This talk reports a new and significantly enhanced analysis of US flood hazard at 30m spatial resolution.  For the first time we consider pluvial, fluvial and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centred on 2035 and 2050 under the RCP4.5 emissions pathway.  Validation against high quality local models and the entire catalogue of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69-0.82.  Significant improvements over a previous pluvial/fluvial model version are shown for high frequency events and coastal zones, along with minor improvements in areas where model performance was already good.  The result is the first comprehensive and consistent national scale analysis of flood hazard for the conterminous US for both current and future conditions.  Even though we consider a stabilization emissions scenario and a near future time horizon we project clear patterns of changing flood hazard (3σ changes in 100yr inundated area of -3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defence protection may become compromised by this time.

How to cite: Bates, P., Quinn, N., Sampson, C., Smith, A., Wing, O., Savage, J., Olcese, G., Sosa, J., and Neal, J.: US fluvial, pluvial and coastal flood hazard under current and future climates, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14646, https://doi.org/10.5194/egusphere-egu21-14646, 2021.

Hydrologic models are employed in the flood risk studies to simulate time series of model responses to given inputs. These simulated time series of pseudo-observations can be next statistically analysed and in this way they can extend existing observed records. Simulations of hydrologic models are however associated with modelling uncertainty, often represented through a simulation ensemble with multiple parameter sets. The need of using multiple parameter sets to represent uncertainty is linked however with increased computational costs that may become prohibitive for long-time series and many input scenarios to be analysed. Due to the non-linear input-output relationship in the hydrologic model, a pre-selection of parameter sets is challenging.

This work presents a clustering approach as a tool to learn about the model hydrologic responses in the flood frequency space from the training dataset. Based on this learning process, representative parameter sets are selected that can be directly used in other model applications to derive prediction intervals at much lower computational costs. The study is supported with sensitivity analysis to the number of clusters. Based on results from a small catchment in Switzerland and 10’000 years of streamflow pseudo-observations, it has been found that grouping the full simulation ensemble with 1000 members into 3 to 10 clusters is already suitable to derive commonly applied prediction intervals (90%, 95% or 98%) in the flood frequency space. The proposed clustering approach can be applied in any flood risk analysis to lower the computational costs linked with the use of a hydrologic model.

How to cite: Sikorska-Senoner, A. E.: Clustering model responses in the frequency space for improved flood risk analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1199, https://doi.org/10.5194/egusphere-egu21-1199, 2021.

Every year flood events cause worldwide vast economic losses, as well as heavy social and environmental impacts, which have been steadily increasing for the last five decades due to the complex interaction between climate change and anthropogenic pressure (i.e. land-use and land-cover modifications). As a result, the body of literature on flood risk assessment is constantly and rapidly expanding, aiming at developing faster, computationally lighter and more efficient methods relative to the traditional and resource-intensive hydrodynamic numerical models. Recent and reliable fast-processing techniques for flood hazard assessment and mapping consider binary geomorphic classifiers retrieved from the analysis of Digital Elevation Models (DEMs). These procedures (termed herein “DEM-based methods”) produce binary maps distinguishing between floodable and non-floodable areas based on the comparison between the local value of the considered geomorphic classifier and a threshold, which in turn is calibrated against existing flood hazard maps. Previous studies have shown the reliability of DEM-based methods using a single binary classifier, they also highlighted that different classifiers are associated with different performance, depending on the geomorphological, climatic and hydrological characteristics of the study area. The present study maps flood-prone areas and predicts water depth associated with a given non-exceedance probability by combining several geomorphic classifiers and terrain features through regression trees and random forests. We focus on Northern Italy (c.a. 100000 km², including Po, Adige, Brenta, Bacchiglione and Reno watersheds), and we consider the recently compiled MERIT (Multi-Error Removed Improved-Terrain) DEM, with 3sec-resolution (~90m at the Equator). We select the flood hazard maps provided by (i) the Italian Institute for Environmental Protection and Research (ISPRA), and (ii) the Joint Research Centre (JRC) of the European Commission as reference maps. Our findings (a) confirm the usefulness of machine learning techniques for improving univariate DEM-based flood hazard mapping, (b) enable a discussion on potential and limitations of the approach and (c) suggest promising pathways for further exploring DEM-based approaches for predicting a likely water depth distribution with flood-prone areas. 

How to cite: Magnini, A., Lombardi, M., Persiano, S., Tirri, A., Lo Conti, F., and Castellarin, A.: Combination of geomorphic classifiers through Machine Learning-based techniques for flood hazard assessment , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4723, https://doi.org/10.5194/egusphere-egu21-4723, 2021.

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. But MS sensors may not penetrate cloud cover, whereas SAR is plagued by operational errors such as noise-like speckle challenging their viability to global flood mapping applications. An attractive alternative is to effectively combine MS data and SAR, i.e., two aspects that can be considered complementary with respect to flood mapping tasks. Therefore, in this study, we explore the diverse bands of Sentinel 2 (S2) derived water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to access their capability in generating accurate flood inundation maps. For this purpose, a fully connected deep convolutional neural network known as U-Net is applied to combinations of S1 and S2 bands to 446 (training: 313, validating: 44, testing: 89) hand labeled flood inundation extents derived from Sen1Floods11 dataset spanning across 11 flood events. The trained U-net was able to achieve a median F1 score of 0.74 when using DEM and S1 bands as input in comparison to 0.63 when using only S1 bands highlighting the active positive role of DEM in mapping floods. Among the, S2 bands, HSV (Hue, Saturation, Value) transformation of Sentinel 2 data has achieved a median F1 score of 0.94 outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Also, when combined with Sentinel 1 SAR imagery too, HSV achieves a median F1 score 0.95 outperforming all the well-established water indices in detecting floods in majority of test images.

How to cite: Konapala, G. and Kumar, S.: Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10445, https://doi.org/10.5194/egusphere-egu21-10445, 2021.

Flooding seems to be the most widespread and common catastrophe in a tropical country such as India. Efficient rainfall, industrial development, huge population, the effect of the tide, and urban growth are actual reasons for flooding in urban coastal regions. Navsari, the city of Gujarat, located 19 km upstream of the Arabian Sea. The city has experienced a devastating flood on 4rth August 2004. Flash flooding and maximum discharge estimated at the Mahuva gauge station of about 8836 m3/sec were responsible for a disaster that resulted in massive damage to property and lives. A two dimensional (2D) flood simulation model is carried out to assessment of flood inundation in an urban coastal area. HEC-RAS is one of the most popular open-source hydraulic software having 2D capabilities including GIS features. In the present study, the distance between the Mahuva gauge station to the Arabian sea was considered for flood inundation assessment, whereas the SRTM 30 m DEM was used for grid generation for Navsari city. The inflow hydrograph was used as the upstream boundary condition, and normal depth was used as the downstream boundary condition during the 4th August 2004 flood event. The unsteady flow simulation was performed and validated for the year of 2004 flood event. The simulated outcomes show that major areas such as Viraval, Kachiawad, Jalalpore, near Railway station, Kaliawad, Tavdi village, and Near TATA School were flooded with 2-4 m depth. Furthermore, the simulated result demonstrates that, if the discharge exceeds 8836 m3/sec in the area of a floodplain, it may take 11 to 13 hours to make the city inundated. The R² value for the model is 0.9679, which shows that the observed value is the best match with the simulated value. The research study illustrates the accurate flood inundation assessment in the urban coastal area using open-source 2D HEC-RAS model. The present study described the applicability of open-source data and model in flood inundation assessment. The study will fill the gap of flood assessment through 2D HEC-RAS model worldwide areas, which are situated nearby coastal region, accompanied by the benefits of open-source dataset and model.

How to cite: Pathan, A. I., Agnihotri, Dr. P. G., Patel, Dr. D., and Prieto, Dr. C.: Improving assessment of flood inundation of Navsari (India) via open-source data and HEC-RAS model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4187, https://doi.org/10.5194/egusphere-egu21-4187, 2021.

The flood caused by a dam-break event generally contains a large amount of energy, and it can be destructive to the downstream buildings and structures. An experiment-validated three-dimensional numerical model was designed to investigate the impact of dam-break flood on structures with different arrangements. The Eulerian two-phase flow model and the smooth particle dynamics method are applied separately to solve the flow motion, and  the deformation characteristics of buildings under the flood impact are evaluated by fluid-structure interaction model. An experiment is constructed to validate the numerical simulation. The results show that the structure suffers a large instantaneous impact pressure when the flood water first contacts the structure, and the value of this pressure can reach 1.5-3.0 times that of the maximum pressure after the first impact, and the maximum total pressure of the upstream building surface is about 1800N. The deformation near the door and windows is obvious, and the maximum deformation can reach 600μm, which further results in the large deformation of the gable and roof on both sides. Moreover, the arrangement of buildings has different blocking effect on flood. The back-row buildings arranged in alignment along the flow direction still has to bear 20% flood impact, and the front row buildings arranged alternately bear 90% high-speed flow impact. The structural damage is evaluated by the material failure criterion, and the weak position of buildings is identified, providing an optimal design of buildings.

How to cite: Rong, Y., Bates, P., and Neal, J.: Safety evaluation of buildings under flood impact, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6049, https://doi.org/10.5194/egusphere-egu21-6049, 2021.

Wave overtopping on grass-covered dikes results in erosion of the dike cover. Once the dike cover is eroded, the core will be washed away and the dike breaches, leading to flooding of the hinterland. Transitions between grass covers and revetments or geometric transitions are vulnerable for cover erosion and are therefore the most likely locations to initiate dike breach. These transitions affect the overtopping flow and thereby the hydraulic load on the dike cover. For example, bed roughness differences can create additional turbulence and slope changes can result in the formation of a jet that increases the load at the jet impact location. Although it is known that dike cover failure often starts at transitions, the effect of transitions on the hydraulic load remains unknown.

We developed a detailed numerical 2DV model in OpenFOAM for the overtopping flow over the crest and the landward slope of a grass-covered dike. This model is used to study the effects of transitions on the overtopping flow variables including the flow velocity, shear stress, normal stress and pressure. Several types of transitions are studied such as revetment transitions, slope changes and height differences. 

The results show that the shear stress, normal stress and pressure increase significantly at geometric transitions such as the transition from the crest to the slope and at the landward toe. The increase depends on the wave volume and the geometry of the dike such as the steepness and length of the landward slope. Furthermore, the results show that roughness changes at revetment transition on a grass-covered crest has no influence on the maximum shear stress, maximum normal stress and maximum pressure. The flow velocity increases from a rough to a smooth revetment, while the opposite occurs for the transition from a smooth to a rough revetment. The variation in the flow velocity is well described by analytical formulas for the maximum flow velocity along the dike profile. These formulas are also able to describe the variation in flow velocity for a revetment transition on a berm on the landward slope. In this case, the shear stress increases from a smooth to a rough revetment and decreases from a rough to a smooth revetment. This means that a rough revetment can locally reduce the shear stress, however the transitions have no effect on the shear stress downstream.

These model results are used to obtain relations for the increase in the hydraulic variables at transitions. These relations can be used to describe the effect of transitions on the hydraulic load in models for grass cover failure by overtopping waves. Accurate descriptions of the hydraulic load in these models will improve the failure assessment of grass-covered dikes with transitions.

How to cite: van Bergeijk, V., Warmink, J., and Hulscher, S.: How do transitions affect the wave overtopping flow locally as well as downstream?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-679, https://doi.org/10.5194/egusphere-egu21-679, 2021.

Estuarine regions are strategically important from an environmental, economic, and social point of view. To reduce vulnerability and increase resilience, it is crucial to know their dynamics that usually are poorly understood. Numerical models have proven to be an appropriate tool to improve this knowledge and simulate scenarios for future conditions. However, as the modelling results may be inaccurate, the application of the ensembles technique can be very useful in reducing possible uncertainties. In the EsCo-Ensembles project, this technique is proposed to improve hydrodynamic predictions for two Portuguese estuaries: Douro and Minho.

Two already validated numerical models (openTELEMAC-MASCARET and Delft3D), which have demonstrated their ability to accurately describe estuarine hydrodynamic patterns and water elevation for river flow in normal and extreme conditions, were applied. Several scenarios for climate change effects were defined including river flood peak flows for the 100 and 1000 year return periods and sea level extreme values for RCPs 4.5 and 8.5 in 2100.

The results demonstrated a clear difference between the hydrodynamic behaviour of the two estuaries. Model outcomes for the Minho estuary, which is dominated by the tide and therefore by oceanographic conditions, show a pronounced effect of rising sea levels on estuarine hydrodynamics. Whereas, for the Douro estuary, which is heavily dominated by the river flow, the effect of the sea level rise is hardly noticeable during flood events.

These and further results of this ongoing project are expected to (i) provide a complete hydrodynamic characterization of the two estuaries; (ii) evaluate future trends; (iii) estimate the flood risks associated with extreme events and (iv) demonstrate that the combined use of different models reduces their uncertainty and increases the confidence and consistency of the forecasts.

Acknowledgements: To the Strategic Funding UIDB/04423/2020 and UIDP/04423/2020 (FCT and ERDF) and to the project EsCo-Ensembles (PTDC/ECI-EGC/30877/2017, NORTE 2020, Portugal 2020, ERDF and FCT). The authors also want to acknowledge the data provided by EDP, IH and Confederación Hidrográfica Miño-Sil.

How to cite: Iglesias, I., Pinho, J. L., Bio, A., Avilez-Valente, P., Melo, W., Vieira, J., Bastos, L., and Veloso-Gomes, F.: Future estuarine circulation patterns characterization based on a hydrodynamic models ensemble, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6541, https://doi.org/10.5194/egusphere-egu21-6541, 2021.

Land use and delineation of flood-prone areas require valuable and effective tools, such as flood mapping. Local authorities, in order to prevent and mitigate the effects of flood events, need simplified methodologies for the definition of preliminary flooded areas at a large scale. In this work, we focus on the workflow GeoFlood, which can rapidly convert real-time and forecasted river flow conditions into flooding maps. It is built upon two methodologies, GeoNet and the HAND model, making use only of high-resolution DTMs to define the geomorphological and hydraulic information necessary for flood inundation mapping, thus allowing for large-scale simulations at a reasonable economical and computational cost. GeoFlood potential is tested over the mid-lower portion of the river Tiber (Italy), investigating the conditions under which it is able to reproduce successful inundation extent, considering a 200-year return period scenario. Results are compared to authority maps obtained through standard detailed hydrodynamic approaches. In order to analyze the influence of the main parameters involved, such as DTM resolution, channel segmentation length, and roughness coefficient, a sensitivity analysis is performed. GeoFlood proved to produce efficient and robust results, obtaining a slight over-estimation comparable to that provided by standard costly methods. It is a valid and relatively inexpensive framework for inundation mapping over large scales, considering all the uncertainties involved in any mapping procedure. Also, it can be useful for a preliminary delineation of regions where the investigation based on detailed hydrodynamic models is required.

How to cite: D'Angelo, C., Passalacqua, P., Fiori, A., and Volpi, E.: Prediction capabilities of GeoFlood for the delineation of flood-prone areas: the Tiber River case study, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7591, https://doi.org/10.5194/egusphere-egu21-7591, 2021.

In this work, we present a general framework for design and risk assessment of hydraulic structures for water control. The framework relies on a “structure-based approach”, accounting for both the statistical behavior of the hydrological load acting on the river system and the hydraulic response of the structure to the environmental load. This approach allows for the reduction of a multivariate and complex statistical problem to a univariate one, focusing on the damage. The framework is applied to an offline detention basin for flood mitigation based on a general, yet simplified routing model. Furthermore, a real-world case study application is presented, with the specific aim of discussing the role of the design parameters and their effect on the probability distribution of damage. Results show the robustness and the effectiveness of the approach for applications to real cases and provide design guidance for practitioners.

How to cite: Cipollini, S., Fiori, A., and Volpi, E.: Design of offline reservoirs for flood mitigation by using a structure-based risk framework, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9118, https://doi.org/10.5194/egusphere-egu21-9118, 2021.

Earthen levees protect flood-prone areas during severe flood events. In most cases, however, flooding is the result of the collapse of the embankments due to the seepage through and under the levee body. The description of the seepage line is difficult mainly because of the uncertainty on the hydraulic parameters, first of all the soil hydraulic conductivity. Barbetta et al. (2017) proposed a practical method for the seepage analysis based on the Marchi’s equation for the estimation of the probability of occurrence of the levee seepage which provides a vulnerability index under the assumption that the groundwater level coincides with the ground. Recently, the method has been tested also considering the groundwater level below the ground pointing out that such a condition has a high impact on the levee vulnerability to seepage. However, it does not consider the interactions between seepage process in the levee body and in the foundation.

In this context, this work proposes a new approach for the analysis of the infiltration line through the body and the foundation, considering a multilayer soil and assuming a different soil hydraulic conductivity for each layer. The new equation is obtained starting from the continuity equation and the flow equation.

The saturation line estimated through the Marchi’s equation and the one derived through the new multilayer model equation are compared. The analysis is first addressed to identify a threshold of the ratio between water head and water table beyond which the Marchi’s equation is no longer applicable. Indeed, the Marchi’s equation is valid when the river water head is lower than the water table. Different values of these two variables are analyzed and a threshold ratio equal to 0.57 is identified.

Furthermore, the levee vulnerability to seepage estimated with the two approaches is compared and the levee is found more vulnerable when the new approach is applied. The results indicate that the difference between the two vulnerability approaches decreases as the distance between the groundwater table and the ground level tends to zero. The proposed approach is an attempt to quantify the seepage probability with more realistic levees characteristics, hydraulic and soil parameters.

Barbetta, S., Camici, S., Bertuccioli, P., Palladino, M. R., & Moramarco, T. 2017. Refinement of seepage vulnerability assessment for different flood magnitude in national levee database of Italy. Hydrology Research, 48(3), 763–775. https://doi.org/10.2166/nh.2017.101.

How to cite: Bonaccorsi, B., Moramarco, T., Noto, L. V., and Barbetta, S.: A multilayer soil approach for seepage process analysis in earthen levees, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11038, https://doi.org/10.5194/egusphere-egu21-11038, 2021.

During intense periods of drought, the development of cracks is observed in peat and clay dikes. Asset managers of the dikes increase the inspection frequency in times of drought to be able to monitor these cracks. Significant development of the cracks contributes to the development of different failure mechanisms. In this study, the occurrence of the cracks is predicted at a large spatial scale. An inspection database in which the observations from the last three years are stored is used as the basis. The database contains hundreds of observed cracks including the  location and time in which they were observed. The database was extended with attributes such as the precipitation deficit, the peat width at the surface, the orientation of the dike body, the subsidence of the dike body and the soil stiffness. Decision tree algorithms were then used to classify which circumstances will lead to cracks and which circumstances will not. From the resulting decision trees it was deduced that high precipitation deficits, low soil stiffness and the peat width can be used as the main predictors for the occurrence of cracks. Both subsidence of the foundation and the dike body being orientated to the sunny side are also contributors, although less prominent. Time-independent cracking criteria were then used to classify which regions are prone to cracking. Dikes which are rich in peat with a low stiffness were thus highlighted. The Mathews correlation coefficient was used as performance criteria resulting in a 0.3 value for the obtained tree. Application of a random forest increased the coefficient to 0.8. An important conclusion is that proper monitoring of the peat width, soil stiffness and precipitation may result in better asset management.

How to cite: Chotkan, S., Aguilar-López, J. P., van der Meij, R., Vardon, P., Jan Klerk, W., and Chacon Hurtado, J. C.: Predicting drought-induced cracks in dikes with machine learning algorithms, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15435, https://doi.org/10.5194/egusphere-egu21-15435, 2021.

Floods are natural disasters caused mainly due to heavy or excessive rainfall. They induce massive economic losses in Bangladesh every year. Physically-based flood prediction models have been used over the years where simplified forms of physical laws are used to reduce calculations' complexity. It sometimes leads to oversimplification and inaccuracy in the prediction. Moreover, a physically-based model requires intensive monitoring datasets for calibration, accurate soil properties information, and a heavy computational facility, creating an impediment for quick, economical and precise short-term prediction. Researchers have tried different approaches like empirical data-driven models, especially machine learning-based models, to offer an alternative approach to the physically-based models but focused on developing only one machine learning (ML) technique at a time (i.e., ANN, MLP, etc.). There are many other techniques, algorithms, and models in machine learning (ML) technology that have the potential to be effective and efficient in flood forecasting. In this study, five different machine learning algorithms- exponent back propagation neural network (EBPNN), multilayer perceptron (MLP), support vector regression (SVR), DT Regression (DTR), and extreme gradient boosting (XGBoost) were used to develop total 180 independent models based on a different combination of time lags for input data and lead time in forecast. Models were developed for Someshwari-Kangsa sub-watershed of Bangladesh's North Central hydrological region with 5772 km² drainage area. It is also a data-scarce region with only three hydrological and hydro-meteorological stations for the whole sub-watershed. This region mostly suffers extreme meteorological events driven flooding. Therefore, satellite-based precipitation, temperature, relative humidity, wind speed data, and observed water level data from the Bangladesh Water Development Board (BWDB) were used as input and response variables.

For comparison, the accuracy of these models was evaluated using different statistical indices - coefficient of determination, mean square error (MSE), mean absolute error (MAE), mean relative error (MRE), explained variance score and normalized centred root mean square error (NCRMSE). Developed models were ranked based on the coefficient of determination (R²) value. All the models performed well with R² being greater than 0.85 in most cases. Further analysis of the model results showed that most of the models performed well for forecasting 24-hour lead time water level. Models developed using XGBoost algorithm outperformed other models in all metrics. Moreover, each of the algorithms' best-performed models was extended further up to 20 days lead time to generate forecasting horizon. Models demonstrated remarkable consistency in their performance with the coefficient of determination (R²) being greater than 0.70 at 20 days lead-time of forecasting horizon in most cases except the DTR-based model. For 10- and 5-days lead time of forecasting horizon, it was greater than 0.75 and 0.80 respectively, for all the model extended. This study concludes that the machine algorithm-based data-driven model can be a powerful tool for flood forecasting in data-scarce regions with excellent accuracy, quick building and running time, and economic feasibility.

How to cite: Haque, M. H., Sadia, M., and Mustaq, M.: Development of Flood Forecasting System for Someshwari-Kangsa Sub-watershed of Bangladesh-India Using Different Machine Learning Techniques, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15294, https://doi.org/10.5194/egusphere-egu21-15294, 2021.

The low lying and sandy coastal areas of the Emilia-Romagna region are heavily threatened by sea storms, often leading to flooding and coastal erosion events with severe impacts on citizens’ quality of life, damages to the cultural heritage and effects on economic activities (e.g. aquaculture, fisheries, tourism, beach facilities). Climate change projections reinforce the need of strategies and tools to prevent damages and promptly react to extreme events. In this context and in the framework of non-structural mitigation measures, the Hydro-Meteo-Climate Service of Arpae Emilia-Romagna (Arpae-SIMC) developed and operationally manages a Coastal Early Warning System (EWS) for the Emilia-Romagna Region (Northeast Italy).

The EWS was developed during the EU Project FP7-MICORE and it is a state-of-the-art coastal forecasting system that follows a chain of operational numerical models: the meteorological model COSMO, the wave model SWAN-MEDITARE, the ocean model AdriaROMS, and the morphodynamic model XBeach. The latter is currently implemented on a series of cross-shore beach profiles covering eight locations distributed along the Emilia-Romagna shore. Deterministic daily forecasts (72-hours) are generated and Storm Impact Indicators (SIIs) used to assess sea-storm induced coastal risk along the region’s littoral (geo.regione.emilia-romagna.it/schede/ews). 

It is widely known that among the limitations of deterministic approaches, the lack of uncertainty estimation is often problematic as decision-makers might be misled if the only forecast available underestimates (or overestimates) incoming conditions. Hence, following the success of probabilistic forecasting in meteorological applications, storm surge EWSs following ensemble frameworks have been recently developed, allowing for more information available to sustain the decision-making process. Towards the new paradigm change, one of the foreseen outputs of the European Interreg Italy-Croatia CBC Programme project Strategic development of flood management (STREAM) involves the development of a “probabilistic EWS for coastal risk implemented and tested on at least one location along the Emilia-Romagna Coast”. 

The initial implementation of the (semi-)probabilistic framework benefits from the EU ADRION I-STORMS (Integrated Sea Storm Management Strategies) project outcomes, in which wave and sea level multi-model ensembles were developed for the Adriatic Sea giving origin to the Transnational Multi-Model Ensemble (TMES). The TMES was made available as one of the six Integrated Web System (IWS) components, combining five wave and six sea level forecasting systems as means to provide 48-hour forecasts in terms of sea level and wave characteristics (Hs, Tm and Dm). Ensemble mean and standard deviation (SD) are calculated based on different forecasting systems’ results. In the initial approach, four TMES combinations have been tested as XBeach forcing: the TMES mean; the mean minus one SD; the mean plus one SD; the mean plus two SDs. Two months were analyzed together with the already implemented deterministic system for two profiles along the region’s coast.

The methodology followed for the test period will be shown as well as the results. Furthermore, the methodology under development will be also shown as means to enhance the discussion involving storm surge ensemble applications.

How to cite: Germano Biolchi, L., Unguendoli, S., Bressan, L., Giambastiani, B. M. S., and Valentini, A.: A (semi-)probabilistic storm surge EWS implementation for the Emilia-Romagna region (Italy), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15210, https://doi.org/10.5194/egusphere-egu21-15210, 2021.

We investigate how European heat waves and their associated heat stress on humans have changed over the 20th century. We find that the heat stress has increased, even in regions where heat waves have not become warmer. As heat stress increases over wide areas of Europe there is also an increase in the total population affected by the heat stress. 

Heat waves pose a serious health risk to humans by reducing our ability to shed heat. We have studied the occurrence and intensity of heat waves as well as a heat stress index based on simplified wet-bulb globe temperature using data from ERA-20C reanalysis 1900-2010. Over the 110 years of data we find an overall warming of the air temperatures and dew point. The 98th percentile of both air temperature has increased by more than 1.5°C over large areas of Europe. 

We find an overall increase in heat wave days per year as well as an increase of air temperature during heat waves over most of Europe. As such, many densely populated areas exhibit increased heat stress during heat waves. For example, the mean heat stress during heat wave days over Paris has increased by one level, from “alert” in 1900-1930 to “caution” in 1980-2010. The fraction of the population exposed to heat waves has increased by 10%/century in central Europe and 25%/century over the Mediterranean. 

We find more heat waves during 1920 - 1950, which may be related to the positive phase of the Atlantic Multidecadal Variation (AMV). This suggests that the heat stress during European heat waves may also be influenced by internal climate variability, and large-ensemble model simulations may be used to disentangle the effects of natural variability and anthropogenic forcing.

How to cite: Kjellsson, J., Niebaum, N., and Pilch Kedzierski, R.: Trends in heat stress over Europe over the 20th century, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2582, https://doi.org/10.5194/egusphere-egu21-2582, 2021.

We use the 100-member Max Planck Institute Grand Ensemble (MPI-GE) to disentangle the contributions from colocated dynamic atmospheric conditions and local thermodynamic effects of moisture limitation as drivers of variability in European summer heat extremes. Using a novel extreme event definition, we find that heat extremes with respect to the evolving mean climate increase by 70% under a moderate warming scenario during the twenty-first century. With a multiple regression approach, we find that the dynamical mechanisms representing blocking and anticyclonic conditions are the main driver of variability in extreme European summer temperatures, both in past and future climates. By contrast, local thermodynamic drivers play a secondary role in explaining the total variability in extreme temperatures. We also find that considering both dynamical and thermodynamical sources of variability simultaneously is crucial. Assessing only one type of drivers leads to an overestimation of their effect on extreme temperatures, particularly when considering only thermodynamical drivers. Lastly, we find that although most past and future heat extremes occur under favorable dynamical atmospheric conditions; this occurs 10–40% less frequently over Central Europe in the twenty-first century. By contrast, heat extremes over Central Europe occur 40% more frequently under concurrent extreme moisture limitation in the twenty-first Century. Our findings highlight a new type of neutral-atmosphere, dryness-driven heat extremes, and confirm that the increase in European heat extremes and associated variability increase are dominated by the local thermodynamic effect of moisture limitation.

How to cite: Suarez-Gutierrez, L., Li, C., Müller, W. A., and Marotzke, J.: Dynamical and thermodynamical drivers of variability in European summer heat extremes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11842, https://doi.org/10.5194/egusphere-egu21-11842, 2021.

Extreme temperatures have warmed substantially over recent decades and are projected to continue warming in response to future climate change. Warming of extreme temperatures is amplified over land where the impacts on human health, wildfire risk and food production are most severe. Using simulations with climate models, I show that hot days over tropical land warm substantially more than the average day. For example, warming of the hottest 1% of land days is 24% larger than the time-mean warming averaged across models. The climate-change response of extreme temperatures over tropical land is interpreted using a theory based on atmospheric dynamics. According to the theory, warming is amplified for hot land days because those days are dry: I term this the "drier get hotter" mechanism. Changes in near-surface relative humidity further increase tropical land warming , with decreases in land relative humidity particularly important. The theory advances physical understanding of the tropical climate and highlights land-surface dryness as a key factor determining how extreme temperatures will respond to future climate change.

How to cite: Byrne, M.: Amplified warming of extreme temperatures over tropical land, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-566, https://doi.org/10.5194/egusphere-egu21-566, 2021.

Extreme heat under global warming is a concerning issue for the growing tropical population. However, model projections of extreme temperatures, a widely used metric for extreme heat, are uncertain on regional scales. In addition, humidity also needs to be taken into account in order to estimate the health impact of extreme heat. Here we show that an integrated temperature-humidity metric for the health impact of heat, namely the extreme wet-bulb temperature (TW), is controlled by established atmospheric dynamics and thus can be robustly projected on regional scales. For each 1°C of tropical mean warming, global climate models project extreme TW (the annual maximum of daily-mean or 3-hourly values) to increase roughly uniformly between 20°S and 20°N latitude by about 1°C. This projection is consistent with theoretical expectations based on tropical atmospheric dynamics, and observations over the past 40 years, which gives confidence to the model projection. For a 1.5°C warmer world, the likely (66 per cent confidence interval) increase of regional extreme TW is projected to be 1.33-1.49°C, whereas the uncertainty of projected extreme temperatures is 3.7 times as large. These results suggest that limiting global warming to 1.5°C will prevent most of the tropics from reaching a TW of 35°C, the limit of human adaptation.

How to cite: Zhang, Y., Held, I., and Fueglistaler, S.: Projections of tropical heat stress constrained by atmospheric dynamics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1587, https://doi.org/10.5194/egusphere-egu21-1587, 2021.

Rising global temperatures are a potential cause for increase of extreme climate events, such as heat waves, both in severity and frequency. Under an increasing extreme event scenario, the world population of mid- and low-latitude countries is more vulnerable to heat related mortality and morbidity.

In India, the events occurred in recent years have made this vulnerability clear, since the numbers of heat-related deaths are on a rise, and heat waves can impact various sectors including health, agriculture, ecosystems and the national economy.

Preliminary results show the prevalence of heat events in seven different regions of India during the pre-monsoon (March, April, May) and transitional (May, June, July) months. We consider daily maximum temperatures (Tmax) and the NOAA’s Heat Index (HI), a combination of temperature and relative humidity that gives an insight into the discomfort because of increment in humidity.

We look into various drivers behind the heat events in the seven different clusters, in particular ENSO and the North Atlantic Regimes that have been linked to the generation of heat waves in different parts of India. The preliminary results indicate Nino 3.4 SST anomalies show positive correlation with Tmax anomalies only in the western coast during pre-monsoon season, while in the transitional months positive correlation extends to central and east India. The Tmax composite anomalies for the cold, warm and neutral phases of ENSO show positive anomalies for only warm years and negative anomalies for the cool and neutral years. Heat Index shows similar spatial patterns for correlation analysis and composite anomaly analysis. The Mean Sea Level Pressure (MSLP) composite associated with heat waves (days exceeding 95th percentile=>3 days) show a persistent ridge over the North Atlantic region.

How to cite: Kapoor, R., Alvarez-Castro, C., Scoccimarro, E., Materia, S., and Gualdi, S.: Heat Events in the Indian Subcontinent under a warming climate scenario: Detection and its Drivers , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12972, https://doi.org/10.5194/egusphere-egu21-12972, 2021.

This study provides an overview of the projected temperature extremes over the MENA region until the end of the 21st century. The main objectives of our analysis are the following: i) analyze the projected changes in temperature extremes using the CMIP5 multi-model ensemble, reveal ii) the warmest model realizations and iii) the “hotspot” locations within MENA with the projected highest temperature extremes. For this purpose, a list of indices of temperature extremes, based on threshold, percentile, heatwave and coldwave characteristics is used, as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We use daily near-surface air (2-metre) temperature (Tmax and Tmin) to derive the extremes-indices for the period 1980-2100. The data were taken from 18 CMIP5 models combining historical (1980-2005) and scenario runs (2006-2100 under RCP 2.6, RCP4.5 and RCP8.5). Using these datasets, the indices of temperature extremes were derived. The changes of the extremes over the 21st century are analyzed, in space and time, relative to the reference period 1981-2000. Moreover, a model ranking is performed based on the magnitude of the projected changes of the indices and the relation with the model climate sensitivity is explored. A further analysis of model statistics over specific locations/grid points reveals the areas with the projected most intense heat extremes.

How to cite: Ntoumos, A., Hadjinicolaou, P., Zittis, G., and Lelieveld, J.: Assessment of the projected temperature extremes over the MENA region from CIMP5 scenario runs , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3140, https://doi.org/10.5194/egusphere-egu21-3140, 2021.

During the last decades, Europe has experienced intense dry and hot spells, which seriously impact socio-economic sectors and the ecosystem by shortages of water in the summer season. The occurrence of two exceptional consecutive dry summers 2018/2019 let a multi-year drought become a conceivable scenario. In order to implement adaptation strategies for such a natural hazard, stakeholders raise the questions, how dry and hot a worst-case drought scenario would turn out and how long it would take to fully recover from those climate anomalies?

We address these concerns through the generation of storylines, describing the driest plausible multi-year droughts over western Europe. By repeatedly resampling the occurrence of precipitation in the climate simulation, using 100-member ensembles, we inhibit rainfall and dehydrate the soils in western Europe. These storylines and a millennial climate control simulation are carried out with CESM1.2 under pre-industrial forcing.

In doing so, local precipitation is reduced by 80% and local soil moisture falls far below the 1^st percentile of the climatology. Even compared to the present and future climate scenarios, still, the number of dry days is very rare in our drought storyline, i.e. we describe a hazardous but unlikely scenario. Moreover, these storylines are associated with the hottest spring, summer and fall temperatures, but also the coldest winter temperatures. Starting large ensembles from each summer of the multi-year drought scenario, i.e. under exceptional dry initial soil conditions, we find that summertime hot and dry spells have a twenty-fold chance to occur plus their persistence extents by about 1.5 days. After strong precipitation deficits in the summer months, the precipitation increases again. Nevertheless, the local soil moisture does not fully recover within the next year so that the following spring and summer season may be affected by re-occurring droughts, aggravating the damage through water deficits for the vegetation growth and the economy.

How to cite: Gessner, C., Fischer, E., Beyerle, U., and Knutti, R.: A multi-year drought scenario for western Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2987, https://doi.org/10.5194/egusphere-egu21-2987, 2021.

Over the last few decades heat waves have intensified, become more common, pose severe health risks, especially in densely populated cities, and have led to excess mortality. While the probability of being adversely affected by heat stress has significantly increased over the last few decades, the risk of heat mortality is rarely quantified. This quantification of heat mortality risk is necessary for systematic adaptation measures. Furthermore, heat mortality records are sparse and short, which presents a challenge for assessing heat mortality risk for future climate projections. It is therefore crucial to derive indicators for a systematic heat mortality risk assessment. Here, risk indicators based on temperature and mortality data are developed and applied to major cities in Germany, France and Spain, using regional climate model simulations. These simulations have biases of up to 3°C with respect to observations and, thus, need to be bias-corrected. Bias-corrected daily maximum, minimum and wet-bulb temperatures show increasing trends in future climate projections for most considered cities. Additionally, we derive a relationship of daily maximum temperatures and mortality for producing future projections of heat mortality risk due to extreme temperatures based on low (Representative Concentration Pathway; RCP2.6) and high (RCP8.5) emission scenario future climate projections. Our results illustrate that heat mortality increases by about 0.9%/decade in Germany, 1.7%/decade in France and 7.9%/decade in Spain for RCP8.5 by 2050. The future climate projections also show that wet-bulb temperatures above 30°C will be reached regularly with maxima above 40°C likely by 2050. Our results suggest a significant increase of heat mortality in the future, especially in Spain. On average, our results indicate that the mortality risk trend is almost twice as high in all three countries for the RCP8.5 scenario compared to RCP2.6.

How to cite: Karwat, A. and Franzke, C. L. E.: Future Projections of Heat Mortality Risk for Major European Cities due to Heat Waves, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9181, https://doi.org/10.5194/egusphere-egu21-9181, 2021.

The Horizon 2020 RECONECT - Regenerating ECOsystems with Nature-Based Solutions for hydro-meteorological risk rEduCTion - Project aims to contribute to a European reference framework on NBS by demonstrating, upscaling and spreading large-scale NBSs in natural areas.

The Italian RECONECT demonstrator is set in the Portofino Park, which represents a unique natural and cultural landscape but is severely endangered by geo-hydrological hazards.

The most frequent processes are shallow landslides and flash floods, sea-storm surges, rockfalls and mud-debris flows. Often, several different processes can occur simultaneously during an intense meteorological event, causing a location specific multi-hazard effect.

This research introduces the NBSs interventions designed within the RECONECT Italian case study in two pilot catchments (San Fruttuoso and Paraggi basins), accessed by thousands of tourists throughout the year.

Amongst all possible interventions that can be implemented in the protected area, NBSs are considered to be most suitable due to their minimal impact and the possibilities for integration within the natural environment. The Portofino Park has already been promoting interventions aimed at reducing the impact of geo-hazards within the protected area in response to climate change. As part of the RECONECT project, and in order to achieve sound engineering and technological solutions which can also preserve unique landscapes of natural and cultural heritage, the Park authority is realizing a set of NBSs in San Fruttuoso and Paraggi catchments. The purpose of the design is to demonstrate how NBSs can be integrated into such areas and how to reduce geo-hydrological risk for given climate change scenarios within the framework of an ecosystem based holistic approach for risk reduction.

The main scope of NBSs in San Fruttuoso is to address following basic challenges: stabilizing of rock masses; reduction of geo-hydrologic risks in order to intercept and reduce suspended and solid transport along the streams as well as reducing erosion; forest management focused to improve biodiversity, to remove non-native species and dangerous old specimen (Pine trees), not suitable in a Mediterranean climate, in order to select the climax species (i.e. Quercus ilex); restoration of dry-stone walls with the aim to valorize the terraced landscape as well as stabilizing the slopes.

The reconstruction of terraces and the regeneration of natural and man-made ecosystems will also be implemented within the Paraggi basin. In addition, hydraulic-forestry arrangements on water courses will be undertaken to improve the outflow and decrease solid transport and floating debris. Furthermore, other measures such as riverbed and tributary implementations, maintenance along hiking paths, slope stabilization, and cleaning and removing dead vegetation and dirt will also be undertaken.

The project also includes hydro-meteorological monitoring activities in the selected basins and the periodic checking of NBSs performance indicators. Lastly, remote sensing surveys are used to quantitatively assess the ongoing gemorphogical processes.

In relation to future projections of natural and socio-economic impacts of climate change, NBS represent a relevant mitigation and adaptation strategy for the Portofino case study, which may be upscaled to national and international level.

How to cite: Faccini, F., Benedettini, A., Brodasca, V., Bruschini, U., Giammarini, R., Luino, F., Mortola, C., Neonato, F., Noce, P., Robbiano, A., Turconi, L., and Paliaga, G.: Nature-Based solutions for geo-hydrological risk reduction: the Portofino Park (Italy) experience in the H2020 RECONECT project, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1501, https://doi.org/10.5194/egusphere-egu21-1501, 2021.

Man-made terraces are widely diffused in hilly-mountainous areas, representing an ancient anthropogenic landscape modification for agricultural purposes. Then, terraces have been involved in several changes through times: socio-economic evolution caused a progressive general abandonment of terraced areas causing land use change and even their obliteration or collapse. In some cases, terraces deeply shaped the landscape and then their maintenance is considered crucial for cultural, aesthetic and even touristic value.

Terraces belong to the soil and water conservation measures as they allow to reduce erosion, improve slope stabilization and retain water runoff; as such they fit perfectly into the Natured-Base Solution definition. The artificial immobilization of debris and stone in terraces may turn in a possible source of geo-hydrological hazard in case of heavy rains, as happened in the Riviera Ligure in the last 20 years; a sequence of events was associated to landslides and flash flood, causing damages and casualties. Then, the proper terraces maintenance and monitoring is crucial for the maintenance of the geomorphological and geotechnical slope stability.

We focused on terraces identification and on the evaluation of debris/stones volume trapped after centuries of human activity in the pilot area of the Portofino Park, which represents a unique natural and cultural landscape that is severely endangered by geo-hydrological hazards. The further step has been the spatial relationships assessment with the exposed elements like buildings, infrastructures and culverted stream, that is the basis of risk assessment and land use planning activities.

The research has been carried out within the framework of the Horizon 2020 RECONECT - Regenerating ECOsystems with Nature-Based Solutions for hydro-meteorological risk rEduCTion; the Italian RECONECT demonstrator is set in the Portofino Park.

Using a detailed Lidar survey, the edges of dry-stone walls were firstly identified, allowing a detailed mapping. Focusing to terrace bases allowed to recognize a possible natural surface through their interpolation along the slope: the difference between the terraced slope profile and the interpolated one allowed a preliminary volume assessment.

Dry-stone wall basis has been detected applying a local upslope curvature routine that is the weighted mean of local curvatures of the directly neighboring upslope contributing cells, controlled with 5 cm orthophoto. In very steep areas terraces stored volume mediumly accounts about 0.35 m³/m², which agrees with the back analysis estimation of volumes collapsed after recent geo-hydrological events in the Ligurian Riviera.

Stored volume is an essential parameter for prioritizing terraces restoration interventions for risk reduction through NBS techniques. Finally, the survey and analysis outcome may be useful to investigate the recent numerous geo-hydrological events that have been triggered in terraced areas in large sectors of the Mediterranean.

How to cite: Paliaga, G., Faccini, F., Luino, F., Turconi, L., and Vojinovic, Z.: The role of man-made terraces as NBS measure for geo-hydrological risk reduction in the Portofino Park (Italy) - H2020 RECONECT project, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3977, https://doi.org/10.5194/egusphere-egu21-3977, 2021.

Heavy rainfall is one of the hydrogeological hazards increasingly connected with climatic changes. Natural Water Retention Measures (NWRMs) implementation represents a chance to build resilient communities and to reduce potential damage. This water management approach has several designs and can be adopted at different scales. However, NWRMs are not widespread, and in some cases they are even ignored by both citizens and public administrations. Understanding how people perceive NWRMs is the first step to promote the implementation of these structures. This study aims at exploring people’s knowledge of NWRMs and their attitudes towards them. We conducted a survey in the Veneto Region (Northeastern Italy) in 2020. Preliminary data exploration shows that the overall knowledge of NWRMs varies depending on the type of retention measure. Respondents’ attitudes towards NWRMs are positive in public areas (e.g. green spaces, parking lots), but are more heterogeneous when it comes to private properties (e.g. houses, private gardens). Further investigations are therefore needed concerning the last point. This study provides a deeper understanding of the dynamics behind water management systems’ implementation to reduce heavy rainfall and flood damage and can inform policymakers dealing with flood risk management.

How to cite: Bernello, G., Mondino, E., and Bortolini, L.: Exploring Perceptions of Natural Water Retention Measures and Their Implementation: A Case Study in Northeastern Italy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3249, https://doi.org/10.5194/egusphere-egu21-3249, 2021.

Live cribwalls are Nature-based solutions consisting of timber-based structures acting as retention walls at the toe of slopes and embankments subjected to instability and erosion events. The structure of live cribwalls resembles a multi-level crib made of timber logs from different plant species (e.g. pine, spruce, hazelnut, etc.). The crib structure is then backfilled with earth materials in which locally-available plant cuttings and/or saplings are inserted to establish a dense cover of native vegetation, providing added reinforcement and stability to the cribwall over time; particularly after the complete decay of the timber structure is reached. However, the effect of vegetation on the reinforcement of live cribwalls has not been examined systematically. Information on how vegetation can contribute to reinforce cribwalls hydrologically and mechanically is essential to evaluate the long-term performance of these Nature-based solutions against hydro-meteorological hazards. In this study, we propose a novel conceptual, numerical model based on empirical knowledge to evaluate the reinforcement effect of vegetation on live cribwalls over time. We also demonstrate how the proposed model can be applied to other Nature-based solutions concerned with slope protection and erosion control, such as live gratings or palisades.

How to cite: Gonzalez Ollauri, A., Mickovski, S., Emmanuel, R., and Sorolla Edo, A.: The reinforcement effect of vegetation on live cribwalls, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5858, https://doi.org/10.5194/egusphere-egu21-5858, 2021.

Increase in extreme rainfall and storm events due to climate change and decrease in water retention in soil due to urbanization has increased the risk of flooding in cities globally. Since majority of the cites are mostly developed, expanding the conventional urban drainage system to account for the excess runoff produced by the rainfall event has limited scope. The challenge is to develop sustainable urban drainage systems (SUDS) to reduce runoff and create a flood control system in major cities. One of the SUDS that are becoming popular is the use of nature-based solutions (NBSs). A set of conventional NBSs to mitigate flood risk include bioswales, bio-retention, tree pits, infiltration trenches. However, even though their performance in flood control is found to be effective, they require considerable land area for deployment, which might be difficult to obtain in cities. For this purpose, green roofs have becoming popular as an alternative NBS in flood control, as it does not require any additional land area for deployment. This study investigates the effectiveness of a green roof in reduction of runoff via real-world case study. A green roof deployed in the CHQ building located at the city centre in Dublin, Ireland has been considered for the study. The green roof has a total size of 70 sq. m. Performance of the green roof in runoff reduction was measured based on rainfall and water retention data collected at four modular units, each having 1 sq. meter area, located at the centre of the roof with an IoT weight scale. The data has been collected for 1 week at 3-minute interval, and the reduction in runoff with and without the presence of the green roof has been estimated. The performance of the green roofs in runoff reduction was found to vary between 20-40% depending on the intensity of storm events.

How to cite: Basu, B., Sarkar Basu, A., Sannigrahi, S., and Pilla, F.: Effectiveness of green roofs in reduction of rainfall-fed runoff: A case study in Dublin, Ireland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14461, https://doi.org/10.5194/egusphere-egu21-14461, 2021.

Natural Flood management (NFM) is a nature-based solution and catchment-based approach to flood mitigation.  Leaky barriers are a form of NFM and are popular amongst community groups working with natural processes as an affordable and sustainable action that they themselves can implement without investment in large infrastructure. At our research site, over 30 Leaky barriers have been implemented along a mile-long stretch of flashy river by a local community flood group and landowner in an attempt to decrease flood risk downstream in partnership with the Environment Agency. The effectiveness of these leaky barriers is being monitored in a number of ways, including: river flow, river level, geomorphic surveys and time-lapse footage. We describe the project dynamics and operational context that shaped the adopted control-intervention monitoring design. Based on previous studies, we hypothesize that leaky barriers will be most effective at mitigating smaller, rather than large flood events, such as in 2007. This is tested by examining the data collected over 2019-20, which includes storm Dennis (13th-19th February 2020) that caused widespread flooding across England and Wales. The results will contribute to a wider evidence base being collected by the Environment Agency, exploring the context in which community projects and monitoring take place against the changing expectations of funders and the evaluation of data produced.

How to cite: Powell, G., Clark, J., and Nisbet, T.: Monitoring Leaky Barriers for Natural Flood Management (NFM) within a community-led project, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7508, https://doi.org/10.5194/egusphere-egu21-7508, 2021.

Nature-based solutions are increasingly implemented to tackle disaster risk reduction and climate change adaptation. Their rising popularity over grey solutions is partially explained by their number of additional benefits (so called co-benefits) for the socio-ecological system (SES). Frameworks are available to monitor and assess co-benefits, however, these frameworks are lacking clear guidance and ex-ante quantification of co-benefits and potential disbenefits of NBS. Another limitation is the accessibility and quality (representativeness) of data for computing indicators, especially, going towards larger scales (regional, pan-European). To develop a comprehensive framework and method for assessing and estimating possible side effects in advance, this paper aligns to existing frameworks but goes beyond those by providing practical guidance on data sourcing (including possible proxy variables) and quantification of both co-benefits and disbenefits. The resulting framework will support decision-making on area specific suitability of NBS for disaster risk reduction. Furthermore, it will enhance the planners’ knowledge and understanding of linked processes which can lead to potential positive and negative side effects; thus, this guidance will build a base for selecting suitable locations and NBS interventions.

How to cite: Ommer, J., Bucchignani, E., Leo, L. S., Kalas, M., Vranić, S., Debele, S., Kumar, P., Cloke, H. L., and Di Sabatino, S.: Quantifying co-benefits and potential disbenefits of NBS for Disaster Risk Reduction: a practical framework for ex-ante assessment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7874, https://doi.org/10.5194/egusphere-egu21-7874, 2021.

The Open-Air Laboratory is a novel concept developed by the EU-funded Operandum project (OPEn-air laboRAtories for Nature baseD solutions to Manage Environmental risk) to co-design, implement and assess the effectiveness of Nature-Based Solutions (NBSs). 

In this work we present the Open-Air Laboratory Italy (OAL-Italy) and discuss the application of the OAL as a framework for the development of innovative NBSs to mitigate the impact of hydro-meteorological hazards in present and future climate.  By combining consolidated practices in an original multidisciplinary frame, the OAL-Italy deploys novel modelling strategies, laboratory measurements and targeted monitoring open-field campaigns. In three operational sites, the NBSs are implemented via a co-design, co-development  and co-deployment approach based on a thorough interaction with key stakeholders. By describing the structure and the approach of the OAL we illustrate salient features of the methodology developed in Operandum that are instrumental for the replicability and the upscaling of the NBSs. 

Presented results address the use of the NBSs to mitigate a range of hydrometeorological hazards such as coastal erosion, flooding, storm surge and salt wedge intrusion. Innovative NBSs tested and developed by the OAL include: deep-rooted plants installed on a river embankment to prevent levee failures, special plants that can live in high salt concentration and remove salt from the river mouth water, an artificial dune and marine seagrass to mitigate the impact of storm surges and coastal erosion. We argue that the OAL constitutes an unprecedented holistic effort towards sustainable land management, adaptation to climate change and the acceptance of Nature-Based Solutions. 

How to cite: Ruggieri, P. and the OAL-Italy: The Open-Air Laboratory Italy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9495, https://doi.org/10.5194/egusphere-egu21-9495, 2021.

The natural reserve in Sacca di Bellocchio, Lido di Spina (Italy) is affected by frequent marine floods and intense erosive phenomena which threaten the freshwater ecosystem and biodiversity at the site. Floods and erosion are linked to the reduction of river sediment transport and a progressive ground subsidence and sea level rise. The persistence of these conditions and the future rise in sea level can expose neighboring anthropized areas to coastal risk.

This work presents the project of a nature-based solution (NBS) as a possible defense and mitigation action against coastal erosion and marine flooding along the Bellocchio beach. The NBS has been newly designed   within the European project H2020 OPERANDUM (OPEn-air laboRAtories for Nature baseD solutions to Manage Environmental risk) and consists of an artificial sand dune made of natural materials, such as sand, wood, geotextiles and geomembranes through naturalistic engineering techniques. On the new dune will then be inserted native herbaceous and shrubby vegetation. The dune design was supported by an accurate hydro-morphodynamic modeling of the site combined with data concerning the morphological structure, the erosive dynamics and the local climate.

This study discusses in detail the modeling techniques and the monitoring system that guided the design of the dune and that constitute a basis for the assessment of performance and effectiveness of any future NBS intervention at the site. The monitoring campaign is still ongoing and allows the collection of critical and updated information on the impacts of coastal storms, storm surges and flood events in the area. The dataset clearly highlights that the site morphology is constantly changing due to a multitude of factors, such as seasonality, the increasing incidence and/or intensity of coastal storms, sea level rise, etc. These rapid, and sometimes drastic, morphological changes pose a substantial challenge to NBS's design and, most importantly, to its deployment planning and timing phase.

How to cite: Aguzzi, M., Bacci, M., De Nigris, N., Leo, L. S., Morelli, M., Pulvirenti, B., Robello, P., Ruggieri, P., Tavaroli, F., Unguendoli, S., Valentini, A., and Cacciamani, C.: Design and pre-assessment of NBS for coastal erosion and marine flooding: a case study., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10094, https://doi.org/10.5194/egusphere-egu21-10094, 2021.

Nature based solutions (NBSs) address key societal challenges through the protection, sustainable management and restoration of both natural and modified ecosystems. In this work we present a modeling application of this innovative approach, inspired by nature, with the goal of mitigating coastal erosion. Within the framework of the OPEn-air laboRAtories for Nature baseD solUtions to Manage environmental risks (OPERANDUM) project, the natural reserve of Bellocchio in Lido di Spina (Italy) faces frequent marine floods and intense erosive phenomena, hence being chosen as Open-Air Laboratory for the NBS implementation. The project aims to mitigate coastal erosion through the realization of an artificial sand dune made of natural materials, such as sand, wood, geotextiles and geomembranes and covered by native herbaceous and shrubby vegetation. We present the modeling activities carried out in the context of the project, aiming on the performance and efficiency evaluation  of the designed NBS, with a specific focus on the coastal morphological modelling. Thus, a numerical modeling chain has been set-up to simulate a long-term current scenario with and without the NBS. The chain is composed of the wave model WAVEWATCH III, the oceanographic model SHYFEM and the morphodynamic model XBeach for the coastal area.

XBeach was validated with available and specific (for the project) topo-bathymetric surveys of the area of interest as means to define the more accurate set-up of the model parameters. The 10 years period 2010-2019 was defined as the time range for modelling simulations. Sea level outputs from SHYFEM and wave outputs from WAVEWATCH III for the 10 years simulations are used to force the coastal model XBeach. Given the huge computational costs related to long-term simulations, an input-schematization was applied (so called “input reduction”). The approach followed for the long-term morphodynamic modelling of the NBS-XBeach setting will be shown. Moreover, the chosen coastal model domain, the model set-up and the input reduction applied will be presented.

How to cite: Unguendoli, S., Valentini, A., Germano Biolchi, L., Pranavam Ayyappan Pillai, U., Jacopo, A., and Nadia, P.: Modelling Nature-based Solutions: an application to mitigate coastal erosion, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11914, https://doi.org/10.5194/egusphere-egu21-11914, 2021.

A protected natural area in the Emilia Romagna region, Northern Italy is threatened by hydro-meteorological hazards, particularly sea storms. In the last 50 years the northern part of the Bellocchio Park (Sacca Bellocchio II Nature Reserve, Site code EUAPP0072 - Ferrara, Italy)  was interested by an intensive urbanization (Lido di Spina) with the realization of infrastructures, e.g. roads and residential settlements. This land use change led to the construction of embankments and to the conversion of wetlands. These modifications, in combination to even more frequent storm surge events increased coastal erosion. In addition, inland flooding caused by storm surges acts with the reduction of the lagoon and the increase of soil salinity. As an example, the last event occurred in December 2020  eroded a large portion of the Bellocchio beach.   

Co-design, co-development and deployment of NBS solutions to reduce storm surge risk in the Bellocchio Park is one of the objectives of the H2020 project OPEn-air laboRAtories for Nature baseD solUtions to Manage environmental risks (OPERANDUM). BellocchioBellochio park is in fact one of the 10 Open Air Laboratories (OAL) where the evidence of mitigation of hydro-meteorological risk by NBS will be demonstrated by the combination of different models, approaches and data.

During the co-design process in the Bellocchio park, potential deployment locations of sand dunes have been identified in collaboration with local authorities devoted to the management of the natural area and to the coast defense (CB and ARSTePC-RER) and an environmental engineering consultant assisting Arpae (IRIS sas). Field visits were devoted to the analysis of the environmental features, strengths and weaknesses of candidate sites.

This work aims to explore the usefulness of the combined use of multisource remote sensing and modeling in decision making during the co-design process of a NBS. The impacts of the most intense extreme storm surge events in the last 30 years have been documented by delineating flooded areas along the coast using Synthetic Aperture Radar and Multispectral image data. Coastal erosion has been also described by means of change detection analysis and very high resolution multispectral EO data. This screening has given a picture of areas at the risk, i.e. the area most likely to be affected by storm-surge events. Auxiliary data like Digital Terrain Models has been assimilated in a dedicated model to produce flood maps under different scenarios, i.e. different locations and size of NBS and different intensities of storm surge.  

The integrated analysis was helpful in defining the priority sites, among the ones defined by the stakeholders and engineers, in term of effectiveness for storm surge risk reduction.

How to cite: Alfieri, S. M., Foroughnia, F., Pulvirenti, B., Ruggieri, P., Aguzzi, M., Linderberg, R., De Nigris, N., Morelli, M., Tavaroli, F., Unguentoli, S., Valentini, A., Robello, P., Cacciamani, C., and Menenti, M.: Supporting co-development phase of Nature Based Solution by combined use of Earth Observation and modeling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14269, https://doi.org/10.5194/egusphere-egu21-14269, 2021.

Abstract

Under climate change scenarios, it is important to evaluate the changes in recent behavior of heavy precipitation events, the resulting flood risk, and the detrimental impacts of the peak flow of water on human well-being, properties, infrastructure, and the natural environment. Normally, flood risk is estimated using the stationary flood frequency analysis technique. However, a site’s hydroclimate can shift beyond the range of historical observations considering continuing global warming. Therefore, flood-like distributions capable of accounting for changes in the parameters over time should be considered. The main objective of this study is to apply non-stationary flood frequency models using the generalized extreme value (GEV) distribution to model the changes in flood risk under two scenarios: (1) without nature-based solutions (NBS) in place and; (2) with NBS i.e. wetlands, retention ponds and weir/low head dam implemented. In the GEV model, the first two moments i.e. location and scale parameters of the distribution were allowed to change as a function of time-variable covariates, estimated by maximum likelihood. The methodology is applied to OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks, which is in Europe. The time-dependent 100-year design quantiles were estimated for both the scenarios. We obtained daily precipitation data of climate models from the EURO-CORDEX project dataset for 1951–2020 and 2022–2100 representing historical and future simulations, respectively. The hydrologic model, HEC-HMS was used to simulate discharges/flood hydrograph without and with NBS in place for these two periods: historical (1951-2020) and future (2022-2100). The results showed that the corresponding time-dependent 100-year floods were remarkably high for the without NBS scenario in both the periods. Particularly, the high emission scenario (RCP 8.5) resulted in dramatically increased flood risks in the future. The simulation without NBS also showed that flooded area is projected to increase by 25% and 40% for inundation depth between 1.5 and 3.5 m under RCP 4.5 and RCP 8.5 scenarios, respectively. For inundation depth above 3.5 m, the flooded area is anticipated to rise by 30% and 55% in both periods respectively. With the implementation of NBS, the flood risk was projected to decrease by 20% (2022–2050) and 45% (2071–2100) with a significant decrease under RCP 4.5 and RCP 8.5 scenarios. This study can help improve existing methods to adapt to the uncertainties in a changing environment, which is critical to develop climate-proof NBS and improve NBS planning, implementation, and effectiveness assessment.

Keywords: Nature-based solutions; flood frequency analysis; climate change; wetlands; GEV model

Acknowledgments

This work has been carried out under the framework of OPERANDUM (OPEn-air laboRAtories for Nature baseD solUtions to Manage hydro-meteo risks) project, which is funded by the European Union's Horizon 2020 research and innovation programme under the Grant Agreement No: 776848.

How to cite: Debele, S., Sahani, J., Alfieri, S. M., Bowyer, P., Charizopoulos, N., Loupis, M., Menenti, M., Renaud, F., Shah, M. A. R., Spyrou, C., Zieher, T., Di Sabatino, S., and Kumar, P.: Evaluating nature-based solutions in a non-stationary climate with changing risk of flooding, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8012, https://doi.org/10.5194/egusphere-egu21-8012, 2021.

Stonewalls4life is an E.U. Life project started in the second half of 2019 involving many subjects, both public bodies and privates, in a multidisciplinary working group. The main objective of the project is to demonstrate how an ancient technology for land use, drystone walling, can be effectively considered to improve the resilience of the territory to climate change by adopting a socially and technically innovative approach.

The project actions are being performed at Manarola, within the Cinque Terre National Park (eastern Liguria, north-western Italy). The pilot site is a narrow strip of land close to the seaside and characterized by small valleys with steep terraced slopes. This anthropogenic landscape represents a high-value peculiarity attracting more than three million tourists every year.

Three replication sites were identified in order to demonstrate the transferability and replicability of the project actions: two are located within the Cinque Terre Natural Park territory and one is in the Can Grau area (Garraf Park, Catalunya, Spain).

The Spanish site is currently under evaluation. An extensive geological, geomorphological, and land-use-land-cover (LULC) analysis is now being carried out in the Can Grau area to define its environmental features, especially concerning geological aspects and land use, and focusing on terraced areas and their state of conservation. This study aims to identify a specific suitable site for the replication of the project actions that will be carried out in Manarola, namely for dry-stone walls recovery, and is based on a multitemporal analysis of aerial images performed in a GIS environment and a wide collection and review of bibliographic data.

This contribution illustrates the preliminary results of the Can Grau area analysis, focusing in particular on the distribution of terraced areas and the variation of LULC from the 1950s to the present day. From this study emerges a progressive abandonment of terraced areas used for cultivation, although, according to historical sources, this process mostly occurred after the phylloxera appeared in the late 19th century, seriously affecting the most important agricultural activity in the Garraf, namely the viticulture.

The outcomes from this study will be useful in terms of both Stonewalls4life project implementation and overall land management, particularly aiming to restore a man-made geomorphological heritage and mitigate geo-hydrological risk.

How to cite: Mandarino, A., Vigo, A., Cevasco, A., Varona Prellezo, P., Valbuena-Ureña, E., Guillén-Villar, A., Traver-Vives, M., Garcia-Martínez, D., and Firpo, M.: Geo-environmental analysis of terraced slopes and dry-stone walls in Can Grau area (Garraf Park, Catalunya, Spain): preliminary results from the Stonewalls4life project., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10696, https://doi.org/10.5194/egusphere-egu21-10696, 2021.

Global warming due to anthropogenic emission of green-house gases has induced climate change which is disturbing and will continue to impact the ecology and energy balance of our earth environment. The duration, frequency and intensity of extreme hot days in summers called heatwaves have increased with the beginning of the 21^st century worldwide and have been projected to increase. Associated human health loss or damage can be managed or mitigated by planning proper management strategies, such as nature-based green and/or blue solutions in advance, along with proper evaluation of the risk of heat. Since heat stress is more pronounced in urban and built areas, most studies for heatwave risk assessment have been limited to big cities. The risk variation in semi-urban, sub-urban and rural areas has not been much investigated. The heat risk develops with time because of changing climate and socio-demographics, and risk assessment is needed to be done utilising recent data on climate and population characteristics. In this study, the heatwave or extreme hot (99 percentile) temperature risk has been estimated by using statistical approach on summer daily temperature and mortality data from Aberdeenshire and South East (SE) England, UK for the duration 1981-2018. A distributed-lag nonlinear model from Poisson regression family was applied to model the relationship between daily temperature and mortality. We calculated relative risk (RR) and mortality attributable fraction (AF) due to high temperature by comparing the extreme heat with the minimum mortality temperature. AF was calculated by dividing the number of excess deaths due to heat from all the days of the time-series by the total number of deaths. The overall risk in SE England was noted 56 % higher (RR 1.067) than Aberdeenshire (RR 1.043), with 36% more excess death in SE England (AF 0.15% and 0.11% respectively) due to different levels of people’s adaptation and resilience to different climate conditions.  The outcome of this study can help in site focused mitigation strategies to certain areas at most risk and develop a scientific framework for early warning, planning and managing the health impacts of heatwave in more rustic regions.

Acknowledgements: This work is supported by the European Union's Horizon 2020 research and innovation programme; funded by and carried out within the framework of OPERANDUM project (Grant no. 776848).

How to cite: Sahani, J., Debele, S., and Kumar, P.: Heatwave risk for two regions of the UK: Aberdeenshire and South East England , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8018, https://doi.org/10.5194/egusphere-egu21-8018, 2021.

The OPERANDUM project is designed to address major hydro-meteorological risks through the deployment and assessment of Nature-Based Solution (NBS). The project pursues a co-creation approach and sets up 7 Open Air Laboratories (OAL) in which a user-centric method, characterized by the active participation of the stakeholders, is promoted. Stakeholder engagement in co-designing, co-developing, and co-deploying NBS is becoming a prominent practice in environmental projects and a crucial part of the process is monitoring and impact evaluation of the engagement strategy and actions. Monitoring aims at providing information about the stakeholder engagement processes throughout the project and should not be seen as a separate part of the stakeholder engagement processes or an aim in itself but as a continuous and integral element of the co-creation process. The poster shows the results of preliminary empirical research conducted among the OALs in order to propose some key indicators useful to evaluate the process and the impact generated by the OPERANDUM co-creative approach.  Starting from a theoretical framework, the research selected and discussed some crucial indicators in order to propose an action plan for the monitoring and impact evaluation of OPERANDUM strategy to involve and support the participation of stakeholders, with a specific focus on the tools used so far and those that are in the pilot phases (i.e Stakeholder Forum experimented in OAL Italy). Both qualitative and quantitative methods have been included in the evaluation for the engagement strategy outcome of the projects to be fully understood and, not secondarily, to identify a sustainability strategy beyond the conclusion of OPERANDUM to reinforce the social acceptance, the shared knowledge, and the upscaling of NBS at local, national and global level.

How to cite: Carlone, T., Mannocchi, M., Bucchignani, E., Ruggeri, P., Leo, L. S., Pulvirenti, B., Polderman, A., Panga, D., Soini, K., and Amirzada, Z.: “Stakeholder engagement strategy: monitoring and evaluate the impact in OPERANDUM project”, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13481, https://doi.org/10.5194/egusphere-egu21-13481, 2021.

Rainfall-induced floods and landslides have occurred and caused devastating impacts in recent years in Japan, and adaptation to natural disaster risks is a key to the sustainability of local communities. Traditional ecological knowledge in Japanese communities exists abundantly, such as those in disaster risk reduction and natural resource use, and it has been passed down from generation to generation. These traditional knowledge and skills have been used to benefit from nature’s gifts or ecosystem services as well as to avoid devastating impacts from natural disasters. Collaboration and cooperation by diverse stakeholders are crucial for recognizing and utilizing traditional ecological knowledge in actual solutions and actions. In this presentation, I introduce how traditional ecological knowledge has been used in disaster risk reduction in Mikatagoko Lakes area located in Fukui Prefecture, Japan. Rainfall-induced floods occur frequently in this area, but traditional land use helps to reduce inundation damage of houses and conserve biodiversity and ecosystem services including local food culture. Embankment built around the lakes has been renovated not only for flood risk reduction but also for biodiversity conservation, also supported by traditional ecological knowledge in this area. The Mikatagoko nature restoration committee, in which diverse local stakeholders participate and collaborate, has played a significant role in these actions and solutions. Our experiences suggest that transdisciplinary ecosystem-based approaches contribute to the sustainability of local communities and the collaborative platform among local stakeholders is important in taking advantage of traditional ecological knowledge in actual solutions and actions.

How to cite: Yoshida, T.: Transdisciplinary ecosystem-based approaches to flood risk reduction supported by traditional ecological knowledge in Mikatagoko Lakes, Japan, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5678, https://doi.org/10.5194/egusphere-egu21-5678, 2021.

Hydro-meteorological hazards such as floods have been a long-standing challenge for urban planners. A substantial increase in urbanization has undeniably pressurized the existing drainage network which has increased the flood proneness. The OPERANDUM project (H2020, grant agreement No 776848) has proposed a unique methodology for handling urban flooding by setting up open-air laboratories (OALs). As a pilot study of open-air laboratory Ireland (OAL-IE), an interdisciplinary methodology is adapted. Flood modeling techniques are identified for better flood risk assessment and flood management. Nature-based innovations are proposed to help identify and improve the existing urban drainage systems. The adaptability of nature-based systems and their efficacy as a supplemental tool to better flood management is a predominant and significant question. The awareness of citizens on their experience, challenges, and narratives are an equally reliable parameter to examine whether the spatio-temporal viability of new flood management techniques through nature-based innovations is a promising path for sustainable urban management. The intermittent relationship of flood hazard and the citizen access to infrastructure such as schools, childcare, old age homes, offices, transportation network holds a place of relevancy. The dynamics of “lived experiences” can help urban planners to pull out the traditional and formal strategies to be implemented for better liveability of citizens. Moreover, the willingness of citizens to maintain and share activities for co-deployment as a successful participatory process for innovative nature-based solutions support the social purpose of the OPERANDUM project. This research focuses on understanding the social background, cognitive thinking, and ideology that holds unique opportunities to OAL-IE for potential retrospective interpretation of nature-based innovations. A detailed survey with the stakeholders is aimed to understand their perspective on flooding, to identify how and where nature-based innovations can assist the city council to develop an efficient sustainable flood management system. This information on how citizens perceived and attributed the delivery of nature-based innovation can provide guidelines for developing better flood management and mitigation policies in Dublin.

How to cite: Sarkar Basu, A., Basu, B., Sannigrahi, S., and Pilla, F.: A citizen-oriented understanding of nature-based innovations: A case study in Dublin, Ireland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14404, https://doi.org/10.5194/egusphere-egu21-14404, 2021.

Nature-based solutions (NbS) are increasingly recognized as sustainable approaches to address socio-environmental challenges. Disaster risk reduction (DRR) has benefited by increasingly moving away from purely ‘grey’ infrastructure measures towards NbS, which can better provide cultural, aesthetic, and recreational co-benefits that are highly valued among European citizens. Public acceptance is of particular importance for NbS since they often rely on collaborative implementation, management, and monitoring, as well as protection against competing land uses. Although public engagement is a common goal of NbS projects and found in the IUCN’s core principles of NbS, outreach efforts are rarely based on a sufficient understanding of the (de)motivating factors tied to public perceptions. As a first step, we conducted a systematic literature review to examine how unique NbS characteristics relate to public acceptance through a comparison with grey measures. We identified influential acceptance factors related to individuals, society, and DRR measures. Based on the review, we introduce the PA-NbS framework as a starting point for the systematic consideration, design, and testing of strategies for increasing public acceptance. The PA-NbS highlights the roles of trust, competing interests, and effectiveness of NbS, as well as public perceptions of risk, nature and place.

A lack of consideration of these factors may lead to misaligned public expectations and failed participatory initiatives, while jeopardizing the success of NbS projects. Therefore, as a second step, we conducted citizen surveys within three NbS host communities. Distinct NbS being implemented within the OPERANDUM project aim to reduce risk from (socio-)natural hazards in Scotland (landslides and coastal erosion), Finland (eutrophication and algal blooms) and Greece (river flooding). Associations of factors related to risk, nature, and place perceptions with pro-NbS attitudes and behavior were tested to determine how these may be leveraged to increase acceptance. We find that trust is a consistent factor for defining attitudes towards the NbS across the sites. Attitudes are strongly associated with respondents’ commitment to nature and concern for risk, while some skepticism of NbS effectiveness leads to high public demand for relevant evidence. Risk perception and particularly the potential for future impacts are associated with behavioural acceptance (i.e. willingness to engage), along with responsibility for nature and connectedness to place.

Current data collection efforts to demonstrate NbS effectiveness for risk reduction are well-positioned to increase public acceptance in Europe. However, recognizing the differences among segments of the public within each site along with distinct hazard types, proposed NbS, and historical, social, and cultural characteristics across the sites is crucial for designing strategies that increase acceptance. An overview of these dynamics leads to evidence-based recommendations for the case-study sites and for successful NbS in Europe.

How to cite: Anderson, C. C., Renaud, F. G., Hanscomb, S., Loupis, M., Munro, K. E., Ollauri, A., Panga, D., Pouta, E., Soini, K., and Thomson, C. S.: Public acceptance of nature-based solutions (NbS): a framework for successful NbS and its application in three European case studies, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4579, https://doi.org/10.5194/egusphere-egu21-4579, 2021.

Po valley in the Emilia Romagna region, Northern Italy, is threatened by hydro-meteorological hazards, such as river flooding. In the last 50 years this area was interested by an intensive urbanization (with cities that span from the size of a village to metropolitan urban areas such as Bologna) with the realization of infrastructures, e.g. roads and residential settlements near rivers. In addition, the strengthening and expansion of the embankment system led to the development of the areas prone to floods located nearby the rivers. These modifications, in combination with the occurrence of high flood peaks recently experienced in this area have increased the impacts and thus, the attention, on riverine floods. The last event occurred in December 2020, where Panaro river, a tributary of the Po river, broke its banks near Modena causing large flooded area.

Co-design and co-deployment of nature based solutions (NBS) to reduce flooding risk in the Panaro river is one of the objective of the H2020 project OPEn-air laboRAtories for Nature baseD solUtions to Manage environmental risks (OPERANDUM). A portion of the Panaro river embankment is one of the Open Air Laboratories (OAL) where special deep rooted plants were implemented to evidence the mitigation of hydro-meteorological risks by NBS.

In this work, a combined approach between Earth Observation (EO) data and multi-scale modelling is shown, to support the co-design process of the NBS. Synthetic Aperture Radar (SAR) and optical EO data were used to identify areas at risk, i.e. the area most likely to be affected by severe flooding events.  A thresholding method was applied to the SAR and optical images available during past extreme events to identify size and location of the floods. The remote sensing analysis allowed the definition of specific portions of the Panaro river where NBS can be more effective for flood risk reduction. In a second step, a multi-scale modelling approach, based on the characterisation of deep-rooted plants by laboratory experiments and in-field measurements, is used to determine the response of the identified portions of Panaro river to flooding events and to evaluate the effectiveness of possible NBS.

Remote sensing analysis indicates that the area between Secchia and Panaro rivers, delimited to the north by the town of Bomporto and to the South by the town of Albareto has been most frequently inundated in the recent extreme events. The integrated analysis leads to the identification of potential sites, along the Panaro river, where NBS could be effective for river flooding risk reduction, contributing to the definition of the priority sites among the ones defined by the stakeholders and engineers.

How to cite: Pulvirenti, B., Ruggieri, P., Domeneghetti, A., Toth, E., Alfieri, S. M., Foroughnia, F., and Menenti, M.: Co-design and co-deployment of nature based solutions for river flooding mitigation in northern Italy river embankments, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15131, https://doi.org/10.5194/egusphere-egu21-15131, 2021.

The concept of Ecosystem-Based Management (EBM) as part of Nature-Based Solutions (NBS) have frequently been adopted in different strategic planning as a cross-sectoral mechanism to manage environmental problems. The EBM combines all relevant approaches, methods, tools, and software that collectively provide key scientific and socioeconomic evidence and eventually address environmental issues more sustainably. The specific application of EBM in different environmental problems, including flooding, have been proven effective in many cases. This ensures the superiority of EBM approaches for designing collaborative programs for solving environmental problems. The EBM offers a variety of sustainable interventions such as reducing impervious surface through porous paving, green parking lots, brownfield restoration, and deployment of green-roofs, which collectively attenuates water runoff and peak discharge, and offers protection against extreme precipitation events by enhancing water infiltration. In addition to the targeted benefits and cost-effectiveness of EBM, the supply of potential ecosystem service co-benefits that usually comes with EBM can contribute substantially to generating environmental benefits and adds community well-being. In order to analyse the superior effects of green-roof as a part of a smart-EBM framework, which has been deployed in CHQ building in Dublin, Ireland, a conceptual upscaling scenario framework has been formulated for measuring the city scale impact of green-roofs in providing multiple-valued ecosystem services. The biophysical and economic benefits of smart green-roof EBM will be estimated using varied ecosystem service modelling and standard cost-benefit analysis. The proposed smart green-roof framework is expected to have a more significant impact in minimising the flooding problems in Dublin city and expected to provide multiple regulating, supporting provisioning, and cultural benefits that can collectively surpass the deployment cost of green-roofs in the long run.

How to cite: Sannigrahi, S., Basu, B., Basu, A. S., and Pilla, F.: The ecosystem service benefits of green-roof as a part of smart ecosystem-based management: A case study in Dublin, Ireland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15504, https://doi.org/10.5194/egusphere-egu21-15504, 2021.

Floods in West Africa repeatedly cause devastating impacts on human life and livelihoods, infrastructure and the environment and they are expected to increase in frequency and severity under a changing climate. Ecosystem-based approaches can be a cost-effective, efficient way to reduce flood risk while at the same time providing co-benefits. However, qualitative and quantitative assessments of ecosystem-based approaches that are suitable for the climatic conditions and socio-ecological system of the region are scarse. This study therefore identifies and evaluates climate-sensitive ecosystem-based approaches for the transboundary Lower Mono River Basin in Benin and Togo. The identification of ecosystem-based approaches has been done based on a review of scientific literature and complemented by a participatory approach with experts from the catchment. During focus group discussions, national stakeholders and policy makers identified, prioritized and mapped existing measures and provided their perspectives on prospective measures to reduce flood risk in the transboundary catchment. They include measures to reduce flow velocity, increase soil infiltration and improve water management. In a next step, we used a multi-criteria analysis considering ecological, climatic and flood hazard data to create suitability maps for different clusters of identified ecosystem-based approaches. This study is part of the CLIMAFRI project, which aims at creating a river basin information system for the Lower Mono Basin as well as creating a flood risk management plan. Through the integration of the suitability maps into the flood risk assessment tool, which has been created in the scope of this project, the ecosystem-based approaches are evaluated quantitatively. In a second round of focus group discussions with representatives from the local communities, feasibility of selected ecosystem-based approaches, co-benefits and trade-offs of the measures are discussed. Through the combination of qualitative and quantitative data, a holistic evaluation of ecosystem-based approaches and their contribution to hazard mitigation, increase of coping capacity, ecosystem resilience and overall flood risk reduction can be achieved.

How to cite: Schudel, L., Walz, Y., and Akpamou, K. G.: Identification and Evaluation of Ecosystem-based Approaches for Flood Risk Reduction in the Transboundary Lower Mono River Catchment in Benin and Togo, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15937, https://doi.org/10.5194/egusphere-egu21-15937, 2021.

Due to the latitude of the Iberian Peninsula, it is repeatedly affected by significant drought episodes. This has been the case of the events observed in the years 1979-1983, 1992-1995, 2005, or 2016-2017. In the historical period, the occurrence of droughts in the Peninsula has been closely linked to the natural variability of the climate itself, which is modulated by multiple factors, such as the surface temperature of the oceans, the polar ice cover, the Oscillation of the North Atlantic or the stratospheric circulation itself (e.g. Lorenzo et al., 2011). Within the context of global warming, the projected increase in temperatures is expected to have a direct impact on the recurrence and severity of droughts on the Iberian Peninsula.

Therefore, the objective of this work is to study the relationships between climatic variables that indicate a high risk of yield loss of rainfed cereals affected by drought, and their projection in the immediate future. This work has been framed in the area of ​​Castilla y León in the North Plateau of Spain.

The selected methodology consisted of the design of agrometeorological indices that allowed capturing the behaviour of the most relevant variables related to the response of the cereals to drought in the study area. For this purpose, meteorological station observations, observations in grid, and simulations of present and future climate generated by regional climate simulation models (EUROCORDEX RCMs, van Meijgaard et al., 2014), which were used to compute the indices after a bias correction. Finally, results maps were obtained.

A total of nine temperature and/or precipitation indices were designed and calculated for periods physiologically meaningful for the crop, both under present and future climate. A discussion of the potential consequences of the indices changes on winter cereal yields in Castilla y León was addressed.

Acknowledgements

Authors are grateful to Agroseguro funding through the project “Drought events in winter cereals in Castilla-León: risk analysis, trends and climate change”.

References

Lorenzo, M.N., Taboada, J.J., Iglesias, I., Gómez-Gesteira, M., 2011. Predictability of the spring rainfall in Northwestern Iberian Peninsula from sea surfaces temperature of ENSO areas. Clim. Change 107 (3–4), 329–341.

van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.: EUROCORDEX: new high-resolution climate change projections for European impact research, Reg. Environ. Change, 14, 563–578, https://doi.org/10.1007/s10113-013-0499-2, 2014.

How to cite: Ruiz-Ramos, M., Rodríguez, A., Saa-Requejo, A., Valencia, J. L., Villeta, M., and Tarquis, A. M.: Risk of drought for winter cereals in Castilla y León (N Spain) under current and future climate, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8459, https://doi.org/10.5194/egusphere-egu21-8459, 2021.

The windbreak system is a major component of successful agricultural systems in arid deserts throughout the world. Ulan Buh Desert is one of the eight biggest deserts in China, and the oases there offer residence and cropland for over 90% of the local residents. However, due to climate change and human disturbances, the Ulan Buh Desert continues spreading to the south, bringing more pressure on the windbreak systems there. Meanwhile, the Chinese government put much effort into greening the desert, establishing artificial shrubs to prevent dune movement and soil loss. How microclimate in the cropland-windbreak-desert system responded to human activities and climate change has rarely been studied. In this study, we investigated the microclimate change dynamics across the cropland-windbreak-desert transition zone during the past 38 years. Two 50 m climatological towers, located in the same distance inner and outside a shelterbelt, have continuously monitored climatic factors, including air temperature, soil temperature, relative humidity, precipitation, evaporation, layered wind speeds, etc., and aeolian erosion related factors, such as layered dustfall. The long-time fluctuations of the inside and outside climatic factors have been analyzed, and the global climate change data, local land-use history, as well as the record of afforestation activities implemented by government and local people, were also collected. The results revealed that both the inside and outside windbreak air temperatures and soil temperatures increased during the past 38 years, which agrees with the global warming phenomenon. The inner windbreak air temperature is consistently lower than the outer windbreak areas, and the temperature difference is biggest in summer and smallest in winter. However, the soil temperature difference between the outside and inner windbreak is unstable. In 1995, 2002, and 2004, the dune areas even had lower soil temperature than the inner cropland. The precipitation is 0.5~100.7mm higher in cropland and the evaporation is lower in cropland when comparing to outside dune areas, but their annual variations changed greatly. The wind speed and erosion rate are significantly lower in cropland than desert dune areas, and the seasonal change exhibited a bimodal curve pattern. The results suggest that the cropland-windbreak-desert transition zone responded to global climate change simultaneously. Although the shelterbelt still creates a favorable regional climatic condition for the cropland, the differences between the inner and outer windbreak areas narrowed during the past 10 years. The aeolian erosion rate reduced significantly in outside windbreak dune areas, which may largely attribute to the artificial Haloxylon ammodendron communities planted at the southeastern margin of the desert.

How to cite: Wang, G., Luo, F., Xin, Z., Li, J., and Xiao, H.: The 38 years of the microclimate change dynamics across a cropland-windbreak-desert transition zone in the Ulan Buh Desert, northern China, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11421, https://doi.org/10.5194/egusphere-egu21-11421, 2021.

The chestnut trees are well adaptated to temperate and humid climates, with moderate annual thermal contrast and without long and severe summer droughts. Bioclimatic studies suggest that chestnut trees have special needs, including at least six months with average monthly air temperature above 10 ⁰C, total annual precipitation of 800 – 900 mm, and 25% of annual precipitation in summer. Weather is also determinant in the phenology of the species. For example, the suitable average air temperature range is: 13 – 15⁰C to initiate the phenological activity, 18 – 20⁰C for flowering, and 20 – 22⁰C for maturation. Therefore chestnut production is highly affected by adverse weather conditions and can be severely reduced by the occurrence of extreme weather/climate extremes: late frosts, heat waves, heavy rainfall, wind gusts, maximum air temperature lower than 25⁰C during flowering or above 32⁰C, which cause thermoinhibition of vegetative activity. Thus, it is important to characterize the chestnut producing regions in present and future climate and estimate how, when and where the weather conditions will be maintained or changed. For this study we used meteorological data from ERA5 for the 1981 – 2010 period and several GCM-RCM simulations from CORDEX Bias-adjusted RCM data for 2011 – 2100 period to assess the climate for current and two future scenarios (RCP 4.5 and RCP 8.5). The meteorological variables selected for this study have been identified in previous studies as having the greatest influence in the phenological activity of the chestnut tree and on the chestnut productivity. The results include the identification of the regions where: (i) the variables will have significantly different statistical distributions in the future; (ii) will be necessary to adopt hazard risk management and climate adaptation measures, including substitution by other varieties more adapted to future conditions or the development of genetic improvement programs; and, (iii) the identification of new production areas.

How to cite: Gonçalves, M., Amraoui, M., Laranjo, J., and Pereira, M.: Climate change in chestnut producing regions in Portugal, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16105, https://doi.org/10.5194/egusphere-egu21-16105, 2021.

In the last decades, we have witnessed increasing losses on crop yield due to an increase in magnitude and frequency of hydrological extremes such as droughts and floods. These hazards promote systematic and regressive impacts on the economy and human behavior. Risk transfer mechanisms are key to cope with the economic impacts of these events, therefore safeguarding income to farmers and building resilience to the overall sector. The index-based insurance establishes an index that can be monitored in real or near-real-time, which is associated with losses to a specific agent. While the manifestation of the causality hazard to exposure and exposure to damage and its mathematical representation in cash flow equations is a hard task, incorporating an objective and transparent index adds up a new challenge to this modeling framework. Moreover, past events that have been used as the main guide to evaluating expected losses given risk can no longer offer an accurate risk estimation due to environmental changes. This work aims to tackle the hydrologic extremes risk transfer modeling in irrigated agriculture to obtain optimized premium values and parameters of an insurance fund for irrigated agriculture in Southeastern Brazil. This study will be developed in the Piracicaba, Jundiaí, and Capivari river basin, also known as PCJ catchment in the states of São Paulo and Minas Gerais, Brazil. The region, with approximately 5 million inhabitants, is considered one of the most important in Brazil due to its economic development, which represents about 7% of the National Gross Domestic Product (GDP). The Hydrologic Risk Transfer Model of the Hydraulic and Sanitation department of the University of São Paulo (MTRH-SHS) will be used to obtain optimized premium values. The main index variable is streamflow fitted to extreme value theory distribution for low and high flows. To evaluate climate change and land-use change scenarios, Regional Climate Models (RCMs) and land use projections will be related to streamflow in a hierarchical Bayesian framework. Synthetic data will be then simulated according to scenarios previously defined in a Monte Carlo approach. The hazard-damage function will be obtained by total crop yield and revenue per municipality, then the relationship between the index and expected losses is determined in an empirical equation. Finally, a cash flow computation is run with synthetic data obtaining optimized premiums in a way to minimize fund storage values. We expect to provide further evidence of the feasibility of actuarially fair premium values for the agents in the sector considering global phenomena of climate change and land-use change. Results will support climate change adaptation plans and policy as well as contribute to methods for estimating risk in a changing environment.

How to cite: Benso, M. R., Gesualdo, G. C., Mendiondo, E. M., Ribbe, L., and Nauditt, A.: Developing resilience to hydrologic extremes in irrigated agriculture through risk transfer mechanisms in the context of southeastern Brazil, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6781, https://doi.org/10.5194/egusphere-egu21-6781, 2021.

Agricultural Insurance (AgI) sector is expanding on a global scale and is projected to grow by €50 B, by 2020. This rapid growth is driven by a set of fundamental structural changes directly affecting the agricultural sector like more frequent and severe extreme weather events, growing global population and intensification of production systems. Insurance solutions are set to grow in importance for agricultural management, given that agriculture will continue to be increasingly dependent on risk financing support. However, the development and provision of insurance services/products in the agricultural sector is generally low as compared to other sectors of the economy, and in their majority, suffer from low market penetration.

In that frame, the BEACON toolbox was born, that aims to provide insurance companies with a robust and cost-efficient set of services that will allow them i) to alleviate the effect of weather uncertainty when estimating risk of AgI products; ii) to reduce the number of on-site visits for claim verification; iii) to reduce operational and administrative costs for monitoring of insured indices and contract handling; and iv) to design more accurate and personalized contracts. Specifically, BEACON scales-up on EO data and Weather Intelligence components, couples them with blockchain, to deliver the required functions for Weather Prediction and Assessment and Smart Contracts and offer the required services:

• Crop Monitoring, which provides contract profiling and crop monitoring data together with yield estimations.
• Damage Assessment Calculator, which supports AgI companies in better assess and calculate damage to proceed with indemnity pay-outs of claims.
• Anti-fraud Inspector, which allows AgI to automatically check the legitimacy of a claim submitted.
• Weather Risk Probability, which provides probabilities maps of extreme weather events that may occur in the upcoming season.
• Damage Prevention/ Prognosis – Early Warning System, which provides extreme weather alerts to AgI providers and their customers.

This work focuses on the Damage Assessment Calculator component. It provides an approach using different types of EO data, implemented in the operational workflow of BEACON that can be used by AgI companies to improve the prediction and crop loss assessment due to drought and hailstorms.

Acknowledgements

This  project  has  received  funding  from  the  European  Union's Horizon 2020 Research and Innovation programme under grant agreement No 821964 (BEACON).

How to cite: Lekakis, E., Tarquis, A. M., Kotsopoulos, S., Mygdakos, G., Dimitrakos, A., Tsioutsia, I. M., Rivas-Tabares, D., and Simeonidou, P.: Evaluation of Earth Observation Products and Their Potential for Crop Damage and Crop Loss Assessment. The Case of Beacon Project., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10829, https://doi.org/10.5194/egusphere-egu21-10829, 2021.

Part of ESA’s Digital Twin Earth Precursor projects, our project focuses on supporting ESA in the definition of the concept of a Digital Twin Earth, and establishing a solid scientific and technical basis to realise this. The project, run by CGI and in close collaboration with Oxford University Innovation, Trillium & IIASA, has a focus on developing a Food Systems Digital Twin, taking on board interdisciplinary systems through the biosphere, atmosphere, and hydrosphere systems. These in turn would allow for new interdisciplinary insights for policies dealing with climate, food production and sustainability. The project is looking at a use case with the prominent use of AI processing, challenges of model integration, ingestion of socio-economic as well as physical measurements, end-to-end chain providing decision support outputs, all with innovation at each stage, and working closely with a series of stakeholders.

The purpose of our use case is to demonstrate the value of the Digital Twin Earth concept to the scientific community, by integrating the outputs of novel algorithms. We will be using selected machine learning extreme precipitation models feeding Global Gridded Crop Models, and after a regional downscaling exercise, the integration into cropland land use and pricing. By taking these steps, the benefits include improvement in routine monitoring with regular seasonal progress, short term policy development including responses to crop shortages due to extremes, and aiding in long term policy development to apply appropriate incentives. The purpose of the architecture and integration within the preparation of the demonstration is to support the use case and draw conclusions for the roadmap. These developments will be based on stakeholder consultations and the drawing together of differing model elements.

This Digital Twin Earth is an exciting project bringing together EO experts, Earth System Scientists, industry, AI experts, modellers, ICT experts and user community. It aims to establish the initial building blocks of an ambitious initiative, and, based on the prototyping activities, to develop a scientific and technology roadmap for the future, addressing current limitations. It ties in closely to both the European Space Agency’s and European Commission’s plan to create a series of interdisciplinary Digital Twin Earths with associated boundary conditions, in order to offer services to public sector users for developing, monitoring and assessing the impact of proposed policy and legislative measures concerning the environment and climate.

How to cite: Taposeea-Fisher, C., Whitelaw, A., Earl, J., Cullingworth, C., Jackman, S., Obersteiner, M., Watson-Parris, D., Gal, Y., Khabarov, N., Folberth, C., Orduña-Cabrera, F., Parr, J., and Silverberg, L.: ESA Digital Twin Earth Precursor: Food Systems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6182, https://doi.org/10.5194/egusphere-egu21-6182, 2021.

Globally, about a third of all losses related to natural hazards are due to flooding. Many studies focused their attention on the estimation of flood damages to buildings and infrastructures. However, floods cause significant losses to the agricultural sector too and negatively affect rural economies due to their impacts on agricultural productivity.

Several tools to quantify flooding economic impacts on the agricultural sector have been proposed, such as the AGRIDE-c conceptual model, and the Joint Research Centre (JRC) depth-damage functions. However, the tools have rarely been validated against data collected from surveys.

The aim of this study is the comparison between the flood economic impacts on agriculture computes using both AGRIDE-c and the JRC tool and the ones retrieved from surveys.

A questionnaire for estimating flood economic impacts on agriculture was prepared and submitted to farmers shortly after the flooding event. The selected case study area was the town of Nonantola (near the city of Modena, Northern Italy), where a flooding event occurred on 6^th December 2020. The flood was caused by the collapse of about 80m levee portion along the right bank of Panaro River resulting in an inundated area around 2000 hectares. The flood involved the Nonantola town where residential buildings and an active industrial area are located, although the dominant land use is agricultural land. The main local crops are represented by forage, wheat, vineyards, fruits (pears and plums) and sugar beet.

The questionnaire is divided into four main sections: The first section is related to the generic information on the farm, the second section to the data on the inundation and damage to crops, the third section to the information on past flood events and risk mitigation strategies eventually adopted during past and present events, the fourth section data to the insurance coverage.

Two existing crop damage models (AGRIDE-c and the JRC) were calibrated using three types of data: crop yields, crop selling prices and crop cost of production. Crop yields were obtained from the Italian National Statistical Institute (ISTAT), crop selling prices and costs of production were instead available from official sources such as ISMEA and Coldiretti (Italian association of farmers).

Finally, the proposed approach will allow the comparison between the damages experienced by farmers evaluated from questionnaires and the damages estimated by the two models in order to evaluate how the models simulate data directly collected from the field surveys.

How to cite: Giusti, R., Monteleone, B., Borzì, I., and Martina, M.: Flood impacts on Agriculture: The case study of Nonantola 2020 Flood event. , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10256, https://doi.org/10.5194/egusphere-egu21-10256, 2021.

Water availability and using the available water in a well-considered manner is becoming increasingly more important for farmers. An increase in dry summers (Gobin, 2018) confirms that in the future irrigation will have to take place in a smart manner, particularly in the water demanding horticultural sector. In times of water scarcity, governments may issue a ban on water extraction from natural water bodies. This on-going research investigates to what extent the supply of alternative water sources, such as treated waste water from domestic use or food processing , can be used for irrigation. In addition to the availability, the quality of irrigation water determines its suitability for crop utilisation. Treated domestic waste water may contain pathogens rendering the irrigated crop unfit for fresh consumption, whereas treated waste water from food companies may contain high salt concentrations affecting soil and crop health. The water demand was investigated on wastewater irrigated field trials and on irrigated farmers’ fields. Irrigation trials with various types of treated waste water elucidated the effects of these water sources on the crop yield, crop quality and the long-term impact on the soil quality. Soil moisture sensors were combined with a crop model, satellite images and meteorological information to monitor crop growth and performance of potato, spinach and cauliflower in on-farm conditions. The regional water demand for all irrigated crops was calculated with a water balance model based on actual evapotranspiration (Zamani et al., 2015) and linked to the supply of waste water sources in an online viewer, which makes it possible to promote water coalitions in regions where the water demand is high.

Acknowledgements

The research was funded by the Flemish Agency for Innovation and Entrepreneurship in Belgium under contract agreement HBC.2017.0817. 

References

Gobin, A., 2018. Weather related risks in Belgian arable agriculture. Agricultural Systems 159: 225-236. https://doi.org/10.1016/j.agsy.2017.06.009

Zamani, S., Gobin, A., Van de Vyver, H., Gerlo, J., 2015. Atmospheric drought in Belgium - Statistical analysis of precipitation deficit. International Journal of Climatology 36(8): 3056–3071. https://doi.org/10.1002/joc.4536

How to cite: Gobin, A., Boeckaert, C., Coudron, W., De Cuypere, T., De Swaef, T., Huits, D., Lootens, P., and Pollet, S.: Bridging the water demand gap with wastewater irrigation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13617, https://doi.org/10.5194/egusphere-egu21-13617, 2021.

The expansion of the agricultural frontier is a process that has been affecting natural ecosystems, driving landscape fragmentation, and promoting habitat loss from 1990 in the Ecuadorian Amazon. Characterizing spatial patterns of the expansion of agricultural frontier can provide valuable data to take forward trade-offs in areas with exacerbated expansion rates and habitat loss (Urgilez-Clavijo et al., 2020). The aim of this work is to identify and characterize the spatial patterns of the expansion of the agricultural frontier in Ecuador and provide an alternative to setting the priority areas.

With this purpose, an image analysis approach was applied to identify process patterns using classified images from 1990 to 2020. A statistical analysis of the agricultural expansion dynamics is performed in the Amazon region accumulating the land use information. Complementary to this, we used a soil map to detect a correlation of the process to soil types. Then the Intensity Analysis (IA) was implemented to characterize and visualize the spatio-temporal rates of the expansion process. This method allows identifying areas in which the process is faster and active.

The results show distinct patterns of agricultural expansion in the Amazon region, especially from Andean hill slopes to the primary forest. These processes are in part explained by soil type suitability, transportation network development, and urban expansion. The spatial priorities of the expansion of the agricultural frontier are identified from two sources, i) from intensity analysis graphs and ii) from regional maps. The spatial characteristics and identification of spatial priorities of the expansion of the agricultural frontier will bring valuable information to policymakers to achieve SDG 15th of the 2030 Agenda in Ecuador.

Keywords: expansion of agricultural frontier, Intensity Analysis, priority areas, image analysis, patterns

Reference

Urgilez-Clavijo, A., J. de la Riva, D. Rivas-Tabares and A.M. Tarquis. Linking deforestation patterns to soil types: A multifractal approach. European Journal of Soil Science, https://doi.org/10.1111/ejss.13032

Acknowledgements

The authors acknowledge support from Project No. PGC2018-093854-B-I00 of the Spanish Ministerio de Ciencia Innovación y Universidades of Spain and the funding from the Comunidad de Madrid (Spain), Structural Funds 2014-2020 512 (ERDF and ESF), through project AGRISOST-CM S2018/BAA-4330

How to cite: Urgilez-Clavijo, A. and Tarquis, A. M.: Agricultural spatial expansion in Ecuador through Intensity Analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13547, https://doi.org/10.5194/egusphere-egu21-13547, 2021.

Soil erosion is an important process of consideration in different erosion risk models and in planning soil conservation. Common erosion models, such as the USLE and its derivatives are widely used. In this context, the slope length is the variable with the most difficulties due to the different scales and procedures available that lead to very different results. Furthermore, many of the calculation procedures are based on a hydrological network definition that poses many problems in areas with a complex topography.

We propose an algorithm implemented in GIS, returning to the original field perspective form defined by the USLE and RUSLE, which is detached from the hydrological network definition. The calculation procedure is based on 5 m DEM and defines overland water flow at the field scale.

This method has been applied in three areas with different climate and geomorphology. The results are similar to those derived from aerial photograph observation.

References

Honghu Liu, Jens Kiesel, Georg Hörmann, Nicola Fohrer. (2011). Effects of DEM horizontal resolution and methods on calculating the slope length factor in gently rolling landscapes. Catena, 87, 368–375

Renard, K.G., Foster, G.R., Weesies, G.A., Mc. Cool, D.K y Yoder, D.C. (1997). Predicting Soil Erosion by Water: A Guide To Conservation Planning With The Revised Universal Soil Los Equation. Agricultural Handbook 703. USA: US Department of Agriculture.

Acknowledgements

Authors are grateful to Authors are grateful to Agroseguro funding this research.

How to cite: Saa-Requejo, A., Sevilla, P., Tarquis, A. M., and Gobin, A.: Computing slope length (USLE): return to original definitions., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13525, https://doi.org/10.5194/egusphere-egu21-13525, 2021.

This paper presents the concept of the project “Advanced monitoring of soil salinization risk in the Neretva Delta agroecosystem” (Delta Sal). Aim of the project is to develop and implement an advanced system for monitoring, forecasting and reporting the water and soil conditions in the Neretva Delta agroecosystem that is primarily used for agriculture. Selected pilot location is specific due to its biodiversity – water network within the delta consists of surface irrigation and drainage canal network, carst aquifer dominated by the tidal regime while also replenished by the freshwater from the upstream river flow, all of which are used for citrus fruits production while at the same time influencing the water regime of adjacent protected salt marshes ecosystem. Neretva Delta is dominated by the traditional farming methods practiced in the polder systems. Salt water intrusion is present in the entire delta, which is reflecting on the irrigation water quality and subsequently on the agricultural production of citruses that are salt-sensitive horticultural crops. Extensive spatial and temporal monitoring of water quality data through multisensory monitoring stations will be used for development of guidelines for salt stress alleviation in citrus fruits. This paper presents the outline of the project, methodology of analysis and selection of representative agricultural parcels for the research, rationale of farmer’s current decision-making that affects the agricultural landscape pattern and proposed monitoring network. Monitoring is focused on continuous real-time measurements of surface water levels and index water velocity using radars, shallow and deep piezometers for monitoring of ground water levels, rain gauges, multiparameter water quality measurements (dissolved oxygen, water depth, electrical conductivity, total dissolved solids, salinity, pH, oxidation reduction potential, temperature, nitrate and chloride). Data is transmitted in real-time to the cloud-based interface for remote access. Integrated data management will be used in the upcoming project stages for analysis of salt water intrusion on Neretva Delta agricultural production. Final outcome of the project are guidelines for Neretva Delta management with the future outlook in the climate change context, compliant with UNFCCC convention under which this area falls into one of the most vulnerable areas in Croatia.

Acknowledgment:

„This work has been supported in part by the European Regional Development Fund under the project Advanced monitoring of soil salinization risk in the Neretva Delta agroecosystem (KK.05.1.1.02.0011)“

How to cite: Gilja, G., Kuspilić, N., Romić, D., Zovko, M., and Harasti, A.: Advanced monitoring of soil salinization risk in the Neretva Delta agroecosystem, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-203, https://doi.org/10.5194/egusphere-egu21-203, 2021.

Rangeland and agricultural landscapes are complex and multifractal based on the interaction of biotic and abiotic factors such as soil, meteorology, and vegetation. The effects of land-uses on these areas modify their characteristics and dynamics.  The use of Normalized Difference Vegetation Index (NDVI) and NDVI anomalies (NDVIa) from satellite time series can effectively aid on understanding the differences among rangeland uses and types.

Multifractal detrended fluctuation analysis (MDFA) focuses on measuring variations of the moments of the absolute difference of their values at different scales. This allows us to use different multifractal exponent such as generalized Hurst exponent (H(q)), and the scaling exponent (ζ(q)) to characterize each area.

We collected the time series using satellite data of MODIS (MOD09Q1.006) from 2002 to 2019. One area from southeastern Spain (Murcia province) of 6.25 Km² were selected. This area comprises 132 pixels with a spatial resolution of 250 x 250 m² and a temporal resolution of 8 days. This area represents a mix of tree crops rainfed and irrigated, rainfed herbaceous crops, and grazelands with shrubs and/or tree coverage.

MDFA was used on every pixel of the study area and H(q) was plotted and compared. Our results report different exponent behaviours for diverse rangeland type or use. Within the same vegetation type, MDFA can allow us to distinguish among pixels, such as the top central part of our area, where different persistence levels are found for the same land use. Comparing the Hurst exponent (H(2)) of NDVI and NDVIa also suggest a difference of influence on the multifractal character of long-range correlations.

We conclude that MDFA is a good tool to characterize arid rangelands spatial heterogeneity, particularly for rangeland with different vegetation types. It can be used to monitor and manage arid rangeland. It can be useful for policy-makers for short- and long-term solutions.

Acknowledgements: The authors acknowledge the support of Project No. PGC2018-093854-B-I00 of the Ministerio de Ciencia Innovación y Universidades of Spain, “Garantía Juvenil” scholarship from Comunidad de Madrid, and the financial support from Boosting Agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020EU, DT-SPACE-01-EO-2018-2020.

How to cite: Sanz Sancho, E., Saa-Requejo, A., Diaz-Ambrona, C. G., Ruiz-Ramos, M., and Tarquis, A. M.: Multifractal analysis of spatial heterogeneity in Spanish arid rangelands, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2698, https://doi.org/10.5194/egusphere-egu21-2698, 2021.

Rainfed crops as cereals in the semiarid are common and extensive land cover in which climate, soils and atmosphere interact trough nonlinear relationships. Earth Observations coupled to ground monitoring network allow to improve the understanding of these relationships during each cropping season. However, novel analysis is required to understand these relationships in larger periods to improve sustainability and suitability of the productive areas in the semiarid.

The aim of this work is to use a joint multifractal approach using vegetation indices, precipitation, and temperatures to analyze atmosphere-plant nonlinear relationships. For this, time series of 20 cropping seasons were used to characterize these relationships in central Spain. The Generalized Structure Function and the derived Generalized Hurst Exponent analysis were implemented to investigate precipitation, vegetation indices and temperature time series. For this, an exhaustive selection based on land use and a land cover change analysis was performed to detect plots in which cereal crop sequences are dedicated to barley and wheat over the period 2000 to 2020.

As a result, two agro zones were characterized by different multifractal properties. Precipitation series show antipersistent characteristics and fractal properties between zones while original vegetation indices show trending behavior but shifted between analyzed zones. Nonetheless, soils and rainfall events can vary interannual conditions in which the crop is developing. For vegetation indices long-term series the trend is persistent. Even so, the dynamics of vegetation indices also provide more information when annual patterns are extracted from the series, exhibiting fractal properties mainly from rainfall pattern of each zone. Finally, in this case, the joint multifractal analysis served to characterize agro zones using earth observation and climate data for extensive cereals in Central Spain.

Reference

Rivas-Tabares D., Tarquis A.M. (2021) Towards Understanding Complex Interactions of Normalized Difference Vegetation Index Measurements Network and Precipitation Gauges of Cereal Growth System. In: Benito R.M., Cherifi C., Cherifi H., Moro E., Rocha L.M., Sales-Pardo M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 943. Springer, Cham. https://doi.org/10.1007/978-3-030-65347-7_51

Acknowledgements

The authors acknowledge support from Project No. PGC2018-093854-B-I00 of the Spanish Ministerio de Ciencia Innovación y Universidades of Spain and the funding from the Comunidad de Madrid (Spain), Structural Funds 2014-2020 512 (ERDF and ESF), through project AGRISOST-CM S2018/BAA-4330 and the financial support from Boosting Agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020_EU, DT-SPACE-01-EO-2018-2020.

How to cite: Rivas-Tabares, D. and Tarquis Alfonso, A. M.: Joint multifractal approach to characterize nonlinear relationships of climate and cereal growth in semiarid, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13498, https://doi.org/10.5194/egusphere-egu21-13498, 2021.

Grasslands are one of the world's major ecosystems groups many of them are now being acknowledged as having a multifunctional role in producing food and rehabilitating croplands, in environmental management and cultural heritage. Multiple studies showed pasture grasslands as a complex agroecological system, depending on multiple variables with a nonlinear dynamic greatly affected by climate fluctuations over time. Remote sensing methods proved to be one of the most effective techniques for monitoring variations over wide areas. In this line, vegetation indices (VIs) demonstrated to be an appropriate indicator of vegetation cover condition. This study aims to perform a method to visualize and quantify the complexity between semiarid grasslands and climate. With this goal, VIs and climate time series are analysed simultaneously with non-linear techniques to reveal the dynamic behaviour of both series over time and their interaction.

A semi-arid grassland area characterized by a Mediterranean climate with a continental character and low precipitation throughout the year were chosen. VIs time series were constructed from MODIS TERRA (MOD09Q1.006) product. Multispectral images composed by 8-days were acquired from 2002 till 2018 and four pixels with a spatial resolution of 250 x 250 m² were chosen in the selected area. Normalized Difference Vegetation Index (NDVI) and Modified Soil-Adjusted Vegetation Index (MSAVI) were calculated based on these images. Temperature and precipitation series were acquired from a near meteorological station and adapted to 8-day time step.

Cross-Recurrence plots (CRP) and recurrence quantification analysis (RQA) were performed to analyse the climate and vegetation dynamics simultaneously. To achieve this goal, several measures of complexity were computed, such as Determinism (DET), average diagonal length (LT) and entropy (ENT).

Our results showed different CRPs depending on the climate variable and the utilized VIs. Temperature and VIs CRPs showed a periodical pattern, implying the temperature seasonality over time. In contrast, precipitation and VIs CRPs showed more chaotical behaviour, due to the occurrence of extreme events and seasonal shifts. These results are quantified by the DET and ENTR values.

Our results indicate that temperature and precipitation present a dynamical complexity that is revealed in VIs response. Both indices showed different results of complexity measures, implying that MSAVI has a higher complexity than NDVI. This fact is probably due to the addition of a variable soil adjustment factor. Consequently, MSAVI should be considered as a potential alternative to NDVI in semiarid areas.

Reference

Almeida-Ñauñay, A. F., Benito, R. M., Quemada, M., Losada, J. C., & Tarquis, A. M. Complexity of the Vegetation-Climate System Through Data Analysis. In International Conference on Complex Networks and Their Applications. Springer, Cham., 609-619, 2020

Acknowledgements

The authors acknowledge support from Project No. PGC2018-093854-B-I00 of the Spanish Ministerio de Ciencia Innovación y Universidades of Spain and the funding from the Comunidad de Madrid (Spain), Structural Funds 2014-2020 512 (ERDF and ESF), through project AGRISOST-CM S2018/BAA-4330 and the financial support from Boosting Agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020_EU, DT-SPACE-01-EO-2018-2020.

How to cite: Almeida Ñauñay, A. F., Benito Zafrilla, R. M., Quemada Sáenz-Badillos, M., Losada, J. C., and Tarquis Alfonso, A. M.: Revealing climate and vegetation indices interactions through Cross Recurrence Techniques, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12723, https://doi.org/10.5194/egusphere-egu21-12723, 2021.

Agroindustry in South and Central America is positioned as a traditional production sector, where exists a need for integration of processes for the implementation of contingency measures in a timely manner against events that create a risk for crops. Diseases affecting agricultural sectors are often closely related to weather conditions and crop management. In particular, for the coffee production, the Coffee Leaf Rust (CLR) is a disease that affects quality and production costs for farmers greatly. 

Detecting the patterns that affect the disease can lead to early actions that lessen its impact. In this sense, some researchers in the sector have focused their efforts on determining over time the relationships between weather conditions and agronomic properties of crops with episodes of epidemics of diseases as coffee rust. 

Different natural processes, such as the climate, can have different and recurrent behaviors in time. Despite its periodicity, climate change has impacted on recurring events, both in their temporality and intensity. Thus, climate variables have properties of dynamic deterministic or nonlinear systems. The recurrence analysis of states in these systems is one of the solutions to carry out a study of their behavior in the time-domain.  Eckmann et al. proposed the Recurrence Plots (RP) for the visualization of state recurrence, allowing to see the space phase trajectories in a bidimensional representation. This analysis, initially applied to a single time series and its recurrence with itself, can also be extended to compare two time series by Cross Recurrence Plots (CRP) and find the recurrence between them. Moreover, the elements of PR and CRP can be quantified, obtaining direct elements of comparison between series or pairs of time series.

The aim of this analysis was to find the times and conditions in which the time series of the climatic variables present events related to anomalies or extreme values in the CLRI time series. In addition, the recurrence analysis allows to know the time delay for which each climatic variable affects the disease.

References

 J. Avelino et al., «The coffee rust crises in Colombia and Central America (2008–2013): impacts, plausible causes and proposed solutions», Food Secur.,  7(2), 303-321, 2015.

 J. M. Waller, M. Bigger, y R. J. Hillocks, Coffee pests, diseases and their management. CABI, 2007.

 A. C. Kushalappa y A. B. Eskes, «Advances in coffee rust research», Annu. Rev. Phytopathol., 27(1), 503–531, 1989.

 E. Lasso, D. C. Corrales, J. Avelino, E. de Melo Virginio Filho, y J. C. Corrales, «Discovering weather periods and crop properties favorable for coffee rust incidence from feature selection approaches», Comput. Electron. Agric., 176, 105640, 2020.

 J. P. Eckmann, S. O. Kamphorst, y D. Ruelle, «Recurrence plots of dynamical systems», World Sci. Ser. Nonlinear Sci. Ser. A, 16, 441–446, 1995.

Acknowledgements

Technical support of Telematics Engineering Group (GIT) of the University of Cauca, the Tropical Agricultural Research and Higher Education Center (CATIE) and the InnovAccion Cauca project of the Colombian Science, Technology, and Innovation Fund (SGR- CTI) for PhD scholarship granted to MSc. Lasso is acknowledge. Financial support by Fundación Premio Arce (ETSIAAB, UPM) financial support under contract FPA18PPMAT08 is greatly appreciated.

How to cite: Tarquis, A. M., Lasso, E., Corrales, J. C., and de Melo, E.: Analysis of time series recurrence and cross recurrence in the relationship of climate with Coffee Leaf Rust, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16527, https://doi.org/10.5194/egusphere-egu21-16527, 2021.

The atmospheric electric potential gradient (PG, the reverse of the atmospheric vertical electric field) is commonly measured near the ground. The PG plays a pivotal role in studying the global electric circuit (GEC) which comprises all large scale quasi-static electrical processes occurring in between the Earth's surface and the lower ionosphere [1]. Therefore, long-term, coherent PG measurements are of high importance in atmospheric electricity research. Nevertheless, it is a challenging task to use PG as a reliable diagnostic tool for investigating global changes in Earth’s electromagnetic environment because of its high variability.

There are few PG datasets around the globe which are long enough and have been recorded continuously for decades. One of the datasets that fulfil these requirements has been recorded in the Széchenyi István Geophysical Observatory, Nagycenk, Hungary, Central Europe (NCK, 47°38’ N, 16°43’ E). A necessary correction of the recorded PG time series due to the time-dependent shielding effect of nearby trees at NCK was introduced earlier [2,3]. In this study, the corrected long-term (1962-2009) variation of PG at NCK is exhibited and discussed.

In the present study, the behaviour of annual minima, maxima, means, and summer and winter means of the PG at NCK are investigated. As these PG time-series exhibited quite different characteristics, the joint analysis of these data is required. The long-term variation of these PG time series can be divided into three periods: the first period (1962-1985) is characterized by a rather steep increase and is mostly driven by the wintertime data. The increase continues with a moderate magnitude and less significantly in the second period (1986-1997) where summertime data dominate the change, whereas there is a pronounced reduction of the PG in the third period (1997-2009) with almost equal magnitude in both the winter- and summertime records. These observed trends are confirmed by independent PG observations made at other measuring sites (e.g., the Swider Observatory, Poland).

The PG at NCK is generally greater in winter than in summer, which is a well-known phenomenon at northern hemisphere continental stations [4]. The annual minima, however, do not comply with this trend in every year. The month with the lowest average PG is in late spring (May) in most years of the examined epoch at NCK but minimum values occur in autumn and winter months as well.

References:

[1] Rycroft, M. J., Israelsson, S., and Price, C.: The global atmospheric electric circuit, solar activity and climate change, J. Atmos. Sol-Terr. Phy., 62, 1563–1576, 2000.

[2] Buzás, A., Barta, V., Steinbach, P., and Bór, J.: Impact of local environmental conditions on atmospheric electrical potential gradient measurements, Geophysical Research Abstracts, 19, EGU2017-1193-1, 2017.

[3] Buzás, A., Horváth, T., Barta, V., and Bór, J.: Revisiting the decreasing trend of atmospheric electrical potential gradient measured in Central Europe at Nagycenk, Hungary, Geophysical Research Abstracts, 20, EGU2018-6723, 2018.

[4] Chalmers, J. A.: Atmospheric Electricity, second edition, Pergamon Press, London, pp. 168-169 1967.

How to cite: Buzas, A., Barta, V., Bór, J., and Horváth, T.: Investigating the long-term variation of atmospheric electric potential gradient at Nagycenk, Hungary, Central Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5761, https://doi.org/10.5194/egusphere-egu21-5761, 2021.

The response of tall structures such as towers to the electrical atmosphere is well known, but much has to be learned about how the rotation of wind turbine blades affects the electrical response of wind turbines. To better understand current induction and the appearance of point/corona discharge from wind turbine blades, a series of experiments lifting vertical wires with drones under fair weather conditions have been conducted. During the experiments, the length of the wire (vertical) and its vertical velocity were recorded using the drone’s telemetry. Additionally, the wire was grounded through a pico-ammeter to measure current induction and a corona discharge detector, based on a wideband current measurement coil, was placed close to the tip of the lifting wire to detect possible point/corona discharge appearance at the wire tip.

Preliminary tests included testing the sensor in the laboratory by measuring artificially generated corona pulses, to verify that pulses from this sensor registered on the field could be attributed to point/corona discharge phenomena. Measured amplitude for this induced current was on the order of hundreds of nano-amps.

For these experiments, an insulated copper wire with  0.14Ω/m resistance and with the top tip exposed to the environment was deployed using two different tips, a rounded tip of 1mm radius and a sharp needle tip of 0.1mm radius. The electric field at the ground level was measured using an electric field mill. All flights were performed during the morning and the ground electric field amplitude ranged from 50V/m to 200V/m.

When using rounded tips, corona discharge was not detected by the coil, but an induced current proportional to the vertical speed of the wire was measured. This component of the current is interpreted as a change of potential in time, and the amplitude of these induced currents is on the order of tens of nano-amps.

Results when using the sharp tip showed two clear sources of induced currents on the wire, vertical speed (as in the rounded case) and corona discharge. When using the sharp tip, corona discharge was detected when the wire reached around 50 m and induced current amplitude increased with altitude. A pulsating current was measured by the coil sensor indicating the existence of corona discharge on the wire.

The rate of decrease of the measured currents after reaching steady positions of the wires might be attributed to the screening effect of the released charge.

These experiments proved that key factors for the current induction on wind turbine blades include the change in height at a certain speed, along with the occurrence of point/corona discharges with the radius of curvature of the blade tips. Under the effects of electrified thunderclouds, the magnitudes of the currents could reach several orders of magnitude.

How to cite: Fontanes Molina, P., Arcanjo, M., Montanyà Puig, J., and Guerra-Garcia, C.: Deploying vertical wires with drones to study wind turbine electrification under fair weather, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4556, https://doi.org/10.5194/egusphere-egu21-4556, 2021.

We present here the results of a study on the changes of PM 2.5 and atmospheric electric field (Potential Gradient, PG) during COVID-19 measures implemented at Xanthi in comparison with the 2019 measurements according to 10 classes of circulation weather types (CWT). There are two study periods. The first period was from February to May of both 2019 (no lockdown measures were implemented) and 2020 (under lockdown), and the second period was from September to December of both 2019 (no lockdown) and 2020 (lockdown). For both study periods of 2020, Xanthi was subjected to additional measures, such as curfew. Specifically, from 01/04/2020 to 27/04/2020 from 20:00 to 08:00 and from 13/11/2020 to 31/12/2020 from 21:00 to 05:00. These periods were selected according the two lockdown periods of 2020 at Xanthi and the same periods were selected for the previous year. PM 2.5 was measured in two different locations, one in the city center of Xanthi and the other is located at a semirural location approximately 2 kilometers from the city center, where also PG was measured. We present results in comparison with mean PM 2.5 and mean PG per circulation weather type on no lockdown and lockdown periods of 2019 and 2020 respectively, at Xanthi. There were changes on mean PM 2.5 and mean PG per circulation weather type between the two years. A moderate decrease of PM 2.5 per CWT between the two periods of lockdown on 2020 due to COVID-19 measures and the same periods for 2019 is observed when there was neither lockdown nor curfew. Fluctuations and a variability on mean PG per CWT are also observed between the two years. We acknowledge support of this work by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).

How to cite: Karagioras, A., Nita, A., and Stavroulas, I.: Changes on atmospheric electric field and PM 2.5 during the COVID-19 measures at Xanthi on 2020 compared to the 2019 measurements and depending on the circulation weather types, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8930, https://doi.org/10.5194/egusphere-egu21-8930, 2021.

Results of the study of the impact of sporadic sources of disturbances on the state of the atmospheric electric field at the high-mountain Tien Shan station (3340 m above sea level, 20 km from Almaty) are presented. The absence of unitary variation (Carnegie curve) is the characteristic feature of diurnal changes in the atmospheric electric field under good weather conditions.

The most geoeffective sporadic sources of disturbances in the near-Earth space and the Earth's atmosphere are giant coronal mass ejections (CME), accompanied by Forbush effects in the intensity of galactic cosmic rays and by geomagnetic storms. Our studies were carried out taking into account the peculiarities of CME manifestations in the atmosphere and magnetosphere of the Earth. It was found that large magnetic storms affect the average level of the atmospheric electric field (increasing or decreasing it due to a change in the rigidity of the geomagnetic cutoff Rc), and also cause its fluctuations in the minute range (10^-3 ÷ 10^-2) Hz. A significant decrease in the atmospheric electric field after CME is due to large Forbush effects during weak geomagnetic disturbances.

Anomalous changes in the atmospheric electric field on the eve and during earthquakes were recorded, which are unambiguously associated with the activation of seismic processes. Since the city of Almaty is surrounded by a number of potential sources of strong earthquakes, the problem of their prediction is actual for the city and its environs.

How to cite: Antonova, V., Kryukov, S., Lutsenko, V., and Malimbayev, A.: Impact sporadic sources of disturbances on the atmospheric electric field оn Tien- Shan, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7250, https://doi.org/10.5194/egusphere-egu21-7250, 2021.

High energy cosmic rays of galactic and solar origin, natural radioactivity, lighting in thunderstorms and electrified shower clouds, produce ion clusters and charge the whole atmosphere causing a ubiquitous potential difference between the ionosphere and the surface. This Global Electric Circuit (GEC) allows the flow of charges to the surface in the fair-weather regions of the globe. Here, we simulate the effect of highly energetic particle radiation, in particular the 774 AD solar proton event, on the GEC with the aid of the global circulation model EMAC/MESSy. The simulations assume pre-industrial atmospheric conditions and the coupling of aerosol and atmospheric electricity schemes allows for ion-ion and ion-aerosol capture reactions. We discuss effects in fair weather current and atmospheric conductivity at different latitudinal bands.

How to cite: Misios, S., F. Knudsen, M., and Karoff, C.: Simulating effects of the 774 AD solar proton event on atmospheric electricity, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13496, https://doi.org/10.5194/egusphere-egu21-13496, 2021.

During the formation of thunderclouds, simultaneous macrophysical and microphysical processes cause the separation of charges inside the cloud, forming the electrical structure of storm clouds. As a result of that, the electric field at the ground level can change significantly. Irregularities on the surfaces of grounded structures can provide conditions for corona discharges that generate ions and form a space charge layer at ground level.

In this work, we investigate the features of corona point discharges from grounded conductive rods installed in three different sites. In all of them, we measured current along the grounded rod under high background electric field conditions or during its fast changes caused by lightning strikes. The current signals reveal pulses with a fast rise time (tens of nanoseconds) and slow decay (hundreds of nanoseconds), with polarity compatible with the background electric field. Comparing laboratory experiments with the results in the field, we observed that positive discharges required a lower electric field threshold than negative discharges. Their pulse frequency is also equivalent to one-tenth of the pulse frequency of negative discharges, for a similar electric field level.

In one of the sites, one current sensor coupled to a grounded rod, 1.5 m above a roof, was installed in a site located at an altitude of 2525 m, near a ski-station. We observed a large number of events, and we were able to correlate the frequency of the pulses with the electric field, as well as evaluate the effect of the wind on the discharges. In the other two sites, the rods were placed near the ground and on the roof of a conventional building. Pulses were registered on some occasions when there was lightning activity nearby, either before or after lightning events. Previous works on this topic correlate the electric field with the average current flow, and on this work, we evaluate the pulse frequency and electric field. This investigation is relevant for understanding the production of corona and space charges from high structures.

How to cite: Arcanjo, M., Montanyà, J., Lorenzo, V., and Pineda, N.: Corona point discharges from grounded rods under high background electric field, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9622, https://doi.org/10.5194/egusphere-egu21-9622, 2021.

Lightning interaction with aircraft becomes an increasingly important research topic due to the recent advancements in aviation industry and pressure put on it from climate regulations. A flying aircraft can interact with three known types of discharges, (i) aircraft-intercepted lightning, (ii) aircraft-triggered lightning, and (iii) electrostatic discharges.

Aircraft-intercepted lightning is a remotely initiated lightning discharge that attaches to the aircraft. Such events are relatively rare and constitute only a few percent of all lightning strikes to aircraft.

Aircraft-triggered discharge is a lightning that is initiated from the aircraft. These events happen when the aircraft polarizes and enhances the ambient electric field to the magnitude sufficiently high for triggering a bi-directional leader from opposite sharp extremities. More than 95% of all lightning strikes to aircraft are of this type.

Electrostatic (EST) discharges can be considered as another type of aircraft discharges but excluded from the above statistics because they can happen without presence of a thundercloud, lightning or strong ambient electric field. They happen when the aircraft collects significant charge on its surface by collisions with ice particles. Such discharges are usually associated with a noise in analog radiocommunication. It is not completely clear if the surface charge is necessary or the EST discharges can be initiated only by polarization of the aircraft in ambient electric field. Remarkably, EST discharges have been reported in association with positron annihilation signatures inside a thundercloud [1].

            In this work we report yet another type of discharge that was recently observed developing from an airplane. These discharges start from the aircraft in response to the electric field change caused by a nearby lightning flash. The remote lightning flash can redistribute the ambient electric field in such a way that the local electric field near the aircraft exceeds the breakdown threshold. We call them a “lightning-triggered discharge”.  Similar initiation mechanism is proposed for the high-altitude sprite discharges.

The lightning-triggered discharges from aircraft have not been studied and characterized before. They were observed and reported in [2] but were not identified as a separate type of aircraft discharges. As will be demonstrated, they are very likely to be underreported by pilots due to their often attachment to wings and relatively low current.

            The Remote Lightning Damage Assessment System (www.reldas.no) has been developed with the purpose to identify and systematically collect data on lightning strikes to aircraft. Besides other discharges, the system collected records of the aircraft-triggered discharges and their characteristics. Examples of such discharges will be shown with the photographs and current measurements.

References

1. Kochkin, P., et al. "In‐flight observation of positron annihilation by ILDAS." Journal of Geophysical Research: Atmospheres123.15 (2018): 8074-8090

2. Kochkin, P., et al. "In‐flight observation of gamma ray glows by ILDAS." Journal of Geophysical Research: Atmospheres122.23 (2017): 12-801.

How to cite: Kochkin, P.: New type of electric discharges from aircraft., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10916, https://doi.org/10.5194/egusphere-egu21-10916, 2021.

Recently, Hare et al. 2020 found that individual leaders steps could be imaged in the VHF band, and for leaders below 5 km altitude, the radio emission from each step is mostly consistent with a point-source. We will report on new observations of negative leaders above 7 km altitude that behave significantly differently than lower altitude leaders. These higher- altitude leaders are a few 100 meters wide and have step lengths a few 100 meters long, as opposed to lower altitude leaders that are at most 10 meters wide with 10 meter stepping lengths. Furthermore, unlike lower altitude leaders, the radio emission from individual steps of higher altitude shows extensive structure. Each step shows a burst of radio radiation, followed by the growth of multiple filamentary structures. The nature of these filaments is presently unclear, but they could be long streamers or leader branches. We have observed one leader that clearly starts at low altitude and propagates to higher altitude. This leader shows that the transition from the low altitude mode of propagation to the higher altitude mode does not occur smoothly as one may expect, but occurs abruptly at around 6 km altitude within only one kilometer, somewhat similarly to a phase change.

Previous work has measured 100 m long stepping lengths of higher altitude leaders, and it is often assumed that this is a simple pressure scaling effect. However, our data shows that the stepping process at lower altitudes and higher altitudes appears very differently in VHF, and that the transition between the two modes occurs rapidly. This implies higher and lower altitude leaders actually have different propagation modes, and are not merely pressure-scaled versions of each other.

We will also present new detailed VHF measurements of needle activity. We will show that needle twinkles have a wide range of propagation speeds, from 10⁵ to 10⁷ m/s, and that needle twinkles sometimes show stepping behavior, which strongly implies that needle twinkles can propagate similar to stepped leaders or dart leaders depending on the conductivity of the needle. We will also show that recoil leaders can quench needle activity, which leads to a cycle of increasing needle activity followed by quenching by a recoil leader, as originally predicted by Hare et al. 2019.

How to cite: Hare, B., Scholten, O., Dwyer, J., Ningyu, L., and Strepka, C. and the LOFAR CR KSP: Needle properties and a new higher altitude negative leader structure; observations by the LOFAR radio telescope, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14435, https://doi.org/10.5194/egusphere-egu21-14435, 2021.

We report on recent observations made by the LOFAR radio-telescope of a fast propagation mode in negative leaders we named Rapid Negative Leader (RNL).
The RNL has a variety of properties that make them clearly distinct from negative leaders or dart leaders, such as -- fast propagation, -- emission of strong broad-band pulses, -- emission of very high VHF power, -- a reduced density of located sources, and -- terminating with the spawning of a large number of negative leaders in a small area. RNLs are almost always observed in the initial stage of a lightning flash, but may also occur much later. They may occur repeatedly in a certain part of the cloud.