. It empowers users to combine and benchmark climate data from diverse Earth Observation (EO) platforms. This dynamic approach enables the assessment of drought risk and its temporal progression. Since the data must be analysed at a consistent geographical scale, all climate and environmental variables are aggregated and preprocessed for further analysis by governmental partners or regional stakeholders. The NGDI dashboard will be added to the CDRF team’s catalogue of tools. All choices regarding the platform’s architecture and technology prioritize sustainability, scalability, and cost-efficient maintenance. The dashboard was developed under the World Bank Disaster Risk Finance and Insurance Program, funded by the Global Shield Financing Facility (GSFF) and the Global Index Insurance Facility (GIIF).

How to cite: Richaud, B., Anthonj, J., Larsen, O., Enenkel, M., and Plevin, J. L.: NextGen Drought Index Dashboard - Designing and piloting a new satellite data platform to strengthen drought risk financing in the Horn of Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22325, https://doi.org/10.5194/egusphere-egu24-22325, 2024.

EGU24-888 | ECS | Posters on site | NH9.11 | Highlight

Identifying Mixing Components by Natural Tracers in the Lake Hévíz System 

Saeed Bidar Kahnamuei, Katalin Hegedűs-Csondor, Petra Baják, Ákos Horváth, Dénes Szieberth, György Czuppon, Márta Vargha, Bálint Izsák, and Anita Erőss

One of the largest natural thermal lakes in the world, Lake Hévíz is located in the southwestern part of the Transdanubian Range’s karst system (Hungary). It is fed by springs with different temperatures, which are located in a cave beneath the lake. The mixing of cold and hot waters generates the lake’s sulphuric therapeutic water, and it is responsible for the cave formation at the bottom, resulting in the lake's unique ecosystem. The presented research aimed at the comprehensive geochemical characterization of waters in the wider surroundings of the lake (lake water, springs, observation, drinking water, and thermal water wells). Investigating the geochemical characteristics of water took on a novel perspective through the innovative application of radionuclides as natural tracers. Within the framework of this investigation, we utilized uranium, radium, and radon isotopes to identify the mixing of fluids and infer the mixing end members in the Hévíz karst system. Alpha spectrometry was applied on selectively adsorbing Nucfilm discs as an inventive approach to measure uranium and radium isotopes. Moreover, stable isotopic ratios of hydrogen and oxygen (δ2H and δ18O) were determined to supplement the information on waters with different origins. Hydrochemical water analysis for measuring the concentration of major ions and trace elements was carried out using ICP-MS, ion chromatography, and UV-Vis spectrophotometry. The inferred fluid end members and their compositions are anticipated to provide insightful information on the hydrogeological functioning of the Lake Hévíz karst system, which is indispensable in sustainable water resource management and understanding climate change's impact.

 

 

Keywords: Thermal lake; Hydrogeochemical characteristics; Mixing fluids; Radionuclides; Stable isotopes; ICP-MS, Nucfilm, Alpha spectroscopy

How to cite: Bidar Kahnamuei, S., Hegedűs-Csondor, K., Baják, P., Horváth, Á., Szieberth, D., Czuppon, G., Vargha, M., Izsák, B., and Erőss, A.: Identifying Mixing Components by Natural Tracers in the Lake Hévíz System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-888, https://doi.org/10.5194/egusphere-egu24-888, 2024.

EGU24-908 | ECS | Posters on site | NH9.11 | Highlight

Proximal Gamma Ray Spectroscopy for monitoring Soil Water Content in vineyards 

Michele Franceschi, Matteo Alberi, Marco Antoni, Ada Baldi, Alessio Barbagli, Luisa Beltramone, Laura Carnevali, Alessandro Castellano, Giovanni Collodi, Enrico Chiarelli, Tommaso Colonna, Vivien De Lucia, Andrea Ermini, Andrea Maino, Fabio Gallorini, Enrico Guastaldi, Nicola Lopane, Antonio Manes, Fabio Mantovani, Samuele Messeri, Dario Petrone, Silvio Pierini, Kassandra Giulia Cristina Raptis, Andrea Rindinella, Riccardo Salvini, Daniele Silvestri, Virginia Strati, and Gerti Xhixha

Soil Water Content (SWC) is a key information in precision agriculture for obtaining high levels of efficiency and health of crops, while reducing water consumption. In particular, for the case of vineyards, due to the recent extreme temperature fluctuations, the knowledge of the SWC of the entire field becomes crucial to allow a timely intervention with emergency irrigation to preserve plant health and yield.

Unlike electromagnetic SWC measurements, that are punctual and gravimetric measurements, that are punctual and also time-consuming, the Proximal Gamma Ray Spectroscopy (PGRS) technique can provide field-scale, non-invasive, and real-time measurements of SWC. This is achievable through an in-situ NaI detector, continuously recording photons resulting from the radioactive decay of 40K in the soil, which are attenuated proportionally based on the amount of stored water. Given the inverse proportionality between soil moisture and photons detected by the gamma ray sensor, the SWC value can be easily obtained.

In this study we investigate the performance of PGRS applied to the case of study of a vineyard at the farm “Il Poggione” located in Montalcino (Siena, Italy).

The effectiveness of the results obtained is supported by different tests: first the validation allowed to compare the PGRS measurement (5.8 ± 1.5)% with a gravimetric measurement (9.0 ± 2.5)%, highlighting a 1-σ agreement; then by the rainfall recognition capability indeed, in correspondence to the most significant rainfall event (18 mm) the SWC value before and after the rain increased of 7.8%.

Moreover, the integration of the in-situ system with an agrometeorological station resulted in a Web App, allowing for real time data storage and thus facilitating data management, spectrum analysis, and display for both gamma ray sensor and agrometeorological station results, enabling comprehensive studies of environmental parameters (e.g., temperature, air humidity).

This research underlines the potential of PGRS as a precise, real-time, and field scale SWC monitoring tool not only in vineyards but for cultivated fields in general. Further refinements concerning the gamma ray spectra analysis and broader applications in environmental monitoring are envisaged for improved agricultural practices.

This study was supported by the project STELLA (Sistema inTEgrato per Lo studio del contenuto d'acqua in agricoLturA) (CUP: D94E20002180009) funded by the Tuscany region under the program POR FESR 2014/2020.

How to cite: Franceschi, M., Alberi, M., Antoni, M., Baldi, A., Barbagli, A., Beltramone, L., Carnevali, L., Castellano, A., Collodi, G., Chiarelli, E., Colonna, T., De Lucia, V., Ermini, A., Maino, A., Gallorini, F., Guastaldi, E., Lopane, N., Manes, A., Mantovani, F., Messeri, S., Petrone, D., Pierini, S., Raptis, K. G. C., Rindinella, A., Salvini, R., Silvestri, D., Strati, V., and Xhixha, G.: Proximal Gamma Ray Spectroscopy for monitoring Soil Water Content in vineyards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-908, https://doi.org/10.5194/egusphere-egu24-908, 2024.

EGU24-1450 | ECS | Orals | NH9.11 | Highlight

Origin of radioactivity in a neoformed mineral: the case of epsomite from the Perticara sulfur mine 

Matteo Giordani, Marco Taussi, Maria Assunta Meli, Carla Roselli, Giacomo Zambelli, Ivan Fagiolino, and Michele Mattioli

Recently, high amounts of toxic and radioactive elements have been discovered in epsomite crystals in the abandoned sulphur mine of Perticara, Italy (Giordani et al., 2022). Epsomite represents a neoformed mineral grown in the galleries after the extraction activities of the sulfur mine. In particular, a content of 5.59 ± 0.84 Bq/g of 210Po was detected in the epsomite phase, coupled with other toxic elements such as 228Th, As, Co, Fe, Mn, Ni, Sr, Ti, Zn.

The anomalous content of polonium led to new investigations of the area through the study of different matrices present in the galleries: minerals, host-rock, water, air, dust and bitumen, with the aim to define the origin and the distribution of this hazardous element. The samples were investigated combining several analytical techniques: X-ray Powder Diffraction (XRPD), Environmental Scanning Electron Microscopy (ESEM-EDS), Inductively Coupled Plasma-Atomic Emission (ICP-AES), Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), Atomic Absorption Spectrometry (AAS), Gamma Spectrometry, Alpha Spectrometry, Radon Monitor, and Alpha Track Detector (ATD).

Water samples showed high Al, Fe, Pb, Mg, and Mn content but not radioactive elements. The bitumen sample showed a higher amount of 210Po and 210Pb (0.12 ± 0.02 Bq/g and 0.11 ± 0.02 Bq/g, respectively), compared to the host-rock and fibrous sericolite samples, but lower than fibrous epsomite crystals (210Po 5.59 ± 0.84 Bq/g; 210Pb 5.93 ± 1.19 Bq/g). A slight anomaly in the 40K and 226Ra content of the host-rock was observed (0.38 ± 0.05 Bq/g and 0.052 ± 0.007 Bq/g respectively), and a high 222Rn concentration (up to 2200 ± 300 Bq/m3) was also detected in the tunnels (Giordani et al., 2024).

The confined atmosphere of the mine, with the high 222Rn concentration, is likely the source of the high level of 210Po and 210Pb, in radioactive equilibrium, detected in epsomite. Thus, the 222Rn-rich, anoxic, and hypoxic atmosphere, coupled with the abundance of Mn, Fe, and organic matter in the mine, could play a key role in the 210Po remobilization. This work highlighted that natural epsomite, which is a very common mineral phase in mines, caves, and underground environments, is able to capture 210Po and 210Pb. For this reason, it should be used as a mineral indicator for the presence of radioactive elements in similar environmental conditions, also helping to ensure safe management. These results indicate that in areas with a long history of mining, despite decommissioning, environmental hazards and human health risks may still emerge in terms of radioactivity and potentially toxic elements (PTEs).

 

Giordani, M., Meli, M.A., Roselli, C., Betti, M., Peruzzi, F., Taussi, M., Valentini, L., Fagiolino, I. and Mattioli, M., 2022. Could soluble minerals be hazardous to human health? Evidence from fibrous epsomite. Environmental Research, 206, p.112579.

Giordani, M., Taussi, M., Meli, M.A., Roselli, C., Zambelli, G., Fagiolino, I. and Mattioli, M., 2024. High-levels of toxic elements and radioactivity in an abandoned sulphur mine: Insights on the origin and associated environmental concerns. Science of the Total Environment, 906, p.167498.

How to cite: Giordani, M., Taussi, M., Meli, M. A., Roselli, C., Zambelli, G., Fagiolino, I., and Mattioli, M.: Origin of radioactivity in a neoformed mineral: the case of epsomite from the Perticara sulfur mine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1450, https://doi.org/10.5194/egusphere-egu24-1450, 2024.

The research aimed to analyse variations in soil gas radon concentrations and geogenic radon potential in areas of typical building plots located in regions known for high and low geogenic radon potential. The study was designated to address the following questions:

  • Are spatial variations in soil gas radon concentrations and radon potential statistically important in the area of a typical building plot? Are these variations similar in regions known for high and low radon potential?
  • How many measurement points should be proposed to properly evaluate geogenic radon potential and radon index on the building plot area?
  • Can an in-situ gamma spectrometric survey, combined with soil properties, be useful in the defining radon index at the area of the building plot?
  • Are seasonal variations of soil gas radon concentration significant at a depth of 0.8 m?  If so, which season is the most appropriate to evaluate geogenic radon potential?

The research was conducted in two counties: Wrocław and Dzierżoniów located in the Lower Silesian Voivodeship in the southwest part of Poland. Dzierżoniów County is among the counties listed in the Regulation of 18 June 2020 of the Minister of Health where the average radon concentration in a significant number of buildings may exceed the reference level of 300 Bq m−3. In both regions, three building plots, each of an area of 300 m2 (which is the size of a typical building plot in an urban area in Poland) were identified. At each building plot, five measurement points were designated -  at the four corners and in the middle of each plot. The research at each measurement point included the following procedures:

  • Soil gas radon concentration measurements at the depth of 0.8 m using solid nuclear track detectors have been performed. The detectors were replaced at the beginning of each season starting from summer 2023.
  • The radionuclides contents in the soil were measured in situ using the gamma-ray spectrometer Exploranium RS-230.
  • The ambient gamma dose rate was measured by the radiometer RK-100
  • Various soil properties including grain size, permeability, and filtration coefficient were determined.

Additionally, at each building plot, the instantaneous radon concentration and soil permeability measurements were performed using Lucas cells and RADON-JOK.

The preliminary research results indicate that in Dzierżoniów County uranium contents were in the range from 1.6 ppm to 3.3 ppm and thorium from 5.4 ppm to 8.2 ppm, whereas in Wrocław County uranium contents were in the range from 1.6 ppm to 2.5 ppm and thorium from 4.3 ppm to 7.4 ppm. The instantaneous survey of radon concentration revealed that in Dzierżoniów County soil gas radon concentration varied from 10.338 kBq m-3 to 31,050 kBq m-3 and soil permeability from 1*10-12 m2 to 1*10 -13 m2, whereas in Wrocław county the soil radon concentration varied from 0.102 to 0.266 kBq m-3 and soil permeability form very low (impossible to measure by used equipment) to 2*10-13m2.

Research project supported by program „Excellence initiative – research university” for years 2020-2026 for University of Wrocław

How to cite: Tchorz-Trzeciakiewicz, D.: Variations of soil gas radon concentrations in a typical building plot area - preliminary results, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3352, https://doi.org/10.5194/egusphere-egu24-3352, 2024.

EGU24-4664 | Orals | NH9.11

Gamma spectroscopy for geological studies 

Rares Suvaila

Gamma Ray spectroscopy is used in a large number of interdisciplinary applications, providing information on the identity of radioactive nuclides and allows their quantitative determination. 

Gamma Rays are electromagnetic radiations of nuclear origin and their detection is not a direct one, as it depends on the production of secondary particles which can be collected together to produce an electric signal.

Of all detector types, we prefer semiconductor ones, particularly Hyper-Pure Germanium detectors, which have very high efficiencies and excellent energy resolution. Following the sample type, occasionally the computerized analysis of the spectra has to be adapted or customized. The enormous differences between the environmental samples we need to face (from air filters to sediment, water to organic matter) drove us to develop protocols which have a general structure/pattern/methodology, but different approaches when it comes to treat the different matrices, would they be homogenous or not.

The opposite extremes in terms of use of Gamma Ray spectroscopy are the low and high count rate systems. Our job is to evaluate limits, to adapt to the statistical conditions, to calculate correction factors in order to get the results as close as possible to the reality.

Among our strengths there are various non standcard protocols, but also the use of information from the sum (coincident) peaks in order to acknowledge source activity and volume distribution; if the study is based only on the simple gamma peaks, the only information one would get is a large domain of possible positions of the source, without clear activity information. Another important topic is the information on the source homogeneity which is given by the count rates for peaks of different nature.

Our work is mainly experimental; most of the experiments are meant to be performed in the laboratory, as an interdisciplinary approach to nuclear and environmental science. One very important issue to consider in this field is the necessity to adapt to the changing radiation background, no matter the origins of the modifications. Also, the possibility of performing in situ gamma spectrometry is not to be neglected, as it offers multuple benefits, as on the spot analysis, quick tests, feasibility studies, accident dosimetry or simply mapping.

Additionally, we perform neutron activation on the samples, which means we can get the initially non-emitting nuclei to de-excite by gamma radiation: following neutron capture, the activated nuclei disintegrate by a beta process and subsequently emit characteristic gamma radiation, which helps un identify initially "silent" isotopes, bringing precious additional information.

 

Our results obtained experimentally and by Monte Carlo simulations in hypothesis testing of homogeneity properties and/or hot spots in volume sources are now being patented. Also, we seek to develop the quantum correlated gamma spectroscopy field, as it is emerging with new possibilities of treating entangled photons from environmental materials and specimens. Our main purpose for this event is to seek for partnership opportunities accross Europe.

 

How to cite: Suvaila, R.: Gamma spectroscopy for geological studies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4664, https://doi.org/10.5194/egusphere-egu24-4664, 2024.

EGU24-5787 | ECS | Posters on site | NH9.11

From the collective to the individual radon risk exposure: an insight in the current European regulation 

Eleonora Benà, Giancarlo Ciotoli, Peter Bossew, Eric Petermann, Luca Verdi, Claudio Mazzoli, and Raffaele Sassi

Radon (222Rn) is a radioactive gas considered the major source of ionizing radiation exposure for the population and represents a significant health risk when it accumulates indoor environments. In Europe the regulation has been implemented in order to address the issue of indoor radon exposure, including pose national reference levels and the identification of the so-called Radon Priority Areas (RPAs). Although the European directive states that RPAs are defined as those areas where the annual average Indoor Radon Concentrations in a significant number of dwellings is expected to exceed the reference level the concept and interpretation of “significant number of buildings” in the European Directive remained unclear. According to this idea, radon is classified as an anthropogenic hazard since it has a strong correlation with IRC. However, indoor radon levels can vary significantly at the municipal level also among neighbouring dwellings, mostly due to differences in building characteristics and inhabitants’ habits. Since in this way the radon natural origin may be bypassed, many authors (mostly geologists) propose to use the Geogenic Radon Potential (GRP) as a hazard indicator. The GRP represents the amount of radon that can potentially influx within buildings from geogenic sources. Being the radon hazard and risk concepts still debated, in the last year, researchers proposed a clear transition from the radon hazard to the more comprehensive radon risk concept proposing that mapping this geo-hazard (GRP) is a fundamental step to define the collective radon risk exposure. The Collective Risk Areas (CRAs) are composed by many possible little Individual Risk Areas (IRAs). Considering that the radiation protection aimed to reduce the detriment, radon abatement policies have to take care of these CRAs not forgetting areas with high individual risk in order to protect individuals from high exposure. On the one hand the collective risk areas have proposed as geological-based risk areas; on the other hand, the individual risk areas are strictly linked to the Indoor Radon Concentration (IRC) and may be assimilated to the “classical” RPAs concept. Considering the absence of an unambiguous methodology at the European scale to define the RPAs and the proposed CRAs mapping as the first step to define the IRAs (“classical” RPA), with this work we aimed to lay the foundation to create a definitive methodology for the individual risk-based RAPs mapping considering, first of all, the number of people involved. The test area chosen for this study is the Bolzano province (Italy) due to the high availability of potential predictors variables and a detailed IRC survey campaign on the entire provincial territory. Starting from this we proposed the first IRAs map (i.e., the first individual risk-based RPAs definition) using a set of Machine Learning techniques allowing to connect and validate the geo-hazard with real IRC measured in the province, with the aim to predict both the collective risk and the possible individual detriment as required by the European regulation.

How to cite: Benà, E., Ciotoli, G., Bossew, P., Petermann, E., Verdi, L., Mazzoli, C., and Sassi, R.: From the collective to the individual radon risk exposure: an insight in the current European regulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5787, https://doi.org/10.5194/egusphere-egu24-5787, 2024.

Brazil is envisaging a large scale plan for indoor radon assessment. Radon levels shall be mapped and priority areas identified. Given the size of the country and its diversity in natural and socio-economical respects, this is a challenging project. Pilot studies and local surveys have been performed in the past but no country-wide assessment exists.

In November 2023, the IAEA organized a workshop on radon survey planning in Poços de Caldas, Minas Gerais, Brazil, to support the project. The objective was to identify items which have to be resolved before starting the actual experimental, i.e., field and laboratory work; so to speak, asking the right questions beforehand to render work as efficiently as possible. Experts from several scientific disciplines related to radon participated (physics, statistics, geology, geography, radiology, national demographic database management, etc.). Among the questions which result from experiences with past surveys, are:

  • Which is the objective of the survey? (Assessment of radon hazard, of collective risk, of detriment attributable to radon, decision base for mitigation action, etc.)
  • Which is the target quantity? (Mean concentration in living rooms over an area, probability to exceed a reference level within an area, status of an area as priority area, etc.)
  • Which is the mapping support, i.e., the geographical area to which a value of the target quantity shall be assigned? (Municipality, administrative region, geological unit, grid cell, etc.)
  • Which spatial estimation strategy is chosen: design based (inference only from radon measurements) or model based (inference from predictor quantities such as geology or ambient dose rate)?
  • How to generate a representative sampling scheme, and how to verify it?
  • In case of a design based strategy: which sample size is required to achieve a given accuracy of the result? More generally: which information is necessary to establish an uncertainty budget of the target quantity?
  • How should an operational database be structured, which metadata should be included?
  • How should a "cooking recipe" look like, which generation of new data should follow? ("Bottom-up harmonization") How can existing data be integrated into the database ("Top-down harmonisation")?
  • How can experiences gained during pilot and local projects be transferred and "upscaled" to different environments and larger regions?
  • How should a QA/QC scheme look like, appropriate to the project?

These questions, some of which are by no means trivial, should be thoroughly discussed and answered before actually starting a survey. Some of them will be addressed in the presentation.

 

How to cite: Bossew, P. and Da Silva, N.: Designing an indoor radon survey - results of a recent IAEA workshop on survey planning in Brazil, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6182, https://doi.org/10.5194/egusphere-egu24-6182, 2024.

EGU24-7604 | Orals | NH9.11 | Highlight

Long-term atmospheric radon measurements and their connection with environmental conditions 

Sebastian Baumann, Valeria Gruber, Joachim Gräser, and Dietmar Roth

Radon is a radioactive noble gas. Accumulated indoors it is a large source of radiation exposure. Atmospheric radon can be used as a tracer for greenhouse gases and for atmospheric modelling.

We analyzed long-term (> 10 years) time series of atmospheric radon (Rn-222 and Rn-220) at 15 locations in Austria and neighboring countries. The measured concentrations are equilibrium-equivalent concentrations (EEC), where decay products of radon are measured on air filters with a PIPS-detector. Other parameters as ambient dose rate and weather data (wind, rainfall and precipitation) are measured at the same location. Additional for one year the atmospheric radon concentration was measured directly with a different measurement system (Alphaguard) at three locations.

The analysis of the EEC showed that the temporal variation of atmospheric radon (Rn-222, Rn-220) depends on meteorological parameters. Seasonal and diurnal variations are linked to the stability of atmospheric layers. Under stable weather conditions higher radon concentrations occur. Correlation of the radon concentrations were found primarily with temperature and wind speed. At temperatures below 0 °C, Rn-220 shows very low concentrations and a different behavior than Rn-222. This reduction of Rn-220 availability could be associated with frozen or snow-covered soils.

The additional measurements (Alphaguard) of atmospheric radon concentrations provided plausible long-term averages, although individual measurements can provide implausible values (e.g. negative values). The temporal patterns of the two measurement systems are very similar, and the atmospheric radon concentrations are predominantly higher than the EEC.

A connection of the long-term average values of the atmospheric radon and the radon potential of an area was found, by comparing atmospheric radon concentrations with indoor radon measurements and predictions of the radon potential in Austria. This indicates that the radon potential determines the average level of the atmospheric radon concentrations and weather conditions temporally modulate the atmospheric radon concentrations around this level.

This work is supported by the federal ministry of Austria for climate action and the project RadoNORM, which has received funding from the Euratom research and training programme 2019-2020 under grant agreement No 900009.

How to cite: Baumann, S., Gruber, V., Gräser, J., and Roth, D.: Long-term atmospheric radon measurements and their connection with environmental conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7604, https://doi.org/10.5194/egusphere-egu24-7604, 2024.

EGU24-8408 | ECS | Posters on site | NH9.11

Indoor 222-Rn Modeling in Data-Scarce Regions: An Interactive Dashboard Approach for Bogotá, Colombia 

Martín Dominguez Duran, María Angélica Sandoval Garzón, and Carme Huguet

Radon (222Rn) is a naturally occurring gas that represents a health threat due to its causal relationship with lung cancer. Despite its potential health impacts, several regions have not conducted studies, mainly due to data scarcity and/or economic constraints. This study aims to bridge the baseline information gap by building an interactive dashboard that uses inferential statistical methods to estimate indoor radon concentration’s (IRC) spatial distribution for a target area. We demonstrate the functionality of the dashboard by modelling IRC in the city of Bogotá, Colombia, using 30 in situ measurements. IRC measured were the highest reported in the country, with a geometric mean of 91 ±14 Bq/m3 and a maximum concentration of 407 Bq/m3. In 57 % of the residences RC exceeded the WHO's recommendation of 100 Bq/m3. A prediction map for houses registered in Bogotá’s cadastre was built in the dashboard by using a log-linear regression model fitted with the in-situ measurements, together with meteorological, geologic, and building specific variables. The model showed a cross-validation Root Mean Squared Error of 56.5 Bq/m3. Furthermore, the model showed that the age of the house presented a statistically significant positive association with RC. According to the model, IRC measured in houses built before 1980 present a statistically significant increase of 72 % compared to those built after 1980 (p-value = 0.045). The prediction map exhibited higher IRC in older buildings most likely related to cracks in the structure that could enhance gas migration in older houses. This study highlights the importance of expanding 222Rn studies in countries with a lack of baseline values and provides a cost-effective alternative that could help deal with the scarcity of IRC data and get a better understanding of place-specific variables that affect IRC spatial distribution.

How to cite: Dominguez Duran, M., Sandoval Garzón, M. A., and Huguet, C.: Indoor 222-Rn Modeling in Data-Scarce Regions: An Interactive Dashboard Approach for Bogotá, Colombia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8408, https://doi.org/10.5194/egusphere-egu24-8408, 2024.

EGU24-9434 | ECS | Posters on site | NH9.11

A combined approach for the correlation between indoor radon and geological background: application in the western Ligurian Alps (Italy) 

Linda Bonorino, Gianluca Beccaris, Paola Bisi, Paolo Chiozzi, Andrea Cogorno, Elga Filippi, Riccardo Narizzano, Sonja Prandi, and Massimo Verdoya

Radon (222Rn) is one of the most common naturally occurring radioactive elements and is particularly interesting to environmental issues, for it is considered a carcinogenic gas. It is a decay product of 238U, contained in most rocks and soils, and can easily escape from the ground to accumulate in closed spaces where it may become dangerous. The knowledge of its potential is vital to urban development plans and to protect people from potential hazards. We recently conducted monitoring campaigns in Liguria (NW Italy) to investigate the relations between the observed indoor radon concentrations and the geo-lithological background. We focused on the geological units of the Western Alps, characterized by various lithotypes, ranging from sedimentary to metasedimentary and metavolcanic rocks. The natural gamma radiation was measured on outcrops. Spectrometric measurements indicated that metamorphic acid rocks have the highest specific activity values of 238U (75-85 Bq/kg). In metasedimentary rocks, quartz and mica schists show the highest concentration of 238U, with an average specific activity of 56 Bq/kg. Sedimentary rock types are characterized by average specific activities < 40 Bq/kg., The dosimetric indoor surveys highlighted that about 40% of the investigated public and private buildings show indoor radon values above 200 Bq/m3. These preliminary campaigns revealed a relationship between the uranium content of the bedrock and the indoor radon. The correlation can be used to predict the geogenic radon potential based on a geological background when dosimetric data are few or scattered. In this paper, we refined our early analysis by integrating the dataset with further spectrometric and indoor dosimetric records, which were also coupled with soil radon measurements. The radon concentration in soil was investigated focusing on the sites where the previous monitoring campaigns showed high indoor radon concentrations. Soil radon was recorded at depths between 50 and 80 cm, where radon diffusion from the ground to the buildings very likely occurs. Soil radon concentrations substantially agree with spectrometric measurements. The largest concentration of 222Rn was found in the soils on more acid metamorphic rocks (porphyroid and porphyric shists) with values of about 100 kBq/m3. The lowest values about (20 kBq/m3) were recorded in soils occurring in sedimentary rocks. Despite the limitations and uncertainties, mainly related to the uneven data coverage and the complex interaction between the building and the bedrock, the combined techniques can identify areas of potentially high indoor radon concentrations.

How to cite: Bonorino, L., Beccaris, G., Bisi, P., Chiozzi, P., Cogorno, A., Filippi, E., Narizzano, R., Prandi, S., and Verdoya, M.: A combined approach for the correlation between indoor radon and geological background: application in the western Ligurian Alps (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9434, https://doi.org/10.5194/egusphere-egu24-9434, 2024.

EGU24-10152 | ECS | Posters virtual | NH9.11

Exploring the hydrothermal vent field of Milos Island in Aegean Seausing novel radiation instrumentation 

Georgios Siltzovalis, Ioannis Madesis, Varvara Lagaki, Theodoros J. Mertzimekis, Pavlos Krassakis, Stavroula Kazana, and Konstantinos Nikolopoulos

Radioactivity monitoring in the marine environment exhibits various challenges. First and foremost, the water-induced attenuation substantially limits the detection ability and range of the sensors. Additionally, the harshness and remoteness of underwater locations pose significant obstacles to existing technological solutions towards dense and extended radioactivity mapping of the oceans. The highly ambitious EU FET Proactive Research Programme RAMONES (Radioactivity Monitoring in Ocean Ecosystems) is aiming towards overcoming existing limitations by developing and deploying novel underwater radiation-sensing instruments, enabling direct correlation of marine radioactivity with underwater geological and geochemical processes.

The present study will focus on the analysis of experimental data collected during field experiments conducted in the extended hydrothermal vents of Milos, an island located on the south Aegean Sea that is part of the Hellenic Volcanic Arc. The shallow active hydrothermal system of Milos is associated with calc-alkaline volcanic rocks from basaltic andesites to dacites, and rhyolites that have been deposited over several cycles of volcanic activity. Novel portable γ-detectors based on lightweight CdZnTe crystals, were deployed to acquire in situ measurements from coastal locations at the eastern part of the island. Complementary sediment samples were collected to offer baseline NORM (Naturally Occurring Radioactive Material) levels from Milos Island having attracted a lot of attention recently due to its role as a potential geohazards source. These measurements are used to benchmark the γ spectrometers and prepare them for underwater operation aboard autonomous underwater gliders. Collected data will feed a prototype Risk Information System (RIS) titled as POIS2ON (PrOtotype Information System for SOcioecoNomic stakeholders). POIS2ON database will include datasets accompanied by geoinformation to be visualized though NORM levels heat maps, as well as support detailed Monte Carlo simulations to evaluate the radiation doses on local marine ecosystems.

How to cite: Siltzovalis, G., Madesis, I., Lagaki, V., Mertzimekis, T. J., Krassakis, P., Kazana, S., and Nikolopoulos, K.: Exploring the hydrothermal vent field of Milos Island in Aegean Seausing novel radiation instrumentation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10152, https://doi.org/10.5194/egusphere-egu24-10152, 2024.

EGU24-12397 | ECS | Posters on site | NH9.11

Cross-Ventilation Strategies for Efficient Indoor Radon Reduction: Experimental Data and CFD Simulations 

Diana Altendorf, Henning Wienkenjohann, Florian Berger, Jörg Dehnert, Michal Duzynski, Hannes Grünewald, Dmitri Naumov, Ralf Trabitzsch, and Holger Weiß

Naturally occurring radon-222 (Rn) is a widespread indoor air pollutant, posing a potential health risk for humans, particularly elevating the risk of lung cancer in indoor living and working spaces. One highly promising solution for existing buildings, requiring relatively minimal technical effort to reduce indoor radon, is the installation of a ventilation system.

As a proof of concept, a series of different ventilation experiments, utilising a decentralised ventilation system with heat recovery (inVENTer GmbH, Germany) were performed in an unoccupied ground-floor flat in Bad Schlema (Germany).

The flat was divided into three individually controllable ventilation zones using strategically positioned ventilation devices, controlled by a novel real-time measurement system for indoor radon activity concentration [Rn] (Smart Radon Sensors by SARAD GmbH, Germany) in each room. This innovative approach to eliminate indoor radon by employing [Rn] as a control parameter enabled automated switching between different ventilation modes or the option to deactivate the system entirely.

Over three years, the different ventilation experiments successfully reduced elevated indoor radon levels from up to 7000 Bq/m³ to 300 Bq/m³ and below. The effectiveness varied based on factors such as the initial room-specific radon levels before each experiment, the performance level of the fans and meteorological parameters.

Furthermore, we developed a true-to-scale three-dimensional Computational Fluid Dynamics (CFD) model based on the actual flat, enabling the quantitative interpretation of various ventilation experiments within a CFD environment. The CFD model utilised a stationary k-ε turbulent flow model to simulate ventilation-induced airflow inside the flat and was coupled with a transient transport model for radon simulation.

For the development of the CFD model, the "Cross-Ventilation" experiment was chosen. This experiment successfully achieved a room-specific reduction of indoor radon levels from approximately 3,000 Bq/m³ to about 300 Bq/m³. To precisely capture the impact of ventilation on indoor radon, the initial radon values for each room were utilised as initial conditions for the transient radon transport model.

Base case results showed an overestimation by the model in radon level reduction due to ventilation. Parameter adjustments of the inflowing radon and the airflow velocity at the inlet resulted in good agreement between experimental values and the CFD model's outcome.

In summary, this study highlights CFD modeling as a versatile tool for evaluating and optimising ventilation systems, offering valuable insights into the mechanism of managing the air quality in complex real-world indoor environments with elevated radon levels.

How to cite: Altendorf, D., Wienkenjohann, H., Berger, F., Dehnert, J., Duzynski, M., Grünewald, H., Naumov, D., Trabitzsch, R., and Weiß, H.: Cross-Ventilation Strategies for Efficient Indoor Radon Reduction: Experimental Data and CFD Simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12397, https://doi.org/10.5194/egusphere-egu24-12397, 2024.

EGU24-12506 | ECS | Orals | NH9.11

Rapid field measurement of uranium in water samples  

Katalin Hegedűs-Csondor, Heinz Surbeck, Petra Baják, and Judit Mádl-Szőnyi

We present an analytical method that allows for the rapid measurement of uranium in water samples. For a 50 ml sample concentrations down to about 2 micro-g/l can be measured within an hour. There are no toxic chemicals used and the whole equipment is portable and can be powered by a 12 V battery. The preparation consists of adding 200 mg silica gel to the 50 ml sample, stirring for 1 hour, filtering out the silica gel and transferring it to a semi-micro cuvette for the measurement. Several samples can be prepared in parallel, depening on the number of magnetic stirrers available. The measurement takes only 1 minute and uses the uranyl fluorescence, enhanced by the adsorption on silica gel. Excitation is done by a pulsed UV-LED at 285 nm. The delayed fluorescence signal around 520 nm is detected by a 6 mm x 6 mm Silicon Photomultiplie (SiPM) behind a 520 nm bandpass filter. Pulsing the LED, converting the SiPM output and displaying the result is controlled by an Arduino microprocessor. All details of the experimental setup as well the software code are presented. It's open source, open to be copied and the whole material costs are only around 500 Euro.

How to cite: Hegedűs-Csondor, K., Surbeck, H., Baják, P., and Mádl-Szőnyi, J.: Rapid field measurement of uranium in water samples , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12506, https://doi.org/10.5194/egusphere-egu24-12506, 2024.

EGU24-12663 | ECS | Posters on site | NH9.11

Preliminary results of two-dimensional multicomponent reactive transport modelling to understand the controlling factors on uranium mobility in a siliciclastic aquifer in Hungary 

Petra Baják, Daniele Pedretti, András Csepregi, Muhammad Muniruzzaman, Katalin Hegedűs-Csondor, and Anita Erőss

In Hungary, the drinking water supply relies upon groundwater resources of up to 98%. As a drinking water resource, groundwater must meet strict quality requirements in order to minimise any health effects arising from daily water consumption. Water-rock interactions enrich groundwater not only with essential elements (e.g. Ca, Mg) but also with undesired substances such as heavy metals or radioactive elements. In the last few years, a thorough drinking water quality monitoring campaign was carried out in Hungary, revealing that some parts of the country are characterised by relatively high uranium concentrations. The causes of these elevated activities have not been properly investigated, yet. However, understanding the controls of the release and mobility of uranium is critical in proper groundwater management.

Baják et al (2022) developed a one-dimensional (1-D) geochemical model using the code PHREEQC (Parkhurst and Appelo, 2013) to examine the processes that determine the fate of uranium in the siliciclastic Miocene-Quaternary aquifer system near Velence Hills, some 50 km off Budapest. Here, the geological build-up (granitic rocks on the surface) favours the high uranium content in groundwater, which is characterised by oxidising conditions. The 1-D model included redox-controlled kinetic reactions as well as other potential uranium-controlling processes (e.g., surface complexation). The results suggested that uranium distribution is sensitive to redox changes in the aquifer and its mobility in groundwater especially depends on the residence time of water compared to the reaction times controlling the consumption of oxidising species.

This study introduces a two-dimensional multicomponent reactive transport model developed using the PHT3D code (Prommer et al., 2003), which is a coupling between MODFLOW and PHREEQC. The model builds on and extends the capability of the 1-D model to simulate uranium mobility across the multiple flow paths of the aquifer systems. The model calibration accounts for 30 groundwater samples collected from drinking water wells in the study area. Physico-chemical parameters (temperature, pH, specific electric conductivity, redox potential) were measured on-site, and the samples were analysed for natural tracers (δ16O, δ2H, 234U, 238U, 226Ra) to gain further insight into the geochemical processes of the aquifer system.

This research was supported by the ÚNKP-23-4 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund and was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences. The research is part of a project which was funded by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014.

References:

Baják, P., Csondor, K., Pedretti, D., Muniruzzaman, M., Surbeck, H., Izsák, B., Vargha, M., Horváth, Á., Pándics, T., Erőss, A., 2022. Refining the conceptual model for radionuclide mobility in groundwater in the vicinity of a Hungarian granitic complex using geochemical modeling. Applied Geochemistry 137, 105201.

Parkhurst, D.L., Appelo, C.A.J., 2013. Description of Input and Examples for PHREEQC Version 3—A Computer Program for Speciation, Batch-Reaction, One-Dimensional Transport, and Inverse Geochemical Calculations. (USGS Technical No. 6(A)43). U.S. Geological Survey, Denver, CO, USA.

Prommer H, Barry, D.A., Zheng, C. (2003). MODFLOW/MT3DMS based reactive multi-component transport modeling. Ground Water, 41(2).

How to cite: Baják, P., Pedretti, D., Csepregi, A., Muniruzzaman, M., Hegedűs-Csondor, K., and Erőss, A.: Preliminary results of two-dimensional multicomponent reactive transport modelling to understand the controlling factors on uranium mobility in a siliciclastic aquifer in Hungary, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12663, https://doi.org/10.5194/egusphere-egu24-12663, 2024.

Understanding the temporal and spatial distribution of soil water content (SWC) is critical for efficient water resource management in agriculture. However, the variability of SWC over time and space presents challenges in obtaining accurate values at field scale using conventional methods. Proximal gamma-ray spectroscopy (PGRS), supported by adequate calibration and biomass corrections, emerge as promising methods for monitoring SWC. The inverse correlation between the gamma counts of the radioisotope 40K (1461 KeV) and volumetric SWC (m3/m3) demonstrates potential for reliable soil moisture estimation in agricultural and hydrological applications. This contribution examines the potential application of a portable sodium iodide (NaI) scintillation detector (PGRS) for estimating SWC in an irrigated wheat field. We explore the sensitivity of the 40K variations to changes in soil moisture and detector height. Over the last two months of the growing season, several one-hour manual monitoring surveys were conducted to capture the effect on 40K signal of irrigation and soil moisture status before and after the harvesting. In each survey, total counts of 40K were recorded using a NaI detector positioned at different elevations above the ground in the middle of a wheat field. Preliminary results indicate a general correlation between 40K (cps) and SWC throughout the study period, suggesting the sensitivity of the PGRS detector to SWC variations. Our findings show a slight increase in 40K counts by decreasing the detector height for all the field surveys conducted. In addition, we observed that the lowest counts of 40K were recorded during the survey with the highest soil water content after irrigation. We can conclude that 40K signal is sensitive to both changes in SWC and the height position of the detector. Furthermore, this detector offers a significant advantage, as it not only captures data on the 40K peak but also analyses the full gamma spectrum.

How to cite: Catalá, A., Navas, A., and Gaspar, L.: Assessing the variability of 40K measurements using a portable gamma-ray spectroscopy in an irrigated agricultural field (Spain), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12700, https://doi.org/10.5194/egusphere-egu24-12700, 2024.

EGU24-15380 | Posters virtual | NH9.11

Application of machine learning methods to improve the radon deficit technique 

David Lorenzo, Fernando Barrio-Parra, Humberto Serrano-García, Miguel Izquierdo-Díaz, and Eduardo De Miguel

The Radon deficit technique is a promising screening method for identifying and mapping potential subsurface organic pollution hotspots and thus, for the optimization of intrusive characterization campaigns. Radon (222Rn) a naturally procuded radionucleid and particularly suitable for use as a natural tracer due to its preferential partitioning with non aqueos phase liquids (NAPLs) and and ease of in situ analytical detection (Kram et al., 2001). The ability of the 222Rn technique to locate organic pollution hotspots and provide a semiquantitative analysis has been widely assessed in sites affected by NAPLs (De Miguel et al., 2018, De Miguel et al. 2020). However, the Radon measurement is affected by several confounding factors, such as variations in soil water saturation and ground-level temperature. Machine learning can be used to study and model these confounding factors and improve the interpretation of in situ radon analytical information.

Machine learning is a class of statistical techniques that have proven to be a powerful tool for modelling the behaviour of complex systems in which response quantities depend on assumed controls or predictors in a complicated way (Janik, 2018). The first purpose of this work is the application of machine learning to analyse sampled data of time series outdoor 222Rn. The algorithms "learn" from complete sections of multivariate series (containing measurements of soil water content, soil temperature and meteorological information), derive a dependence model. The model trained in this work can be used to improve the accuracy and reliability of the radon deficit technique, making it a more valuable tool for identifying and mapping subsurface contamination.

 

De Miguel, E., Barrio-Parra, F., Elío, J., Izquierdo-Díaz, M., Jerónimo, García-González, E., Mazadiego, L.F., Medina, R., 2018. Applicability of radon emanometry in lithologically discontinuous sites contaminated by organic chemicals. Environ. Sci. Pollut. Res. 25, 20255–20263. https://doi.org/10.1007/s11356-018-2372-9

De Miguel, E., Barrio-Parra, F., Izquierdo-díaz, M., Fernández, J., García-gonzález, J.E., 2020. Applicability and limitations of the radon-deficit technique for the preliminary assessment of sites contaminated with complex mixtures of organic chemicals: a blind field-test. Environ. Int. 138, 105591. https://doi.org/10.1016/j.envint.2020. 105591.

Janik, P. Bossew, O. Kurihara, 2018,Machine learning methods as a tool to analyse incomplete or irregularly sampled radon time series data, Scie. Tot. Environ.,630, 1155-1167, https://doi.org/10.1016/j.scitotenv.2018.02.233.

Schubert, M., 2015. Using radon as environmental tracer for the assessment of subsurface non-aqueous phase liquid (NAPL) contamination – a review. Eur. Phys. J. Spec. Top. 224, 717–730. https://doi.org/10.1140/epjst/e2015-02402-3.

How to cite: Lorenzo, D., Barrio-Parra, F., Serrano-García, H., Izquierdo-Díaz, M., and De Miguel, E.: Application of machine learning methods to improve the radon deficit technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15380, https://doi.org/10.5194/egusphere-egu24-15380, 2024.

EGU24-16925 | ECS | Posters on site | NH9.11

Deciphering Radon Variability in the Northern Upper Rhine Graben: An Analysis Using Passive and Active Detection with Random Forest Modelling 

Johannes Mair, Eric Petermann, Rouwen Lehné, and Andreas Henk

This study, conducted about 30km south of Frankfurt in the Northern Upper Rhine Graben, focuses on deepening the understanding of Radon concentrations in soil air. The selected area, where neotectonic activity was proven in an accompanying project, provides an ideal setting for investigating Radon variability, particularly its potential correlation with fault zones in unconsolidated rocks or sedimentary basins. Understanding the factors influencing Radon levels in the environment is a complex task, as they are affected by a multitude of variables. Our work aims to decipher these influences and, if possible, quantitatively analyse the contributions of each variable. By doing so, we hope to gain a clearer understanding of how different environmental factors interact to determine Radon levels.

A central element of our research is the use of Random Forest models, chosen to handle our multidimensional dataset. This dataset includes a variety of parameters such as Radon measurements, nuclide content, soil grain sizes, weather data, and the distance to fault zones. Random Forest models are particularly effective for this type of complex data because they can analyse many different factors at once and uncover hidden patterns.

Contrary to initial hypotheses, our findings indicate that in unconsolidated rocks and sedimentary basins, the grain size of soil is the most influential factor in determining soil air Radon levels, closely followed by soil moisture. These results challenge the previously held belief that fault zones are the primary influencing factors on Radon concentrations in these geological settings.

How to cite: Mair, J., Petermann, E., Lehné, R., and Henk, A.: Deciphering Radon Variability in the Northern Upper Rhine Graben: An Analysis Using Passive and Active Detection with Random Forest Modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16925, https://doi.org/10.5194/egusphere-egu24-16925, 2024.

EGU24-17300 | ECS | Posters on site | NH9.11 | Highlight

Investigating the sensitivity of flux maps in simulating radon concentrations at greenhouse gas monitoring sites 

Adam Howes, Dafina Kikaj, Edward Chung, Ute Karstens, Alistair Manning, Stephan Henne, Angelina Wenger, Grant Foster, Simon O'Doherty, Chris Rennick, and Tim Arnold

Given its unique properties as a radioactive chemically inert gas, radon can act as a valuable atmospheric tracer, for evaluating the performance of atmospheric transport models to calculate the sources of trace gases to the atmosphere. A radon flux map is the scientific starting point for simulating atmospheric radon concentrations using atmospheric transport models. As such, it is important to assess the available high resolution radon flux maps to ensure that simulated concentrations can be accurately interpreted. The spatial fluxes of radon primarily depend on soil and rock types, while temporal variations are influenced by soil moisture content.

The recent advancements in generating two high-resolution radon flux maps for Europe using two different soil moisture reanalysis, GLDAS Noah and the ERA5 maps1, have significantly enhanced our understanding of radon flux dynamics. Yet, the radon flux values diverge notably between these two maps and sometimes these variations can be substantial, with differences as large as the absolute radon flux itself.

In our work, two available versions of European radon flux maps are coupled with two Lagranian particle dispersion models – the Met Office’s Numerical Atmospheric Modelling Environment (NAME) and the FLEXPART model – are used to simulate radon concentrations measured at four tall tower sites in the United Kingdom: Heathfield, Ridge Hill, Tacolneston and Weybourne. We calculate the differences between the modelled radon concentrations to the observed radon concentrations at these sites and use this to investigate the sensitivity of two radon flux maps: GLDAS Noah and ERA5.

 

References: 12022: https://doi.org/10.18160/2ST9-3NAD

How to cite: Howes, A., Kikaj, D., Chung, E., Karstens, U., Manning, A., Henne, S., Wenger, A., Foster, G., O'Doherty, S., Rennick, C., and Arnold, T.: Investigating the sensitivity of flux maps in simulating radon concentrations at greenhouse gas monitoring sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17300, https://doi.org/10.5194/egusphere-egu24-17300, 2024.

EGU24-17369 | Posters on site | NH9.11 | Highlight

INGV experience on radon monitoring in the Ciampino Municipality (Rome, Italy): a link between research and territory 

Alessandra Sciarra, Luca Pizzino, Gianfranco Galli, Daniele Cinti, Giancarlo Ciotoli, and Sabina Bigi

Ciampino area has been the subject, from 1999 onwards, to reiterated geochemical surveys on soil-gas, spring waters and groundwater, commissioned by the municipality to INGV (National Institute of Geophysics and Volcanology). Indeed, this area is affected by huge CO2 emissions of volcanic origin and high levels of indoor radon. Both gases can constitute a big concern for local population known as Natural Gas Hazard (NGH). Accordingly, the distribution of the two gases in groundwater, soils and indoor buildings must be assessed in order to define sectors of the territory more exposed to NGH.
Interest in the Natural Gas Hazard arose mainly starting from November 1995, when several homes, basements and wells were affected by widespread exhalations, to the point of danger to human health.
The most area affected is characterized by abundant and concentrated gas leaks which caused the death of 29 cattle and some sheep in September 1999 and March 2000, until December 2000 when a paroxysmal episode caused the death of a man.
The main activities carried out in the last 25 years have concerned:
-    sampling of water sites (about 100 natural springs, public and private wells), measuring chemical-physical parameters, CO2 and 222Rn contents;
-    monthly indoor radon measurements (around 500/year) in 14 selected sites (both private homes and workplaces, including schools);
-    measurements of radon in soils (about 300) to identify the areas with the greatest degassing and the possible relationship with existing tectonic structures;
-    continuous indoor radon measurements in a selected home;
-    spot measurements in groundwater and intervention in the event of reports from the municipality and/or private citizens of emergency situations resulting from gaseous emanations falling in areas of the municipal territory of Ciampino.
The data obtained include measurements of flux and concentration of soil gases, distribution of pCO2 and radon in groundwater, radionuclide content in soils from different geological units, indoor radon measurements.
All this data has allowed us to define the sectors at greatest risk, by identification and delimitation of NGH risk areas. Dissemination and information activities on the NGH were carried out through public meetings, seminars and the drafting of brochures. Also training activities for the staff of the Civil Protection and Environment Offices of the Municipality were performed.
The experience gained has allowed the participation of INGV in a European project Life Respire for the monitoring and remediation of the radon problem.
Based on the distribution of the different samples collected: soil gas, terrestrial gamma dose rate and rock/soil samples by radionuclide content, we were able to provide the local authorities the map of the geogenic potential of radon for the whole municipal territory.

How to cite: Sciarra, A., Pizzino, L., Galli, G., Cinti, D., Ciotoli, G., and Bigi, S.: INGV experience on radon monitoring in the Ciampino Municipality (Rome, Italy): a link between research and territory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17369, https://doi.org/10.5194/egusphere-egu24-17369, 2024.

Fumaroles spread out several elements to the atmosphere and may include radon that contributes to environmental radioactivity. The long-lasting vigorous gaseous emissions of the Campi Flegrei volcanic caldera, i.e., Solfatara and Pisciarelli, occur in densely inhabited areas of Naples where the population may be exposed to ionizing radiation from 222-radon. In 2021, we started a study on radon levels from the Solfatara and Pisciarelli fumaroles by using the RAD7 commercial detector, one of the most widely used instruments for measuring 222Rn, either dissolved in water or in soil gas. However, the local high H2S levels and hot temperatures did not allow direct measurements of Rn, resulting in the instrumentation (RAD7) damage. Thus, we developed a proper technique for sampling and measuring radon gas from fumarolic gases in such a “critical” areas to overcome the instrumental issue.

At fumarole sites i.e., Bocca Nuova and Bocca Grande within the Solfatara crater, and Pisciarelli, the gas was periodically sampled in Tedlar® bag of 1 or 3 liters in order to have the possibility to repeat the measurements two or three times to verify the accuracy of the data.

In laboratory, at first, H2S traps were prepared by filling silicone tubes with lead acetate powder, bordered, at both ends, by hydrophilic cotton and closed. Then the fumarole gas was transferred from the Tedlar® bag into a glass tube. Finally, radon gas was measured via a closed loop by using the RAD7. Rn printouts obtained from RAD7 were corrected for the time lag between sampling and measurement. RAD7 and charcoal canister measurements were compared to check the obtained results.

Preliminary results, published in Iovine et al. (2023), demonstrate that the methodology utilized enables the analysis of Rn concentrations even in H2S-bearing gases, discharged from the fumaroles of the Campi Flegrei volcano and, most importantly, without instrumental issues. Fumaroles sampled and analyzed over time according to the methodology adopted, may be suitable for environmental radioactivity assessment and volcanic monitoring purposes as well.

 

Iovine RS, Avino R, Minopoli C, Cuoco E, Caliro S, Galli G, Piochi M. (2023). A procedure to use the RAD7 detector for measuring 222Rn in soil gases exceeding instrumental limits: an application to chemically aggressive fumaroles of the Campi Flegrei area. Rapp. Tec. INGV, 473: 1­18, https://doi.org/10.13127/rpt/473.

How to cite: Iovine, R. S., Minopoli, C., Avino, R., Caliro, S., Galli, G., and Piochi, M.: Determination of 222Radon (222Rn) from the hot and acidic fumaroles gases to the atmosphere of the highly populated Campi Flegrei caldera (Naples, Southern Italy) by using a RAD7 detector: a procedure overcoming instrumental limits, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17908, https://doi.org/10.5194/egusphere-egu24-17908, 2024.

EGU24-18058 | ECS | Orals | NH9.11

Studies on radon time series in various underground environments: Case of abandoned Kővágószőlős uranium mine 

Tóth Szabolcs, Horváth Ákos, and Sajó-Bohus László

Field uranium research began in Hungary in 1947 under the guidance of Hungarian specialists. After the research period, mining plants were opened one after the other, and an ore processing plant was also established. The ore grade found in the Mecsek Mountains was less favorable than average, 1 ton of ore contained 1.2 kg of uranium metal. The characteristic of the uranium ore found in the permian sandstones is that it occurs in several layers and levels, not continuously, but in lenticular spots with varied development. This geological occurence significantly increased the costs. By 1989, Hungarian uranium ore mining had become uneconomical, and a government decision was made to close it down, dating back to 1997. The recultivation process began in 1998. Currently, environmental damage is being eliminated under the title of long-term monitoring. Due to the proximity of inhabited areas, NORM anomalies, and the presence of radon gas, radiation protection played a particularly important role during and after remediation.

The radon monitoring of the abandoned mine cavity system was carried out with active radon monitors placed in different boreholes, closed shafts and adits. In the last two years, a radon soil gas monitoring station has also been operated on a waste rock pile site covered with 1 m of loess cover to check the radon retention capacity of the soil.

For radon detection alpha-sensitive photodiode (sensitive area: 1 cm2) or PIPS detector (sensitive area: 3 cm2) are used. The Dataqua monitoring system gives one impulse per hour for 140 and 56 Bq/m3222Rn concentration, respectively, for the photodiode and PIPS detector. The multi-channel devices beside the radon detector can include other additional sensors for temperature, pressure, humidity, water level, salinity, etc. measurements to study the relation between the variation of radon concentration and other environmental parameters. The radon concentration together with other environmental parameters are continuously recorded with one measurement per hour sampling frequency for several years.

In closed, underground places extremely high radon concentration (a couple of tens up to hundred kBq/m3, may occur in the absence of ventilation, even in rocks of average radionuclide content. According to our measurements both the daily and the yearly variation is well recognizable, which originate from the variation of the meteorological and lunisolar parameters. In the case of a few time series, we revealed a strong correlation between the outside temperature and the resulting radon concentrations.  We found the atmospheric pressure also affects radon levels, but extent and only on a smaller scale than temperature. 

Comprehensive statistics and Fourier analysis were also carried out in order to examine the dominant frequencies, and we also examined the change of the one day long components as a function of time.

How to cite: Szabolcs, T., Ákos, H., and László, S.-B.: Studies on radon time series in various underground environments: Case of abandoned Kővágószőlős uranium mine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18058, https://doi.org/10.5194/egusphere-egu24-18058, 2024.

EGU24-19068 | ECS | Orals | NH9.11

Long-term Evaluation of HPGe Calibration for Environmental Radioactivity Assessment Using IAEA-U and IAEA-Th Sources 

Debora Siqueira Nascimento, Riccardo Ciolini, Andrea Chierici, Stefano Chiappini, Francesco d'Errico, and Massimo Chiappini

The investigation of the dynamics between environmental radioactivity and its implications for human health stands as a fundamental pursuit in contemporary scientific research. Employing the Gamma Spectrometry technique, particularly utilizing High Purity Germanium (HPGe) detectors, emerges as a pivotal methodology to study environmental radioactivity with precision. The veracity and dependability of these analyses hinge upon the scrupulous and precise energy and efficiency calibration of the HPGe system. Within this framework,  we used calibrated IAEA-U and IAEA-Th sources, thereby not only ensuring measurement accuracy but also establishing a robust foundation for comprehensive evaluation of radioactivity levels. Our findings illuminate a comprehensive understanding of the energy and efficiency calibration of the HPGe detector, exemplified by linear relationships in the energy calibration curves for both IAEA-U and IAEA-Th sources, manifesting high correlation coefficients (R² > 0.99). Essential for translating count rates to activity, the efficiency calibration consistently yielded low errors, with the maximum observed efficiency error being less than 4% for both sources, significantly below the recommended by standard rules. This study affirms the reliability and stability of our calibration methods through repeatability assessments over four years. Looking forward, the calibrated HPGe systems are prepared to assume a central role in the spectral analysis of different Italian terrains. Application of these calibrated detectors to Italian soil aims to discern and quantify the presence of radionuclides, thereby contributing into the radioprotection of the region. This prospective dimension underscores the practical application and broader implications of our calibrated systems in addressing environmental and health-related concerns.

How to cite: Siqueira Nascimento, D., Ciolini, R., Chierici, A., Chiappini, S., d'Errico, F., and Chiappini, M.: Long-term Evaluation of HPGe Calibration for Environmental Radioactivity Assessment Using IAEA-U and IAEA-Th Sources, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19068, https://doi.org/10.5194/egusphere-egu24-19068, 2024.

EGU24-19881 | Posters on site | NH9.11

Multi-level continuous monitoring of residential radon in the urban contest of Rome 

gaia soldati, maria grazia ciaccio, antonio piersanti, Valentina cannelli, and gianfranco galli

The urbanized area of Rome is largely built over volcanic deposits, characterized by  a significant radionuclides content and radon emanation potential.  A first step towards the mitigation of the indoor radon exposure is the accurate monitoring of workplaces and residential dwellings. Due to the complex interactions among many environmental parameters on different time scales, a proper assessment of radon diffusion dynamics and concentration variations can be better achieved by means of active monitoring approaches. We present here the results of one year of continuous measurements conducted in 6 premises (5 apartments and a basement) at different floors of the same building in the Esquilino district, in the historical center of Rome. The simultaneous tracking of different floors should cancel the influence of geogenic radon and of building characteristics like age, typology, and construction materials, and reveal the characteristics of the gas emanation and transport inside the buildings, and of its temporal fluctuations, with the final goal to select the most suitable preventive measures to reduce radon exposure. Conducting the experiment in the Roman urban contest, we cannot ignore the specificity of the retrieved data, affected not only by endogenous factors like heating and ventilation of the apartments, but also by exogenous factors like the urban heat islands effect.

How to cite: soldati, G., ciaccio, M. G., piersanti, A., cannelli, V., and galli, G.: Multi-level continuous monitoring of residential radon in the urban contest of Rome, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19881, https://doi.org/10.5194/egusphere-egu24-19881, 2024.

EGU24-20104 | Orals | NH9.11 | Highlight

Assessing the chemical availability and environmental fate of fallout radionuclides in cryoconite 

Caroline Clason, Harriet Davidson, Geoffrey Millward, Andrew Fisher, and Alex Taylor

Glaciers are stores for contaminants, both local and further afield in origin, that are released into the environment through anthropogenic processes. Cryoconite, a heterogenous granular material commonly found on glacier surfaces, is now known to be an efficient accumulator of contaminants such as fallout radionuclides (FRNs) and potentially toxic elements, with multiple regional studies reporting notable concentrations of radioactivity in cryoconite that far exceeds that which is found in other environmental matrices. Indeed, concentrations of FRNs in cryoconite can be as much as three orders of magnitude higher than those found in nearby proglacial sediments. While we now understand that this ‘hyper-accumulation’ of FRNs is commonplace on glaciers around the world, our understanding of the extent to which release of contaminants stored in cryoconite poses an environmental downstream risk is in its infancy. To assess both the activity concentrations and chemical availability of FRNs within cryoconite, we conducted novel sequential chemical extractions twinned with gamma spectrometry for cryoconite samples from glaciers in Arctic Sweden and Iceland. Major and minor elemental composition of cryoconite was also analysed with Wavelength Dispersive X-ray Fluorescence (WD-XRF) spectrometry. The results of these experiments demonstrate that different cryoconite-bound FRNs undergo varying degrees of solubilization, with consequences for increased contaminant mobilization under higher melt scenarios. Our work identifies a clear requirement for further research in this field in order to improve understanding of downstream environmental risk from the secondary release of legacy contaminants under continued glacier retreat.

How to cite: Clason, C., Davidson, H., Millward, G., Fisher, A., and Taylor, A.: Assessing the chemical availability and environmental fate of fallout radionuclides in cryoconite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20104, https://doi.org/10.5194/egusphere-egu24-20104, 2024.

EGU24-21822 | Orals | NH9.11

Observation and geological interpretation of the longest vertical radon profile to date: variability of radon concentrations along a 323 m deep drilling 

Rouwen Lehne, Jessica Daum, Johannes Mair, Heiner Heggemann, Christian Hoselmann, and Andreas Henk

Radon soil air measurements and associated permeability measurements are a mandatory prerequisite for the calculation of radon potentials as an important basis for the statistical derivation of an expected radon situation in a defined area. Accordingly, in the federal state of Hesse, as almost everywhere in Germany, numerous measurements have been carried out in recent years and made available to the Federal Office for Radiation Protection (BfS) for the modelling of a radon potential map of Germany, which has since been an important (sometimes the only) basis for the definition of radon precautionary areas for all federal states in Germany. The associated benefits are undoubtedly great.

From a geological perspective, however, the question arises to what extent the large lateral variability of measurable radon concentrations also exists in the vertical and, if so, whether this variability can be placed in a context with the geological development of the area under consideration. The background to this is the fact that the radon soil gas measurements usually address a depth of between 0.8 and 1 m below the ground surface, in rare cases reaching a depth of up to 2 metres.

In addition to the scientific added value, such an investigation approach is also associated with an applied benefit, as building foundations are usually founded significantly deeper than 1 m below the ground surface, which means that a significant part of the building envelope in contact not only with the soil layers, but also to the geological subsurface, must be seen decoupled from the radon concentration determined near the surface, depending on the heterogeneity of the geological bedding.

For this reason, we took a total of 175 samples along an 323 m deep research drilling in the northern Upper Rhine Graben and determined the radon concentration for these in the laboratory (= stationary). The results show a very high variability of the measurable radon concentrations, ranging from 16 Bq/m³ to 9086 Bq/m³ with a mean value of approx. 1527 Bq/m³. At the same time, the radon concentrations determined show a very good correlation with both the geological response of the drill core and the gamma log measurements carried out.

In this presentation, we would like to show the results obtained so far and look at the possibility of regionalising the measured values as well as the next work steps.

How to cite: Lehne, R., Daum, J., Mair, J., Heggemann, H., Hoselmann, C., and Henk, A.: Observation and geological interpretation of the longest vertical radon profile to date: variability of radon concentrations along a 323 m deep drilling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21822, https://doi.org/10.5194/egusphere-egu24-21822, 2024.

EGU24-2012 | ECS | Posters on site | NH9.15

Tsunami Impacts Scenarios for the Albanian Coasts: Durres City case study 

Edlira Xhafaj, Chiara Scaini, Antonella Peresan, and Hany M. Hassan

The ultimate aims of this study is to assess the risk associated with plausible earthquake generated tsunamis along the coasts of Albania, adopting a case study approach based on the modelling of tsunamigenic earthquake scenarios based on the maximum moment magnitude (Mmax) reported in DISS-3.3 joint with the 2019 Mw6.4 Durres earthquake source models. In order to assess the expected impact, we computed the tsunami hazard in terms of maximum amplitude, estimated time of arrivals and inundation zone on the Albanian coast for a set of tsunamis resulting from potential earthquakes generated by the major identified seismogenic sources (namely, Lushnje source from DISS-3.3 database) in the eastern Adriatic Sea. Our approach combines current available information on regional tectonics, recent earthquake swarms in 2019 in scenario-based approach to contribute to tsunami risk assessment for the selected urban area along the Albanian Adriatic coast. The goal is to analyse the propagation of tsunami waves generated by the source set of scenarios, which is potentially able to generate an aggregated scenario of Mmax 7.5, that could cause significant impacts in the region. The modelling are performed by NAMI DANCE numerical code (e.g., Dogan et al., 2021, Natural Hazards, 106(2), 1195–1221; and references therein). For the exposure analysis concerning buildings, landuse and infrastructure, a Geographic Information System (GIS) formatted database is created for the Durres municipality. The Durres exposure analysis in terms of population and built environment were presented in the form of maps, and provide insights for future evacuation plans. Approximately 63% of the buildings consist of single-storey structures, and the number of exposed buildings strongly increased during the period 2000 to 2010. Understanding the composition and construction timelines of the buildings is crucial in assessing their vulnerability and potential impact associated to the simulated tsunamis scenarios. Regarding human impact, the exposure analysis indicates vulnerability in residential, commercial, and public service areas. In Durres city only, the expected population by 2036, estimated at 138,000 inhabitants according to the National Agency of Territorial Planning (AKTP, 2022), will be located in vulnerable urban areas. The results highlight the significant vulnerability of the most important sectors in Durres to possible tsunamis and the need for a rigorous urban planning and enforcement to mitigate future seismic related hazards. This study provides the first extensive examination of urban-scale tsunami risk assessment for cities along the Albanian coastline, highlighting the paramount role of exposure and vulnerability assessment to increase preparedness and inform resilient urban planning.

How to cite: Xhafaj, E., Scaini, C., Peresan, A., and Hassan, H. M.: Tsunami Impacts Scenarios for the Albanian Coasts: Durres City case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2012, https://doi.org/10.5194/egusphere-egu24-2012, 2024.

EGU24-2108 | ECS | Posters on site | NH9.15

How are households contributing to flood risk management? Empirical evidence from a highly flood-prone urban region in Central Vietnam 

Dominic Sett, Lena C. Grobusch, Ulrike Schinkel, Chau Le Dang Bao, Chau Nguyen Dang Giang, Linh Nguyen Hoang Khanh, Matthias Garschagen, and Michael Hagenlocher

Flood risks are exacerbating around the globe, often exceeding capacities to adapt, thus leaving people at risk and raising critical questions on how adaptation gaps can be overcome. In response to observed flood protection gaps, a behavioural turn in flood risk management is observed (Kuhlicke et al. 2020). This turn is characterised by an increased motivation of households to engage in individual flood protection on the one hand and institutionally shifted responsibilities from public authorities towards individuals on the other. This however evokes critical social, political, and ethical questions on the role and contribution of households (and other actors) in risk management. Therefore, our research aims to explore how contributions to flood risk management are divided between households, different levels of government, and other actors on paper vs. in practice, by highlighting key empirical research findings from the case study of Hue, a flood-prone urban region in Central Vietnam. Methodologically, the study draws upon a qualitative content analysis of national and provincial legal flood risk governance documents and statistical analyses of household survey results (n=606) from March and April 2023. Conceptually, the research draws on social contract theory (Blackburn & Pelling 2018) to reveal differences between the legal-institutional, perceived, and practised social contracts for flood risk management, including underlying drivers for observed disparities.

On paper, public authorities at different levels of government (from national to local) are legally assigned a primary role in flood risk management, particularly when it comes to financing, preparedness, and response. At the same time, 60% of surveyed households perceive themselves as being the most responsible actor for flood risk management. Hence, households attribute a significantly higher level of responsibility for engaging in flood risk adaptation to themselves as opposed to local and national government authorities, civil society, foreign aid actors, and the private sector. In practice, a significant share of households (89%) has engaged in diverse temporary preparedness and response actions during past flooding incidents, such as placing sandbags in front of the house. However, only few households (16%) have engaged in permanent actions such as elevating the house floor, and only 5% have implemented these actions proactively, highlighting a significant gap for adaptive actions compared to coping interventions. The assessment of underlying drivers of perceived and practised social contracts revealed that amongst other factors, income and risk perception particularly shape perceived responsibility to act, while past experiences and coping appraisal shape people’s motivation to act. The presentation concludes with context-specific policy recommendations and avenues for future research that can contribute to closing flood risk management gaps. All-in-all, the presentation thus provides novel insights for navigating complex questions around flood risk management contribution divisions between different stakeholders, and more specifically understanding and optimising household engagement in flood risk governance practice in Hue and other cities facing similar challenges.

How to cite: Sett, D., Grobusch, L. C., Schinkel, U., Le Dang Bao, C., Nguyen Dang Giang, C., Nguyen Hoang Khanh, L., Garschagen, M., and Hagenlocher, M.: How are households contributing to flood risk management? Empirical evidence from a highly flood-prone urban region in Central Vietnam, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2108, https://doi.org/10.5194/egusphere-egu24-2108, 2024.

EGU24-2451 | ECS | Posters on site | NH9.15

Centennial landslide risk evolution in Medellin, Colombia 

Ugur Ozturk, Sara Manuela Nieto Lopera, and Edier Vicente Aristizabal Giraldo

The metropolitan area of Medellin, Colombia, gradually expanded toward steep hillslopes due to the constraining rugged topography surrounding the city. Steeper hillslopes are more prone to landslides by default. When combined with inadequate planning due to high population pressure, the landslide risk in the city increases disproportionately. 

We analyzed the city's expansion in 18 time steps since 1770. In particular, we explored the empirical relation between urban growth and landslide occurrences. From 1976 to 2023, the city nearly duplicated its area, going from 56 km2 to 110 km2. We showed that gradually, steeper hillslopes were urbanized, especially since 1941, accompanied by a growing proportion of land in high landslide hazard zones. We also found that landslide activity predominantly occurred on the outskirts of the urban area at any given time, resulting in harm primarily to newly emerged neighbourhoods.

Within the study period, in 2005, when areal images were available, we also categorized the metropolitan area into consolidated urbanization, i.e., compact regular mesh, compact irregular mesh, condominiums, and equipment; and unbound urbanization, i.e., level I: scarce urbanization, level II: road deficit/scattered urbanization, and level III: urbanization scattered around an axis. 

We assigned each category to variables such as hillslope angles, landslide hazards, and socioeconomic strata. Unbound urbanization was identified on steeper hillslopes, coinciding with poorer communities. Hence, we conclude that the persistent expansion of Medellin into landslide-prone areas poses a considerable threat to the population, especially those with limited opportunities in deprived neighbourhoods. By documenting the city's evolution in relation to landslide occurrences, we want to emphasize the pressing landslide risk to local and international policymakers.

How to cite: Ozturk, U., Nieto Lopera, S. M., and Aristizabal Giraldo, E. V.: Centennial landslide risk evolution in Medellin, Colombia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2451, https://doi.org/10.5194/egusphere-egu24-2451, 2024.

EGU24-3891 | Orals | NH9.15 | Highlight

Crafting Flood Risk Maps and Intensifying Social Vulnerability Studies for Heightened Awareness and Damage Mitigation: Villahermosa, Mexico case 

Rosanna Bonasia, Mackendy Ceragene, Luis Cea, and Maria de la O Cuevas Cancino

In recent decades, the state of Tabasco, particularly its capital, Villahermosa, has faced recurrent flooding due to a combination of natural and human-induced factors. Situated in the southeast region of Mexico, the convergence of the powerful Usumacinta and Grijalva rivers, coupled with clayey soil and a semi-confined aquifer inhibiting water infiltration, has made the region susceptible to saturation and subsequent flooding. Deforestation in the river basins since the 1970s, transforming land use from forest to agriculture, has exacerbated runoff, contributing to increased flood risk.

The intensification of tropical cyclones and extreme weather events, indicative of global climate change, further heightens the vulnerability of the region. Despite experiencing significant economic losses and ecological degradation in the past two decades, Tabasco's flood prevention policies have proven ineffective. Recognizing the need for a more proactive approach, this study emphasizes the importance of long-term flood risk assessment, incorporating both the probability of occurrence and potential impact.

In Mexico, guidelines for flood risk maps were established in 2014, resulting in the National Atlas of Flood Risk. However, these maps predominantly focus on flood rates and historical occurrences, lacking a comprehensive approach to long-term forecasting. This study addresses this gap by constructing the first risk maps for Villahermosa. Following National Water Commission guidelines, the methodology considers hydrological studies, hydraulic simulations, and social vulnerability indexes.

The vulnerability maps incorporate socio-economic factors like employment, education, and housing composition, while hazard maps determine the severity index and impact on residential structures. Through GIS-based intersection, risk maps are generated, revealing that even areas exposed to flooding during high-return period scenarios exhibit a medium risk index. Nevertheless, limitations arise from incomplete socio-economic and demographic data, hindering accurate vulnerability assessments.

Despite challenges, the study estimates annual damages, projecting over 33,000 affected individuals and economic losses exceeding MXN 250 million (USD 14 million). The creation of risk maps for Villahermosa, albeit challenging with current data constraints, serves as an essential initial step. It calls for further research to develop comprehensive databases, fostering public awareness and informed territorial policies to address flood risks in Villahermosa and other flood-prone areas in Mexico.

The methodology employed in this study lays a robust foundation for flood risk management, community safety, and sustainable development. It not only aids in precise identification of flood-prone areas but also serves as a crucial tool for the scientific community to address hydrological hazards. Furthermore, it supports the evaluation of existing public policies and the formulation of more effective strategies for reducing losses and enhancing resilience.

How to cite: Bonasia, R., Ceragene, M., Cea, L., and Cuevas Cancino, M. D. L. O.: Crafting Flood Risk Maps and Intensifying Social Vulnerability Studies for Heightened Awareness and Damage Mitigation: Villahermosa, Mexico case, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3891, https://doi.org/10.5194/egusphere-egu24-3891, 2024.

EGU24-5873 | Orals | NH9.15

A participatory planning approach for identifying crucial urban functions and their interdependencies for disaster recovery 

Soheil Mohammadi, Serena Cattari, Francesca Pirlone, Giorgio Boni, Ilenia Spadaro, Fabrizio Bruno, and Silvia De Angeli

Recovery planning is essential to ensure that communities build back better after a natural hazard event and ensure their long-term resilience. Involving stakeholders in recovery planning not only facilitates the accurate identification of recovery needs but also ensures the integration of a variety of viewpoints into recovery plans. Neglecting the varied perspectives arising from diverse stakeholder groups in urban areas when defining recovery objectives can lead to worsening inequality within the community.

Participatory planning acknowledged as a time-consuming process, stands in contrast to the timely interventions often demanded during post-disaster recovery. This urgency may potentially compromise both the effectiveness and equity of the participatory planning process. For this reason, it is essential to involve stakeholders and convince them to think about recovery plans before a disaster occurs, through participatory processes.

This study focuses on involving stakeholders in pre-disaster recovery planning for the identification of crucial urban functions for disaster recovery and their interdependencies. Local stakeholders have an in-depth knowledge of their urban system and are able to effectively convey the importance and interdependencies among various urban functions. Consequently, they can contribute to identifying the key urban elements that must remain functional after a disaster to ensure the initiation and progression of the recovery process.

The study employs a two-stage methodology. The first stage allows the delineation of the research objectives and the development of a participatory planning framework by means of focus groups and literature review. Initially, a focus group was conducted involving disaster risk management experts and mayors from various parts of Europe. Subsequently, a literature review has been undertaken based on the focus group findings to consolidate and refine the identified framework. The obtained framework includes 44 urban ‘functions’ divided into 6 different ‘resources’, which are required for the initiation and progression of the recovery process.

The second stage, which represents the core of this research, encompasses the application of Fuzzy Cognitive Mapping (FCM). The framework developed in the first stage is used as input to engage local stakeholders in determining the most crucial functions and their interdependencies inside the urban system through the FCM approach. The FCM has been implemented in the city of Sanremo, in the western part of Liguria Region, Italy. A group of participants, representing different sectors, created their individual cognitive maps. The individual maps have been then aggregated into a single map, which has been analyzed through the perspectives of voting mechanisms and network analysis to determine the most important and impactful urban functions and their interdependencies that contribute to recovery in their municipality. As a result, beyond the functions designated as emergency service providers crucial for the response phase after a disaster, a set of functions essential for sustaining community livelihoods such as grocery stores, supermarkets, educational services, and pharmacies have been identified. Notably, these functions are centered around the temporary sheltering function, marking it as a pivotal element from the stakeholders' perspective in the recovery process.

How to cite: Mohammadi, S., Cattari, S., Pirlone, F., Boni, G., Spadaro, I., Bruno, F., and De Angeli, S.: A participatory planning approach for identifying crucial urban functions and their interdependencies for disaster recovery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5873, https://doi.org/10.5194/egusphere-egu24-5873, 2024.

EGU24-6288 | ECS | Orals | NH9.15

The Impact of Anthropogenic Activities on the Distribution of Urban Landslides in Istanbul Megacity 

Abdüssamet Yılmaz, Tolga Görüm, Mehmet Lütfi Süzen, Tarık Talay, and İsra Bostancıoğlu

As a megacity, Istanbul has been a regional center of attraction in terms of its historical, cultural, and economic importance from past to present. In terms of this feature, it has continuously received migration and expanded its urban area due to the increasing population. Rapid urbanization has brought an urban growth model with low resilience to natural hazards. In this city, which is expected to face a major earthquake in the near future, the distribution of landslides has not been focused on covering the entire urban area. In order to make the city resilient in terms of current hazards and secondary hazards after a possible earthquake, different geoscience projects were initiated by Istanbul Metropolitan Municipality in 2022. In this context, we conducted a detailed landslide assessment for the entire city of Istanbul using Digital Elevation Models (DEMs) derived from LiDAR, multi-temporal optical stereo-photo derived, and satellite imageries covering the period between 2013 and 2023. In total, 20,537 individual landslides were identified and mapped in the entire city area from the airborne LiDAR data and multi-temporal aerial photos. In order to determine the change in the distribution of landslides we prepared multi-temporal landslide inventories using multi-temporal optical aerial photographs and satellite images between 2013 and 2023. In this respect, we found that 3241 landslides were excavated, and 468 new landslides were triggered due to anthropogenic activities such as infrastructure, road construction, mining, airport construction, urban parks, and new settlement areas. We also revealed that the legacy effect in paleo-landslide complexes plays a vital role in the reactivation of many deep-seated landslides. Many of these landslides were also reactivated due to construction and infrastructure problems. In this context, we have revealed that anthropogenic impacts are the most important parameter on the current distribution dynamics of urban landslides in Istanbul. We conclude our study by highlighting that this new and comprehensive landslide inventory prepared for the megacity of Istanbul will contribute to determining landslide avoidance zones for planning new settlements and industrial areas.

How to cite: Yılmaz, A., Görüm, T., Süzen, M. L., Talay, T., and Bostancıoğlu, İ.: The Impact of Anthropogenic Activities on the Distribution of Urban Landslides in Istanbul Megacity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6288, https://doi.org/10.5194/egusphere-egu24-6288, 2024.

Adapting to climate change impacts requires a coherent social contract in which different actors agree on a clear distribution of roles and responsibilities. It is hence important to understand what roles and responsibilities different actors in a city or other social system expect and how they negotiate to ultimately arrive at a shared vision for a coherent social contract on adaptation for the coming decades. An urgent requirement is to understand the imagined social contracts on expected roles and responsibilities, which is particularly relevant in cities where very diverse social groups come together. However, there is limited empirical evidence on these expectations as they are often tacit and hard to capture across large populations and heterogeneous groups. Here using the concept of social listening in combination with Twitter data we assess the social contract on flood risk management in Mumbai. Social media data offer a new data source to inductively capture and assess the exchange and negotiations of roles and responsibilities of different actors such as public sector, citizens, civil society and private sector, including nuanced sentiments and opinions. In order to understand the imagined social contracts by different actors in Mumbai, we captured all flood risk related tweets over the monsoon season of 2021 (~70,000 tweets). We collected data through specific hashtag and keyword combinations. We manually coded the tweets in order to show the major themes in the dominant debate on flood risk management and filtered the most relevant tweets for the social contract analysis. The tweets were subsequently coded and analysed more comprehensively (e.g. for underlying sentiments).

Overall, our results show that there are gaps in the social contract on flood risk management in Mumbai on two levels: first, between different social contracts such as the practiced and imagined or the legal-institutional and imagined and, second, between different imagined social contracts. On the former, we found a large gap between the aspirational and realistic levels of expectations from the public sector. On the latter, we found surprisingly stark contestations regarding the roles and responsibilities towards the poor and most vulnerable populations living in informal and highly flood-prone settlements. Sentiments such as frustration and apathy expressed in tweets explain these gaps and highlight the need to build trust for achieving accepted and effective social contracts for adaptation. The results suggest that laying open these gaps is a necessary first step towards closing them and building a coherent future social contract. Twitter is an upcoming arena to negotiate and express opinions between different actors and hence, an important empirical database for analysing evolving social contracts. We suggest that such social listening approaches using Twitter or other platforms of active exchange can be of great relevance in high-risk contexts, including urban areas, across the globe in which different actors are faced with a high adaptation pressure and diverse competing, or even conflicting perspectives but currently lack a clear and agreed strategy or even vision to jointly move adaptation forward.

How to cite: Doshi, D. and Garschagen, M.: Assessing social contracts for climate change adaptation through social listening on Twitter: general considerations and urban application, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6345, https://doi.org/10.5194/egusphere-egu24-6345, 2024.

Risk depends on the frequency and magnitude of river-related hazards, but also on the number, type and economic value of exposed assets (i.e. the exposure). For this reason, land use planning can increase or decrease the overall societal exposure to river-related risks. In this contribution, we bring together experiences that look into understanding and mapping the perception of river-related risks (both from and to the river) as well as riverine socio-cultural values linked to rivers, such as identity and sense of place. These connections between locals and rivers are essential to understand how to mitigate, adapt to, and revert the effects of human-induced changes on rivers. Using a transdisciplinary approach including questionnaires, interviews, a map-based participatory approach as well as evidence-based data on land and water use, biodiversity and risks, we look into how the perception of such values can influence water resources- and decision management in rivers including Tagliamento (Italy), Soča/Isonzo (Slovenia/Italy), and Upper Neretva (Bosnia-Herzegovina). We look into differences and commonalities in light of conflicting values, such as risk management, energy production and land use impacts on water resources and biodiversity, and transboundary water issues. We explore the synergies between river conservation efforts and ecosystem-based land use planning, and discuss the potential benefit of integrating local knowledge and historical evidence in assessing river-related hazards. 

How to cite: Scaini, A. and Scaini, C.: Uncovering the link between river conservation and disaster risk reduction through the invisible connection between people and rivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9243, https://doi.org/10.5194/egusphere-egu24-9243, 2024.

EGU24-10811 | ECS | Posters on site | NH9.15

Participation in climate change adaptation  

Nadejda Komendantova and Dmitry Erokhin

This paper presents a comprehensive analysis of participatory elements in climate change adaptation policies at both the EU level and within national contexts, focusing on Germany and Spain. The study delves into the crucial role of co-production and citizen engagement in shaping effective climate adaptation strategies. The research methodology involves policy identification and selection, analysis of participatory elements, and the application of Arnstein's ladder of citizen participation to evaluate the level of citizen engagement in the identified policies. The analysis reveals the diverse mechanisms and approaches employed to foster inclusive and participatory processes in climate adaptation policies. The study highlights the significance of stakeholder involvement, consultation mechanisms, transparency, capacity building, and feedback mechanisms in shaping robust climate adaptation strategies. Furthermore, it underscores the importance of citizen participation in driving transformative climate adaptation initiatives, emphasizing the need for broad geographical representation, inclusive approaches, and the integration of diverse knowledge systems. The study identifies gaps and areas for improvement in the participatory elements of the analyzed policies, emphasizing the need for more comprehensive mechanisms to engage the general public and vulnerable communities in the adaptation planning process. It also underscores the importance of systematic studies of gaps and barriers to stakeholder participation and the representation of marginalized communities in adaptation planning and decision-making processes. The paper offers valuable insights into the participatory elements of climate change adaptation policies, providing a nuanced understanding of the approaches employed at both the EU and national levels. The findings contribute to the ongoing discourse on inclusive and effective climate adaptation strategies, emphasizing the need for continuous improvement and the meaningful involvement of diverse stakeholders in shaping resilient climate futures.

How to cite: Komendantova, N. and Erokhin, D.: Participation in climate change adaptation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10811, https://doi.org/10.5194/egusphere-egu24-10811, 2024.

EGU24-11010 | ECS | Orals | NH9.15 | Highlight

Urban landslides triggered under similar rainfall conditions in cities globally 

Lisa Luna, Maria Isabel Arango Carmona, Georg Veh, Elizabeth Lewis, Ugur Ozturk, and Oliver Korup

As growing cities expand into steeper terrain, urbanization activities like clearing vegetation, cutting and filling slopes, and building infrastructure can increase rainfall-triggered landslide hazard compared to unmodified slopes. Landslide early warning systems can help to reduce rainfall-triggered landslide risk in susceptible areas, but few cities worldwide have established dedicated systems. Such systems often rely on rainfall thresholds that identify landslide triggering conditions, but determining these thresholds requires landslide inventory data that is not available everywhere. Furthermore, the variability of thresholds between cities, and the applicability of previously estimated global thresholds to urban areas has yet to be assessed, such that cities with limited landslide inventory data have few options to learn from areas with more information.

Here, we compiled 1216 rainfall-triggered urban landslide records from 26 cities worldwide to address two open questions: 1. how variable are rainfall thresholds between cities? and 2. how do global rainfall thresholds for urban landslides compare to previously estimated thresholds from multiple land use types?  Using hourly, station-based precipitation data from the Global Sub-daily Rainfall Dataset (Lewis et al., 2019), we applied Bayesian multi-level quantile regression to estimate intensity-duration thresholds for each city and a global threshold for urban landslides. 

We found that landslides were triggered under surprisingly similar rainfall conditions in most cities despite widely varying climates, topographies, and income classes.  Median thresholds in cities with the highest and lowest mean annual precipitation were not credibly distinguishable, and in 77% of cities, the median threshold was indistinguishable from the global average. We show that urban landslides occurred at lower threshold intensities than previously reported for multiple land-use types, and that 31% of landslides occurred during moderate storms, not only during extreme rainfall.

Our results suggest that urban hillslopes may be more adjusted to urbanization activities than to local environmental conditions, leading to similar thresholds between cities. Reports of urban landslides at relatively low intensity rainfall likely also reflects the role of anthropogenic hillslope modification and malfunctioning infrastructure in causing and triggering failures.  We offer a baseline for warning in cities with sparse landslide records and suggest that future updates to regional and global landslide early warning systems consider differing thresholds for urban and rural regions.

How to cite: Luna, L., Arango Carmona, M. I., Veh, G., Lewis, E., Ozturk, U., and Korup, O.: Urban landslides triggered under similar rainfall conditions in cities globally, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11010, https://doi.org/10.5194/egusphere-egu24-11010, 2024.

EGU24-11779 | ECS | Orals | NH9.15

Interrelations between urban sprawl and national hydro-geomorphological emergencies in Italy 

Alessio Gatto, Stefano Clo', Federico Martellozzo, and Samuele Segoni

Climate change and urban expansion are significantly contributing to an increase in catastrophic hydro-geomorphological events, which cause huge damage to society and economy. Since Italy is a relevant hot spot for these huge events, it was taken as a comprehensive case study for this work. The general aim is to analyze the interrelations between the recurrence of disasters at the province and municipality level and urban expansion. All the carried-out analyses are based on a dataset of municipalities and provinces affected by recent hydro-geomorphological disasters for which a national-level state of emergency was declared. The database consists of sets of every municipality and province hit by a critical event and included in the national state of emergency, which suffered damages and obtained subsidies for reconstruction in the last 9 years. For this work, the correlation between the recurrence of disasters on a province and municipality basis and urbanization was tested with a series of state-of-the-art indicators of hydrogeological hazard or risk provided by ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale – higher institute for environmental research and protection). Over 300 variables were considered and over 50 were tested, to find out which ones related better with impacts on territories. Starting from 2013 until now, were calculated soil sealing trends in areas at risk. The increase or decrease for each municipality hit by a critical event was analyzed to better understand local territories’ policies and how they face catastrophes. Firstly, it was discovered that in Italy, during the last ten years, there had been more than one hundred events that have required the intervention of National Civil Protection, with the declaration of a national-level state of emergency and the funding of interventions for first aid and restoration. Secondly, the best correlation between risk-related variables and hit municipalities was found considering cumulative months of emergency and the amount of urbanization in areas at medium hydro-geological risk. Lastly, taking into account this information, the study focused on soil urbanization trends: it was found that in each municipality the trend kept increasing at the same rate despite past damages and economic losses. The last focus of this work was, once the test was completed, evaluating the interplays over time between catastrophic events and policies of urban expansion. This work showed how urban expansion is deeply linked to hydro-geomorphological emergencies, demonstrating that at present the medium-hazard areas are underestimated by policymakers and are the main source of damages. Moreover, the urbanization trends for each municipality highlighted how local administrations, despite damages, don’t change their policies.

How to cite: Gatto, A., Clo', S., Martellozzo, F., and Segoni, S.: Interrelations between urban sprawl and national hydro-geomorphological emergencies in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11779, https://doi.org/10.5194/egusphere-egu24-11779, 2024.

EGU24-12454 | Posters on site | NH9.15

Perception of volcanic risk in communities close to a monogenetic volcanic field: the case of Olot (Garrotxa Volcanic Field, Catalonia) 

Daniela Cerda, Adelina Geyer, Xavier Bolós, Dario Pedrazzi, and Julie Morin

Nowadays, volcanic eruptions pose a significant threat to society, particularly in monogenetic volcanic fields where prolonged recurrence periods lead to increased human settlements in their vicinity. This is mostly attributed to a false sense of security within the community potentially exposed to a future eruptive event. Such misconceptions often result in a lack of preparedness programs and resilience capabilities for potential future eruptions.

In this context, the city of Olot (~34,400 inhabitants, Catalonia, Spain), located within the Garrotxa volcanic field, serves as an example of human settlement around monogenetic volcanoes, which the last known eruption occurred ~ 10.4 – 15.7 ka ago. Although communities residing in this volcanic field demonstrate a sound understanding of their environment, there is a prevalent misconception regarding volcanic hazards, which often leads to perceive the area as inactive or even extinct. 

To evaluate the perception of volcanic risk among the population of Olot, we have conducted a survey segmented by age groups. The main objectives are: (i) identifying knowledge gaps and misconceptions within the population; (ii) analyzing the factors most relevant in determining risk perception within the community; (iii) contributing to the assessment of the population's resilience in the face of a future eruptive event: and (iv) ultimately evaluating the contrast between the perception of the Olot community and its actual volcanic risk. This work was funded by the BECAS CHILE- ANID, PhD Scholarship Abroad, announcement 2022/Folio 72220257.

How to cite: Cerda, D., Geyer, A., Bolós, X., Pedrazzi, D., and Morin, J.: Perception of volcanic risk in communities close to a monogenetic volcanic field: the case of Olot (Garrotxa Volcanic Field, Catalonia), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12454, https://doi.org/10.5194/egusphere-egu24-12454, 2024.

EGU24-12735 | Orals | NH9.15 | Highlight

Identifying, Assessing, and Governing Systemic Risks: Towards an Integrative Framework Applied to Urban Settings 

Pia-Johanna Schweizer, Benjamin Hofbauer, and Paul Einhäupl

This presentation outlines a framework of how to identify, assess, and govern systemic risks, applied to the context of urban and metropolitan settings. In contrast to routine risks, systemic risks appear on a systemic and structural level, produced, and affected by complex endogenous and exogenous interdependencies. Systemic risks are unintended by-products of current transformation processes, such as the deployment and innovation of new technologies, infrastructural changes, or socio-political dynamics, for example. Urban and metropolitan provide fertile ground for systemic risks, exhibiting a nexus of tightly coupled dynamic natural, societal, and technological systems.

However, so far systemic risks lack adequate assessment, evaluation, and governance approaches, which is a barrier toward developing effective policy measures. This gap in governance mechanisms is particularly glaring in the context of increased of pluvial and fluvial floods, wildfires, storms, and other extreme weather events across European cities. Failing to take the systemic interdependencies of urban settings into account may lead to higher socio-economic losses and potential systemic breakdowns, e.g., on the energy-supply, healthcare, or infrastructure level. The framework we propose entails the qualitative identification and assessment of systemic risks, ethical and societal implications, as well as the quantitative analysis thereof. We suggest a two-step approach towards the assessment and governance of systemic risks.

First, a clear identification of the systemic risk in question needs to take place. The analysis of systemic risks needs to pay attention to casual relations and feedback mechanisms between various system factors at the intra- and inter-system level, which result in transboundary cascading effects. Accordingly, delineating both the relevant systems and entangled risks requires an interdisciplinary approach, combining the quantification of risks alongside their qualitative assessment. This entails understanding, conceptualizing, and modeling vulnerabilities, scenario development, as well as the integration of stakeholders to identify potential leverage points and enable the facilitation of transformative processes. In the context of urban environments, this means delineating the various affected systems, and how they interact (e.g. healthcare, water supply, and electricity infrastructure). Second, identified systemic risk requires adequate governance. Governance of systemic risks must be concerned with the analysis of embedded systems, procedural considerations of inclusion and deliberation, as well as closure. The salient features of reflection, iteration, inclusion, transparency, and accountability have been identified as guiding principles for governance processes concerned with systemic risk. The procedural governance approach also explicitly relies on ethical considerations, tied to recognition and participatory justice. In the context of urban environments, this entails for example analyzing the relevant governance bodies (e.g. local vs. national), understanding their respective responsibilities and interdependencies, and assessing the decision-making process surrounding disaster risk management.

The presentation outlines a framework to address the challenges of complexities, uncertainties, and ambiguities associated with systemic risks. The framework draws on conceptual contributions as well as empirical evidence from transdisciplinary stakeholder and public engagement processes in urban and metropolitan contexts.

How to cite: Schweizer, P.-J., Hofbauer, B., and Einhäupl, P.: Identifying, Assessing, and Governing Systemic Risks: Towards an Integrative Framework Applied to Urban Settings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12735, https://doi.org/10.5194/egusphere-egu24-12735, 2024.

EGU24-14870 | ECS | Posters on site | NH9.15

Understanding the historical, technical, and local perception of displacement activity in Joshimath town of Uttarakhand, India 

Shobhana Lakhera, Michel Jaboyedoff, Marc-Henri Derron, Ajanta Goswami, and Deepak Kc

The study highlights the current situation of displacement activities in Joshimath town of Uttarakhand Himalayas. Positioned in the vicinity of Viakrita and Pandukeshwar thrust, the town is situated on an old landslide and glacial moraine material, and rests on giant gneiss boulders embedded in loose sand matrix (Bhattacharya et al, 1982). Consequently, the slopes are prone to movements like mass wasting and related land subsidence. Moreover, the decadal rise in population, unplanned infrastructure, and toe cutting from Dhauli Ganga river has exacerbated the immense pressure on the already vulnerable slopes.

Thus, to understand the cause-impact and the current situation of displacement activity in Joshimath town, the historical and technical findings by previous studies were assessed with respect to the present on-ground situation of displacements and compared to the people’s perception of these disturbances. The historical evidence suggests that slope creep and related subsidence in Joshimath dates from the1960’s and has since been reappearing (Sati et al. 2023). Different technical studies have linked the cause of displacements in Joshimath to land subsidence, groundwater fluctuation and infrastructure overburden with less stress on the landslide displacement being the primary factor. Thus, a comprehensive mapping of landslide scars was done, and it was found that the recorded ground cracks and damaged buildings corresponded well with the mapped landslide scars. The recent field studies conducted in December 2023, suggested that people of Joshimath are not unaware of the landslide activities along the rim regions of Joshimath slope, and at least two communities in the past had to relocate to uphill areas, due to increased toe cutting and slope destabilization along Dhauli Ganga River. Moreover, according to the locals, slope destabilization and related subsidence in Joshimath was exacerbated post the 7th Feburary 2021 debris flow and successive heavy rainfall events in October 2021. Satellite images also suggest the reactivation of old landslides due to toe cutting after the 2021 event and similar destabilization was also triggered post the 2013 flash floods (Sharma et al., 2014). The field observations also highlighted the presence of new cracks and fissures on roads, fields, and repaired constructions. Thus, the increase in toe cutting, followed by slope failures may lead to upslope progression of landslide scars. Also 99% of buildings in Joshimath are non-compliant with the national building codes of 2016, and most of the adversely affected buildings lie in regions on steep slopes of hill (CBRI, 2023). Consequently, the unplanned infrastructure development along such unstable old landslide scars could accelerate slope instability.

Keywords: Displacement, Landslides, cracks, toe-cutting, infrastructure

How to cite: Lakhera, S., Jaboyedoff, M., Derron, M.-H., Goswami, A., and Kc, D.: Understanding the historical, technical, and local perception of displacement activity in Joshimath town of Uttarakhand, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14870, https://doi.org/10.5194/egusphere-egu24-14870, 2024.

Natural hazards, particularly floods, pose significant threats to societies, demanding effective risk management strategies. In some nations, such as China and Vietnam, flood risk management historically followed a predominantly top-down approach, with limited citizen involvement in decision-making processes. Despite past success of this approach in minimizing losses, the escalating frequency and intensity of floods, driven by climate change, raise questions about solely relaying on conventional methods. In addition to or due to a lack of governmental initiatives, individuals and households often employ their own distinctive adaptation approaches, demonstrating a form of "bottom-up resilience". Without idealizing either approach, integrating aspects of both strategies and ultimately initiating a transformation of flood risk management is necessary to prevent exceeding capacity limits. However, there is still a profound lack of understanding how to genuinely enable transformation, especially in practical terms. Due to their potential to facilitate change, leverage points – places to intervene within a complex system – are becoming increasingly important in system research as a lens for evaluating and planning interventions that support transformation. However, existing research rarely considers leverage points in the context of identifying interventions with transformative potential in flood risk management.

This presentation attempts to fill the gap in research by providing a framework for identifying deep leverage points crucial in the intricate dynamics among individuals, communities, and governments in flood risk management, while acknowledging the challenges, limitations and possibilities inherent in bridging top-down and bottom-up approaches. To overcome the gap between theory and practical implementation, the utilization of an Agent-Based Model (ABM) is proposed to simulate and analyze the impact of concrete interventions at the identified leverage points. An expected result from the ABM includes more in-depth knowledge on the effectiveness of trainings or platforms for information exchange, and about responsibilities within communities as an entry point to enhance community resilience to floods. The model results will provide a tangible and dynamic representation of the potential outcomes of integrated strategies, offering valuable insights for policymakers, researchers, and practitioners alike.

How to cite: Heinzel, C.: A Trigger for Transformation? Exploring Leverage Points to Bridge Top-Down and Bottom-Up Approaches in Flood Risk Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15111, https://doi.org/10.5194/egusphere-egu24-15111, 2024.

EGU24-16779 | Orals | NH9.15

Cyber-Echoes of Climate Crisis: Unraveling Anthropogenic Climate Change Narratives on Social Media 

Abraham Yosipof, Or Elroy, and Nadejda Komendantova

Social media platforms have a key role in spreading narratives about climate change, and therefore it is crucial to understand the discussion about climate change in social media. The discussion on anthropogenic climate change in general, and on social media specifically, has multiple different narratives. Understanding of the discourses can assist efforts of mitigation, adaptation, and policy measures development. In this work, we collected 333,635 tweets in English about anthropogenic climate change. We used Natural Language Processing (NLP) and machine learning methods to embed the semantic meaning of the tweets into vectors, cluster the tweets, and analyze the results. We clustered the tweets into four clusters that correspond to four narratives in the discussion. Analyzing the behavioral dynamics of each cluster revealed that the clusters focus on the discussion of whether climate change is caused by humans or not, scientific arguments, policy, and conspiracy. The research results can serve as input for media policy and awareness-raising measures on climate change mitigation and adaptation policies, and facilitating future communications related to climate change.

How to cite: Yosipof, A., Elroy, O., and Komendantova, N.: Cyber-Echoes of Climate Crisis: Unraveling Anthropogenic Climate Change Narratives on Social Media, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16779, https://doi.org/10.5194/egusphere-egu24-16779, 2024.

Climate change, one of the most remarked anthropogenic changes, has increased the intensity and frequency of heavy rainfall events. Heavy rainfall events pose challenges especially in urban areas, which have a higher rate of impervious surface, compared to non-urban areas. Seoul, the capital city of South Korea is not an exception for the cities that contend with flooding. During summer, the meteorological condition forming over the Korean peninsula brings rainfall constituting approximately 35-55% of the country’s annual precipitation. Seoul has undergone rapid development and urbanization, which also are the examples of anthropogenic changes, for the last five decades; the city’s current population is about 4.7 times larger than that of the early 1960s. This fast population increase created a distinctive housing type known as semi-basement housing, symbolizing socioeconomic marginalization. Despite ongoing efforts by the Seoul Metropolitan Government to mitigate flood risk citywide, most of the households living in the semi-basement housing, particularly in low-lying areas, remain highly susceptible to flooding whenever heavy rainfall events occur. This study focuses on Gwanak-gu, one of Seoul’s 25 districts and the district with the highest concentration of semi-basement housing. The study examines how anthropogenic changes in both physical (i.e., climate change) and social (i.e., urban development and urbanization) environment exacerbate the already marginalized people’s vulnerability floods. The results show that the same amount of heavy rainfall (e.g., 100mm per hour) pouring in the district significantly heightens the level of exposure for the semi-basement housing than the exposure level of housing that is not semi-basement. This implies that the climate change and urban development and urbanization (i.e., anthropogenic changes) make the vulnerable people even more vulnerable, even as the measures aim to alleviate overall flood risk across the city have been implemented. In other words, anthropogenic changes, even though the government’s risk mitigation efforts exist, tend to polarize the vulnerability and exposure to floods. Drawing from the results, the study emphasizes the need for more considerate measures to truly reduce the flood risk of the city. It concludes by suggesting potential strategies that could contribute to reducing flood vulnerability of the marginalized populations and lowering overall flood risk in the city.

How to cite: Ro, B. and Park, H.: The impact of anthropogenic changes on socioeconomically marginalized population in urban areas: A case study of flood risk in Seoul, South Korea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17950, https://doi.org/10.5194/egusphere-egu24-17950, 2024.

EGU24-18272 | Posters on site | NH9.15

Tourists' perception of volcanic hazards and volcanic risk in Tenerife Island 

David Afonso Falcón, Claudia Rodríguez-Pérez, Adriana Quezada-Ugalde, GInevra Chelli, Grace James, Kenza Rahli, José G. Cantero, Beverley C. Coldwell, Carmen Solana, Fátima Rodríguez, Eleazar adrón, Nemesio M. Pérez, Pedro A. Hernández, Gladys V. Melián, German Padilla, and María Asensio-Ramos

The entire Canarian Archipelago can be considered a volcanically active area and its volcanic risk is now much higher than 50 years ago as a result of the actual high levels of population and socio-economic value exposure to the volcanic hazards present on the territory. The knowledge of perception of volcanic hazards and volcanic risk of different groups of the society will be essential to develop an effective reduction volcanic risk strategy as a collective responsibility. The different groups can be communication professionals, tourists, urban and territorial planners and the general public, among others. While some may have more specific roles and responsibilities in this endeavor, visitors and tourists can make a significant contribution to volcanic risk management efforts. The Canary Islands register between 8 to 13 millions of visitors every year (source: Statistics National Institute-INE), what means a significant number of floating populations visiting an active volcanic area. This research aims to assess the level of understanding and interest that tourists have about volcanoes and volcanic risk management in Canary Islands, and to examine the potential and desired role of the tourists in enhancing the effectiveness of volcanic risk management efforts.

To assess tourists' perceptions of volcanic hazards and risks on Tenerife, we have designed a face-to-face questionnaire. The questionnaire consists of approximately 30 questions and is completed in about 10 or 15 minutes. Approximately 20% of the questionnaire covers demographic data, while questions about volcanic phenomenon and volcanic risk management account for roughly 40%, with the remaining 40% centered on respondents' perception of volcanic hazards and risks. The questionnaire was released from July 18 to the end of September 2023, with a total of 419 tourists surveyed.

How to cite: Afonso Falcón, D., Rodríguez-Pérez, C., Quezada-Ugalde, A., Chelli, G., James, G., Rahli, K., Cantero, J. G., Coldwell, B. C., Solana, C., Rodríguez, F., adrón, E., Pérez, N. M., Hernández, P. A., Melián, G. V., Padilla, G., and Asensio-Ramos, M.: Tourists' perception of volcanic hazards and volcanic risk in Tenerife Island, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18272, https://doi.org/10.5194/egusphere-egu24-18272, 2024.

EGU24-19009 | Posters on site | NH9.15

ALERTA CO2: An alert system to monitor and mitigate the hazard associated with high concentrations of indoor and outdoor air CO2 at the inhabited areas of Puerto Naos and La Bombilla, La Palma 

Germán D. Padilla, Nemesio M. Pérez, Carmen López, Rubén López, Pedro A. Hernández, David Moure, Luca D'Auria, Pedro Torres, José Barrancos, Gladys V. Melián, Daniel D'Nardo, Alexis M. González, and Antonio Álvarez

Anomalous CO2 degassing were observed by the end of November 2021 in the neighborhoods of La Bombilla and Puerto Naos, and some banana plantations, located at the North-West flank of Cumbre Vieja volcano ridge, La Palma island, at about 6 km distance southwestern of the 2021 Tajogaite eruption vents. These urban areas, not directly damaged by lava flows, were included in the exclusion zone due to the strong volcanic-hydrothermal carbon dioxide emissions (CO2>5-20%). CO2 is an invisible toxic gas, as well as asphyxiant gas, and may be lethal when is present in concentrations higher than 14V%.

During the last two years, several institutions deployed indoor and outdoor own gas networks, to try to delimitate the CO2 anomalies where CO2 air concentration exceed hazardous thresholds, but with an insufficient number of CO2 sensors (less than 100) to cover all homes, garages, basements and stores in real time. These studies aim to understand the dynamics of CO2 emission to delimitate the CO2 anomalies where CO2 air concentration exceed the hazardous thresholds, and help the authorities’ decision-making of people's return to their homes and stores.

The ALERTACO2 project was born with the objective of implementing a much more extensive network of CO2 sensors (1,200) sensors in most of the building of both inhabited areas, the creation of a 24-hour monitoring room and an information and awareness campaign for the population about this volcanic hazard. The financing (3M EUROS) comes from the Spanish Government, and has the participation of the National Geographic Institute (IGN) and the Volcanological Institute of the Canary Islands (INVOLCAN).

Each sensor has a color light code to indicate the CO2 concentration (green, yellow, orange and blue if the sensor is not working), and a QR code to view the information remotely. So far 35% of the 1,200 sensors have been installed inside and outside homes of both urban areas (including beaches and Sol Melia Hotel). Each sensor sends the data to the 24-hour monitoring room via a gateway installed at the roof of each building. Thanks to the project, some families in the area marked green have been able to return to their homes in safety conditions in December 2023 since their homes CO2 concentrations were below 1,000 ppm.

How to cite: Padilla, G. D., Pérez, N. M., López, C., López, R., Hernández, P. A., Moure, D., D'Auria, L., Torres, P., Barrancos, J., Melián, G. V., D'Nardo, D., González, A. M., and Álvarez, A.: ALERTA CO2: An alert system to monitor and mitigate the hazard associated with high concentrations of indoor and outdoor air CO2 at the inhabited areas of Puerto Naos and La Bombilla, La Palma, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19009, https://doi.org/10.5194/egusphere-egu24-19009, 2024.

EGU24-19300 | ECS | Posters on site | NH9.15

Persistence of Rumours and Hate Speech Over the Years: the Manchester Arena Bombing  

Rosa Vicari, Or Elroy, Nadejda Komendantova, and Abraham Yosipof

Following the 2017 Manchester Arena bombing, the ensuing discussions in the media and on social platforms highlighted the potential of terrorism to deepen societal divisions. This study investigates the dynamics of rumors on social media and in the press after the attack, as well as the subsequent discourse on migration policies. We compiled a dataset comprising 3,184 press articles and 89,148 tweets pertaining to the Manchester Arena bombing. The research aims to identify prevalent rumors, assess their short- and long-term effects on user engagement, analyze the sentiment in tweets related to each rumor, and scrutinize perceptions of terrorism threats and migration policies among both the press and Twitter users.

The findings reveal that Twitter acted as an echo chamber for misinformation, amplifying specific rumors related to the attack, while the press demonstrated fact-checking practices and offered nuanced perspectives. Notably, one rumor suggesting the attacker was a refugee gained traction over time, reflecting a surge in anti-immigrant sentiments. Emotional responses on Twitter varied from a neutral tone to heightened distress and anger, underscoring the significant impact of social media narratives on public sentiment. The research highlights the polarization of views on social media, influenced by the concise format of tweets and the rapid production cycle, with Twitter users predominantly expressing very negative attitudes toward immigration. This study emphasizes the crucial role of the media in dispelling misinformation and cultivating a nuanced public understanding in complex socio-political contexts.

How to cite: Vicari, R., Elroy, O., Komendantova, N., and Yosipof, A.: Persistence of Rumours and Hate Speech Over the Years: the Manchester Arena Bombing , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19300, https://doi.org/10.5194/egusphere-egu24-19300, 2024.

EGU24-19362 | ECS | Posters on site | NH9.15

Intention to apply Artificial Intelligence using fact checking tools in disaster management 

Tahere Zobeidi and Nadejda Komendantova

The daily dissemination of a substantial amount of information concerning to disasters and crises on social media platforms, including Facebook, Instagram and Twitter in one side, and the sensitivity of this information, on the other hand, underscores the importance of evaluating the credibility of online information in this area. Fact-checking tools employing artificial intelligence represent a novel approach to verifying the validity of online information across various fields, including disaster management. The inclination of individuals to utilize fact-checking tools in such circumstances is influenced by their perceptions. Although there is a limited studies on the impact of perceptions and information processing on the intention to employ fact-checking tools in disaster-related contexts, it is anticipated that factors like critical thinking, as a concept that involves meticulous assessment of unclear or requiring careful consideration, heuristic processing, a concept indicating acceptance of news content without filtering, and the new-source tracking a concept demonstrating openness and positivity towards social media information, play pivotal roles in predicting this intention. Consequently, a conceptual framework was formulated wherein critical thinking, aside from its direct impact on the intention to use fact-checking tools, also exerts influence through two mediators of information processing and the new source tracking variables. This study's framework was examined using data from 202 respondents across various European countries, collected through an online survey. The conceptual framework analysised utilizing AMOS software. Descriptive findings indicate a moderate level of familiarity with misinformation detection tools among respondents (M=2.65; sd=1.04). Respondents exhibited close knowledge levels regarding fact-checking tools such as Rbutr, Foller, me and Botometer, Fakespot, NewsGuard, and Greek Hoaxes Detector, ranging between approximately (1.57-1.70). Contrary to initial expectations, the study's results reveal that critical thinking, was unable to directly predict the intention to use fact-checking tools. However, the indirect effect of critical thinking was confirmed through the two mediators of new source tracking and information processing (heuristic processing). Critical thinking significantly influenced the new source tracking (β=.49; p <0.0001) and heuristic processing (β=.41; p <0.0001). Both new source tracking (β=.19; p=0.043) and heuristic information processing (β=.31; p=0.001) emerged as direct predictors of the intention to use fact-checking tools. The evidence examined in this study provides empirical support that the conceptual framework has been able to predict 22% of the changes in the intention to use fact checking tools and still a significant amount of it needs to be researched.

How to cite: Zobeidi, T. and Komendantova, N.: Intention to apply Artificial Intelligence using fact checking tools in disaster management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19362, https://doi.org/10.5194/egusphere-egu24-19362, 2024.

The role of citizens and local communities in disaster risk assessment, preparedness and mitigation has always been fundamental, but long obscured in public memory, in media translation and often also in scientific reading of natural disasters.

During recent years, the citizen science approach - which has become very popular -has drawn attention to the need for active involvement of citizens and communities to produce resilient responses to disasters, through inclusive and participatory bottom-up activities.More specifically, it can increase resilience by building the collective and self-efficacy of individuals, organisations, and communities; above all , it can help to recognize and nurture the local social capital, trust and sense of community. In addition, it can make it possible to exploit previous experiences of disaster governance (e.g. through local memories), activating a knowledge transfer process useful for preparing and responding to catastrophes.

Many factors interact on capacity of individuals, communities, and institutions to respond to disasters (e.g., Lindell & Prater, 2002; Paton & Johnston, 2006): the collective and self-efficacy (Paton & Johnston, 2006; Paton et al., 2010); outcome expectancy, action coping, leadership, individual and community empowerment, trust, sense of community, and place attachment (Aldrich & Meyer, 2014; Norris, Stevens, Pfefferbaum, Wyche, & Pfefferbaum, 2008); and so on.

These factors interact in a "social space-time" in which the socio-cultural characteristics of contexts , the role played by institutional decision-makers, by regulations, by the times of actions become very important.

Here we present an overview of some case studies carried out in Italy, focused on contexts affected by natural disasters, particularly harmful from a physical and social point of view. These case studies can be useful to highlight factors/conditions that can hinder or encourage forms of community resilience in the response to events.

How to cite: Zaccaria, A. M.: Spaces of resilience. Citizen science for community resilience building, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19861, https://doi.org/10.5194/egusphere-egu24-19861, 2024.

Rapidly increasing climate risks result in a fundamental and quickly growing need for societies to adapt their settlements, infrastructure, managed ecosystems and social systems. In many contexts, this task is so large that is requires to significantly reconsider the roles and responsibilities different actors can and should have in it. Already today, many of the current risk management regimes and their institutionalized distributions of responsibilities are reaching their limits. For example, municipalities around the globe already face difficulties to maintain their established levels of flood risk protection and carry them into the future, hence arguing that private households and firms should more strongly take care of their own protection.

However, to date consistent frameworks to analyze the existing distribution of roles and responsibilities for adaptation and to guide a future debate on their re-distribution are lacking, both from an analytical as well as normative point of view. We therefore present and discuss a novel framework to that end, using the lens of social contracts. The framework builds on a comprehensive review of the theoretical literature and empirical data acquired in a range of adaptation projects across the globe. The framework differentiates between legalized, otherwise institutionalized, enacted and envisioned social contracts. It helps to not only lay open these individual dimensions but also to examine the rifts between them. It further proposes a typology of different social contracts with a view towards the level of agreement or disagreement different actors have on how they envision the distribution of roles and responsibilities. In doing so, the framework can be applied to different cultural settings across the globe as well as to the analysis and policy guidance from local to global scales. The framework takes temporal dynamics into account in order to effectively inform transition processes within the context of climate resilient development.

The presentation lays out the framework, illustrates it applicability along a number of case studies from different contexts across the globe and discusses its potential for wider application in what is deemed to be a critical decade not only in adaptation science but also adaptation action.

How to cite: Garschagen, M., Doshi, D., Grobusch, L., and Petzold, J.: Social contracts for climate change adaptation: an analytical and normative framework for the distribution of roles and responsibilities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20422, https://doi.org/10.5194/egusphere-egu24-20422, 2024.

EGU24-4468 | ECS | Posters on site | NH9.16

Activation mechanism and failure process of an ancient landslide induced by landslide impact loads in China 

Zhaoyue Yu, Jiewei Zhan, and Jianbing Peng

On September 9, 2021, a catastrophic landslide occurred in Zhanjiaping Village, Zhenba County, Shaanxi Province, China, blocking the Yushui River and forming a landslide barrier lake. To gain a deeper understanding of this catastrophic event, we have utilized a combination of engineering geological exploration, multi-source remote sensing and geotechnical testing techniques to elucidate the dynamic evolution and formation mechanisms of the landslide. Zhanjiaping landslide is located in the core of the Luoquanyan Syncline within the Daba Mountain foreland arc structure zone, with the plunge direction of 319° and plunge of 11° along the fold axis. Zhanjiaping landslide is developed in the ancient landslide area, which is a typical sliding and tension-fracturing landslide with a very gentle sliding surface, and the volume of the landslide is estimated to be 7.44 × 106 m3. The strata in the landslide area exhibits a layered structure with alternating soft and hard formations. Under the influence of continuous rainfall, the steep slopes on the north flank of the Luoquanyan Syncline were destabilized along the bedding planes of the underlying mudstone, and forming a deposit on the gentle slope to the northeast of Zhanjiaping Village in the syncline core area. Then, affected by the landslide impact loading and rainfall infiltration, the strength of the contact surface between the paleoslide body and bedrock in the core area of Luoquanyan Syncline decreases, leading to the resurrection of the ancient landslide. However, blocked by the south flank of Luoquanyan Syncline, the downward sliding of the slide body was impeded, which in turn to both sides to undergo multiple extrusion and braking phenomena. This study provides a case study of a small landslide destabilization that eventually triggered the resurrection of a large-scale ancient landslide under the control of geological structure, which can provide a reference for the prevention and control of similar landslide disasters.

How to cite: Yu, Z., Zhan, J., and Peng, J.: Activation mechanism and failure process of an ancient landslide induced by landslide impact loads in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4468, https://doi.org/10.5194/egusphere-egu24-4468, 2024.

EGU24-10680 | Posters on site | NH9.16

Modelling and evaluating GLOF risk management measures in the Kyrgyz Ala-Archa valley 

Laura Niggli, Vitalii Zaginaev, Holger Frey, Simon Allen, and Christian Huggel

Glacier lake outburst floods (GLOF) are mass flow hazards of severe destructive potential and far reach that can cause extensive damage to the natural and built environment posing a threat to people and their livelihoods. Diverse risk management measures have been proposed and been implemented in order to reduce the risks associated with GLOFs. However, systematic studies on the effectiveness and cost-benefit of such measures in the contest of disaster risk management (DRM) are largely lacking.

Here we model, map and evaluate GLOF risk measures and analyse how the implementation of different GLOF DRM measures alters GLOF risk. We compare cost and benefit of five potential measures in the mountainous Ala-Archa catchment in the Kyrgyz range south of Bishkek, the capital of the Kyrgyz Republic. Using the RAMMS debris flow software, the extent of two GLOF scenarios are modelled for the situations of (i) no DRM measure (current state), (ii) lake volume reduction, (iii) a deflection dam, (iv) a retention dam and reservoir, (v) an Early Warning System, and (vi) land use planning.

We analyse the effect of the different DRM measures by examining the three components of risk, namely hazard, exposure and vulnerability. We estimate the expected cost of the respective DRM measures and compare it to the costs of the potential damage caused by the GLOF scenarios. While we assess hazard and exposure quantitatively, we analyse vulnerability in a qualitative way, based on socio-economic characteristics such as age, gender, education, economic diversity and dependency.

With increasing numbers of glacier lakes and potential disastrous lake outbursts linked to climate change, often combined with increasing exposure of infrastructure and human assets, cost effective GLOF DRM is of growing importance.  While the absolute numbers based on the exposed assets, cost and damage will differ for other settings, the conceptual approach of this case study can be applied to other mountainous catchments. This study’s main findings serve as a basis for decision making in similar settings with stakeholders aiming for cost-effective GLOF risk management.

How to cite: Niggli, L., Zaginaev, V., Frey, H., Allen, S., and Huggel, C.: Modelling and evaluating GLOF risk management measures in the Kyrgyz Ala-Archa valley, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10680, https://doi.org/10.5194/egusphere-egu24-10680, 2024.

EGU24-10855 | Posters virtual | NH9.16

Assessment of terrigenous sediment input into Plastiras lake (Greece) as deduced from UAS and multibeam surveys: insights from the “IANOS” Medicane effect 

Emmanuel Vassilakis, Aliki Konsolaki, Spyros Maroulakis, George Anastasakis, and Efthymios Lekkas

Plastiras artificial lake is formed upstream of an 83 m-high arched dam, at an altitude of 795.20 m above msl. A hydroelectric power plant constructed back in 1959, started functioning in 1960 with an average annual electricity production of 180 GWh. Moreover, its water provides potable supply, after treatment, to surrounding towns and essential agricultural irrigation to 140,000 acres of land. The 23.5 km² lake and its surroundings are extensively used for environmental recreational activities and the local ecosystem is sensitive to human activities and environmental factors.

Recently the region was affected by two extreme weather events, in 2020 and 2023, evidently causing extensive mass wasting phenomena in the surrounding drainage basins and torrent discharge points into the lake. Especially after the “IANOS” Medicane (September 17-18, 2020), a systematic monitoring of the lake and its drainage was decided. A synergy of methodologies with state-of-the-art equipment was used, to evaluate the volumes of terrigenous sediment brought into the lake, drastically reducing the water storage capacity of the dam. The reference dataset was a single and multibeam survey carried out back in 2009, accompanied by a photogrammetric mapping of the lake coast at the maximum lake water level.

Our 2023 surveys encompass more than 14,000 images which were acquired with a Trinity F90 UAS, flying at a relative height of 160 meters, covering a 200-meter-wide zone around the coast of the lake, with a 70% overlap between the images. Image capturing of the latter took place during the lowest lake water level so that most of this zone would be revealed from the water's surface. The establishment of 15 Ground Control Points (GCPs) at certain locations around the lake increased the spatial credibility of the extracted 2.5 cm resolution Digital Terrain Model. For co-registration reasons, the same GCPs were also used as references during the multibeam survey, which was conducted at transects parallel and vertical to the shoreline routes, 20-90 meters apart, pending on the lake depth, to achieve a complete swath coverage of the lake bottom. The multibeam-sounding survey was carried out at near maximum lake water level, with continuous hourly monitoring of the water level and the water speed of sound.

Both methodologies resulted in point-clouds which were unified, and a DTM of the entire lake bottom was constructed, representing the full extent of the water body during the highest water level. The latter was compared to the 2010 dataset and a significant change in the water volume was detected reaching almost 4 million m3. This is clearly related to the volume of sediments brought into the lake, by both sediment gravity flows entering the lake especially within the torrent inlets along the west coast while finer suspended sediment mostly settles in the deepest areas towards the dam.

How to cite: Vassilakis, E., Konsolaki, A., Maroulakis, S., Anastasakis, G., and Lekkas, E.: Assessment of terrigenous sediment input into Plastiras lake (Greece) as deduced from UAS and multibeam surveys: insights from the “IANOS” Medicane effect, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10855, https://doi.org/10.5194/egusphere-egu24-10855, 2024.

EGU24-11236 | ECS | Posters virtual | NH9.16

Frequency analysis of compound heat and wet extremes over Nepal 

Bishnu Prasad Neupane, Ravi Kumar Guntu, and Ankit Agarwal

Nepal faces a spectrum of climate-related challenges, such as floods, landslides, and droughts, causing substantial economic and environmental consequences. The country’s vulnerability to climate change is intensified by its geographic features and inadequate preparedness, underscoring the significance of studying compound extremes for water resources management and disaster mitigation. The susceptibility to climate change, coupled with geographic vulnerability heightened by extreme weather events, like floods and landslides, poses significant threats to Nepal’s socioeconomic development, necessitating further research. Studying compound extremes is crucial due to the escalating disastrous effects of cascading disasters, impacting agriculture, food security, and water resources. This study utilizes observed and model data to analyze compound heatwaves and extreme precipitation events, categorizing extreme precipitation as values surpassing the 95th percentile and defining heatwaves as three or more consecutive days with maximum temperatures exceeding the 95th percentile. Station data from 1981-2020 along with CMIP6 13 models data from 1951-1982 for past event analysis and from 2015 to 2100 for future projections reveal varying trends in heatwaves, extreme precipitation, and compound events across Nepal. Different models indicate diverse distributions of heatwaves and wet extremes, with some regions experiencing a decline in heatwave events in the past. The sensitivity of compound events to lagging periods is evident, resulting in a shift from 15 to 30 days and a subsequent increase in compound events. SSP scenarios project an overall rise in compound heatwaves and extreme precipitation in the future, emphasizing the risk of cascading disasters and urging stakeholders and governments to implement robust disaster risk reduction and management strategies. The study underscores the complexities of extreme events in Nepal’s climate data and model results, stressing the importance of considering spatial, temporal, and modeling factors for effective climate change impact adaptation and mitigation.

 

How to cite: Neupane, B. P., Guntu, R. K., and Agarwal, A.: Frequency analysis of compound heat and wet extremes over Nepal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11236, https://doi.org/10.5194/egusphere-egu24-11236, 2024.

EGU24-15032 | ECS | Posters on site | NH9.16

Identification of Potentially Dangerous Glacial Lakes (PDGLs) in the Northwest Himalayas  

Anup Upadhyaya and Abhishek K. Rai

The retreat of glaciers has emerged as a significant threat in recent decades, leading to the emergence and growth of glacial lakes. Many of these lakes are vulnerable to Glacial Lake Outburst Floods (GLOFs) as a result of challenging geotectonic settings and adverse climatic environments. Satellite imageries, Digital Elevation Models (DEMs), seismic and meteorological data were utilized in this study to asses the vulnerability posed by more than 1300 glacial lakes in the Northwest Himalayas (NWH) to a potential GLOF event in the future. We employed the Analytic Hierarchy Processes (AHP) - Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and AHP - Complex Proportional Assessment of Alternatives (COPRAS) approaches to identify Potentially Dangerous Glacial Lakes (PDGLs), using 15 key conditioning factors.  Over 20 lakes were identified as having very high risk to GLOFs, while more than 130 lakes were classified as being at a high risk. The upper Indus basin possessed the most number of vulnerable lakes, which are at a greater risk of experiencing a probable GLOF event, followed by the Jhelum basin. To authenticate our results, we examined the past GLOFs incidents and our analysis revealed that most of the previous GLOFs are classified as PDGLs falling into either the very high or high risk categories. The findings of this study will provide valuable insights for stakeholders and decision makers enabling them to implement preventive measures to mitigate risks during a potential GLOF event in future.

How to cite: Upadhyaya, A. and Rai, A. K.: Identification of Potentially Dangerous Glacial Lakes (PDGLs) in the Northwest Himalayas , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15032, https://doi.org/10.5194/egusphere-egu24-15032, 2024.

EGU24-16448 | ECS | Posters on site | NH9.16

Detection and analysis of GLOF events at Alemania (Roncagli) Glacier, Cordillera Darwin 

Maria Schliermann, Ilaria Tabone, David Farias-Barahona, Jan Erik Arndt, and Ricardo Giesecke

The rapid retreat of glaciers due to warmer temperatures has resulted in an increase in both number, size and volume of glacial lakes across the Andes. Indeed, a recent study found that Patagonian lakes have more than doubled in volume during the last three decades. These lakes, constrained by unstable moraine dams or ice walls, hold the potential for catastrophic outbursts, known as Glacial Lakes Outburst Flood (GLOF) events. Glacial inventories are available since 1986 for Central Andes, Northern Patagonia and Southern Patagonia and GLOF occurrence and distribution has been widely studied for Chilean and Argentinian Andes. However, very few information on glacial lakes and related GLOF events exists in the Cordillera Darwin. Although the sudden release of immense volumes of water, sediments, and debris in such a remote area does not have the potential of affecting communities and infrastructures downstream, as in more populated areas, it still poses severe threats to the fiords ecosystems. Here we present the detection and analysis of a GLOF event at Alemania (Roncagli) glacier, in the south-western flank of the Cordillera Darwin, occurred in April 2023. The GLOF event was initially identified through FerryBox data collected across the Beagle Channel and subsequently confirmed using satellite imagery, analysing changes in the area of Lake Martinic, where the secondary front of Alemania glacier terminates. Moreover, a detailed analysis of 35 satellite images reveals a regular occurrence of such events since 2018, emphasising the repetitive nature of GLOFs at Alemania Glacier and its potential of disrupting the Beagle Channel ecosystem. 

How to cite: Schliermann, M., Tabone, I., Farias-Barahona, D., Arndt, J. E., and Giesecke, R.: Detection and analysis of GLOF events at Alemania (Roncagli) Glacier, Cordillera Darwin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16448, https://doi.org/10.5194/egusphere-egu24-16448, 2024.

EGU24-17940 | ECS | Posters on site | NH9.16

Three-dimensional simulations of future GLOF events in High Mountain Asia under different SSP scenarios 

Wilhelm Furian, Tobias Sauter, and Christoph Schneider

In High Mountain Asia (HMA), rising temperatures and retreating glaciers are leading to the formation of new glacial lakes and the expansion of existing ones. The sudden release of water from such lakes can lead to devastating glacial lake outburst floods (GLOF) threatening people and infrastructure for many kilometers downstream. Therefore, it is important to obtain information on future glacial lakes, e.g., their location, area, and volume as well as the timing of their development. This data can in turn be used to estimate the range and destructive potential of future GLOF events, which is crucial for the sustainable development of settlements and infrastructures.

Dam failures at glacial lakes and the subsequent flooding events are often investigated using two-dimensional models (e.g. HEC-RAS). These 2D models are based on the solution of the shallow water equations, which assume that the vertical velocity of the water is always much lower than the horizontal velocity. In case of a moraine failure, however, high vertical accelerations are observed in the behavior of the dam break wave in mountainous terrain, which violates the shallow water equations. To overcome these shortcomings of 2D models, fully three-dimensional Computational Fluid Dynamic (CFD) models can be used, which are based on the solution of the Navier-Stokes equations along with the volume of fluid method to locate the interface between water and air.

In our research project, we use the 3D open-source CFD model OpenFOAM to determine the possible range of GLOF events at future glacial lakes in HMA. To capture the different climate pathways and the corresponding differences in lake volume, we use previously published data on the evolution of future glacial lakes over the course of the 21st century under different SSP scenarios. To account for the uncertainties of future moraine height or composition, we simulate different moraine failure scenarios resulting in different magnitudes of GLOFs. These simulations allow us to determine the velocity of the initial break wave and identify potential inundation areas. By intersecting the resulting flood map with land-use and land-cover maps (while taking into consideration the potential changes in this data during the coming decades), we can estimate affected agricultural land and potentially damaged infrastructures. Our findings can contribute to helping local communities adapt to emerging challenges, implement risk minimization measures, and enhance sustainable development in HMA.

How to cite: Furian, W., Sauter, T., and Schneider, C.: Three-dimensional simulations of future GLOF events in High Mountain Asia under different SSP scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17940, https://doi.org/10.5194/egusphere-egu24-17940, 2024.

EGU24-676 | ECS | PICO | HS5.3.3

The effect of commercial export farms on drought risk and adaptation of agropastoral communities in the drylands of Kenya 

Ileen Streefkerk, Jeroen Aerts, Jens de Bruijn, Khalid Hassaballah, Rhoda Odongo, Teun Schrieks, Oliver Wasonga, and Anne Van Loon

Drought poses a thread in the already existing water challenges in dryland regions. Drought hazard and risk are, however, not merely a natural phenomenon. Instead they are shaped and influenced by human behaviour and interventions. This raises questions about how to distribute the limited available water in an equitable manner, especially in drought prone areas such as drylands where water is key to people’s livelihood and fragile ecosystems.

In the Horn of Africa Drylands (HAD) conflict over water and vegetation is prominent. On top of that, large-scale land acquisitions (LSLAs) are increasing the competition of water, putting local communities at increased risk. A key impact of increasing LSLA's is the decrease in water and land availability for vulnerable agropastoral communities. For such communities, drought adaptation is key to reduce drought risk, especially under climate change. Despite these recent studies, there is still a lack of research that includes the influence of upstream-downstream dynamics on drought risk and adaptation behaviour with a focus on the impacts of agropastoralists.

This study, therefore, further develops an agent-based model (ADOPT-AP) to investigate how upstream large scale commercial farms influence downstream drought risk and adaptation of agropastoralists. We apply and test the ADOPT-AP model for the Ewaso N’giro north catchment in Kenya. Main novelties of our method are the ability to capture heterogeneous and dynamic drought-human interactions (including different water users) in a spatially-explicit manner. After the model has been calibrated and validated, we test how commercial exporting farms affect drought risk and impact of downstream communities by simulating different scenarios. We show for various drought periods how both drought characteristics (soil moisture, discharge and groundwater levels) and impacts (milk production, crop production, distance to water) differ among the scenarios.

How to cite: Streefkerk, I., Aerts, J., de Bruijn, J., Hassaballah, K., Odongo, R., Schrieks, T., Wasonga, O., and Van Loon, A.: The effect of commercial export farms on drought risk and adaptation of agropastoral communities in the drylands of Kenya, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-676, https://doi.org/10.5194/egusphere-egu24-676, 2024.

EGU24-1415 | PICO | HS5.3.3

Capturing geospatial data on farm management practices in vulnerable farmer-water systems: Lessons from the Sahel 

Nadir Ahmed Elagib, Bashir M. Ahmed, Hussein M. Sulieman, Abbas E. Rahma, Marwan M.A. Ali, and Karl Schneider

 Emphasis has been placed worldwide recently on the need to view social sensing and geospatial big data as an analogue of remote sensing data. The attempt to establishing a firm footing of this kind of data is essential, for example, to: 1) understand the complex coupling of human and natural systems and 2) make useful policy interventions related to sustainable land and water management. However, most vulnerable communities to natural disasters, whose livelihood and economies are dependent on farming, lack such data. Without suitable socio-economic and farm management data, agricultural governance becomes less responsive or even fails, particularly when the agricultural systems are affected by natural disasters. In this study, we highlight nine lessons learned from our first experience during extensive and comprehensive household surveys of farm management practices recently conducted in the arid and semi-arid zones of Sudan. The aim here is to offer guidelines for researchers and practitioners to carry out successful campaigns in similar settings. These campaigns were implemented as part of the DFG funded SHADRESS project, “Sociohydrological analysis of drought resilience in Sahelian Sudan farming systems”. The surveys were conducted by means of Information and Communication Technology (ICT) via smartphone app and traditional paper-based approach. Two hypotheses were assessed: First, the two survey methods can be integrated and utilized to generate direct and ongoing communication between farming stakeholders. Second, this stakeholder network and dialogue can help acquire big social datasets to fill the data gap within the agriculture sector and, subsequently, address water and food security. We categorize the lessons and guidelines as logistics, technology, culture and behavior related. More than 70 questions related to the socio-hydrological farming system were addressed. The surveys resulted in capturing responses from ~1640 households distributed over three farming systems, namely traditional rainfed, mechanized rainfed and irrigated systems. This dataset contains rich information to enable detailed spatial analyses of farm management strategies and understanding of generic concepts of farmer-water interactions in a drought-vulnerable region. 

How to cite: Elagib, N. A., Ahmed, B. M., Sulieman, H. M., Rahma, A. E., Ali, M. M. A., and Schneider, K.: Capturing geospatial data on farm management practices in vulnerable farmer-water systems: Lessons from the Sahel, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1415, https://doi.org/10.5194/egusphere-egu24-1415, 2024.

EGU24-4678 | ECS | PICO | HS5.3.3

Assessing the Impact of Climate Change on Water Scarcity in the Tormes ‎Catchment, Spain: A Human-Water System Modeling Approach 

Osama Gasimelseed Bakhit Hassan, C. Dionisio Pérez-Blanco, and Héctor González-López

Climate change presents a pressing challenge to global water availability resulting in ‎increased variability in precipitation and increased temperatures, imposing more stress ‎on existing water resources and the economic activities that depend on them. The ‎Tormes catchment, located in a semi-arid region, is facing increasingly severe water ‎shortages, which may be further aggravated under climate change. This catchment is ‎extensively employed for agricultural purposes, and a potential reduction in the ‎availability of water for irrigation emerges as a significant concern.‎
This study evaluates the impact of climate change on water availability, and the ‎responses implemented by irrigators to adapt to growing scarcity, in the Tormes ‎catchment. To this end, we develop a human-water system model that couples the Soil ‎and Water Assessment Tool (SWAT) model and a Positive Multi-Attribute Utility ‎Programming (PMAUP) model using a dynamic and modular approach. The coupled ‎model runs the water (SWAT) and human (PMAUP) system models iteratively and ‎over time using inputs from six different bias-corrected Global Climate ‎Models(GCMs) under CMIP6 scenarios, as follows: i) CMIP6 climate change scenario ‎simulations are fed to the SWAT model to estimate relevant hydrological data ‎including water availability in March (beginning of the irrigation campaign); ii) ‎information on water availability is fed to the PMAUP model to simulate the adaptive ‎responses of irrigators in terms of water and land allocation; iii) land and water use ‎choices by irrigators are fed into the SWAT model, which reproduces the ‎consequences of human decisions on the water system; iv) when the hydrological year ‎is over, a new iteration starts where CMIP6 climate change scenario simulations for ‎the following year are fed into the SWAT model and the process is repeated again. The ‎non-linearity and modular approach in both the hydrological and economic models ‎imply complex and interconnected interactions within these systems, with behaviors ‎that may or may not follow linear patterns.‎
Six bias-corrected GCMs under CMIP6 scenarios were employed for the climate ‎change scenario simulations. The dataset covered precipitation, maximum and ‎minimum temperatures for the historical period (1981–2010) and projections for ‎SSP245 and SSP585. Future data was analyzed for three periods: 2020–2039, 2040–‎‎2059, and 2060–2100. A multi-model ensemble approach was applied, averaging ‎outputs from the six models. Precipitation and temperature data were integrated into ‎the SWAT model.‎
The hydrological analysis revealed a downward trend in projected precipitation, with ‎reductions of 0.7% (2020s), 0.3% (2040s), and up to 5.3% (2060s) under SSP245. ‎SSP585 showed declines of 6.4% (2020s), 6.6% (2040s), and 16.1% (2060s). ‎Maximum and minimum temperatures exhibited an upward trend under both ‎scenarios. Simulated mean annual runoff under SSP245 experienced a drastic ‎reduction of 48.1% in the 2020s, followed by 43.8% (2040s) and 53% (2060s). ‎Similarly, under SSP585, mean annual runoff decreased by 47.2% over the entire ‎projection period. While the hydrological analysis reveals concerning trends in ‎precipitation, temperature, and mean annual runoff under different scenarios, the ‎economic results, reflecting the effects of these hydrological changes on human ‎activities, are still being investigated and are not yet finalized.‎

How to cite: Hassan, O. G. B., Pérez-Blanco, C. D., and González-López, H.: Assessing the Impact of Climate Change on Water Scarcity in the Tormes ‎Catchment, Spain: A Human-Water System Modeling Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4678, https://doi.org/10.5194/egusphere-egu24-4678, 2024.

EGU24-5621 | PICO | HS5.3.3 | Highlight

The Water System Explorer: understanding interactions between the natural and anthropogenic water system on a regional scale 

Marjolein van Huijgevoort, Sija Stofberg, Klaasjan Raat, and Ruud Bartholomeus

In the Netherlands the natural water system has been altered significantly to address human needs. Historically, the main water issues were related to water excess. However, recent dry years (2018-2020, 2022) have made it clear that drought affects many sectors as well. To deal with both extremes, a transition of the water system is needed with integral solutions.

Exploring the effects of measures needed to improve the water system is challenging and needs to be done in an integrated way that considers the natural water system as well as the anthropogenic influence on that system. Often these effects are investigated using complex, spatially-distributed models that usually don’t include all interactions between water users and the water system, have long calculation times and require a certain computer capacity. To attain a first crude estimate of the effects, it is also possible to use a different approach like system dynamics models. System dynamics models provide less details and include less spatial variation, but can include more interactions between the different subsystems and have short calculation times.

We have developed a system dynamics model, the Water System Explorer, that can be used to simulate the effect of human interventions on the water system. The Water System Explorer provides insight into the water system at a regional scale and can be used as a tool to support conversations between different stakeholders in a region. It is a strong simplification of reality, so it serves to give a first indication of potential measures and their effects, including trade-offs, in a specific region.

The Water System Explorer includes the natural and anthropogenic system. For the natural system, four different landuse types are defined: agriculture, urban area, groundwater-dependent nature and groundwater-independent nature. The phreatic groundwater level is determined for each land use type, which interacts with the surface water and deep groundwater. The anthropogenic system includes the water demand of industry and households, drinking water supply and a wastewater treatment plant. Several interventions are included, for example, a ban on water abstractions for agriculture, introducing separated sewers, increasing surface water levels, applying managed aquifer recharge and re-use of effluent in agriculture, industry, or drinking water supply.

The Water System Explorer has been applied for a region in the Netherlands. The tool reproduced general characteristics of the water system and illustrated the side-effects of water system interventions as a result of feedback mechanisms. The tool shows much potential for gaining insight into a regional water system to discuss measures with all stakeholders and for education purposes. 

How to cite: van Huijgevoort, M., Stofberg, S., Raat, K., and Bartholomeus, R.: The Water System Explorer: understanding interactions between the natural and anthropogenic water system on a regional scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5621, https://doi.org/10.5194/egusphere-egu24-5621, 2024.

Resilience has been defined as the ability of a system to withstand stressors while preserving its structure and functions. Various resilience assessment frameworks and metrics have been developed for understanding individual water system behaviour. However, in coupled human-water systems, the increased complexity presents new challenges in the application of these frameworks. This exploratory study first conducted a literature review on system performance indicators, failure thresholds, and resilience metrics, across urban water supply, drainage, wastewater, groundwater, and river systems. Challenges are identified in intercomparison between system performance indicators, robustness of thresholds selection, and resilience metrics synthesis as well as their applicability to inform water management. Based on the insights, a bottom-up resilience assessment framework for coupled human-water systems is developed. This framework sets double thresholds to characterise the vulnerable and critical systems state during a disruptive period. Four shape-based resilience metrics are designed and uniformly applied to various performance indicators to facilitate intercomparison between subsystems. The application of the metrics crosses temporal scales, from event-level assessments for understanding system behaviour to annual-level evaluations of system reliability, which are ultimately synthesised at the system level for multi-stakeholder decision-making. The efficacy of this framework is demonstrated through its application with the integrated water system model (WSIMOD) in Luton, UK, serving as a case study. The findings highlight river water quality as the least resilient subsystem that needs prioritised management. Sensitivity analysis is conducted to examine the robustness of results, with subsequent interpretation linking these metrics to specific design variables for enhanced management. This framework can be further applied with stakeholder engagement and multi-criteria analysis for more effective decision-making to achieve better system performance under deep uncertainties. 

 

How to cite: Mijic, A. and Liu, L.: An exploratory bottom-up resilience assessment framework for coupled human-water systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6073, https://doi.org/10.5194/egusphere-egu24-6073, 2024.

EGU24-7616 | ECS | PICO | HS5.3.3

Societal Pathways of Cooperation for Water-related Conflict Mitigation 

Elisie Kåresdotter, Zipan Cai, Haozhi Pan, and Zahra Kalantari

Over the past decade, water conflicts have risen, and cooperation has declined. Research highlights multiple factors driving this change, with climate change acting as a threat multiplier. Human activities, like dam construction and irrigation, and climate-induced hydro-climatic shifts, including extreme precipitation and prolonged droughts, contribute to the risk of increased water conflicts. To guide interventions and reverse this trend, our focus is on enhancing the understanding of factors that facilitate successful cooperation and mitigate water conflicts effectively. In this study, we investigate cooperation and conflict events worldwide in the last 70 years, together with climatic and socioeconomic factors, such as wealth, export dependency, demographics, water use, and hydro-climate trends. The dataset on cooperation and conflict events used is based on the Transboundary Freshwater Dispute Database and Water Conflict Chronology in combination with more current cooperation events extracted from media news reports. Relationships between investigated factors and cooperation are analyzed by combining panel data analysis and qualitative text content analysis of events. The results provide a deeper understanding of the factors behind why certain events are more successful in achieving conflict mitigation than others. We found that cooperation between countries struggling with water-related challenges can reduce expected conflicts over the next five years. The economic benefits of cooperation show a positive correlation between water-related cooperation and improved wealth (measured by GDP growth), particularly in countries with high export dependency. As such, economic collaboration can be an effective tool for enhancing resilience in high-water stress areas, where collaboration in these areas can contribute to a substantial reduction in future conflicts while simultaneously improving economic prosperity. Engaging in cooperation with other countries can therefore contribute to economic growth and resilience, as well as decreasing conflict risk. Understanding successful conflict mitigation factors can provide helpful insights to global policymakers and leaders in water management to avoid future conflict based on current and projected water availability.

 

Keywords: water conflict; collaboration; conflict mitigation; mixed methods; socioeconomic factors;

How to cite: Kåresdotter, E., Cai, Z., Pan, H., and Kalantari, Z.: Societal Pathways of Cooperation for Water-related Conflict Mitigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7616, https://doi.org/10.5194/egusphere-egu24-7616, 2024.

EGU24-9372 | ECS | PICO | HS5.3.3 | Highlight

Human drivers of flood losses in Europe since 1950 

Dominik Paprotny, Aloïs Tilloy, Michalis I. Vousdoukas, Heidi Kreibich, Luc Feyen, Oswaldo Morales Nápoles, and Matthias Mengel

Human drivers significantly influence flood occurrence and impacts  through multiple avenues. In this work, we explore how human drivers contributed to flood risk in 42 European countries between 1950 and 2020, with particular focus on 1504 historical floods that caused significant socioeconomic impacts. Our modelling chain covers both riverine and coastal floods and is able to reconstruct past extreme events including the influence of (1) human impact on catchment hydrology through changing land use, water demand and reservoir capacity, (2) increase in exposure related to land use change, demographic and economic growth, and evolving structure of the economy, and (3) changes in flood preparedness, exhibited by flood protection levels (primarily from structural defences) and flood vulnerability (relative loss at given intensity of hazard). The results indicate that although construction of large reservoirs (the number of which increased six-fold in the study area since 1950) has locally led to a pronounced decline in riverine flood risk, human alterations to catchments overall increased the flood risk in Europe due to land-use change, particularly through strong increase in soil sealing caused by urbanization. An even stronger relative effect on the increase in flood impacts is caused by exposure growth, consisting of population growth, particularly in cities, a rapid increase in gross domestic product per capita, and further compounded by growth in capital-to-income ratio. Exposure growth is more pronounced for coastal floods compared to riverine floods. On the other hand, historical flood impact data analysed in this study show evidence of improving preparedness over time. Flood defences currently protect against higher return periods of floods than before, particularly for coastal floods, though they are mostly much lower than assumed in previous pan-European studies. A decline in flood vulnerability (relative losses) over time is also observed, partially compensating for negative human influences on flood risk.

How to cite: Paprotny, D., Tilloy, A., Vousdoukas, M. I., Kreibich, H., Feyen, L., Morales Nápoles, O., and Mengel, M.: Human drivers of flood losses in Europe since 1950, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9372, https://doi.org/10.5194/egusphere-egu24-9372, 2024.

EGU24-9602 | PICO | HS5.3.3

Droughts influence changes in human settlement patterns in Africa 

Serena Ceola, Johanna Maard, and Giuliano Di Baldassarre

Human displacements due to climate and weather extremes are dramatically increasing worldwide, mainly across areas where extreme events interact with high vulnerability and low adaptive capacity, such that they are now recognized as a primary humanitarian challenge of the 21st century. Human mobility from droughts is multifaceted and depends on environmental, political, social, demographic and economic factors. Although droughts cannot be considered as the single trigger, they significantly influence people's decision to move. Yet, the ways in which droughts influence patterns of human settlements have remained poorly understood.

Here we explore the relationships between drought occurrences and changes in the spatial distribution of human settlements across 50 African countries for the period 1992–2013. Since long-term yearly data on human displacements are not consistently available for the entire African continent, we employ both country-based and spatially explicit data sets as reliable proxies. We base our continental study on urban population data and nighttime lights, as a proxy for the spatial and temporal distribution of human settlements. For each country, we evaluate annual relative urban population and human distance to rivers. To identify drought years, we extract annual drought occurrences from two indicators, the international disaster database EM-DAT and the standardized precipitation evapotranspiration index (SPEI-12) records. We then compute human displacements as variations in human distribution between adjacent years, which are then associated with drought (or non-drought) years. We finally examine the consistency between drought occurrences and changes in human settlement patterns to identify macroscopic trends at the continental scale.

Our results show that drought occurrences across Africa are often associated with (other things being equal) human mobility toward rivers or cities. In particular, we found that human settlements tend to get closer to water bodies or urban areas during drought conditions, as compared to non-drought periods, in 70%–81% of African countries.

This large-scale trend clearly highlights that the occurrence of drought events, although not being the single driving factor, significantly influences human mobility. By interpreting this outcome from a broader perspective, which includes consecutive drought-to-flood events, adverse consequences might occur. An increased human presence in urban areas and close to rivers may result into an increased human exposure to floods, and thus leading to a potentially increased flood risk. Therefore, further investigations are foreseen and encouraged to better understand the interplay between human mobility and climate change in order to increase the resilience of vulnerable areas and population to hydrological extreme events and support the development of sustainable and effective planning strategies for the near future.

How to cite: Ceola, S., Maard, J., and Di Baldassarre, G.: Droughts influence changes in human settlement patterns in Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9602, https://doi.org/10.5194/egusphere-egu24-9602, 2024.

EGU24-11342 | ECS | PICO | HS5.3.3

More Droughts, More Irrigation? Modeling the Adaptive Behavior of German Farmers to Hydrometeorological and Socioeconomic Change  

Jasmin Heilemann, Mansi Nagpal, Simon Werner, Christian Klassert, Bernd Klauer, and Erik Gawel

The shifting precipitation patterns and rising temperatures in Central Europe and Germany present an existential challenge for farmers. Recent severe summer droughts, such as those in 2003 and 2018, underscore the imperative for farmers to adapt to evolving climatic conditions, for instance through the application of irrigation in areas where it was previously unnecessary or economically unfeasible. However, expanding the currently only 3% irrigated agricultural area in Germany has the potential to significantly impact freshwater resources and hydrological processes.

Here, we model the adaptive behavior of farmers regarding irrigation, by employing an empirically validated multi-agent system (MAS) model. This model simultaneously simulates decisions about annual crop choices, acreages, and irrigation water application. Spatially disaggregated, the MAS model is calibrated using an Econometric Mathematical Programming (EMP) approach, based on historical land use data for eight major field crops. To account for the implications of future climate change, we couple the MAS model with a statistical crop yield model driven by meteorological indicators and soil moisture anomalies derived from the mesoscale Hydrologic Model (mHM) for a EURO-CORDEX scenario ensemble (RCP2.6, RCP4.5, RCP8.5). Socioeconomic variables that influence farmers' decisions, including changes in crop prices, costs, and subsidies, are projected based on Shared Socioeconomic Pathway (SSP) scenarios.

Across various combinations of SSP and RCP scenarios, we find a notable surge in irrigation water demand. This development is particularly pronounced in SSP3-RCP8.5, where the MAS model projects several irrigation hotspots with a high irrigation water demand. Shifts in cropping patterns thereby significantly affect the resulting irrigation water demand. To dissect the effects of hydrometeorological, socioeconomic, and policy changes on irrigation water demand, we conduct sensitivity analyses on individual parameters.

The MAS model emerges as a robust tool for analyzing farmers' adaptive behavior and assessing the impact of diverse policies on future irrigation water demand. This research contributes valuable insights into agricultural adaption under changing environmental and socioeconomic conditions.

How to cite: Heilemann, J., Nagpal, M., Werner, S., Klassert, C., Klauer, B., and Gawel, E.: More Droughts, More Irrigation? Modeling the Adaptive Behavior of German Farmers to Hydrometeorological and Socioeconomic Change , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11342, https://doi.org/10.5194/egusphere-egu24-11342, 2024.

EGU24-11646 | ECS | PICO | HS5.3.3

Correlation of Social Media-Driven Risk Perception and Flood Insurance Uptake for Floods in the US 

Nadja Veigel, Heidi Kreibich, Jens de Bruijn, Jeroen C.J.H. Aerts, and Andrea Cominola

Social media platforms play a key role in enhancing human response to natural hazards. They serve as tools for individuals to share first-hand observations, insights, and experiences, thus contributing to improved resilience. Increased attention of social and communication media content toward natural hazards has the potential to foster take up of private precaution and resilience measures such as purchasing a flood insurance. This study investigates the driving factors behind flood insurance purchase decisions in the US, with a focus on the roles of risk perception and social media as potential drivers for such decisions. We investigate the relationship between household flood insurance uptake and social media attention for flood events that occurred in the continental US from 2014 to 2021. We argue that the surge in insurance uptake in counties affected by flood events is primarily attributed to heightened risk perception resulting from direct exposure to flooding and from citizens’ awareness due to exposure to flood related information. We compare the time series of insurance take-up rate in a county with the number of flood-related social media posts in the adjacent counties using Dynamic Time Warping, which measures the similarity between two time series by optimally aligning their temporal structures. Additionally, we control for time passed since the last flood as well as the number of communities participating in the Community Rating System since these factors have shown to be important drivers of insurance uptake and may otherwise distort the temporal patterns associated to social media exposure. With our data-driven analysis we first evaluate the correlation between exposure to flood-related content on platforms like X (formerly Twitter) and an increased likelihood of purchasing flood insurance. Consecutively, we quantify variations in risk perception and resilience due to exposure to flood-related content on social media. This analysis provides a comprehensive view of risk communication through social media and its implications for resilience-building efforts.

How to cite: Veigel, N., Kreibich, H., de Bruijn, J., Aerts, J. C. J. H., and Cominola, A.: Correlation of Social Media-Driven Risk Perception and Flood Insurance Uptake for Floods in the US, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11646, https://doi.org/10.5194/egusphere-egu24-11646, 2024.

EGU24-11816 | ECS | PICO | HS5.3.3

Modeling heterogeneous farmers' response to climate change via agent-based simulation 

Paolo Gazzotti, Sandra Ricart, Claudio Gandolfi, and Andrea Castelletti

Farmers' risk preferences significantly shape their decision-making processes, influencing key strategies like crop selection and irrigation practices. Concurrently, climate change poses significant threats to agricultural activities, necessitating an in-depth examination of coupled human-nature systems. Farmers perceive changes in climate patterns, such as severe and more frequent droughts, but their reactions to these changes may be highly heterogeneous, influenced by factors such as individual risk aversion, satisfaction, uncertainty, interaction and comparison with other farmers. Agent-based modeling (ABM) has emerged as a powerful tool to capture the complexities of agricultural systems and simulate the interactions between farmers, their environment, and climate change. However, despite increasing calls to incorporate realistic human behavior, the prevailing paradigm remains the use of representative rational agents.

This study presents an ABM application in the Adda River basin, Italy, where agents represent farmers who make decisions on crop type and irrigation method. The main goal is to understand how the system reacts and withstands the impact of emerging climate-change-driven scenarios. The study attempts to find a more realistic approach to agents' decision-making by implementing different behavioral models. The first model assumes profit maximization under perfect foresight, a traditional approach commonly used in ABM literature. The second model introduces uncertainty about future climate conditions and heterogeneity in farmers' risk aversion preferences on the basis of past performances. The third model embraces a more comprehensive approach to behavioral modeling, incorporating behavioral concepts such as reference points and loss aversion. This model acknowledges that farmers' decision-making is not solely guided by profit maximization, but also influenced by their prior experiences, perceptions of losses, and the potential for regret. This more comprehensive approach aims to offer a more comprehensive representation of farmers' decisions on crop selection and irrigation practices, under conditions of uncertainty and risk.  Agents’ individual preferences have been calibrated using survey data from the domain’s field.

Implementing these different decision modules, we tested the agents’ response to various climate change scenarios, including historical conditions and future projections for representative storylines. Preliminary results reveal notable differences in system dynamics and resilience across the behavioral models and risk aversion levels. These findings provide insights into the appropriateness of behavioral modeling tools for understanding agricultural decision-making under evolving climatic conditions.

How to cite: Gazzotti, P., Ricart, S., Gandolfi, C., and Castelletti, A.: Modeling heterogeneous farmers' response to climate change via agent-based simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11816, https://doi.org/10.5194/egusphere-egu24-11816, 2024.

EGU24-12542 | ECS | PICO | HS5.3.3 | Highlight

Too little or too dirty? Global modelling framework for analyses of sectoral water use responses under droughts and heatwaves 

Gabriel Antonio Cárdenas Belleza, L.P.H. (Rens) van Beek, Marc F.P. Bierkens, and Michelle T.H. van Vliet

Drought-heatwave events increase water use mainly for domestic and irrigation water use sectors (Cárdenas et al., 2023). Moreover, water quality deterioration caused by human activities is exacerbated by more frequent and longer-lasting extreme hydro-climatic events, such as droughts and heatwaves. These circumstances challenge the supply of water of suitable quality and increase the cross-sectoral competition forclean water.

Water use models are useful in estimating responses in water demand and use ‑in terms of consumption and withdrawals‑ of the main water use sectors (i.e., irrigation, livestock, domestic, energy and manufacturing); however, there are few water use models that account for both water quantity and quality dimensions simultaneously. The main objective of our research is to assess the cross-sectoral water deficit due to sectoral competition for limited clean water resources, explicitly considering water quantity and water quality requirements.

To address this objective a new sectoral water use model framework has been developed, that evaluates simultaneously water quantity and water quality requirements for the main water use sectors. This globally applicable model framework builds on the PCR-GLOBWB 2 hydrological model (Sutanudjaja et al, 2018) and DynQual v1.0 global surface water quality model (Jones et al, 2023), which simulates surface water temperature, salinity as indicated by total dissolved solids (TDS), organic pollution as indicated by biochemical oxygen demand (BOD), and pathogen pollution as indicated by faecal coliform (FC).

Preliminary results show that high salinity (TDS) is the predominant water quality constituent limiting water use for irrigation most of the year; while for the domestic sector it is organic pollution, particularly in regions with limited water treatment capacities. For such sectors, accounting for water quality requirements lead to substantial reductions in surface water withdrawals over the Conterminous United States when compared to results obtained from only water quantity-based models.

This modelling framework provides the basis for an integrated water scarcity assessment driven by changes in water quantity and quality under current and future droughts and heatwaves.

References

Cárdenas B., G.A., Bierkens, M.F.P., van Vliet, M.T.H.: Sectoral water use responses to droughts and heatwaves: analyses from local to global scales for 1990-2019. Environ. Res. Lett. 18 104008. https://doi.org/10.1088/1748-9326/acf82e, 2023.

Sutanudjaja, E. H., van Beek, L. P. H., de Jong, S. M., van Geer, F. C., and Bierkens, M. F. P.: Calibrating a large-extent high-resolution coupled groundwater-land surface model using soil moisture and discharge data, Water Resour. https://doi.org/10.5194/gmd-11-2429-2018, 2018.

Jones, E. R., Bierkens, M. F. P., Wanders, N., Sutanudjaja, E. H., van Beek, L. P. H., and van Vliet, M. T. H.: DynQual v1.0: a high-resolution global surface water quality model, Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, 2023.

How to cite: Cárdenas Belleza, G. A., van Beek, L. P. H. (., Bierkens, M. F. P., and van Vliet, M. T. H.: Too little or too dirty? Global modelling framework for analyses of sectoral water use responses under droughts and heatwaves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12542, https://doi.org/10.5194/egusphere-egu24-12542, 2024.

EGU24-13415 | PICO | HS5.3.3

Carbonate deposits from historical aqueducts in urban area: an archive for human impact on water management and quality 

Edwige Pons-Branchu, Philippe Branchu, Arnaud Dapoigny, Eric Douville, Emmanuel Dumont, Mathieu Fernandez, Alexino Progam, and Liliane Jean Soro

We have developed a methodology for constructing diachronic views of the chemical state of water that infiltrates soils and forms perched aquifers in the north and south of Paris (France). These waters have been drained for centuries and distributed by historic underground aqueducts. The CaCO3 layers deposited by these waters in the aqueducts have been studied.

The first challenge is to construct chronologies of these deposits, using uranium-thorium or 14C chronometers and/or lamina counting.

Past water quality has been reconstructed using trace elements measured along the growth axis of CaCO3 deposits, combined with isotope analysis (lead, sulfur and strontium) and, in some cases, carbon isotopes.

With this methodology, we demonstrate that in Paris, over the last 300 years, the transformation of land use is the most important factor affecting water quality, not only through the presence or absence of building industries, but also through the use of certain materials for construction or embankment. 

We use this methodology for the study of ancient aqueducts in archaeological sites to discuss water provenance and quality.

How to cite: Pons-Branchu, E., Branchu, P., Dapoigny, A., Douville, E., Dumont, E., Fernandez, M., Progam, A., and Jean Soro, L.: Carbonate deposits from historical aqueducts in urban area: an archive for human impact on water management and quality, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13415, https://doi.org/10.5194/egusphere-egu24-13415, 2024.

EGU24-15100 | ECS | PICO | HS5.3.3

A comprehensive inventory of large hydropower systems in the Italian Alpine Region 

Soroush Zarghami Dastjerdi, Andrea Galletti, and Bruno Majone

The threat of climate change and water resource overexploitation to river network ecosystems and their natural flows is evident, particularly in mountainous regions where hydropower production is also responsible for significant alterations of the natural streamflow. Hydrological modeling in these watersheds is hindered by limited knowledge of technical and geometrical information. Key characteristics and parameters related to hydropower operating schedule and their hydraulic infrastructures are usually hard to obtain as they are mostly confidential data producers hold. Consequently, modeling hydropower systems over large domains often relies on simplified methods which may decrease the reliability of these studies. In response to these challenges, we created a comprehensive inventory designed to model the interaction between natural stream networks and hydropower-related infrastructures at the mesoscale. This inventory, tailored for the large hydropower systems in the northern mountainous region of Italy (Italian Alpine Region - IAR), includes detailed hydraulic parameters essential for the reliability of water-energy-nexus modeling implementations. The selected region includes over 300 large hydropower systems with complex infrastructures, among those, nearly 160 plants are reservoir-fed, causing a significant alteration in streamflow. To assess the reliability of the provided inventory, we employed HYPERstreamHS as the reference hydrological model. We assessed the accuracy of our designed inventory by comparing the modelled hydropower production with the finest observations available, which are province-aggregated monthly hydropower production data from 1995 to 2008. The outcomes revealed a commendable similarity ranging from 83% to 100% across simulated areas, with an overall average of 90%, solidly confirming the accuracy of the crafted inventory.

How to cite: Zarghami Dastjerdi, S., Galletti, A., and Majone, B.: A comprehensive inventory of large hydropower systems in the Italian Alpine Region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15100, https://doi.org/10.5194/egusphere-egu24-15100, 2024.

EGU24-1795 | Orals | EOS4.5

Engaging with geoscientists’ conference mobility: a living lab approach 

Simone Rödder, Ella Karnik Hinks, Max Braun, and Youssef Ibrahim

Conference attendance forms a key part of academic life (Arsenault et al. 2019; Lassen 2022) and scholars of science have pointed to its functions for individual careers as well as for advancing knowledge production and integration Yet mega-conferences, such as EGU, constitute a significantly carbon-intensive aspect of scientific work, with estimates that the American counterpart, AGU, has a carbon footprint similar to that of the city of Edinburgh in one week (Klöwer et al. 2020). Advocating for sustainable transformations while simultaneously relying on air travel for mobility thus exposes academia, and especially climate scientists, to accusations of hypocrisy (Dey and Russell 2022, Nordhagen et al. 2014). How do geoscientists navigate the dilemma created by the competing demands of attending conferences for their scholarly, social, and professional development and their desire to lead an exemplary pathway?

By using the space of this session at EGU as a ‘living lab’, we as social scientists want to engage with geoscientists, gather their perceptions of academic travel and reflect on their own position in this incongruous mode of knowledge exchange. We will employ interactive methodologies such as Mentimeter mini-surveys and focused discussions to introduce reflective questions that geoscientists can ask themselves regarding the sociocultural aspects of conference attendance, the perceived impact on academic reputation, the challenges faced by early career scientists, and the complex navigation of the environmental tensions associated with high carbon footprint meetings. This contribution is informed by a research project that studies and compares academic conference and travel cultures across disciplines.  

References

Arsenault, Julien; Talbot, Julie; Boustani, Lama; Gonzalès, Rodolphe; Manaugh, Kevin (2019): The environmental footprint of academic and student mobility in a large research-oriented university. In Environ. Res. Lett. 14 (9), p. 95001. DOI: 10.1088/1748-9326/ab33e6.

Colin Dey; Shona Russell (2022): Still Flying in the Face of Low-carbon Scholarship? A Final Call for the CSEAR Community to Get on Board. In Social and Environmental Accountability Journal 42 (3), pp. 208–222. DOI: 10.1080/0969160X.2022.2094983.

Klöwer, Milan; Hopkins, Debbie; Allen, Myles; and Higham, James (2020): An analysis of ways to decarbonize conference travel after COVID-19. In Nature 583, pp. 356–359. DOI: 10.5281/ZENODO.3553784.

Lassen, Claus (2022): Aeromobilities and Academic Work. In Kristian Bjørkdahl (Ed.): Academic Flying and the Means of Communication. With assistance of Adrian Santiago Franco Duharte. Singapore: Springer Singapore Pte. Limited, pp. 269–296.

Nordhagen, Stella; Calverley, Dan; Foulds, Chris; O’Keefe, Laura; Wang, Xinfang (2014): Climate change research and credibility: balancing tensions across professional, personal, and public domains. In Climatic Change 125 (2), pp. 149–162. DOI: 10.1007/s10584-014-1167-3.

How to cite: Rödder, S., Karnik Hinks, E., Braun, M., and Ibrahim, Y.: Engaging with geoscientists’ conference mobility: a living lab approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1795, https://doi.org/10.5194/egusphere-egu24-1795, 2024.

EGU24-4006 | ECS | Orals | EOS4.5

What responsibilities of geosciences in the turmoil of the Anthropocene? Example of a political ecology perspective. 

Gabriel Hes, Jean-Michel Hupé, Sylvain Kuppel, Iris-Amata Dion, Laure Laffont, and Marieke Van Lichtervelde

Given the ever-widening gap between current policies and the socio-economic transformations required to mitigate and adapt to the ongoing environmental and related social upheaval, a growing number of academics question their role within and beyond academia. Geoscientists are holding important responsibilities, some of them they could be regarded as accountable for: if, on the one hand, they bring strong disciplinary knowledge on climate change, and they contribute to modeling scenarios of socio-economic trajectories (and, therefore, sociological imagination); on the other hand, as geological survey is key to fossil fuel exploration and minerals extraction, they have close relationships with companies and institutions that are threatening the habitability of the planet. Accepting those responsibilities means a significant departure from the research-as-usual stance, which defines a barrier between knowledge and how society uses that knowledge. Geoscientists who do not consider such a barrier as relevant may act in many different ways, such as taking moral positions in the professional arena, learning from humanities within interdisciplinary studies, or adopting a situated knowledge standpoint in place of the illusory principle of scientific neutrality. We should emphasize that these behaviors do not necessarily undermine scientific integrity. But they do reflect an epistemic view different from research-as-usual, and which requires learning and careful practices. Under the Atécopol acronym (“Atelier d’écologie politique”), the Toulouse Studies in Political Ecology is a network of academics created 5 years ago to experiment those practices. The Atécopol collectives (now about 7 in France) take a political ecology perspective, in which environmental issues necessarily imply socio-economical choices. These choices convey representations and value systems that require scientists to take a reflexive and situated stand. The collectives bring together a diversity of disciplines and professional status, with the aim to create bridges between scientific knowledge and social and political debates at a regional scale and beyond. As such, they constitute an alternative way to conduct scientific research leveraging conscious, transformative actions: an ethical posture, transdisciplinarity, horizontality and reflexivity. The Atécopol collectives therefore intend to transform local organizations and institutions within the research community, and more broadly within society as a whole. The actions undertaken so far by the Atécopol collectives include (i) knowledge circulation, such as, training, communication and scientific events, (ii) appeals to the general public in the form of opinion columns and petitions, (iii) initiating local interdisciplinary research projects and (iv) challenging research policies. Here, we intend to share the outcomes of these experiences in order to pause, reflect upon and radically question research-as-usual in the field of geoscience.

How to cite: Hes, G., Hupé, J.-M., Kuppel, S., Dion, I.-A., Laffont, L., and Van Lichtervelde, M.: What responsibilities of geosciences in the turmoil of the Anthropocene? Example of a political ecology perspective., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4006, https://doi.org/10.5194/egusphere-egu24-4006, 2024.

EGU24-8098 | Posters on site | EOS4.5

From carbon footprint to transition plan in a French geosciences laboratory 

Emilie Jardé, Laure Guérit, Val Kaupp, Annick Battais, Pierre Dietrich, Marion Fournereau, Géraldine Gourmil, Laurent Jeanneau, and Frédérique Moreau

As people from a research lab, we are committed to participate in limiting the increase of Earth's average temperature and try to resolve this dilemma: how can we carry on producing knowledge and ideas in a world of limited resources. We are aware of the need for an environmental transition that would be achieved for our professional aspect/life by a profound evolution of our research practices (ie: French CNRS ethics committee: “integrating environmental issues into research practices_ an ethical responsibility”, opinion n° 2022-43).

The Sustainable Development & Social Responsibility working group of the research laboratory “Géosciences Rennes” was created in 2021 to (i) estimate the annual C footprint by using GES1.5 (Research Consortium Laboratory 1.5) protocol, (ii) propose awareness-raising and training initiatives and communicate, (iii) propose actions to reduce our environmental impacts. Based on the GES1.5 toolkit, we have determined our environmental impact from 2019 to 2022 through the calculation of the C footprints of 3 main domains: purchases, scientific missions and operation of the premises whose respective C footprint are 879, 520 and 708 and 775 T CO2eq, corresponding to 5.8, 3.6, 5.1 and 5.1 T CO2eq/person. The purchase of goods and services is the main item, representing 48 ± 7 % (mean ± SD) of the total C footprint over the 4 years. Scientific missions represent 16 ± 8 %. Sanitary restrictions induced a drastic decrease of this C footprint in 2020 and 2021, but it has resumed and increased since.

These data were the corner stone of collaborative workshops (participatory workshops, surveys, suggestion boxes…) to invent our low-carbon laboratory and to vote a transition plan based on specific actions to collectively reduce the C footprint. The propositions do not intend to limit freedom to carry out research, but at transforming the way we do research to adapt to environmental constraints our societies are facing. 36 propositions were submitted to vote in autumn 2023 and 89% of the staff (about 150 persons) expressed an opinion. 26 propositions received more than 50% of “yes”, and will therefore be gradually implemented over 6 years (2024-2030) as the reduction targets are set for 2030 (ambition: -45% compared with 2019). The trajectory and relevancy of the adopted propositions will be re-evaluated annually by calculating the laboratory's C footprint.

Our experience shows that appropriation of the issues takes time, which we no longer have. It emphasizes the need to go further than awareness measures. In addition, working at the lab level results in an average that conceals the considerable heterogeneity in terms of staff status, thematic profiles and methods used (observation/experimentation/ modelling). Such heterogeneity generates a plurality of situations and it is uneasy to define just only strategy. More precise C footprints need to be defined, potentially on a one by one discipline basis, in order to identify avenues of research that will enable these disciplines to adapt to the conditions of a post-transition society.

How to cite: Jardé, E., Guérit, L., Kaupp, V., Battais, A., Dietrich, P., Fournereau, M., Gourmil, G., Jeanneau, L., and Moreau, F.: From carbon footprint to transition plan in a French geosciences laboratory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8098, https://doi.org/10.5194/egusphere-egu24-8098, 2024.

EGU24-8836 | ECS | Orals | EOS4.5

Climate Change Competence Needs in the Society 

Joula Siponen, Marianne Santala, Janne Salovaara, Sakari Tolppanen, Veli-Matti Vesterinen, Jari Lavonen, Katja Anniina Lauri, and Laura Riuttanen

The role of geoscientists is evolving in response to the changing world and the crises we are facing. Geoscientists, whom some of us authors identify as, possess crucial insight into phenomena of existential relevance. However, we seem to lack agency to contribute to the urgently needed transformation. Inspired by the question of what society demands, especially regarding climate change expertise, we approached individuals who play important roles in mitigation and adaptation in their organisations across different sectors of Finnish society. Using qualitative methodology, including a questionnaire to fifty-eight and in-depth expert interviews with twenty-four professionals—we developed a competency framework. This framework aims to support the development of higher education and continuous learning that is based on research and scientific knowledge on climate change and addresses the needs of society.

Our study revealed six categories of competencies: systemic climate change insight; visions and strategies in changing climate; compassionate climate leadership; active engagement in networks; courage and determination in climate action; and climate values and justice. These categories represent a combination of skills, knowledge, and attitudes useful for individuals aiming to drive climate change action, but also as basis for developing collective competence. For instance, a geoscientist might have strong systemic insight based on their training, but may lack compassionate leadership skills, meaning either that further education is needed or a group of differently skilled experts could fill the gaps to form a climate-competent team.

Competent experts and professionals must be educated hand in hand with societal transformation. Therefore education must be transdisciplinary, involving a multitude of actors and stakeholders. To respond to the societal needs, University of Helsinki is developing new continuous education to professionals in the field and a two-year 60-credits Specialisation programme in climate expertise is planned to start in spring 2024. 

How to cite: Siponen, J., Santala, M., Salovaara, J., Tolppanen, S., Vesterinen, V.-M., Lavonen, J., Lauri, K. A., and Riuttanen, L.: Climate Change Competence Needs in the Society, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8836, https://doi.org/10.5194/egusphere-egu24-8836, 2024.

EGU24-9536 | ECS | Orals | EOS4.5 | Highlight

Going Beyond Research: A Large-scale Investigation of Climate Change Engagement by Scientists 

Fabian Dablander, Maien Sachisthal, Viktoria Cologna, Noel Strahm, Anna Bosshard, Nana-Maria Grüning, Alison Green, Cameron Brick, Adam Aron, and Jonas Haslbeck

Climate change is one of the greatest threats facing humanity. Scientists are well-positioned to help address it beyond conducting academic research, yet little is known about their engagement with the issue. We investigate scientists’ engagement with climate change using quantitative and qualitative analyses of a large-scale survey (N = 9,220) across 115 countries, all disciplines, and all career stages. We explore their beliefs about the role of scientists and scientific institutions in the context of climate change as well as their engagement in climate actions. These actions include forms of advocacy and activism ranging from signing petitions to engaging in civil disobedience and high-impact lifestyle changes such as reducing flying or adopting a plant-rich diet.

We find, for example, that 91% of surveyed scientists believe that fundamental changes to social, political, and economic systems are needed to address climate change; that a large majority of scientists feel a responsibility as scientists to address climate change; that more scientists agree than disagree that scientists should become more involved in advocacy and protest; and that the proportion of scientists who say they are willing to engage in these actions is substantial, suggesting that there is great potential for increased engagement by scientists on climate change beyond research. We also find that climate researchers engage in considerably more climate advocacy and activism than their peers in other research fields, but that this difference is significantly smaller for high-impact lifestyle changes.

Based on the qualitative and quantitative responses to our survey, we propose a two-stage model of engagement in advocacy and protest: Scientists must first overcome intellectual barriers (e.g., low levels of worry, lack of efficacy beliefs, lack of identification with activists) and practical barriers (e.g., lack of skills, fear of losing credibility, fear of repercussions) to be willing to engage, and then additional barriers (e.g., lack of time, lack of opportunity, not knowing any groups) to actually engage. Based on this model, we provide concrete recommendations for increasing scientists’ engagement with climate change.

Paper I: https://osf.io/preprints/psyarxiv/73w4s
Paper II: https://osf.io/preprints/psyarxiv/5fqtr

How to cite: Dablander, F., Sachisthal, M., Cologna, V., Strahm, N., Bosshard, A., Grüning, N.-M., Green, A., Brick, C., Aron, A., and Haslbeck, J.: Going Beyond Research: A Large-scale Investigation of Climate Change Engagement by Scientists, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9536, https://doi.org/10.5194/egusphere-egu24-9536, 2024.

EGU24-9671 | Posters on site | EOS4.5

Geosciences for a Sustainable Planet: a new collaborative network to address societal and environmental challenges in the Anthropocene 

Juan Antonio Ballesteros-Canovas, Emilio L. Pueyo, Blas Valero Garcés, Concepción Ayala, Angeliki Karanasiou, Juan Tomás Vázquez Garrido, José María González-Jiménez, Eva Calvo, María del Pilar Mata Campo, José Javier Álvaro Blasco, and Ana Moreno

The Geosciences for a Sustainable Planet network is an initiative reinforced by the recent integration of the Spanish Geological Survey (IGME) and the Oceanographic Spanish Institute (IEO) within the Spanish Scientific Research Council (CSIC). The network is aimed to provide Geosciences in Spain with a collaborative framework, to maximize synergies and address sustainability and future challenges with a planetary perspective. The network shares the strategic vision for the study and care of planet Earth as the only home available for our future, as embraced by many international organizations (e. g. the European Geosciences Union (EGU), United Nations Environment Programme (UNEP), International Union of Geological Sciences (IUGS), and the European Marine Board (EMB)).

In Spain, Geosciences have played a fundamental role in properly assessing, managing, and seeking solutions for several natural and anthropogenic crises, e.g. the oil spill after the sinking of the Prestige petroleum vessel, the dumping of toxic mine sludge in Aznalcóllar, the eruption of the Cumbre Vieja volcano in La Palma island, the 2011 earthquake of Lorca, the environmental collapse of the Mar Menor oastal lagoon, or the decline in the groundwaters of Doñana National Park. Geoscientists have engaged as first responders with government agencies in emergency situations. Besides, geosciences is providing essential knowledge for public administration, as well as energy and mineral resources companies, water supply, contamination and waste elimination and reuse, and adaptation to geological and natural hazards. The network will enhance the capacity of the CSIC to respond to both, societal and public administration demands.

Geosciences also provide the temporal and spatial scale to place current climate and environmental crises in the appropriate context. The network will implement outreach activities to illustrate the interactions of surface processes and biosphere with climatic fluctuations, atmospheric CO2 variations, sea-level changes, biodiversity collapses, etc, during the evolution of life on Earth over millions of years. We believe an essential aspect of science's contribution to sustainability is improving the communication of trans-disciplinary knowledge to citizens, future generations, administrations, and companies so they can take informed decisions. The Geoscience network will focus on outreach actions, training new generations of Geoscientists and technology and knowledge transfer.

The Geosciences network seeks to facilitate the integration of research groups in the disciplines of Earth Sciences to improve our knowledge of the planet's geological processes across temporal scales ranging from millions of years to instrumental observation. This integration of basic and applied knowledge will enable Geosciences to provide tools to address the social challenges of the UN Sustainable Development Goals. Among them, we have selected four main areas: (1) energy and ecological transition, (2) access to water and geological resources, (3) mitigation and adaptation to geological hazards and risks, and (4) tools for solving environmental and climate crises. We believe that Geosciences network will offer the spatial dimension (from local to planetary) and temporal insight (natural variability beyond the human scale) to provide a common framework with a global, integrative, transversal, and multidisciplinary vision to tackle these challenges.

How to cite: Ballesteros-Canovas, J. A., Pueyo, E. L., Valero Garcés, B., Ayala, C., Karanasiou, A., Vázquez Garrido, J. T., González-Jiménez, J. M., Calvo, E., Mata Campo, M. P., Álvaro Blasco, J. J., and Moreno, A.: Geosciences for a Sustainable Planet: a new collaborative network to address societal and environmental challenges in the Anthropocene, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9671, https://doi.org/10.5194/egusphere-egu24-9671, 2024.

EGU24-9910 | Posters on site | EOS4.5

An example of reflexive and ethical work on a geoscientific speculation bubble: the case of natural hydrogen 

Odin Marc, Loïs Monnier, and Mickael Coriat

Recently, in the context of intensifying calls for a rapid decarbonation of the economy and energy systems, there has been a growing interest in developing the use of hydrogen, either as a fuel or as an energy storage system. However, hydrogen production suffers from various drawbacks, due to its carbon footprint or cost, which has led the field of geosciences to renew its interest in the possibility to collect naturally occurring hydrogen (so called "white hydrogen"), found in gas reservoirs or in hydrothermal waters for example, or stimulate natural production of hydrogen before harvesting it (so called "orange hydrogen").
Querying the Web of Science database, the average number of annual scientific publications including "natural hydrogen" in their title or abstract, was steady around 2 between 1984 and 2016, it was 6 over 2017-2019, 16 over 2020-2022 and reaching 27 in 2023, thus appearing to follow an exponential growth. Similarly in media in France we retrieved 37 articles mentioning "natural hydrogen" between 2010 and 2019, with terms such as "infancy", "pilot project" or "future energy?" , while there were 44 between 2020-2022 and 227 in 2023 alone, with terms such as "rush", "game changer", "revolution" or "bright hopes".
This exponential growth and the rapid shift toward very enthusiastic vocabulary make us hypothesize that the rising interest in natural hydrogen is a process similar to an economic bubble, in which a commodities is over-valued during a transient period.
In this work we will present reflexive work based on an analysis of the recent scientific literature and on associated media coverage, on basic comparisons between energy available from recent H2 fluxes or estimated reservoirs and from other renewable energy sources, and on semi-directive interviews of some geoscientist specialists of hydrogen.
These elements allow us to confront this hypothesis and to gain insights on the intertwined effects that may favor the over-valuation of natural hydrogen. In particular, we also discuss reasons why geoscientists contribute, actively or not, to the growth of a speculative bubble, a mechanism generally associated with irrational market dynamics. We do so by exploring the potential roles of undeclared conflicts of interests, temptation to access facilitated research funding, lack of interdisciplinary analysis, and of the predominant belief that technological innovation or adjustments is needed and sufficient to address the ecological emergencies.

How to cite: Marc, O., Monnier, L., and Coriat, M.: An example of reflexive and ethical work on a geoscientific speculation bubble: the case of natural hydrogen, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9910, https://doi.org/10.5194/egusphere-egu24-9910, 2024.

EGU24-11035 | Orals | EOS4.5

ClimarisQ: A game on the complexity of the climate systems and the extreme events 

Davide Faranda and the ClimarisQ team

ClimarisQ is a smartphone/web game from a scientific mediation project that highlights the complexity of the climate system and the urgency of collective action to limit climate change. It is available in four languages: English, French, Spanish and Italian. It is an app-game where players must make decisions to limit the frequency and impacts of extreme climate events and their impacts on human societies using real climate models. ClimarisQ is a game conceived by the CNRS researcher Davide Faranda through the CNRS – AMCSTI – ISC-PIF scientific mediation incubator on complex systems. The development of ClimarisQ, powered by the videogame company Opal Games, has been financially supported by the University of Paris-Saclay : La Diagonale Paris-Saclay.

The goal of the game is to explore the effects of mitigation and adaptation choices to extreme climate events at the local, regional and global levels. Can you achieve a greener trajectory than the IPCC RCP 4.5 emission scenario by playing ClimarisQ? Explore the feedback mechanisms (notably physical, but also economic and social) that produce extreme effects on the climate system.

In the game, you make decisions on a continental scale and see the impact of these decisions on the economy, politics and the environment. You will have to deal with extreme events (heat waves, cold waves, heavy rainfall and drought) generated by a real climate model. Then, you will have to try to balance the “popularity”, “ecology” and “finance” gauges as long as possible. Fulfill all the missions to explore different climates. The game-over displays both the PPM (parts per million) of CO2 deviation from the intermediate scenario of greenhouse gas emissions established by the IPCC (RCP4.5), as well as the number of survival game turns. These elements stimulate thinking about climate change and motivate the player to do better next time. Thanks to the hazards introduced by the extreme events and cards, every game is different!

How to cite: Faranda, D. and the ClimarisQ team: ClimarisQ: A game on the complexity of the climate systems and the extreme events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11035, https://doi.org/10.5194/egusphere-egu24-11035, 2024.

EGU24-11091 | Posters on site | EOS4.5 | Highlight

Climate Horizons: a graphic novel of key IPCC findings to reach a wider audience 

Iris-Amata Dion and Xavier Henrion

For over 30 years, the Intergovernmental Panel on Climate Change (IPCC) has been synthesizing the state of scientific knowledge on global climate change and communicating it through a series of reports. These reports highlight both the responsibility of humans in triggering this rapid climate change and the direct threat it represents for living organisms including humans. However, despite being freely available to all, many still lack basic understanding of the climate system and the associated anthropogenic forcings. One explanation to this is that these reports are not made intelligible to people outside the academic world and the decision-making sphere. The graphic novel format offers the advantage to blend art and science, making it easier for non-scientific readers to access the information contained in the IPCC reports. Therefore, we proposed an alternative way of presenting the IPCC findings through the collaboration between a climate scientist and a cartoonist. We interviewed 9 authors of the three main IPCC working groups to present the content of these reports in an accessible and intelligent graphic novel named Climate Horizons


In the story, two main characters engage in a dialogue with these IPCC co-authors allowing them to discover the complexity of natural ecosystems, climate inaction and political power struggles. While explaining their field of study, each author shares a vision of what their role as geoscientists should be in the face of urgent climate and environmental issues. Over the course of the story, the main characters gradually change the way they see the world, and go through a range of emotions (shock, denial, anger, acceptance, etc.) as they become aware of the major problem of climate change.

This approach by committed citizens and researchers responds to the need to be informed about possible solutions and encourages individual and collective reflection to imagine new possible horizons.

How to cite: Dion, I.-A. and Henrion, X.: Climate Horizons: a graphic novel of key IPCC findings to reach a wider audience, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11091, https://doi.org/10.5194/egusphere-egu24-11091, 2024.

EGU24-11357 | Orals | EOS4.5

Is the definition of the Anthropocene a political question for and within the geosciences? 

Michael Wagreich, Colin Waters, Diana Hatzenbühler, and Eva Horn

The Anthropocene Working Group (AWG) of the Subcommission on Quaternary Stratigraphy (SQS) of the International Commission on Stratigraphy (ICS) was founded in 2009 to investigate the potential of the Anthropocene as a chronostratigraphic unit of the Geological Time Scale. After more than 14 years of work, many key publications and fierce discussions both within and outside the AWG, and several rounds of voting, the AWG concluded by great majority that the Anthropocene concept of Crutzen (2002) has stratigraphic reality and that a formal GSSP definition is pragmatic and suitable at the mid-twentieth century, coincident with the Great Acceleration of Earth System Sciences. The resulting  GSSP proposal  is located in Crawford Lake (Canada) sediment core with the base of the Anthropocene marked by an upturn in plutonium coincident with autumn 1952.  However, during the years of AWG investigations, criticisms from outside and a minority group within the AWG opposed to the majority consensus and published results of the AWG (see Zalasiewicz et al., in press), have undermined the significance, importance and usefulness of the Anthropocene as a (chrono)stratigraphic unit. However, beyond its debated geological implications but in it’s wider interdisciplinary and popular context, the term has evolved into a symbol emblematic of global change, the current climate, and ecological crisis. An argument of prominent geoscientists is that the AWG is politically and not scientifically motivated when dealing with the Anthropocene. Despite the AWG following established ICS protocols and procedures for stratigraphic working groups and founding their conclusions transparently through publications (e.g. Waters et al., 2016, 2023; Zalasiewicz et al., 2017), a political dimension is implicitly imposed on both AWG members, but also at their critics. To what extent would rejection of the Anthropocene proposal be interpreted outside of the sciences as a rejection of the scale of the current global crises? Research into the Anthropocene by the AWG has resulted in awareness and engagement of involved scientists in a crisis for which geology has some liability, but also in a wider interest of the humanities, media and arts on the stratigraphic work of the AWG. Hence, one may interpret geological research in the Anthropocene as a great and timely societal mission for the geosciences, resulting, hopefully, in a sustainable geological discipline emerging out of its historical linkage with the fossil energy sector.

Crutzen, P.J., 2002. Geology of Mankind. Nature 415: 23.

Waters, C.N. et al., 2016. The Anthropocene is functionally and stratigraphically distinct from the Holocene. Science 351(6269): 137.

Waters, C.N. et al., (Eds.), 2023. Candidate sites and other reference sections for the Global boundary Stratotype Section and Point of the Anthropocene series. The Anthropocene Review 10(1): 3–24.

Zalasiewicz, J. et al., 2017. The Working Group on the Anthropocene: Summary of evidence and interim recommendations. Anthropocene 19: 55–60.

Zalasiewicz, J. et al., in press. The Anthropocene within the Geological Time Scale: analysis of fundamental questions. Episodes.

How to cite: Wagreich, M., Waters, C., Hatzenbühler, D., and Horn, E.: Is the definition of the Anthropocene a political question for and within the geosciences?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11357, https://doi.org/10.5194/egusphere-egu24-11357, 2024.

EGU24-11767 | Posters on site | EOS4.5

“Slow science” concept: first insights of perceptions and suggestions in an oceanography laboratory 

Simon Barbot, Guillaume Roullet, and Guillaume Serazin

In the attempt to look back on our practices and to plan their evolution, a debate has been conducted in our lab to share the different perceptions about the “slow-science” concept. This debate surprisingly gathered more curiosity than expected and all profiles of scientists were represented from the BSc, PhD students and engineers to emeritus researchers. Suggestions have been made for future practices that would increase the quality of the scientific results and knowledge as well as better working conditions while reducing green gas emission. A generational inequity was pointed out to initiate the changes: early-career researchers are selected based on project-and-paper-productive metric, while established researchers have positions of influence throughout institutions. Although such changes would need institutional decisions and technical innovation for lowering the measurement’ impact, many suggestions are already feasible through hindsight and self-discipline.

How to cite: Barbot, S., Roullet, G., and Serazin, G.: “Slow science” concept: first insights of perceptions and suggestions in an oceanography laboratory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11767, https://doi.org/10.5194/egusphere-egu24-11767, 2024.

EGU24-12554 | Orals | EOS4.5

'Les Sacoches du Climat': An outreach cycling initiative for covering the last mile of climate communication in rural France 

Les Sacoches du Climat, Juliette Bernard, Antoine Bierjon, Julie Carles, Antoine Ehret, Rémi Gaillard, Alexandre Legay, Alban Planchat, and Christophe Cassou

Rural and medium-sized town populations already regularly face the tangible impacts of climate change, particularly in relation to their professional activities. However, they are often overlooked by the scientific community when it comes to knowledge sharing, even though they equally deserve attentive listening and consideration. 'Les Sacoches du Climat' (i.e. 'The Climate Panniers') is a French scientific outreach initiative led by a collective of young climate researchers specializing in various fields. The initiative was designed to raise awareness of climate issues in such regions, taking on the challenge of reaching the last mile in the large-scale French awareness campaign 'La Tournée du Climat et de la Biodiversité' (i.e. 'The Climate and Biodiversity Tour') — a traveling exhibition in major cities addressing climate and biodiversity issues led by a multidisciplinary team of scientists. 

Our journey unfolded over a week, navigating the landscapes of rural France on bicycles. During the day, we engaged with secondary school audiences, delivering an introduction to climate challenges followed by interactive discussions and workshops, with a particular emphasis on a sensitive approach. This educational endeavor was seamlessly intertwined with collaborative projects involving teaching staff. In the evening, we engaged adult audiences through conferences and debates, fostering collaboration with local communities and associations. Accompanied by esteemed French climatologists riding tandem with us, our collective presents here a brief retrospective of this journey and the messages derived from it. This initiative serves as an earnest call for climatologists to step beyond the traditional confines of research, immerse themselves in the field, and consider the impacts, adaptation, and vulnerability of territories in all their diversity and specificity in the face of climate change, fostering a responsible societal paradigm shift.

How to cite: du Climat, L. S., Bernard, J., Bierjon, A., Carles, J., Ehret, A., Gaillard, R., Legay, A., Planchat, A., and Cassou, C.: 'Les Sacoches du Climat': An outreach cycling initiative for covering the last mile of climate communication in rural France, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12554, https://doi.org/10.5194/egusphere-egu24-12554, 2024.

EGU24-13761 | Orals | EOS4.5

Continuing wetland drainage: drivers, effects, and the role of science-based partnerships and understanding 

Helen Baulch, Phil Loring, Christopher Spence, Lauren Miranda, Don Selby, and Colin Whitfield

The prairie pothole region of North America has been described as a breadbasket for the world, and a ‘duck factory’ for North America, reflecting the tremendous ecosystem services associated with the vast agricultural lands, and millions of pothole wetlands in the region.  Pressure to increase agricultural outputs and profitability has led to accelerating wetland drainage, leading to a wicked problem worsened by the lack of enforcement of existing policy and vast numbers of unlicensed drainage projects.

Responsive to questions from partners, we embarked on a multi-dimensional research program to understand options for managing the drainage of prairie wetlands.  Novel ecosystem service models, based upon the unique hydrology of the region demonstrate important threats of drainage, including flooding, increased nutrient export, and profound impacts on habitat and biodiversity.  Expert-driven scenario development also shows potential for dire changes in the region associated with climate and land use change.  Importantly, there are fundamental differences among stakeholders in their understanding of how the system works, leading to divergent interpretations of the benefits, and consequences of drainage.  Not surprisingly, wetland drainage has led to conflict, as power dynamics and the effort to coordinate drainage approvals have contributed to winners, losers, and those without voice. However, in some cases drainage conflicts may simply be a resurgence of long-standing disputes over varied issues. 

While interdisciplinary and transdisciplinary work has helped understand the context of wetland drainage in this vast geographic area, problems, and possible ways forward, a weak policy environment is expected to persist because of local ideologies for limited government intervention, a highly politicised environment with strong power imbalances and strong government support of the agriculture sector.  Our work, guided by stakeholders since project inception to inform decision-making, demonstrates significant impacts of drainage with tangible policy implications, yet concerns have emerged about the role of science and representation of science in the policy process. While transdisciplinary research has clear benefits, it is not a panacea in complex, multi-sector, and conflict-prone arenas such as this. 

How to cite: Baulch, H., Loring, P., Spence, C., Miranda, L., Selby, D., and Whitfield, C.: Continuing wetland drainage: drivers, effects, and the role of science-based partnerships and understanding, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13761, https://doi.org/10.5194/egusphere-egu24-13761, 2024.

EGU24-15634 | Orals | EOS4.5 | Highlight

Conference of the Parties or Conference of the People? Introducing a series of alternative grassroots COPs 

Sylvain Kuppel and the Scientifiques en rebellion collective

The Conferences of the Parties (COP) annually assess progress in dealing with climate change and towards legally-binding obligations to reduce or limit greenhouse gas emissions. Despite almost three decades of COPs and landmark treaties such as the Kyoto protocol (1997) and the Paris agreement (2015), global greenhouse gas emissions are a far cry from the emission pathways limiting global warming below 1.5-2°C as defined by the scientific consensus synthesized by the Intergovernmental Panel on Climate Change (IPCC). The failure at igniting state-level actions for climate mitigation stems from many factors, including a politico-economic hegemony, vested interests and techno-economic mindsets (Stoddard et al., 2021), well-embodied in the meager, voluntarism-based outcomes of increasingly questioned COPs. It may make sense that leading scientists still go to COPs to carry the voice of scientific consensus and convey the need for rapid action. However, scientists may also consider taking part in transformative changes through bottom-up initiatives where the conversation between scientists, collectives, citizens and media is more easily insulated from intense lobbying and greenwashing, allowing to focus on fact-based and ethics-driven endeavors, while showcasing unbridled perspectives for policymakers. Here we report the example of alternative COPs that took place in France in parallel to the COP28 in Dubai, organized by the Scientifiques en rebellion collective during the international Scientist Rebellion campaign “How much more climate failure can we take?”. Articulating a series of short events across French cities culminating with a 4-day alterCOP in Bordeaux, this grassroots initiative by scientists and activists was an invitation to take time to germinate new imaginations and popular initiatives, in a certain way “slowing down” to catalyze action considering the broader picture. Topics covered by this alterCOP took a systemic approach, beyond the climate breakdown, to include the other intertwined planetary boundaries (ecosystem health, water cycle, land use, etc.), discussing other economic systems (e.g. degrowth), international solidarity, and stimulating various world representations (present or desirable) and communication media, from artistic performances to a mock trial of a fossil fuel company.

References
Stoddard, I, et al. (2021). Three decades of climate mitigation: why haven't we bent the global emissions curve?. Annual Review of Environment and Resources 46, 653-689.

How to cite: Kuppel, S. and the Scientifiques en rebellion collective: Conference of the Parties or Conference of the People? Introducing a series of alternative grassroots COPs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15634, https://doi.org/10.5194/egusphere-egu24-15634, 2024.

The growing involvement of researchers in the public debate is triggering reflections in various scientific institutions. Here we report on the reflections of a working group of the University of Lausanne (UNIL) gathering researchers from all faculties, coordinated by the Competence Centre in Sustainability (CCD) and the Interdisciplinary Centre for Ethics Research (CIRE). Commissioned by UNIL’s Rectorate, the working group met thirteen times between April 2020 and May 2022 and independently defined the themes, approaches and methods that it deemed relevant to mobilize in this perspective. In particular, it conducted a literature review, a survey and focus groups with the UNIL community in the spring of 2021.

The working group's reflections were primarily aimed at clarifying the issues related to the engagement of scientists in the public debate and at better understanding the practices and perceptions of the UNIL community in this respect. They also aimed to propose answers to questions such as: should researchers be free to engage in public advocacy and activism? Is this compatible with the swiss legal framework and with notions such as science neutrality and academic freedom? What good practices should be followed when engaging in advocacy and/or activism? How should UNIL, as an institution, support its engaged researchers?

The main conclusion of the working group, published in a report in May 2022, is that participation in the public debate, advocacy and activism is compatible with research activities and as such should be supported by the academic institutions. However, it recommends a few good practices such as being as transparent as possible about the role that is endorsed (expert, researcher, activist, etc.) and about the nature of the statements that are made in public (scientific findings, personal opinion, political recommendation, etc.). In this brief oral, I will delve into the main conclusions of the working group’s report and address the questions mentioned above.

How to cite: Fragnière, A.: Exploring key issues in public engagement and activism. Findings of a working group at the University of Lausanne., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16862, https://doi.org/10.5194/egusphere-egu24-16862, 2024.

EGU24-17314 | ECS | Orals | EOS4.5

An oceanography lab in its journey toward temperance 

Etienne Pauthenet, Simon Barbot, Pierre Amael Auger, and Eric Machu

The current ecological crisis requires changes in our way to make science in order to reduce the ecological footprint of scientific research activities. This is particularly crucial for setting a good example for the rest of society. Here we present the process engaged by an oceanography laboratory to reduce its environmental footprint. Using a tool developed by the French collective Labos 1point5, we calculated the carbon footprint of our laboratory separated by activities (missions, consumables, buildings, campaigns at sea, etc.). This exercise allows us first of all to quantify the contribution of the various components of our scientific activity. It also shows that the environmental footprint of our scientific activities is significant, and that it needs to be taken seriously by the community studying the Earth system. Reducing this footprint highlights different possible scales of action. Some actions involve internal laboratory processes, while others require broader societal changes. The measures implemented by our laboratory members to minimize our activities' impact will be presented, representing a part of a broader initiative under Labos 1point5.

 

How to cite: Pauthenet, E., Barbot, S., Auger, P. A., and Machu, E.: An oceanography lab in its journey toward temperance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17314, https://doi.org/10.5194/egusphere-egu24-17314, 2024.

EGU24-17840 | Orals | EOS4.5 | Highlight

The pivotal roles of the scientists in the initiative lead by the French government to train all civil servants on climate, biodiversity and natural resources issues 

Christophe Cassou, Luc Abbadie, Laurence Tubiana, Ulysse Dorioz, Jane Lecomte, and Claire Gouny and the GAES (Groupe d'Appui et d'Expertise Scientifique)

As anticipated by scientists for decades, impacts of climate change, biodiversity losses and natural resources scarcity, are increasingly challenging human societies in these early 2020s. To respond to this challenge, a large number of countries are undertaking profound societal shifts towards low-carbon and biodiversity-friendly lifestyles. So far, these efforts have been clearly insufficient to achieve sustainable development goals and more ambitious action will be needed at all decision levels.

In France, the government has taken the decisive step to train all civil servants on the three above-cited environmental issues. The aim of this unique and ambitious initiative is to engage as many state stakeholders and practioners as possible, by raising their awareness and knowledge about both environmental risks and challenges to be faced, in order to initiate an effective, societal-scale transition that has to be collective, collaborative and systemic by essence. This initiative is partly related to a "foot in the door" media operation carried out in June 2022, just after the presidential and legislative elections, and initiated by the scientific community to offer free training courses on climate and biodiversity issues to newly-elected members of parliament.

The ongoing inter-ministerial initiative is steered at national level by an interdisciplinary group of scientists who are responsible for framing training content and methods. Its operational implementation is ensured by regional committees of scientists to address local issues grounded in actionable reality, and to facilitate effective scaling-up. The ambition is to train 25,000 top managers civil servants by the end of 2024, and 5,7 million civil servants by 2027. Scientific knowledge is at the heart of the training program and the entire cursus runs over 28 hours in face-to-face to ensure cooperative dynamics during workshops, masterclasses, debates and field trips. More than 1,200 academics have volunteered to disseminate scientific facts as aid to decision-making, and to present the scientific methods that supports them. Training courses in scientific mediation will be offered to scientists engaged in the project, especially to early career researchers. The evaluation of the full initiative will be independently carried out through 3 PhD theses.

The ultimate aim of this initiative is to create shared and long-lasting spaces for dialogue and trust between public decision-makers and the scientific community. In this talk, we will describe and discuss the pivotal role played by the scientific community in this initiative. We will report the lessons learnt from the first training courses, as well as the successes and various obstacles that have been encountered.

How to cite: Cassou, C., Abbadie, L., Tubiana, L., Dorioz, U., Lecomte, J., and Gouny, C. and the GAES (Groupe d'Appui et d'Expertise Scientifique): The pivotal roles of the scientists in the initiative lead by the French government to train all civil servants on climate, biodiversity and natural resources issues, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17840, https://doi.org/10.5194/egusphere-egu24-17840, 2024.

EGU24-18413 | Orals | EOS4.5

Reducing the carbon footprint of a research lab: how to move from individual initiatives to collective actions? 

Claire Lauvernet, Céline Berni, Marina Coquery, Leslie Gauthier, Louis Héraut, Matthieu Masson, Louise Mimeau, and Jean-Philippe Vidal and the Riverly Downstream team

This communication aims at exposing the steps taken by a research lab – in this case INRAE RiverLy – to reduce its carbon footprint. INRAE RiverLy is an interdisciplinary research unit for the functioning of hydrosystems. The environmental transition process originates in 2020 with the creation of the RiverLy Downstream group launched to address the downstream impacts of research practices (see Vidal et al., 2023).

The first step taken by the RiverLy Downstream group relates to monitoring the laboratory's carbon footprint and identifying the main emission sources. Yearly carbon accountings carried out since 2019 using the GES1.5 tool (https://apps.labos1point5.org/ges-1point5) show that purchases (equipment, consumables, etc.) account for the majority (>50%) of the lab footprint. They also highlight the impact of changes in individual practices related to business travel, with -63% of travel-related emissions in 2022 compared to 2019.

A second step focused on raising awareness through a Climate Day and testing the willingness to change within our research unit through an opinion poll. Results led to writing down a lab charter which was unanimously adopted by the lab council in October 2023. This charter sets a collective 10%/year cut-down trajectory with respect to the 2022 carbon accounting, while affirming the determination to preserve the positive impact of our research on society.

A third step now being undertaken by the RiverLy Downstream team is to come up with concrete collective actions to effectively reduce the lab footprint. Participatory workshops are being organised in January and February 2024 to specify agreed actions for the various research activities: long-distance travelling, purchasing scientific and IT equipment, setting up a research project, doing lab and field experiments, performing biological and chemical analyses, performing scientific computations, and organising seminars and conferences. Consolidated and agreed propositions will then be submitted to the lab council for formal acceptation and implementation.

The whole process benefits from rich interactions with the INRAE national to regional strategy for reducing its environmental footprint (https://www.inrae.fr/en/corporate-social-responsibility-inrae), and with the French national initiative Labos1point5 which set up a national network of labs in transition (https://apps.labos1point5.org/transition-1point5).

Vidal, J.-P., Berni, C., Coquery, M., Devers, A., Gauthier, L., Lauvernet, C., Masson, M., Mimeau, L., and Turlan, M. and the RiverLy Downstream team: How to collectively engage in reducing the carbon footprint of a research lab?, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3462, https://doi.org/10.5194/egusphere-egu23-3462, 2023.

How to cite: Lauvernet, C., Berni, C., Coquery, M., Gauthier, L., Héraut, L., Masson, M., Mimeau, L., and Vidal, J.-P. and the Riverly Downstream team: Reducing the carbon footprint of a research lab: how to move from individual initiatives to collective actions?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18413, https://doi.org/10.5194/egusphere-egu24-18413, 2024.

Building transdisciplinary solutions at the first ever Climate Security Festival

In September 2023, the first ever Climate Security Festival was organized in Helsinki, Finland. The event gathered close to 100 participants including researchers, civil society actors, climate security experts, artists, activists, students and others at the Finnish Meteorological Institute for two days.

The idea of the festival was to bring people together and to enable discussing the risks related to climate change in an open and equal space. The two-day program was built around parallel workshop sessions, with the aim of strengthening and fostering cooperation between different sectors. The workshop topics were: 1) War and its effects on climate and the environment 2) Climate, death & (mental) wellbeing and 3) Who owns the climate security discussion? In addition, the festival included two keynote talks, joint discussion, a transdisciplinary poster session, artistic performances and side program; a safety walk, a photography exhibition and a collaboration movie screening and panel discussion in collaboration with Finland’s biggest film festival. The event was organized in person and participants were encouraged to leave aside their electronic devices, titles and prejudice.

Based on the encouraging results and feedback from participants, some key findings from the festival can be pointed out and utilized in building sustainable collaborations and co-creating climate solutions in geosciences and beyond. The results indicate, for example, the importance of;

  • embracing a truly transdisciplinary approach (including non-academic methods)
  • putting the work in building safer spaces for discussing ethical, fundamental and even painful topics in the context of climate change and geosciences
  • involving artists, art institutions and artistic methods in climate security related discussions and action in non-performative roles
  • expanding ownership of the discussion on climate change related risks beyond ‘traditional’ research and security/foreign political frameworks

Results are presented briefly with visual materials from the festival, workshop proceedings and participant feedback.

The festival was organized by the Safer Climate network (Institute for Atmospheric and Earth System Research, University of Helsinki) in collaboration with the Committee of 100 in Finland. The next festival will be organized in 2024.

How to cite: Rantanen, R.: Building transdisciplinary solutions at the first ever Climate Security Festival, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18757, https://doi.org/10.5194/egusphere-egu24-18757, 2024.

With detailed understanding of planetary boundaries like the connection of continuously increasing global greenhouse gas emissions and the frequency and severity of climate change impacts (geo)scientists recognize the critical need for ambitious political action perhaps more urgently than non-experts. Yet, global policies have consistently failed to deliver on their ambitions, goals, and implementation, making necessary transformations elusive. We argue that (geo)scientists can have a considerable impact beyond the traditional avenues of publishing papers and reports or advising policy makers. Drawing inspiration from historical successes, particularly in non-violent civil disobedience, we explore the considerations of engaging in climate activism from the dual perspectives of scientists and civil servants. Using the example of scientists at public scientific institutions in the Netherlands, we delve into questions surrounding one’s rights, duties, and responsibilities. We aim to stimulate reflection on effective strategies for scientists to advocate for change in the critical arena of climate action and climate justice.

How to cite: Jüling, A. and Keizer, I.: Navigating the Intersection of Science, Activism, and Civil Service: Reflections on the role of scientists in civil service, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18782, https://doi.org/10.5194/egusphere-egu24-18782, 2024.

EGU24-19128 | Posters on site | EOS4.5

IPSL climactions and the bottom-up ecological transformation of  a climate research institute (2016-2024) 

Lea Bonnefoy and the IPSL Climactions

For several decades now, research communities working on the climate, its changes, including current global warming, and its consequences have been recommending drastic reductions in human-made greenhouse gas emissions and, more generally, in the ecological footprint of human activities. This implies the implementation over the next 10 to 20 years of profound and rapid systemic transformations. The latest IPCC reports show that such transformations are only possible if they involve all parts/sectors of society. Given the existence of a range of ecological constraints and the foreseeable limits to scientific and technical advances, the transformations to be implemented must also include a strong component of sufficiency ("avoidance”).

Since 2016, IPSL scientists and support staff have been working together along these lines to transform the institute's professional practices.  This engagement is generally seen as : (i) a necessity: to initiate a transition in its research practices that will bring its professional behavior in line with the message of climate urgency that it has been diffusing for over 30 years; (ii) an opportunity: to accelerate the transition at a societal level by opening up new channels of exchange with society, encouraging collective action by example, and reinforcing the credibility of its warning message; (iii) a safeguard: collective bottom-up thinking at laboratory level to ensure that this transition takes place with maximum respect for our research practices and our well-being at work, and is not imposed by potentially inappropriate top-down measures.

Achievements include (i) the development of methodologies for calculating the carbon footprint generated by staff activities and professional practices, (ii) concrete contributions to the reduction of the environmental footprint of professional travels, digital and high performance computing activities, purchases and finally observation of the earth. We will present here our approach, methodologies, achievements, and reflections at this stage, with the hope to stimulate exchange with other ongoing or emerging initiatives in other parts of the world.  

How to cite: Bonnefoy, L. and the IPSL Climactions: IPSL climactions and the bottom-up ecological transformation of  a climate research institute (2016-2024), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19128, https://doi.org/10.5194/egusphere-egu24-19128, 2024.

EGU24-19470 | Posters on site | EOS4.5 | Highlight

Scientific debunking of institutional and corporate communication 

Laurent Husson and the Scientifiques en Rébellion collective

Greenwashing sounds like a trivial manoeuvre that can easily be circumvented. In practice, private companies and institutions deploy a wealth of inventiveness to take away your vigilance. As a canonical example, it took forever before it was realized and admitted that the tobacco industry had a tremendous health burden. As scientists, we have the means to scrutinize the borderline communication, that stands half way between journalistic investigation and activism. That is the purpose of Scientist Rebellion in particular, which is particularly concerned with environmental challenges. Of course, it often requires to go beyond our daily scientific expertises, that we are trained for. Using two recent examples, I will showcase two case studies from Scientist Rebellion in France. The first one deals with the analysis of financial institutions regarding their oil and gas strategies, and the subsequent media coverage of activist communication, and an insider view on the impact of it had on the orientation of their strategies. The second one is an exploration of the governmental communication on adaptation strategies to climate change, with consideration on its political implications. 

How to cite: Husson, L. and the Scientifiques en Rébellion collective: Scientific debunking of institutional and corporate communication, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19470, https://doi.org/10.5194/egusphere-egu24-19470, 2024.

EGU24-19960 | ECS | Orals | EOS4.5

Climate activism as a form of science communication and public engagement 

Arthur Oldeman, Iris Keizer, and André Jüling

The current state and future projections of the climate and environmental crises call for science to be able to have a deep impact on society, and to have it quickly. Here we discuss how scientists engaging in climate activism can contribute to educating the general public and press for urgent action, as well as under which conditions such scientific activism can be most effective.

Traditionally, science has mostly interacted with society by making scientific results public, without interfering in how politicians, business and the general public would make use of them. Similarly, the role of science educators has been often confined to spreading knowledge to students and broader audiences, independently of how this knowledge affects society. However, such communication and education efforts appear insufficient considering unambitious policies with regards to the current climate and ecological crises. As a result, many scientists, both within and outside academia, have been looking for other ways to communicate the urgency of the climate crisis. Notably, communication efforts have increasingly extended to public support of environmental action movements and participation in protests and civil disobedience actions.

In this work, we discuss how activism can be complementary to classical approaches of science communication and public education on the urgency of the climate and environmental crises. We will highlight recent examples of civil disobedience by scientists with a focus on the Netherlands. We also present the reaction from stakeholders such as politicians and representatives of companies, as well as the reception of such actions by the scientific community. We discuss the place of activism in the broader scientific community, where our viewpoint is that scientific activism can only become an efficient way of science communication and public engagement if (i) it is accepted and respected within the scientific community, and (ii) it adheres to rules allowing such communication to maintain or increase scientific reputation in society. We also stress the supportive role of universities and research institutes in enabling the engagement with activism, especially for early career scientists. Scientific institutions should emphasize that climate activism and advocacy is welcome among both researchers and educators, that their freedom of speech is protected, and that such activities are recognized as valuable.

How to cite: Oldeman, A., Keizer, I., and Jüling, A.: Climate activism as a form of science communication and public engagement, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19960, https://doi.org/10.5194/egusphere-egu24-19960, 2024.

EGU24-20093 | Posters on site | EOS4.5

Beyond Traditional Science Advocacy: Should Scientists engage in Climate Action?  

Iris Keizer, Arthur Oldeman, and André Jüling

The current climate and environmental crisis requires immediate societal changes. Here, we propose a discussion on whether scientists should engage in climate action. Activism offers a new avenue for climate advocacy that goes beyond traditional methods. We explore how scientists engaging in climate activism can educate the general public and press for urgent action and the conditions under which scientific activism can be most effective. 


Using historical and recent examples of non-violent civil disobedience by scientists, including actions we joined and/or supported as members of Scientist Rebellion, we demonstrate how such activism can be effective in complementing classical approaches to public education about the urgency of the climate and environmental crises, as well as in pushing for critically needed political action. We invite all scientists to engage in a discussion on whether we should engage in climate action as we acknowledge the complexities around scientific values, ethics, authority, and integrity. 



How to cite: Keizer, I., Oldeman, A., and Jüling, A.: Beyond Traditional Science Advocacy: Should Scientists engage in Climate Action? , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20093, https://doi.org/10.5194/egusphere-egu24-20093, 2024.

EGU24-20180 | ECS | Orals | EOS4.5 | Highlight

Mapping Fossil Ties: Decentralised research into ties between universities and the fossil fuel industry 

Maien Sachisthal, Aaron Pereira, and Linda Knoester

Universities are under increasing scrutiny from students, staff and society about their ties with the fossil fuel industry. Such ties include research cooperations and commissions, influence and participation in study programmes, sponsoring of students and student societies, sponsored professorships and staff ancilliary activities, presence at careers fairs and alumni networks. For fair and open discussion on what relationships between universities and the fossil fuel industry are appropriate, such relationships must be transparent - currently this is not the case. 

In the Netherlands, the Mapping Fossil Ties coalition - a research coalition of student and staff activists, NGOs and independent investigators - map these "fossil ties" and track the influence of fossil fuel companies in universities. We use a variety of methods: freedom of information (FOI) requests to universities and funding bodies, web scraping, and decentralised, crowdsourced information gathering on campus. From this, we could build a fuller picture of how Dutch academia interacts with and is influenced by the fossil industry, and can identify hidden, yet problematic ties. 

The collaborations, news coverage, and state of the debate are continually updated on a web portal (mappingfossilties.org) for the use of investigative journalists, (activist) student and university staff, NGOs, policymakers, and the public. In this talk we present our methodology, the impact that this research has had on the Dutch public debate, how this research underpins student and staff activism, and points for improvement and learning. Finally we discuss how we are replicating such research in other countries, and how others can do so too.

How to cite: Sachisthal, M., Pereira, A., and Knoester, L.: Mapping Fossil Ties: Decentralised research into ties between universities and the fossil fuel industry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20180, https://doi.org/10.5194/egusphere-egu24-20180, 2024.

EGU24-346 | Orals | EOS1.1

Decolonizing geoscience communication: a case study of a new human evolution exhibition at the Iziko South African Museum 

Robyn Pickering, Wendy Black, Tessa Campbell, Nkosingiphile Mazibuko, Amy Sephton, and Rebecca Ackermann

Communication with the public is a necessary part of geoscience outreach and museums are an established medium for this. However, in many places, including South Africa, even the physical structures of museums are colonial which can create an atmosphere of exclusion, rather than one of learning, discovery and inspiration. South Africa has a rich record of the history of life, from deep time to our own human origins and the public are fascinated with these stories. We need to acknowledge that, like most scientific disciplines, human evolution (or palaeoanthropology) itself has a colonial history. As a result, narratives of human origins are often racist and patriarchal, and demographic representation remains skewed to the Global North. The combination of this colonial legacy with our colonial museums means that human evolution narratives in this space tend to othering, which can alienate young people and impede both knowledge transfer and uptake of this field by young scholars. Here we present a case study of a new permanent human evolution museum exhibit, titled HUMANITY, at the Iziko South African Museum in Cape Town, South Africa. Our goal in producing this exhibit was to decolonize the narrative of human evolution and decenter Whiteness, specifically the Great White Explorer narrative of discovery, which is central to most museum displays on this theme. This exhibit was co-created, with active community engagement, and input from researchers, curators, artists, community leaders, educators, school teachers, university students and more. The exhibit does not fit traditional Western museum aesthetics of white walls, square information boards and objects on plinths. We flipped the order in which such exhibits are normally presented, i.e., starting in the deep past and working towards the present day. Our flipped approach has the advantage of starting with the visitor themselves and drawing people in, focusing on the biological and cultural diversity of people in South Africa today as a means for exploring how that diversity came to be. Throughout the exhibit, we weave a story of complex human interconnectedness, a narrative that is consistent with our current understanding of the braided stream analogy for human origins. The exhibit also addresses the negative legacies of palaeoanthropological practice and encourages critical reflection on race, skin color variation, and privilege. The biggest departure from previous exhibits comes from our intention to examine our own practice and to co-create an exhibit which speaks to a much broader audience. We believe this intentionality played a significant role in the success of the final installation and reaction from the public. We believe that being deliberate about moving away from colonial and Western norms is vital in the communication of science, in this case palaeosciences, to the public and scholars within the educational system. Our new HUMANITY exhibit could be a model for considering similar museum displays, especially those dealing with aspects of geosciences, palaeonthology and human origins, many of which have the same problems.

How to cite: Pickering, R., Black, W., Campbell, T., Mazibuko, N., Sephton, A., and Ackermann, R.: Decolonizing geoscience communication: a case study of a new human evolution exhibition at the Iziko South African Museum, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-346, https://doi.org/10.5194/egusphere-egu24-346, 2024.

EGU24-1438 | Orals | EOS1.1

Using mental models as a tool to understand perspectives of scientific uncertainty and effectively communicate natural hazards science advice. 

Emma Hudson-Doyle, Jessica Thompson, Stephen Hill, Matt Williams, Douglas Paton, Sara Harrison, Ann Bostrom, and Julia Becker

Science communication associated with natural hazards risk contains many levels of complex, interacting, uncertainties. These uncertainties arise due to variabilities between systems, lack of scientific knowledge, comprehension, incomplete information, and undifferentiated alternatives. Uncertainties also occur due to relationships, roles, responsibilities, and needs.   This is compounded by the evolving nature of response needs and changing communication networks. Further, varied understanding of what scientific uncertainty is, and where it comes from, affects people’s trust in and use of science advice. Thus, official guidelines, such as the International Panel on Climate Change and the World Meteorological Organisation, indicate that to communicate ethically, we should be open and transparent about any associated uncertainties. However, to communicate uncertainty effectively across diverse audiences, users, and decision-makers, we must understand and adapt to the different ways people perceive that uncertainty.

We thus conducted mental model interviews to understand perspectives of uncertainty associated with natural hazards science. Participants ranged from officials involved in decisions around natural hazards in Aotearoa NZ, through to scientists and the public. The interviews included three phases: an initial elicitation of free thoughts about uncertainty, a mental model mapping activity, and a semi-structured interview protocol to explore further questions about scientific processes and their personal philosophy of science. Two phases of data collection and analysis occurred. In phase 1, an initial qualitative analysis considering a cohort of 25 participants led to the construction of key themes, including: (a) understanding that, in addition to data sources, the ‘actors’ involved can also be sources of uncertainty; (b) acknowledging that factors such as governance and funding decisions partly determine uncertainty; (c) the influence of assumptions about expected human behaviours contributing to ‘known unknowns’; and (d) the difficulty of defining what uncertainty actually is.  Additional influences on perceived uncertainty were also recognised, and require further research, including: an individual’s understanding of societal factors; the role of emotions; using outcomes as a scaffold for interpretation; and the complex and noisy communications landscape.

To investigate how views on uncertainty varied with familiarity with, and experience in, science an additional 6 interviews were conducted with non-scientists. This enabled a secondary qualitative investigation in Phase 2, exploring how mental models of uncertainty varied with levels of science expertise. This considered all participants across both data collection periods (n=31). Participants were categorised across three cohorts: Scientists, Science-Literate, and Lay Public. A comparative qualitative analysis of their mental model maps identified an increase in map organisation with science experience, suggesting greater science training results in a more developed and structured mental model of uncertainty. There were also substantive differences, with Lay Public participants focused more on perceptions of control, safety, and trust, while Scientists focused more on formal models of risk and likelihood. These findings are presented to enhance hazard and risk communication, alongside the design of our interview methodology, which could be adapted for participatory and co-development research and to identify decision-relevant communication approaches.

How to cite: Hudson-Doyle, E., Thompson, J., Hill, S., Williams, M., Paton, D., Harrison, S., Bostrom, A., and Becker, J.: Using mental models as a tool to understand perspectives of scientific uncertainty and effectively communicate natural hazards science advice., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1438, https://doi.org/10.5194/egusphere-egu24-1438, 2024.

EGU24-2760 | ECS | Orals | EOS1.1 | Katia and Maurice Krafft Award Lecture

Reclaiming the rocks: ukuthetha ngezifundo zomhlaba ngesiXhosa 

Sinelethu Hashibi and Rosalie Tostevin

South Africa has an exceptionally rich geological heritage, including tourist attractions such as Table Mountain and the Cradle of Humankind, as well as important economic deposits, such as gold, diamonds, coal, and Platinum-Group-metals. South Africa also has a rich cultural and linguistic heritage. Our people are known for their resilience, born from our uncomfortable and ugly past – apartheid. Although apartheid came to an end in 1994, its impact remains visible today, with widespread poverty, inequality, poor education, violence and corruption. English, despite only being a first language for 8% of the population, dominates scientific discourse in South Africa. This is partly a result of apartheid, whose aim was to exclude the majority of non-white South Africans from the scientific community. Given the poor education system, many South Africans, despite holding a grade 12 qualification, still struggle with the language, particularly at varsity level. IsiXhosa is the mother tongue of over 8 million people, and is mutually intelligible with Zulu, Northern Ndebele and Southern Ndebele, meaning it is potentially accessible to 23 million people. Classroom studies have demonstrated that people engage more and understand better when the conversation is in their native tongue1-3

Despite the fact that South Africa is an exporter of many geological resources, and the intertwined history of mining with the black community, geology remains inaccessible to most people. South Africans, and Africans in general, are big storytellers - stories about the constellations, the moon, and the universe as a whole. This project, Reclaiming the rocks: ukuthetha ngezifundo zomhlaba ngesiXhosa, is an open invitation to invite all South Africans to share in their rich geological history through storytelling. It is a statement that science, like music, knows no language. We have summarized the most compelling stories about South Africa’s geological history, translated them into isiXhosa, and host them on an open access website (chosindabazomhlaba.com), and on YouTube. Recently, we started a school drive, reading these stories to school children. This project has had an impact on the lives of many people, whether they spoke isiXhosa or not, geologists or not. Next, we plan to write a children’s book and expand the school drive. Our ultimate goal is to develop a Geological encyclopedia written in isiXhosa and the other South African languages.


1Benson, (2004) The importance of mother tongue-based schooling for educational quality. Paper commissioned for the EFA Global Monitoring Report 2005, The Quality Imperative, UNESCO, Paris

2King, K and Mackey, A (2007) The bilingual edge: Why, when, and how to teach your child a second language. New York: Collins.

3Salili, F and Tsui, A (2005) ‘The effects of medium of instruction on students’ motivation and learning’, in Hoosain, R and Salili, F (eds) Language in multicultural education (Series: Research in Multicultural Education and International Perspectives) 135-156. Greenwich, CT: Information Age Publishing.

 

How to cite: Hashibi, S. and Tostevin, R.: Reclaiming the rocks: ukuthetha ngezifundo zomhlaba ngesiXhosa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2760, https://doi.org/10.5194/egusphere-egu24-2760, 2024.

This presentation shares experiences of delivering educational and outreach content via YouTube. It examines the reach of videos, their longevity and the utility of the platform for sharing materials – based on a personal case-study of a relatively popular and content-rich YouTube channel.

In common with many university teachers, during the Covid pandemic I developed online educational resources, including a suite of videos. These not only covered content previously delivered through in-person lectures but also enacted worked demonstrations of practical exercises. The content supported teaching in the interpretation of geological maps, field techniques, structural geology/tectonics and the geological interpretation of seismic reflection profiles. Initially these videos were hosted through the university’s Panopto account but in April 2021 I decided to collate these and publish through YouTube. Even though teaching has returned to pre-pandemic norms, I still use the videos, largely to permit flipped learning activities and for providing debriefs on practical classes. I continue to populate the channel (a new video every c 2 weeks) – chiefly making short documentaries “on location” to share geo-sites, geological techniques and concepts (including the history and primary publications behind them), and practical exercise demonstrations. While students and professional geoscientists seeking educational materials remain key audiences, the videos also target “engaged amateurs” – especially those interested in discovering field locations. Moderated discussion and clarifications are delivered through the “comments” facility on YouTube. There is a parallel website (hosted on WordPress) that holds many of the practical exercises, creating an open-access resource for geological training.

But how effective is the channel at sharing geology with diverse audiences?

YouTube provides statistics on viewer demographics and view-times. As of January 2024, the Shear Zone Channel hosts 228 videos, with c 380k views and has attracted 5.78k subscribers. Unsurprisingly most users are based in the UK, with few based elsewhere in Europe. Significant user-communities live in North America, India, Indonesia and the Philippines. Through weeks there is a drop-off of views on Fridays. Annual viewing peaks occur in early-mid December, with a rapid drop-off through the festive season that follows, as might be expected for a student-dominated viewing population. Life-time views of individual videos are remarkably variable: some show steady accumulation, others plateau after a few days of publication, a few grow exponentially. These differences reflect video content, and presumably therefore, the type of viewer. The algorithms used by YouTube to expose content to site users, and the ways users search for content, preferentially display recent video along with popular content (watched, liked, commented upon) along with that from channels to which the user has subscribed. Interrogation of activity statistics shows few users explore hosting channels or their playlists. Many find channel content through YouTube (algorithm-based) recommendations.

Content exposure on YouTube, in common with many digital resources, is prone not only to recency bias but also herding, whereby viewing populations repeatedly access the same content. Content creators can modulate this by pairing with other social media platforms or soliciting peer-recommendations.

The channel is available at: https://www.youtube.com/channel/UCIUYjr1yPCZQWYl9cJCO1mA

 

How to cite: Butler, R.: Sharing outreach and educational materials through YouTube: a case study from the Shear Zone Channel, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3201, https://doi.org/10.5194/egusphere-egu24-3201, 2024.

What started as an idea to incorporate geoeducation in community art practices evolved into youth-led educational workshops that integrated scientific and local knowledge to understand the physical, social, and cultural aspects of a landscape. The Nomad Projects are community art initiatives in the Philippines that explore the relationship of communities with their landscape through artistic practices and dialogue.

In 2023, The Nomad Projects launched the OpenEdu workshops which invites young professionals (artists, musicians, scientists, etc.) to share their expertise and knowledge relevant to the areas where partner communities reside. These workshops aimed to bring information about the landscape that may not be easily accessible to these communities that reside in them. However, due to the grassroots and participatory nature of these projects, the workshops evolved into a “pot-luck” style knowledge sharing where all participants share knowledge through dialogue. Young professionals with diverse backgrounds, from the humanities to the sciences, shared their expertise and also introduced scientific instruments while residents shared their experiences and their own understanding of their landscape. These workshops became a unique ‘format’ of geoeducation that integrates scientific theories and local knowledge for a holistic understanding of the landscape. These workshops also served as avenues to discuss landscape-related social issues such as landscape modification (i.e. dam-building, reclamation), sea level rise, and geohazards. These discussions strengthened calls for social justice, especially for these vulnerable communities that bear the brunt of irresponsible anthropogenic landscape modifications and climate change. Here we share best practices and reflections of two OpenEdu workshops : “Landscape as Classrooms” and “Wetlands as Classrooms”. 

Landscape as Classrooms was a small group-conversation facilitated by a geoscientist attended by young professionals like artists, academics and members of the Dumagat Remontado indigenous group. It was held outdoors with the participants sitting in a circle on a gravel bar at the Tinipak River. This allowed the discussion on river processes and river morphology where participants can see the actual landforms being discussed around them. This is one of the first ‘formal’ introductions of the geodiversity concept outside the Philippine academe. Geoheritage value of the area was recognized from the rare occurrence of a bedrock channel as well as the importance of the river’s geosystem services to the indigenous population that reside there. 

“Wetlands as Classrooms” included a bigger audience of community members of Sitio Apugan, a hamlet in the Pampanga delta at the coast of Manila Bay. This hamlet has experienced landscape changes through sea-level rise that are documented in the residents’ memories of their area. Presently, this hamlet is perpetually flooded and is one of the “sinking” villages in the Philippine coasts. The workshop was also facilitated by geoscientists and included discussions on delta morphologies, watersheds, groundwater, subsidence, and sea-level rise.

We present our experiences and reflections of organising, facilitating, and participating in these workshops to show examples of youth-led initiatives outside the traditional “top-down” and “bottom-up” approaches to geoeducation, where knowledge is shared by and for the participants through meaningful exchanges. 

How to cite: Irapta, P. N. and Valencia, V.: Filipino youth-led place-based geoducation through knowledge sharing between young professionals and residents : the Nomad Projects OpenEdu workshops, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3519, https://doi.org/10.5194/egusphere-egu24-3519, 2024.

The term "Science Communication" describes the scientific field of theoretical knowledge and practical skills that focuses on issues of two-way communication between the "scientific laboratory" and society, but also on communication between scientists coming from different fields of expertise. Its integration into school environments and educational institutions is an absolutely innovative action in the educational landscape. In addition, it can be safely considered as an expression of leadership of the persons and agencies involved since the role of the people who are called upon to apply the principle of leadership consists mainly in the management and coordination of systems and groups both on a synchronous and a longitudinal level: Leaders should contribute catalytically in the areas of motivating, supporting and developing colleagues, cultivating solidarity, encouraging innovative actions, establishing and defending the appropriate work culture and, ultimately, shaping strategy and vision. In short, leaders are actually charged with the task of achieving the goals set at the collective level by exerting a positive influence on the behavior of his associates, an effect that can greatly activate the feelings of passion, excitement and assimilation that characterize the scientific phenomenon. A typical case of all the above mentioned is the project Connect (https://www.connect-science.net/), a three-year project (2020-2023) in which the Regional Directorate of Education of Crete participated, included in the European Program "Horizon 2020" in framework of the "Science with and for Society" (SwafS) module. It was aimed at schools and offered a model that strengthens children's confidence in their engagement with science as a method of solving everyday problems and at the same time brings them into contact with scientists by involving parents and the local community. In other words, Connect tried to foster the belief that “science is for me”. Its evaluation has shown that the successful exercise of leadership, both at the level of the project coordinators and at the level of the principals of the participating schools, has been the critical factor for the success of the project and the achievement of the goal, i.e. Communication of Science with society.

How to cite: Kartsonakis, E. and Kokkori, A.: The role of leadership in education as a decisive factor for the Communication of Sciences: The case of the European project Connect  (Horizon2020), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6320, https://doi.org/10.5194/egusphere-egu24-6320, 2024.

In this paper, I focus on my personal experiences as an academic, educator, and researcher serving as an expert witness in environmental litigation. I discuss the relevance of my work in these roles within the context of two legal cases: the first, centered on soil erosion and sedimentation in small reservoirs, and the second, involving property damage from catastrophic flooding during two tropical storms.  

My objective is to demonstrate the extent and impact of the geosciences overall, and the field of geomorphology specifically, in contributing to legal proceedings related to environmental disputes. Throughout the years, I have collaborated with exceptional lawyers, each of whom has been invaluable in preparing me for cases, particularly in simplifying complex concepts and conveying them effectively. The ability to articulate the scientific process and principles to non-specialist audiences, such as lawyers, judges, and juries, in a lucid and comprehensible manner, is crucial to ensuring that the expert's testimony is relatable and compelling.

How to cite: Slattery, M.: Science communication and the law: Lessons learned from being an expert witness, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6322, https://doi.org/10.5194/egusphere-egu24-6322, 2024.

EGU24-6332 | Posters on site | EOS1.1

#ClimateResearchNet - a collaboration of climate communicators 

Hazel Jeffery and Helena Martins

#ClimateResearchNet

Climate Science is an active field of research whose findings are constantly feeding our knowledge about the changing climate, future scenarios and possible solutions. The climate-research community plays a key role in informing policy- and decision-makers, business and society. Hence, climate researchers are frequently urged to engage in climate change dialogues, as they are crucial stakeholders.

There is often a long gap before published research results reach the policy universe and an even longer time before they reach the rest of society. This network aims to give climate research communication a push so that its results are shared faster, more efficiently and more broadly.

A group of EU and nationally-funded climate research projects identified the need to collaborate and build a community of climate communicators to increase the impact of our research. Currently, there are over 20 projects represented in our network.

Objectives of the Network

  • Increasing the impact of each member’s communication by:
  •        Reaching a broader and more diverse audience,
  •        Having a pool of valuable content to share regularly - to keep our social networks active.
  • Creating a community of practice to build common knowledge on best practices and to make climate-research communication more impactful.
  • Establish a strong presence of the climate research community in communication networks and on social media. 

Whilst the network is still in its infancy, there have been some initial achievements, including:

  •  A science-to-policy meeting with EU officials in Brussels, which involved research from 5 EU projects,
  • Submission of a Great Debate session at EGU2024 – “Unleashing your potential as an Early-Career researcher: bridging the research-policy divide”,
  • Network meetings where we have shared our experiences, provided project introductions, and mapped out stakeholder engagement, communications and early career researcher activities across the projects and identified some topics of common interest eg. participation in COPs.

We would love to engage with other projects, hearing about their experiences in managing communication of their project results, types of activities that have been impactful and how communication roles in projects can be better networked to provide a community of practice.

Authors: Hazel Jeffery, Mariana Rocha, Helena Martins, Sara Octenjak, Rosa Rodriguez Gasen

How to cite: Jeffery, H. and Martins, H.: #ClimateResearchNet - a collaboration of climate communicators, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6332, https://doi.org/10.5194/egusphere-egu24-6332, 2024.

EGU24-6381 | ECS | Orals | EOS1.1

Remote sensing as a tool for science education and engagement: the case of the All-Ukrainian competition "Ecoview" 

Svitlana Babiichuk, Stanislav Dovgyi, and Lidiia Davybida

The war in Ukraine has harmed all areas of public life. Educational institutions have had to adapt to restrictions and threats to ensure the safety and accessibility of education in challenging conditions, working to restore children's inalienable right to access knowledge. The Junior Academy of Sciences of Ukraine (JASU) is the largest Ukrainian out-of-school organisation, with over 200,000 students annually, which supports the development of science education in regions. It is also a Category 2 Centre under the auspices of UNESCO and the first organisation in Ukraine to join the Copernicus Academy network. 

The All-Ukrainian Competition "Ecoview" has been organised annually since 2019 by the GIS and Remote Sensing Laboratory of the JASU. The Competition aims to promote science education and improve students' climate literacy and environmental awareness. Using remote sensing data is the main requirement for participation.

Between 2021 and 2023, over 1000 students of all ages from different regions of Ukraine registered to take part in the Competition. Participants commonly chose topics related to climate change, air pollution, deforestation, land cover change, and urbanisation. Since 2022, there has been an increase in the number of projects dedicated to studying the war effects on the environment in Ukraine. The study focused on various aspects including the destruction of settlement infrastructure, the impact of hostilities on nature reserves, and the pollution of the Black Sea caused by the sunken cruiser „Moskva”. The participants most commonly used open satellite monitoring data as sources of information for their research, processing them using NASA Giovanni, EO Browser, Google Earth, QGIS, etc.

Results of the entrance survey, conducted during registration, show a notable boost in participants' awareness of remote sensing, enhanced critical thinking, and improved ability to work with primary sources. Thus, when asked about their experience with satellite imagery, 9.5% of the total number of respondents answered in the affirmative in 2021, 19.7% in 2022 and 22.5% in 2023. Furthermore, the survey results show that an increasing number of participants are consistently fact-checking information published in the media or on the Internet (72.6% in 2021, 74.8% in 2022 and 85% in 2023). Knowledge of satellite imagery sources and analysis methods enables students to independently verify expert opinions and media-provided information, which contributes to the development of media literacy.

The results of the annual competition are inevitably covered in the media and on social networks. To assist potential participants in selecting their own project topic and research tools, a specialised video course titled „Ecoview: Satellite Data in Nature Research” has been developed. This course is available for public access on the GIS and Remote Sensing Laboratory`s YouTube channel (https://www.youtube.com/playlist?list=PLbqB1gQogHvsyFDiOO0y6EVAVdjQnveDI).

Based on the experience and results of the Competition "Ecoview" in Ukraine, it will be organised internationally in 2024. The event is aimed to establish relationships between participants from different countries and to create an international community of like-minded people interested in using remote sensing for environmental research and protection.

How to cite: Babiichuk, S., Dovgyi, S., and Davybida, L.: Remote sensing as a tool for science education and engagement: the case of the All-Ukrainian competition "Ecoview", EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6381, https://doi.org/10.5194/egusphere-egu24-6381, 2024.

EGU24-7951 | ECS | Posters on site | EOS1.1

"Quake Shake" - A New Citizen Earthquake Outreach Programme In Ireland. 

Laura Reilly

 "Quake Shake" transcends its catchy name; it is a captivating and educational earthquake outreach initiative tailored specifically for the Irish community. The programme is run by DIAS and co-financed by Geological Survey Ireland. Building on the success of the Seismology in Schools programme (SiS), Quake Shake aims to facilitate the operation of affordable seismometers called Raspberry Shakes in schools, homes, and public institutions. The overarching objective is to foster the development of an integrated community of citizen seismologists throughout Ireland. This poster provides a glimpse into the programmes development: to educate people from all walks of life in Ireland when it comes to earthquake awareness about both Irish and Global earthquakes.  It illustrates how Quake Shake is actively currently building a community of citizen seismologists across Ireland.

How to cite: Reilly, L.: "Quake Shake" - A New Citizen Earthquake Outreach Programme In Ireland., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7951, https://doi.org/10.5194/egusphere-egu24-7951, 2024.

EGU24-9101 | Orals | EOS1.1

Climate and Media: an efficient and original training for journalists 

Gilles Ramstein, Bruno Lansard, and Olivier Aballain

During the COP21 which took place in Paris, many climate researchers enhanced their interactions with different population sectors, to explain future and past climate changes.

Our group organized a seminar in one of the most prestigious journalist school (ESJ in Lille). Researchers on modelling and documenting past and future climate changes, as well as researchers from human and social sciences, provided a series of seminars. After the session devoted to questions from the audience, journalists and professors of the ESJ came down from the amphitheater. They emphasized the idea that our responsibility as researchers was also to teach journalists the different aspects / impacts of climate change. Their main point was to argue that it was in fact pivotal to get a better understanding of climate issues from the population.

This event was the onset of a big project that officially begun in 2016. We took some time to finally build an original training course. The novelty of this formation is based on 3 major ideas:

  • Co-construction of the formation by experts and journalists. For each issue of this training (past and future climate changes, biodiversity, justice, social impacts, economy, energy…), the courses were delivered by two teachers; one scientific expert and one journalist.
  • The structuration in different themes. Indeed, in most media, there is only one journalist that is responsible for climate and environment. Now that climate changes have modified many aspects of life in general, it is necessary to take them into account.
  • The accessibility. We decided to train through online-only courses at the level of a Master’s degree. For this first step, we used the large network of ESJ Lille and a collaboration with French-speaking countries to deliver all the lessons in French. This strategy allows students and journalists from more than 20 countries to gain access to this training. For instance, we have students from Haiti, Cameroon, Senegal, Algeria, Ivory Coast, Vietnam, Cambodia, Belgium…

 

The present evolution of this training is as followed:

  • Thematic evolution. We are now building new teaching modules that are not based on large issues, but rather on regions which allow us to tackle all the associated impacts. The first one has been finished last year on the Mediterranean basin; and a new one will be developed on the polar region.
  • Audience evolution. At the beginning, we only had 15 students, most of them being master degree’s students. Now, we have more than 55 students (and more than 150 applications per year), mostly journalists and continuing-education profiles.

The next step, and the main reason for this talk, is to push for similar trainings in different countries. We already have a relationship with South Korea, and would like to provide an English version of our training to share our experience with other scientists and journalists from different countries.

How to cite: Ramstein, G., Lansard, B., and Aballain, O.: Climate and Media: an efficient and original training for journalists, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9101, https://doi.org/10.5194/egusphere-egu24-9101, 2024.

EGU24-9402 | Orals | EOS1.1

Supporting Children’s Space Careers Education: “I’m a Space Person”  

Martin Archer, Cara Waters, Simon Foster, Antonio Portas, and Carol Davenport

Educational research shows participation issues across Science Technology Engineering and Mathematics (STEM) are largely due to whether students see these areas and their potential career opportunities as relevant and accessible to “people like me”. These perceptions form early and remain relatively stable with age, which has led to recommendations for increased provision and quality of careers education/engagement at both primary and secondary levels. Of STEM-related fields, the space sector is one of the most diverse and rapidly growing industries worldwide and of strategic priority to many countries. This highlights the need for space careers education in particular. We introduce a new space careers resource “I’m a Space Person”, which leverages personal attributes to help children identify with different space careers. Information about each of the 36 varied roles featured is distilled down onto a simple postcard format, with an accompanying website to enable further exploration. Resources for parents/carers and teachers are also provided to assist them in supporting children’s careers education. We present the development process of this resource and its usage thus far by the UK Space Agency in a nationwide roadshow. Finally, we discuss how the existing resources could be used and adapted for different countries and contexts.

How to cite: Archer, M., Waters, C., Foster, S., Portas, A., and Davenport, C.: Supporting Children’s Space Careers Education: “I’m a Space Person” , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9402, https://doi.org/10.5194/egusphere-egu24-9402, 2024.

EGU24-9830 | Posters on site | EOS1.1

Engaging with Local Spaces: Student-created digital field tours to facilitate community learning 

Heidi Daxberger, Sarah Peirce, Katie Maloney, Andreia Hamid, Marco Esquivel Spindola, Teagan Sharrock, Magnus Roland Marun, Lingfei Liu, John Johnston, Kirsten Kennedy, Phillip Ruscica, Deana Schwarz, and Hazen Russell

The disciplines of geology and physical geography often rely on experiential learning and real-world observations, like those offered on field trips, to share knowledge and engage students. During the shift to online teaching during the COVID-19 pandemic, those in higher education had to quickly embrace innovative technologies (e.g., handheld LiDAR scanners, 3D scanner apps, affordable drones, and 360-cameras) and online applications such as ArcGIS StoryMaps to simulate these field investigations. 

Here, we are applying what we learned in higher education teaching to share knowledge and engage the general public with the geology and geomorphology of their region. Furthermore, we are employing a user-created content approach, whereby university students create educational content aimed at other students and the general public, to enhance their learning and professional development. 

Since 2020, undergraduate and graduate university students have collected photos, synthesized literature, and created digital content of outdoor spaces that can be explored freely online. This content includes digital tours of urban and natural spaces highlighting local points of interest, with a focus on geology and geomorphology (e.g., tour of the University Campus, regional geology of Southern Ontario), presented with ArcGIS StoryMaps.

Our goal is to equip all users with fundamental scientific knowledge, along with real-world observations and examples, so that they can recognize natural landforms and processes (like weathering and erosion) while deepening their understanding of the role and impact of human activities (e.g., erosion control) on the environment. To engage users and have them reflect on their learning, we will be incorporating interactive components such as knowledge check questions and citizen science contributions (e.g., photo submissions, and observational surveys) in the StoryMaps. 

To monitor professional development and learning progress of our student creators, we will include goal-setting and self-evaluation components throughout the project. Student creators will also be asked to evaluate whether participating in these projects enhanced their connection with their environment, provided opportunities to apply knowledge from their classes, and helped develop a sense of accomplishment given the finished products, their ability to share knowledge with others, and their ability to learn new skills and technologies.

Beyond regional geology and University campus tours, we are now expanding the network of sites into popular recreational spaces like parks and walking trails alongside interesting natural and designed landscapes, like urban rivers. These projects consider regional geology alongside surface processes, natural hazards, and environmental change, as well as the connections between historical and cultural context with the landscape.

How to cite: Daxberger, H., Peirce, S., Maloney, K., Hamid, A., Esquivel Spindola, M., Sharrock, T., Marun, M. R., Liu, L., Johnston, J., Kennedy, K., Ruscica, P., Schwarz, D., and Russell, H.: Engaging with Local Spaces: Student-created digital field tours to facilitate community learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9830, https://doi.org/10.5194/egusphere-egu24-9830, 2024.

EGU24-10242 | ECS | Orals | EOS1.1

Creating safety through media narratives: A framework for investigating potential biases in describing adverse complex phenomena. 

Martina Ivaldi, Fabrizio Bracco, Marina Mantini, and Luca Ferraris

In the contemporary era dominated by media, communication channels significantly shape citizens’ perception and preparedness for environmental emergencies. Specifically, media narratives about floods contribute significantly to citizens’ comprehension of river conditions, warning systems, and appropriate behaviors for safety. However, if these narratives oversimplify events there is a risk of limiting citizens’ learning, potentially leading to distorted perceptions. Similarly, media descriptions that focus on assigning blame, spotlighting the negligent behavior of infrastructure managers, scientists, politicians, and others, may lead citizens to perceive the event solely because of individual mistakes or violations. This perspective has the potential to foster a sense of citizen disengagement during emergencies, instead of emphasizing the pivotal role that each individual plays in ensuring safety during floods. Moreover, when institutions errors occur, such as inaccurate predictions, public opinion may deem these institutions unreliable, nurturing mistrust. Distrust in institutions negatively affects the communication of risk to the population, risking the cultivation of a heightened sense of autonomy among citizens, which could potentially translate into risky behaviour.

In the aftermath of floods, individuals form explanations and beliefs that influence their behavior. Therefore, media narratives should consider multiple factors for a comprehensive understanding.

This research aims to investigate whether media descriptions of a flood event in the Marche Region, in Italy, on September 15-16, 2022, exhibit tendencies towards oversimplification of causal factors, individual culpability, signs of institutional distrust, or whether the narratives account for the complexity of the phenomenon through a systemic approach. The event was caused by a severe storm, resulting in injuries and fatalities eight years after a previous flood.

This research was conducted in three distinct phases. The initial phase involved the creation of a dataset through an extensive review of narratives provided by the Civil Protection Unit of Marche Region in articles published in both local and national newspapers. In the second phase, various themes were outlined based on the literature covering blame approach, systemic approach, and institutional distrust in the context of natural disasters. A framework organized into four categories was established: 1) simplistic descriptions of causes, 2) inclination to attribute blame to institutions, groups, individuals, 3) indicators of institutional distrust, and 4) systemic and multifactorial perspectives. In the third phase, independent judges were tasked with evaluating the presence of these categories of the framework within the media review. Inter-judge agreement was then calculated to validate the framework, ensuring a thorough analysis of the media narratives surrounding the flood event. We discuss the potential usefulness of the framework for the assessment of media narratives accuracy and as a guide for future accounts of complex natural disasters, for the sake of fostering in citizens a proper representation of the events, an accurate risk perception and, eventually, setting the ground for community resilience.

How to cite: Ivaldi, M., Bracco, F., Mantini, M., and Ferraris, L.: Creating safety through media narratives: A framework for investigating potential biases in describing adverse complex phenomena., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10242, https://doi.org/10.5194/egusphere-egu24-10242, 2024.

EGU24-10867 | ECS | Orals | EOS1.1

"Up-Goer Five Challenge": A way to make science more accessible? 

Philipp Aglas-Leitner, Maxime Colin, Caroline Jane Muller, Yi-Ling Hwong, and Steven Sherwood

Scientists of all fields share a duty to communicate their findings to the public. This is especially true in a time where false claims spread like wildfire and the correct information has a hard time receiving the necessary attention. Therefore, a multitude of different science communication approaches has been developed, including the so-called "Up-Goer Five Challenge". In recent years, this particular approach, sparked by an XKCD comic blueprint of the Saturn V Rocket, has become very popular among many science communicators and has even made its way to several scientific conferences.

The aim of this challenge is to encourage scientists to describe their research or other complex scientific topics in very simple terms, by only using the thousand most commonly used words. Apart from encouraging scientists to rethink jargon-loaded presentation styles, this approach has the advantage of potentially reaching a very broad audience by making science more accessible and at the same time inspire researchers to improve their communication skills and even see their own work from a different angle. However, this communication method will, of course, also come with certain downsides, as for example, depending on the audience, a very rigid application of the rules of the game might end up being more of a hurdle than a beneficial way of presenting complex issues.

Here is an example describing an atmospheric phenomenon called "Convective Memory":

Each day, when we look up in the sky, we can see those white soft-looking flying things above our heads. Sometimes they are tiny. One piece here, and another further away. But on some days, they can get really big and dark. Even kind of angry-looking. And then we, very often, wonder "Why do you have to be above my head and not somewhere else?"

One of the reasons is that this flying sky water has a very good memory and obviously likes to stay where it is: "I very much enjoy it here. I don't care if those humans down there are annoyed with me."

This memory works a bit like the piece of paper that you take with you when you go shopping so you don’t forget what to buy. This way, you can’t easily forget what you wanted to buy and stick to the stuff you need. This will help you even if the store owner decides to move some or all of the shopping goods in the store to another place. Thanks to that store owner, it is possible that you end up with "new" stuff that was not planned but you will at least have your piece of paper (your memory) to get the stuff you really need (see Maxime Colin 2020). The white flying things in the sky are like people going shopping: with a good memory, they stick to what they are, and do not become "new" and bigger so easily.

In this talk, we present the "Up-Goer Five Challenge" as applied to Convective Memory, discuss some challenges faced in using it, and offer potential remedies.

How to cite: Aglas-Leitner, P., Colin, M., Muller, C. J., Hwong, Y.-L., and Sherwood, S.: "Up-Goer Five Challenge": A way to make science more accessible?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10867, https://doi.org/10.5194/egusphere-egu24-10867, 2024.

EGU24-11368 | ECS | Orals | EOS1.1

Hilfswerk International: An NGO in Central Asia as Science Communicator between the Society, Governments and the Private Business Sector 

Gisela Domej, Stoyanka Manolcheva, Umed Aslanov, and Shuhrat Qodirov

A commonly encountered hurdle to overcome in international project implementation - particularly between “Western” and developing countries - are communication standards as cultural and language barriers as well as country-specific political or hierarchical structures may differ considerably.

In this context, we present the Central Asia Mission of the Austrian NGO Hilfswerk International (HWI; www.hilfswerk.tj) and its role in general communication and decision-making at the interface between science, society, and governments. Drawing from the experience of two different project setups, we delineate its activities not only in outreach but also in feedback transfer.

First, we discuss the classic geoscientific PAMIR Project dedicated to a large-scale geohazard assessment in Central Asia. Besides the traditional expected scientific outcomes, one major aspect of the project was to improve the livelihoods of local communities. Here, Hilfswerk International gradually deepened communication links among relevant stakeholders and actively engaged in the design, implementation, and coordination of actions directly dedicated to mountain communities. Key outreach activities consisted of training and info-campaigns, involving specialized staff like social workers, publications in different languages, gathering feedback and evaluation of the perception of tasks, personal visits to residents and direct talks to local communities, adapted means of communication and science dissemination, school programs, emergency awareness building at different levels, respecting of typical hierarchies (e.g. the Kyrgyz Ayl Ykmyty or the Afghan Village Council), etc.

Second, we present the mechanism of operation of an agro-economic project series initially consisting of two different grant concepts: economic development of small farming in the framework of the EU Program “Central Asia Invest”, and food safety on academic levels within Erasmus+. Hilfswerk International individually designed communication strategies ultimately linking (initially non-complementary) project types and creating win-win situations through outreach. For example, experiences of local farming communities were incorporated into academic curricula, while agricultural standards elaborated on academic levels were brought back in adequate forms to respective units of produce, i.a., by tailored training for farmers, round-tables, or the creation of local working groups that nowadays sustain themselves.

From these – and other – projects, we conclude several essential points:

  • Science often serves as a neutral base for argumentation and a ground for mutual agreement; however, it needs to be communicated in a way understandable for all involved parties respecting mentalities, traditions, cultural differences, levels of education, and the local context.
  • Strategies of science communication are to be adapted for every project, requiring versatility and flexibility; here, NGOs as non-partial organizations might have a wider scope.
  • Cooperation through a neutral science communicator has a positive effect on the working climate and, in the long term, makes communication channels self-sustaining.

At the example of Hilfswerk International, we point out the beneficial role of NGOs in general communication and outreach as successful international cooperation will become increasingly important in times of climate change, environmental pollution, water security, and resource consumption.

How to cite: Domej, G., Manolcheva, S., Aslanov, U., and Qodirov, S.: Hilfswerk International: An NGO in Central Asia as Science Communicator between the Society, Governments and the Private Business Sector, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11368, https://doi.org/10.5194/egusphere-egu24-11368, 2024.

In an area of widespread misinformation, it is crucial for scientists to reach out to the general public and explain their research topic to increase knowledge and, more importantly, to enhance curiosity and to stimulate people to pay more attention to their geophysical environment. The general aim of this research is testing an innovative approach to actively engage people on geosciences topics, in a funny and informal way, through short interactive food-related activities. As rainfall scientists, we carefully designed these activities to unveil part of the underlying complexity of this geophysical field. In particular, we focus on the  extreme variability of rainfall over wide ranges of scales in both space and time, of which people are usually unaware despite commonly experiencing rainfall. 

 

Each activity is designed with similar underlying concepts: 1) A single simple take home message on rainfall. 2) The studied feature is visible at first sight to strike people’s minds. 3) Real rainfall data is somehow mimicked with food. 4) The activity itself lasts a few minutes. 5) It is designed as a game to foster people's engagement. 

 

Various activities were designed with these specifications. An illustration is the rainfall drop size distribution variability which is highlighted through sweet or salty cookies (ex: macaron / “baci di dama”) representing drops variability in shape and in the actual size in their fall. Another illustration is the representation of rainfall monthly distribution and its variability, through the use of glasses with liquid (champagne, soda, water…) height corresponding to rainfall depth during a month. In each case, there is an incentive to engage in the game through the hope of getting the bigger cookie or most filled glass. Activities are implemented in informal settings (family, friends, lab meetings) during either snacks or dinner. In the former case, a single one is carried out while in the latter several ones -typically one per course- are. 

 

In order to evaluate if active engagement is indeed achieved, the following methodology is implemented. During the activity, a previously briefed outside observer fills a pre-defined grid to assess the level of engagement of people. After the activity, people are invited to let us know  about new ideas, observations, questions, and send us pictures on the topic of the activity. The latter step is much more qualitative. As a side product, how the “take home messages” are remembered by people is also partially assessed keeping the informal approach of the activity.  Implementation and interpretation of the activities in various contexts will be discussed in this presentation.

How to cite: Gires, A. and Dallan, E.: Actively engaging people on rainfall (or any geoscience topic) through short interactive food related activitie, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11442, https://doi.org/10.5194/egusphere-egu24-11442, 2024.

EGU24-11655 | Posters on site | EOS1.1

Raising awareness to geo-hydrological hazard risks in African countries: A guide booklet for stakeholders, policy markers and the public at large 

Olivier Dewitte, Joseph Martial Akame, Diawara Bandiougou, Özlem Adiyaman Lopes, Antoine Dille, François Kervyn, Benoît Smets, Caroline Michellier, and Camille François

Many regions of Africa are exposed to a large variety of geo-hydrological hazards such as earthquakes, volcanic eruptions, landslides, floods, karst collapses and large urban gullies. Despite the soaring impacts on population, infrastructure and the environment associated with the occurrence of these hazard risks, most regions are under-studied. In addition to this lack of information, stakeholders, policy makers and the public at large remain relatively poorly aware of the hazard and risk problems, whether it is about their causes, their impact, and/or their mitigation. This overall lack of knowledge and awareness is associated with an aggravation of the impacts as the growing and vulnerable population of these regions, in search for new settlements and opportunities, is often moving towards areas that are more prone to natural hazards. This is in this context that UNESCO supports the preparation and dissemination of a guide booklet on geo-hydrological hazards for stakeholders, policy makers and the general public. The booklet targets ten African countries (Angola, Burundi, Cameroon, Central African Republic, Chad, Democratic Republic of the Congo, Equatorial Guinea, Gabon, Republic of the Congo, São Tomé and Príncipe) that are covered by the UNESCO regional office of Yaoundé. The aim of this work is to raise collective awareness of the need to prevent natural hazard risks at local, regional and national levels in order to ensure the protection of populations and promote the sustainable development of territories. In this way, UNESCO aims to guide and advise the ten African countries by providing them with useful and practical information.

How to cite: Dewitte, O., Akame, J. M., Bandiougou, D., Adiyaman Lopes, Ö., Dille, A., Kervyn, F., Smets, B., Michellier, C., and François, C.: Raising awareness to geo-hydrological hazard risks in African countries: A guide booklet for stakeholders, policy markers and the public at large, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11655, https://doi.org/10.5194/egusphere-egu24-11655, 2024.

EGU24-11941 | ECS | Orals | EOS1.1

Communicating the KNMI’23 Climate Scenarios for the Dutch Caribbean   

Iris Keizer, Nadia Bloemendaal, Peter Siegmund, and Rein Haarsma

We share insights from the communication efforts surrounding the KNMI`23 climate scenarios for the Dutch Caribbean islands of Bonaire, Sint Eustatius, and Saba (the BES islands). The scenarios were published by the Royal Netherlands Meteorological Institute (KNMI) in October 2023. We focus on the approach used, lessons learned, and insights gained. We communicate our scenarios through various approaches, including a report aimed at the general public, active engagement with stakeholders, end-users, policy and decision makers, and local communities through presentations, workshops, and discussions. These interactions aim to increase awareness, understanding, and cooperation. We aim to provide valuable insights for policy and decision makers and scientists across disciplines. As a government institute, we are committed to conducting policy-relevant research that supports the development of climate plans tailored to each BES island. This presentation examines the challenges, successes and lessons learned from our communication initiatives.

How to cite: Keizer, I., Bloemendaal, N., Siegmund, P., and Haarsma, R.: Communicating the KNMI’23 Climate Scenarios for the Dutch Caribbean  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11941, https://doi.org/10.5194/egusphere-egu24-11941, 2024.

EGU24-11952 | ECS | Orals | EOS1.1

Connecting worlds: Mutual benefits of teacher–researcher interaction. 

Rory Selby-Smith, Siobhán Power, Fergus McAuliffe, Hannah Binner, and Elspeth Sinclair

Launched in 2021, the Geoscience for Leaving Certificate Geography Continuing Professional Development Course, run by iCRAG, the Science Foundation Ireland research centre in Applied Geosciences, and Geological Survey Ireland, a division of the Government of Ireland, has entered its third iteration. Addressing the absence of geoscience as a standalone subject in Irish schools, this course introduces post-primary teachers, and therefore their students, to geoscience through the non-compulsory subject of geography. 

In this course, teachers work in collaboration with geoscience researchers to produce an array of free, readily accessible geoscience resources via the iCRAG and Geological Survey Ireland websites. This addresses the shortage of specialised geoscience material available to Irish geography educators, thus ensuring that students have access to contemporary and accurate geoscience information. Furthermore, the involvement of teachers from a variety of educational contexts guarantees that the resulting lesson plans are versatile and suitable for a broad spectrum of educational settings.

In the 2023 iteration of the course, a diverse range of educational resources were developed, including field guides, a 6-week module and lesson plans. These materials integrated seven of the eight recognised active learning intelligences: Linguistic, Logical-mathematical, Visual-spatial, Bodily-kinaesthetic, Interpersonal, Intrapersonal and Naturalistic. With the support of researchers, teachers were able to incorporate essential geoscience skills such as field work, data collection, mapping/GIS, critical thinking and other scientific skills into the curriculum. The lessons were differentiated to meet the varied needs of students, whilst ensuring there was a focus on the Leaving Certificate exam (the final exam of the Irish secondary school system and main gateway to third level). Teachers reported significant benefits from their interactions with geoscientists, appreciating the opportunity to consult with specialists for in-depth inquiries and clarifications. Likewise, it is hoped that students reap the rewards of this educational approach, deepening their understanding of geoscience.

Researchers, from iCRAG and Geological Survey Ireland, participating in the program also derived significant benefits, particularly in gaining an understanding of how to distil complex scientific topics for a varied student audience, something that teachers are expert at. The preparation phase for their presentations underscored the importance of balancing technical accuracy with the existing curriculum constraints, an important consideration given the occasional misalignment between current geoscience knowledge and the content of the Leaving Certificate geography syllabus. This exposure to curriculum limitations gives researchers an insight into the public’s perception of science. Additionally, teachers exposed the researchers to a range of student perspectives, such as the diverse reactions to geothermal energy. Also, the observation of differentiated teaching methods, which are not often found in the traditional university lecturing styles, provided invaluable insights into the diversity of educational approaches.

The CPD course exemplifies a successful model of collaboration between teachers and geoscientists, enhancing geoscience education while providing mutual benefits. It not only enriches the teaching methodology but also offers researchers a unique perspective on the dissemination of scientific knowledge, thereby bridging the gap between academic research and practical classroom application.

How to cite: Selby-Smith, R., Power, S., McAuliffe, F., Binner, H., and Sinclair, E.: Connecting worlds: Mutual benefits of teacher–researcher interaction., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11952, https://doi.org/10.5194/egusphere-egu24-11952, 2024.

EGU24-12003 | Orals | EOS1.1 | Highlight

Climate Change: Communicating What We Don’t Know 

David Stainforth

When it comes to communicating climate change, both our understanding of what we don’t know and the uncertainties in the science are themselves core elements of our knowledge. That’s to say, what we know about uncertainty is part of what we know. Failing to communicate uncertainty and the limits of our understanding is failing to communicate the full picture of climate change.

In 2023, after many years of writing, my book, “Predicting Our Climate Future: What we know, what we don’t know, and what we can’t know”, came out. The book is targeted at a public audience and addresses the many exciting, deep, conceptual and practical challenges that we face in climate change science and climate change social science. It aims to show that there are fundamental questions here that are simply fascinating in themselves: intrinsically interesting irrespective of the social relevance of the research.

In doing this it has to shine a spotlight on the many things that we don’t know - particularly our limited ability to describe the climate of the future at local scales, and the consequences of climate change for the societies in which we live. Some might be concerned that doing this could undermine trust in climate science and work against our ability to tackle climate change. In practice the opposite is true. Acknowledging and presenting the limits of our knowledge upfront, increases the credibility of climate change information. It also provides a handle for people and diverse disciplines to actively engage with climate science and to bring their values and attitudes to risk into the debate.

Of course it is also important to be clear about what we do know: what really isn’t open to debate and why. Here I will discuss how I approach this balancing act between communicating the exciting aspects of what we don’t know while being clear about what we do. I will also discuss my experience of presenting these issues to public, academic and business audiences.

 

Further materials:

Stainforth, D., “Predicting Our Climate Future: What we know, what we don’t know and what we can’t know”, Oxford University Press, 2023.
(https://global.oup.com/academic/product/predicting-our-climate-future-9780198812937)

Stainforth, D.A. The big idea: can we predict the climate of the future?, The Guardian, 30th Sept 2023
(https://www.theguardian.com/books/2023/oct/02/the-big-idea-can-we-predict-the-climate-of-the-future)

Podcast: Instant Genius - Can we predict the climate of the future?

Podcast: Challenging Climate - Models and uncertainty

Podcast: Empty Space Inbetween - In conversation with David Stainforth

How to cite: Stainforth, D.: Climate Change: Communicating What We Don’t Know, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12003, https://doi.org/10.5194/egusphere-egu24-12003, 2024.

EGU24-12836 | Posters on site | EOS1.1

Enriching the inclusivity of geophysical data communication using tactile resources  

Adam Booth, Raymond Holt, and Briony Thomas

There is an increasing demand on the geoscience community for effective dissemination of data and inferences, equitably engaging a wide audience with communication resources. Geophysical surveys are widely applied to image subsurface structures, in disciplines spanning archaeological mapping, delineating environmental and engineering risk, and resource assessment. Many of these disciplines are of great interest to public stakeholders, whether they inspire curiosity, inform local planning decisions or extend to government policy.  

As informative as geophysical images can be, they are almost exclusively presented in visual formats. Our project explores how geoscience engagement can be enriched for users with a visual impairment and/or neurodiverse condition, by converting geophysical images into tactile surfaces. Working with a local heritage agency (Barnsley Museums, UK), our initial prototypes are tactile versions of geophysical data acquired over buried industrial archaeology at the Yorkshire village of Elsecar. Through a series of co-creative interviews, we are appreciating the requirements of visually-impaired users and progressively refining the design of the tactile models – while ensuring that production remains practical (i.e., cost effective, durable product). A key consideration is the amount of detail in a dataset that can be appreciated by touch alone, requiring a balance to be struck between offering the full complexity of the geophysical dataset versus presenting a simplified interpretation. Other issues to consider include ensuring sufficient relief such that features can be discerned (workshops suggest 4 mm is both effective for a user, and practical from a manufacturing standpoint), and how to convey distance and orientation.  

Three fabrication materials have been tested to date: plywood, swell paper and acrylic. Although plywood is cheap, it proves to be insufficiently robust and carries a grain that distracts from the features of interest. Swell paper (paper which, when heat-treated, swells to produce a low-relief topography) is also cheap, and may be valuable for large-scale outreach in which the outreach resources can be considered disposable (e.g., newsletters, schools programmes, etc). Acrylic shows the most promise for permanent installations, such as in museum exhibits: while expensive, it is robust and durable, and its translucency means it could be backlit to exaggerate contrast for users with residual sight. 

We envisage presenting tactile models of the archaeological site in Barnsley Museums’ exhibits, but our broader aim is to define a series of design considerations that would allow any geophysical dataset to be effectively reproduced as a tactile surface.  

How to cite: Booth, A., Holt, R., and Thomas, B.: Enriching the inclusivity of geophysical data communication using tactile resources , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12836, https://doi.org/10.5194/egusphere-egu24-12836, 2024.

EGU24-12980 | ECS | Posters on site | EOS1.1

Phoebe Paints Rocks: Creative geologist and adventurer 

Phoebe Sleath

When on PhD fieldwork on the Pembrokeshire coast in SW Wales in 2021, in my breaks I would paint the view of the rocks and sea with watercolours. I noticed that when painting I was making useful geological recordings and interpretations, which I included in my research. I bought a sketchbook and started to paint whenever I was outside, both on fieldwork and adventurers into the hills hiking and climbing. By allowing me to take the time to properly look at the changing landscape, painting became a process that increased my understanding of geology, the world, and my place within both.

Through finding my creative voice as an artist, I also found my voice both as a scientist and a person. It became easier to communicate my research, helping with writing, discussions with colleagues and drawing figures. My research moved to explore the creative side of geology, the uncertainty in how we observe and interpret faults in mountain building areas, and the way geologists communicate their findings through drawings and illustrations. I am interested in connection and perspective of landscapes across time. As a qualified Mountain Leader I love sharing the outdoors with others, to share skills and stories.

Sharing my work with others on social media has led to lots of opportunities including exhibitions and events with the Scottish Mountaineering Press, the Scottish Geology Trust, North East Open Studies, Fort William Mountain Festival and Artist-in-Residence for the Dundee Mountain Film Festival. I find people are interested in my connection to the landscape, my painting process and how they can connect better with the landscapes they love and want to protect.

How to cite: Sleath, P.: Phoebe Paints Rocks: Creative geologist and adventurer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12980, https://doi.org/10.5194/egusphere-egu24-12980, 2024.

EGU24-13276 | Posters on site | EOS1.1

Raising Sand's Value Awareness: Science and Communication Initiatives. 

Teresa Drago, Jacqueline Santos, Emanuel Surducan, Ana Alberto, João Afonso, Ana Ramos, and Aurélie Fernandes

Sand is one of the most used resources in the world (50 billion tonnes per year). It plays a strategic key role in delivering geosystems services, maintaining biodiversity, supporting economic development, and securing livelihoods within communities (UNEP, 2022). Sand is everywhere in our societies: buildings, roads, dams and other infrastructures. Despite this “endless” use, sand is a finite resource, and its use occurs at a faster rate than its generation by geological processes. However, the importance of sand and the need of a sustainable management of this raw material are unknow to students at basic and secondary levels and to the public in general.

The EDUCOAST project (funded by EEAGrants) aims to promote nature-based education in coastal and marine geosciences through experimental learning. A series of initiatives to increase awareness on sand conservation were carried out as part of the EDUCOAST project. They included field and lab activities for basic and secondary school students at sandy environments (such as barrier islands and dunes) and observation of various types of sand from around the world under binocular microscope.  These “hands-on” activities focused on topics such as “what is the sand made of?” and “Let’s get to know sand better”. In total, about 500 students participated in these “hands-on” activities and the conducted surveys showed very positive feedback, where the students learnt more about these sandy environments (origin and their processes), the sand characteristics (grain-size, composition, carbonates contents) and the need for more sustainable management practices for the environmental conservation of the coastal systems.

Communication and outreach play an important role in achieving the proposed objectives. In this context, the project also participated in various initiatives such as the “European Research Night”, "Science in Summer" (promoted by the Portuguese Programme "Ciência Viva") and the "Week of Science and Technology" among others, making it possible to increase awareness in addressing issues like sand importance and conservation for approximately 700 people.

These initiatives contributed to highlight the importance of public awareness and the potential for positive change through informed and engaged students and general public.

This is a contribution of the EDUCOAST (EEAGrants, PT-INNOVATION-0067) and EMSO-PT (PINFRA/22157/2016) projects.

This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/ UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020)

Reference: UNEP 2022. Sand and sustainability: 10 strategic recommendations to avert a crisis. GRID-Geneva, United Nations Environment Programme, Geneva, Switzerland

How to cite: Drago, T., Santos, J., Surducan, E., Alberto, A., Afonso, J., Ramos, A., and Fernandes, A.: Raising Sand's Value Awareness: Science and Communication Initiatives., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13276, https://doi.org/10.5194/egusphere-egu24-13276, 2024.

EGU24-14964 | ECS | Posters virtual | EOS1.1

Strengthening the Bridge between Singapore and Norway: How Education Exchanges and Public Outreach are Applied in Climate Science 

Yu Ting Yan, Yun Fann Toh, Giuliana Paneiri, and Benjamin Horton

Universities have a critical role to play in the response and recovery from the climate crisis. As institutions, universities have been resilient to changes. This resilience supplies the human, intellectual, and financial capital to understand and address the major challenge of climate change. Singapore and Norway have education exchange programmes through various scholarship programs, research collaborations, and Erasmus+. In 2023, the third expedition of Advancing Knowledge of Methane in the Arctic (AKMA3) by the Arctic University of Norway (UiT) provided students from Singapore a platform to experience how offshore expeditions in the Arctic are conducted.

On board the Norwegian Research Vessel Kronprins Haakon, Singapore students used state-of-the-art research facilities to help collect samples and data from extreme environments (cold seeps) from high-latitudes seafloor. Daily interactions with international experts of different backgrounds help us to better understand the various aspects of the scientific work related to the expedition and outreach efforts undertaken to promote Arctic science to the public.

Here, we demonstrate how our learned experience in Norway can be applied to our research projects in Singapore. Despite the differences in geological location and polar and tropical climates, we strive to show how student collaboration can help build strength between the two countries. By highlighting the adaptability and transferability of acquired knowledge, this collaborative effort aims to transcend geographical boundaries and contribute to the global advancement of scientific understanding of climate change.

How to cite: Yan, Y. T., Toh, Y. F., Paneiri, G., and Horton, B.: Strengthening the Bridge between Singapore and Norway: How Education Exchanges and Public Outreach are Applied in Climate Science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14964, https://doi.org/10.5194/egusphere-egu24-14964, 2024.

EGU24-15324 | ECS | Orals | EOS1.1

Youth education and empowerment through outdoor experiential learning and peer-to-peer communication 

Jane Walden, Léa Rodari, and Kathrin Naegeli and the Girls on Ice Switzerland Team

Anthropogenic climate change is a daunting issue facing today’s society. In recent years, youth have shown a growing interest in preserving the planet by becoming involved in political demonstrations and school strikes. It is thus of paramount importance that youth are well-informed on the topic and equipped with the necessary skills to share information with their communities. We seek to educate youth, particularly those from traditionally underrepresented genders in the sciences, about geosciences, art, and mountaineering, especially in the context of ongoing climate change. 

At Girls on Ice Switzerland, we believe that first-hand experience is the key to both learning and motivating scientific concepts. We offer tuition-free glacier expeditions for teenage girls*, where the selection process is independent of academic performance, giving equal opportunities to all interested youth, and ensuring socio-cultural diversity within the team. During the week-long expedition, participants conduct artistic and scientific modules with professionals, learn new techniques and carry out an experiment in small groups, and finally present their work to the public. Following the expedition, school workshops led by participant-scientist tandems build upon the scientific content of the expedition, allowing participants to share their knowledge with peers and distribute scientific information to a broader audience. This fosters self-confidence in the participants, helping them to become scientific ambassadors for their peers, and also provides them with invaluable networking and mentoring opportunities through their interaction with female scientists. 

Through these steps, participants are exposed to the scientific process: experimental design and performance, resiliency in the face of unforeseen challenges, and analyzing and communicating findings. The expedition experience has been shown to be empowering for participants: it boosts their confidence, motivates them at a critical stage in their lives, and provides them the opportunity to learn from female role models. School workshops and expeditions allow former expedition participants to be leaders amongst their peers and further deepen their understanding of the topics. In this way, we prepare future generations of scientists and members of society to think critically, and this experience gives them the knowledge and power to dispense information within their communities as scientific ambassadors.

*cisgender girls and transgender, agender, nonbinary, intersex, and genderqueer youth

How to cite: Walden, J., Rodari, L., and Naegeli, K. and the Girls on Ice Switzerland Team: Youth education and empowerment through outdoor experiential learning and peer-to-peer communication, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15324, https://doi.org/10.5194/egusphere-egu24-15324, 2024.

Imagine that you  a (semi-governmental) scientific institute, conducting important and state-of-the-art research that you want to share with society. In addition to the science enthusiast that follows your every move and reads the news outlets that regularly cover your stories, you want to include groups of people that do not automatically come in contact with your communication efforts. How do you improve the accessibility of your science communication, specifically towards groups of people that are not automatically included? I will share valuable insights from my empirical social study on climate communication accessibility at the KNMI, the Dutch research and information center for meteorology, climate, air quality, and seismology.

In my presentation at EGU 2024, I will describe several factors that play a role on the perceived accessibility of climate change communication. These insights are based on interviews and focus groups held with respondents living in low socio-economic status neighborhoods and rural areas. In addition,  focus groups and interviews with KNMI-employees involved in climate communication took place.

[J(8] blog-like articles written by KNMI-employees were presented to respondents to read and evaluate. These articles aim to create understanding and awareness of climate phenomena and concepts and have been a vital part of KNMI's communication efforts for 10 years. I have analyzed this data through the lens of a conceptual model containing theories on accessibility and equity, models of communication, and framing and narratives.

My research confirms well-known factors which influence accessibility to broader audiences. For example, the excessive use of scientific jargon has a negative impact on the understanding and accessibility of communication. In addition, my research probes deeper to identify aspects that explain why these well-known factors cannot easily be overcome and to uncover which other, less obvious factors, play a role. Aspects like cultural identity, social acceptance and peer pressure, literacies and capital, recognition, and equity all play a part in the machine of social inclusion and accessibility of climate communication. Challenges and opportunities arise both within the institution and in relation to the social groups included in this research.

Based on the results and conclusions of this study, I will provide recommendations on how to improve the accessibility of climate communication to communities  that are typically reached to a lesser extent. While they are based on communication practices of the KNMI, they are generally applicable to other scientific institutions and/or governmental institutions. On the EGU 2024, I will present my recommendations to improve climate communication accessibility, as well as the results that these recommendations are based on.

How to cite: Johannes, B.: How to make climate communication more accessible to more  communities? Results from a case study featuring KNMI, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15622, https://doi.org/10.5194/egusphere-egu24-15622, 2024.

Geologists, Geoscientists, or Earth Scientists – however we identify or whatever we do in our daily work, we are needed for stable human habitation on our planet in the future. Although people who know and understand the Earth are needed, there has been a decline in the number of people considering the possibility of entering our professions. What are we doing about it in Ireland? 

Ireland has a relatively good education system and a population with an interest in natural science, and yet the Earth-related sciences do not feature strongly in the national curriculum at primary nor secondary level, there is no national science museum, and with teachers lacking the tools to inspire students, very few students are doing degrees in the Earth sciences and continuing in careers in those areas. 

Various professional, cultural, and educational organisations have been working separately and together to address this issue in the last few years, and while the feedback is encouraging, and progress is being made, there is a lot more to be done. Some of the activities include a temporary exhibition at the national museum, a primetime television series, professional scientists input to national curriculum development, sponsoring of national young scientist prize, co-creation of teaching resources, teacher workshops, and an increase in publicly funded outreach projects.

As we look towards the next phase of activities and plans in a crowded and busy field of science communications and messaging, we need to learn from international best practice, place ourselves in the global context, and work together in a co-ordinated way to inspire the next generations to enable humans to question, understand, and live sustainably on the Earth.  

How to cite: Power, S.: We need new generations of people who know about the Earth – what are we doing about It … in Ireland?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16522, https://doi.org/10.5194/egusphere-egu24-16522, 2024.

EGU24-17240 | Posters on site | EOS1.1

From research to outreach – an example from the Smøla island, Mid-Norway 

Guri Venvik, Øystein Nordgulen, Matthew Hodge, Eline Barkaas Garseth, and Per Terje Osmundsen

The BASE project, short for Basement Fracturing and Weathering on- and offshore Norway, is a research project funded by the Norwegian Research Council. While the project`s primary focus has been on disseminating its findings through scientific channels, there is growing interest emerging from local communities and schools. After several seasons of extensive fieldwork and a comprehensive core drilling campaign, we have observed an increased local curiosity and interest, particularly regarding the "why" and "what" behind our efforts. In our quest to synthesize the wealth of collected data, our goal is to contribute to a local geological exhibition showcasing updated bedrock information and delivering a compelling geological narrative of the Smøla island. This exhibition will illuminate the age of the rocks, the processes that formed them, and unravel the intricate story they convey. Our fieldwork has uncovered remarkable geological outcrops, which we believe should be shared with the broader community. In collaboration with the local “Friluftsliv” (outdoor life) community, we plan to create stops along their popular “Stikk UT!” routes. These routes and paths are clearly marked on maps and equipped with informative signs. We plan to incorporate geological insights about selected outcrops to enrich the experience for those who visit this remarkable area. Furthermore, in addition to our outreach efforts, we are dedicated to making our research relevant for primary and secondary school, with specific focus on 5th and 8th -grade pupils studying geology as part of their curriculum. To achieve this, we will employ a comprehensive approach that includes interactive storytelling on the Geological Surveys website, Geologisk arv (ngu.no) (Geoheritage), and we will provide ample information to teachers. By combining these strategies, our aim is not only to make geology accessible, but also to make it attractive and fascinating for the 5thand 8th -grade pupils. We hope to inspire the next generation of geologists and curious minds based on the captivating geological history of Smøla.  References (format style Heading)Geologisk arv (ngu.no)Stikk UT!

How to cite: Venvik, G., Nordgulen, Ø., Hodge, M., Barkaas Garseth, E., and Osmundsen, P. T.: From research to outreach – an example from the Smøla island, Mid-Norway, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17240, https://doi.org/10.5194/egusphere-egu24-17240, 2024.

EGU24-17948 | Orals | EOS1.1

Know before you act. Effective risk education (should) starts from knowing gaps and preconceptions. A case study on sea level rise. 

Stefano Solarino, Gemma Musacchio, Maddalena De Lucia, Elena Eva, and Marco Anzidei

Nowadays everybody agrees that increasing preparedness for natural and not-natural hazards and fostering best practices is of paramount importance for a resilient society. Therefore, in the last years many scientific projects included a task, a work package - or were themselves - fully devoted to transferring the results of the studies carried on within the project to the society. This included intensive education activities to train people about a specific hazard.

However, educative and dissemination packages are often too generic or too specific, especially in cases where the natural hazard is not well known by the public or affects a limited area or population. In these cases, it may be helpful to carry out preparatory research to finely tune the educational aims/objectives.

We present the results of an online survey carried out in 2020–2021 to understand citizens’ level of knowledge about the phenomenon of sea level rise, including causes, effects and exacerbation, in order to finalize educational tools.

Since the last century, global warming has triggered sea level rise at an unprecedented rate. In the worst-case climate scenario, sea level could rise by up to 1.1 m above the current level, causing coastal flooding and cascading effects, thus affecting around one billion people worldwide and potentially becoming one of the most important climate issues in the future.

Our survey revealed that, although widespread and threatening, the phenomenon is not well known to citizens as it is often overshadowed by other effects of global warming. The results of our study were peculiar to prepare an educational campaign and set up initiatives for students and the public.

How to cite: Solarino, S., Musacchio, G., De Lucia, M., Eva, E., and Anzidei, M.: Know before you act. Effective risk education (should) starts from knowing gaps and preconceptions. A case study on sea level rise., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17948, https://doi.org/10.5194/egusphere-egu24-17948, 2024.

EGU24-19052 | ECS | Orals | EOS1.1

uniWeather™: Advancing real-time outreach in urban environmental sciences through app and platform 

Gregor Feigel, Matthias Zeeman, Marvin Plein, Dirk Schindler, Andreas Matzarakis, Andreas Christen, and Swen Metzger

Research concerning the general public and influencing decision-making necessitates timely dissemination of easily accessible results and data, with a focus on directly verifiable hands-on exploration rather than authoritative assessments in order to raise awareness and engage the public. This applies, for instance, to the high spatial and temporal resolution street-level weather and thermal comfort monitoring network operated in the City of Freiburg. Germany, by the University of Freiburg, to raise awareness for the significant spatial and temporal differences in, e.g., outdoor heat stress patterns in urban areas, which are crucial for informed urban planning and climate resilience. 

Addressing this gap, the uniWeather™ app and platform were developed to provide end-users, stakeholder and the general public with free, easily accessible near-real-time data and interpretation. With regard to the FAIR principles, the platform is being developed to support data form other research organisations such as universities, government agencies or companies that operate environmental sensor networks to be provided free of charge. uniWeather™ aims to encourage the sharing and access to data in near real-time by providing an easy-to-integrate service for tailored visualisation and interpretation.

In June 2023, the uniWeather™ app and monitoring network were announced in a press release from the University of Freiburg and in a newspaper article providing access to maps and real-time data from 42 street-level weather stations in the Freiburg region within 60 seconds of measurement. The app was readily welcomed by the public, researchers and the city of Freiburg. The project was also well received at public outreach events such as the Eucor-MobiLab Roadshow 2023 in Freiburg (26-30 June 2023) and the exhibition DATEN:RAUM:FREIBURG (4-31 August 2023) of the city of Freiburg. With more than 1.5k users in the first few weeks and continued interest in further functionalities, the platform will be continued and further developed to address the needs of the general public and different scientific communities.

How to cite: Feigel, G., Zeeman, M., Plein, M., Schindler, D., Matzarakis, A., Christen, A., and Metzger, S.: uniWeather™: Advancing real-time outreach in urban environmental sciences through app and platform, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19052, https://doi.org/10.5194/egusphere-egu24-19052, 2024.

EGU24-19582 | Posters on site | EOS1.1

Interactive visualisation system for compound weather and climate extremes in Hungary based on station data series 

Zsuzsanna Dezső, Márk Zoltán Mikes, and Rita Pongrácz

Due to climate change, the frequency and intensity of extreme weather events is expected to increase. Compound events, when several extreme events occur simultaneously or amplify each other, may also become more frequent in the future. To provide a realistic picture of the extremity of everyday weather events to citizens, it is important to show which phenomena are considered extreme in a given location and season. For this purpose, we developed an interactive visualisation system for the compound weather and climate extremes in Hungary. The system uses the daily measured data of 70 synoptic and climatological stations in Hungary from 2002 to the present, which are available in the database of the Hungarian Meteorological Service. The following extreme events and their intensities are calculated from the stations’ data series: days with extreme cold and warm mean temperatures, days with extreme warm maximum temperatures, days with extreme cold minimum temperatures, days with extreme daily temperature range, stormy days, days with extreme high precipitation, extreme rainy periods, extreme dry periods.The visualisation system allows users to view the extremity of weather events for a single station, regionally or nationally, with customised settings. This tool can be used as a communication platform from scientists towards non-professional users to raise climate change awareness with a special focus on extremes with high potential impacts.

Acknowledgements: Research leading to this study has been supported by the Hungarian National Research, Development and Innovation Fund (under grant K-129162) and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).

How to cite: Dezső, Z., Mikes, M. Z., and Pongrácz, R.: Interactive visualisation system for compound weather and climate extremes in Hungary based on station data series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19582, https://doi.org/10.5194/egusphere-egu24-19582, 2024.

EGU24-19634 | Posters on site | EOS1.1

Educational games to foster schoolchildren's understanding of natural hazards and raise their disaster risk awareness - Lessons learned from Central Africa 

Caroline Michellier, Innocent Bahati Mutazihara, Steven Bakulikira, Yves Ngunzi Kahashi, Blaise Mafuko Nyandwi, Bernardin Ulimwengu Biregeya, Matthieu Kervyn, and François Kervyn

Improving understanding and awareness of risks associated with natural hazards among the population at risk and DRR managers is essential for achieving the objectives of the Sendai Framework. This is particularly crucial in contexts where natural hazard risk knowledge is scarce and poorly disseminated, while the frequency of disasters and the severity of their impacts are high.

Highly interactive, educational games are an engaging method for exposing players to disaster risk situation by allowing them to observe and acquire knowledge, train their problem-solving and decision-making skills, and test different disaster risk reduction (DRR) strategies, while experiencing the consequences of disasters in a safe and entertaining environment.

Such an approach based on educational games is experimented in eastern DRC, with the Hazagora and Chukuwa games. Hazagora is a board game originally designed for secondary school children. It is used not only as a knowledge-building tool, but also to raise awareness regarding the potential impacts of disasters and how to reduce them, through active engagement of participants in discussion on DRR strategies. As such, this approach sits at the science-policy-practice interface, involving not only children, but also teachers, scientists, civil society organisations and civil protection representatives. Building on this experience, the Chukuwa card game was developed as a disaster risk awareness tool for primary school children, whose ability to take their new understanding back to their families is recognized as a vector for disseminating knowledge.

After several years of experimentation, some practical limitations linked to the contextualisation and institutionalisation of these games have however been identified. Based on the lessons learned, adaptations of the Hazagora game are being considered, as is the translation of the Chukuwa card game into local languages, alongside the strengthening of the involvement of secondary and primary education authorities and the integration of these tools into school (extra-)curricula.

Educational games are therefore an effective learning tool for introducing participants to the concepts of natural hazards, risks and disasters, as well as for actively and sustainably engaging them in discussions and reflections on DRR strategies conducive to strengthening the risk culture within the community.

How to cite: Michellier, C., Bahati Mutazihara, I., Bakulikira, S., Ngunzi Kahashi, Y., Mafuko Nyandwi, B., Ulimwengu Biregeya, B., Kervyn, M., and Kervyn, F.: Educational games to foster schoolchildren's understanding of natural hazards and raise their disaster risk awareness - Lessons learned from Central Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19634, https://doi.org/10.5194/egusphere-egu24-19634, 2024.

EGU24-20046 | Posters on site | EOS1.1

An exercise in the Civil Protection Operations Room to explain to high school students how an earthquake emergency is handled 

Antonella Peresan, Gabriele Peressi, Barbara Zar, and Carla Barnaba

Inspired by the constructive experiences acquired during the past years with high school students (e.g. Peresan et al, 2023 and references therein) the National Institute of Oceanography and Applied Geophysics (OGS), in collaboration with the Civil Protection of the Friuli Venezia Giulia Region (PCFVG) developed a new educational project on seismic risk awareness, prevention and mitigation. The students from a high school in Northeastern Italy, were mainly involved in communication activities, training and the development of a culture of civil protection and risk awareness, as well as self-protection measures to be taken in the event of a crisis.

The project was coordinated by OGS staff and an official from Regional Civil Protection. The involvement of these two bodies was essential in the event of an earthquake occurring in the Region: the OGS provides real-time earthquake parameters (epicentre, magnitude and ground shaking), while the Civil Protection has the task of coordinating the emergency management (including services and bodies responsible for maintaining roads and buildings).

The exercise in the operations room was especially  useful for students  to understand the most important aspects to consider in an emergency, how priorities are handled and how the decisions made by the decision makers are communicated. This type of exercise showed that actively involving students is the right way to teach them about complex issues (earthquakes) and turn them into active citizens. In fact, after this experience, two students signed up for their community's disaster response team.

Peresan A. et al, 2023. Earth Sci. Syst. Soc., 22 August 2023, https://doi.org/10.3389/esss.2023.10088

How to cite: Peresan, A., Peressi, G., Zar, B., and Barnaba, C.: An exercise in the Civil Protection Operations Room to explain to high school students how an earthquake emergency is handled, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20046, https://doi.org/10.5194/egusphere-egu24-20046, 2024.

Today, our world of 8 billion people and countless other species faces planetary crises that are interconnected, complex, and existential in scale and comprehension, including climate change, biodiversity loss, pollution, nitrogen, and poverty. Scientists are at the heart of designing the studies to understand these threats, producing the data that calibrates them, and interpreting the those data. They are among the first members of society to recognise these threats and often the most committed to preventing their worst outcomes. For action on these crises, the general public, and policymakers representing them, need to understand the risks and also care about the outcomes: a job for the media, authors, artists and filmmakers. However, science and the media have very different communication styles and approaches, something that scientists often find uncomfortable. How can scientists best manage their public outreach, and work with the media to ensure their expertise and knowledge helps society navigate a better future?

How to cite: Vince, G.: Existential Threat: How Scientists Can Work With The Media To Communicate Complex Systemic Crises, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21986, https://doi.org/10.5194/egusphere-egu24-21986, 2024.

NH10 – Multi-Hazards

EGU24-538 | ECS | Orals | NH10.1

A spatio-temporal analysis of the risks of flooding and landslides in Greater Abidjan, Ivory Coast, by applying a multi-risk framework. 

Habal Kassoum Traore, Silvia De Angeli, Sébastien Lebaut, Gilles Drogue, and Eugène Konan Kouadio

Most scientific research acknowledges the overall complexity of the interaction mechanisms between different natural hazards, as well as complex interdependencies with societal drivers such as exposure and vulnerability. Comprehensive understanding of multi-risk dynamics remains crucial for sustainable development in many parts of the world. Moreover, the integration of multi-risk approaches into the planning and implementation of adaptation, resilience and disaster risk reduction measures remain a priority, specifically in developing countries.

Located in West Africa, Ivory Coast faces recurring floods and landslides, mainly due to heavy rainfall during the rainy season. These hazardous events have significant consequences, particularly in coastal urban areas such as Greater Abidjan, where continued and uncontrolled urbanization increases disaster risk, as highlighted in the Disaster risk profile of Ivory Coast by UNDRR in 2019. In this context, a multi-risk approach is essential to deal with the complexity of these interacting threats and their interdependencies with dynamic social and demographical conditions. The limited availability of open disaster risk data, such as the ‘Desinventar’ database endorsed by the UNDP and UNDRR, hinders a comprehensive assessment of risks in the country, particularly in Greater Abidjan, the most populated area. In addition to this gap, there is minimal research focused on conducting a multi-risk analysis on the scale of Greater Abidjan.

By applying the multi-hazard impact framework developed by De Angeli et al. (2022), we seek on the one hand to carry out a multi-hazard assessment with an emphasis on the causal dependencies between heavy rains, floods and landslides. In a second part, we carry out an assessment of the impact of these hazards, focusing on their spatial and temporal evolution, by including an assessment of the physical vulnerability of the built environment and the socio-economic vulnerability of affected populations. Our research draws on various georeferenced data sources, including historical meteorological data, satellite images, digital elevation models, as well as field surveys. These sources enable an in-depth understanding of the spatial and temporal dynamics of flood and landslide risk in the region.

Our research will make it possible to establish a multi-risk framework across Greater Abidjan, emphasizing the importance of considering flood and landslide risks in an integrated manner in the region. All the research falls within the scope of the national action plan of the Sendai framework for capacity building for disaster risk reduction in Ivory Coast (2016-2020).

How to cite: Traore, H. K., De Angeli, S., Lebaut, S., Drogue, G., and Konan Kouadio, E.: A spatio-temporal analysis of the risks of flooding and landslides in Greater Abidjan, Ivory Coast, by applying a multi-risk framework., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-538, https://doi.org/10.5194/egusphere-egu24-538, 2024.

EGU24-1060 | Orals | NH10.1

Is Europe's Transportation Network ready to face Climate Change? 

Cristina Deidda and Wim Thiery

Climate change impacts are evident across a wide range of society sectors. Extreme events like floods, heatwaves, and storms pose a significant threat to the Trans-European Transport Network (TEN-T), resulting in infrastructure damage, economic losses, and health issues for the population. Future projections indicate an elevated risk of coastal flooding for seaports and ports, along with heightened exposure of railways and roads to extreme temperatures. This escalating risk underscores the imperative for implementing effective adaptation measures to enhance the resilience of the entire transport network. Our analysis focuses on assessing the vulnerability of all modes within the European Core Network (airports, seaports, railways, roads, inland water) to climate-related extreme events. We examine the specific challenges and impacts on each transport mode, while also investigating the increasing exposure across different Representative Concentration Pathway (RCP) scenarios.

 

How to cite: Deidda, C. and Thiery, W.: Is Europe's Transportation Network ready to face Climate Change?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1060, https://doi.org/10.5194/egusphere-egu24-1060, 2024.

EGU24-1622 | Posters on site | NH10.1

Including Dynamics in a Network Based Stochastic Multihazard Model 

Mark Bebbington, Alexandre Dunant, David Harte, Melody Whitehead, and Stuart Mead

We outline a conceptual approach to forecast multihazard risk from a cascade of natural hazards events. Network models have been proposed for cascades of natural hazard events, for example storm, flooded river, breached stop banks, damaged infrastructure. These have generally not taken time into account, with the cascade of events effectively assumed to occur instantaneously. We extend the methodology to account for multiple temporal processes, often occurring on quite different time scales, and hence incoporating variable delays. Further, since state of the art physical models generally involve heavy computation, we advocate the use of computationally simple probability distributions to describe the dynamics and interaction of the hazard events in our proposed network model. All model components have estimable parameters, which permits application to specific situations. This enables a larger number of simulations of the model, ensuring greater accuracy of probabilistic model forecasts. The modelling approach takes into account the dynamic and evolving nature of the temporal processes. Thus, it may be possible to identify key elements of the system that are most vulnerable, develop strategies for mitigating risks, and examine restoration strategies.

How to cite: Bebbington, M., Dunant, A., Harte, D., Whitehead, M., and Mead, S.: Including Dynamics in a Network Based Stochastic Multihazard Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1622, https://doi.org/10.5194/egusphere-egu24-1622, 2024.

EGU24-2125 | Orals | NH10.1

Reclassifying historical disasters: from single to multi-hazards 

Christopher White, Mohammed Adnan, Ryan Lee, John Douglas, Miguel Mahecha, Fiachra O'Loughlin, Edoard Patelli, Alexandre Ramos, Matthew Roberts, Olivia Martius, Enrico Tubaldi, Bart van den Hurk, Philip Ward, and Jakob Zscheischler

Multi-hazard events, characterized by the simultaneous, cascading, or cumulative occurrence of multiple natural hazards, pose a significant threat to human lives and assets. This is primarily due to the cumulative and cascading effects arising from the interplay of various natural hazards across space and time. However, their identification is challenging, which is attributable to the complex nature of natural hazard interactions and the limited availability of multi-hazard observations. This presentation, focused on a recently published article in Science of the Total Environment (https://doi.org/10.1016/j.scitotenv.2023.169120), presents an approach for identifying multi-hazard events during the past 123 years (1900-2023) using the EM-DAT global disaster database. Leveraging the ‘associated hazard’ information in EM-DAT, multi-hazard events are detected and assessed in relation to their frequency, impact on human lives and assets, and reporting trends. The interactions between various combinations of natural hazard pairs are explored, reclassifying them into four categories: preconditioned/triggering, multivariate, temporally compounding, and spatially compounding multi-hazard events. The results show, globally, approximately 19% of the 16,535 disasters recorded in EM-DAT can be classified as multi-hazard events. However, the multi-hazard events recorded in EM-DAT are disproportionately responsible for nearly 59% of the estimated global economic losses. Conversely, single hazard events resulted in higher fatalities compared to multi-hazard events. The largest proportion of multi-hazard events are associated with floods, storms, and earthquakes. Landslides emerge as the predominant secondary hazards within multi-hazard pairs, primarily triggered by floods, storms, and earthquakes, with the majority of multi-hazard events exhibiting preconditioned/triggering and multivariate characteristics. There is a higher prevalence of multi-hazard events in Asia and North America, whilst temporal overlaps of multiple hazards predominate in Europe. These results can be used to increase the integration of multi-hazard thinking in risk assessments, emergency management response plans and mitigation policies at both national and international levels.

How to cite: White, C., Adnan, M., Lee, R., Douglas, J., Mahecha, M., O'Loughlin, F., Patelli, E., Ramos, A., Roberts, M., Martius, O., Tubaldi, E., van den Hurk, B., Ward, P., and Zscheischler, J.: Reclassifying historical disasters: from single to multi-hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2125, https://doi.org/10.5194/egusphere-egu24-2125, 2024.

EGU24-3054 | ECS | Orals | NH10.1

Decoding vulnerability dynamics in a multi-hazard context. An Impact Chain-based exploration 

Andra-Cosmina Albulescu and Iuliana Armas

During the last years, the co-occurrence of various natural hazards and the COVID-19 pandemic significantly added to the multi-hazard tapestry worldwide, translating into a boost in multi-risk research. Nevertheless, the dynamics of vulnerability across time and space within the more and more prominent multi-hazard contexts is only beginning to be explored, emerging as an intriguing but also challenging research topic.

Concurrent or cascading hazards lead to compounded impacts that may increase the vulnerability to a certain hazard, while mitigation strategies can also misfire and contribute to the augmentation of vulnerability. Such convoluted interactions prove that it has never been more important to understand how and why vulnerability to natural hazards varies across scales and evolve depending on the unfolding of multi-hazards, if we are to break down the silos of hazard management approaches and devise fruitful multi-risk management plans.

This study aims to explore the dynamics of vulnerability in a multi-hazard context under an Impact Chain approach, focusing on two independent, co-occurrent hazardous events that impacted Romania in 2020-2021, namely river floods and the COVID-19 pandemic. The enhanced Impact Chain builds on its previous variant developed within the Paratus Project, integrating data pertaining to hazards, impacts, exposed elements, vulnerabilities, adaptation options, and the various connections established among them. The chain is based on diverse data and information sources: scientific literature, hydrological warnings, legal documents, official medical reports, official press releases, statistical data, and grey literature in the form of news reports. The input of first responders and leaders in charge of emergency management is added to this list, integrating into the enhanced Impact Chain the perspectives of influential stakeholders.

The main novelty consists of new links and element types that capture 1) the augmentation of vulnerabilities that stem from different hazard impacts, and 2) the unwelcome effects of adaptation options that are intended to mitigate vulnerabilities or impacts, but inadvertently lead to their escalation. These additions enable both the diagnosis of past or present multi-risk management, the anticipation of potential crises, shortcomings of management approaches, and the transformation of certain vulnerabilities into drivers of vulnerability.

The Impact Chain informs on the focal point of mitigation efforts, also bringing to light the vulnerabilities that remained unaddressed by the adaptation options, as well as the ones that were most augmented by impacts or adaptation options working in asynergy. Due to their potential to perpetuate the failures of multi-risk management, these vulnerabilities represent the foremost considerations for future strategic initiatives.

This study takes a leading initiative in research dedicated to vulnerability, being the first to address vulnerability fluctuations applied in a case study focusing on multiple co-occurrent hazards. The Impact Chain approach stands as a novel framework for examining vulnerability, also demonstrating high reproducibility across different hazards and scales. In the face of the new challenges posed by the increasingly frequent concurrent or cascading hazards, such tools can make the difference between effectively managed multi-hazards and those that escalate into unprecedented disasters.

How to cite: Albulescu, A.-C. and Armas, I.: Decoding vulnerability dynamics in a multi-hazard context. An Impact Chain-based exploration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3054, https://doi.org/10.5194/egusphere-egu24-3054, 2024.

EGU24-3392 | Orals | NH10.1

Role of Earth Observation in multi-(hazard-)risk assessment and management  

Carlos Domenech, Èlia Cantoni-Gómez, Philip Ward, Nicole van Maanen, Stefano Terzi, Roxana Ciurean, Gianluca Pescaroli, Irene Manzella, Silvia Torresan, and Claudia Vitolo and the EO4MULTIHAZARDS Team

Impacts from hazards have drastically increased over the last decades, leading to both economic and non-economic consequences across the globe (Cutter 2018; IPCC 2023; Poljansek et al. 2017). When multiple hazards and their interactions are taken into consideration, it becomes apparent that the impacts of a combination of hazards are different than the sum of the individual events (Kappes et al. 2012; Terzi et al. 2019). In response to the widespread consequences of recent multi-hazard events and the appeals from the international community to improve their assessment and management (e.g., UNDRR 2019), there has been a transition in recent years from a primarily single-hazard paradigm towards a more comprehensive assessment of multi-hazards (Ward et al. 2022; De Angeli et al. 2022; AghaKouchak et al. 2020). While there is an urgent need to enhance preparedness for high-impact multi-hazard events, the means to achieve this are currently not clear.

In the context of the European Space Agency’s (ESA) EO4Multihazards project (High-Impact Multi-Hazards Science), we capitalize on the latest advances in satellite Earth Observation technology, including the Copernicus Sentinels series, the ESA’s Earth Explorers, and the meteorological missions to better understand the drivers and dynamics leading to high impact cascading and compounding multi-hazard events, and to improve the estimation of the impacts on society and ecosystems. The project will develop four science cases, tackling both compound and cascading events, along with corresponding demonstration cases aiming to derive actionable information from the scientific developments. The outcomes will be part of an open multi-hazard events database designed to facilitate collaborative research and future scientific progress.

Two science cases investigate the effects of climate-related extreme events in the Adige River catchment. One focusing on hot/dry events on the Alpine mountainous region, where raising temperatures and lack of snowfalls cause hydrological impacts that compound with heatwaves and wildfires. The other one evaluates the impact of climate-related extreme events on the middle-lower course of the river: data driven tools will be implemented to describe the interactions between climate-related hazards, coastal hazards such as sea level rise and saltwater intrusion, anthropogenic land use, and water quantity and quality parameters. The third science case is located in the Southeast region of the UK where the impacts of hot/dry compound in a scenario of sustained high temperatures and their effects on the stability of the terrain and geologically driven events are being evaluated. The last science case focuses on the small island developing State of Dominica to evaluate the multi-hazard scenario mainly from a wet compound and volcanic perspective (i.e., successive storms, landslides, volcanic hazards, and cross-border issues) using digital twins and advanced modelling.

The overall goal is to maximize societal benefits by evaluating where space-based EO can support disaster risk management, aligning with literature calls for such evaluations, and contributing to a comprehensive understanding of multi-hazard events to support decision-makers and relief efforts.

How to cite: Domenech, C., Cantoni-Gómez, È., Ward, P., van Maanen, N., Terzi, S., Ciurean, R., Pescaroli, G., Manzella, I., Torresan, S., and Vitolo, C. and the EO4MULTIHAZARDS Team: Role of Earth Observation in multi-(hazard-)risk assessment and management , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3392, https://doi.org/10.5194/egusphere-egu24-3392, 2024.

In recent years extreme climate events have been increasing in frequency and severity. Multi-hazard risks and its cascading effects cause higher economic and non-economic losses, such as human lives and declines in people’s well-being. This brings forward the need for improvement in disaster risk reduction measures, including the transition from a response-based to a preventive-based measures to minimize the loss in the future. However, adaptation measures differ based on the local context, which also means one methodology in assessing disaster risk reduction in one area might be different to another. This paper will analyse the existing assessment methodologies addressing the measures taken in reducing multi-hazard risks, taking into consideration the local characteristics where the methodology is applied, the type of multi-hazards, the most effected sectors and vulnerable groups, the future scenarios considered, and the costs and benefits of the measures which are included in the assessment. The type of hazards considered in this paper are based on The HuT Nexus Project, including forest fires, landslides, droughts, heatwaves, floods, and storm-surges. The aim of this paper is to review the methodologies of disaster risk reduction and climate change adaptation assessment and analyse the strengths and weaknesses thus enhancing the possibility to be transferred and adapted in other case studies.

How to cite: Lukman, C. S. and Huang-Lachmann, J.-T.: Integrating Disaster Risk Reduction and Climate Change Adaptation: A Critical Review on Methodologies Addressing Multi-Hazard Risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3784, https://doi.org/10.5194/egusphere-egu24-3784, 2024.

EGU24-3843 | ECS | Posters on site | NH10.1

Challenges in Assessing and Managing Multi-Hazard Risks: A European Stakeholders' Perspective 

Robert Sakic Trogrlic, Karina Reiter, Roxana Ciurean, Stefania Gottardo, Silvia Torresan, Anne Sophie Daloz, Lin Ma, Noemi Padron-Fumero, Sharon Tatman, and Philip Ward and the MYRIAD-EU Team

Recent findings indicate an increasing frequency of multiple hazards and their interrelationships (such as triggering, compound, and consecutive events) across Europe, highlighting the urgency for resilience enhancement. This shift demands a transition from focusing solely on single-hazard risks to embracing multi-hazard risk assessment and management strategies. Despite substantial progress in understanding these complex events, the predominant approach still concentrates on individual hazards (like floods, earthquakes, droughts), with a relatively narrow grasp of the actual needs of stakeholders on-site. Addressing this gap, our study aims to explore the challenges of shifting towards multi-hazard risk management from the viewpoint of European stakeholders. Through five workshops conducted in various European locations (Danube Region, Veneto Region, Scandinavia, North Sea, and Canary Islands) and a specialized expert workshop, we pinpoint five key challenges: governance issues, understanding of multi-hazards and multi-risks, current disaster risk management practices, bridging scientific knowledge to policy and practice, and the lack of data. These challenges are interdependent and must be approached comprehensively, as the legacy of existing practices presents a significant obstacle in moving from single-hazard to multi-hazard risk management. Looking ahead, we identify several promising strategies to address some of these challenges, including novel methods for multi-hazard characterization, a unified terminology, and an all-encompassing framework to guide multi-hazard risk assessment and management. We advocate the necessity to broaden our perspective beyond natural hazards, incorporating other types of threats for a more complete multi-hazard risk understanding, and to integrate multi-hazard risk reduction within broader developmental objectives.

How to cite: Sakic Trogrlic, R., Reiter, K., Ciurean, R., Gottardo, S., Torresan, S., Daloz, A. S., Ma, L., Padron-Fumero, N., Tatman, S., and Ward, P. and the MYRIAD-EU Team: Challenges in Assessing and Managing Multi-Hazard Risks: A European Stakeholders' Perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3843, https://doi.org/10.5194/egusphere-egu24-3843, 2024.

EGU24-4275 | ECS | Orals | NH10.1

A Systematic Overview of Hazard Interrelationships in the Philippines 

Richard Ybañez, Alfredo Mahar Francisco Lagmay, and Bruce Malamud

Natural hazards interrelationships include one natural hazard process triggering or influencing another (e.g., an earthquake triggering a landslide) and often contribute to the severity of disasters. This study focuses on a methodology for systematically providing an overview of natural hazard interrelationships in the Philippines. We first explore the breadth of single hazards that might occur in the Philippines, subdividing them into 22 different natural hazard types (with groupings of geophysical, hydrological, shallow-earth, atmospheric, biophysical, space). A 22x22 natural hazard interaction matrix is subsequently developed to identify primary natural hazards that could potentially trigger or increase the probability of secondary natural hazards. Then, for each potential interrelationship (e.g., earthquake-flood) we critically review the literature to find evidence whether that interrelationship might occur, based on past case histories or theory. In total, we use 250 sources, consisting of local scientific and grey literature, and civil defence bulletins. The detailed information is synthesized into a database of 12 types of information (e.g., process, primary and secondary hazards, date and period). Interactions without existing records in the Philippines, but plausible based on global literature, are also incorporated. A total of 76 interrelationships out of a possible 484 were identified. High-impact interrelationships between natural hazards commonly observed in the Philippines include earthquake-triggered landslides, rainfall-induced landslides, and subsidence. Less common hazard interrelationship examples are the 2022 Abuyog landslide-tsunami and the 2008 Panay landslide-flood. The majority (34 out of 76) of the primary hazards involved geophysical hazards such as earthquakes, volcanic eruptions, and landslides, triggering or increasing the likelihood of other geophysical hazards, flooding, and shall earth hazards. Tropical storms, having a very high frequency in the Philippines, also trigger or increase the likelihood of several secondary hazards. The number of unique interactions (76) identified in the matrix continues to grow as more literature, both in the Philippines and globally, are collected. This matrix would serve to inform scientists, policymakers, and first-responders on possible secondary hazards in anticipation of an impending natural hazard impact. The Philippines’ geologic and meteorological setting exposes it to a large variety of high frequency and magnitude natural hazards necessitating the identification of historical and hypothetical hazard interactions for the purpose of preparedness and mitigation.

How to cite: Ybañez, R., Lagmay, A. M. F., and Malamud, B.: A Systematic Overview of Hazard Interrelationships in the Philippines, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4275, https://doi.org/10.5194/egusphere-egu24-4275, 2024.

Natural disasters and extreme weather events are defining this decade and will continue to do so in the future, impacting societies and ecosystems worldwide. The Sendai Framework for Disaster Risk Reduction, adopted to mitigate these risks, also significantly emphasizes the protection and preservation of cultural heritage. It calls for cooperation among national authorities to raise awareness about the impact of hazards on cultural heritage and aligns with the goals of international organizations such as ICOMOS. Although earthquake risk vulnerability has been extensively studied, research on other extreme events, such as landslides and floods, is still limited. Additionally, a growing body of literature on multi-hazard management deals with managing combined natural events. However, there has not been enough research explicitly addressing the vulnerability of cultural heritage.

The research focuses on vulnerability as a multidimensional characteristic and its relationship to multi-scale architectural assets, including individual buildings, aggregates and historic urban cores. Vulnerability is determined by physical, social, and economic dimensions and explores its significance in different phenomena, including compounding and cascading events. A workflow is proposed, consisting of several steps: identifying significant events, assessing affected areas, evaluating the level of damage incurred, and conducting a vulnerability assessment. To understand how to address the issue of vulnerability assessment in a multi-hazard context, it is necessary to observe the effects of past disasters on the built environment.

The proposed methodology follows an inductive approach. The first part of the study, which is also the current focus of the work, consists of the selection of suitable cases for field investigation, intending to analyze the level of physical damage, the geology and hydrology, the history of the environment and events, and the development of building techniques. These studies explore possible relationships between disasters, building techniques and changing settlement patterns. The second phase, transitioning from the particular to the general, will be displayed by defining a list of methodological guidelines based on a critical abstraction from the findings of the first phase. Specifically, this will involve moving from damage observation to vulnerability assessment. General multi-hazard vulnerability criteria for historic centres will be established to analyze practical implications and purposes, including raising community awareness through increased knowledge of the architectural heritage and reconsidering historical studies as essential tools to mitigate future vulnerability.

How to cite: Bosi, E.: Through damage analysis and historical learning: a workflow for multi-hazard vulnerability assessment in cultural heritage preservation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6139, https://doi.org/10.5194/egusphere-egu24-6139, 2024.

EGU24-6422 | ECS | Orals | NH10.1

Correlation of wind and precipitation annual aggregate severity of European cyclones 

Toby Jones, David Stephenson, and Matthew Priestley

The risk from compound natural hazards (such as extratropical cyclones) can be large, but the aggregate loss over yearly timescales is significantly greater. The total insured losses from three European cyclones in February 2022 was over €3.5 billion.

This study has investigated the correlation between wind and precipitation annual aggregate severity caused by extra-tropical cyclones over the Europe-Atlantic region (from 30°N 100°W to 75°N 40°E ) in the 41 years of ERA5 reanalyses from 1980-2020.

Simple aggregate severity indices were constructed by summing exceedances above chosen thresholds of wind gust speed maxima and precipitation totals for all storms in a year that pass within 5° radius of each grid point location.

At low thresholds, there is a strong positive correlation between wind and precipitation aggregate severity most likely induced by the common dependence on the total number of storms. However, at higher thresholds, where the aggregate indices are expected to be better predictors of wind and flood losses, negative correlations start to appear especially over western Europe e.g. a correlation of -0.22 for severity indices aggregated over France at thresholds of 20ms-1 and 20mm.

This suggests that accumulated wind and flood losses in Europe should not be assumed to be either independent or positively correlated, and that there is a potential for risk diversification.

How to cite: Jones, T., Stephenson, D., and Priestley, M.: Correlation of wind and precipitation annual aggregate severity of European cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6422, https://doi.org/10.5194/egusphere-egu24-6422, 2024.

The warming climate has increased the frequency and intensity of floods in urban areas globally. The accelerating populace, coupled with rapid urbanization, amplifies the impact of floods that strain local communities. Existing disparities of unequal exposure to floods in vulnerable communities further burden post-disaster recovery, necessitating comprehensive urban-scale risk assessments. In this study, we quantify this unequal exposure by integrating flood hazards induced by stream flow, rainfall, and storm tides with the measure of socio-economic disadvantage. A 3-way coupled hydrodynamic model has been developed on the MIKE+ over the flood-prone city of Kozhikode, integrating the influence of stormwater drains, tide, and flow through the channel to generate flood hazard scenarios. Socio-economic vulnerability is quantified using a nonparametric data envelopment analysis that accounts for demographic indicators. The initial assessment reveals a disparity in flood exposure, with socially vulnerable populations in Kozhikode bearing a disproportionately higher burden, exacerbating challenges for less resilient communities. The results from the application of the Lorenz curve at the ward level further emphasize the inequitable distribution of flood risk. Our study provides valuable insights into the nuanced dynamics of different drivers of floods and their impact on communities for formulating targeted planning and adaptation strategies for reducing flood risk equitably and sustainable urban resilience. 

How to cite: Dave, R. and Bhatia, U.: Unveiling Socio-economic Inequity in Local-Scale Compound Flood Risks in Indian Coastal City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7332, https://doi.org/10.5194/egusphere-egu24-7332, 2024.

EGU24-7475 | Orals | NH10.1

Development of framework for decision support integrated impact assessment platform and application technology for climate change adaptation 

Songmi Park, Young-Il Song, Jinhan Park, Ara Kim, Eunbi Lee, and Joohyun Park

Climate change is having simultaneous impacts on various sectors such as health, ecology, and agriculture, increasing the demand for assessment and technology development for each sector and their interactions. South Korea's climate change is progressing more rapidly than the global average, leading to an increasing trend in natural disasters such as heatwaves, cold snaps, floods, and droughts due to high climate variability. The damages caused by the four major disasters (heatwaves, cold snaps, floods, and droughts) are interconnected with the occurrence of vector-borne diseases, infectious diseases, and food supply issues, leading to an increased demand for integrated impact assessments on these interactions.
The need for policy decision support in evaluating climate policies and developing robust plans for climate change response is increasing in South Korea. To address this, a research team is currently developing a climate change integrated assessment platform that takes into account both internal and external factors related to climate change. Specifically, they are in the process of developing an integrated assessment model based on interconnections between sectors to evaluate the impact and vulnerability of climate change. Furthermore, work is underway to develop climate change impact assessment models for health, water management, agriculture, forestry, behavior, and the marine and fisheries sectors. Additionally, they are considering the development of climate change impact assessment models for environmental policy coordination.

Acknowledgement
This work was supported by Korea Environment Industry &Technology Institute(KEITI) through "Climate Change R&D Project for New Climate Regime." , funded by Korea Ministry of Environment(MOE) (2022003570007)

How to cite: Park, S., Song, Y.-I., Park, J., Kim, A., Lee, E., and Park, J.: Development of framework for decision support integrated impact assessment platform and application technology for climate change adaptation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7475, https://doi.org/10.5194/egusphere-egu24-7475, 2024.

EGU24-9418 | ECS | Posters on site | NH10.1

A mathematical framework to quantify physical damages from concurrent and consecutive hazards 

Silvia De Angeli, Alessandro Borre, Eva Trasforini, Daria Ottonelli, Giorgio Boni, and Tatiana Ghizzoni

When two or more natural hazards occur in the same location simultaneously or within a short time frame, the physical integrity of assets and infrastructures can be compromised, and the resulting damage can be higher than the simple sum of the damages generated by individual hazards occurring in isolation. Current literature highlights the lack of comprehensive frameworks to quantify the damages caused by multiple hazards. Complexity in formalizing quantitative aspects and understanding feedback loops between hazard, exposure, and vulnerability emphasizes this gap. 

This research presents a comprehensive mathematical framework for quantitatively assessing multi-hazard physical damage on exposed assets, such as buildings or critical infrastructures, over time. The proposed framework covers both the damages generated by concurrent hazards (i.e., hazards that impact the same assets simultaneously), as well as by consecutive hazards (i.e., the second hazard impacting the asset while it is still undergoing recovery from the damages caused by the first hazard). In case of concurrent hazards, the proposed framework models the increased damage resulting from the combined impacts. In the case of consecutive events, the proposed formalization considers the effect of cumulative damages, the reduction in the exposure value, the modification of vulnerability in the time in between hazards, and the recovery dynamics. 

The framework is applied to a real-world case study in Puerto Rico, including the impacts from the concurrent wind and flood generated by the passage of Hurricane Maria, as well as the impacts caused by the consecutive seismic sequence of 2019-2020. The application to the Puerto Rico case study well highlights the potentialities and limitations of the proposed approach, specifically regarding data availability.

By offering a generalized formalization to perform quantitative multi-hazard impact assessments across a diverse array of natural hazards and incorporating amplification phenomena and recovery dynamics, the framework provides scientists and decision-makers with a thorough and enhanced comprehension of the impacts resulting from concurrent and consecutive events. This deeper understanding serves as valuable input for conducting comprehensive multi-hazard risk assessments and implementing effective disaster risk reduction strategies.

How to cite: De Angeli, S., Borre, A., Trasforini, E., Ottonelli, D., Boni, G., and Ghizzoni, T.: A mathematical framework to quantify physical damages from concurrent and consecutive hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9418, https://doi.org/10.5194/egusphere-egu24-9418, 2024.

EGU24-9760 | Orals | NH10.1

Hotspots of Multi-hazard Risk to Human Health in a Changing Climate 

Zélie Stalhandske, Jonathan Chambers, Chahan Kropf, Marleen C. de Ruiter, and David N. Bresch

The health effects of climate change, from intensified heatwaves to increased environmental suitability for infectious diseases, have become increasingly evident in recent years. In this study, we investigate the intersection of multiple climate-related health hazards from 2003 to 2022 using indices from the Lancet Countdown on Health and Climate Change, including heatwaves, drought, malaria, and wildfire smoke exposure. Through a global analysis at a 0.25-degree resolution, we identify regions where these hazards have overlapped, highlighting hotspots of simultaneous exposure. We then perform detailed case studies in countries most affected by these hazards, where we explore the interactions between seasonal climate variations, demographic shifts, and the exposure to health hazards. The findings of this study can help guide health system adaptations and inform policy by revealing where, when, and whom these hazard combinations affect. Finally, while the health effects of some of these combinations have been studied, the compounding effects are generally unknown. Mapping their co-occurrence can help in designing relevant epidemiological studies to better understand these consequences.

How to cite: Stalhandske, Z., Chambers, J., Kropf, C., de Ruiter, M. C., and Bresch, D. N.: Hotspots of Multi-hazard Risk to Human Health in a Changing Climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9760, https://doi.org/10.5194/egusphere-egu24-9760, 2024.

EGU24-10177 | ECS | Orals | NH10.1

Analysing historical disasters to support multi-hazard risk assessment: enhancing forensic analysis through Impact Chains  

Liz Jessica Olaya Calderon, Silvia Cocuccioni, Federica Romagnoli, Funda Atun, Massimiliano Pittore, Stefan Schneiderbauer, Cees van Westen, Richard Sliuzas, Iulana Armas, Ruxandra Mocanu, and Seda Kundak

Analysing past disaster events is essential for advancing our comprehension of the complex interactions among risk factors and the subsequent cascading impacts. Assessing the direct and indirect consequences of past events and the reasons why these occurred can help estimate the impacts and losses for future events as well as pinpoint risk mitigation measures. Although forensic analysis investigation aims to address disasters and tackle the root causes comprehensively, a systematic method is still needed to represent the interplay among diverse risk factors and enable a cross-cutting and quantitative analysis of disaster databases.

Impact chains provide a clear and intuitive conceptual representation of risk, the interaction among their elements (hazard, exposure, and vulnerability) and their cascading impacts.  Highlighting the type of relation between the risk elements, impact chains explicitly consider risk mitigation and climate change adaptation measures and aim to integrate multiple data collections and analytical approaches. This interdisciplinary approach enables a more holistic analysis of disaster events, providing a structured framework to identify past weaknesses and deficiencies, thereby enhancing strategies for disaster risk management and fostering improvements in disaster databases.

Our research aimed to explore the potentialities of impact chains for analyzing historical disaster events, including how this method can support the forensic analysis approach in the context of compounding events. We pursued the following goals: (i) to develop a multi-hazard impact chain from historical disaster events, (ii) to collect the disaster data based on the impact chain developed in order to analyze the interrelationships between the risk components, and (iii) discuss how the results can support the forensic analysis approach.To accomplish this objective, a diverse set of disaster events were analysed. These events are characterized by being multi-hazard, having a significant impact, and covering a diversity of sectors, geographic locations, and scales (Romania, Turkey, the Caribbean, the Alps, etc.). These analyses were carried out under the PARATUS project.

Preliminary results showcase the significant potential for using this method to develop more comprehensive impact chains, particularly when representing multi-hazard events. One of the key achievements identified is that this approach emphasizes the role of vulnerability and the underlying risk drivers in the overall assessment.   The subsequent phase of this study focuses on enhancing the disaster databases by collecting data for the different elements included within the impact chain. This undertaking aims to facilitate a quantitative analysis of available data, scrutinize the interconnectedness of variables, and elucidate how these variables influence overall risk. Finally, through this comprehensive approach, we aim to provide valuable insights into the field of disaster research and management, fostering a deeper understanding of potential disaster risks and impacts and planning risk reduction measures accordingly.

How to cite: Olaya Calderon, L. J., Cocuccioni, S., Romagnoli, F., Atun, F., Pittore, M., Schneiderbauer, S., van Westen, C., Sliuzas, R., Armas, I., Mocanu, R., and Kundak, S.: Analysing historical disasters to support multi-hazard risk assessment: enhancing forensic analysis through Impact Chains , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10177, https://doi.org/10.5194/egusphere-egu24-10177, 2024.

EGU24-10199 | Orals | NH10.1

Conversations on multi-hazard risk: Qualitative and quantitative insights from MYRIAD-EU interviews on the dynamics of risk drivers and disaster risk reduction synergies in Europe 

Nicole van Maanen, Marleen de Ruiter, Wiebke Jäger, Veronica Casartelli, Anne Sophie Daloz, David Geurts, Stefan Hochrainer-Stigler, Lin Ma, Letizia Monteleone, Noemi Padron, Karina Reiter, Robert Šakić Trogrlić, Silvia Torresan, Sharon Tatman, and Philip Ward and the MYRIAD-EU

Navigating the complexities of multi-hazard risks poses a significant challenge, requiring a holistic understanding that extends beyond theoretical frameworks. Although recent frameworks have contributed greatly to theoretical advancements, a critical gap remains in providing practical insights for on-the-ground stakeholders. These stakeholders, including policymakers, decision-makers, and practitioners are often responsible for preparing and dealing with the risks arising from multi-hazard events. Within the MYRIAD-EU project, the objective is to empower stakeholders on the ground with a systemic approach encompassing multi-risk and multi-sector assessment and management.

 

To unravel the intricate web of systemic risk interdependencies across and within Europe and facilitate an improved assessment and management of multi-hazard risks, several comprehensive semi-structured interviews were conducted within the Pilot regions of the MYRIAD-EU project. These interviews spanned diverse geographic, hazard, and sectoral domains. The Pilot regions are the Canary Islands, the Veneto region, the Danube region, Scandinavia, and the North Sea.

 

The insights obtained from these interviews, both qualitative and quantitative, including perspectives from both land and sea, offer a nuanced understanding of hazard combinations, vulnerability characteristics, changes in exposure and vulnerability over time, and the synergies and asynergies inherent in disaster risk reduction measures across Europe. Our findings aim to bridge the gap between theoretical frameworks and practical applications, providing valuable information for stakeholders to enhance their preparedness and response strategies in the face of multi-hazard risks. At the same time, the results will be used to develop a better understanding about the dynamic vulnerability and exposure of multi-(hazard-)risk.

How to cite: van Maanen, N., de Ruiter, M., Jäger, W., Casartelli, V., Daloz, A. S., Geurts, D., Hochrainer-Stigler, S., Ma, L., Monteleone, L., Padron, N., Reiter, K., Šakić Trogrlić, R., Torresan, S., Tatman, S., and Ward, P. and the MYRIAD-EU: Conversations on multi-hazard risk: Qualitative and quantitative insights from MYRIAD-EU interviews on the dynamics of risk drivers and disaster risk reduction synergies in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10199, https://doi.org/10.5194/egusphere-egu24-10199, 2024.

EGU24-10316 | Orals | NH10.1

Towards a Multi-Criteria Analysis for the evaluation of risk reduction strategies effectiveness in multi-hazard environments 

Daniela Molinari, Panagiotis Asaridis, Diana Caporale, Daria Ottonelli, and Alessandro Rubino and the RETURN WP 7.2 research team

Within the context of the Italian RETURN (Multi-risk science for resilient communities under a changing climate) project, the objective of WP 7.2 is the definition of national guidelines for the evaluation of the effectiveness of alternatives of intervention in natural risks management, by considering in detail Multi Criteria Analysis (MCA) tools. The focus is on (i) multi-hazard contexts, for which state-of-the-art and knowledge is limited, (ii) the different phases of the risk management chain, and (iii) the variety of structural and non-structural measures that can be adopted. The present contribution describes results reached so far in this direction. First, First, we propose a flowchart that illustrates the process leading to the ranking of alternative strategies through MCA. The objective of the flowchart is to highlight the operative steps required for its implementation, including: (i) the identification of intervention alternatives and their characterization in terms of spatial and temporal scale of effectiveness, potential risk reduction, and secondary impacts on interested communities, (ii) recognition of stakeholder’s objectives and their respective dimensions, (iii) definition of attributes and indicators according to which alternatives are evaluated, (iv) selection of the most appropriate MCA tool and definition of related parameters, and (v) performance of sensitivity analysis. The development of the flowchart emphasized that establishing guidelines for applying MCA to multi-hazard risk management requires two ongoing fundamental steps (i) an in-depth, generalized investigation of the types of elements exposed to the different natural hazards as well as the identification of potential direct and indirect impacts on them in case of an event; (ii) the definition of an abacus of alternatives which identifies the most promising measures that can be implemented in a given context, and characterizes them in terms of potential risk reduction or increase (with respect to different hazards), and temporal and spatial scale of effectiveness.

How to cite: Molinari, D., Asaridis, P., Caporale, D., Ottonelli, D., and Rubino, A. and the RETURN WP 7.2 research team: Towards a Multi-Criteria Analysis for the evaluation of risk reduction strategies effectiveness in multi-hazard environments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10316, https://doi.org/10.5194/egusphere-egu24-10316, 2024.

EGU24-10353 | ECS | Orals | NH10.1

A Holistic Asset-Level Modelling Framework for a Comprehensive Multi-Hazard Impact Assessment: Insights from the ICARIA Project 

Agnese Turchi, Amanda Tedeschi, Daniela De Gregorio, Giulio Zuccaro, Alex de la Cruz Coronas, Marianne Bügelmayer-Blaschek, Ioannis Zarikos, and Mattia Leone

The risk/impact assessment of climate-related extreme events has been historically addressed through single-hazard approaches that so far limited the development of a comprehensive, harmonized and integrated multi-hazard modelling framework capable of holistically understanding the weight of climate impacts on complex socio-eco-technological systems, as well as the definition of possible climate-resilient development pathways (IPCC, 2022). The expected increase in frequency and magnitude of meteorological hazards aggravated by climate change often manifests itself through the occurrence of complex interactions, characterised by compound events (e.g., floods and landslides, triggered by heavy rainfalls) and cascading effects (e.g., forest fires fuelled by persistent drought, triggered by heat wave conditions).

Depending on how the combination of these events occurs over time and space, the impacts resulting from multi-hazard conditions might be greater than the sum of the effects of individual hazards, and the nature of the damage will vary depending on both the complexity and interdependencies between hazards and/or impacts involved. Understanding the implications of compound events (whether coincident or consecutive) on specific categories of risk receptors – and of cascading effects arising from the propagation of impacts across assets and services – is the starting point to develop an asset-level modelling framework that effectively supports and orients decision-making processes towards the identification of strategies and measures to improve resilience.

In this perspective, a paradigm shift towards an effective multi-hazard impact modelling approach requires that 1) the possible interactions between hazards, and their dependence on global warming and climate change trends are taken into account, 2) the multi-sectoral consequences of complex impact scenarios leading to cascading effects are identified, and 3) the effect of possible organizational, spatial, functional and physical resilience measures targeting multiple hazards are evaluated.

This contribution presents the holistic multi-hazard impact modelling framework developed within the EU-funded Horizon Europe ICARIA Project (Improving ClimAte Resilience of crItical Assets, www.icaria-project.eu, GA: 101093806). The framework aims at ensuring consistency in the analysis across different hazard categories (heat waves, forest fires, droughts, floods, storm surges, and wind gusts, including compound events), a harmonized evaluation of exposure and vulnerability of critical assets (buildings, open spaces and infrastructures) and services (water, transport, energy, waste, natural areas, and tourism sectors) potentially at risk, and the potential tangible direct and indirect impacts of complex multi-hazard scenarios, including cascading effects across interconnected service networks and systems. The modelling framework is also designed to quantify the benefits of resilience strategies and measures and to define suitable, sustainable and cost-effective solutions for climate resilience.

The methodological approach is grounded on interconnected “elementary bricks”, namely Hazard, (H) Exposure (E), Vulnerability (V), Dynamic Vulnerability (DV), and Damage (D), framed with respect to time and space interdependencies and interacting with local Coping Capacity (CC), Adaptive Capacity (AC) and Transformative Capacity (TC) as main resilience components. The contribution introduces relevant taxonomies, replicable modelling workflows, and quantifiable impacts and resilience metrics applicable in different geographical contexts, proposing a service-oriented implementation approach aimed at maximising the exploitation of existing models and data while introducing specific methods to address uncertainties and data/knowledge gaps.

How to cite: Turchi, A., Tedeschi, A., De Gregorio, D., Zuccaro, G., de la Cruz Coronas, A., Bügelmayer-Blaschek, M., Zarikos, I., and Leone, M.: A Holistic Asset-Level Modelling Framework for a Comprehensive Multi-Hazard Impact Assessment: Insights from the ICARIA Project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10353, https://doi.org/10.5194/egusphere-egu24-10353, 2024.

EGU24-10624 | ECS | Orals | NH10.1 | Highlight | NH Division Outstanding ECS Award Lecture

Advancing multi-(hazard)risk science: embracing complexity and cross-disciplinary collaborations 

Marleen de Ruiter

Recent disasters have demonstrated the growing challenges faced by society as a result of multi-hazards and compound events. The impacts of such disasters differ significantly from those caused by single hazard disasters: often the impacts of a multi-hazard disaster exceed those of the sum of the impacts of the individual hazards. Recognizing this complexity, the scientific community and international organizations, such as the UNDRR, have been advocating for a more integrated approach in multi-(hazard)risk research. This requires bridging across individual hazard types, but also learning from methodological advances made in neighbouring research fields such as the compound events community.

This talk aims to highlight recent advances in assessing the complexities of multi-(hazard)risk and discusses opportunities for further enhancing our modeling capabilities through multidisciplinary collaboration. A crucial challenge of modelling compound and multi-hazard risk, is that of the spatiotemporal dynamics of risk. This includes for example, an improved understanding of post-disaster recovery after multi-hazard disasters and the role of (changing) local contexts within which disasters take place such as the dynamics of socioeconomic vulnerability and the likelihood of post-disaster disease outbreaks. Embracing these challenges and opportunities can support more comprehensive and effective disaster risk management strategies in the future.

How to cite: de Ruiter, M.: Advancing multi-(hazard)risk science: embracing complexity and cross-disciplinary collaborations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10624, https://doi.org/10.5194/egusphere-egu24-10624, 2024.

EGU24-12934 | Orals | NH10.1

The EO4MULTIHA open Multi-Hazard events database 

Andrea Vianello, Stefano Terzi, Peter James Zellner, Kathrin Renner, Alexander Jacob, and Massimiliano Pittore

Multi-hazard events are causing severe impacts on our economy, society and environment. Moreover, the final damages are usually greater than the sum of single hazard impacts. However, the amount of data and observations covering multi-hazard conditions is still very limited. For this reason, the EO4MULTIHA project (https://eo4multihazards.gmv.com/), funded by the European Space Agency, aims at developing an open database gathering and harmonizing event information coming from already existing event databases to support multi-hazard(-risk) research. 

In particular, the database of the EO4MULTIHA project is a Relational Data Base Management System, based on open-source solution, that includes several novelties and features, such as 

(i) the link to existing event datasets through cross links and APIs to increase reusability with open standards (e.g. RESTfull APIs and OGC standards), 

(ii) the link to an extensive suite of data from satellite, climatological, in-situ, campaign and relevant statistics needed to describe hazard, exposure, vulnerability and impacts of multi-hazard events, 

(iii) the possibility to apply spatial and temporal filtering of events, 

(iv) the integration of Geostories focusing on specific multi-hazard events combining the available data and information into explanatory reports and 

(v) an initial focus on the 3 project study areas (the Adige River Basin in Italy, the southern part of the United Kingdom and the Dominica Island in the Carribean) with the possibility for future expansion to other areas, 

(vi) the development of a publicly available and open database with uploads coming from authorized contributors, 

(vii) standard metadata that describe datasets and allow their findability in international catalogues of the research community. 

The final product will be made available in a web portal facilitating the access of researchers, decision-makers and citizens to quantitative data supporting the understanding and analysis of complex multi-hazard events.

How to cite: Vianello, A., Terzi, S., Zellner, P. J., Renner, K., Jacob, A., and Pittore, M.: The EO4MULTIHA open Multi-Hazard events database, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12934, https://doi.org/10.5194/egusphere-egu24-12934, 2024.

EGU24-14261 | ECS | Orals | NH10.1

A framework for multi-hazard risk indicators 

Marcello Arosio, Christopher J. White, Mohammed Sarfaraz Gani Adnan, Mario Martina, and Claire Kennedy

The occurrence of multiple hazards poses significant risks to both human lives and assets. These risks often surpass those associated with individual hazards as they result from the interaction of natural hazards through simultaneous, cascading, or cumulative incidents. In several European regions, vulnerable to a range of climatic extremes, the society and environment are expected to undergo significant impacts in the next few decades. This is attributed to the rising frequency and severity of multi-hazard events, which are closely tied to changing climatic conditions.

In this context, the aim of this work is to develop and test a new framework for multi-hazard risk indicators that are suitable for use in risk-based assessments and decisions making. Indicators are used within different disciplines, offering insights into hazards, risk, resilience, vulnerability and other impacts related to climate change, amongst other factors. Such indicators can be used to model interacting hazards and cascading impacts within risk assessments, including a decision support system for multi-hazard disaster risk. This work, supported by a systematic literature review grounded on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), introduces a framework for a suite of simple and usable multi-hazard indicators that balance complexity and usability to enable their uptake within natural hazard risk assessments (e.g., multi-hazard/risk rate). We adopt the following definition “Indicators are observable and measurable characteristics that can be used to simplify information to help understand the state of a concept or phenomenon, and/or to monitor it over time to show changes or progress towards achieving a specific change”. The development of these indicators prioritises the needs of end-users in disaster risk management, aiming to overcome limitations associated with their evolution being driven by climate scientists, without considering sectoral impacts or risk-based assessments. The framework for indicator development can contribute valuable insights for progressing multi-hazard risk management policies globally, particularly in regions experiencing an increased susceptibility to multi-hazard events.

The research has been carried out within the framework of the Horizon Europe project MEDiate (Multi-hazard and risk-informed system for Enhanced local and regional Disaster risk management). The primary objective of this project is to create a decision-support system (DSS) for disaster risk management that takes into account the complexities of multiple interacting natural hazards and their cascading impacts. The framework is implemented on four interactive multi-hazard pairs—compounding coastal and riverine flooding, extreme heat and drought, extreme wind and precipitation, and extreme precipitation and landslides—in four European testbeds: Oslo (Norway), Nice (France), Essex (UK), and Múlaþing (Iceland), respectively.

How to cite: Arosio, M., White, C. J., Gani Adnan, M. S., Martina, M., and Kennedy, C.: A framework for multi-hazard risk indicators, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14261, https://doi.org/10.5194/egusphere-egu24-14261, 2024.

EGU24-14927 | Orals | NH10.1

Climate Extremes and Systemic Risks for Sustainable Development Pathways – Artificial Intelligence for Risk Mitigation? 

Markus Reichstein, Vitus Benson, Nuno Carvalhais, Dorothea Frank, and Claire Robin

Climate change is increasingly leading to severe and frequent extreme events, ranging from forest fires to heatwaves, droughts, and floods. These events are likely not only intensifying as our climate continues to warm but also interlink across various environmental and social systems. For example, a heatwave can trigger forest fires, which in turn lead to air pollution impacting public health. Droughts can disrupt agricultural production, causing market fluctuations and exacerbating socio-economic inequalities, potentially leading to social unrest. Despite the growing systemic risks posed by these extreme climate events, they are often inadequately addressed in national strategies for achieving the United Nations Sustainable Development Goals (SDGs).
The core challenge in tackling these risks stems from their roots in the dynamic boundary conditions of global warming, such as rising temperatures and altered precipitation patterns. Conventional risk models designed for assessing discrete, non-climate-related hazards or based on past climate are becoming increasingly invalid in this non-stationary scenario. In addition, process-based models are challenged by high-resolution complex-systems forecasting tasks. This is due to both epistemic limitations in understanding climate-ecosystem-society interactions and computational constraints. We discuss howArtificial Intelligence (AI) can serve as a complementary and effective tool in understanding, managing, and communicating these systemic risks, given its ability to process vast datasets and uncover patterns within complex systems. The vision is an AI enabled Early warning system of complex risk, operating on several time-scales (hours to decadal).

How to cite: Reichstein, M., Benson, V., Carvalhais, N., Frank, D., and Robin, C.: Climate Extremes and Systemic Risks for Sustainable Development Pathways – Artificial Intelligence for Risk Mitigation?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14927, https://doi.org/10.5194/egusphere-egu24-14927, 2024.

EGU24-15835 | ECS | Orals | NH10.1

What can we learn about multi-hazard impact and risk dynamics from the international disaster database EM-DAT?  

Wiebke Jäger, Timothy Tiggeloven, Marleen de Ruiter, and Philip Ward

Understanding multi-hazard impacts and dynamics is essential for understanding risk and developing effective risk reduction measures. Recent studies have been reporting more extreme, compounding impacts from compound events, consecutive disasters or multi-hazards than from individual hazard events owing to complex dynamics and interdependencies of the risk drivers hazard, exposure and vulnerability. As our current understanding of these impacts is primarily based on individual notable events, this study aims to contribute with a systematic review and comparison of socio-economic impacts from historical single- versus multi-hazard events globally. To this end we analyze the data of the international disaster database EM-DAT, which is the main publicly available source that contains quantitative information on socio-economic impacts with global coverage and widely-used in disaster risk science. Being aware of its known issues and limitations, including biases and inconsistencies, we also investigate and evaluate its trustworthiness for the purpose of gaining understanding on multi-hazard impact and risk dynamics.

How to cite: Jäger, W., Tiggeloven, T., de Ruiter, M., and Ward, P.: What can we learn about multi-hazard impact and risk dynamics from the international disaster database EM-DAT? , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15835, https://doi.org/10.5194/egusphere-egu24-15835, 2024.

EGU24-17565 | ECS | Orals | NH10.1

Consecutive Disasters: an approach to multi-hazard exposure, vulnerability, and recovery evaluation at global scale  

Alessandro Borre, Eva Trasforini, Daria Ottonelli, Tatiana Ghizzoni, and Roberto Rudari

In an era marked by consecutive natural disasters, an advanced methodology for risk and impact assessment is critical. Recent disasters in Puerto Rico in 2017, Nepal between 2015 and 2017, and Indonesia in 2018 have highlighted the urgency of identifying regions at high risk of consecutive natural events, which are also characterised by vulnerabilities in organizational, social, and economic aspects that heavily influence the response and recovery stages following a disaster. The initial phase involved an analysis of the EM-DAT database to chart a global impact timeline within a multi-hazard scenario. Subsequent detailed assessments focused on riverine floods, individually and in conjunction with pluvial and wind events, across specific countries.

The research goal is to identify countries where the complex interplay between consecutive disasters is crucial to risk evaluation, given the significant impact on the components of exposure and vulnerability. Initially adopting a single hazard approach, the research analyses the sequence and probability of flood events alongside local exposure levels to identify at-risk countries. Subsequently, the study expanded to incorporate a multi-hazard perspective, including floods, intense rainfall, and strong winds, within a specific country to evaluate the relevance of this innovative approach in risk assessment. Early findings underscore the necessity to adapt damage assessments to the specific needs and scales of the regions studied, accounting for both single and multiple hazard scenarios.

Results demonstrate notable disparities in the annual exposure value percentage affected by consecutive disasters, providing key insights for stakeholders, academics, policymakers, and local administrators. This information provides them with a complex understanding of risk assessment and simplifies the formulation of more effective mitigation strategies. In conclusion, an integrated assessment of consecutive natural disasters alongside regional exposure levels provides a comprehensive framework for identifying areas in need of innovative risk management. Interdisciplinary cooperation is essential to comprehensively understand and improve the collective response and recovery from natural disasters, with particular emphasis on the socio-economic and infrastructural factors that distinctly affect the dynamics of consecutive events.

How to cite: Borre, A., Trasforini, E., Ottonelli, D., Ghizzoni, T., and Rudari, R.: Consecutive Disasters: an approach to multi-hazard exposure, vulnerability, and recovery evaluation at global scale , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17565, https://doi.org/10.5194/egusphere-egu24-17565, 2024.

EGU24-19858 | ECS | Orals | NH10.1

Multi-hazard exposure characterization of urban settlements: a clustering proposal using open source data 

Gabriella Tocchi, Maria Polese, Carlo Del Gaudio, and Antonella Peresan

A comprehensive understanding of essential characteristics of urban settlements, including typo-morphological, demographic, social, economic and institutional features is essential for developing effective strategies to enhance the resilience of urban settlements to natural hazards. The complexity and concentrated infrastructure in urban settlements can exacerbate the vulnerability to natural hazards . The high population density in cities increases the potential for casualties and impacts during events like earthquakes, floods, and hurricanes. Indeed, rapid urbanization often occurs without adequate consideration of natural hazard risks, leading to poorly planned structures and insufficient resilience measures. The interconnectedness of urban systems, including transportation, utilities, and communication, heightens the susceptibility of cities to systemic failures during disasters. Informal settlements and marginalized communities within urban areas are often disproportionately affected, lacking the resources and infrastructure to withstand natural hazards. The reliance on centralized resources and critical facilities can exacerbate vulnerabilities, as disruptions to these systems have cascading effects on the entire urban population.

In this study, a national-scale characterization of urban settlements in Italy is proposed using only open-source data. Urban settlements range from small towns and cities to large metropolis, with local government or administrative boundaries often defining their limits. Publicly available data on the built environment and population in urban areas is typically provided with reference to the administrative level. Information on the degree of urbanization, urban centeredness, residential population, and altimetric zone are used for a preliminary classification of Italian municipalities. Using such information, clustering of the municipalities is also carried out. Clustering urban settlements may help understand the most common types and features of urban settlements in a country.

For a proper characterization of an urban context, the impending hazard should also be identified. Due to the variability of geomorphological, climatic, and hydrological features, the incidence of different hazards throughout the Italian territory varies, as does their potential to generate significant impacts. A score-based procedure is proposed to allow the ranking of different hazards and to infer which hazards could be more relevant in a given urban context. For each relevant peril, the value of the corresponding intensity measure on the hazard map at a given return period is used to define a normalized score. Through scoring, a ranking of all Italian municipalities with respect to a given hazardous event is carried out.

This study was carried out within the RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005

How to cite: Tocchi, G., Polese, M., Del Gaudio, C., and Peresan, A.: Multi-hazard exposure characterization of urban settlements: a clustering proposal using open source data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19858, https://doi.org/10.5194/egusphere-egu24-19858, 2024.

EGU24-19965 | ECS | Orals | NH10.1

Modelling the impact from cascading geohazards using hypergraphs 

Alexandre Dunant, Alexander Densmore, Thomas Robinson, Sihan Li, Mark Kincey, Nick Rosser, Ramesh Guragain, Ragindra Man Rajbhandari, Max Van Wyk de Vries, Sweata Sijapati, Katherine Arrell, Erin Harvey, and Simon Dadson

Modelling risk systems, in which natural hazards and exposure elements are intricately intertwined, poses a significant challenge, especially over large spatial and temporal scales. To address this issue, this study introduces the use of hypergraphs as a modelling framework for dynamic multi-hazard systems. Hypergraphs have found applications across disciplines for effectively capturing complexities in various systems.

The study demonstrates the suitability of hypergraphs to multihazard risk assessment through a case study of  the 2015 Gorkha earthquake in Nepal and its subsequent coseismic landslides. The initial test case is followed by the generation of cascading scenarios initiated by thirty high-magnitude simulated earthquakes across Nepal and analysis of the subsequent cascading impacts arising from landsliding on buildings and roads. The modelling is being developed to provide scientific evidence to inform preparedness planning at a range of scales.

Our results show that this approach is effective, offering several key advantages. First, the easy compatibility with spatial data enables a more accurate representation of real-world scenarios. Second, the proposed method is hazard-agnostic, allowing it to accommodate various types of natural hazards. Third, the high computational efficiency of the hypergraph-based model enables the use of large scenario ensembles. Finally, the capability to handle complex interactions between hazard processes and exposure elements streamlines the risk assessment process.

We emphasise that the adoption of hypergraphs as a modelling framework has the potential to substantially enhance multi-hazard risk assessment in natural systems. By providing a comprehensive and flexible approach, this method offers a promising avenue for improving risk management strategies and bolstering preparedness measures to mitigate the impacts of environmental disasters.

 

How to cite: Dunant, A., Densmore, A., Robinson, T., Li, S., Kincey, M., Rosser, N., Guragain, R., Man Rajbhandari, R., Van Wyk de Vries, M., Sijapati, S., Arrell, K., Harvey, E., and Dadson, S.: Modelling the impact from cascading geohazards using hypergraphs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19965, https://doi.org/10.5194/egusphere-egu24-19965, 2024.

EGU24-20217 | Orals | NH10.1

An approach to modeling interactions between extreme weather events during multi-hazard events 

Alex de La Cruz Coronas, Beniamino Russo, Barry Evans, Agnese Truchi, Mattia Leone, and Marianne Buegelmayer-Blaschek

Multi-hazard events refers to scenarios where two or more hazards occur in the same region and/or time period where the resulting impact is either greater or lesser than the sum of their impacts if they were to happen independently. The combined effects resulting from multi-hazard scenarios are therefore unlikely to be assessed through simple addition of losses, due to the independent effects, and instead require system approaches to understand and quantify risk.

The dynamics between single hazards during multi-hazard events are complex and diverse. Hence, as a first step, it is necessary to differentiate their main typologies (coincident or consecutive) based on their occurrence in time and space. On the one hand, coincident hazards represent events happening within the same geographical region, either simultaneously or with overlapping time frames (i.e. a secondary hazard is occurring whilst a primary hazard is still taking place). On the other hand, consecutive hazards take place sequentially in the sense that a second hazard impacts a system prior to its full recovery from the previous one. A second step in understanding multi-hazard situations involves identifying the interrelationships established (between single hazards) during compound events (interdependence, triggering, change conditions, association or mutual exclusion). 

Following these steps it becomes possible to understand the way that one hazard can influence the magnitude and/or likelihood of subsequent hazards. Furthermore, in order to adequately develop a risk assessment of multi-hazard scenarios, it is also necessary to evaluate the exposure and vulnerability (and the changes that they might suffer) of the risk receptors. 

In this context, project ICARIA (Improving ClimAte Resilience of crItical Assets, www.icaria-project.eu, GA: 101093806) aims at developing a comprehensive asset level modeling framework to quantify the risk associated with multi-hazard events for critical infrastructures and services in European Regions. Specifically, it focuses on three case studies:  the Barcelona Metropolitan Area in Spain, the Salzburg Region in Austria and the South Aegean Region in Greece. 

Based on a literature review, workshops with relevant stakeholders and the analysis of historic events, the main multi-hazard events of interest for the case studies have been identified. For all of them, the physical interactions established between the single-hazards involved have been determined in order to set an initial step to develop multi-hazard risk assessment methodologies in a later phase of the project. The joint probability of these events will be also estimated for current and future scenarios. The multi-hazard events taken into account within ICARIA are the following ones:

  • Pluvial flood and storm surge
  • Drought and forest fire
  • Drought and heat wave
  • Heat wave and forest fire
  • Extreme wind and forest fire
  • Heat wave, drought and forest fire

The understanding of the mechanism and effect of the abovementioned events will enable the assessment of the risk that these scenarios pose to the critical infrastructures of a region. Thus, these methodologies will stand as a valuable tool to improve the preparedness of key infrastructure to cope with such events.

How to cite: de La Cruz Coronas, A., Russo, B., Evans, B., Truchi, A., Leone, M., and Buegelmayer-Blaschek, M.: An approach to modeling interactions between extreme weather events during multi-hazard events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20217, https://doi.org/10.5194/egusphere-egu24-20217, 2024.

EGU24-20325 | Orals | NH10.1

Storylines and impact chains of multi-hazard risk scenarios in the framework of disaster risk reduction and climate change adaptation 

Anna Maria Zaccaria, Massimiliano Pittore, Claudio Marciano, Maria Polese, Gabriella Tocchi, Cristine Griffo, Andrea Pirni, Stefano Terzi, Silvia De Angeli, Francesca Ferretti, Luca Pozza, Serena Cattari, Sergio Lagomarsino, Antonella Peresan, and Daniela Di Bucci

Storylines are increasingly used in climate science to integrate the physical and socioeconomic components of phenomena, make climate evolution more tangible and provide unity of discourse. This approach has proved successful in describing realistic realizations of complex and uncertain processes, such as those related to climate change, and communicating it to both scientific and praxis-oriented audiences, hence supporting decision making. However, storylines have been applied in single-hazard contexts without addressing complex multi-hazard conditions. For these reasons, here we propose to extend storylines for multi-hazard risk assessments combining both disaster risk reduction and climate change adaptation activities.

In this context we introduce the concept of risk storylines, which refers to a defined, plausible combination of events, their consequences and the factors possibly affecting these elements (e.g., vulnerability or external risk drivers), as well as the physical, socio-ecological and functional elements at risk. Risk storylines are therefore scenario-based and can refer either to past events or to plausible future events, always considering the most relevant direct and indirect drivers of risk. A risk storyline should contain all relevant information necessary to describe the risks of concern, including a comprehensive description of the scope of the storyline (e.g., the purpose and operational context, the related urban configuration and the reference timeframe), the most relevant risks and related factors in play, namely hazards, exposure, vulnerabilities, and the different impacts that are linking together the former elements, as well as a synthetic narrative description of the risk storyline, describing main facts and consequences. Also, any scenario describing one or more current or future environmental conditions should be explicitly indicated, e.g. the Shared Socioeconomic Pathways (SSPs) or any other demographic / socio-economic future scenarios (in the case of storylines developed for future events). Whenever possible, reasoning on the probability of occurrence of such scenarios is also developed.

In order to complement the narrative description of the risk storyline with a more structured conceptual and graphical representation, the integrated use of impact chains has been explored. This combination provides a flexible and convenient framework to convey actionable information about those dynamic and complex environmental and socio-economic conditions possibly associated with high-impact, multi-hazard events and processes, and to consider in a single consistent framework both climate-driven (e.g., extreme hydrometeorological conditions) and climate-independent (e.g., earthquakes) hazards.

Risk storylines can be developed through participative, desktop-based or partly-analytic approaches and are particularly suitable for co-development activities with stakeholders and domain experts, with a great potential for supporting and improving risk prevention and mitigation decision-making under relevant aleatoric and epistemic uncertainty.

How to cite: Zaccaria, A. M., Pittore, M., Marciano, C., Polese, M., Tocchi, G., Griffo, C., Pirni, A., Terzi, S., De Angeli, S., Ferretti, F., Pozza, L., Cattari, S., Lagomarsino, S., Peresan, A., and Di Bucci, D.: Storylines and impact chains of multi-hazard risk scenarios in the framework of disaster risk reduction and climate change adaptation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20325, https://doi.org/10.5194/egusphere-egu24-20325, 2024.

EGU24-21355 | ECS | Orals | NH10.1

Developing a practical approach to assessing the drivers of multi-hazard risk in the Alpine space 

Amelie Hoffmann, Theresa Frimberger, Michael Krautblatter, and Daniel Straub

Unprecedented weather extremes have affected the Alpine space in recent years, significantly impacting human populations, the economy, and the environment. Extreme weather events can trigger a multitude of alpine hazards that, due to the distinct characteristics of the Alpine natural and built environment, have the potential to induce severe compound and cascading impacts. Despite recent scientific evidence that climate change will contribute to more intense and more frequent weather extremes, our understanding of local implications on multi-hazards, compound and cascading effects, and future risks remains insufficient. Consequently, risk managers and decision-makers lack a systematic approach to assess future changes in multi-hazard risk.

We are developing a practical approach that aims to help local risk managers answer fundamental questions about the drivers of multi-hazard risk in their respective Alpine regions. To that end, we combine a questionnaire about the current risk situation with a systematic basis for propagating the effects of future changes, covering all aspects of the risk chain, namely hazard, exposure, vulnerability, and capacity. Ultimately, the method aims to help (1) identify important drivers of (future) risk, (2) assess their contribution to the (future) risk landscape, and (3) identify relevant risk pathways for targeting (future) risk management practice.

The approach relies on detailed knowledge of local conditions that can only be provided by local stakeholders as well as more general input on the future trends in climate and anthropogenic developments that must be provided by higher authorities and the scientific community. This work is part of the X-RISK-CC project, funded by the Interreg Alpine Space Program 2021-27. The approach will be applied to some of the project's pilot regions to help generate insights that will assist risk managers in the evaluation and management of newly emerging risks associated with weather extremes in their respective regions.

How to cite: Hoffmann, A., Frimberger, T., Krautblatter, M., and Straub, D.: Developing a practical approach to assessing the drivers of multi-hazard risk in the Alpine space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21355, https://doi.org/10.5194/egusphere-egu24-21355, 2024.

EGU24-22042 | ECS | Orals | NH10.1

Web-Based Severity Assessment of Natural Hazards: Natural Language Processing Based Extraction of Severity Impact Factors for Informed Decision Support 

Lakshmi S Gopal, Hemalatha Thirugnanam, Maneesha Vinodini Ramesh, and Bruce D. Malamud

This study introduces an automated information extraction (IE) method for assessing natural hazard severity using online sources (news articles and social media). A web crawler collects 4-15 daily news articles from diverse web sources, amassing 4,000 reports on natural hazard events between 05/2020 and 11/2023, while adhering to respective web page privacy rules. The extracted data analyses hazard severity, focusing on the impact factors of casualties and damages. This analysis aids decision-makers and researchers in comprehending the impact of hazards and developing mitigation strategies. Real-time web data severity analysis can also support first responders in resource allocation during and post-disasters.

A natural language processing-based algorithm identifies hazard impact factors using grammatical patterns, PoS (Parts of Speech) tagging, and NER (Named Entity Recognition). From these, we identify numeric values for casualties, infrastructural and financial damages and public necessities, along with place names. The data is structured in a database for analysis.

We utilize TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), a Multi-Criteria Decision-Making method, to assign a severity rank to each location. In TOPSIS, we define the positive ideal solution as the maximum values for positive attributes (e.g., number of rescue operations, people rescued, and government authorities’ involvement). The negative ideal solution represents the minimum values for negative attributes (e.g., damages and fatalities) in each criterion. We then calculate relative closeness (0.0 to 1.0) by measuring each criterion’s distance from the positive and negative ideal solutions. A higher relative closeness indicates less severity, while a lower value suggests greater severity in hazard events. This rank aids in identifying the area with the highest severity, enabling first responders to allocate resources effectively by prioritizing the locations with the most significant impact. Each location’s severity rank is based on relative closeness to positive and negative ideal solutions.

We apply our methodology to the 2018 Kerala, India floods, using 200 news reports (national and local news portals, blogs), identifying the Alappuzha district as the most severely affected (highest severity score) and the Kasargod district the least affected (lowest severity score). Agricultural loss emerges as a significant factor, emphasizing the need for sustainable solutions. Results are consistent with official Kerala State Disaster Management Authority documentation, demonstrating the methodology’s accuracy. Our methodology provides near real-time information for identifying and prioritizing severely affected areas, aiding efficient resource allocation, rehabilitation efforts, and post-disaster decision-making.

How to cite: S Gopal, L., Thirugnanam, H., Vinodini Ramesh, M., and Malamud, B. D.: Web-Based Severity Assessment of Natural Hazards: Natural Language Processing Based Extraction of Severity Impact Factors for Informed Decision Support, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22042, https://doi.org/10.5194/egusphere-egu24-22042, 2024.

EGU24-509 | ECS | Orals | NH10.5

Global Ionospheric Responses in Both Hemispheres during the 2015 St. Patrick's Day Storm 

Bhupendra Malvi and Pramod Purohit

On St. Patrick's Day, March 17, 2015, the first historical intense geomagnetic storm (Dst < −200 nT) of the 24th solar cycle occurred. This storm caused complex effects around the globe. Geomagnetic storms are a concern for society, especially the strongest storms and how they affect satellite communications, navigations and power grids. Using Global Positioning System (GPS) data to compute the Total Electron Content (TEC) of the Earth's ionosphere is one of the most common methods used to investigate perturbations in the ionosphere. GPS TEC variations may reveal ionospheric anomalies, which might endanger the continuity and availability of GPS performance metrics. Thus, the ionospheric consequences of geomagnetic storms have been researched intensively for decades but are still not fully understood. This study investigates the ionospheric behaviour during an intense geomagnetic storm that occurred from 14 - 24 March 2015. In particular, we used geomagnetic indices and GPS TEC data from various IGS stations all over the world to give a comprehensive analysis of how the ionospheric total electron content changes in both the northern and southern hemispheres at different latitude and longitude stations.

How to cite: Malvi, B. and Purohit, P.: Global Ionospheric Responses in Both Hemispheres during the 2015 St. Patrick's Day Storm, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-509, https://doi.org/10.5194/egusphere-egu24-509, 2024.

Disastrous earthquakes are a permanent threat to every second resident of our planet causing a massive loss of lives and property. Understanding the nature of earthquake precursory signatures and related hazard mitigation has immense potential for scientific advancement as well as for societal benefits. To study these multidisciplinary and complicated precursory signatures, several models have been proposed in favor of the Lithosphere- Atmosphere- Ionosphere- Coupling (LAIC) mechanism by earlier workers. The major objective of this study is to investigate the short-term perturbations in land surface temperature (LST), atmospheric air temperature (AT), atmospheric relative humidity (ARH), and in ionospheric vTEC prior to the destructive shallow sheeted Turkey-Syria earthquake (Mw 7.8, Depth 10 Km, Intensity IX) on 6th February 2023 and its major aftershocks (Mw 7.5, 6.8, 6, 6). Earthquakes of such large magnitude causes synchronization changes, not only in the atmospheric parameters but also in the ionospheric TEC. The GPS and GNSS (IGS) derived ionospheric TEC data are now being used extensively to investigate seismo-ionospheric perturbations over and near the epicentral regions of earthquakes over the last two decades. To identify the perturbation in the LST and atmospheric parameters (AT and RH), we have studied the spatio-temporal variation of MODIS (Terra) derived LST data and MERRA 2 (NASA) derived atmospheric temperature and relative humidity at 2 meter height. The Terra-MODIS derived LST differential time series reveals a prominent increase ~ 6-16 ⁰C from 18th to 26th Jan, 2023 around the epicentral region. Moreover, the hourly varying atmospheric parameters (AT, RH) have shown significant and synchronous deviations from 18th Jan to 26th Jan. The highest positive (+ve) deviation in the AT is found to be 10.33 ⁰C and the lowest negative (-ve) anomaly in the RH is found to be 45.67% on 19th Jan. The observed atmospheric anomalies are identified with respect to the constructed bounds using past 5 years hourly data (m ± 2σ). The temporal variation of ionospheric vTEC of the nearest grid point, derived from both GNSS (IGS) and GPS receivers shows a series of prominent –ve anomalies from 25th Jan to 1st Feb about 5-12 days prior to the main shock. After ruling out possible contributions due to the solar terrestrial environment with respect to F10.7 Scale and Ap index, it is found that the evolved TEC anomaly is seismogenic in origin. In order to visualize the TEC anomaly in spatio-temporal domain, we have plotted 2D latitude-longitude time (LLT) maps of different epochs during those anomalous days (Max anomaly~ -15 TECu on 28th Jan at UTC 11th and 12th hour). Considering the nearest plate boundary, spatial extent of TEC conjugates and TEC gradient we have determined the probable epicenter which showed very promising correlation in comparison to actual epicenter. This multi parametric spatio-temporal analysis of the pre-seismic signature will produce some beneficial insight to understand the LAIC mechanism in detail and somehow be able to save so many lives.

How to cite: Dutta, B. and Malik, J. N.: Potential Utilization of Multi-Parametric Earthquake Precursory Signatures in Support of LAIC Mechanism: A case study on Turkey- Syria Earthquake (6th Feb, 2023)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1054, https://doi.org/10.5194/egusphere-egu24-1054, 2024.

EGU24-2380 | ECS | Posters on site | NH10.5

Modeling Equatorial Plasma Bubbles with SAMI3/SD-WACCM-X: Large-Scale Wave Structure 

Min-Yang Chou, Jia Yue, Nicholas Pedatella, Sarah McDonald, and Jennifer Tate

Large-scale wave structure (LSWS) in the bottomside F layer is pivotal in developing equatorial plasma bubbles (EPBs), potentially serving as a precursor of EPBs. Gravity waves, hypothesized to contribute through the wind dynamo mechanism, face experimental challenges. This study, utilizing the coupled SAMI3 and SD-WACCM-X models, investigates the role of gravity wave wind dynamo effect and gravity in LSWS development. We found that the gravity waves originating from the lower atmosphere induce vertical E×B drift perturbations in the nighttime ionosphere. Notably, LSWS can manifest independently of gravity, emphasizing the dominance of the gravity wave wind dynamo mechanism. However, LSWS exhibits more pronounced vertical E×B drift perturbations, indicating an additional eastward Pedersen current driven by equatorial winds (i.e., downward wind) via the gradient drift instability. Gravity-driven Pedersen current, therefore, plays a role in amplifying the LSWS and EPB development. Simulations also show the emergence of pre-dawn turbulent bubble-like irregularities in the bottomside ionosphere even without gravity, attributed to concentric gravity waves over the magnetic equator. Our findings underscore the significant influence of gravity waves on the formation of LSWS and ionospheric irregularities.    

How to cite: Chou, M.-Y., Yue, J., Pedatella, N., McDonald, S., and Tate, J.: Modeling Equatorial Plasma Bubbles with SAMI3/SD-WACCM-X: Large-Scale Wave Structure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2380, https://doi.org/10.5194/egusphere-egu24-2380, 2024.

The Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere, and Ionosphere (MVP-LAI) instrumental array was established in Sichuan, China, in 2021. The MVP-LAI station has demonstrated its efficacy in investigating the causal mechanisms of LAI coupling among multiple geophysical parameters in the vertical direction above a specific area on the Earth's surface during natural hazards such as earthquakes, volcanic eruptions, and landslides. Another MVP-LAI station will be established in Yunnan, approximately 200 km away from the first one, this year. Additionally, a high-frequency Doppler sounder array, comprising two transmitters with distinct frequencies and eight receivers, will be installed in areas covering both MVP-LAI stations to monitor vertical changes in ionospheric layers at two specific altitudes. It is noteworthy that observations from seismometers, magnetometers, and ground-based GNSS receivers in this area can be utilized to capture waves and/or perturbations propagating along the horizontal layer at the Earth's surface, at altitudes of approximately 100 km and 350 km, respectively. The two frequencies employed by the high-frequency Doppler sounder array can aid in comprehending how waves and/or perturbations propagate along the horizontal layers at approximately 200 km and 250 km in altitude. When the two MVP-LAI stations, the high-frequency Doppler sounder array, and substations are integrated, vibrations and/or perturbations propagate both vertically and along the five horizontal layers, even in slant directions, can be detected. The collaboration between MVP-LAI stations and horizontal observations forms the Greater Omnidirectional Ascertain Technology (GOAT), which enhances the understanding of the proportional mechanism for the LAI coupling.

How to cite: Chen, C.-H., Sun, Y.-Y., Lin, K., and Zhang, X.: Greater Omnidirectional Ascertain Technology (GOAT) of the Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere, and Ionosphere (MVP-LAI) Array, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2698, https://doi.org/10.5194/egusphere-egu24-2698, 2024.

The sudden cutoff of solar radiation caused by the solar eclipse could cause significant changes in the thermosphere and ionosphere, considering the fact that the solar radiation plays a significant role in their dynamical processes. In this study, the thermospheric neutral wind recorded by the Michelson Interferometer for Global High-Resolution Thermospheric Imaging (MIGHTI) on the Ionospheric Connection Explorer (ICON) spacecraft and metero radar were analyzed to examine the variations in thermospheric wind during and after the 21 June 2020 annular solar eclipse over the East China area. The neutral wind observations showed direct evidences that the solar eclipse disturbed the mesosphere and low thermosphere for more than 10 hours. The clear enhancement of the meridional wind during the moon obscuration and sharply decreased meridional wind after local sunset suggested that a large-scale oscillation was caused by the solar eclipse, which persisted from daytime to nighttime.

How to cite: Wang, J. and Sun, Y.-Y.: Thermospheric wind response to the annular solar eclipse on 21 June 2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2968, https://doi.org/10.5194/egusphere-egu24-2968, 2024.

A FORMOSAT-5 satellite was launched on 25 August 2017 CST into a 98.28° inclination sun-synchronous circular orbit at 720 km altitude along the 1030/2230 local time sectors.  Advanced Ionospheric Probe (AIP), a piggyback science payload developed by National Central University for the FORMOSAT-5 satellite, has measured in-situ ionospheric plasma concentrations at a 1,024 Hz sampling rate over a wide range of spatial scales for more than 6 years.  In this poster, global plasma density irregularities in the pre-midnight sector had been seasonally selected from FORMOSAT-5/AIP data during 2018 to 2023.  Yearly variations of these irregularity patterns with solar cycle could be clearly observed.

How to cite: Chao, C.-K.: Equatorial Plasma Density Irregularities Observed by Advanced Ionospheric Probe Onboard FORMOSAT-5 Satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2985, https://doi.org/10.5194/egusphere-egu24-2985, 2024.

EGU24-2998 | ECS | Orals | NH10.5

Simulation of the atmospheric Acoustic-gravity waves caused by a finite fault 

Ting Li and Yongxin Gao

Based on the stratified lithosphere-atmosphere model, we present a semi-analytic method for calculating acoustic-gravity waves (AGWs) excited by a finite fault in the lithosphere. A finite fault is decomposed into a series of small subfaults, each treated as a point source with distinct rupture times. The fault is assumed to slide uniformly at a constant velocity along a specific direction. Simulation results reveal that both sides of the fault generate two types of AGWs when the fault rupture initiates and ceases. One type is the head AGW, generated by the P and Rayleigh waves propagating along the surface. The other one is the epicenter AGW, produced by direct seismic waves. The propagation of the AGWs is directional and related to the fault mechanism. We investigated a vertical strike-slip fault and a thrust fault, finding that the velocity amplitudes of the AGWs caused by both types of faults along the rupture direction are larger than the opposite direction. The AGWs induced by the thrust fault are stronger than those caused by the strike-slip fault. Furthermore, variations in the rupture velocity result in differences in waveform.

How to cite: Li, T. and Gao, Y.: Simulation of the atmospheric Acoustic-gravity waves caused by a finite fault, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2998, https://doi.org/10.5194/egusphere-egu24-2998, 2024.

EGU24-3089 | ECS | Orals | NH10.5

Design, Testing, and Preliminary Data Analysis of the Seafloor Absolute Pressure Gauge 

Ching-Ren Lin, Ya-Ju Hsu, Feng-Sheng Lin, and Kun-Hui Chang

Taiwan is situated in the collision zone between the Philippine Sea Plate and the Eurasian Plate, where these two plates are converging at an average rate of 8.2 centimeters per year, leading to significant crustal deformation on the island. Utilizing data from GPS (Global Positioning System) measurements processed and analyzed using Bernese software, the average velocity field of crustal movements can be estimated, providing a more comprehensive understanding of crustal deformation. The combination of GPS and seafloor geodesy observations can aid in unraveling the seismic processes along plate boundaries. Due to the inability of GPS signals to penetrate seawater, acoustic methods are employed to make ocean bottom pressure (OBP) measurements, serving as a valuable and unique tool for monitoring integrated ocean currents and observing sea level changes.

OBP measurements have been applied for various geophysical purposes, including ocean physics and marine geodesy. Seafloor Absolute Pressure Gauges (SAPG) based on quartz oscillation principles have been employed to record phenomena such as tsunamis, ocean tides and non-tidal sea level variations, as well as seafloor vertical deformations. These instruments play a crucial role in marine physics research.

In recent years, the Academia Sinica has also conducted research in the surrounding waters of Taiwan using acoustic positioning methods for seafloor geodetic observations. In conjunction with seafloor geodetic observations, ocean bottom pressure (OBP) measurement is another method employed.

The seafloor absolute pressure gauge (SAPG) developed by the Academia Sinica is composed of a Paroscientific Inc. quartz vibrating pressure sensor, integrated with an OEM data logger from RBR-Global Co. (http://www.rbr-global.com/products/bpr) and components such as the BART Boards with Regular Tuning ROUND and Acoustic Transducer that made by EdgeTech Co. The assembly of SAPG has been completed, and it has been deployed in the waters off the eastern coast of Taiwan for long-term observations. This paper will introduce the instrument assembly of SAPG, pre-deployment testing, and preliminary analysis results of the marine data.

How to cite: Lin, C.-R., Hsu, Y.-J., Lin, F.-S., and Chang, K.-H.: Design, Testing, and Preliminary Data Analysis of the Seafloor Absolute Pressure Gauge, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3089, https://doi.org/10.5194/egusphere-egu24-3089, 2024.

In fair weather, the vertical atmospheric electric field is oriented downward (positive in the earth surface ordinate system) in the global atmospheric circuit. Some researchers revealed the unique phenomenon whereby once an upward vertical atmospheric electric field is observed in fair weather, an earthquake follows within 2-48 hours regardless of the earthquake magnitude. However, the mechanism has not been explained with a suitable physical model. In this paper, a physical model is presented considering four types of forces acting on charged particles in air. It is demonstrated that the heavier positive ions and lighter negative ions are rapidly separated. Finally, a reversed fair weather electrostatic field is formed by the above charge separation process. The simulation results have instructive significance for future observations and hazard predictions and it still needs further research.

How to cite: Chen, T. and Li, L.: Atmospheric charge separation mechanism due to gas release from the crust before an earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3308, https://doi.org/10.5194/egusphere-egu24-3308, 2024.

EGU24-3330 | Orals | NH10.5

Acoustic-gravity waves generated by a point earthquake source 

Yongxin Gao and Ting Li

It is reported that earthquakes can trigger coseismic ionospheric disturbances, leading to the so called Lithosphere-atmosphere-ionosphere (LAI) coupling phenomenon. The acoustic-grave wave (AGW) is an important mechanism to induce such a phenomenon. In this study, we present a semi-analytic method to calculate AGWs excited by an earthquake source in the stratified lithosphere-atmosphere model and conduct numerical simulations to investigate characteristics of the AGWs. The results show that mainly two kinds of AGWs can be generated by the earthquake source. One is the head AGWs wave generated by the Rayleigh wave propagating along the surface, which propagates upwards nearly vertically. Another one is the epicenter AGWs generated by the direct seismic waves from the source. Both the head and epicenter AGWs are sensitive to the earthquake focal mechanism and are influenced by the structures of the atmosphere and solid earth. We also apply our method to a real earthquake event and compare the synthetic signals with the observed data.

How to cite: Gao, Y. and Li, T.: Acoustic-gravity waves generated by a point earthquake source, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3330, https://doi.org/10.5194/egusphere-egu24-3330, 2024.

EGU24-3553 | Orals | NH10.5

Differences between ionospheric infrasound induced by a strong volcanic eruption and an earthquake. 

Jaroslav Chum, Petra Koucká, Tereza Šindelářová, and Jan Rusz

 Strong earthquakes and volcano eruptions generate atmospheric waves in the infrasound range that can reach ionospheric heights and cause electron density disturbances that can be monitor remotely, e.g., using electromagnetic waves. Using infrasound measurement in the ionosphere by continuous radio Doppler sounding in Europe, the differences between ionospheric disturbances induced by earthquakes and volcano eruption are discussed on the examples of the recent M=7.7 Turkey 6 February 2023 earthquake and Hunga eruption on 15 January 2022. It will be shown that the main difference is that co-seismic (induced by seismic waves) infrasound detected in the ionosphere propagated roughly vertically and is generated locally (below the observation in the ionosphere) by vertical movement of ground surface. On the other hand, the infrasound induced by volcano eruption propagated most probably from the source (volcano) and leaked to the ionosphere from the imperfect stratospheric and thermospheric wave guide. In addition, a distinct travelling ionospheric disturbance was observed.    

How to cite: Chum, J., Koucká, P., Šindelářová, T., and Rusz, J.: Differences between ionospheric infrasound induced by a strong volcanic eruption and an earthquake., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3553, https://doi.org/10.5194/egusphere-egu24-3553, 2024.

EGU24-3948 | ECS | Orals | NH10.5

Electromagnetic response to undersea earthquakes in marine layered model 

Qianli Cheng and Yongxin Gao

In this study, we adopt a horizontally layered model which consisting of air, seawater and undersea porous rock and develop an analytically-based method to calculate the seismic and EM fields generated by undersea earthquakes. We conduct numerical simulations to investigate the characteristics of the EM response in three case (the receivers located at the seafloor, in the seawater near the sea surface and in the air, respectively). The results show that two kinds of EM signals can be identified in the EM records at these receivers. The first is the early EM wave arriving before the seismic waves and the second is the coseismic EM fields with apparent speed of the seismic waves. The EM signals observed at the seafloor are mostly stronger than those observed in the seawater and air near the sea surface. We applied this method to simulating the EM response to the 2022 Mw 7.3 earthquake that took place in the sea near Fukushima, Japan. At the receiver with 80 km epicentral distance at the seafloor, the predicted coseismic electric and magnetic signals reach the amplitudes of 2 μV/m and 2 nT, respectively. The results suggest a possibility to monitor the EM disturbances associated with marine earthquakes and use them to serve the earthquake early warning or earthquake mitigation.

How to cite: Cheng, Q. and Gao, Y.: Electromagnetic response to undersea earthquakes in marine layered model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3948, https://doi.org/10.5194/egusphere-egu24-3948, 2024.

EGU24-4579 | Orals | NH10.5

Ionospheric space weather and seismo-ionospheric precursors observed by China seismo-electromagnetic satellite 

Jann-Yenq Liu, Fu-Yuan Chang, Yun-Cheng Wen, and Xuhui Shen

The China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate seismo-ionospheric precursors (SIPs) and ionospheric space weather.  The CSES probes manifest longitudinal features of 4-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs.  CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric disturbances induced by an intense storm with the Dst index of -175 nT on 26 August 2018.  Spatial analyses of GIM TEC and CSES plasma quantities discriminate SIPs from global effects and locate the epicenter of possible forthcoming large earthquakes.  CSES ion velocities are useful to derive SIP- and storm-related electric fields in the ionosphere.

How to cite: Liu, J.-Y., Chang, F.-Y., Wen, Y.-C., and Shen, X.: Ionospheric space weather and seismo-ionospheric precursors observed by China seismo-electromagnetic satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4579, https://doi.org/10.5194/egusphere-egu24-4579, 2024.

EGU24-4806 | Posters on site | NH10.5

Rapid Estimation of 2022 Tonga Erupted Volume from the Remote Seismo-Acoustic Resonance 

Cheng-Horng Lin, Min-Hung Shih, and Ya-Chuan Lai

The powerful acoustic waves generated by the major eruption on January 15, 2022 on Hunga Tonga Hunga Ha’apai (HTHH) of Tonga were unambiguously recorded in Taiwan by several infrasonic stations and Formosa array, which consists of 146 broadband seismic stations with an average spacing of ~5 km in northern Taiwan. Based on the carefully analyses of the broadband frequency-wavenumber method (BBFK) and the Fast Fourier Transform (FFT), it was interesting to see that both data sets consistently showed a resonant frequency of ~0.0117 Hz persisted for more than 25 minutes after the first major eruption. Such a long-duration resonance of the remote seismo-acoustic waves provides a rapid estimation of the erupted magma volume of 0.215 ± 0.015 if the volcanic cavity produced by the erupting magma is considered as a classic Helmholtz resonator. Thus, we may obtain that the first major eruption alone of HTHH rated a 4 on the VEI scale. But the total erupted volume could reach up VEI 5 or even 6 if we consider all of the accumulated magma from the following eruptions.

How to cite: Lin, C.-H., Shih, M.-H., and Lai, Y.-C.: Rapid Estimation of 2022 Tonga Erupted Volume from the Remote Seismo-Acoustic Resonance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4806, https://doi.org/10.5194/egusphere-egu24-4806, 2024.

EGU24-4922 | Posters on site | NH10.5

Indicators of the Activity Associated with Concealed Feeding Volcanic Fluids in the Tatun Volcano Group, Northern Taiwan 

Hsin-Chieh Pu, Cheng-Horng Lin, Hsiao-Fen Lee, Ya-Chuan Lai, Min-Hung Shih, Guo-Teng Hong, and Po-Tsun Lee

We analyzed 3,330 earthquake focal mechanisms and the fumarolic gases in the Tatun Volcano Group (TVG) during 2018–2021. Between June/2020 and June/2021, we found a concealed inflation beneath a depth of 2 km. We indicate this inflating mechanism was associated with the feeding volcanic fluids, which induced the past inflating cases in the TVG before 2018. We deliberated about the feeding features regarding this and the past cases and purpose three indicators to monitor such concealed activities, including the inflating indicator associated with the behaviors of earthquake faulting, heating indicator determined by the systematically high HCl/CO2 ratios, and discharging indicator displayed by the lasting high St/CO2 ratios. Using these indicators, we concluded that it was not rare during the last one decade that the concealed activities whose volcanic fluids were discharged occasionally.

How to cite: Pu, H.-C., Lin, C.-H., Lee, H.-F., Lai, Y.-C., Shih, M.-H., Hong, G.-T., and Lee, P.-T.: Indicators of the Activity Associated with Concealed Feeding Volcanic Fluids in the Tatun Volcano Group, Northern Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4922, https://doi.org/10.5194/egusphere-egu24-4922, 2024.

A solar storm can trigger severe geomagnetic and ionospheric disturbances, and activities originating from the Earth’s surface can do so as well. This presentation will introduce the sudden changes in the ionospheric plasma structure and electrodynamics after large lithospheric disturbances, such as earthquakes/tsunamis and volcanic eruptions. The main focus will be on the two significant events of the magnitude 9.0 Tohoku earthquake/tsunami (38.3°N 142.4°E) in the northeastern sea area of Japan on 11 March 2011, and the undersea volcanic eruption in Tonga (20.6°S 175.4°W), Central Pacific, on 15 January 2022. This presentation will also discuss the main characteristics of disturbances in ionospheric structures and electrodynamics. Investigating the two events enhances our comprehension of the sensitivity of the ionosphere response to lithospheric activities.

How to cite: Sun, Y.-Y.: Electrodynamic changes in the ionosphere due to large lithospheric disturbances, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4979, https://doi.org/10.5194/egusphere-egu24-4979, 2024.

Pre-earthquake anomalous phenomena in different geospheres have been widely reported.  Scientists found that the anomalies appear days to months prior to earthquakes from distinct geophysical parameters.  It is urgent and challengeable to investigate impending-earthquake anomalous signals for earthquake prediction.  The MVP-LAI (Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere, and Ionosphere) system was established at Leshan, Sichuan, China in 2021.  The system monitors the changes of over 20 various geophysical parameters from subsurface to ionosphere.  It aims to gain insights into the mechanisms of the lithosphere-atmosphere-lithosphere coupling (LAIC) during natural hazards.  On 5 September 2022, a M6.8 earthquake occurred at Luding, which is approximately 175 km from the MVP-LAI system.  The results show that the seven parameters from the MVP-LAI system simultaneously exhibited abnormal signal approximately 3 hours before the Luding earthquake. The parameters include ground tilts, air pressure, radon concentration, atmospheric vertical electric field, geomagnetic field, wind field, and total electron content. The enhancement in radon concentration suggests that the chemical channel could be a promising mechanism for the coupling of geospheres. On the other hand, air pressure, the geomagnetic field, and total electron content exhibit similar anomalous spectral characteristics. These anomalies may be attributed to atmospheric resonance before the earthquake. Furthermore, the reduction of the horizontal wind speed, and the increase of upward vertical wind support the resonance channel. The results demonstrate that the LAIC before earthquakes could be dominated by multiple potential mechanisms. The multi-parameter anomalies identified in this study guarantee approximately 3 hours of warning for people to prepare for the seismic event and mitigate hazards.

How to cite: Mao, Z. and Chen, C.-H.: Multi-parameter anomalies of the lithosphere, atmosphere, and ionosphere approximately three hours prior to the M6.8 Luding earthquake in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7128, https://doi.org/10.5194/egusphere-egu24-7128, 2024.

The ionosphere owns a complex electric current system mainly driven by the ionospheric electric field and thermospheric wind. Changes in current can generate geomagnetic signals that can be observed both on the ground and in space. In this study, we analyzed the ionospheric current in the Asia-Oceania region by utilizing geomagnetic data collected from magnetometers of ground-based observatories and SWARM satellites at ~450 km altitude. The results present the geomagnetic variations at the two distinct altitudes, encompassing longitudinal, latitudinal, and seasonal variations. Furthermore, the Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) was employed to simulate the associated geomagnetic signals. This study is the first to combine dense geomagnetic data from multiple altitudes and simulations to understand the ionospheric current in the Asia-Oceania region. The differences between the observational geomagnetic signals at different altitudes, along with the simulations, reveal a unique current structure that has not been previously discovered. The findings provide a new understanding of the intricate evolution of the current systems, which contributes to our knowledge of the electric dynamics within Earth's ionosphere.

How to cite: Zhang, P. and Sun, Y.-Y.: A unique structure of the ionospheric current over the Asian-Oceania region determined by the combination of the ground-based and space-borne magnetometers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8677, https://doi.org/10.5194/egusphere-egu24-8677, 2024.

The Qinling Orogenic Belt (QOB) is one of the most important orogens in Eastern Asia formed by the collision between the North China Block (NCB) and the South China Block (SCB). The evolution history of the QOB is essential to the assembly processes of the major blocks in China and the evolution history of the Proto-Tethys Ocean (Shangdan Ocean). Paleomagnetism can quantitatively restore the paleo-position of blocks, which is key to studying the related tectonic evolution. Hindered by the complex tectonic process, few paleomagnetic results have been reported from the QOB. Here we reported a primary paleomagnetic study from the northern QOB by conducting both rock magnetic and paleomagnetic experiments on the early Devonian Lajimiao pluton (~413Ma) in the North Qinling belt (NQB), to constrain its paleo-position and the evolution of the QOB during the early Paleozoic period.

253 cores from 28 sites were drilled by portable gasoline drills, and oriented by a magnetic compass and also a sun compass if possible. Rock magnetic experiments indicate that the main magnetic mineral in most of the samples is mainly magnetite in a pseudo-single domain or multi-domain state. Both thermal demagnetization and alternating-field demagnetization were applied to obtain the characteristic remanent magnetization. The Fisher-mean direction of the low-temperature/coercivity component is roughly consistent with the present geomagnetic field (PGF), suggesting that it is probably a viscous remanent magnetization caused by the PGF. The high-temperature/coercivity component yielded a Fisher-mean direction Ds/ Is = 355.8°/19.1° in stratigraphic coordinates, corresponding to a paleomagnetic pole of 65.8°N/299.9°E (A95=2.4°). It is the first Devonian paleomagnetic pole among the scarce paleomagnetic results from the QOB. This pole indicates that the NQB may have been located at a low latitude at the early Devonian, probably in proximity to both the North China and South China blocks. However, the difference between the coeval paleomagnetic poles from the three blocks (NQB, NCB, SCB) may hint the assembly process of the several major blocks is not simple and direct. Anyway, the newly obtained paleomagnetic pole from the NQB would be able to refine our understanding of the tectonic evolution of the QOB and the Proto-Tethys Ocean.

How to cite: Xu, H., Liang, Y., Lai, Y., and Li, G.: Primary Devonian paleomagnetic results from the Qinling orogenic belt and its implication for the evolution of the Proto-Tethys Ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9414, https://doi.org/10.5194/egusphere-egu24-9414, 2024.

EGU24-11811 | ECS | Orals | NH10.5

Comparative analysis of recent seismic and volcanic events in the Tonga-Kermadec zone: Insights into Lithosphere-Atmosphere-Ionosphere Coupling 

Serena D'Arcangelo, Mauro Regi, Angelo De Santis, Loredana Perrone, Gianfranco Cianchini, Maurizio Soldani, Alessandro Piscini, Cristiano Fidani, Dario Sabbagh, Stefania Lepidi, and Domenico Di Mauro

The Tonga-Kermadec zone stands out as one of the most active areas in the world for continuous subduction processes characterizing the area. In the recent few years, it has been affected by two important geophysical events: first a strong earthquake of M7.2 on June 15, 2019, with the epicentre in Kermadec Islands (New Zealand), and then an exceptional eruption of Hunga Tonga-Hunga Ha’apai volcano on January 15, 2022. We focused our attention on the phenomena appearing before, during and soon after each event, employing a multi-parametric and multi-layer approach in order to analyse the geodynamics of the entire area and the involved lithosphere-atmosphere-ionosphere coupling (LAIC). In details, for the lithosphere we conducted a seismic analysis of the earthquake sequence culminating with the mainshock on June 15, 2019, and of those preceding the big eruption, within a circular area with Dobrovolsky strain radius corresponding to that of an equivalent seismic event of magnitude equal to the energy released during the eruption. Moving to the atmosphere, we considered some parameters possibly influenced by seismic and volcanic events, using the CAPRI algorithm to the ECMWF datasets to detect anomalies in their values. Finally, by observing satellite data, we analysed the magnetic field and electron burst precipitations, potentially correlated to the events. All these observations, along with their similarities and differences, provide a better insight of the complex tectonic context.

How to cite: D'Arcangelo, S., Regi, M., De Santis, A., Perrone, L., Cianchini, G., Soldani, M., Piscini, A., Fidani, C., Sabbagh, D., Lepidi, S., and Di Mauro, D.: Comparative analysis of recent seismic and volcanic events in the Tonga-Kermadec zone: Insights into Lithosphere-Atmosphere-Ionosphere Coupling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11811, https://doi.org/10.5194/egusphere-egu24-11811, 2024.

EGU24-12565 | Posters on site | NH10.5

TROPOMAG - Influence of geomagnetic storms on the TROPOsphere dynamics: Can the Earth’s MAGnetic field be considered a proxy of climate changes? Some results 

Lucia Santarelli, Valentina Bruno, Igino Coco, Sofia De Gregorio, Paola De Michelis, Fabio Giannattasio, Paolo Madonia, Michael Pezzopane, Marco Pietrella, Massimo Rossi, and Roberta Tozzi

The TROPOMAG project investigates the possible effects of changes of the Earth’s magnetic field on the atmosphere and weather conditions with the aim to better quantify the natural sources of the atmospheric variability. This need raises to assess the observed climate trends more correctly, with a consequent better understanding of manmade effects on climate. Specifically, this work explores possible connections between atmospheric pressure anomalies and the occurrence of geomagnetic storms. To accomplish this task pressure data, recorded over some Italian volcanic areas, are analysed according to different methods and considering geomagnetic indexes. This work describes and discusses corresponding preliminary results.

How to cite: Santarelli, L., Bruno, V., Coco, I., De Gregorio, S., De Michelis, P., Giannattasio, F., Madonia, P., Pezzopane, M., Pietrella, M., Rossi, M., and Tozzi, R.: TROPOMAG - Influence of geomagnetic storms on the TROPOsphere dynamics: Can the Earth’s MAGnetic field be considered a proxy of climate changes? Some results, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12565, https://doi.org/10.5194/egusphere-egu24-12565, 2024.

EGU24-12791 | Orals | NH10.5

The case of the missing ionosphere: Investigating the ionospheric hole following the 2022 Tonga volcanic eruption 

Claire Gasque, Brian Harding, Thomas Immel, Yen-Jung Wu, and Colin Triplett

Following the eruption of the Hunga Tonga-Hunga Ha'apai (hereafter called ‘Tonga’) volcano just before local sunset on 15 January 2022, satellite data reveals the formation of a large-scale plasma depletion surrounding the region. This depletion persisted for roughly 14 hours, until local sunrise resumed plasma production. By combining in-situ and remote satellite observations, we seek to characterize the depletion's magnitude, spatial scale, and temporal evolution in the hours following the eruption. We will compare this to observations of ionospheric holes following previous impulsive lower atmospheric events, such as the 2011 Tohoku earthquake. Finally, we will investigate the dominant mechanism for locally depleting the plasma following this event, considering field-aligned ion drag, cross B transport due to electric fields arising from dynamo or other effects, and changing recombination rates. We aim ultimately to better understand the coupling between the lower atmosphere and ionosphere/thermosphere system following impulsive events such as this eruption. 

How to cite: Gasque, C., Harding, B., Immel, T., Wu, Y.-J., and Triplett, C.: The case of the missing ionosphere: Investigating the ionospheric hole following the 2022 Tonga volcanic eruption, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12791, https://doi.org/10.5194/egusphere-egu24-12791, 2024.

EGU24-13179 | Orals | NH10.5

Experimental data and models for radio diagnostics of extreme impacts “from above” and “from below” on ionospheric space weather: VLF, LOFAR and GNSS 

Yuriy Rapoport, Volodymyr Grimalsky, Andrzej Krankowski, Leszek Błaszkiewicz, Paweł Flisek, Kacper Kotulak, Adam Fron, Volodymyr Reshetnyk, Asen Grytsai, Vasil Ivchenko, Alex Liashchuk, and Sergei Petrishchevskii

Radio diagnostics, including scattering of electromagnetic waves (EMW) by spatiotemporal disturbances of the ionospheric plasma in the ELF (Extremely Low Frequencies, Hz), VLF (Very Low Frequencies, kHz), HF (High Frequencies, MHz) and microwaves (GHz) ranges, is one of the most effective methods for detecting and studying extreme modifications of ionospheric “space weather”. Such modifications are caused, in particular, by influences “from above” (from the Solar wind and magnetospheric storms) and “from below” (from tropical cyclones, earthquakes and volcanoes) and other Natural Hazards. Such ionospheric modifications are manifested, in particular, in the excitation of TIDs (Traveling Ionospheric Disturbances) and scintillations on various scales of the HF waves detected by LOFAR (Low Frequency Array) Radio Telescope.

In combination with other ionosphere sounding techniques (as GNSS) LOFAR can give a complementary insight to the ionospheric structures. We present LOFAR scintillation observations compared with GNSS-observed ionospheric irregularities in order to assess the ionospheric plasma structures. Classified ionospheric scintillation data will be presented. These include quasi-periodic, quasi-pulse, flare-like and other disturbances detected on the LOFAR radio telescopic systems in Poland, Great Britain, Germany and other countries. Spectral processing of LOFAR data is currently being carried out to identify various types of ionospheric disturbances, including TIDs, that characterize ionospheric space weather. We are currently developing TID modelling methods aimed at comparison with experimental data. Theoretical and experimental data on ionospheric disturbances associated with the eruption of the Hunga-Tonga-Hunga-Ha'apai volcano in January 2022 are presented and the results of their comparison are discussed. Based on the data-driven approach, effective current sources associated with lightning discharges caused by the eruption of the Hunga-Tonga-Hunga-Ha'apai volcano are identified in the ULF (Ultra-Low Frequency), ELF and VLF ranges. In particular, theoretical results are given on: (i) the excitation of the first and second modes of the Schumann resonator; (ii) the fundamental possibility of simultaneous excitation of coupled global Schumann and local Alfvén resonators. The results of applying the model for the scattering of HF electromagnetic waves (EMWs) on ionospheric disturbances such as increased and decreased plasma densities will be presented. The effects of birefringence, the dependence of EMW frequency on time in moving plasma, diffraction and dispersion of EMWs will be included, based on the advanced method of Complex Geometrical Optics.

An information is provided on the Ukrainian Ground-Based Space Weather Monitoring Network. This network includes GNSS stations, VLF receivers, Magnetotelluric stations, Ionosonde and magnetometer INTERMAGNET. Examples of corresponding measurements are presented.

Yu.R. and L.B. are grateful, for partial funding this research, by National Science Centre, Poland, grant No 2023/49/B/ST10/03465, “Modern Radio-Diagnostics of the Ionosphere using LOFAR and GNSS Data”

How to cite: Rapoport, Y., Grimalsky, V., Krankowski, A., Błaszkiewicz, L., Flisek, P., Kotulak, K., Fron, A., Reshetnyk, V., Grytsai, A., Ivchenko, V., Liashchuk, A., and Petrishchevskii, S.: Experimental data and models for radio diagnostics of extreme impacts “from above” and “from below” on ionospheric space weather: VLF, LOFAR and GNSS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13179, https://doi.org/10.5194/egusphere-egu24-13179, 2024.

The M7.8 and M7.5 earthquakes that occurred on 6 February 2023 in Turkey caused co-seismic ionospheric disturbances, and ionospheric total electron content (TEC) disturbances can be detected by Beidou geostationary satellites. The 17 GNSS continuous observation stations from IGS Net around the epicenters receive electromagnetic wave signals emitted by two Beidou geostationary satellites located above the equator at a frequency of 1 Hz. That allows us to obtain the TEC time series at fixed ionospheric piercing points (IPPs). Disturbances triggered by the M7.5 earthquake propagate farther and have a larger amplitude in general traveling at least 1600 km northwest and 800 km south and reaching the furthest area of the study with the maximum amplitude of about 2.5 TECU. For Mw 7.8 earthquake, the disturbances can be observed about 800 km northwest of the epicenter while no significant disturbances detected further away and the maximum amplitude of the disturbances is about 0.25 TECU. The TEC disturbances propagation speeds corresponding to the M7.5 and M7.8 earthquakes are 2.77 km/s and 2.60 km/s as the results of least squares fitting performed on epicentral distances and travelling times of the disturbances with the greatest amplitude. The speeds are closer to Rayleigh waves velocity of about 3 km/s at the surface rather than acoustic waves velocity of about 1 km/s in the ionosphere. The velocity of propagation for the co-seismic ionospheric disturbances, as determined by utilizing the Beidou geostationary satellites during two earthquakes, is consistent with that of the Rayleigh waves determined from the seismometers. Meanwhile, the velocity exhibits directional disparities for M7.5 earthquake.

How to cite: Rao, H. and Chen, C.-H.: Co-seismic ionospheric total electron content disturbances of Turkey earthquake doublet in 2023 detected by Beidou geostationary satellites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14108, https://doi.org/10.5194/egusphere-egu24-14108, 2024.

EGU24-14234 | Posters virtual | NH10.5

Simulation and Analysis of Disastrous earthquakes in the plains of SW Taiwan 

Strong Wen, Yulien Yeh, and Kuan-Ting Tu

There are many types of natural disasters in the world, among which earthquakes are sudden and highly uncertain, which may cause direct or indirect disasters, resulting in casualties, property losses, and infrastructure damage. Local seismic hazard analysis has been studied for a long time. This study uses historical earthquake data and virtual earthquake sources to simulate the propagation of seismic waves in urban areas in SW Taiwan. However, due to the limited number of existing free-field seismic stations and insufficient installation density, the accuracy of earthquake damage assessment is directly affected. Past research has pointed out that the use of scenario earthquake simulation can effectively simulate ground motions in local areas. Therefore, the goal of this study is to use numerical methods to construct a 3D seismic wave simulation, using numerical data and virtual seismic observation stations to simulate regional scales. However, due to limitations in computing resources and underground structure information, seismic waves calculated by 3D seismic wave propagation simulations can only cover relatively low-frequency (<1 Hz). However, for structural analysis in urban areas, in addition to inputting this relatively low-frequency signals, it is also necessary to utilize seismic waves covering high frequencies (>1 Hz) to calculate the vibration process and seismic resistance of the structure. Therefore, the goal of this study is to calculate low-frequency and high-frequency seismic waves separately, and to obtain broadband seismic waves containing low-frequency and high-frequency information through a hybrid method. The findings could be applied to future earthquake risk and building damage assessments.

How to cite: Wen, S., Yeh, Y., and Tu, K.-T.: Simulation and Analysis of Disastrous earthquakes in the plains of SW Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14234, https://doi.org/10.5194/egusphere-egu24-14234, 2024.

The magnetic storm that occurred in May 1921 ranks among the most extreme events ever observed by magnetic observatories. Some parts of this storm were also recorded in declination and vertical intensity by the variation station at the Stará Ďala observatory (present-day Hurbanovo in Slovakia). However, the magnetogram on photographic paper for this event not only contained data gaps, it also did not have a marked timeline, and the values of the divisions for the geomagnetic elements were not known. We identified timestamps using global variations observed by other observatories and estimated the values of the divisions based on data from before and after the studied event. Then, the magnetograms were digitized. To interpret the obtained data, we compared them with hourly averages from other observatories in different parts of the globe. Our results seem to confirm the expected assumption that, in the morning hours of 15 May 1921, the equatorward boundary of the auroral oval extended to the European mid-latitude observatories.

How to cite: Koči, E. and Valach, F.: The extreme geomagnetic storm on 13–15 May 1921: a study based on hourly means, including observations at Stará Ďala (Hurbanovo), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16216, https://doi.org/10.5194/egusphere-egu24-16216, 2024.

Typhoon is a key dynamic factor triggering landslides. In view of the fact that the previous susceptibility evaluation models rarely consider the interaction between typhoon and static factors, carry out research on the optimal dynamic and static factors combination of typhoon-induced landslides susceptibility. Using the interpretability of machine learning, the importance ranking of dynamic and static factors is carried out to identify key impact factors. On this basis, the importance of static factors under the influence of typhoon is compared, and the interaction between typhoon and static factors is analyzed. Finally, the optimal combination of dynamic and static factors is proposed by using k-fold cross-validation method and taking the average descent accuracy as the index. The results show that the importance of the key influencing factors of typhoon-induced landslide from high to low mainly includes: elevation, NDVI, road and other factors; the addition of typhoon and rainstorm factors significantly increased the importance of factors susceptible to typhoon, such as water system and vegetation, with an increase rate of 24.8-151.7 %. The optimal dynamic and static factors combination of typhoon rainstorm landslide includes all key static factors and four dynamic factors, among which the dynamic factors are: maximum sustained wind speed, rainfall, distance from typhoon center and near gale wind circle radius. The results of ROC curve verification show that the selection of the optimal factor combination can increase the accuracy of the evaluation model by 1.5%-3.5%, which can significantly improve the accuracy and rationality of the susceptibility mapping of typhoon-induced landslides.

Keywords: Impact factor, Typhoon, Landslides susceptibility, Interpretability of machine learning.

How to cite: Wang, F., Zhou, L., Liu, Y., and Chen, F.: Optimal factor combinations selection in typhoon-induced landslides susceptibility mapping using machine learning interpretability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16885, https://doi.org/10.5194/egusphere-egu24-16885, 2024.

EGU24-17238 | Posters on site | NH10.5

Anomalous Atmospheric Electric Field Just around the Time of Earthquakes: Case and statistical studies 

Yasuhide Hobara, Mako Watanabe, Mio Hongo, Hiroshi Kikuchi, Takuo Tsuda, and Masashi Hayakawa

In this paper, we report on the Atmospheric Electric Field (AEF) anomalies immediately before and after earthquakes (within 12 hours) in Japan. We demonstrate the results of a case study for several earthquakes that occurred close to our AEF observation network (within 100-200 km of the epicenter) under relatively fair local weather conditions. We found the common features for different earthquakes at different field sites e.g. 20~90 min period of clear anomalous signatures in wavelet spectrograms within a few hours around the main shock. Clear arrival time differences between AEF stations indicate propagating nature of observed AEF anomaly and enable us to calculate the propagation velocities and its occurrence timing. The observational results are compared with the dispersion relation of Internal Gravity Waves (IGW). Moreover, statistical results of the occurrence rate of the AEF anomalies support above mentioned results. Above-mentioned results may indicate the Lithosphere-Atmosphere Coupling, and we propose the physical mechanism of the observed electric field anomalies considering IGW originating from the epicenter region propagating over the field site and disturbing the local atmospheric electric field. 

How to cite: Hobara, Y., Watanabe, M., Hongo, M., Kikuchi, H., Tsuda, T., and Hayakawa, M.: Anomalous Atmospheric Electric Field Just around the Time of Earthquakes: Case and statistical studies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17238, https://doi.org/10.5194/egusphere-egu24-17238, 2024.

EGU24-556 | ECS | Posters on site | NH10.6 | Highlight

Forensic insights into Gloria's storm multi-hazard damages in Catalonia 

Nuria Pantaleoni Reluy, Marcel Hürlimann, and Nieves Lantada Zarzosa

Conducting a forensic analysis of catastrophic multi-hazard episodes is a challenging yet essential undertaking to enhance our understanding and preparedness for future events. In this study, the multiple direct damage costs for repairing and replacing the effects of the Gloria storm, which struck Catalonia from January 20 to 23, 2020, are thoroughly examined. The storm, characterized by persistent and intense rainfall coupled with strong winds, resulted in a significant sea-level rise heightened by large waves, numerous slope failures and widespread pluvial and fluvial floods, leading to substantial direct economic losses. While databases of damage and losses provide valuable insights into documenting disaster effects, we propose an integrative approach that combines post-event data compilation with forensic analysis to understand the hazard conditions. The resulting database in our study includes parameters such as geographical location, triggering hazard, exposed element at risk, and cost, providing a comprehensive understanding of the Gloria storm's impact. By interpreting the collected data, we derive with key insights of the economic impacts and severity of the hazards caused by the storm in Catalonia. The compilation of data from 14 different sources revealed extensive repair and replacement costs of approximately 390 million Euros for the damages caused by the Gloria storm. Fluvial and coastal processes were the primary contributors to direct economic losses in Catalonia, with fluvial hazards accounting for 44% and coastal processes for 41%. Slope failures and meteorological hazards accounted for 9% and 5%, respectively, in the overall damages. By complementing this with forensic analysis, the integrated approach allows us to discern how and why these events occurred, whether they were amplified or diminished by management strategies, and what strategies could be applied. Additionally, the study incorporates the development of an impact chain, illustrating potential sequences of events and relationships based on the Gloria Storm case. This analytical diagram serves to better comprehend the interrelationships and cascading effects of different hazards, as well as the environmental and socio-economic factors contributing to the damages. The integrated approach contributes to more effective risk management strategies and enhances the broader field of disaster analysis.

How to cite: Pantaleoni Reluy, N., Hürlimann, M., and Lantada Zarzosa, N.: Forensic insights into Gloria's storm multi-hazard damages in Catalonia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-556, https://doi.org/10.5194/egusphere-egu24-556, 2024.

EGU24-567 | ECS | Orals | NH10.6

Coupling hydrological and geotechnical models for enhanced flood–landslide cascading disaster modelling 

Flavio Alexander Asurza Véliz, Marcel Hürlimann, and Vicente Medina

Flash floods, fluvial floods and shallow landslides triggered by intense rainfall present substantial threats to both human lives and infrastructure. Furthermore, floods and landslides often manifest in a cascading sequence, where an initially lower-consequence event like heavy rainfall can lead to more severe floods and/or landslides, intensifying the impact to affected communities. Losses resulting from these combined hazards may be significantly greater than the sum of losses from individual hazards. Therefore, there is a crucial need to integrate hydrological and geotechnical modelling into an integrated flood–landslide cascading preparedness and hazard management. This research introduces a coupled flood and landslide initiation modelling system, integrating a temperature index-based snowmelt model (SNOW-17), the Coupled Routing and Excess STorage (CREST) model, and the Fast-Shallow Landslide Assessment Model (FSLAM). The proposed approach is evaluated in the Val d’Aran region that experienced multiple landslides and important flooding due to a combination of heavy rainfall and snowmelt in June 2013. The coupled-model involves three main steps: i) The SNOW-17 model is applied to quantify the snow melting process which is further included in ii) the hydrological model CREST in order to estimate soil water content conditions, discharge and flood extent. Later, iii) the FSLAM model generates landslide susceptibility maps based on the hydrological model outputs, and finally iv) a random walk runout model will determine the landslides trajectories and the amount of sediment that may reach the river network. Preliminary results, related to snow, hydrological and landslide model calibration, have shown good statistical performance when comparing modelled daily soil water equivalent and daily hydrographs with observations from 2012-2020. Landslide predictions also showed a good accuracy (72%). Further steps will try to include the cascading effect of sediments being delivered to drainage network during landslides episodes. This study highlights the importance of the physical connection among snow melting, hydrological processes and slope stability, and aims to provide a prototype model system for operational forecasting of floods and landslides.

How to cite: Asurza Véliz, F. A., Hürlimann, M., and Medina, V.: Coupling hydrological and geotechnical models for enhanced flood–landslide cascading disaster modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-567, https://doi.org/10.5194/egusphere-egu24-567, 2024.

Compounding and cascading effects of rainfall-induced floods and landslides pose significant challenges and existing research has predominantly focused on individual hazards and the multi-hazard aspect has been understudied. To bridge the gap, the current study develops a multi-hazard approach by building upon validated flood and landslide hazard assessment methods.

The first steps in our approach involve determining the flood hazard in the river network and landslide warnings. With the landslide warnings denoting the initiation areas of the landslides, the warnings are combined with a morphological index to determine the potential sediment amount generated in subbasins and their connectivity to the drainage network. Finally, the multi-hazard aspect in the river network is obtained by integrating sediment transport and flood hazards. The results indicate the regions that have amplified hazards due to the combined effect of floods and sediment transport.

An initial version of the proposed framework was tested in the Tordera River basin, with a focus on the Gloria storm that occurred in January 2020. This storm caused widespread floods and landslides across Catalonia (NE Spain), resulting in substantial damage. Choosing this area allowed us to see how well the framework works in understanding multi-hazard aspects. The results highlight the areas with the highest occurrence of landslides and also the regions in the drainage network where significant changes occurred due to floods and sediment transport. The identified areas match with regions where noticeable alterations were observed during the Gloria storm. The preliminary results showcase the capability of the framework to effectively capture the amplified hazard, providing valuable insights into the compounding and cascading effects of rainfall-induced floods and landslides.

How to cite: Yeditha, P. K., Hürlimann, M., and Berenguer, M.: A multi-hazard framework integrating flood and landslide early warning systems: Application to the Tordera river basin (Catalonia, Spain), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-943, https://doi.org/10.5194/egusphere-egu24-943, 2024.

EGU24-2689 | ECS | Orals | NH10.6

A framework for investigating multi-hazard interactions to develop a decision-support system for disaster risk management  

Mohammed Sarfaraz Gani Adnan, Christopher White, Eleonora Perugini, John Douglas, Enrico Tubaldi, Talfan Barnie, Esther Jensen, Matthew Roberts, Natalia Castillo, Marco Gaetani, Marcello Arosio, Frederiek Weiland, and Mario Martinelli

Multi-hazard events pose significant threats to human lives and assets, often exceeding the risks associated with single hazards due to simultaneous, cascading, or cumulative occurrences of multiple interacting natural hazards. The society and environment in various European regions, susceptible to many climatic extremes, are anticipated to be profoundly impacted in the coming decades due to the increasing frequency and severity of multi-hazard events linked to changing climatic conditions. While most natural hazard studies have predominantly focused on single hazards or multi-layer single hazards, the quantitative assessment of multi-hazard interactions remains in its early stage of development. Investigating diverse types of multi-hazard events is particularly challenging due to complex interactions between hazard drivers and the spatial and temporal heterogeneity of multiple hazard occurrences. This study aims to introduce an approach for investigating four distinct types of multi-hazard interactions: preconditioned and triggering, multivariate, temporally compounding, and spatially compounding events, under present-day and future climate change scenarios. The research is conducted as part of a Horizon Europe project MEDiate (Multi-hazard and risk informed system for Enhanced local and regional Disaster risk management), which seeks to "develop a decision-support system (DSS) for disaster risk management by considering multiple interacting natural hazards and cascading impacts." The framework is implemented on four interactive multi-hazard pairs—compounding coastal and riverine flooding, extreme heat and drought, extreme wind and precipitation, and extreme precipitation and landslides—in four European testbeds: Oslo (Norway), Nice (France), Essex (UK), and Múlaþing (Iceland), respectively. The proposed multi-hazard interaction framework aims to estimate the probability of occurrence of multiple hazards over various time and space scales, associated with the four types of multi-hazard events. The framework involves two key steps. First, it identifies extreme events for individual hazard indicators (e.g., peak river flow, surge, near-surface wind speed, precipitation, air temperature) at different time intervals (e.g., daily, monthly, quarterly) and locations within the testbed regions. Second, a nonparametric bivariate copula-based approach is employed to estimate joint return periods for various combinations of hazard indicators associated with different types of multi-hazard events. The analysis is conducted for both present-day conditions and the 2050 RCP 8.5 climate change scenario, by using several freely available regional and global observation and modelled datasets related to different indicators of multi-hazard events. The findings of this study illustrate the degree of statistical dependence between various combinations of interactive hazards in space and time, quantifying joint probabilities of multi-hazard events. Furthermore, it demonstrates how these probabilities are likely to change in the future due to the impacts of climate change. This research emphasises the importance of considering diverse scenarios of multi-hazard events in formulating future climate change adaptation responses. The findings of this study will inform the DSS being created in the MEDiate project by developing accurate multi-hazard scenarios to estimate the potential effects of different disaster risk mitigation and adaptation strategies. The results could also contribute valuable insights for developing multi-hazard risk management policies elsewhere globally, where susceptibility to multi-hazard events is increasing.

How to cite: Adnan, M. S. G., White, C., Perugini, E., Douglas, J., Tubaldi, E., Barnie, T., Jensen, E., Roberts, M., Castillo, N., Gaetani, M., Arosio, M., Weiland, F., and Martinelli, M.: A framework for investigating multi-hazard interactions to develop a decision-support system for disaster risk management , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2689, https://doi.org/10.5194/egusphere-egu24-2689, 2024.

Digital Twins (DT) are dynamic digital representations of physical entities ranging from individual systems to entire cities. They leverage real-time data to create accurate models and simulations, offering significant potential for post-disaster risk management (PRM) applications. However, the integration of DT into PRM is still in its infancy, with its full capabilities yet to be realized.

This study introduces the Digital Post-Disaster Risk Management Twinning (DPRMT) paradigm, which aims to harness AI and ML within DT frameworks to reinforce the resilience of urban areas and communities in the face of disasters. A critical review of 335 research papers on DPRMT from reputable databases indicates that existing literature often fails to fully appreciate the dynamic and interconnected nature of disasters, typically relying on static historical data and neglecting important financial, social, and demographic factors in affected communities.

We propose a tansformative DPRMT framework that encompasses six interconnected components. “Entities at Risk” identifies a variety of elements vulnerable during disasters, including human lives, buildings, critical infrastrucres, and social networks. “Data collection and preparation” employ various methods such as remote sensing, crowdsourcing, and social sensing to gather and prepare dynamic data for analysis. Data Processing leverages artificial intelligence and machine learning to validate, fuse, and analyze collected data, enhancing its accuracy and reliability. Digital Modeling encompasses diverse techniques like AI-based modeling, socio-economic modeling, and physical modeling to create computer-based representations of entities at risk, enabling in-depth analysis and prediction. Information Decoding involves comprehensive data and model analysis, integration, and visualization, delivering timely and actionable information to enhance decision-making and transparency. User Interaction and Application ensure effective communication between digital twin models and end-users through various technologies, facilitating real-time information delivery and stakeholder engagement in disaster response and recovery. This framework is designed to fill current gaps in traditional disaster recovery methods by integrating real-time, detailed, and data-driven modeling solutions, fostering improved decision-making in areas such as policy development, resilience assessment, casualty and hazard prediction, resource distribution, evacuation planning, scenario testing, and community involvement.  

Despite the promise of ML in improving DT capabilities for PRM such as data validation, information extraction, predictive maintenance and anomaly detection, the results show that challenges remain, including the need for high-quality and diverse data, privacy concerns, and cost-effectiveness, particularly in less developed countries. The use of remote sensing technologies, such as satellites and drones, is presented as a viable solution to overcome these challenges. These technologies supply high-quality, detailed data on buildings, infrastructure, land cover changes, and post-disaster scenarios while addressing privacy and security concerns. Nonetheless, issues with model generalization persist, necessitating training on varied disaster contexts, managing large datasets, capturing the dynamic nature of disasters, and maintaining transparency in decision-making for practical real-time application. The limitations of current ML methods, especially their time-consuming nature and the need for frequent re-training in evolving disaster scenarios, may impede their seamless integration with DT frameworks. This highlights the need to develop more efficient and rapid ML and Deep Learning models specifically designed for the unique requirements of post-disaster recovery management.

How to cite: Lagap, U. and Ghaffarian, S.: Transforming Post-Disaster Risk Management: A Comprehensive Framework for Digital Twinning with AI and Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4202, https://doi.org/10.5194/egusphere-egu24-4202, 2024.

EGU24-6680 | Posters on site | NH10.6

Exploring the World of Multi-Hazard Susceptibility Mapping With Deep Learning 

Timothy Tiggeloven, Davide Ferrario, Wiebke Jäger, Judith Claassen, Yuliya Shapovalova, Maki Koyama, Marleen de Ruiter, James Daniell, Silvia Torresan, and Philip Ward

A crucial component of disaster preparedness is the development of a multi-hazard susceptibility map, which plays a vital role in comprehensive risk assessment, resource allocation, land use planning, emergency management, community preparedness, and decision-making. Recently deep learning methods have been showing potential to map susceptibility at a finer resolution. While prior research has predominantly focused on advanced single-hazard or simplified multi-hazard susceptibility mapping, an approach to explore multi-hazard susceptibility mapping using deep learning methods and explainable AI’s remains lacking to date. Addressing this gap, our research employs an ensemble Convolutional Neural Networks, to develop a multi-hazard susceptibility map. Leveraging diverse datasets and the MYRIAD-HESA framework, our analysis considers a range of hazards and their interactions, offering a more integrated view of the complex risk landscape faced by communities. Using Japan as a case study, the resulting susceptibility map serves as a valuable tool for informing land use and urban planning, resilient infrastructure development, and identification of suitable locations for critical facilities. Furthermore, it supports emergency management by facilitating resource prioritization, coordination, evacuation planning, and community awareness. This research contributes to evidence-based decision-making, policy development, and global disaster preparedness efforts.

How to cite: Tiggeloven, T., Ferrario, D., Jäger, W., Claassen, J., Shapovalova, Y., Koyama, M., de Ruiter, M., Daniell, J., Torresan, S., and Ward, P.: Exploring the World of Multi-Hazard Susceptibility Mapping With Deep Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6680, https://doi.org/10.5194/egusphere-egu24-6680, 2024.

EGU24-9223 | Posters on site | NH10.6

Role of Earth Observation in multi-(hazard-)risk assessment and management  

Philip Ward, Nicole van Maanen, and Marleen de Ruiter and the EO4MULTIHAZARDS team

Natural hazard impacts are becoming increasingly complex, as demonstrated by real world examples of multi-hazards events. This requires major improvements of our current multi-hazard scientific modelling capabilities. High-quality earth observation (EO) data have the potential to contribute to improving our understanding of multi-hazard events and multi-risk impacts. However, to date there have been limited attempts to include EO data into the workflow of multi-hazard analysis, modelling, forecasting and added-value generation. In this contribution, we review recent developments in using EO data in multi-hazard and multi-risk assessment. We examine how EO data can support our practical understanding of multi-(hazard-)risk, and how this can be made accessible, useful and practical. We provide recommendations for improving EO information (tools, methodologies, accessibility, etc.) and an outlook on the potential evolution of using EO in disaster risk management.

How to cite: Ward, P., van Maanen, N., and de Ruiter, M. and the EO4MULTIHAZARDS team: Role of Earth Observation in multi-(hazard-)risk assessment and management , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9223, https://doi.org/10.5194/egusphere-egu24-9223, 2024.

Intensive and extensive risks are growing at an unprecedented rate as reported by the Global Assessment Report on Disaster Risk Reduction. While disasters are claiming fewer lives annually, they are also costing more and increasing poverty and economic losses. Understanding and managing risk and resilience helps governments, institutions, businesses, and communities make better decisions in a world of uncertainty. Building on the existing risk and resilience management processes (e.g., national risk assessments, international risk management standards, literature on risk and resilience assessment), this study proposes a novel operational risk and resilience management process for emergency planning and civil contingency. The proposed framework is an iterative process consisting of interrelated phases:

  • Scope, context and criteria
  • Risk and Resilience Identification, analysis and evaluation
  • Risk mitigation and resilience strengthening
  • Monitoring and review
  • Communication and consultation
  • Recording and reporting
  • Initial and detailed assessment

The proposed operational framework will provide guidance for disaster management authorities to better understand and manage complex impact and systemic risk from a multi-hazard and disaster risk perspective.

How to cite: Meslem, A. and Huang, C.: A Novel Operational Risk and Resilience Management Process for Emergency Planning and Civil Contingency, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9686, https://doi.org/10.5194/egusphere-egu24-9686, 2024.

EGU24-9940 | ECS | Posters on site | NH10.6 | Highlight

Multi-hazard Impact Assessment for Volcanic and Storm Hazards: the Saint Vincent Case Study 

Salsabila Prasetya, Irene Manzella, and Cees van Westen

Small Island-Developing States (SDIS) are susceptible to a broad range of risks coupled with a constrained capacity to manage them effectively. The Caribbean is one of three geographical regions in which SDIS are located, with a high vulnerability to multi-hazard events, such as tropical storms and volcanic eruptions. According to the European Commission, the Caribbean is the second most disaster-prone region in the world with extreme climatic events. Based on the EM-DAT database, tropical storms are the most frequent disastrous event in the Caribbean. A tropical storm triggers a combination of coupled hazardous phenomena such as strong winds and heavy rainfall which often leads to floods and landslides. The Caribbean also lies on several active tectonic plates which makes it home to several active volcanoes. There are 21 volcanoes across 11 volcanically active islands.

A low-probability high-impact combination of compounding storm and volcanic event happened in 2021 in Saint Vincent where an eruption of the La Soufriere volcano was followed by a storm which triggered several lahars and other cascading effects. Based on historical event records, volcanic eruptions occur on average every 77 to 94 years in Saint Vincent alternating between effusive and explosive eruptions. Meanwhile, tropical depressions affect the island on average once every 3 years for direct hit or brush and 18 years for major hurricane hit. This study will assess the impact of compounding storms and volcanic events in the Caribbean with a case study from Saint Vincent.  

A comprehensive multi-hazard risk assessment which considers multiple spatial and temporal scales plays a role in disaster risk reduction and response planning. The present work uses a multi-hazard and multi-phase modular framework based on literature review of historical events in Saint Vincent. Several scenarios are developed that show a variety of hazard types and intensities as well as the impacts. Impact chain models are used to present these scenarios. Impact chains are conceptual models based on cause-effect chains that include all major factors and processes leading to specific risks in a specific context. Compounding scenarios developed resulted in impacts much more severe as compared to the individual events. This study highlights the importance of studying compounding risks and the effectiveness of impact chains assessment for better disaster risk reduction planning and mitigation.

 

Keywords: multi-hazard, impact assessment, impact chain, volcanic eruption, storm, hurricane, Caribbean. 

How to cite: Prasetya, S., Manzella, I., and van Westen, C.: Multi-hazard Impact Assessment for Volcanic and Storm Hazards: the Saint Vincent Case Study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9940, https://doi.org/10.5194/egusphere-egu24-9940, 2024.

EGU24-11170 | ECS | Orals | NH10.6

Geomorphic Hazards and the Imperative of Multi-Hazard Assessment for Road Infrastructure in Mountain Areas 

Till Wenzel, Philipp Marr, and Thomas Glade

Road infrastructure in mountain areas is essential for connecting local communities and for cross-regional mobility, such as fright transit and vacation traffic. The lack of redundancy and the high frequency of traffic indicate the critical importance of these roads. However, compounding and cascading geomorphic processes can have effects leading to the blockage or destruction of infrastructure. These geomorphic processes are amplified by anthropogenic activities such as slope undercutting, deforestation, and indirectly by ongoing climate change. It is therefore important to model the processes associated with these hazards that can cascade to cross-regional impacts. Here, we explore the possibility of using publicly available data, including topographic information and historical hazard data, as well as practitioner input, to produce appropriate assessments that delineate areas prone to geomorphic hazards along the Brenner Corridor connecting southern and northern Europe which is the most important infrastructure connection between northern and southern Europe.

To analyse the impact of geomorphic cascades, a comprehensive literature review of past hazardous events in the study area, and susceptibility maps will be prepared. Multi-hazard risk approaches to critical road infrastructure will be reviewed and, where applicable, evaluated for dynamic geomorphic hazard modelling. A conceptual framework combining both practitioner’s knowledge and data analysis with susceptibility assessments will be developed into impact chain models to combine qualitative expert input and quantitative data.

Preliminary results show that certain hazards that were not anticipated a few years ago may be changing in their processes, e.g. from avalanche hazard to landslide hazard, due to changing temporal precipitation patterns. One such example is a debris flow that blocked parts of the Brenner highway near the border between Italy and Austria, at the bottleneck of the corridor with highway, country road, and railroad, in a valley section only 70 m wide. The question remains whether such events are more likely to occur in the future in areas that have not yet been studied for these hazards. Further work will include whether, for example, land-use or climate-related changes can be incorporated into scenario impact modelling.

How to cite: Wenzel, T., Marr, P., and Glade, T.: Geomorphic Hazards and the Imperative of Multi-Hazard Assessment for Road Infrastructure in Mountain Areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11170, https://doi.org/10.5194/egusphere-egu24-11170, 2024.

EGU24-12033 | ECS | Posters on site | NH10.6

Learning from the past to prepare for the worst. Impact Chain on the multi-hazard of COVID-19 pandemic and a powerful earthquake in Bucharest 

Cristina Savu, Andra-Cosmina Albulescu, Iuliana Armaș, and Dragos Toma-Dănăilă

In the last years, the impacts of natural hazards have been coupled with and sometimes overshadowed by those of the COVID-19 pandemic. Such co-occurrences added extra layers to risk management and highlighted the need for updated multi-hazard risk models and management plans. While developing the tools, models, and strategies to battle the challenges of the post-pandemic world, an unsettling question lingers: What if the most impactful and feared hazard in a specific area were to occur during a pandemic wave?

This study aims to 1) take an in-depth look at the impact of the COVID-19 pandemic on the hospital system in Bucharest, Romania, and 2) identify the compounded impacts of a powerful earthquake that would potentially affect the city during a pandemic wave, under an Impact Chain-based approach. To this end, two Impact Chains are analysed side by side: one of them presents the actual impacts of the pandemic documented for 2020-2022, and the other focuses on the potential impacts of a powerful earthquake, similar to the one that affected Romania in March 1977 (7.4 MW). The co-occurrence of such powerful hazardous events poses a worst-case scenario for Bucharest, which stands out as the European capital with the highest seismic risk and one of the urban centres severely affected by the COVID-19 pandemic.

 

The Impact Chain centred on the COVID-19 pandemic dwells on a wide range of sources: scientific literature, data collected from hospital administration (e.g., reports on available medical resources, including human resources), official reports from international health care organisms, legislative documents that regulate COVID-19 prevention protocols, official press releases, and grey literature in the form of news reports. The earthquake-based Impact Chain represents a simplified, expert knowledge-based version of a larger chain developed within the Paratus Project as part of the analysis of present and future outcomes of a major earthquake in Bucharest.

 

By juxtaposing the two Impact Chains, this study addresses the research gap concerning the compounded impacts of earthquakes and the COVID-19 pandemic, an area currently open for further investigation. This analysis offers an initial answer to the worrisome question posed earlier, aiding in the preparation for “the worst” in Bucharest.

Keywords: COVID-19 pandemic, earthquake, impact chain, hospital system, Romania

How to cite: Savu, C., Albulescu, A.-C., Armaș, I., and Toma-Dănăilă, D.: Learning from the past to prepare for the worst. Impact Chain on the multi-hazard of COVID-19 pandemic and a powerful earthquake in Bucharest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12033, https://doi.org/10.5194/egusphere-egu24-12033, 2024.

EGU24-13832 | Posters on site | NH10.6

A review of opportunities and challenges for AI driven multi-hazard risk assessment and resilience enhancement in climate services 

Marcello Sano, Davide Ferrario, Margherita Maraschini, Silvia Torresan, and Andrea Critto

As climate change accelerates and environmental uncertainties mount, traditional models fall short in effectively handling the complexity and fluidity of multi-hazard risk and corresponding resilience measures. Notably, the vast amount of data being collected and the rapid advancements in artificial intelligence offer extraordinary potential. These advancements can equip us to tackle complex climate risks and develop innovative services that empower both government and communities to adapt and thrive.

This review aims to bolster research on the transformative potential of Artificial Intelligence (AI), propelled by Machine Learning (ML) and Big Data (BD), to address the escalating challenges posed by climate change across several key areas. On the one hand, it examines AI's capability to process and integrate diverse data sources, such as satellite imagery, monitoring stations, climate models, social data, with varying spatial and temporal resolutions, including the potential of AI tools in identifying and quantifying cascading and interconnected hazard events and potential resilience measures. On the other hand, the review delves into the development of AI-powered climate services designed to manage climate risk and enhance resilience across various sectors. It evaluates the integration of AI techniques in climate services for dynamic, user-centric platforms that offer actionable insights and decision support. The current and future data constraints and emerging opportunities in implementing these services are explored, alongside strategies to overcome these challenges. Additionally, the review considers the scalability and adoption of AI-powered climate services in the future, highlighting the role of AI in revolutionizing the landscape of climate risk assessment and resilience planning.

In summary, this comprehensive literature review synthesizes insights from multi-hazard risk assessment and resilience building. It aims to bridge the gap between static risk models and the dynamic reality of climate threats, paving the way for a comprehensive AI-driven framework helping building climate resilience.

This research is funded under the European projects MYRIAD-EU (Horizon 2020) and EXPEDITE (Horizon 2021 MSCA).

How to cite: Sano, M., Ferrario, D., Maraschini, M., Torresan, S., and Critto, A.: A review of opportunities and challenges for AI driven multi-hazard risk assessment and resilience enhancement in climate services, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13832, https://doi.org/10.5194/egusphere-egu24-13832, 2024.

Vulnerability is the most important predictive variable in the risk equation, but it isn't easy to evaluate the best objective approach to quantify it. Another hot topic of debate among scientists is whether vulnerability analysis describes only patterns or can also produce a quantitative value. The need to streamline and provide comparable and easy-to-use results has led to developing vulnerability indicators. Generally, these provide some form of aggregation of underlying factors, often including hazard exposure. Factor selection varies from deductive approaches, based on theoretical understanding, to inductive ones, based on statistical relationships.

For the past thirty years, there have been significant efforts to measure vulnerability, but up to now, the field of vulnerability assessments has been dominated by hierarchical versus inductive approaches.

The hierarchical analysis is a transparent approach, more accessible to stakeholders due to its logical structure and statistical support, and capable of functioning with more available datasets for assessing vulnerabilities in the studied areas. These are the most eloquent reasons for preferring the hierarchical approach in stakeholder territorial management and mitigation policies.

The inductive, statistical approach developed by Cutter (based on the hazards-of-place model, Cutter, 1996) uses the principal component analysis (PCA) to establish vulnerability factors over time and eliminates the biases from aggregated decisions.

Against this background, our study proposes a new model for quantifying vulnerability using an Impact Chain-based approach, taking as an initial case study the powerful flood events and the COVID-19 pandemic that affected Romania in 2020-2021. The hazards, impacts, vulnerability, exposed elements, and adaptation options pertaining to the case study are integrated into a comprehensive Impact Chain that is used as the foundation for the model.

The proposed model relies on factorial techniques and ANOVA, with a focus on identifying statistically significant multiple regressions. It also integrates an optimization procedure that enables either a maximum value response or a minimum accepted value.

This new framework allows for identifying vulnerability's influencing role in unfolding a multi-hazard and pinpointing the potential ways in which vulnerability can be affected by this unfolding. Thus, the model looks at vulnerability with a double lens, assessing its power to induce change by conditioning impacts and adaptation options and its propensity to change by certain impacts and adaptation options working in asynergy. Only by thoroughly analyzing both of these facets and understanding their implications can we produce bias-(more) free vulnerability assessments, particularly in multi-hazard contexts.

 

Keywords: vulnerability, vulnerability approaches, hierarchical approach, inductive approach, Impact Chain

How to cite: Armas, I., Albulescu, A.-C., and Dobre, D.: Impact Chain-based model to assess multi-hazard systemic vulnerability. Case study: Flood and the COVID-19 pandemic in Romania, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15048, https://doi.org/10.5194/egusphere-egu24-15048, 2024.

EGU24-15139 | Posters on site | NH10.6 | Highlight

A web-based multi-hazard risk simulation service based on impact chains 

Cees Van Westen, Bastian van den Bout, Rabina Twayana, Massimiliano Pittore, Ashok Dahal, Manzul Hazarika, and Yu Han

There is a need for the development of databases for representing the complex hazard interactions and cascading impacts of multi-hazard extreme events, such as sequences of earthquake or storm-related events. The concept of impact chains has proven to be a useful concept for conceptually representing the risk related to such complex events, but applications have been mostly used for visualization purposes only.  In the context of the EU PARATUS project, a web-based simulation service is being developed for first and second responders and other stakeholders to evaluate the impact and risk related to multi-hazard events building upon a representation of scenario risk through impact chains. The simulation service includes a series of tools to gather, integrate, and develop new hazard and risk information. The central tool is the impact chain builder, where users can develop their own impact chain of past events, or future disaster events, and is used as a basis for quantifying direct damage and prioritizing secondary losses in different sectors. Several tools for hazard assessment will provide fast estimations of multiple hazards and can be linked to the impact chains. One of these is the FastFlood tool which allows to generate flood extent and depth maps for any area, within seconds, based on global datasets, or more detailed user-supplied data. The tool can also be used to evaluate the effect of risk reduction measures. Also, hazard tools for other processes are developed such as for mass movements, with initiation and runout components and linked to flood events. The hazard data is combined with elements-at-risk data, for exposure analysis in the RiskChanges tool. This tool allows to quantify losses, using a database of vulnerability functions. Multi-hazard losses are calculated using specific combination rules for different hazard interactions. The tool can also be used for evaluating optimal risk reduction alternatives, where the risk components are re-analyzed and the risk reduction is compared with investment in a cost-benefit analysis. Changes in risk for future scenarios, related to climate change, land use change, and population change, for certain future years, can also be analyzed using the tool. Other tools are still under development, such as a tool for collaborative planning. The exact number of components and the final structure of the platform will be determined iteratively through a series of stakeholder consultations, following a user-centered design. The platform is designed flexibly to be able to support stakeholders that work in different sectors, geographic settings, and interacting hazards, and at the same time to address (a number of) their needs for analyzing the impact of compounding multi-hazard events with cascading impacts.  

How to cite: Van Westen, C., van den Bout, B., Twayana, R., Pittore, M., Dahal, A., Hazarika, M., and Han, Y.: A web-based multi-hazard risk simulation service based on impact chains, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15139, https://doi.org/10.5194/egusphere-egu24-15139, 2024.

EGU24-15767 | ECS | Posters on site | NH10.6

Automatic identification of ensembles of critical futures in large datasets 

Amal Sarfraz, Charles Rougé, Lyudmila Mihaylova, Jonathan Lamontagne, Abigail Birnbaum, and Flannery Dolan

In climate risk modelling, the growing trend of simulating large ensembles is driven by the need to understand a wide range of possible future scenarios. This approach generates vast datasets, which presents a challenge: identifying the most critical scenarios that could have significant impacts. While mainstream data patterns offer general insights, outliers provide unique perspectives, specifying areas for further investigation. However, focusing on single outliers is not optimal. Instead, analysing groups of outliers enables a more comprehensive exploration for the identification of patterns in multiple plausible future outcomes.

In this context, we introduce the term ensemble of outliers to describe groups of data points deviating significantly from the mean of the dataset. An ensemble of outliers can help uncover underlying patterns and highlight areas for deeper exploration. These ensembles of outliers, once identified can possess distinct properties and indicate phenomena that are not represented in the rest of the dataset.

Our research proposes a new method to address the challenge of identifying these ensembles of outliers within large datasets. Our methodology, Mahalanobis distance-based Ensemble of Outlier Detection (MEOD) includes Gaussian Mixture Models for probabilistic clustering coupled with Enhanced Mahalanobis distance-based statistical analysis to identify an ensemble of outliers in complex large datasets. MEOD's efficiency is validated through extensive testing on thousands of synthetic datasets, encompassing diverse configurations of both the dataset and an ensemble of outlier characteristics. The results indicate a high degree of accuracy for MEOD, with an average purity of 99.65% and an average F1 score of 0.92.

To demonstrate the utility of MEOD to climate risk assessment, we implement our method on a large dataset of future agricultural production scenarios for the Indus River Basin (IRB). This large dataset was generated using an Integrated Assessment Model, Global Change Analysis Model and encompasses 3,000 scenarios outlining potential socioeconomic, water supply-demand, and land use changes up to the century's end. Our goal is to use MEOD to identify and analyse a critical ensemble of outliers that significantly drives water scarcity in IRB's agricultural sector. We successfully identified 150 scenarios as an ensemble of outliers, characterised by their unique socioeconomic attributes and agricultural practices.

These scenarios predominantly fall into two categories: 1) those involving increased competition for resources due to regional disparities and 2) those incorporating a mix of sustainable and conventional agricultural practices. This dichotomy highlights both overuse and intensive water resource utilisation scenarios, signalling significant agricultural withdrawals and high scarcity risks.

Our findings demonstrate the MEOD's efficiency as a robust, versatile tool for analysing complex, large-scale datasets, providing nuanced insights into intricate data patterns.

How to cite: Sarfraz, A., Rougé, C., Mihaylova, L., Lamontagne, J., Birnbaum, A., and Dolan, F.: Automatic identification of ensembles of critical futures in large datasets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15767, https://doi.org/10.5194/egusphere-egu24-15767, 2024.

EGU24-16163 | ECS | Posters on site | NH10.6 | Highlight

Building an agent-based model to assess multi-risk caused by climate change in coastal areas: the case study of the Jesolo municipality (Italy) 

Maria Katherina Dal Barco, Sebastiano Vascon, Silvia Torresan, and Andrea Critto

Over the past three decades, the global climate has experienced a significant and unprecedented increase of temperature, leading to the occurrence of many extreme events worldwide. Coastal areas are particularly vulnerable to the impacts of climate change, due to the high population density, interconnected economic activities and the presence of fragile habitats and ecosystems. The interactions between multiple hazards, acting at different temporal and spatial scales, can amplify the effects on dynamic vulnerability and exposure patterns.

In order to address these complex challenges, an integrated approach becomes crucial, considering the relationships among all risk factors (hazard, exposure, and vulnerability) at the land-sea interface.

Agent-based model (ABM) approaches are able to simulate the interactions between different individuals, households or communities, playing a vital role in the analysis of their responses to environmental hazards (e.g., sea-level rise, heavy precipitation, extreme wind) and adaptation strategies (e.g., beach nourishment, nature-based solutions).

Here we present the development of a local-scale ABM to assess coastal risks caused by climate change on various sectors, such as local communities, tourism, and ecosystems. In particular, the model aims at exploring the interactions among atmospheric and marine hazards (e.g., sea-level rise, extreme precipitation, and wind), exposure and vulnerability factors (e.g., land-use, population) to simulate coastal risks for the municipality of Jesolo (Italy). The ABM will be trained with local-scale records over the 2009-2020 baseline timeframe, and then used to project future climate risk until 2100, under the climate change scenarios (e.g., RCP2.6, 4.5, and 8.5), as well as the potential effect induced by different coastal protection measures and nature-based adaptation strategies (e.g., beach nourishment, groins).

The resulting outcomes could represent a valuable tool to inform stakeholders and decision-makers on climate change adaptation, in line with EU, national and local adaptation strategies. Furthermore, they can be used to improve disaster risk preparedness as well as raise awareness in local communities.

How to cite: Dal Barco, M. K., Vascon, S., Torresan, S., and Critto, A.: Building an agent-based model to assess multi-risk caused by climate change in coastal areas: the case study of the Jesolo municipality (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16163, https://doi.org/10.5194/egusphere-egu24-16163, 2024.

EGU24-16585 | ECS | Orals | NH10.6

Artificial Intelligence for climate change multi-risk assessment: a Myriad-EU case study in the Veneto Region 

Davide Mauro Ferrario, Marcello Sano, Timothy Tiggeloven, Judith Claasen, Elena Petrovska, Margherita Maraschini, Marleen de Ruiter, Silvia Torresan, and Andrea Critto

The escalating frequency and intensity of extreme climate events underscore the need for robust multi-risk assessment methodologies. Conventional approaches often struggle unravelling the intricate interplays among diverse hazards and their impacts on vulnerability and exposure factors. Understanding the complex impact chains and the consequences of extreme climate events on socio-economic and natural systems is crucial for formulating effective risk reduction and preparedness strategies. Artificial Intelligence (AI) has emerged as a powerful tool for analysing intricate environmental data, fusing information from different heterogeneous sources, and modeling non-linear relationships.

A stepwise AI-based framework has been developed to assess the risk induced by extreme climate events—specifically, heatwaves, droughts, storm surges, extreme precipitation, and extreme wind events—in the Veneto Region (North-East Italy). The first step consists in the identification of single hazard spatial and temporal footprints from climate data, using statistical methods (quantiles and percentiles) for identifying anomalies and extreme events and unsupervised machine learning (DBSCAN) for clustering. The second step aims at building multi-hazard event sets, by combining the dynamic single hazard clusters extracted in the first step with static footprints of other hazards, such as wildfires and landslides. In particular, different time lags and spatial overlaps are applied to identify compound or consecutive events. Finally, the third step employs supervised ML algorithms, such as Random Forest, Support Vector Machine (SVM), and Convolutional Neural Networks (CNN), to model multi-hazard susceptibility over different multi-hazard combinations. Footprints of past single and multi-hazard events are used as assessment endpoints to train the ML model and identify the most important vulnerability and exposure factors and multi-risk hotspots within the Veneto region.

This comprehensive approach integrates advanced data driven and AI techniques to enhance the understanding of the complex dynamics associated with multi-risk events. This framework has been applied and tested within the Myriad-EU project, in the Veneto Region case study, demonstrating its efficacy in assessing and predicting the impacts of multi-risk events under different climate change scenarios.

How to cite: Ferrario, D. M., Sano, M., Tiggeloven, T., Claasen, J., Petrovska, E., Maraschini, M., de Ruiter, M., Torresan, S., and Critto, A.: Artificial Intelligence for climate change multi-risk assessment: a Myriad-EU case study in the Veneto Region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16585, https://doi.org/10.5194/egusphere-egu24-16585, 2024.

EGU24-16910 | Posters on site | NH10.6

An adaptive and flexible Climate Risk Assessment Framework for regions 

Michaela Bachmann, Reinhard Mechler, Oscar Higuera Roa, Anna Pirani, Jeremy Pal, Lena Reimann, Maurizio Mazzoleni, Ted Buskop, and Jaroslav Mysiak

With climate change increasingly affecting people, assets and the environment, Climate Risk Assessments (CRA) are seeing strong attention for understanding the scope and scale of climate risks in order to plan and implement adaptation and climate risk management responses.

In the context of the EU Horizon 2020 project CLIMAAX we developed an inclusive and harmonized CRA framework adapted for NUTS-1 and NUTS-2 level. This framework aligns with state-of-the-art methodologies and is further complemented by a user-friendly toolbox tailored for risk quantification across European regions. Our approach integrates insights from UCPM documents, European National Adaptation Plans and Strategies, peer-reviewed literature as well as existing CRA frameworks and international standards to respond to needs, recent advancements and best practices in the CRA field. The framework was collaboratively developed with five European pilot regions to ensure feasibility and applicability while pursuing adaptive flexibility.

The practical need of the CRA framework led to a five-step assessment cycle (with special emphasis on key risk assessment as a novelty), underpinned by a conceptual context addressing principles, technical choices (e.g. future scenarios) and participatory processes. The framework allows for toolbox extension (the risk analysis) as well as indicates entry points for Climate Risk Management and Adaptation options thereby creating a feedback loop within the CRA cycle. To address compound and multi-hazards aspects of risk, the framework is designed to tackle complexity by referring to a variety of options such as workflows for climate risk quantification or qualitative options together with participatory processes and stakeholder inclusion.

The developed CRA framework brings together practical needs and scientific, standardized knowledge. However, further insights are needed to efficiently connect climate risk estimations with climate risk management and adaptation strategies to support communities and regions in their efforts towards building climate resilience.

How to cite: Bachmann, M., Mechler, R., Higuera Roa, O., Pirani, A., Pal, J., Reimann, L., Mazzoleni, M., Buskop, T., and Mysiak, J.: An adaptive and flexible Climate Risk Assessment Framework for regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16910, https://doi.org/10.5194/egusphere-egu24-16910, 2024.

EGU24-18352 | Orals | NH10.6

On the integration of ontological models of risk in artificial intelligence and machine learning applications to advance multi-hazard risk assessment 

Massimiliano Pittore, Cristine Griffo, Alessandro Mosca, Davide Ferrario, and Piero Campalani

Many areas of the world are prone to several natural hazards, with their occurrences possibly compounded, cascaded, or otherwise connected, either causally or across space and time, and effective risk reduction is only possible if all ensuing relevant threats are considered and analyzed. The examination of multiple hazards for the assessment of risk poses a range of additional challenges partly due to the differing characteristics of underlying processes, partly due to the broader range of consequences and the related risk-driving factors (e.g, exposure and vulnerability).

Considering the increasing availability of data about some components of risk, in the past decade several frameworks and approaches including artifical intelligence and in particular machine learning algorithms have been proposed to support multi-hazard/multi-risk assessment studies.

However, several challenges can be acknowledged that hinder the application of machine learning: the complex interplay among the risk components in multi-hazard contexts, for instance, along with the paucity of available quantitative information on impact (i.e., damage, loss) might impair the development of training datasets of adequate size and quality. Furthermore, information on multi-hazard risk is relying on heteogeneous data, often qualitative. Lastly, but not least, additional uncertainty is associated to the complexity and current lack of consensus in the conceptual definition of high-impact multi-hazard events by the different involved scientific as well as praxis-oriented communities.

In this context, the use of ontologies and semantic data representations may prove useful to tackle the above-mentioned challenges. An ontology is a structured representation of shared knowledge about a specific domain, encoded in the form of axioms, natural language labels, synonyms, definitions and other types of annotation properties. Risk-oriented ontologies can be used for instance to provide a common operational basis to the basic underlying conceptual definition, to be agreed upon and shared across communities with different scientific background. Furthermore, ontologies can be used to access and exploit background knowledge in order to build better predictive models, expand or enrich feature engineering in machine learning or to constrain the search for a solution to an optimization problem (e.g., setting hard constraints based on logical inferences). Formal ontological representations can also provide a consistent support to the development of so-called explainable models, therefore controlling the unnecessary spread of "black box" models in sensitive operational environment such as, e.g., impact forecasting and early warning.

How to cite: Pittore, M., Griffo, C., Mosca, A., Ferrario, D., and Campalani, P.: On the integration of ontological models of risk in artificial intelligence and machine learning applications to advance multi-hazard risk assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18352, https://doi.org/10.5194/egusphere-egu24-18352, 2024.

EGU24-19199 | Posters on site | NH10.6

PARATUS Forensic Analysis Approach of Past Disasters to Develop Quantifiable Multi-Hazard Impact Scenarios 

Funda Atun, Federica Romagnoli, Silvia Cocuccioni, Liz Jessica Olaya Calderon, Iuliana Armas, Ruxandra Mocanu, Caglar Goksu, Seda Kundak, Massimiliano Pittore, and Richard Sliuzas

Understanding complex interactions between hazardous events and dynamic risk conditions in today’s geographies requires carefully analyzing the historical data. Learning from the past will contribute to developing models and multi-hazard risk scenarios. Current disaster databases often concentrate on individual hazards and their direct consequences, lacking the ability to attribute impacts resulting from hazard interactions or adequately depict risk pathways from root causes to ensuing losses. Although the Post Disaster Needs Assessment (PDNA) approach is widely used to assess physical damages, economic losses, and recovery costs following major disasters, it proves less straightforward in estimating impacts and losses for future events.

In forensic analysis, when examining post-event conditions, the investigator formulates hypotheses regarding the pre-event conditions and gathers relevant evidence and facts. Forensic investigations of disasters, i.e. FORIN, highlight the necessity to characterize systemic, structural root causes and risk drivers at global, national, and local levels. While historical disaster data is indispensable, acknowledging the dynamic nature of economic, social, and environmental conditions, at the same time it challenges the prevailing notion that "the past is the key to the future."

Within the realm of disaster risk literature, several forensic analysis approaches are present. In the context of the PARATUS project's development of a forensic approach, three specific methodologies are incorporated: Investigation of Disasters (FORIN), Post Event Review Capability (PERC), and Detecting Disaster Root Causes (DKKV). PARATUS approach applies a combination of these three forensic approaches to a set of learning case studies drawn from selected past disaster events to analyze and navigate the complexity of disaster impacts across diverse contexts.

In PARATUS, we employ forensic analysis alongside historical datasets and earth observation across 18 learning case studies. Three primary criteria guide the selection of these case studies: 1) featuring hazard interactions representative of the European context; 2) having an impact on diverse sectors; and 3) global scenarios that could potentially occur in Europe.

How to cite: Atun, F., Romagnoli, F., Cocuccioni, S., Olaya Calderon, L. J., Armas, I., Mocanu, R., Goksu, C., Kundak, S., Pittore, M., and Sliuzas, R.: PARATUS Forensic Analysis Approach of Past Disasters to Develop Quantifiable Multi-Hazard Impact Scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19199, https://doi.org/10.5194/egusphere-egu24-19199, 2024.

EGU24-19323 | ECS | Orals | NH10.6 | Highlight

Investigating Spatial-Behavioral Patterns in Hazards: A Virtual Reality Study as A Data Gathering Method 

Duygu Kalkanlı, Seda Kundak, Funda Atun, and Cees J. van Westen

Analyzing multi-hazards requires a comprehensive approach, involving complexities in studying multiple hazards and challenges in visualizing numerous risks due to the abundance of information (Kappes, et.al.2012). Risk perception research, on the other hand, has emerged to aid decision-makers in understanding how people characterize and evaluate different hazards, anticipating behavioral responses, and guiding risk communication. Although the risk perception concept has been integrated into various behavioral theories applied to examine preparedness for numerous hazard types, there remains a gap in understanding which theories are suitable for examining multiple hazard types simultaneously (Gill & Malamud, 2017). Therefore, anthropogenic factors indirectly influencing multi-hazard risk assessment need addressing. Studying human behavior in multi-hazard scenarios presents inherent challenges, primarily due to the retrospective nature of analyses conducted after the event. The lack of direct observation during occurrences hampers the formulation of questions and modeling beforehand, limiting the ability to address perception and recall biases in real time. Despite these challenges, a thorough examination of catastrophes necessitates understanding not only how people behave but also delving into the underlying reasons for their behavior, a longstanding challenge in economics and social sciences (Wilson, 2017).

Virtual Reality (VR) environments emerge as valuable tools for overcoming these challenges. VR facilitates a more natural interaction among participants, providing an ideal setting to explore complex behavioral dynamics in disaster scenarios, previously nearly impossible in controlled settings. Combining the internal validity of laboratory experiments with the external validity of field or natural experiments (Fiore et al., 2009), VR enables repeated experiments with large subject pools, a challenge in real disaster situations. This allows researchers to achieve realistic yet replicable results that traditional methods struggle to attain. In contrast to real-world disasters, VR experiments avoid participant attrition, a common issue in natural research studies introducing biases. Conducting numerous identical experiments with a significant number of participants allows researchers to subtly manipulate factors and interactions, exploring specific questions comprehensively. Participants in VR experiments can engage in multiple scenarios, facilitating the exploration of learning behavior beyond one-time event analyses. Fiore et al. (2009) emphasize that VR participants can experience long-term scenarios in a short time, generating multiple counterfactual scenarios.

While traditional laboratories played a central role in advancing behavioral economics, VR is poised to be vital for inclusive multidisciplinary behavioral research in more realistic environments. It not only addresses methodological challenges associated with disaster research but also opens avenues for nuanced exploration of the reasons behind human behavior in disasters. This study examines the use of VR as an innovative tool for new risk assessment in complex contexts, considering behavioral differences and mobility preferences of participants with and without familiarity with the spatial environment.

How to cite: Kalkanlı, D., Kundak, S., Atun, F., and van Westen, C. J.: Investigating Spatial-Behavioral Patterns in Hazards: A Virtual Reality Study as A Data Gathering Method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19323, https://doi.org/10.5194/egusphere-egu24-19323, 2024.

EGU24-19673 | Posters on site | NH10.6

Identification of urban critical context using multi-risk composite-index 

Maria Polese and Gabriella Tocchi

Given the complexity of the urban environment and the intricate social fabric within cities the multi-risk assessment in urban settlements is a particularly challenging task. The nature of urban risk is inherently multi-dimensional, encompassing physical, social, economic, institutional, and environmental factors. Each element of the systems constituting the urban settlement is characterized by different exposure and vulnerability to natural hazards. Moreover, the key features of the exposed elements can vary spatially and temporally, leading to an even more complex estimation of potential across an urban area. Additionally, the interrelated nature of various hazards adds another dimension of complexity to traditional risk frameworks.

This study presents a framework for integrating multiple dimensions in risk analysis. A straightforward risk index that combines multiple hazards and physical, social, and environmental exposure and vulnerability information is proposed. The index is obtained by combining single indicators representative of the aforementioned dimensions, resulting in a more holistic representation of risk. Moreover, selected indicators are combined, defining suitable weights that may reflect stakeholders’ priorities in policymaking. Recognizing the extreme complexity of urban systems and the difficulties in capturing different exposure/vulnerability conditions with a single index, a viable approach is to define a priori the multi-hazard scenario and risk metric of interest and select only the most representative exposure/vulnerability indicators to build the composite risk index. To this end, risk storylines and related impact-chains can be used as a practice-oriented support to guide the selection of the basic elements contributing to the relevant impact scenario and to account for unexpected cascading effects activating different types of vulnerabilities and eventually amplifying the final impact.

This approach allows for ranking regions exposed to multiple hazards and identifying urban critical contexts, i.e., urban areas where potential risk generated by different sources is higher and that are more in need of application of disaster risk reduction strategies. The prioritization of urban areas exposed to natural hazard risks provides several advantages for effective risk management and mitigation strategies. Concentrating efforts on high-risk areas is often more cost-effective, as it minimizes the need for widespread interventions and allows for the efficient allocation of limited resources. Furthermore, by applying a variation of single indicators composing the index, the proposed approach enables accounting for the effect of mitigating actions in risk analysis. the Thus, this tool also represents a helpful mean to evaluate the effectiveness of risk reduction policies.

This study was carried out within the RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005

How to cite: Polese, M. and Tocchi, G.: Identification of urban critical context using multi-risk composite-index, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19673, https://doi.org/10.5194/egusphere-egu24-19673, 2024.

EGU24-21937 | Posters virtual | NH10.6

Advancing Coastal Resilience through Integrated Modeling of Compound Flooding Events 

Wonhyun Lee, Alexander Y. Sun, and Bridget R. Scanlon

Coastal areas, facing escalating hazards intensified by climate change, are particularly vulnerable to wind-driven storm surge, waves, and flooding. The unprecedented events of Hurricane Harvey in 2017 highlighted the urgent need to better predict and understand storm-induced impacts in complex coastal environments. This study integrates two numerical modeling frameworks, namely the Delft3D Flexible Mesh (DFM) and Super-Fast INundation of CoastS (SFINCS), to provide a comprehensive approach addressing the challenges of coastal hazards and compound flooding in the Texas Gulf Coast region. This integrated DFM approach incorporates features like surface wave, hydrological, and hydraulic model-coupling, alongside grid nesting procedures to capture the wave and flow dynamics. The variable grid configuration optimally represents bathymetry while improving 
simulation time and accuracy. Model validation against measurements ensures a high level of accuracy, with a focus on estimating spatiotemporal variability in storm-induced surge and flooding. Addressing challenges faced by Texas Gulf Coast communities, a probabilistic surge 
and flood-inundation modeling system employing SFINCS is proposed. This system offers probabilities for different water depth thresholds, supporting surge and flood risk assessments, resilient infrastructure design, and coastal planning decisions. SFINCS, with reduced computational demand, uses essential physics for efficiency and accuracy, overcoming limitations of High-Performance Computing (HPC) systems. The study's outcome includes probabilistic predictions of compound flooding events in the Texas Gulf Coast region, presented through a probabilistic map and data. Stakeholders and end-users will benefit from this information for short and long-term planning and management, contributing to the resilience of coastal communities facing the complex challenges of climate-induced hazards. This integrated approach advances scientific understanding, supports decision-making, and promotes mutual benefit for researchers, policymakers, and coastal communities 
alike

How to cite: Lee, W., Sun, A. Y., and Scanlon, B. R.: Advancing Coastal Resilience through Integrated Modeling of Compound Flooding Events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21937, https://doi.org/10.5194/egusphere-egu24-21937, 2024.

Between January and June 2022, the UK experienced the driest weather in over 40 years. This culminated in July, when temperatures exceeded 40 degrees Celsius for the first time since records began. Unprecedented hot, dry conditions resulted in hazards and multi-hazard interactions that have not previously been experienced in the UK. This expression of high temperature induced multi-hazards along with more commonly seen hot weather induced hazards with longer residence times may lead to increased direct and indirect impacts on society and ecosystems as experienced in other parts of the world.

The accurate, timely, and efficient derivation of information and data products from EO data and technologies is instrumental in predicting, monitoring, assessing, and evaluating the occurrence of single natural hazard events and their potential impacts. What is not so well understood is the role of EO-derived environmental indicators in characterizing complex causal relationships and underlying mechanisms leading to cascading or compounding multi-hazard impacts. This may be demonstrated using time series analysis of a single indicator or derived from several time series of two or more indicators of interrelated hazard events such as droughts, heatwaves, subsidence, wildfires, flooding, and landslides.

In this study, we aim to advance the state-of-the-art by using long-term EO satellite data to identify thresholds, trends, and tipping points within time series of established environmental metrics which indicate the dynamic evolution of a multi-hazard event. This information will be complemented by in-situ observations and local, regional, and global models to identify environmental precursors and chains of effects that may be suggestive of multi-hazard event onset conditions. By utilizing several vulnerability and impact assessment models, such as impact chains, we will demonstrate the utility of EO techniques and datasets in enhancing multi-hazard risk assessment and management.

In this presentation, we briefly introduce the research context, questions, methodological approaches, preliminary results, and future direction of the UK Science Case as part of the High Impact Multi-hazards Science (EO4Multihazards) project funded by the European Space Agency (2023 – 2026).

How to cite: Bateson, L., Ciurean, R., Winson, A., Smith, K., and Mills, E.: The role of Earth Observation in advancing our understanding of high sustained temperature leading to dry conditions compound events: the UK Science Case, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22201, https://doi.org/10.5194/egusphere-egu24-22201, 2024.

EGU24-224 | Posters on site | GM4.2

Assessment of sediments dynamics through the identification of main deposition shapes in large reservoirs  

Jose Luis Molina, Fernando Espejo, Jorge Mongil-Manso, Teresa Diez-Castro, Santiago Zazo, and Carmen Patino-Alonso

Sediment deposition at the bottom of artificial reservoirs have become a worldwide problem that represent a dual problem. First, it is related to the reduction of storage capacity and lifetime. In this sense, associated impacts may comprise a capability reduction to provide water for irrigation, hydropower production and other uses, as well as to intercept floods and regulate the flow. Second, problems come from the threat that the sediment represents for the dam structure. In case the sediment deposits get too close from the structure, they may block the outlets affecting the dam safety. Also, if high-charged water pass through the turbines, it causes abrasion of mechanical equipment. This may generate inefficiencies such as decrease power generating efficiency and ultimately production loss. This primarily stems from the absence of a holistic and integrated strategy for creating a durable and sustainable strategy for managing sedimentation in dams and reservoirs.  In this sense, a whole plan should incorporate a sequential nature that incorporate three chronological phases: preventive, mitigative and corrective measurements. It is clear the lack of preventive actions that have taken during the initial decades of dam/reservoirs functioning. The main objective of this work is to identify the main sediment deposition shapes in large reservoirs that allows inferring the driven processes. Based on the pervious analysis, 6 categories of shapes have been identified based on 4 parameters listed as follows: slope continuity, slope break, absolute and relative slope, and arc configuration. In this sense, categories are:  Flat Areas (FA), SubFlat Areas (SFA), Breaking Lines (BL), Vertical Jumps (VJ), Non-Vertical Jumps (NVJ) and Arc-Shapes. This will allow inferring the main deposition and transport processes that may help to prevent, palliate and/or correct this phenomenon. This research was applied in Rules reservoir (Granada) which is key hydraulic infrastructure with huge sediments issues. Future policies will have to implement a plan route incorporating scientific analysis taking to consideration sediments dynamics.

Keywords: dynamics, bathymetric measurement, dam sedimentation, hydraulic infrastructure, storage capacity

How to cite: Molina, J. L., Espejo, F., Mongil-Manso, J., Diez-Castro, T., Zazo, S., and Patino-Alonso, C.: Assessment of sediments dynamics through the identification of main deposition shapes in large reservoirs , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-224, https://doi.org/10.5194/egusphere-egu24-224, 2024.

EGU24-1049 | ECS | Orals | GM4.2

Exploring Uncertainties Within a Framework for Assessing Extreme Precipitation-Induced Cascading Hazards in the Himalayas  

Sudhanshu Dixit, Srikrishnan Siva Subramanian, and Sumit Sen

The Himalayas are increasingly vulnerable to the impacts of climate change, with recent years experiencing a surge in the frequency of natural hazards. The risk escalates when events unfold in a cascading manner, where a primary hazard triggers a secondary one. Therefore, it is crucial to develop an integrated framework to assess the ramifications of these cascading hazards. This framework plays a pivotal role in providing early warnings, considering the uncertainty introduced by rainfall input. The presented framework simulates the dynamic interplay between intense precipitation events and hill slopes, potentially triggering landslides. It subsequently models the debris flow resulting from the runoff formed by precipitation mixing with landslide deposits, culminating in debris runout. To address data uncertainties, the framework integrates four diverse precipitation data sources: gridded observation datasets, reanalysis data, satellite data, and numerical weather prediction models. The methodology assesses sediment volume originating from hillslopes and anticipates the sediment volume reaching river junctions during extreme events. Additionally, it involves the numerical simulation of the initial stages of the cascading nature of geohazards, specifically the transformation of landslides into debris flows. The framework's validation is conducted using the 2013 North India Floods, an extreme precipitation event that triggered over 6000 landslides and debris flows.

How to cite: Dixit, S., Subramanian, S. S., and Sen, S.: Exploring Uncertainties Within a Framework for Assessing Extreme Precipitation-Induced Cascading Hazards in the Himalayas , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1049, https://doi.org/10.5194/egusphere-egu24-1049, 2024.

EGU24-1577 | Posters on site | GM4.2

Exploring connections between liquid/solid runoff fractions and water quality in large reservoirs´ catchments through Multivariate statistics  

Jorge Mongil-Manso, Carmen Patino-Alonso, José Nespereira-Jato, José-Luis Molina, Fernando Espejo, María-Teresa Díez-Castro, and Santiago Zazo

In river environments, the interaction between liquid and solid runoff fractions plays a crucial for understanding water flow. The magnitude of liquid runoff is directly influenced by of sediments levels, impacting water resource management and quality. Sediment mobilization by total runoff fundamentally shapes river morphology. The imperative need to comprehensively understand hydrological behavior leads us to examine the relationship between these variables and water chemical aspects. Understanding the intricate dynamics between liquid and solid runoff, influenced by sediment levels and chemical variables, is crucial for the effective sediment management of reservoirs. Multivariate statistics are commonly used to identify factors influencing sediment production during hydrological processes. The objective of this study is to apply Partial Least Squares Regression (PLSR) to identify and understand the relationship between chemical variables as predictors and hydrological processes (liquid and solid runoff), allowing a comprehensive assessment of their influence in river environments.  The case study was conducted in the Rules (Granada), Casasola, and La Viñuela reservoirs (Málaga). The results indicated a positive correlation between sediments (solid runoff) and variables such as pH, Clay (CY), Silt (ST), and Carbonates (CA). This means that as sediment levels increase, these variables also show an increasing tendency. Nevertheless, this study also revealed a negative association between sediments and Dissolved Oxygen (EG) and sand (SD) implying that as sediment levels rise, Dissolved Oxygen and sand content tend to decrease. In terms of liquid runoff, a direct relationship was primarily observed with electrical conductivity (CE), Organic Matter (MO), and Sand Content (SD). This suggests a positive connection between these variables, where higher liquid runoff is associated with higher values of electrical conductivity, organic matter, and sand content. Chemical parameters manifest in two distinct groups: one shows a strong positive relationship with sediments (pH, CY, ST, and CA), while the other (CE, MO, SD, and EG) is associated with liquid runoff. In conclusion, the study underscores the intricate dynamics between liquid runoff, sediments (solid runoff), and chemical variables in river systems, using PLSR to unveil relationships. In summary, this study underscores the crucial connection between total runoff (water and sediments), and chemical variables in river environments. These findings highlight the complexity of interactions in river systems, providing valuable insights for water management and understanding hydrological processes. Furthermore, the interaction between liquid and solid runoff fractions in river environments has direct applications for sediment management in reservoirs, enhancing decision-making knowledge for authorities.

How to cite: Mongil-Manso, J., Patino-Alonso, C., Nespereira-Jato, J., Molina, J.-L., Espejo, F., Díez-Castro, M.-T., and Zazo, S.: Exploring connections between liquid/solid runoff fractions and water quality in large reservoirs´ catchments through Multivariate statistics , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1577, https://doi.org/10.5194/egusphere-egu24-1577, 2024.

Sediment connectivity is a pivotal concept in geomorphological studies aimed at assessing watershed sediment dynamics. It is expressed through the spatial arrangement and physical linkages of system components (Structural Connectivity, SC) and the actual transfer of water and sediments facilitated by dynamic processes (Functional Connectivity, FC). However, a limited number of studies have simultaneously assessed SC and FC. Moreover, traditionally sediment connectivity studies primarily rely on comparing independent results from GIS modelling, field-based assessments, and mapping. Thus, it remains a common practice to treat geomorphic processes and connectivity as separate variables, often without joining them into an integrated modelling approach.

Accordingly, this research aims to introduce a novel methodology that integrates geomorphological data derived from a detailed mapping approach with SC and FC. In particular, we developed a new GIS-based integrated model named HOTSED, designed to assess potential hotspots of sediment sources and related sediment dynamics at the watershed scale.

We tested our approach in a geomorphologically highly active Mediterranean watershed in the Northern Apennines (Italy), starting with the elaboration of an Inventory Map (IM) of sediment sources through fieldwork, photointerpretation, terrain analysis, and digital mapping. Furthermore, we used IM-derived data to estimate the geomorphic Potential of Sediment Sources (PSS) adopting a relative scoring system. Moreover, we computed Structural Sediment Connectivity (STC) and the Potential for Sediment Transport (PST) by combining terrain and hydrological parameters, land use data, and rainfall erosivity. Subsequently, the integration of PSS, STC, and PST was achieved through a raster-based calculation method, yielding the HOTSED model.

The application of the model in the study area provided a single and intuitive output depicting the location of hotspots of sediment sources. It allowed the derivation of “relative hazard” classes for sediment production and delivery using the fluvial system as target feature. The results show that HOTSED successfully highlighted hotspots associated with active complex and polygenetic geomorphic systems located in areas close to the main channels, as well as linear hotspots corresponding to tributary drainages acting as stream corridor sources. Furthermore, it successfully identified areas prone to store sediments in depositional landforms with low hazard, considering both low geomorphic potential and sediment connectivity. Thus, this study proves that our conceptual model is particularly effective in geomorphologically complex areas such as the Northern Apennines.

How to cite: La Licata, M., Bosino, A., Sadeghi, S. H., and Maerker, M.: Assessing hotspots of sediment sources and related sediment dynamics through the integration of geomorphological data, sediment connectivity and sediment transport modelling – The HOTSED model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4101, https://doi.org/10.5194/egusphere-egu24-4101, 2024.

EGU24-4411 | ECS | Posters virtual | GM4.2

Reconstruction of spatial and temporal variability of debris flow in northern Apennines (Italy): Case study of the Alpe di Succiso area 

Muhammad Ahsan Rashid, Giovanni Leonelli, Roberto Tinterri, Roberto Valentino, and Alessandro Chelli

Debris flows are within the most common and extensive natural hazards in mountain areas, where they may impact humans and their assets. On the surroundings of Alpe di Succiso (2000 m a.s.l., Reggio Emilia Province, Italy) multiple debris flows can be found but there is no information about the spatial and temporal variability. To fill the gap, various methods such as geomorphological mapping, geo-mechanical classification of source areas, grain size analysis, dendro-geomorphic method and climate data have been used to assess the spatial extent and the past occurrence of debris-flow events. Here the preliminary results of the analysis performed in the Fossa Lattara Site, NW of Alpe di Succiso, are shown.

The landforms and deposits present in the surroundings of Alpe di Succiso are the product of different morphogenesis (glacial, gravitational, and torrential) which revealed the evolution of the morpho-climatic conditions that have affected the study area over time. Field work has been carried out to identify the morphological features of debris flows revealing distinctive features such as detachment scarps, debris flow cones, lobes, levees, and channels.

To understand the slope stability mechanism of the source area, a discontinuous survey was conducted and it is found that wedge failure is common. Additionally, in both source and depositional areas, grain size analysis was performed by using various methods: direct field measurement was used for particles greater than 16 mm, a sieve analysis covered the range from 2 to 16 mm, and the laser granulometer technique was applied to particles smaller than 2 mm. Notably, the coarser particles were abundant in depositional area than source area.

On forested areas, dendro-geomorphic analysis contributes to detection of trends of debris flow. Dendro-geomorphic technique is based on the identification of growth anomalies recorded by the annual rings of trees disturbed by debris flows. For debris flow dating, identification of reaction wood, abrupt growth changes and eccentric growth are essential.  Trees samples from debris flow area and reference sites (undisturbed areas) have been collected on site to cross date climate influences and debris flow events. According to the dendro-chronological preliminary results, the debris flow was identified in 1989, 2013 and 2017. Further, debris flow events are linked with precipitation events of the study area.

Moreover, daily rainfall depths in the period 1961-2022 have been collected from ARPAE Emilia Romagna database to understand the impact of climate change on debris flow and it is observed that daily precipitation intensity (dpi) has increased from 1961 to 2022. Seasonal variations are also observed. Noticeably, in the months of December, January, and February the sum of dpi has increased by 162 to 220 mm. Future studies will be performed to analyze the effects of climate change on debris flow.

How to cite: Rashid, M. A., Leonelli, G., Tinterri, R., Valentino, R., and Chelli, A.: Reconstruction of spatial and temporal variability of debris flow in northern Apennines (Italy): Case study of the Alpe di Succiso area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4411, https://doi.org/10.5194/egusphere-egu24-4411, 2024.

EGU24-5386 | ECS | Orals | GM4.2

How is climate change affecting hydro-meteorological triggering for debris flows? An assessment based on convection-permitting models and a bias-neutral procedure 

Andrea Menapace, Eleonora Dallan, Francesco Marra, Lorenzo Marchi, Michele Larcher, and Marco Borga

Debris-flow activity is expected to change in the future following the expected changes in sub-daily rainfall rates. In this study, we connect high-resolution climate simulations from an ensemble of recently developed convection-permitting models (CPM) and a threshold-based precipitation model for debris-flows triggering. We are considering CPM runs over historical (1996-2005), near future (2041-2050) and far future (2090-2099) decade-long periods. Given the biases affecting the CPM simulations and the desire to avoid bias-correction procedures, which may introduce distortions into the precipitation simulations, we propose a methodology to map the debris-flow threshold into the simulated climates. This is obtained by evaluating the return levels of the threshold precipitation rates at different durations, and mapping these in the climate simulations using the same return levels. The Simplified Metastatistical Extreme Value (SMEV) methodology is exploited for the precipitation statistical analysis. The suitability of the proposed framework is tested on the Moscardo catchment, a small study basin located in the eastern Italian Alps, where the debris flow activity is mainly transport-limited. This case study is particularly remarkable due to the high frequency of debris flows and a monitoring system working since 1990, which has permitted establishing reliable rainfall . The debris-flow triggering precipitation events are assessed by considering changes in their frequency, depth and seasonality. The promising preliminary results support the use of this approach to assess debris flow hazards in a changing climate.

How to cite: Menapace, A., Dallan, E., Marra, F., Marchi, L., Larcher, M., and Borga, M.: How is climate change affecting hydro-meteorological triggering for debris flows? An assessment based on convection-permitting models and a bias-neutral procedure, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5386, https://doi.org/10.5194/egusphere-egu24-5386, 2024.

EGU24-5581 | ECS | Orals | GM4.2

Quantifying the effects of rainfall temporal variability on landscape evolution processes 

Taiqi Lian, Nadav Peleg, and Sara Bonetti

Rainfall characteristics such as intensity, duration, and frequency are key determinants of the hydro-geomorphological response of a catchment. The presence of non-linear and threshold effects makes the relationship between rainfall variability and geomorphological dynamics difficult to quantify. This is particularly relevant under predicted exacerbated erosion induced by an intensification of hydroclimatic extremes. In this study, we quantify the effects of changes in rainfall temporal variability on catchment morphology and sediment erosion, transport, and deposition across a broad spectrum of grain size distributions and climatic conditions. To this purpose, multiple rainfall realizations are simulated using a numerical rainfall generator, while geomorphic response and soil erosion dynamics are assessed through a landscape evolution model (CAESAR-Lisflood). Virtual catchments are used for the numerical experiments and simulations are conducted over centennial time scales. Simulation results show that higher rainfall temporal variability increases net sediment discharge, domain erosion and deposition volumes, and secondary channel development. Particularly, dry regions respond more actively to rainfall variations and finer grain size configurations amplify the hydro-geomorphological response. We find that changes in erosion rates due to rainfall variations can be expressed as a power-law function of the ratio of rainfall temporal variabilities (quantified here through the Gini index). Results are further supported by long-term observational data and simulations over real catchments. Such quantification of the effects of predicted changes in rainfall patterns on catchment hydro-geomorphic response, as mediated by local soil properties, is crucial to forecasting modifications in sediment dynamics due to climate change.

How to cite: Lian, T., Peleg, N., and Bonetti, S.: Quantifying the effects of rainfall temporal variability on landscape evolution processes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5581, https://doi.org/10.5194/egusphere-egu24-5581, 2024.

EGU24-8030 | ECS | Posters on site | GM4.2

The use of normalized difference vegetation index (NDVI) in sediment connectivity analysis: insights for considering land cover changes in Sediment flow Connectivity Index (SfCI) 

Marina Zingaro, Giovanni Scicchitano, Alberto Refice, Alok Kushabaha, Antonella Marsico, Deodato Tapete, Alessandro Ursi, and Domenico Capolongo

Land cover plays a fundamental role in surface dynamics that involve sediment connectivity. The processes of sediment erosion, transport and deposition are strongly conditioned by land coverage types (classes) that physically can mitigate, prevent or increase sediment production and mobility on the surface. In fact, land cover and land use data are required for the computation of some indices and models of sediment connectivity. However, it should be considered that land cover changes can impact these processes, especially if they occur over a short period of time.

This work presents an assessment of land cover changes in three different hydrographic basins (river Severn basin in UK, river Vernazza basin in northwestern Italy and Lama Camaggi basin in southern Italy) in relation to their respective sediment connectivity patterns, described by Sediment flow Connectivity Index (SfCI) in previous works (Zingaro et al., 2019; Zingaro et al., 2020; Zingaro et al., 2023). The main aim is to evaluate the use of normalized difference vegetation index (NDVI) to consider land cover changes in sediment connectivity analysis. The NDVI is computed from satellite multi-spectral images (Sentinel-2) in time period between the reference year of the land cover used in previous SfCI calculation and the last year (2023) in each of study area. The results show that (1) NDVI highlights the occurrence of land cover changes over short time periods in many areas of the basins, (2) the introduction of NDVI in SfCI modifies sediment mobility values also affecting the definition of sediment connectivity pattern.

The use of NDVI can improve the analysis of sediment connectivity by providing more dynamism in the description of sediment pathways on both spatial and temporal scales. The present experimentation gives new insights to consider surface cover changes in SfCI contributing to update the algorithm and to investigate the possibility of its enhancement.

Acknowledgments

Research performed in the framework of the project “GEORES - Applicativo GEOspaziale a supporto del miglioramento della sostenibilità ambientale e RESilienza ai cambiamenti climatici nelle aree urbane”, funded by the Italian Space Agency (ASI), Agreement n. 2023-42-HH.0, as part of ASI’s program “Innovation for Downstream Preparation for Science” (I4DP_SCIENCE).

References

  • Zingaro, M.; Refice, A.; Giachetta, E.; D’Addabbo, A.; Lovergine, F.; De Pasquale, V.; Pepe, G.; Brandolini, P.; Cevasco, A.; Capolongo, D. Sediment Mobility and Connectivity in a Catchment: A New Mapping Approach. Science of The Total Environment 2019, 672, 763–775, doi:10.1016/j.scitotenv.2019.03.461.
  • Zingaro, M.; Refice, A.; D’Addabbo, A.; Hostache, R.; Chini, M.; Capolongo, D. Experimental Application of Sediment Flow Connectivity Index (SCI) in Flood Monitoring. Water 2020, 12, 1857, doi:10.3390/w12071857.
  • Zingaro, M.; Scicchitano, G.; Palmentola, P.; Piscitelli, A.; Refice, A.; Roseto, R.; Scardino, G.; Capolongo, D. Contribution of the Sediment Flow Connectivity Index (SfCI) in Landscape Archaeology Investigations: Test Case of a New Interdisciplinary Approach. Sustainability 2023, 15, 15042, doi:10.3390/su152015042.

How to cite: Zingaro, M., Scicchitano, G., Refice, A., Kushabaha, A., Marsico, A., Tapete, D., Ursi, A., and Capolongo, D.: The use of normalized difference vegetation index (NDVI) in sediment connectivity analysis: insights for considering land cover changes in Sediment flow Connectivity Index (SfCI), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8030, https://doi.org/10.5194/egusphere-egu24-8030, 2024.

EGU24-10204 | Orals | GM4.2

A stochastic landscape evolution model framework for debris flow and fluvial processes 

Dingzhu Liu, Hui Tang, Jean Braun, and Jens Turowski

Debris flow is an important process that shapes steep landscapes, connecting the hillslopes and fluvial domains. Yet, it is unclear how debris flows quantitatively influence the topography. Here, we propose and develop a new framework considering debris flows as stochastic processes in long-term landscape evolution. We assume that debris flows occur randomly in time with different initial debris flow volumes, which we model using five different distribution functions. Debris flows propagate along the channel and increase their volume by eroding additional material using deterministic equations. The model predicts the slope-area relationship that is generally assumed to be indicative of debris-flow-dominated landscapes. We suggest a new equation to fit the slope-area relationship, including both debris flow and fluvial domains. This equation features a total of five metrics, two of which are power law exponents, two are representative areas, and one representative slope. The topography in the debris flow-dominated domain is sensitive to the properties of the debris flow, e.g., the initial volume of debris flow, frequency, erosion coefficient, Manning coefficient, uplift rate, and channel width and length. The representative slope and area are primarily sensitive to the total initial volumes of the debris flow, and secondarily to the frequency of occurrence of debris flows. The type and shape parameters of distributions and the debris flows’ volume and frequency have limited effects on the slope-area relationship.

How to cite: Liu, D., Tang, H., Braun, J., and Turowski, J.: A stochastic landscape evolution model framework for debris flow and fluvial processes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10204, https://doi.org/10.5194/egusphere-egu24-10204, 2024.

Devoting more efforts to understand how arid landscapes respond to extreme rainfall events, given the expected increase in storm frequency in the future due to global warming projections, is of great relevance and therefore needs to be addressed. While local studies of recent storm impacts in drylands have proven to be useful, our understanding of global impacts at local-and-regional-scales over longer time-scales is now more qualitative than quantitative.

Deciphering the effects of erosion runoff processes operating during extreme rainstorm events requires developing practical measuring approaches that assist understanding the temporal and spatial extent of erosion and sediment pathways in the ephemeral drainage networks of bare lands. The advent of Synthetic Aperture Radar (SAR) satellite missions with, for example, the Sentinel 1 constellation from the ESA, has provided a great number of images that can be used to map the areal and temporal extent of erosion during rainstorm events. As a result, we are now able to unravel surface runoff erosion operating in arid areas using InSAR coherence change detection following, for example, the work of Cabré et al. (2020, 2023). Interferometric SAR (InSAR) coherence can be used to decipher the sediment entrainment areas and identify channels and drainages disturbed by the passage of floods. However, the coherence remains a dimensionless parameter with no physical meaning of surface change. Thus, it cannot be used yet to estimate surface change processes in an automatic basis. For this reason, we have explored the areas with surface change identified in InSAR coherence images using SAR amplitude and field calibration data. In the identified surface change areas we have performed grain-size measurements to prove that sediment grain-size diameter (e.g., D84, D50) in ephemeral channels is well correlated (R=0.93 and 0.72, respectively) with SAR amplitude values and therefore can be used to (i) unravel the downstream variations in grain-size by providing valley-floor grain-size maps and, (ii) identify fluvial features (e.g., longitudinal bars) preserved within the ephemeral channels after the passage of a flood. The latter can be of wide application to monitor ungauged ephemeral channels in arid areas worldwide and provide insights about the dryland sedimentary system dynamics during extreme storm events.

How to cite: Cabré, A., Marc, O., Remy, D., and Carretier, S.: Integrating InSAR coherence and SAR amplitude to unravel the surface change processes operating during extreme rainstorm events in the Atacama Desert., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10362, https://doi.org/10.5194/egusphere-egu24-10362, 2024.

EGU24-10429 | ECS | Orals | GM4.2

Interaction Between Large Wood and Sediment Transport in an Alpine Torrent in the Dolomites 

Marco Martini, Francesco Bettella, and Vincenzo D'Agostino

Large wood (LW), defined as woody pieces exceeding 1 m in length and 10 cm in diameter, significantly shapes channel morphology and ecological habitats within Alpine torrents. Lower-order alpine torrents, with their smaller drainage areas and steeper gradients, are particularly sensitive to LW dynamics. The movement of LW greatly affects channel processes, altering flow patterns and sediment dynamics. LW can retain sediments and form log steps that may reduce bed erosion. Moreover, the accumulation of LW at bridge piers and filters or openings of retention check dams can exacerbate flood hazards, emphasizing the crucial need for its accurate quantification for more effective hazard assessments and protection measure design. Our investigation aims to assess changes in the LW budget in the Ru de Vallaccia catchment (covering 1.72 km2, Melton number 0.97, mean channel slope 45%) in the province of Belluno, Veneto, Italy. Specifically, we explore variations in LW volume before and after a heavy rainstorm event with a return period between 2 and 5 years that occurred between the 30th of October and the 2nd of November 2023. Furthermore, this study examines the correlation between segments of the channel affected by sediment erosion and deposition and changes in both the spatial distribution and volume of LW within the channel. Field surveys coupled with high-resolution topography (HRT) assessments conducted before and after the rainstorm event (July and November 2023) allow for a comprehensive evaluation of sediment and LW budgets. Our methodology involves direct field measurements of LW and photointerpretation using GIS software on orthophotomosaics resulting from HRT surveys. Additionally, we utilize the Digital Elevation Model (DEM) obtained from HRT surveys to analyze channel geomorphological changes through the DEM of Differences (DoD) technique, enabling precise quantification and visualization of sediment alterations related to erosion and deposition phenomena. Preliminary findings reveal pronounced sediment mobility, significant alterations in channel morphology, and notable changes in both the spatial distribution and volume of LW. The results of the study highlight the close link between patterns of erosional or depositional sediment dynamics and alterations in the LW budget, elucidating the intricate interaction between geomorphic processes and the presence and evolution of LW during subsequent flood events in steep mountain basins. In addition, these insights have substantial implications for addressing or guiding periodic monitoring of LW and thereby improving our hazard mitigation strategies against those sediment transport events (bedload, debris flood, and debris flow) capable of encompassing significant amounts of LW.

How to cite: Martini, M., Bettella, F., and D'Agostino, V.: Interaction Between Large Wood and Sediment Transport in an Alpine Torrent in the Dolomites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10429, https://doi.org/10.5194/egusphere-egu24-10429, 2024.

EGU24-10776 | Orals | GM4.2

Amplified Risk: How Climate Change is Modifying the Risks from Geological Hazards 

Mary Antonette Beroya-Eitner, Heidi Stenner, Luke Bowman, and Kate Nelson

The global climate is changing, and the effects of these changes on natural hazards are increasingly being felt, particularly by the populations in low- and middle-income countries. Consequently, in the last decades, there has been much research examining the extent of these effects, but the focus has largely been on hydrometeorological hazards. The potential effects of climate change on geological hazards, like earthquakes and volcanic activity, is less studied and deserves greater attention.

Amplified Risk is a four-year program currently being led by the GeoHazards International (GHI), a non-profit committed to saving lives by empowering at-risk communities worldwide to build resilience ahead of disasters and climate impacts. Funded by the United States Agency for International Development (USAID), the overarching goal of the program is to increase collective understanding of how volcanic and earthquake hazards and their societal impacts may be affected by climate change in at-risk low- and middle-income countries.

In line with this, we have thus far explored through literature review and subject matter expert consultations how climate change may alter earthquake and volcanic processes and associated hazards, considering eight climate change signals as the starting point: increased precipitation, decreased precipitation, increased temperature, increased rain-drought cycles, increased free-thaw cycles, increased typhoons, increased wind and sea level rise. Our results show the potential amplifying, cascading, and compounding effects of climate change on geological hazards.   

In general, climate change can affect earthquake and volcanic hazards in two ways: Firstly, it can directly trigger or contribute to directly triggering the hazards as a result of stress regime change following climate-induced variations of loads on the earth surface, mainly due to changes in the volume of ice and water, e.g., glacier melting. Secondly, climate change prepares the ground so that the occurrence of secondary hazards becomes more likely should an earthquake or volcanic eruption occur. For instance, increased precipitation increases soil saturation, making liquefaction more likely in the event of an earthquake.     

In this presentation, we discuss the findings to date in more detail. We also present the flowchart that summarizes our result, which we intend to publish online as an interactive informational tool that may be useful to risk managers, authorities, community leaders, and researchers in appraising the range of effects from climate change on local hazards, and therefore in determining and prioritizing intervention measures.

How to cite: Beroya-Eitner, M. A., Stenner, H., Bowman, L., and Nelson, K.: Amplified Risk: How Climate Change is Modifying the Risks from Geological Hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10776, https://doi.org/10.5194/egusphere-egu24-10776, 2024.

EGU24-13482 | ECS | Orals | GM4.2

Secondary Lahars Impacting on Building Structures at Chimborazo Volcano: A Retrospective and Scenario-Based Modeling Approach 

Simon Mühlbauer, Theresa Frimberger, and Michael Krautblatter

The intense melting of glacial ice and permafrost can increase the presence of temporarily stored liquid water in dynamic high-alpine environments. A sudden release of this water, especially in volcanic settings, might trigger a process chain of severe consequences. During a period of increased periglacial degradation between 2015 and 2017, several large-volume (> 6.0 × 105 m³), outburst-related secondary lahars damaged local infrastructure on the populated southeastern slopes of Chimborazo volcano in Ecuador. The insufficient understanding of secondary lahars associated with the sudden outburst of water complicates the identification of initiating processes and hinders the ability to decipher the governing mechanisms involved during propagation.

In this study, we present how we (1) identified initiation mechanisms of past secondary lahars at Chimborazo, (2) numerically back-calculated these events, (3) developed future lahar scenarios, and (4) quantified their impact on the local population. We performed a retrospective calibration approach to simulate a secondary lahar using the physics-based model RAMMS::Debris Flow. By introducing a novel two-stage outburst scenario development concept, we were able to predict potential future lahars. Finally, applying a standards-based verification of the structural components of residential development allowed us to evaluate the physical impact of potential lahars on infrastructure. We also assessed how increasing the wall thickness affects high- and low-risk areas.

Our results show that the observed secondary lahars can be numerically reproduced with a set of frictional parameters of µ = 0.028 (Coulomb-type friction) and ξ = 600 ms-2 (turbulent friction). The model shows high agreement with locally obtained data (Vasconez et al., 2021) on total lahar volume, flow distance, discharge, and flooded area (deviation from target value = 20 %). By comparing the climatic and topographical situation of similar events at other study sites with the conditions at Chimborazo, we assume that glacial/periglacial destabilization processes may have accompanied the initiation of past lahars. Through deciphering the past initiation processes, our scenarios resulted in volumes between 2.7 × 105 m³ (high probability) and 10.8 × 105 m³ (very low probability) for a climatically derived reference period of 180 years. The structural validation of the component resistance identified high risk for approximately 24 % of the entire runout area. The adjustment to 11 cm wider bricks reduces this area by 5 %.

Only a precise quantification of the ice content and dynamic behavior within the source region enable to estimate the influence of destabilization processes on lahar initiation. However, this work makes an important contribution to supporting informed decision-making in land use planning by implementing an interdisciplinary methodology for analyzing the impacts of mass movements.

In this study, we showed that a retrospectively calibrated numerical model enables the simulation of future outburst-triggered lahars, and we further provided a quantification of their impact on downstream communities.

Vasconez, F.J., Maisincho, L., Andrade, S.D., Cáceres Correa, B.E., Bernard, B., Argoti, C., Telenchana, E., Almeida, M., Almeida, S. & Lema, V. (2021): Secondary Lahars Triggered by Periglacial Melting at Chimborazo Volcano, Ecuador. – Revista Politécnica, 48: 19–30.https://doi.org/10.33333/rp.vol48n1.02

How to cite: Mühlbauer, S., Frimberger, T., and Krautblatter, M.: Secondary Lahars Impacting on Building Structures at Chimborazo Volcano: A Retrospective and Scenario-Based Modeling Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13482, https://doi.org/10.5194/egusphere-egu24-13482, 2024.

EGU24-14250 | ECS | Orals | GM4.2 | Highlight

Widespread cascading torrential hazards in tropical regions  

Maria Isabel Arango, Marcel Hürlimann, Edier Aristizábal, and Oliver Korup

Over the past decades, cascading hazards that include landslides, debris flows, and floods have caused several major disasters in tropical mountain regions. Even though such cascading hazards also occur in steep terrain elsewhere, some natural drivers such as very high humidity with associated heavy rainfalls, and deeply weathered soil profiles, may amplify the reach and impacts of these cascades in tropical mountains. There, torrential fans sustaining dense settlements are especially prone to rainfall-triggered hazard cascades but remain largely understudied compared to temperate mountain regions. Challenges in their hazard assessment include a lack of consensus regarding the scientific terminology to describe, analyse, and record these events; and their complexity, given that, combining traditional single hazard assessment fails to capture the amplification of the damages. On the other hand, their occurrence in remote, undeveloped regions where they are poorly or not documented, and their low temporal recurrence, decreases hazard awareness and increases the growth of urban settlements in exposed areas.

The goal of this study is to review widespread cascading torrential hazards in the tropics as a common and destructive interaction of mass-wasting and flow processes. The study has two different steps: the first is a review of existing terminology concerning regional hydrometeorological cascading hazards in different latitudes and environments, as an attempt to clarify the existing gaps and differences in information between tropical and higher latitude areas. The second step is the description of the main morphological and triggering characteristics of such events. For this, we compiled a dozen regional cascading torrential events that occurred between 2017 and 2023 in different tropical regions of the American, Asian, and African continents, caused by different triggering mechanisms, including extreme rainfall and earthquakes, or both. Using high-resolution satellite images, the events were mapped differentiating the extent of landslide initiation, debris flows runout, and floodings. Additionally, we used freely available remote sensing sources to extract information concerning the geomorphology, soil texture, and triggering rainfall of each study area. Using different statistical tools, we analysed the relationship between different morphological features, triggering rainfall and soil texture, to distinguish the main characteristics of such events in both the basin and the sub-process scale.

As preliminary results of this ongoing research, we have found an important gap in information concerning widespread cascading torrential hazards in tropical regions. Furthermore, the analysis of our inventory allowed us to identify key factors that contribute to the triggering, propagation, and connection of hazards, including the very high availability of coarse-textured soils and higher sediment connectivity within affected catchments. Furthermore, we found that the spatial connection of the sub-processes involved in these events (landslides, debris flows, and floods), is given by their overlap within the different process domains of basins.

This initial approach provides a preliminary understanding of the conditions that promote cascading torrential hazards in tropical regions, which can aid in developing more accurate hazard assessment tools and implementing effective strategies to mitigate risks in the tropics, considering its unique multi-hazard and complex setting.

How to cite: Arango, M. I., Hürlimann, M., Aristizábal, E., and Korup, O.: Widespread cascading torrential hazards in tropical regions , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14250, https://doi.org/10.5194/egusphere-egu24-14250, 2024.

EGU24-14699 | ECS | Posters on site | GM4.2

How will bedload transport respond to climate change in Alpine regions? The "ALTROCLIMA" project 

Felix Pitscheider, Anne-Laure Argentin, Mattia Gianini, Leona Repnik, Simone Bizzi, Stuart Lane, and Francesco Comiti

Alpine regions are among the areas that are the most intensely impacted by climate change. Predictions of how such changes affect meteorological conditions, as well as snow and ice cover and water discharge in mountain regions, are well established. However, how climate change has affected and will affect sediment transport in general and bedload transport in particular in such environments has yet to be studied.

Bedload transport within Alpine rivers is of ecological importance for river systems, impacts the economic efficiency of hydropower and is a critical parameter in assessing hydrogeological risks. This transport is determined by the sediment supplied to the river and the river's capacity to transport these sediments. These complex processes are closely intertwined with climatological conditions within a catchment, particularly in catchments with substantial glacial coverage. However, predicting how bedload transport behaves due to a changing climate is challenging.

This project fills this knowledge gap and investigates the link between bedload transport and rapid climate change in Alpine environments and aims to predict future trends for the current century. To reach this goal, a wide range of objectives has been set. We work towards providing the first reliable, multi-site quantification of past bedload transport changes under warming conditions, as well as to determine the role of geomorphic processes on bedload export in the analysed river networks. Furthermore, we are working on establishing modelling frameworks to predict subglacial and hillslope sediment supply as well as hydrological discharge to create a bedload transport modelling chain. The modelling chain is based upon the D-CASCADE model, which allows quantifying the spatio-temporal bedload (dis)-connectivity in river networks. Supplying the model with climatological and hydrological predictions enables the estimation of future bedload flux and erosion/deposition patterns under different scenarios. The approach for estimating the evolution of bedload transport will be developed and tested in the Solda (Italy) and Navisence (Switzerland) catchments, due to the data availability of the recent bedload transport history. Once validated and calibrated, the approach will be applied to further selected catchments.

In summary, the project aims to provide a decadal-scale quantification of changes in Alpine bedload transport due to climate warming and predict its evolution in the 21st century. We anticipate an initial increase in sediment transport with increasing glacial melt, driven by climate warming. However, this surge may be temporary as diminishing glaciers reduce their contribution to river discharge after a phase of maximum discharge rates. Beyond the academic value of this research, it will offer critical insights for water resource managers in Alpine regions.

How to cite: Pitscheider, F., Argentin, A.-L., Gianini, M., Repnik, L., Bizzi, S., Lane, S., and Comiti, F.: How will bedload transport respond to climate change in Alpine regions? The "ALTROCLIMA" project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14699, https://doi.org/10.5194/egusphere-egu24-14699, 2024.

EGU24-15047 | Orals | GM4.2

Assessing slope-river connectivity for evaluating cascading landslide hazards: A case study of Tordera river basin, NE Spain. 

Clàudia Abancó, Marta Guinau, Marta González, Jordi Pinyol, and Rosa M Palau

Landslides and torrential flows are among the most dangerous processes that occur on hillslopes, and they are mostly triggered by intense rainfall events. These phenomena are not only hazardous in themselves, but they can also have a more significant impact downstream when they interact with channels or the river network. When multiple landslides are simultaneously triggered by a rainfall event that affects an extensive area, they can initiate chains of further hazards due to the sudden and massive influx of sediment they bring onto channels and rivers. Therefore, it is crucial to study the connectivity between slopes and the river network to evaluate areas with a potentially higher sediment contribution to the river network. Ultimately, this information will help to assess flood hazards and mitigate risks, as well as assist in the planning of protective structures, drainage works, and other relevant measures.

We conducted a study on the slopes of the Tordera River basin (NE Spain). This river flows from the Montseny (Catalan Coastal range)  into the Mediterranean Sea. The study area was affected by a regional landslide event that occurred in January 2020 during the Gloria Storm (more than 480 mm of rainfall was measured in 96 hours in the region). We employed the index of connectivity, which is based on Borselli et al. (2008), to examine the connectivity between the slopes and the river network. The outcomes of this analysis were subsequently compared to a landslide inventory (more than 1000 mass movements) to determine whether the high amount of sediment present in the lowlands could have originated from landslides in the upper part of the basin.

According to the results of this study, slopes with high connectivity experienced a high density of landslides. The sediment that flowed down the slopes and reached the rivers added to the flood that occurred downstream. This flood carried a considerable amount of sediment which caused the widening of the active channel and the growth of the Tordera delta. The impacts of the Gloria storm on the infrastructure caused significant economic losses.

 

Borselli, L.;  Cassi, P.;  Torri, D. Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment, CATENA, Volume 75, Issue 3, 2008, Pages 268-277, ISSN 0341-8162, https://doi.org/10.1016/j.catena.2008.07.006.

How to cite: Abancó, C., Guinau, M., González, M., Pinyol, J., and Palau, R. M.: Assessing slope-river connectivity for evaluating cascading landslide hazards: A case study of Tordera river basin, NE Spain., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15047, https://doi.org/10.5194/egusphere-egu24-15047, 2024.

Under the background of global warming, the risk of geo-hazard in the cryosphere has increased with the retreat of glaciers. Several similar large-scale glacial debris flows with high mobility occurred in the southeast Tibet Plateau during the summer season which has drawn the attention of scientists. One typical event occurred on 10 September 2020 near Namcha Barwa Peak. The initial landslide finally changed into a glacial debris flow with high water content and high mobility under the condition of little precipitation. To solve the questions: 1) why is the glacial debris flow in southwest Tibet more prone in the warm season? 2) How is the initiation mechanism of this glacial debris flow with little rainfall? 3) What is the major source of water for this large debris flow? and 4) Which factors dominate the high mobility characteristic of this debris flow event? By conducting field investigation and comparing the satellite images before and after the event, we have revealed a rock-ice avalanche on the ridge above the landslide area to be contemporary with the event. This finding produced the hypothesis on the initiation process: rock-ice avalanche – moraine deposit failure – glacial debris flow, which has been inferred for many other similar events but not quantitatively proved. To test the hypothesis, we conducted thermal-hydraulic-mechanical coupled numerical modeling with the impact of freeze-thaw cycles and rock-ice avalanche on the stability of the moraine deposit. The results demonstrate that the avalanche event triggered the moraine landslide, with freeze-thaw cycles as the control factor. Generally, long-term freeze-thaw cycles alone are insufficient to set off the hazard chain. At the same time, seasonal temperature variation that controls ice-water phase change dominates the stability of moraine deposits under rock-ice avalanche in different seasons. In warm seasons, rock-ice avalanches would trigger moraine deposit failure more easily due to abundant water content that facilitates pore pressure increase, and liquefaction of moraine. By conducting multi-phase modeling of glacial debris flow, we have proven that the initial water content and entrainment of water during the development of the debris flow are the main water sources of this debris flow event. Moreover, the high water content in the initial landslide together with the entrainment process should also account for the high mobility characteristic of glacial debris flow. This work answered the long-lasting scientific questions about the initiation mechanism and dynamics of hyper-mobility glacial debris flow disaster chain under the background of climate change.

How to cite: Wang, T., Huang, T., and Shen, P.: Unravaling the cascading mechanisms of rock-ice avalanche triggering hyper-mobility glacial debris flow in southeast Tibet, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15190, https://doi.org/10.5194/egusphere-egu24-15190, 2024.

EGU24-16937 | Orals | GM4.2 | Highlight

Cascading Hazards – the challenges to understand interactions 

Margreth Keiler

Cascading hazards come into focus of hazard and risk research in the last 15 years and is strongly connected to studies on multi-hazards and compound hazards. Unexpected cascading events and related casualties and losses of properties draw the attention to consider the possible amplified risks induced by cascading hazards.

The contribution will focus in the first part on key concepts in relation to cascading hazards and will address briefly the challenges which may occur due to the general terminological ambiguity because the term cascading hazards tends to be used interchangeably with multi-hazards, cascading events, cascading disasters, or compound hazards or events. The main focus is on the analyses of different types of interactions which may occur during a cascading hazard events and their dependency on time and space. In the second part, the main question addresses the influence of climate and environmental change on cascading hazards including the occurrence of cascading hazards, changes of types of cascading hazards or interactions within the cascading hazard event. Current challenges regarding the approaches used to analyse and better understand cascading hazards are presented as well as first ideas to answer the questions what is missing, what is needed and how it can be used for hazard and risk analysis/management. 

How to cite: Keiler, M.: Cascading Hazards – the challenges to understand interactions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16937, https://doi.org/10.5194/egusphere-egu24-16937, 2024.

EGU24-17658 | ECS | Posters on site | GM4.2

Addressing the 'Black Hole' amidst Sediment Connectivity and Multi-Hazards 

Ishmam Kabir, Bernhard Gems, Martin Rutzinger, and Margreth Keiler

‘Sediment Connectivity’ and ‘Multi-Hazard’ – two booming topics over the last decade; have experienced intensive methodological and conceptual developments. Research so far has acknowledged their interrelationships and established sediment connectivity as a crucial component in the framework of hazard and risk research, but mostly through the so called ‘single-hazard’ approaches. Sediment connectivity referring to the entire assemblage of connectivity network would by definition occupy a significant amount of space, which may often accommodate multiple interactive and interrelated hazards, making a single-hazard approach fairly inadequate and thus leaving a crucial research gap.

The primary aim of this study is to draw the attention of future research on this gap while attempting to address it through developing a new perspective to look into multi-hazard events. In line of that we propose a semi-quantitative index based on the classification of hazard events and their interactions through an inverse event tree approach – assuming a cascading process flow. The event classification is based on the type of interactions (e.g. process-process, triggering, impeding, structure-process, etc.) to facilitate the understanding and inclusion of the connectivity concept. The index would assess each step and the interlinkages of such cascading events and assign weights to them based on their significance from a sediment connectivity viewpoint. Furthermore, it would also address how these weights may alter the probabilities across the event tree. Overall, this study proposes a novel perspective into the inter-connectedness of geomorphic/sediment connectivity and multi-hazard events, in line with the ‘Gaia’ and ‘Systems’ theories. 

How to cite: Kabir, I., Gems, B., Rutzinger, M., and Keiler, M.: Addressing the 'Black Hole' amidst Sediment Connectivity and Multi-Hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17658, https://doi.org/10.5194/egusphere-egu24-17658, 2024.

EGU24-18379 | Orals | GM4.2

Quantifying surface process dynamics during extreme events from storm characteristics and landslide inventories 

Marin Clark, Ries Plescher, Madeline Hille, Christoff Anderman, Chan-Mao Chen, Deepak Chamlagain, Dimitrios Zekkos, and A. Joshua West

Extreme precipitation events drive landsliding in many regions across the globe and are an important part of the erosional cycle and related hazards. The intensity and frequency of extreme events are likely increasing due to rising global temperatures, causing greater future threat to society and an urgent need to quantify the relationships between surface process dynamics and extreme events. In steep mountain belts, orography also plays a role in focusing precipitation and intensifying erosion. Yet, the influence of orography on the intensity-duration characteristics of extreme precipitation remains a subject of debate because we lack spatially distributed and high time-resolution gauge datasets needed to resolve convective-scale, short-duration storm events and satellite-derived precipitation products struggle to accurately resolve precipitation gradients over areas of high relief and altitude. Annual periods of monsoon-related landsliding in the Himalaya offer a natural laboratory in which to explore relationships between extreme precipitation, orography and landsliding processes. Here we scale the NASA’s Global Precipitation Measurement (GPM) IMERG 30-minute, 0.1x0.1 degree product with local rain gauge data to produce high-temporal resolution records used to characterize extreme rainfall events (EREs) in central Nepal where hundreds of shallow landslides occur each summer. Individual storms from the time series are defined using the average inter-accumulation time as a measure for the minimum dry period between storms and extreme storms are extracted from the series using a 90th percentile threshold for each gauge station. Variability in storm characteristics is defined using paired K-means agglomerative cluster and principal component analyses to evaluate spatial patterns in storm characteristics over a 10 year period compared to annual landslide inventories. Spatial patterns emerge that suggest orography increases the intensity and frequency of storms, which in turn focuses landsliding in specific, and potentially predictable, regions along the steep windward flank of the mountain belt.

How to cite: Clark, M., Plescher, R., Hille, M., Anderman, C., Chen, C.-M., Chamlagain, D., Zekkos, D., and West, A. J.: Quantifying surface process dynamics during extreme events from storm characteristics and landslide inventories, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18379, https://doi.org/10.5194/egusphere-egu24-18379, 2024.

EGU24-18653 | ECS | Posters on site | GM4.2

Seven decades of debris flow activity. Spatio-temporal observations at connected and disconnected debris flow fans to the Lake Plansee (AT). 

Natalie Barbosa, Carolin Kiefer, Juilson Jubanski, and Michael Krautblatter

Debris flow activity at Lake Plansee, Austria, is evident through numerous debris cones continuously transferring sediment to the lake. Lacustrine sediment records of fan deltas were used to analyze the debris flow activity since 2120 BCE with Kiefer et al. (2021) identifying a drastic increase in debris flow activity since 1920. Furthermore, the photointerpretation of historical aerial imagery combined with modeling of debris flow volumes at the northern slope of Lake Plansee since 1947 suggests an increased trend since the 1980s (Dietrich et al., 2016). Despite the lithological and climatic similarities between the slopes that surround Lake Plansee, debris cones at the northern slope are primarily connected to the lake, while those on the southern slope remain highly active but disconnected.

This contribution aims to advance our understanding of spatio-temporal dynamics on debris flow fans and factors influencing sediment connectivity to the lake. We revise the historical aerial imagery since 1952 to automatically detect ‚active‘ debris channels using image processing and derive time series of photogrammetric Digital Surface Models (DSMs) for change detection.We identified 34 debris catchments with debris flow activity since 1952. Our objectives include (i) analysis of the spatio-temporal patterns of erosion and deposition at each fan to trace their evolution, (ii) quantifying sediment transfer rates from connected fans to lake Plansee in the last 70 years, (iii) identifying the role of vegetation changes in debris fan evolution and (iii) refining our understanding of precipitation and temperature as controlling factors influencing debris flow activity and connectivity or dis-connectivity of active debris channels to lake Plansee. The presented results intend to comprehend the intricate patterns that lead to debris flow exhaustion and increased or decreased activity.

 

Dietrich, A., & Krautblatter, M. (2017). Evidence for enhanced debris-flow activity in the Northern Calcareous Alps since the 1980s (Plansee, Austria). Geomorphology, 287, 144-158.

Kiefer, C., Oswald, P., Moernaut, J., Fabbri, S. C., Mayr, C., Strasser, M., & Krautblatter, M. (2021). A 4000-year debris flow record based on amphibious investigations of fan delta activity in Plansee (Austria, Eastern Alps). Earth Surface Dynamics, 9(6), 1481-1503.

How to cite: Barbosa, N., Kiefer, C., Jubanski, J., and Krautblatter, M.: Seven decades of debris flow activity. Spatio-temporal observations at connected and disconnected debris flow fans to the Lake Plansee (AT)., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18653, https://doi.org/10.5194/egusphere-egu24-18653, 2024.

EGU24-19175 | Orals | GM4.2

Non-uniqueness in sediment transport in river network hydrology-sediment modelling 

Peter Molnar, Sascha Meierhans, Giulia Battista, Jacob Hirschberg, Jessica Droujko, and Scott Sinclair

Sediment cascades are a convenient way of conceptualizing the transfer of sediment from hillslope production areas, through the river network, to the river basin outlet. Distributed hydrology-sediment models play an important role in the prediction of these source-to-sink links, because they can explicitly connect water and sediment fluxes along topographically-driven pathways. Here, we provide some examples of such cascade-based hydrology-sediment model applications in alpine environments and some problems related to their use.

In particular, we highlight two critical problems with hydrology-sediment modelling that go beyond trivial model calibration difficulties. These address fundamental issues of (a) non-uniqueness in sediment source mixing, and (b) sediment supply limitations. The first problem of non-uniqueness is known in hydrological modelling as the curse when models perform well at basin outlets for the wrong reasons, misrepresenting hydrological processes within the basin. In geomorphology, this concept has not received the same level of attention. Here we show that even a calibrated physically-distributed hydrology-sediment model can be subject to non-uniqueness, and provide the same suspended sediment yields at the basin outlet with completely different combinations of sediment sources. Including sediment tracers in model validation helps to identify this problem, and it is also helpful to check simulations at sub-basin scales where we are closer to distinct sediment sources. The second problem of sediment supply limitations is a challenge for all models that rely on transport capacity formulas for sediment transport. In our experience, both supply and transport capacity limit sediment transport at the basin scale, and we need to include this in our models. For example, we show that supply limitations can completely change the seasonality of sediment yields and render many climate change impact studies worthless.

Finally, we argue that both problems above, at least for suspended load, can be partially addressed by novel monitoring. For example by low cost smart sensors that allow a distributed sensing of sediment fluxes above and below potential sediment sources at high resolutions, or by high resolution remote sensing to capture space-time variability in river turbidity. This kind of data can dramatically improve our ability to calibrate models, reduce non-uniqueness, and over the long term identify the key signatures of sediment supply in river systems. It is our opinion that improving the predictions of climate and environmental change effects on sediment yields requires both better model validation as well as new data.

How to cite: Molnar, P., Meierhans, S., Battista, G., Hirschberg, J., Droujko, J., and Sinclair, S.: Non-uniqueness in sediment transport in river network hydrology-sediment modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19175, https://doi.org/10.5194/egusphere-egu24-19175, 2024.

EGU24-19438 | ECS | Posters on site | GM4.2

Post-event forensic survey after a recent catastrophic flash flood in Central Spain: morphosedimentary and hydrodynamic reconstruction 

K. Patricia Sandoval-Rincón, Julio Garrote, Daniel Vázquez-Tarrío, Ana Lucía, Mario Hernández-Ruiz, María Ángeles Perucha, Amalia Romero, José Ortega, and Andrés Díez-Herrero

Catastrophic flash floods are among the deadliest and most damaging natural processes worldwide. Despite this, they are rarely well recorded in instrumental (e.g. rain gauges, gauging stations) and documentary records (archives and newspaper archives). For their analysis and future prevention, it is therefore essential to carry out post-event forensic studies to collect as much information as possible in the field, from which the morphodynamic, hydrological and hydraulic characteristics of these events can be reconstructed.

In early September 2023, an exceptional ‘cut-off low’ weather situation (DANA) crossed the centre of the Iberian Peninsula, causing heavy rainfall and flash floods in several river basins (Alberche, Perales, Grande, Guadarrama). There were seven deaths and hundreds of millions of euros of damage to property and infrastructure.

This work summarises all the post-event forensic analyses and field observations collected after this episode along the Grande-Perales-Alberche river system, consisting of: (i) documentation of the historical morphological changes of these rivers, obtained from old cartographies, geomorphological maps, aerial photographs and recent orthoimages; (ii) compilation of all meteorological (rainfall) and hydrological (flow) information available for the event; (iii) acquisition of aerial images and video recordings using drones; iv) field georeferencing with differential GPS of high water marks (HWM) and paleo-stage indicators (PSI); v) field topographic measurements; vi) detailed measurement of bedform parameters such as wavelength and amplitude of current ripples; vii) grain size and composition sampling of flood deposits.

With all this information and other still being collected (such as orthophotographs and post-event DEMs generated by digital photogrammetry techniques based on images taken by drones), detailed digital elevation models are obtained. All this information will be used as calibration and validation information for 2D hydrodynamic and landscape evolution numerical models that attempt to reproduce and predict this type of event in the study rivers.

How to cite: Sandoval-Rincón, K. P., Garrote, J., Vázquez-Tarrío, D., Lucía, A., Hernández-Ruiz, M., Perucha, M. Á., Romero, A., Ortega, J., and Díez-Herrero, A.: Post-event forensic survey after a recent catastrophic flash flood in Central Spain: morphosedimentary and hydrodynamic reconstruction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19438, https://doi.org/10.5194/egusphere-egu24-19438, 2024.

EGU24-20877 | ECS | Posters on site | GM4.2

Snow preparation in landslide scenarios under multi-hazard perspective: experiences from Lake Campotosto (Italy) 

Matteo Ferrarotti, Maria Elena Di Renzo, Gian Marco Marmoni, Carlo Esposito, and Salvatore Martino

Landslides are a natural land-forming process and their interaction with urbanized areas and infrastructures makes them one of the most common geo-hazards. Landslides are controlled by three macro-categories of factors, namely the “predisposing”, “preparatory”, and “triggering” ones. In particular, preparatory factors are time-changing and gradually reduce the slope stability without initiating the movement. Snow melting and accumulation are generally discussed in the literature as triggering factors of landslides, particularly shallow ones, although, the here presented approach focuses on their contribution as preparatory factors. In mountainous areas, snow loading and, especially, snow melting can increase the soil pore water pressure, causing a reduction of available strength. Their influence on soil stability is time-dependent and, in particular, changes cyclically throughout the year. Snow usually begins to fall in the late autumn and accumulates especially in winter, whereas in spring it melts, resulting in water infiltration into the soil and resistance reduction. In seismic areas, where earthquakes can act as triggers for shallow landslides, seismic action might discover different levels of soil weakness throughout the year depending on the season, resulting in distinct landslide scenarios.

This research illustrates some multi-hazard scenarios that consider earthquakes as triggering factor of landslides, varying the degree of saturation of soil covers. The case study is the area around Lake Campotosto (Italy), located in one of the Apennines areas with the highest amount of snowfall per year, is in the near fault sector of one of the most important seismogenic source of the Apennines (Mt. Gorzano Fault System) and is characterized by different sizes and mechanisms landslides.

The approach applied for generating landslide scenarios is the PARSIFAL (Probabilistic Approach for Rating Seismically Induced slope FAiLures), a probabilistic multi-hazard tool that includes a three steps procedure: 1) susceptibility analysis including differentiated approach for rock and earth failure mechanisms; 2) slope stability analysis; 3) synthetic mapping of generated scenarios, based on grid or slope units.

Preliminary research on the stability of soil covers under seismic conditions emphasizes importance of hydraulic conditions during earthquake, which also suggests the relevance of snow loading and, in particular, snow melting in regulating slope stability.

Further research is being done utilizing satellite and meteorological data, and geomorphological features, and then elaborating them using statistical and geostatistical tools, up to advanced computing.

The goal is to generate time-dependent landslide hazard scenarios by weighting the effects of snow precipitation throughout the year as a preparatory factor and adding a related tool to PARSIFAL.

The majority of these concepts are being studied at Sapienza's Department of Earth Sciences in the CN1 (National Centre for HPC, Big Data, and Quantum Computing) – Spoke5 PNRR Linea Tematica 1 (Reconstruction of multi-hazard scenarios from seismic source models to the simulation of seismic-induced instabilities), which aims at generating ground effects scenarios in terms of instabilities induced by nonlinear effects produced by the propagation of seismic waves from the seismogenic source to the surface, also considering geomorphological and geotechnical characteristics of the near subsurface.

How to cite: Ferrarotti, M., Di Renzo, M. E., Marmoni, G. M., Esposito, C., and Martino, S.: Snow preparation in landslide scenarios under multi-hazard perspective: experiences from Lake Campotosto (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20877, https://doi.org/10.5194/egusphere-egu24-20877, 2024.

Torrential risk protection works have a long tradition in the Alps, where these measures have allowed more intensive use of the landscape since the twentieth century and form the basis for rational management of the risk of torrential floods. While the maintenance and management of protective works makes it possible to control their inevitable deterioration and to extend their life, the collapse of these systems should be always considered in the frame of the residual risk management. This work aims to i) analyse the catastrophic debris flow occurred on October 2018 in the Rotian river basin (Eastern Italian Alps) during which a series of check dams collapsed magnifying the event and causing a casualty and severe damages, and ii) to identify implications for hazard monitoring and management. The work is based on post-event investigations, witness accounts, remote sensing information and local station data, hydrogeomorphic data and models, and systematically analyses the geo-environment, climate conditions and check dam structural conditions which characterized the geohazard cascade of events. In particular, results from the application of a couple hydrological and hydraulic model for the triggering and propagation of the debris flows event are used to inform the analysis. The results from this work are exploited to inform a discussion about the future of these works, which concerns not only the structural and maintenance aspects of the single work, but also involves the risk management requests of the systems of works which in recent decades have evolved significantly.

How to cite: Marchi, L., Borga, M., Zugliani, D., and Rosatti, G.: Geohazard cascade and mechanism of large debris flows in the Rotian river basin (NE Italy): implications to hazard monitoring and management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21166, https://doi.org/10.5194/egusphere-egu24-21166, 2024.

EGU24-1297 | Posters on site | HS4.5 | Highlight

Better weather forecasts = better human health? Yes, with TRIGGER(s) 

Claudia Di Napoli and Fredrik Wetterhall

As the impacts of climate change on human health become increasingly evident, so does the need for a systemic and interdisciplinary understanding on the climate-health connection. Achieving such an understanding is key to the development of effective and rational adaptation plans, including those involving the creation of weather forecasts-driven systems that can increase the preparedness and response to health hazards.

To address this shortcoming, the Horizon Europe project TRIGGER (SoluTions foR mItiGatinG climate-induced hEalth thReats) aims to generate and disseminate information about upcoming conditions detrimental to human health, such as heatwaves and cold spells, via an innovative prototype that integrates state-of-the-art climate and weather indicators with personal exposure monitoring data.

We here present the TRIGGER prototype with a focus on the hydrometeorological prediction system that is tasked to forecasts health-impacting climate variables and indicators on temporal scales ranging from the short-range (hours) to sub-seasonal lead-time. Using a co-design approach involving medical doctors and epidemiologists, we describe how the system utilizes the ECMWF forecasts, provides probabilistic predictions for the near future, and enables the assessment of the associated uncertainty.

How to cite: Di Napoli, C. and Wetterhall, F.: Better weather forecasts = better human health? Yes, with TRIGGER(s), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1297, https://doi.org/10.5194/egusphere-egu24-1297, 2024.

EGU24-3809 | ECS | Posters on site | HS4.5 | Highlight

MeteoAlarm – Towards Tomorrow’s Warnings 

Johannes Fleisch and Giora Gershtein

MeteoAlarm serves as a central and comprehensive one-stop shop for hydrometeorological warnings across 38 European countries. Designed to provide critical awareness information for preparing and responding to hazardous weather events, MeteoAlarm consolidates warnings from National Meteorological and Hydrological Services (NMHSs) on a unified platform, aggregating and making them readily accessible through the MeteoAlarm Visualisation and Feeds.

The platform's primary objective is to present the current awareness situation coherently, ensuring a consistent interpretation throughout Europe in an easily comprehensible manner. This is achieved by using a simple three-colour code (yellow, orange, and red) and by providing impact scenarios and advisories to the general public. This approach enables individuals to stay informed about the latest warnings, take necessary precautions, and minimise risks associated with hazardous weather conditions, supporting decision-makers on the European level, such as the Emergency Response Coordination Centre (ERCC) of the European Commission. Essential to MeteoAlarm's success are its redistributors, such as AccuWeather, Apple, Google, or IBM/The Weather Company, fundamental in disseminating warnings to hundreds of millions of end-users.

MeteoAlarm actively engages in the RODEO project, a collaborative effort involving eleven European NMHSs, ECMWF, and EUMETNET. This initiative spans from 2023 to 2025 and aims to develop a Federated European Meteo-hydrological Data Infrastructure (FEMDI). The realisation of FEMDI includes the creation of a user interface and Application Programming Interfaces (APIs) designed for accessing meteorological datasets designated as High-Value Datasets under the EU Open Data Directive. Within this project, MeteoAlarm focuses on enhancing the accessibility and usability of its warnings. The goal is to ensure warnings remain reliable, of high quality, and standardised across diverse regions and countries. The development of APIs not only facilitates machine-readable data but also enables near-real-time access through bulk downloads and cross-border querying, seamlessly integrated with the existing MeteoAlarm Service. In parallel, efforts concentrate on improving the quality and harmonisation of warnings, achieved through collaborations with data providers, redistributors, and international frameworks related to the Common Alerting Protocol (CAP).

Looking ahead, MeteoAlarm prioritises key initiatives to maintain its prominent role in weather warning services. A central focus is the shift towards an impact-based multi-hazard approach, aligned with the WMO-led initiative, Early Warnings for All (EW4All). This goes hand in hand with the aim to advance the MeteoAlarm CAP Profile, emphasising adaptability for diverse weather events. The establishment of an Impact-based Warning (IbW) Working Group and the extension of early warnings beyond the current two-day limit are short-term objectives, supporting MeteoAlarm's overarching vision. Strengthening collaboration with redistributors and enhancing knowledge sharing and communication between MeteoAlarm Members collectively reinforces resilience, adaptability, and engagement within the meteorological community.

The anticipated impact of MeteoAlarm’s efforts will enhance the ability of individuals and organisations to engage in more efficient disaster preparedness and response at both national and international levels, ensuring a safer and more resilient future for all.

How to cite: Fleisch, J. and Gershtein, G.: MeteoAlarm – Towards Tomorrow’s Warnings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3809, https://doi.org/10.5194/egusphere-egu24-3809, 2024.

EGU24-5309 | Orals | HS4.5 | Highlight

Africa Multi-Hazard Early Warning and Early Action System for Strengthening Resilience to Natural Hazards  

Andrea Libertino, Lorenzo Alfieri, Laura Poletti, Nicola Testa, Alessandro Masoero, Simone Gabellani, Marco Massabò, Jully Ouma, Ahmed Amdihun, Godefroid Nshimirimana, John Mathias KiriwaiJ, Lusajo Ambukeje, Luca Rossi, Katarina Mouakkid Soltesova, and Huw Beynon

The Africa Multi-Hazard Early Warning and Action System for Disaster Risk Reduction (AMHEWAS for DRR) is a joint effort, led by the African Union Commission (AUC) in coordination with Regional Economic Communities and Member States and with the technical and scientific support of UNDRR and CIMA Foundation, aimed at strengthening Africa's resilience to natural hazards. This comprehensive system encompasses a multi-scale approach, spanning from continental to regional and national levels, to enhance early warning capabilities and promote effective disaster risk management strategies. 

On the continental scale, AMHEWAS operates through a network of Situation Rooms. These interconnected hubs facilitate real-time information exchange, coordination of response efforts, and dissemination of advisories on potential threads and related impacts to national institutions. To ensure standardized operational procedures across the continent, AMHEWAS has established unified standard operating procedures, ensuring consistent application protocols and methodologies. 

Central to AMHEWAS' approach is the Continental Watch (CW), an impact-based forecast bulletin for rain, wind and flood hazards, that synthesizes insights from automated impact-based forecast systems. The CW provides timely and actionable information to decision-makers across the continent, enabling proactive measures to mitigate potential disaster impacts. Ongoing disasters can trigger Disaster Situation Reports (DSRs), co-produced by the AUC with the affected Regional Economic Communities (RECs) and the national AMHEWAS stakeholders, for informing disaster risk reduction (DRR) efforts and ensuring timely and appropriate responses to emergencies.  

AMHEWAS integrates risk data and forecasting products from global and regional authoritative sources to produce advisories as a combination of hazards, exposure, vulnerability and national copying capacity. Based on the possible expected impacts in the next 5 days, advisories are issued with a threshold-based mechanism with 4 levels of activation of the system. High level is related with the potential of the estimated impacts to overcome the capacity of the countries, while for lower advisories the effects are expected to be managed by national or subnational authorities. The potential impacts are estimated with an innovative automatic approach, that involves the overlap of the forecasted hazards, with layers of exposed elements, taking into consideration the lack of copying capacity derived from the INFORM database. 

In order to maximize the robustness of the forecasts AMHEWAS adopts a multimodel approach. As regards wind and rain, the forecast is carried out considering the combination of different meteorological global models. As regards flood, the reference model is GLOFAS, combined for the Great Horn of Africa region with the results of the impact-based flood forecast system FloodPROOFS East Africa (FPEA). FPEA is an operational system based on open-source technologies that employs an impact-based approach, integrating weather forecasting, hydrology and hydraulic modeling, as well as risk assessment to provide accurate and actionable flood forecasts up to five days in advance. Given its cross-border nature, the system allows for a comprehensive approach to large-scale hydrological assessment, easily scalable in an operational framework on a national scale. 

AMHEWAS is working on further integration of regional forecasting products from WMO specialized centers and national level, in order to improve the risk knowledge and information products generated.

How to cite: Libertino, A., Alfieri, L., Poletti, L., Testa, N., Masoero, A., Gabellani, S., Massabò, M., Ouma, J., Amdihun, A., Nshimirimana, G., KiriwaiJ, J. M., Ambukeje, L., Rossi, L., Mouakkid Soltesova, K., and Beynon, H.: Africa Multi-Hazard Early Warning and Early Action System for Strengthening Resilience to Natural Hazards , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5309, https://doi.org/10.5194/egusphere-egu24-5309, 2024.

Effective management and communication of earthquake risks is crucial for enhancing societal preparedness and resilience. This study investigates earthquake management strategies using Multi-Criteria Decision-Making (MCDM), specifically the Analytic Hierarchy Process (AHP). The focal earthquake event driving this investigation occurred on September 8, 2023, at 11:11 PM local time. With a magnitude of 6.8, the seismic incident had its epicenter approximately 72 km southwest of Marrakech within the Al Haouz province.
A comprehensive assessment is conducted on ten distinct earthquake management strategies in Morocco. These encompass building codes and construction standards (S1), early warning systems (S2), public education and awareness (S3), land use planning (S4), emergency response plans (S5), international cooperation (S6), research and monitoring (S7), infrastructure resilience (S8), community preparedness (S9), and insurance and financial preparedness (S10). The evaluation involves a thorough examination against a set of criteria encompassing aspects such as effectiveness in risk reduction (C1), cost-effectiveness (C2), inclusivity and social equity (C3), adaptability and flexibility (C4), environmental impact (C5), compliance with standards and insurance uptake (C6), interagency collaboration (C7), and data utilization (C8).
The resulting criteria weights underscore their relative importance, with C1 deemed highly significant (30%), C2 and C3 moderately important (20% and 15%, respectively), and C4, C5, C6, C7, and C8 holding lesser significance (ranging from 10% to 5%).
Performance scores are assigned to rank the earthquake management strategies, revealing that A2 attains the highest score (0.45), followed by A4 (0.43), A10 (0.42), A9 (0.41), A3 (0.4), A8 (0.39), A7 (0.38), A6 (0.37), and A5 (0.35). A1 achieves a moderate score (0.32), providing valuable insights for decision-making in earthquake risk reduction.
This research underscores the pivotal role of early warning systems in earthquake management, emphasizing the significance of timely alerts, community engagement, and financial preparedness within Morocco's comprehensive risk reduction strategy. The study advocates for data-driven decision-making to enhance preparedness, response capabilities, and mitigation measures. Moreover, this research holds implications for recent seismic events, such as the magnitude 7.6 earthquake in Japan on January 1, 2024.

How to cite: Bouramdane, A.-A.: Morocco’s Earthquake Risk Management: A Multi-Criteria Decision-Making Approach and Implications for the Recent Japan Earthquake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6158, https://doi.org/10.5194/egusphere-egu24-6158, 2024.

EGU24-9073 | ECS | Posters on site | HS4.5

Bridging gaps, saving lives: Integrating communities’ voices in advancing flood early warning system in developing countries  

Anup Shrestha, Anise McCrone, Josias Láng-Ritter, Maija Taka, and Olli Varis

Safeguarding lives and properties during major disasters, such as floods, relies on timely and comprehensive communication and dissemination of early warning information. According to UNDRR, an effective Early Warning System (EWS) consists of four pillars: risk knowledge, monitoring and warning services, dissemination and communication and response capability. It is crucial to assess the operational status of EWS, particularly in vulnerable rural areas of developing countries, where technical EWS capacity as well as residents' awareness, understanding of messages, and taking appropriate actions may be hindered by multifaceted factors such as communication of complex forecast information and their pathways, lack of sufficient monitoring stations, low literacy, geographical challenges, and other socio-economic factors.  

The present study focuses on advancing knowledge on the challenges in implementing the four pillars of flood EWS from the perspective of vulnerable communities for planning necessary interventions to enhance flood resilience. We conducted community surveys, key informant interviews, and reviewed publicly available information in the flood prone West Rapti Basin of Nepal. Further, we applied statistical tests to analyze the community surveys and examined the key informant interviews through thematic analysis based on the four EWS pillars. Finally, we assessed the potential economic impacts across various flooding scenarios to integrate early actions in EWS for saving lives and properties. 

Our study reveals that most of the local population face difficulties interpreting associated risks when they are communicated with risk maps. However, the understanding of early warning and reception of SMS alerts varies strongly among rural municipalities due to language, literacy status, and mobile network problems. The community’s interest to participate in warning process and to help in warning others suggests the importance of a community-centric approach and feedback mechanism to the existing top-down approach of EWS. The study also highlights the potential of impact-based risk maps integrated with the findings of community surveys and key informant interviews to plan early actions for informed decision making. 

The potential improvements of EWS include upgradation of warning information dissemination, participatory early warning process, development of protocols for early actions and response mechanism, warning production based on impact-based forecast, improving technical capabilities for monitoring hazards, and creating community-level database to record the post flood impacts and community feedback to validate warning and impact-based forecasts. Our study contributes to strengthening EWS through impact-based quantitative risk analysis which is implementable worldwide. Future research is called for on how to develop the impact-based forecasting chain for different future scenarios and incorporate citizen science to improve this process.

How to cite: Shrestha, A., McCrone, A., Láng-Ritter, J., Taka, M., and Varis, O.: Bridging gaps, saving lives: Integrating communities’ voices in advancing flood early warning system in developing countries , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9073, https://doi.org/10.5194/egusphere-egu24-9073, 2024.

EGU24-10635 | ECS | Posters on site | HS4.5

Heavy-rain Forecasting with the Application of High-density Swarm Network of Optical Rain Sensors and Artificial Intelligence. 

Nibesh Shrestha, Alexander Buddrick, Benjamin Mewes, and Henning Oppel

Heavy rainfall, a prominent consequence of climate change, induces substantial pluvial flooding as the urban drainage systems fail to deal with the water surge. The risks intensify with the cloud-burst rain on a catchment area without any gauge. Especially in topographically complex watersheds, the limitations associated with conventional precipitation monitoring tend to exacerbate. These heavy-rain events, if undetected, pose severe threats, causing extensive damage to the settlements and industries without timely warning.

With a motive to bridge this gap, we present the exemplary development of a cutting-edge AI-supported early warning system and cell detection (now-casting) of heavy rainfall events. Utilizing an IoT-based optical method, we record qualitative rainfall intensity data with a high-density swarm network of rainfall sensors spread across the target region. These data can be immediately used to forecast the path of the rain with the physical optical-flow method. Furthermore, these data are used to train the AI, generating heavy rain forecasts up to 60 minutes before the rain reaches points of interest. This lead time is crucial for citizens and rescue forces to reduce the chaos phase and prepare themselves on time even before the heavy rain cells reach their location and create havoc.

The innovative optical rainfall sensors have been installed and tested in Liederbach am Taunus since the summer of 2022, demonstrating their efficacy and accuracy during the August 2023 heavy rainfall storm event. The system adeptly captured heavy rainfall data, showcasing great potential for early warnings when implemented at a full scale alongside AI applications.

How to cite: Shrestha, N., Buddrick, A., Mewes, B., and Oppel, H.: Heavy-rain Forecasting with the Application of High-density Swarm Network of Optical Rain Sensors and Artificial Intelligence., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10635, https://doi.org/10.5194/egusphere-egu24-10635, 2024.

EGU24-11042 | Posters on site | HS4.5

Impact-based forecasting for human displacement by tropical cyclones to support anticipatory humanitarian action 

Pui Man Kam, Fabio Ciccone, Chahan M. Kropf, Lukas Riedel, Christopher Fairless, and David N. Bresch

Tropical cyclones (TCs) displace the second-largest number of people each year among all natural hazards, following floods.  While TCs impose hardships and threaten lives, the negative impacts can be mitigated through anticipatory action such as evacuation, emergency protection, and humanitarian aid coordination. An impact-based forecast can support anticipatory action planning by providing detailed information about the numbers and locations of people at risk of displacement.

Here we introduce the first implementation of a globally consistent and regionally calibrated TC-related displacement forecast that combines the (1) TC weather forecast with (2) the spatially explicit representation of population distribution and (3) their vulnerability. Furthermore, we emphasise the importance of incorporating uncertainties from all three components in a global uncertainty analysis to reveal the full range of possible outcomes. Additionally, sensitivity analysis can help us helps us understand how the forecast outcomes depend on uncertain inputs.

We demonstrate the TC displacement forecast through a case study of storm Yasa in the Fidji in 2020. Additionally, we conduct a global uncertainty and sensitivity analysis for all recorded TC displacement events from 2017 to 2020. Our findings suggest that for longer forecast lead times, decision-making should focus more on meteorological uncertainty, while greater emphasis should be placed on the vulnerability of the local community shortly before TC landfall. The open-source code and implementations are also readily transferable to other hazards and impact types.

How to cite: Kam, P. M., Ciccone, F., Kropf, C. M., Riedel, L., Fairless, C., and Bresch, D. N.: Impact-based forecasting for human displacement by tropical cyclones to support anticipatory humanitarian action, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11042, https://doi.org/10.5194/egusphere-egu24-11042, 2024.

EGU24-11496 | ECS | Orals | HS4.5

Sub-seasonal prediction of heat-related mortality in Switzerland 

Daniela I.V. Domeisen, Maria Pyrina, Dominik Büeler, Ana M. Vicedo-Cabrera, Sidharth Sivaraj, Adel Imamovic, Christoph Spirig, and Lionel Moret

Heatwaves have various impacts on human health, including an increase in premature mortality. The summers of 2018 and 2022 are two prominent examples with record-breaking temperatures leading to thousands of excess deaths in Europe. Nevertheless, there is a limited assessment of the potential for heat-health warning systems on timescales up to several weeks ahead at a regional level. This study combines methods of climate epidemiology and sub-seasonal forecasting to predict the expected heat-related mortality for two regions in Switzerland during the summers of 2018 and 2022. The sub-seasonal forecasts were first downscaled to a 2km-by-2km grid using a quantile mapping approach. The statistical heat-mortality relationship for the Swiss cantons of Zurich and Geneva between 1990 and 2017 was estimated in a two-stage time-series analysis using observed daily temperature and mortality. Then, heat-related mortality in the summers of 2018 and 2022 was calculated using the estimated heat-mortality relationship and the observed total mortality and temperature. The resulting estimated heat-related mortality was subsequently compared with the predicted heat-related mortality based on sub-seasonal temperature forecasts. Preliminary results show that we can successfully predict short-term heat-related mortality peaks for lead times up to 2 weeks, while longer periods of heat-related mortality can be anticipated by lead week 3 and even lead week 4 forecasts. Our findings demonstrate that sub-seasonal forecasts can be a valuable tool for estimating and potentially issuing warnings for the excess health burden observed during central European summers.

How to cite: Domeisen, D. I. V., Pyrina, M., Büeler, D., Vicedo-Cabrera, A. M., Sivaraj, S., Imamovic, A., Spirig, C., and Moret, L.: Sub-seasonal prediction of heat-related mortality in Switzerland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11496, https://doi.org/10.5194/egusphere-egu24-11496, 2024.

EGU24-11868 | ECS | Orals | HS4.5

Post-processing seasonal meteorological forecasts with artificial intelligence 

Dariana Isamel Avila-Velasquez, Hector Macian-Sorribes, and Manuel Pulido-Velazquez

Raw meteorological forecasts from global meteorological models are always biased and require post-processing to tailor them to the regional and local climatic features before they can be used for other applications.  However, this might be challenging depending on the features and the meteorological variable considered. This contribution applies and evaluates the use of an artificial intelligence (AI) technique, fuzzy logic (FL), to post-processing meteorological seasonal forecasts, comparing its performance in terms of improved forecasting skills with other post-processing techniques for different forecasting systems and variables. The analysis is applied to the Jucar basins River Basin (Eastern Spain), which are characterized by extreme meteorological events (heavy rains, droughts, heatwaves).

For this area, six daily-scale seasonal forecasting systems from the Copernicus Climate Change Service (C3S) and six variables (precipitation; minimum, mean and maximum temperature; solar radiation and wind speed) are considered. ERA5 is used as reference dataset for post-processing, and daily data for the period 1995-2014 is employed to perform the comparison. The evaluation of the performance of AI is done by comparing the skill of AI-based post-processed forecasts with two common post-processing algorithms: linear scaling (LS) and quantile mapping (QM). The algorithms for all three post-processing methods are coded in a Python script. For each system, variable and post-processing alternative, the forecasting skill is measured using the Continuous Range Probability Skill Score (CRPSS).

Results show that, with the exception of precipitation, the relative performance of thes methods does not depend on the forecasting system but on the variable considered. FL dominates in maximum and minimum temperature and linear scaling in average temperature, wind speed, and solar radiation. However, LS shows the worst performance in maximum and minimum temperatures, while FL never yields the lowest skill. For precipitation, the ranking between methods depends on the forecasting system. According to the results, FL logic provides robust, skillful post-processing across variables, providing adequate performance for all variables and forecasting systems, while the rest of the methods show a wider spread of performance, from poor to the best.

Acknowledgments: This research has been supported by the University Teacher Training (FPU) grant from the Ministry of Universities of Spain (FPU20/0749); the project “INtegrated FORecasting System for Water and the Environment (WATER4CAST)”, funded by the Valencian Government through the Program for the promotion of scientific research, technological development and innovation in the Valencian Community for research groups of excellence, PROMETEO 2021 (ref: PROMETEO/2021/074); and "THE HUT project” (The Human-Tech Nexus– Building a Safe Haven to cope with Climate Extremes), under the European Union’s horizon research and innovation programme (GA No. 101073957) 

How to cite: Avila-Velasquez, D. I., Macian-Sorribes, H., and Pulido-Velazquez, M.: Post-processing seasonal meteorological forecasts with artificial intelligence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11868, https://doi.org/10.5194/egusphere-egu24-11868, 2024.

EGU24-12075 | Orals | HS4.5

Protocol for an end-to-end evaluation of operational warning systems 

Michele Calvello, Guido Rianna, and Brian Golding

The contribution addresses, from a conceptual point of view, the complex issue of evaluating the performance of warning systems that are operating over large areas to cope with the risk posed by extreme weather events. In the protocol, the performance of the systems is evaluated, at each step in the warning production process, considering the “warning value chain” schematization developed in the HIWeather project of the World Meteorological Organization (http://hiweather.net/Lists/130.html). In a perfect warning chain, the warning received by the end user would contain precise and accurate information that perfectly met their need, contributed by each of the many players in the chain; in real warning chains, information, and hence value, are always lost as well as gained at each link in the chain (Golding 2022, https://link.springer.com/book/10.1007/978-3-030-98989-7).

The protocol is structured as a three-part evaluation process: 1) description of the system; 2) assessment of criticalities during high impact events; 3) routine assessment of daily operations. For each part, the protocol prescribes a set of must-do. The description of the warning system must be based on the schematic subdivision of the warning value chain, i.e., six main capabilities and outputs and five information exchanges elements. An important focus on the evaluation of an operational warning system must be devoted to high impact events. For such cases, the evaluation must include: essential information on the event; information on how each element of the warning value chain has been working during the event; synthetic assessment on the performance of the warning system. Finally, the routine assessment must include: identification of the system’s operational elements; identification of the areas covered by the system; identification of period for which to conduct the assessment and sources of data to be used; identification of appropriate and computable (considering the available data) performance indicators for the different elements of the warning value chain; analysis of relevant data for the chosen time period in the identified areas; evaluation of the performance of the different elements of the waring value chain; final judgment on the overall performance of the system.

This study is being carried out within the Horizon Europe project “The HuT: The Human-Tech Nexus - Building a Safe Haven to cope with Climate Extremes” (https://thehut-nexus.eu/). The protocol has been developed considering two cases studies, and will be further put to test during the remaining part of the project. Through this action, detailed information from many different warning systems will be collected and used for a comparative study between warning systems operating, in different areas of the world, for different weather and climate related risks.

How to cite: Calvello, M., Rianna, G., and Golding, B.: Protocol for an end-to-end evaluation of operational warning systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12075, https://doi.org/10.5194/egusphere-egu24-12075, 2024.

EGU24-12509 | ECS | Posters on site | HS4.5

Evaluating a +100-year storm surge using a real-time distributed flood forecasting system  

Emma Dybro Thomassen, Michael Butts, Sanita Dhaubanjar, Jonas Wied Pedersen, Sara Lerer, Mathias Rav, Morten Andreas Dahl Larsen, Kristine Skovgaard Madsen, Phillip Aarestrup, and Grith Martinsen

Estimating the geographical flood extent is a key element in impact-based flood forecasting and crucial for countries with long coastlines, and places where storm surges pose a significant risk, such as Denmark. For local flood mitigation measures and climate adaptation strategies, inundation mapping is often performed using physical models. However, in the context of flood forecasting and early warning, these are computationally demanding and therefore may not be able to provide timely forecasts and effective warnings.

The Danish Meteorological Institute (DMI) has developed a real-time flood forecasting system for storm surge events in Denmark together with the company SCALGO. This system couples the HBM regional oceanic storm surge forecasting model, developed by DMI, with a rapid inundation mapping, developed by SCALGO, using a 0.4 m resolution Digital Elevation Model (DEM). All inland pixels in the DEM are connected to a coastline pixel through pre-computed hydrological flow paths. The predicted water level from the storm surge model at each coastline pixel is then instantaneously projected inland through the pre-mapped flow paths. This study evaluates the performance of the flood forecasting system on the Oct. 20-21 (2023) storm surge event, with an estimated return period of over 100 years and affecting large parts of southern Denmark (and northern Germany).

This flood forecasting system creates a simple inundation mapping based on forecasted sea levels based on a high-resolution DEM modified to account for hydrological flow processes. This real-time flood mapping allows for a visualization of full five-day ocean model forecasts updated continuously at 6h intervals and has been operational for flood warning since October 2022, to supplement DMIs operational ocean forecasting system [1]. 

The evaluation is performed by comparing the inundation map from the flood forecasting system with media reports, photographs, and other data sources to get an overview of spatial and temporal accuracy and accuracy of the severity of the event. We see a large overlap between areas with forecasted flood risks and actual flooded areas. In some cases, the extent of the flooding differs from the area at risk due to errors in the DEM or local emergency services mitigation strategies.

We conclude that the flood forecasting system is useful for identifying coastal areas at risk. While it does not account for detailed physics of flow on land, it is able to reflect the effects of, even very local, geographical variations in sea level that determine the distributions of local-scale flood risk. The current inundation mapping does not currently include the impact of waves, which resulted in larger differences between predictions and actual flooded areas, for easterly-facing locations exposed to large waves. Proposed activities to include the effect of waves will therefore improve the flood forecasting system. 

[1] Andrée, E., Su, J., Larsen, M. A. D., Madsen, K. S., & Drews, M. (2021). Simulating major storm surge events in a complex coastal region. Ocean Modelling, 162, 101802.

How to cite: Thomassen, E. D., Butts, M., Dhaubanjar, S., Pedersen, J. W., Lerer, S., Rav, M., Larsen, M. A. D., Madsen, K. S., Aarestrup, P., and Martinsen, G.: Evaluating a +100-year storm surge using a real-time distributed flood forecasting system , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12509, https://doi.org/10.5194/egusphere-egu24-12509, 2024.

EGU24-13096 | ECS | Orals | HS4.5 | Highlight

Harnessing decision timelines to improve understanding and integration of local and scientific knowledges across the Climate Services value chain 

Sumiran Rastogi, Micha Werner, and Marc van den Homberg

Climate services are increasingly being co-produced through a negotiation process between climate service providers, purveyors, and end users. Their different knowledge systems (scientific and local) determine to a large extent this process. Local knowledge, covers a range of different knowledges, and includes how individuals perceive their surroundings, validate new information such as coming from science-based climate services, and solve problems. As such, local knowledge holders can range from indigenous, rural, or urban communities to professionals working at various levels of governance and various positions across the climate services value chain (e.g., service providers and purveyors).

Given the diversity of knowledges and knowledge holders, the actual integration of local knowledge in a climate service is challenging. In this research, we present an approach to collect, understand, and integrate local knowledge for climate services through the utilization of decision timelines. Decision timelines are effective tools for elucidating and understanding the decision-making process, allowing stakeholders to visualise changes and patterns over time (e.g., months, seasons, multiple years, etc). Through visual representation, decision timelines offer an effective way to understand links between different knowledges, stimulate discussions, co-design, and co-evaluate climate services with users. Traditionally such timelines have been limited to agricultural users to introduce the topic of climate information and how it relates to the key decisions that farmers need to make. However, in this research, we expand the scope of these timelines to different sectors (e.g., tourism, urban environment) and also to other actors in the climate services value chain (so not only the end user of a climate service). The timelines are instrumental to understand the decision-making over time and to elicit environmental and socio-economic cues (from local or scientific knowledge). Making timelines for those actors more upstream in the climate services value chain also allows to understand the co-production and knowledge management underpinning the governance process and climate service provision itself. We present examples from the different living labs that have been established in the I-CISK project (an EU research initiative), where these decision timelines have been used as a tool to elicit and understand local knowledge.

How to cite: Rastogi, S., Werner, M., and van den Homberg, M.: Harnessing decision timelines to improve understanding and integration of local and scientific knowledges across the Climate Services value chain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13096, https://doi.org/10.5194/egusphere-egu24-13096, 2024.

EGU24-14892 | Orals | HS4.5

Enduser Driven and Impact-based Time Dependent Tsunami Early Warning (TiDeTEW) in Aotearoa New Zealand 

Bill Fry, Christopher Mueller, Chris Moore, Emily Lane, Jen Andrews, Chris Zweck, Aditya Gusman, Sophia Tsang, Emeline Wavelet, Anna Kaiser, Ciaran King, Xiaoming Wang, and Biljana Lukovic

Since the 1960s, tsunami early warning has, for the most part, been predicated on using earthquake characterisation as proxy information for tsunami generation. Shortcomings with this approach include large epistemic uncertainties in wave forecasts that typically preclude actionable impact-based forecasts. Fortunately, the tsunami early warning paradigm is shifting. Here we present a prototype next-generation tsunami early warning system implemented by the New Zealand RCET (Rapid Characterisation of Earthquakes and Tsunamis) programme that is currently operational on a best-endeavours basis in New Zealand. This system is based on 1) observational advances including the densification of deep-ocean tsunami meters, 2) scientific advances provided by direct tsunami inversion 3) ensemble and time-dependent forecasting and 4) co-creation with end users of impact-based forecasts products. We call this system TiDeTEW (Time Dependent Tsunami Early Warning)

Following the recent deployment of the 12-station NZ DART tsunamimeter array (Fry et al., 2020), New Zealand’s Tsunami Expert Panel (TEP) can now use direct observations of tsunamis to underpin time-dependent tsunami early warning forecasts. By using DART inversions and ensemble modelling, we reduce uncertainties in forecasts enough to generate actionable early warning products that provide information about the evolution of the threat prior to land arrival, analogous to weather forecasting of storm evolution. Our forecasting products are being improved through co-development with at risk coastal communities that are dominantly indigenous Māori. In past natural disasters, the social structure of Māori communities has proven to be a major advantage in response and incorporation of Māori values into decisions around risk tolerance of the early warning products guides our levels of forecast conservatism. Understanding the response structure in these communities and its strong reliance on marae (Māori communal meeting houses) is also guiding our product development.

In an aligned effort within the UNESCO Intergovernmental Oceanographic Commission (UNESCO-IOC), we have developed a risk-based approach to assess the efficacy of this tsunami early warning method. We quantify the relative number of tsunami sources for which data support at least 20 minutes of pre-impact warning time to vulnerable coastal populations. We further map the warning gaps to population density of exposed coastlines. We apply this scheme using the NZ DART network to better quantify domestic and Southwest Pacific risk and resilience gains delivered by NZ DART and further highlight existing gaps and opportunities, largely around local source tsunamis.

How to cite: Fry, B., Mueller, C., Moore, C., Lane, E., Andrews, J., Zweck, C., Gusman, A., Tsang, S., Wavelet, E., Kaiser, A., King, C., Wang, X., and Lukovic, B.: Enduser Driven and Impact-based Time Dependent Tsunami Early Warning (TiDeTEW) in Aotearoa New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14892, https://doi.org/10.5194/egusphere-egu24-14892, 2024.

EGU24-15463 | ECS | Posters virtual | HS4.5

Community-led AA for flash floods: Lessons learned from the last-mile community during 2022 Extreme Event in North-Eastern Bangladesh  

Md Rayhan, Md. Hasanur Rahman, Rashel Dewyan, Shampa Shampa, Sonia Binte Murshed, and Shammi Haque

Forecast-Based Early Action (FbA) is a promising disaster risk reduction technique that allows communities to take proactive steps with the help of accurate forecasting before a disaster strikes. The current global evidence indicates that timely FbA can save more lives and minimize the impact on communities in the emergency and recovery stages. However, the FbA funded by humanitarians or governments needs some specific forecast window (e.g., 7 to 9 days for riverine floods in Bangladesh) from impact identification to intervention deployment. But in the case of rapid on-set disasters (such as flash floods (FF)), such forecast windows might be difficult to identify as these disasters might happen within 5 to 6 hours. In such cases, our research focuses on how the last mile community takes anticipatory action (AA). As a case study site, we selected the north-eastern (NE) region of Bangladesh, which experienced extreme FF during June 2022.

The first goal of this study was to look into how flash floods change the impact dynamics of last-mile communities over time. The second goal was to investigate how forecasting can be improved in terms of effectiveness and inclusiveness. The third goal was to investigate community-led AA during normal and extreme FF events. To understand local experiences and observations related to climate and environmental cues, 12 Key Informant Interviews (KIIs) and 14 Focus Group Discussions (FGDs) were conducted during Nov-Dec 2023. The Key Informant Interviews (KII) were conducted with representatives from NGOs, CBOs, trade organizations, and government officials. FGDs were held with a variety of groups, including women, the elderly, the disabled, ethnicity, religion, and occupation.

Our research found that rather than official forecasting, communities rely on indigenous knowledge such as cloud patterns, wind flow, atmospheric changes in hilly areas, sudden water temperature drops, color changes, and so on. These indicators serve as early warning signs of impending flash floods, allowing residents to plan ahead of time. Based on these predictive indicators, they take proactive measures such as elevating house plinths and safeguarding essential assets related to their livelihoods around 2.5 months before the FF period. Because the global lead time for FF is short, any AA must rely on community action. Because the NE region of Bangladesh has a long history of FF, their solution would be beneficial for other parts of the world to learn about, especially as the world experiences more FF because of climate change.

How to cite: Rayhan, M., Rahman, Md. H., Dewyan, R., Shampa, S., Murshed, S. B., and Haque, S.: Community-led AA for flash floods: Lessons learned from the last-mile community during 2022 Extreme Event in North-Eastern Bangladesh , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15463, https://doi.org/10.5194/egusphere-egu24-15463, 2024.

EGU24-15644 | Orals | HS4.5

Establishing effective links between early warnings and early action: general criteria for floods  

Sabrina Meninno, Marta Giambelli, Miranda Deda, Rocco Masi, Antonio Gioia, Enrico Ponte, Marco Massabò, Marina Morando, Romanella Vio, Chiara Paniccia, and Stefania Renzulli

The development and implementation of an effective Early Warnings to Early Actions system (EW-EAS) represent a complex system that integrates scientific insights with practical preventive measures on the ground. This complexity is enhanced by the involvement of diverse actors from various sectors and territorial levels, making the system vulnerable to potential breakdowns arising from factors such as unclear messages, unmet user needs, and implementation gaps.

 Recognizing this complexity and the necessity of merging scientific knowledge with operational field expertise, a set of general criteria for establishing “effective links between EW and EA” as related to floods was formulated in in the framework of the IPA Floods and Fires program for the Western Balkans and Türkiye. They resulted from a collaborative capacity development process conducted by experts from the CIMA Research Foundation and the Italian Civil Protection Department in collaboration with Disaster Risk Management Authorities and hydrometeorological services of the IPA countries.

Specifically designed for technicians and operators of the National Hydro-Meteorological and civil protection agencies, the general criteria serve as valuable resource of knowledge, experience and guidance for practitioners of national and local institutions which have the mandate to protect people, assets and the environment, by reducing the impacts of a flood and preventing the occurrence of emergency situations.

The General Criteria address several areas of the EWS with the ultimate purpose of enhancing a timely response to warnings before a flood occurs, in a progressive way and through early actions that are coordinated among all actors and integrated into plans and procedures. More specifically, the general criteria explore four key areas:

  • Early Warning. As an example, providing clear, consistent, and informative early warning messages (stating who produces the warning, to whom it is addressed, what the expected hazard scenario is, where it is likely to occur, when it is expected, and why it is significant) permits a correct and informed activation of the system.
  • Early Actions and the integration of an EW-EA link within emergency response plans. For instance, defining activation phases of the civil protection system linked to specific alerts enables a systematic and incremental mobilization of resources as flood severity escalates. This key area also offers guidance for constructing a set of early actions, ensuring early actions align with forecasted alert levels and risk information codified within the early warning system.
  • Communication flows for the dissemination of EWs and exchange of information among operational centres and institutions before, during and after the emergency and consequently an effective response. Central to this is the coordination and collaboration across actors in EW-EA, optimizing scarce resources for effective delivery.
  • Simulation exercises. Testing through simulation exercises enables continuous improvements and corrections of gaps to further refine the system.

The general criteria offer a framework for practitioners and institutions for improving the link from EW to EA, transforming risk information into actions on the field that can reduce the impacts of floods to communities.

How to cite: Meninno, S., Giambelli, M., Deda, M., Masi, R., Gioia, A., Ponte, E., Massabò, M., Morando, M., Vio, R., Paniccia, C., and Renzulli, S.: Establishing effective links between early warnings and early action: general criteria for floods , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15644, https://doi.org/10.5194/egusphere-egu24-15644, 2024.

EGU24-15879 | Orals | HS4.5

From Tsunami Hazard Modelling to Vulnerability Assessment in Mayotte’s east coast: an Interdisciplinary Risk Analysis 

Annabelle Moatty, Mangeney Anne, Le Friant Anne, Poulain Pablo, Marboeuf Alexis, Silver Maxwell, Lemoine Anne, and Pedreros Rodrigo

Mayotte island is divided in two main islands, Grande Terre (363 km²) and Petite Terre (11 km²), and is located in the Comoros archipelago in the Indian Ocean between Madagascar and Mozambique. From a social point of view, this French department is characterised by a young and highly vulnerable population (over 70% live below the poverty line). Furthermore, many households are exposed to hazards such as floods and landslides, cyclones, earthquakes and tsunamis. Concerning these last two, the 2018 seismo-volcanic crisis linked to Fani Maoré (the submarine volcano located 50 km east of Mayotte) has generated a demand from the local and national authorities for decision support elements to implement a risk prevention strategy and anticipate crisis situations.

The objective of this study is to question the interdisciplinary contributions of landslide-generated tsunami numerical modelling and geographical analysis in order to characterise Mayotte’s vulnerability regarding tsunami hazard. By combining the results of numerical simulations performed with the HySea model (Poulain et al, 2022) with available data on the assets (location, level of vulnerability to tsunami risk, etc. (Sahal, 2011)), we carried out a spatial analysis to identify the critical areas in the event of a tsunami, and the consequences of their potential damage.

Our results provide a characterisation of land use in hazard prone areas for four levels of hazard, from low to very high, resulting from the correlation of water depths and velocity. They also support an analysis of the vulnerability of part of the built environment of Petite Terre (which is most at-risk) by mapping these hazard data with vulnerability data at building level. Although the proportion of buildings and roads potentially affected remains relatively low (around 3%), the modelled scenario highlights major organisational vulnerability. Indeed, early warning strategies and systems are challenged on the one hand by the arrival times of the first simulated wave (between 4 min at the airport in the south of Petite Terre, and 13,5 min in Mamoudzou, the capital located to the east of Grande Terre (Poulain et al., 2022)), and on the other by the complexity of detecting a submarine landslide in advance if it is not generated by an earthquake.

References:

Poulain, P., le Friant, A., Pedreros, R., Mangeney, A., Filippini, A. G., Grandjean, G., Lemoine, A., Fernández-Nieto, E. D., Castro Díaz, M. J., and Peruzzetto, M. (2022) Numerical simulation of submarine landslides and generated tsunamis: application to the on-going Mayotte seismo-volcanic crisis. Comptes Rendus - Geoscience 354(S2): 1–30.

Sahal A. (2011), Le risque tsunami en France : contributions méthodologiques pour une évaluation intégrée par scénarios de risque, Thèse de doctorat de géographie, dir. Pr. F. Lavigne et F. Leone, Université Paris 1 Panthéon-Sorbonne.

How to cite: Moatty, A., Anne, M., Anne, L. F., Pablo, P., Alexis, M., Maxwell, S., Anne, L., and Rodrigo, P.: From Tsunami Hazard Modelling to Vulnerability Assessment in Mayotte’s east coast: an Interdisciplinary Risk Analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15879, https://doi.org/10.5194/egusphere-egu24-15879, 2024.

EGU24-16207 | ECS | Posters virtual | HS4.5

Communicating Life-Saving Information in Emergencies: Implementation of Multi-Hazard Early Warning System in India 

Sandeep Sharma, Saurabh Basu, Suvam Suvabrata Behera, Sumit Kumar Jha, Akshay Dawar, Niraj Kant Kushwaha, Sabyasachi Majumdar, Smriti Sachdev, Anugandula Naveen Kumar, Manish Bhaskar, Arun Yadav, and Pankaj Kumar Dalela

Disaster risk reduction is a pressing global challenge owing to climate change and other anthropogenic factors. Communicating timely, trusted, and actionable life-saving information to the public in emergency or disaster situations can make a significant difference by reducing the potential impacts and improving preparedness and mitigation efforts. In the direction of building a disaster-resilient India, inline with the global initiatives like Early Warnings for All, an end-to-end AI-driven Multi-Hazard Early Warning System has been established, standardizing and streamlining the flow of disaster warning dissemination in the country. The system utilizes International Telecommunication Union (ITU’s) Common Alerting Protocol (CAP) for disaster warning information exchange between the entities. Existing non-CAP compliant legacy infrastructure have also been integrated with the system by implementation of cost-efficient Interworking Systems (IWS). More ways for enhanced communication, making use of different ICTs and networks, including telecom (SMS and Cell Broadcast), broadcasting (Radio and Television), satellite, internet (Mobile Application, Web Dashboards, Browser-based Notifications), public addressing systems (Coastal Sirens, Railway Passenger announcement systems) etc. have been integrated for ensuring last mile reachability. The implementation of an indigenously developed cell broadcast system allows warnings to be disseminated within a few seconds to a large area population. Satellite based messaging services have been integrated for areas with no network coverage, such as alerting fishermen in high sea and targeting the tough terrain. The platform has been rigorously utilized in recent disaster situations, including Cyclone Michaung, Biparjoy, Mandous, Sitrang, etc. and more than 14 billion SMS have been disseminated till date across different geographical regions. It is operational across PAN India in all 36 State/ UTs, integrating 100+ stakeholders on the converged platform, supporting dissemination in over 22 regional languages, and addressing massive climatic, digital, linguistic, and geographic diversity in the country. The collective efforts have resulted in key advancements in the direction of disaster risk reduction.

How to cite: Sharma, S., Basu, S., Behera, S. S., Jha, S. K., Dawar, A., Kushwaha, N. K., Majumdar, S., Sachdev, S., Kumar, A. N., Bhaskar, M., Yadav, A., and Dalela, P. K.: Communicating Life-Saving Information in Emergencies: Implementation of Multi-Hazard Early Warning System in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16207, https://doi.org/10.5194/egusphere-egu24-16207, 2024.

EGU24-16805 | Orals | HS4.5

Toward large-scale demonstration of local multi-hazard early warning tools 

Shinju Park, Berenguer Marc, and Daniel Sempere-Torres

Catalonia is located in north-eastern Spain and in a predominantly subtropical Mediterranean climatic zone. Due to the diverse geographical and orographic features, the climate within the region exhibits variations due to local continental, oceanic, and alpine influences.
Within the Horizon Europe RESIST project (2023-2027), Catalonia is one of the leading regions for the demonstration of climate change adaptation strategies toward climate change resilience through innovation, science, and technology. The strategies being analyzed in Catalonia focus on the sector of civil protection to achieve improved preparedness and tools for disaster risk and emergency management for weather-related hazards (e.g., flash floods, wildfires, heat waves, etc.).
The presentation will address the key enabling tools and activities toward better adaptation; e.g., improving and expanding the existing Multi-Hazard Early Warning System (EWS) over Catalonia, improving the assessment of vulnerabilities and including vulnerable communities, raising awareness. These aspects will be evaluated during a long-term demonstration in several local municipalities of the region. The first results obtained during 2023 will be presented; particularly for the major flood event in June 2023 in Terrassa city.

How to cite: Park, S., Marc, B., and Sempere-Torres, D.: Toward large-scale demonstration of local multi-hazard early warning tools, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16805, https://doi.org/10.5194/egusphere-egu24-16805, 2024.

EGU24-17969 | ECS | Posters on site | HS4.5

Drought impact-based forecasting of crop yield in India 

Anastasiya Shyrokaya, Sameer Uttarwar, Giuliano Di Baldassarre, Bruno Majone, and Gabriele Messori

The reliable prediction of drought impacts on crop yield in India poses a significant challenge due to the complex interactions of climatic variables, systems vulnerabilities and impacts propagation. Advanced approaches, such as impact-based forecasting, become necessary to address the intricate nature of this challenge. In this study, we leveraged remote sensing-based vegetation indicators as proxies for crop yield, along with multiple drought indices across various accumulation periods, to establish a robust indicator-impact relationship. We further performed a comparative analysis of various machine-learning algorithms to assess their efficacy in predicting crop yield impacts on a subseasonal-to-seasonal scale. We finally evaluated the accuracy of predicting the crop yield impacts based on drought indices computed from ECMWF’s seasonal forecast system SEAS5.

Our analysis not only unveils seasonal trends and spatio-temporal patterns in indicator-impact links but also marks a pioneering effort in comparing diverse machine-learning algorithms for establishing an impact-based forecasting model. As such, these findings offer valuable insights into the dynamics of drought impacts on crop yield, providing a monitoring tool and a foundational basis for implementing targeted drought mitigation actions within the agricultural sector. This research contributes to advancing the understanding of impact-based forecasting models and their practical application in addressing the challenges associated with drought impacts on crop yield in India.

How to cite: Shyrokaya, A., Uttarwar, S., Di Baldassarre, G., Majone, B., and Messori, G.: Drought impact-based forecasting of crop yield in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17969, https://doi.org/10.5194/egusphere-egu24-17969, 2024.

EGU24-2202 | Orals | ERE4.5 | Highlight

Repurposing former underground coal mines by deploying emerging renewable energy and circular economy technologies 

Pedro Riesgo Fernández, Alicja Krzemień, Gregorio Fidalgo Valverde, Antonio Luis Marqués Sierra, and Francisco Javier Iglesias Rodríguez

This presentation introduces the Research Fund for Coal and Steel (RFCS) GreenJOBS project, which approach is premised on leveraging five competitive advantages of underground coal mines to deploy emerging renewable energy and circular economy technologies:

(1) mine water for geothermal and green hydrogen. Geothermal energy is a renewable source that harnesses the heat from inside the earth, in our case, through the water that floods the mines. From a certain depth, the temperature of the subsoil is constant regardless of the season. Thus, a continuous and accessible energy source is available all year round. On the other hand, mine water represents an essential raw material for producing green hydrogen by electrolysis;

(2) connections to the grid that can be adapted to inject the electricity produced;

(3) large waste heap areas for installing photovoltaic/wind;

(4) deep shafts suitable for unconventional pumped hydro storage using dense fluids that has a smaller footprint and higher energy density than conventional pumped hydro energy systems; and

(5) fine coal waste for recycling into dense fluids employed by the unconventional pumped hydro storage; artificial substitutes for soils from coal waste and wastes from closely located agricultural industries, coal-fired power plants, and water plants; and rare earths from fine coal wastes.

The objective is to provide mining companies with two innovative business plans: a Virtual Power Plant where the energy produced will be sold to the grid or used to power electro-intensive industries or companies with constant energy consumption located close to mines, such as aluminium factories or green data centres; and a Green Hydrogen Plant where renewable hydrogen will be produced by electrolysis of mine water and electricity from renewable sources.

How to cite: Riesgo Fernández, P., Krzemień, A., Fidalgo Valverde, G., Marqués Sierra, A. L., and Iglesias Rodríguez, F. J.: Repurposing former underground coal mines by deploying emerging renewable energy and circular economy technologies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2202, https://doi.org/10.5194/egusphere-egu24-2202, 2024.

EGU24-3065 | Orals | ERE4.5 | Highlight

A GIS-Based Decision Support System for Multi-Hazard Assessment in Post-Mining Regions 

Moncef Bouaziz, Bejamin Haske, Marwan Al Heib, and Joerg Benndorf

Abandoned mines are generally exposed to multi-hazard: natural and man-mad hazards. The risk assessment is one of the challenges of the site management. This paper presents first the categories of hazards and potential interactions, then it shows a Geographical Information System (GIS)-based Decision Support System (DSS), as part of the European research project titled "POst-mining Multi-Hazards Multi-Assessment for Land-Planning (POMHAZ)." Utilizing predominantly open-source tools (PostGIS, Geoserver, and Leaflet) and Python Scripts, the DSS aims to tackle the intricate challenges posed by post-mining hazards in European mining regions. The objective is to furnish a functional web-based tool tailored for EU administrative units, ensuring a comprehensive evaluation of various hazards that impact their territories.

In the context of post-mining landscapes, conventional environmental policies often encounter challenges due to the lack of operational and accessible tools. The proposed DSS seeks to bridge this gap by catering to a diverse user base, including citizens, scholars, associations, and public bodies.

The DSS streamlines the acquisition, management, and processing of both static and dynamic data, providing web-accessible data visualization. Customized for post-mining multi-hazards, this tool contributes to enhanced decision-making by generating data, statistics, reports, and maps for various EU areas of interest. Validation is obtained through a case study of abandoned coal mine (France), this validation demonstrates its capabilities. This paper showcases the practical application of the DSS in North Rhine Westphalia offering valuable insights to address the intricate challenges posed by post-mining hazards.

How to cite: Bouaziz, M., Haske, B., Al Heib, M., and Benndorf, J.: A GIS-Based Decision Support System for Multi-Hazard Assessment in Post-Mining Regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3065, https://doi.org/10.5194/egusphere-egu24-3065, 2024.

EGU24-3957 | ECS | Posters on site | ERE4.5

Comprehensive analysis and risk assessment of tailings storage facilities in China  

Chenxu Su, Nahyan M. Rana, Stephen G. Evans, Bijiao Wang, and Shuai Zhang

The historical failures of Tailings Storage Facilities (TSFs) in China have led to severe downstream consequences, encompassing loss of life, economic damage, and environmental contamination. Despite these consequences, the comprehensive documentation and quantitative evaluation of TSFs in China have been notably lacking. The existing records of TSFs are incomplete, and there is a deficiency in accurately assessing the frequency of their failures. This gap in knowledge has been a significant obstacle in effectively assessing and mitigating risks associated with TSFs. Our research involved compiling and analyzing new databases, shedding light on the historical failures and current status of TSFs in China. We uncovered 143 TSF failure incidents between 1957 and 2022. This figure largely exceeds the approximately 20 failures reported in earlier studies, highlighting a critical underestimation in past assessments. The human and economic damage of these incidents has been considerable, with 840 lives lost, 1,416 houses damaged, and 28,923 individuals adversely affected. Furthermore, the total volume of tailings released in these failures surpassed 12.7 million m3. A notable observation from our study is that about 75% of these failures involved tailings flowing into water bodies, exacerbating environmental pollution significantly. Our study also presents an in-depth statistical analysis of the magnitude and frequency of these failures. We found that the average return period for TSF failures in China, resulting in at least 10 fatalities, is approximately every five years. For failures with released volumes exceeding 1 million m3, the average return period extends to about 16 years. In addition to historical data, we include a comprehensive review of current TSFs. Our review confirms that there are 14,217 existing TSFs in China alone, leading to an estimated cumulative failure rate of approximately 1%. Our work further includes the development of a supplementary database encompassing 1,853 TSFs, providing essential statistics such as storage volume and dam height. This database is a crucial tool for ongoing and future risk assessments. Applying our database-driven, regionally-simplified risk assessment approach, we conducted a case study in Jilin Province. The results are concerning, indicating 11 TSFs bearing intolerable risks, among which the most hazardous TSF presents a potential loss of life estimated at 175 individuals. Our study offers the most comprehensive overview of TSF failures and their implications in China to date. The extensive scope of this research bears substantial implications for prospective nationwide utilization, particularly in the enhancement of risk assessment methodologies and the enforcement of efficacious mitigation measures for TSFs in China.

How to cite: Su, C., Rana, N. M., Evans, S. G., Wang, B., and Zhang, S.: Comprehensive analysis and risk assessment of tailings storage facilities in China , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3957, https://doi.org/10.5194/egusphere-egu24-3957, 2024.

EGU24-5645 | Posters on site | ERE4.5

Sensor-based Multi-Level Analysis of Ferronickel Furnace Slag: Exploring Economic Opportunities    

Feven Desta, Oscar Kamps, and Mike Buxton

The ever-growing demand for mining products has led to the extraction and processing of large volumes of materials, resulting in the production of significant amounts of mine waste. While the composition of mine waste materials can vary and may cause environmental impacts, they can also be a valuable source of raw materials to meet the current and future mineral demand. The efficient re-mining of minerals of economic interest from mine waste materials (such as slag) requires accurate and reliable estimation. This can be achieved using state-of-the-art sensor technologies coupled with advanced data analytics. Such technologies include laser-induced breakdown spectroscopy (LIBS), x-ray fluorescence (XRF), short-wave infrared (SWIR) and Fourier transform infrared spectroscopy (FTIR). This study evaluates the usability of LIBS, FTIR, SWIR, and XRF technologies for the characterization of Ferronickel slag materials at a multi-level. Methodological approaches were developed to assess the usability of each technique for the identification, classification, or semi-quantification of the target elements (such as Ni, Ti, Pb, and Cr) in the analyzed samples. The results demonstrate that the use of the techniques enabled a comprehensive compositional analysis of slag materials. Moreover, the findings suggest that such an approach could promote sustainable mining practices by providing valuable insights into the potential economic benefits of reusing slag materials for secondary recovery. Such an approach could contribute to reducing the possible environmental impact of waste and could enable achieving a circular economy.

How to cite: Desta, F., Kamps, O., and Buxton, M.: Sensor-based Multi-Level Analysis of Ferronickel Furnace Slag: Exploring Economic Opportunities   , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5645, https://doi.org/10.5194/egusphere-egu24-5645, 2024.

EGU24-5800 | Orals | ERE4.5

Macro- to nanoscale mineral relationships in mining wastes of the As–Sb–Tl–Au Allchar mine, North Macedonia 

Tamara Đorđević, Michael Stöger-Pollach, Sabine Schwarz, Goran Tasev, Todor Serafimovski, Ivan Boev, and Blažo Boev

In the mining waste dumps and tailings of the former As–Sb–Tl–Au Allchar deposit, North Macedonia, secondary oxides and oxy-salt minerals partially control the mobilization of arsenic (As), antimony (Sb) and thallium (Tl). Depending on the pH condition and the proportion of primary sulfide and sulfosalt minerals, we have observed two major scenarios for the retention of As, Sb and Tl through secondary minerals.

We have investigated three dozens of solid samples from the profiles and excavation holes at the three sites of former Alchar mine, analyzed them for their major and minor chemical elements, and characterized them for their mineralogical composition, with a special focus on Tl-secondary minerals at the nano- to centimeter scale.

At the Tl- and As-rich Crven Dol locality, As and Tl dissolved during weathering under circumneutral to slightly alkaline conditions are precipitated as micaceous crystals of poorly crystalline to amorphous thallium arsenates, forming porous aggregates up to 100 µm. These Tl arsenates are intergrown with dolomite and Ca-Fe-arsenates and appear as two different phases. In the first, more common phase Tl:As ratio range from ca. 2.1 to 4.1. In the second, Tl-richer phase, the Tl:As ratio varies from 5.1 to 8.4. In the waste dumps showing acidic pH-values common Tl precipitate is dorallcharite [TlFe3+3(SO4)2(OH)6]. Tl is also accumulated in Mn-oxides (up to 3.6 at.%), pharmacosiderite (up to 0.9 at.%), and jarosite-group minerals (up to 0.9 at.%).

The orpiment-rich tailings are mostly composed of orpiment, quartz, realgar and scorodite, followed by gypsum and kaolinite-group minerals. Realgar and orpiment are the major As-sources and Tl-sulfosalts lorándite, fangite, and raguinite are the primary Tl-sources. The most common Tl-bearing precipitate is dorallcharite mostly embedded in scorodite. Tl is also accumulated in Mn-oxides (up to 5 at.%) and thalliumpharmacosiderite, TlFe4[(AsO4)3(OH)4]·4H2O.

In the deposit is Sb-rich central region, the primary Tl sources are sulfosalts such as fangite, lorándite, and pierrotite, while stibnite is the primary Sb source. Tl dissolved during weathering under circumneutral conditions is reprecipitated as avicennite, Tl2O3, and tiny, fibrous Tl-bearing Mn-oxides (up to 8.5% Tl). Furthermore, tiny spherulitic aggregates (up to 3 µm) of a Tl-Sb-oxide (a new mineral species) have been found intergrown with quartz, muscovite, and minor dolomite. TEM-based EBSD on Tl-Sb-oxide particles confirmed that the Tl-Sb-oxide is crystalline, and EDS-line and area scans confirmed a Tl:Sb ratio of 2.5, indicating that Tl enters the crystal structure of the new Tl-Sb oxides rather than being hosted in the nanophase.The oxidative weathering of Tl-bearing metal-sulfides generates both nano- and microcrystalline Tl-minerals.

Our future investigation focuses on the formation and dissolution of these phases and will offer a much deeper understanding of the mechanisms of mineral association formation.

Financial support of the Austrian Science Fund (FWF) [P 36828-N] is gratefully acknowledged.

How to cite: Đorđević, T., Stöger-Pollach, M., Schwarz, S., Tasev, G., Serafimovski, T., Boev, I., and Boev, B.: Macro- to nanoscale mineral relationships in mining wastes of the As–Sb–Tl–Au Allchar mine, North Macedonia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5800, https://doi.org/10.5194/egusphere-egu24-5800, 2024.

EGU24-7632 | ECS | Orals | ERE4.5 | Highlight

Environmental monitoring of pollution at legacy mines in Greenland using portable X-ray Fluorescence Spectrometry (pXRF) 

Christian Frigaard Rasmussen, Christian Juncher Jørgensen, Jens Søndergaard, and Anders Mosbech

As the world’s need for raw materials increases, more mines are planned to be established in the Arctic. The Arctic provides a unique and challenging environment for mining operations and introduces concerns for the potential spread of pollution. Arctic environmental conditions linked to wind- and waterborne pollution transport such as hydrology, precipitation, temperature, windspeed and wind direction vary markedly throughout the year and the environment is sensitive to anthropogenic influence.

In Greenland, several legacy mines provide testimony to how pollution still affects the sensitive Arctic environment. These legacy mines serve as valuable study sites that can improve future predictions on environmental consequences of mining operations in Greenland and other areas in the Arctic. Environmental studies at legacy mine sites in Greenland have previously focused on the leaching of pollutants into the marine environment and little is known about the spatial distribution of pollution in the terrestrial environment at these sites.

In the current study, we present preliminary data from an environmental survey at the Blyklippen legacy mine. Blyklippen was a lead and zinc mine in East Greenland that operated between 1956-1963. Mining operations caused substantial pollution of lead (Pb), zinc (Zn), and other heavy minerals such as cadmium (Cd), barium (Ba) and copper (Cu), still measurable today. The primary sources of pollution today are the tailings storage facility and remains of ore concentrate spills along the haul road and at the quay areas at the harbor. Pollution is dispersed from these sites into the surrounding environment by wind and water.

The aim of the current study is to investigate and map the spatial distribution of heavy metals in the environment surrounding the Blyklippen legacy mine using both field measurements by portable X-Ray Fluorescence spectrometry (pXRF) on depth specific sediment samples at in situ conditions and laboratory measurements on freeze-dried samples to investigate the effect of soil moisture on the accuracy of the field screening. Field measurements were conducted using short measurement times of 5-10 seconds, whereas laboratory measurement times were 180 seconds.

A total number of 995 discrete sediment samples were collected over 10 days at the Blyklippen mine site and surrounding area of Mestersvig from 178 sampling locations at depth intervals of 5 cm. Our results demonstrate the effectiveness of pXRF as a field measurement tool for identifying the spatial delineation of soil pollution by comparing in situ measurements against pre-defined natural background values for heavy metals such as Pb and Zn. Comparison between Pb and Zn concentrations measured in the field versus in the laboratory on freeze-dried samples showed a good agreement for mineral soils. On organic and/or wet samples, field concentrations were underestimated for some elements.

Overall, the approach shows that a fast and cost-effective large-scale field survey at legacy mines is obtainable using pXRF, enabling an effective identification of pollution ‘hotspots’ directly in the field. In combination with geostatistical mapping, the approach can improve the overall accuracy of environmental monitoring and mapping of pollution with enhanced environmental protection at both legacy, recent and future mines.

How to cite: Rasmussen, C. F., Juncher Jørgensen, C., Søndergaard, J., and Mosbech, A.: Environmental monitoring of pollution at legacy mines in Greenland using portable X-ray Fluorescence Spectrometry (pXRF), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7632, https://doi.org/10.5194/egusphere-egu24-7632, 2024.

EGU24-8042 | ECS | Posters on site | ERE4.5

Origin of Rare Earth Elements in Acid Mine Drainage: Mineralogical Insights from the Iberian Pyrite Belt (SW Spain) 

Rafael León Cortegano, Francisco Macías, Carlos R. Cánovas, Rafael Pérez-López, Ricardo Millán-Becerro, Jonatan Romero-Matos, Laura Sánchez-López, and José Miguel Nieto

The Iberian Pyrite Belt (IPB), located in the SW of the Iberian Peninsula, is one of the largest polymetallic massive sulfide provinces in the world. Historical mining activity in the area has left a significant legacy of mine residues, including 90 abandoned mines and more than 1.000 ha of waste rock dumps and tailings. Therefore, large volumes of Acid Mine Drainage (AMD) are produced due to oxidation of pyrite-rich residues exposed to atmospheric conditions, which end up in the Tinto and Odiel rivers and subsequently into the ‘‘Ría de Huelva’’ estuary (SW Spain), polluting these water environments. During the passive treatment of AMD with Dispersed Alkaline Substrate (DAS) technology, sequential precipitation of Fe3+ as schwertmannite and Al as basaluminite occurs, and Rare Earth Elements (REE) are preferentially concentrated within the Al-rich precipitate layer. This could be an interesting alternative source of REE, given that AMDs of the IPB are enriched in middle REE (MREE) and heavy REE (HREE). A rough estimation of the REE potential of these AMD sources, based on 40 DAS plants operating in the Odiel basin with variable content of REE, will be the production of 11 kton/year of basaluminite containing 21 ton/year of REE2O3 with grade of 0.19%. However, the origin of REE in AMD is not well understood. This work examines the concentration and pattern of REE in AMD, ore bodies, and country rocks in two representative mining areas of the IPB: Perrunal and Poderosa mines. Leaching experiments were conducted on sulfide ores and host rocks under simulated AMD formation conditions, and the results were compared with the AMD formed in these two mining areas. The preliminary results indicate that the host rocks (felsic and mafic volcanics and shales) are the primary source of REE in the AMD. A mineralogical and chemical study of the country rocks in Perrunal and Poderosa mines reveals that secondary phosphates and carbonates contain the highest REE content, which are also soluble under acidic conditions. REE-rich monazite-type is systematically present in felsic volcanics and shales in both mining areas. HREE-rich xenotime-type is also present in most felsic volcanics, while REE-rich carbonates (mainly parasite-type) are present in carbonate-rich shales from the Perrunal mine. Other minor REE-bearing minerals, such as apatite and zircon, have been identified in the host rocks. However, due to their lower abundance and solubility under acidic conditions, they are not considered an important source of REE in the AMDs of the studied mining areas. Finally, the petrographic evidence shows a selective leaching of these REE-bearing phosphates and carbonates which highly supports their involvement as the main source of REE in AMD.

Acknowledgements: This work is part of the I+D+i TRAMPA project (PID2020-119196RB-C21), funded by MCIN/AEI/10.13039/501100011033/.

How to cite: León Cortegano, R., Macías, F., R. Cánovas, C., Pérez-López, R., Millán-Becerro, R., Romero-Matos, J., Sánchez-López, L., and Nieto, J. M.: Origin of Rare Earth Elements in Acid Mine Drainage: Mineralogical Insights from the Iberian Pyrite Belt (SW Spain), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8042, https://doi.org/10.5194/egusphere-egu24-8042, 2024.

EGU24-8964 | Orals | ERE4.5

Delineation of mine tailings by ambient noise horizontal-to-vertical spectral ratio method 

Ayse Kaslilar, Zbigniew Wilczynski, Christopher Juhlin, and Mehrdad Bastani

The increasing need for mineral resources and critical rare earth elements (REE) due to the transition to clean energy has attracted interest in mine wastes as they may contain significant amounts of REE that were not of interest in the past but are today. Detailed knowledge about the 3D geometry and size of the waste deposits and their mineral content is important to understanding whether waste tailings can serve as a secondary resource, contributing to the energy transition, sustainability, and the circular economy, and promoting recycling.  Geophysical methods can provide information on the geometry, and help to characterize and estimate the size of the mine waste. In the last two decades developments in sensor and computational technology have enabled cost-effective and environmentally friendly seismic ambient noise methods to be widely applied for imaging the subsurface. Among others, one of the ambient noise methods is the horizontal-to-vertical spectral ratio (HVSR) method, which is an efficient technique widely used for site characterization, estimating the thickness of overburden above bedrock, monitoring landslide, and examining the stability of tailing dams.

In this study, ambient noise data and the HVSR method are used to estimate the thickness and delineate the 3D geometry of mine tailings. We use three-component (3C) ambient noise data that we collected with 50m spacing between the sensors and profiles in one of the non-active mine tailings of Nordic Iron Ore in Blötberget, Sweden, which might be a potential resource for REE.  We process the 3C data and obtain the fundamental frequency at each receiver location. Moreover, one-component ambient noise data that we collected along two perpendicular profiles with a receiver spacing of 5m are used to estimate the surface wave velocity. Combining the fundamental frequency and velocity information, we calculate the depth of the contrasting interface. We show our preliminary results obtained from ambient noise data and compare them with the previous results from the radio magnetotelluric measurements conducted by Geological Survey of Sweden.

This work is part of a project supported by the Geological Survey of Sweden. We gratefully acknowledge this support.

How to cite: Kaslilar, A., Wilczynski, Z., Juhlin, C., and Bastani, M.: Delineation of mine tailings by ambient noise horizontal-to-vertical spectral ratio method, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8964, https://doi.org/10.5194/egusphere-egu24-8964, 2024.

EGU24-9303 | Posters on site | ERE4.5

Recycle of quarry byproducts for producing a new Zn fertilizer 

Giulio Galamini, Daniele Malferrari, Fabiana Altimari, Silvia Orlandi, and Luisa Barbieri

Zinc (Zn) is a crucial micronutrient for plants, related with tolerance against diseases. When crop demand exceeds Zn availability in the soil, using Zn­-fertilizers becomes necessary (biofortication), however, even in foliar application, soluble Zn salts are mostly used, which are prone to leaching and consequently exhibit limited uptake by plants.

In response to this challenge, a novel controlled-release formulation, utilizing mine wastes as carrier, was developed, involving an energy-efficient process with ambient temperature and pressure, and a reaction time of approximately 8 hours.

Formulations were prepared by mixing a zeolite-rich (clinoptilolite) tuff with 2 quarry by-products, namely lapillus and pumice, using different dosages. We conducted studies on the kinetics of Zn adsorption and release, ultimately identifying the most effective mixture which comprised 70% zeolite-rich tuff and 30% pumice.

To assess the effectiveness, a fertilization test was performed via foliar application in Vitis vinifera, aiming to evaluate the Zn coverage, and the persistence of the product against simulated rainfall, in comparison with conventional ZnSO4 fertilizer.

The test confirmed greater Zn resistance to rain leaching, also suggesting potential for reducing treatment dosages, thereby mitigating environmental-related impacts. Moreover, the presence of 30% pumice would allow significative reuse of mining byproduct.

Project funded under the PNRR–M4C2INV1.5, NextGenerationEU-Avviso 3277/2021 -ECS_00000033-ECOSISTER-spk1

 

How to cite: Galamini, G., Malferrari, D., Altimari, F., Orlandi, S., and Barbieri, L.: Recycle of quarry byproducts for producing a new Zn fertilizer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9303, https://doi.org/10.5194/egusphere-egu24-9303, 2024.

EGU24-10941 | Posters on site | ERE4.5

Cost – Benefit Analysis through Stochastic Risk Assessment on Mining Waste Management 

Evangelos Machairas, Emmanouil Varouchakis, and Michail Galetakis

Cost Benefit & Bayesian Analysis for Mining Waste Management contributes positively to developing an alternative methodology that could be implemented on an industrial scale. Two case scenarios are examined. The first scenario refers to the presentation of mining activities without 3R’s policy (reduce, recover, reuse wastes) and non-implementation of environmental protection measures. The second scenario refers to the presentation of mining activities with full implementation of environmental protection requirements by a closed system of industrial units for metal recovery and avoiding free disposal of tailings in soil areas. Considering a) each project’s aim and scope, b) legislative requirements for environmental protection, and c) escalation of penalty cost for non-compliance with the corresponding legislation, the total cost for each case scenario is extracted. Cost-benefit analysis (CBA) evaluates the sustainability of each case scenario by its Financial Risk.

The scope of this paper is to ensure the adaptability of the CBA appraisal tool to each similar subject of study, in which the lowest Financial Risk indices characterize optimal business decisions. CBA’s evaluation involves each case scenario’s parameters converted into monetary terms. CBA’s extracted results are calibrated through Bayesian Analysis to provide more accurate Financial Risk (FR) estimation. The physical meaning of Bayesian Analysis’s provided calibration to the CBA is to obtain the ability to implement stochastic risk in realistic conditions.

How to cite: Machairas, E., Varouchakis, E., and Galetakis, M.: Cost – Benefit Analysis through Stochastic Risk Assessment on Mining Waste Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10941, https://doi.org/10.5194/egusphere-egu24-10941, 2024.

EGU24-11299 | ECS | Posters on site | ERE4.5

Developing PRIME Technology for Enhanced Coal Tip Assessment: Innovations in Continuous Geoelectrical Monitoring and Landslide Decision Support 

Yin Jeh Ngui, Adrian White, Harry Harrison, Judith Porter, James Boyd, Phil Meldrum, Paul Wilkinson, Oliver Kuras, Jonathan Chambers, and Sam Deeley

Disused coal tips formed by waste materials from coal mining activities can become unstable over time. Landslides or avalanches of coal waste can occur, especially during heavy rainfall or by other environmental factors, leading to significant safety hazards for nearby residents and infrastructure. The Welsh Government Coal Tip Safety Taskforce has recently identified over 2,500 disused coal tips in Wales potentially posing a risk, following a significant landslip in Tylorstown after the 2020 storms. Ongoing climate change further destabilises these legacies of past mining activities, posing great challenges to land management and hazard remediation, as instability within the coal tip can be invisible to surface surveys and inspections.

Wattstown in the Rhondda Cynon Taf County Borough was identified as a preferred location for deploying long-term 4D geoelectrical monitoring, with the aim of observing the moisture dynamics between a heavily vegetated basin area upslope of the coal tip (where a previous landslip has occurred) and the downslope tip materials. A BGS-designed Proactive Infrastructure Monitoring & Evaluation (PRIME) system has been deployed here to characterise this site using eight 32-electrode arrays. PRIME is a low-cost, low-power, non-invasive 4D geo-electrical imaging technology designed for near-real-time infrastructure monitoring.  The eight ERT sensor arrays are arranged so that four arrays form two long 2D survey lines to monitor the main slope in directions perpendicular to each other, while a further five arrays cover the landslip region in a 3D configuration, in which one of the arrays is common between the linear and the grid configuration. A full daily measurement schedule allowing for ground motion tracking has been implemented since Mid-2023. Measured data is transferred daily to the BGS servers, and system diagnostics reports are automatically generated to confirm the recent monitoring status and performance of the PRIME system.

The baseline resistivity model shows a lower resistivity layer with a variable thickness of 0 - 5 m covering the whole monitored area. This layer is interpreted as spoils that have been deposited and subsequently reprofiled. Our observation also matches with the presence of high clay contents found in the hand-augered soil. Below the reprofiled spoils resistivity values increase significantly, likely to be underlying bedrock that is composed of sandstone with interbedded layers of coal and silt.

Time-lapse inversion revealed the influence of effective precipitation on the moisture dynamics of the coal tip. Several anomalies were observed within the gradually decreasing resistivity distribution in the near-surface. Along the line perpendicular to the slope, larger low-resistivity features are observed in both the ditches that run parallel to the slope. This could be the result of preferential infiltration in these areas and the ponding of surface water. In the rotational landslip area, PRIME monitoring data has identified what is potentially a preferential flow path from 5 m to 10 m below ground level.

Through continuous monitoring of the disused coal tip, the PRIME system demonstrated its capability for enhanced coal tip assessment, detecting critical hydrogeological processes through minimally-invasive subsurface imaging. Ongoing work aims to establish in-situ petrophysical relationships.

How to cite: Ngui, Y. J., White, A., Harrison, H., Porter, J., Boyd, J., Meldrum, P., Wilkinson, P., Kuras, O., Chambers, J., and Deeley, S.: Developing PRIME Technology for Enhanced Coal Tip Assessment: Innovations in Continuous Geoelectrical Monitoring and Landslide Decision Support, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11299, https://doi.org/10.5194/egusphere-egu24-11299, 2024.

Sulfide minerals present in mine waste, upon oxidation by oxygen and water, can lower the pH, leading to increased metal solubility. This study focuses on mine waste containing sulfide mineral, utilizing fuel cell technology to recover valuable resources. The aim is to explore the potential conversion of mining by-products into valuable energy and resources, addressing environmental impact and transforming mining waste into a valuable asset. The electrochemical oxidation of pyrite (FeS2) (ΔG0 = -27.15 kJ/mol) is induced through electrode installation, with the reaction facilitated by employing electrodes. In this process, pyrite acts as an electron donor, and oxygen, mediated by the electrode, acts as an electron acceptor. The cathode is designed to induce the oxidation of pyrite (Pyrite→Fe3+), while the anode, exposed to oxygen in the air, promotes the reduction of oxygen (O2→H2O). Pyrite (150-250 μm in diameter) was placed in the anode cell containing 125 mL of anolyte (distilled water adjusted to pH 2.0 with hydrochloric acid), and the cathode cell was exposed to air. After 4 weeks of reaction 23 mg of pyrite was dissolved leaching 0.73 mM of Fe, and generating 4.1616×10−7 W of power. In the further study the fuel cell technology will be applied to utilize sulfidic mining residues (XRD analysis result: FeS1.6Se0.4 42%, FeS2 14%, Mg2CaWO6 12%, etc.), generated during the ore beneficiation process at a tungsten mine in Yeongwol, Gangwon Province, South Korea, for the recovery of energy and valuable metals.

How to cite: Ju, W. J. and Nam, K.: Electrochemical conversion of sulfide mineral-containing mine waste for energy and resource recovery using fuel cell technology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12537, https://doi.org/10.5194/egusphere-egu24-12537, 2024.

EGU24-14563 | Orals | ERE4.5

Reimagining Australia's mine waste: New resources, new challenges 

Anita Parbhakar-Fox, Laura Jackson, Kamini Bhowany, Rosie Blannin, Allan Gomes, and LeXi K'ng

Meeting the needs of the energy transition is a once-in-a-generation challenge like no other before. To meet the projected metal demand to support things, the global community will produce increased volumes of mine waste requiring best practice management. Mine waste is suspected to be a host of critical metals and minerals (i.e., cobalt, indium, REEs, Ga and Ge have typically been by-products since concentrating in waste streams). If identified as significant resources of critical metals, remining waste can support Australia’s effort to adopt circular economy principles, a notable socio-economic driver.

Whilst this sounds relatively straightforward, practical investigations show this is anything but. From sampling to metal recovery, mine waste materials are complex and heterogenous originating, in some cases, from multiple ore sources, processed by different methods, and eventually subjected to weathering under changing climatic conditions. Therefore, multi-scale multidisciplinary characterisation is required to truly develop a valorisation process which not only recovers critical metals and minerals, but also substantially reduces any associated environmental legacy issues and mining footprints.    

In collaboration with the QLD, NT, NSW and SA State Governments and Geoscience Australia mine waste (i.e., tailings, slag, waste rock and metallurgical residues) at historical and operational mines across the country have been sampled (n= 50 of 77: 2019-2024). Highlights so far include potential for Co resources in QLDs NW Minerals Province with metallurgical studies now being conducted to recover Co from pyrite.  Indium, hosted in a range of sulfides, sulfosalts and cassiterite has been recognised in greisen and VHMS mine waste, whilst Sb (and REE) enrichment has been identified in the sampled NT. New investigations are underway to better understand SAs waste with desktop studies suggesting Ni, REEs and Mn fertility. 

 

Whilst these data will ultimately feed into the national Mine Waste Atlas being developed by Geoscience Australia, opportunities to manage the new waste streams are being explored. With new markets coming online seeking feedstocks which are more enviro-ethically sourced. However, the challenge remains, how to ensure policies are in place to support these activities, whilst ensuring that the right technologies to support valorisation are accessible. As global communities align to tackle these hurdles, mine waste transformation looks certain to be the business model of the future. 

  

How to cite: Parbhakar-Fox, A., Jackson, L., Bhowany, K., Blannin, R., Gomes, A., and K'ng, L.: Reimagining Australia's mine waste: New resources, new challenges, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14563, https://doi.org/10.5194/egusphere-egu24-14563, 2024.

EGU24-14982 | Posters on site | ERE4.5 | Highlight

Analysis of ground movements in the post-mining area of the lignite mine “Babina” (W Poland) 

Natalia Walerysiak, Jan Blachowski, Jarosław Wajs, and Paulina Kujawa

Post-mining areas require constant monitoring due to the risk of secondary ground movements of a continuous or discontinuous nature. This study focuses on the analysis of ground movements in the post-mining area of the “Babina” mine in Western Poland. The complex nature of the “Muskau Arch” glaciotectonic area, subjected to both underground and open pit mining, further complicates the understanding and monitoring of these movements.

The study site was subjected to precise levelling monitoring between 2020 and 2023, and the results of five measurement campaigns form the basis of the analysis, with the first measurement being the reference for the subsequent ones. For this purpose, a geodetic monitoring network was established to cover key locations in the “Babina” mine area. The network was made up of 99 control points set-up as concrete pillars with metal control bolts and was connected to 4 reference benchmarks of the national levelling network situated beyond the post-mining area. In addition, 7 local research networks have been established in specific study sites. The levelling measurements were carried out using geodetic precision levelling. The total length of the levelling lines was approximately 36 km. The ground movements recorded between the first (initial), carried out in May 2020, and the last measurement campaign, in September 2023, range from -5.58 mm to +4.97 mm. Ground movements in the specific dense networks range from -39.46 mm to +115.39 mm.

Three interpolation methods were used to obtain continuous maps of the ground movements from discrete levelling observations: Inverse Distance Weighted, Radial Basis Function and Ordinary Kriging. The latter technique produced the smallest root-mean-square errors assessed with the cross-validation technique. In the result, we obtained 24 maps representing elevation changes between the first and the last measurement, as well as maps representing movements between consecutive measurements.

The maps of ground movements were used to identify areas of statistically significant displacements and to analyse the evolution of these displacements over time and in relation to the extent of past underground and open-pit mining activities and current land use. The results indicate present-day activity of the ground in the post-mining area that varies in the magnitude and direction of movements in different parts of this complex area. The observed seasonal fluctuations may indicate relationship of benchmark movements with periodic change of ground water level and the effect of climate change.

Our findings confirm the presence of ground movements in post-mining area five decades after the end of mining activity and of varied nature, as well as substantiate the need for further investigation of this activity in the study area. These should include detailed analysis of the relation between groundwater level and benchmark heights and correlation of movements with the extent of shallow underground mining.

The research has been financed from the OPUS National Science Centre projects grant no. 2019/33/B/ST10/02975 and grant no 2021/43/B/ST10/02157.

How to cite: Walerysiak, N., Blachowski, J., Wajs, J., and Kujawa, P.: Analysis of ground movements in the post-mining area of the lignite mine “Babina” (W Poland), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14982, https://doi.org/10.5194/egusphere-egu24-14982, 2024.

EGU24-15004 | ECS | Posters on site | ERE4.5

Flash Water Detection in Mining Areas Using Satellite Imagery and Meteorological Data  

Aleksandra Kaczmarek

Detection of temporary surface water is a critical aspect of monitoring the impact of mining on the environment and the impacts of underground gas storage (UGS) sites in particular. Recent years have been very dynamic for the energy sector, as increasing energy demand and the progression of global warming require constant improvements and changes. The general trend is to move away from conventional energy sources. However, green fuels require large storage volumes, which can be provided by geological storage. It can also be used to trap CO2 and thus contribute to the reduction of CO2 emission into the atmosphere.

Injection and withdrawal of gases in underground magazines affect the environment in a number of ways. Pressure changes and corresponding stress induce seismic activity, surface subsidence, and uplift. Gas leakage poses a risk to soil, water and air contamination. Therefore, it is necessary to treat UGS sites together with their surroundings in a holistic manner considering all potential impacts. The study UGS site is located in northern Poland. Natural gas is stored in salt caverns. The terrain to the north of the facility is of particular interest, as it is agricultural land with an old drainage system. It has not been maintained for years and the water reoccurs periodically. Low elevation and short distance to the sea favour flash flooding, which might be reinforced by UGS induced surface movements. The purpose of the test study is to detect surface water with a remote sensing based approach and establish the correlation between rainfall and surface water dynamics.

Satellite remote sensing provides a valuable means of continuous and large-scale monitoring of surface water dynamics. Spectral bands and indicators enable the discrimination of various types of land cover and their changes, including the appearance of flash water. The proposed methodology involves time-series analysis of open satellite data (Sentinel-2), spatial statistics, and comparative analysis of selected indicators and spectral bands used for water detection. Additionally, daily precipitation data from a local meteorological station were integrated into the analysis to evaluate the accuracy of surface water detection. Regression analysis has been done to analyse the relationship between the accumulation of water and rainfall, and therefore assess whether the indicators tested are suitable. 

The test analysis covers the period August 2015 - December 2023. The area of interest is cultivated. Crop fields, after harvest and before the vegetation season, are mostly bare soil, which can be mistakenly interpreted using basic plant moisture indices. Therefore, more combinations were tested and verified with rainfall data. By incorporating meteorological data, we aim to establish a more comprehensive understanding of the temporal variability in the presence of surface water near the gas storage site. The findings of this study contribute to the development of a complex monitoring system at a UGS site.

The research has been carried out under the project acronym CLEAR (grant no WPN/4/67/CLEAR/2022) financed from the Polish National Centre for Research and Development.

How to cite: Kaczmarek, A.: Flash Water Detection in Mining Areas Using Satellite Imagery and Meteorological Data , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15004, https://doi.org/10.5194/egusphere-egu24-15004, 2024.

EGU24-17054 | Orals | ERE4.5

Exploration and reevaluation of a tailing storage facility from a high-sulfidation epithermal gold deposit 

Petya Gutzmer, Kai Bachmann, Raimon Tolosana-Delgado, Laura Tusa, Cecilia Contreras, Philipp Büttner, and Jens Gutzmer

Reevaluating tailings material originating from a high-sulfidation epithermal gold deposit has unveiled the potential for a holistic remining endeavour. The primary objective of this operation would be the mitigation of minerals containing penalty elements, specifically sulphur in pyrrhotite, a major contributor to acid mine water drainage, alongside the concentration of precious elements like gold. Furthermore, exploring the applicability of the silicate fraction for industries such as ceramics, glass, and geopolymer production has been considered.

To accomplish these objectives, an initial drill core campaign featuring six drill holes was executed, accompanied by a thorough material characterization using automated mineralogy, geochemical assays, and hyperspectral analysis. The subsequent step involved a geometallurgical domaining process based on 64 geochemical assays, particle size measurements, and mineralogy assessments. A Mahalanobis distance hierarchical cluster analysis was employed to differentiate domains, and predictions for these domains were extended to all hyperspectral imaging samples.

The outcome of this comprehensive approach revealed the delineation of four distinct domains, each characterized by variations in modal mineralogy and trace elemental contents. This strategic analysis provides valuable insights into the heterogeneity of the tailings material, laying the groundwork for targeted interventions to address environmental concerns and maximize the extraction of valuable resources.

How to cite: Gutzmer, P., Bachmann, K., Tolosana-Delgado, R., Tusa, L., Contreras, C., Büttner, P., and Gutzmer, J.: Exploration and reevaluation of a tailing storage facility from a high-sulfidation epithermal gold deposit, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17054, https://doi.org/10.5194/egusphere-egu24-17054, 2024.

EGU24-17315 | Posters on site | ERE4.5

A Web-Based Tool for Assessing Sustainability in Secondary Raw Material Recovery Projects Using the UNFC Framework 

Soraya Heuss-Aßbichler, Laddu Bhagya Jayasinghe, Alireza Sobouti, Iman Dorri, and Juan Antonio Munizaga-Plaza

The increasing demand for raw materials in our society and the requirements for supply security in particular regarding the critical raw materials require the implementation of sustainable resource management in the sense of the best possible conservation of natural resources as well as the promotion of recycling and recovery of valuable materials from waste. In the mining sector, classification systems like CRIRSCO were introduced to communicate the viability of projects. In the realm of resource classification, the United Nations Framework Classification of Resources (UNFC) stands as a crucial tool, offering a principles-based approach to classifying the viability of any kind of resource development projects including renewable energy or groundwater. By systematically classifying projects based on their environmental, socio-economic, and technical aspects, the UNFC provides decision-makers with valuable insights for making choices regarding their viability and offers the opportunity to take sustainability aspects into account. A consistent evaluation and classification of projects according to the same premises as for primary raw materials can significantly contribute to the efficiency of initiatives for the recovery and recycling of secondary raw materials including mining waste. There is a Guidance[1] for the Application of the United Nations Framework Classification for Resources (UNFC) for Mineral and Anthropogenic Resources in Europe. However, it doesn’t include end-of-life products as anthropogenic resources. There are also no instructions on how to evaluate and classify SRM projects.

To bridge the gap, our focus has centered on the development of a web-based tool explicitly designed for the assessment of SRM recovery projects in line with the principles of the UNFC. A seven-stage approach was developed to streamline the evaluation process and by that, improve the accessibility and applicability of the classification system. Its design, features, and functionalities are tailored to ensure a user-friendly interface. Users are guided from the outset by defining the project and its systems boundaries, formulating the project’s objective and the context of evaluation, including the choice of the controlling factors, to carry out a thorough analysis of SRMs and thus align their initiatives with the principles of the UNFC. At the end, a template is available for reporting.

This poster presentation aims to emphasize the versatility and effectiveness of our web-based tool through a practical example, using a publication developed to classify a tailings storage facility in Germany. Through an interactive demonstration, the user-friendly interface, the power of customizable inputs, and the seven coordinated steps that guide users in assessing the feasibility and viability of secondary raw material projects will be discussed. Attendees will gain a deeper understanding of how the tool facilitates informed decision-making by providing a systematic approach to evaluating projects involving secondary raw materials, aligning with the principles of the UNFC.


[1] https://unece.org/sites/default/files/2022-11/UNFC%20GUIDANCE%20EUROPE-FINAL.pdf

How to cite: Heuss-Aßbichler, S., Jayasinghe, L. B., Sobouti, A., Dorri, I., and Munizaga-Plaza, J. A.: A Web-Based Tool for Assessing Sustainability in Secondary Raw Material Recovery Projects Using the UNFC Framework, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17315, https://doi.org/10.5194/egusphere-egu24-17315, 2024.

EGU24-17319 | Posters on site | ERE4.5

Converting mine shaft into compressed air energy storage – shafts screening and assessment 

Marcin Lutyński and Konrad Kołodziej

Increase in the share of renewables in the energy mix of European Union gained interest in the large scale energy storage technologies. One of the promising technologies is the Compressed Air Energy Storage (CAES) where in conventional approach compressed air is stored in the cavern. An alternative solution that was developed at the Silesian University of Technology is to use a post-mining shaft for adiabatic compressed air energy storage (A-CAES). Availability of post-mining infrastructure and large number of shafts in European coal basins (over 178 shafts only in the Upper Silesia Coal Basin) shows a significant potential of this solution. In order to select a proper shaft with a considerable volume a screening tool was developed that uses multicriteria analysis for an initial selection of shafts that could be used for this technology. This tool takes into account shaft depth, diameter, type of shaft collar lining, water inflow rates and other criteria that are important for safety and energy capacity of the system. The presentation shows results of analysis of the shafts screening tool and case study for one of the shaft located in Poland.

How to cite: Lutyński, M. and Kołodziej, K.: Converting mine shaft into compressed air energy storage – shafts screening and assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17319, https://doi.org/10.5194/egusphere-egu24-17319, 2024.

EGU24-17569 | Orals | ERE4.5

Certification systems for the ecological rehabilitation of mined areas 

Michail Galetakis, Emmanouil Varouchakis, Christos Roumpos, and Georgios Louloudis

Ecological reclamation of mined areas is a critical step in restoring environmental balance. Mining companies and operators are usually required to restore their sites to a condition that supports an agreed post-mining land use and to mitigate environmental and social impacts. To achieve rehabilitation approval, specific closure objectives and completion criteria must be defined to determine whether the necessary outcomes have been attained.  Certifications in this area typically focus on ensuring that reclamation processes meet certain standards and effectively restore the ecosystem. Some well-known certifications include the Society for Ecological Restoration (SER) certification and the International Standards Organisation (ISO) environmental management system certification. SER certification often assesses projects based on ecological integrity, historical and cultural considerations, and sustainable management. It ensures that reclamation efforts promote biodiversity, soil health and overall ecosystem resilience. On the other hand, older ISO certifications, particularly ISO 14001, focus on environmental management systems and ISO 26000 on social responsibility. While not specific to ecological reclamation, it provides a framework for organisations to develop and implement environmentally responsible practices. Recent ISO standards like 21795:2021 specify the framework and the processes involved in mine closure and reclamation planning for new and operating mines, and they also provide requirements and recommendations.  These certifications play a critical role in establishing credibility and ensuring that ecological reclamation efforts meet recognised standards. They also contribute to the broader goal of sustainable mining practices. This study examines the evolution of standards for the certification of rehabilitation of mined sites, reflecting the growing awareness of environmental impact and the shift toward sustainable practices.

How to cite: Galetakis, M., Varouchakis, E., Roumpos, C., and Louloudis, G.: Certification systems for the ecological rehabilitation of mined areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17569, https://doi.org/10.5194/egusphere-egu24-17569, 2024.

EGU24-19060 | ECS | Posters on site | ERE4.5

The bioleaching of metals from organic-rich black shale by Pseudomonas fluorescens 

Mateusz Wolszczak, Anna Potysz, and Grzegorz Lis

Biohydrometallurgy is known as one of techniques of beneficiation of metal ores, utilizing microorganism activity to enhance the extraction of metal ions from ore minerals. The method is widely known from its economic and environmental advantages in comparison to other beneficiation methods, i.e. pyrometallurgy. The development of biohydrometallurgy applications for the mining industry has continued since the eighties when several bioleach operations for low-grade copper ores and refractory gold concentrates have been commissioned. Although significant extraction rate, biological-induced leaching does not constitute main processing technique due to economic reasons, what drive researchers to searching novel ways to enhance the efficiency of metal recovery.

 

This research came with the idea of improving the efficiency of metal bioleaching by presence of dispersed organic matter naturally occurring in some rocks. Main hypothesis of the research assumes using dispersed organic matter as a source of organic carbon by heterotrophic bacteria that could further enhance dissolution of ore minerals. The idea came from both facts: consumption and metabolic utilization of dispersed organic matter by heterotrophic microorganisms and influence of consumed organic compounds on microbial activity e.g. secretion of siderophores (metal chelating compounds, crucial for solubilization metal ions and thus acceleration the metal leaching).

 

The examined rock is metalliferous-bearing shale enriched in dispersed organic matter (with average TOC parameter from few to even 30 wt.%). Two shale samples different in their metal and organic matter quantity were chosen for testing the hypothesis. The potential of black shale for bioleaching was examined through series of incubation experiments. Different experiment conditions were applied, involving both autotrophic (Acidithiobacillus thiooxidans) and heterotrophic (Pseudomonas fluorescens) bacteria and different medium compositions (with presence and absence of organic nutrient in particular).

 

The incubation experiment took place in a shaker incubator at a controlled temperatures for a period of five weeks. After the incubation experiment the leachates were collected and analyzed for the concentrations of eight metals: copper, lead, zinc, molybdenum, arsenic, nickel, cobalt and vanadium. The metal recovery percent features variation depending on shale sample, specific metal, and incubation condition. The highest metal recovery was achieved for heterotrophic bacterium in case of copper and molybdenum and for autotrophic one in case of arsenic, while rest of metals showed insignificant recovery. Lack of organic nutrients weakened the activity of P. fluorescens compared to bacterium supplied with organic nutrient, however metal leaching was still maintained.

How to cite: Wolszczak, M., Potysz, A., and Lis, G.: The bioleaching of metals from organic-rich black shale by Pseudomonas fluorescens, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19060, https://doi.org/10.5194/egusphere-egu24-19060, 2024.

EGU24-19879 | Posters on site | ERE4.5

Erosion rates estimates on a post-mining site 

Thomas Grangeon, Tur Raphaël, Louis De Lary de Latour, Florian Masson, and Cerdan Olivier

Mining waste serves as a significant example illustrating the transport of contaminants in association with rainfall, runoff, and erosion. Due to past or ongoing metal extraction activities, mining waste deposits are widespread across numerous countries. Rainfall events affecting these areas can lead to environmental concerns due to both liquid and particulate transfers. Acid mine drainage has been extensively researched in this context, illustrating the transfers linked to the liquid phase. Furthermore, rock crushing and high metal concentrations in the waste create materials with minimal cohesion and little vegetation cover, making them highly susceptible to surface erosion. As a result, mine wastes may also be particularly prone to contaminant transport in the particulate phase, although such transfers have received comparatively less attention than liquid transfers. Assessments of surface erosion caused by rainfall and runoff are still lacking in literature, which limits our comprehension and ability to model these processes in these unique environments.

We propose estimating erosion rates on a 3.8-hectare post-mining site located in central France. Given the high erosion rates, we opted to combine two distinct methodologies based on elevation differences: i) erosion pins for simple and reliable but localized estimates of erosion rates, and ii) differences in Digital Elevation Models (DEMs). In this study, the DEM was obtained using a novel handheld laser scanner. Both methods yielded results within the same range, indicating substantial erosion rates and thereby highlighting the significance of particulate transport. Depending on the local circumstances (e.g., tailings characteristics, tailing-to-stream connectivity), future studies should consider both liquid and particulate transport from post-mining sites to develop relevant mitigation strategies.

How to cite: Grangeon, T., Raphaël, T., De Lary de Latour, L., Masson, F., and Olivier, C.: Erosion rates estimates on a post-mining site, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19879, https://doi.org/10.5194/egusphere-egu24-19879, 2024.

EGU24-20090 | ECS | Posters on site | ERE4.5

Towards migration of fines within a soil matrix 

Shane Aulestia, Jasmina Toromanovic, and Jan Laue

Suffusion is an internal erosion mechanism observed in embankment dams, caused by washing out fine-grained particles within the dam core as a consequence of seepage with various hydraulic gradients. The initiation of internal erosion is conditional upon three primary factors: grain size distribution, stress conditions, and hydraulic gradient. Graded moraines, such as glacial tills, exhibit an increased susceptibility to suffusion when compared to other soil types used in dam construction. Many Swedish embankment dams in mining and hydropower industry were constructed with glacial till cores over 50 years ago, lacking specific guidelines related to grain size boundaries for core and filter materials. This deficiency has given rise to instances of internal erosion, therefore elevating safety concerns.

Previous research aimed to enhance dam safety by exploring the susceptibility of glacial till soils to suffusion. Silva (2022) reviewed existing methods for assessing soil susceptibility, comparing testing conditions, and presents an experimental study on critical hydraulic gradients for suffusion initiation in glacial till soils. Results indicate the critical hydraulic gradient depends upon testing conditions, including axial loading, the rate of gradient increase, and time intervals. Furthermore, it underscores the efficacy of Kenney and Lau (1985, 1986) method for assessing suffusion susceptibility. These insights offer valuable contributions to the assessment and mitigation of internal erosion in embankment dams, thereby addressing a significant safety concern within the Swedish dams infrastructure.

Silva (2022) has offered valuable insights into suffusion phenomena while the intricacies of erosion processes remain unclear, hindering the implementation of rehabilitation measures to ensure the longevity of embankment dams. A follow-up project utilizing the advantages of transparent soil seeks to further comprehend the migration of fines within a soil matrix. Transparent soils, emerging as a viable alternative with likely properties to sand and clays, consist of a two-phase medium by refractive index allow solids to represent the soil skeleton and a fluid solution to mimic pore fluids. Various solids, such as amorphous silica, silica gel, hydrogel, fused quartz, and laponite, have been employed in conjunction with fluid solutions, depending on the solid, as mineral oil and paraffinic solvent, calcium bromide brine, sucrose solution, or water.

Transparent soils offer the potential to replicate the behavior of glacial till cores employed in embankments, particularly those designed for the storage of tailings material in the mining industry, and water retention for hydropower. The applicability of these findings may address and enhance rehabilitation measures in such structures, which are imperative to mitigate potential socio-economic and environmental ramifications in the event of failure. Given the escalating global demand for mining resources and renewable energy, proactive measures are essential to predict long-term issues looking for a more sustainable and efficient construction methodologies to extend infrastructure lifespans.

How to cite: Aulestia, S., Toromanovic, J., and Laue, J.: Towards migration of fines within a soil matrix, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20090, https://doi.org/10.5194/egusphere-egu24-20090, 2024.

EGU24-20831 | Orals | ERE4.5

Post-mining earthquakes and changes in observed vertical ground displacements during the period of mine flooding  

Violetta Sokoła-Szewioła, Zbigniew Siejka, and Patrycja Jarczyk

The period of coal mine closures can be accompanied by many hazards, including the post-mining seismic hazard. Seismic phenomena, particularly during mine flooding, are felt by people, can cause minor or severe damage to buildings and affect shallow mine workings, and can cause reactivation of shallow mine workings in the form of sinkholes or other discontinuous deformations. It is therefore important to deepen the knowledge concerning these phenomena, particularly their relationship to surface deformations. This issue was the subject of a European research project with the acronym PostMinQuake financed by the Research Fund for Coal and Steel in 2020- 2023 (Grant Agreement No: 899192). The project involved the study of surface deformation in relation to registered post-mining earthquakes during the flooding of the Kazimierz- Juliusz coal mine. The research area was located in Poland in the area of the Upper Silesian Coal Basin. In this area, continuous monitoring of surface deformation was carried out for more than 2 years on single observation points using GNSS technology. The monitoring was carried out using an automatic GNSS monitoring system developed in the project. 

The paper presents the results of an analysis of the course of changes in vertical displacements at the above-mentioned points, in relation to the post-mining earthquakes registered during the study period. The analysis showed that in the case of more than 58% of the analyzed phenomena in the course of vertical displacements in the period associated with the occurrence of the post-mining earthquake, there were some regularities in the course of these displacements. It was found that, an increased uplift was observed prior to the occurrence of the event, in the next period of time, after the occurrence of the event, an increased increment in subsidence was generally observed, after that period, stabilization of the changes in vertical displacements was observed, as well as a slow increment of subsidence and/or the increment of uplifts. On this basis, it was concluded that there was a relationship between the observed course of displacements and the occurrence of post-mining earthquake. It was assumed that the significant increase in observed uplift can be a predictor of the occurrence of a post-mining earthquake.

 

How to cite: Sokoła-Szewioła, V., Siejka, Z., and Jarczyk, P.: Post-mining earthquakes and changes in observed vertical ground displacements during the period of mine flooding , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20831, https://doi.org/10.5194/egusphere-egu24-20831, 2024.

NH11 – Climate Hazards

EGU24-1647 | ECS | Orals | NH11.2

Decision-Relevant Climate Storylines: Using Seasonal Decision-Scaling to Identify Flood Changes in Uncertain GCM Trends 

Ted Buskop, Frederiek Sperna Weiland, and Bart van den Hurk

As global climate patterns shift, Europe faces increasing challenges from key risks such as floods. However, translating this knowledge into locally usable risk information presents a significant challenge. A primary reason is the large variability associated with climate projection outcomes, particularly in precipitation patterns. This paper introduces a seasonal decision-scaling approach to identify decision-relevant climate storylines for regional discharge patterns, which are crucial in assessing flood risks. We sample scenarios within the uncertainty space of future projections and employ a statistical weather generator to determine probabilistic flow changes. Through the analysis of flow changes across various climate scenarios, we identify the most impactful seasonal climate parameters. These parameters are then used to cluster Global Climate Models, from which we create a set of decision-relevant climatological storylines for floods. A case study in Latvia demonstrates that river flows depend on only a few key seasonal parameters, indicating that the uncertainty can be effectively captured with a select number of distinct climatological storylines. This study not only simplifies the complexity of analysing future climate risks but also enhances the practicality of climate information at the regional level. Our novel seasonal approach to decision-scaling and the selection of decision-relevant climate storylines can be applied globally in areas where GCMs indicate varying climate trends and can also be used for drought analyses. This methodology leads to simpler climate risk information, thereby fostering improved and more robust adaptation strategies.

How to cite: Buskop, T., Sperna Weiland, F., and van den Hurk, B.: Decision-Relevant Climate Storylines: Using Seasonal Decision-Scaling to Identify Flood Changes in Uncertain GCM Trends, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1647, https://doi.org/10.5194/egusphere-egu24-1647, 2024.

EGU24-1978 | ECS | Orals | NH11.2

Forecast-based attribution for midlatitude cyclones 

Shirin Ermis, Nicholas Leach, Sarah Sparrow, Fraser Lott, and Antje Weisheimer

The widespread destruction incurred by midlatitude storms every year makes it an imperative to study how storms change with climate. The impact of climate change on midlatitude windstorms, however, is hard to evaluate due to the small signals in variables such as wind speed, as well as the high interannual variability in Atlantic storms.

Here, we compare multiple severe midlatitude cyclones with both wind and precipitation impacts using forecast-based event attribution. We use a recent version of the ECMWF IFS ensemble prediction system which is demonstrably able to predict the storms, significantly increasing our confidence in its ability to model the key physical processes and their response to climate change.

The comparably high resolution of our simulations, and the focus on individual case studies are particularly useful for dynamically driven events like storms. Our approach is able to combine a dynamical analysis of the storm in question with an analysis of past and future changes.

Our results confirm trends of increased severity in storm impacts found in climate projections but add reliability to the forecasted structure and impacts of the storm. This indicates that forecast-based attribution is viable for reliable and fast attribution systems.

How to cite: Ermis, S., Leach, N., Sparrow, S., Lott, F., and Weisheimer, A.: Forecast-based attribution for midlatitude cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1978, https://doi.org/10.5194/egusphere-egu24-1978, 2024.

EGU24-2476 | ECS | Orals | NH11.2

TC-induced Increases in Extreme Rainfall over the Northeast United States  

Bor-Ting Jong, Hiroyuki Murakami, and Thomas Delworth

The Northeast US has faced the most rapidly increasing occurrences of extreme rainfall within the US in the past few decades. The latest fully-coupled 25-km GFDL SPEAR simulation, possessing 10 ensemble members, presents a good opportunity to study changes in regional extreme rainfall and relevant physical processes in both current and future climates. The surge in extreme rainfall over the Northeast US since the 1990s is primarily linked to events associated with tropical cyclones (TCs). In a future warming climate, the 25-km GFDL SPEAR SSP5-8.5 simulations project unprecedented rainfall events over the Northeast US, driven by increasing anthropogenic radiative forcing and distinguishable from natural variability, by the mid-21st century. Also, the occurrences of extreme rainfall related to both atmospheric rivers and TCs are projected to increase, even though the number of TC in the North Atlantic is projected to decrease in the 25-km GFDL SPEAR SSP5-8.5 simulations. Factors such as enhancing TC intensity, strengthening TC-related rainfall, or/and westward shift in TC tracks may offset the influence of declining TC numbers in the model projections, leading to more frequent TC-related extreme rainfall over the Northeast US in the future. On the other hand, the increase in extreme rainfall linked to atmospheric rivers is projected to outpace that associated with TCs. Given the distinct spatial patterns of rainfall resulting from atmospheric rivers and TCs, shifts in their relative contributions carry profound implications for risk prevention and mitigation strategies.

How to cite: Jong, B.-T., Murakami, H., and Delworth, T.: TC-induced Increases in Extreme Rainfall over the Northeast United States , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2476, https://doi.org/10.5194/egusphere-egu24-2476, 2024.

EGU24-2771 | ECS | Posters on site | NH11.2

Population exposure to extreme precipitation under a changing climate in Eastern China 

Hemin Sun, Ruozi Yang, and Lin Li

Under the global warming, the frequency of extreme precipitation has increased, and the return period of it has changed. The original extreme analysis method based on stationary theory will underestimate the risk of extreme precipitation. Based on observed hourly precipitation data during 1960 to 2019, a non-stationary frequency analysis of the annual maximum (AM) precipitation for China was conducted, then estimate the difference between stationary and non-stationary estimated return periods using Bayesian inference. After that, projected the extreme precipitation risk under different SSP-RCPs scenarios by the CMIP6 models. The results shown that the trends of 1-, 2-, 3-, 6-, 12-, 24-, 48-, 96- and 168-hr AM precipitation in China are complex. The shorter the duration, the more stations that show an upward trend. For a 20-yr to 100-yr return period of 1-hr extreme precipitation, the difference between the non-stationarity and stationarity extreme precipitation is large, and at the station with the upward trend that a stationary assumption may lead to underestimation of extreme precipitation about 32%; the average difference over 24-hr is relatively small, and the difference at station with downward trend is about -17%~-23%. The difference between the extreme precipitation return period under non-stationarity and stationarity assumption decreases with the extension of the duration, and the uncertainty increases as the return period increases in all conditions. The ensembled GCMs show that the precipitation in the 21st century show a fluctuating upward trend in China. The 100-yr return period of 24 -, 48 -, 96 - and 168-hr extreme precipitation changed differently under different scenarios in the early period (2021-2040), the middle period (2041-2060) and the later period (2081-20100). The area exposed to extreme precipitation with 1995 to 2014 100-yr return period under different scenarios varies greatly, among which SSP5-8.5 is the largest and SSP1-1.9 is the smallest. In the short, medium and long period, with the increase of extreme precipitation intensity, the exposure area is increasing. Because of the population change, the characteristics of the exposed population and the exposed area are different. In the medium period, the exposed population is also the largest as the population reaches the peak. Under the assumption of a non-stationary climate, the social-economic exposure of extreme precipitation return level and return period providing new methods and scientific information for design, decision-making, and assessing the impacts of climatic events.

How to cite: Sun, H., Yang, R., and Li, L.: Population exposure to extreme precipitation under a changing climate in Eastern China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2771, https://doi.org/10.5194/egusphere-egu24-2771, 2024.

The impacts of the western North Pacific (WNP) tropical cyclone (TC) on East and Southeast Asian inland regions are analyzed. Here, based on a stringent TC selecting criterion, robust increase of TC-related inland impacts between 1979 and 2016 over East and Southeast Asian regions have been detected. The storms sustained for 2–9 h longer and penetrated 30–190 km further inland, as revealed from different best track datasets. The most significant increase of the TC inland impacts occurred over Hanoi and South China. The physical mechanism that affects TC-related inland impacts is shortly discussed. First, the increasing TC inland impacts just occur in the WNP region, but it is not a global effect. Second, besides the significant WNP warming effects on the enhanced TC landfall intensity and TC inland impacts, it is suggested that the weakening of the upper-level Asian Pacific teleconnection pattern since 1970s may also play an important role, which may reduce the climatic 200 hPa anti-cyclonic wind flows over the Asian region, weakening the wind shear near the Philippine Sea, and may eventually intensify the TC intensity when the TCs across the basin. Moreover, the TC inland impacts in the warming future are projected based on a high-resolution (20 km) global model according to the Representative Concentration Pathway 8.5 scenario. By the end of the 21st century, TC mean landfall intensity will increase by 2 m/s (6%). The stronger storms will sustain 4.9 h (56%) longer and penetrate 92.4 km (50%) farther inland, thereby almost doubling the destructive power delivered to Asian inland regions. More inland locations will therefore be exposed to severe storm–related hazards in the future due to warmer climate. Long-term planning to enhance disaster preparedness and resilience in these regions is called for.

How to cite: Chen, J., Tam, C.-Y., Chueng, K., and Wang, Z.: Changing impacts of tropical cyclones on East and Southeast Asian inland regions in the past and a globally warmed future climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3003, https://doi.org/10.5194/egusphere-egu24-3003, 2024.

EGU24-3643 | ECS | Orals | NH11.2 | Highlight

Storylines of Hurricane Sandy under climate change to assess compound coastal flooding impacts in New York City 

Henrique Moreno Dumont Goulart, Irene Benito Lazaro, Karin van der Wiel, Linda gavras-van Garderen, Dewi Le Bars, Elco Koks, and Bart van den Hurk

While high impact weather events pose considerable challenges to society, we have limited understanding of their risks and potential impacts due to their rare nature. Climate change, in combination with internal climate variability, increases the uncertainty around these events and their impacts in the future. Storylines offer a non-probabilistic approach into estimating and understanding such events and their impacts conditioned on specific assumptions and scenarios, such as climate change and internal climate variability. Our study presents storylines of Hurricane Sandy (2012) to assess compound coastal flooding's impact on New York City's critical infrastructure under different scenarios. These include the effects of climate change, such as changes in storm dynamics and sea-level rise, as well as internal climate variability, accounting for variations in storm intensity and location. We use a comprehensive modelling framework, spanning from the driving climatological conditions to compound flooding and societal impacts. Our findings indicate that a 1m sea level rise could increase flood volumes by an average of 4.2 times, while internal climate variability could lead to a 2.5-fold increase in flood volumes. We find that impacts on critical infrastructure depend not only on flood volume, but also on the predominant flood hazard in each storyline, like storm surge or local precipitation. This study highlights the importance of developing societal-relevant scenarios that consider both climate change and internal variability. Such scenarios, coupled with a comprehensive modelling framework, provide useful information for decision making when preparing for high impact events in the future.

How to cite: Moreno Dumont Goulart, H., Benito Lazaro, I., van der Wiel, K., gavras-van Garderen, L., Le Bars, D., Koks, E., and van den Hurk, B.: Storylines of Hurricane Sandy under climate change to assess compound coastal flooding impacts in New York City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3643, https://doi.org/10.5194/egusphere-egu24-3643, 2024.

The study focuses on the distribution of landslide susceptibility in the future under climate change in the Laonong river watershed (abbreviated as LRW) in southwestern Taiwan. LRW is a mountainous watershed prone to sediment disaster and had caused serious sediment disaster during 2009 Typhoon Morakot. The study used the downscaled daily rainfall data provided by Taiwan Climate Change Estimation Information and Adaptation Knowledge Platform (TCCIP) as the daily rainfall data in the future in LRW. We combined the daily rainfall data and the landslide susceptibility model in the LRW to assess the distribution of landslide susceptibility in the future in the LRW.

The landslide susceptibility model was composed of 9 landslide-related factors, including elevation, slope, aspect, geological setting, landuse, Topographic Wetness Index, distance from the rivers, landslide frequency, and daily rainfall. This study built the landslide susceptibility model of LRW based on the daily rainfall data and landslide inventory after 2009 Typhoon Morakot. The AUC (area under receiver operating characteristic curve) of the landslide susceptibility model is 0.712, and the accuracy by using the confusion martix is 0.731.

The study also compared the rainfall characteristic in the past (the rainfall data from 1998 to 2022) and the future (the downscaled rainfall data from 2023 to 2100) in the LRW. No significant difference shows between the characteristic of average annual rainfall in the past and the future, but the monthly rainfall is obviously concentrated in the rainy season, i.e. from May to October. The occupied percentage of accumulated rainfall in the rainy seasons to annual rainfall in the future is larger by 0.3% to 4.1% than that in the past. The daily rainfall with 50 years return period in the future is larger by 56% to 125% than that in the past.

The study combined the daily rainfall data in the future under climate change scenarios SSP126 and SSP585 and the landslide susceptibility model based on 2009 Typhoon Morakot to assess the distribution of landslide susceptibility in the LRW in the future. The area of middle-high and high landslide susceptibility in the LRW increased obviously based on the distribution of landslide susceptibility in the future under climate change. The average landslide susceptibility value in the future in the LRW is larger by 1.7 times than that in the past.

How to cite: Wu, C.: Assessment of Landslide Susceptibility under Climate Change in the Laonong river watershed in Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3729, https://doi.org/10.5194/egusphere-egu24-3729, 2024.

Boreal summer circulation over the Eastern Mediterranean is characterized by background subsidence, which is linked to both mid-latitude wave activity and to convective activity generated in the tropical belt. Background subsidence is accompanied by northerly winds over the Aegean Sea and the Eastern Mediterranean basin, which bring cooler air from the Eurasian landmass towards the Middle East and northeast Africa. These winds, also known as Etesians, can thus mitigate heatwaves in the region. Using the Peter and Clark momentary conditional independence (PCMCI) algorithm, the causal drivers of the Etesians have been identified (Di Capua et al. in preparation). This set of causal drivers consists of (i) Rossby waves propagating from North America via the North Atlantic and (ii) convective activity over the Indian summer monsoon (ISM) region, which affects the Eastern Mediterranean circulation via a geopotential height ridge forming over the Middle East. In this new work, the aim is first to quantify the effect of enhanced Etesians in mitigating heatwaves in the Middle East. Secondly, given the causal pathway identified between the Etesians and the ISM, the aim is to quantify the effect of interannual ISM activity as a potential amplifying (or inhibiting) factor of heatwaves activity. As future projection under different anthropogenic global warming scenarios predict an intensification of rainfall activity in the ISM region, it is crucial to understand how the ISM-Mediterranean teleconnection can affect heatwave activity in the Eastern Mediterranean.

 

Di Capua G., Tyrlis E., Matei D., Donner R. “Tropical and mid-latitude causal drivers of the summer Etesians in the eastern Mediterranean” (in preparation)

How to cite: Di Capua, G.: Indian summer monsoon as a driver of summer heatwaves in the Eastern Mediterranean , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5266, https://doi.org/10.5194/egusphere-egu24-5266, 2024.

How can we best apply our science to predicting risks of extreme behaviour in a system as complex as the climate? It would be desirable to be able to represent all of our knowledge about the risks so that it can be applied to enable effective decision-making. Risk assessments often consider only the range of behaviour displayed by climate models, but a substantial part of the risk seems likely to be due to the possibility of the real world veering outside this range. It will be illustrated how implicitly ignoring this component would lead to risks being systematically underestimated, and how multi-model and initial condition large ensembles can be misleading. Recent work on storyline methods has illustrated potential ways to think beyond numerical model simulations, but downplays the quantification of event risks. But since we generally lack clear bounds on how intense extreme events can be, this seems to leave open the question of just how intense should the events be that are considered in analyses. It also does not seem to satisfy decision analyses that seek to quantitatively trade off protection against extremes against other benefits. This presentation considers how we can go beyond counting events in simulations, using tools such as climate models to inform our future projections without being constrained to ignore possible outcomes that they cannot simulate, whilst also retaining as much quantitative knowledge about event risks as possible and acknowledging when ambiguities become very large. Frameworks from philosophy and decision analysis will be surveyed and it will be discussed how these may help to show a way forward in our climate prediction predicament. It will be suggested that climate science should aim to be pluralistic in the knowledge frameworks it considers, to be of use to the broadest possible range of decision making.

How to cite: Watson, P.: Frameworks for considering extreme weather risks in future climates given major uncertainties, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5428, https://doi.org/10.5194/egusphere-egu24-5428, 2024.

EGU24-6217 | ECS | Orals | NH11.2

An outlook into Iberia’s population exposure to hot and dry extreme weather events at the end of the century 

Virgílio A. Bento, Daniela C.A. Lima, and Ana Russo

Climate change is a pressing concern impacting contemporary society, with anticipated global warming trends poised to exacerbate environmental challenges. This study explores the implications for the Iberian Peninsula (IP) at the close of the 21st century, exploring the effects of warming and drying trends on population exposure to hot and dry extreme weather events (HDEs). Despite a potential decline in overall population across the IP, warming and drying trends are expected, as highlighted by various studies. Projections indicate increased temperatures and aridity, and a surge in the frequency and intensity of droughts and heatwaves.

For this research, two EURO-CORDEX experiments (13 simulations RCM-GCM (Regional Climate Models – Global Climate Models)) were considered, encompassing different time periods, namely the historical period from 1971 to 2000 and the projected end of the century period spanning 2066 to 2095, aligned with two distinct emission scenarios: RCP4.5 and RCP8.5. The Standardized Precipitation-Evapotranspiration Index (SPEI) is used to quantify the duration of droughts, and the number of hot days is used to quantify warm months. Two representative concentration pathways (RCPs), specifically RCP4.5 and RCP8.5, are employed to delineate distinct greenhouse gas emission trajectories. A weighted multi-variable multi-model ensemble was used with the aim of improving climate simulations and providing reliable projections over the IP.

The findings of this study reveal a notable projected surge in population exposure to both droughts and warm months throughout the entire IP by the close of the century, with climate change identified as the predominant factor for this escalation. Specific regions may undergo a particularly pronounced increase in drought exposure, while instances of exposure to warm months may surpass the 500% mark. Assessment of exposure to future droughts and warm months indicates that climate change plays a predominant role, accounting for a significant percentage of exposure in both Portugal and Spain.

In conclusion, population exposure to droughts and warm months is projected to escalate significantly in the IP by the end of the century, primarily driven by climate change. The study also emphasizes the critical need for mitigation and adaptation strategies to address the potential consequences, particularly in sectors such as water resources, agriculture, human health, and wildfire management. The findings underscore the urgency for regional authorities, policymakers, and society to prioritize adaptation planning and develop a comprehensive understanding of the vulnerabilities and potential strategies to cope with the challenges posed by hot and dry extreme events.

This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). This work was performed under the scope of project https://doi.org/10.54499/2022.09185.PTDC (DHEFEUS) and supported by national funds through FCT. DL and AR acknowledge FCT I.P./MCTES (Fundação para a Ciência e a Tecnologia) for the FCT https://doi.org/10.54499/2022.03183.CEECIND/CP1715/CT0004 and https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006, respectively.

How to cite: Bento, V. A., Lima, D. C. A., and Russo, A.: An outlook into Iberia’s population exposure to hot and dry extreme weather events at the end of the century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6217, https://doi.org/10.5194/egusphere-egu24-6217, 2024.

EGU24-6242 | ECS | Orals | NH11.2 | Highlight

Global warming increases the proportion of more damaging heat extremes 

Yinglin Tian, Axel Kleidon, Corey Lesk, Sha Zhou, Xiangzhong Luo, Sarosh Alam Ghausi, Guangqian Wang, Deyu Zhong, and Jakob Zscheischler

Extreme heat events often result in considerable harm to both ecosystems and human populations. Heat extremes arise from diverse processes, resulting in heatwaves with distinct characteristics and therefore potentially strongly varying impacts and trends. Relying on the surface energy balance decomposition of temperature, we categorize terrestrial summer heat extremes from 1979 to 2020 into four types: Sunny-humid (36.5%), Sunny–dry (24.5%), Advective (25.0%), and Adiabatic (14.0%). Sunny-humid and Sunny-dry heat extremes are characterized by high-pressure systems and diminished cloud cover, resulting in heightened solar radiation. However, they diverge concerning soil moisture and latent heat fluxes. Conversely, the latter two types emerge from advective heating due to anomalies in the horizontal wind and adiabatic heating from air subsidence, respectively. Both are correlated with an upsurge in downward longwave radiation. Sunny-dry and Advective heat extremes lead to more detrimental effects on terrestrial ecosystem production (reducing net ecosystem uptake by 0.09 gC/m2/d and decreasing maize yield by 7.6%) and human health (raising the thermal stress index by 8.6 K and increasing human mortality by 3.3%), respectively.

State-of-the-art climate models (CMIP6) generally replicate the relative proportions and the geographical distributions of the four types of heatwaves but tend to underestimate the Advective heatwave days. Under a high emission scenario (SSP585), the proportion of Sunny-dry and Advective heat extremes increases by 3.4% and 1.5%, respectively, while Sunny-humid and Adiabatic heatwave days decrease by 3.2% and 1.7%, respectively. This suggests, on top of the already expected increase in heatwaves, additional heat stress on both terrestrial carbon uptake potential and human populations. Our findings underscore the importance of distinction among different types of heat extremes and their impacts, paving the way to develop tailored adaptive.

How to cite: Tian, Y., Kleidon, A., Lesk, C., Zhou, S., Luo, X., Alam Ghausi, S., Wang, G., Zhong, D., and Zscheischler, J.: Global warming increases the proportion of more damaging heat extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6242, https://doi.org/10.5194/egusphere-egu24-6242, 2024.

EGU24-7321 | ECS | Posters on site | NH11.2

Physical Drivers and Future Risks of the 2014-like Southeast Asia Drought 

Shuping Ma, Xiao Peng, and Xiaogang He

The Western Malay Archipelago undergoes a severe drought in early 2014, with Singapore experiencing its longest recorded drought period of 62 days from January 13 to March 15, a record dating back to 1929. Here we conduct in-depth analysis to examine the physical drivers of this unprecedented drought. We find that the 2014 drought is primarily due to anomalously high pressure over Southeast Asia. This condition induces the convergence of mid-to-upper level airflows, which then intensifies the subsidence. Simultaneously, the dry and cold airflows from the western and northern continents further exacerbated the subsidence. Anomalous geopotential heights are closely related to the North Atlantic Oscillation (NAO) and the Madden-Julian Oscillation (MJO): during the drought, Atlantic sea temperatures exhibit an abnormal tripole pattern, with the MJO in phases 7 and 8. The wave activity flux analysis show that, the NAO induces an eastward-propagating wave train at mid to low latitudes, leading to suppressed convection over the tropical Indian Ocean and a positive anomaly in geopotential height over Southeast Asia. In addition, we find that the seasonal averaged vertical motion (Omega) and relative humidity (RH) anomaly during 2014 Jan-Mar is unprecedented in the observational record from 1980 to 2020, with a return period of Omega and RH likely (>66% probability) in the range of 43~98 years with a median of 147 years. Climate projections based on the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models indicate that dynamical component under global warming is the main driver increasing the frequency of 2014-like droughts in the future.

How to cite: Ma, S., Peng, X., and He, X.: Physical Drivers and Future Risks of the 2014-like Southeast Asia Drought, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7321, https://doi.org/10.5194/egusphere-egu24-7321, 2024.

EGU24-7944 | ECS | Orals | NH11.2

Anticipating the unseen: a community review on how to better prepare for exceptional weather events 

Timo Kelder, Lisette Klok, Louise Slater, Vikki Thompson, Henrique M. D. Goulart, Laura Suarez-Gutierrez, Rob Wilby, Dorothy Heinrich, Erin Coughlan de Perez, Liz Stephens, Ed Hawkins, Stephen Burt, Bart van den Hurk, Hylke de Vries, Karin van der Wiel, and Erich Fischer

Extreme weather events of unprecedented intensity in historical records can have major impacts on society and ecosystems. While adaptation plans often consider past trends in extreme weather events, few consider the possibility of exceptional extremes. This oversight leaves society underprepared and ill-equipped to handle ‘surprising’ events. There is a long history of science inquiry into the question of what low likelihood weather events are possible. Here, we present an overview of the methods used to identify exceptional weather events. We discuss tools for scientists, practitioners and policy-makers to ‘see the unseen’ and evaluate unexpected yet plausible disruptive events. We first discuss existing approaches for estimating rare extremes; then give an example for exceptional heat in The Netherlands; and finally outline how this knowledge can be leveraged to strengthen resilience and adaptation efforts.

How to cite: Kelder, T., Klok, L., Slater, L., Thompson, V., Goulart, H. M. D., Suarez-Gutierrez, L., Wilby, R., Heinrich, D., Coughlan de Perez, E., Stephens, L., Hawkins, E., Burt, S., van den Hurk, B., de Vries, H., van der Wiel, K., and Fischer, E.: Anticipating the unseen: a community review on how to better prepare for exceptional weather events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7944, https://doi.org/10.5194/egusphere-egu24-7944, 2024.

EGU24-11146 | ECS | Orals | NH11.2

Projections of the large-scale drivers influencing the North Atlantic tropical cyclones 

Naveen Goutham, Hiba Omrani, Lila Collet, and Carole Legorgeu

Understanding the evolution of tropical cyclones (TC) over the 21st century under a changing climate is essential to improve the resilience of the North American electricity system. In this regard, several studies have projected future changes in TC behavior by detecting and tracking their evolution using climate simulations. One of the key limitations of climate models, specifically attributed to their limited spatial resolution, is that they are unable to simulate all the non-linear interactions between various components of the Earth system. Hence, in this study, instead of tracking TCs in the coarse spatial-resolution climate models, we investigate the evolution of the large-scale drivers influencing the North Atlantic TCs over the mid-future (2041-2060) and far-future (2081-2100). We use five bias-corrected simulations under two shared socio-economic pathway scenarios from the 6th generation Coupled Model Intercomparison Project. In particular, we examine the changes in the large-scale thermodynamic and atmospheric dynamic indicators favorable for TCs, namely sea surface temperature, wind shear, and lapse rate. 

Our results show an increase in the seasonal mean North Atlantic sea surface temperature (between +1 and +3°C), the length of the TC season (between +2 and +5 months), and the ocean heat content (3-6 times) relative to the historical period (1995-2014), while a decrease in the temperature lapse rate (between -0.8% and -1.45%) over both the mid-future and far-future. We find no significant changes in the vertical wind shear under a changing climate. These results suggest an increase in both the frequency and intensity of TCs over the North Atlantic, the latter by 2.6%-5.2% on average. Additionally, our results show a plausible reduction in the conditions favorable for TCs by mitigating from high-emission to moderate-emission scenarios.

How to cite: Goutham, N., Omrani, H., Collet, L., and Legorgeu, C.: Projections of the large-scale drivers influencing the North Atlantic tropical cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11146, https://doi.org/10.5194/egusphere-egu24-11146, 2024.

EGU24-11579 | ECS | Orals | NH11.2

Climate Risk Projections with Pattern Scaling 

Sally Woodhouse, Nicholas J. Leach, Jonathan J. Davies, and James Brennan

The financial sector is becoming increasingly interested in understanding how it is exposed to the risks due to climate change. At Climate X our multi-disciplinary team of hazard and climate scientists work to generate useful projections of risk for a variety of users.

To assess future changes in weather-related hazards we use publicly available climate model outputs from projects such as CMIP and CORDEX. However, these experiments are often not designed with decision-makers and risk assessment at the forefront. Most global climate models are still run at relatively low resolution, whereas decision makers are interested in very local changes (down to asset level). Projects that are run at high resolution, such as HighResMIP and CORDEX, often do not include all the scenarios that decision-makers are interested in and have limited ensemble members.

This talk will explore how the use of pattern scaling can address these limitations. Pattern scaling extracts the signal from local changes in atmospheric variables to global mean temperatures (GMT). It can therefore be used to explore emissions scenarios for which there are limited (or no) GCM runs. This allows us to generate custom scenarios such as global warming levels or a client’s individual projections with only a trend in GMT. Additionally, by extracting temperature uncertainty in the climate sensitivity, local hazard responses and internal variability can be separated.

How to cite: Woodhouse, S., Leach, N. J., Davies, J. J., and Brennan, J.: Climate Risk Projections with Pattern Scaling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11579, https://doi.org/10.5194/egusphere-egu24-11579, 2024.

EGU24-12765 | Posters on site | NH11.2

Assessment of tropical cyclone hazard and risk in a changing climate by means of a new global hybrid model 

Mathieu Boudreault, Roberto Ingrosso, and Francesco Pausata

The future evolution of tropical cyclones (TCs) in a warming world is an important issue, considering their potential socio-economic impacts on the areas hit by these phenomena. Understanding the natural variability and sources of uncertainties over present and future climates and modelling the impacts of TCs remains an important challenge as climate projections do not always provide robust responses about their future evolution. With questions arising about the insurability of coastal communities in the future, risk management requires more robust quantification as to how climate change affects TCs dynamics. It is therefore important to develop TC models that are computationally efficient to provide a full distribution of outcomes for the present and future.

Here, we present a global TC wind model based upon statistical models forced with 10 variables from the 40 members of the Community Earth System Model (CESM) Large Ensemble (LE). The model provides a full description of the frequency, spatial cyclogenesis patterns, tracks and intensities from 1980 to 2060 under the RCP 8.5 emissions scenario. The resulting event sets can therefore be used for risk management in the financial services industry. We find that future frequency of TCs in the North Atlantic is heavily dependent upon how Sea Surface Temperature (SST) and vorticity are accounted for to generate cyclogenesis patterns. Nevertheless, we obtain a larger proportion of Cat. 4-5 storms in the future independently on how SST and vorticity are accounted for with greater intensification along the Gulf of Mexico and the east coast of the U.S. This is consistent with a projected increase (decrease) in the SST (wind shear) over those regions in the CESM-LE. Finally, we find that, especially for Cat. 4+ hurricanes, population growth and climate change should both contribute significantly to the increase in TC risk.

How to cite: Boudreault, M., Ingrosso, R., and Pausata, F.: Assessment of tropical cyclone hazard and risk in a changing climate by means of a new global hybrid model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12765, https://doi.org/10.5194/egusphere-egu24-12765, 2024.

EGU24-13248 | ECS | Orals | NH11.2

On the connection between the jet stream and high-impact, extreme storms in midlatitudes 

Hilla Afargan Gerstman and Daniela I.V. Domeisen

Extreme storms are a major natural hazard in the extratropics. These storms can cause substantial economic damage due to strong winds and flooding, interrupt transportation networks and electricity supply and lead to casualties. Future climate projections predict an extension of the storm track further into Europe posing a potential for increased risk with climate change, especially in winter. However, despite its importance, the connection between extreme, high-impact extratropical storms in midlatitudes and changes in the jet stream remains uncertain. 

Using reanalysis data and multi-model ensemble of climate models under future socio-economic scenarios, we examine the variability of extreme and high-impact storms in the northern hemisphere midlatitude and investigate the connection between jet stream intensity and extreme storm impacts. For this purpose, extreme storm events are diagnosed using the wind field (defined as spatially organized clusters exceeding the 98th percentiles of wind speeds over a specific area for a specific duration). High-impact storms, on the other hand, are identified according to the Emergency Events Database, a global database on natural and technological disasters, for the period 1998 to 2023. This comparison provides insights on extreme storm damage variability in midlatitudes and allows us to explore regional differences in storm damage and future changes. Understanding and connecting the dynamical processes controlling the variability of the jet stream and extreme, high-impact storms in midlatitudes is essential for skillful prediction of these extreme hazards under climate change and for assessing their potentially devastating impacts.

How to cite: Afargan Gerstman, H. and Domeisen, D. I. V.: On the connection between the jet stream and high-impact, extreme storms in midlatitudes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13248, https://doi.org/10.5194/egusphere-egu24-13248, 2024.

EGU24-15240 | Orals | NH11.2

Extreme climatic events and public health in the UK 

Michael Sanderson, Kimberley Eastaugh, Rosa Barciela, and Dan Bernie

Extreme events such as storms, heatwaves and flooding are increasing in severity worldwide owing to climate change. This study evaluates impacts of future projected climate events that could pose a threat to public health in the UK. An aging population means more people will be susceptible to trips and falls during and following extreme climatic events, such as being blown over during high winds. Data from the UK Climate Projections 2018 (UKCP18) were used to analyse daily extreme events for the current climate and assess projected changes in these events during the remainder of the 21st century. The hazards studied are heat and cold waves, heat stress related events, extreme precipitation and extreme wind speeds and gusts. The use of the latest convection-permitting climate model simulations (2.2 km resolution) from UKCP18 allows better simulation of localised events which could lead to differing levels of impact on public health across the UK. Under a high emission scenario (RCP8.5), extreme heat and precipitation events are projected to increase in frequency (and in some cases duration) throughout the 21st century. Alternately, extreme cold and cold wave events could reduce in frequency, although extreme cold events could still occur and thus monitoring annually would be advised. Little change is projected in extreme wind speeds and gusts. Many of the existing hazards that the UK is already vulnerable to are therefore likely to increase in severity in most cases, which therefore escalates the threat to public health. Although this study focuses on public health in the UK, a similar approach could be used for hazards in other countries.

How to cite: Sanderson, M., Eastaugh, K., Barciela, R., and Bernie, D.: Extreme climatic events and public health in the UK, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15240, https://doi.org/10.5194/egusphere-egu24-15240, 2024.

EGU24-15708 | ECS | Orals | NH11.2

Towards a storyline approach for examining future flood risk: A Central American case study 

Jennifer Dentith, Paul Young, Valeriya Filipova, James Butler, Anya Hawkins, David Leedal, Meredith Pascoe, Kirsty Styles, and Andrew Walkden

Climate change will impact the probabilities of different weather conditions and make new weather conditions possible, with implications for societal exposure to extreme weather hazards. While there is agreement that the frequency and intensity of many hazards will increase at the global scale, there is uncertainty in the spatial distribution of the changes, which needs to be considered in assessments of future extreme weather risk. Typically, this uncertainty is quantified by exploring the range of hazard intensities across a climate model ensemble for a given climate forcing. An alternative approach is to consider the range of atmospheric circulation changes across an ensemble – the driver of much of the relevant uncertainty – and extract a limited set of “physical storylines”. Rather than viewing an ensemble as a continuum of possibilities from which percentiles can be drawn, this physical storyline approach identifies “scenarios within scenarios”, thereby enabling risk modelers to work with more tractable amounts of climate data, end users to explore a “plausible worst case”, and scientists to focus their efforts on which circulation changes might be most likely.

Here, we demonstrate a prototype storyline approach for future flood risk in Central America. We consider how the frequency and intensity of flooding might change by using a pattern-scaling approach to extract the climate signal from climate model output. As a first step towards quantifying the uncertainty in our future flood risk data, we use output from three CMIP6 models that span the range of climate sensitivities and provide different flood storylines for Central America because of their distinct precipitation and temperature trends. We show how return periods for precipitation and streamflow may change under a range of policy-relevant global warming levels, providing useful insights about future surface water and river flooding for the financial, insurance, and development sectors.

How to cite: Dentith, J., Young, P., Filipova, V., Butler, J., Hawkins, A., Leedal, D., Pascoe, M., Styles, K., and Walkden, A.: Towards a storyline approach for examining future flood risk: A Central American case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15708, https://doi.org/10.5194/egusphere-egu24-15708, 2024.

EGU24-17261 | ECS | Posters on site | NH11.2

Severe heat waves in Islamabad and its links with global mitigation benchmarks 

Cristian Zuniga, Peter Pfleiderer, Niels Souverijns, Fahad Saeed, and Carl-Friedrich Schleussner

Anthropogenic climate change encompasses shifts in weather and climate patterns that result in more severe extreme weather events such as tropical storms and heat waves. Observations and climate model simulations show that compound heat waves are becoming more frequent and intense with increasing global mean temperatures. Nevertheless, appropriate local and actionable climate information is scarce and may hinder an adequate adaptation response.

Here, we use a reversal of the traditional impact chain methodology to find emissions constraints that avoid severe heat waves in Islamabad, Pakistan. We use high-resolution urban climate simulations from UrbClim, global climate simulations from CMIP6, and climate simulations from the simple climate model FaIR to estimate local risk threshold exceedances for a large set of emission scenarios. By doing so, we can link specific levels of local climatic impact-drivers to global climate trajectories and assess emission constraints that would avoid severe heat events in Islamabad.

Connecting local risk threshold exceedance to global emission benchmarks can clarify the benefits of reduced emissions for society and decision-makers. Furthermore, our modeling framework allows to investigate different combinations of heat thresholds with occurrence frequencies and can easily be used to answer specific questions from various stakeholders.

How to cite: Zuniga, C., Pfleiderer, P., Souverijns, N., Saeed, F., and Schleussner, C.-F.: Severe heat waves in Islamabad and its links with global mitigation benchmarks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17261, https://doi.org/10.5194/egusphere-egu24-17261, 2024.

EGU24-17837 | Orals | NH11.2 | Highlight

Changing risk from extratropical windstorms in Europe 

Jennifer Catto, Matthew Priestley, and Alexander Little

Future projections of European windstorms and the resultant socioeconomic losses are subject to large uncertainties associated with model differences, internal variability, and emissions scenarios. Here we have used a dataset of objectively identified extratropical cyclones from reanalysis and a multi-model ensemble of climate models under different future warming scenarios. We have applied two storm severity indices; one that is only a measure of the severity of the windstorms; and one that takes into account the population (and its projected future changes) to better understand projections of losses from windstorms. Over northern and central Europe the storm severity itself more than doubles, but the losses estimated from the population-weighted index more than triple due to projected population increases. We also consider an idealised adaptation scenario, where future damage thresholds are used that take into account the increasing future wind speeds. This indicates that adaptation can only partially offset the increased losses. Considering different emissions scenarios, future increase in risk is reduced when following a lower emissions scenario. We show that to understand the future changing risk associated with European windstorms, there is a need to go beyond physical hazard modelling to consider risk and adaptation from a socio-economic perspective.

How to cite: Catto, J., Priestley, M., and Little, A.: Changing risk from extratropical windstorms in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17837, https://doi.org/10.5194/egusphere-egu24-17837, 2024.

EGU24-18675 | Orals | NH11.2 | Highlight

Future changes in weather and climate hazards to aviation 

Paul Williams, Mark Prosser, and Isabel Smith

The human impacts of weather and climate hazards are usually felt at ground level. Aviation is perhaps unique, however, in the sense that the impacts often occur in the upper atmosphere at cruising altitudes of around 40,000 feet. Anthropogenic climate change is occuring at those altitudes in the upper troposphere and lower stratosphere, too. Weather-related hazards such as turbulence already cause a large fraction of commercial aircraft accidents. This presentation will review how these hazards are changing over time because of the changing climate.

Turbulence currently causes 71% of weather-related aircraft accidents, injuring hundreds of passengers and flight attendants annually and costing hundreds of millions of dollars. Recent evidence shows that clear-air turbulence that is strong enough to lift passengers from their seats has increased by 55% since 1979 over the North Atlantic, with similar increases over the USA and elsewhere. Climate model projections indicate a doubling or trebling in turbulence this strong around the midlatitudes in the coming decades, as the jet streams become more sheared in response to anthropogenic temperature changes at cruising altitudes.

Other weather and climate hazards to aviation that will be reviewed in this presentation include the propsect of more lightning strikes; rising sea levels and storm surges flooding coastal airports with increasing frequency; and warmer air on the runway reducing lift generation and making it more difficult for aircraft to take-off.

How to cite: Williams, P., Prosser, M., and Smith, I.: Future changes in weather and climate hazards to aviation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18675, https://doi.org/10.5194/egusphere-egu24-18675, 2024.

Rising global temperatures have been linked to changes in rainfall patterns and an increase in extreme rainfall-related weather events worldwide. Because of its fluctuating precipitation, Bangladesh, a nation susceptible to natural catastrophes, has experienced and will continue to confront more catastrophic calamities. Among these hazards, drought is a more concerning issue for an agriculture-dependent country like Bangladesh. This study has addressed this issue and analyzed the drought condition for the historical period (1985–2014) and near future (2025–2054) by estimating the SPI index in the north-west region of Bangladesh. In this study, an investigation has been done for future projections under various scenarios, such as SSP-245 and SSP-370, using seven suitable Coupled Model Intercomparisons Project 6 (CMIP6). Also, the SPI index has been predicted using a feed-forward backpropagation algorithm in an artificial neural network (ANN). This study has compared the results from two analyses (7 CMIP6 models) and machine-learning-based predictive output. For this study, the drought index was determined to be the Standard Precipitation Index (SPI) on three timescales: three months, six months, and twelve months. For the analysis, a three-layer artificial neural network model was used. In order to determine the most accurate predictive model for the SPI, this model was trained utilizing the SPI timescales with varying lag durations. The correlation coefficient indicated a high accuracy range (75%–85%) in predictive values, demonstrating the model's effectiveness. Additionally, the comparison of observed versus predicted curves for the SPI index across the three timescales also revealed similar trends. The SPI index, derived from 7 CMIP6 models, shows that in the near future, drought events for SSP-370 scenarios are more frequent than SSP-245 scenarios. For the historical period, Chirps precipitation data has been used along with CMIP6 model data, and it has also shown an increasing trend in drought frequencies with time. This study has analyzed the historical and future drought conditions, which can benefit policymakers by improving infrastructure for giving early warning to farmers and taking necessary precautions to protect the losses due to drought.

How to cite: Sarkar, I. and Islam, T.: Comparative Analysis of SPI Index for Drought Conditions in North-West Bangladesh: A Study of CMIP6 Model Data and Machine Learning-Based Predictions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18895, https://doi.org/10.5194/egusphere-egu24-18895, 2024.

EGU24-21161 | Orals | NH11.2 | Highlight

Regional Information for Society within the World Climate Research Programme 

Naomi Goldenson, Bruce Hewitson, Sara Pryor, Silvina Solman, Lincoln Alves, Paul Block, Dragana Bojovic, Louis-Philippe Caron, Alessandro Dosio, Luke Harrington, Kevin Horsburgh, Morten Larsen, and Jemimah Maina

The World Climate Research Programme (WCRP) has created a new core project: Regional Information for Society (RIfS), which has begun to plan its inaugural activities. Recognizing a gap between core disciplinary projects of WCRP and societal impact, RIfS seeks to foster community exchange around the practices of creating and utilizing climate information. The members of the Scientific Steering Group and International Project Office see this as a collaborative process with stakeholders from various sectors of society. Rather than reproducing more climate services, we are focused on identifying best-practices, building worldwide capacity and equity, and contributing to existing projects at the regional scale, particularly in regions where there are limited resources for such services. This RIfS presentation will focus on the identification of best-practices, particularly in the assessment of climate information. Currently there is no systematic, consistent, or accepted approach to assessing which climate information is robust and actionable, at regional or global scales. This recognizes the multiplicity of non-congruent data and information sources that may be used, the choice of which depends often on subjective selections that can lead to different decision outcomes and the commensurate consequences. At the same time, the volumes of data and demand for information are only growing, and new organizations are emerging offering products to decision-makers with varying levels of transparency about methods. Decisions are being made that affect the global distribution of resources, for example in finance and the insurance sectors. No professional organization has so far managed to establish widely accepted standards and guidelines for what constitutes robust information appropriate for various types of decision-making. This is the central challenge of the moment for the community of climate researchers interested in societal applications. RIfS will begin a process of consensus-building with an expert meeting on robustness of climate information just after the EGU meeting this year, to be followed by additional opportunities to come together around these questions.

How to cite: Goldenson, N., Hewitson, B., Pryor, S., Solman, S., Alves, L., Block, P., Bojovic, D., Caron, L.-P., Dosio, A., Harrington, L., Horsburgh, K., Larsen, M., and Maina, J.: Regional Information for Society within the World Climate Research Programme, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21161, https://doi.org/10.5194/egusphere-egu24-21161, 2024.

EGU24-1193 | ECS | Posters on site | CL2.3

Climate drivers of meteorological droughts in north-western Europe (1836-2022) 

Emile Neimry, Hugues Goosse, and Mathieu Jonard

Droughts have garnered global attention due to their adverse effects on crops, ecosystems, and society. Despite their frequent occurrence in north-western Europe, the causes of these droughts remain poorly understood. This study investigates the historical climate drivers of meteorological droughts in the region. The identification of drought events since 1836 is conducted using the Standardized Precipitation Evapotranspiration Index at a 3-month scale, based on reanalysis datasets (ERA5 and 20CRv3). Subsequently, by employing clustering methods, we categorize the diverse atmospheric conditions leading to droughts into discernible patterns. Our next objective is to assess the long-term variability and trends within these patterns. This research provides a long-term regional analysis of meteorological drought drivers, contributing to a deeper understanding of regional climate changes over the past two centuries.

How to cite: Neimry, E., Goosse, H., and Jonard, M.: Climate drivers of meteorological droughts in north-western Europe (1836-2022), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1193, https://doi.org/10.5194/egusphere-egu24-1193, 2024.

EGU24-1722 | ECS | Orals | CL2.3

Revealing a systematic bias in percentile-based temperature extremes 

Lukas Brunner and Aiko Voigt

Worsening temperature extremes are among the most severe impacts of human-induced climate change. To quantify such extremes and their changes various methods have been applied over the years. One frequently used approach is to define extremes relative to the local temperature distribution as exceedances of a given percentile threshold. 

For hot extremes, the Expert Team on Climate Change Detection and Indices (ETCCDI) defines TX90p relative to the 90th percentile of maximum temperature on each calendar day in the 30-year period 1961-1990. To increase the number of samples available for the percentile calculation a 5-day running window is recommended leading to a total of 30x5=150 samples for each calendar day. However, this still limited number of samples can lead to internal variability being mixed into the percentile and cause a strongly varying extreme threshold, which is undesirable. Therefore, many studies do not follow the ETCCDI recommendation and use longer seasonal windows of 15- or even 31-days to increase the number of samples available for the percentile calculation. 

We show that the use of such long seasonal windows introduces a systematic bias that leads to a striking underestimation of the expected extreme frequency. This expected exceedance frequency is 10% for the 90th percentile when evaluating the extreme frequency in the same period as the threshold is calculated (in-base). For ERA5 the 1961-1990 average, global average temperature extreme frequency is only 9% – a relative bias of -10%. In individual regions and seasons, the bias can be considerably larger, exceeding -75%. 

We develop a simple bias correction and use it to show that the bias generally decreases in a warming climate in CMIP6. It, therefore, also affects estimates of future temperature and related heatwave changes. The decrease of the bias can lead to an overestimation of changes in the heatwave frequency by as much as 30%. Based on these results, we strongly warn against the use of long seasonal windows without correction when calculating extreme frequencies and their changes.

How to cite: Brunner, L. and Voigt, A.: Revealing a systematic bias in percentile-based temperature extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1722, https://doi.org/10.5194/egusphere-egu24-1722, 2024.

EGU24-1791 | Orals | CL2.3 | Highlight

Storylines of high-impact climate events 

Theodore Shepherd

High-impact climate events are generally expected to be exacerbated by climate change. For heatwaves, heavy precipitation, and evaporatively-driven drought, the IPCC AR6 made very strong general statements about changes in hazard. But as soon as one attempts to attribute high-impact climate events, the particular details of those events (which are inevitably compound events) and of the human-managed environment take centre stage. Because real-world events are not independent and identically distributed, one cannot reliably apply a general statement to a particular event. This basic aspect of statistical inference, widely recognized in other fields, seems not well appreciated within the climate science community. Physical climate storylines (physically-based unfoldings of past climate or weather events, or of plausible future events or pathways) offer a way to respect the complexity of high-impact climate events and the multiple causal factors involved, of which climate change will only be one. Indeed, identifying the non-climatic factors that affect vulnerability and exposure is essential for good decision-making around climate adaptation. In this talk I will describe the rationale behind the use of storylines for high-impact climate events from the broader perspective of attribution, and explain how conditional attribution allows probability and risk to enter in a physically interpretable and meaningful way.

How to cite: Shepherd, T.: Storylines of high-impact climate events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1791, https://doi.org/10.5194/egusphere-egu24-1791, 2024.

EGU24-2132 | ECS | Posters on site | CL2.3

A Regional Perspective of Storyline Simulations of the Recent European Summer Heatwaves 

Tatiana Klimiuk, Patrick Ludwig, Antonio Sánchez Benítez, Helge Goessling, Peter Braesicke, and Joaquim G. Pinto

Heatwaves are a major natural hazard affecting Europe, and their maximum temperatures are projected to increase strongly with climate change. In recent years, the event-based storyline approach has proven its applicability for climate change attribution studies. Constraining the large-scale dynamics to that of the recent past serves to separate the thermodynamic effects of increasing greenhouse gas concentrations from the largely uncertain dynamic changes. Within the SCENIC project, the storylines are produced with the spectrally nudged global coupled AWI-CM1 model (90 km horizontal resolution). They are downscaled with ICON-CLM to the Euro-Cordex (12 km) and subsequently to the central European domain (3 km). Using this model chain, we captured the series of European summer heat waves and droughts of 2018-2022. We placed them into the pre-industrial climate and three environments corresponding to +2, +3, and +4 K warmer worlds. We quantified the warming rate per degree of global warming (which sometimes exceeds 2.5 over larger areas) and assessed the role of soil-atmosphere feedback in contributing to these rates. More specifically, for several European heatwaves, we explored the connection of the evaporative regime of a region affected by a heatwave to the region's response to global warming during this event. Taking advantage of the high signal-to-noise ratio of event-based storylines, we add one more dimension - the global warming level - to the scope of land-atmosphere feedback studies.

How to cite: Klimiuk, T., Ludwig, P., Sánchez Benítez, A., Goessling, H., Braesicke, P., and G. Pinto, J.: A Regional Perspective of Storyline Simulations of the Recent European Summer Heatwaves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2132, https://doi.org/10.5194/egusphere-egu24-2132, 2024.

EGU24-2258 | ECS | Posters on site | CL2.3

Storyline approach for the analysis of the 2012 drought in Serbia and possible future similar events 

Milica Tosic, Vladimir Djurdjevic, Ivana Tosic, and Irida Lazic

In 2012, Serbia experienced one of its warmest and driest years on record. The summer of 2012 marked the highest temperatures recorded since meteorological measurements began in Serbia, in relation to the reference period from 1991 to 2020. Throughout the summer, the entire country faced severe drought conditions persisting until the end of November. Serbia's agriculture is very vulnerable to drought - an estimated annual economic loss is approximately 2 billion euros due to extreme 2012 drought. Recent studies emphasize the value of the storyline approach in offering a comprehensive and manageable framework for evaluating environmental, societal and economic risks associated with climate change. Considering the potential for more intense climate events resulting from climate change, we decided to apply the storyline approach, to determine what future events similar to drought 2012 might look like and how they are influenced by different climate change scenarios. We constructed drought metrics based on precipitation deficit, following the method proposed by van der Wiel et al. [1], and with the use of the EOBS dataset. Analyzing future scenarios involved creating a meteorological analogue to the 2012 drought, using single model large ensemble historical and future scenario simulations from CMIP6 database - the MPI-M Earth System Model version 1.2, for different SSP scenarios. This analysis offers insights into different storylines, aiding the assessment of climate risks and the potential impacts of hypothetical drought scenarios.

The summer of 2012 was extraordinarily warm, and, as previous studies show significant changes in temperature extremes during the summer season in Serbia, we included analyses of temperature anomalies during the summer. Additionally, to create more comprehensive storylines, our study involves analyzing large-scale atmospheric patterns. Our results show an increase in drought severity in a warmer future, offering an enhanced understanding of how extreme events like the 2012 drought (or more severe) are changing measurably due to climate change, and provide examples of potential impacts, in order to raise public awareness about the potential consequences of future climate change in Serbia.

[1] van der Wiel, K., Lenderink, G. and de Vries, H., 2021. Physical storylines of future European drought events like 2018 based on ensemble climate modelling. Weather and Climate Extremes33, p.100350.

How to cite: Tosic, M., Djurdjevic, V., Tosic, I., and Lazic, I.: Storyline approach for the analysis of the 2012 drought in Serbia and possible future similar events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2258, https://doi.org/10.5194/egusphere-egu24-2258, 2024.

EGU24-2286 | ECS | Posters on site | CL2.3

Extreme rainfall in Northern China in September 2021 tied to air–sea multi‐factors 

Yue Sun, Jianping Li, Hao Wang, Ruize Li, and Xinxin Tang

The September rainfall over Northern China (NC) in 2021 was the heaviest since 1961 and had unprecedented socioeconomic impacts. Holding the hypothesis that the drivers of extreme climate events usually contain extreme factors, we firstly propose the Ranking Attribution Method (RAM) to find the possible air–sea multi-factors responsible for this rainfall event. Via the atmospheric bridges of zonal-vertical circulation and Rossby wave energy propagation, the remote factors of warm sea surface temperature anomalies (SSTA) over the tropical Atlantic, cold SSTA over the tropical Pacific, Southern Annular Mode-like pattern in the Southern Hemisphere and North Pacific Oscillation-like pattern in the Northern Hemisphere jointly strengthened the Maritime Continent (MC) convection and Indian monsoon (IM). Through meridional-vertical circulation, the intensified MC convection enhanced the subtropical high over southern China and induced ascending motion over NC. The local factor of extreme air acceleration in the east Asian upper-level jet entrance region further anchored the location of the southwest-northeast rain belt. The strengthened IM and subtropical high over southern China induced considerable moisture transport to the rain belt via two moisture channels. The combined effect of these extreme dynamic and moisture conditions formed this unprecedented rainfall event. This study suggests that the RAM can effectively reveal the factors that contributed to this extreme rainfall event, which could provide a new pathway for a better understanding of extreme climate events.

How to cite: Sun, Y., Li, J., Wang, H., Li, R., and Tang, X.: Extreme rainfall in Northern China in September 2021 tied to air–sea multi‐factors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2286, https://doi.org/10.5194/egusphere-egu24-2286, 2024.

EGU24-2365 | ECS | Orals | CL2.3

Sub-seasonal UK winter precipitation intensifies in-line with expected temperature scaling 

James Carruthers, Selma Guerreiro, Hayley Fowler, and Daniel Bannister

Interannual to multi-decadal variability in large-scale dynamics such as atmospheric and oceanic circulation results in significant noise and temporary trends in regional climate. Attempting to understand longer term trends as a result of anthropogenic climate change requires disentangling internal variability and climate change signals. One of these climate signals is the Clausius-Clapeyron (CC) scaling in precipitation resulting from temperature increases. In this work, we characterise and constrain variability in sub-seasonal winter rainfall in the UK resulting from synoptic scale-conditions. The UK experiences periods of sustained precipitation in some winters which result in widespread flooding due to extreme accumulation, such as the winter of 2013/2014. Using categorised sea-level pressure fields and gridded precipitation between 1900-2020, we simulate ‘expected’ precipitation resulting from North Atlantic synoptic conditions. We find a rising trend since the 1980s in observed monthly accumulation which is not reflected in the simulated precipitation timeseries, indicating that recent wet winters in the UK have been wetter than expected given the synoptic conditions. The rising trend in the residual (observed - simulated) mean monthly precipitation is in line with expected CC scaling rate of ~6-7% per degree warming according to changes in UK annual mean temperature. However, the residual in extreme monthly precipitation has scaled at approximately twice that rate. To better understand differences in changes for average and extreme precipitation accumulation, we explore the influence of dynamical feedbacks which may increase precipitation at higher intensities. We find that residual precipitation is influenced by the persistence of synoptic conditions and exhibits remote teleconnections to sea surface temperature and atmospheric conditions in the tropics and sub-tropics. This work highlights the importance of considering variability in large-scale dynamics when identifying climate change signals and sheds light on influences on sub-seasonal to seasonal winter precipitation in the UK.ences on sub-seasonal to seasonal winter precipitation in the UK.

How to cite: Carruthers, J., Guerreiro, S., Fowler, H., and Bannister, D.: Sub-seasonal UK winter precipitation intensifies in-line with expected temperature scaling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2365, https://doi.org/10.5194/egusphere-egu24-2365, 2024.

EGU24-2574 | Orals | CL2.3

Statistically impossible temperatures. 

Michael Wehner, Mark Risser, Likun Zhang, and William Boos

The 2021 heatwave in the Pacific Northwest of the United States and Canada was unusual in many regards. In particular, not only was the event deemed impossible prior to the human interference in the climate system, standard out-of-sample non-stationary generalized extreme value (GEV) analyses revealed it to be statistically impossible in 2021 as many observed temperatures were above the upper bound of the upper bound of fitted GEV distributions. Obviously, as the event actually occurred, these statistical models are not fit for the purpose of estimating the influence of climate change on the event’s probability.

By expanding the number of physical covariates beyond just greenhouse gas concentrations and by incorporating spatial statistical techniques in a Bayesian hierarchal framework, we are able to construct a statistical model where observed temperatures during this heatwave were not “impossible” and thus estimate the change in their probabilities leading to Granger-type causal inference attribution statements.

We further extend this statistical framework to all quality daily GHCN station measurements and find that while many physically plausible outlier temperatures are impossible in the simple non-stationary GEV framework, they can be explained using our more complicated non-stationary Bayesian spatial statistical model embedded in a deep learning machinery.

 

How to cite: Wehner, M., Risser, M., Zhang, L., and Boos, W.: Statistically impossible temperatures., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2574, https://doi.org/10.5194/egusphere-egu24-2574, 2024.

EGU24-3153 | ECS | Posters on site | CL2.3

A systematic bias in future heatwave diagnostics throughout the seasonal cycle 

Maximilian Meindl, Lukas Brunner, and Aiko Voigt

Human-induced climate change is leading to a warming Earth, resulting in more frequent and intense temperature extremes. Daily temperature extremes can be defined following various approaches, with relative percentile-based thresholds being a common method. Here we explore spatio-temporal heatwaves across the seasonal cycle derived from daily temperature extremes, emphasizing the critical role of the extreme threshold chosen in their definition.

To investigate the sensitivity of heatwave characteristics to the extreme threshold definition, we focus on the approach utilizing a so-called moving threshold. This method involves a 31-day running window to increase the sample size for percentile calculations as well as an additional 31-year running window to account for the impact of global warming. We recognize that introducing a seasonal running window may introduce biases in threshold exceedances. To address this issue, Brunner and Voigt (2023) proposed a simple bias correction method, involving the removal of the mean seasonal cycle before percentile threshold calculation, which we also use here to explore effects on downstream impact metrics. 

We focus on the 99th percentile as threshold and show the potential for a significant bias in the extreme frequency, exceeding 50% in certain regions according to 5 selected CMIP6 models. Our findings further reveal that without bias correction this also leads to a substantial underestimation of derived heatwave properties, in particular area, duration, and magnitude. For the ACCESS-CM2 model, the difference in heatwave area can reach up to 40%, when comparing bias-corrected and not bias-corrected results for the 100 biggest events in the period 1960-1990.

Our results contribute to a better understanding of the implications of using a seasonally running window on heatwave characteristics, providing valuable insights for future climate projections. We emphasize the importance of adopting appropriate methods and bias correction techniques to enhance the accuracy of temperature extreme assessments in the context of ongoing climate change.

 

References:

Brunner and Voigt (2023): Revealing a systematic bias in percentile-based temperature extremes. EGU General Assembly 2024. EGU24-1722

How to cite: Meindl, M., Brunner, L., and Voigt, A.: A systematic bias in future heatwave diagnostics throughout the seasonal cycle, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3153, https://doi.org/10.5194/egusphere-egu24-3153, 2024.

EGU24-3174 | Orals | CL2.3

Storylines of East Asian cold extremes in 2020/2021 under different warming climate 

Wenqin Zhuo, Antonio Sánchez-Benítez, Helge Goessling, Marylou Athanase, and Thomas Yung

Whether cold-air outbreak over mid-latitude in a warmer climate would become more or less extreme is a subject of debate, particularly due to uncertainty links between Arctic amplification and these cold extremes, which complicated by the atmosphere internal variability.  Here we employ an event-based storyline approach, which fixed the atmospheric circulation to the observed  through spectral nudging, to quantify thermodynamic effect on extreme cold events during the winter of 2020/2021 in East Asia under different warming scenarios. Notably, we detect the strongest warming, up to +10K, over Eastern Siberia in the +4K-warmer climate, which is related to warmer cold air mass originating from unfrozen sea ice over Siberia region. In contrast, in the southern China, due to the observed and expected increasing aerosol concentration, peaking by the mid-21st century and altering the radiative balances, a mild cooling is present from pre-industrial to present-day climates. The cooling in this region is likely to persist in +2K-warmer scenario but was not observed when up to the +4K warmer climate. Correspondingly, no prominent temperature variation is observed in the middle East Asia, with the warming extent largely mirroring the overall climate background.

How to cite: Zhuo, W., Sánchez-Benítez, A., Goessling, H., Athanase, M., and Yung, T.: Storylines of East Asian cold extremes in 2020/2021 under different warming climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3174, https://doi.org/10.5194/egusphere-egu24-3174, 2024.

A “once-in-a-millennium” super rainstorm battered Zhengzhou, central China, from 07/17/2021 to 07/22/2021 (named “7.20” Zhengzhou super rainstorm). It killed 398 people and caused billions of dollars in damage. ​A pressing question, however, is whether rainstorms of this intensity can be effectively documented by geological archives to understand better their historical variabilities beyond the scope of meteorological data. Here, four land snail shells (Cathaica fasciola) were collected from Zhengzhou in 2021, and weekly to daily resolved snail shell δ18O records from June to September of 2021 were obtained by gas-source mass spectrometry (GSMS) and secondary ion mass spectrometry (SIMS). The daily resolved records show a dramatic negative shift between 06/18/2021 and 09/18/2021, which has been attributed to is related to the “7.20” Zhengzhou super rainstorm. Moreover, the measured amplitude of the shell δ18O shift caused by the “7.20” Zhengzhou super rainstorm is consistent with the theoretical value estimated from the flux balance model and local instrumental data within the error range. Our results suggest that the ultra-high resolution δ18O of land snail shells have the potential to reconstruct local synoptic scale super rainstorm events quantitatively. And the proposed “best practice” of current work indicated that fossil snail shells in sedimentary strata can be valuable material for investigating the historical variability of local super rainstorms under different climate background conditions.

How to cite: Wang, G., Dong, J., and Yan, H.: Quantitative reconstruction of a single super rainstorm using daily resolved δ18O of land snail shell, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4973, https://doi.org/10.5194/egusphere-egu24-4973, 2024.

EGU24-6659 | Orals | CL2.3

Empirical storylines of climate change using clustering analysis 

Xavier Levine and Priscilla Mooney

Storylines are intended to provide concrete realizations of the climate response to global warming, to help anticipate the possible impacts of climate change on society and nature. Recent studies on climate change storylines have used a multivariate linear regression (MLR) framework to determine those climate realizations, for specific variables, regions and seasons (called target variables); this is achieved by leveraging known climatic interactions across a large number of model projections, which are represented by the covariability of the target variable with pre-determined climate indices (called predictor indices). Yet, a systematic methodology for selecting the best set of predictor indices for a specific target variable is lacking, with the set of predictors usually being chosen according to our current understanding of the most important climatic interactions. Furthermore, the storylines that emerge from it are tailored to explain changes in one specific variable, region and season (the target variable), and thus are unable to be generally applicable to a range of target variables.

Even if the MLR framework succeeds in generating an array of representative climate outcomes for specific cases, we hypothesize that alternative methodologies can be used to generate likely climate outcomes from model simulations while alleviating some of the limitations of the MLR framework. Here, we propose to use clustering analysis to provide possible climate realizations from model projections. Clustering ensures a comprehensive and efficient decomposition of the spread in climate projections found across model simulations, without the need of predefining predictors (both an advantage and inconvenience), but also can be applied to more than one target variable at a time. 

We present findings from various empirical clustering methods, using the three main categories of algorithm (e.g. distribution-, density-, and centroid-based) to produce our so-called empirical storylines. We focus on the Arctic region during the boreal summer season, comparing storylines obtained from each clustering method with findings from a set of “classic” storylines obtained using the MLR framework. We discuss the implications of our results for improving our understanding of the spread in climate projections, and conclude on the existence of a most likely cluster (storyline) by relating our climate change clusters with clusters for the present-day climate. 

How to cite: Levine, X. and Mooney, P.: Empirical storylines of climate change using clustering analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6659, https://doi.org/10.5194/egusphere-egu24-6659, 2024.

EGU24-6945 | ECS | Orals | CL2.3

Not as Rare as Expected: Assessing Singapore’s Unprecedented Droughts in a Changing Climate 

Xiao Peng, Biao Long, and Xiaogang He

There has been growing evidence suggesting a rising frequency and/or intensity of droughts in tropical regions in a warming climate. Singapore, a water-scarce city heavily reliant on water imports, faces heightened vulnerability to extreme drought episodes. Preparing for unprecedented droughts is thus pivotal for this tropical island city to safeguard a sustainable and resilient water supply. However, the accuracy of quantifying the probability and severity of unprecedented droughts, such as those with a 1000-year return period, is hindered by observations (e.g., in situ measurements, satellite data, etc.) with limited data length, typically spanning only about 50 years. Physics-based regional climate models offer a distinct advantage in simulating extreme droughts beyond historically available data. Yet, naïve Monte Carlo simulations for rare events becomes computationally infeasible at high spatiotemporal resolutions, a scale most relevant in urban drought risk mitigation. In this study, building upon the Giardina-Kurchan-Lecomte-Tailleur algorithm, we develop a computationally efficient framework to simulate Singapore’s unprecedented drought events. Our framework couples the Weather Research and Forecasting (WRF) model with a sequential importance sampling procedure, incorporating the ‘Darwinian pressure’ to favor trajectories conducive to extreme drought conditions. With just slightly over 100 trajectories, we can efficiently simulate very rare drought events (e.g., 1-in-10000-years and rarer) while maintaining their physical plausibility. The WRF model also enables detailed spatiotemporal dynamics of unprecedented droughts, allowing direct estimation of potential compounding extremes, such as concurrent droughts and heatwaves. Moreover, we quantify changes in the likelihood of plausible yet unprecedented droughts under various future climate change scenarios, such as Shared Socioeconomic Pathway 5-8.5 (SSP585), in comparison to the present climate. Our results reveal a robust increase in the chance of unprecedented droughts, emphasizing the importance of developing resilient water strategies for Singapore to prepare for such events in the near future.

How to cite: Peng, X., Long, B., and He, X.: Not as Rare as Expected: Assessing Singapore’s Unprecedented Droughts in a Changing Climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6945, https://doi.org/10.5194/egusphere-egu24-6945, 2024.

EGU24-7744 | ECS | Orals | CL2.3 | Highlight

Storylines for heat-mortality extremes 

Samuel Lüthi, Erich Fischer, and Ana Vicedo-Cabrera

Recent heat extremes reached records far out of the observational temperature range. These extremes challenged the risk view of climate scientists on what could be physically possible within the current climate conditions. However, it is precisely such unprecedented events that pose a large risk to underprepared societies. To better anticipate and prepare for such potential extreme events, the climate risk community started producing storylines which are designed to draw potential and plausible worst-case scenarios without aiming to quantify their probability of occurrence.

The recent development of the ensemble boosting method allows investigating physically plausible extreme heatwaves by re-initializing a climate model with random round-off perturbed atmospheric initial conditions shortly before the onset of a great heat anomaly. This allows for creating storylines whilst ensuring physical consistency. However, so far these storylines were only used to estimate the pure physical climate extreme without the additional quantification of impacts on society.

In this study, we therefore aim to produce several storylines for potential worst-case heat-mortality scenarios. For that, we aim to combine ensemble boosted climate model output with methods from environmental epidemiology to quantify heat-mortality. Concretely, we model the empirical relationship between daily mean temperature and daily mortality counts by using quasi-Poisson regression time series analyses with distributed lag nonlinear models, which is a well-established approach in climate change epidemiology. We then combine these empirical temperature-mortality relationships with the bias-corrected extreme storylines that we developed by ensemble boosting a fully-coupled free-running climate model (CESM2).

The findings of this study have significant implications for societies, particularly in the context of public health policy development, to effectively respond to unprecedented but anticipatable heat extremes.

How to cite: Lüthi, S., Fischer, E., and Vicedo-Cabrera, A.: Storylines for heat-mortality extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7744, https://doi.org/10.5194/egusphere-egu24-7744, 2024.

EGU24-8388 | ECS | Orals | CL2.3

The Future of Hot-Dry Events in the World’s Breadbasket Regions 

Victoria Dietz, Johanna Baehr, and Leonard Borchert

We use a 50-member large ensemble of the CMIP6 version of the MPI-ESM1.2-LR model to examine the future of hot-dry compound events at 1.5 and 2°C of global warming. By targeting the largest maize production areas (breadbasket regions) and their corresponding growing seasons, we tailor our analysis to food production, indicating potential future threats to global food security. Our results suggest a notable shift in the extremes associated with maize harvest failure in the breadbaskets between 1.5 and 2°C of global warming, highlighting the value of mitigating climate change and the future need to adapt to climate challenges in the agricultural sector.

Our analysis shows a significant increase in the likelihood of these extremes during maize growing seasons across almost all examined regions and variables. In particular, the occurrence probability of heat events and hot-dry compounds at least doubles in most regions when the world warms from 1.5 to 2°C. Locally, cumulated heat excess increases everywhere, while the spatial extent of heat consistently expands across all regions in contrast to the relatively stable pattern we find for precipitation as we transition from one level of global warming to another. We additionally explore spatial compounding, where multiple breadbasket regions experience simultaneous extremes in the same growing season, exacerbating global food security challenges. Scenarios that were virtually impossible in the past, such as hot-dry events affecting at least three regions simultaneously, take on non-zero probabilities in a world that is 1.5 or 2°C warmer. The probabilities of simultaneous heat and hot-dry compounds in a 2°C warmer world significantly exceed those in a 1.5°C warmer world, to the extent that there is little to no overlap between the corresponding ensemble spreads.

How to cite: Dietz, V., Baehr, J., and Borchert, L.: The Future of Hot-Dry Events in the World’s Breadbasket Regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8388, https://doi.org/10.5194/egusphere-egu24-8388, 2024.

In 2015, Limin Jiao et al. used concentric circles and inverse S function curves to analyze the construction land density of 28 major cities in China and successfully divided the internal structure of urban areas. Based on this, this study takes  Beijing-Tianjin-Hebei core area (Beijing, Tianjin and Langfang) and  Shanghai metropolitan area (Yangtze River Delta region) as the research objects, analyze the changes in construction land structure and urban heat island effect from 2001 to 2020.
It is feasible to use the Anselin local Moran I tool of Arcgis to analyze urban centers based on population density (Yingcheng Lia; Xingjian Liu, 2018). We established a fishing net analysis, and the grid with HH significant clustering (high population density surrounded by those of similar high densities) can be regarded as the center of the city. Then, concentric circles with a diameter of 1KM are established based on these center points, and the proportion of construction land in each circle is extracted. And use the inverse S function (Formula 1) to fit the extraction results.
 (1)
The determination coefficient R2 of all fitting results is greater than 0.98, and the results are highly reliable. Then the fitted function is differentiated twice. The two extreme points correspond to the concentric radius of the inner city and the suburbs (R1, R2, and R1<R2) respectively. We found that the radius of the central city and peripheral urban areas of both metropolitan areas has expanded over the past 20 years, with Shanghai's peripheral cities expanding at a faster rate. In addition, the urban radius of Beijing-Tianjin-Hebei is about twice that of Shanghai.
In this study, the urban heat island effect is represented by the difference in surface temperature between suburban areas and Inner City. The results show that the urban heat island effect in the two regions has shown an increasing trend over 

How to cite: Zhang, X., Roca Cladera, J., and Arellano Ramos, B.: Research on urban heat island effect based on concentric circle division of urban structure - Take the Beijing-Tianjin-Hebei and Shanghai metropolitan areas as examples, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9680, https://doi.org/10.5194/egusphere-egu24-9680, 2024.

EGU24-9911 | ECS | Posters on site | CL2.3

Attribution of European Heatwaves to Global Warming Using Spectrally Nudged Storylines 

Dalena Leon, Frauke Feser, and Linda Van Garderen

This study employs Spectrally Nudged Storylines to attribute heatwaves to anthropogenic global warming. Utilizing high-resolution global (ECHAM) and regional (CCLM) climate models, we aim to discern the influence of anthropogenic climate change on the characteristics of European heatwaves observed in the last decade. Differently to the statistical approach that uses large ensembles/datasets to study large amount of similar events and attribute their occurrence to climate change, the storylines simulate a specific extreme event under different thermodynamical conditions by constraining the large scale dynamics of the system. Thus, directly attributing the change in characteristics of the extreme event to the changes in the thermodynamics, based on the prescribed sea surface temperature and greenhouse gases emission levels. In such way, three storylines are built: a Factual storyline that resembles the climate state as we know it, a Counter Factual storyline that is fixed to the past century representing a world without climate change, and a Plus 2°C storyline that shows how these extreme events change in a world where the global mean temperature is 2°C higher than in pre-industrial times. By the use of these three storylines, we can tell to what extent global warming has provoked heatwaves to be as extreme in a world as we know it, and what can we expect them to be in a warmer future climate.

How to cite: Leon, D., Feser, F., and Van Garderen, L.: Attribution of European Heatwaves to Global Warming Using Spectrally Nudged Storylines, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9911, https://doi.org/10.5194/egusphere-egu24-9911, 2024.

EGU24-10006 | ECS | Orals | CL2.3

Impacts of regional grid refinement on climate extremes over the Arctic in storyline-based earth system model simulations. 

René R. Wijngaard, Willem Jan van de Berg, Adam R. Herrington, and Xavier Levine

Over the last few decades, the Arctic region has warmed up at a greater rate than elsewhere at the globe, partly resulting from the on-going loss of sea ice and snow over land. It is projected that the amplified warming of the surface will continue in the future, most likely altering the magnitude and frequency of temperature extremes, such as heat waves and cold spells. In addition, the intensity and frequency of extreme precipitation and droughts are projected to change, which may pose serious threats for the human infrastructure and livelihoods. To assess (future) climate extremes, Earth System Models (ESMs) with (regionally) refined resolution could be helpful, particularly in mountainous regions.

In this study, we use the variable-resolution Community Earth System Model version 2.2 (VR-CESM) to evaluate and assess present-day and future climate extremes, such as heat waves and heavy precipitation, over the Arctic. Applying a globally uniform 1-degree grid and a VR grid with regional grid refinements to 28 km over the Arctic and Antarctica, we run present-day (2005–2014) and future (2090–2099) simulations with interactive atmosphere and land surface models, and prescribed sea ice and surface temperatures. The simulations follow two storylines of Arctic climate change that represent a combination of strong/weak polar Arctic amplification and strong/weak SST warming in the Barents-Kara seas. We evaluate the ability of the VR grid to simulate climatic extremes by comparison with gridded outputs of the globally uniform 1-degree grid and the ERA5 reanalysis and assess future climate extremes by focussing on temperature and precipitation extremes. The initial outcomes generally show that for some temperature/precipitation extremes indices the VR grid performs better than the globally uniform 1-degree grid, while for other indices the globally uniform 1-degree grid performs better. Future projections suggest that warm temperature extremes will generally increase both in magnitude and frequency, whereas cold temperature extremes will decrease in magnitude, especially over regions dominated by large sea ice loss. Further, precipitation is projected to increase in intensity and volume. The outcomes of this study may contribute to an improved understanding on future climate extremes and its implications.

How to cite: Wijngaard, R. R., van de Berg, W. J., Herrington, A. R., and Levine, X.: Impacts of regional grid refinement on climate extremes over the Arctic in storyline-based earth system model simulations., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10006, https://doi.org/10.5194/egusphere-egu24-10006, 2024.

It is well established that internal variability arising spontaneously from the chaotic nature of the climate system can amplify or obscure anthropogenically-forced signals, especially at near-term and at regional scale in the extratropics. In this talk, we focus on Northern Europe (NEU) winter climate changes over the 2020-2040 period and propose a set of internal variability storylines (IVS) to tackle related uncertainties. IVS are built from the combined evolution of the North Atlantic Oscillation (NAO) and the Atlantic Meridional Overturning Circulation (AMOC) diagnosed as drivers of variability for temperature over NEU.

We first show, based on a large ensemble of historical-scenario simulations from CNRM-CM6-1, that, depending on the near-term [AMOC-NAO] doublet evolution, anthropogenically-forced changes can be either considerably amplified with much warmer-wetter mean conditions, almost doubled, or considerably masked with marginal warming and unchanged mean precipitation with respect to present day. We then provide evidence for the robustness of our results by using large-ensembles from several models which ultimately allows assessing the full range of uncertainties for near-term climate change.

We finally use the 2010 severe winter case as an illustrative example of the added-value in expressing climate change knowledge in a conditional form through IVS to plan at best climate-related risks and local adaptation strategies at near term. Reframing the uncertain climate outcomes into the physical science space through IVS grapples the complexity of regional situations; it is also informative to more efficiently communicate towards the general public as well as for climate literacy in general.

How to cite: Cassou, C., Line, A., and Msadek, R.: Assessment of climate change at near-term (2020-2040) over Northern Europe through internal variability storylines, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11961, https://doi.org/10.5194/egusphere-egu24-11961, 2024.

EGU24-11971 | Posters on site | CL2.3

Insights and Reflections: The 'Exploring Unprecedented Extremes' Workshop 

Dominique Paquin, Dominic Matte, Jens H. Christensen, Martin Drew, and Alexandrine Bisaillon

Due to the various regions and contexts around the world with distinct climatic characteristics, climate hazards vary significantly in their nature, frequency, and impact, causing property damage, population distress, communication failures, environmental damage, and economic losses. Unfortunately, 2023 showcased extreme weather and climate events that have surpassed previous records. These include heatwaves, floods, wildfires, tornadoes. The occurrence of these extreme events poses a challenge to our comprehension of future climates, primarily due to their divergence from our conventional thought patterns or their status as out-of-sample scenarios. With ongoing climate warming, the potential for more severe events in the future is a concern. Insufficient preparation may result in breakdowns within specific sectors or even societal collapse. Effective preparation involves multiple factors, with the initial challenge lying in forming expectations - a task complicated by events that fall outside our usual anticipations, such as out-of-sample occurrences. 

 

In the face of those climate challenges, understanding and mitigating the impacts of unprecedented climate extremes has become a critical area of focus. To shed light on this challenge, a workshop titled "Exploring Unprecedented Extremes" was convened in November 2023. This event brought together experts from diverse fields to deliberate on innovative approaches to climate change adaptation and mitigation. Emphasizing co-creation and interdisciplinary collaboration, the workshop addressed key themes such as the integration of various sectors into climate change strategies, the complexities of decision-making under uncertainty, and the crucial role of transdisciplinary research in comprehensively understanding and effectively responding to climate extremes. This poster focuses on the key takeaways and strategic reflections that emerged following the workshop, capturing the essence of our collaborative discourse on climate challenges.

How to cite: Paquin, D., Matte, D., Christensen, J. H., Drew, M., and Bisaillon, A.: Insights and Reflections: The 'Exploring Unprecedented Extremes' Workshop, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11971, https://doi.org/10.5194/egusphere-egu24-11971, 2024.

EGU24-12519 | ECS | Orals | CL2.3

Storyline simulations suggest a northward expansion of European droughts in warmer climates. 

Antonio Sánchez Benítez, Monica Ionita, Marylou Athanase, Thomas Jung, Qiyun Ma, and Helge Goessling

Climate change is causing an increase in the frequency, intensity and persistence of heatwaves and droughts, as seen, for example, in Central Europe in recent years. These changes are expected to be even more severe in the future. Two factors contribute to these changes in extreme events: dynamic changes – changes in the likelihood of weather patterns  – and thermodynamic changes. While the former are uncertain in future climate projections, the latter are characterized by a high signal-to-noise ratio, as there is a robust and ubiquitous rise in land-surface temperatures.

To better understand and analyze both contributions, we employ the so-called "event-based storyline approach", which involves nudging our global CMIP6 coupled climate model (AWI-CM1) towards the observed large-scale free-troposphere winds using various climate background conditions and initial states. This enables us to simulate the same weather conditions, including jet streams and blockings, in different climates: preindustrial, present, and in 2 °C, 3 °C, and 4 ºC warmer worlds. This methodology provides an efficient way of making the consequences of climate change more understandable to experts and non-experts, as extreme events that are fresh in people's memory are simulated in different climates with moderate computational resources.

Our simulations successfully reproduce recent hot and dry extreme events, like the 2019 or 2022 European heatwaves and the record-breaking 2022 drought. Our experiments reveal an intensification of these extremes from preindustrial to present climates (attribution), mainly in southern Europe, with no major changes in Central and Northern Europe. However, we project that this exacerbation will expand northward in future warmer climates, leading to even more severe drought in Central Europe and the Mediterranean by the end of the century. Taking advantage of our methodology we explore the physical mechanisms helping to exacerbate these events in future warmer climates.

How to cite: Sánchez Benítez, A., Ionita, M., Athanase, M., Jung, T., Ma, Q., and Goessling, H.: Storyline simulations suggest a northward expansion of European droughts in warmer climates., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12519, https://doi.org/10.5194/egusphere-egu24-12519, 2024.

EGU24-12974 | ECS | Orals | CL2.3

On the key role of anthropogenic warming in triggering extreme convective events: the case of the destructive Mediterranean derecho in 2022 

Juan Jesús González-Alemán, Damian Insua-Costa, Eric Bazile, Sergi González-Herrero, Mario Marcello Miglietta, Pieter Groenemeijer, and Markus G. Donat

A derecho is a widespread, long-lived, straight-line windstorm that is associated with a fast-moving group of severe thunderstorms known as a mesoscale convective system.

During 18 August 2022, a highly intense and organized convective storm, classified as a derecho, developed over the western Mediterranean Sea affecting Corsica, northern Italy and Austria, with wind gusts up to 62 m/s and giant hail (~11 cm). There were 12 fatalities and 106 people injured. This event received much attention in the media for its extraordinary impact and the rareness over the Mediterranean Sea. The derecho developed over an extreme marine heatwave that persisted during the whole summer. Therefore, the hypothesis of a relationship between the extreme atmospheric event and the extreme marine heatwave rapidly arose, and thus, a possible link with anthropogenic climate change.

This convective event can be considered as extreme from the affected locations point of view (in terms of winds) but also is between one of the most powerful derechos ever recorded in the USA and Europe. Also, the event developed over an extreme marine heatwave that was mainly affecting the western Mediterranean Sea during summer 2022.

Here, by performing model simulations with both the NCAR Model for Prediction Across Scales and the Météo-France nonhydrostatic operational AROME model and using an storyline approach, we find a relationship between the marine heatwave, the actual anthropogenic climate change conditions, and the development of this extremely rare and severe convective event. We also find a future worrying increase in intensity, size and duration of such an event with future climate change conditions.

How to cite: González-Alemán, J. J., Insua-Costa, D., Bazile, E., González-Herrero, S., Miglietta, M. M., Groenemeijer, P., and Donat, M. G.: On the key role of anthropogenic warming in triggering extreme convective events: the case of the destructive Mediterranean derecho in 2022, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12974, https://doi.org/10.5194/egusphere-egu24-12974, 2024.

EGU24-15314 | ECS | Orals | CL2.3

Investigating typical patterns for co-occurring heatwaves 

Vera Melinda Galfi

The typicality of extreme weather and climate events denotes their property to exhibit similarities in spatial patterns, temporal evolution, and underlying physical processes, with this resemblance intensifying as events become more extreme. Recent findings highlight that highly intense heatwaves, defined as prolonged local temperature anomalies, are consistently associated with specific large-scale circulation patterns. This suggests that there is a typical way to realise very extreme local temperature anomalies. Here, I will explore typical ways for the emergence of extremely intense hemispheric anomalies, characterized by notably large zonal variations in air temperature or geopotential height. This investigation aims to shed light on preferred atmospheric configurations leading to the simultaneous occurrence of heatwaves on a hemispheric scale.

How to cite: Galfi, V. M.: Investigating typical patterns for co-occurring heatwaves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15314, https://doi.org/10.5194/egusphere-egu24-15314, 2024.

EGU24-15334 | Orals | CL2.3

Changes in land-atmosphere coupling may amplify increases in very rare temperature extremes 

Douglas Maraun, Reinhard Schiemann, Albert Osso, and Martin Jury

Extreme heat events are becoming more severe. Attribution studies have demonstrated the effect of anthropogenic climate change on recent devastating events, including the heat waves in Canada in 2021, Northern India in 2022 and the Western Mediterranean in 2023. Such impactful events are very rare with return periods of 100 years and more even in present climate. Their rareness is in stark contrast to the typically considered return periods ranging from less than a year to maybe 20 years. This choice might often be inevitable because of practical limitations, mainly the length of observational and climate model records. But generalising from such analyses to extreme events in general tacitly assumes that very rare events respond to climate change in a similar way as the analysed moderate extreme events. Several studies investigating land-atmosphere feedbacks and atmospheric circulation changes indicate, however, that this assumtion may not be justified.

Here we use three single model initial condition large ensembles (SMILES) to assess differences between projected changes in moderate heat extremes (represented by 2-year return values of the hottest day in a year) and very rare extreme events (represented by corresponding 200-year return values). We analyse changes from 1990-2014 to 2075-2099 according to the SSP5-8.5 scenario.

We find large regions where projected changes in very extreme events are markedly different - both stronger or weaker - to those in moderate extreme events. Model uncertainty about these differences is very high though: all considered SMILES suggest that such regions exist, but they do not agree on the locations.  The underlying mechanisms, however, are robust across models: in regions of increasing soil moisture temperature coupling strength, changes in very rare events can be almost twice as high as those in moderate extremes. Vice versa, in regions of decreasing coupling strength, changes may be much weaker. These changes can to a large extent be traced back to changes in precipitation patterns, highlighting the role of atmospheric circulation changes.  

The corresponding patterns emerge already over shorter time horizons and are thus relevant for mid-century projections, low emission scenarios and event attribution studies. Robust inference about these differences is impossible based on individual model simulations, but requires the sample size of SMILES.  Not accounting for these changes could lead to a dramatic misrepresentation of future climate risks from heat events. Our findings therefore confirm the importance of studies specifically targeting very extreme events.

How to cite: Maraun, D., Schiemann, R., Osso, A., and Jury, M.: Changes in land-atmosphere coupling may amplify increases in very rare temperature extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15334, https://doi.org/10.5194/egusphere-egu24-15334, 2024.

EGU24-15505 | ECS | Posters on site | CL2.3

Evaluating the simulation of extreme events with the land surface model CLM5.0 over Europe for 2018-2022: comparison with in situ and remotely sensed data 

Arpita Bose, Christian Poppe Terán, Bibi Naz, Visakh Sivaprasad, Stefan Kollet, and Harrie-Jan Hendricks Franssen

Climate change is expected to amplify the frequency and intensity of extreme events in the future. Recently there was a series of summers with heat waves and droughts over central Europe from 2018 to 2022, but also severe flooding in 2021. These events had substantial effects on agriculture, water resources, and human lives. To monitor and assess the impacts of extreme events, in situ and remote sensing data for soil moisture, evapotranspiration and carbon fluxes are important. In this study we evaluate simulation results by the Community Land Model (CLM, version 5.0) over the EUROCORDEX domain for past extreme events between 2018 and 2022 and analyze to which degree the model is able to reproduce low soil moisture levels, and changes in evapotranspiration, leaf area index and carbon fluxes in the areas most affected by the extreme event, on the basis of a comparison with in situ (e.g., ICOS) and remotely sensed (e.g., SMAP, MODIS) data. Additionally, we will compare CLM5.0 results to other land surface models, such as ERA5-Land, GLDAS, GLEAM. Our model setup over EUROCORDEX is driven by atmospheric forcings from the ERA5 reanalysis. The soil texture information is obtained from FAO at 10 km resolution and the land use data is from LULC from NCAR mapped to plant/crop functional types. It was found that CLM5.0 overestimates soil moisture and exhibits a wet bias compared to SMAP during heat waves. In addition, the comparison of measured evapotranspiration with CLM5.0 shows that drought stress response is underestimated by the model. A systematic underestimation or overestimation of the impact of past extreme events on the land surface would point to model limitations which is important to resolve to gain confidence in the simulation of future extreme events under conditions of climate change.

How to cite: Bose, A., Poppe Terán, C., Naz, B., Sivaprasad, V., Kollet, S., and Hendricks Franssen, H.-J.: Evaluating the simulation of extreme events with the land surface model CLM5.0 over Europe for 2018-2022: comparison with in situ and remotely sensed data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15505, https://doi.org/10.5194/egusphere-egu24-15505, 2024.

EGU24-16575 | ECS | Posters on site | CL2.3

Enhanced surface temperature over India during 1980–2020 and future projections: causal links of the drivers and trends 

Rahul Kumar, Jayanarayanan Kuttippurath, Gopalakrishna Pillai Gopikrishnan, Pankaj Kumar, and Hamza Varikoden

The Earth’s surface temperatures have increased significantly since the beginning of industrialisation. The substantial emissions of greenhouse gases have played a role in global warming and the ongoing climate change, with projections indicating continued trends. This study explores the long-term surface temperature trends in India from 1980 to 2020, utilizing surface, satellite, and reanalysis data. Causal discovery is employed to assess the impact of geophysical drivers on temperature changes. Southern India exhibits the highest mean surface temperatures, while the Himalayas experience the lowest, aligning with solar radiation patterns. The causal discovery analysis identifies the varying influence of atmospheric processes, aerosols, and specific humidity on surface temperature. Positive temperature trends are observed during the pre-monsoon (0.1–0.3 °C dec−1) and post-monsoon (0.2–0.4 °C dec−1) seasons in northwest, northeast, and north-central India. Northeast India demonstrates substantial annual (0.22 ± 0.14 °C dec−1) and monsoon (0.24 ± 0.08 °C dec−1) warming. Post-monsoon trends are positive across India, with the western Himalaya (0.2–0.5 °C dec−1) and northeast India (0.1–0.4 °C dec−1) experiencing the highest values. Projections based on the Coupled Model Intercomparison Project 6 (CMIP6) indicate potential temperature increases of 1.1–5.1 °C by 2100 under the Shared Socioeconomic Pathways (SSP5)–8.5 scenario. The escalating temperature trend in India raises concerns, emphasizing the necessity for adaptation and mitigation measures to counteract the adverse impacts of accelerated warming and regional climate change.

How to cite: Kumar, R., Kuttippurath, J., Gopikrishnan, G. P., Kumar, P., and Varikoden, H.: Enhanced surface temperature over India during 1980–2020 and future projections: causal links of the drivers and trends, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16575, https://doi.org/10.5194/egusphere-egu24-16575, 2024.

EGU24-17486 | ECS | Orals | CL2.3

Hydro-economic assessment of biophysical drought impacts on agriculture 

Mansi Nagpal, Jasmin Heilemann, Bernd Klauer, Erik Gawel, and Christian Klassert

As climate changes globally and locally, the risk of temperature anomalies, heat waves and droughts have significantly increased. Studies have demonstrated that droughts exert adverse biophysical effects on crop production, posing an unprecedented threat to harvests and resulting in substantial economic losses in Europe. Assessing these biophysical drought impacts on agriculture is crucial for developing effective strategies for drought preparedness, mitigation, and adaptation. This paper contributes to this effort by presenting a framework to estimate economic costs associated with droughts that specifically captures the biophysical impact of climate change on crop output.

Existing analyses for drought damages in agriculture are developed for a specific drought event and primarily focus on the reduction in farmer’s income or crop yields in drought events. In these assessments, the biophysical impacts of droughts are not isolated and evaluated from their effects on other economic variables such as output prices, resulting in inaccurate damages. Additionally, lack of single universal definition of drought adds complexity to estimating the costs of droughts. This paper is aimed to contribute by focusing on agricultural droughts, which occurs when variability in soil moisture affects plant growth and development. We simulate this biophysical effect of drought on crop yields by applying a statistical crop yield model to data on soil moisture, temperature and perception. This approach helps isolate the direct impact of drought on agriculture from other changes in aggregate economic production (e.g. business conditions, commodity prices) and farmer management decisions (e.g. intermediate input use). The simulated biophysical yield effects are then quantified into monetary terms to estimate economic damages of droughts. We further look into the relationship of the economic damages and the intensity of droughts to determine drought thresholds that lead to increased economic losses.

The results provide bottom-up estimates of the economic damages of drought induced water deficiency in agriculture across Germany for the years 2016-2020. The spatio-temporal patterns of drought impacts can be useful for drought policy planning at local and national level. The economic costs estimation framework could be valuable in estimating farmer compensations and loss and damage of droughts. The results of the study can provide reliable estimates of the costs of climate-change-related extreme weather events, which may help inform macroeconomic and integrated impact assessment models of economic losses (and gains).

How to cite: Nagpal, M., Heilemann, J., Klauer, B., Gawel, E., and Klassert, C.: Hydro-economic assessment of biophysical drought impacts on agriculture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17486, https://doi.org/10.5194/egusphere-egu24-17486, 2024.

EGU24-17759 | Orals | CL2.3 | Highlight

A daily ensemble of Past and Future Weather for rapid attribution and future perspectives 

Hylke de Vries, Geert Lenderink, Erik van Meijgaard, Bert van Ulft, and Wim de Rooy

Europe faced many extreme events in the year 2023; storms, heatwaves, intense precipitation, widespread flooding, to mention a few. Long-standing records were broken, and re-broken again. The events invariably received a lot of attention by the media and triggered many questions from journalists, eager to report about them. These questions are typically about the frequency or ‘extremeness’ of the event, whether or how already occurred climate change has impacted this frequency, and what the future perspectives are: Would a similar event in future or past climate have (had) a larger or smaller impact? 

It is a challenge for scientists to answer such (attribution) questions rapidly, i.e., before or on the day of the event, or in the immediate aftermath. Weather attribution teams like WWA (World Weather Attribution) now apply standardised procedures based on combining observations and climate modelling, to produce such analyses within weeks.

Here we discuss an approach that may augment the set of already existing tools and frameworks for rapid attribution analysis. The approach is based on regional downscaling in combination with pseudo global warming (PGW). Each day a small downscaled ensemble is created using as initial and boundary conditions the ECMWF analysis and forecasts. In addition to this ‘present-day’ ensemble, also a ‘past’ and ‘future’ ensemble are created using PGW. Due to the synchronicity of the time-evolution of the past, current and future ensembles, the signal-to-noise ratio is high, allowing an immediate estimate of how (thermodynamic) changes could have contributed to the event, and how a similar event in a future climate could look. Inherent limitation of PGW is that it cannot, or only in a limited way, address the frequency-change aspect. 

We illustrate the PGW-ensemble with a number of events that occurred during 2023 such as storm Hans (August), the December snowfall, and the unprecedented yearly rainfall amount in the Netherlands.

How to cite: de Vries, H., Lenderink, G., van Meijgaard, E., van Ulft, B., and de Rooy, W.: A daily ensemble of Past and Future Weather for rapid attribution and future perspectives, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17759, https://doi.org/10.5194/egusphere-egu24-17759, 2024.

EGU24-17826 | ECS | Orals | CL2.3

Where and when will the next precipitation record be broken?  

Iris de Vries, Erich Fischer, Sebastian Sippel, and Reto Knutti

Not only will climate change lead to more intense extreme precipitation, it will also lead to more frequent record-breaking daily rainfall. Given the tendency of society to design critical infrastructure and emergency plans based on (statistics derived from) historical observations, an increasing occurrence of record-breaking events – events that are more intense than ever recorded – poses a high risk for loss and damage. 

A major challenge in the projection of very extreme events is their inherent rarity. This problem is even more prominent for record events: by definition these events are not present in sample data because they have not yet occurred. An additional difficulty, which is particularly challenging for precipitation, is the high internal variability in and local character of very rare extremes. This implies that, by chance, an observed data sample of finite size might contain few extremes, whereas the true probability and intensity of extremes given by the (unknown) underlying distribution is much higher. In practice, this can lead to “surprise extremes”. 

With the help of extreme value theory, we approach this problem from two angles, using multi-model CMIP6 data and two different ground-station based observational datasets. Firstly we assess, for all observed land grid cells, where the last observed precipitation record is “extraordinarily long ago” given the theoretical record breaking rate prescribed by historical and future climate according to the CMIP6 models. Secondly, we assess where the last observed record value is “extraordinarily low in intensity” given the historical and future modelled distribution of extreme precipitation. Combining these two approaches, we highlight regions on earth where the probability of record precipitation events in the near future is high.

We find that grid points where the last observed precipitation record is extraordinarily long ago are ubiquitous and scattered globally. When combining this with the observed record intensity, the number of grid points that stand out for their high near-term record probability decreases drastically. We find a somewhat higher density of high-probability grid points in Australia and southern South America, but the pattern is not very clear. Nonetheless, every world region contains a number of grid points where the current observed record is both extraordinarily long ago and low in intensity, and where the near-term probability of a new precipitation record is thus high.

How to cite: de Vries, I., Fischer, E., Sippel, S., and Knutti, R.: Where and when will the next precipitation record be broken? , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17826, https://doi.org/10.5194/egusphere-egu24-17826, 2024.

EGU24-17905 | Posters on site | CL2.3

Climate projections over the Eastern Mediterranean Black Sea region using a pseudo global warming (PGW) approach.  

Patrick Ludwig, Soner C. Bagcaci, Ismail Yücel, M. Tugrul Yilmaz, and Omer L. Sen

This study presents high-resolution (4 km) simulations of the Weather Research and Forecasting (WRF) model using the pseudo-global-warming (PGW) approach. The aim is to investigate seasonal climatic changes in the Eastern Mediterranean Black Sea (EMBS) region between the periods of 2071-2100 and 1985-2014. The climate change signals retrieved from the CMIP6 GCMs under the highest emission scenario (SSP5-8.5) were added to ERA5 data to account for future climate perturbation. During the baseline period  (1995-2014), the dynamically downscaled ERA5 (not perturbed) and ground observations yielded daily near-surface temperature reach correlations of around 0.98 and daily precipitation correlations ranging from 0.60 to 0.76. The WRF simulations for the future climate accurately represent the low-level anticyclonic circulation over the EMBS caused by anomalous ridge development over southern Italy in winter (DJF) and the decrease in vertical pressure velocity and resulting low-level circulation due to heat-low development over the Eastern Mediterranean in summer (JJA) as represented by the GCMs. Likewise, the wetting and drying patterns in the regional WRF simulations match those in the GCM ensemble over the subregions of the EMBS in winter. However, abnormal precipitation increases occur in the WRF simulations over the Caucasus and nearby regions, which is a new insight as this pattern does not exist in the GCM ensemble. This abnormality is likely caused by the higher-than-expected sea-surface temperature (SST) of the Caspian Sea and considering high-resolution simulations over the complex topography of that region.

How to cite: Ludwig, P., Bagcaci, S. C., Yücel, I., Yilmaz, M. T., and Sen, O. L.: Climate projections over the Eastern Mediterranean Black Sea region using a pseudo global warming (PGW) approach. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17905, https://doi.org/10.5194/egusphere-egu24-17905, 2024.

EGU24-18632 | ECS | Posters on site | CL2.3

A climatological look on the intersection of synoptic conditions and extreme weather-induced potential impact events in the cross-border region of Austria and Italy 

Sebastian Lehner, Katharina Enigl, Alice Crespi, Massimiliano Pittore, and Klaus Haslinger
Extreme weather events and associated natural hazards pose a significant global threat to all levels of society. It is scientific consensus that climate change contributes to an increasing frequency and intensity of these events. One of the key challenges for decision-makers in the field of civil protection is to deal with the changing landscape of weather-induced impact events, that are driven by climate change. Hence, assessing the current and changing conditions across spatiotemporal scales for extreme weather events under a changing climate is essential.

This study explores the potential of utilizing weather circulation type classification through its correlation with observed weather-induced extreme events and their potential impacts on the local-scale. Thereby, high-impact weather types can be determined as a relevant background field, serving as a measure about the potential of severe weather hazards. We employ ERA5 reanalysis data as baseline meteorological input data to derive long-term and robust time series of weather types from mean sea level pressure that are relevant for the cross-border region of Austria and Italy. The classification scheme 'Gross-Wetter-Typen' (GWT) with 18 classes was used to assign each day a prevailing weather type class. The overlap between derived classes is further investigated by means of unsupervised clustering techniques, to evaluate clusters of groups across all GWT classes. Additional meteorological fields (e.g. equivalent potential temperature, geopotential height, precipitable water, ...) are validated on top of the GWT classes for further characterisation of extreme weather events. Days exhibiting extreme weather-induced potential impact events are derived via percentile methods applied to precipitation data from observational gridded datasets (Enigl et al., 2024, EGU24-10058). Finally, we extend our analysis with an evaluation of potential changes by applying found relationships to state-of-the-art climate model data from the Coupled Model Intercomparison Project 6 (CMIP6) to investigate the changing landscape of potential weather extremes.

Our findings indicate that a specific subset of large-scale weather circulation patterns acts as a crucial precursor to high-impact weather extremes. Furthermore, considering the climate change scenario SSP3-7.0, the frequency and associated precipitation totals linked to these weather patterns exhibit an increase. This suggests a potential rise in both the frequency and intensity of extreme weather events and their corresponding impacts if emissions continue to increase.

How to cite: Lehner, S., Enigl, K., Crespi, A., Pittore, M., and Haslinger, K.: A climatological look on the intersection of synoptic conditions and extreme weather-induced potential impact events in the cross-border region of Austria and Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18632, https://doi.org/10.5194/egusphere-egu24-18632, 2024.

EGU24-19572 | ECS | Posters on site | CL2.3

Heatwaves and compound extremes under atmospheric blocking 

Magdalena Mittermeier, Laura Suarez-Gutierrez, Yixuan Guo, and Erich Fischer

In early September 2023, Europe was under the influence of a pronounced atmospheric block in the shape of the Greek letter “omega”. Such an omega-blocking is characterized by a persistent anticyclone in the center flanked by two low pressure systems to the south in the west and east. The omega-block interrupts the mean westerly flow and leads to prolonged persistent conditions lasting for at least five days. The core of the omega-blocking in September 2023 was located over Central Europe and Southern Scandinavia, which experienced a heatwave in the first week of September 2023. On the other hand, the regions positioned at the eastern flanks of the omega-blocking (Greece, Bulgaria, Libya) were hit by heavy precipitation resulting in major floods.

While omega-blocking situations can result in severe spatially compounding extremes, there is still a research gap on current and future dynamics of (omega) blocking. Current generations of climate models underestimate blocking frequencies – especially over Europe. This makes it difficult to derive robust statistics about blocking related compound extremes under current and future climate, because the observational record only offers a limited number of event examples and atmospheric blocking underlies a high natural climate variability.

We employ the novel method of ensemble boosting to explicitly boost blocking situations in the Community Earth System Model 2 (CESM2) large ensemble. With this model re-initialization method initial conditions 10 to 30 days before the event are slightly perturbed, which results in hundreds of coherent physical event trajectories (event storylines). This allows to study following research questions: Is the CESM2 model capable of reproducing an omega blocking event with spatially compounding extremes in the magnitude of the September 2023 event? Could the September 2023 event have been even more devastating by chance? Have we experienced anything close to the most intense compound omega-blocking event possible under current climatic conditions? In our poster, we present our research concept as well as preliminary results.

How to cite: Mittermeier, M., Suarez-Gutierrez, L., Guo, Y., and Fischer, E.: Heatwaves and compound extremes under atmospheric blocking, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19572, https://doi.org/10.5194/egusphere-egu24-19572, 2024.

EGU24-19808 | Posters on site | CL2.3 | Highlight

Unveiling and communicating climate change by near-real-time attribution and projection of the current weather based on nudged storyline simulations 

Helge Goessling, Marylou Athanase, Antonio Sánchez-Benítez, Eva Monfort, and Thomas Jung

Attribution and projection of climate change by event-based storylines has recently been established as a powerful tool that complements the well-established probabilistic approach. Event-based storylines which nudge the observed atmospheric winds in climate models have been particularly helpful in isolating the thermodynamic component of climate change. The approach is characterised by a high signal-to-noise ratio because differences due to internal variability are effectively removed by imposing (via nudging) the same large-scale atmospheric circulation in different climates. Nudging-based storylines make it possible to unveil the “climate change signal of the day” for the actually observed weather, be it an extreme or an every-day event, which comes with a great potential for climate change communication. Here we take the approach one step further and present our efforts to provide nudging-based climate storylines in near-real-time. This includes not only the automated extension of storyline simulations on a daily basis, but also the dissemination via an online tool that allows both scientific and non-scientific users to explore the “climate change signal of the day” for a number of relevant variables in useful and intuitive ways. While the omission of possible dynamical changes and the reliance on a single model need to be communicated as clear limitations, we envisage that tools like our prototype may become an important piece of the future dissemination portfolio of climate change information.

How to cite: Goessling, H., Athanase, M., Sánchez-Benítez, A., Monfort, E., and Jung, T.: Unveiling and communicating climate change by near-real-time attribution and projection of the current weather based on nudged storyline simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19808, https://doi.org/10.5194/egusphere-egu24-19808, 2024.

EGU24-585 | ECS | Orals | CL3.2.2

Stability analysis of sea-cliffs coupling stress strain and hydrodynamic modelling as a tool for modern archeological site preservation strategies 

Federico Feliziani, Gian Marco Marmoni, Denis Istrati, Valentina Gianni, Francesca Bozzano, and Salvatore Martino

Cultural heritage (CH) sites are frequently situated in coastal areas that experience landslide activity, potentially influenced by climatic effects. A growing number of studies have directed their attention toward investigating mitigation strategies for CH sites impacted by landslides. Nevertheless, there is a paucity of quantitative studies dedicated to elucidating the relationships between coastal landslide activity and climate-related factors. Specifically, the comprehensive understanding of the extent to which both preparatory and triggering climate-related factors contribute to slope instabilities remains incomplete. This knowledge gap is particularly pronounced in the case of waves and wind, whose impact is extensively examined in coastal engineering applications.
The Punta Eolo sea-cliff (Ventotene island, Italy) is here analyzed since it is frequently affected by rock-falls and topples that are threatening the vulnerable remnants of the roman archaeological site of Villa Giulia. This latter is one of the pilot sites selected in the framework of the H2020 TRIQUETRA European project, aimed to proposing a methodological framework for mitigating climate-related natural hazards affecting cultural heritage.
To account for the action of sea waves on a sea cliff, a preliminary attempt was made to couple hydrodynamic modeling of sea-related actions with stability analysis managed through limit-equilibrium and stress-strain approaches.  For the hydrodynamic modelling a mesh-based computational fluid dynamics (CFD) method, that had been validated previously for extreme wave impact on coastal structures both in 2D and 3D conditions, was utilized. The results of the hydrodynamic analysis (e.g., stress field applied on the cliff by waves impact) were then used as input data for the stability analysis. The slope stability conditions of Punta Eolo's sea cliff were evaluated for a rock-toppling mechanism; following that, slope stability analyses were carried out under static and pseudo-static conditions. The analysis considered both seismic action and static water pressure within the joint sets. In a subsequent phase of investigation, the sea-wave action was incorporated as a force accountable for an elastic rebound sensu Hutchinson (1988). Through hydrodynamic modeling, the maximum computed force exerted by sea waves against the cliff was converted into a pseudo-static coefficient. This latter served as input for the factor of safety (FOS) calculation.
The quantitative analysis has brought to light the potential occurrence of instability conditions in specific rock blocks when the hydrostatic backpressure resulting from the filling of rock cracks is coupled with a pseudo-static force, originating from the elastic rebound induced by the impact of sea waves. This scenario represents the most frequently encountered action at the examined cliff of Punta Eolo.
Finally, the project of the ongoing installation of a tailor-designed monitoring system in Punta Eolo is presented. This system aims to characterize the physical attributes of sea-related preparatory and triggering factors affecting the cliff, and to assess the deformative response of the cliff itself under the influence of periodic thermal and hydrodynamic stressors.

How to cite: Feliziani, F., Marmoni, G. M., Istrati, D., Gianni, V., Bozzano, F., and Martino, S.: Stability analysis of sea-cliffs coupling stress strain and hydrodynamic modelling as a tool for modern archeological site preservation strategies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-585, https://doi.org/10.5194/egusphere-egu24-585, 2024.

EGU24-1753 | ECS | Posters virtual | CL3.2.2

Advanced sensing and IoT for monitoring climatic risks and natural hazards at underwater and coastal cultural heritage 

Lampros Pavlopoulos, Panagiotis Michalis, Marios Vlachos, Anastasios Georgakopoulos, and Angelos Amditis

As climate change progresses, shifting weather events are expected to become more severe [1], posing a significant threat to heritage sites but also to connected communities. The monitoring of climatic risks at coastal and underwater heritage sites is considered of significant importance to enhance understanding of degradation processes but it constitutes a resource-intensive and intricate process. Frequently, data collection from devices requires the coordination of expeditions for sensor retrieval and manual data acquisition. The monitoring area's spatial extent is limited due to the utilization of stationary sensors. Another challenge lies in the integration of both subaquatic and terrestrial parameters into an advanced monitoring solution that provides an unobstructed assessment of the hazards encompassing the heritage area.

The development of multiple low-cost sensors endowed with Internet of Things (IoT) capabilities, can facilitate real-time monitoring and positioning for both subaquatic and terrestrial data collection of environmental parameters that amplify the deterioration of heritage assets.

To address subaquatic data acquisition, an IoT Conductivity Depth Temperature (CDT) device has been designed to measure salinity and temperature characteristics with a dual role of a wearable sensor for divers and a static sensor affixed near the seabed. To streamline data transmission beyond aquatic environments, the device is engineered to transmit data when situated outside the water. The second subaquatic sensor developed serves the purpose of crowdsourcing and designed to be attached to vessels from local communities, enabling real-time data collection on salinity, temperature, and chlorophyll concentration. Both subaquatic devices integrate Inertial Measurement Unit (IMU), Narrowband Internet of Things (NB-IoT), and Global Navigation Satellite System (GNSS) technologies within their design.

The proposed coastal monitoring solution incorporates a weather station with the capacity to measure and transmit real-time data on diverse weather parameters, encompassing temperature, humidity, rain volume, wind speed, UV index, and light intensity. The fourth device integrates strain gauges and accelerometers, offering valuable data for both static and dynamic monitoring. This enables the assessment of vibration levels and provides information on the evolution of cracks and tilts within the monitored site. To optimize energy efficiency, all four devices have been engineered with low power consumption capabilities. Furthermore, devices located outside the water are equipped with solar panels to ensure complete energy autonomy.

In conclusion, the development of multiple low-cost sensors with IoT capabilities demonstrates a commitment to overcoming the financial and logistical complexities of data collection. By incorporating advanced technologies such as IMU, NB-IoT, and GNSS into subaquatic devices, we enhance the precision and versatility of real-time monitoring and positioning. By seamlessly integrating technological innovation with practical considerations, we aim to provide a comprehensive and efficient means of safeguarding these invaluable cultural and environmental treasures.

Acknowledgement:

This research has been funded by European Union’s Horizon Europe research and innovation programme under THETIDA project (Grant Agreement No 101095253).

References:

[1] Michalis, P.; Tarantino, A.; Tachtatzis, C.; Judd, M.D. (2015). Wireless monitoring of scour and re-deposited sediment evolution at bridge foundations based on soil electromagnetic properties. Smart Mater. Struct. 2015, 24, 125029.

How to cite: Pavlopoulos, L., Michalis, P., Vlachos, M., Georgakopoulos, A., and Amditis, A.: Advanced sensing and IoT for monitoring climatic risks and natural hazards at underwater and coastal cultural heritage, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1753, https://doi.org/10.5194/egusphere-egu24-1753, 2024.

EGU24-1958 | ECS | Posters virtual | CL3.2.2

Unveiling the Hidden Data Ecosystems: A Pathway towards conservation and protection of Cultural Heritage sites 

Aikaterini Karagiannopoulou, Panagiotis Michalis, Chrysovalantis Tsiakos, and Angelos Amditis

Underwater and Coastal Cultural Heritage (CH) sites face unprecedented threats from climatic risks and natural hazards, making their preservation, conservation and protection complex and challenging issues. One primary challenge for designing efficient preservation strategies is the absence of curated open data streams that could allow local authorities to have a better understanding of the evolving degradation parameters at CH sites. The existing data silos and the lack of circular, sustainable and curated open data ecosystems (ODE) also leave the key players (i.e., asset managers, local authorities, etc.) of the heritage sites and their connected communities defenceless as they are usually equipped with obsolete and coarse information, a condition that generates a knock-on effect on the adaptation and mitigation strategies against these threats.

This study focused on providing a methodological approach towards data circularity by leveraging on the Open Data Institute's (ODI) Data Landscape Playbook (DLP) methodology. The ODI DLP serves as a comprehensive guide for developing effective data ecosystems. By adapting this playbook to the unique challenges posed by underwater and coastal cultural heritage preservation, stakeholders can harness the power of data to enhance resilience, response, and recovery efforts in the aftermath of natural disasters. This specific methodology consists of four consecutive steps, involving the investigation of the context of the objectives of each pilot case, the identification of all the relevant Data Assets and Data Owners, and therefore details related to the interfaces/infrastructures and standardised data formats that are commonly adopted. The last pillar of this methodology is declared as a prerequisite towards the data circularity, as it tries to profile heritage sites perspectives regarding the ethical, legal, and regulatory context that is chosen based on the Data Spectrum classification so as to disseminate the data sources through the public. The DLP also emphasises the importance of data quality assurance and control measures, ensuring this way about the credibility of the existing information and acknowledging the best practices so as to succeed.

The engagement of diverse stakeholders under the prism of the ODI-DLP attempts to foster collaboration and partnerships among governments, archaeologists, marine biologists, and local communities, and thus facilitate to formulation of sustainable strategies for risk assessment and mitigation, forming the cornerstone of resilient preservation practices. Towards this process, community involvement not only enriches the data ecosystem but also facilitates the integration of traditional knowledge, ensuring a more holistic and culturally sensitive approach to CHs’ preservation. This ODI-DLP methodology is currently applied to seven underwater and coastal heritage sites of THETIDA project, i.e., Mykonos (Greece), Gallinara and Equa (Italy), Algarve (Portugal), Paralimni (Cyprus), Svalbard (Norway), and Ijsselmeer (Netherlands) and thus, will contribute to the digitalisation of each site, creating this way a framework towards the generation of resilient data ecosystems and pathways to improve and enhance CH protection.

Acknowledgement:

This research has been funded by European Union’s Horizon Europe research and innovation programme under THETIDA project (Grant Agreement No 101095253). 

How to cite: Karagiannopoulou, A., Michalis, P., Tsiakos, C., and Amditis, A.: Unveiling the Hidden Data Ecosystems: A Pathway towards conservation and protection of Cultural Heritage sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1958, https://doi.org/10.5194/egusphere-egu24-1958, 2024.

EGU24-2090 | Posters on site | CL3.2.2 | Highlight

THETIDA: Safeguarding and protecting Europe’s coastal and underwater cultural heritage from the effects of climate change and natural hazards 

Panagiotis Michalis, Claudio Mazzoli, Vassilia Karathanassi, Deniz Ikiz Kaya, Flavio Martins, Michele Cocco, Anaïs Guy, and Angelos Amditis

Climate change and natural hazards pose significant threats to heritage sites, with major impact on people's livelihoods and connected communities. Increased frequency and intensity of extreme weather conditions have a substantial detrimental impact on cultural heritage (CH), both on tangible assets (e.g. monuments, historic buildings, and sites), and intangible elements (e.g. knowledge, cultural practices, and oral traditions) that are inherited from the past. Factors contributing to the deterioration of heritage sites are attributed to sea level rise, ocean acidification, intensified storm activity, temperature elevation, and coastal erosion that put significant stress on the stability, preservation, conservation, and security of both tangible and intangible cultural heritage in underwater and coastal environments.

However, limited knowledge exists on risk assessment and protective measures actions to mitigate these multiple hazards and complex risks posed by climatic conditions and natural disasters. This highlights the need for more integrated assessments that consider the collective impacts of various hazards on cultural heritage and their corresponding protection systems. It is therefore of significant importance to employ and test the effectiveness of novel measures across a spectrum of heritage sites threatened by various climatic conditions and risks.

Addressing these two points, the THETIDA project focuses on the development of a preventive conservation strategy that includes monitoring, risk preparedness and management, for underwater and coastal CH. The main objective is to identify and ward off climatic risks and natural hazards and promote adaptation, reconstruction, and other post-disruption strategies to restore normal conditions to the historic area. THETIDA project also emphasizes long-term strategic approaches to adapt to climate change and to wield policy tools for economic resilience. This is achieved through an interdisciplinary team of researchers, experts and practitioners that will develop, test and validate an integrated multiple heritage risk assessment and protection system with evidence-based monitoring frameworks, innovative tools and instruments and through participatory and crowdsourcing processes. The project actions will be implemented at seven pilot sites across the European continent, linking social innovations with state-of-the-art technologies, including ICT and IoT harmonised tools, to enhance resilience of underwater and coastal heritage sites.

Acknowledgement:

This research has been funded by European Union’s Horizon Europe research and innovation programme under THETIDA project (Grant Agreement No. 101095253) (Technologies and methods for improved resilience and sustainable preservation of underwater and coastal cultural heritage to cope with climate change, natural hazards and environmental pollution).

How to cite: Michalis, P., Mazzoli, C., Karathanassi, V., Ikiz Kaya, D., Martins, F., Cocco, M., Guy, A., and Amditis, A.: THETIDA: Safeguarding and protecting Europe’s coastal and underwater cultural heritage from the effects of climate change and natural hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2090, https://doi.org/10.5194/egusphere-egu24-2090, 2024.

EGU24-2448 | ECS | Orals | CL3.2.2

Innovative financing strategies for the resilience of cultural landscapes. A literature and practice review 

Dana Salpina, Veronica Casartelli, Angelica Marengo, and Letizia Monteleone

According to the Intergovernmental Panel on Climate Change (IPCC) coastal risks are projected to increase by at least one order of magnitude over the 21st century due to committed sea level rise, impacting cultural and natural heritage in coastal areas. Amidst the urgency of climate change adaptation and mitigation, which often exceeds available public budgets, there is a growing recognition of the vital role played by innovative financing strategies and business models .

The existing body of knowledge on resilience financing for cultural heritage and landscapes is somewhat fragmented and primarily focuses on the conservation or reuse of the built heritage. Few studies addressed the financial strategies for productive cultural landscapes. Unlike conventional cultural heritage categories such as historical monuments, archaeological artefacts, and museum collections, productive cultural landscapes are dynamic socio-ecological systems. Consequently, their resilience demands a holistic approach that addresses not only the physical dimension but also ensures the continuity of underlying activities, such as agriculture, forestry, and fishery.

As part of the  “RescueMe” project – focused on equitable resilience solutions to strengthen the link between cultural landscapes and communities – this study aims to consolidate fragmented knowledge. It seeks to provide an initial state-of-the-art overview of existing financing strategies, with a specific focus on productive cultural landscapes, such as agricultural landscapes. Based on a systematic review of existing literature, databases, and drawing insights from prior projects, this study presents a thorough review of innovative financial strategies. This encompasses economic, financial, and business models that have the potential to leverage regenerative capital investments in landscape resilience.

The study reveals dominant themes and categories of financing strategies for the resilience of productive cultural landscapes. The selected innovative financial strategies will be gathered in the RescueME resilience meta-repository, to offer an integrated searchable database of solutions, elaborated jointly with the researchers from the Università di Bologna and the Conexiones improbables, with the consultation of partners representing resilience landscape laboratories (R- labscapes) of the project.

The findings offer valuable insights for policymakers, businesses, and cultural institutions seeking to develop strategies for scaling up investments. This contribution is instrumental in navigating the complex landscape of innovative financing, providing actionable knowledge for sustainable and effective decision-making. The information available in the meta-repository will be accessible for reuse to a wide-range of stakeholders, including policymakers, researchers and practitioners.

How to cite: Salpina, D., Casartelli, V., Marengo, A., and Monteleone, L.: Innovative financing strategies for the resilience of cultural landscapes. A literature and practice review, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2448, https://doi.org/10.5194/egusphere-egu24-2448, 2024.

EGU24-2539 | Orals | CL3.2.2 | Highlight

R&I solutions and Blue Culture Technology Hubs supporting Underwater Cultural Heritage research 

Lydia Stergiopoulou, Angelos Manglis, Polyvios Raxis, and Stelios Krinidis

This work presents the framework of BCT Hubs project that operates in the space of Blue Culture Technologies (BCT) supporting the Underwater (UW) Cultural Heritage (CH) scientific research. The development of BCT Excellence Hubs and their promoted R&I solutions support, as regional ecosystems, the sustainable protection, restoration, valorization, management, and accessibility of UWCH by consolidating capacities of public sector, research/academia, NGOs, and business stakeholders. An innovative framework is under development that combines sensors information with navigational data and GIS-based software to provide high-quality 3D/4D UW representations. These R&I services will be linked to virtual reality (VR) technologies improving on-site and remote accessibility to UWCH via dry-dive; as well as to an augmented reality (AR) app that based on sensing solutions can augment diving capability. Ongoing additional developments combination of the 3D/4D models with real-time streams and AI algorithms aiming at detecting looting or degradation of UW assets.  

The development of the BCT Excellence Hubs in Greece, Malta, Bulgaria aims at the establishment of regional ecosystems, where R&I actors will offer access to excellence, knowledge transfer and development of entrepreneurial skills. The technical support needed, as well as the digital maturity level of the Blue Culture value chain of the ecosystems will be analysed and assessed, towards receiving tools and support with respect to their UWCH missions. Overall aim is the management of UW heritage under threat, UW documentation, archaeological excavation, safeguarding, promotion and accessibility.

How to cite: Stergiopoulou, L., Manglis, A., Raxis, P., and Krinidis, S.: R&I solutions and Blue Culture Technology Hubs supporting Underwater Cultural Heritage research, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2539, https://doi.org/10.5194/egusphere-egu24-2539, 2024.

EGU24-3000 | Orals | CL3.2.2

Monitoring an Arctic cultural heritage site with state-of-the-art remote sensing techniques – Lessons from the THETIDA project 

Ionut Cristi Nicu, Kleanthis Karamvasis, Vassilia Karathanassi, and Paloma Guzman

The Svalbard archipelago lies 1100 km south of the North Pole and 800 km north of the Norwegian coast. The region is one of the most important and strategic terrestrial nodes on Earth, separating the Greenland Sea, the Barents Sea, and the Arctic Ocean. The cultural landscape reflects human life and activity in a harsh and fragile environment.

We present here the preliminary results of the pilot site from the Thetida project – the coal cableway station at Hiorthhamn, 1917 (Taubanestasjonen i Hiorthhamn). The study area was extended to the “town” of Longyearbyen, located across the bay from Hiorthhamn. Longyearbyen is the settlement with the largest number of Svalbard residents (approximately 2500) and with an impressive number of protected cultural heritage sites – approximately 400. The total number of protected cultural heritage sites in Svalbard is 4590.

Previous studies have shown that the main risks to the Hiorthhamn site are coastal erosion, permafrost degradation, rockfall, thaw slumps, snow avalanches, surface erosion and thermo-erosion gullies, weathering, river flooding, and solifluction. Previous data (NPI orthophotos from 1936, 2009 – 2011, field surveys with UAV and total station in 2019 and 2020) and the most recent remote sensing data (Planet Sky Sat images – 2023) are used to assess the risk of degradation. Coastal erosion, calculated with the help of DSAS, for the sector where the site is located, shows high erosion rates of −0.77 m/yr (for the period 1927-2020) when compared to other studies from Svalbard. The latest forecast analysis estimates that the entire area will be eroded over the next two decades.

Furthermore, previous studies have shown that InSAR-based time series of land deformation appears to show continuous subsidence over permafrost regions in recent years. In this study, a method based on persistent scattering interferometry was used to estimate land deformation in the wide area of Longyearbyen, Svalbard. The InSAR-based land deformation estimates were calculated by processing 268 Sentinel-1 images from early 2018 to late 2023. Within the city of Longyearbyen, regions of stable, uplifting, and subsiding ground motion were identified. The land deformation results were interpreted by considering in-situ permafrost data and building characteristics, such as roof material, age, and heating mechanisms under building foundations. The results are important for better understanding the dynamics of the permafrost landscape under a warming climate and for predicting flooding using SAR altimetry data. The study makes a significant contribution to the protection of cultural heritage. The coal cableway station is the most iconic and visible object in Hiorthhamn, so much so that it can be seen from Longyearbyen, encouraging tourists to take a boat or a kayak to visit. Longyearbyen is the main tourist attraction on the island. It is therefore important to assess and monitor the risk of degradation so that, together with the local authorities, the most sustainable and climate-friendly measures can be taken for future generations.

Acknowledgment: This research has been funded by European Union’s Horizon Europe research and innovation funding under Grant Agreement No: 101095253, THETIDA project.

How to cite: Nicu, I. C., Karamvasis, K., Karathanassi, V., and Guzman, P.: Monitoring an Arctic cultural heritage site with state-of-the-art remote sensing techniques – Lessons from the THETIDA project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3000, https://doi.org/10.5194/egusphere-egu24-3000, 2024.

EGU24-3132 | ECS | Orals | CL3.2.2 | Highlight

Living Labs for participatory value, risk and impact assessments in coastal and underwater heritage sites  

Deniz Ikiz Kaya, Paloma Guzman, Cristina Veiga-Pires, Sonia Oliveira, Tina Katika, Anne Veere Hoogbergen, Kevin Pulles, and Ionut Cristi Nicu

Climate change can have detrimental effects on biodiversity and people’s livelihoods and communities. Extreme weather conditions triggered by climate change significantly impact cultural heritage that represents tangible (i.e., historic sites, cultural landscapes) and intangible (i.e., knowledge, cultural practices, oral traditions) assets, especially in coastal areas and underwater sites. Inclusive risk monitoring, preparedness, and management are necessary to identify and ward off additional threats, and to promote inclusive and sustainable adaptation and safeguarding of the heritage sites.  

Stakeholder and end-user engagement is gaining ground in risk mitigation and monitoring impacts of climate change to support co-creation processes for climate adaptation strategies. Stakeholders often have valuable knowledge, insights and expertise, and their engagement allows collection of diverse perspectives and data, which can lead to better-informed decisions and identify potential risks and opportunities. However, it can also be difficult to establish collaboration and open communication among different actors and parties. This paper presents the potential of Living Labs (LL), a participatory social innovative methodology, that functions as multi-stakeholder platforms. LL create interaction spaces in which multiple stakeholders and end users collaborate in creating new solutions to complex problems. 

This paper presents the initial stage of development and testing of the LL methodology to be implemented in seven pilot sites of underwater and coastal heritage across three different Europe oceanic climates that are vulnerable to varied impacts of climate change. Results present common challenges in the identification of diverse range of stakeholders and their engagement in co-creation processes of value and impact assessment, decision and future making, as well as testing and validating of a new crowdsourcing tool in real-life contexts. The goal has been building inclusive multi-stakeholder communities for establishing sustainable participatory processes for co-designing and co-creating risk assessment and adaptation strategies that take sociocultural values at their core. For this purpose, a LL toolkit has been developed that compiles different sets of tested methods that have been applied in the case studies adaptable to local contexts.  

This paper will show the outcomes of a training workshop and the preliminary results of the adopted and tested LL tools and processes in which stakeholders from pilot sites identify heritage inherent values based on sociocultural relationships. Results highlighting diverse understandings of climate impacts and challenges but are also expected to show a shift on peoples’ perspectives when providing meaning to climate change impacts. Such insights and feedback are discussed in terms of strengths and weaknesses that are unique to the site, as well the LL methods and tools employed in each site. Such exercises are increasingly needed to customize participatory methods adapted to fit integrated multiple hazard assessment tools and strengthen sustainable pathways for cultural heritage management. Overall, these processes will contribute to better understanding of the complexity of climate impacts, not only on heritage, but also in related social dynamics. 

Acknowledgement:  This research has been funded by European Union’s Horizon Europe research and innovation funding under Grant Agreement No: 101095253, THETIDA project. 

How to cite: Ikiz Kaya, D., Guzman, P., Veiga-Pires, C., Oliveira, S., Katika, T., Hoogbergen, A. V., Pulles, K., and Nicu, I. C.: Living Labs for participatory value, risk and impact assessments in coastal and underwater heritage sites , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3132, https://doi.org/10.5194/egusphere-egu24-3132, 2024.

EGU24-3517 | Orals | CL3.2.2 | Highlight

Empowering Communities Through Digital Innovation and Crowdsourcing for Cultural Heritage Preservation 

Tina Katika, Konstantinos Koukoudis, Panagiotis Michalis, Deniz Ikiz Kaya, Paloma Guzman, Cristina Veiga-Pires, and Angelos Amditis

Climatic risks and natural hazards pose a serious threat with long lasting impacts on cultural heritage, as well as on people’s livelihoods and connected communities. It is therefore considered of major importance to better understand the multivaried impacts of climate change on coastal and underwater cultural heritage through the active involvement of scientists, citizens and other relevant stakeholders in citizen science to engage them in data collection and involve their diverse perspectives, reflections and relationships with heritage for multi-hazard and risk monitoring.

This study focuses on exploiting the full potential of digital solutions together with co-creation and co-design processes through citizen science, crowdsourcing and participatory Living Lab methodologies. The main goal is to help citizens identify the values of coastal and underwater heritage, to understand the risks, and engage them in monitoring the changes and documenting the impacts of climate change and natural hazards on the heritage elements to collaboratively develop sustainable preservation and adaptation strategies. An immersive mobile application will be developed to raise awareness to citizens and their communities about digitalization and its benefits for cultural heritage protection and preservation. The proposed technological advancement exploits Augmented Reality (AR) technology to seamlessly integrate in-situ and remotely sensed data, effectively bridging the gap between valuable underwater cultural assets and a broader audience, that may not have had the opportunity to experience them otherwise.  

The digital solution is being co-designed and co-developed with citizens and their communities exploiting immersive crowdsourcing techniques using user-centered applied research and open innovation approaches. It employs crowdsourced techniques to promote the appreciation of the tangible and intangible heritage assets, empowering communities to actively participate in preserving and showcasing their cultural treasures. Citizens will be able to share their feedback, observations, comments and other data considered relevant to establish their unique point of view. The mobile application will then facilitate the demonstration and visualization of sensed data obtained by underwater and coastal crowdsensing units provided to the community (e.g. fishing boats, divers) to inform about environmental parameters, providing a comprehensive understanding of heritage dynamics and potential risks. Finally, the proposed digital solution will enhance citizen engagement, creating immersive experiences through AR features that bridge the gap between the past and present, fostering a deeper connection between people and their cultural legacy.

The immersive digital solution is being co-developed with seven different demonstration sites across Europe and will also be made available to a large stakeholder community at the end of 2024 for the first iteration of user feedback. Together, these functionalities establish a powerful tool for the proactive management and protection of heritage while actively involving and raising awareness among connected communities.

Acknowledgement:

This research has been funded by the European Union’s Horizon Europe research and innovation programme under THETIDA project (Grant Agreement No. 101095253) (Technologies and methods for improved resilience and sustainable preservation of underwater and coastal cultural heritage to cope with climate change, natural hazards and environmental pollution).

How to cite: Katika, T., Koukoudis, K., Michalis, P., Ikiz Kaya, D., Guzman, P., Veiga-Pires, C., and Amditis, A.: Empowering Communities Through Digital Innovation and Crowdsourcing for Cultural Heritage Preservation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3517, https://doi.org/10.5194/egusphere-egu24-3517, 2024.

EGU24-3792 | ECS | Orals | CL3.2.2

Augmented Reality localization technology for Ancient Greek Heritage Exploration and Preservation 

Konstantinos Koukoudis, Tina Katika, Spyridon Nektarios Bolierakis, George Karafotias, and Angelos Amditis

CirculAR, an innovative Augmented Reality (AR) application, introduces a gamified and engaging user-environment interaction, creating a unique platform for the exploration of Ancient Greek cultural heritage. Through a blend of educational and entertaining elements, CirculAR immerses end-users in an interactive experience, leveraging localized simulation technology and visual detection to augment information and present three-dimensional (3D) models at two prominent archaeological sites and a museum. 

The AR application seamlessly integrates with the existing infrastructure of archaeological sites, enhancing the overall visitor experience by providing appealing and enjoyable interactions. CirculAR's distinctive features, including visual and audio descriptions, content manipulation, virtual tours, and a virtual agent, contribute to an inclusive and accessible immersive encounter for on-site users. The app incorporates gamified and educational components such as quizzes, animations, visualizations, and scoring mechanisms to enrich the learning experience. 

Moreover, CirculAR extends its impact beyond visitor engagement by offering an authoring tool with a user-friendly interface addressed mainly to institutions, research centers, and organizations. This tool empowers content owners to preserve, curate, and disseminate their cultural heritage data effectively. Augmented storylines within the application faithfully replicate ancient sites, drawing on 3D content design and extensive research conducted by museums and archaeological sites. 

CirculAR’s immersive nature, emphasizing archaeological elements, is positioned to contribute significantly to highlighting existing components and recovering missing fragments crucial for a comprehensive understanding of historical areas. The application aligns with long-term strategic approaches for resilience and sustainability of historical monuments by seamlessly integrating with established infrastructure and supporting the preservation and dissemination of cultural heritage data. By fostering engagement, education, and preservation, the application supports cultural heritage management and proves a valuable tool for heritage conservation and public awareness. 

CirculAR has been tested and evaluated as part of internal testing procedures; evaluating how external parameters (such as, the change of scenery, lighting, angle, and positioning affect the localized content). The application will be tested and evaluated in real-life settings the upcoming spring at the three selected locations. Part of the future advancements of CirculAR include its evolution into formidable crowdsourcing tool, leveraging enhanced algorithms and user participation to collaboratively map climate change and natural hazards affecting cultural heritage sites. This transformation will empower a diverse and interconnected user base to collectively generate valuable insights, fostering a sense of shared responsibility and innovation. 

This research is part of APSIM project and has been co‐financed by the European Union NextGenerationEU under the call RESEARCH – CREATE – INNOVATE 16971 Recovery and Resilience Facility (project code:ΤΑΕΔΚ‐06171).

How to cite: Koukoudis, K., Katika, T., Bolierakis, S. N., Karafotias, G., and Amditis, A.: Augmented Reality localization technology for Ancient Greek Heritage Exploration and Preservation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3792, https://doi.org/10.5194/egusphere-egu24-3792, 2024.

Submerged underwater cultural heritage (UCH) provides insight into past human behavior and history and thus the preservation of these artifacts at the site of discovery is crucial. However, marine environmental conditions such as physical, chemical, and biological processes directly impact the degradation of these underwater historical sites. Under the frame of the Horizon Europe project THETIDA (Technologies and methods for improved resilience and sustainable preservation of underwater and coastal cultural heritage to cope with climate change, natural hazards and environmental pollution), which runs between 2023 and 2026, the current work aims to demonstrate the suitability of process-based numerical models to (1) predict in real-time hazards threatening UCH sites associated with currents and sediment abrasion and (2) to estimate the risks associated with these oceanic conditions. This general approach is demonstrated for the Coast of Algarve (southern coast of Portugal), focusing specifically on the B-24 wreck. This WWII bomber airplane rests on the bottom of the coastal shelf at 20 m deep and approximately three kilometers offshore of Praia de Faro. The methodology couples a wave model (SWAN) to an existing operational hydrodynamic system SOMA powered by the MOHID model, which will provide inputs to run a non-cohesive sediment transport model. In-situ measurements and laboratory experiments will be used to determine deterioration rates that will provide insights into risk categorization and impacts on UCH sites. The final product will be a demonstrative operational ocean model for UCH management, assessment, and emergency response.

Acknowledgement: This research has been funded by the European Union’s Horizon Europe research and innovation programme under THETIDA project (Grant Agreement No. 101095253) (Technologies and methods for improved resilience and sustainable preservation of underwater and coastal cultural heritage to cope with climate change, natural hazards and environmental pollution). The authors also acknowledge Fundação para a Ciência e Tecnologia (FCT), under the project LA/P/0069/2020 granted to the Associate Laboratory ARNET and UID/00350/2020 CIMA (https://doi.org/10.54499/UIDP/00350/2020).

How to cite: Garzon, J. L., Mills, L., and Martins, F.: Operational hydrodynamic modeling as a tool to predict risks on underwater cultural heritage sites. Demonstration for the Algarve Coast., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3913, https://doi.org/10.5194/egusphere-egu24-3913, 2024.

EGU24-5614 | Posters on site | CL3.2.2 | Highlight

Recent past and future climate change over the TRIQUETRA cultural heritage sites and related damage risk 

Aristeidis K. Georgoulias, Dimitris Akritidis, Efstathia Tringa, Haralambos Feidas, and Prodromos Zanis

Within the framework of TRIQUETRA (Toolbox for assessing and mitigating Climate Change risks and natural hazards threatening cultural heritage; https://triquetra-project.eu/) research project, meteorological data from weather stations (observations) as well as simulations from regional climate models (RCMs) have been analyzed to assess recent past and future climate change over eight cultural heritage (CH) sites in six countries. From South to North the CH sites are Choirokoitia in Cyprus, Aegina, Epidaurus, and Kalapodi in Greece, Ventotene in Italy, Les Argilliez in Switzerland, Roseninsel in Germany, and Smuszewo in Poland. The observations were acquired from weather stations (from various networks) with long meteorological records at the proximity of the examined CH sites, while the RCM data come from the EURO-CORDEX. More specifically, 11 sets of high resolution (~12.5 km) RCM simulations were analyzed, covering the historical period 1950-2005 and the future period 2006-2100 under three different Representative Concentration Pathways (RCPs) of the Intergovernmental Panel on Climate Change (IPCC), namely the RCP2.6 (strong greenhouse gas mitigation), RCP4.5 (medium mitigation), and RCP8.5 (no further mitigation). The climate analysis over the recent-past period 1970-2020 revealed a robust warming and increasing of heat stress at the materials of the CH assets. Furthermore, the multi-model climate analysis based on the RCM simulations for the three different future scenarios points towards a hotter and drier future climate for the CH sites at the South and a hotter and wetter climate for the CH sites in the North. Analysis of the Heritage Outdoor Microclimate Risk (HMRout) and Predicted Risk of Damage (PRD) indices over the recent past period indicates notable variations in microclimate conditions with aggravation of heat stress at CH assets made of stone and marble, pointing towards an increase in predicted risk of damage. Analyzing the future changes in HMRout and PRD indices based on the multi-model ensembles of RCM simulations for the three different future scenarios will provide a more comprehensive understanding of how the resilience of materials and the overall preservation of stone and marble CH sites may be affected.

This work is based on procedures and tasks implemented within the project “Toolbox for assessing and mitigating Climate Change risks and natural hazards threatening cultural heritage - TRIQUETRA”, which is a Project funded by the EU HE research and innovation programme under GA No. 101094818.

How to cite: Georgoulias, A. K., Akritidis, D., Tringa, E., Feidas, H., and Zanis, P.: Recent past and future climate change over the TRIQUETRA cultural heritage sites and related damage risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5614, https://doi.org/10.5194/egusphere-egu24-5614, 2024.

EGU24-5619 | Orals | CL3.2.2

The TRIQUETRA Knowledge Base Platform 

Christos Kontopoulos, Anastasia Anastasiou, Efthymios Magkoufis, Apostolos Sarris, Victor Klinkenberg, Miltiadis Polidorou, Styliani Verykokou, and Vasiliki Charalampopoulou

The TRIQUETRA project seeks to establish an evidence-based assessment platform for precise risk assessment. Functioning as a Decision Support Tool, this platform aims to enhance efficiency in risk mitigation and site remediation. The TRIQUETRA project's overall approach is structured around three key elements: (i) Risk Identification, (ii) Risk Quantification, and (iii) Risk Mitigation.

Within this framework, a novel Knowledge Base Platform (KBP) has been created, serving as an electronic repository equipped with advanced search tools and capabilities. It encompasses information on Climate Change (CC), geological, historical, and site-specific data, along with risks and mitigation measures for Cultural Heritage (CH) sites based on the verified data, geographical identification and results obtained from the outputs of the project.

The primary goal of the KBP is to comprehensively integrate and visualize all shared project data, utilizing both a searchable literature database and a sophisticated WebGIS platform that adheres to the standards set by the Open Geospatial Consortium (OGC) and INSPIRE. It also incorporates various features for the deployment, cataloguing and categorisation of the data produced and shared within the project, to enhance the discoverability of the data. The KBP is structured based on two distinct key components, namely the Bibliography inventory and the WebGIS. These distinct sections of the platform gather all the data and information related to the pilot CH sites of the project. The combination of available datasets for each pilot site leads to the creation of a data cube - a multidimensional structure facilitating the efficient representation and analysis of data across various dimensions, including time and location.

It is imperative to point out that the platform will keep evolving throughout the course of the project in order to align with upcoming project outputs, enabling the fusion of different data types and efficient research on each pilot CH site. This, in turn, contributes to advancing knowledge in CH monitoring and facilitating optimal preservation and risk mitigation actions.

How to cite: Kontopoulos, C., Anastasiou, A., Magkoufis, E., Sarris, A., Klinkenberg, V., Polidorou, M., Verykokou, S., and Charalampopoulou, V.: The TRIQUETRA Knowledge Base Platform, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5619, https://doi.org/10.5194/egusphere-egu24-5619, 2024.

EGU24-8951 | ECS | Orals | CL3.2.2

Policy matrices – A tool for reviewing the effectiveness of risk management policies across scales and disciplines.  

Louis Durrant, Jacques Teller, Angela Santangelo, and Benedetta Baldassarre

Policies are a deliberate system that defines action and guides short-term decisions in pursuing a goal. Policy is a fundamental instrument of governance which is extensively used worldwide. However, not all policies are created equally. Contemporary literature is littered with examples of policy failures, and a large research emphasis is dedicated to co-creating ‘good’ policy. This challenge of developing good policy is exacerbated when we consider the rapidly evolving risks related to climate change. The evolving risks can make it difficult to define valid policy goals over the longer term. Furthermore, stakeholders are increasingly needed across policy and practice to overcome siloed working and co-create transdisciplinary risk management policies, considering both long-term strategic objectives and short- to medium-term operational solutions. Risk management policy instruments are relevant across spatial scales and engage with policies from other disciplines (urban planning, heritage conservation, environmental management). The article presents an innovative tool called the policy matrix to address challenges faced by policy experts. The policy matrix capitalises upon the co-creative research of the Organigraphs technique defined by Durrant et al. (2021) to co-create disaster risk management governance maps.  The article compares two policy matrices developed as part of a Horizon 2020-funded project called SHELTER. In its simplest form, a policy matrix arranges risk management policy instruments around an issue depending on their scale of implementation and disciplinary lens. This allows stakeholders to see all the policy instruments considered relevant to some specific issues. It can further provide stakeholders a robust platform to critique those policies.  By way of example, providing them with a tool to clearly “measure” the links between these policies, to identify policy gaps in thematic/operationalisation, or, from a practical perspective, to provide a tool for experts to review the level of participation in the design of these policies or the effectiveness of these policies in practice.

 

How to cite: Durrant, L., Teller, J., Santangelo, A., and Baldassarre, B.: Policy matrices – A tool for reviewing the effectiveness of risk management policies across scales and disciplines. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8951, https://doi.org/10.5194/egusphere-egu24-8951, 2024.

EGU24-10181 | Posters on site | CL3.2.2

Remote sensing techniques for monitoring cultural heritage sites  

Vassilia Karathanassi, Kleanthis Karamvasis, Viktoria Kristolari, Polychronis Kolokoussis, Margarita Skamantzari, and Andreas Georgopoulos

Climate change is likely to have a direct impact on tangible cultural heritage. Cultural heritage sites are already experiencing the impact of variations in temperature, precipitation, atmospheric moisture, and wind strength, along with rising sea levels and shifts in the frequency of extreme events. Leveraging remote sensing tools presents an opportunity for the effective surveillance and detection of potential threats to Cultural Heritage sites, along with monitoring the material deterioration in monuments. Since monuments are not isolated in the geographical space, assessment and evaluation of changes in their broader area are important because they serve as warning signals to the concerned stakeholders and facilitate them to take measures for preventing CH asset damages. Satellite data after appropriate processing provide significant “background” information by pointing out a) hazards with a slow or gradual onset in the broad area of the CH monuments and facilitating change assessment including ground deformation and land cover changes and b) assessing damage on both the surrounding region and the monuments after events like floods, landslides, earthquakes, etc.

Within HYPERION project (https://www.hyperion-project.eu/), RS-based methods have been developed for routine monitoring of the CH sites and were tested at four pilot sites. Routine monitoring includes displacement and land cover change detection maps of the broad area for all the pilot sites that are studied within the Hyperion project (city of Rhodes, Granada, Venice and Tønsberg), flood monitoring maps, three-dimensional models for all the CH assets, and deterioration and material loss estimation for specific parts of the facades of two monuments in the pilot site of the city of Rhodes, the Fort of Saint Nikolas and the Roman bridge in the Rhodes island.

To this end, a) advanced methodologies using PS and SBAS functionalities and Convolutional Neural Network architectures have been applied on satellite data aiming to produce reliable land deformation and land cover change detection maps, respectively, b) time series analysis and classification have been employed to identify changes in backscattering and to map flood occurrences, c) point clouds, light models, texture models and sections have been created in order to obtain a detailed 3D representation of the assets, and c) hyperspectral processing methods have been employed for fast and efficient assessment of the material deterioration level.

The effectiveness of the developed methods has been evaluated through their implementation on the pilot sites and disseminated to the scientific community through relevant publications. This paper presents a comprehensive overview of the results they have achieved and highlights the capabilities of remote sensing as a valuable tool in preserving Cultural Heritage.

Acknowledgement:
This work was implemented in the framework of the HYPERION project (H2020-LC-CLA-2018-2 H2020 program under GA 821054). Funding for participation in the conference has been provided by the HORIZON-CL2-2022-HERITAGE-01 program, with grant agreement number 101095253.

How to cite: Karathanassi, V., Karamvasis, K., Kristolari, V., Kolokoussis, P., Skamantzari, M., and Georgopoulos, A.: Remote sensing techniques for monitoring cultural heritage sites , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10181, https://doi.org/10.5194/egusphere-egu24-10181, 2024.

EGU24-11315 | Posters on site | CL3.2.2

The ARCH Resilience Assessment Dashboard: An Online Scorecard Approach to Assess the Resilience of Historic Areas 

Daniel Lückerath, Katharina Milde, Valerie Wischott, and Anna Klose

The increasing recognition of the importance of resilience in various sectors, such as disaster risk management, climate change adaptation, and urban planning resulted in a growing demand for tools and frameworks that can effectively measure and evaluate resilience. Scorecard approaches for the assessment of resilience have become more prominent in recent years. They provide a structured and quantitative way to assess resilience, allowing a monitoring of the resilience building progress of different systems or communities. In addition, the complexity and interconnectedness of modern systems requires a comprehensive assessment of resilience, considering multiple dimensions and factors. Scorecards offer a holistic view by incorporating various indicators and metrics, providing a more comprehensive understanding of resilience and its strengths and weaknesses. Scorecard approaches also facilitate decision-making and planning by providing clear and actionable information, enabling stakeholders to identify areas of improvement, prioritize interventions, and track progress over time.

Until recently, no scorecard approach for the assessment of the resilience of historic areas existed. The ARCH Resilience Assessment Dashboard (RAD) [1] closes this gap by providing an online scorecard that allows heritage managers, urban planners, disaster risk managers and other actors to jointly self-assess the resilience of their historic area.

The core of the RAD are 221 questions, categorized into ten overarching Essentials – an adapted version of the Ten Essential for Making Cities Resilient [2] – three disaster risk management phases, four topics (disaster risk management, climate change adaptation, heritage management, social justice), and six resilience dimensions (built environment, natural environment, economy, policy, society, and culture). Each question is answered on a 6-point Likert scale and supported by explanatory information, including potential stakeholders who have the information needed to answer the question.

The RAD provides users with a score, which indicates the performance in the different aspects relevant to building resilience. By analyzing the results, users can identify weak points in the resilience of the historic area. Based on these results, users can formulate a list of actions for increasing the resilience. To support this process, the RAD is linked to the ARCH Resilience Measures Inventory, an online database of resilience measures compatible with the Essentials of the RAD. By conducting several resilience assessments, the RAD can also be used to monitor resilience over time.

The RAD was co-developed and evaluated for four historic areas as part of the Horizon 2020 project ARCH (grant agreement No. 820999): the Old Town of Bratislava (Slovakia), the Old Town of Camerino (Italy), the World Heritage Site Speicherstadt and Kontorhausviertel in Hamburg (Germany), and the Huerta de Valencia (Spain).

This contribution will introduce the concept of the RAD and present the results of its trial application in the four historic areas.

References

[1] Fraunhofer IAIS, „Resilience Assessment Dashboard“, https://rad.savingculturalheritage.eu/

[2] UNDRR, “The TEN Essentials for Making Cities Resilient,” https://mcr2030.undrr.org/ten-essentials-making-cities-resilient

How to cite: Lückerath, D., Milde, K., Wischott, V., and Klose, A.: The ARCH Resilience Assessment Dashboard: An Online Scorecard Approach to Assess the Resilience of Historic Areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11315, https://doi.org/10.5194/egusphere-egu24-11315, 2024.

EGU24-12355 | Orals | CL3.2.2

Unveiling Risks and Leveraging the Knowledge Base Platform for Cultural Heritage sites in the Context of the TRIQUETRA Project 

Apostolos Sarris, Prodromos Zanis, Salvatore Martino, Anastasia Anastasiou, Charalabos Ioannidis, Styliani Verykokou, Victor Klinkenberg, and Miltiadis Polidorou

The TRIQUETRA EU research project embarks on a pioneering initiative aimed at enhancing climate change (CC) resilience in Cultural Heritage (CH) sites. Within the scope of TRIQUETRA, certain provisions have been made for studying the geological and historical climatic data towards risk identification that the pilot CH sites of the project are facing.  The geological risk quantification was based on monitoring and modelling approaches to classify the intensity of geohazards related to ground instabilities, earthquake-induced effects, coastal retreat, sea-waves, water runoff, wind storms, wildfires etc. Digital twins derived by in-filed monitoring and surveying are assumed at the basis of geohazard quantification. Similarly, the assessment of historical climatic information has been based on observations and a multi-model ensemble of high-resolution Regional Climatic Model (RCM) simulations, aiming to identify potential risks at the selected CH sites. The datasets will be used for further experimentation, and continuous collection of new data will take place throughout the course of the project, serving towards the proposal of mitigation action against the CC-induced risks. 

Similarly, emphasis was given to gather information from past initiatives and directives to create a node of reference for the future, crucial for understanding the vulnerabilities of CH sites in the face of CC. An extensive literature review on CC and other risks and mitigation measures for CH sites worldwide has been made, in addition to gathering of existing and historical site-specific data, identification of geological conditions at CH sites and classification of geological hazards associated with environmental and climatological data that pose direct or indirect risks to the pilot CH sites.

The development of the TRIQUETRA Knowledge Base platform (an electronic repository) based on the retrieved data, accompanied by advanced search tools and a “Self Service Portal” hosted on the project website (https://triquetra-project.eu/), ensures that contents related to CC, geological conditions, historical data, site-specific information, as well as risks and mitigation measures for CH sites are discoverable for future decision-making actions. The Knowledge Base platform includes a dedicated database and a WEBGIS platform, which store collected data in a common geospatial database providing a secure environment, which has an open access policy and will offer further analysis beyond the end of the project.

The above lay the groundwork for holistic research to CC resilience in CH sites. The findings presented herein not only advance the objectives of the TRIQUETRA project but also offer insights that can guide future research in the preservation of global CH in the face of an ever-evolving climate.

How to cite: Sarris, A., Zanis, P., Martino, S., Anastasiou, A., Ioannidis, C., Verykokou, S., Klinkenberg, V., and Polidorou, M.: Unveiling Risks and Leveraging the Knowledge Base Platform for Cultural Heritage sites in the Context of the TRIQUETRA Project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12355, https://doi.org/10.5194/egusphere-egu24-12355, 2024.

EGU24-13431 | Orals | CL3.2.2 | Highlight

Striving for the aspiring UNESCO Global Geopark Algarvensis: Connecting Climate Change Threats with Cultural and Natural Heritage 

Cristina Veiga-Pires, Sónia Oliveira, Lídia Terra, Dália Paulo, Telma Carroço, and Luís Pereira

Since 2019, a team of scientists, technicians, and politicians from Southern Portugal has been planning and implementing a new project aimed at involving the local population in fostering sustainable development alongside the preservation and conservation of natural and cultural assets. This initiative has evolved into the aspiring UNESCO Global Geopark (aUGGp) Algarvensis, reaching maturity earlier this year when its southern territorial boundary was established at sea, aligning with a bathymetric depth of 130 meters, representing the coastline of 20,000 years ago.

Situated in the Algarve region, this territory is facing several threats associated to climate change, the most significant ones being the sea level rise, reduced rainfall and freshwater availability, and the impact of the extreme events.

The natural and cultural heritage assets are abundant, both on land, along the coast, and underwater. Given the diverse stakeholders responsible for their management based on their type, characteristics, size, and location, there has been no global and integrated approach to assessing their vulnerabilities, both specific and common. The aUGGp Algarvensis aims to rectify this by identifying, quantifying, and mitigating risks drived from natural, climatic, anthropogenic, and biological hazards across various types of heritage.

Although relatively unknown, the continental territory of the aUGGp Algarvensis boasts a rich and diverse cultural heritage, featuring over 228 listed and referenced sites encompassing various types of heritage. Over the last decades, several coastal heritage sites have vanished into the sea due to intense coastal erosion, with underwater heritage primarily appreciated by divers..

This study explores how climate change poses risks to the region's geological, cultural, and ecological features. It emphasizes the intricate relationship between environmental changes and heritage preservation within the context of the UNESCO Global Geopark Algarvensis initiative. Our goal is to not only present the survey and compilation data gathered so far under the aUGGp Algarvensis coordination but also to underscore the importance and impact that such a local/regional non-governmental structure can bring to implement an efficient and proactive management strategy in the face of evolving risks to heritage.

 

Acknowledgement:  

This study had the support of national funds through Fundação para a Ciência e Tecnologia (FCT), under the project LA/P/0069/2020 granted to the Associate Laboratory ARNET and UID/00350/2020 CIMA, as well as from the Municipalities of Loulé, Silves and Albufeira.

How to cite: Veiga-Pires, C., Oliveira, S., Terra, L., Paulo, D., Carroço, T., and Pereira, L.: Striving for the aspiring UNESCO Global Geopark Algarvensis: Connecting Climate Change Threats with Cultural and Natural Heritage, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13431, https://doi.org/10.5194/egusphere-egu24-13431, 2024.

EGU24-15540 | ECS | Orals | CL3.2.2 | Highlight

Using Impact Chains for Co-creating Cause-Effect Models of Climatic and Anthropogenic Hazards in Cultural Landscapes 

Valerie Wischott, Anna Klose, Katharina Milde, and Daniel Lückerath

Cultural landscapes represent the intersection of natural and cultural heritage, encompassing the physical environment as well as the cultural practices, traditions, and values associated with a specific place. These landscapes often have important socioeconomic and community dimensions, serving as centers of livelihoods, tourism, and community identity. Moreover, these landscapes have intrinsic value and contribute to the overall diversity and richness of our global heritage. They hold stories, knowledge, and traditions that connect us to our past and shape our collective identity.

Climatic and anthropogenic hazards pose significant risks to these landscapes, including the degradation or loss of cultural heritage sites, changes in traditional land-use practices, and the erosion of cultural identities and knowledge systems.

To understand and evaluate these potential impacts, helping to safeguard and preserve the cultural significance and integrity of these landscapes, it is necessary to identify the specific risks and vulnerabilities that cultural landscapes face, allowing for the development of targeted adaptation strategies, enabling proactive measures to mitigate the impacts and ensure the resilience and continuity of these landscapes for future generations.

One widely adopted tool for risk assessments are Impact Chains [1], i.e., cause-effect models that describe the relationship between a hazard (e.g., a storm surge, a heatwave), exposed elements (e.g., residents, birdlife, agricultural practices) and their vulnerability (e.g., dike maintenance practices), and resulting impacts (e.g., coastal erosion). Impact Chains are composed of all these elements and additionally, intermediate impacts, i.e., cascading effects related to hazard and vulnerability elements. Impact Chains are typically developed through participative processes that involve local stakeholders. These stakeholders provide valuable input and feedback for the development of the Impact Chain. The validated Impact Chain provides a structured representation of the cause-effect relationships associated with the investigated risk.

Until now, Impact Chains have mainly been used as a basis for indicator-based Climate Risk and Vulnerability Assessments from the national to the local level, but not for modelling anthropogenic hazards like over-tourism or the abandonment of agricultural practices. In addition, only few Impact Chains for cultural sites have been developed.

In this contribution, we present Impact Chains that have been developed for five cultural landscapes as part of the Horizon Europe project RescueME (GA No. 101094978) and cover both climatic as well as anthropogenic hazards. These Impact Chains have been developed within case studies of the island of Neuwerk in the Waddensea of Hamburg (Germany), the Huerta and Albufera de Valencia (Spain), the Defensive System of the City of Zadar (Croatia), the region of Portovenere, Cinque Terre and the Islands (Italy), and the UNESCO Geopark in Crete (Greece). This contribution will describe the co-creation process for Impact Chain development, the involved stakeholder types, as well as the adaptations made to the standard Impact Chain representations [1].

 

References

[1] GIZ (2016). The Vulnerability Sourcebook. https://www.adaptationcommunity.net/download/va/vulnerability-guides-manuals-reports/vuln_source_2017_EN.pdf.

How to cite: Wischott, V., Klose, A., Milde, K., and Lückerath, D.: Using Impact Chains for Co-creating Cause-Effect Models of Climatic and Anthropogenic Hazards in Cultural Landscapes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15540, https://doi.org/10.5194/egusphere-egu24-15540, 2024.

EGU24-16558 | Posters on site | CL3.2.2

Effects of environmental stresses and climate change on the deterioration of underwater cultural heritage: the THETIDA approach 

Claudio Mazzoli, Ludovica Pia Cesareo, Chiara Coletti, Luigi Germinario, Lara Maritan, Loriano Ballarin, Isabella Moro, Stella Demesticha, Flávio Martins, Fabio Ruberti, and Panagiotis Michalis

This research, conducted within the THETIDA project (https://thetida.eu), focuses on identifying threats posed by climate change to underwater cultural heritage sites, with a specific emphasis on the diverse risks – both direct and indirect – that endanger metallic materials, such as anchors, cannons, and structural elements. Notable pilot sites within THETIDA include the US Army WWII PB4Y-1 bomber aircraft Liberator off the coast of Praia de Faro (Portugal), the sunken submarine chaser Equa near La Spezia, and an Ottoman shipwreck in Famagusta bay, Cyprus. These sites offer varied historical backgrounds, construction materials, and biological ecosystems, enabling a comprehensive comparison between sites protected in bays and those in dynamic open ocean environments with currents, sediment dynamics, and biological actions influencing deterioration processes [1].

Being aware of successive reports of the Intergovernmental Panel on Climate Change (IPCC), documenting climate phenomena such as rising sea levels, ocean surface temperature increases, ocean acidification, changes in ocean circulation, extreme wave events and deoxygenation [2], the objectives of the research are to investigate the deterioration effects associated with climate change, assess their evolution across different environments, and develop prediction models. The ultimate goal is to provide practical recommendations for site preservation. The methodology involves studying the sites, historical backgrounds, material compositions, and deterioration characteristics, including physical, chemical, and biological factors of underwater weathering, classification of decay patterns, biocolonisation and biodeterioration characteristics through a multidisciplinary approach. In underwater heritage sites, materials undergo physical, chemical, and biological changes influenced by water, sediment, and living organisms [3, 4]. The study will consider variables such as temperature, salinity, pH, oxygen levels, and the intensity and direction of currents, alongside the depth and location of the site. Mock-up samples will undergo accelerated weathering and autoclave corrosion tests to observe the degradation related to specific environmental parameters. Mock-up samples will also be placed in the real sites to compare the results with the controlled environment aged samples and explore the early stages of deterioration and biocolonisation.

This research contributes to understanding the impact of climate change on underwater cultural heritage sites, providing valuable insights for preservation efforts in the face of evolving environmental challenges.

Acknowledgement:

This research has been funded by European Union’s Horizon Europe research and innovation programme under the THETIDA project (Grant Agreement No. 101095253) (Technologies and methods for improved resilience and sustainable preservation of underwater and coastal cultural heritage to cope with climate change, natural hazards, and environmental pollution).

 

References

[1] THETIDA project websites https://thetida.eu/#/home

[2] Gregory et al. (2022). Of time and tide: the complex impacts of climate change on coastal and underwater cultural heritage. Antiquity 96.390: 1396-1411 (https://doi.org/10.15184/aqy.2022.115).

[3] Gregory (2009). In situ preservation of marine archaeological sites: Out of sight but not out of mind. In: Situ Conservation of Cultural Heritage: Public, Professionals and Preservation; Richards, V., Mckinnon, J. (Eds) 1-16.

[4] Bethencourt et al. (2018). Study of the influence of physical, chemical and biological conditions that influence the deterioration and protection of Underwater Cultural Heritage. Sci. Total Environ. 613: 98-114 (http://dx.doi.org/10.1016/j.scitotenv.2017.09.007).

 

How to cite: Mazzoli, C., Cesareo, L. P., Coletti, C., Germinario, L., Maritan, L., Ballarin, L., Moro, I., Demesticha, S., Martins, F., Ruberti, F., and Michalis, P.: Effects of environmental stresses and climate change on the deterioration of underwater cultural heritage: the THETIDA approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16558, https://doi.org/10.5194/egusphere-egu24-16558, 2024.

EGU24-17228 | Orals | CL3.2.2 | Highlight

The Green Cluster of Cultural Heritage: Climate Effects TeamEU funded projects  

Athanasios Gerakis, Jens Hemmelskamp, Irena Kowalczyk-Kedziora, and Melpomeni Vyzika

Europe’s built heritage, cultural landscapes and sites are under immediate threat from the effects of climate change, including rising sea levels, prolonged droughts, floods, and strong storms. Acid rain and other environmental pollutants cause wear and defacement of monuments and historic buildings, while soil erosion accelerates the deterioration of underwater and coastal heritage sites. The effects of climate change also affect, directly or indirectly, indoor cultural heritage.

Horizon Europe, the 9th European Framework Programme for Research and Innovation (2021-2027), is a key instrument of the Union to tackle global challenges such as the impact of climate change and natural disasters on cultural assets, as well as to promote cooperation and the influence of research and innovation in the design, support, and implementation of EU policies. To further enhance efficiency and research collaboration, the European Commission (EC) clusters the consortia with similar research objectives during their lifecycle. The idea is to facilitate researchers to share insights and best practices, identify synergies for dissemination and communication actions, and propose integrated feedback recommendations to policy makers in the EC and beyond.

Since 2021, three calls for proposals have invited research teams to respond to the demands for more sustainable methods and technologies to restore monuments and works of art[i], the impact of climate change and natural hazards on cultural heritage[ii], and advanced technologies for remote monitoring in the field[iii]. The eleven projects selected for the EU funding have been encouraged to form the Green Cluster on Cultural Heritage.

Within the Green Cluster, the ‘’Climate Effects’’ Team, currently composed of four active EU projects (THETIDA, RescueME, TRIQUERTA, STECCI), has an overarching aim to address the urgent need to protect monuments, historic buildings, and sites from the diverse impacts of climatic risks, natural and anthropogenic hazards. This is expected to contribute to the conservation and protection of Europe’s heritage by exploiting cutting-edge remote monitoring technologies and modelling tools for multi-hazard risk understanding and better preparedness.

Research within the Green Cluster is complemented by other consortia that develop sustainable methodologies, materials and techniques for the preservation and restoration of art objects and explore the use of advanced and sophisticated technologies for more accurate, targeted, and reliable remote monitoring purposes.

The impact of the scientific research is furthermore amplified by the active involvement of Artificial Intelligence tools, a wide range of community groups, stakeholders, and participants covering the full spectrum of ongoing research activities. This includes participatory and inclusive approaches, such as citizen science and participatory Living Lab methodologies.

The overall goal of the EC is to support transdisciplinary joint efforts of researchers to develop sustainable preservation and adaptation plans, and to bring community involvement and inclusiveness to the forefront of large collaborative research projects funded by the EU. The long-term outcome will be the creation of a sustainable cultural heritage research ecosystem.


[i] https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/horizon-cl2-2021-heritage-01-01

[ii] https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/horizon-cl2-2022-heritage-01-08

[iii] https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/horizon-cl2-2023-heritage-01-01

 

 

How to cite: Gerakis, A., Hemmelskamp, J., Kowalczyk-Kedziora, I., and Vyzika, M.: The Green Cluster of Cultural Heritage: Climate Effects TeamEU funded projects , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17228, https://doi.org/10.5194/egusphere-egu24-17228, 2024.

EGU24-17678 | ECS | Orals | CL3.2.2

A baseline approach for downscaling the Euro-CORDEX data for wind risk assessment of the Metsovo village in Greece 

Akrivi Chatzidaki, Dimitrios Vamvatsikos, Fotios Barmpas, Antti Hellsten, Mikko Auvinen, and George Tsegas

A methodology is presented for downscaling the wind projections of Euro-CORDEX in order to derive temporally and spatially correlated region-wide wind fields that can be used for assessing the wind risk for cultural heritage sites. The coarse spatial and temporal resolutions of the Euro-CORDEX projections prohibit their use as a direct input for such purposes, especially for cultural heritage assets that are spatially distributed within the Euro-CORDEX grid and dynamically respond differently to wind. To improve the temporal resolution of the Euro-CORDEX data, we leverage machine learning tools and weather station measurements, aiming to generate composite “Frankenstein” days at the locations of the weather stations that comprise 144 jigsaw pieces of actually measured 10min wind time-series that are matched together to form a continuous daily record. The “Frankenstein” days are expanded spatially to all locations where critical assets can be found by employing spatially distributed wind fields that are computed via high-fidelity computational fluid dynamics simulations and provide contemporaneous wind values at all locations of interest. This process allows generating “Frankenstein” days and wind fields with a temporal resolution of 10min and spatial resolution that allows assessing the wind risk for spatially distributed assets. As a case study, the Euro-CORDEX wind projections are downscaled for the cultural heritage village of Metsovo that is found at the Western part of Greece. Most of the buildings within this village are made of stone masonry and tiled roofs and are vulnerable to extreme wind actions as wind can cause damages e.g., on the tiled roofs thus making the buildings vulnerable to rainfall, or even lead to their partial or complete failure. Thus, the Frankenstein days and wind fields are employed for assessing the wind risk for the cultural heritage buildings of Metsovo both on an event-basis and in the long-term.

How to cite: Chatzidaki, A., Vamvatsikos, D., Barmpas, F., Hellsten, A., Auvinen, M., and Tsegas, G.: A baseline approach for downscaling the Euro-CORDEX data for wind risk assessment of the Metsovo village in Greece, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17678, https://doi.org/10.5194/egusphere-egu24-17678, 2024.

EGU24-18072 | ECS | Orals | CL3.2.2 | Highlight

Unveiling End Users Needs and Requirements for Coastal and Underwater Heritage Sites under the impacts of Climate Change  

Sónia Oliveira, Cristina Veiga-Pires, Deniz Ikiz Kaya, Panagiotis Michalis, and Claudio Mazzoli

Coastal and underwater cultural heritage play a crucial role in local and regional cultural resources. However, this tangible cultural heritage is under threat due to extreme weather events, changing conditions caused by climate change, natural hazards, and environmental pollution. This study aims to understand how end users (entities or people related to or who interact with heritage sites ) perceive these risks and what they need to better cope, adapt, or be resilient to the anticipated changes. Additionally, it explores how science can address the needs and requirements of local and regional end users.

This research is part of the larger THETIDA project, focusing on technologies and methods for improved resilience and sustainable preservation of underwater and coastal cultural heritage, funded by the European Union’s Horizon 2020 research and innovation programme. The THETIDA project concentrates on seven pilot sites, comprising coastal locations such as Svalbard in Norway, Ijsselmeer in the Netherlands, Mykonos in Greece, and underwater sites including Algarve in Portugal, Gallinara and Spezia in Italy, and Paralimni in Cyprus.

The THETIDA team conducted surveys to analyze threats, needs, and preservation requirements for each pilot site, incorporating data from consortium partners and workshops held with local stakeholders in several pilot sites. The results identified material deterioration and human-induced development interventions as primary threats. Essential needs include assessing risk and exposure to various hazards, implementing conservation measures for buildings and sites, and promoting awareness, education, and training.

Survey responses unanimously emphasize the critical requirement for site assessment and risk evaluation concerning both human-induced and climate changes. These findings offer valuable insights for developing tools and services within the project to support local and regional end users. Furthermore, they underscore the importance of fostering a scientific culture among communities, a role that science centers and museums can fulfill, as verified during the 2023 Portuguese Science and Technology Week.

Finally, the resulting end-user ecology is integrated into the Living Lab methodology, another facet of THETIDA Project research, aiming to co-create, test, and validate a new crowdsourcing tool in real-life contexts.

 

Acknowledgement:  

This research has been funded by European Union’s Horizon Europe research and innovation funding under Grant Agreement No: 101095253, THETIDA project (Technologies and methods for improved resilience and sustainable preservation of underwater and coastal cultural heritage to cope with climate change, natural hazards and environmental pollution). Authors would also like to acknowledge the financial support of the Portuguese Foundation of Science and Technology (FCT) to CIMA through UID/0350/2020

How to cite: Oliveira, S., Veiga-Pires, C., Ikiz Kaya, D., Michalis, P., and Mazzoli, C.: Unveiling End Users Needs and Requirements for Coastal and Underwater Heritage Sites under the impacts of Climate Change , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18072, https://doi.org/10.5194/egusphere-egu24-18072, 2024.

EGU24-19282 | ECS | Orals | CL3.2.2

Risk of falling stone material on the Ramps of Piazzale Michelangelo in Florence 

Anna Palamidessi, Emanuele Intrieri, Teresa Salvatici, Irene Centauro, and Carlo Alberto Garzonio

The Ramps of Piazzale Michelangelo (Michelangelo Square) in Florence are a pedestrian connection between the Arno riverside and the higher Piazzale Michelangelo, leaning against the side of the hill called "Monte alle Croci," a hill delimiting Florence to the south. Over the years, this area has experienced a long series of instabilities that have affected some of the most significant testimonies of the city's architecture. The Ramps of Piazzale Michelangelo are popular both with tourists visiting the city and with the residents of Florence, who use them as a picturesque place to stroll.

The Ramps and contiguous Viale dei Colli (Hills Avenue) are one of the most interesting projects of the architect Giuseppe Poggi during the period when Florence was the capital of Italy (1865-1871). The staircases of the Ramps feature stone balustrades, topped with Pietraforte sandstone caps. Geologically, Pietraforte is a turbiditic sandstone characterized by numerous sedimentary layers typical of the Bouma sequence and by the presence of secondary calcite veins. These features are the main weak points where detachment phenomena can occur.

The action of rainwater leads to the dissolution of calcium carbonate, present both in the calcite veins and in the carbonatic cement within the rock. In the first case, this mechanism can result in the decohesion of the rock with the complete opening of veins and possible detachment and fall of blocks (even blocks with volume up to about 50 dm3). In the second case, detachments occur as a superficial exfoliation rather than detachments of entire portions of material.

Recent restoration works, completed in May 2019, focused on the conservation and recovery of architectural elements. However, in July 2020, a wedge collapsed, hitting a vehicle below. Subsequently, as a temporary countermeasure, the parapets were covered with nets to prevent new possible accidents.

For a long-term countermeasure, this architectural problem has been investigated assimilating it to a rockfall scenario. First of all it was necessary to manually detect and evaluate every block's discontinuity to assess susceptibility. An equation for calculating the risk of each identified block was then implemented. Differentiated interventions were proposed for each block based on its possible kinematics.

Using an approach based on statistical analysis of the rockfall’s susceptibility, this study aims to: 1) Quantify the spatial distribution of rockfalls; 2) Build an equation to identify the more dangerous blocks; 3) Propose safety interventions with minimal impact, diversifying them based on the kinematics of each individual block.

 

Keywords: Cultural Heritage, Stone element risk, rockfall, road safety, susceptibility.

How to cite: Palamidessi, A., Intrieri, E., Salvatici, T., Centauro, I., and Garzonio, C. A.: Risk of falling stone material on the Ramps of Piazzale Michelangelo in Florence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19282, https://doi.org/10.5194/egusphere-egu24-19282, 2024.

EGU24-20296 | Orals | CL3.2.2 | Highlight

The EU R&I Task Force for Climate Neutral and Resilient Historic Areas 

Katherine Peinhardt, Dr. Cristina Garzillo, Dr. Daniel Lückerath, Aitziber Egusquiza, Panagiotis Michalis, and Denis Istrati

Climate change poses a significant and alarming threat to cultural and natural heritage in urban and rural areas, jeopardizing the preservation of tangible and intangible aspects of our shared human history, including cultural traditions, knowledge, and practices. Rising sea levels, extreme weather events, and increased temperatures contribute to the degradation of cultural sites. Coastal regions face the imminent danger of inundation and erosion, endangering landscapes that have withstood centuries. At the same time, Indigenous communities are vulnerable, as their cultural heritage is often intricately connected to specific ecosystems and landscapes. On top of these climatic threats, cultural and natural heritage is also threatened by impacts from anthropogenic stresses, like unsustainable tourism and consumption patterns or environmental pollution.

Against this backdrop the H2020 projects ARCH, HYPERION, and SHELTER founded the EU R&I Task Force for Climate Neutral and Resilient Historic Urban Districts in 2021. The task force aims to bring together diverse groups of practitioners, researchers, and policy makers at the cross section of heritage management, climate change adaptation / mitigation, disaster risk management, and sustainable development. This coincides with the objective to identify and discuss current developments in research and practice; bridge knowledge gaps between these fields; boost collaboration among the cross-sectoral actors involved; and ultimately make our historic areas more climate neutral and resilient. In doing so, the task force aims to provide practical support to European authorities and decision makers for developing harmonised, evidence-based policies, strategies, and procedures. The Task Force has thus far convened three times: June and December 2021, and June 2022, and resulted in a joint white paper, Paving the Way for Climate Neutral and Resilient Historic Districts.

With the successful conclusion of the three funding projects, the work of organizing the task force has been taken over by their follow-up projects RescueME, THETIDA, and TRIQUETRA in 2023, shifting the focus from urban districts to historic areas, encapsulating cultural and natural heritage in urban and rural areas and other cultural landscapes, including coastal and underwater heritage.

In this presentation, we present the last results of the task force, the way forward regarding its development and activities within the updated partnership, and potential collaboration opportunities with other initiatives, projects, and actors.

How to cite: Peinhardt, K., Garzillo, Dr. C., Lückerath, Dr. D., Egusquiza, A., Michalis, P., and Istrati, D.: The EU R&I Task Force for Climate Neutral and Resilient Historic Areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20296, https://doi.org/10.5194/egusphere-egu24-20296, 2024.

Cultural Heritage (CH) monuments are often subject to various environmental threats, with climate change (CC) exacerbating their vulnerability. These historical sites, valuable for their cultural and archaeological significance, face increasing risks of deterioration due to land deformation, flooding, acid rain, erosion, and man-made hazards like illegal excavations. Such threats not only endanger the structural integrity of these monuments but also risk depriving humanity of crucial archaeological information and artifacts, which are key to understanding our collective past.

This article explores a novel approach that leverages the capabilities of satellite-based remote sensing techniques for monitoring CH sites under shallow water conditions. A wide array of data will be used for a more frequent and comprehensive analysis of the site's condition over time, enabling the detection of subtle changes that might go unnoticed with conventional methods.

The case study focuses on the submerged port of Amathous archaeological site along the coast of Cyprus. The site's unique geographical and historical characteristics make it an exemplary model for applying advanced remote sensing technologies.

By integrating satellite data with on-site ground truth measurements (topographical and aerial-born imagery), the study aims to develop a robust framework for the preservation and protection of underwater CH sites. This approach can not only enhances the understanding of the impacts of CC and human activities on these sites but also paves the way for developing proactive measures to safeguard heritage assets. The findings from this study are expected to contribute significantly to the field of heritage conservation, offering scalable and efficient solutions to monitor and protect CH sites worldwide.

How to cite: Abate, D., Kalogeriou, E., Themistocleous, K., and Hadjimitsis, D.: Change detection monitoring of archaeological sites submerged in shallow waters using remote sensing data: the case study of the port of the Ancient Amathous in Cyprus, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20439, https://doi.org/10.5194/egusphere-egu24-20439, 2024.

EGU24-20699 | Posters on site | CL3.2.2

Digitalizing historical buildings of Western Greece – from point clouds, to building information modeling and 3D printing 

Theodora Filippa, Panagiotis Tsikas, Aggeliki Kyriou, Panagiotis Triantafyllidis, Epameinondas Lyros, Konstantinos Nikolakopoulos, Ioannis Koukouvelas, and Christoforos Pappas

Cultural heritage worldwide is of great interest for general public and scientific communities across disciplines. In the Mediterranean region, and in Greece in particular, historic buildings and monuments are widespread. Ongoing environmental change, and the increased frequency and severity of climatic extremes and natural hazards in the Mediterranean regions, challenge the protection of cultural heritage, making essential the detailed documentation and digitalization of these monuments in tailored geodatabases. In the present study, example historical buildings of Western Greece were selected, covering a wide environmental gradient from coastal to mountainous landscapes, namely, a 19th century emblematic stone-built lighthouse at Cape Drepano, close to Patras, in Northern Peloponnese, as well as historical buildings in the Aetolia-Acarnania region, including 19th and 20th century monuments in the lagoon region of Messolonghi (the Old Hatzikosta Hospital and the Palamas School), as well as a 18th century post-Byzantine monastery located in a mountainous area near Agrinio. Geodetic field surveys were conducted with Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle (UAV) photogrammetry. The collected point clouds were processed to generate Building Information Models (BIMs) of the examined structures which were then 3D printed at scale. The derived digital database of these monuments offers a detailed documentation and baseline of the present status of these monuments. This baseline, when combined with future field surveys, set the basis for accurate monitoring of the response of these structures to natural and anthropogenic stressors (e.g., costal erosion, land displacement, etc.). Moreover, this documentation could assist the efficient planning of maintenance and restoration interventions, while the derived digital and printed 3D models offer tangible tools for raising public’s awareness and valorizing further these historical buildings. Technological advancements in geodetic instruments as well as the continuous development of numerical tools for BIM applications, 3D modeling and printing, facilitate the seamless digitalization of cultural heritage and its archiving into interactive geodatabases, complementing existing efforts towards coordinated documentation and monitoring of historical buildings at national and international levels.

How to cite: Filippa, T., Tsikas, P., Kyriou, A., Triantafyllidis, P., Lyros, E., Nikolakopoulos, K., Koukouvelas, I., and Pappas, C.: Digitalizing historical buildings of Western Greece – from point clouds, to building information modeling and 3D printing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20699, https://doi.org/10.5194/egusphere-egu24-20699, 2024.

EGU24-20848 | Posters on site | CL3.2.2

TRIQUERTA: Towards next generation risk assessment and mitigation of climate change and natural hazards threatening cultural heritage 

Charalabos Ioannidis, Constantine Spyrakos, Styliani Verykokou, Denis Istrati, Sofia Soile, Vasiliki (Betty) Charalampopoulou, and Panagiotis Georgiadis

Cultural heritage (CH) sites face increasing risks from climate change (CC) and various hazards, posing threats such as rising sea levels, extreme weather events, and environmental degradation, endangering their preservation and long-term existence. A lot of research has been done on protecting CH sites, but we still lack systemic approaches towards identifying and mitigating risks to CH sites. The TRIQUETRA EU research project proposes a technological toolbox and a methodological framework for tackling climate change risks and natural hazards threatening CH, in the most efficient way possible. The main strategic objectives of TRIQUETRA include: the creation of a repository of knowledge on effects of CC and natural hazards on CH, including lessons learnt from existing mitigation measures; the implementation of a systemic approach towards identification of upcoming risks and hazards to CH; and the usage of novel technologies allowing efficient and accurate quantification of threats to CH.

The TRIQUETRA project’s methodology is structured around three fundamental stages: (i) identifying risks, (ii) quantifying risks, and (iii) mitigating risks, forming what is known as the “trifecta” approach. This approach constructs a robust framework for evaluating and addressing the following categories of risks: (i) climate-related risks; (ii) extreme water, snow and ice hazard risks; (iii) geological and geophysical risks; and (iv) chemical and biological hazard risks. Furthermore, it assesses the damage and failure modes of CH structures as well as the compounded effects of various environmental stressors on CH sites. TRIQUETRA will be validated in eight different CH sites across Europe. The main project results can be summarized as follows:

  • a novel risk quantification framework for CH sites;
  • an expanded knowledge base platform;
  • a decision-support platform (TRIQUETRA DSS) including risk severity quantification tools and mitigation measure selection and optimization tools;
  • novel protective materials;
  • a novel flash LiDAR;
  • water quality analysers; and
  • a CH site digitization framework.

How to cite: Ioannidis, C., Spyrakos, C., Verykokou, S., Istrati, D., Soile, S., Charalampopoulou, V. (., and Georgiadis, P.: TRIQUERTA: Towards next generation risk assessment and mitigation of climate change and natural hazards threatening cultural heritage, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20848, https://doi.org/10.5194/egusphere-egu24-20848, 2024.

EGU24-21295 | ECS | Posters virtual | CL3.2.2

A framework for Resilient Cultural heritage 

Manal Ginzarly and Jacques Teller

It is acknowledged by International declarations and policy guidance documents that cultural heritage (CH) can contribute directly to many of the Sustainable Development Goals (SDGs), including resilience and adaptation to climate change (SDG 13). CH can support climate change action as it conveys local knowledge that builds resilience for change through mitigation and adaptation. Moreover, the vulnerability of the built environment to climate change possesses inherent resilient properties that allow it to resist damage. The integration of policies and practices of CH conservation into the wider framework of sustainable urban development entails the application of a landscape approach that (i) responds to local cultural contexts and value systems, (ii) integrates distinct theoretical perspectives to address the complex layering of the spatial, mental, and functional process-related dimensions of the landscape, and (iii) addresses policies and governance concerns at international and local levels (Ginzarly et al., 2019). Yet, the application of a landscape approach to CH conservation in the context of climate change is faced with different challenges.
First, while at the turn of the twenty-first century the concept of CH has extended from monuments to cultural landscapes and cities as living heritage, assessment processes have been slow to evolve and address the interdisciplinary nature of heritage (Déom & Valois, 2020). Second, there is a challenge around assessing the vulnerability of CH to climate change and integrating its vulnerability status into the broader context of sustainable urban development. This challenge is imposed by the lack of a framework that addresses landscapes rather than heritage sites in isolation (Cook et al., 2021).
To address the above-mentioned challenges, this presentation presents a landscape people-centered conceptual framework for resilient CH that is applicable at the city scale (i) to map how different stakeholder groups value heritage in the context of climate change, (ii) using social networks as a tool to engage communities and get access to information about heritage values, and (iii) assess the vulnerability of urban heritage and its associated values to climate change.The conceptual framework is structured around four prominent themes: (1) the city is a living heritage that encompasses the physical, mental, and digital heritage landscapes; (2) digitally mediated heritage practices provide new prospects for digitally-enabled forms of co-creation of heritage values; (3) longitudinal records on social media serve as a data source for the assessment of heritage values and their vulnerability to change; and (4) online communities contribute to communities’ disaster resilience.


References
Cook, I., Johnston, R., & Selby, K. (2021). Climate Change and Cultural Heritage: A Landscape Vulnerability Framework. The Journal of Island and Coastal Archaeology, 16(2–4), 553–571.Déom, C., & Valois, N. (2020). Whose heritage? Determining values of modern public spaces in Canada. Journal of Cultural Heritage Management and Sustainable Development, 10(2), 189–206.
Ginzarly, M., Houbart, C., & Teller, J. (2019). The Historic Urban Landscape approach to urban management: A systematic review. International Journal of Heritage Studies, 25(10), 999–1019.

How to cite: Ginzarly, M. and Teller, J.: A framework for Resilient Cultural heritage, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21295, https://doi.org/10.5194/egusphere-egu24-21295, 2024.

The estimation of reference evapotranspiration (ETo) holds significant importance for the hydrological cycle, necessitating an extensive understanding of the various climate variables and their influence on ETo variability. This study aims to examine spatio-temporal variations in Penman Monteith based ETo estimations and the factors contributing to their changes over the Indian subcontinent in the historic and future climate change. Using climate variables from the ERA5 reanalysis and CMIP6 simulations this study focuses on the changes in ETo across different aridity zones in the study area. Further, the partial least squares (PLS) regression was employed to determine the relative contribution of different climate variables on ETo trends. Results show that the majority (70%) of the areas in the subcontinent exhibited decreasing ETo trends in the historical past. Zonal analysis of ETo trends revealed all zones except the humid zone exhibited a significant decreasing trend for ETo. Contribution analysis shows that, across the study area, temperature and radiation are the most significant factors influencing ETo, followed by wind speed and relative humidity. Further, temperature and ETo were found to be having opposing tendencies, highlighting an “evapotranspiration paradox” that encompasses the majority of the study area. CMIP6 simulations show that ETo is projected to increase significantly across the Indian subcontinent, especially in the semi-arid and arid regions with temperature and radiation being the dominant factor contributing to increases in ETo.

How to cite: Varghese, F. C. and Mitra, S.: Spatio-temporal variation of reference evapotranspiration and its contributing factors over the Indian subcontinent under historic and future climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-675, https://doi.org/10.5194/egusphere-egu24-675, 2024.

EGU24-878 | ECS | Orals | CL4.1

Land-Climate Nexus: Unravelling Extremes with Attention Networks 

suchismita subhadarsini, D. Nagesh Kumar, and S. Govindaraju Rao

The intricate interplay between land use, climate dynamics, and other contributing factors significantly influences the occurrence of extreme events such as droughts, floods, and heatwaves. Modeling this complex system in a high-dimensional space poses a formidable challenge, given incomplete understanding and limited availability of data. This study explores the application of deep learning approaches, specifically leveraging transformer architectures, to capture long-range dependencies in spatiotemporal data. These mechanisms are then employed to encapsulate the complex interactions between land use, climate, and other factors influencing extreme events. The proposed approach incorporates attention mechanisms, enhancing interpretability by highlighting crucial spatial and temporal features essential for forecasting. To evaluate the effectiveness of this methodology, a case study was conducted on the Godavari River Basin in India. Utilizing vegetation indices as a representation of crop type and land use, alongside climate data spanning from 2000 to 2020, the results provide valuable insights into the driving factors behind land use change and climate extremes in the region. The study not only demonstrates predictive capabilities of the proposed approach but also offers insights into the intricate relationships within the land-atmosphere feedback system. The extracted information is useful for making informed decisions related to land management, climate adaptation, and disaster risk reduction.

How to cite: subhadarsini, S., Kumar, D. N., and Rao, S. G.: Land-Climate Nexus: Unravelling Extremes with Attention Networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-878, https://doi.org/10.5194/egusphere-egu24-878, 2024.

EGU24-1608 | Orals | CL4.1

Forest Canopy Transpiration: A Key Moderator of Hydroclimate Variability and Extreme Rainfall in the Maritime Continent 

Min-Hui Lo, Ting-Hui Lee, Jason Hsu, Chun-Lien Chiang, and Yan-Ning Kuo

This study investigates the interannual variability of evapotranspiration (ET) in the Maritime Continent (MC), focusing on the dynamics behind its minimal fluctuations despite significant changes in precipitation due to the El Niño-Southern Oscillation. We analyze ET components - canopy evaporation (CE), canopy transpiration (CT), and soil evaporation (SE) - and uncover a self-compensating mechanism between CE and CT. During El Niño, increased CT offset decreased CE and SE, maintaining ET's stability. Conversely, La Niña shows an inverse pattern. Additionally, the research examines the impacts of deforestation on extreme precipitation in MC. Deforestation disrupts the ET balance by removing CT's stabilizing effect, amplifying ET variability, and altering precipitation patterns. Our findings propose a new precipitation paradigm in MC under deforestation: "rich-get-richer, poor-get-poorer, and the middle-class-also-get-poorer," marked by increased variability in extreme precipitation events. The study highlights the critical role of MC's forest canopy transpiration in moderating ET variability and its significant influence on the hydroclimatological cycle, especially under deforestation. This intricate interplay between deforestation, ET, and precipitation emphasizes the need to consider both local land use and broader climatic changes in understanding and managing the region's water cycle and extreme climate events.

How to cite: Lo, M.-H., Lee, T.-H., Hsu, J., Chiang, C.-L., and Kuo, Y.-N.: Forest Canopy Transpiration: A Key Moderator of Hydroclimate Variability and Extreme Rainfall in the Maritime Continent, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1608, https://doi.org/10.5194/egusphere-egu24-1608, 2024.

EGU24-1973 | ECS | Orals | CL4.1

Global South most affected by socio-ecosystem productivity decline due to compound heat and flash droughts 

Lei Gu, Erich Fischer, Jiabo Yin, Louise Slater, Sebastian Sippel, and Reto Knutti

Flash droughts (FDs) and heatwaves are posing disproportionate biophysical and social losses worldwide, particularly threatening the disadvantaged communities in the Global South. However, the underlying physical mechanisms behind compound heat-flash drought (CHFD) events and their impacts on global socio-ecosystem productivity remain elusive. Here using satellites, reanalysis, reconstructions, and field measurements, we find more dry regions (53%~62%) with above-average ratios of FDs accompanied by extreme heat than humid regions (50%~57%), due to asymmetric effects by synoptic weather systems. The CHFDs associated with strong soil moisture-temperature coupling aggravate the constraint on plant photosynthesis in dry regions, whereas this coupling-related vegetation stress is not significant in humid regions. We further develop a global risk framework that integrates CHFD hazards, population/agriculture exposures, and vulnerability, and find the Global South is the primary region affected by CHFDs, contributing to greater-than-usual carbon uptake reduction, 90%~94% and 76%~86% of risks to world population and agriculture over the past four decades. We reveal the Global South is severely affected by the impacts of CHFDs on socio-ecosystem productivity decline and underscore the importance of efforts to monitor, predict, and mitigate the rise in CHFDs. 

How to cite: Gu, L., Fischer, E., Yin, J., Slater, L., Sippel, S., and Knutti, R.: Global South most affected by socio-ecosystem productivity decline due to compound heat and flash droughts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1973, https://doi.org/10.5194/egusphere-egu24-1973, 2024.

The land-atmosphere coupling is responsible for flash droughts as the reduced soil moisture increases sensible heat and consequently the lifting condensation level, which ultimately reduces convective precipitation. Meanwhile, the decrease in atmospheric humidity increases the evaporation demand, facilitates the drying of the land surface, and triggers flash droughts with rapid onset and devastating impact. However, whether the role of the land-atmosphere coupling is enhanced or weakened under climate change remains elusive, as previous studies are usually based on unconditional analysis without discriminating dry or wet extremes. Here, we start the investigation from a mega-flash drought occurred over the Yangtze River basin in southern China during the summer of 2022. Both the offline high-resolution land surface model simulations and the CMIP6 climate model data are used for the analysis. It is found that high temperature aggravates the 2022 flash drought onset speed and intensity, highlighting the importance of climate warming. Even under natural climate forcings, the land-atmosphere coupling increases the risks of flash drought intensity and onset speed. The synergy of coupling and anthropogenic climate change would further increase the risks. The synergistic effect on the long-term trends of flash droughts is also being explored, shedding light on the mechanism of flash droughts in a changing climate.

How to cite: Yuan, X.: Synergistic effect of land-atmosphere coupling and climate change on flash droughts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2848, https://doi.org/10.5194/egusphere-egu24-2848, 2024.

EGU24-3079 | ECS | Orals | CL4.1

Causal analysis of Heatwaves in India: Impact of Remote Soil Moisture 

Abhirup Banerjee, Armin Koehl, and Detlef Stammer

Heatwaves are a significant threat to human health, agriculture, and infrastructure; particularly in India, where they are prevalent during the pre-monsoon months. May is a critical period for heatwave occurrences, severely impacting the Indian subcontinent. This work delves into the underlying mechanisms driving heatwaves in India, specifically focusing on those that occur in May. Utilizing an intermediate complexity earth system model, PLASIM1, and its adjoint2 for sensitivity analysis3, we systematically investigate the causal role of remote soil moisture in heatwave formation. We find that variations in remote soil moisture significantly influence the strength and duration of pre-monsoon heat waves in India. Our analysis shows that at a lead time of 10-15 days, higher soil moisture particularly over the Middle East, can prolong heatwave conditions over India. On the other hand, high soil moisture over India suppresses the development of heatwaves with no lag. The delayed mechanism of remote soil moisture works through the altered atmospheric circulation patterns induced by heat flux forcing modulated by soil moisture anomalies, leading to enhanced subsidence and reduced moisture transport to India. Our study provides valuable insights into the mechanisms driving heatwaves in India, particularly those in May. These insights are crucial for developing effective early warning systems, enhancing disaster preparedness, and implementing mitigation strategies to reduce the adverse impacts of these extreme events.

1The Planet Simulator (PlaSim): a climate model of intermediate complexity for Earth, Mars and other planets.

2Marotzke, Jochem, et al. "Construction of the adjoint MIT ocean general circulation model and application to Atlantic heat transport sensitivity." Journal of Geophysical Research: Oceans 104.C12 (1999): 29529-29547.

3Köhl, Armin, and Andrey Vlasenko. "Seasonal prediction of northern European winter air temperatures from SST anomalies based on sensitivity estimates." Geophysical Research Letters 46.11 (2019): 6109-6117.

How to cite: Banerjee, A., Koehl, A., and Stammer, D.: Causal analysis of Heatwaves in India: Impact of Remote Soil Moisture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3079, https://doi.org/10.5194/egusphere-egu24-3079, 2024.

Assessing the impacts of anthropogenic land use and land cover change (LULCC) on climate extremes is of public concern, calling for the use of state-of-the-art experiments and datasets to update our knowledge. Here, we used the CMIP6-LUMIP experiment results to depict the realistic LULCC effects on extreme temperature and extreme precipitation over both historical and future periods. We pointed out some interesting findings over the historical period: Approximately 1oC decrease in the maximum temperature, and up to nearly 2oC decrease in the minimum temperature in the mid-high latitude of the North Hemisphere. About 10 annual heatwave days can be avoided by LULCC effects in 10% of specific LULCC-intense regions. Three LULCC-intense regions in the North Hemisphere have experienced cooling effects in intensity, frequency, and duration aspects. The precipitation displayed a clear contrast change between the North Hemisphere (wetter) and the South Hemisphere (drier), especially on light rainy days (R1mm). Results of the future period indicate that the tropical deforestation regions are projected to induce a remarkably hotter and drier trend. However, the climate responses averaged globally to deforestation have no obvious changes due to the colder and wetter compensation responses in other regions. The maximum temperature increase in deforestation regions is prominent in intensity, frequency, and duration aspects, while the drought is mainly manifested by frequency and duration reduction of precipitation. Seasonal cycle of changes in temperature indices can be discovered in the North Hemisphere mid-latitude deforestation region, tropical region shows year-round consistency. Changes in LULCC induced climate extremes are more obvious under the low-emission scenario in general. Our work is devoted to portraying the latest and more realistic picture of LULCC impacts on climate extremes and gives early warning information to policymakers and the public.

How to cite: Zhang, M. and Gao, Y.: Impacts of anthropogenic land use and land cover change on climate extremes based on CMIP6-LUMIP experiments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4834, https://doi.org/10.5194/egusphere-egu24-4834, 2024.

EGU24-5226 | Posters on site | CL4.1

Using HydroTiles to represent different hydrological regimes in a global Earth System model 

Tobias Stacke, Philipp de Vrese, Veronika Gayler, and Victor Brovkin

Land surface regions that are of crucial importance for climate dynamics, such as Arctic permafrost landscapes, are often extremely heterogeneous. In these areas, hydrological processes and heat fluxes, which are influenced by topographic features on the scale of a few meters, can affect processes such as permafrost thaw over large regions. Despite the emergence of Earth system models that can operate at a resolution down to one kilometer, hydrological heterogeneity at smaller scales is often overlooked. In addition, high-resolution models are computationally intensive, making them unsuitable for the time scales required to study the climate impacts of processes such as permafrost thaw.

In this study, we present an extension to the tiling infrastructure of the ICON Earth system model that enables the representation of different hydrological regimes within individual grid cells. This innovative approach facilitates the representation of lateral water flow connections between different areas within grid cells and the simultaneous representation of different surface water and soil moisture states, such as dry and wet conditions, within a single grid cell. The impact of this improvement is twofold. First, it provides a more accurate representation of surface and soil hydrology. Second, it is expected to improve the representation of land-atmosphere coupling, allowing us to better capture feedbacks across landscapes affected by strong hydrologic contrasts.

By enabling the representation of hydrological features in subgrids through tiles, which we call HydroTiles, we hypothesize that the HydroTiles setup could replicate some features of high-resolution simulations even at lower resolutions. This approach offers the potential to make simulations more computationally cost-efficient. In our presentation, we would like to highlight the advantages and disadvantages of the HydroTile setup compared to high-resolution simulations.

How to cite: Stacke, T., de Vrese, P., Gayler, V., and Brovkin, V.: Using HydroTiles to represent different hydrological regimes in a global Earth System model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5226, https://doi.org/10.5194/egusphere-egu24-5226, 2024.

EGU24-5392 | ECS | Posters on site | CL4.1

Examining the impact of extreme land surface temperature and land cover on heatwave occurrence: The case of MENA region  

Mohammadsaeed asghariian, Parvin Azizi, Milad Aminzadeh, and Nima Shokri

The increase in Land Surface Temperature (LST) in a changing climate is expected to alter the intensity and frequency of heatwaves by shifting the energy partitioning over the land surface. The relationship between LST and hot air temperatures, influenced by land cover and associated changes in surface properties is not fully understood, particularly in dry regions of the world experiencing prolonged droughts. Extremely high LSTs and their projected changes [1] may stress resilience and adaptive capacities of the growing population in the Middle East and North Africa (MENA). We thus investigate the evolution of extremely high LSTs in MENA over the past two decades to identify its coupling with hot air temperatures considering different land cover types. Our preliminary results highlight the difference in warming rates of LST and air temperature across different land covers thus enabling to identify the role of land temperature extremes in triggering heatwave events. We observed that variation of land temperature arising from land cover changes (affecting soil moisture dynamics and surface thermal and radiative properties) may significantly influence the occurrence and the intensity of heatwaves in this region. The study offers valuable insights into the complex interplay between land and air hot extremes that are particularly important in local climate investigations, agricultural practices, and ecosystem functions.

Reference

[1] Aminzadeh, M., Or, D., Stevens, B., AghaKouchak, A., & Shokri, N. (2023). Upper bounds of maximum land surface temperatures in a warming climate and limits to plant growth. Earth's Future, 11, e2023EF003755. https://doi.org/10.1029/2023EF003755

How to cite: asghariian, M., Azizi, P., Aminzadeh, M., and Shokri, N.: Examining the impact of extreme land surface temperature and land cover on heatwave occurrence: The case of MENA region , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5392, https://doi.org/10.5194/egusphere-egu24-5392, 2024.

EGU24-5644 | ECS | Orals | CL4.1 | Highlight

The relationship between forest fragmentation and extreme high temperature 

Ran Du and Yanhong Gao

Warming lead to a surge in extreme climate events, including heatwaves, droughts, flooding, and wildfires. Numerous studies demonstrate that these occurrences have become more frequent, which exerts notable influences on socio-economic development and human health. Besides natural climate changes, land use and land cover changes (LULCC) play a crucial role in shaping extreme climates. As the most extensive land use type globally, forest has experienced great changes since the industrial evolution. Deforestation is one of the most notable global environmental issues. Besides the decrease of the coverage, fragmentation is one of the appearances of deforestation. Many studies have demonstrated that forest distribution shows high agreements with climate regimes generally, however, the relationship between forest fragmentation and extreme climate events remain unclear. This study analyzes the relation between forest fragmentation and main extreme high temperature indices in 2000-2020. Global continental areas are categorized into regions with increased and decreased forest fragmentation index. Regions with increased index, such as the southeast Amazon, Congo Basin, and parts of the Southeast Asia are emphasized. The 11 extreme temperature indices are analyzed responded to the forest fragmentation index change. This study could provide insights for forest management strategies adapting to climate change in the future.

How to cite: Du, R. and Gao, Y.: The relationship between forest fragmentation and extreme high temperature, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5644, https://doi.org/10.5194/egusphere-egu24-5644, 2024.

The Vietnamese Mekong Delta (VMD) is the most productive region in Vietnam in terms of agriculture and aquaculture. Unsurprisingly, droughts have emerged as a persistent concern for stakeholders throughout the VMD in recent decades. In the evolution and intensification of droughts, local feedbacks in the Land-Atmosphere (LA) interactions were considered to play a crucial role. Previous studies mainly focused on the water cycle feedback loop (e.g., soil moisture-evaporation-precipitation) in the LA interactions. However, there is a noticeable gap in the feedback loop of coupled water and energy balances (e.g., soil moisture-sensible heat-precipitation) associated with the anomalies in sensible heat and precipitation. Therefore, deep understanding of the roles of key variables and their inter-relationships in the LA interactions is of great significance for local communities and authorities. In this study, a deep learning model, named Long- and Short-term Time-series Network (LSTNet), was applied to simulate the LA interactions over the VMD. With the ERA5 data as modelling inputs, the role of each key variable (e.g., soil moisture, sensible and latent heat) in the LA interactions over the past decade (2011-2020) was investigated, and the variations of these variables and their inter-relationships in the future period (2015-2099) were also analyzed based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) data. The LSTNet model has demonstrated that the deep learning algorithm can effectively capture the relative importance of key variables in the LA interactions. We found it is crucial to evaluate the effect of coupled temperature and sensible heat on the LA interactions, particularly for the regions that are susceptible to concurrent droughts and heatwaves, as the co-occurrence of dry and hot weather conditions would inhibit the formation of precipitation and intensify the drought severity. Moreover, the decline in soil moisture and the rise in sensible heat under a changing climate are anticipated to further diminish precipitation in the future. This study would not only enhance our knowledge of the feedback mechanisms in the LA interactions during the drought evolution and intensification, but also provide valuable insights for further development and advancement of hydrologic models for drought monitoring and forecasting.

How to cite: Zhou, K., Shi, X., and Renaud, F.: Deep Learning-Based Analyses of Feedback Mechanisms in the Land-Atmosphere Interactions during Droughts over the Vietnamese Mekong Delta, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5756, https://doi.org/10.5194/egusphere-egu24-5756, 2024.

EGU24-6099 | ECS | Orals | CL4.1

How strong is land-atmosphere coupling in global storm-resolving simulations? 

Junhong Lee and Cathy Hohenegger

The debate on the sign of land-atmosphere coupling has not been solved so far. On the one hand, studies using global coarse-resolution climate models have claimed that the land-atmosphere coupling is positive. But, such models use convective parameterizations, which is a source of uncertainty. On the other hand, studies using regional climate models with explicit convection have reported negative coupling. Yet, the large-scale circulation is prescribed in such models, and interactions with the ocean are neglected. In this study, we revisit the land-atmosphere coupling using a global fully coupled storm-resolving simulation that has been integrated at a grid spacing of 5 km over a full seasonal cycle, and we compare these results to a coarse-resolution climate model simulation using parameterized convection. We find that the coupling between soil moisture and precipitation is weaker and more negative in the storm-resolving than in the coarse-resolution simulation. Further analysis indicates that not only the feedback between soil moisture and evapotranspiration but also between evapotranspiration and precipitation is weaker in the storm-resolving simulation, in better agreement with observations. Reasons for the differences will be mentioned.

How to cite: Lee, J. and Hohenegger, C.: How strong is land-atmosphere coupling in global storm-resolving simulations?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6099, https://doi.org/10.5194/egusphere-egu24-6099, 2024.

EGU24-7942 | ECS | Orals | CL4.1

The cooling effect induced by the Three Gorges Reservoir operation in observations and model simulations 

hongbin li, weiguang wang, and giovanni forzieri

The Three Gorges Dam, the world's largest hydropower project, and its impoundment reservoir have notably modified land cover, with potential implications for regional hydroclimate. However, the seasonal dynamic climate feedbacks arising from variations in water body areas managed by the Three Gorges Reservoir (TGR) remains poorly understood. Based on data-driven analysis and regional climate simulations, we depict the impact of the TGR regulation activities on local land surface temperature (LST) and biophysical processes across different spatiotemporal dimensions, determine the spreading extent of this effect to external territories, and further identify the quantitative attributions between regional climate variabilities and the TGR operation. Results indicate that the TGR induces more pronounced daytime cooling from May to October, particularly in June-August (JJA) with -2.41±0.23 K. The influence of TGR on nighttime LST transitions to warming effects in most regions from November to April (NDJFMA). The significantly increased latent heat (LH) from evaporation growth dominates cooling effects, particularly during daytime, while in JJA, the effects of evaporation are constrained to some extent by abundant precipitation. Albedo exerts a comparatively significant dominance on the nighttime LST in NDJFMA. The TGR-induced surroundings LST changes are notably discernible within an approximately 10 km buffer. The simulations amplify the magnitude and extent of the TGR cooling effect. The simulation results reveal significant reductions in LST of 6.08% (-1.42 K, JJA) and 4.58% (-1.04 K, December-January-February, DJF). respectively, TGR-induced LH variations are dominant for cooling (contributions: -52.09% in JJA; -71.98% in DJF, respectively) among the diverse energy components. This study is valuable for providing scientific guidance in reservoir planning under changing climate.

How to cite: li, H., wang, W., and forzieri, G.: The cooling effect induced by the Three Gorges Reservoir operation in observations and model simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7942, https://doi.org/10.5194/egusphere-egu24-7942, 2024.

EGU24-8546 | Orals | CL4.1

Role of infiltration on land–atmosphere feedbacks in Central Europe: WRF-Hydro simulations evaluated with cosmic-ray neutron soil moisture 

Joel Arnault, Benjamin Fersch, Martin Schrön, Heye Reemt Bogena, Harrie-Jan Hendricks-Franssen, and Harald Kunstmann

The skill of climate models partly relies on their ability to represent land–atmosphere feedbacks in a realistic manner, through the coupling with a land surface model. However, these models often suffer from insufficient or erroneous information on soil hydraulic parameters. In this study, the land–atmosphere model WRF-Hydro driven with ERA5 reanalysis is employed to reproduce the regional climate over Central Europe with a horizontal resolution of 4 km, for the period 2017-2020 during which cosmic-ray neutron sensor (CRNS) soil moisture is available at three Terrestrial Environmental Observatories. The soil hydraulic parameter datasets referred to as SoilGrids and EU-SoilHydroGrids, together with Campbell and van Genuchten–Mualem retention curve equations, are used to assess the role of infiltration on modeled land–atmosphere feedbacks. After calibration of the percolation parameter to better capture observed discharge amounts in the observatories, it is found that WRF-Hydro with Campbell and SoilGrids gives the lowest mean temperature and mean precipitation differences compared to the E-OBS product from European Climate Assessment & Dataset, by reducing soil moisture in the rootzone, increasing temperature, and decreasing precipitation through a positive soil moisture–precipitation feedback process. WRF-Hydro with van Genuchten–Mualem and EU-SoilHydroGrids best reproduces CRNS soil moisture daily variations, despite enhanced positive biases that generate a larger proportion of convective precipitation favored over wet soils and spurious discharge peaks. The question remains open whether an infiltration modeling option that better captures CRNS soil moisture dynamics can also lead to a clear improvement of the simulated climate.

How to cite: Arnault, J., Fersch, B., Schrön, M., Bogena, H. R., Hendricks-Franssen, H.-J., and Kunstmann, H.: Role of infiltration on land–atmosphere feedbacks in Central Europe: WRF-Hydro simulations evaluated with cosmic-ray neutron soil moisture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8546, https://doi.org/10.5194/egusphere-egu24-8546, 2024.

EGU24-9084 | ECS | Posters on site | CL4.1

Sensitivity of the simulated regional climate to changes in the prescribed soil type distributions: Insights from Coupled Regional Climate Model EBU-POM 

Irida Lazic, Vladimir Djurdjevic, Ivana Tosic, and Milica Tosic

In previous studies, it was noticed that many high-resolution Regional Climate Models (RCMs) simulations within the state-of-the-art EURO-CORDEX multi-model ensemble tend to overestimate air temperature and underestimate precipitation in summer leading to the so-called summer drying problem. One of the possible and considerable sources of uncertainty in simulated regional climate is the choice of soil texture database and its soil parameter values. This is crucial because soil hydrophysical properties, influenced by such choices, have an impact on soil moisture and therefore affect the partitioning of surface fluxes [1]. These properties among others play a role in controlling the evolution of soil and air temperature, evapotranspiration, runoff, and precipitation. 

To better understand one of the possible reasons for this problem, we performed two simulations with the coupled regional climate model EBU-POM with two different prescribed soil type distributions. One simulation used the soil type dataset derived from the Zobler dataset and in the second simulation, we used FAO/STATSGO dataset. Two 11-year EBU-POM simulations were conducted, spanning the period from 2000 to 2010. These simulations were initiated in 1998, allowing a two-year spin-up time to reduce the impact of initial fields. The area of interest was Central Europe with a focus on Pannonian Basin because previous studies indicated pronounced dry and warm biases during summer and autumn in low-lying areas, especially in south-eastern Europe. 

The soil moisture capacity is influenced by its hydrophysical characteristics, wherein the size of soil grains plays a crucial role. In this investigation, we emphasized and analyzed the significance of soil hydrophysical properties in shaping surface fluxes. We performed the comprehensive analysis with a focus on the most common specific soil category transitions related to changes in soil parameters and bias changes in surface and near-surface variables and fluxes. The main goal of this study is not to inspect the accuracy of the soil texture map but rather to comprehend the impact on modeled surface and near-surface variables when employing one soil texture dataset versus the other. 

On the other hand, Seneviratne et al. [2] suggested that a new transitional zone characterized by strong land-atmosphere interactions shifted northwards to central and eastern Europe as a consequence of global warming. Their findings highlighted that increased temperature variability in this region is mainly due to land-atmosphere feedbacks. Hence, we analyzed bias in surface and near-surface variables and fluxes and their relation to extreme events such as the heat wave occurred in 2007 to determine their influence on heat wave formation.

[1] Dennis, E. J., and Berbery, E. H. (2021). The role of soil texture in local land surface–atmosphere coupling and regional climate. Journal of Hydrometeorology22(2), 313-330.

[2] Seneviratne, S. I., Lüthi, D., Litschi, M., and Schär, C. (2006). Land–atmosphere coupling and climate change in Europe. Nature, 443(7108), 205-209.

Keywords: regional climate modelling, soil moisture, soil texture, land-atmosphere interactions

Acknowledgement: This research was supported by the Science Fund of the Republic of Serbia, No. 7389, Project Extreme weather events in Serbia - analysis, modelling and impacts” - EXTREMES

How to cite: Lazic, I., Djurdjevic, V., Tosic, I., and Tosic, M.: Sensitivity of the simulated regional climate to changes in the prescribed soil type distributions: Insights from Coupled Regional Climate Model EBU-POM, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9084, https://doi.org/10.5194/egusphere-egu24-9084, 2024.

EGU24-9091 | ECS | Orals | CL4.1

Analysis of trends in surface energy fluxes under hot conditions using remote sensing products 

Almudena García-García and Jian Peng

Studying land-atmosphere interactions is important for understanding the mechanisms leading to changes in temperature and precipitation extremes. However, the non-conservation of energy and water in most products and their coarse spatial and temporal resolution hamper the study of land-atmosphere feedbacks. The combination of remote sensing data and modelling frameworks allows to greatly improve the spatial coverage and resolution of data products. Here, we investigate trends in surface fluxes over Europe using the new data product generated with the high-resolution land surface fluxes from satellite and reanalysis data (HOLAPS) framework. HOLAPS is a one dimensional modelling framework that solves the energy and water balance at the land surface, providing consistent surface and soil variables derived from remote sensing data and reanalysis products as forcings. The evaluation of the HOLAPS product against eddy covariance measurements shows slightly better results than other ET and H products at daily scales in summer (KGE > 0.0 for ET and KGE > -0.3 for H) and during hot extremes (KGE > -0.15 for ET and KGE >-0.7 for H), while the state-of-the-art products show KGE > -0.49 for ET and KGE > -1.2 for H in summer and KGE > -0.49 for ET and KGE > -1.5 for H during hot extremes. These results together with the 1D conservation of energy and water in the modeling framework makes this product the perfect tool for the analysis of trends in surface energy and water fluxes during the last decades. Preliminary results for the period 2001-2016 reveals a larger increase in the energy reaching the surface during the hottest month of the year than during summer over central Europe and the Mediterranean coast. This extra energy is released as sensible heat over dry areas during the hottest month of the year. In areas where soil water is available, the extra energy available during the hottest month is released as latent heat flux, adding it to the already large latent heat flux during summer. These results support previous analyses indicating an increase of latent heat flux during hot conditions at monthly scales. However, trends at higher temporal resolutions should be examined to improve the robustness of this conclusion. 

How to cite: García-García, A. and Peng, J.: Analysis of trends in surface energy fluxes under hot conditions using remote sensing products, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9091, https://doi.org/10.5194/egusphere-egu24-9091, 2024.

EGU24-11141 | ECS | Posters on site | CL4.1

The drought response of European ecosystem processes via multiple components of the hydrological cycle 

Christian Poppe Terán, Bibi Naz, Harry Vereecken, and Harrie-Jan Hendricks Franssen

Droughts have become more frequent and severe in Europe over the last decade - a trend expected to continue. Recent studies have shown widespread responses of energy, water, and carbon fluxes in ecosystems to single drought years from flux observations. 

However, to better understand how ecosystems react to droughts, we need to gain explicit knowledge about the different factors that influence their response. In this light, it is crucial to associate the influence of droughts on diverse ecosystem types with particular compartments of the hydrological cycle (atmosphere, surface, soil, and groundwater reservoirs). For instance, during a drought, atmospheric dryness might be the dominant factor in arid regions as opposed to dry soils in humid regions.

Here, we use states and fluxes of water and carbon (vapor pressure deficit, surface runoff, soil moisture, and water table depth) from the Community Land Model 5 in a 3 km resolution over Europe from 1995 to 2018 to determine the drought anomalies of ecosystem processes (gross primary production and evapotranspiration). Importantly, we apply a systematic drought concept integrating lags between deficits in a network of multiple sections of the hydrological cycle during a drought.

Our analyses indicate that the dominance of a particular water resource in controlling ecosystem processes converges regionally and is predominantly consistent across drought events. This finding emphasizes using more comprehensive drought indices incorporating time lags and multiple water resources when analyzing ecosystem responses. Lastly, it identifies areas potentially threatened by droughts and their controlling water resource.

How to cite: Poppe Terán, C., Naz, B., Vereecken, H., and Hendricks Franssen, H.-J.: The drought response of European ecosystem processes via multiple components of the hydrological cycle, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11141, https://doi.org/10.5194/egusphere-egu24-11141, 2024.

EGU24-11163 | ECS | Orals | CL4.1

Examining the influence of forest changes on drought across time scales in Europe through multiple regional climate model simulations 

Yan Li, Bo Huang, Chunping Tan, Yi Liu, and Henning W. Rust

Land cover changes, notably forest alterations, have been observed across Europe due to extensive land management policies. These changes have significant influence on local climates through diverse biophysical mechanisms, given the crucial role of forests in the land ecosystem. While modeling studies have emphasized the impact of forest changes on regional temperature and precipitation in recent decades, their effects on drought conditions in this region remain largely unexplored. To address this gap, our study analyzes multiple simulations with regional climate models to comprehensively investigate how forest changes impact drought across various timescales in Europe. Specifically, we explored seven models, each simulated two extreme scenarios: maximum forest coverage and grass coverage in the region. The comparison between extreme forest coverage and grass coverage serves to evaluate the impact of deforestation on drought. The Standardized Precipitation Evapotranspiration Index was chosen as our metric to assess drought conditions. Our findings reveal considerable variation among the models in depicting the response to deforestation in terms of drought, particularly notable in Scandinavia and Eastern Europe. Our results suggest an increase in aridity on the Iberian Peninsula following deforestation. In Scandinavia the response varies during the year: winter months tend toward increased dryness, while summer months display a tendency toward greater wetness post-deforestation. Our primary objectives encompass quantifying the potential impacts of deforestation in Europe, identifying resilient model responses, and unraveling the sources of uncertainty within these simulated impacts. Through a meticulous analysis of model responses across regions and timescales, we aim to offer insights into the nuanced effects of forest change on drought conditions. This exploration is crucial in guiding future land management policies and devising strategies to mitigate potential adverse impacts of deforestation on regional drought susceptibility in Europe. Ultimately, our study seeks to contribute to informed decision-making regarding land use practices and their implications for climate and ecosystems.

How to cite: Li, Y., Huang, B., Tan, C., Liu, Y., and Rust, H. W.: Examining the influence of forest changes on drought across time scales in Europe through multiple regional climate model simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11163, https://doi.org/10.5194/egusphere-egu24-11163, 2024.

Extreme climate events such as droughts and heatwaves significantly impact the stability of ecosystem function and are expected to intensify in the future. The mid-high latitude regions of the Northern Hemisphere (23.5° to 90°N) exhibit pronounced seasonality and are highly sensitive to climate variations. However, further research is needed to understand the vegetation decline and its changing trends driven by extreme hydroclimatic and their compound events in this region. This study, based on multi-source data including NDVI, LAI, and GPP from 1982 to 2015 as vegetation growth indicators, amid to identify vegetation decline during the growing season and explore its temporal trends, and to further reveal the seasonal response. The research supported the importance of drought and high temperature compared to extreme wet and cold conditions. Due to the high frequency, wide impact and long duration of impact, independent low SM dominated the cumulative vegetation decline, followed by low SM and high VPD compound events. High VPD caused stronger negative impacts on vegetation growth than high T and that it was more strongly coupled to SM. We further found a turning point in vegetation decline. Because of the significant increase in VPD and its enhanced coupling with low SM, low SM and its compound events, especially SM- & VPD+ & T+ compound events, led to a significant enhancement of the vegetation decline after about the 21st century. Furthermore, the sensitivity of vegetation growth to extreme hydroclimatic has also significantly increased, with stronger intensity of vegetation decline. Seasonally, early growing season vegetation was more vulnerable (with the strongest continuous decline) due to experiencing the longest duration of negative impacts, while summer vegetation was more sensitive to extreme hydroclimatic, with the strongest intensity. Notably, compound events of high VPD and low SM primarily affected summer vegetation growth. Additionally, there was a significant lag time in vegetation response to extreme hydroclimatic, especially to high VPD and high T. In over half of the regions, the vegetation response to high T and high VPD had a lag time exceeding two months, which may be associated with seasonal legacy. In the context of global warming, further investigation is needed to explore the inter-seasonal connections. This research significantly contributes to a deeper understanding of ecosystem responses to extremes hydroclimatic and its future changes.

How to cite: Du, R. and Wu, J.: The turning point in vegetation decline in the Northern Hemisphere driven by hydroclimatic extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11693, https://doi.org/10.5194/egusphere-egu24-11693, 2024.

EGU24-12392 | ECS | Posters virtual | CL4.1

Heatwaves and Droughts in Europe: A multi-year analysis using MODIS Land Surface Temperature Anomalies 

Foteini Karinou, Ilias Agathangelidis, and Constantinos Cartalis

In recent decades, European societies and ecosystems have faced recurrent extreme temperatures that contribute to a significant number of impacts, such as wildfires, heat-related illnesses, and crop losses. As heat extremes are further projected to increase in frequency and intensity, a better understanding and close monitoring of these events is necessary. In this study, remotely-sensed Land Surface Temperatures (LSTs) from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to assess recent heatwaves and droughts in Europe (2003 – 2023). Our results reveal that surface heat extremes are intensifying and becoming more frequent. Moreover, a strong coupling is found between surface thermal extremes, heatwaves (based on near-surface air temperatures) and droughts. Finally, surface LST anomalies are investigated in the context of shifts in energy partitioning under heatwaves/droughts, using eddy covariance flux measurements from the Integrated Carbon Observation System network.

How to cite: Karinou, F., Agathangelidis, I., and Cartalis, C.: Heatwaves and Droughts in Europe: A multi-year analysis using MODIS Land Surface Temperature Anomalies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12392, https://doi.org/10.5194/egusphere-egu24-12392, 2024.

EGU24-12955 | ECS | Posters on site | CL4.1

The influence of temperature–moisture coupling on the occurrence of compound hot and dry events over South America: historical and future perspectives 

João L. Geirinhas, Ana Russo, Renata Libonati, Diego G. Miralles, Daniela C. A. Lima, Andreia F. S. Ribeiro, and Ricardo M. Trigo

The strong global warming observed in the past 50 years has intensified the Earth’s water cycle, triggering more frequent and severe rainfall and drought episodes, a trend that is expected to be aggravated in many regions1,2. Consequently, significant changes in the distribution of temperature, precipitation and evaporation are foreseen. Such changes will likely cause disturbances to the physical coupling between temperature and moisture and, ultimately, to the occurrence of compound hot and dry (CDH) extremes, leading to severe environmental and socio-economic impacts3–5. These coupling interactions can be conceptualized by (1) the correlation between temperature and precipitation to characterize atmospheric coupling, and (2) the correlation between temperature and evaporation, as a proxy for land–atmosphere coupling.

Data from ERA5 reanalysis and from a weighted CORDEX-CORE ensemble6 assuming two different emission scenarios (RCP2.6 and RCP 8.5), was used to assess, for seven climate regions in South America, the influence of these coupling interactions on the occurrence of CDH conditions.

Results obtained by applying multivariate regression models for the historical period (1980–2005) demonstrate that the dependence of CDH conditions on these two metrics of coupling varies considerably from region to region. While in some areas of South America a monotonical influence of a particular coupling mechanism dominates, in other regions of the continent a jointly impact of both coupling processes in the occurrence of CDH conditions is present.  We also investigate how the distribution levels of these two coupling processes will change in future due to long-term disturbances expected by climate change in temperature and in the water balance, and how a higher or lower occurrence of CDH episodes can be explained by changes in the type and strength of the dominant coupling mechanism.  

References

  • Chagas, V. B. P. et al. Climate and land management accelerate the Brazilian water cycle. Nat. Commun. 13, 5136 (2022).
  • Donat, M. G. et al. More extreme precipitation in the world’s dry and wet regions. Nat. Clim. Chang. 6, 508–513 (2016).
  • Berg, A. et al. Interannual Coupling between Summertime Surface Temperature and Precipitation over Land: Processes and Implications for Climate Change. J. Clim. 28, 1308–1328 (2015).
  • Miralles, D. G. et al. Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges. Ann. N. Y. Acad. Sci. 1436, 19–35 (2019).
  • Lesk, C. et al. Stronger temperature–moisture couplings exacerbate the impact of climate warming on global crop yields. Nat. Food 2, 683–691 (2021).
  • Lima, D. C. A. et al. A multi-variable constrained ensemble of regional climate projections under multi-scenarios for Portugal – Part I: An overview of impacts on means and extremes. Clim. Serv. 30, 100351 (2023).

Acknowledgments:

JG is grateful to Fundação para a Ciência e a Tecnologia I.P./MCTES (FCT) for the PhD Grant 2020.05198.BD. JG, AR, RMT, and DCAL also thank FCT I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). AR, RMT, RL, JG and AFSR thank also FCT for project DHEFEUS (https://doi.org/10.54499/2022.09185.PTDC). AR was supported by FCT through https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006. DCAL was supported by FCT through https://doi.org/10.54499/2022.03183.CEECIND/CP1715/CT0004. DGM acknowledges support from the European Research Council (HEAT, 101088405).

How to cite: Geirinhas, J. L., Russo, A., Libonati, R., Miralles, D. G., Lima, D. C. A., Ribeiro, A. F. S., and Trigo, R. M.: The influence of temperature–moisture coupling on the occurrence of compound hot and dry events over South America: historical and future perspectives, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12955, https://doi.org/10.5194/egusphere-egu24-12955, 2024.

EGU24-13027 | ECS | Posters on site | CL4.1

Unveiling the influences of soil moisture on moist heat stress extremes: a global assessment using CMIP6 data 

Jingwei Zhou, Dragan Milosevic, and Adriaan Teuling

Soil moisture is a key variable in land-atmosphere interactions, as it affects the partitioning of near-surface energy fluxes and thereby temperature and humidity of the lower atmosphere. Both ambient temperature and humidity play a crucial role in the removal of heat from the human body through direct heat transfer and sweat evaporation, therefore these two factors are commonly used in measuring moist heat stress. As moist heat stress describes the combined effects of temperature and humidity on human health and well-being, understanding the intricate relationship between soil moisture and moist heat stress is crucial for accurately assessing and mitigating moist heat extremes. Whereas the impact of soil moisture on temperature is well understood, previous research has found non-trivial and complex relations between soil moisture and moist heat stress due to humidity feedbacks. We selected two metrics among four widely used metrics which involve both temperature and humidity, indoor and open-air wet-bulb globe temperature, heat index, and humidex, to represent the heat stress in our study. We use different levels to describe the significance of the heat stress and tolerance level among the population.

In this study, we aim to investigate the impacts of soil moisture on moist heat stress at the global scale using the Land Surface, Snow and Soil moisture Model Intercomparison Project (LS3MIP) dataset within the sixth phase of the Coupled Model Intercomparison Project (CMIP6). We use the historical and future simulations from LS3MIP to analyze the spatial and temporal variations of soil moisture-heat stress coupling, and to identify the regions that are most susceptible to moist heat stress. Interactions between soil moisture and moist heat stress tend to be particularly pronounced in hot and humid regions,. These regions are likely to experience more frequent events with higher moist heat stress, posing serious challenges for human health and adaptation.

To our best knowledge, this study is the first to show a global picture of the interactions between soil moisture and moist heat stress using CMIP6 dataset. The pattern of heat stress in relation to soil moisture in perspectives of the time of day, season, and soil moisture regime will be investigated. Our study provides a novel insight into the role of soil moisture in modulating moist heat stress, and highlights the need for more accurate representation of land surface processes and feedbacks in climate models. The findings are crucial for developing effective strategies in managing moist heat stress risks and protecting vulnerable populations.

How to cite: Zhou, J., Milosevic, D., and Teuling, A.: Unveiling the influences of soil moisture on moist heat stress extremes: a global assessment using CMIP6 data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13027, https://doi.org/10.5194/egusphere-egu24-13027, 2024.

EGU24-13484 | ECS | Orals | CL4.1

Seasonal Variability of Deforestation-Induced Warming in the Congo Basin Using Remote-Sensing Data 

Coralie Adams and Luis Garcia-Carreras

Deforestation impacts in the Congo Basin remain significantly understudied compared to other tropical regions. The main driver of Congo Basin deforestation is small-scale industrial agriculture, which leads to the formation of the rural complex; a mosaic patch of deforested land comprising small fields at different stages of regrowth being deforested repeatedly. Transition from primary forest to rural complex may induce lesser changes in albedo, Bowen ratio, and surface roughness than primary forest to cropland, suggesting the impacts of deforestation on temperatures in the Congo Basin will differ from those in other rainforest regions. The Basin's long-term warming trend and possible ongoing drying could exacerbate warming due to deforestation. It is therefore essential that we understand how the specific nature of deforestation in the Congo Basin influences temperatures, and how this is affected by changes in the large-scale conditions driven by global climate change.

In this study, we used MODIS satellite data for LST and EVI, CHIRPS2 for rainfall, and the Global Forest Change dataset for deforestation analysis from 2000 to 2019 to assess how observed deforestation is affecting LST in the Congo Basin and how the deforestation-induced warming varies with climate anomalies, LST and rainfall (SPI), and Δ EVI (deforested EVI – surrounding forest EVI). Due to limited data availability, caused by the prevalence of cloud cover throughout much of the year, our focus narrowed to the most data-consistent dry season (DJF), where land-atmosphere interactions are also likely to be strongest.

We found a linear relationship between cumulative deforestation and warming over deforested land, which varied in intensity by month. A typical 1 km rural complex pixel within the region will warm by +0.33 °C in December, +0.85 °C in January, and +1.54 °C in February, relative to the surrounding forest. We then assessed the cause of the strong seasonal differences by looking at the deforestation-induced warming as a factor of the climate anomalies and Δ EVI. The amount of warming of a typical 1 km rural complex pixel did not show a relationship with the LST anomaly or SPI for the individual months. However, when considering all months collectively, a correlation emerged with the LST anomaly, suggesting a seasonal evolution where the LST anomaly acts as a proxy. We then found a link between the warming of a typical 1 km rural complex pixel and Δ EVI which is present for each month; this partially explains the interannual variability of the results, but it doesn’t explain the seasonal evolution. Comprehensive and high-quality observations are needed over the Congo Basin to fully untangle these relationships. Accurate soil moisture data could be crucial in understanding the pronounced seasonal differences in warming. These findings suggest that even though the rural complex differs from cropland, and might be expected to have a smaller impact, the additional warming can still be substantial (+1.54 °C), although it has a strong seasonal dependency.

How to cite: Adams, C. and Garcia-Carreras, L.: Seasonal Variability of Deforestation-Induced Warming in the Congo Basin Using Remote-Sensing Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13484, https://doi.org/10.5194/egusphere-egu24-13484, 2024.

EGU24-14184 | ECS | Orals | CL4.1

Links between seasonal precipitation intermittency and soil moisture variability 

Woon Mi Kim, Isla Simpson, Clara Deser, Flavio Lehner, and Angeline Pendergrass

Precipitation is an important control of soil moisture on land. Thus, many studies have focused on understanding the influences of mean or total precipitation variability on soil moisture. However, the relationship between precipitation intermittency (the temporal distribution of rainfall events) and soil moisture variability remains largely underexplored. This question requires more attention as climate models are known to be deficient in their representation of precipitation intermittency (PI), and PI is projected to increase in a future warmer climate, potentially affecting soil moisture variability. In this study, we examine the associations between seasonal PI and soil moisture (SM) across the globe in observation-based datasets (ERA5, MSWEP, and GLEAM) and model simulations (CESM2 Large Ensembles – LENS2) for the period 1981–2020. As a methodology to quantify the associations between PI and SM, we use a conditional regression analysis of 10cm soil moisture onto a metric of PI (reverted number of wet days in a season) after the removal of the influence of total seasonal precipitation from each variable. 

The result suggests that in many regions, higher PI leads to decreases in SM under the same amount of seasonal precipitation. These associations are explained by increased runoff under higher PI. Therefore, the spatial patterns of the magnitude and sign of the linkage between PI and SM align with the global patterns of PI-runoff interactions. Additionally, the regions where evapotranspiration (ET)–SM correlations are high (>0.5) present higher SM sensitivity to changes in PI. CESM2 exhibits spatial consistency in the PI–SM associations with ERA5, although noticeable differences exist in the magnitudes of the regression coefficients between the two datasets. In general, the PI–SM associations are weaker in CESM2. This disparity is attributed to the different runoff sensitivity to changes in precipitation and PI. CESM2 exhibits reduced runoff sensitivity to PI than ERA5 over the entire globe. This finding implies that how runoff is modeled and constrained in climate models will affect future projections of soil moisture.

How to cite: Kim, W. M., Simpson, I., Deser, C., Lehner, F., and Pendergrass, A.: Links between seasonal precipitation intermittency and soil moisture variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14184, https://doi.org/10.5194/egusphere-egu24-14184, 2024.

Land-atmosphere interactions are crucial in both weather and climate extremes. Studies have revealed certain large atmospheric circulation patterns such as amplified circumglobal wave 5 and 7 play important role in generating and maintaining surface extremes. These extremes can occur at the same time but different locations, for example in 2010, the wave 5 pattern was the driver for Russian heatwave and Pakistan flooding. But how soil moisture and land-atmosphere interactions affect the climatology states of jetstreams, amplified waves, and hence persistent extremes still remains unclear.

Here, we employ large ensemble simulations from climate model EC-Earth 3 to study the role of soil moisture in affecting large-scale atmospheric circulation for the period of 2009 to 2016. Three sets of experiments (each set has 100 ensemble members) are carried out with perturbed atmosphere-soil moisture interactions and one reference run (100 members) in which the interaction between the atmosphere and the land is fully interactive. We show that atmosphere-soil moisture interactions strongly influence the climatological mean states of atmospheric circulation in the Northern Hemisphere during the summer season (June to August) and especially in July. With the same soil moisture climatology, the reference run showed an overall land warming that led to poleward migration of jet and a more Arctic front jet state.

 Additionally, West Russia is chosen for the case study area as it is a hotspot for both amplified wave 5 and wave 7 heat extremes. We define the long duration heatwave event as near-surface temperature exceeding 30oC for at least eight days. The results show that with the soil-atmosphere interaction, the probability of such events increased from 2.2% to 5.8% for wave 5 and 0.47% to 4.5% for wave 7.

How to cite: Luo, F., Selten, F., and Coumou, D.: The role of soil moisture on summer atmospheric circulation climatology and persistent heatwaves in the Northern Hemisphere, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14484, https://doi.org/10.5194/egusphere-egu24-14484, 2024.

EGU24-14774 | Orals | CL4.1

Drought Changes Growing Season Length and Vegetation Productivity 

Josh Gray, Eunhye Choi, Mark Friedl, and Patrick Griffiths

Meteorological droughts are increasing in intensity, frequency, and duration due to climate change. These events may have substantial impacts on vegetation productivity that influence the global carbon balance. Effects vary considerably, however, with the intensity of the drought as well as local abiotic and biotic conditions such as vegetation type, soil type, and the timing of the drought. Productivity is primarily reduced because droughts decrease the efficiency with which plants can convert atmospheric CO2 into carbohydrates, largely because of stomatal closure when energy is not limiting. However, another aspect by which droughts can reduce productivity is by shortening the growing season length (GSL). GSL reduction may be particularly pronounced in vegetation communities already sensitive to precipitation variability, in particular, short-rooted grassland and croplands ecosystems. Here, we use evidence from satellite observations of ecosystem activity, meteorological measurements, and data from eddy-covariance flux towers to reveal the impact of several large-scale meteorological droughts on vegetation productivity on natural and managed ecosystems. In particular, we show that the timing of the drought is important, with late droughts being particularly diminishing to productivity. We also demonstrate that while plant physiological responses to drought dominate the reduction in productivity, the diminishment of GSL plays an underappreciated role. These results have wide implications for the future carbon balance under a changing climate, and suggests that ecosystem models could better explain productivity by incorporating the effects of droughts on GSL.

How to cite: Gray, J., Choi, E., Friedl, M., and Griffiths, P.: Drought Changes Growing Season Length and Vegetation Productivity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14774, https://doi.org/10.5194/egusphere-egu24-14774, 2024.

EGU24-15546 | ECS | Orals | CL4.1

Challenges in simulating ground surface temperature based on remote sensing land surface temperature over mountain grasslands 

Raul-David Șerban, Giacomo Bertoldi, Paulina Bartkowiak, Mariapina Castelli, and Andrea Andreoli

Ground surface temperature (GST), measured at a depth of around 5 cm below the ground surface, is essential for understanding the climate change impacts in the Earth Critical Zone. Large spatiotemporal variations of GST have been reported in mountain regions due to the heterogeneity of surface cover and topography. This work aims to improve the monitoring of GST using a physical land-surface model driven by satellite-based land surface temperature (LST). In this regard, GST was simulated using the physical GEOtop model at 1500 m elevation in Matsch Valley, north-eastern Italian Alps, from 2014 to 2017 during the phenological cycle, between April and October. The model was forced only by the LST derived from the Terra MODerate resolution Imaging Spectroradiometer (MODIS). The 1-km MODIS LST was first downscaled to a finer spatial resolution of 250-m using data-driven sharpening from random forest algorithm. The simulated GSTs correlate well with the in-situ observations with a Pearson correlation of 0.88 and a coefficient of determination of 0.77. However, the model overestimated the GST for the whole period with a mean bias of 8.72 °C. These overestimations are similar to the differences between in-situ GST and MODIS LST which range from 4.8 to 19 °C with an average of 8.5 °C. They are mainly caused by the low temporal resolution of LST data with only one observation per day which is additionally limited by frequent cloud cover contamination and the low spatial resolution of the MODIS thermal channels. Modelling the damping of the LST signal in the first centimeters of soil to simulate GST in very heterogeneous areas like alpine pastures is still challenging. This is mainly due to the resolution mismatch between ground and remote sensing observations and the poor knowledge of soil and vegetation properties needed to parametrize physical models.

How to cite: Șerban, R.-D., Bertoldi, G., Bartkowiak, P., Castelli, M., and Andreoli, A.: Challenges in simulating ground surface temperature based on remote sensing land surface temperature over mountain grasslands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15546, https://doi.org/10.5194/egusphere-egu24-15546, 2024.

EGU24-16559 | Orals | CL4.1 | Highlight

Assessing extreme temperature volatilities across Germany between 1990 and 2022 

Elisa Jordan, Ankit Shekhar, and Mana Gharun

Climate change causes a global rise in mean air temperature and increased frequency of temperature extremes. Recent studies link sharp temperature changes between consecutive days to increased mortality, reduced economic growth, and negative effects on ecosystems. While climatological analyses predominantly focus on mean temperatures, extreme temperatures have higher impacts on human health. This study assesses the variability of the daily maximum air temperature between two consecutive days (i.e., volatility) across Germany from 1990 to 2022. We used observation-based raster data of the maximum daily temperature assessed volatility regarding: 1) magnitude, 2) seasonality, 3) the direction of temperature change, and 4) trends during the entire period. As changes of land use and land cover have a direct impact on local temperatures, we analysed the land cover changes during the same period and examine its correlation to extreme volatilities.

The results showed a higher magnitude of rapid temperature decreases compared to temperature increases. Extreme volatilities increased with further distance to the coast from north of Germany to south. Overall, abrupt day-to-day temperature changes occurred mostly during the warming half-year (from March to August). During the study period, significant trends of 0.5 °C and 0.2 °C per decade showed a widening range of extreme volatility in spring and autumn. Compared to unchanged areas, changing land cover was predominantly liked to increasing volatilities of up to 0.5 °C. Understanding rapid temperature changes is crucial for climate change mitigation strategies and limiting impacts on human health and on the environment.

How to cite: Jordan, E., Shekhar, A., and Gharun, M.: Assessing extreme temperature volatilities across Germany between 1990 and 2022, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16559, https://doi.org/10.5194/egusphere-egu24-16559, 2024.

EGU24-16729 | ECS | Posters on site | CL4.1

Poleward migration of soil moisture–temperature coupling hotspots under global warming 

Daniel F.T. Hagan, Diego Miralles, Guojie Wang, Alan T. Kennedy-Asser, Mingxing Li, Waheed Ullah, and Shijie Li

Global hotspot regions where soil moisture (SM) constrains temperature changes are expected to migrate and change in intensity under climate change, impacting hydroclimatic events; however, the nature of these changes is still uncertain. Using multiple model outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we assessed potential future changes in the coupling between boreal summer SM and near-surface mean air temperature (T) across the globe under four Shared Socioeconomic Pathways (SSPs, 2015–2100). We find weakening SM impacts on T (SM-T coupling) in semi-arid, low-latitude regions with increasing emission scenarios due to reduced sensitivity of evaporation to SM. However, our results showed intensifying SM-T coupling primarily over humid regions with increasing precipitation yet decreasing SM due to increasing evaporation. We demonstrate that these changes could be linked to the poleward expansion of the Hadley cells and water-limiting conditions, shifting SM controls on partitioning the surface net radiation and subsequently on T under global warming. These results suggest a higher likelihood of extreme hydroclimatic events, such as heatwaves in higher latitudes associated with the SM–T coupling, which could impact food and water security.

How to cite: Hagan, D. F. T., Miralles, D., Wang, G., Kennedy-Asser, A. T., Li, M., Ullah, W., and Li, S.: Poleward migration of soil moisture–temperature coupling hotspots under global warming, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16729, https://doi.org/10.5194/egusphere-egu24-16729, 2024.

EGU24-17393 | Orals | CL4.1

Investigating the Climate Impacts of Afforestation and Deforestation in Europe via 5 km climate model simulations 

Luca Caporaso, Gregory Duveiller, Matteo Piccardo, Emanuele Massaro, Caspar Roebroek, Mirco Migliavacca, and Alessandro Cescatti

In the context of the European Green Deal framework, understanding the intricate and varied impacts of afforestation and deforestation across different regions is paramount. A complex interplay of environmental factors shapes the resulting climate effects. Evaluating these impacts and their spatial variability is crucial for formulating effective and context-specific climate mitigation and adaptation strategies.

This study takes a comprehensive approach, investigating both local and non-local effects of afforestation and deforestation within Europe, with a specific emphasis on the radiative budget and temperature dynamics.  Utilizing the cutting-edge Regional Climate Model (RegCM5) in conjunction with the Community Land Model version 4.5 (CLM4.5), we conducted simulations at a fine-scale, convective-permitting resolution of 5 km. This granular approach allows for an in-depth understanding of climate dynamics, shedding light on the distinct climate responses to forest cover alterations at various locations.

We conducted three simulations spanning the period 2004-2014: a control run and two scenarios involving afforestation and deforestation.  We concentrated on analyzing climatic changes through variables such as land surface temperature, near-surface air temperature, and the energy fluxes at the Earth's surface and the top of the atmosphere (TOA). Results suggest that afforestation/deforestation can yield substantial impacts on the climate system. It underscores the critical importance of evaluating biophysical effects at a high resolution, emphasizing the need to incorporate such considerations into climate change mitigation strategies.

Recognizing the location-dependent nature of afforestation and deforestation climate impacts, combined with the capabilities of advanced modeling tools, underscores the importance of flexible and adaptable land use planning. The practical implications of our findings extend to policymaking, offering insights that can inform sustainable land use decisions. These insights can guide the formulation of resilient and sustainable land use policies, aligning with the ambitious objectives of the European Green Deal.

How to cite: Caporaso, L., Duveiller, G., Piccardo, M., Massaro, E., Roebroek, C., Migliavacca, M., and Cescatti, A.: Investigating the Climate Impacts of Afforestation and Deforestation in Europe via 5 km climate model simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17393, https://doi.org/10.5194/egusphere-egu24-17393, 2024.

EGU24-17662 | ECS | Orals | CL4.1

Large biases in soil moisture limitation across CMIP6 models 

Francesco Giardina, Ryan S. Padrón, Benjamin D. Stocker, Dominik L. Schumacher, and Sonia I. Seneviratne

Accurate soil moisture representation is crucial in climate modeling, due to its significant role in land-atmosphere interactions. Our study focuses on water storage dynamics and analyzes how soil moisture limitation is represented in simulations from the land component (land-hist experiment) of seven models within the Coupled Model Intercomparison Project phase 6 (CMIP6). We quantified the annual maximum depletion in soil moisture, contrasting model results with observations of terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE). Our analysis shows that CMIP6 models mostly underestimate these annual extremes in soil moisture reductions, with the Amazon consistently emerging as the most biased region. We further computed the critical soil moisture thresholds and quantified the frequency of soil moisture limitation in CMIP6 simulations, comparing model estimates against solar-induced fluorescence (SIF) and GRACE observations. We found consistent results with the annual maximum depletion in soil moisture, with models almost always overestimating the frequency of soil moisture limitation globally compared to observations. We validated our findings with data from 128 eddy-covariance sites from eight biomes worldwide. Our study illuminates the biases in soil moisture storage and dynamics between CMIP6 models and empirical observations, highlighting the importance of improving the representations of soil moisture and land-atmosphere interactions in Earth System Models.

How to cite: Giardina, F., Padrón, R. S., Stocker, B. D., Schumacher, D. L., and Seneviratne, S. I.: Large biases in soil moisture limitation across CMIP6 models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17662, https://doi.org/10.5194/egusphere-egu24-17662, 2024.

EGU24-17860 | Orals | CL4.1

The International Soil Moisture Network (ISMN): providing a permanent service for earth system sciences 

Matthias Zink, Fay Boehmer, Wolfgang Korres, Kasjen Kramer, Stephan Dietrich, and Tunde Olarinoye

Soil moisture is recognized as an Essential Climate Variable (ECV), because it is crucial to assess water availability for plants and hence food production. Having long time series of freely available and interoperable soil moisture data with global coverage enables scientists, practitioners (like farmers) and decision makers to detect trends, assess the impacts of climate change and develop adaptation strategies.

The collection, harmonization and archiving of in situ soil moisture data was the motivation to establish the International Soil Moisture Network (ISMN) at the Vienna University of Technology in 2009 as a community effort. Based on several project funding periods by the European Space Agency (ESA), the ISMN became an essential means for validating and improving global land surface satellite products, climate and hydrological models. In December 2022, the ISMN was transferred to a new hosting facility the International Centre for Water Resources and Global Change (ICWRGC) and the German Federal Institute of Hydrology (BfG) in Koblenz (Germany). ISMN data are successfully provided from the new host since then and will be for decades to come as the German government committed to its long-term funding.

This presentation is going to showcase the International Soil Moisture Network (ISMN). Beyond offering comprehensive in situ soil moisture data, ISMN freely disseminates additional environmental variables, including soil temperature, snow depth, snow water equivalent, precipitation, air temperature, surface temperature and soil water potential if they are available from our data providers. With a global reach, ISMN has already accumulated 3000 stations with observations at various depths, while about 1000 stations are updated on a daily basis. Ongoing efforts are concentrated on expanding the database by incorporating additional stations and networks from institutional or governmental sources. Substantial resources are directed towards fortifying the operational system and improve usability to better serve our users. Additional efforts are undertaken to include ISMN in the data-to-value chain by contributing to international initiatives like WMO, FAO and GCOS. One example is the contribution to WMO’s yearly Global State of the Water Resources report.

How to cite: Zink, M., Boehmer, F., Korres, W., Kramer, K., Dietrich, S., and Olarinoye, T.: The International Soil Moisture Network (ISMN): providing a permanent service for earth system sciences, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17860, https://doi.org/10.5194/egusphere-egu24-17860, 2024.

EGU24-18231 | ECS | Orals | CL4.1

Summer Drought Prediction in Europe combining Climate Simulations and Remote Sensing 

David Civantos Prieto, Jesús Peña-Izquierdo, Lluis Palma, Markus Donat, Gonzalo Vilella, Mihnea Tufis, Arjit Nandi, Maria Jose Escorihuela, and Laia Romero

The occurrence of droughts is ruled by the interplay of complex processes with very different natures and spatio-temporal scales. Different modes of climate variability, like the North Atlantic Oscillation or ENSO (El Niño-Southern Oscillation), set the prevalence of distinct weather regimes providing sources of predictability at large-scale. On the other hand,  land-atmosphere feedbacks play a crucial role in climate extremes, and particularly, in the evolution and amplification of droughts. However, the weak predictability of the former large-scale variability in the extratropics together with the poor representation of these feedbacks in current seasonal predictive systems lead to a limited capability of predicting droughts months in advance. In this study (part of the AI4Drought project, funded by ESA), we aim to enhance summer drought prediction in Europe from spring conditions by the combination of state-of-the-art climate simulations and remote sensing.

A hybrid model combining climate simulations and high-resolution remote sensing data is proposed to boost the predictability signal at seasonal time-scale through the integration of two machine learning (ML) models. The first model (model-A) enhances large-scale predictability. It consists of a generative model (conditional variational auto-encoder, based on Pan et al., 2022), which is trained with 10.000s years of CMIP6 climate simulations to empirically learn the probability distributions between global spring fields; e.g., sea surface temperatures and 500 hPa geopotential height; and summer drought conditions (SPEI3). A local-scale model for extremes amplification is developed (model-B). A pixel-based (multi-layer neural network) model aims to capture land-atmosphere feedbacks; integrating local conditions from satellite-based products and reanalysis data, e.g. soil moisture (SM), temperatures and NDVI together with information from the large-scale predictions from model-A in order to predict SM anomalies for the whole summer season.

Preliminary results highlight the significance of local conditions in enhancing drought predictions, particularly in the Mediterranean region, where land-atmosphere feedbacks are pronounced. Experiments conducted under ideal conditions, knowing the future large-scale conditions in advance, demonstrate improved prediction skill when local conditions (e.g., soil moisture, NDVI) are included as predictors.

Moreover, a DeepSHAP analysis (eXplainableAI-based method) is performed to understand which are the most important drivers for the local-scale model prediction of summer SM anomalies. As expected, the spring’s SM anomalies are the most important input features; together with the large-scale conditions described by August SPEI-3. Additionally, temperature anomalies have a relatively high importance when predicting summer drought conditions.

This research underscores the potential of a hybrid approach integrating climate simulations and remote sensing data to advance the understanding and prediction of summer droughts in Europe.

How to cite: Civantos Prieto, D., Peña-Izquierdo, J., Palma, L., Donat, M., Vilella, G., Tufis, M., Nandi, A., Escorihuela, M. J., and Romero, L.: Summer Drought Prediction in Europe combining Climate Simulations and Remote Sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18231, https://doi.org/10.5194/egusphere-egu24-18231, 2024.

EGU24-18682 | ECS | Posters on site | CL4.1

Uncovering the moisture and heat sources to croplands during agricultural failure events 

Hao Li, Jessica Keune, and Diego Miralles

Dry and hot climate anomalies threaten rainfed agricultural productivity worldwide. Land–atmosphere feedbacks play a critical role during these abnormal weather events; for example, dry soils reduce evaporation and enhance sensible heating over the land surface, thereby amplifying air temperatures and water deficits for crops, consequently leading to agriculture failure. Moreover, these anomalies of moisture and heat upwind can be translated into downwind regions, thus leading to the spatial propagation of crop-adverse climate conditions. 

In this presentation, we analyse precipitation and temperature anomalies associated with crop failure events over the world’s largest 75 rainfed breadbaskets. Then the spatio-temporal origins of moisture and heat over these breadbaskets are determined using a novel atmospheric Lagrangian modelling framework along with satellite observations. Results indicate that upwind and local land–atmosphere feedbacks together cause lower moisture and higher heat transport into these breadbaskets, leading to decreases in yield of up to 40%. By zooming into the Southeastern Australia wheat belt as an example, known for experiencing recurrent droughts and heatwaves, we provide a detailed analysis of the anomalies of water and energy fluxes and atmospheric circulation and their impacts on moisture and heat sources. We find a substantial impact of advection of dry and hot air from upwind terrestrial regions, particularly during crop failure events, i.e., 1994, 2002, and 2006. Persistent high-pressure systems significantly alter moisture and heat imports into the wheat belt during these events, with upwind drought conditions intensifying rainfall deficits and heat stress in the agricultural region.

Our study suggests the potential for upwind land management to mitigate agricultural losses in rainfed, water-limited regions. Further understanding the intricate relationships between upwind and local influences on global breadbaskets, and specific regions like Southeastern Australia, may provide crucial insights for developing adaptive measures to avert food shortages in the face of a changing climate.

How to cite: Li, H., Keune, J., and Miralles, D.: Uncovering the moisture and heat sources to croplands during agricultural failure events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18682, https://doi.org/10.5194/egusphere-egu24-18682, 2024.

EGU24-19126 | Orals | CL4.1

Development of a land model for the next generation MIROC climate model and evaluation of its simulated land-atmosphere coupling 

Tomoko Nitta, Takashi Arakawa, Akira Takeshima, Dai Yamazaki, and Kei Yoshimura

We have been developing Integrated Land Simulator as a land model for the next generation of the MIROC climate model. Using a general-purpose coupler, ILS couples various land component models with minimum modifications and makes a land model independent from the atmospheric model. The major changes from the previous version of the land model in MIROC6 are the method of coupling land and atmosphere, the independent grid system and spatial resolution for the land model, and the river model. In MIROC6, the land model was part of the physical process of the atmospheric model and was run sequentially, but in the new model (MIROC-ILS), the land and atmospheric models are run in parallel. We have confirmed the MIROC-ILS meets the requirements such as water balance closure and computation time. In the presentation, we will show how the changes of land-atmosphere coupling method and coupling frequency affects the simulated atmosphere field.

How to cite: Nitta, T., Arakawa, T., Takeshima, A., Yamazaki, D., and Yoshimura, K.: Development of a land model for the next generation MIROC climate model and evaluation of its simulated land-atmosphere coupling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19126, https://doi.org/10.5194/egusphere-egu24-19126, 2024.

EGU24-19526 | ECS | Orals | CL4.1

Exploring the influence of land-atmosphere interactions on humid heat extremes in a convection permitting model simulation 

Guillaume Chagnaud, Chris Taylor, Cathryn Birch, Lawrence Jackson, John Marsham, and Cornelia Klein

Ambient humidity reduces the ability of the body to cool down through sweating, adding to the heat 
stress caused by elevated air temperature alone. Indeed, humid heat waves (HHWs) are already a threat
for humans, livestock and wildlife, and their impacts are projected to increase with global warming.
HHWs result from the combination of thermodynamic and dynamic processes interacting on a range of 
time and space scales and whose relative importance may vary according to location and time of year.

Africa is one continent where HHWs, defined here as extremes of wet-bulb temperature (Twb), are 
expected to become more important under global warming. Local-scale humid heat extremes may occur 
within more moderate larger-scale events across much of the continent. Yet, climatological 
characteristics of these smaller-scale events such as location and timing (in year and day) are poorly 
documented in the current climate, due to a lack of high-resolution data and research focus. Moreover, 
a comprehensive understanding of their meso- to synoptic-scale drivers is still lacking. Here, we explore 
these two issues using a 10-year pan-African convection-permitting model simulation that explicitly 
resolves land-atmosphere interactions, and particularly those involving moist processes that are 
instrumental to HHWs.

We find humid heat extremes in semi-arid regions occurring in the core of the rainy season, on length 
scales down to a few tens of kilometers. During HHWs, Twb peaks several hours 
later than the climatological peak in the late morning. This diurnal cycle shift is likely due to HHWs 
typically developing in the aftermath of a rainfall event: the resulting positive anomaly in soil moisture 
induces increased latent heat fluxes, low level divergence, and a reduced PBL height, all ingredients
displaying sharp spatial gradients conducive to locally high Twb values. These results have implications 
for the improvement of localized HHW predictability based on local soil moisture conditions, a key step 
towards climate change adaptation through e.g., early-warning systems.

How to cite: Chagnaud, G., Taylor, C., Birch, C., Jackson, L., Marsham, J., and Klein, C.: Exploring the influence of land-atmosphere interactions on humid heat extremes in a convection permitting model simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19526, https://doi.org/10.5194/egusphere-egu24-19526, 2024.

EGU24-20049 | ECS | Orals | CL4.1

Impact of soil moisture data assimilation on short-term numerical weather prediction 

Zdenko Heyvaert, Michel Bechtold, Jonas Mortelmans, Wouter Dorigo, and Gabriëlle De Lannoy

Land-atmosphere (LA) coupling describes the dynamic interaction between the Earth’s land surface and (the bottom of) the atmosphere. This coupling involves the exchange of energy, water, and momentum between the two systems and its strength varies depending on several factors (e.g., season, land cover, topography, and climate zone). Several metrics that quantify the strength of the LA coupling, both physical and statistical, have been developed and explored extensively in the literature.

Coupled systems that model the atmosphere, the land surface, and their interaction require an initialization of both the atmospheric and the land components. For the latter, a land surface model (LSM) is typically spun up in a so-called ‘offline’ manner, i.e., not coupled to the atmospheric model but forced by an atmospheric reanalysis product. So far, little research has focused on the potential impact of satellite-based soil moisture data assimilation (DA) during this spin-up period on the subsequent forecast by the coupled system. However, several studies in the land surface modeling community have demonstrated the potential benefit of soil moisture DA to improve estimates of hydrological variables and land surface fluxes in offline simulations.

In this study, soil moisture retrievals from the 36 km Soil Moisture Active/Passive (SMAP) Level 2 product are assimilated into the Noah-MP LSM with dynamic vegetation, forced by the MERRA-2 atmospheric reanalysis. This is done using a one-dimensional Ensemble Kalman Filter (EnKF) within the NASA Land Information System (LIS). The DA updates the moisture in each of the four soil layers of the LSM. The resulting land reanalysis provides consistent estimates of land surface variables and fluxes from 1 January 2016 through 31 December 2020 on an 18 km grid over the contiguous United States.

This land reanalysis is subsequently used to initialize the land component of an experiment where the Noah-MP LSM and the Weather Research & Forecasting (WRF) atmospheric model are coupled within the NASA Unified WRF (NU-WRF) framework. The atmospheric component is initialized with MERRA-2, which also serves as the boundary condition for the atmospheric model. We compare the results in terms of short-term atmospheric estimates (e.g., of evaporative fraction, growth of the planetary boundary layer, screen-level temperature and humidity) with an initialization that uses a purely model-based land spin-up. 

Our study allows the quantification of land DA impact during spin-up and the assessment of its relationship with the LA coupling strength. The results will provide important insights into where and when short-term atmospheric forecasts may benefit from assimilating satellite-based soil moisture retrievals.

How to cite: Heyvaert, Z., Bechtold, M., Mortelmans, J., Dorigo, W., and De Lannoy, G.: Impact of soil moisture data assimilation on short-term numerical weather prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20049, https://doi.org/10.5194/egusphere-egu24-20049, 2024.

The latest assessment report (AR6) of the Intergovernmental Panel on Climate Change includes a new element to climate research, i.e. the Interactive Atlas (IA), which is very useful for users from different sectors. As the new CMIP6 global climate model simulations use the brand-new SSP-scenarios paired with the RCP-scenarios, the latest climate change projections should be evaluated in order to update the regional and national adaptation strategies. Keeping this in mind we focused on Europe, with a special emphasis on Hungary in our study.

Our aim was to analyse the potential future changes of different temperature indices for Europe, in order to recognize spatial patterns and trends that may shape our climate in the second half of the 21st century. For this purpose, multi-model mean simulation data provided by the IPCC AR6 WG1 IA were downloaded on a monthly base. We chose two climate indices beside the mean temperature values, which represent temperature extremes, namely, the number of days with maximum temperature above 35 °C and the number of frost days (i.e. when daily minimum temperature is below 0 °C). We focused on the end of the 21st century (2081–2100) with also briefly considering the medium-term changes of the 2041–2060 period (both compared to the last two decades of the historical simulation period, i.e. 1995–2014 as the reference period). For both future periods we used all scenarios provided in the IA, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5.

Several zonal and meridional segments over the continent were defined, where we analysed the projected changes of the indices. The zonal segments provide an insight on two different effects that may induce spatial differences between future regional changes. (i) Continentality can be recognized as an increasing effect from the western parts of the segment towards the east. (ii) Topography also appears as the influence of mountains, plains, and basins emerge. The meridional segments provide information about the north-to-south differences as well, as the effects of sea cover. The changes in the indices are plotted on diagrams representing the different months, where the differences in the scenarios are also shown. These diagrams are compared to their respective landscape profiles, furthermore, statistical parameters were calculated. In addition, a monotony index was defined as the cumulative direction of differences between the neighbouring grid cells and analysed within the study.

Our results show that in the changes of mean temperature, both the zonal location and sea cover will play a key role in forming spatial differences within Europe. However, for the extreme temperature indices, topography and continentality are likely to become more dominant than sea cover, while the zonal location remains an important factor. 

Acknowledgements: This work was supported by the Hungarian National Research, Development and Innovation Fund [grant numbers PD138023, K-129162], and the National Multidisciplinary Laboratory for Climate Change [grant number RRF-2.3.1-21-2022-00014]. 

How to cite: Divinszki, F., Kis, A., and Pongrácz, R.: Analysing the projected monthly changes of temperature-related climate indices over Europe using zonal and meridional segments based on CMIP6 data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-389, https://doi.org/10.5194/egusphere-egu24-389, 2024.

EGU24-868 | ECS | Posters on site | CL4.3

Relationship of the predictability of North Pacific Mode and ENSO with predictability of PDO 

Jivesh Dixit and Krishna M. AchutaRao

PDO and ENSO are most prominent variability modes in the Pacific Ocean at decadal and interannual timescales respectively. Mutual independence between ENSO and PDO is questionable (Chen & Wallace, 2016). Linear combination of the first two orthogonal modes of SST variability in our Study Region (SR; 70oN - 20oS, 110oE - 90oW) i.e. mode 1 (interannual mode, we call it, IAM; ENSO like variability) and mode 2 (North Pacific Mode (NPM; Deser & Blackmon (1995)); a decadal mode) produces a PDO like variability (Chen & Wallace, 2016). It suggests that PDO is not independently hosted in the Pacific Ocean and can be represented by two linearly independent variability modes.

To produce credible and skillful climate information at multi-year to decadal timescales, Decadal Climate Prediction Project (DCPP), led by the Working Group on Subseasonal to Interdecadal Prediction (WGSIP), focuses on both the scientific and practical elements of forecasting climate by employing predictability research and retrospective analyses within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Component A under DCPP experiments concentrates on hindcast experiments to examine the prediction skill of participating models with respect to actual observations.

As linear combination of  IAM and NPM in SR produces PDO pattern and timescales efficiently, we compared the  ability of DCPP-A hindcasts to predict  IAM, NPM, and  PDO. In this analysis we use output from 9 models (a total of 128 ensemble members), initialised every year from 1960 to 2010. To produce the prediction skill estimates.

At lead year 1 from initialisation, the prediction of NPM,  IAM and PDO is quite skillful as the models are initialised with observations. In subsequent years, skill of either IAM or NPM or both drop significantly and that leads to drop in skill of predicted PDO index. Both the deterministic estimates and probabilistic estimates of prediction skill for DCPP hindcast experiments suggest that the ability of hindcast experiments to predict NPM governs the prediction skill to predict PDO index.

Keywords: PDO, ENSO, NPM, CMIP6, DCPP, hindcast

References

Chen, X., & Wallace, J. M. (2016). Orthogonal PDO and ENSO indices. Journal of Climate, 29(10), 3883–3892. https://doi.org/10.1175/jcli-d-15-0684.1

Deser, C., & Blackmon, M. L. (1995). On the Relationship between Tropical and North Pacific Sea Surface Temperature Variations. Journal of Climate, 8(6), 1677–1680. https://doi.org/10.1175/1520-0442(1995)008<1677:OTRBTA>2.0.CO;2

How to cite: Dixit, J. and AchutaRao, K. M.: Relationship of the predictability of North Pacific Mode and ENSO with predictability of PDO, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-868, https://doi.org/10.5194/egusphere-egu24-868, 2024.

EGU24-1757 | Posters on site | CL4.3

Is the NAO signal-to-noise paradox exacerbated by severe winter windstorms? 

Lisa Degenhardt, Gregor C. Leckebusch, Adam A. Scaife, Doug Smith, and Steve Hardiman

The signal-to-noise paradox is known to be a limitation in multiple seasonal and decadal forecast models where the model ensemble mean predicts observations better than individual ensemble members. This ‘paradox’ occurs for different parameters, like the NAO, temperature, wind speed or storm counts in multiple seasonal and decadal forecasts. However, investigations have not yet found the origin of the paradox. First hypotheses are that weak ocean – atmosphere coupling or a misrepresentation of eddy feedback in these models is responsible.

Our previous study found a stronger signal-to-noise error in windstorm frequency than for the NAO despite highly significant forecast skill. In combination with the underestimation of eddy feedback in multiple models, this led to the question: Might the signal-to-noise paradox over the North-Atlantic be driven by severe winter windstorms?

To assess this hypothesis, the signal-to-noise paradox is investigated in multiple seasonal forecast suites from the UK Met Office, ECMWF, DWD and CMCC. The NAO is used to investigate the changes in the paradox depending on the storminess of the season. The results show a significant increase of the NAO-signal-to-noise error in stormy seasons in GloSea5. Other individual models like the seasonal model of the DWD or CMCC do not show such a strong difference. A multi-model approach, on the other hand, shows the same tendency as GloSea5. Nevertheless, these model differences mean that more hindcasts are needed to conclusively demonstrate that the signal-to-noise error arises from Atlantic windstorms.

How to cite: Degenhardt, L., Leckebusch, G. C., Scaife, A. A., Smith, D., and Hardiman, S.: Is the NAO signal-to-noise paradox exacerbated by severe winter windstorms?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1757, https://doi.org/10.5194/egusphere-egu24-1757, 2024.

EGU24-1940 | ECS | Orals | CL4.3

Study of the Decadal Predictability of Mediterranean Sea Surface Temperature Based on Observations 

Xiaoqin Yan, Youmin Tang, and Dejian Yang

Sea surface temperature (SST) changes in the Mediterranean Sea have profound impacts on both the Mediterranean regions and remote areas. Previous studies show that the Mediterranean SST has significant decadal variability that is comparable with the Atlantic multidecadal variability (AMV). However, few studies have discussed the characteristics and sources of the decadal predictability of Mediterranean SST based on observations. Here for the first time we use observational datasets to reveal that the decadal predictability of Mediterranean SST is contributed by both external forcings and internal variability for both annual and seasonal means, except that the decadal predictability of the winter mean SST in the eastern Mediterranean is mostly contributed by only internal variability. Besides, the persistence of the Mediterranean SST is quite significant even in contrast with that in the subpolar North Atlantic, which is widely regarded to have the most predictable surface temperature on the decadal time scale. After the impacts of external forcings are removed, the average prediction time of internally generated Mediterranean SST variations is more than 10 years and closely associated with the multidecadal variability of the Mediterranean SST that is closely related to the accumulated North Atlantic Oscillation forcing.

How to cite: Yan, X., Tang, Y., and Yang, D.: Study of the Decadal Predictability of Mediterranean Sea Surface Temperature Based on Observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1940, https://doi.org/10.5194/egusphere-egu24-1940, 2024.

EGU24-3190 | ECS | Orals | CL4.3

Seasonal forecasting of the European North-West shelf seas: limits of winter and summer sea surface temperature predictability 

Jamie Atkins, Jonathan Tinker, Jennifer Graham, Adam Scaife, and Paul Halloran

The European North-West shelf seas (NWS) support economic interests and provide environmental services to several adjacent populous countries. Skilful seasonal forecasts of the NWS would be useful to support decision making. Here, we quantify the skill of an operational large-ensemble ocean-atmosphere coupled dynamical forecasting system (GloSea), as well as a benchmark persistence forecasting system, for predictions of NWS sea surface temperature (SST) at 2-4 months lead time in winter and summer. We also identify sources of- and limits to NWS SST predictability with a view to what additional skill may be available in the future. We find that GloSea NWS SST skill is generally high in winter and low in summer. Persistence of anomalies in the initial conditions contributes substantially to predictability. GloSea outperforms simple persistence forecasts, by adding atmospheric variability information, but only to a modest extent. Where persistence is low – for example in seasonally stratified regions – both GloSea and persistence forecasts show lower skill. GloSea skill can be degradeded by model deficiencies in the relatively coarse global ocean component, which lacks a tidal regime and likely fails to properly fine-scale NWS physics. However, using “near perfect atmosphere” tests, we show potential for improving predictability of currently low performing regions if atmospheric circulation forecasts can be improved, underlining the importance of development of atmosphere-ocean coupled models for NWS seasonal forecasting applications.

How to cite: Atkins, J., Tinker, J., Graham, J., Scaife, A., and Halloran, P.: Seasonal forecasting of the European North-West shelf seas: limits of winter and summer sea surface temperature predictability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3190, https://doi.org/10.5194/egusphere-egu24-3190, 2024.

EGU24-4538 | ECS | Orals | CL4.3

Statistical downscaling of extremes in seasonal predictions - a case study on spring frosts for the viticultural sector 

Sebastiano Roncoroni, Panos Athanasiadis, and Silvio Gualdi

Spring frost events occurring after budburst of grapevines can damage new shoots, disrupt plant growth and cause large economic losses to the viticultural sector. Frost protection practices encompass a variety of vineyard management actions across timescales, from seasonal to decadal and beyond. The cost-effectiveness of such measures depends on the availability of accurate predictions of the relevant climate hazards at the appropriate timescales.

In this work, we present a statistical downscaling method which predicts variations in the frequency of occurrence of spring frost events in the important winemaking region of Catalunya at the seasonal timescale. The downscaling method exploits the seasonal predictability associated with the predictable components of the atmospheric variability over the Euro-Atlantic region, and produces local predictions of frost occurrence at a spatial scale relevant to vineyard management.

The downscaling method is designed to address the specific needs highlighted by a representative stakeholder in the local viticultural sector, and is expected to deliver an actionable prototype climate service. The statistical procedure is developed in perfect prognosis mode: the method is trained with large-scale reanalysis data against a high-resolution gridded observational reference, and validated against multi-model seasonal hindcast predictions.

Our work spotlights the potential benefits of transferring climate predictability across spatial scales for the design and provision of usable climate information, particularly regarding extremes.

How to cite: Roncoroni, S., Athanasiadis, P., and Gualdi, S.: Statistical downscaling of extremes in seasonal predictions - a case study on spring frosts for the viticultural sector, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4538, https://doi.org/10.5194/egusphere-egu24-4538, 2024.

EGU24-4873 | ECS | Orals | CL4.3

Why does the Signal-to-Noise Paradox Exist in Seasonal Climate Predictability? 

Yashas Shivamurthy, Subodh Kumar Saha, Samir Pokhrel, Mahen Konwar, and Hemant Kumar Chaudhari

Skillful prediction of seasonal monsoons has been a challenging problem since the 1800s. However, significant progress has been made in Indian summer monsoon rainfall prediction in recent times, with skill scores reaching 0.6 and beyond, surpassing the estimated predictability limits. This phenomenon leads to what is known as the “Signal-to-noise Paradox.” To investigate this paradox, we utilized 52 ensemble member hindcast runs spanning 30 years.

Through the application of ANOVA and Mutual Information methods, we estimate the predictability limit globally. Notably, for the boreal summer rainfall season, the Indian subcontinent exhibited the paradox, among several other regions, while the Equatorial Pacific region, despite demonstrating high prediction skill, does not have the Signal-to-Noise paradox. We employed a novel approach to understand how sub-seasonal variability and their projection in association with predictors are linked to the paradoxical behavior of seasonal prediction skill.

We propose a new method to estimate predictability limits that is free from paradoxical phenomena and shows much higher seasonal predictability. This novel method provides valuable insights into the complex dynamics of monsoon prediction, thereby creating opportunities for expanded research and potential improvements in seasonal forecasting skill in the coming years.

How to cite: Shivamurthy, Y., Saha, S. K., Pokhrel, S., Konwar, M., and Chaudhari, H. K.: Why does the Signal-to-Noise Paradox Exist in Seasonal Climate Predictability?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4873, https://doi.org/10.5194/egusphere-egu24-4873, 2024.

EGU24-7134 | ECS | Orals | CL4.3

Towards the Predictability of Compound Dry and Hot Extremes through Complexity Science 

Ankit Agarwal and Ravikumar Guntu

Compound Dry and Hot Extremes (CDHE) have an adverse impact on socioeconomic factors during the Indian summer monsoon, and a future exacerbation is anticipated. The occurrence of CDHE is influenced by teleconnections, which play a crucial role in determining its likelihood on a seasonal scale. Despite the importance, there is a lack of studies unravelling the teleconnections of CDHE in India. Previous investigations specifically focused on teleconnections between precipitation, temperature, and climate indices. Hence, there is a need to unravel the teleconnections of CDHE. This study presents a framework combining event coincidence analysis (ECA) with complexity science. ECA evaluates the synchronization between CDHE and climate indices. Subsequently, complexity science is utilized to construct a driver-CDHE network to identify the critical drivers of CDHE. A logistic regression model is employed to evaluate the proposed drivers' effectiveness. The occurrence of CDHE exhibits distinct patterns from July to September when considering intra-seasonal variability. Our findings contribute to the identification of drivers associated with CDHE. The primary driver for Eastern, Western India and Central India is the indices in the Pacific Ocean and Atlantic Ocean, respectively, followed by the indices in the Indian Ocean. These identified drivers outperform the traditional Niño 3.4-based predictions. Overall, our results demonstrate the effectiveness of integrating ECA and complexity science to enhance the prediction of CDHE occurrences.

How to cite: Agarwal, A. and Guntu, R.: Towards the Predictability of Compound Dry and Hot Extremes through Complexity Science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7134, https://doi.org/10.5194/egusphere-egu24-7134, 2024.

EGU24-8028 | ECS | Orals | CL4.3

Constraining near to mid-term climate projections by combining observations with decadal predictions 

Rémy Bonnet, Julien Boé, and Emilia Sanchez

The implementation of adaptation policies requires seamless and relevant information on the evolution of the climate over the next decades. Decadal climate predictions are subject to drift because of intrinsic model errors and their skill may be limited after a few years or even months depending on the region. Non-initialized ensembles of climate projections have large uncertainties over the next decades, encompassing the full range of uncertainty attributed to internal climate variability. Providing the best climate information over the next decades is therefore challenging. Recent studies have started to address this challenge by constraining uninitialized projections of sea surface temperature using decadal predictions or using a storyline approach to constrain uninitialized projections of the Atlantic Meridional Overturning Circulation using observations. Here, using a hierarchical clustering method, we select a sub-ensemble of non-initialized climate simulations based on their similarity to observations. Then, we try to further refine this sub-ensemble of trajectories by selecting a subset based on its consistency with decadal predictions. This study presents a comparison of these different methods for constraining surface temperatures in the North-Atlantic / Europe region over the next decades, focusing on CMIP6 non-initialized simulations.

How to cite: Bonnet, R., Boé, J., and Sanchez, E.: Constraining near to mid-term climate projections by combining observations with decadal predictions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8028, https://doi.org/10.5194/egusphere-egu24-8028, 2024.

EGU24-9049 | Posters on site | CL4.3

Constraining internal variability in CMIP6 simulations to provide skillful near-term climate predictions 

Rashed Mahmood, Markus G. Donat, Pablo Ortega, and Francisco Doblas-Reyes

Adaptation to climate change requires accurate and reliable climate information on decadal and multi-decadal timescales. Such near-term climate information is obtained from future projection simulations, which are strongly affected by uncertainties related to, among other things, internal climate variability. Here we present an approach to constrain variability in future projection simulations of the coupled model intercomparison project phase 6 (CMIP6). The constraining approach involves phasing in the simulated with the observed climate state by evaluating the area-weighted spatial pattern correlations of sea surface temperature (SST) anomalies in individual members and observations. The constrained ensemble, based on the top ranked members in terms of pattern correlations with observed SST anomalies, shows significant added value over the unconstrained ensemble in predicting surface temperature 10 and also 20 years  after the synchronization with observations, thus extending the forecast range of the standard initialised predictions. We also find that while the prediction skill of the constrained ensemble for the first ten years is similar to the initialized decadal predictions, the added value against the unconstrained ensemble extends over more regions than the decadal predictions. In addition, the constraining approach can also be used to attribute predictability of regional and global climate variations to regional SST variability.

How to cite: Mahmood, R., G. Donat, M., Ortega, P., and Doblas-Reyes, F.: Constraining internal variability in CMIP6 simulations to provide skillful near-term climate predictions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9049, https://doi.org/10.5194/egusphere-egu24-9049, 2024.

There is an ongoing discussion about the contributions from forced and natural sources to the Atlantic Multi-decadal Variability (AMV).  As the AMV influences the general climate in large regions, this question has important consequences for climate predictions on decadal timescales and for a robust estimation of the influence of climate forcings.

Here, we investigate the Atlantic Multi-decadal Variability (AMV) in observations and in a large CMIP6 historical climate model ensemble. We compare three different definitions of the AMV aimed at extracting the variability intrinsic to the Atlantic region. These definitions are based on removing from the Atlantic temperature the non-linear trend, the part congruent to the global average, or the part congruent to the multi-model ensemble mean of the global average. The considered AMV definitions agree on the well-known low-frequency oscillatory variability in observations, but show larger differences for the models. In general, large differences between ensemble members are found.

We estimate the forced response in the AMV as the mean of the large multi-model ensemble.  The forced response resembles the observed low-frequency oscillatory variability for the detrended AMV definition, but this definition is also the most inefficient in removing the forced global mean signal. The forced response is very weak for the other definitions and only few of their individual ensemble members show oscillatory variability and, if they do, not with the observed phase.

The observed spatial temperature pattern related to the AMV is well captured for all three AMV definitions, but with some differences in the spatial extent. The observed instantaneous connection between NAO and AMV is well represented in the models for all AMV definitions. Only non-significant evidence of NAO leading the AMV on decadal timescales is found.

How to cite: Christiansen, B., Yang, S., and Drews, A.: The Atlantic Multi-decadal Variability in observations and in a large historical multi-model ensemble: Forced and internal variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9100, https://doi.org/10.5194/egusphere-egu24-9100, 2024.

EGU24-9274 | ECS | Orals | CL4.3 | Highlight

The Role of the North Atlantic for Heat Wave Characteristics in Europe 

Sabine Bischof, Robin Pilch Kedzierski, Martje Hänsch, Sebastian Wahl, and Katja Matthes

The recent severe European summer heat waves of 2015 and 2018 co-occurred with cold subpolar North Atlantic (NA) sea surface temperatures (SSTs). However, a significant connection between this oceanic state and European heat waves was not yet established.

We investigate the effect of cold subpolar NA SSTs on European summer heat waves using two 100-year long AMIP-like model experiments: one that employs the observed global 2018 SST pattern as a boundary forcing and a counter experiment for which we removed the negative NA SST anomaly from the 2018 SST field, while preserving daily and small-scale SST variabilities. Comparing these experiments, we find that cold subpolar NA SSTs significantly increase heat wave duration and magnitude downstream over the European continent. Surface temperature and circulation anomalies are connected by the upper-tropospheric summer wave pattern of meridional winds over the North Atlantic European sector, which is enhanced with cold NA SSTs. Our results highlight the relevance of the subpolar NA region for European summer conditions, a region that is marked by large biases in current coupled climate model simulations.

How to cite: Bischof, S., Pilch Kedzierski, R., Hänsch, M., Wahl, S., and Matthes, K.: The Role of the North Atlantic for Heat Wave Characteristics in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9274, https://doi.org/10.5194/egusphere-egu24-9274, 2024.

EGU24-9690 | ECS | Orals | CL4.3

Hybrid statistical-dynamical seasonal prediction of summer extreme temperatures over Europe 

Luca Famooss Paolini, Paolo Ruggieri, Salvatore Pascale, Erika Brattich, and Silvana Di Sabatino

Several studies show that the occurrence of summer extreme temperatures over Europe is increased since the middle of the twentieth century and is expected to further increase in the future due to global warming (Seneviratne et al., 2021). Thus, predicting heat extremes several months ahead is crucial given their impacts on socio-economic and environmental systems.

In this context, state-of-the-art dynamical seasonal prediction systems (SPSs) show low skills in predicting European heat extremes on seasonal timescale, especially in central and northern Europe (Prodhomme et al., 2022). However, recent studies have shown that our skills in predicting extratropical climate can be largely improved by subsampling the dynamical SPS ensemble with statistical post-processing techniques (Dobrynin et al., 2022).

This study assesses if the seasonal prediction skill of summer extreme temperatures in Europe in the state-of-the-art dynamical SPSs can be improved through subsampling. Specifically, we use a multi-model ensemble (MME) of SPSs contributing to the Copernicus Climate Change Service (C3S), analysing di hindcast period 1993—2016. The MME is subsampled by retaining a subset of members that predict the phase of the North Atlantic Oscillation (NAO) and the Eastern Atlantic (EA), typically linked to summer extreme temperatures in Europe. The subsampling relies on spring predictors of the weather regimes and thus allows us to retain only those ensemble members with a reasonable representation of summer heat extreme teleconnections.

Results show that by retaining only those ensemble members that accurately represent the NAO phase, it not only enhances the seasonal prediction skills for the summer European climate but also leads to improved predictions of summer extreme temperatures, especially in central and northern Europe. Differently, selecting only those ensemble members that accurately represent the EA phase does not improve either the predictions of summer European climate or the predictions of summer extreme temperatures. This can be explained by the fact that the C3S SPSs exhibits deficiencies in accurately representing the summer low-frequency atmospheric variability.

Bibliography

Dobrynin, M., and Coauthors, 2018: Improved Teleconnection-Based Dynamical Seasonal Predictions of Boreal Winter. Geophysical Research Letters, 45 (8), 3605—3614, https://doi.org/10.1002/2018GL07720

Prodhomme, C., S. Materia, C. Ardilouze, R. H. White, L. Batté, V. Guemas, G. Fragkoulidis, and J. Garcìa-Serrano, 2022: Seasonal prediction of European summer heatwaves. Climate Dynamics, 58 (7), 2149—2166, https://doi.org/10.1007/s00382-021-05828-3

Seneviratne, S., and Coauthors, 2021: Weather and Climate Extreme Events in a Changing Climate, chap. 11, 1513—1766. Cambridge University Press, https://doi.org/10.1017/9781009157896.013

How to cite: Famooss Paolini, L., Ruggieri, P., Pascale, S., Brattich, E., and Di Sabatino, S.: Hybrid statistical-dynamical seasonal prediction of summer extreme temperatures over Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9690, https://doi.org/10.5194/egusphere-egu24-9690, 2024.

EGU24-9905 | ECS | Orals | CL4.3

Optimization-based driver detection and prediction of seasonal heat extremes 

Ronan McAdam, César Peláez Rodríguez, Felicitas Hansen, Jorge Pérez Aracil, Antonello Squintu, Leone Cavicchia, Eduardo Zorita, Sancho Saldez-Sanz, and Enrico Scoccimarro

As a consequence of limited reliability of dynamical forecast systems, particularly over Europe, efforts in recent years have turned to exploiting the power of Machine Learning methods to extract information on drivers of extreme temperature from observations and reanalysis. Meanwhile, the diverse impacts of extreme heat have driven development of new indicators which take into account nightime temperatures and humidity. In the H2020 CLimate INTelligence (CLINT) project, a feature selection framework is being developed to find the combination of drivers which provides optimal seasonal forecast skill of European summer heatwave indicators. Here, we present the methodology, its application to a range of heatwave indicators and forecast skill compared to existing dynamical systems. First, a range of (reduced-dimensionality) drivers are defined, including k-means clusters of variables known to impact European summer (e.g. precipitation, sea ice content), and more complex indices like the NAO and weather regimes. Then, these drivers are used to train machine learning based prediction models, of varying complexity, to predict seasonal indicators of heatwave occurrence and intensity. A crucial and novel step in our framework is the use of the Coral Reef Optimisation algorithm, used to select the variables and their corresponding lag times and time periods which provide optimal forecast skill. To maximise training data, both ERA5 reanalysis and a 2000-year paleo-simulation are used; the representation of heatwaves and atmospheric conditions are validated with respect to ERA5. We present comparisons of forecast skill to the dynamical Copernicus Climate Change Service seasonal forecasts systems. The differences in timing, predictability and drivers of daytime and nighttime heatwaves across Europe are highlighted. Lastly, we discuss how the framework can easily be adapted to other extremes and timescales.



How to cite: McAdam, R., Peláez Rodríguez, C., Hansen, F., Pérez Aracil, J., Squintu, A., Cavicchia, L., Zorita, E., Saldez-Sanz, S., and Scoccimarro, E.: Optimization-based driver detection and prediction of seasonal heat extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9905, https://doi.org/10.5194/egusphere-egu24-9905, 2024.

EGU24-10539 | ECS | Orals | CL4.3

Exploring multiyear-to-decadal North Atlantic sea level predictability using machine learning and analog methods 

Qinxue Gu, Liwei Jia, Liping Zhang, Thomas Delworth, Xiaosong Yang, Fanrong Zeng, and Shouwei Li

Long-term sea level rise and multiyear-to-decadal sea level variations pose substantial risks of flooding and erosion in coastal communities. The North Atlantic Ocean and the U.S. East Coast are hotspots for sea level changes under current and future climates. Here, we employ a machine learning technique, a self-organizing map (SOM)-based framework, to systematically characterize the North Atlantic sea level variability, assess sea level predictability, and generate sea level predictions on multiyear-to-decadal timescales. Specifically, we classify 5000-year North Atlantic sea level anomalies from the Seamless System for Prediction and EArth System Research (SPEAR) model control simulations into generalized patterns using SOM. Preferred transitions among these patterns are further identified, revealing long-term predictability on multiyear-to-decadal timescales related to shifts in Atlantic meridional overturning circulation (AMOC) phases. By combining the SOM framework with “analog” techniques based on the simulations and observational/reanalysis data, we demonstrate prediction skill of large-scale sea level patterns comparable to that from initialized hindcasts. Moreover, additional source of short-term predictability is identified after the exclusion of low-frequency AMOC signals, which arises from the wind-driven North Atlantic tripole mode triggered by the North Atlantic Oscillation. This study highlights the potential of machine learning methods to assess sources of predictability and to enable efficient, long-term climate prediction.

How to cite: Gu, Q., Jia, L., Zhang, L., Delworth, T., Yang, X., Zeng, F., and Li, S.: Exploring multiyear-to-decadal North Atlantic sea level predictability using machine learning and analog methods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10539, https://doi.org/10.5194/egusphere-egu24-10539, 2024.

The inter-annual to multi-decadal variability of recurrent, synoptic-scale atmospheric circulation patterns in the Northern Hemisphere extratropics, as represented by the Jenkinson-Collison classification scheme, is explored in reanalysis data spanning the entire 20th century, and in global climate model (GCM) data from the historical, AMIP and DCPP experiments conducted within the framework of CMIP6. The aim of these efforts is to assess the effect of coupled vs. uncoupled and initialised vs. non-initialized GCM simulations in reproducing the observed low-frequency variability of the aforementioned circulation patterns.

Results reveal that the observed annual counts of typical recurrent weather patterns, such as cyclonic or anticyclonic conditions and also situations of pronounced advection, exhibit significant oscillations on multiple time-scales ranging between several years and several decades. The period of these oscillations, however, is subject to large regional variations. This is in line with earlier studies suggesting that the extratropical atmospheric circulation’s low frequency variability is essentially unforced, except in the Pacific-North American sector where the forced variability is enhanced due to ENSO teleconnections. Neither the periods obtained from historical nor those obtained from AMIP experiments align with observations. Likewise, not even the periods obtained from different runs of the same GCM and experiment correspond to each other. Thus, in an non-initialized model setup, ocean-atmosphere coupling or the lack thereof essentially leads to the same results. Whether initialization and/or augmenting the ensemble size can improve these findings, will also be discussed.

Acknowledgement: This work is part of project Impetus4Change, which has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101081555.

How to cite: Brands, S., Cimadevilla, E., and Fernández, J.: Low-frequency variability of synoptic-scale atmospheric circulation patterns in the Northern Hemisphere extratropics and associated hindcast skill of decadal forecasting systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10551, https://doi.org/10.5194/egusphere-egu24-10551, 2024.

EGU24-10574 | Orals | CL4.3 | Highlight

Will 2024 be the first year above 1.5 C? 

Nick Dunstone, Doug Smith, Adam Scaife, Leon Hermanson, Andrew Colman, and Chris Folland

Global mean surface temperature is the key metric by which our warming climate is monitored and for which international climate policy is set. At the end of each year the Met Office makes a global mean temperature forecast for the coming year. Following on from the new record 2023, we predict a high probability of another record year in 2024 and a 35% chance of exceeding 1.5 C above pre-industrial. Whilst a one-year temporary exceedance of 1.5 C would not constitute a breech of the Paris Agreement target, our forecast highlights how close we are now to breeching this target. We show that our 2024 forecast can be largely explained by the combination of the continuing warming trend of +0.2 C/decade and the lagged warming affect of a strong tropical Pacific El Nino event. We further highlight 2023 was significantly warmer than forecast and that much of this warming signal came from the southern hemisphere and requires further understanding.

How to cite: Dunstone, N., Smith, D., Scaife, A., Hermanson, L., Colman, A., and Folland, C.: Will 2024 be the first year above 1.5 C?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10574, https://doi.org/10.5194/egusphere-egu24-10574, 2024.

EGU24-11485 | ECS | Orals | CL4.3

Summer drought predictability in the Mediterranean region in seasonal forecasts 

Giada Cerato, Katinka Bellomo, and Jost von Hardenberg

The Mediterranean region has been identified as an important climate change hotspot, over the 21st century both air temperature and its extremes are projected to rise at a rate surpassing that of the global average and a significant decrease of average summer precipitation is projected, particularly for the western Mediterranean. On average, Mediterranean droughts have become more frequent and intense in recent years and are expected to become more widespread in many regions. These prolonged dry spells pose a substantial threat to agriculture and impact several socio-economic sectors. In this context, long-range weather forecasting has emerged as a promising tool for seasonal drought risk assessment. However, the interpretation of the forecasting products is not always straightforward due to their inherent probabilistic nature. Therefore, a rigorous evaluation process is needed to determine the extent to which these forecasts provide a fruitful advantage over much simpler forecasting systems, such as those based on climatology. 

In this study, we use the latest version of ECMWF’s seasonal prediction system (SEAS5) to understand its skill in predicting summer droughts. The Standardized Precipitation Evapotranspiration Index (SPEI) aggregated over different lead times is employed to mark below-normal dryness conditions in August. We use a comprehensive set of evaluation metrics to gain insight into the accuracy, systematic biases, association, discrimination and sharpness of the forecast system. Our findings reveal that up to 3 months lead time, seasonal forecasts show stronger association and discrimination skills than the climatological forecast, especially in the Southern Mediterranean, although the prediction quality in terms of accuracy and sharpness is limited. On the other hand, extending the forecast range up to 6 months lead time dramatically reduces its predictability skill, with the system mostly underperforming elementary climatological predictions. 

This approach is then extended to examine the full ensemble of seasonal forecasting systems provided by the Copernicus Climate Change Service (C3S) to test their skill in predicting droughts. Our findings can help an informed use of seasonal forecasts of droughts and the development of related climate services.

How to cite: Cerato, G., Bellomo, K., and von Hardenberg, J.: Summer drought predictability in the Mediterranean region in seasonal forecasts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11485, https://doi.org/10.5194/egusphere-egu24-11485, 2024.

EGU24-11930 | ECS | Posters on site | CL4.3

A global empirical system for probabilistic seasonal climate prediction based on generative AI and CMIP6 models  

Lluís Palma, Alejandro Peraza, Amanda Duarte, David Civantos, Stefano Materia, Arijit Nandi, Jesús Peña-Izquierdo, Mihnea Tufis, Gonzalo Vilella, Laia Romero, Albert Soret, and Markus Donat

Reliable probabilistic information at the seasonal time scale is essential across various societal sectors, such as agriculture, energy, or water management. Current applications of seasonal predictions rely on General Circulation Models (GCMs) that represent dynamical processes in the atmosphere, land surface, and ocean while capturing their linear and nonlinear interactions. However, GCMs come with an inherent high computational cost. In an operational setup, they are typically run once a month and at a lower temporal and spatial resolution than the ones needed for regional applications. Moreover, GCMs suffer from significant drifts and biases and can miss relevant teleconnections, resulting in low skill for particular regions or seasons. 

In this context, the use of generative AI methods that can model complex nonlinear relationships can be a viable alternative for producing probabilistic predictions with low computational demand. Such models have already demonstrated their effectiveness in different domains, i.e. computer vision, natural language processing, and weather prediction. However, although requiring less computational power, these techniques still rely on big datasets in order to be efficiently trained. Under this scenario, and with sufficiently high-quality global observational datasets spanning at most 70 years, the research trend has evolved into training these models using climate model output. 

In this work, we build upon the work presented by Pan et al., 2022, which introduced a conditional Variational Autoencoder (cVAE) to predict global temperature and precipitation fields for the October to March season starting from July initial conditions. We adopt several pre-processing changes to account for different biases and trends across the CMIP6 models. Additionally, we explore different architecture modifications to improve the model's performance and stability. We study the benefits of our model in predicting three-month anomalies on top of the climate change trend. Finally, we compare our results with a state-of-the-art GCM (SEAS5) and a simple empirical system based on the linear regression of classical seasonal indices based on Eden et al., 2015.

 

Pan, Baoxiang, Gemma J. Anderson, André Goncalves, Donald D. Lucas, Céline J.W. Bonfils, and Jiwoo Lee. 'Improving Seasonal Forecast Using Probabilistic Deep Learning'. Journal of Advances in Modeling Earth Systems 14, no. 3 (1 March 2022). https://doi.org/10.1029/2021MS002766.


Eden, J. M., G. J. van Oldenborgh, E. Hawkins, and E. B. Suckling. 'A Global Empirical System for Probabilistic Seasonal Climate Prediction'. Geoscientific Model Development 8, no. 12 (11 December 2015): 3947–73. https://doi.org/10.5194/gmd-8-3947-2015.

How to cite: Palma, L., Peraza, A., Duarte, A., Civantos, D., Materia, S., Nandi, A., Peña-Izquierdo, J., Tufis, M., Vilella, G., Romero, L., Soret, A., and Donat, M.: A global empirical system for probabilistic seasonal climate prediction based on generative AI and CMIP6 models , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11930, https://doi.org/10.5194/egusphere-egu24-11930, 2024.

EGU24-12969 | ECS | Orals | CL4.3

How unusual is the recent decade-long pause in Arctic summer sea ice retreat? 

Patricia DeRepentigny, François Massonnet, Roberto Bilbao, and Stefano Materia

The Earth has warmed significantly over the past 40 years, and the fastest rate of warming has occurred in and around the Arctic. The warming of northern high latitudes at a rate of almost four times the global average (Rantanen et al., 2022), known as Arctic amplification, is associated with sea ice loss, glacier retreat, permafrost degradation, and expansion of the melting season. Since the mid-2000s, summer sea ice has exhibited a rapid decline, reaching record minima in September sea ice area in 2007 and 2012. However, after the early 2010s, the downward trend of minimum sea ice area appears to decelerate (Swart et al., 2015; Baxter et al., 2019). This apparent slowdown and the preceding acceleration in the rate of sea ice loss are puzzling in light of the steadily increasing rate of greenhouse gas emissions of about 4.5 ppm yr−1 over the past decade (Friedlingstein et al., 2023) that provides a constant climate forcing. Recent studies suggest that low-frequency internal climate variability may have been as important as anthropogenic influences on observed Arctic sea ice decline over the past four decades (Dörr et al., 2023; Karami et al., 2023). Here, we investigate how unusual this decade-long pause in Arctic summer sea ice decline is within the context of internal climate variability. To do so, we first assess how rare this is deceleration of Arctic sea ice loss is by comparing it to trends in CMIP6 historical simulations. We also use simulations from the Decadal Climate Prediction Project (DCPP) contribution to CMIP6 to determine if initializing decadal prediction systems from estimates of the observed climate state substantially improves their performance in predicting the slowdown in Arctic sea ice loss over the past decade. As the DCPP does not specify the data or the methods to be used to initialize forecasts or how to generate ensembles of initial conditions, we also assess how different formulations affect the skill of the forecasts by analyzing differences between models. This work provides an opportunity to attribute this pause in Arctic sea ice retreat to interannual internal variability or radiative external forcings, something that observation analysis alone cannot achieve.

How to cite: DeRepentigny, P., Massonnet, F., Bilbao, R., and Materia, S.: How unusual is the recent decade-long pause in Arctic summer sea ice retreat?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12969, https://doi.org/10.5194/egusphere-egu24-12969, 2024.

EGU24-14341 | Posters on site | CL4.3

Compound Heat and Dry Events Influenced by the Pacific–Japan Pattern over Taiwan in Summer 

Szu-Ying Lin, Wan-Ling Tseng, Yi-Chi Wang, and MinHui Lo

Compound dry and hot events, characterized by elevated temperatures and reduced precipitation, pose interconnected challenges to human social economics, necessitating comprehensive strategies for mitigation and adaptation. This study focuses on the Pacific-Japan (PJ) pattern, a significant climate variability influencing summer climates in East Asia. While previous research has explored its impact on Japan and Korea, our investigation delves into its effects on Taiwan, a mountainous subtropical island with a population of approximately 24 million. Utilizing long-term temperature and rainfall data, along with reanalysis dynamic downscaling datasets, we examine the interannual impacts of the PJ pattern on summer temperature and compound heat and dry events. Our findings reveal a significant temperature increase during the positive phase of the PJ pattern, characterized by anticyclonic anomalous circulation over Taiwan. Additionally, both the Standardized Precipitation Index and soil water exhibit a decline during this phase, reflecting meteorological and hydrological drought conditions. A robust negative correlation (-0.7) between drought indices and temperature emphasizes the compound effect of heat and dry events during the PJ positive phase. This study enhances the understanding of the PJ pattern as a climate driver, describing its role in hot and dry summers over Taiwan. The insights gained, when integrated into seasonal prediction and early warning systems, can aid vulnerable sectors in preparing for potential heat and dry stress hazards.

How to cite: Lin, S.-Y., Tseng, W.-L., Wang, Y.-C., and Lo, M.: Compound Heat and Dry Events Influenced by the Pacific–Japan Pattern over Taiwan in Summer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14341, https://doi.org/10.5194/egusphere-egu24-14341, 2024.

EGU24-14379 | Posters on site | CL4.3

Linkage between Temperature and Heatwaves in Summer Taiwan to the Pacific Meridional Mode 

Chieh-Ting Tsai, Wan-Ling Tseng, and Yi-Chi Wang

Over the past century, Taiwan has gradually recognized the hazards posed by extreme heat events (EHT), prompting the development of mid-term adaptation strategies to address challenges in the coming decades. However, our understanding of decadal-scale temperature variations remains insufficient, requiring further research into influencing factors. Our study reveals the crucial role of the Pacific Meridional Mode (PMM) in modulating decadal-scale variations in summer temperatures in Taiwan. During the positive phase of PMM, warm sea surface temperature anomalies trigger an eastward-moving wave train extending into East Asia. This leads to the development of high-pressure circulations near Southeast Asia and Taiwan, enhancing the temperature increase. This mechanism has been reproduced in experiments using the Taiwan Earth System Model. Moreover, our study utilizes the calendar day 90th percentile of maximum temperature (CTX) as the threshold for extreme high-temperature events (EHT), while also employing the heatwaves magnitude scale (HWMS) as the criterion for defining heatwaves. During the positive phase of PMM, the frequency and duration of EHT increase, with variations observed across different regions. The overall intensity of heatwave events also strengthens, primarily due to extended durations. Notably, in a single city, this results in exposure of up to 800,000 person-days to EHT, presenting a tenfold increase compared to the annual effect observed in the long-term warming trend. These findings on the decadal-scale relationship between summer temperatures in Taiwan and PMM contribute to a deeper understanding of EHT and heatwaves events impacts, providing more nuanced insights for future regional strategies in mitigating heatwave disasters.

How to cite: Tsai, C.-T., Tseng, W.-L., and Wang, Y.-C.: Linkage between Temperature and Heatwaves in Summer Taiwan to the Pacific Meridional Mode, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14379, https://doi.org/10.5194/egusphere-egu24-14379, 2024.

EGU24-14688 | ECS | Orals | CL4.3

Exploring ML-based decadal predictions of the German Bight storm surge climate 

Daniel Krieger, Sebastian Brune, Johanna Baehr, and Ralf Weisse

Storm surges and elevated water levels regularly challenge coastal protection and inland water management along the low-lying coastline of the German Bight. Skillful seasonal-to-decadal (S2D) predictions of the local storm surge climate would be beneficial to stakeholders and decision makers in the region. While storm activity has recently been shown to be skillfully predictable on a decadal timescale with a global earth system model, surge modelling usually requires very fine spatial and temporal resolutions that are not yet present in current earth system models. We therefore propose an alternative approach to generating S2D predictions of the storm surge climate by training a neural network on observed water levels and large-scale atmospheric patterns, and apply the neural network to the available model output of a S2D prediction system. We show that the neural-network-based translation from large-scale atmospheric fields to local water levels at the coast works sufficiently well, and that several windows of predictability for the German Bight surge climate emerge on the S2D scale.

How to cite: Krieger, D., Brune, S., Baehr, J., and Weisse, R.: Exploring ML-based decadal predictions of the German Bight storm surge climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14688, https://doi.org/10.5194/egusphere-egu24-14688, 2024.

Atlantic meridional overturning circulation (AMOC) is one of the mechanisms for climate predictability and one of the properties that decadal climate predictions are attempting to predict. The starting point for AMOC decadal predictions is sensitive to the underlying data assimilation and/or initialization procedure. This means that different choices during the data assimilation procedure (e.g., assimilation method, assimilation window, data sources, resolution, nudging terms and strength, full field vs anomaly initialization/assimilation, etc) can result in a different mean and even variability of reconstructed ocean circulation. How coherent the AMOC initial states should be among the CMIP-like decadal prediction experiments? How good in general should the initial AMOC be for decadal predictions? And do initialization issues of the ocean circulation influence the prediction skill of other variables that are of interest for application studies? These are the questions that we were attempting to address in our study, where we analyzed twelve decadal prediction systems from the World Meteorological Organization Lead Centre for Annual-to-Decadal Climate Prediction project. We identify that the AMOC initialization influences the quality of predictions of the subpolar gyre (SPG). When predictions show a large initial error in their AMOC, they usually have low skill for predicting the internal variability of the SPG five years after the initialization.

How to cite: Polkova, I. and the Co-Authors: Initialization shock in the ocean circulation reduces skill in decadal predictions of the North Atlantic subpolar gyre, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15358, https://doi.org/10.5194/egusphere-egu24-15358, 2024.

EGU24-15476 | Posters on site | CL4.3

Statistics of sudden stratospheric warmings using a large model ensemble 

Sarah Ineson, Nick Dunstone, Adam Scaife, Martin Andrews, Julia Lockwood, and Bo Pang

Using a large ensemble of initialised retrospective forecasts (hindcasts) from a seasonal prediction system, we explore various statistics relating to sudden stratospheric warmings (SSWs). Observations show that SSWs occur at a similar frequency during both El Niño and La Niña northern hemisphere winters. This is contrary to expectation, as the stronger stratospheric polar vortex associated with La Niña years might be expected to result in fewer of these extreme breakdowns. We show that this similar frequency may have occurred by chance due to the limited sample of years in the observational record. We also show that in these hindcasts, winters with two SSWs, a rare event in the observational record, on average have an increased surface impact. Multiple SSW events occur at a lower rate than expected if events were independent but somewhat surprisingly, our analysis also indicates a risk, albeit small, of winters with three or more SSWs, as yet an unseen event.

How to cite: Ineson, S., Dunstone, N., Scaife, A., Andrews, M., Lockwood, J., and Pang, B.: Statistics of sudden stratospheric warmings using a large model ensemble, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15476, https://doi.org/10.5194/egusphere-egu24-15476, 2024.

EGU24-15709 | ECS | Orals | CL4.3

Predicting Atlantic and Benguela Niño events with deep learning  

Marie-Lou Bachelery, Julien Brajard, Massimiliano Patacchiola, and Noel Keenlyside

Extreme Atlantic and Benguela Niño events continue to significantly impact the tropical Atlantic region, with far-reaching consequences for African climate and ecosystems. Despite attempts to forecast these events using traditional seasonal forecasting systems, success remains low, reinforcing the growing idea that these events are unpredictable. To overcome the limitations of dynamical prediction systems, we introduce a deep learning-based statistical prediction model for Atlantic and Benguela Niño events. Our convolutional neural network (CNN) model, trained on 90 years of reanalysis data incorporating surface and 100m-averaged temperature variables, demonstrates the capability to forecast the Atlantic and Benguela Niño indices with lead times of up to 3-4 months. Notably, the CNN model excels in forecasting peak-season events with remarkable accuracy extending up to 5 months ahead. Gradient sensitivity analysis reveals the ability of the CNN model to exploit known physical precursors, particularly the connection to equatorial dynamics and the South Atlantic Anticyclone, for accurate predictions of Benguela Niño events. This study challenges the perception of the Tropical Atlantic as inherently unpredictable, underscoring the potential of deep learning to enhance our understanding and forecasting of critical climate events. 

How to cite: Bachelery, M.-L., Brajard, J., Patacchiola, M., and Keenlyside, N.: Predicting Atlantic and Benguela Niño events with deep learning , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15709, https://doi.org/10.5194/egusphere-egu24-15709, 2024.

EGU24-15974 | ECS | Posters virtual | CL4.3

Recalibrating DWD’s operational climate predictions: towards a user-oriented seamless climate service 

Alexander Pasternack, Birgit Mannig, Andreas Paxian, Amelie Hoff, Klaus Pankatz, Philip Lorenz, and Barbara Früh

The German Meteorological Service's (Deutscher Wetterdienst DWD) climate predictions website  (www.dwd.de/climatepredictions) offers a centralized platform for accessing post-processed climate predictions, including subseasonal forecasts from ECMWF's IFS and seasonal and decadal predictions from the German climate prediction system. The website design was developed in collaboration with various sectors to ensure uniformity across all time frames, and users can view maps, tables, and time series of ensemble mean and probabilistic predictions in combination with their skill. The available data covers weekly, 3-month, 1-year, and 5-year temperature means, precipitation sums and soil moisture for the world, Europe, Germany, and particular German regions. To achieve high spatial resolution, the DWD used the statistical downscaling method EPISODES. Moreover, within the BMBF project KIMoDIs (AI-based monitoring, data management and information system for coupled forecasting and early warning of low groundwater levels and salinisation) the DWD provides climate prediction data of further hydrological variables (e.g. relative humidity) with corresponding prediction skill on a regional scale.

However, all predictions on these time scales can suffer from inherent systematic errors, which can impact their usefulness. To address these issues, the recalibration method DeFoReSt was applied to decadal predictions, using a combination of 3rd order polynomials in lead and start time, along with a boosting model selection approach. This approach addresses lead-time dependent systematic errors, such as drift, as well as inaccuracies in representing long-term changes and variability.

This study highlights the improved accuracy of the recalibration approach on decadal predictions due to an increased polynomial order compared to the original approach, and its different impact on global and regional scales. It also explores the feasibility of transferring this approach to predictions with shorter time horizons of the provided variables.

How to cite: Pasternack, A., Mannig, B., Paxian, A., Hoff, A., Pankatz, K., Lorenz, P., and Früh, B.: Recalibrating DWD’s operational climate predictions: towards a user-oriented seamless climate service, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15974, https://doi.org/10.5194/egusphere-egu24-15974, 2024.

EGU24-16366 | ECS | Orals | CL4.3

Decadal predictions outperform projections in forecasting winter precipitation over the Mediterranean region 

Dario Nicolì, Silvio Gualdi, and Panos Athanasiadis

The Mediterranean region is highly sensitive to climate change, having experienced an intense warming and drying trend in recent decades, primarily due to the increased concentrations of anthropogenic greenhouse gases. In the context of decision-making processes, there is a growing interest in understanding the near-term climate evolution of this region.

In this study, we explore the climatic fluctuations of the Mediterranean region in the near-term range (up to 10 years ahead) using two different products: projections and decadal predictions. The former are century-scale climate change simulations initialized from arbitrary model states to which were applied anthropogenic and natural forcings. A major limitation of climate projections is their limited information regarding the current state of the Earth’s climate system. Decadal climate predictions, obtained by constraining the initial conditions of an ensemble of model simulations through a best estimate of the observed climate state, provide a better understanding of the next-decade climate and thus represent an invaluable tool in assisting climate adaptation.

Using retrospective forecasts from eight decadal prediction systems contributing to the CMIP6 Decadal Climate Prediction Project (CMIP6 DCPP) and the corresponding ensemble of non-initialized projections, we compare the capabilities of the state-of-the-art climate models in predicting future climate changes of the Mediterranean region for some key quantities so as to assess the added value of initialization. 

Beyond the contribution of external forcings, the role of internal variability is also investigated since part of the detected predictability arises from internal climate variability patterns affecting the Mediterranean. The observed North Atlantic Oscillation, the dominant climate variability pattern in the Euro-Atlantic domain, as well as its  impact on wintertime precipitation over Europe are well reproduced by decadal predictions, especially over the Mediterranean, outperforming projections. We also apply a sub-sampling method to enhance the respective signal-to-noise ratio and consequently improve precipitation skill over the Mediterranean.

How to cite: Nicolì, D., Gualdi, S., and Athanasiadis, P.: Decadal predictions outperform projections in forecasting winter precipitation over the Mediterranean region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16366, https://doi.org/10.5194/egusphere-egu24-16366, 2024.

EGU24-16985 | Posters on site | CL4.3

Investigating signals in summer seasonal forecasts over the North Atlantic/European region 

Julia Lockwood, Nick Dunstone, Kristina Fröhlich, Ramón Fuentes Franco, Anna Maidens, Adam Scaife, Doug Smith, and Hazel Thornton

The current generation of seasonal forecast models struggle to skilfully predict dynamical circulation over the North Atlantic and European region in boreal summer.  Using two different state-of-the-art seasonal prediction systems, we show that tropical rainfall anomalies drive a circulation signal in the North Atlantic/Europe via the propagation of Rossby waves.  The wave, however, is shifted eastwards compared to observations, so the signal does not contribute positively to model skill.  Reasons for the eastward shift of the Rossby wave are investigated, as well as other drivers of the signal in this region.  Despite the errors in the waves, the fact that seasonal forecast models do predict dynamical signals over the North Atlantic/Europe signifies seasonal predictability over this region beyond the climate change trend, and understaning the cause of the errors could lead to skilful predictions.

How to cite: Lockwood, J., Dunstone, N., Fröhlich, K., Fuentes Franco, R., Maidens, A., Scaife, A., Smith, D., and Thornton, H.: Investigating signals in summer seasonal forecasts over the North Atlantic/European region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16985, https://doi.org/10.5194/egusphere-egu24-16985, 2024.

EGU24-17418 | Posters on site | CL4.3

Strengthening seasonal forecasting in the Middle East & North Africa (MENA) through the WISER Programme. 

Stefan Lines, Nicholas Savage, Rebecca Parfitt, Andrew Colman, Alex Chamberlain-Clay, Luke Norris, Heidi Howard, and Helen Ticehurst

In this presentation, we introduce the WISER MENA projects SeaFOAM (Seasonal Forecasting Across MENA) and SeaSCAPE (Seasonal Co-Production and Application in MENA). These projects explore both the improvement to the regional-level seasonal forecast in the MENA region, as well as how to tailor the information in ways useful to a range of climate information stakeholders. SeaFOAM works alongside Maroc Meteo, Morocco's National Meteorological and Hydrological Service (NMHS) and the Long Range Forecasting node of the Northern Africa WMO Regional Climate Centre (RCC), to develop a framework for objective seasonal forecasting. This approach will blend techniques such as bias correction via local linear regression and canonical correlation analysis (CCA), with skill-assessed sub-selected models, to improve forecasting accuracy. Multiple drivers of rainfall variability, including the North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO), are investigated for their calibration potential. SeaSCAPE works with the WMO and various partners across MENA to understand the use of seasonal information in multiple sectors, exploring existing gaps and needs. Through stakeholder engagement workshops, training and bespoke support for the Arab Climate Outlook Forum (ArabCOF), SeaSCAPE operates collaboratively to tailor regional and national-level climate information to improve accessibility and usability of climate information on seasonal timescales.

How to cite: Lines, S., Savage, N., Parfitt, R., Colman, A., Chamberlain-Clay, A., Norris, L., Howard, H., and Ticehurst, H.: Strengthening seasonal forecasting in the Middle East & North Africa (MENA) through the WISER Programme., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17418, https://doi.org/10.5194/egusphere-egu24-17418, 2024.

EGU24-17585 | Orals | CL4.3

Skill of wind resource forecasts on the decadal time scale 

Kai Lochbihler, Ana Lopez, and Gil Lizcano

Accurate forecasts of the natural resources of renewable energy production have become not only a valuable but a crucial tool for managing the associated risks of specific events, such as wind droughts. Wind energy, alongside with solar power, now provide a substantial part to the renewable energy share of the global energy production and growth in this sector will most likely further increase. The naturally given fluctuations of wind resources, however, pose a challenge for maintaining a stable energy supply, which, at the end of the chain, can have an impact on the energy market prices.
Operational short-term forecasting products for the wind energy sector (multiple days) are already commonly available and seasonal to sub seasonal forecasting solutions (multiple months) can provide valuable skill and are gaining in popularity. On the other side of the spectrum, typically on a time scale of multiple decades, we find risk assessment based on climate change projections. In between the long and short term time scales, however, there is a gap that still needs to be filled to achieve seamless prediction of risks that are relevant for the energy sector: decadal predictions.

Here, we present the results of an evaluation study of a multi-model decadal prediction ensemble (DCPP) for a selection of wind development regions in Europe. The evaluation is based on multiple decades long hindcasts and carried out with a focus on the skill of predicting specific event types of wind resource availability in a probabilistic context, alongside with basic deterministic skill measures. We further investigate specific event constellations and their large-scale drivers that, in combination, can provide windows of opportunity with enhanced predictive skill. We conclude with a discussion on how this hybrid approach can be used to potentially increase not only forecast skill but also the trust of the end user.

How to cite: Lochbihler, K., Lopez, A., and Lizcano, G.: Skill of wind resource forecasts on the decadal time scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17585, https://doi.org/10.5194/egusphere-egu24-17585, 2024.

EGU24-19229 | ECS | Orals | CL4.3

Comparing the seasonal predictability of Tropical Pacific variability in EC-Earth3 at two different horizontal resolutions 

Aude Carreric, Pablo Ortega, Vladimir Lapin, and Francisco Doblas-Reyes

Seasonal prediction is a field of research attracting growing interest beyond the scientific community due to its strong potential to guide decision-making in many sectors (e.g. agriculture and food security, health, energy production, water management, disaster risk reduction) in the face of the pressing dangers of climate change.

Among the various techniques being considered to improve the predictive skill of seasonal prediction systems, increasing the horizontal resolution of GCMs is a promising avenue. There are several indications that higher resolution versions of the current generation of climate models might improve key air-sea teleconnections, decreasing common biases of global models and improving the skill to predict certain regions at seasonal scales, e.g. in tropical sea surface temperature.

In this study, we analyze the differences in the predictive skill of two different seasonal prediction systems, based on the same climate model EC-Earth3 and initialized in the same way but using two different horizontal resolutions. The standard (SR) and high resolution (HR) configurations are based on an atmospheric component, IFS, of ~100 km and ~40 km of resolution respectively and on an ocean component, NEMO3.6, of ~100 km and ~25 km respectively. We focus in particular on the Tropical Pacific region where statistically significant improvements are found in HR with respect to SR for predicting ENSO and its associated climate teleconnections. We explore some processes that can explain these differences, such as the simulation of the tropical ocean mean state and atmospheric teleconnections between the Atlantic and Pacific tropical oceans. 

A weaker mean-state bias in the HR configuration, with less westward extension of ENSO-related SST anomalies, leads to better skill in ENSO regions, which can also be linked to better localization of the atmospheric teleconnection with the equatorial Atlantic Ocean. It remains to be assessed if similar improvements are consistently identified for HR versions in other forecast systems, which would prompt their routine use in seasonal climate prediction.

How to cite: Carreric, A., Ortega, P., Lapin, V., and Doblas-Reyes, F.: Comparing the seasonal predictability of Tropical Pacific variability in EC-Earth3 at two different horizontal resolutions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19229, https://doi.org/10.5194/egusphere-egu24-19229, 2024.

EGU24-19251 | Orals | CL4.3 | Highlight

The opportunities and challenges of near-term climate prediction 

Hazel Thornton

Accurate forecasts of the climate of the coming season and years are highly desired by many sectors of society. The skill of near-term climate prediction in winter in the North Atlantic and European region has improved over the last decade associated with larger ensembles, improving models and boosting of the prediction signal using intelligent post processing. International collaboration has improved the availability of forecasts and promoted the uptake of forecasts by different sectors. However, significant challenges remain, including summer prediction, understanding the risk of extremes within a season, multi-seasonal extremes and how best to post process the forecasts to aid decision making. This talk will summarise recent near-term climate prediction research activities at the UK Met Office and will detail our experience of providing such forecasts to the energy and water sectors.  

How to cite: Thornton, H.: The opportunities and challenges of near-term climate prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19251, https://doi.org/10.5194/egusphere-egu24-19251, 2024.

This study focuses on applying machine learning techniques to bias-correct the seasonal temperature forecasts provided by the Copernicus Climate Change Service (C3S) models. Specifically, we employ bias correction on forecasts from five major models: UK Meteorological Office (UKMO), Euro-Mediterranean Center on Climate Change (CMCC), Deutscher Wetterdienst (DWD), Environment and Climate Change Canada (ECCC), and Meteo-France. Our primary objective is to assess the performance of our bias correction model in comparison to the original forecast datasets. We utilise temperature-based indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) to evaluate the effectiveness of the bias-corrected seasonal forecasts. These indices served as valuable metrics to gauge the predictive capability of the models, especially in forecasting natural cascading hazards such as wildfires, droughts, and floods. The study involved an in-depth analysis of the bias-corrected forecasts, and the derived indices were crucial in understanding the models' ability to predict temperature-related extreme events. The results of this research contribute valuable information for decision-making and planning across various sectors, including disaster risk management and environmental protection. Through a comprehensive evaluation of machine learning-based bias correction techniques, we enhance the accuracy and applicability of seasonal temperature forecasts, thereby improving preparedness and resilience to climate-related challenges. 

How to cite: Mbuvha, R. and Nikraftar, Z.: Machine Learning Approaches to Improve Accuracy in Extreme Seasonal Temperature Forecasts: A Multi-Model Assessment , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19297, https://doi.org/10.5194/egusphere-egu24-19297, 2024.

EGU24-19359 | ECS | Posters on site | CL4.3

Seasonal forecast of the late boreal winter temperature based on solar forcing and QBO 

Mikhail Vokhmianin, Antti Salminen, Kalevi Mursula, and Timo Asikainen

The ground temperature variability in the Northern Hemisphere winter is greatly influenced by the state of the polar vortex. When the vortex collapses during sudden stratospheric warmings (SSWs), rapid changes in stratospheric circulations propagate downward to the troposphere in the subsequent weeks. The ground effect following SSWs is typically manifested as the negative phase of the North Atlantic Oscillation. Our findings reveal a higher frequency of cold temperature anomalies in the Northern part of Eurasia during winters with SSWs, and conversely, warm anomalies in winters with a strong and stable vortex. This behavior is particularly evident when temperature anomalies are categorized into three equal subgroups, or terciles. Recently, we developed a statistical model that successfully predicts SSW occurrences with an 86% accuracy rate. The model utilizes the stratospheric Quasi-Biennial Oscillation (QBO) phase and two parameters associated with solar activity: the geomagnetic aa-index as a proxy for energetic particle precipitations and solar irradiance. In this study, we explore the model's potential to provide a seasonal forecast for ground temperatures. We assess the probabilities of regional temperature anomalies falling into the lowest or highest terciles based on the predicted weak or strong vortex state. Additionally, we demonstrate that the QBO phase further enhances the forecast quality. As the model provides SSW predictions as early as preceding August, our results carry significant societal relevance as well, e.g., for the energy sector, which is highly dependent on prevailing weather conditions.

How to cite: Vokhmianin, M., Salminen, A., Mursula, K., and Asikainen, T.: Seasonal forecast of the late boreal winter temperature based on solar forcing and QBO, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19359, https://doi.org/10.5194/egusphere-egu24-19359, 2024.

NH12 – Short Courses

NH13 – Inter- and Transdisciplinary Sessions

Against the backdrop of the global heightened geopolitical tensions and climate change, the issue of food security is a major topic currently faced by countries around the globe. As the most populous country in the world, China's food security issues will impact the sustainability of global food production and supply stability. Despite the emphasis on food security and cultivated land protection, China is facing the latent threat to food production caused by the non-grain use of cultivated land, where land previously used for cultivating food crops is being extensively planted with cash crops or used for forestry development. Not only will this phenomenon increase the pressure on China's self-sufficiency in food, but it will also damage the stability of the agricultural ecosystem and weaken the sustainability of food production in the long term. As the main grain-producing area in Sichuan Province and even in western China, the Sichuan Basin has a solid agricultural foundation. In recent years, the phenomenon of non-grain use has become increasingly prominent, necessitating an exploration of its driving mechanisms and the implementation of governance measures. Set in the Sichuan Basin, this paper employed the sliding window method to continuously monitor and extract the non-grain patches between 1991-2018 in the study area based on the annual China Land Cover Dataset (CLCD). We used advanced data-driven approaches, including geographically weighted regression models and geographical detector models, to explore the direction and strength of the impact of driving factors on the non-grain phenomenon. Finally, using process tracing based on policy texts, non-grain evolution is interpreted. In conclusion, increased economic activity exacerbates non-grain use, and objective spatial positions constrain the impact of locational factors on non-grain use. Natural factors fundamentally and decisively explain the level of non-grain use. Decreased temperature and increased slope will intensify this phenomenon, and the impact of precipitation on non-grain exhibits a threshold effect. China's three agricultural structural adjustments have potentially influenced the overall trend of the non-grain phenomenon. The Wenchuan earthquake and subsequent reconstruction had a short-term impact, while the central and local government's attention to the issue of non-grain and a series of arable land protection measures are the main reasons for the sharp decrease in the non-grain phenomenon after 2015. Differentiated policy measures are recommended for mountainous and plain regions to address these socio-ecosystem changes, balancing the goals of food production and ecological protection. This approach will ensure grain production is more adaptable to climate change and aligned with the intensity of economic activities.

How to cite: Chen, S., Xiao, W., Xu, S., Niu, L., and Zhang, Z.: Unveiling the Spatio-Temporal Characteristics and Driving Mechanisms of Non-Grain Land Use Dynamics in Agricultural Socio-Ecosystems: A Case Study of the Sichuan Basin, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-644, https://doi.org/10.5194/egusphere-egu24-644, 2024.

EGU24-905 | ECS | Orals | ITS4.10/NH13.1

Navigating climate risk in humanitarian action: The potential of storyline approaches 

Martha Marie Vogel and Christopher David Jack

The humanitarian community has a long history of attempting to reduce the human impact of extreme weather and climate events. Over the past decade there has been an increasing shift in the humanitarian community towards using climate science to better anticipate climate impacts on vulnerable communities and hence guide humanitarian planning and responses. However, large uncertainties, climate and non-climate, and complex compounding risks pose significant challenges to integrating climate information into humanitarian planning.

In the glossary of the IPCC Working Group I contribution to the Sixth Assessment Report storylines are defined as “A way of making sense of a situation or a series of events through the construction of a set of explanatory elements” and “can be used to describe plural, conditional possible futures or explanations of a current situation, in contrast to single, definitive futures or explanations”.

With this they are valuable for the humanitarian sector as storylines related approaches including impact pathways and complex risk frameworks offer the potential to provide robust and valuable understanding of risk, as well as supporting the development of effective interventions. They do not remove the underlying uncertainty, however, they do help to shift the questions asked from “What is going to happen”, to “What would unfold if this storyline occurred".  This shift has the potential to connect with decision making options and processes far more effectively than presentations of aggregate uncertainty ranges.

We explore the potential value  of storylines for climate risk management within the humanitarian sector, we present practical examples of effectively applying them to estimate and describe  systemic climate-related risks, especially in vulnerable regions.

How to cite: Vogel, M. M. and Jack, C. D.: Navigating climate risk in humanitarian action: The potential of storyline approaches, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-905, https://doi.org/10.5194/egusphere-egu24-905, 2024.

EGU24-1496 | ECS | Orals | ITS4.10/NH13.1

Analyzing impact cascades: an integrative approach for assessing the interconnected effects of extreme events across sectors and systems 

Mariana Madruga de Brito, Jan Sodoge, Zora Reckhaus, Miguel Mahecha, and Christian Kuhlicke

In today’s interconnected world, assessing the risks of extreme events has become increasingly complex. These events often trigger far-reaching consequences that spread throughout various sectors and systems due to complex interactions, resulting in compound and cascading impacts. While qualitative and quantitative approaches are commonly used separately in systemic impact research, we argue that methodological pluralism is necessary to address the complexity of these social-ecological systems. In this talk, we propose an integrative methodological approach for studying impact cascades and exemplify it via two case-study applications. The first focuses on using dimensionality reduction and pattern-mining techniques to assess spatiotemporal patterns in the occurrence of drought impacts in Germany. We explore how these patterns differ during multi-year drought events in contrast to short-lived droughts. Second, we leverage qualitative cognitive maps derived from 25 stakeholder interviews to investigate how drought impacts propagate in a case study in Thuringia, Germany. By using graph theory, we identify influential variables and show how pooling the knowledge of diverse stakeholder crowds can create new, emergent knowledge. We find that combining different methods helps revealing various facets of impact cascades and helps compensating for the limitations of individual methods. This can strengthen the research confidence as results that agree across different methods are less likely to be artefacts.

How to cite: Madruga de Brito, M., Sodoge, J., Reckhaus, Z., Mahecha, M., and Kuhlicke, C.: Analyzing impact cascades: an integrative approach for assessing the interconnected effects of extreme events across sectors and systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1496, https://doi.org/10.5194/egusphere-egu24-1496, 2024.

EGU24-1616 | Orals | ITS4.10/NH13.1 | Highlight

Extreme Event Impact Attribution: The state of the art 

Ilan Noy, Daithi Stone, and Tomas Uher

Extreme weather events lead to many adverse societal, economic, and environmental consequences. Anthropogenic climate change has been identified as a factor that, in many cases, increases the frequency and intensity of these weather extremes. In the last two decades, the methods of Extreme Event Attribution (EEA) have been used to quantify the extent to which climate change affected the nature of specific recent extreme weather events. More recently, these methods are being combined with socioeconomic impact data to quantify extreme weather’s impacts attributable to climate change in what we term Extreme Event Impacts Attribution (EEIA). EEIA is a quickly developing field that considers which kinds of questions about the impacts of climate change on extreme weather events we should ask, what methods are best suited to answer them, how to interpret the results these methods provide, and what purpose these results can serve. In this survey, we discuss the basic structure and methods of EEIA, review the results of the existing EEIA studies, and discuss the implications and outlook for this strand of research including its relevance for quantification of climate change costs, the Loss and Damage Fund, climate litigation, or adaptation planning.

How to cite: Noy, I., Stone, D., and Uher, T.: Extreme Event Impact Attribution: The state of the art, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1616, https://doi.org/10.5194/egusphere-egu24-1616, 2024.

Cities are facing increasing challenges of flood risk due to combined effects of climate change and socioeconomic development. At the same time understanding of the complexity of urban flood risk is still limited, hampering decision-making and effective urban adaptation planning. A socio-ecological system (SES) perspective offers a promising approach to analyze risk as a non-isolated entity by recognizing human and natural systems as complex and coupled structures and considering their interactive dynamics (e.g., delays, feedbacks, and non-linearity). Qualitative system dynamics modeling tools, such as causal loop diagrams, are particularly useful for this, as they allow the inclusion of different kinds of system variables.

This study applies a qualitative system dynamics modeling framework to holistically investigate urban flood risk under climate change and barriers to adaptation in a coupled SES using the city of Hamburg as a case study. The study deals with urban flood risk in the context of ‘water from 4 sides’ addressing questions in the growing research field of climate hazard interactions and compound risks. In a stepwise approach, a qualitative system dynamics model was developed based on an integrated interdisciplinary knowledge of researchers. Disciplinary mental maps were created by the researchers in various group interviews, followed by the development of an overall group causal loop diagram based on the disciplinary mental maps to form a holistic qualitative model. For the model analysis, causal chains of sub-processes and feedback loops were visually isolated and highlighted. Particular emphasis is placed on identifying and analyzing the reinforcing feedback loops underlying the complex urban system in order to understand the vicious circles of barriers that perpetuate and thus hinder the adaptation process. The findings on the system’s feedback loops help to understand why and how system behavior evolves in a specific direction. The integrated model shows that the main drivers of urban flood risk growth in the system are linked to socio-economic and institutional processes. Climate change mainly affects the city externally by increasing flood hazards, while the city itself contributes to flood risk through processes of exposure and social vulnerability. The results show that increasing flood risk and barriers to adaptation in the city are linked to the amplifying feedback loops of path dependency, river engineering measures, urban development, car dependency, the ‘levee effect’, poverty, urban health and silo-thinking.

The case study demonstrates the usefulness of the qualitative system dynamics modelling approach in developing a shared understanding of the complex social, economic, environmental and political and institutional interactions among multiple drivers of flood risk. Causal loop diagrams can be successfully used to articulate the viscous circles of barriers and lock-in effects of unsustainable development in urban adaptation. However, it should be noted that the model reflects the state of knowledge of the researchers involved in the model-building process and therefore only represents a ‘dynamic hypothesis’ of the structure and dynamics of the system under consideration. Further work is in progress to place this qualitative system dynamics model in the broader context of decisions support and policy through stakeholder involvement.

How to cite: Hanf, F. S. and the 'water from 4 sides' project team: A socio-ecological system perspective on urban flood risk and barriers to adaptation under climate change using causal loop diagrams – Case study of the city of Hamburg, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2008, https://doi.org/10.5194/egusphere-egu24-2008, 2024.

EGU24-2158 | ECS | Orals | ITS4.10/NH13.1

Personalized warnings – Swiss public’s preferences and needs  

Lorena Daphna Kuratle, Irina Dallo, and Michèle Marti

There are numerous efforts globally to enhance societies’ ability to prepare for and cope with disasters triggered by natural and human-made hazards such as heatwaves, flash floods, terrorist attacks, or earthquakes. Some of these efforts aim to enhance the effect of warnings by personalizing them. By addressing individual factors such as health issues and caregiving responsibilities and including tailored behavioral recommendations, they can become more inclusive. However, the compilation of these personalized warnings requires data, which can either be generated by a (one-time) query or extracted from individuals’ digital footprints. Thereby, the following key questions arise: Is there a desire for personalized warnings? Do these warnings improve safety culture, enhancing preparedness and responses in the face of disasters? Moreover, is the public aware of the type of data required to receive such warnings?

We will answer these questions by the means of a representative online survey in Switzerland with a between-subjects experiment by assigning participants to personalized heat warnings. It allows us to assess if people would like to receive personalized warnings and whether those warnings influence their intention to take protective measures and enhance inclusiveness. Further, we will analyze people’s data sharing preferences, their trust in warnings, and the influence of their online behavior (e.g., online-shopping, use of smart watches) on their preference for those warnings. Moreover, we will assess participants’ demographics to find patterns in what type of data different social groups are willing to share.

In our talk, we will present the first results of this survey and discuss implications for the further development of personalized warning messages.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101021746

How to cite: Kuratle, L. D., Dallo, I., and Marti, M.: Personalized warnings – Swiss public’s preferences and needs , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2158, https://doi.org/10.5194/egusphere-egu24-2158, 2024.

EGU24-2376 | ECS | Posters on site | ITS4.10/NH13.1

Understanding the multiple linkages between climate risks and water supply: a case study of Southern Sweden 

Jeanne Fernandez, Giuliano Di Baldassarre, Claudia Teutschbein, and Johanna Mård

There are numerous studies of the impacts of climate-related natural hazards, such as droughts, heatwaves and wildfires, to water supply. These range from the global mapping of water scarcity to local-level evaluations of damages to production and distribution infrastructure. However, comprehensive and dynamic assessments of climate impacts to water supply that consider both fast (e.g., floods, landslides) and slow onset risks (e.g., drought) as well as changes in water consumption are still lacking, especially in regions perceived as “water-rich”.

This study reviewed climate change impacts to water supply in northern temperate climates which, in recent years, have been exposed not only to multiple floods but also to seasonal droughts despite predicted increases in average precipitation. By adopting an extended risk framework, we developed a conceptual overview and visualization of the linkages between climate, water, and society in the context of Southern Sweden.

The results highlight the multiple knowledge gaps in the Swedish water sector related to climate change uncertainties at local scales, compound and cascading risks, and the challenge of implementing adaptation measures in practice. When acknowledging intersectoral connections, the conceptualization becomes increasingly complex, emphasizing broader implications for a functional society as a whole.

This research contributes to a sparse literature on the impacts of climate change to water supply in northern regions. We argue that conceptual and systemic approaches can benefit water utilities and municipalities where drought risk tends to be overlooked and discuss possible venues for moving adaptation forward.

How to cite: Fernandez, J., Di Baldassarre, G., Teutschbein, C., and Mård, J.: Understanding the multiple linkages between climate risks and water supply: a case study of Southern Sweden, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2376, https://doi.org/10.5194/egusphere-egu24-2376, 2024.

Climate risk is systemic risk. Despite this, extreme risk cascades from climate change are underexplored. This is a mistake since such cascades are likely to occur even at relatively low temperature rises of 1.5-2°C. Such heating risks triggering six or more tipping elements in the Earth system.  Here we use a novel form of expert elicitation and systems mapping to trace out potential paths from climate impacts to societal collapse at 2°C of warming. We contacted 8 experts from a range of different fields, including climatology, earth systems science, and existential risk studies, and had them compose systems diagrams of the most likely scenarios in which expected climate impacts cascade into widespread systems failures. We then compared and synthesised these to identify key, common feedbacks and pathways. These include food crises and extreme weather events undermining state legitimacy and triggering socio-political violence. Climate resilience efforts need to account for such extreme cascades.  

How to cite: Stephenson, S. and Kemp, L.: Mapping the end of the world: Understanding plausible routes to collapse from 2°C of warming, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3917, https://doi.org/10.5194/egusphere-egu24-3917, 2024.

EGU24-4128 | ECS | Posters on site | ITS4.10/NH13.1

Oil palm yield in Southeast Asia impacted by management and climate change 

Luri Nurlaila Syahid, Xiangzhong Luo, and Janice Ser Huay Lee

Oil palm is a primary commodity in the Southeast Asian region and has replaced a substantial portion of natural forests in this area, resulting in a shift in regional ecosystem and ecosystem-climate interactions. Previous site-level evidence suggested that oil palm activities (i.e., production yield) are influenced by social, biological, and climatic factors, however, it remains unclear how oil palm yield has changed across Southeast Asia and the dominant driver for the changes. In this study, we used ground survey of oil palm yield, in combination of remote sensing of near-infrared reflectance (NIRv), to examine the dynamics of oil palm yield from 2001 to 2017 in Southeast Asia, particularly in Malaysia and Indonesia. Utilizing multiple sources of open datasets, we investigated the roles of management (i.e., smallholder and industrial), biotic (i.e., stand age) and climate in influencing oil palm yield in Southeast Asia, and provide a quantification of their respective contributions to yield changes. The study advances our understanding of the historical changes in oil palm yield and their dominant factors, providing guidance to the future management of oil palm for sustainable production and ecosystem services.

How to cite: Syahid, L. N., Luo, X., and Lee, J. S. H.: Oil palm yield in Southeast Asia impacted by management and climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4128, https://doi.org/10.5194/egusphere-egu24-4128, 2024.

Amidst the growing urgency to sustain forest ecosystems, this study presents a crucial analysis of forest fragmentation susceptibility in Poland's Tuchola Forest—a region recurrently devastated by windstorm events. Our research aims to innovatively harness remote sensing technologies for a comprehensive assessment of forest fragmentation from 2015 to 2020. The study primarily revolves around three objectives: selecting the most suitable remote sensing dataset for monitoring fragmentation, identifying key contributing factors to forest fragmentation, and developing a susceptibility map to illustrate the forest’s fragmentation dynamics.

Employing a comparative analysis with the GTB tool, we scrutinized the capabilities of PALSAR (25m resolution) and Dynamic World (10m resolution) datasets. Our findings highlighted PALSAR's superior proficiency in detecting rare-patchy fragments, despite its marginally higher resolution. To construct a forest fragmentation susceptibility map, we used fragmented patches observed over the last six years as indicators of regions prone to intense fragmentation. These patches were further analyzed through the Weight-of-Evidence (WOE) method, where causative factors were normalized and scrutinized using a Correlation matrix.

The results indicate a heightened vulnerability of forest areas proximal to agricultural lands (<200 m) and barelands (<50 m), especially those with younger trees (5-15 years) and shorter tree heights (<18m). Such areas are more susceptible to fragmentation, exacerbated by high wind speeds (25-27 m/sec) and moderate vegetation water content. In contrast, regions distant from agricultural lands, particularly those on steeper slopes, demonstrate lower fragmentation susceptibility.

Our methodology, validated with an 82% accuracy, calls for immediate conservation measures in Tuchola Forest's fragile areas. It offers a scalable approach, underscoring the critical role of forest conservation in maintaining biodiversity and resilience against climate adversities. This study marks a pivotal contribution to Polish forestry research, providing actionable insights for decision-makers in forest reforestation, restoration, and afforestation strategies.

How to cite: Dutt, S.: Forest Ecosystem on the Edge: Mapping Forest Fragmentation Susceptibility in Tuchola Forest, Poland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5038, https://doi.org/10.5194/egusphere-egu24-5038, 2024.

EGU24-5296 | ECS | Posters on site | ITS4.10/NH13.1

Application of climate risk assessment framework for selected Italian airports: a focus on extreme temperature and extreme precipitation events 

Carmela De Vivo, Giuliana Barbato, Marta Ellena, Vincenzo Capozzi, Giorgio Budillon, and Paola Mercogliano

Due to increased extreme weather events as a consequence of climate change, climate risk analysis has become an essential issue for all critical infrastructures, including airports. The aim of this study is to apply a climate risk assessment framework to evaluate the impacts of extreme temperatures and extreme precipitation events on several Italian airports: Malpensa, Linate, Bergamo, Ciampino, Fiumicino, Napoli, Catania, Palermo, and Cagliari. According to the risk definition recommended in the Sixth Assessment Report of IPCC (2022), specific hazard, exposure and vulnerability indicators were identified. The hazard indicators were calculated using the UERRA regional reanalysis for the observed period (1981-2010). The climate variations were evaluated by an ensemble mean of high-resolution climate projections from the EURO-CORDEX initiative for the short (2021-2050), medium (2041-2070), and long-term future period (2071-2100), under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios. Exposure and vulnerability data were collected from multiple sources, such as official airports documents or websites. The final risk index obtained from the combination of these three factors allowed us to identify which of the selected airports are probable to face the major impacts due to extreme temperature and precipitation events.

In addition, starting from this study, a further innovative methodology is currently being evaluated to be adopted for climate change risk assessment by an individual airport. Main steps of this procedures involve the identification of hazard indicators, exposure and vulnerability factors. The success of the analysis performed is closely linked to the ability to actively involve the airport managers/operators through the participation to the workshops as well as the compilation of specific questionnaires in order to establish a participatory process with the aim to provide a comprehensive and detailed analysis.

All the methods and analysis (planned and ongoing) have the main goal of supporting the risk assessment airports and providing key information to enable the definition, selection and implementation of appropriate adaptation strategies in relation to characteristics of the airports and then to improve their resilience to climate change.

How to cite: De Vivo, C., Barbato, G., Ellena, M., Capozzi, V., Budillon, G., and Mercogliano, P.: Application of climate risk assessment framework for selected Italian airports: a focus on extreme temperature and extreme precipitation events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5296, https://doi.org/10.5194/egusphere-egu24-5296, 2024.

EGU24-5548 | ECS | Orals | ITS4.10/NH13.1

Examining the Spatial-Temporal Evolution of the Chongzhen Drought (1627-1644) in China and Its Impact on Famine 

Siying Chen, Yun Su, Xudong Chen, and Liang Emlyn Yang

Climate change is a critical context for the development of human civilization. Case studies on the societal impacts of climate change contribute to the understanding of the mechanisms of interactions between natural forces, ecosystems, and human societies. This study investigates the Chongzhen Drought occurring in 1627-1644 in China, which was very likely the worst drought in eastern China in the past 1500 years. Its duration, scope, and number of people affected are rare in history. At the same time, a large-scale famine broke out, which is argued as a main trigger of the peasant uprisings that led to the fall of the Ming Dynasty. This paper extracted 1,802 drought records and 1,977 famine records from Chinese historical documents (mainly local chronicles and history books) and reconstructed the spatio-temporal evolution of drought from 1627 to 1644 in eastern China as well as its impact on famine. First, we classified the drought events into four levels according to the duration and severity, based on the semantic differences. Then the kernel density estimation was used to reconstruct the spatial pattern of drought at annual resolution, as well as a series of Drought Kernel Density Index (DKDI) in different regions. The main drought area in 1627-1644 was located north of 29°N and shifted from Northwest China to North China and then expanded to the south. The development of drought in different regions was not synchronized. The DKDI series of North China approximated a single-peaked curve, with the drought gradually worsening from 1633-1640; the peak of DKDI in Northwest China also appeared in 1640. However, the DKDI series of the Yangtze-Huai Region showed a multi-peaked curve, constantly experiencing a cycle of drought aggravation-reduction in the early period and reaching its peak in 1641. Second, the spatio-temporal evolution of famine was also reconstructed and compared with drought. It showed that the range of drought and famine largely overlapped and their developing trends were generally similar.  However, the movement of the Famine Kernel Density Index (FKDI) series tended to be 1-2 years later than that of DKDI, suggesting a lag and continuation of transmission of drought impacts to the human system. Finally, the regression analysis showed that drought was the most critical factor triggering famine in this case with a contribution weight of 67.3%. The weight is higher at 73.4% in North China in comparison with other subnational regions. The study identified the transmission pathway from climate change to social consequences through “persistent drought → declining agricultural harvests → food shortage → famine”. While socioeconomic factors and human behaviours also played various roles in regulating the transmission process.

How to cite: Chen, S., Su, Y., Chen, X., and Yang, L. E.: Examining the Spatial-Temporal Evolution of the Chongzhen Drought (1627-1644) in China and Its Impact on Famine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5548, https://doi.org/10.5194/egusphere-egu24-5548, 2024.

The losses caused by flood emerges from the intricate interplay between natural and human systems. Particularly noteworthy is the flood disaster induced by exceptionally intense precipitation within densely populated mega-citys. A poignant illustration of this dynamic unfolded on July 20th, 2021, in the city of Zhengzhou, China. This event precipitated 380 fatalities, accompanied by a direct economic loss  exceeding  5.6 billion U.S. dollars, thereby exerting profound repercussions on national economic and social development. To unravel the intricate interactions between human systems and the extreme natural setting, our investigation delves into specific disaster events, such as fatalities occurring in metro line 5 and the tunnel of Jing-guang urban expressway, the overtopping peril of Guojiazui reservoir, and the explosion at an aluminum alloy factory. Employing a systemic perspective, we analyze human activities during the phases of early warning, response and disposal. Our findings underscore pivotal factors contributing to the substantial loss of life, including inefficient organization and preparedness by local government entities, inadequate emergency response measures from various departments, and a lack of readiness among the local populace. In response to these identified shortcomings, we proffer concrete recommendations for disaster prevention. These suggestions serve as valuable references for mega-cities, advocating measures such as fortifying the linkage mechanism among governmental departments and enhancing public awareness regarding flood hazards.

How to cite: Qi, S.: Analysis and research on interactions between human systems and the extreme rainstorm setting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5590, https://doi.org/10.5194/egusphere-egu24-5590, 2024.

EGU24-5855 | Orals | ITS4.10/NH13.1

IRISCC: supporting society’s capacity to address and strengthen resilience to climate change risks  

Janne Rinne, Magdalena Brus, Nikolaos Nikolaidis, Jaana Bäck, Paolo Laj, Werner Kutsch, Dick Schaap, Klaus Steenberg Larsen, Sabine Phillippin, Rosa Petracca Altieri, Cathrine Lund, Katrine Vendelboe, Päivi Haapanala, Säde Virkki, Niku Kivekäs, and Sanna Sorvari Sundet

Anthropogenic climate change, driven by elevated levels of greenhouse gases, is accelerating at an unprecedented rate, causing significant changes in climatic and biogeochemical conditions. The adverse effects of climate change include detrimental impacts on natural and managed ecosystems, as well as on socio-economic systems, human health, and welfare. Recognising the urgent need to address these challenges, the IRISCC (Integrated Research Infrastructure Services for Climate Change Risks) project aims to provide scientific and knowledge-based services to support societal adaptation to climate change. The project is funded by the European Union under grant agreement No 101131261 (HORIZON Research and Innovation Actions in Research Infrastructure Programme topic HORIZON- INFRA-2023-SERV-01-01) and has over 70 partners providing research services.

For the researchers focusing on climate change risks, IRISCC will offer services, such as open data and access to research platforms via transnational access and virtual access programs. Here IRISCC employs an integrated approach to understanding climate change risks, encompassing hazards, exposure, and vulnerability. By fostering interdisciplinary collaboration, the project strives to support science enabling all users of IRISCC services to better predict, mitigate, and adapt to climate-related risks affecting human and natural systems. The project's overarching mission is to facilitate in-depth knowledge production on climate change risks and accelerate the translation of scientific knowledge into innovative solutions.

The IRISCC consortium comprises expertise from several research infrastructures, covering domains such as Earth systems, health and environment, and social sciences, each bringing in their research service portfolios. Through inter- and transdisciplinary approaches, the project aims to provide transnational and virtual access to cutting-edge research, innovation, training, and digital services. 

In summary, the IRISCC project aligns with the session's focus on systems thinking approaches, presenting a comprehensive strategy supporting users to tackle the interconnected issues of climate-related hazards, risks, and impacts. The commitment of the project to provide integrated research infrastructure services positions it as a key player in advancing our ability to predict, mitigate, and adapt to the multifaceted challenges posed by climate change in European regions and cities.

How to cite: Rinne, J., Brus, M., Nikolaidis, N., Bäck, J., Laj, P., Kutsch, W., Schaap, D., Steenberg Larsen, K., Phillippin, S., Petracca Altieri, R., Lund, C., Vendelboe, K., Haapanala, P., Virkki, S., Kivekäs, N., and Sorvari Sundet, S.: IRISCC: supporting society’s capacity to address and strengthen resilience to climate change risks , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5855, https://doi.org/10.5194/egusphere-egu24-5855, 2024.

During Hurricane Katrine in New Orleans in 2005, the failure of telecommunication systems was a disaster by itself, creating chaos and seriously hampering mitigation measures during and directly after the event. Half of the telecom towers was destroyed by the heavy wind, the electrical grid was destroyed and an area as large as The Netherlands and Belgium combined was flooded. The rest of the telecom towers ceased operation 48 hours later, when their backup power was depleted. In some parts of New Orleans the water stood 4.5 meters high, and debris was making roads impassable, blocking emergency repairs. This created a disaster in a disaster, leaving local authorities and first responders without intercommunication and status updates, rendering well-informed and coordinated actions impossible.

Similarly, during Hurricane Irma in 2017, on the island of St. Maarten, 50% of the telecom towers were blown over, seriously hampering communications in large sections of the island. Fortunately, the sea cables connecting the island to the rest of the world remained unharmed, although even that was a close shave. Therefore, while the mobile phone network failed in large areas, the Emergency Support Functions of the government could still communicate with the outside world via the internet, to ask for support and specific equipment for emergency repairs (such as new telecom towers).

Similarly, after the Nepal earthquake in 2015, roads were rendered impassable by debris and all telecommunication networks were silenced, and the electrical grid destroyed. The first messages to the outside world were conveyed by radio amateurs, via ionospheric radio. Several inland villages remained isolated for several days, with no means to issue a call for assistance or medical help.

Despite these and other examples, most of the models and impact chains drawn by scientist to investigate disaster events ignore the role of telecommunication failure that aggravates the situation in the field. Also, scientific tools to predict risks and support decisions when the disaster unfolds and directly after it, are often provided via internet links, ignoring the likelihood of them being inaccessible when they are needed most, due to a telecom blackout.

It is therefore of the utmost importance to draw more attention of researcher to the role of telecommunications in impact chains, even when that is not their direct competence, and to interact with telecommunication experts and emergency organizations in the field to better prepare for telecommunication failure during and after disasters. A good example of such an initiative was shown in PARATUS, a scientific project on societal resilience, where information gathering on St. Maarten specifically included telecommunication during disasters. Crossing these boundaries between sectors will greatly amplify the practical impact of the scientific work.

How to cite: Witvliet, B.: Telecommunication – a blind spot in disaster resilience science, yet essential for disaster mitigation and recovery, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6634, https://doi.org/10.5194/egusphere-egu24-6634, 2024.

Loss exceedance curves have fat tails arising from cascading losses.  Even though such losses are rare, insight can be gained by considering alternative downward counterfactual realizations of historical events.  The use of downward counterfactuals provides a methodology for constructing climate change storylines (e.g. Climate Risk Management, 2021).

The downward counterfactual search for cascading losses can identify potential tipping points for disasters.  Such tipping points can arise from the perturbation of a historical system state through additional climate forcing, combined with human factors, such as human error, negligence or malicious action.   

Examples are given of how lessons learned from historical compound events, e.g. wind and heatwave, might have averted disaster.  The Californian utility, Pacific Gas & Electric (PG&E), narrowly missed liability for the 2017 Tubbs Fire in Northern California.  Increased inspection of their electricity power lines would have mitigated the risk of liability from future wildfires.  The following year, the Camp fire occurred, the deadliest and most destructive in Californian history.  PG&E were indicted for repeatedly ignoring warnings about its aging power lines and faulty maintenance, and in early 2019, PG&E were forced to file for Chapter 11 bankruptcy.

On 9 September 2023, Storm Daniel transitioned into a Mediterranean tropical cyclone, and made landfall near Benghazi in Libya, the following day.  The intense rainfall caused the collapse of the two Wadi Derna dams on 11 September, and the devastation of Derna.  Counterfactual analysis would have given prior warning. A Libyan hydrologist had pointed out in 2022 that the 1959 storm would have caused the failure of the dams, had they existed then.

Exploration of downward counterfactuals would augment societal resilience against climate extremes and compound events.

 

 

 

How to cite: Woo, G.: Downward counterfactual search for cascading losses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7449, https://doi.org/10.5194/egusphere-egu24-7449, 2024.

EGU24-7487 | ECS | Orals | ITS4.10/NH13.1

River Regulation Reshaped Human-water Interaction in the Lower Yellow River Floodplain 

Chentai Jiao, Xutong Wu, Shuang Song, Shuai Wang, Bei Xiang, and Bojie Fu

Floodplains have been crucial agricultural and populated areas throughout history and in present. Rivers typically shape the human activities within floodplains through water supply and flood risk, forming unique human-water interaction patterns. Here, we focus on the Lower Yellow River Floodplain, where continuous levees divide homogenous cultivated plain with different flood risk, creating a quasi-natural experiment, while the river's hydrology has undergone dramatic transformation since the 1990s. We utilize Landsat-based data including open-surface water bodies, cropland and NDVI to analyze the mechanism of river-agriculture interaction and whether this mechanism has changed. The results reveal that agriculture activities were less developed inside the floodplain than outside, and were even worse in regions closest to the river. This was attributed to frequent channel diversions, heightened flood threat, and actual inundation within the floodplain. However, the Lower Yellow River experienced a silt-load reduction, trenching, and channel stabilization after the late 1990s, while submerged cropland area in the floodplain also decreased. The declining flood threat has encouraged cultivation and agriculture investment in the floodplain, consequently reducing the productivity difference across the levees. This study illustrates a prototypical human-water interaction pattern in floodplains, underscoring the significance of effective river management for sustainable development in these regions, and provides a reference on understanding regional human-environment relationship in other floodplain areas.

How to cite: Jiao, C., Wu, X., Song, S., Wang, S., Xiang, B., and Fu, B.: River Regulation Reshaped Human-water Interaction in the Lower Yellow River Floodplain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7487, https://doi.org/10.5194/egusphere-egu24-7487, 2024.

EGU24-7653 | Orals | ITS4.10/NH13.1

Identifying financial actors exposed to tipping point risks 

Juan Rocha and Victor Galaz

Ecosystems around the world are showing symptoms of resilience loss. With them there is an increasing risk of critical transitions or regime shifts: large, abrupt and difficult to reverse changes in the function and structure of ecosystems. When regime shifts occur they often impact the flow of benefits that people get from nature, and with them the ability of companies, cities or nations to satisfy human needs. Here we ask who is exposed to ecological regime shift risks, and by being exposed, who has the agency or power to intervene and perhaps avoid tipping points?

To answer this question we match companies whose activities imply the use or extraction of natural resources in places vulnerable to regime shifts. First, we use Earth observations to quantify resilience loss in marine systems. We also used temeprature records to quantify the probability of extreme and severe heat wave events in the oceans. Both are conditions that can reduce primary productivity and impact fisheries. Then, we identify vessels that fish in these areas of the world and match their owners and shareholders when available in public databases.

For publicly listed companies we reconstruct social networks of companies ownership and investments. The networks serve to identify financial actors exposed to ecological tipping points through several investments or regions of the world. The multilayer network can be centred around companies, shareholders, investors, or countries. Clustering at different levels of aggregation allow us to identify actors with disproportional risk exposure, but also companies, investors or countries who could make a difference in mitigating risk.

How to cite: Rocha, J. and Galaz, V.: Identifying financial actors exposed to tipping point risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7653, https://doi.org/10.5194/egusphere-egu24-7653, 2024.

EGU24-7721 | Orals | ITS4.10/NH13.1

Assessing the deforestation embodied in the European Union consumption and trade of forest risk commodities.  

Mirco Migliavacca, Teresa Bras, Paul Rougieux, Selene Patani, Giovanni Bausano, Frederic Achard, Valerio Avitabile, Rene Beuchle, Clement Bourgoin, Alessandro Cescatti, Guido Ceccherini, Rene Colditz, Valeria De Laurentiis, Vasco Orza, Christelle Vancutsem, and Sarah Mubareka

Deforestation and forest degradation, particularly in the tropics, are recognised as important drivers of global warming and biodiversity loss. Forest loss can be driven by several factors, including the expansion of agriculture and pastureland to produce commodities and agroforestry. 

On 29 June 2023, the European Union (EU) Regulation on deforestation-free products came into force, promoting the consumption of 'deforestation-free' products with the aim of reducing the EU's impact on global deforestation and forest degradation, as well as greenhouse gas emissions and biodiversity loss. 

The Regulation states that products related to cattle, timber, cocoa, soy, palm oil, coffee and rubber must be produced on land that is free from deforestation, after 31 December 2020.  

In this contribution, we combine the use of statistics on agricultural and wood production, trade flow data, earth observation on land use change and deforestation, with physically based land footprint and a land use balance models to calculate the impacts embodied in EU bilateral trade and consumption of the selected forest risk commodities. Specifically, we evaluated the impact in terms of land area of forest biomass stocks displaced for the production and consumption of the commodities listed in the Deforestation Free Product Regulation.  

Our evaluation reveals that, in relative terms, the EU significantly contributes to the impacts linked to the production of cocoa and coffee. Soy, cattle, and palm oil emerge as the overall major contributors to deforestation embodied in the EU consumption and are globally responsible for most forest biomass loss. 

How to cite: Migliavacca, M., Bras, T., Rougieux, P., Patani, S., Bausano, G., Achard, F., Avitabile, V., Beuchle, R., Bourgoin, C., Cescatti, A., Ceccherini, G., Colditz, R., De Laurentiis, V., Orza, V., Vancutsem, C., and Mubareka, S.: Assessing the deforestation embodied in the European Union consumption and trade of forest risk commodities. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7721, https://doi.org/10.5194/egusphere-egu24-7721, 2024.

EGU24-7883 | ECS | Orals | ITS4.10/NH13.1 | Highlight

Increased temperature-related newspaper coverage and more negative sentiment during hot and cold extremes 

Ekaterina Bogdanovich, Mike S. Schäfer, Alexander Brenning, Markus Reichstein, Kelley De Polt, Lars Guenther, Dorothea Frank, and René Orth

More frequent, intense, and prolonged temperature extremes due to climate change increase the risk of human morbidity and mortality. However, public perception of these risks is often low, while people's awareness is crucial to reducing the health impact of temperature extremes. News media plays a key role in raising awareness by providing essential information on heat waves and cold spells such as releasing warnings, sharing weather forecasts, and discussing impacts. Any sentiment conveyed within newspaper articles about temperature extremes, either through positive, negative, or neutral phrasing, can influence the audience's perception of risk and, potentially, their actions. Newspaper coverage of temperature extremes and the related sentiment may be influenced by multiple factors other than the actual temperature anomalies, such as political alignment or editorial decisions, but also potentially the countries’ vulnerability to climate change. 

In this study, we analyze and compare the sentiment of temperature-related newspaper articles in eight countries (Israel, Malaysia, New Zealand, Philippines, Singapour, Pakistan, South Africa, and the United Kingdom) with different climates and societal vulnerabilities to climate change (food, water, health, ecosystem services, human habitat, and infrastructure). We consider leading English language, national newspapers and use daily maximum temperature data from the day of each article’s publication from the ERA5 reanalysis. The sentiment is determined in an automated way based on the fraction of positive and negative words in text. In addition to the sentiment, we determine whether or not each article mentions climate change. 

We find clear differences during times of extreme temperatures versus times with near-normal temperatures in all countries. During days with comparatively cold or warm temperatures (i) more temperature-related articles are published, (ii) their sentiments are more negative, and (iii) climate change is mentioned less frequently. While the latter finding is surprising, it suggests that there are unobserved confounding factors that require further research, which might relate to other events and anomalies occurring simultaneously. A comparison of the results across countries shows more negative sentiment and fewer mentions of climate change in countries with higher climate change vulnerability. Being aware of these media reporting patterns of extreme temperatures may help media outlets reassess their role in aiding public health responses.

How to cite: Bogdanovich, E., Schäfer, M. S., Brenning, A., Reichstein, M., De Polt, K., Guenther, L., Frank, D., and Orth, R.: Increased temperature-related newspaper coverage and more negative sentiment during hot and cold extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7883, https://doi.org/10.5194/egusphere-egu24-7883, 2024.

EGU24-8646 | ECS | Orals | ITS4.10/NH13.1

A Global Climate-Driven Stochastic Drought Model for Risk Assessment  

Marie Shaylor, Nicolas Bruneau, Mathis Joffrain, Frederic Azemar, and Thomas Loridan

Drought affects people, agriculture, and businesses across all sectors in every populated continent on Earth, and with climate change, both drought frequency and duration are increasing globally. Losses of $124 Billion to the global economy over the last two decades (1998 - 2017) have been directly attributed to drought. Hence, it is vital to gain an accurate understanding of drought risk in the present and how it may change in the future. 

Here, we describe the development of a climate-driven drought model which provides a global view of drought risk for (re)insurers. 

First, a historical catalogue (1950-present) consisting of yearly aggregated drought severity and duration footprints is derived by combining a selection of state-of-the-art drought indexes over varied time scales. Second, leveraging this historical catalogue, a large stochastic set of drought footprints is generated via the use of Principle Component Analysis, in which the drought risk is conditioned to the climate state. The model is then deployed on historical climate conditions (ERA5) or alternative and future climate conditions (indicated by the CEMS-LENS multi-member reanalysis model (present-2100)). 

These products are critical to inform damage models in the (re)insurance sector, with the model thus far proving useful in predicting subsidence risk in a France-based use case. Showcased results will provide an evaluation of drought risk both in the historical and changing future climate, as well as a newly developed risk score metric based on merged severity and duration information.

How to cite: Shaylor, M., Bruneau, N., Joffrain, M., Azemar, F., and Loridan, T.: A Global Climate-Driven Stochastic Drought Model for Risk Assessment , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8646, https://doi.org/10.5194/egusphere-egu24-8646, 2024.

EGU24-8746 | ECS | Posters on site | ITS4.10/NH13.1

The feedback of greening on local hydrothermal conditions in Northern China 

Yu Zhang, Xiaoming Feng, Chaowei Zhou, Ruibo Zhao, Xuejing Leng, Yunqiang Wang, and Chuanlian Sun

Northern China has experienced a significant increase in vegetation cover over the past few decades. It lacks a comprehensive understanding of how greening impacts local hydrothermal conditions. To address this issue, in our study, the RegCM-CLM45 model was used to conduct a thorough assessment of the impacts of greening on temperature, vapor pressure deficit (VPD), precipitation, and soil moisture. The findings revealed that the local climatic effects of greening varied across different drought gradients based on the aridity index (AI). In drier regions with AI<0.3, the increased energy induced by greening tended to dissipate as sensible heat, exacerbating both warming and drought conditions. Conversely, in wetter regions with AI>0.3, a greater proportion of energy was lost through evapotranspiration, attenuating warming. Additionally, greening enhanced precipitation and soil moisture in drier regions and moderated their decline in wetter regions. Significantly, our research emphasized the effectiveness of grassland expansion and conservation as prime strategies for ecological restoration, particularly in drylands, where they could effectively alleviate soil drought. Given the diverse responses of different land cover transformations to local hydrothermal conditions in drylands, there is an urgent need to address potential adverse effects arising from inappropriate ecological restoration strategies and to develop an optimal restoration framework for the future.

How to cite: Zhang, Y., Feng, X., Zhou, C., Zhao, R., Leng, X., Wang, Y., and Sun, C.: The feedback of greening on local hydrothermal conditions in Northern China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8746, https://doi.org/10.5194/egusphere-egu24-8746, 2024.

EGU24-9524 | ECS | Orals | ITS4.10/NH13.1

Global economic impact of weather variability on the rich and the poor 

Lennart Quante, Sven Willner, Christian Otto, and Anders Levermann

The distribution of temperature and precipitation has been shown to impact economic productivity all around the world.
These heterogeneous patterns change under future warming and impact consumers not only locally but also remotely through supply chains. Due to the possibility of a non-linear economic response, these effects are difficult to quantify and have been subject to limited empirical assessment focusing on direct impacts of weather extremes.
Here we show in numerical simulations of weather-induced production disruptions (of more than 7000 profit-maximising producers and utility-optimising consumers with more than 1,8 million supply linkages) that, under present-day climatic conditions, consumption loss risks resulting from production disruptions propagating through the economic network are larger for lower than for higher income groups within countries. Comparison between countries shows that risks are larger for medium-income countries than for low and high-income countries, which emerges from differing trade dependencies as well as heterogeneous exposure and response.
Projecting observed econometric relations of weather variability and economic productivity until 2040, we find an amplification of loss risks due to near-term climate change in most regions. This amplification increases with income for middle and high-income countries, while it is homogeneous across income groups in low-income countries. 
Global warming thus poses an increasing challenge to consumers through supply chains around the globe which needs to be addressed by fostering resilience. To avoid further harm to productivity and consumer welfare the climate has to be stabilised. 

How to cite: Quante, L., Willner, S., Otto, C., and Levermann, A.: Global economic impact of weather variability on the rich and the poor, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9524, https://doi.org/10.5194/egusphere-egu24-9524, 2024.

EGU24-9721 | ECS | Posters on site | ITS4.10/NH13.1

Uncertainties in flood damage assessment under projected future extreme rainfall conditions: a case study in Northeastern Sicily 

Jeewanthi Sirisena, Armelle Remedio, Cecilia Nievas, Giuseppe Aronica, and Laurens Bouwer

Floods are among the world’s most frequently occurring natural hazards, affecting more people than other natural disasters while causing enormous damage to the socio-economy, developments, and environment. Because of the increasing frequency of heavy precipitation events and storm surges, large areas are at increasing risk of inundation. Many countries, thus, are forced to spend millions of dollars every year to recover from the floods’ aftermath as well as on disaster prevention, mitigation, and adaptation. Over the last decades, these kinds of extreme events have presented a significant challenge in Europe, particularly in the Mediterranean region which experienced intense rainfall and flash floods. Many coastal urban areas in France, Italy and Spain have undergone severe damages and losses due to extreme rainfall events causing flash floods. This situation may further exacerbate due to the climate-change-driven impacts and intense human activities in the region.

As key components of risk assessment, modelling of hazard, vulnerability, and exposure are required to categorize the potential future damages and events. However, uncertainties in damage and risk estimation can be introduced from different sources such as model input data and model structure and parameters. Especially short-duration extreme events are often under-researched. Here, we focus on addressing uncertainties in the chain of multi-hazard risk assessment, particularly floods in the Mili and Santo Stefano di Briga Basins in the Northeastern Sicily. This study is a part of the “risk workflow for CAScading and COmpounding hazards in COastal urban areas” (CASCO) project, which aims to develop a framework to evaluate the damage as well as economic and human losses due to a series of several important natural hazards acting in a quick temporal succession: floods, earthquakes, tsunamis, heat waves, and landslides.

In this study, we use daily and sub-daily in-situ observations (2001 - 2022) and projected hourly rainfall from 8 ensemble runs of the EURO-CORDEX regional climate change projections under the RCP 8.5 scenario (2031-2060) to establish the intensity-depth-frequency (IDF) curves and drive a hydrological model for short-duration rainstorm events between 6 and 12 hours. The resulting flood depths, area, and velocities were obtained from 1D/2D hydrodynamic modelling. To model subsequent flood damages, we investigate different fragility curves in the literature relevant for Italian building classes. The exposure data are obtained from the newly developed European High-Resolution Exposure (EHRE) model (Nievas et al. 2023).

Our results show that in general, future rainfall extremes are projected to be more frequent and severe in the study area, leading to increasing flood hazard levels. As a consequence, damages in several areas are projected to increase as well. Overall damage estimation depends on the inputs at different stages of the modelling chain, which cause uncertainties and variability in the model estimations and resulting risk evaluations.  

Keywords: Extreme rainfall, Flood hazard and damage, Sicily, Uncertainty

Reference: 

Nievas, C. I., Kriegerowski, M., Delattre, F., Garcia Ospina, N., Prehn, K., Cotton, F. (2023): The European High-Resolution Exposure (EHRE) Model, (Scientific Technical Report STR ; 23/05), Potsdam : GFZ German Research Centre for Geosciences, 64 p. https://doi.org/10.48440/gfz.b103-23055

How to cite: Sirisena, J., Remedio, A., Nievas, C., Aronica, G., and Bouwer, L.: Uncertainties in flood damage assessment under projected future extreme rainfall conditions: a case study in Northeastern Sicily, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9721, https://doi.org/10.5194/egusphere-egu24-9721, 2024.

EGU24-10132 | ECS | Orals | ITS4.10/NH13.1

An assessment of global-scale drivers of climate disaster impacts and risk 

Khalil Teber, David Montero, and Miguel D. Mahecha

The complex interplay between environmental and anthropogenic factors across the globe results in differing impacts of climate and weather related disasters. Communities living in deprived socioeconomic conditions are usually subjected to severe impacts, as they are more vulnerable to disasters. However, in a world of rapid natural and anthropogenic change, this is not the only cause behind amplified risks and impacts. The aim of this study is to identify the pivotal global-scale factors that make a significant contribution to the impact severity of climate disasters.

Using an expansive dataset with disaster impact records, complemented with socioeconomic indicators and climate variables from >6000 events in >150 countries, our work is a global-scale investigation of the roles of hazard severity, exposure, and vulnerability influencing the impacts and risk of climate disasters. We use a spatio-temporal stratified approach to define hazard severity, exposure, and vulnerability with relevant variables at the local, regional and global levels. Then, we determine the main factors contributing to impact severity across regions and disaster types using a robust machine learning pipeline.

This study illustrates the importance of considering comprehensive aspects of risk in order to build resilient societies to climate extremes. Our research contributes to advancing scientific understanding of the drivers of climate disaster impacts, with the aim of developing more effective policies. It highlights the importance of integrating diverse data sources and advanced analytical methods to better anticipate, prepare for, and respond to the multifaceted challenges posed by climate disasters in a changing climate.

How to cite: Teber, K., Montero, D., and Mahecha, M. D.: An assessment of global-scale drivers of climate disaster impacts and risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10132, https://doi.org/10.5194/egusphere-egu24-10132, 2024.

Keywords: risk communication, protection-motivation, flood type, household, survey

Whether and how flood-affected people prepare for flooding is commonly assumed to depend on their perception of risk, options to cope and responsibilities. However, the influence of different flood types, i.e., fluvial, flash and urban pluvial floods, is unclear, but might be relevant for effective risk communications. We use survey data from more than 3000 households affected by different types of flooding in Germany to investigate their influence on adaptive behaviour and influencing factors. We use descriptive statistics, Kruskal-Wallis Tests and single factor ANOVA to identify differences and similarities between respondents. We use linear regressions to identify factors that influence adaptive behaviour of households in the context of fluvial, pluvial and flash flooding.

We found that most respondents were motivated to protect themselves, but that there were flood type specific differences in the factors influencing an adaptive response. For example, those affected by fluvial events have had implemented most often measures before the last flooding, showed signs of emotional coping frequently and were less likely to implement (more) measures, while those affected by flash flooding showed less confidence in the effectiveness of measures, but were less likely to rate their costs as too high and were most likely to implement measures after the event. We argue that inter alia the severity and experience of flooding, as well as the management of flooding, shapes adaptive behaviour. We further found that regardless of the type of flooding, the perception of the effectiveness of adaptive measures and a positive perception of personal responsibility are critical to promote the protection motivation of those affected. We found, that these two key elements can be strengthened by offering financial support for adaptive measures. We also found that communication on a municipality level enhances the sense of self-responsibility. We conclude that communication and management strategies need to involve municipalities and should be tailored to the type of flooding. Up to now, risk communication mainly addresses fluvial flooding situations.

How to cite: Dillenardt, L. and Thieken, A.: Individual Flood Risk Adaptation in Germany: Exploring the Role of Different Types of Flooding, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10652, https://doi.org/10.5194/egusphere-egu24-10652, 2024.

EGU24-10949 | ECS | Orals | ITS4.10/NH13.1

Projected changes in compound dry-hot events in South Asia 

Farhan Saleem, Torsten Weber, and Armelle Remedio

South Asia is one of the hotspot regions for extreme weather and climate events such as heatwaves, droughts, and extreme precipitation. This work aims to present a comprehensive analysis of the future changes (2071-2100) in the frequency and duration of compound dry-hot extremes in South Asia. Given the current gap in specific data for such compound events in this region, our approach involves utilizing state-of-the-art regional climate models from the Coordinated Output for Regional Evaluations (CORE) project embedded in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. The focus will be on understanding the interplay between dry and hot days conditions, and how their concurrent occurrence may exacerbate environmental and socio-economic challenges. We will analyze an ensemble of regional climate projections to identify potential trends in these compound events by the end of the 21st century. The outcomes of this study are expected to provide valuable insights into the evolving nature of compound climate extremes in South Asia, thereby informing policy and adaptation strategies for enhanced regional resilience.

How to cite: Saleem, F., Weber, T., and Remedio, A.: Projected changes in compound dry-hot events in South Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10949, https://doi.org/10.5194/egusphere-egu24-10949, 2024.

EGU24-11122 | ECS | Posters on site | ITS4.10/NH13.1

Impacts of climate-modified disturbance regimes on coastal ecosystems and their services 

Sarah Hülsen, Laura Dee, Chahan Kropf, Nicolas Colombi, and David Bresch

Coastal ecosystems, such as mangroves, coral reefs, salt marsh, seagrass, and kelp forests, provide crucial regulating, provisioning, and cultural services to human societies. Previous research has demonstrated the various ways in which these ecosystems can reduce disaster risk and contribute to climate change adaptation. Simultaneously, the potential effects of climate extremes and extreme weather events on ecosystem composition and functioning are increasingly gaining attention.

While it is apparent that these ecosystems are subject to changing disturbance regimes under climate change, assessments of what these future disturbance regimes are likely to look like in the future have rarely been attempted and are often limited to single ecosystem and hazard pairs.

Therefore, we propose a global multi-layer hazard assessment for coastal ecosystems to assess i) the changing disturbance regimes coastal ecosystems are exposed to with regards to tropical cyclones, storm surge, sea level rise, and marine heatwaves, ii) potential ecological responses to these changes, and iii) implications for ecosystem service provision. We will present preliminary results as a starting point for further discussion.

How to cite: Hülsen, S., Dee, L., Kropf, C., Colombi, N., and Bresch, D.: Impacts of climate-modified disturbance regimes on coastal ecosystems and their services, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11122, https://doi.org/10.5194/egusphere-egu24-11122, 2024.

EGU24-11552 | ECS | Posters on site | ITS4.10/NH13.1

Impact-based forecast for critical infrastructure during Tropical Cyclones 

Gabriela Espejo Gutierrez, Zélie Stalhandske, Evelyn Mühlhofer, David Bresch, and Stefan Brönnimann

Critical infrastructures, such as healthcare facilities or roads, play a vital role in society as they provide essential services for the functioning of communities. Disruptions to these infrastructures have far-reaching consequences, affecting public health, safety, security, well-being, and economic activities. Weather extremes, such as tropical cyclones or floods, can lead to widespread failures in lifeline services such as power, communication, transportation, and healthcare. Forecasting the potential impact of weather extremes in the weeks to days before they happen can help increase the preparedness in the areas that might be affected. The emerging field of research on impact-based forecast models is instrumental in this regard, aiding international organizations and governments in making informed decisions, taking early actions, and allocating resources efficiently. This study aims to build upon the pioneering research by developing an impact forecast tool of tropical cyclones on critical infrastructure. While earlier efforts concentrated on estimating the potential affected population, our focus shifts to understanding the impact on critical infrastructure, starting with healthcare facilities, schools and road networks. We present a case study of Tropical Cyclone (TC) Freddy, which hit Mozambique and Madagascar in 2023. We calculate direct impacts using two sets of vulnerability curves for structural damage and another based on the Saffir-Simpson scale to ensure global applicability when needed. To better understand the significance of these impacts, we further assess their indirect impacts on the population. Additionally, to ensure the utility of this tool for international organizations, we exchange with stakeholders from these entities.

How to cite: Espejo Gutierrez, G., Stalhandske, Z., Mühlhofer, E., Bresch, D., and Brönnimann, S.: Impact-based forecast for critical infrastructure during Tropical Cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11552, https://doi.org/10.5194/egusphere-egu24-11552, 2024.

EGU24-11668 | Orals | ITS4.10/NH13.1

Water resilience to policy implementation and engineered measures in the Yellow River Basin 

Lu Yu, Shuang Song, Xutong Wu, Shuai Wang, and Bojie Fu

River basins couple the natural ecosystem with the socio-economic system. Regime shifts due to climate change and social-economic factors highlight the importance of quantifying and strengthening the water resilience in the river basin. Water resilience in river basin systems requires more specific quantification. The Yellow River Basin (YRB) was well-known for its historically severe water supply pressure in recent decades, profoundly adjusted by the social-economic system. A system dynamic model named the Water-Sediment-Social Economic-Ecological Model (WSSEEM) was proposed around the interactions and feedback among water supply, sediment discharge, vegetation changes, food production and social-economic development in the YRB. Using WSSEEM, we simulate water supply and demand resilience to changes and distributions, including policy implementation and engineered measures during the historical time (1981-2020) and future scenarios. Our result indicates that technology enhancement and engineered measures are instructive in water management and sediment discharge. The WSSEEM offers a comprehensive approach to representing the river basin system, providing valuable insights into using model simulation to achieve sustainable goals and resilient water management.

How to cite: Yu, L., Song, S., Wu, X., Wang, S., and Fu, B.: Water resilience to policy implementation and engineered measures in the Yellow River Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11668, https://doi.org/10.5194/egusphere-egu24-11668, 2024.

EGU24-11895 | ECS | Posters on site | ITS4.10/NH13.1

Flooding risk assessment of power grids by modelling and simulation 

Panagiotis Asaridis, Daniela Molinari, Francesco Di Maio, Francesco Ballio, and Enrico Zio

Power grids can be significantly affected by floods that can cause power outages with widespread impact on social and economic activities. In this work, we propose a “What-if” scenario analysis by modelling and simulation, which makes use of a hydraulic model to simulate hazard scenarios, fragility curves to describe the process of failure of the power grid components, and a power flow model to assess power outages. A synthetic case study is worked out with reference to the IEEE 14 bus system benchmark serving different categories of electricity customers. The proposed modelling and simulation-based analysis can be used to identify the most critical components to protect for the security of power supply.

How to cite: Asaridis, P., Molinari, D., Di Maio, F., Ballio, F., and Zio, E.: Flooding risk assessment of power grids by modelling and simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11895, https://doi.org/10.5194/egusphere-egu24-11895, 2024.

EGU24-12087 | ECS | Orals | ITS4.10/NH13.1

Preferences on funding humanitarian aid and disaster management under climatic losses and damages: A multinational Delphi panel 

Juha-Pekka Jäpölä, Sophie Van Schoubroeck, and Steven Van Passel

Losses and damages from climate change and the frequency of extreme events will burden our global budgetary constraints and adaptive capacities. Scientific and analytical support for allocating public funding in humanitarian aid and disaster management to counter them involves determining the most pertinent criteria to use or where to design forecasting. Their priorities are often assumed, and assumptions can be ill-fitting. Thus, we asked the key users of such information for their preferences.

A two-round anonymous Delphi method utilising global frameworks for a funding allocation simulation was employed to survey the stated preferences of a stratified panel of losses and damages experts (N=36). They were experts from 19 countries of origin representing international organisations (e.g., United Nations, European Union, World Bank), the research sector, the public sector, and civil society (e.g., Save the Children, World Vision). The consensus was analysed with parametric measures.

We find that the near-future preference for magnitude-indicating criteria, such as people-centric and disaster risk-based, outweighs the importance of indicators related to governance, the rule of law, or a socio-economic aspect. Likewise, financing adaptation options to climate change-related risks to food security, human health, and water security are a high near-future priority for minimising losses and damages compared to, for example, risks to living standards or risks to terrestrial and ocean ecosystems. The covariance suggests that these priorities are an emergent preference in the losses and damages sector. Thus, it raises further questions on what we can and should prioritise with scarce resources.

How to cite: Jäpölä, J.-P., Van Schoubroeck, S., and Van Passel, S.: Preferences on funding humanitarian aid and disaster management under climatic losses and damages: A multinational Delphi panel, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12087, https://doi.org/10.5194/egusphere-egu24-12087, 2024.

Floods impact a series of interconnected urban systems (referred to as the Urban Multiplex) that include the power grid and transportation networks, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams – all intertwined with the natural environment and socioeconomic and public health sectors. While the Urban Multiplex is physically and functionally connected, the data produced within its individual sectors are not. This is the core reason why we still do not fully understand the total impact of floods on cities.

The Urban Flooding Open Knowledge Network (UFOKN) is an information infrastructure that (i) integrates Urban Multiplex data, (ii) produces real-time and long-term flood forecasts across the continental U.S., and (iii) serves as the foundation to evaluate the total impact of floods on cities. The latter includes assessment of cascading economic impacts of floods across multiple sectors, as well as cascading failures across infrastructure, ecosystems, and communities.

UFOKN aims to provide actionable answers to questions such as:

  • Real-time flood mitigation and response: Will my house or place of business flood? Will I have access to water and power? Which district to evacuate first? When? Which traffic routes are safe? Will this storm disrupt the power grid, drinking water treatment plant, or a bridge?
  • Long-term design, planning and research: Which critical urban infrastructure will likely fail in a future flood? Which failures will affect the most people or the most vulnerable people? Which areas will experience repeated flooding? Which houses should the city buy out? Should a hospital be built at location X? What are the common triggers of Urban Multiplex failures?

The interdisciplinary team behind this project has brought together academic researchers, industry, federal government, U.S. National labs and local stakeholders. UFOKN is funded by the U.S. National Science Foundation’s Convergence Accelerator Program that is structured to enable rapid advancement in highly complex problems of critical societal importance.

How to cite: Yeghiazarian, L. and the Lilit Yeghiazarian: The Urban Flooding Open Knowledge Network: From Real-Time Flood Forecasts to Cascading Failures Through Infrastructure, Ecosystems, Communities and Economy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13258, https://doi.org/10.5194/egusphere-egu24-13258, 2024.

EGU24-13297 | ECS | Posters on site | ITS4.10/NH13.1

Atmospheric Rivers as a Component of Multi-hazards and their Influence on Western U.S. Water Management 

Eric Shearer, Emily Wells, Sharmin Siddiqui, Amir AghaKouchak, Christine Albano, Jeremy Giovando, Ian Floyd, and Cary Talbot

The Forecast Informed Reservoir Operations (FIRO) initiative, led by the United States Army Corps of Engineers (USACE) in collaboration with multiple agencies and university partners, marks a significant shift in integrating advanced weather and hydrologic forecasting into reservoir management, particularly on the US West Coast. At the heart of FIRO is the utilization of the predictability of atmospheric river (AR) landfall over multi-day timescales. However, challenges remain in fully understanding and predicting the interactions of ARs with critical environmental conditions, such as post-burn fire scars, saturated watersheds, and heavy snowpack, as well as other phenomena that contribute to hazards, including in the context of water management. Given the evolving patterns of rain, snow, and wildfires in the region, these factors underscore the urgency for proactive insights into multi-hazards and their effect on water management.

In addressing these challenges, our project conducts a thorough analysis of literature regarding ARs as drivers of hazards and their contributions to multi-hazard events, noting that their interactions vary geographically and temporally in response to climate change, necessitating spatially distributed climate change adaptation strategies for USACE water management for hazard conditions. This project is complimented by the creation of a comprehensive multi-hazard inventory for California, encompassing various hazards across different timescales. This inventory is supported by diverse data sources, including the NOAA NCEI Storm Event Data, the Rutz AR Catalog, USGS/USDA Monitoring Trends in Burn Severity Fire Data, and USACE's annual state-level flood damage reports. A key aspect of our study is the inclusion of the location of USACE infrastructure, particularly dams and reservoirs, to identify those most vulnerable to multi-hazard events historically.

The outcomes of this project are anticipated to offer critical insights and practical tools for decision-makers within the USACE water management community and beyond. These tools and insights are aimed at equipping them to better navigate the complex and evolving challenges presented by climate change. Through this initiative, we aim to contribute significantly to the development of more resilient and adaptive water management strategies in the face of a dynamic and changing environment.

How to cite: Shearer, E., Wells, E., Siddiqui, S., AghaKouchak, A., Albano, C., Giovando, J., Floyd, I., and Talbot, C.: Atmospheric Rivers as a Component of Multi-hazards and their Influence on Western U.S. Water Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13297, https://doi.org/10.5194/egusphere-egu24-13297, 2024.

EGU24-13615 | ECS | Posters on site | ITS4.10/NH13.1

Analysis of the potential direct and indirect impacts of dam failures on storage services for multiple purposes 

Maria Castro, Luis Rapalo, Pedro Silva, and Eduardo Mendiondo

Unprecedented natural disasters due to the climate crisis are a global issue, threatening sustainable development, mostly because they are associated with life, assets, and infrastructure losses and damages to the environment. Recent disasters, such as floods, were responsible for the death and displacement of thousands of people. A storm could subsequently trigger dam failures, reinforcing the disastrous consequences, as these could be part of an infrastructure network that would irrigate and supply surrounding cities and communities with much-needed water. This shows that natural disasters can induce an interruption in water services due to a cascade effect on existent measures. Since dams are usually employed to tackle multiple water management problems such as water supply and flood control, the collapse is an event that causes direct, intense and rapid impacts, and indirect ones in the medium and long term. According to the National Dam Safety Information System (SNISB), the dam risk degree depends on the Risk Category (CRI) and their Associated Potential Damage (DPA), these consider variables such as technical characteristics, dam safety plan, potential for human losses, among others. However, this classification is mostly associated with direct impacts,, which does not prioritize hydrodynamic modeling associated with the socioeconomic impacts resulting from the interruption of service to user sectors, this will be considered an indirect impact. This research aims to evaluate the direct and indirect effects of the impacts caused by the failure of the 10 largest volume and high-risk dams in the state of Pernambuco, a region with semi-arid characteristics in northeastern Brazil. Here, we employed a simplified model of the explicit Saint-Venant equations, the HydroHP-1D. Based on the preliminary dam break simulations, parameters such as maximum flow, depth, speed, extravasated volume, area flood wave and flood wave arrival time were estimated and used to identify the region’s vulnerability degree, which direct impacts have a significant correlation. The proposal of assessing the indirect impacts involves quantifying the storage service loss from the dam considered through a water balance of the studied area. This service interruption covered the supply of water to human activities, energy generation or even combating drought in certain regions. The expected results of the modeling associated with quantification of the interruption of the storage service of the respective dam made through a water balance of the study area, can reinforce the need to consider, in the preparation of contingency and water security plans, studies that explore the consequences of the interruption of supply to dams, in case of rupture. In general, this research promotes relevant discussions about disaster risk water resources management through the phases of prevention, reduction, preparation, response and recovery, which is enhanced when society is aware of the conditions of vulnerability, in order to prevent losses of life and property.

How to cite: Castro, M., Rapalo, L., Silva, P., and Mendiondo, E.: Analysis of the potential direct and indirect impacts of dam failures on storage services for multiple purposes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13615, https://doi.org/10.5194/egusphere-egu24-13615, 2024.

EGU24-13940 | ECS | Posters on site | ITS4.10/NH13.1

A “Parallel Evolution” of Flood Risk Management along the Rhine and the Sacramento Rivers 

Ben Daniels, Indumanti Roychowdhury, Andrew Calderwood, Lidia Mezei, Bethany Rader, Kathy Schaefer, Erin Tracy, Mariana Webb, Nicholas Pinter, Jay Lund, Helen Dahlke, and Sarah Yarnell

The Sacramento River in California, USA, and the Rhine River in Europe both have histories of major flooding events and great efforts to manage flood risk. We compare these two watersheds with an interdisciplinary lens to explore the goals, approaches, outcomes, and “parallel evolution” of differing flood risk management paradigms.

The two basins share hydrologic similarities, but each approach to managing floods reflects the basin’s unique historical, environmental, and governance context. The Sacramento basin is entirely within the state of California, whereas the Rhine is a transnational river that drains nine European countries. The Rhine basin is larger and has a much larger population compared with the Sacramento basin.  The Sacramento basin has high interannual precipitation variability and receives most of its precipitation in the winter with significant mountain snowfall. The hydrology of the Rhine is also strongly influenced by mountain snowpack, but has precipitation that is more evenly distributed throughout the year. Flood-risk management on both the Sacramento and Rhine Rivers has evolved from ad hoc and local approaches, towards more systematic planning, culminating in significant state-level control in California, and state, federal, and transnational management on the Rhine. This transition was driven in recent years by the Central Valley Flood Protection Act and the European Floods Directive.

Management of each basin has been shaped by an event-based evolution, in which disasters have driven management responses, tools, and approaches. Flood-risk paradigms in both basins include significant investment in engineering protection and, increasingly, soft-policy adaptations. Over time, flood management methods and objectives in each basin have become more diverse. For example, single-objective approaches have evolved towards multi-benefit projects. Both basins are expanding consideration of floodplain ecosystem importance and both now consider climate change to some in flood risk management.  Flood-protection levels are higher on the Rhine than on the Sacramento. Some areas of the Rhine have 1000-year or better protection whereas a  200-year-level protection for urban areas is now required in the Sacramento basin.

The Sacramento River and the Rhine River are geographically and hydrologically similar in surprisingly many ways, including in the flood risk they pose.  But the flood-risk management paradigms in the two basins have evolved differently.  We argue that the differences are a form of “parallel evolution,” reflecting historical and political contrasts between the two systems.  Such contrasts present opportunities for alternative tools and lessons that can be explored and perhaps imported in both directions.

How to cite: Daniels, B., Roychowdhury, I., Calderwood, A., Mezei, L., Rader, B., Schaefer, K., Tracy, E., Webb, M., Pinter, N., Lund, J., Dahlke, H., and Yarnell, S.: A “Parallel Evolution” of Flood Risk Management along the Rhine and the Sacramento Rivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13940, https://doi.org/10.5194/egusphere-egu24-13940, 2024.

EGU24-14111 | ECS | Orals | ITS4.10/NH13.1

Cascading impacts of extreme events across an interconnected and warming world 

Laurie Huning and Manuela Brunner

Extreme events (e.g., heatwaves, wildfires, droughts, floods, etc.) are anticipated to become more severe, persistent, and frequent throughout many parts of the world due to warming. Such extreme events occur across a diverse set of ecosystems and climatic regions and their multifaceted impacts cascade in space, time, and across sectors (e.g., water, energy, agriculture, economic, human health). To better understand the cascading impacts of extreme events and their feedbacks, we draw on recent examples such as the 2023 heatwaves and wildfires in Canada. In addition, we also examine other extreme events (e.g., droughts, floods) around the world and their feedbacks and interactions that pose challenges for modeling, monitoring, and managing associated risks. For example, we quantify how snowpack changes and drought across agricultural regions have wide-reaching impacts that affect remote areas. Our study highlights that the impacts of extreme events have important feedbacks that should be considered in resource and risk models and management as well as remote impacts that are not yet fully understood or well-tracked. Furthermore, we identify other challenges, existing knowledge gaps, and future directions to guide global monitoring and modeling of impact cascades for improved mitigation, adaptation, and climate change resilient policy advancements.

How to cite: Huning, L. and Brunner, M.: Cascading impacts of extreme events across an interconnected and warming world, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14111, https://doi.org/10.5194/egusphere-egu24-14111, 2024.

EGU24-15454 | Posters on site | ITS4.10/NH13.1

Metryc and DeepCyc: Pioneering Tools from Reask in Disaster Risk Financing and Humanitarian Impact Mitigation 

David Schmid, Thomas Loridan, and Marie Shaylor

The escalation of climate-related disasters presents an urgent need for innovative risk financing mechanisms. Metryc, a groundbreaking product by Reask, emerges as a pivotal tool in this domain, especially in the context of tropical cyclones. It represents a significant advance in parametric insurance, facilitating swift, post-disaster financial recovery. Metryc’s intensity-based approach, distinct from traditional distance-based models, minimizes basis risk and offers cost-effective risk transfer solutions. This method’s superior accuracy in modeling wind speeds post-cyclone landfall enables rapid insurance payouts, crucial for immediate disaster response and recovery.

Complementing Metryc, DeepCyc, another Reask product, stands as a probabilistic hazard model integrating current climate data and future climate scenarios. This climate-connected model transcends the limitations of conventional models reliant on historical data, thus offering a more robust and future-oriented risk assessment. DeepCyc’s high-resolution (1x1 km²) probabilistic hazard modeling is instrumental in precise insurance structuring and premium determination, reflecting modern-day climatic realities.

The humanitarian impact of these tools is profound. By ensuring expedited financial relief, Metryc significantly enhances the capacity of affected communities to recover from catastrophic events. This rapid response mitigates the long-term socio-economic impacts of disasters, facilitating quicker restoration of livelihoods and infrastructure. Moreover, DeepCyc’s forward-looking approach in risk modeling acknowledges the evolving nature of climate risks, ensuring that risk assessments remain relevant and effective in a changing world.

In summary, Metryc and DeepCyc represent a synergistic approach in disaster risk financing. Metryc’s immediate post-disaster financial support and DeepCyc’s comprehensive, climate-informed risk assessment model together provide a robust framework for mitigating the humanitarian and economic impacts of climatic disasters. This dual approach underscores the potential of advanced technology in transforming disaster risk management and resilience-building in the face of climate variability and change.

How to cite: Schmid, D., Loridan, T., and Shaylor, M.: Metryc and DeepCyc: Pioneering Tools from Reask in Disaster Risk Financing and Humanitarian Impact Mitigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15454, https://doi.org/10.5194/egusphere-egu24-15454, 2024.

EGU24-15783 | ECS | Orals | ITS4.10/NH13.1

AutoVal: A framework for scientific validation of flood catastrophe models 

Ashleigh Massam, Douglas Burns, Owen Jordan, Barbara Nix, Niamh O'Malley, Philip Oldham, Brijkishore Sahu, and Ksenija Vasiljeva

Catastrophe models are complex numerical models that simulate extreme events to estimate the economic cost of natural disasters, usually developed by model providers and adopted by clients in the (re)insurance, finance, and other sectors. Before adopting a model, the model user typically engages in an evaluation process that can be a challenging and resource-intensive task, and challenging for non-experts. This process is not standardised across the industry, so model users need to establish their approach from scratch. Yet effective evaluation is repetitive and takes time and resources – an effort that is being duplicated across organisations and teams, which would be better placed on an exploratory side of testing that progresses knowledge and understanding of models. By automating the repetitive part of model evaluation, data visualisations and results can be reproduced quickly. This would allow for more frequent assessment, leading to an improved understanding of the limitations of catastrophe models and increased confidence in the insights gained from using a catastrophe model.

We present AutoVal, a catastrophe model evaluation tool that automates standard loss validation tests. The premise of AutoVal is very simple: third party data is transformed at the point of use into benchmark expectations, for assessment against catastrophe model outputs. In our work to date, third party insurance claims data or published estimates of event losses are used to calculate average annual losses, loss exceedance curves, and map spatial and temporal distributions of loss for comparison with modelled estimates. Further work is ongoing to expand the capability of AutoVal to evaluate components within the natural catastrophe model, including vulnerability functions and hazard maps.

AutoVal can aid model users from both industry and academic backgrounds through the application of standard, repeatable tests. It assists with the effective review of model configurations across a range of perils or scenarios, allowing decision makers to better understand model sensitivity and behaviour. AutoVal also has the potential to remove the repetition in model evaluation, allowing for more frequent model evaluation and faster feedback loops between developers and users. In this presentation, we will share our progress so far with designing and automating the evaluation of our catastrophe models, including – but not limited to – standardised schemas for benchmark data, validation exercises to assess modelled estimates of loss, and new approaches to interpreting model sensitivity.

To realise the potential of AutoVal, we invite colleagues from the risk management sector to discuss our ongoing work towards establishing a set of benchmark tests that can complement industry-wide progress towards consistent and common standards.

How to cite: Massam, A., Burns, D., Jordan, O., Nix, B., O'Malley, N., Oldham, P., Sahu, B., and Vasiljeva, K.: AutoVal: A framework for scientific validation of flood catastrophe models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15783, https://doi.org/10.5194/egusphere-egu24-15783, 2024.

EGU24-15846 | ECS | Posters on site | ITS4.10/NH13.1

Measuring Resilience: A Systematic Meta-Review 

Tony Wei-Tse Hung, Tina Comes, and Giulia Piccillo

Resilience to natural hazards and climate change is a rather wicked and complex subject, such that it requires the knowledge of several disciplines such as economics, governance, engineering, sociology, and environmental science. The intertwining of these different disciplines results in a symphony of clashes and harmony, but all of this relies heavily on the foundations of research methods.

With a PRISMA-guided systematic meta-review on the measurement of social, community, disaster, organizational, urban, and infrastructural resilience angles, 708 records of systematic reviews were filtered down to 29 reviews after snowballing through articles. Through social-computational analysis, our meta-review focuses on three key questions:

  • How are the different resilience reviews related?
  • What are the most apparent resilience characteristics considered?
  • What are some general characteristics of quantitative metrics from different resilience angles?

 

Through our analysis, several insights could be deduced:

  • Through bibliographic coupling, infrastructural resilience reviews are tightly coupled together, and are distinct from the other resilience angles.
  • Using text analysis, such as word clouds and hierarchical clustering, definitions of resilience are diverse and vary within and between resilience angles.
  • By surveying the indicators used in quantifying resilience, there is a clear disconnect between infrastructural resilience quantification and other angles of resilience. In particular, non-infrastructural resilience measurements tend to focus on the inherent capacity approach of resilience, whereas infrastructure resilience tends to capture both inherent resiliency of systems and the performance approach of resilience.

 

Lastly, we have found that infrastructural resilience measurements tend to fixate on the technical domain it is in, whereas urban resilience measurements tend to take a more comprehensive approach encompassing several disciplines. This distinction highlights the need for a comprehensive and integrated approach to measuring resilience. We urge that infrastructural resilience should not solely focus on the functionalities of its systems, but also include the actors, users, and societal dynamics which critical infrastructure systems are embedded in. With the emergence of the System of Systems approach, it is a ripe opportunity to transform beyond disciplinary boundaries and focus on the interdependencies between humans and the built environment.

How to cite: Hung, T. W.-T., Comes, T., and Piccillo, G.: Measuring Resilience: A Systematic Meta-Review, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15846, https://doi.org/10.5194/egusphere-egu24-15846, 2024.

EGU24-16716 | Orals | ITS4.10/NH13.1

Novel instruments for flood risk mitigation in small, fast reacting watersheds by means of sensor integration, advanced computing and socio-technical translation 

Paolo Reggiani, Svenja Fischer, Andreas Kolb, Kristof Van Laerhoven, and Cornelius Schubert

Increasingly frequent extreme hydro-meteorological events, attributable among others to non-stationary climate, can lead to devastating flooding and cause large costs to affected societies. A recent and prominently featured example includes the July 2021 flood in Germany with more than 140 casualties and billions of Euros in material damages. Such types of events could strike other parts of Europe at any time. Especially small-scale systems are likely to be affected more frequently by high intensity events. To ready society against such occurrences, preparedness needs to be increased form different viewpoints: 1) extreme value statistics and forecasting, 2) real-time data acquisition and high performance computing, 3) socio-technical translation into domains.

First, fast and accurate forecasting with reduced uncertainties requires integration of predictors at different spatial and temporal scales. Such predictors must be conditioned by local, real-time information retrieved from multi-sensor systems, whereby special attention is devoted to extreme event statistics. The uncertainty of prediction resulting from sources like forecast model deficiencies, measurement errors, or various critical system states, need to be adequately represented, as well as de-biased and sharpened in real-time through statistical approaches.

Second, real-time acquisition of local data plays an essential role in risk detection. To this end, novel sensor system integration must provide robust real-time information, either on the basis of flexibly positioned or body-mounted devices. The extended complexity of the methods involved make the efficiency of the computational methods and the integration of model-driven physical processes with data driven approaches and ubiquitous computing as key factor. This also concerns the reduction of computational complexity without compromising efficacy as well as the efficient interoperability between different system components or scales.

Third, such novel instruments need to be socio-technically translated for decision-makers as well as emergency services and citizens. User involvement needs to be bidirectional, that is, stakeholders and their concerns must be understood and taken seriously for them to gain confidence and adopt innovative, multi-sensor integrated forecasting technologies for risk mitigation. Moreover, proper visual mapping of hazardous situations including uncertainties and potential options for decision-support need to be provided.

 

How to cite: Reggiani, P., Fischer, S., Kolb, A., Van Laerhoven, K., and Schubert, C.: Novel instruments for flood risk mitigation in small, fast reacting watersheds by means of sensor integration, advanced computing and socio-technical translation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16716, https://doi.org/10.5194/egusphere-egu24-16716, 2024.

EGU24-17384 | Posters on site | ITS4.10/NH13.1

Building databases of multi-hazards and compound events 

Carlo De Michele and Fabiola Banfi

Multi-hazards and compound (climate-related or weather-related) events are characterized by complex dynamics with interactions between various physical processes across multiple spatial and temporal scales. Examples of these include the joint/successive occurrence of landslides and floods, or heatwaves, droughts, and wildfires.

In literature, databases of natural hazards are in general single hazard, like databases of floods (European Flood Database, AVI database), landslides (Global Fatal Landslide Database, AVI database), droughts (European Drought Observatory).

The assessment and understanding of multiple hazards and compound events require an integrated perspective, with the integration of data from multiple variables, combining multiple databases.

Here, we try to address this emerging need, illustrating a possibility of building a database of multi-hazards/compound events, and presenting some examples.

How to cite: De Michele, C. and Banfi, F.: Building databases of multi-hazards and compound events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17384, https://doi.org/10.5194/egusphere-egu24-17384, 2024.

EGU24-17789 | ECS | Orals | ITS4.10/NH13.1

Comprehensive assessment of hazard, exposure, and vulnerability using a new database of climate impact indicators to identify hotspots for adaptation needs 

Michaela Werning, Edward Byers, Daniel Hooke, Marina Andrijevic, Volker Krey, and Keywan Riahi

In the 21st century, an increasing global population will be exposed to various risks caused by climate change. The impact depends not only on the geophysical climate change hazards, but also on the population’s vulnerability, its spatial distribution, and its capacity to adapt. Here we present a new database of climate impact indicators at various global warming levels (1.2 - 3.5°C) using global climate and hydrological model data from the latest Coupled Model Intercomparison Project (CMIP6) and Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b) simulation rounds.

Indicators include a variety of temperature and precipitation extremes, heatwaves, drought intensity, hydrological variability, and water stress. Building on previous work (Byers et al. 2018),  the first novel aspect of this work is the development of a bi-variate hazard index that includes statistics on the absolute hazard level (e.g. low or high precipitation) and the relative change under global warming compared to the historical baseline (e.g. a large change from low to high precipitation).

We combine this new index with gridded projections of population from the Shared Socioeconomic Pathways (SSPs) and land area to calculate temporal and spatial exposure.  Finally, to allow for risk assessment, we introduce the layer of vulnerability measured through various socio-economic indicators, such as income, inequality, or the Notre-Dame Global Adaptation Index (ND-GAIN).

In aggregate, we find that impacts manifest substantially even in the near-term at lower global warming levels. For example, even at 1.5°C 93% of the population of South Asia will face a medium exposure to heatwave events. Countries predominantly in the low latitudes and global south are comparatively more severely affected by multiple climate impacts. The window for reducing the risk burden is rapidly closing while there is substantial unavoidable risk even at 1.5C, thus adaptation actions will be key. By analysing impact and vulnerability hotspots, our work can help identify these adaptation needs, i.e. for financial assessments or loss and damage, down to high spatial resolution but also at the country level. With further categorisation, we can assess populations at the highest risk, such as those with high impacts, high vulnerability and lowest institutional governance capacities.

How to cite: Werning, M., Byers, E., Hooke, D., Andrijevic, M., Krey, V., and Riahi, K.: Comprehensive assessment of hazard, exposure, and vulnerability using a new database of climate impact indicators to identify hotspots for adaptation needs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17789, https://doi.org/10.5194/egusphere-egu24-17789, 2024.

When evaluating a view of risk for the purposes of pricing insurance business or mitigating potential large losses, one salient question that arises is whether the view is representative of the present-day. What time-period the ‘present-day’ represents is not a trivial decision, as it very much depends on the timeframe of the business you insure. An insurer that specialises in high-frequency transactions may choose to adopt a transient short-term view of risk, whereas insurers involved with real estate (e.g. mortgages) would require a much longer, stable view of the present-day to encapsulate the longevity of their liabilities. This study presents a framework and example of reconditioning a long-term historical modelled baseline, as one might determine from any catastrophe model, for North Atlantic Hurricane towards a 5-year medium-term present-day. This study takes a data-driven compartmentalised approach to reconditioning hurricane risk, by separately adjusting storm frequency, intensity, regionality and the temporal distribution of storms (i.e. storm clustering), such that each component is explicitly accounted for. This study aims to elucidate on the most pertinent sources of uncertainty present when reconditioning a view of risk, with application beyond hurricane risk.

The results of this study suggest a coherent poleward shift in hurricane risk along the contiguous US coastline, alongside a general increase in hurricane risk. The explicit representation of clustering supports non-local inter-hurricane dependency and subsequently a change in the relationship between two key insurance metrics, the occurrence loss (max in a given year) and the aggregate loss (sum in a given year).

How to cite: Webber, C.: Reconditioning a North Atlantic Hurricane View of Risk to a Chosen Present-Day, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17991, https://doi.org/10.5194/egusphere-egu24-17991, 2024.

EGU24-18130 | ECS | Orals | ITS4.10/NH13.1

Towards hurricane impact forecasting for the Dutch Caribbean   

Nadia Bloemendaal, Rob Sluijter, Jos Diepeveen, and Elco Koks

The Royal Netherlands Meteorological Institute (KNMI) has been responsible for weather forecasting in the Dutch Caribbean (Bonaire, St. Eustatius and Saba – the BES islands) since 2016. And while weather patterns in the Caribbean often exhibit homogeneous characteristics, this region is also prone to some of the most violent storms on earth in the form of hurricanes. The most infamous example of this is Hurricane Irma (2017), which passed close to Saba and St. Eustatius but made a direct landfall on and severely impacted several other Caribbean islands, including Sint Maarten. Over 90% of the buildings on St. Maarten were damaged, including most of the infrastructure on the island. The estimated damage totaled to be around 2.7 billion USD (approximately 200% of the country's GDP).  

With its extensive weather forecasting expertise as a solid foundation, KNMI is now moving towards impact-based forecasting through the development of the Early Warning Centre (EWC). For the BES islands, this means that we will design a hurricane impact model, combining KNMI's forecasting experience with impact modeling expertise nested within academia. With respect to the latter, we follow the traditional risk modeling approach and set up a hazard – exposure – vulnerability type of model chain. In such model chain, it is predominantly the choice of hazard data that determines the nature and applicability of the output data. For instance, (ensemble) forecast tracks provide insights into possible impacts of an imminent hurricane. Similarly, using synthetic hurricane tracks from a statistical model like STORM will result in a full spectrum of risk and associated probabilities. We will also incorporate local knowledge to develop and improve exposure and vulnerability input data. 

In this presentation, we discuss the different input datasets needed to build an impact model, and how the different output products can assist weather forecasters in better understanding the impact of imminent hurricanes in the Dutch Caribbean.

How to cite: Bloemendaal, N., Sluijter, R., Diepeveen, J., and Koks, E.: Towards hurricane impact forecasting for the Dutch Caribbean  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18130, https://doi.org/10.5194/egusphere-egu24-18130, 2024.

EGU24-19407 | Posters on site | ITS4.10/NH13.1

Realistic storm surge scenarios for UK (re)insurers 

Carlotta Scudeler and Iain Willis

The UK has experienced several coastal floods over the last century, which have threatened the society and the (re)insurance industry. The Winter of 2013/2014 was especially notable, in that several events have largely affected many different areas in England as 50 defence breaches occurred. Thus, simulating credible scenarios, capable of capturing the likelihood of coastal flood events arising at different locations during the same storm and modelling the impact of breaching of defence, is crucial to both disaster management planning as well as the insurance industry. In this study, which was carried out jointly by the Gallagher Research Centre and the research partner HR Wallingford (HRW), two extreme but realistic UK storm surge scenarios were developed separately for the East and West coasts of UK. The scenarios explore simultaneous flooding along extended coastline and the impact of realistic defence breaching, both in the present day and in 2050. A high-resolution footprint for each scenario run (present day non-breach, present day breach, future non-breach, and future breach) was generated by means of a 2D hydrodynamic model run on a 5m LiDAR Digital Elevation Model. Flood breaching was based on a national set of fragility curves created by HRW’s defence model. To account for climate change, the UKCP6 (UK climate projections) were used to assign the projected RCP 4.5 surge estimates for 2050. Finally, the loss potential for each simulated footprint was estimated for Gallagher Re’s insured market portfolio. Among the major findings of the analysis, it is shown how defence breaching has a significant impact on the potential loss, particularly for the East coast scenario, for which it results in a 10x increase in the number of properties affected. Climate change has also two impacts, on the number of properties flooded, but also on the depth of flooding experienced by properties already at risk, further exacerbating the potential loss. Finally, it is shown how these Realistic Disaster Scenarios are supporting UK (re)insurers in helping stress test their exposure to storm surge, while helping build a robust view of risk.

How to cite: Scudeler, C. and Willis, I.: Realistic storm surge scenarios for UK (re)insurers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19407, https://doi.org/10.5194/egusphere-egu24-19407, 2024.

EGU24-19535 | ECS | Posters on site | ITS4.10/NH13.1

Bridge Failure and Consequences: the Existing Infrastructures Need of Mitigation Techniques 

Pietro Giaretta and Paolo Salandin

Bridges represent a critical issue in case of hazardous events, like extreme floods and debris flows, being their proper operation of fundamental relevance to avoid cascading effects on population.

The reduction of the risk of failure of river crossings is fundamental to ensure the service given by the infrastructural network for the safety of the populations. The serviceability of the road and railway network must be guaranteed during hazardous events, when the efficiency of the infrastructure becomes fundamental to ensure the mobility of the rescue and a possible evacuation of the inhabitants during critical situations. Moreover, the safety of the bridge affects the surrounding environment with impacts on social and economic activities, representing a connection between different populations living along the sides of the river.

Hydraulic phenomena are responsible of more than 50% of bridge failure (e.g. Montalvo et al., 2020; Wardhana & Hadipriono, 2003), and scouring around piers and abutments always causes serious damages if proper deepening of foundation is not provided in the design. These aspects are exacerbated due to the climate change that in the last decades increases the frequency of extreme events, occurring flood events more often than in the past (e.g. Seneviratne et al., 2021). Lacks in scientific and technical knowledges have led in the past to the realization of inadequate foundations, and this fact joined with the occurrence of hazardous events in the climate change context, amplifies the risk of failure of bridges. However, many bridges realized in the past are actually still working probably thanks to the ancient custom of filling the riverbed around bridge piers and abutments with stones and boulders after relevant flood events as an empirical maintenance technique.

Therefore, the effectiveness of the described technique to reduce the risk of failure needs to be investigated to establish its effectiveness. Here this is done by physical modelling of the sediment-flow-structures interaction, technique that leads the possibility to check the performances of countermeasures like riprap mattresses, investigating the size of the boulders, the lined area, and their durability over time.

The experiments have been developed in a rectangular flume 1 m wide and 15 m long, using quite uniform sands (median grain size d50=0.4mm) to simulate the riverbed. Different pier geometries and water depths are considered in the experiments developed in steady state clear water conditions. According to the Froude and Shields similitudes, different arrangements and boulders size have been tested, evaluating the scour evolution in long time experiments.

The effectiveness of the aforementioned maintenance techniques is analysed to understand the reduction of the risk of failure of bridges to limit the resulting cascading effects.

How to cite: Giaretta, P. and Salandin, P.: Bridge Failure and Consequences: the Existing Infrastructures Need of Mitigation Techniques, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19535, https://doi.org/10.5194/egusphere-egu24-19535, 2024.

EGU24-20037 | ECS | Orals | ITS4.10/NH13.1

From systemic risks to systemic resilience: A pathways approach for disaster and climate risk management in Malawi and South Africa 

Edward Sparkes, Davide Cotti, Albert Manyuchi, Stern Kita, Nkemakonam Naomi Ukatu, Samira Pfeiffer, Saskia E. Werners, and Michael Hagenlocher

To comprehensively manage the impacts from hazards and disasters, a nuanced understanding of the systemic nature of risks is needed. The effects of natural hazards, climate change and other human-generated shocks transcend borders, sectors and systems, highlighting the interconnected nature of risks. The lack of resilience in one sector can propagate risks across multiple other sectors, and interventions in response can generate trade-offs and unintended negative consequences leading to maladaptation. This emphasises that not only do we need to analyse risk from a systemic perspective, we must also approach risk management and adaptation to consider interconnected positive and negative cascading effects. 

Despite recent progress in complex risk assessment, translating information into actionable inputs for risk management remains a challenge. These challenges are especially pressing in countries burdened by increasing exposure to natural hazards and extreme climate effects. To support addressing this challenge, we integrated a novel  systemic risk analysis method named Impact Webs (Sparkes et al., 2023) with a pathways approach, to co-create disaster and climate risk management pathways with stakeholders, using the Republics of Malawi and South Africa as case studies. 

Impact Webs are system-oriented conceptual risk models that identify interconnections between hazards, risks, impacts, interventions, drivers of risks and root causes, mapping their interaction  across different sectors and at various scales. We co-developed Impact Webs with stakeholders, building on them to identify lessons for risk management adopting a pathways approach. Pathways are a flexible planning approach that incorporates stakeholders’ perspectives into decision making, reducing path dependencies and managing trade-offs. Decisions are taken based on how future conditions unfold. Our pathways development was also driven by stakeholders’ inputs, first using Impact Webs to identify entry points for risk management options. Barriers to implementing options were then identified, as well as enabling conditions to overcome them. We then engaged with potential trade-offs and positive cascading effects, identifying pathways for Malawi and South Africa that could strengthen resilience across multiple sectors. We took a transformational pathways approach, developing pathways for wide-ranging system changes needed to reach high resilience futures. The work was done over four workshops with a range of expert stakeholders, and was complemented by desk study and interviews.

Reflecting on the approach, a challenge arose in sequence actions, i.e., justifying the selection of one risk management option before another. This was due to developing pathways at the national scale across many sectors, therefore they were not targeted towards a specific decision or group of decision-makers. Despite this, the integration of the Impact Webs and pathways provides a useful methodology to move from systemic risk analysis to systemic risk management. Collecting feedback from stakeholders during the workshops, the co-creation process, and engaging with the visual output of an Impact Web, helped them think about risks and risk management in an interconnected manner, by considering cascading effects and response risks of interventions. This can foster understanding among decision makers about the interdependencies between sectors, thus supporting disaster and climate risk management that strengthens system-wide resilience across multiple sectors.

How to cite: Sparkes, E., Cotti, D., Manyuchi, A., Kita, S., Naomi Ukatu, N., Pfeiffer, S., Werners, S. E., and Hagenlocher, M.: From systemic risks to systemic resilience: A pathways approach for disaster and climate risk management in Malawi and South Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20037, https://doi.org/10.5194/egusphere-egu24-20037, 2024.

EGU24-21292 | ECS | Posters on site | ITS4.10/NH13.1

Analysis of extreme hydrological events over the Great Hungarian Plain based on Earth Observation data 

Edina Birinyi, Anikó Kern, Dániel Kristóf, Roland Hollós, and Zoltán Barcza

In Hungary, especially in the Great Hungarian Plain, hydrological cycle related extreme events – such as floods, inland excess water and droughts – are recurrent problems of increasing economic importance. These extremes often occur in the same area and sometimes within the same growing season, largely affecting agricultural production and raising questions related to water conservation and potential land use adjustments. In addition to climate change, the regulation of large rivers and poor water management are also likely to influence the phenomenon. The last major extreme events occurred in 2022 (drought) and 2023 (inland excess water). Relevant studies are mostly based on meteorological data, with one of the most comprehensive describing the frequency of extremes for the period 1931–2010. However, based on more than two decades of MODIS time series, it is possible to analyze variables such as vegetation conditions and water-covered areas, and hence, to investigate the relationship between the vegetation state and the environmental factors. Our study attempts to provide objective, time-series based statistical evidence specifically on the vulnerability of arable lands of the Great Plain and the relationship between environmental and EO-based variables for the period 2000-2023. In addition to spectral indices and land surface temperatures and their anomalies derived from MODIS measurements, land cover (CORINE), meteorology (FORESEE), soil moisture (ERA5-Land), soil properties (DoSoReMi), optical-based relative inland excess water incidence map (1998–2023), radar-based relative inland excess water incidence maps (2020– 2023), as well as aggregated yield loss compensation claims submitted to the Agricultural Risk Management System are included in the analysis. All the variables are aggregated to a spatial grid of 1-km resolution, and their relationship is analysed with mathematical methods (e.g. BORUTA, linear regression). Project no. 993788 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the KDP-2020 funding scheme and by the TKP2021-NVA-29 project of the Hungarian National Research, Development and Innovation Fund and by the OTKA FK-146600 and by National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014 project.

How to cite: Birinyi, E., Kern, A., Kristóf, D., Hollós, R., and Barcza, Z.: Analysis of extreme hydrological events over the Great Hungarian Plain based on Earth Observation data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21292, https://doi.org/10.5194/egusphere-egu24-21292, 2024.

Climate change remains one of the greatest challenges of the 21st century. Humans are not only the key driver of climate change, but are also affected by its consequences, with profound impacts on human life arising through changes in environmental and social circumstances. Climate change impacts on human behaviour are observed via two principle data types which both reflect daily human activity: social media and mobility data. Specifically, social media data are employed to analyse temperature impacts on hate speech online. Even though links between temperature and physical aggression are known, it remains unclear how these patterns extend to online environments, where hate speech can have detrimental consequences for the mental health of the affected persons. Using machine learning classifiers to identify hate speech in four billion geolocated tweets, we show that temperature has strong non-linear impacts on the occurrence of online hate speech across the USA with hate-tweet levels remaining low at moderate temperatures but sharply rising during both hot and cold extremes. This pattern persists across income groups, religious beliefs, and election outcomes and even various climate zones, including those where heat is common which suggests adaptation limits to hot temperatures. A complementary analysis for six European countries finds quasi-quadratic, nonlinear temperature impacts on digital racism and xenophobia across Europe. To assess not only the impacts of heat but also the ability to adapt we employ mobility data from New York City. An analysis of daily passenger data of more than 400 subway stations over six years shows that there is not only a strong, non-linear temperature impact on subway usage but also disparities between neighborhoods with respect to the capacity for heat mitigation. Correlations between neighbourhood-level mobility reductions and socioeconomic indicators suggest that the ability to reduce mobility on hot days is afforded by those that also hold other privileges, hence leading to unequal, compounding health impacts in disadvantaged neighbourhoods. Finally, we harness a combination of mobility data, Google search trends and Covid-19 data to explore how behavioural responses may develop under a prolonged or repeated risk exposure. The econometric approach explores changes in the response to Covid-19 risk through two channels: risk perception and the resulting behavioural response, i.e. mobility reduction. Across both channels, the risk response diminishes over time even before the availability of vaccines. This highlights the attenuation of behavioural responses to prolonged risks, with implications for managing long-term crises such as increasingly repeated exposure to weather extremes under ongoing climate change.

How to cite: Stechemesser, A.: Living in a warming world – climate impacts on society , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21492, https://doi.org/10.5194/egusphere-egu24-21492, 2024.

Nighttime Light (NTL) data, offering insights into cross-regional human activities and infrastructure changes, has gained widespread use in disaster monitoring. This study explores the application of NASA's Black Marble daily data in monitoring post-typhoon responses. In a landscape characterised by a high mix of urban built-up areas and peri-urban villages, we investigate differences in nighttime light recovery across various land-use types after disasters. Combining interpretable machine learning, we explore the reasons behind these disparities by comparing Shapley values and specific Accumulated Local Effects (ALE) between regions, evaluating high importance of individual predictive factors and identifying potential non-linear patterns and threshold effects.
  Our findings reveal more instances of sustained nighttime light decline in rural areas (residential and agricultural land), while urban areas exhibit increased nighttime light during disasters. These differences primarily relate to infrastructure features, especially roads. Meteorological factors, such as precipitation probability and wind speed, impact NTL predictions in urban and rural areas. Post-disaster relief activities significantly influence NTL changes in rural settlements. Additionally, the occurrence of extreme weather increases the likelihood of cascading disasters. Our study finds that disaster impact zones in coastal areas extend deeper into the mainland, posing threats to adjacent mountainous regions and elevating the risk of secondary disasters like landslides.
  In conclusion, this study provides a regional assessment of resilience differences and influencing mechanisms using nighttime light data. It offers valuable information for policymakers to identify key factors influencing typhoon disaster resilience, enabling them to mitigate systemic risks and enhance overall system resilience. The significance of this research extends to serving as a valuable reference for data-driven recovery quantification from typhoon hazards and other crises.

How to cite: Ma, Y.: Urban-Rural Disparity in Disaster Resilience: Harnessing Nighttime Light Data and Interpretable Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21837, https://doi.org/10.5194/egusphere-egu24-21837, 2024.

EGU24-1285 | ECS | PICO | ITS2.11/NH13.2

The contribution of participatory decision making in the planning of ecosystem-based adaptation 

Mar Riera Spiegelhalder and Luís Campos Rodrigues

Inland and coastal floods are becoming more frequent and severe, affecting natural and socioeconomic systems. Coastal urban areas, where population and economic activity are highly concentrated, appear as particularly vulnerable to these events. Local adaptation to climate change benefits from the integration of opinions from different stakeholders in the design and decision process, helping practitioners, planners, and policy makers to address climate change. This process can be operated under the umbrella of Living Labs, where innovative solutions to specific problems can be defined, designed and created through a social-iterative approach. Multicriteria analysis (MCA) is a suitable decision-making tool to develop within the context of Living Labs and climate change adaptation as it allows to capture perceptions from different actors about adaptation measures characterised though various criteria. This study presents the results of an MCA applied to the evaluation of Ecosystem-based Adaptation (EbA) to flooding in three Coastal City Living Labs of the Iberian Peninsula: An ex-ante analysis in Vilanova i la Geltrú (Spain) focused on potential measures to be implemented in an intermittent river-stream; Benidorm (Spain) followed an interim evaluation of planned EbA to address flooding in different city areas; and an ex-post analysis was performed in Oeiras (Metropolitan area of Lisbon; Portugal) to assess the perception of different stakeholders about the performance of already implemented measures along a river stream.

How to cite: Riera Spiegelhalder, M. and Campos Rodrigues, L.: The contribution of participatory decision making in the planning of ecosystem-based adaptation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1285, https://doi.org/10.5194/egusphere-egu24-1285, 2024.

Due to the particularity of geographical location, coastal areas are not only affected by climate change and urbanization, but also affected by the lower boundary jacking caused by sea level rise, so it is easier to form a flood process with "high peak, large quantity and short duration". This study comprehensively considered future climate change, land use change, and sea level change, combined with hydrological model, simulated the flood process of the Qianshan River Basin in the future, and explored the effects of multiple future environmental changes on flooding in the coastal area. The results show that the flood characteristics of Qianshan River Basin will increase due to multiple future environmental changes, and the increase rate will increase with the increase of future scenario level. Among them, the increase of peak discharge is the largest in Dachong; The increase of peak water depth is the largest in Hongwanchong under normal conditions and Guangchangchong under extreme conditions; The location of the inundation has not changed obviously, and it is mainly concentrated in the southern part of the basin; The high risk areas showed a significant increase trend, and concentrated in Tanzhou Town and outlet of Qianshanshuidao. The increase pattern of these flood characteristics basically follows: In the future SSP126, SSP245, SPP370, and SSP585 scenarios, the flood characteristics produced by a design rainfall of grade n correspond to those produced by a design rainfall of grade (n+1), (n+2), (n+3), and (n+4) in the current period, respectively.

How to cite: Yao, Z. and Huang, G.: Effects of multiple future environmental changes on flooding in coastal area: A case study of Qianshan River Basin, South China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2240, https://doi.org/10.5194/egusphere-egu24-2240, 2024.

EGU24-4725 | PICO | ITS2.11/NH13.2

Coastal Dynamics of Thua Thien Huế, Vietnam: Insights from 35 Years of Earth Observation Data 

Felix Bachofer, Ronja Lappe, Hoang Khanh Linh Nguyen, Dang Giang Chau Nguyen, Patrick Sogno, Tobias Ullmann, and Claudia Kuenzer

For the entire shoreline of Vietnam, a comprehensive analysis spanning from 1984 to 2021 was conducted. The study employed a cloud-based processing strategy on Google Earth Engine, utilizing Landsat-derived annual composites based on the Modified Normalized Difference Water Index (MNDWI). Coastline change rates were quantified using linear regressions along shore-normal transects, and hotspots were identified based on erosion and accretion rates. Notable erosion hotspots were observed in the Mekong Delta and Nam Dinh province, while accretion was prominent near Hai Phong city.

The coastal region of Vietnam, including Thua Thien Hue province, is exceptionally susceptible to sea level rise, storm surges and changing sedimentation patterns due to urbanization, agriculture, aquaculture, tourism, and industrial activities competing for limited and attractive coastal zones. Thua Thien Hue, home to the largest lagoon in Southeast Asia, the Tam Giang-Cau Hai lagoon, emerged as a unique case emphasizing the significance of understanding and monitoring coastline dynamics. An extensive dune, stretching across approximately 70 km, acts as a natural barrier, separating the lagoon from the sea. This region encompasses a distinctive ecosystem, agricultural expanses, aquaculture ventures, and the culturally rich City of Hue, once the imperial capital boasting numerous heritage sites. The hinterland, sheltering this amalgamation of natural and cultural treasures, faces the recurrent challenge of compound flooding events. These events are intensified by the interplay of storm surges from the sea and associated backwater effects. Given this, comprehending the historical dynamics becomes imperative, serving as a cornerstone for informed decisions on future adaptation strategies in the realms of coastal and flood protection.

More than half of Thua Thien Hue's coast was classified as predominantly stable, but localized erosion and accretion patterns revealed varying dynamics. The central finding was the identification of five local hotspots with strong coastline change rates. These hotspots exhibited dynamic patterns of erosion and accretion, notably at the Thuan An inlet and in Tu Hien in the south of Hue province.

The Thuan An inlet showcased an erosion hotspot with an average erosion rate of -4 m/yr over 900 meters. This erosion intensified in the 2000s, stabilizing after 2014, illustrating the temporal variability of coastal dynamics. Conversely, on the opposite side of the lagoon inlet, a headland was identified as an accretion hotspot with an average rate of +3 m/yr and alternating phases of erosion and accretion. Severe erosion hotspots were also noted north and south of the lagoon inlet in Tu Hien.

Thua Thien Hue's coastline changes are multifaceted but understudied. They are probably influenced by sediment redistribution, reduced coastal sediment availability, and direct human interventions. Despite the overall stability of most parts of the coastline, the localized changes underscore the intricate interplay of natural and anthropogenic factors shaping the coastal dynamics of Thua Thien Hue over the past three and a half decades.

 

How to cite: Bachofer, F., Lappe, R., Nguyen, H. K. L., Nguyen, D. G. C., Sogno, P., Ullmann, T., and Kuenzer, C.: Coastal Dynamics of Thua Thien Huế, Vietnam: Insights from 35 Years of Earth Observation Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4725, https://doi.org/10.5194/egusphere-egu24-4725, 2024.

EGU24-5640 | ECS | PICO | ITS2.11/NH13.2

Integrated Hydrological Modeling of Climate Change Scenarios on Future Flood Estimations: A Case Study of Bafra Subbasin in the Black Sea Region, Türkiye 

Şule Haliloğlu, Neslihan Beden, Vahdettin Demir, Sema Arıman, Nazire Göksu Soydan Oksal, and Bahtiyar Efe

A primary concern about climate change is the possible rise in the frequency and severity of extreme meteorological/climatological events, like heat waves, intense storms, severe flooding, or droughts. Extreme precipitation events are predicted to increase in size and frequency due to climate change, which could result in more frequent and severe river flooding. Hydrological modeling is integral to accurately deriving flow hydrographs, which is crucial for hydraulic models. This study employs various statistical distributions to assess future simulations' rainfall-runoff relationship and project flow hydrographs under climate change scenarios in the Bafra subbasin of the Black Sea Region. The investigation centers on obtaining flow hydrographs for the Bafra subbasin in the Black Sea Region. The annual maximum precipitation value for the relevant year is determined from daily total precipitation values, and its compatibility with statistical distributions is systematically evaluated. The modeling process considers two climate change scenarios, a moderate radiative forcing scenario (RCP 4.5) and a warming scenario (RCP 8.5), extending projections from 2006 to 2100. The RCP 4.5 and RCP 8.5 scenarios’ data sets are sourced from the Coordinated Regional Climate Downscaling Experiment (CORDEX) data for future estimations. MNA-44 domain that covers Türkiye with a horizontal resolution of 0.44 degrees and 232 points in longitude and 118 points in latitude is used. An accurate determination of flow hydrographs is essential in hydrological modeling. Various statistical distributions, such as Normal Distribution, Log-Normal (2 Parameters), Log-Normal (3 Parameters), Pearson Type-3 (Gamma Type-3), Log-Pearson Type-3, and Gumbel distributions, are employed to identify the most suitable distribution, and the base flow is taken as the current 95% of the time for flow hydrographs. The goodness of fit tests using the Kolmogorov-Smirnov test are conducted to assess distribution types.

As a result of the conducted analyses, in the RCP4.5 flow hydrograph, the Q50 value is determined as 334.7 m3/s, the Q100 value as 350.5 m3/s, and the Q500 value as 382.3 m3/s. In contrast, in the RCP8.5 flow hydrograph, these values are obtained as 395.5 m3/s, 429.4 m3/s, and 506.1 m3/s, respectively. Accordingly, in the pessimistic scenario, the discharge amount that would lead to flooding is 18% higher at Q50, 22% higher at Q100, and 32% higher at Q500. The integration of statistical analyses and climate scenarios enhances the accuracy and reliability of flood estimations, contributing to a comprehensive understanding of the potential impacts of climate change on hydrological processes in the Black Sea Region. In further studies, hydraulic modeling of the flood will be carried out using the Hydrologic Engineering Center - River Analysis System (HEC-RAS) with the most appropriate hydrographs that are obtained from future simulations (RCP 4.5, RCP 8.5). The inundation area of the flood will be computed employing this model, and the hydrological impacts resulting from diverse climate simulations will be acquired through two-dimensional modeling, thereby enhancing comprehension.

How to cite: Haliloğlu, Ş., Beden, N., Demir, V., Arıman, S., Soydan Oksal, N. G., and Efe, B.: Integrated Hydrological Modeling of Climate Change Scenarios on Future Flood Estimations: A Case Study of Bafra Subbasin in the Black Sea Region, Türkiye, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5640, https://doi.org/10.5194/egusphere-egu24-5640, 2024.

EGU24-8109 | ECS | PICO | ITS2.11/NH13.2

Investigating Extreme Wave-Induced Runup in Villanova, Spain: A Comparative Analysis of Extreme Value Models 

Iulia Anton, Roberta Paranunzio, Michele Bendoni, Sudha-Rani Nalakurthi, Salem Gharbia, and Luca Baldini

Coastal cities are increasingly vulnerable to the impacts of extreme wave-induced runup (ssh-runup), which can cause significant damage to infrastructure, ecosystems, and human life. A comprehensive understanding of the characteristics and future trends of extreme ssh-runup is crucial for effective coastal risk management and adaptation strategies. This study employs extreme value analysis (EVA) to investigate wave-induced runup (ssh-runup) in Villanova, Spain, a coastal community participating in the SCORE project's Coastal City Living Labs initiative.

Historical (1956-2005), evaluation run (1980-2018), and future (2015-2094) ssh-runup data are analyzed under two representative concentration pathways (RCP 4.5 and 8.5). Four statistical models are applied for EVA: Block Maxima Generalized Extreme Value (GEV) with L-moments using Gumbel and Peak Over Threshold (POT) Generalized Pareto Distribution (GPD) with a 98% threshold and a constant threshold (0.82). Model performance is evaluated using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), as well as different plots (e.g., QQ plot). Results indicate that the GPD model performs consistently better than the other methods in all datasets. The GPD model exhibits a slight improvement over GEV and other models in the historical and evaluation runs, while it outperforms GEV and other models significantly in future projections. This suggests that the GPD model is better suited for capturing the increasing trend in extreme ssh-runup under climate change scenarios.

The findings of this study provide valuable insights into the characteristics and future trends of wave-induced runup in Villanova, aiding in coastal risk assessment and adaptation planning. Applying different EVA techniques highlights the importance of selecting the most appropriate model for the specific data and context. These findings contribute to the understanding of coastal hazards and inform the development of effective adaptation strategies to mitigate the risks associated with extreme wave-induced runup.

How to cite: Anton, I., Paranunzio, R., Bendoni, M., Nalakurthi, S.-R., Gharbia, S., and Baldini, L.: Investigating Extreme Wave-Induced Runup in Villanova, Spain: A Comparative Analysis of Extreme Value Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8109, https://doi.org/10.5194/egusphere-egu24-8109, 2024.

One of the most significant consequences of climate change that is already felt today and will be felt even more in the future is the frequency and severity of natural disasters. Of those, sea-caused floods and storm surges will have the biggest impact on coastal communities, which will be further potentiated on one hand by the sea level rise and on the other by increasing coastal population and economic activity which will make those communities even more vulnerable. As the underlying causes of extreme weather events cannot be circumvented, alternatively it is feasible to decrease the flood vulnerability of most affected areas and implement the right flood control measures. But before any steps can be taken in this direction it is of the utmost importance to analyse the patterns of such events and to establish an early warning system that will allow the local community to respond to such events in a timely manner. Slovenia keeps records on natural disasters to inform civil protection services for performing mobilizing actions during calamity interventions, and an environmental agency that keeps records on past weather conditions through various stationary land and sea sensors. In the case of coastal storms, the latter informs the first, as a matter of public safety during potentially emerging extreme weather conditions giving rise to coastal flooding. Piran, a coastal historic town situated on a narrow peninsula surrounded by North Adriatic Sea waters, is especially vulnerable to coastal floods with 7.3 floods per year on average occurring generally from October through March. Low-lying parts are especially flood-prone, of which the areas below 2.3 m above sea level cover a large percentage of the town covering a mixture of residential, commercial and cultural heritage buildings. With no long-term preventative sustainable measures yet in place and urban sensors 4 to 15 km away from the town, the early warning system does not rely on local climate services but uses general national forecasts. Here we combine the historic records on past flooding events and environmental data to understand the local flood patterns in Piran. This study aims to offer a more nuanced understanding of flood patterns in Piran through the combination of localized field-report and sensor systems from national databases to reliably enhance the precision of flood predictions. The study underscores the pivotal role of accurate, localized data to be extracted from national or regional registries where available that aid in fortifying coastal towns against the escalating impacts of climate change, safeguarding both the inhabitants and the invaluable architectural heritage of historic areas.

 

How to cite: Kralj, E., Kumer, P., and Meulenberg, C.: Insight into temporal and spatial coastal flooding through databases with historic meteorological data and national registry-reported natural disaster events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12104, https://doi.org/10.5194/egusphere-egu24-12104, 2024.

EGU24-13455 | PICO | ITS2.11/NH13.2

Creating the world’s first Weather Risk Free & Climate Resilient area: WeRISE Project  

Michail Elaiopoulos, Ciro Borrelli, Takehiro Oyama, Hiroki Watanabe, Michelle Boella, Emanuele Giorgi, Antonino Caliri, Roberto Minerdo, and Federico Ottavio Pescetto

“WeRise” is a medium scale, applied research, cooperative project, initiated in the coastal communities of the central east Italian peninsula, in the coasts of Abruzzi Region. The project aims in evaluating an holistic approach to address existing and future weather and climate risks. The central pillars of the proposed solutions consist in providing hyper-localized, high accuracy weather alerts and climate analysis (50, 100 and 150 years), integrated with all civic activity, from infrastructural project design to urban planning and economic development of the whole region. From an architectural and IT point of view, the project consists in a digital comunication platform that, from one side enables citizens to access high accuracy weather alerts and climatic projections, while give to local governments a power tool to stay connected with the citizens and coordinate activities in cases of extreme weather events and disasters. Of course the system represents also a powerfull approach to disaster preparedness and prevention. WeRise employs a two-phased strategy - an initial pilot application that involves 12 comunities in the cities of Lanciano, San Vito Chietino, Ortona and Francavilla al Mare, followed by a regional scale up designed to integrate around 100K citizens. The pilot phase focuses on deploying and testing technology in a controlled environment, assessing its effectiveness in real-world settings. The project aims to bring a new level of precision to weather alerts and risk management, directly benefiting both infrastructure planning and communities’ safety. Primary goals include enhancing weather resilience at the local level, improving emergency response mechanisms, and supporting informed decision-making in urban planning and economic activities. Initial findings from the pilot phase indicate a significant impact on community preparedness and risk mitigation, promising for broader applications. The project’s next steps involve expanding the tested approach to larger, more diverse regions, with an aim to evaluate and develop a national-scale model to organically manage weather and climate risks in Italy.

How to cite: Elaiopoulos, M., Borrelli, C., Oyama, T., Watanabe, H., Boella, M., Giorgi, E., Caliri, A., Minerdo, R., and Pescetto, F. O.: Creating the world’s first Weather Risk Free & Climate Resilient area: WeRISE Project , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13455, https://doi.org/10.5194/egusphere-egu24-13455, 2024.

Climate change and sea level rise is expected to increase the flood risk in coastal regions. These areas will not only suffer from more frequent and severe storm surges, it will also become increasingly challenging to naturally discharge the excess water from rivers and precipitation. Large pumping stations along the coast can contribute in discharging excess water if high sea levels prevent the natural outflow. A large pumping station is already employed in the Netherlands at IJmuiden, which is responsible for the drainage of a large area in the western Netherlands, including cities as Amsterdam and Utrecht. Pumping stations will often not function at full capacity due to failures, maintenance, or high sea water levels that may reduce the operational pump capacity or even exceed the operational threshold.  Pump reliability can have a significant effect on the flood risk in a water system and thereby strongly influence the optimal investment strategy. Nevertheless, the influence of pump reliability is not considered when designing pumping-sluice stations.  Two separate approaches (graphical and computational modelling) were developed in this study to include pump reliability in when determining the required buffer and pump capacity in a water system. The graphical approach is most suitable for comprehensive visualizations and sensitivity analysis of the water system, while the computational modelling approach allows for a more detailed analysis. Including pump reliability in the design can lead to an increase in required buffer capacity or pumping capacity. However, it can also optimize the mitigation strategy and prevent unnecessary investments as the sensitivity of water systems depends on the system’s characteristics such as water storage capacity.

How to cite: Van Gijzen, L. and Bakker, A.: The effect of the reliability of pumping stations on coastal flood risk under a changing climate , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16618, https://doi.org/10.5194/egusphere-egu24-16618, 2024.

EGU24-18125 | ECS | PICO | ITS2.11/NH13.2

Are the physical barriers sustainable to saltwater intrusion under changing climatic conditions? 

Rajagopal Sadhasivam, Venkatraman Srinivasan, and Indumathi Nambi

Physical barriers such as subsurface dams (SSD) and cutoff walls (COW) and hydraulic barriers such as freshwater recharge and saltwater pumping are some of the widely studied control measures to mitigate saltwater intrusion (SWI) in coastal aquifers. Past studies have focused on optimizing the design of these control measures, including installation location, depth, pumping, and injection rates under the specified hydraulic and boundary conditions of the aquifer. On the other hand, sea-level rise (SLR) and freshwater flux reduction (FFR) (caused by groundwater pumping and/or reduced aquifer recharge) alter the hydraulic conditions and can potentially change the optimum design of these control measures as well as their performances. Unlike hydraulic barriers with some potential to adapt to these altered hydraulic conditions (by modifying pumping and injection rates), physical barriers are fixed and not easily modifiable. Hence, the performances of physical barriers are highly subjected to changing climate conditions (SLR and FFR), and systematic vulnerability assessment of physical barriers is lacking. Here, we use a widely studied field-scale problem to assess the vulnerability of SSD and COW under SLR and FFR scenarios using constant flux inland boundary conditions. Our results indicate that SSD and COW are resilient to SLR, with SSD being more effective compared to COW. Furthermore, SSD and COW are highly vulnerable to FFR. While SSD is more effective than COW under small declines in FFR, COW outperforms SSD under large FFR. Using sensitivity simulations, we show that our results are valid across a range of aquifer and barrier parameters. These results add insights to the design of physical barriers, taking into account future climatic conditions. Also, our analysis aids in selecting appropriate mitigation measures to address the changing climatic conditions.

How to cite: Sadhasivam, R., Srinivasan, V., and Nambi, I.: Are the physical barriers sustainable to saltwater intrusion under changing climatic conditions?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18125, https://doi.org/10.5194/egusphere-egu24-18125, 2024.

EGU24-18909 | ECS | PICO | ITS2.11/NH13.2

Assessment of Coastal Concrete Structures Exposed to Extreme Weather Conditions using Concrete Petrography (ASTM C856) 

Audrei Anne Ybañez, Nancy Aguda, Kate Cuyno, Jeremy James Jimenez, Chelly Mei Tanpoco, Reyno Antonio, and Carlo Arcilla

Concrete is used worldwide; however, it is susceptible to fluctuations in temperature and exposure to moisture. Coastal concrete structures, in particular, are exposed to extreme conditions brought about by hydrometeorological processes. The Philippines, as a maritime country, is highly dependent on its coastal structures for its economic development, mobility, and national defense. The country is exposed to the impacts of extreme conditions and natural hazards by virtue of its geologic setting.

In this study, concrete assessment is applied to three major ports using concrete petrography complemented by standard physical tests. Petrography offers information on concrete composition, distribution of air voids, water-cement ratio used, depth of carbonation, and the presence and degree of cracking and concrete deterioration phases. The use of petrography in concert with physical testing greatly expands the understanding of the impacts of extreme coastal conditions to these port structures. Structures assessed exhibited carbonation of the cement paste and the presence of cracking, alkali-silica reaction, and delayed ettringite formation. The researchers investigated further, the possible causes of the concrete degradation including the material sources, the existing coastal and climatological conditions on site, and past extreme weather events such as tropical storms and high waves. These technical findings will contribute to the formulation of standards and recommendations on appropriate concrete cover thickness and mix designs for the assurance of resilient coastal concrete structures in the face of extreme weather conditions.

How to cite: Ybañez, A. A., Aguda, N., Cuyno, K., Jimenez, J. J., Tanpoco, C. M., Antonio, R., and Arcilla, C.: Assessment of Coastal Concrete Structures Exposed to Extreme Weather Conditions using Concrete Petrography (ASTM C856), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18909, https://doi.org/10.5194/egusphere-egu24-18909, 2024.

EGU24-18919 | ECS | PICO | ITS2.11/NH13.2

Impacts of Climate Change on Small Island Nations: A Data Science Framework using Remote Sensing and Observational Time Series 

Myriam Prasow-Émond, Yves Plancherel, Philippa J. Mason, Matthew D. Piggott, and Jonas Wahl

Small Island Developing States (SIDS) comprise a group of 58 nations identified by the United Nations as facing unique sustainability challenges. These challenges include high exposure to climate change and a lack of data and limited resources. The effects of climate change are already observed in SIDS, notably an increase in the magnitude and frequency of natural disasters, biodiversity loss, ocean acidification, coral bleaching, sea-level rise, and coastal erosion. The coastal zone is considered to be the main economic, environmental, and cultural resource of SIDS, making them particularly vulnerable to the adverse effects of climate change. This project focuses on quantifying and disentangling coastal changes, including erosion, accretion and coastline stability. Existing literature lacks a comprehensive understanding of the patterns of coastal changes, as well as the main anthropogenic and environmental drivers involved. We address this research gap by quantifying the challenges that SIDS encounter, with a particular emphasis on coastal changes.

The approach is data-driven, relying on observational time series extracted from remote sensing (e.g., Sentinel-2, Planet Scope, Landsat missions), in situ measurements (e.g., tide gauge data), and open-access databases. We have developed a robust method based on image segmentation to extract the island's shape over time, enabling us to illustrate the island's dynamics and obtain reliable time series of the coastline position.

 The main drivers of coastal changes are then identified and quantified using time series analysis methods, including causal inference and discovery methods, for SIDS worldwide. We place a specific focus on the Maldives (Indian Ocean) due to its low elevation and high human activity. Additionally, the methodology expands to investigate a spectrum of issues, including the impacts of human activities (e.g., land reclamation, sand mining, shoreline armouring) on the natural responses of coastlines, as well as the effects of confounding factors or common drivers (e.g., Indian monsoon, tropical cyclones, and El Niño/Southern Oscillation). The ultimate goal is to develop a spatiotemporal variable coastline vulnerability index by integrating socioeconomic and environmental time series data, facilitating the assessment of environmental policies in SIDS.

How to cite: Prasow-Émond, M., Plancherel, Y., Mason, P. J., Piggott, M. D., and Wahl, J.: Impacts of Climate Change on Small Island Nations: A Data Science Framework using Remote Sensing and Observational Time Series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18919, https://doi.org/10.5194/egusphere-egu24-18919, 2024.

EGU24-19086 | ECS | PICO | ITS2.11/NH13.2

Evaluation of atmospheric forces induced by extreme Bora wind on a high-rise hospital in the coastal city of Trieste, Italy 

Petros Ampatzidis, Carlo Cintolesi, Andrea Petronio, and Silvana Di Sabatino

Extreme weather events dominate the disaster landscape of the 21st century and disaster risk is becoming systemic with one event overlapping and influencing another in ways that are testing our resilience to the limit. This is particularly true for critical infrastructure, such as hospitals, that are vital to the functioning of society but have received limited attention in terms of investment in prevention, climate change adaptation and risk reduction. One of the most severe weather events, present in mountainous coastal areas is the Bora wind, a strong and often gusty regional katabatic wind generated by cold and dry air spilling down from a mountain range. The Bora wind has been studied extensively from a meteorological point of view. However, there is limited research on its consequences on the critical infrastructure of coastal urban areas, particularly tall buildings that are susceptible to high wind and wind-driven rain. In Europe, strong Bora winds are encountered on the east coast of the Adriatic Sea. The scope of this study is to assess the Bora-wind-induced atmospheric forces exerted on the high-rise Cattinara hospital in Trieste, Italy, a location where strong Bora winds often occur during the autumn and winter seasons and an increased risk of functionality loss is present. High-resolution RANS simulations are performed for the hospital and the surrounding buildings over the complex and mountainous topography of the area. The imposed boundary conditions approximate the extreme February 2012 Bora wind event that saw gusts of more than 40 m/s in the region. The results provide an evaluation of the methodological framework, assess the inherent complexities of atmospheric simulations over intricate landscapes and demonstrate that a comprehensive understanding of the aerodynamic loads is imperative for mitigating potential vulnerabilities in critical infrastructure subjected to such extreme meteorological phenomena. The study is conducted within the remit of the HORIZON-EU project RISKADAPT (Asset Level Modelling of RISKs in the Face of Climate-Induced Extreme Events and ADAPtation) that seeks to provide solutions to support systemic, risk-informed decisions regarding adaptation to climate change induced compound events at the asset level.

How to cite: Ampatzidis, P., Cintolesi, C., Petronio, A., and Di Sabatino, S.: Evaluation of atmospheric forces induced by extreme Bora wind on a high-rise hospital in the coastal city of Trieste, Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19086, https://doi.org/10.5194/egusphere-egu24-19086, 2024.

In the intricate tapestry of coastal urban areas, the realities of climate change unfold with discernible impacts across regions like Nigeria, Chad, Cameroon, Rwanda, Somalia, and Kenya. Experiencing a spectrum of climate-related challenges, from extreme weather patterns to rising sea levels, these areas underscore the pressing need for proactive measures. The Lake Chad Basin, encompassing Nigeria, Chad, and Cameroon, grapples with heightened climate upheavals, exacerbating existing insecurities. Simultaneously, nations in East Africa, such as Rwanda, Somalia, and Kenya, navigate the repercussions of unpredictable weather patterns affecting agriculture, water resources, and community livelihoods. The humanitarian community, entrenched in its response, often finds itself constrained by the reactive nature of interventions. Here, the transformative potential of predictive analysis and artificial intelligence (AI) shines a light on proactive measures. Consider the INFORM Climate Change Index1, a forward-looking projection providing quantified estimates of climate change impacts on the future risk of humanitarian crises and disasters. Developed through collaboration between the Euro-Mediterranean Center on Climate Change and the Joint Research Centre of the European Commission, this innovative index modifies indicators in the hazard and exposure dimensions based on projected climate and socio-economic trends. The link between anticipatory humanitarian action and predictive analysis becomes more apparent when we delve into the numbers. Incorporating digital solutions, especially AI, significantly boosts the effectiveness of anticipatory measures. Recent initiatives show that when predictive analysis, AI-driven solutions, and innovative indices are integrated, a substantial percentage of climate-related events can be avoided. These digital tools empower coastal urban communities to construct preemptive barriers, devise effective mitigation strategies, and navigate challenges with resilience. The transformative impact is not just theoretical; it's quantifiable, with numbers indicating that a significant portion of potential crises can be averted through proactive measures informed by predictive analytics. This groundbreaking approach, where digital solutions are seamlessly integrated into anticipatory humanitarian action, transforms coastal urban communities from mere responders to architects of their climate destinies. The narrative, rooted in real-world examples and bolstered by numerical evidence, showcases the tangible benefits of technology. The path forward involves AI, predictive analysis, and innovative indices as indispensable tools in scripting resilience stories. As we explore the depths of climate-induced insecurities across diverse regions, the abstract underscores the pivotal role of AI, coupled with innovative indices like INFORM Climate Change, in guiding coastal urban communities towards a future where climate challenges are met with informed, proactive, and resilient responses.

1https://drmkc.jrc.ec.europa.eu/inform-index/INFORM-Climate-Change

How to cite: Ndatabaye, S., Dabiri, Z., Lang, S., and Wendt, L.: Anticipatory Climate Resilience in Coastal Urban Areas: Transformative Impact of Predictive Analysis, AI Solutions, and Innovative Indices, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20281, https://doi.org/10.5194/egusphere-egu24-20281, 2024.

EGU24-21671 | PICO | ITS2.11/NH13.2

Does everyone speak English? 

Julian Mühle, Julie Ann Ewald, and Robert Eyres Kenward

Now, more than ever, the ‘eye-in-the-sky’ needs to work with the ‘grunt-on-the-ground’. This is
not just a matter of ground-truth checks on accuracy of remote mapping. For biodiversity
forecasts, of abundance, threats and restoration for species and systems, one needs to map not
only ground cover, but soil and water quality and content, not to mention individuals of small
species. Beneficial activities at local community and citizen level are needed too, as well as
guidance and motivation from above. This will require engagement and love of nature as well as
the support of governments that enable services from nature and do not ignore climate change.
Encouraging benefits at local level, and linkage with guidance or imagery from above, requires
simple communication and for conservation chores to become fun. It requires conservation
communication networks for the 80% in the world who do not speak English. Ideas for
transacting local knowledge as an enjoyable engagement were developed in a Framework 7
project to design a Transactional Environmental Support System but considered too challenging
socially. This verdict stimulated multilingual networking in the civic sector, leading to 10-
language www.sakernet.org (2014) and 23-language www.perdixnet.org (2017) for UNEP and
NGOs, before 43-language www.naturalliance.org was launched for IUCN in 2019. A new
Horizon project is now addressing issues of social motivation for engagement with such systems
in a project for A PROactive approach for COmmunities to enAble Societal Transformation which
is running from November 2023 for 3 years. PRO-COAST (project 101082327) brings together 20
partners from 14 countries to develop, apply and validate an innovative socio-ecological
framework for the study of coastal ecosystem dynamics for the benefit of the people most
exposed to risk deriving from biodiversity loss. Starting in 9 case studies across Europe, it will
develop scaled-up multilingual networking for much wider areas along coasts and inland, using
the global-with-local information networking developed by European Sustainable Use Group.

How to cite: Mühle, J., Ewald, J. A., and Kenward, R. E.: Does everyone speak English?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21671, https://doi.org/10.5194/egusphere-egu24-21671, 2024.

Hydropower dams can lead to changes in the access and use of surrounding natural resources, such as land and water. However, in complex socio-ecological systems (SES), taking into consideration different temporal and spatial scales, dams can be just one of the shocks suffered by the SES. Changes in a SES are not linear and can be part of a cycle of causes and effects in a large chain of system processes. We explore these connected processes in the context of Colombia’s Andean region, one of the hotspots of hydropower expansion in the world. This area is also responsible for 70% of the Colombia's agricultural production. We investigated two large hydropower dams: El Quimbo (Huila Departament) and Hidrosogamoso (Santander Department). This study aims to analyze the changes in land-water systems related to cash crops production and the drivers of these change from the commissioning of the dams until recent years (2009 to 2020). Our goal is to understand how perceived changes in the land-water system are induced (or not) by the construction and operation of the dam and how this influence interacts with other global and regional shocks. We conducted 80 semi-structured interviews with representatives of the agricultural sector from the main food chains (palm oil, coffee, cocoa, and rice), and with government representatives responsible for managing the land and water systems. Regional land use and land cover change maps, national agricultural data and hydropower licenses were used to sample design. The influence of the dams in land use patterns regarding crops was different depending on the geographical location of the crops (downstream or upstream dams, and north or south of the Andes), and on the water and land demands for these crops. For example, in the case of rice, an irrigated crop, interviewees declared that the effects of the dam were minimal, unlike the case of coffee, which predominantly uses rainwater for production. In addition, there are some evidence that the influence of the dams in certain crops had indirect effects in some ecosystems, such as the case of oil palm and the wetlands ecosystems. These indirect changes also increased inequalities, as interviewees from large oil palm owners reported that they were switching to an irrigated system, while smallholders would keep relying on rainwater. We also found that global drivers might be able to mask the effect of local drivers, e.g., climatic variability and the variation in commodities prices in comparison to the influence of the dams. Another example are the changes in agricultural practices induced by the increase in prices of fertilizers due to the war in Ukraine, which illustrates the fact that several drivers, including external ones, are concomitantly influencing transformations in land-water system. This study highlights that the influence of certain shocks in SES, such as large infrastructures, cannot be analyzed separately from other concomitant processes, but in a broader perspective, investigating how these processes interact with each other. Different shocks, such as dams, can also aggravate disputes over land and water resources and increase inequalities.

How to cite: Salomão, C., Nascimento, N., and Lima, L.: Beyond energy production: A local perception about the drivers of change in land-water systems for cash crops production surrounding Colombian water reservoirs., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1199, https://doi.org/10.5194/egusphere-egu24-1199, 2024.

EGU24-2446 | ECS | Orals | ITS3.4/NH13.4

Navigating uncertainties: an interdisciplinary approach to land use management in favour of the water cycle  

Itxaso Ruiz, Ambika Markanday, Noelia Zafra, and Marcela Brugnach

Exacerbated by climate change, water scarcity in the Mediterranean basin poses one of the most significant environmental challenges in the region, compromising adaptation capacities. Current knowledge of how forests contribute to rainwater recycling, i.e. by increasing evapotranspiration and promoting orographic precipitation, has led to the proposal of forest management strategies to mitigate desertification in the western Mediterranean basin. Focusing on a case study in eastern Spain, where formerly arable lands are today covered by dense forests, we reflect on the uncertainties that arise from this relation between land use changes and orographic precipitation at the watershed scale. We aim to transform the encountered uncertainties into actionable opportunities for adapting this territory to ongoing climate change. To support the development of intervention strategies that increase climate resilience, we use an interdisciplinary approach that integrates participatory processes for co-designing sustainable land management measures and a systematic literature review from which we identify the physical and biophysical uncertainties arising from the rainwater recycling hypothesis. In search of practical applications, we are developing a decision support game to test the implementation conditions of the management strategies. This game provides decision-makers with a tool to assess how the proposed measures align with the needs, capabilities, and willingness of local stakeholders, and it also enables reflecting on potential trade-offs. This research contributes to strengthening the water cycle through adaptive land management and, thus, promoting a more resilient western Mediterranean basin.

How to cite: Ruiz, I., Markanday, A., Zafra, N., and Brugnach, M.: Navigating uncertainties: an interdisciplinary approach to land use management in favour of the water cycle , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2446, https://doi.org/10.5194/egusphere-egu24-2446, 2024.

Monitoring mulch-based solutions to reduce runoff and erosion in a variety of land uses in the Alentejo agro-silvo-pastoral systems

 

Canedo, J.1*, Coelho, L.1, Basch, G.1, Cabrita, M.J.1, Cachapa, F.1, Caldeira, F.1, Gonzalez-Pelayo, O.1,2, Marques, T.1,  Muñoz-Rojas, J.1,4, Palma, P.3, Pinto-Correia, T.1, Pinto-Cruz, C.1, Tomaz, A.3, Prats, S.A.1

1MED (Instituto Mediterrâneo para a Agricultura, Ambiente e Desenvolvimento) & CHANGE – Global Change and Sustainability Institute, Universidade de Évora, Pólo da Mitra, Ap. 94, 7002-554 Évora, Portugal.

2CESAM (Centro de Estudos do Ambiente e do Mar), Universidade de Aveiro, 3810 – 193 Aveiro, Portugal.

3Instituto Politécnico de Beja – Departamento de Tecnologias e Ciências Aplicadas, Edifício da Escola Superior Agrária, Campus do Instituto Politécnico de Beja, Rua Pedro Soares, 7800-295 Beja, Portugal.

4DPAO (Departamento de Paisagem, Ambiente e Ordenamento) – Universidade de Évora, Colégio Luis António Verney, Rua Romão Ramalho, 59 7000-671 Évora, Portugal.

 

*Corresponding author: joao.canedo@uevora.pt

 

Soil erosion is a critical socio-environmental problem for rural Mediterranean ecosystems and landscapes. Erosion inflicts multiple, serious damages in agro-ecosystems, including vineyards and olive groves, and also in other semi-natural ecosystems such as the Montado (cattle-sheep pastureland combined with Quercus sp. trees). In particular, erosion reduces the water storage capacity, soil organic matter, nutrients and valuable soil biota, which are transported off-site with runoff water. Nature-based solutions, such as the application of organic mulching, reduces runoff and soil erosion between 40% and 90%, respectively. Agri-forest residues such as olive and vineyard by-products can also be transformed to biochar and applied to the soil, increasing soil organic matter, soil moisture and, ultimately, improving the soil status and agronomic soil properties.

Our aim was to verify the effects of the application of combined mulch and biochar upon the mitigation of runoff and soil erosion. Runoff-erosion experimental plots were developed to independently measure runoff, by using pressure sensors, and erosion, by emptying, drying and weighing the sediments stored in sediment fences. A total of 60 plots were installed and monitored during 3 months in olive orchards, vineyards and Montado, which were consistently treated with mulch (2 Mg ha-1 straw/olive leaves) and mulch + biochar (2 Mg ha-1 straw + 10 Mg ha-1). All plots were located across Alentejo, the region of Portugal with a most marked Mediterranean climate.

Preliminary results showed that mulch reduced runoff peakflows in 7% and mulch + biochar reduced it in 28%. Soil erosion was reduced around 60 and 80%, respectively. There were important differences between olive orchards, vineyards and Montado systems. In general, the vineyards and olive orchards are much more prone to erosion when compared to the Montado. Further research is being carried out and will allow the assessment of the effects of mulch and mulch + biochar in other ecosystem services, such as water retention, carbon storage, soil habitat protection and soil fertility.

 

Keywords: Agriculture, climate change, sustainability, water storage, soil fertility

 

How to cite: Gomes Vicente Canedo, J. N.: Monitoring mulch-based solutions to reduce runoff and erosion in a variety of land uses in the Alentejo agro-silvo-pastoral systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5589, https://doi.org/10.5194/egusphere-egu24-5589, 2024.

EGU24-6526 | ECS | Posters on site | ITS3.4/NH13.4

Seasonal movement behavior of goats related to grazing intensity and environmental variability using Hidden Markov Models 

Hua Cheng, Kasper Johansen, Baocheng Jin, and Matthew Francis McCabe

Key research in movement ecology is investigating shifts in animal behavior and identifying the factors that induce alterations in movement behavior and mechanics. The impact of natural environments and human activities on the underlying behavioral processes of domestic goats are still being elucidated. We applied seasonal multivariate Hidden Markov Models (HMMs) to characterize the fine-scale movements (30- second intervals) of GPS-tracked Zhongwei goats for 124 days and determine how grazing intensity, seasonal food resources, terrain factors and daylight hours affect movement behavior in the mountain grassland in China. We classified the goats’ activities as two basic behavioral states of foraging (low step length, varied and undirected turning angle) and travelling (long step lengths, low and directed turning angles). Grazing intensity, a management factor, exerted the most significant influence on goats across different seasons. Additionally, factors such as daylight hour and slope had a more pronounced impact on their movement activities compared to the normalized difference vegetation index (NDVI). Elevation and solar radiation were found not explain much of the variability in movement behavior of goats. Their probability of foraging behavior was most likely to increase with grazing intensity, slope, diurnal hours and NDVI. In addition, the percentage time allocation of foraging was higher in spring and winter with lower food resources periods and shorten daylight hours, than summer and autumn with larger food resources and long daylight hours. The foraging percentage increased from morning to afternoon. HMMs are found useful for disentangling movement behavior and understanding how goats respond to seasonal grazing intensity, time of daylight, NDVI and slope. Our findings underscore the importance of accounting for interactions between movement behavior and gazing management, not only the environmental factors and behavioral rhythms, when assessing the movement characteristics and behavioral transitions of goats. These results are important for designing grazing management strategies that satisfy ecological and socioeconomic demands on mountain grassland ecosystems.

How to cite: Cheng, H., Johansen, K., Jin, B., and McCabe, M. F.: Seasonal movement behavior of goats related to grazing intensity and environmental variability using Hidden Markov Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6526, https://doi.org/10.5194/egusphere-egu24-6526, 2024.

EGU24-7209 | ECS | Posters on site | ITS3.4/NH13.4

Synergies of Land Use Land Cover and Climate Change on Water Balance Components in SSP–RCP Scenarios over Munneru basin, India 

Loukika Kotapati Narayanaswamy, Venkata Reddy Keesara, and Eswar Sai Buri

The growing human population accelerates alterations in land use and land cover (LULC) over time, putting tremendous strain on natural resources. Rapid land use transformations, encompassing urbanization, intensive agriculture, and changes in natural landscapes, have a profound impact on water cycle. This necessitates the development and implementation of sustainable land management strategies to mitigate adverse effects on water resources. Anticipating future land use and cover (LU&LC) dynamics in the Munneru river basin is pivotal for modelling of hydrological processes. This study delves into the combined impact of Land Use and Land Cover Scenarios (LU&LC) which is based on Shared Socioeconomic Pathway (SSP2-45, SSP3-75 and SSP5-85) and climate change within the context of representative concentration pathway (RCP 4.5 & RCP 8.5) scenarios on water resources for Munneru river basin, India. Landsat data was employed for preparing LU&LC maps from the Google Earth Engine (GEE) using the random forest (RF) method for the period 2005-2020 with the accuracy of 91% and kappa coefficient of 0.89. The future scenarios of LU&LC’s were projected by integrating Global Change Assessment Model (GCAM) data and DynaCLUE model for 2030, 2050 and 2080. DynaCLUE model uses driving factors, Binary Logistic Regression analysis for past LU&LC maps for projecting future LU&LC maps. The SWAT model is calibrated and validated for the period 1983–2017 in SWAT-CUP using the SUFI2 algorithm for 2015 LU&LC map. The future projected LU&LC maps based on SSP’s are incorporated in SWAT model for future periods under both RCP 4.5 & 8.5 scenarios. The average monthly streamflow’s are simulated for the baseline period (1983–2005) and for three future periods, namely the near future (2021–2039), mid future (2040–2069) and far future (2070–2099) under both LU&LC and climate change scenarios. Results indicate that there is increase in surface runoff and water yield and decrease in evapotranspiration, groundwater and total aquifer for three SSP scenarios under both RCP’s. Assessing the impact on water balance components, provides the necessity for adaptive strategies in the face of shifting climate and land use dynamics.

How to cite: Kotapati Narayanaswamy, L., Keesara, V. R., and Buri, E. S.: Synergies of Land Use Land Cover and Climate Change on Water Balance Components in SSP–RCP Scenarios over Munneru basin, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7209, https://doi.org/10.5194/egusphere-egu24-7209, 2024.

EGU24-10846 | Posters on site | ITS3.4/NH13.4

Canal use purposes impact the water quality: a case study within the Life Green4Blue project floodplain area  

Mauro De Feudis, Gloria Falsone, William Trenti, Andrea Morsolin, and Livia Vittori Antisari

Most of the floodplain ecosystems in the world have been reclaimed for allowing urbanization and agriculture. In reclaimed floodplains, water is addressed in artificial canals which could have several purposes such as irrigation, soil draining, hydraulic safety of the floodplain and source of biodiversity. In this context, the main aim of the present study was to evaluate the influence of artificial canal use (irrigation and receiving canals) crossing the Life Green4Blue project floodplain area on water quality. The study area is located within the Po plain (Italy) characterized by heavy reclamation activities for agricultural purposes in the last century. The irrigation canals, used for agricultural purposes, are fed during summer season (from April to September) by the Emiliano Romagnolo Canal which carries water from the Po River. The receiving canals, larger than irrigation canals, are mainly used as discharging canals for both irrigation and draining canal and to lesser extent for irrigation purposes. During the autumn and winter seasons (from October to March), both type of canals is used for hydraulic safety of the investigated floodplain area by keeping the water level of them low. The water survey was monthly conducted from the beginning of 2020 till December 2023. The cluster analysis (CA) showed a clear distinction between water of receiving canals and that from irrigation canals. According to the principal component analysis (PCA), the differences were mainly related to the amounts of nutrients and salts. In fact, water of receiving canals was characterized by higher amount of nutrients (e.g., N–NH4, Ca, K, Mg, P and S) and higher values of electrical conductivity (EC). The poorer water quality of receiving canals can be attributed both to the water origin, namely soil leachates and water of irrigation canals that already flowed for several kilometres the agricultural land, and the absence of freshwater inflow. Therefore, the water quality index (WQI) showed higher value for the irrigation canals (67) compared to the receiving ones (61). For both canals’ type the PCA highlighted the worsening of water quality during the autumn and winter (AW) seasons. Indeed, during AW seasons a greater loading of nutrients and EC were observed compared to spring and summer (SS) seasons. The higher load of nutrients in AW compared to SS might be due to the higher nutrient leaching from soils resulting from the higher rainfalls occurring in AW seasons. In addition, the lower water flow during AW seasons prevented a ‘dilution effect’ and allowed a greater exchange of both cations and anions from the bed sediments. However, it was interesting to observe that the water quality worsening during the AW seasons was marked for irrigation canals compared to receiving ones suggesting the major role of freshwater input on water quality of such type of canals. The present study highlighted the importance of canal use on water quality. Specifically, in a view of a sustainable conservation of floodplain ecosystem services, this study showed the needing to ensure the input of freshwater in all canals’ type and throughout the year.

How to cite: De Feudis, M., Falsone, G., Trenti, W., Morsolin, A., and Vittori Antisari, L.: Canal use purposes impact the water quality: a case study within the Life Green4Blue project floodplain area , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10846, https://doi.org/10.5194/egusphere-egu24-10846, 2024.

EGU24-14569 | ECS | Posters on site | ITS3.4/NH13.4

Fine mapping of crop patterns in the North China Plain from 2013 ‒ 2022 

Liang Dong, Di Long, Caijin Zhang, Yingjie Cui, and Bridget R. Scanlon

A nuanced understanding of crop patterns is pivotal for accurate crop yield and irrigation water use calculations, holding profound implications for national food security and sustainable environmental development. In the water-scarce North China Plain (NCP), where agricultural intensity faces challenges due to groundwater suppression and ecological restoration, this study employs random forest classification on Sentinel-2 Multispectral Instrument (MSI) and Landsat 8 Operational Land Imagery (OLI) time series to reveal the spatial and temporal dynamics of crop patterns from 2013 to 2022. Our classification, featuring a finer scheme (nine categories), higher spatial resolution (10/30 m), and extensive field sampling points, aligns well with China's statistical yearbooks. The annual mapping exposes a shift towards economic forests, mainly from other food crops, across all NCP provinces. Distinct spatial patterns emerge, with wheat-maize rotation decreasing at higher latitudes, countered by an increase in single maize and economic forests. Despite these shifts, wheat-maize rotation remains dominant, and seasonal fallow is concentrated in regions with poor irrigation, notably in groundwater funnel areas. Overall, our crop pattern mapping provides a robust dataset for water conservation and land management, contributing to regional resilience planning.

How to cite: Dong, L., Long, D., Zhang, C., Cui, Y., and Scanlon, B. R.: Fine mapping of crop patterns in the North China Plain from 2013 ‒ 2022, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14569, https://doi.org/10.5194/egusphere-egu24-14569, 2024.

EGU24-16027 | ECS | Posters on site | ITS3.4/NH13.4

Hypoxia exposure of short-term residents in the Qinghai-Tibet Plateau 

Wenyixin Huo and Peijun Shi

The unique habitat and plateau hypoxia in the Qinghai-Tibet Plateau have always troubled tourists. The study of plateau hypoxia is of great significance to improve tourists' well-being and formulate related policies. In this paper, based on the data of oxygen content and blood oxygen saturation of short-term residents in the Qinghai-Tibet Plateau, Qinghai Province was divided into severe hypoxia region, hypoxia region and non-hypoxia region according to the established relationship between blood oxygen saturation and oxygen content. Combined with the results of the spatialization of short-lived population, the exposure numbers of short-lived population under different hypoxic zones in summer and winter were calculated. The results show that: 1) The distribution of tourist population in Qinghai Province presents a distribution rule of "one center gathering", and the population is mainly concentrated in the eastern region. The population density is high in the main urban areas with dense POI, and very low in woodland, remote mountain and other areas. 2) With the decrease of oxygen content, blood oxygen saturation decreased exponentially. 3) Compared with winter, short-term residents is more suitable to travel to the plateau in summer.

How to cite: Huo, W. and Shi, P.: Hypoxia exposure of short-term residents in the Qinghai-Tibet Plateau, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16027, https://doi.org/10.5194/egusphere-egu24-16027, 2024.

EGU24-16294 | Posters on site | ITS3.4/NH13.4

Surface oxygen concentration on the Qinghai-Tibet Plateau (2017–2022) 

Xiaokang Hu, Yanqiang Chen, Wenyixin Huo, Wei Jia, Heng Ma, Weidong Ma, Lu Jiang, Gangfeng Zhang, Yonggui Ma, Haiping Tang, and Peijun Shi

For the ecologically vulnerable Qinghai-Tibet Plateau (QTP), hypoxia is increasingly becoming an extremely important environmental risk factor that significantly affects the health of both humans and livestock in the plateau region, as well as hindering high-quality development. To focus on the problem of hypoxia, it is especially urgent to study the surface oxygen concentration (i.e., oxygen concentration). However, the existing research is not sufficient, and there is a lack of oxygen concentration data collected on the QTP. In this study, through the Second Tibetan Plateau Scientific Expedition and Research and field measurements, the oxygen concentration data and corresponding geographic environmental data were collected at 807 measurement points on the QTP from 2017 to 2022, and the spatiotemporal oxygen concentration patterns were estimated. This work filled the gaps in the measurement and research of oxygen concentrations on the QTP while providing data support for analyses of the influencing factors and spatiotemporal characteristics of oxygen concentrations, which is of great significance for promoting the construction of ecological civilization in the QTP region.

How to cite: Hu, X., Chen, Y., Huo, W., Jia, W., Ma, H., Ma, W., Jiang, L., Zhang, G., Ma, Y., Tang, H., and Shi, P.: Surface oxygen concentration on the Qinghai-Tibet Plateau (2017–2022), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16294, https://doi.org/10.5194/egusphere-egu24-16294, 2024.

High mountains are hotspots of climate and global environmental change. Mountain biodiversity is threatened by quickly rising temperatures which cause vegetation shifts, such as upslope migration. At the same time, natural hazards develop as mountain slopes become increasingly unstable due to permafrost degradation and changes in rain and snowfall regimes. Resulting slope movements, such as rockfalls and debris flows, can limit colonization by plants. However, plants that manage to colonize mountain slopes can stabilize them through their roots and above ground biomass.

Therefore, we believe that an interdisciplinary approach linking ecology and geomorphology is needed as a next step to better understand how climate change affects high mountain landscapes and ecosystems. Combining results from previous geomorphic, ecological and palaeoecological studies, we show that the response of high mountain environments to climate change can depend on the balance between slope movement intensity and the trait-dependent ability of plants to colonize and stabilize moving slopes. For this ‘biogeomorphic balance’ we envisage three possible scenarios: (1) Intensifying slope movements impede vegetation shifts, amplifying instability. (2) Ecosystem engineer species, adapted to moving slopes, stabilize slopes and facilitate shifts for less movement-adapted species. (3) Competitive trees and tall shrubs, shifting on stable slopes, reduce instability but potentially diminish biodiversity. Given the disparate rates of ecological and geomorphic responses to climate change, coupled with high environmental heterogeneity and elevational gradients in in mountains, we anticipate that future biogeomorphic balances will be variable and heterogeneous in both space and time.

To unravel these intricate biogeomorphic balances, we advocate for collaborative research between mountain geomorphologists and ecologists and propose three distinct future directions that combine advancing field measurement, remote sensing techniques and modeling approaches. We believe that by recognizing high mountains as 'biogeomorphic ecosystems', shaped by the interplay of geomorphic and ecological processes, we can improve our ability to safeguard people, infrastructure and ecosystems in mountain environments around the world.

 

References:

Eichel J, Stoffel M, Wipf S. 2023. Go or grow? Feedbacks between moving slopes and shifting plants in high mountain environments. Progress in Physical Geography: Earth and Environment 47 : 967–985. DOI: 10.1177/03091333231193844

How to cite: Eichel, J., Stoffel, M., and Wipf, S.: Go or grow? An interdisciplinary ‘biogeomorphic balance’ concept linking moving mountain slopes and shifting mountain plants, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16482, https://doi.org/10.5194/egusphere-egu24-16482, 2024.

EGU24-16547 | Posters on site | ITS3.4/NH13.4

Exploring runoff sensitivity based on runoff ratio in the UK during 2000 to 2015 

Pei Xue, Dominick Spracklen, and Joseph Holden

The runoff ratio is important in hydrology and water resource management because it helps quantify the efficiency of a watershed or catchment area in handling precipitation. The runoff ratio can vary widely depending on factors such as land cover (e.g., urban, forested, agricultural), soil type and permeability, land slope, and climate.  Some previous research revealed that the number of days of precipitation is the major determinant of runoff ratio, while how runoff sensitivity changes at different ratio has been not fully understood. Here, we use runoff ratio as a hydrological indicator to explore the influencing factors of changes in runoff sensitivity. Since land cover types have not changed a lot in the UK after 2000. We calculated runoff ratio for catchments in the UK during 2000 to 2015 and its sensitivity to a range of controlling factors. This study will outline the key findings on runoff ratio controls, which will then be tested in other regions to determine the relative role of land cover change.

How to cite: Xue, P., Spracklen, D., and Holden, J.: Exploring runoff sensitivity based on runoff ratio in the UK during 2000 to 2015, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16547, https://doi.org/10.5194/egusphere-egu24-16547, 2024.

EGU24-16826 | Posters virtual | ITS3.4/NH13.4

Restoration of pastures under tree canopy: effects of the undergrowth clearing and grazing in the maintenance of herbaceous species diversity and production  

Ana María Foronda Vazquez, Héctor Lafora, Olivia Barrantes, Yolanda Pueyo, Javier Ferrer, and Ramón Reiné

In a context of global change, the mountains of southern Europe have suffered in recent decades processes of land abandonment, leading to the loss of cultural mosaic landscapes, with negative effects on ecological and economic sustainability of agroecosystems. In the framework of the MIDMACC Project (LIFE18 CCA/ES/001099), landscape management measures to adapt marginal areas of Spanish mid-mountain to the impacts of global change have been tested. In this regard, experiences of forest management measures (thinning and undergrowth scrub clearing) followed by grazing with native cattle breeds have been conducted in two reforested areas in “La Garcipollera” valley (Huesca, Spain) to create and maintain herbaceous pastures under tree canopy (one area with Pinus nigra and the other with Populus x canadensis). The effects of forest management and grazing on the floristic composition and production of the herbaceous pasture were analysed in both areas separately. For this purpose, three replicates per each of three typologies of monitoring plots with a surface of 400 m2 were established: i) control plots (without neither forest management nor livestock), ii) managed plots without livestock and iii) managed plots with livestock (2 cows per plot for 48 hours and twice a year). Vegetation surveys were conducted every spring from 2020 in the pine area and 2021 in the poplar area to 2023. In those, the coverage of the bare soil and every plant species growing within four 1m2 subplots per plot were recorded. Additionally, in order to estimate dry biomass (production of the pasture) for the initial and final stage of the experiment, at each plot we collected the plants growing within four 0,5m2 subplots adjacent to the previous. Our results indicated that, after three years of experimentation, forest management decreased the bare soil cover, increased the cover, richness and biomass of herbaceous species and reduced the cover and richness of woody species compared to the control plots. This trend was common for both the pine and poplar areas. In the case of grazing effects, we found that the entry of livestock in the plots in the managed pine areas increased the bare soil cover and herbaceous plants cover and richness but reduced the biomass production and the woody species cover (thus controlling scrub encroachment). Regarding plots in the managed poplar areas, grazing affects differently from pine areas since no significant effects on herbaceous nor woody species cover and richness were found compared to control plots (shorter study period). Nevertheless, a positive effect of grazing was found since bare soil cover was reduced and herbaceous biomass production was increased compared to the plots with no livestock entry. Although in the mid-term (three/two years after the measures) the whole expected effects of grazing are not yet evident, the improvement of the herbaceous species and the control of scrub encroachment by cattle are apparent.

Acknowledgements: This research was supported by the LIFE MIDMACC (LIFE18 CCA/ES/001099), funded by the EC.

How to cite: Foronda Vazquez, A. M., Lafora, H., Barrantes, O., Pueyo, Y., Ferrer, J., and Reiné, R.: Restoration of pastures under tree canopy: effects of the undergrowth clearing and grazing in the maintenance of herbaceous species diversity and production , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16826, https://doi.org/10.5194/egusphere-egu24-16826, 2024.

EGU24-17005 | ECS | Orals | ITS3.4/NH13.4

Alpine vegetation community patterns and implications to eco-hydrology in the Khumbu region, Nepalese Himalaya 

Ruolin Leng, Stephan Harrison, Elizabeth Byers, and Karen Anderson

The Himalayan alpine zone (HAZ) – a high altitude zone above approximately 4100 m.a.s.l., is projected to experience strong eco-environmental changes with climate change. As plants expand their range in this region, the plant-water functioning is likely to be impacted. Satellite remote sensing provides one means of understanding the distribution pattern of HAZ vegetation communities, but the often patchy distribution of alpine vegetation creates challenges when using coarse-grained satellite data whose pixels are typically coarser than the grain of vegetation pattern. Also, the lack of in-situ measurements limits the validation of remote sensing products, and our understanding to the eco-hydrological processes within this area. Here we use fine spatial resolution satellite imagery from WorldView-2 (2 m2 per pixel) coupled with elevation model data from the Copernicus GLO-30 product to produce a land cover classification for HAZ. Grassy meadows and dwarf shrubs belonging to the Rhododendron and Juniperus families dominate the ecology of HAZ in this region so we created three vegetation classes for mapping indicative major plant communities dominated by these species. Based on this land cover map, we compared in-situ measurements in shrubby and open area, to explore the impacts of Rhododendron spp. and Juniperus spp. on temperature under plant canopy. Afterwards, we coupled in-situ measurements with meteorological metrics derived from ERA5, to simulate the evapotranspiration (ET) of these two dominant plant communities. We found that altitude and aspect were dominant drivers of vegetation distribution in HAZ and that the average vegetation cover of Rhododendron spp. and Juniperus spp. reduced with increasing altitude, as expected. South- and east- facing slopes were dominated by Juniperus spp., while north- and west- facing slopes were dominated by Rhododendron spp., and the growth extent of Rhododendron spp. (between 4010 to 4820 m.a.s.l.) and meadow (between 4010 to 4680 m.a.s.l.) were vertically wider than Juniperus spp. (between 4010 to 4660 m.a.s.l.). In general, maximum temperatures under shrub canopies were lower and minimum temperatures were higher compared to unvegetated or open areas at the same location. Juniperus plants had more significant influences on temperature than Rhododendron. Results from this study demonstrate the present vegetation distribution pattern in HAZ at the plant community level, and the potential ET status relevant to the vegetation expansion trend within this area. This study provides an impetus for studies that seek further understanding to eco-hydrological interactions between dwarf plants and water flows and stores in HAZ.

How to cite: Leng, R., Harrison, S., Byers, E., and Anderson, K.: Alpine vegetation community patterns and implications to eco-hydrology in the Khumbu region, Nepalese Himalaya, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17005, https://doi.org/10.5194/egusphere-egu24-17005, 2024.

Groundwater is the primary reservoir of unfrozen freshwater, a critical element in the
water cycle. It is constantly extracted, which has resulted in irreversible depletion.
The significant extraction of groundwater led to a shift in the Earth's rotational pole
and has been attributed to global sea level rise, and disruption of the regional energy
budget. The extraction has influenced the soil quality and the interaction between
surface and subsurface water. The Hindon River basin, situated in the north-western
region of the Ganga plain in India, once witnessed the Indus Valley civilization, is
now facing adverse effects from anthropogenic activities. The groundwater level has
decreased by over a meter in recent decades, and the concentration of dissolved
nitrate, an indicator of pollution, has exceeded safe limits. The pollution in
groundwater has resulted in numerous severe health issues, including cancer and
liver disorders. Consequently, it is crucial to comprehend the human-induced
alterations in the water cycle, focusing on identifying pollutant sources and the
processes responsible for redistribution of water mass among different components
of the regional hydrological cycle. In this study, we have used remote sensing data in
the Soil and Water Assessment Tool (SWAT) to understand impact of crop patterns
on regional water budget. Chemical tracers such as stable water isotopes (δD-H2O,
δ18O-H2O), dissolved nitrate isotopes (δ15N-NO3 , δ18O-NO3 ), and ionic chemistry [NO3- ]
have been used to validate the model results. The initial output of the model
suggests that changes in existing cropping patterns can improve the discharge in the
river.

How to cite: Mandal, R., Sanyal, P., and Samantaray, S.: Agricultural impact on quality and quantity of groundwater in the north-western Ganga plain, India: A stable isotopes and remote sensing approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17140, https://doi.org/10.5194/egusphere-egu24-17140, 2024.

EGU24-17364 | Posters on site | ITS3.4/NH13.4

Sustainability of water transfers in the Crau plain 

Gilles Belaud, Kevin Daudin, Marielle Montginoul, François Charron, Pauline Igbui, Crystele Leauthaud, and Paul Vandôme

The Crau plain, 600 km2 located in South-East France, is mainly associated with the production of high quality hay (around 15,000 ha) irrigated from open-channel networks. Traditional irrigation practices consist in high discharge in order to reach the end of long plots, the excess of water being both drained by run-off to ditches and percolated to the so-called “Crau aquifer”. The aquifer recharge depends for around 70% on hay irrigation, the organization of its management thus relies on the sustainability of irrigation practices. However, hay production faces social and physical pressures from local to regional scales.

  • Socially, water management in the fields requires to be fine-tuned to balance working time dedicated to irrigation (difficult labor conditions with high workload and night shifts) with water flows throughout irrigated plots, farms and canals.
  • Physically, the low-performance hay irrigation is under tension because of local land-use changes due to the development of urban areas and other agricultural production (orchards and horticulture), in a context of hydraulic infrastructures requiring important rehabilitation works.
  • Locally, return flows provide a mix of interdependent services, the aquifer being used for the extraction of drinking water for 300,000 inhabitants, for other irrigated crops like orchards, and for industries.
  • Regionally, water comes from an historical inter-basin transfer, passing through a succession of hydraulic infrastructures and hydroelectric power plant before entering the plain. The climate change impacts on upstream precipitation make incoming water being less abundant, leading to water restrictions as experienced in 2022.

The sustainability of water transfers questions the integration of land and water planning. The aim of our research is to propose an original perspective coupling the characterization of water flows in relation to irrigation practices at the plot and scheme scales with the evaluation of farmers leeway in terms of economic and organizational constraints. The objective of this communication is to present each part of this work and to draw up further correspondences between the hydraulic and economic dimensions. First, an agrarian diagnosis revealed the lack of information on water flows, motivating in turn the original development of affordable measuring devices to track water in an irrigated block and automate parts of irrigation practices. Second, the context of water and land increasing scarcities motivated the characterization of the vulnerability of hay productions in terms of access to water, labor and markets. These studies aimed to directly contribute to water management in the Crau plain, respectively in the search for technical optimization to use water in the agricultural system more efficiently (contributing to reduce working flows) and for the definition and evaluation of strategies for adapting agriculture to meet the challenges of farm economics, groundwater recharge and water conservation. Finally, we will draw on both inputs to assess land cover scenarios and their impacts on aquifer recharge; we may also evaluate possible impacts of water restrictions on land uses.

How to cite: Belaud, G., Daudin, K., Montginoul, M., Charron, F., Igbui, P., Leauthaud, C., and Vandôme, P.: Sustainability of water transfers in the Crau plain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17364, https://doi.org/10.5194/egusphere-egu24-17364, 2024.

EGU24-17956 | ECS | Posters on site | ITS3.4/NH13.4

Multi-temporal assessment of Groundwater Recharge Capacity in Protected Areas of Lithuania 

Marius Kalinauskas and Paulo Pereira

Groundwater recharge is one of the key Ecosystem Services (ES) supplied by protected areas (PAs). However, such drivers as biodiversity loss, climate, and land use change affect the capacity for groundwater recharge (GRC). National-scale PA studies focused on GRC ES are scarce, thus leaving a knowledge gap on a global scale. Therefore, it is critical to map and assess the groundwater recharge spatiotemporal dynamics in supporting human wellbeing. In this study we mapped and assessed GRC at different timeframes (1990, 2000, 2012, 2018, 2022) in the PAs of Lithuania at national scale. For the model we used 15 indicators such as annual average evapotranspiration and precipitation, topographic properties (slope inclination, topographic position index, topographic wetness index, roughness index, curvature index, drainage density, lineament density), lithology, geomorphology, soil (texture, depth, imperviousness), land use (Corine Land Cover, Esri Land Cover). The results show that the highest GRC is observed in PAs to the west of the country, closer to the Baltic Sea, and PAs located in the eastern part of Lithuania with dense network of lakes, less intensive agriculture, fewer impervious areas, and soil properties more suitable for water infiltration. Lesser GRC is observed in urban PAs with higher imperviousness (Vilnius city). PAs in south and southwest of Lithuania with more intense agriculture practices, higher drainage density, and less water bodies also show lower GRC, as well as coastal PAs with sandy soils, no freshwater bodies, and higher roughness. The Kruskal-Wallis test showed no significant difference between GRC spatial distribution through different years due to low variation of evapotranspiration and precipitation values, and lesser land use changes within the PAs. Our findings contribute to a better understanding the spatiotemporal dynamics of one of the key provisioning ES in the Lithuanian PAs – the GRC. Mapping and assessing groundwater recharge support better management of the PAs, and contributes to achieving global and regional (e.g., Sustainable Development Goals, EU Biodiversity Strategy for 2030) policy targets.

How to cite: Kalinauskas, M. and Pereira, P.: Multi-temporal assessment of Groundwater Recharge Capacity in Protected Areas of Lithuania, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17956, https://doi.org/10.5194/egusphere-egu24-17956, 2024.

EGU24-18023 | ECS | Posters on site | ITS3.4/NH13.4

Urbanization and River Health: Analyzing the Effects of Land Cover Change on the Upper Yamuna Basin 

Neenu Neenu and Mitthan Lal Kansal

Rapid urbanization and intensive agricultural practices have resulted in considerable changes in land use and land cover (LULC), underscoring the paramount significance of land cover analysis and change detection assessments for river ecosystems. The Yamuna River, a major tributary of the Ganges, is notably polluted, particularly in the Delhi region3. Thus, the compromised Yamuna River's health in Delhi necessitates an intricate exploration of land change intensity. In this context, the study seeks to enhance comprehension of landscape changes in the urbanized expanse of Delhi and scrutinize their repercussions on the Yamuna River. The Land Change Intensity (LCI) analysis, covering the period from 2016 to 2023, was conducted to examine the evolving dynamics of Delhi's temporal and spatial land use patterns. The LCI analysis assesses land use changes by examining the rate of overall change and the patterns of land transitions, determining their consistency across different time periods1. The findings of the study reveal prominent land use changes, with notable expansions into built-up and agricultural areas, resulting in encroachments upon barren land and green areas. During the period, an observable transformation in land cover was discerned, with 12% for built area and a concurrent 10% for crop area. The period also witnessed a 13% decrease in barren land alongside a 5% reduction in green spaces. The land use changes, particularly the expansion of urban areas, adversely affect the Yamuna River's health through a surge in water demand, reduction in capacity for pollutant absorption, extensive agricultural practices involving fertilizer use, and the occurrences of extreme events like floods2. Moreover, the visible and persistent foam formation in the Yamuna River is primarily attributed to urbanization and agricultural activities occurring in the Delhi stretch of the river4. Therefore, there is an urgent need to establish an equilibrium between developmental pursuits and environmental conservation for the holistic well-being of the river ecosystem. Through this study, we corroborate that the encroached floodplain of the Yamuna River in Delhi can be effectively utilized for phytoremediation. Such techniques would facilitate biotic absorption and neutralization of agricultural effluents and emerging pollutants like surfactants.

Keywords: Delhi, Land Change Intensity (LCI), LULC, Phytoremediation, Yamuna River

References

1. Aldwaik, S. Z., and R. G. Pontius. 2012. "Intensity analysis to unify measurements of size and stationarity of land changes by interval, category, and transition." Urban Plan., 106 (1): 103–114. Elsevier B.V. https://doi.org/10.1016/j.landurbplan.2012.02.010.

2. Kumar, M., M. Sharif, and S. Ahmed. 2020. "Impact of urbanization on the river Yamuna basin." J. River Basin Manag., 18 (4): 461–475. Taylor & Francis. https://doi.org/10.1080/15715124.2019.1613412.

3. Rajan, S., and J. R. Nandimandalam. 2024. "Environmental health risk assessment and source apportion of heavy metals using chemometrics and pollution indices in the upper Yamuna river basin, India." Chemosphere, 346 (May 2023): 140570. Elsevier Ltd. https://doi.org/10.1016/j.chemosphere.2023.140570.

4. Sejwal, G., and S. K. Singh. 2023. "Perspective: The unexplored dimensions behind the foam formation in River Yamuna, India." Sci. Pollut. Res., 30 (39): 90458–90470. Springer Berlin Heidelberg. https://doi.org/10.1007/s11356-023-28857-3.

How to cite: Neenu, N. and Kansal, M. L.: Urbanization and River Health: Analyzing the Effects of Land Cover Change on the Upper Yamuna Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18023, https://doi.org/10.5194/egusphere-egu24-18023, 2024.

EGU24-18580 | Orals | ITS3.4/NH13.4

Terrain-Based Groundwater Potential and Groundwater Level Monitoring in Mountainous Regions of Central Taiwan 

Jung-Jun Lin, Feng-Mei Li, Nai-Chin Chen, Chien-Chung Ke, Yen-Tsu Lin, Chia-Hung Liang, Tzi-Hua Lai, and Chi-Chao Huang

The scarcity of freshwater has become a global issue in recent years, particularly in the plain regions of Taiwan. To address this challenge and enhance groundwater management for sustainable use, it is crucial to assess the groundwater resource potential in mountainous regions, as they serve as major recharge sources for the plains in Taiwan. To understand the relationship between groundwater potential and the geological settings of mountainous regions, various field investigation techniques were employed, including geological drilling, core logging, down-hole geophysical well logging, packer tests, and constant-rate pumping tests. This study focused on the main watershed in Central Taiwan, integrating all field investigation results to assess and analyze groundwater potential. Long-term groundwater monitoring wells were established to observe seasonal fluctuations.

Given the geological complexity of the mountainous region, a total of 75 boreholes with a depth of 100 meters were drilled in different geological units. Among the 48 selected sites with higher groundwater potential, groundwater monitoring stations were established, and constant-rate pumping tests were conducted to determine well yields and estimate the hydraulic properties of the rock aquifer. Integration of core and well logging revealed a composition of regolith and fractured bedrock. Geomorphological assessments, including slope analysis and the index of topographic position and wetness, categorized seven terrains: areas near the roof, at ridges, steep slopes, flat slopes, valleys or creek bottoms, alluvial fans downstream from valleys, and main riverbed deposits.

The results showed that the thickness of regolith ranged from 0.5 to 80.8 meters, with a geometric average of 14.7 meters, depending on different terrain types. Well yields ranged from 0.5 to 900 L/min, with an average of 134.4 L/min. Groundwater-level fluctuations ranged from 2.04 to 39.71 meters in shallow aquifers and 1.64 to 29.62 meters in deep aquifers, with outliers reaching 60.53 meters. Notably, higher average well yields and groundwater fluctuations were observed in main riverbed deposits and flat slopes. These findings highlight the observed terrain-based groundwater potential, emphasizing the pivotal role of groundwater-level fluctuation in recharge dynamics.

How to cite: Lin, J.-J., Li, F.-M., Chen, N.-C., Ke, C.-C., Lin, Y.-T., Liang, C.-H., Lai, T.-H., and Huang, C.-C.: Terrain-Based Groundwater Potential and Groundwater Level Monitoring in Mountainous Regions of Central Taiwan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18580, https://doi.org/10.5194/egusphere-egu24-18580, 2024.

EGU24-19961 | ECS | Posters on site | ITS3.4/NH13.4

What if the deforestation stops: impact on water budget components in West Africa 

Francis E. Oussou, Souleymane Sy, Jan Bliefernicht, Harald Kunstmann, Thomas Rummler, Nicaise Yalo, and Yinusa Ayodele Asiwaju-Bello

The land cover degradation in the Anthropocene under a changing climate threat remains one of the significant concern for water resources preservation and planning. The reciprocal effects of land degradation and climate change is reported as a complex scenario with direct and indirect impact on land surface processes (IPCC, 2023). The purpose of this work is to simulate the water fluxes and states under the anthopogenic influence (control - CTRL) and natural evergreen (EBF) conditions using the hydrological model WRF-Hydro with NoahMP as the Land Surface Model (LSM). The change in the temporal and spatial patterns is evaluated in terms of the potential impact associated with preserving the natural land cover in WA. To achieve this, the offline mode of WRF-Hydro is forced with meteorological dataset from ERA5-land for the two land cover scenarios at ~11km spatial resolution between 2011 and 2023. The water budget outputs are post-processed with the R package “rwrfhydro” which computes the total precipitation partitioning into surface runoff, evaporation, and water storage in the surface and subsurface components. The water budget terms are analysed with Man-Kendall’s statistics and the difference between the two scenarios evaluated using multivariate techniques (Principal component analysis - PCA and Canonical correlation analysis - CCA), and Wavelet analysis.The results show that whatever the land cover scenario the leading temporal variations of the total precipitation (PC1) have a strong relationship with the water storage (groundwater, total soil moisture, and canopy water) while lags in the signals are more likely to have higher correlation with the surface and subsurface runoff. Further, the canonical loadings of the CCA modes of the water storage terms, evaporation terms and total precipitation indicate a shift towards the dry northern part (Sahel) of the study area. Compared to the CTRL simulation, the EBF scenario decreases the runoff fraction while increases the evaporation and storage change fractions. The natural land cover scenario simulated in this study provide considerable insight into the potential benefits of land reforestation actions in West Africa and offers opportunities for better decision making.

How to cite: Oussou, F. E., Sy, S., Bliefernicht, J., Kunstmann, H., Rummler, T., Yalo, N., and Asiwaju-Bello, Y. A.: What if the deforestation stops: impact on water budget components in West Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19961, https://doi.org/10.5194/egusphere-egu24-19961, 2024.

EGU24-20216 | ECS | Orals | ITS3.4/NH13.4

Agent-based modelling for understanding the socio-ecological resilience in alpine mountain communities 

Andreas Mayer, Claudine Egger, and Veronika Gaube

European mountain regions are becoming more vulnerable to natural hazards due to global change, climate change, and land-use change. Therefore, it is essential to understand their resilience. Currently, quantitative and dynamic models of coupled human-landscape interactions are in their infancy. However, agent-based modelling (ABM) approaches have high potential to advance the analysis of the interplay of natural and social factors affecting socio-ecological resilience in European mountain communities. The Socio-Ecological Land Agent-Based Model (SECLAND) integrates information from qualitative interviews and spatial data into a quantitative modelling environment. This enriches the diversity of scenario modelling beyond economic rationales by incorporating individual agent's motivations for land-use decisions. The outputs from this model have been used as input to hydrological or ecological models on multiple occasions.

SECLAND has been used to model the potential success of various adaptation strategies for coping with climate-induced natural hazards. In a study conducted in the department of Ariège, France, we analysed the potential impacts of intensified livestock grazing on mountain pastures under scenarios with strong climate change effects and increased extreme events. In this scenario, farmers use mountain pastures to seek additional forage resources in specific years. However, these grazing areas require considerate management in years when they are not needed for food provision. Our study also found that the utilization patterns of mountain pastures are strongly influenced by farm succession, vegetation regrowth on unused mountain pastures, and the search for cost-efficient forage resources. In a case study conducted in Eastern Austria, we found that adaptive learning moderates the decline in the number of active farms and farmland, regardless of the scenario conditions, compared to scenarios without adaptive learning. However, the results also indicate that adaptation increases the workload of farmers. This highlights the importance of considering more than just simplistic economic rationales when making land-use decisions. Agent-based models can be used to model socio-ecological responses and help cope with adaptation in complex socio-ecological systems.

Both studies emphasise that in the context of risk management and socio-ecological resilience, learning and managing additional workload are key factors for achieving adaptive success. To further improve, it is necessary to couple agent-based models with climatic and landscape models, allowing for bi-directional feedback between social and natural systems. SECLAND has been adapted to integrate adaptive learning processes, demonstrating the possibility of capturing mutual system dynamics and feedback loops. This allows the full capacity of agent-based models to be used to assess the resilience of mountain communities to cope with natural hazards, using a scenario approach that includes heterogeneous agents, different trajectories of socio-economic conditions, as well as global and climate change dynamics. This presentation outlines a conceptual framework for operationalizing an interdisciplinary effort within a modelling environment that integrates human decision-making, socio-economic conditions, and climatic and landscape dynamics.

How to cite: Mayer, A., Egger, C., and Gaube, V.: Agent-based modelling for understanding the socio-ecological resilience in alpine mountain communities, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20216, https://doi.org/10.5194/egusphere-egu24-20216, 2024.

Gender vulnerabilities to climate change are increasingly recognized in the global arena; however, attention to gender in the context of climate change in India is relatively recent. Agriculture is a crucial part of the country’s economy and the agricultural practices in the Indian Himalaya are highly influenced by gender dynamics due to traditional gender roles and various social and cultural constraints. This study provides empirical evidence on how gender plays a role in the susceptibility to climate change from a district of Central Himalaya in Uttarakhand. The study identifies the key indicators that affect vulnerability both within and between genders. Additionally, the gender data is categorized based on caste (social segregation) and lower and higher elevation in the hills (geographical segregation) for investigating gender-specific vulnerabilities - both inter and intra-gender - in agricultural households. The primary data were collected in the months, April - June 2022 from 298 sample households based on stratified sampling selected from 20 villages in the district, Almora, Uttarakhand. Categorical principal component analysis (Cat-PCA) was used to develop weights for adaptive capacity and sensitivity indicators. Based on the Inter-governmental Panel on Climate Change (IPCC) framework 2014 and the theory of intersectionality, an intrinsic gender vulnerability index is developed. A sensitivity analysis approach is further adopted to pinpoint the major indicators influencing gender intersectional vulnerabilities. The expected results go beyond the conventional gender paradigms by exploring the intersectional nature of vulnerability and recognizing the complex interplay of various socioeconomic factors such as caste, education, income, and access to resources that contribute to differential gender vulnerabilities.

Keywords: Gender vulnerability, intersectionality, climate change, Cat-PCA, Sensitivity analysis.

How to cite: Choudhary, A., Sam, A. S., Kaechele, H., and Joshi, P. K.: Identifying key indicators and exploring gender intersectional vulnerabilities to climate change in agricultural households: A study of Central Himalaya, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1005, https://doi.org/10.5194/egusphere-egu24-1005, 2024.

EGU24-1695 | ECS | Orals | ITS2.5/NH13.5

Emergent vulnerabilities: exploring the role of drought for increasingly diverse groundwater conflicts in Germany  

Jan Sodoge, Giuliano Di Baldassarre, Christian Kuhlicke, and Mariana Madruga de Brito

Historically, groundwater resources have been perceived as inexhaustible in Central Europe by policy-makers and the general public. However, recently increasing drought periods and user groups with competing interests caused conflicts about the usage of and access to groundwater resources. Groundwater-related conflicts, defined here as social issues resulting from divergent viewpoints among diverse stakeholders, have been extensively examined in regions with an extended history of water scarcity. Yet, there is limited research on the emergence of groundwater-related conflicts in Central Europe and the role of recent drought events in shaping these. Here, we study the emergence of groundwater-related conflicts in Germany since 2000 using a text-mining approach. Specifically, we investigate four research questions: (i) how are groundwater-related conflicts characterized, (ii) which influential stakeholders are shaping these conflicts, (iii) what are the spatio-temporal patterns of these conflicts and (iv) how do drought events and different socio-economic factors influence their occurrence? To address these questions, we use machine learning and text-mining techniques on more than one million newspaper articles to develop a spatio-temporal database of conflicts. We also extract and categorize involved stakeholders using a named entity recognition algorithm. Then, we use statistical modeling to link the occurrences of groundwater conflicts with drought indices and other additional explanatory variables. Our results reveal the growing diversity and geographical spread of groundwater-related conflicts in Germany. Also, our results shed light on the role of the recent drought events’ influence on conflicts. Our findings contribute to mapping the evolving landscape of groundwater-related conflicts in Germany and the effects of drought events. The proposed methods have the potential to enable large-scale studies of environmental conflicts using vastly available text data.

How to cite: Sodoge, J., Di Baldassarre, G., Kuhlicke, C., and Madruga de Brito, M.: Emergent vulnerabilities: exploring the role of drought for increasingly diverse groundwater conflicts in Germany , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1695, https://doi.org/10.5194/egusphere-egu24-1695, 2024.

EGU24-2160 | ECS | Posters on site | ITS2.5/NH13.5

The Tail End of Migration: Assessing the Climate Resilience of Migrant Households in Ethiopia 

Ann-Christine Link and Roman Hoffmann

Climate change is associated with increasing frequencies and intensities of extreme weather events. These can, directly and indirectly, shape human (im)mobility. While most research on migration in the context of climate change focuses on climate as a migration driver in origin areas, there is a gap in knowledge on the role of migration for climate resilience in the destination areas. This paper studies differences in resilience (resistance and recovery) to climatic shocks between migrant and non-migrant households in Ethiopia, a country that is highly exposed and vulnerable to climate change. We use longitudinal data from the Living Standards Measurement Study (LSMS) conducted by the World Bank to construct a comprehensive Well-Being Index, which is used to analyze the impacts of climatic shocks and identify households that are more or less able to resist and recover from shocks. We use fixed effect panel regression approaches to model the impacts of climatic shocks on well-being over time for migrant and non-migrant households. Further explorative mediation analyses yield insights into mechanisms explaining differences between households. We find that migrant households have an overall lower climate resistance as they experience double as high well-being impacts when exposed to climatic shocks compared to non-migrant households. Climatic shocks significantly reduce the food security of all affected households and, in addition, negatively impact access to basic infrastructures and health for migrant households. Mediation analyses suggest that these differential climatic impacts are mainly driven by characteristics of migrant-origin regions, including poverty. Migrant households originating from less prosperous regions still face disadvantages even if they now reside in more prosperous regions. This contrasts the experience of non-migrant households whose resilience benefits from increased prosperity in their region of residence. While migrant households show a lower resistance to climate shocks, they recover faster from climatic shocks, which can be associated with diversified livelihoods and remittances that take time to unfold. This research is highly relevant to policy as it improves the understanding of underlying factors shaping differential vulnerability to climate change impacts and supports targeted interventions to increase the resilience of affected households.

How to cite: Link, A.-C. and Hoffmann, R.: The Tail End of Migration: Assessing the Climate Resilience of Migrant Households in Ethiopia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2160, https://doi.org/10.5194/egusphere-egu24-2160, 2024.

EGU24-3460 | ECS | Posters on site | ITS2.5/NH13.5

Using data and findings from natural and social sciences to assess urban heat vulnerability: a comparison of different methodologies. 

Karina Löffler, Andrea Damm, Heinz Gallaun, Judith Köberl, Dominik Kortschak, Petra Miletich, Lena Oberhuber, and Manuel Strohmaier

Climate change is causing temperatures around the globe to rise, leading to an increase in the frequency and intensity of hot days and heatwaves. In urban areas, this trend is further exacerbated by urban characteristics, such as the high building density and degree of sealing, the high concentration of anthropogenic heat sources or the reduced outgoing radiation. Extreme heat puts a strain on health, especially for elders and people with pre-existing illnesses. For effective and targeted prevention of heat-related morbidity and mortality, information on the spatial variance of people’s exposure and sensitivity, but also their adaptability towards heat can be of great importance.

A common practice for determining the distribution of vulnerable population groups within a city or an area is to construct a spatial Heat Vulnerability Index (HVI) based on findings and data from natural and social sciences, including e.g. socio-economic data, health data, remote sensing data, and climate data. However, there is no standardized workflow but a variety of approaches for the construction of an HVI, which may lead to significant differences in the calculated index ranks. In order to assess the impact of changes in the method design on the resulting index, we test different input data sets, weighting methods and spatial scales for the construction of a spatial HVI for the city of Graz (Austria). The input parameters for the HVI include temperature data, derived from satellite data and weather stations, as well as spatial socio-economic data that describe the population’s sensitivity towards heat and the capability to adapt to high temperatures. By conducting an uncertainty analysis and a global variance-based sensitivity analysis, the partial contribution of changing input variables, chosen weighting methods and different spatial scales to the output’s variance is determined. In addition, a local sensitivity analysis compares the application of land surface temperature derived from thermal satellite imagery to the use of station temperature data for the construction of an HVI.

How to cite: Löffler, K., Damm, A., Gallaun, H., Köberl, J., Kortschak, D., Miletich, P., Oberhuber, L., and Strohmaier, M.: Using data and findings from natural and social sciences to assess urban heat vulnerability: a comparison of different methodologies., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3460, https://doi.org/10.5194/egusphere-egu24-3460, 2024.

EGU24-3565 | ECS | Posters on site | ITS2.5/NH13.5

The lethal grip of heat: mapping the heat wave-mortality nexus in Spain (1975-2019) 

Dariya Ordanovich, Ana Casanueva, Aurelio Tobías, and Diego Ramiro

Nowadays, the rise in the global temperatures are a source of concern, particularly in the Mediterranean region, where Spain is already witnessing notable consequences for its aging population. Predictions for the end of the XXI century reveal a persistent increase in air temperatures along with an increment of extreme episodes. Abnormal heat, once considered an 'environmental accident', is now a serious public threat. This contribution endeavors to quantify the added effects of heat wave exposure on mortality by demographic and socioeconomic strata during the period of 45 years in Spain at the provincial level. Moreover, we aim to explore the temporal evolution in these effects and variations in its spatial patterns, especially focusing on the inequality aspects that shape the health outcomes in an increasingly aging population.

Here we leverage daily individual mortality data and other contextual data on population from the National Institute of Statistics of Spain and air temperature estimates from the ERA5 global reanalysis. We also use the historical settlement data as a proxy for population distribution from 1975 onward. To estimate the main and added effects of heat waves we fit a quasi-Poisson time-series regression model using a distributed lag non-linear model with 10 days of lag, controlling for trends and day of the week.

We analyze approximately 15.8 million of deaths registered in Spain between 1975 and 2019. During the selected time window, we expect to see a shift in the temperature-mortality association from a V-shape in the first decades of the observation to a U-shape by the end of the period all across the provinces, thus revealing a progressive flattening of the exposure-response curve. We also expect to observe an overall reduction in the mortality burden associated with the temperatures. In particular, we anticipate more significant and rapid decline in the cold-related risks and attributable fractions in comparison with the heat-related ones, with some latitudinal variations across the country.

On the other hand, we witness a steady increase in the incidence of the heat wave episodes with time all over the country. We expect to see a positive added effect of heat wave on mortality, however this effect is assumed to be smaller than the primary effect. In addition, we anticipate observing variations in the effect depending on the heat wave order, duration, intensity, geographic location and demographic strata. The largest added effects are expected for the longest and strongest heat waves in the oldest-old population in the less accustomed to extreme heat areas.

How to cite: Ordanovich, D., Casanueva, A., Tobías, A., and Ramiro, D.: The lethal grip of heat: mapping the heat wave-mortality nexus in Spain (1975-2019), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3565, https://doi.org/10.5194/egusphere-egu24-3565, 2024.

EGU24-4065 | ECS | Posters on site | ITS2.5/NH13.5

Quantifying the Stability of Refugee Populations: A Case Study in Austria 

Ola Ali, Elma Dervic, Rainer Stütz, Ljubica Nedelkoska, and Rafael Prieto-Curiel

The global surge in displacement, with nearly 110 million people uprooted due to violence, underscores the pressing need to comprehend the challenges faced by refugees. Population growth, environmental crises, and political instability contribute to this crisis, projecting an escalating trend in the decades ahead. While hosting countries strive to address concerns related to labour markets, state provisions, and cultural integration, understanding the well-being of refugees upon entry needs to be more adequately explored. This study focuses on refugee stability and integration, employing Austria as a case study. Utilising comprehensive administrative data spanning November 2022 to November 2023, we examine residence movements as a proxy for stability. Our findings reveal a stark contrast in the stability of refugees compared to other migrant groups. Analysing movement profiles, we establish that refugees exhibit significantly higher rates of residential mobility than their counterparts, especially among male refugees. This imbalance persists even when comparing refugees to migrants from top refugee-sending countries without official refugee status. This study contributes valuable insights into the intricate dynamics of refugee stability, shedding light on the enduring challenges faced by this population. By examining movement patterns as a key indicator, we provide a nuanced understanding of the residential experiences of refugees, that can inform targeted policies and interventions for enhanced refugee well-being and integration.

How to cite: Ali, O., Dervic, E., Stütz, R., Nedelkoska, L., and Prieto-Curiel, R.: Quantifying the Stability of Refugee Populations: A Case Study in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4065, https://doi.org/10.5194/egusphere-egu24-4065, 2024.

Drought, flood, hail and low temperature frost (LTF) are the main agrometeorological disasters in China. However, a comprehensive and quantitative study on the long-term trend of farmland and economic damage across the country is still lacking and needs to be carried out urgently. Based on historical statistical data from yearbooks and bulletins, the overall characteristics of the impacts of provincial meteorological disasters on population, economy and farmland during 1989-2022 were analyzed by using Mann-Kendall trend test at yearly and provincial scales in China. The results showed that the proportion of direct economic losses caused by meteorological disasters to GDP showed a decreasing trend. The SGD13.1 index, based on the number of deaths and the value of disaster losses, shows that there are abrupt years on the time scale under the Mann-Kendall trend test. In the past 30 years, crop loss in China has increased first and then decreased under natural disasters, and drought is the most serious type of disaster that causes farmland loss. The Person correlation analysis combining disaster intensity index and multiple factors shows that agricultural economic output has a significant negative correlation with disaster intensity, SDG13.1 and total precipitation, and a positive correlation with average annual temperature. There was a significant positive correlation between SDG13.1 and disaster intensity index. The results of this study systematically reveal the damage characteristics of meteorological disasters to socio-economic system in China, which are critical and necessary for disaster risk reduction and adaptive strategy development.

How to cite: airiken, M. and Li, S.: Spatiotemporal variations in damages to socio-economic system from meteorological disasters in mainland China during 1989–2022, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4576, https://doi.org/10.5194/egusphere-egu24-4576, 2024.

EGU24-4863 | ECS | Posters on site | ITS2.5/NH13.5

Influence of Extreme Weather and Climate Events on Crop Yields in China 

Dezhen Yin and Fang Li

Extreme weather and climate events, such as extreme temperatures, droughts, and floods, cause significant yield losses and threaten global food security. Their frequency and intensity have increased in recent decades, a trend expected to continue. China is the world's largest grain producer and also a country where extreme events occur frequently. Nevertheless, the influence of extreme weather and climate events on crop yields in China is not yet well understood. This study quantified the impact of heat waves, frost, droughts, and floods on the yields of wheat, maize, rice, and soybean in China from 1970 to 2019, using the superposed epoch analysis (SEA) method, agricultural statistics collected from the National Bureau of Statistics of China, and crop calendar reanalysis dataset. Furthermore, the performance of 13 global gridded crop models (GGCMs) in simulating these impacts is evaluated. The results show that heat waves, frost events, droughts, and floods significantly decrease crop yields by 2.1%, 1.0%, 2.2%, and 1.7% for wheat, maize, rice, and soybean, respectively, accounting for 23.6%, 10.5%, 21.4%, and 18.9% of the interannual variability. Yields of different crop types in China are sensitive to specific extreme weather events. The GGCMs effectively capture the impact of droughts, with nine out of thirteen models detecting a significant effect, yet they struggle to accurately simulate the effects of heat waves, frost events, and floods, with only five, two, and two models detecting these impacts, respectively.

How to cite: Yin, D. and Li, F.: Influence of Extreme Weather and Climate Events on Crop Yields in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4863, https://doi.org/10.5194/egusphere-egu24-4863, 2024.

Event attribution science quantifies the influence of anthropogenic climate change on the occurrence of extreme weather events. One incentive for such research is an assumed motivational effect on people’s climate change mitigation and adaptation efforts, but little empirical evidence exists regarding this. While subjective attribution has been shown to matter, the few studies concerned with scientific attribution were gathered in societies polarised above average. Moreover, scientists and stakeholders have suggested that intellectual and communicative obstacles hinder motivational effects. They also questioned any effect on adaptation (rather than mitigation) intentions.

Here, we present results using the high-impact flood in July 2021 in Germany to empirically test the motivational effect of scientific attribution on mitigation and adaptation intentions. Data from a nationally representative sample and oversamples from the two flood-affected federal states in a control (n=663) and an attribution (n=611) group were collected in March 2022. Both groups learned about the consequences and immediate causes of the flood. The attribution group additionally learned about the World Weather Attribution's result that climate change to date had made the associated heavy rainfall more likely and more intense and that this influence would increase further in future. Groups did not differ in socioeconomic factors; mediation analyses and ordinary least squares linear regressions were applied.

Results showed that learning about event attribution results increased people’s subjective attribution of the event to climate change and their mitigation and adaptation intentions. It also increased their belief that the climate is changing and that this is due to human activities. Subjective attribution, but not personal flooding experience, mediated these effects. The effect on adaptation but not mitigation intentions was positively related to low education and to far-right political orientation. We set the results in the context of related evidence, highlight methodological caveats, and discuss implications for climate/impact attribution science.

How to cite: Undorf, S. and Undorf, M.: Increased climate change mitigation and adaptation intentions through learning about an event attribution result for the 2021 European floods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5601, https://doi.org/10.5194/egusphere-egu24-5601, 2024.

Migration is one of human’s most drastic adaptation strategies against unfavorable conditions. In this work, we developed a minimalistic mechanistic model for human migration, dubbed CHASE, is developed. The model is named after the factors it includes to capture human migration, namely CH = Changing mindset, A = Agglomeration, S = Social ties, and E = the Environment.  Numerical experiments were conducted by subjecting the human agents in the model to two different kinds of disturbances: sudden shocks and gradual changes. Model results revealed highly nonlinear interplay among diversity, distance barrier, and social ties. The results also showed distinct responses to sudden shocks and gradual changes, both in terms of dynamics of the populations and diversity patterns.  Some ongoing and future work will also be briefly discussed.

How to cite: Muneepeerakul, R.: Modeling human migration: a minimalistic mechanistic modelling approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7400, https://doi.org/10.5194/egusphere-egu24-7400, 2024.

EGU24-8637 | ECS | Posters on site | ITS2.5/NH13.5

An inclusive assessment framework for exploring climate-resilient nutrition security in sub-Saharan Africa 

Stewart Jennings, Andrew Challinor, Jennie Macdiarmid, Edward Pope, Thomas Crocker, Weston Anderson, Richard King, Stephen Whitfield, Rebecca Sarku, Christian Chomba, Masiye Nawiko, Lucas Rutting, and Marieke Veeger

Achieving climate-smart nutrition security in sub-Saharan Africa is an urgent challenge due to increasing climate risks to agricultural production, population growth and food price volatility This necessitates an integrated evidence base that takes into account not only future food system modelling but wider academic expertise and stakeholder knowledge and the plausible and desirable transformations that these information streams can provide. Accordingly, we use the integrated Future Estimator for Emissions and Diets (iFEED) to explore scenarios of food system transformation towards nutrition security. iFEED integrates climate, crop and land use modelling to explore scenarios of relevance to the policy landscape, as informed by stakeholders, assessing the adequacy of energy and nutrient supplies to meet dietary requirements at a population level. Our results show that calories are not always sufficient at the population level in extremely hot and dry years by mid-century in Zambia, even when maximising food production on available land. The majority of micronutrients also remain below population requirements. An alternative scenario where crops for population level nutrition security are prioritised shows that there are larger calorie shortfalls in extremely hot and dry years, although more micronutrient requirements are met than in the production-focused scenario. Both scenarios show benefits, and we point to ways forward that address the challenges to achieving climate-resilient nutrition security in the region. We also introduce our latest thinking on a new inclusive assessment framework that aims to expand iFEED to incorporate bottom-up disruptive seeds work and top-down modelling across spatial scales to deliver socially-equitable nutrition security in Kenya.

How to cite: Jennings, S., Challinor, A., Macdiarmid, J., Pope, E., Crocker, T., Anderson, W., King, R., Whitfield, S., Sarku, R., Chomba, C., Nawiko, M., Rutting, L., and Veeger, M.: An inclusive assessment framework for exploring climate-resilient nutrition security in sub-Saharan Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8637, https://doi.org/10.5194/egusphere-egu24-8637, 2024.

Hurricanes are among the most frequent and devastating natural disasters in tropical regions. These events often necessitate massive evacuations when warnings are issued, which often place a significant burden on transportation systems. The situation becomes even more complex and challenging when hurricanes coincide with other disruptive events, such as pandemics or compounded infrastructure damages. These compound scenarios not only dramatically increase community vulnerability but also add layers of complexity to emergency management, particularly in coastal communities with direct impacts. Understanding individual responses to such emergencies is vital for developing effective emergency management strategies. The focus of this study is to enhance our understanding of how individuals react and respond to emergencies in the face of such compound hazards. We concentrated specifically on the evacuation behaviors of residents in the state of Florida, U.S., during a major hurricane event. To this end, an activity-based model was developed. The model employs the Metropolis-Hastings algorithm, to generate a simulated population. The simulated population, characterized by diverse socioeconomic attributes, is designed to reflect the demographics and behaviors of the actual population in the study area. We integrated information from a local household hurricane evacuation survey and aggregated evacuation data to measure the evacuation decisions, timing, and destinations of individuals. We then applied the model to examine three distinct evacuation scenarios: a standalone hurricane, a hurricane coinciding with a pandemic, and a hurricane combined with storm surge flooding on the transportation systems. Our findings underscore the profound impact that compound hazards on transportation systems. We observed that the average travel time for evacuation could potentially double under compound hazard conditions. This highlights the potential inadequacy of current infrastructure resilience in handling complex emergency situations under compound hazards. This developed model offers valuable insights for assessing system-wide impacts of natural disasters in coastal regions and can be adapted for various scenarios to aid in disaster preparedness and response planning.

How to cite: Han, Y. and van Westen, C.: Modeling Evacuation Strategies in Response to Compound Hazards: Lessons Learned from a Major Hurricane Event in the US, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9975, https://doi.org/10.5194/egusphere-egu24-9975, 2024.

EGU24-13023 | Posters on site | ITS2.5/NH13.5

Water Footprints of Growing Maize Crops in the Danube Plain (Bulgaria) 

Nina Nikolova and Simeon Matev

The water footprint of maize production is an indicator that provides information not only about direct water use for crop yields but also about indirect water use and virtual water trade. The general aim of the present research is to enlarge the knowledge about climate variability's impact on agriculture concerning improving sustainable water use for crop production. The accent of the proposed work will be on the assessment and analysis of green (rainfed production) and blue (irrigation water) water used for growing maize crops in the Danube Plain (Bulgaria).

The investigation is based on the following data: climatic data (air temperature, precipitation, wind speed, relative humidity); statistical data from agriculture, local authorities, and farmers (data about crop parameters and yields, and irrigation), and geographical data (climatic maps, maps about land use, soil maps, maps of main agricultural plants dissemination). The calculation and assessment of the water footprint of growing maize is done by the application of Cropwat software. The water needed for irrigation under various crop management options is determined. The main investigated period is 1961-2022 but special attention is given to water footprints of maize production during the extreme dry and extreme wet years. The results of the present work allow us to identify the hotspots regarding water use and water scarcity. The knowledge about the water footprint and climate-agriculture relationship could be used in water resources management and for effectively coping with the environmental and economic problems related to water scarcity and drought.

Acknowledgments: This study has been carried out in the framework of the project “The Nexus Approach in Agriculture. The water-food nexus in the context of climate change”, supported by the Ministry of Education and Science (MES) of Bulgaria (Agreement № КП-06-КОСТ-2/17.05.2022 and is based upon work from COST Action NEXUSNET, CA20138, supported by COST (European Cooperation in Science and Technology).

How to cite: Nikolova, N. and Matev, S.: Water Footprints of Growing Maize Crops in the Danube Plain (Bulgaria), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13023, https://doi.org/10.5194/egusphere-egu24-13023, 2024.

An increasing number of organizations are providing climate risk information for real estate properties in the form of climate risk scores. We investigate individuals' attitudes toward the accuracy of such information and whether this information impacts participants' willingness to buy properties. In a series of online experiments, participants (N=612) were asked to rate the desirability of a range of properties based on different attributes, including price, size, and year built. These properties were paired with high, low, or no climate risk scores. Following these tasks, participants completed surveys measuring their beliefs and perceptions regarding climate risk. Experiment 1 manipulated risk-level between subjects and found that participants were less willing to buy high-risk properties than low-risk properties or properties with no risk information, with no significant differences between the last two. Experiment 2, manipulated risk scores within-subject and found that not only were the high-risk properties rated lower than no risk and low-risk ones, but participants were also more willing to buy the low-risk properties than those with no risk information. In Experiment 3, the same tendency to buy low-risk properties compared to high-risk ones was found among a sample of homeowners, regardless of the timeframe (12 months vs. 30 years) and the granularity (risk at the property-level vs. postcode-level) of the risk information. The findings also revealed that individual beliefs and perceptions of climate change did not impact willingness ratings for any of the property types, except in Experiment 3, in which the higher expected risk due to climate change was negatively related to willingness to buy high-risk properties. Together, the findings suggest that climate risk scores impact individuals' assessments of properties, regardless of their beliefs and experience with climate-related events. 

How to cite: Newell, B. and Ghasemi, O.: Evaluating the Impact of Climate Risk Scores on Property Purchase Decisions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13476, https://doi.org/10.5194/egusphere-egu24-13476, 2024.

EGU24-14015 | ECS | Orals | ITS2.5/NH13.5 | Highlight

Urban Residents’ Justice Preferences in the Design of Climate Adaptation Flood Policy 

Melissa Tier, Elke Weber, and Michael Oppenheimer

There is an increasing need for ex-ante climate adaptation policy planning and design. Moreover, meeting robust standards to minimize harm and environmental inequities will require innovative practices and foresight, but little is currently known regarding how such standards influence residents’ preferences for or against climate policies. One set of climate adaptation strategies ripe for such consideration is urban risk management for worsening flooding. These strategies are often complex and controversial (e.g., choices between protection, retreat, and relocation), and can vary widely in structure with regard to key justice components (e.g., types of distributive, procedural, and corrective justice).

 

This presentation will share results from a large-scale, international survey that examined a comprehensive set of justice values underlying residents’ urban flood policy preferences. The online survey was translated and administered in 5 cities globally (n=650 residents per city): Buenos Aires (Spanish), Johannesburg (Zulu & English), London (English), New York City (English, Spanish, & Korean), and Seoul (Korean). The survey explores which urban climate adaptation flood policies are generally preferred by residents, whether certain categories of policies are preferred over others, and whether certain characteristics of residents best predict their preferences. More specifically, analysis of survey data considers which variables are best predictors of differences in policy preferences: a) self-perceived vulnerability to flood risk; b) city of residence; c) political, economic, and psychological worldviews; or d) other common demographics. Preliminary analysis of survey results suggests that residents with higher self-perceived vulnerability to flood risk also have an increased likelihood of preferring more expansive adaptation strategies (i.e., not just homeowner-focused policies, not just protection strategies, and more reparative actions).

 

This survey was designed to integrate contemporary topics in environmental justice, climate adaptation, and urban planning. The hypothesis was that people who self-identify as more vulnerable to flood risk prefer policies that focus more on other vulnerable people – in other words, an empathy effect caused by higher salience of vulnerability. Moreover, this effect was expected to be stronger than that of city of residence, worldviews (e.g., political identities), and other demographic characteristics. The presentation will both review detailed statistical analysis of the survey data, as well as discuss recommendations for how to best frame risk management policies in order to increase support for policies aimed at minimizing environmental inequities.

 

This dissertation thesis project has been supported by the Princeton School of Public & International Affairs and the 2023 Young Scientists Summer Program at the International Institute of Applied Systems Analysis.

How to cite: Tier, M., Weber, E., and Oppenheimer, M.: Urban Residents’ Justice Preferences in the Design of Climate Adaptation Flood Policy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14015, https://doi.org/10.5194/egusphere-egu24-14015, 2024.

Despite feeding the majority of the global population, small (<2 ha) farmers are among the poorest and disproportionately vulnerable to climate changes. Their ability to improve yields amid increasingly severe and frequent climate shocks will largely determine the success of the UN’s Sustainable Development Goals (SDGs) to eliminate poverty and hunger. Because smallholder farmers play a central role in efforts to achieve global food security, many governmental and private institutions have influenced smallholders’ on-farm management practices through interventions. However, interventions led by different institutions have pushed communities of smallholders to adopt divergent adaptation strategies: Some communities have taken proactive measures by diversifying their crop rotations or implementing tree-based systems as natural climate solutions, while others have primarily used reactive measures, implementing adaptations that were directly informed by their recent experiences with extreme weather events (e.g., altering sow and harvest dates to avoid a period of extreme heat). Despite the deadly consequences of food shortages in smallholder communities, very little research has quantified the impact of specific adaptations on their sensitivity to inter-annual climate variability. Fortunately, the recent influx of satellite sensors has enabled us to remotely monitor changes in smallholder field-level cultivation practices and tree-based systems, and with high performance computing, we can scale these analyses across landscapes. Here, we integrated administrative yield data, multi-source satellite and weather data, and household and field survey data across India, Nepal, and Bangladesh in mixed-effect models to answer: Where, and how have smallholder communities adapted their cultivation practices? And, how have these adaptations impacted their resilience to weather shocks? The results of these findings were contextualized using household survey data of 2,000 smallholder farmers to understand the drivers of farmers’ decisions and their perspectives on climate-induced adaptations. Our findings can inform future interventions in the region, and the algorithms will be directly transferable to other regions of smallholder agriculture where farmers adopt distinct adaptations and experience other climate threats.

How to cite: Hinks, I. and Gray, J.: From Satellites to Soil: Integrating Satellite and Household Survey Data to Assess the Impacts of Adaptations on Smallholder Farmers’ Climate Resilience, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14059, https://doi.org/10.5194/egusphere-egu24-14059, 2024.

It is well known that the impacts of climate change to health and well-being are exacerbated by existing social inequality. Throughout the world, women face heightened vulnerability to climate stress due to pervasive power imbalances, gender norms, and economic marginalization. Interdisciplinary collaborations that carefully integrate social and physical data are critically needed to foster a deeper understanding of the processes that increase women’s exposure. In this talk, I share findings from recent work examining the effects of extreme weather on early and forced marriage, intimate partner violence, and social isolation of girls and women. I will discuss these trends in relation to recent progress in the opportunities available to women, and offer insights into the conditions that might support women’s well-being in the face of climate risk.

How to cite: Carrico, A.: Gendered Responses to Climate Change and the Well-Being of Girls and Women , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14376, https://doi.org/10.5194/egusphere-egu24-14376, 2024.

Social network plays a critical role in risk communication diffusing information in near real time. Disaster-affected communities utilize their social network to report catastrophic damages and increase the perceived risk of the ongoing disaster by non-affected communities, which enhance their willingness to donate and support emergency aids to the affected communities. Previous studies have focused on social network structure or information diffusion separately. This study strives to reproduce the social response to natural disasters aims integrating the two aspects of social network structure and information diffusion. This study focuses on two classical and catastrophic U.S. disasters, such as 2012 flash drought and wildfire, to establish the social network during these two disasters and understand difference in the patterns of the risk communication within the data-driven social network and random social network (e.g., (the equal chance/importance of a nodes). Random social network is made from the LFR benchmark algorithm using the properties of the data-driven network, including node number, degree distribution, community distribution, and average degree. This study leverages over 120,000 (53,000) tweets that contains a term, drought (wildfire). In this study, a Susceptible-Infected-Recovered (SIR) model is employed to simulate the information diffusion patterns using the data-driven and random social network. After fitting SIR model with the Twitter data using these two social network-based simulations, this study aims to assess 1) the impact of the structure difference on risk communication and 2) the impact of influential users in different social network structures. Result shows that the trained SIR model using the data-driven social network reproduced the observed information diffusion patterns for the 2012 drought and wildfires but with relatively higher uncertainty in the information diffusion pattern for wildfires. The SIR model simulation with data-driven social network shows a faster information diffusion pattern with a higher information reach rate than that with the random social network. In closing, this study discusses limitations and opportunities of next-generation social dynamic modeling for natural disaster risk communication. This study highlights the value of an interdisciplinary approach in improving risk communication and developing a more efficient and effective mitigation policies for not only droughts and wildfires and other natural disasters.

How to cite: Song, J. and Kam, J.: Understanding the dynamics of information diffusion through data-driven social network modeling for the 2012 U.S. drought and wildfire, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14972, https://doi.org/10.5194/egusphere-egu24-14972, 2024.

EGU24-14994 | Posters on site | ITS2.5/NH13.5

Calibrating Displacement Curves to Forecast Forced Migration due to Sea-Level Rise and Tropical Storms 

David Lallemant, Sonali Manimaran, Thannaletchimy Housset, and Sylvain Ponserre

Coastal communities are expected to be highly exposed to rising sea levels and more frequent and intense tropical storms in the coming decades, with forced migration (or displacement) highly likely in many of these places. The exposure to these hazards is driven not just by climate change, but also by growing populations and rapid urbanisation of coastal cities. However, the extent of forced migration will be highly variable, and will be dependent on pre-existing physical and social vulnerabilities present in each location. Therefore, in order to reliably forecast future forced migration due to sea-level rise and tropical storms, it is necessary to construct spatially explicit displacement curves that link hazard levels to the migratory response of communities. This study has calibrated displacement curves through regression analysis for the Philippines based on historical internal migratory movements due to coastal flooding and tropical storms. The data for calibration was obtained from the Internal Displacement Monitoring Centre and governmental disaster reports, and the calibration was performed at the level 3 administrative boundaries. With the displacement curves, critical thresholds of flood and wind damage, at which point forced migration occurs, are identified. Subsequently, these displacement curves are combined with projections of future sea-levels and tropical storms in order to forecast the forced migration of communities under climate change. The displacement curves can be used by researchers, planners and policymakers to understand the varied migratory response of communities to sea-level rise and its associated hazards. This will allow for effective adaptation plans to be devised in advance in order to manage such forced migration in a manner that allows communities, including vulnerable ones, to relocate and avoid the adverse impacts of a changing climate.

How to cite: Lallemant, D., Manimaran, S., Housset, T., and Ponserre, S.: Calibrating Displacement Curves to Forecast Forced Migration due to Sea-Level Rise and Tropical Storms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14994, https://doi.org/10.5194/egusphere-egu24-14994, 2024.

EGU24-16735 | ECS | Posters on site | ITS2.5/NH13.5

Modeling human displacement in the 2022 Pakistan floods: Current gaps and opportunities. 

Steffen Lohrey, Pui Man Kam, Bianca Biess, Tabea Cache, Sabrina Di Vincenzo, Radley M. Horton, and Lisa Thalheimer

The 2022 Pakistan floods have been unprecedented in their extent. They affected around 33 million people, caused about 15 billion USD in damages, and took the lives of more than 1,800 persons, dominantly in the southern parts of the country.

Effective disaster response requires fast assessments of likely impacts from hazardous weather to inform decision-makers and guide relief efforts for early action. Displacement modeling is a key technique towards these goals. However, displacement modeling which accounts for socio-economic components and uncertainties is methodologically challenging, and quantitative evidence largely remains limited and fragmented. Much work is needed to resolve these.

This study aims at providing a case study for disaster displacement modeling by using the open-source impact assessment platform CLIMADA to investigate the extent by which flood-related hazards can be used to quantify displacement numbers in a data-limited region. Here, we estimate displacement from the 2022 Pakistan floods in Sindh province as a case study. We combine data on flood depth, exposed population, and provide impact functions that relate vulnerability of people likely to be displaced. We further use published numbers of affected people as target data for our model. The centerpiece of our analysis is the choice of impact functions. We test different forms of impact functions as well as assumptions about critical flood depths to proxy the number of displaced people, first using ex-ante assumptions, and then a numerically optimized version.

With ex-ante assumptions, our model predicts a range of 1.94 to 5.65 million of displaced people in Sindh province, as compared to a total number of 6.76 million as reported by government sources. When we apply numerically optimized impact functions, the results closely resemble those obtained using the ex-ante assumptions, indicating that the current methods underestimate the extent of displacement. Additionally, we have evaluated the relationship between local vulnerability and the level of urbanization, and our findings reveal a negative correlation.

We use this model to explain different displacement estimates for the 2022 floods across Pakistan and thereby contribute a case study to the growing field of displacement models, and towards the development of more refined ones. It highlights opportunities as well as limitations, and is a quantitative contribution to an existing discussion on how much disaster-related displacement can be modelled, and in how far assumptions can be generalized. These insights also support a better understanding of displacement and migration from future climate risks.

How to cite: Lohrey, S., Kam, P. M., Biess, B., Cache, T., Di Vincenzo, S., Horton, R. M., and Thalheimer, L.: Modeling human displacement in the 2022 Pakistan floods: Current gaps and opportunities., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16735, https://doi.org/10.5194/egusphere-egu24-16735, 2024.

EGU24-16971 | Orals | ITS2.5/NH13.5

Regional probabilistic flood displacement risk assessment: the Horn of Africa case study 

Eva Trasforini, Lorenzo Campo, Tatiana Ghizzoni, Andrea Libertino, Daria Ottonelli, Sylvain Ponserre, Lauro Rossi, and Roberto Rudari

The risk of displacement caused by natural hazards has been increasingly impactful and emerges as a topical issue point in the field of disaster risk management. Given the potential escalation of this phenomenon due to climate change, population growth and urbanization, enhancing displacement risk assessment through reliable models and data has become increasingly crucial. Different applications require approaches that can be adapted at different spatial scales, from local to global scale. In pursuit of this goal, we have devised a probabilistic procedure for estimating the potential displacement of individuals due to riverine floods. The methodology is based on a novel approach to vulnerability assessment which considers that people’s vulnerability depends on several physical and social factors such as direct impacts on houses, livelihoods and critical facilities (such as schools and hospitals). These concepts are seamlessly woven into a comprehensive probabilistic risk assessment. A modelling chain that incorporates climatic, hydrological, and hydraulic and exposure/vulnerability models can be run different resolution to predict impacts at different special scales, from local to global scale.

This approach already demonstrated its validity for in Fiji and Vanuatu, where the small size of the countries allows for the definition of a building scale exposure model. In the present study, our focus turns towards adjusting the methodology for large countries, where using a high-resolution exposure model becomes impractical.

For our case study, we selected three countries in the Horn of Africa—Ethiopia, Somalia, and Sudan—acknowledging their particular vulnerability to the challenges posed by recurrent floods and the resulting internal displacement.

To properly match the 90m resolution of riverine flood hazard maps and avoid distortions in the final risk computations, a specific procedure for downscaling global exposure dataset, such as the 1-km resolution Global Exposure Socio-Economic and Building Layer (GESEBL), was implemented using high-resolution population distribution products. The resulting exposure layers are a set of population distributions associated to different sectorial assets (residential, industrial and agricultural production, services), characterized in terms of physical vulnerability to floods.

Impacts of current and future flood scenarios on those assets may render them unable to provide their function, thus causing people to forcedly move. In this procedure we took special care to avoid double counting, i.e. those cases where people lose both habitual place of residence and livelihoods.

Displacement risk expressed in annual average displacement and probable maximum displacement was evaluated under current and future climate conditions with optimistic and pessimistic scenarios. The results indicate a potential 2 to 4 times increase in average annual displacement for optimistic scenarios compared to current conditions, with even higher risk for pessimistic scenarios.

The application of this methodology in larger countries paves the way for its implementation on a global scale.

How to cite: Trasforini, E., Campo, L., Ghizzoni, T., Libertino, A., Ottonelli, D., Ponserre, S., Rossi, L., and Rudari, R.: Regional probabilistic flood displacement risk assessment: the Horn of Africa case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16971, https://doi.org/10.5194/egusphere-egu24-16971, 2024.

EGU24-17120 | ECS | Posters on site | ITS2.5/NH13.5

Investigating the Effects of Extreme Weather and their Interactions with Farm Management on Crop Yields in the Netherlands 

Sinne van der Veer, Raed Hamed, Hande Karabiyik, and Jamal Roskam

Recent studies that address the impacts of extreme weather on crop yields, are predominantly focused on expansive geographical scales and generally ignore the role of management practices in modulating the dynamics of weather-crop sensitivities. In our study, a unique dataset containing data from the Dutch Minerals Policy Monitoring Program and the Farm Accountancy Data Network (FADN) is used to explore the relationship between extreme weather and crop yields at farm level in the Netherlands. The dataset consists of unbalanced panel data from the years 2006 to 2021 including an average of about 1,500 farms. The Standardized Precipitation Evapotranspiration Index (SPEI) is used to reflect weather anomalies, both extreme wet and dry conditions. The climatological variables necessary to compute the SPEI are estimated at field-level using data gathered by the Royal Netherlands Meteorological Institute from 277 precipitation stations and 18 climate stations. In total, ten types of crops are covered and the role of soil type, irrigation and nutrient application in modulating the relationship between extreme weather and crops is elucidated. Distinction is made between drought and excessive precipitation during the planting-, growing- and harvesting period. The results show substantial impacts from drought during the growing- and harvesting period and excessive precipitation during the planting- and growing period. Severe droughts show statistically significant (p≤0.05) reductions in yield for nine crops, and lead to yield reductions ranging from 10 to 25 percent when only occurring during the growing period. Meanwhile, eight crops show statistically significant (p≤0.05) reductions in yield due to severe precipitation excess, with reductions ranging from 5 to 20 percent from excessive precipitation during the planting period. Soils such as sand or loess amplify the negative impact of drought on crop yield, while softening the impact of excessive precipitation. Furthermore, irrigation and nutrient application (both nitrogen and phosphate) are shown to moderately decrease the impact of extreme weather on crop yield, with substantial differences depending on crop type and the period in which the extreme weather event occurred. The findings of this study provide valuable insights to guide local adaptation priorities which are critical given the projected increase in the intensity and frequency of extreme weather under climate change.

How to cite: van der Veer, S., Hamed, R., Karabiyik, H., and Roskam, J.: Investigating the Effects of Extreme Weather and their Interactions with Farm Management on Crop Yields in the Netherlands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17120, https://doi.org/10.5194/egusphere-egu24-17120, 2024.

EGU24-18164 | ECS | Orals | ITS2.5/NH13.5

Can we understand the variability in flood-induced displacement using process-based global flood modelling?  

Sandra Zimmermann, Katja Frieler, and Jacob Schewe and the ISIMIP Team

Every year, disasters force millions of people around the world to leave their homes. Disaster-induced displacement often leads to humanitarian hardship and imposes substantial costs on vulnerable, low-income societies in the Global South. With anthropogenic climate change increasing the intensity and number of extreme events in many regions globally, understanding and projecting disaster-induced displacement becomes increasingly important. Floods are among the main causes of disaster-induced displacements. However, the causes of variability in flood displacement over time and space are not well understood. Therefore, it is not known to what extent climate change has already affected displacement in the past, making it difficult to produce reliable estimates of future displacement risk.

In our study, we address the question of how much of the observed variability can be explained on the basis of process-based flood hazard modeling. We use the output of state-of-the-art global hydrological models forced with observational climate and direct human forcings to derive flood extents from the global hydrodynamic model CaMa-Flood. We first assess how well modelled flood hazards can explain annual variations in past displacement as recorded by the Internal Displacement Monitoring Center at a global as well as national scale, before also accounting for different vulnerabilities of communities by applying spatially-disaggregated vulnerability factors derived from comparing the simulated number of people affected by flooding to observational displacement data. We hence provide a comprehensive assessment of the explanatory power of the process-based fluvial flood hazard component concerning displacement.

How to cite: Zimmermann, S., Frieler, K., and Schewe, J. and the ISIMIP Team: Can we understand the variability in flood-induced displacement using process-based global flood modelling? , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18164, https://doi.org/10.5194/egusphere-egu24-18164, 2024.

EGU24-18203 | ECS | Orals | ITS2.5/NH13.5 | Highlight

Temporal Dynamics of Internal Mobility in Response to Climate Extremes: A Global Analysis. 

Kristina Petrova, Karim Zantout, Sandra Zimmermann, Katja Frieler, and Jacob Schewe and the the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)

This study presents a novel approach to understanding the impact of climate extremes on human mobility by examining not only the immediate response to the occurrence of such events per se but also the effect of their duration and frequency over time. Utilizing the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) climate data in combination with recently released geo-located sub-national net migration data provided by Niva et al. 2023, we assess the influence of various climate-related events, including droughts, floods, crop failures, and tropical cyclones. Our analysis goes beyond the traditional binary assessment of whether climate extremes affect mobility, delving into the nuanced ways these recurrent events shape migration patterns in areas with different levels of socio-economic development and political inclusivity over time. We aim to capture the shifts in net migration at a granular level, providing insights into how populations respond to environmental stressors over short, medium, and long-term periods. This temporal aspect is crucial in understanding the resilience and adaptability of communities in the face of climate change. Our findings reveal significant variations in mobility responses depending on the nature and duration of climate extremes.  This study contributes to the broader discourse on climate change and human mobility by highlighting the importance of considering temporal dynamics in policy development and planning for climate resilience.

How to cite: Petrova, K., Zantout, K., Zimmermann, S., Frieler, K., and Schewe, J. and the the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP): Temporal Dynamics of Internal Mobility in Response to Climate Extremes: A Global Analysis., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18203, https://doi.org/10.5194/egusphere-egu24-18203, 2024.

EGU24-18416 | ECS | Orals | ITS2.5/NH13.5

An agent-based model for testing the impact of policy options on flood displacement in Sudan 

Eleonora Panizza, Yared Abayneh Abebe, Roberto Rudari, and Mauro Spotorno

The IGAD region in East Africa has experienced a rise in the occurrence and severity of floods over time, as a consequence of climate variability and change. Among member states, Sudan stands out as one of the most affected by recurrent floods, suffering significant damage to houses, livelihoods, infrastructure, and economic activities. Areas along the River Nile, in particular, are often affected by riverine flooding. These events continue to displace thousands of people annually in the country, while immobility in the face of disasters is also an issue. In response to this challenge, the design and implementation of effective flood risk mitigation policies have become paramount, addressing both physical and socio-economic perspectives. 

The aim of this research was to develop an agent-based model (ABM) to simulate human behavior and assess the impact of policies on flood displacement patterns in seven locations in Khartoum State, Sudan. To lay the groundwork for the ABM, a household survey was conducted to collect information about the socioeconomic characteristics, flood displacement experience, and risk perceptions of the resident population. The ABM operates as a tool for modeling the behavior of autonomous household entities in various 30-year hazard and policy scenarios. Policies, tested both individually and in combination, include the Early Warning System, the Awareness Programme, the Basic Income Programme, the House Repair Programme and the Build Back Better Programme. 

In the model, households’ actions and decisions within the different flood and policy scenarios depend on their personal characteristics. Elements that influence the decision to move or stay include risk perception, socioeconomic characteristics, and flood damage. This innovative model serves as an instrument for estimating the volume of displacement, evacuation, and immobility across different scenarios. It supports the identification of the most effective intervention strategy for the context under consideration. 

The focus of the presentation is on the results of the comparative policy analysis derived from the ABM simulations. These findings are also instrumental in supporting local and national decision-makers in mitigating the risk of flood displacement and immobility, thereby strengthening the resilience of communities to flood challenges.

How to cite: Panizza, E., Abebe, Y. A., Rudari, R., and Spotorno, M.: An agent-based model for testing the impact of policy options on flood displacement in Sudan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18416, https://doi.org/10.5194/egusphere-egu24-18416, 2024.

EGU24-18736 | ECS | Posters on site | ITS2.5/NH13.5

Abandoned villages in the Catalan and Aranese Pyrenees during the Little Ice Age and the 20th Century: exploration of climate forcings through historical documents 

Mercè Cisneros, Josep Barriendos, Mariano Barriendos, Agustí Esteban i Amat, Cristina Simó, Claudi Aventín-Boya, and Javier Sigró

The unequivocal global warming of the climate system and the clear influence of human activities underscore the urgency of addressing the present challenge of Earth's warming. The exploration of past climate patterns presents significant opportunities in this regard.

Past climate information in high-mountain-areas, such as the Catalan or Aranese Pyrenees, is often still scarce. This is attributed to various reasons. On one hand, instrumental data series for these regions during the 20th century are not abundant and/or frequently start only from the 1960s. On the other hand, concerning climate information derived from historical documents for the past centuries in some of these regions, although its potential has been demonstrated in previous studies, it remains largely unexplored. Given all of this, it is not difficult to realize that these high-mountain-regions may exhibit a particular vulnerability in the face of current conditions of global warming. At the same time, its reactivity allows for the swift documentation of changes, as observed in the rapid regression of permanent Pyrenean glaciers over the past 50 years.

It is important to note that, given the strategic position of many of these locations as passages and border areas, especially from the mid-17th century onward, with the consolidation of European nation-states, there comes the implementation of the concept of political borders, various events throughout history (such as fires, wars, etc.) have led to the total or partial destruction of numerous documents. Frequently, the history of certain events is only preserved through oral accounts passed down from generation to generation.

Life in the Pyrenees has often been challenging, sustained by those individuals who have remained faithful, resisted, and persevered. The people of the Pyrenees have relied on the forest, pastures, and rather lean lands for their livelihood, and transportation has consistently posed difficulties. Additionally, sporadic phenomena of various kinds, whether historical, economic, or natural (avalanches, floods, earthquakes...), the latter strongly impacting the natural hazards in mountainous areas, have triggered changes in the villages or, in the worst cases, their abandonment and/or disappearance. The impact on these communities has often resulted from a combination of phenomena that is challenging to disentangle.

Here, we present an initial exploration of abandoned villages in the Catalan and Aranese Pyrenees during the Little Ice Age and the 20th century. The developed methodology includes the classification of depopulated areas based on various attributes: moment of disappearance, cause, altitude, and location. We have examined the climatic trends that could have affected the regions of the depopulated areas at different times. Causes include natural phenomena such as avalanches and landslides, as well as other factors like epidemics or plagues. The combination of these physical and biological factors can produce strong economic crisis at different scales. In extreme cases, this deterioration leds to the abandonment of specific villages. It is worth noting the centrifugal effect of large industrial and service agglomerations located in proximity, which have significantly contributed to the depopulation of Pyrenean settlements, whether seasonally (especially in the 19th century) or permanently (particularly in the 20th century).

How to cite: Cisneros, M., Barriendos, J., Barriendos, M., Esteban i Amat, A., Simó, C., Aventín-Boya, C., and Sigró, J.: Abandoned villages in the Catalan and Aranese Pyrenees during the Little Ice Age and the 20th Century: exploration of climate forcings through historical documents, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18736, https://doi.org/10.5194/egusphere-egu24-18736, 2024.

EGU24-19158 | ECS | Posters on site | ITS2.5/NH13.5 | Highlight

A data-driven approach to predict water security and societal impacts: the risk of drought-induced internal displacement in the Horn of Africa. 

Marthe Wens, Hans de Moel, Anne van Loon, Michel Isabellon, Daria Ottonelli, Sylvain Ponserre, and Lauro Rossi

The characterization of drought hazards remains a complex endeavor, primarily due to the absence of a universally accepted definition for a "drought event." Different deficits across various parts of the water cycle contribute to a spectrum of drought consequences, rendering the definition contingent upon the impacts incurred. Moreover, quantifying drought vulnerability poses challenges given the intricate interplay among socioeconomic, political, and environmental factors that influence the relationship between a drought event and its impacts on exposed production systems, people and nature. 
Our work addresses these challenges by introducing a novel data-driven methodology employing an array of drought indices and several datasets on observed drought impacts. Applying decision tree-based AI techniques, this method identifies combinations of hydrometeorological conditions known to generate societal consequences, and as such is able to estimate probabilistic drought disaster risk.

The presented impact-based approach is generalizable and impacts evaluated include energy production losses, internal displacement, crop and livestock damage, malnutrition, ecosystem health degradation, and strains on drinking water utilities. Illustrated through a case study in the Horn of Africa, this contribution exemplifies the quantification of expected annual drought impact, whereby impact is measured as the number of drought-induced internally displaced persons (IDPs). Drawing on the latest IDMC Displacement Tracking Matrix data, we assessed drought displacement risks under current and projected climate scenarios for Somalia and Ethiopia. Both countries grapple with complex human mobility dynamics, driven by a multitude of push and pull factors. Our findings reveal average annual IDPs up to 2% in some regions in Ethiopia, rising to 3% with unmitigated climate change. In Somalia, the majority of regions are anticipated to experience on average >10,000 drought-induced IDPs annually, under all future projections. Our model demonstrates proficiency in distinguishing prolonged and flash droughts as drivers for displacement. Furthermore, it facilitates the identification of hotspot areas, thereby supporting drought disaster risk reduction decisions and proactive policies.

How to cite: Wens, M., de Moel, H., van Loon, A., Isabellon, M., Ottonelli, D., Ponserre, S., and Rossi, L.: A data-driven approach to predict water security and societal impacts: the risk of drought-induced internal displacement in the Horn of Africa., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19158, https://doi.org/10.5194/egusphere-egu24-19158, 2024.

Climate change interacts with a multitude of socioeconomic characteristics (i.e. income, age, employment), determining individual risk and coping capacities. However, existing impact assessments of climate risk commonly focus on aggregate levels, leaving blind spots with respect to within-country distributional effects. Adhering to the concept of intersectionality, this study examines differential vulnerabilities and factors determining heterogeneities on a household level in the context of heat and flood related risks in Austria. 

We extend upon previous research by identifying differential vulnerabilities and the patterns determining heterogeneities among agents. To this end, we develop a mixed-methods approach, bringing together two ends of the spectrum: the generic representation of a single representative household and highly context specific individual risk determinants. Building on stakeholder involvement at different governance levels, qualitative insights from workshops and interviews are developed into narratives and storylines. These are vital for identifying key drivers of vulnerability and later integrated and combined with multivariate statistical analysis. Using the K-modes clustering algorithm, we combine geocoded socioeconomic data (e.g. age, sector and type of employment and income) with climate impact data (flood inundation level for different return periods, kysely days) on a 1kmx1km scale. Such development of archetypes aligns quantitative clusters with qualitative narratives, fostering mutual validation and a profound understanding of differential climate risk. Thus, the iterative exchange between quantitative and qualitative methods constitutes the backbone of this study. 

Through this approach, we identify reoccurring indicator combinations to disentangle the socioeconomic drivers of differential vulnerabilities and coping capacities in the context of flood- and heat-related climate risk. This sheds light on the within-country distributional implications of climate change, characterizing archetypical patterns of vulnerability and the constraints underlying adaptive capacities. Our findings contribute towards a more nuanced representation of society in climate impact assessments and enhance the understanding of the individual constraints limiting adaptive capacities, informing the development of targeted and just adaptation. 

How to cite: Beier, J., Preinfalk, E., and Hanger-Kopp, S.: Identifying archetypes of climate vulnerability: A mixed-methods approach for heat and flood related risk in Austria , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19508, https://doi.org/10.5194/egusphere-egu24-19508, 2024.

EGU24-20205 | Posters on site | ITS2.5/NH13.5

An integrated assessment of future risks of climate change for Austria: spatio-temporal trends of ozone, heat, and social vulnerability  

Michael Friesenecker, Thomas Thaler, Monika Mayer, Harald Rieder, Herbert Formayr, Christian Schmidt, and Lehner Fabian

Assessing the spatio-temporality of risks associated with climate change have become dominant in disaster risk research. However, integrated assessments of spatio-temporal aspects combing hazard, exposure and social vulnerability is still under-researched, especially in the fields extreme heat events and heightened ozone concentrations. Studies frequently tend to concentrate either solely on the hazard dimension, such as heatwaves and ozone exceedances, neglecting their interactions (Feron et al. 2023), or solely on isolated spatio-temporal assessments of social vulnerability and exposure (Santos et al. 2022). Using the recent risk conception of the latest IPCC report, we analyze risk as the cumulative interaction of hazard, exposure and vulnerability for historical trends and near future scenarios.

A novel data set allows for an integrated assessment of historic spatio-temporal trends as well as near-future trends using different SSP-RCP combinations (SSP2-4.5 & SSP3-8.5) at census tract level. To assess the combined impact of temperature and ozone extremes, we utilize bias-corrected model fields from high resolution runs of the coupled chemistry-climate model WRF-Chem. Population data was projected until 2050 by combining historical growth rates for selected indicators with national change rates from the Shared Socio-economic Pathways (SSP) database by IIASA (Riahi et al. 2017). Regional variations in national SSP change rates are weighted with regionalized projections for population and age groups, and historic data on income and education from the Eurostat Database.

Methodologically, we use the Adjusted Mazziotta-Pareto Index (AMPI) normalization method to overcome the limitations of comparing z-scored values over time as reported by Santos et al. (2022). This has the advantaged that all values across all periods of time are considered in normalization (Mazziota & Pareto 2022). Bases on the integration into a composite indicator, we, first, performed a multivariate analysis of how sub-indicators for hazard, exposure and social vulnerability relate to each other for Austria. Second, we applied global and local Moran’s I statistics to analyze if the spatial patterns have changed in terms of spatial heterogeneity or spatial clustering over time.

The paper concludes by highlighting the needs of integrated risk assessments and discusses the potentials and limitations of our assessment approach. Finally, possible benefits of the interdisciplinary and small-scale use of SSP-RCP combinations for a more comprehensive formulation of informed policy guidelines.

 

Feron, S., Cordero, R. R., Damiani, A., Oyola, P., Ansari, T., Pedemonte, J. C., ... & Gallo, V. (2023). Compound climate-pollution extremes in Santiago de Chile. Scientific Reports13(1), 6726.

Mazziotta, M., & Pareto, A. (2022). Normalization methods for spatio‐temporal analysis of environmental performance: Revisiting the Min–Max method. Environmetrics33(5), e2730.

Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O’neill, B. C., Fujimori, S., ... & Tavoni, M. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global environmental change42, 153-168.

Santos, P. P., Zêzere, J. L., Pereira, S., Rocha, J., & Tavares, A. O. (2022). A novel approach to measuring spatiotemporal changes in social vulnerability at the local level in Portugal. International Journal of Disaster Risk Science13(6), 842-861.

How to cite: Friesenecker, M., Thaler, T., Mayer, M., Rieder, H., Formayr, H., Schmidt, C., and Fabian, L.: An integrated assessment of future risks of climate change for Austria: spatio-temporal trends of ozone, heat, and social vulnerability , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20205, https://doi.org/10.5194/egusphere-egu24-20205, 2024.

EGU24-20639 | ECS | Orals | ITS2.5/NH13.5

Integrating adaptive approaches in addressing climate-induced stresses: Evidence of a mixed-method study in coastal Bangladesh  

Md Abdullah Al Mamun, Jianfeng Li, Aihong Cui, Raihana Chowdhury, and Md Lokman Hossain

The coastal regions of Bangladesh have been struggling with extreme weather events, including frequent storm surges, heatwaves, droughts, and rising sea levels. These coastal regions provide the majority of the produced agricultural crops and sustain the lives and livelihoods of marginalized people of the country. Given the increasing frequency and intensity of extreme weather events, understanding the existing challenges in agriculture and the adaptive mechanisms in crop production is critical for ensuring agricultural sustainability and ensuring livelihoods in smallholder farmers in the coastal region. In this study, using qualitative and quantitative methods, we assessed the challenges and adaptive techniques in agriculture and the trajectory of climatic conditions in two agriculture-dominated but climate-vulnerable sub-districts in the southeastern coastal region of Bangladesh.

Using focus group discussions (FGDs) and key informant interviews (KIIs), we explored (i) the challenges faced by the farmers, and (ii) adaptive techniques farmers have adopted in addressing climate-induced stresses in two highly climate-vulnerable sub-districts in the southeastern coastal region of Bangladesh. Two drought indices (Standardized Precipitation Evapotranspiration Index: SPEI, and the Standardized Terrestrial water storage Index: STI) were used to assess the temporal trends of climatic conditions in the studied sub-districts. Qualitative information was analyzed by thematic and content analyses, while quantitative information was analyzed by the Kendall test.

Respondents in FGDs and KIIs identified untimely precipitation, droughts in crop growing seasons, limited irrigation water, and outbreaks of pests during flowering time are the major challenges in agriculture. Farmers have adopted resilient crop varieties to address these challenges. The prominent crop varieties are heat- and salt-tolerant rice, drought-tolerant vegetables, and pest-resistant crops. Notably, qualitative findings show that farmers are utilizing organic fertilizers (vermicompost) to improve soil health, mulching to keep the soil moist, storing rainwater in ponds to irrigate winter and summer crops, and growing shallow-rooted and short-rotation crops to better adjust to changing weather conditions. The study highlights the growing popularity of vermicompost in improving soil fertility and improving soil water holding capacity, indicating its potential as a nature-based solution in agricultural sustainability. Examination of the temporal trend of climatic conditions obtained from SPEI and STI values, we found that both of our studied sub-districts experienced increasing dry climatic conditions. The observed increasing growing season dry climatic conditions (obtained from 3- and 6-month SPEI and STI values) in both sub-districts support the documented responses of the respondents in FGDs and KIIs.

This study highlights the extensive problem of climate-induced stresses in coastal Bangladesh and its impact on crop production. It emphasizes the significance of adaptive practices, like stress-tolerant crop varieties, bio-fertilizers, rainwater harvesting, mulching, and cultivating short rotation and shallow-rooted crops to address the adverse impacts of climate change. The findings are of practical importance for the government, NGOs, and stakeholders for ensuring sustainable agriculture and food security in coastal Bangladesh.

How to cite: Mamun, M. A. A., Li, J., Cui, A., Chowdhury, R., and Hossain, M. L.: Integrating adaptive approaches in addressing climate-induced stresses: Evidence of a mixed-method study in coastal Bangladesh , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20639, https://doi.org/10.5194/egusphere-egu24-20639, 2024.

EGU24-21029 | Orals | ITS2.5/NH13.5 | Highlight

Global Evidence of the Impacts of Natural Disasters on Economic Preferences  

Sara M. Constantino, Giovanna d’Adda, Milica Vranic, and Elke U. Weber

Extreme weather events are increasing in frequency and severity, directly affecting economic growth and development, especially in low-income countries. Disasters may also have indirect effects through their impacts on economic preferences, including risk, time, and social preferences, which shape individual investment decisions and economic relationships. Using experimentally validated measures of six economic preferences in 64 countries, we find that recent exposure to natural disasters makes individuals on average more risk averse, less patient and less prosocial. The effects are strongest among individuals who are less resilient to shocks because they (a) live in countries with limited resources and inadequate social and institutional safety nets; or b) are in cultural contexts with “looser” social norms and lower social cohesion; or (c) are exposed to shocks against which it is hard to prepare. We also find that short- term exposure to natural disasters may hamper interpersonal relationships by decreasing negative reciprocity and social trust, but that higher lifetime exposure may actually increase trust and positive reciprocity over the long-term. Our results point to the importance of climate adaptation and mitigation policies and robust and rapid post-disaster relief measures that reduce the negative impacts of natural disasters, mitigating their indirect as well as direct impacts on economic growth and human development.

How to cite: Constantino, S. M., d’Adda, G., Vranic, M., and Weber, E. U.: Global Evidence of the Impacts of Natural Disasters on Economic Preferences , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21029, https://doi.org/10.5194/egusphere-egu24-21029, 2024.

EGU24-270 | ECS | Posters virtual | ITS2.4/NH13.7

Domino effects of Climate Change on Financial Capital of India under CMIP6 Projections 

Vivek Ganesh, Santonu Goswami, and Harini Nagendra

Climate change is a major driver of increased flood risk, which is causing economic meltdown in many parts of the world. Globally, economic losses incurred by floods are estimated at around 453 billion USD. In the Asian region, India experienced the third highest economic loss of 4.2 billion USD due to flooding. Mumbai, India’s financial capital, faces climate change threats due to rising sea level, increased rainfall, and intense cyclones, posing risks to infrastructures, economy, and population, especially in low-lying areas. The Mithi river which overflows during monsoon season, plays a crucial role in carrying storm water to the sea in Mumbai. As it flows through an international airport, major industrial complexes and densely populated residentials, these areas became more vulnerable to flooding. This study demonstrates the domino effects of climate change on Mithi River watershed by utilising CMIP6 13 GCM ensembled daily mean precipitation model data for the near future 2030 under shared socio-economic pathways (SSP) 245 and 585 scenarios. Using the Hydrodynamic model GeoHECRAS, the flood inundation depth and extent were estimated. Under both projections, July 25-26, 2030, observed maximum rainfall and exhibited maximum streamflow with a peak discharge of 51.2 m3/sec (SSP245) and 38.5 m3/sec (SSP585). A quantitative risk assessment conducted based on the domino effects triggered by flooding to determine the projected impacted population and economic losses. The annual projected impacted population under both scenarios is observed as SSP245: Very High (0.24M), High (0.74M), Moderate (0.80M), Low (2.90M), and SSP585: Very High (0.68M), High (0.70M), Moderate (0.86M), Low (2.45M). The annual expected amount of urban property damaged due to this effect will range from $157 billion to $535 billion, with a projected affected GDP of more than $84 billion. This cascading effect is likely to disrupt Mumbai's million-dollar trade, affecting global financial flows. This study will be useful to understand the domino effect and raising the flood risk awareness for the development of sustainable policies.

Keywords: Domino effects, CMIP6, economic loss, hydrodynamic, flood depth and extent

How to cite: Ganesh, V., Goswami, S., and Nagendra, H.: Domino effects of Climate Change on Financial Capital of India under CMIP6 Projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-270, https://doi.org/10.5194/egusphere-egu24-270, 2024.

Energy systems across the world are rapidly evolving to meet climate mitigation targets. This requires a rapid transition to electricity systems lower reliance on fossil fuels and greater weather-dependent renewable generation (such as wind power, solar power, and hydropower). This increased weather dependence adds a new set of challenges for balancing supply and demand due to the inherent variability of weather, increasing the need for investment in storage and flexible technologies. The impacts of climate variability and climate change on national energy systems is a topic of current academic interest. Both in terms of security of supply risks from system level challenges (e.g., energy shortfall events, where existing generation is insufficient to meet demand) or from smaller-scale infrastructure challenges (e.g., extreme weather impacting the operability of energy system components).

This talk will discuss a programme of work on energy sector impacts using the UK Climate projections data (UKCP18). This is a suite of state-of-the-art climate model projections available at 60km resolution globally, 12km spatial resolution over Europe, and 2.2km resolution over the UK. Electricity demand, wind power, and solar photovoltaic power timeseries are developed for the period 1980-2080 using the regional climate model outputs. Climate data of this high spatial and temporal resolution is critical for the accurate quantification of meteorological hazards of relevance to the energy sector. The UK energy sector will be used as a case study in this talk due to its large share of variable renewables and commitments to reach net-zero emissions by 2050 and decarbonising the electricity system by 2035.

This talk will highlight weather-driven risks to the energy sector in both a present and future climate, with a particular focus on compound events. At short timescales examples of these risks could be periods of high demand combined with low wind power generation, or weather patterns extending over a very large area of Europe (therefore creating a spatial compound event) or sequences of extreme weather (such as several storms happening in quick succession, which could damage energy infrastructure). At longer timescales these types of compound events could be years with low renewable energy production relative to demand, or as successive years with low production. Future work will use the years containing extreme events highlighted in this talk as inputs within high resolution power system modelling simulations.

 

How to cite: Bloomfield, H.: Using high resolution climate data to help prepare future energy systems for weather-driven extremes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8794, https://doi.org/10.5194/egusphere-egu24-8794, 2024.

EGU24-8945 | Orals | ITS2.4/NH13.7

Bringing high-resolution climate data into action: Experiences from the transdisciplinary funding measure RegIKlim 

Kevin Sieck, Joaquim Pinto, Jan-Albrecht Harrs, Bente Tiedje, Astrid Ziemann, Elena Xoplaki, Beate Geyer, Hendrik Feldmann, Julia Mömken, Heiko Paeth, Katja Trachte, Christopher Kadow, and Laura Dalitz

In the RegIKlim funding measure (Regional Information for Action on Climate Change, https://www.fona.de/en/measures/funding-measures/regional-information-for-action-on-climate-change.php), the cross-sectional project NUKLEUS (Actionable Local Climate Information for Germany) is concerned with the provision of useful, actionable, and high-resolution climate information for Germany and the improvement of the interface between climate data and subsequent use, e.g. in impact models for adaptation to climate change, in six pilot regions distributed across Germany.   

Climate simulations on the convection-permitting scale were hardly available at the beginning of the project and their simulation areas generally did not cover all model regions or longer time periods. Based on the requirements of the users from the model regions, the prototype of an ensemble with simulations of three regional climate models was generated and thus the first multi-decadal multi-climate model ensemble on a convection-permitting scale (approx. 3 km horizontal resolution) for Germany. It can be shown that the model results are within the expected deviations compared to measured values and that the high-resolution data of the 3 km simulations on short time and spatial scales offer added value compared to the EURO-CORDEX simulations. 

In order to improve the interface between climate data and impact models for application, a data and analysis portal (Freva) was set up in NUKLEUS, which facilitates users from the model regions to find suitable data and generate customized data sets using small programs (plugins). The first user-driven plugins have been developed and their application will be presented.  

The improvement of the interface also includes information on the uncertainties of certain influencing variables in the impact modeling and the reduction of systematic deviations of the simulations from the observed climate by e.g. bias correction methods. An important result of the uncertainty analysis of the model chain is that the range of climate information is not always the most important variable. Insufficient or outdated land use information can also have a decisive influence on the climate signal. The testing of different bias correction methods shows that the bias correction in principle leads to a reduction in systematic errors, but that the availability of high-resolution observational data for the correction is a major challenge in s. With the statistical refinement approach, good results were achieved for precipitation at a very high resolution of 300-500 m, especially in geographically highly structured regions. 

To ensure the translation of the modeling-based information into practical application, the cross-sectional project WIRKsam (Scientific Coordination for the Development of a Regional Climate Register) has developed a set of best practices based on transdisciplinary working group discussions.  To specifically address public spatial planning, it is important to exemplify the utilization potential of the data in pilot application (e.g. development plans) and develop user-oriented capacity-building modules and interpretations guidelines. Through surveys and workshops, transdisciplinary research projects can identify crucial municipal administrative processes, develop information tools for decision support and learn how they could benefit from the new data. This might involve facilitating a cross-departmental understanding of roles and responsibilities.

How to cite: Sieck, K., Pinto, J., Harrs, J.-A., Tiedje, B., Ziemann, A., Xoplaki, E., Geyer, B., Feldmann, H., Mömken, J., Paeth, H., Trachte, K., Kadow, C., and Dalitz, L.: Bringing high-resolution climate data into action: Experiences from the transdisciplinary funding measure RegIKlim, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8945, https://doi.org/10.5194/egusphere-egu24-8945, 2024.

EGU24-9098 | ECS | Posters on site | ITS2.4/NH13.7

Climate risk analysis for adaptation planning in Zambia’s agricultural sector 

Rahel Laudien, Abel Chemura, Carla Cronauer, Tim Heckmann, Stephanie Gleixner, Christoph Gornott, Lisa Murken, and Julia Tomalka

Climate change and climate extremes increasingly threaten agricultural production and thereby pose a serious risk to agricultural livelihoods, particularly in the Global South. In support of adaptation planning, science-based information on projected climate impacts and sound information on the suitability of adaptation options is needed.

This study provides a comprehensive analysis of current and future climate-related risks in Zambia – a country that is highly vulnerable to climate change due to its geographic location and the strong socio-economic dependency on agriculture. Using data from ten Global Climate Models (GCMs) under two climate change scenarios (SSP1-RCP2.6 and SSP3-RCP7.0), we analyze future trends in climatic conditions and model their impacts on agricultural yields and crop suitability. Moreover, the study evaluates two adaptation options to promote climate-resilience in the agricultural system i.e. 1) conservation agriculture and 2) a climate and agricultural extension service called PICSA (Participatory Integrated Climate Services for Agriculture). The evaluation includes biophysical, economic, financial and gender aspects to provide comprehensive and usable information that can inform adaptation policies on the ground. The study was co-designed together with stakeholders from Zambian governmental institutions, civil society, academia, the private sector, practitioners and development partners.

Results show the strongest negative impacts of climate change in South Western Zambia where the strongest increases in temperature and dry conditions are projected. The projected impacts underline the need for strong adaptation efforts: 1) Conservation agriculture can buffer climate impacts in the near term and even increase sorghum yields by 25 to 31% in drought-prone areas in Zambia. It can play a vital role in adapting to increasingly extreme and dry climatic conditions. 2) The PICSA approach proved to be a highly economically beneficial adaptation option with each USD invested generating between 3.6 and 3.8 USD in benefits.

In addition, the study reflects on lessons learned from interdisciplinary and stakeholder-driven research – focusing not only on the Zambian context, but also on climate risk analyses that were conducted in Burkina Faso, Cameroon, Ethiopia, Ghana, Madagascar, Niger and Uganda.

How to cite: Laudien, R., Chemura, A., Cronauer, C., Heckmann, T., Gleixner, S., Gornott, C., Murken, L., and Tomalka, J.: Climate risk analysis for adaptation planning in Zambia’s agricultural sector, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9098, https://doi.org/10.5194/egusphere-egu24-9098, 2024.

EGU24-9297 | ECS | Orals | ITS2.4/NH13.7 | Highlight

From Stakeholder Engagement to Inclusivity: Advancing Participatory Modeling for Net-Zero Sustainable Development 

Victoria Herbig, Stephanie Briers, and Bianca Vienni-Baptista

Despite the significant advancements of Integrated Assessment Models [IAMs] in recent years, criticisms underscore their limitations in effectively responding to questions on climate change adaptation and mitigation (4). Such critiques highlight the need for IAMs to be not only technologically advanced but also transparently accessible to both the modeling community and stakeholders (1).

The Horizon Europe project “Delivering the next generation of Open Integrated Assessment Models for net-zero, sustainable development” [DIAMOND] seeks to bridge these gaps. By leveraging participatory and transdisciplinary approaches, DIAMOND aims to enhance, extend, and open up IAMs, aligning them more closely with climate action and sustainable development objectives through open and responsible stakeholder engagement.

Engaging a broad range of stakeholders and working collaboratively with them stands out as pivotal in bolstering the credibility and effectiveness of modeling results (5; 6). Acknowledging policymakers’ inputs further strengthens the potential integration of modeling results into policy-making processes (1). This paper presents co-created comprehensive good practice guidelines for inclusive stakeholder engagement, grounded in a case study of the DIAMOND project. The focus is on establishing an inclusive modeling environment that ensures representation and decision making embody diverse stakeholders’ perspectives, knowledge, and interests, including those of policymakers. Utilizing a transdisciplinary approach facilitates a move towards genuine inclusivity, ensuring all relevant parties, regardless of their background or expertise, are given the opportunity to participate, contribute, and have their voices heard in the decision-making process (2). Employing a mixed-methods approach that combines a literature review, stakeholder elicitation, an online survey, and semi-structured interviews, this study triangulates these methods to comprehensively assess collaborative dynamics, adaptive strategies, and the operational context, providing a nuanced understanding of the complex interactions at play.

This paper endeavors to guide modelers, irrespective of their modeling background, towards producing relevant and actionable results that are aligned with real-world implications and policy needs (3). Through assessing and integrating the dimension of “inclusivity” within participatory modeling processes and demonstrating its integration within a transdisciplinary framework, this study aspires to offer valuable insights to the broader modeling community. The insights derived can empower modelers across disciplines to provide policymakers with evidence-based approaches for designing effective climate change adaptation measures and informing mitigation decisions, paving the way for better-informed policies guiding society towards a sustainable and net-zero future.

References:

(1) Doukas, H., Nikas, A. (2019). European Journal of Operational Research, 280, 1-24. https://doi.org/10.1016/j.ejor.2019.01.017
(2) Ernst, A., Fischer-Hotzel, A., Schumann, D. (2017). Energy Research & Social Science, 29, 23-35. http://dx.doi.org/10.1016/j.erss.2017.04.006
(3) Jordan, R., Gray, S., Zellner, M., Glynn, P. D., Voinov, A., et al. (2018). Earth’s Future, 6, 1046–1057. https://doi.org/10.1029/2018EF000841
(4) Keppo, I., Butnar, I., Bauer, N., Caspani, M., Edelenbosch, O., et al. (2021). Environmental Research Letters, 16, 053006. https://doi.org/10.1088/1748-9326/abe5d8
(5) McGookin C., Gallachóir B., Byrne, E. (2021). Renewable and Sustainable Energy Review, 151, 111504. https://doi.org/10.1016/j.rser.2021.111504
(6) Pisano, U., Lange, L., Lepuschitz, K., Berger, G. (2015). European Sustainable Development Network. ESDN Quarterly Report, 39.

How to cite: Herbig, V., Briers, S., and Vienni-Baptista, B.: From Stakeholder Engagement to Inclusivity: Advancing Participatory Modeling for Net-Zero Sustainable Development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9297, https://doi.org/10.5194/egusphere-egu24-9297, 2024.

Climate change poses a significant threat to communities on regional scale as well as worldwide, and the urgency for adaptation is particularly crucial for small- and medium-sized communities and cities. However, a pervasive knowledge gap exists in these regions, hindering their ability to adapt effectively. The lack of accessible and tailored climate information and services exacerbates the vulnerability of these communities. Therefore, this study focuses on addressing this knowledge gap and developing effective science communication strategies, emphasizing the regional scale through the implementation of Regional Climate Information Platforms.

The chosen case study location, Oberland (Upper Bavaria, Germany), is characterized by complex terrain, encompassing Alpine and Pre-Alpine regions, with three distinct climate zones in close proximity. The diverse topography of Oberland presents unique challenges, as climate change impacts may manifest differently across the region, particularly for hydro-meteorological extremes. Moreover, the region heavily depends on tourism, making it economically susceptible to changing climate conditions and increasing extreme events, such as extreme precipitation, flooding, summer heatwaves and decreasing snowfall affecting tourism activities (e.g. skiing, hiking, climbing, etc.).

Thus, the study aims to follow a comprehensive workflow, starting with the collection of climate data, followed by bias correction and regionalization for Oberland. High-resolution rainfall statistics will be developed and integrated into hydrodynamic simulations and cluster analyses of flood triggering mechanisms. The outcome will be the creation of risk maps for hydro-meteorological extremes, providing crucial information for stakeholders and decision-makers. Finally, these risk maps will be then incorporated into the digital decision support system, Platform Oberland within the KARE (Klimawandelanpassung auf regionaler Ebene) Project.

In addition to the scientific aspects, the study emphasizes the importance of stakeholder interaction and co-design in the development of Platform Oberland. The collaboration between scientists and stakeholders ensures that the information generated is relevant and usable for decision-making. With this study, it is also aimed to identify "best-practice" approaches for transferring scientific workflows and results into actionable climate-related measures for small- and medium-sized communities.

This case study in Oberland could serve as a regional model for effective science communication and adaptation strategies at the regional level for hydro-meteorological extremes, offering insights into the development of climate indicators and the integration of scientific findings into practical, community-centered climate adaptation.

How to cite: Koc, G., Lorenz, C., Feldmann, D., and Böker, B.: Effective Science Communication for Climate Change Adaptation on Regional Scale – Regional Climate Information Platforms: A Case Study in Oberland (Upper Bavaria – Germany), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10592, https://doi.org/10.5194/egusphere-egu24-10592, 2024.

EGU24-10602 | ECS | Posters on site | ITS2.4/NH13.7

Bias correction of SMILEs: A bulk approach to preserve internal variability 

Jorge Sebastian Moraga, Sabine Undorf, Peter Uhe, Natalie Lord, and Nans Addor

Single Model Initial-condition Large Ensembles (SMILEs) represent a pivotal progress in climate modeling, offering multiple simulations from a single model to address the inherent uncertainties in climate projections (Maher et al., 2021). However, biases intrinsic to climate models can distort SMILEs' outputs, potentially misrepresenting climate risks and uncertainties.

In climate impact studies, bias correction of Earth System Models (ESMs) typically aligns model outputs with observed historical data, using statistical methods to adjust climatic variables. While essential, this correction may suppress the range of climatic conditions, particularly when applied individually to each ensemble member, thus diminishing the ensemble's diversity and its ability to represent varied climate futures. Instead, we explore whether a bulk approach to bias correction is more appropriate for SMILEs. This method involves applying a consistent correction across the entire ensemble, thereby maintaining the relative differences and natural variability among the ensemble members and preserving the unique capacity of SMILEs to represent a broad spectrum of climatic conditions, in particular under current and near-future climate.

Our analysis used the 100-member dataset from the Community Earth System Model Large Ensemble Project Phase 2 (CESM-LENS2, Rodgers et al., 2021), covering historical and future climate simulations. We adjusted key climate variables—precipitation, temperature, relative humidity, and surface pressure within the CONUS domain—using the ISIMIP3basd algorithm (Lange, 2019), with MSWX reanalysis data as the historical reference (Beck et al., 2022). Our experiment involved a twofold comparison: We first evaluated the results after adjusting the entire ensemble at once using (the bulk approach) and, secondly, after adjusting each individual ensemble member separately (member-by-member approach). This comparative analysis allowed us to discern the effects of these two different bias correction methodologies on the ensemble's ability to represent climate variability and extremes.

Our results show the effect of both bias correction approaches on the variability of crucial climate extreme statistics and the correlation between ENSO and climate variables. Additionally, we discuss how the choice of bias adjustment method can influence the magnitude of projected changes under future climate scenarios, a key consideration in climate impact studies.

References:

  • Beck, H. E., Van Dijk, A. I., Larraondo, P. R., McVicar, T. R., Pan, M., Dutra, E., & Miralles, D. G. (2022). MSWX: Global 3-hourly 0.1 bias-corrected meteorological data including near-real-time updates and forecast ensembles. Bulletin of the American Meteorological Society, 103(3), E710-E732.
  • Lange, S. (2019). Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1. 0). Geoscientific Model Development, 12(7), 3055-3070.
  • Maher, N., Milinski, S., & Ludwig, R. (2021). Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble. Earth System Dynamics, 12(2), 401-418.
  • Rodgers, K. B., Lee, S. S., Rosenbloom, N., Timmermann, A., Danabasoglu, G., Deser, C., ... & Yeager, S. G. (2021). Ubiquity of human-induced changes in climate variability. Earth System Dynamics, 12(4), 1393-1411.



How to cite: Moraga, J. S., Undorf, S., Uhe, P., Lord, N., and Addor, N.: Bias correction of SMILEs: A bulk approach to preserve internal variability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10602, https://doi.org/10.5194/egusphere-egu24-10602, 2024.

EGU24-12154 | Posters on site | ITS2.4/NH13.7

Assessing and explaining future changes on sub-daily precipitation extremes using an ensemble of convection-permitting models 

Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, and Marco Borga

Anticipating and understanding the future evolution of intense precipitation events is crucial for improved risk management, especially in regions with mountainous terrain and urban areas vulnerable to natural disasters from extreme weather. Convection-permitting climate models (CPMs) operating at kilometer scales realistically depict convective precipitation mechanisms and complex terrain, enhancing the description of sub-daily extreme precipitation. However, their computational demands restrict simulations to short time periods (10-20 years), and limit the availability of ensemble members, hindering the evaluation of extreme event change and associated uncertainty.

This study employs an innovative non-asymptotic extreme value approach, proven effective in estimating rare return levels with reduced stochastic uncertainty even from short datasets, and which can help in providing insights on the changing processes. We apply the Simplified Metastatistical Extreme Value distribution (SMEV) to estimate the projected changes in future extreme sub-daily precipitation in a region characterized by complex terrain—specifically, the North Italy area encompassing both lowlands and the Italian Alps. Our analysis focuses on an ensemble of 9 CPMs from the CORDEX-FPS project, with a spatial resolution of 3 kilometers. We investigate three time periods: historical (1996-2005), near future (2041-2050), and far future (2090-2099) under the RCP8.5 emission scenario. We estimate return levels up to a 1% yearly exceedance probability (100-year return time) for precipitation durations from 1 to 24 hours. Their future change is evaluated at each grid point, conducting a permutation test to assess the statistical significance of the changes.

Results indicate a general increase in extreme precipitation across the domain and all durations, with spatial patterns of significant changes varying with durations, time period, and location. A pronounced increase occurs in some of the mountainous areas: at short durations in Eastern Alps, and across all durations in the northern Apennines. The western Alps and surroundings show moderate and not-significant change. Leveraging SMEV's ability to separate precipitation intensity distribution from event occurrence, we also examine the change in distribution parameters to interpret the shift in return levels in term of changes in thermodynamics (linked to temperature and water vapor content) and atmospheric dynamics controls. Interestingly, thermodynamics seems to be driving significant changes at short durations, while small-scale local dynamics contribute across all durations. Differences emerge between the Eastern Alps and Northern Apennines, with the latter showing a stronger intensification of intense versus moderate extreme events.

These findings provide valuable insights towards quantifying and understanding the future changes in precipitation extremes, benefiting stakeholders involved in risk management and design of adaptation measures.

This study was carried out within the RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005).

How to cite: Dallan, E., Marra, F., Fosser, G., Marani, M., and Borga, M.: Assessing and explaining future changes on sub-daily precipitation extremes using an ensemble of convection-permitting models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12154, https://doi.org/10.5194/egusphere-egu24-12154, 2024.

EGU24-12378 | ECS | Posters on site | ITS2.4/NH13.7

Comparing extreme sub-daily rainfall projections from temperature-scaling and convection-permitting climate models across an Alpine gradient 

Rashid Akbary, Marco Marani, Eleonora Dallan, and Marco Borga

Understanding projected changes in sub-daily extreme rainfall in mountainous basins can help increase our capability to adapt to and mitigate against flash floods and debris flows. Here we compare the changes in extreme rainfall projections from apparent Clausius-Clapeyron (CC) temperature scaling against those obtained from convection-permitting climate model simulations. Temperature and precipitation projections are obtained from an ensemble of convection-permitting climate models (CPM), which are suitable to the task given their ability to explicitly represent deep convection and to resolve the mountainous topography. The CPM data provided by the CORDEX-FPS Convection project at 1-hour temporal and remapped to 3 km spatial resolution, cover historical and far-future (2090-2099) time periods under the extreme climate change scenario (RCP8.5). Due to the computational demands however, CPM simulations are still too short (typically 10-20 years) for analyzing extremes using conventional methods. We use a non-asymptotic statistical approach (the Metastatistical Extreme Value, MEVD, Marani and Ignaccolo, 2015) for the analysis of extremes from short time periods, such as the ones of CPM simulations. We use hourly precipitation and temperature data from 174 stations in an orographically complex area in northeastern Italy as a benchmark.

Results from our analysis reveal that the apparent CC temperature scaling method demonstrates effective performance when applied to 1-hour extreme rainfall projections and for high return periods. However, its accuracy decreases as the precipitation duration increases, highlighting potential limitations in accurately predicting changes in longer-duration extreme rainfall. Variations in performance are also noted when considering different return periods, as we find CPM changes depending on them, contradicting traditional CC-scaling. Furthermore, we show that elevation is a key factor influencing temperature variations, with higher elevation locations experiencing more pronounced temperature increases with respect to lowland areas. This affects more the results for 1 hr extreme rainfall projections, whereas it is less relevant for 24-h duration. These findings identify some serious limitations of traditional CC scaling and emphasize the need for a nuanced understanding of the scaling method's applicability under various conditions.

How to cite: Akbary, R., Marani, M., Dallan, E., and Borga, M.: Comparing extreme sub-daily rainfall projections from temperature-scaling and convection-permitting climate models across an Alpine gradient, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12378, https://doi.org/10.5194/egusphere-egu24-12378, 2024.

EGU24-12806 | ECS | Posters on site | ITS2.4/NH13.7

The effect of terrestrial water storage anomalies on regional economic growth 

Anna Reckwitz, Maximilian Kotz, Christian Voigt, and Leonie Wenz

Terrestrial water storage (TWS) is an essential resource for agriculture, urban development, and energy production, as well as ecosystem health and climate change mitigation. Through satellite gravimetry methods, GRACE and GRACE-FO measurements enable the assessment of TWS anomalies globally, revealing significant alterations over the past two decades due to natural variability, climate change impacts, and direct human influence. Existing studies focus on the impacts of TWS changes on the production of specific crops or agricultural output in specific countries, yet the effects on agro-economic output on a more global scale are not yet well understood. 

To address this gap in our understanding of the macroeconomic impacts of TWS changes, we combine GRACE measurements with data on economic growth from more than 1600 subnational regions worldwide over the last 60 years. We then empirically assess the impact of TWS anomalies on regional economic growth, employing a long-difference model and fixed-effects panel regression, following recent work on temperature and precipitation impacts. We find that negative groundwater anomalies are associated with reductions in economic growth in a majority of regions. This highlights the critical role of freshwater availability, in particular in low-income regions. Furthermore, we observe that the relationship between TWS and economic growth depends on both meteorological and socioeconomic factors. These heterogeneous relations reflect the complex interplay between water resources and economic development, and indicate potential endogeneity therein. We therefore further discuss instrumental variable approaches for isolating the meteorological drivers of water storage and their causal impact on economic output. These findings contribute valuable insights to the ongoing discourse on sustainable water management and its implications for economic prosperity.

How to cite: Reckwitz, A., Kotz, M., Voigt, C., and Wenz, L.: The effect of terrestrial water storage anomalies on regional economic growth, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12806, https://doi.org/10.5194/egusphere-egu24-12806, 2024.

EGU24-13127 | ECS | Posters on site | ITS2.4/NH13.7 | Highlight

Climate adaptive urban extreme weather risk assessment and management 

Lingyan Kang, Jiang Wu, and Fengting Li

Climate change, an escalating global predicament, is intricately linked with the uncertainties surrounding urban development, a process that is intricately tied to economic growth and social progress. This interconnectedness gives rise to new interconnected risks that present significant social and economic challenges, threatening the sustainability of our urban centers. This study takes into account climate change risk mitigation and adaptation strategies, focuses on urban climate risk identification and establishment of climate adaptive city risk assessment index system. Through the sorting of historical data, the improvement of disaster statistics and other interconnection to clarify regional risks in different fields, and discusses methods to achieve efficient risk management and governance of climate-resilient cities under the dual background of urbanization and climate change. By adopting a perspective centered on climate risk management, this research provides forward-thinking guidance for long-term perspectives on urban planning and construction.

How to cite: Kang, L., Wu, J., and Li, F.: Climate adaptive urban extreme weather risk assessment and management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13127, https://doi.org/10.5194/egusphere-egu24-13127, 2024.

The IPCC AR6 assessment of the impacts and risks associated with projected climate changes for the 21st century is both alarming and ambiguous. According to computer projections, global surface may warm from 1.3 to 8.0 °C by 2100, depending on the global climate model (GCM) and the shared socioeconomic pathway (SSP) scenario used for the simulations. Actual climate-change hazards are estimated to be high and very high if the global surface temperature rises, respectively, more than 2.0 °C and 3.0 °C above pre-industrial levels. Recent studies, however, showed that a substantial number of CMIP6 GCMs run “too hot” because they appear to be too sensitive to radiative forcing, and that the high/extreme emission scenarios SSP3-7.0 and SSP5-8.5 must be rejected because judged to be "unlikely" and "highly unlikely", respectively. Yet, the IPCC AR6 mostly focused on such alarmistic scenarios for risk assessments. This paper examines the impacts and risks of “realistic” climate change projections for the 21st century generated by assessing the theoretical models and integrating them with the existing empirical knowledge on global warming and the various natural cycles of climate change that have been recorded by a variety of scientists and historians. This is achieved by combining the "realistic" SSP2-4.5 scenario and empirically optimized climate modeling. The GCM macro-ensemble that best hindcast the global surface warming observed from 1980–1990 to 2012–2022 is found to be made up of models that are characterized by a low equilibrium climate sensitivity (ECS) (1.5<ECS<3.0 °C), in contrast to the IPCC AR6 likely and very likely ECS ranges of 2.5-4.0 °C and 2.0-5.0 °C, respectively. This GCM macro-ensemble projects a global surface temperature warming of 1.68-3.09 °C by 2080–2100 instead of 1.98-3.82 °C obtained with the 2.5-4.0 °C ECS GCMs. However, if the global surface temperature records are affected by significant non-climatic warm biases — as suggested by satellite-based lower troposphere temperature records and current studies on urban heat island effects — the same climate simulations should be scaled down by about 30%, resulting in a warming of about 1.18-2.16 °C by 2080–2100. Furthermore, similar moderate warming estimates (1.15-2.52 °C) are also projected by alternative empirically derived models that aim to recreate the decadal-to-millennial natural climatic oscillations, which the GCMs do not reproduce. The obtained climate projections show that the expected global surface warming for the 21st century will likely be mild, that is, no more than 2.5-3.0 °C and, on average, likely below the 2.0 °C threshold. This should allow for the mitigation and management of the most dangerous climate-change-related hazards through appropriate low-cost adaptation policies. In conclusion, enforcing expensive decarbonization and net-zero emission scenarios, such as SSP1-2.6, is not required because the Paris Agreement temperature target of keeping global warming below 2 °C throughout the 21st century should be compatible also with moderate and pragmatic shared socioeconomic pathways such as the SSP2-4.5.

Reference: Scafetta, N.: 2024. Impacts and risks of “realistic” global warming projections for the 21st century. Geoscience Frontiers 15(2), 101774. https://doi.org/10.1016/j.gsf.2023.101774

How to cite: Scafetta, N.: Impacts and risks of “realistic” global warming projections for the 21st century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16297, https://doi.org/10.5194/egusphere-egu24-16297, 2024.

The correct representation of fine-scale atmospheric processes, like convection, is vital for predicting extreme weather events and CPMs have already shown to provide more reliable representation of extreme precipitation. However, in most cases their validation is limited to the precipitation field and based on sparse in-situ observations or coarser resolution observational gridded dataset. In this study, we first explore whether high-resolution (i.e., grid spacing 2.2km) reanalysis product SPHERA provides a realistic representation of the in-situ observations, thus offering  a comprehensive overview of the atmosphere at fine scale and functioning as a reliable reference dataset for CPMs evaluation. Then the sub-daily precipitation and wind fields of the CPMs ensemble from the CORDEX Flagship Pilot project on Convective Phenomena over Europe and the Mediterranean (FPS Convection) is validated against both in-situ observation and SPHERA. The validation focuses on extreme quantiles, spatial variability and event representation with a quantile based approach (i.e., the event starts when atmospheric variables are above a certain quantile, and ends when it goes below). Results show a general good agreement between in-situ observations and SPHERA, that is found to be a good reference dataset to evaluate the CPM models. When looking at the extreme quantiles, the CPMs well represent  both wind and precipitation fields, although they underestimate heavy precipitation in summer (i.e., June-July-August). Similarly, the spatial distribution of precipitation and wind is well represented for all the season, with a decrease in the spatial variability and spatial correlation for the heavy precipitation in the summer. Finally the CPMs underestimate the number of the events when precipitation and wind are treated singularly, while they substantially overestimate the number of compound events of rainfall and winds. The analysis shows the capability of CPMs to represent the precipitation and wind fields and highlights the possibility of using high-resolution reanalysis into the evaluation of convection-permitting models. Moving from point-based measurements to high-resolution gridded observational datasets opens the path to the use of SPHERA for advanced bias correction methods that could take into account the full 3D dimension of the atmosphere and the processes within it.

How to cite: Cesarini, L. and Fosser, G.: Validation of CPM’s wind and precipitation field against observations and the highresolution reanalysis dataset SPHERA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17774, https://doi.org/10.5194/egusphere-egu24-17774, 2024.

EGU24-17775 | Posters on site | ITS2.4/NH13.7

Assessment of convection-permitting sub-daily extreme precipitation simulations over Italy 

Marco Borga, Paola Mazzoglio, Marco Lompi, Francesco Marra, Eleonora Dallan, Roberto Deidda, Pieluigi Claps, Salvatore Manfreda, Leonardo Noto, Alberto Viglione, Mario Raffa, and Enrica Caporali

Convection-permitting climate models have the potential to capture crucial processes in the climate system, presenting an opportunity to significantly enhance climate projections by providing more accurate representations of precipitation extremes. In this work, we conduct an evaluation of the accuracy of sub-daily precipitation extremes obtained from VHR-PRO_IT (Very High-Resolution PROjections for Italy, Raffa et al., 2023) over the Italian peninsula,. VHR-PRO_IT is generated through dynamic downscaling of the Italy 8km-CM climate projection at approximately 2.2 km resolution under the IPCC RCP4.5 and RCP8.5 scenarios, employing the Regional Climate Model COSMO-CLM.

Gauged locations are used to assess the accuracy of VHR-PRO_IT in reproducing observed extremes. More specifically, the observed dataset used as ground truth for the comparison is I2-RED (Improved Italian – Rainfall Extreme Dataset; Mazzoglio et al., 2020). For this work, 742 rain gauges covering the entire country with a minimum of 30 years of short-duration (1, 3, 6, 12, 24 h) annual maximum rainfall depths recorded from 1980 to 2022 are used. Conversely, the dataset derived from the VHR-PRO_IT climate projections includes annual maxima from a 30-year time series, connecting the historical period (1981-2005) with 5 years of the RCP8.5 scenario (2006-2010) of the CPM. Return levels are obtained for both dataset by means of a GEV distribution and inform the assessment of the CPM simulations. 

Preliminary results outline the quality of the CPM simulations, especially at 24 hours duration, and show the impacts of return period, seasonality, elevation, latitude and proximity to the sea on the CPM model deviations. The results from this work are expected to have implications for both water resources management and adaptation measures.

References

Mazzoglio P., Butera I., Claps P. (2020). I2-RED: a massive update and quality control of the Italian annual extreme rainfall dataset. Water, 12, 3308.

Raffa M., Adinolfi M., Reder A., Marras G.F., Mancini M., Scipione G., Santini M., Mercogliano P.  (2023). Very High Resolution Projections over Italy under different CMIP5 IPCC scenarios. Scientific Data, 10, 238.

How to cite: Borga, M., Mazzoglio, P., Lompi, M., Marra, F., Dallan, E., Deidda, R., Claps, P., Manfreda, S., Noto, L., Viglione, A., Raffa, M., and Caporali, E.: Assessment of convection-permitting sub-daily extreme precipitation simulations over Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17775, https://doi.org/10.5194/egusphere-egu24-17775, 2024.

In the contemporary landscape, the aftermath of each weather-related disaster triggers swift estimations of economic losses, often accompanied by attributions of increased frequency or intensity of such events. The prompt assignment of blame for weather-related disaster losses is a complex endeavor, as discerning the precise role of climate change proves challenging due to the intricacy arising from intertwining climate alterations with societal transformations, contributing to the evolving dynamics of disaster impacts. In parallel, assessing disaster loss and damage is crucial, especially in vulnerable areas prone to natural disasters, such as the Himalayan region, as it is highly susceptible to climate-induced events and potentially severe consequences for the environment and human settlements. The study focuses on the state of Uttarakhand in India, aiming to comprehensively understand the interplays between climate change, societal shifts, and economic repercussions following weather-related calamities. The primary objective is to develop a detailed loss inventory for Uttarakhand, specifically focusing on past events, types of losses, and their spatial distribution. The methodology thoroughly examines secondary sources, data from the Em-Dat database, government reports, and relevant research articles. This comprehensive approach enables understanding of weather-related disaster losses, considering the impacts of climate change and societal changes in the region. The study also employs a robust time-series analysis methodology to unravel the temporal and spatial distribution of disasters due to extreme events, recognizing their significance in shaping disaster dynamics. The analysis aims to identify vulnerable rural and urban clusters within Uttarakhand, provide valuable insights into the spatial patterns of specific loss types, and map high-risk areas within Uttarakhand, contributing to proactive disaster mitigation strategies. This information is crucial for adapting disaster response and recovery strategies, allowing for the effective allocation of resources based on the unique needs of affected regions by integrating loss inventory creation, time-series analysis, and vulnerability mapping. The findings are expected to not only deepen our understanding of the complex interplays between climate change, societal shifts, and disaster losses but also provide actionable insights for mitigating the impact of future weather-related calamities in the Himalayan region, particularly in the state of Uttarakhand.

How to cite: Goyal, S. and Mukherjee, M.: Comprehensive Assessment of Climate-Induced Disaster Losses in Uttarakhand: A Time-Series Analysis and Vulnerability Mapping Approach , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18267, https://doi.org/10.5194/egusphere-egu24-18267, 2024.

EGU24-19847 | ECS | Orals | ITS2.4/NH13.7 | Highlight

Challenges in quantifying physical risk to assets globally 

Joe Stables, Graham Reverly, James Brennan, Sally Woodhouse, Nicholas Leach, Laura Ramsamy, Patricia Sullivan, and Jonathan Davies

As the physical processes of our world change, the landscape of risk has changed with it. At Climate X, we provide high-quality data to the financial sector so that evolving risks to global portfolios can be quantified. A crucial element of this is the physical risk from events, including extreme weather events.

Traditionally risk assessments have been carried out at an asset level on small scales, with a dedicated team spending days on tens of assets. The high price and slow turnaround makes this unfeasible for large scale operations. We provide an alternative, leveraging open source datasets and research to estimate the physical risk to over half a billion buildings worldwide. This talk will highlight some challenges of working at this scale, and illustrate our approaches to resolving them.

How to cite: Stables, J., Reverly, G., Brennan, J., Woodhouse, S., Leach, N., Ramsamy, L., Sullivan, P., and Davies, J.: Challenges in quantifying physical risk to assets globally, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19847, https://doi.org/10.5194/egusphere-egu24-19847, 2024.

EGU24-20739 | Orals | ITS2.4/NH13.7 | Highlight

Incorporating Ethics into Climate Intervention Research, Experimentation, and Potential Deployment 

Mark Shimamoto, Janice Lachance, and Billy Williams

Climate change requires urgent action. Aggressive actions toward carbon emissions reduction must remain the primary strategy for reversing and addressing climate change. However, increasingly the world is considering technology-based climate intervention approaches—often called climate engineering. There are major practical and ethical questions about the significant risks and potential trade-offs some of these approaches would bring and how they would be measured against the risks of our warming world. Recognizing the need for guiding principles in this fast-moving, dynamic space and building on AGU’s longstanding history of advancing and advocating for strong scientific ethics, AGU is facilitating the development of a draft Ethical Framework for Climate Intervention Research, Experimentation, and Deployment. The ethical framework will be released in 2024 and will serve as a resource to help governments, researchers, NGOs, and the private sector make responsible decisions when engaging in climate intervention research or policy. In 2023, the draft framework completed a rigorous three-month public comment period and consultation process to include more holistic input from other scientists and ethicists, as well as community voices, youth advocates, and many more. This presentation will highlight the ethical principles and how the science community can incorporate and advocate for ethics in climate intervention research.

How to cite: Shimamoto, M., Lachance, J., and Williams, B.: Incorporating Ethics into Climate Intervention Research, Experimentation, and Potential Deployment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20739, https://doi.org/10.5194/egusphere-egu24-20739, 2024.

Considerable risk is involved in the use of climate models or their products (i.e., simulations and data) when there is a lack of adequacy or fitness for one’s purpose. Of specific concern is the risk of generating information in response to an actionable or applied question or aim that is irrelevant, misleading, inappropriate, inconsistent, or highly inaccurate, as this can lead to downstream harms such as maladaptation. This form of “misuse” is innocent or unintentional, and is largely a function of a user’s misunderstanding or misinterpretation of the intended purposes of a model and/or modeling exercise and the applicability of the model’s products. Ineffective communication and lack of transparency into the intended purposes, assumptions, representational features, adequacies, as well as inadequacies and limitations of a model, can lead to this form of inappropriate and unjustified repurposing. Currently, there is an increase in the demand for open and accessible data, and an increase in the use of climate data, especially data from high-resolution modeling efforts, for applied and actionable purposes (contexts in which derived products are used to inform decision-making). Given both conditions, the reduction and management of possible inappropriate repurposing, i.e., misuse, has become a highly salient consideration for any modeling effort. Producers of models and their products have a moral duty to implement mechanisms to aid users in the identification, understanding, and control of this risk. This can happen by way of the distribution of expert guidance, increase in intentional transparency, and instantiation of systematic norms for clearly and plainly communicating the fitness of purpose and inadequacies of models and their products. This would provide a large step forward toward the reduction of misuse of information in climate science that could lead to harmful consequences, and pave the way for the development of an ethics of scientific practice for the climate science community.

How to cite: Morrison, M.: Towards an Ethics of Modeling and Data Use for Actionable Climate Science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20838, https://doi.org/10.5194/egusphere-egu24-20838, 2024.

EGU24-22469 | Posters on site | ITS2.4/NH13.7

Dynamic agricultural weather indicators for extreme weather prediction in agriculture 

Timm Waldau, Pedro Batista, Peter Baumann, Thorsten Behrens, Peter Fiener, Jens Foeller, Markus Moeller, Ingrid Noehles, Karsten Schmidt, and Burkhard Golla

The project “DynAWI – dynamische Agararwetterindikatoren” (dynamic agriculture weather indices) aims to develop a process chain for data integration and real-time analysis for extreme weather. Extreme weather events have a major impact on agriculture and horticulture and cause significant economic costs. The damage depends not only on the type of extreme weather event (e.g. heat wave, drought stress or heavy precipitation), but also on the ontogenetic development of the crops. Previously, farmers calculated their risk with fixed weather indicators and because of the multi-dimensionality of the source data and it was difficult to calculate using traditional relational databases in an acceptable time.

We have developed a web application for real-time calculation of dynamic weather indicators by linking a back-end infrastructure of Datacube servers and a Vue front-end infrastructure with a machine learning model in an R environment. The web application can perform real-time analyses based on multi-dimensional spatio-temporal data. Future plans include enriching the web application with additional agricultural weather indicators and linking it to weather forecasts to provide an in-season risk assessment for crop losses.

How to cite: Waldau, T., Batista, P., Baumann, P., Behrens, T., Fiener, P., Foeller, J., Moeller, M., Noehles, I., Schmidt, K., and Golla, B.: Dynamic agricultural weather indicators for extreme weather prediction in agriculture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22469, https://doi.org/10.5194/egusphere-egu24-22469, 2024.

EGU24-22471 | Orals | ITS2.4/NH13.7

From National Climate Scenarios to National Climate Information 

Carol McSweeney, Jason Lowe, and Neha Mittal

National Climate Scenarios provide a common basis for national risk assessment and adaptation planning. Recent examples include the UK’s UKCP18, the Netherlands’ KNMI23 and the Australian ‘Climate Change in Australia’ (2015).

Advances in climate modelling approaches provide the potential for a step change in the quality, and type of national climate scenarios that will likely be produced over coming years. While these advances include improvements in the traditional approaches employed in the provision of future climate projections for adaptation planning (updated global model ensembles, various downscaling approaches including convective permitting regional projections, improvements in constraining model ensembles), developments in a wider range techniques are increasingly being used in the assessment of climate resilience. These include large initial-condition ensembles, event attribution, the exploration of ‘High Impact Low Likelihood’ (HILL) scenarios, as well as the potential to exploit enhanced skill in initialised seasonal and decadal forecasts.

Here we will share what we are learning through parallel activities which seek to (a) develop our understanding of the needs of the diverse user community in the UK through an extensive user consultation to enhance usefulness and usability and (b) scope the opportunities emerging from the climate science community may have to address the gaps in existing information, and their readiness to contribute to a National Climate Information package.

How to cite: McSweeney, C., Lowe, J., and Mittal, N.: From National Climate Scenarios to National Climate Information, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22471, https://doi.org/10.5194/egusphere-egu24-22471, 2024.

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