EGU General Assembly 2022  

There is serious concern that the hazard, or probability, of river floods is increasing over time. Anticipating any change in flood hazard is extremely important for adapting flood management strategies and thereby reducing potential damage and loss of life. However, floods are the result of complex interactions of runoff generation processes within the catchment area not easy to quantify. This presentation will review recent advances in understanding how and why river floods, and their probabilities, are changing over time.

Land use change, such as deforestation, urbanisation and soil compaction resulting from more intense agriculture, modify river floods by altering the infiltration capacity and soil moisture. Locally, these processes are well understood but less so at the catchment scale. The effect of land use on floods is particularly pronounced for flash floods in small catchments because of the role of soil permeability in infiltration at this scale. For regional floods, and for the most extreme events, land use is usually not the most important control, because areas of soil saturation are more relevant in runoff generation, which are less driven by soil permeability.

Instead, hydraulic engineering works, such as river training, reservoirs and levees, are more relevant. The effect of individual hydraulic structures can be captured well by hydraulic  modelling based on mass and momentum balance, and their role depends on the event magnitude. There is a tendency for all of these engineering works to exert the greatest effect on floods for events of intermediate magnitude, e.g. associated with return periods of the order of ten to one hundred years. Regional effects of engineering works are an active research topic.

Climate change can affect river floods at all catchment scales, from a few hectares to hundreds of thousands of square kilometres. Observed changes in river floods, e.g. in Europe, suggest that climate change is indeed modifying the river flood hazard, but the changes are not necessarily directly linked to precipitation, nor are they directly linked to rising air temperatures. The key to understanding climate change effects on floods is therefore the seasonal interaction between soil moisture (influenced by precipitation and evaporation), snow processes, extreme precipitation and runoff generation. In Europe, there have been a number of flood-rich periods in the past 500 yrs and we are currently in one of them. A trend of storm tracks to move further north in Europe has increased both average and extreme precipitation and thus river flood hazard in the Northwest of Europe, but floods are decreasing where snowmelt is relevant due to shallower snowpacks. There is a tendency for climate change to have the greatest effect on floods of large event magnitudes.

It is concluded that substantial progress has been made in recent years in understanding the role of land use, river works and climate in changing river flood hazards, both through data based and modelling approaches. Considering all three controls of change is essential in reliable flood risk assessment and management in order to maximise protection levels at an affordable cost.

Publications: https://hydro.tuwien.ac.at/forschung/publikationen/download-journal-publications/

How to cite: Blöschl, G.: Understanding changing river flood hazards, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1892, https://doi.org/10.5194/egusphere-egu22-1892, 2022.

Floods and droughts are often studied from a univariate perspective, which ignores their multivariate nature and can lead to risk under- or overestimation. The multivariate nature of hydrological extremes makes them particularly impactful, e.g. when they affect large areas or several components of the hydrological cycle, and should be considered when deriving frequency and magnitude estimates for hydraulic design and adaptation. However, studying multivariate extremes is challenging because different variables are related and because they are even less abundant in observational records than univariate extremes.
In this talk, I discuss different types of multivariate hydrological extremes and their dependencies including spatially co-occurring flood events, floods described by peak and volume, or droughts characterized by deficit and duration. I present different strategies to describe and model multivariate extremes, to assess their hazard potential, and to increase sample size – for example, the openly available R-package PRSim that stochastically simulates streamflow and hydrological extremes at multiple locations. I illustrate potential applications of some strategies using different large-sample datasets ranging from sets of alpine catchments in Switzerland to sets of hydro-climatologically diverse catchments in the United States and on the European continent. The strategies discussed enable a multivariate perspective in hydrological hazard assessments, which allows us to derive more comprehensive risk estimates than the classical univariate perspective commonly applied.

How to cite: Brunner, M. I.: Floods and droughts: a multivariate perspective on hazard estimation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3458, https://doi.org/10.5194/egusphere-egu22-3458, 2022.

How to cite: Buytaert, W.: Local solutions for global water security, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10506, https://doi.org/10.5194/egusphere-egu22-10506, 2022.

Droughts have major economic, social and environmental impacts around the world, and they are expected to increase in severity and magnitude because of changes in climate and its variability. In recent years we have seen incredible developments in the field of drought research and we have significantly improved our understanding of this complex phenomenon. While observations have become more abundant, we have also seen significant improvements in hydrological models that are better constrained by these observations. These model improvements also include the addition of new, relevant processes, needed to fully understand drought feedbacks.

In this talk I will discuss my experience with modeling drought at larger scales and including human-water interactions at these scales. These models are also used to study the impact of climate change on drought and show the impact of rising temperatures on society’s exposure to these impactful events. Spatial resolutions of hydrological models have improved significantly and the complexity of processes that we are able to simulate has increased, leading to exciting new insights. At the same time, we have to communicate these findings with not only the scientific community, but also the general public. This brings new challenges for scientists and affects our science.

I’ll highlight recent advances in the field of drought research and hydrological modelling, as well as frontiers and interesting developments in the field. I’ll mention some key challenges that we still have to face to better understand the impact and feedbacks of extreme hydroclimatic events.

How to cite: Wanders, N.: Dry drier drought – Understanding drought in a changing society and climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3416, https://doi.org/10.5194/egusphere-egu22-3416, 2022.

Thermal infrared (TIR) and visible/near-infrared (VNIR) surface reflectance imagery from remote sensing can be effectively combined in surface energy balance models to map evapotranspiration (ET) and vegetation stress, with broad applications in agriculture, forestry, and water resource management. Particularly valuable are ET retrievals at medium resolution (100 m or finer), resolving scales at which water and land are actively managed over much of the Earth’s surface. At this scale, TIR and VNIR data in the Landsat archive provide a 40-year and growing global record of coupled land and water use change.  In this presentation we will discuss the unique information content conveyed by the land-surface temperature signal regarding the surface moisture status and vegetation health. We will explore applications for field-scale temperature and ET retrievals in promoting sustainable water use, forest health, and regenerative agricultural practices. Widespread and routine generation of ET data at this scale has been enabled by cloud computing technologies, with the OpenET ensemble modeling platform as an example of collaborative geospatial information development.  Looking forward, integration of Landsat with new sources of medium-resolution TIR imagery (e.g., ECOSTRESS, LSTM, TRISHNA, SBG, Landsat-Next, and Hydrosat), as well as all-sky microwave-based temperature retrievals, will improve our ability to detect rapid changes in water use and availability – a key factor in real-time decision making.

How to cite: Anderson, M., Yang, Y., Xue, J., Knipper, K., Yang, Y., Gao, F., Hain, C., Holmes, T., Kustas, W., Fischer, M., and Trnk, M.: On the value of thermal infrared remote sensing for water and land management, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6797, https://doi.org/10.5194/egusphere-egu22-6797, 2022.

According to future climate projections both droughts and floods are expected to increase in severity and frequency. A lot of research has been done on the adaptation of society and the feedbacks between hazard and society for these individual hazards, while the feedbacks between hazards and society in a system that experiences drought followed by flooding are less well known. In this study we aim to identify common variables and characteristics of different human-water systems that experience drought-to-flood events and use this to inform model development. Through a literature study of a variety of case studies across the world we investigate the hydrological and socio-economic settings and characteristics of each system as well as the underlying processes and adaptation measures that played a role in the events. Drought-to-flood events can have very different drivers and impacts. In some cases the main driver is human adaptation, such as in the case of the Millennium Drought in Australia where flood prevention reservoirs were already full because they were being used to store water to cope with the drought (Van Dijk et al. 2013). In other cases the combination of hydrological drivers plays a more important role, such as in the case of Peru where a drought followed by extreme rainfall resulted in mud-slides (Fraser 2017). The comparison across cases provides an overview of common variables as well as differences between case studies and is used to inform the construction of one socio-hydrological model that fits all or multiple models that capture the specifics of each case. In future work the model(s) will be used for a more in-depth investigation of the behaviour of a selection of human-water systems, using qualitative and quantitative data in combination with the models to investigate possible future pathways and policy interventions.

References

Fraser, B. (2017). Peru’s floods teach tough lessons. Nature, 544(7651), 405-406.

Van Dijk, A. I., Beck, H. E., Crosbie, R. S., de Jeu, R. A., Liu, Y. Y., Podger, G. M., ... & Viney, N. R. (2013). The Millennium Drought in southeast Australia (2001–2009): Natural and human causes and implications for water resources, ecosystems, economy, and society. Water Resources Research, 49(2), 1040-1057.

How to cite: Barendrecht, M. H., Matanò, A., Mendoza, H. D., Weesie, R. V., and van Loon, A. F.: Modelling human-water systems experiencing drought-to-flood events: is there one model that fits all?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-222, https://doi.org/10.5194/egusphere-egu22-222, 2022.

In the words of David Sellars, engineering hydrologists ply their craft in the twilight, always looking for a shaft of illumination to enhance their understanding. Many decisions on flood risk management around the world are made using techniques that hydrological scientists would barely recognise. The Rational method, first formulated in 1850, is still widely used for design of structures, despite the availability of more scientifically justified alternatives. Software packages used by practitioners offer a variety of modelling techniques, sometimes without any guidance on their validity. It is common to see uncritical application of infiltration equations at a catchment scale with no acknowledgement that they ignore preferential pathway flow. There is a responsibility on both practitioners and software developers to improve scientific understanding.

Meanwhile, research projects and programmes, even with an operational focus, can produce reports, papers and even new techniques that never influence any engineering design, planning decision or operational forecast. In the UK, research into national flood frequency estimation by continuous simulation was completed in 2005 but has seen little implementation. One barrier was the decision to generalise rainfall-runoff model parameters using catchment properties which were not readily available to practitioners. Other UK initiatives have been more successfully adopted by practitioners, including recent development of guidance and tools for non-stationary flood frequency estimation. This produced a software tool that could be applied with a basic knowledge of the R language, along with practitioner-focused guidance, all freely available to download.

As an alternative to regulators trying to impose new approaches, a more promising avenue for implementation of research could be to create an environment in which the practitioner community is encouraged and incentivized to innovate, seeking out shafts of illumination from academia.

How to cite: Faulkner, D.: How to illuminate the twilight world of engineering hydrology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2504, https://doi.org/10.5194/egusphere-egu22-2504, 2022.

A decline in spring flows has been observed in the Indian Himalayas due to changes in landuse and rainfall variability (Matheswaran et al., 2019). Consequently, the Himalayan communities face water scarcity issues, as springs remain a significant source of drinking and agriculture. To ensure water and livelihood security, management of these springs through landscape interventions and source protection is critical. But lack of fundamental understanding of factors influencing its flow regime limits the impact of management approaches (Vashisht and Bam, 2013) in hydrologically complex and ungauged Himalayan watersheds. To increase the flows, aquifer recharge is aided through interventions. Aquifers recharge is a function of hydrogeology, landuse and rainfall, and conventional hands-on management approaches (conceptual mapping, digging contour trenches, recharge area protection, vegetative measures) for improving spring flows are partially effective (Tarafdar et al., 2019). As the mitigating measures don’t incorporate aquifer recharge functions. Hence, understanding the flow behavior is a prerequisite for instituting a best-suited management practice.

In this study, four springs (A₁, P₁, P₂, P₃) were instrumented for high-resolution monitoring in two pilot watersheds in Almora and Pauri region, Uttarakhand, India. Hydrograph analysis, including Recession and Flow durations curves (FDC), facilitated the assessment of spring hydrodynamics. In addition, autocorrelation and cross-correlation functions (ACF and CCF) aided in understanding the memory of the system and the interdependence of rainfall and spring discharge. Results showed that spring A₁ in Almora has intricate flow networks and slow flow velocities while P₁, P₂, P₃ spring clusters in Pauri show characteristics of transmissive fractures. This is Indicative of better storage capacity and homogeneity of underlying geology for A₁ compared to P₁, P₂, P₃. Recession coefficient ‘α’ for A₁, P₁, P₂, P₃ was calculated as 0.038, 0.109, 0.088 and 0.081 respectively. The low value of α for A₁ depicts diffused fracture system compared to P₁, P₂, P_3, which indicate rapid emptying of the aquifer, the shallow spatial extent of the recharge area and a well-interconnected flow network. Steep FDC for P₁, P₂, P₃ indicates high variability in springflows, while A₁ has a gradually flattening curve attributed to the presence of storage. ACF for A₁ shows a steady decline of r_xx(k) value till 0.4, a high memory for more than 120 lag days, while P₁, P₂, P₃ have r_xx(k) value rapidly declining below 0.2 (significance threshold) in 50, 60 and 70 lag days exhibiting shorter system memory and poor drainage of the extensive flow network.

Such a multi-approach analysis of spring flow systems aids in spring flow characterization, assessment of response lags and flow regimes. The combined usage of such techniques permits detailed process understanding and limits erroneous interpretations (Torresan et al., 2020). Policymakers can extend the results across the Indian Himalayas to design site-specific management frameworks.

Keywords : Springshed management, memory effect, high-resolution dataset, spring aquifer, Himalayas

How to cite: Dass, B. and Sen, S.: Investigating spring flow dynamics towards solving water management issues in the Indian Himalayan region., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3559, https://doi.org/10.5194/egusphere-egu22-3559, 2022.

The steadily growing demand for energy and the simultaneous pursuit of decarbonization are increasing interest in the expansion of renewable energies worldwide. Hydropower produces around 60% of Switzerland's electricity and plays a key role in this energy transition strategy. However, habitat and ecosystem protection and climate friendly renewable energy production are sometimes at odds. While the environmental impact is usually addressed at some level, there is a lack of standardization and tools for a global assessment are still scarce. The GIS-based tool HYDROpot_integral allows the consideration of the total hydropower potential as well as the ecological potential of a region. Based on ecological and socio-economic geodata, both the current state of each river reach and the hydropower potential is assigned a rank. To record the suitability, every river reach is ranked according to their ecological, cultural and economic ecosystem services. A low rank means that a river reach is more suitable for hydropower production at low cost in terms of ecological and cultural ecosystem services; a high rank indicates high ecological and cultural ecosystem services and low economic services and is therefore more suitable for protection. As the limit between hydropower use and protection is adjustable, different scenarios can be explored. Results from five mesoscale test catchments in Switzerland show the feasibility of the present method, to provide a comprehensive and meaningful basis that can support the decision-making process. Overall, the assessment method is to be understood as a flexible tool to address tradeoffs between hydropower potential and ecological potential.

How to cite: Hug Peter, D., Wechsler, T., Weingartner, R., and Zappa, M.: Addressing tradeoffs beyond disciplinary borders: HYDROpot_integral as a tool to simultaneously assess hydropower potential and ecological potential, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5738, https://doi.org/10.5194/egusphere-egu22-5738, 2022.

Hydrological sciences can contribute to society in numerous impactful ways: thus, it is crucial that we make an effort to enhance the opportunities for collaboration between academia and society, such as industry and territorial authorities. With the support of the Italian Hydrological Society (‘Società Idrologica Italiana'), in 2021, the Italian Young Hydrologic Society (YHS-Italy) organized a series of webinars to reduce the gap between academic researchers and practitioners, belonging to both private and public sectors.

The webinar ‘Beyond Academic Research Talks’ (BAR Talks) hosted a total of 24 guests during five online public meetings discussing three overarching topics: i) the professional careers of Italian researchers, ii) the research in the private sector, particularly at consulting and manufacturing firms of any size, iii) the hydrological and hydrogeological research in the public sector.

The goal was to document heterogeneous experiences and promote a discussion on potential practical applications of academic research. The meetings also served as an opportunity to understand similarities and differences between the role of a hydrological researcher across different institutions. All webinars have been organized online with live sessions, where the audience could interact with the speakers and ask questions. Each meeting was also recorded and made available on YouTube for asynchronous attendances (https://www.youtube.com/channel/UCjDrMpQvRQrp3lxtZTr7Trg).

The initiative has been positively welcomed, particularly by young researchers, and many new interesting topics have been raised. The BAR Talks presented a comprehensive selection of professional paths available to researchers interested in working outside academia, and looking for a more immediate impact on society. The guests talked about the challenges of doing hydrological innovation and research outside academia, and highlighted some of the skills that become particularly handy in the private sector (e.g., open-source software, programming languages, digital water, project management, soft skills). 

Finally, one issue that came out strongly from the BAR Talks series was the need, especially for the private sector, to close the gap between academic research and its real-world applications in order to improve the positive impact that academic research can have on society. Indeed, real-world applications often encounter constraining challenges that are sometimes missing from academic research. Overall, we observed that there is a widespread desire for a closer collaboration between hydrological academic researchers and practitioners, which may take the form of joint research projects aimed at producing impactful knowledge. 

How to cite: Meggiorin, M., Cristiano, E., Siena, M., Peli, M., and Zuecco, G.: BAR Talks: a YHS-Italy webinar series to bring hydrological researchers and practitioners close together, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5977, https://doi.org/10.5194/egusphere-egu22-5977, 2022.

Extreme weather events are increasing and will follow this trend due to climate change. In this scenario, adaptation, and mitigation in the face of them becomes essential both through technological innovations and through behavioural changes. In recent years, progress has been made in scientific knowledge on extreme hydrometeorological phenomena and climate change, and more funding is available for adaptation to climate change, both from European funds (e.g. Next Generation funds), country-level or regional funding. However, there are difficulties for to become this into a change in behaviors and actions to be more resilient to extreme phenomena both at the level of the general population and the public and private sector. This leads us to wonder if the knowledge and tools that are being generated are adjusted to the needs of these audiences in relation to adaptation and what are the facilities and barriers to carry out these changes towards more resilient patterns.

In order to analyze this aspect, a study has been carried out in which the viability and fitting of products and tools to improve the resilience of different type of end-users have been tested. For this, the first step was to conceptualize the tools and define hypotheses associated with them. The next step was to design the interviews to validate these hypotheses. Forty interviews were conducted with representatives of local administration, flood management companies, individuals, and so on. The interviews were customized to suit these different sectors and audiences. The answers served to validate or invalidate the starting hypotheses. In addition to the interviews, sources of expert information were consulted to identify similar strategies or tools and their level of success in their execution.

The interviews have made it possible to identify barriers to the implementation of changes both in individual habits (such as less interest than expected in attending participatory processes), and in organizations: budgetary limitations, political calendar or little knowledge/interest in knowing historical events. Motivations and interests were also identified, such as having a platform with centralized information on extreme phenomena or the prestige of collaborating with the academy to find optimal solutions to this problem.

This research has been done in the framework of the C3-Riskmed project (FEDER/MICINN-AEI/ PID2020-113638RB-C22) funded by the Spanish Ministry of Science and Innovation and EU Horizon 2020 project I-CHANGE (grant agreement 101037193).

How to cite: Llasat-Botija, M., Llasat, M. C., and Caballero-Leiva, I.: Study of end-user needs regarding behavior change to be more resilient to extreme weather events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7178, https://doi.org/10.5194/egusphere-egu22-7178, 2022.

Effective policy problem structuring – especially for ‘wicked’ environmental problems such as river pollution – involves the abstraction of governable elements of often diffuse ‘problematic situations’ through analysis and deliberation in order to identify tractable policy space. This involves facilitating some convergence around problem conditions, matching said conditions with available solutions, and mediating the diverse priorities and perspectives of large groups of stakeholders.

For large river basins characterized by multi-level governance and high population, industrial, and agricultural density – as in the Brantas River in East Java, Indonesia – the process of structuring water quality problems and formulating management plans is inevitably complex. Three shifts in water resource management, all aimed to improve efficacy, policy legitimacy, and representativeness, also present new challenges for problem structuring and planning. First, the evidence-based policy movement has been tempered by recognition of the political nature of science, driving inclusion of additional kinds of knowledge beyond hydrological, chemical, and biological science. Second, the mainstreaming of IWRM has encouraged a shift towards horizontally-arranged, multilevel governance networks of diverse actors across sectors, who bring their own problem perspectives and strategic preferences. Third, renewed interest in implementation studies has refocused attention on institutional, cultural, and capacity-related design requirements.

This research posits that the effective implementation of river environmental solutions depends largely on their responsiveness to administrative, social, and institutional factors as well as on their sympathetic alignment with stakeholders’ established priorities. Nevertheless, these important design factors often fall to the wayside in the design and selection of interventions, simply because they are not specifically and intentionally included in the processes of problem analysis and policy deliberation.

As part of a multi-stakeholder water quality management project in the Brantas basin, this research gathers and analyzes administrative and political knowledge inputs to complement technical inputs in the design of an Integrated Water Quality Management Plan. It combines two policy enquiries with hydrological science to support problem-structuring, namely perceptions survey research of water managers and systematic review of government agencies’ medium-term strategic plans. The survey research gathers perceptions of water managers across agencies and levels of government in East Java regarding the legal environment of water quality governance (legal basis, allocation of responsibilities, regulatory settings, conflict mediation), policy conditions (planning, coordination, monitoring, finance), and administrative and management arrangements, revealing differing perspectives on institutional opportunities and challenges amongst agency representatives within the same basin. The second identifies areas of strategic commonality centered on hydrological data management, community engagement, integrated solid waste management, industrial wastewater enforcement, and communal wastewater treatment. These findings are set out for consideration in two subsequent processes: the appraisal of feasibility and sustainability of interventions proposed for inclusion in the management plan, and to inform the nomination of implementing bodies for component activities within the plan.

How to cite: Houser, S., Pramana, R., and Ertsen, M.: Getting to the crux(es) of the matter(s): Water quality and problem-setting in the Brantas River basin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7276, https://doi.org/10.5194/egusphere-egu22-7276, 2022.

Water policy and hydrological planning are critical aspects regarding water supply systems adaptation to water scarcity risk, aggravated by the uncertainties that climate change may pose on water availability. The importance of the science-policy interface is especially relevant in coupled human-nature systems where different water uses and high competition for water resources (urban, agricultural, and tourist) coexist. This situation is particularly challenging in the coastal areas of the Mediterranean, subject to summer water shortages during the consumption peaks motivated by mass-tourism activity. Although national hydrological planning already includes the primary users’ participation in revising the five-year hydrological plans to reduce water conflicts and promote collaborative water management, on numerous occasions the need to improve these processes has been evidenced to propose feasible technical and political solutions in the water sector. Taking the coastal water system of the Marina Baja, located in the province of Alicante in Southeastern Spain, as example, we carried out an iterative participatory process involving the main representatives of the water sector management and both agricultural and tourism water demands to identify which topics should be collaboratively addressed to guarantee water supply in a future climate change scenario. Stakeholders’ perceptions about the main threats and needs to improve the functioning of the water system and their influence capacity, confronted interests, and power relations have been considered. Results determined that some hydrological policies applied at a regional scale, such as protocols for the monthly water discharge of reservoirs, the setting of ecological flows, or the sanitary policies for the management of swimming pool waters, collide with the individual experience and water management protocols applied by local stakeholders. Identifying these management issues through local experiences provides evidence about particular water management and policy challenges that must be addressed to increase the adaptation capacity of water supply systems conditioned by water stress or water confronted demands to the worst forecasts of climate change.

How to cite: Villar-Navascués, R., Ricart, S., Rico-Amorós, A. M., and Hernández-Hernández, M.: Identifying hydrological planning and water management and policy issues through an iterative participatory process: A coastal tourist experience in Benidorm, Spain, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7342, https://doi.org/10.5194/egusphere-egu22-7342, 2022.

Participatory processes provide opportunities for stakeholders such as: scientists, policy makers and citizens to meet, exchange information, deliberate and share values. The artefacts through which the water professionals (scientists and policy makers) and the other stakeholders can enable these participatory processes are defined as tools. There is a diversity of rapidly evolving tools for supporting the process of designing nature-based solutions (NbS) together with the stakeholders (participatory designing). This, however, requires a systematic and informed selection to facilitate the adequate choice of tool, aligned to the requirements and context of the water professionals but also the stakeholders. Despite this, there is still little progress and knowledge accumulation over preferred tools. Moreover, while tailored participatory tools could facilitate and accelerate the design process of NbS, a comprehensive mapping of their availability and capacity to respond to the values, requirements and needs of the stakeholders is still missing.

Consequently, in this research, we propose a stepwise framework for the use of tools as support in three interconnected processes: i) tools used for co-designing NbS with stakeholders - co-creation tools, ii) tools used for defining the hydro-meteorological hazards (HMH) and its effects with stakeholders – knowledge tools and iii) tools used for co-implementing the transition towards NbS – transition tools. We then test this stepwise framework in six brook catchments spread in four countries: the Netherlands, Belgium, France and the United Kingdom. The stepwise framework is designed in the following order: tool collection and selection; classification; grading and mapping. We are content that this stepwise framework could show how the water professionals, could make an informed selection and decision on the most suitable tool, based on the usability index of the tool for the specific stakeholder groups and the following criteria: tool category, objective of the tool, the required decision making process stage, the type of stakeholders, and the practical requirements (time, budget, number of participants).

Therefore we designed and tested a framework that allows the water professionals to make a decision on which tool/s could be best used based on their usability but also in terms of their characteristics analysed and described from the water professionals/practitioners themselves. What further discussion on this framework might entail is regarding the trends that we notice in the Co-Adapt project, the limitations and what happens after the tool or suite of tools is applied based on actual field experiences.

How to cite: Bogatinoska, B., Lansu, A., Huitema, D., Hugé, J., and Dekker, S.: Designing Nature-based Solutions in a Participatory Way: Usability of Tools for Water Professionals, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7785, https://doi.org/10.5194/egusphere-egu22-7785, 2022.

The European Commission in 2015, as part of the Common Implementation Strategy (CIS), defined the Ecological Flow (EFlow) in natural surface water bodies as “a hydrological regime consistent with the achievement of the environmental objectives of the WFD in natural surface water bodies as mentioned in Article 4”. These environmental objectives refer to (i) non-deterioration of the existing status, (ii) achievement of good ecological status in natural surface water bodies, and (iii) compliance with standards and objectives for protected areas. The Report does not define a standard protocol for setting an EFlow but it provides some recommendations.

The approaches for determining the EFlow, which must be defined in the River Basin Management Plans, are grouped into four classes hydrological, hydraulic, habitat, and holistic method. However, few methods have been specifically defined for temporary rivers. Most of these waterways have been poorly monitored in the past. The lack of historical hydrological and biological data in natural conditions ("reference") further complicates the definition of the EF.

This work analyses the implementation EFlow in the European Member States in Southern Europe under Mediterranean climate with specific reference to temporary rivers, which are the most common waterways in Spain, Portugal, France, Greece, and Italy. Through an examination of the case studies reported in the literature, a critical review of the methodologies adopted in these EU Member States for setting an EFlow has been carried out.

Results of this study showed that although all States have integrated into their legislation the EFlow recommendations by the EC, in several cases its implementation is not enforced sufficiently and several difficulties still exist in setting an EFlow. Case studies where the EFlow implementation was specifically designed for temporary rivers are still very few and most of the applications are based on hydrological methods. The paucity of hydrological and water quality data is the most important limit in setting an EFlow.

How to cite: Leone, M., Gentile, F., Lo Porto, A., and De Girolamo, A. M.: Ecological flow in southern Europe: implementation in temporary rivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8309, https://doi.org/10.5194/egusphere-egu22-8309, 2022.

The excessive use of pesticides in agriculture poses a threat to water and environmental quality. Under Horizon Europe, considering the priorities of the European Green Deal (EGD), research activities, technological innovation, and investments are needed to contribute to reducing the use of pesticides, fertilizers, and antimicrobials. In this scenario, there is a need to carry out studies on the short and long-term effects of the use of pesticides in the agro-environment and on the effect of mitigation measures. For this purpose, hydrological models are useful tools for the simulation of the fate and transport of pesticides.

Through a critical review, this study aims to: (i) update the status of the use of the hydrological models to simulate pesticides coming from diffuse pollution, (ii) Analyze the spatial and temporal scale of the model applications, (iii) Investigate possible relationships between models and specific pesticides. The ISI papers were selected based on six keywords were used on Scopus: “pesticides, model, watershed, hydrology, water quality, diffuse pollutant”. After removing articles, not in English and articles not related to modeling applications, 37 papers were found and analyzed by constituting a database containing information about the study areas, the pesticides, the model, and the methodology adopted (I.e. warm-up, calibration, and/or validation). Pesticides were classified into three categories: herbicides, fungicides, and insecticides.

Results showed that most of the study areas were localized in Europe (55.5%) followed by North America (22.3%), Asia (13.9%), and South America (8.3%). Soil and Water Assessment Tool was the most commonly used model with a percentage of 45.95%. Regarding the substances investigated, herbicides were the most modeled (71.4%) followed by insecticides (18.2%) and fungicides (10.4%). In particular, among the most commonly modeled herbicides were atrazine, metolachlor, isoproturon, glyphosate, and acetochlor. Among the insecticides, chlorpyrifos and metaldehyde were the substances most frequently modeled. Finally, chlorothalonil and tebuconazole were the most investigated fungicides.

This work will be useful to create an updated guideline to facilitate the water and the landscape managers in selecting a specific hydrological model to assess the transport and fates of pesticides and to simulate the effect of potential mitigation practices.

How to cite: Centanni, M., Ricci, G. F., De Girolamo, A. M., and Gentile, F.: Modeling pesticides in surface runoff: a review of the current status, progress achieved and desirable improvements., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8317, https://doi.org/10.5194/egusphere-egu22-8317, 2022.

The constantly expanding research literature in hydrological sciences underlines the necessity of knowledge integration and synthesis. Review papers aim to provide a comprehensive overview of the published literature with focus on research gaps and priorities on a specific topic and/or region. While the hydrological science community has responded well to address the needs for knowledge integration and synthesis through publishing many review papers, it is not clear if and how these review papers can be helpful beyond academia. This is particularly important for tackling water-related issues in collaboration with water practitioners and stakeholders working towards providing operational hydrology services (e.g., data collection and management, modelling, prediction, hydroinformatics, decision support). Despite the societal relevance of applied hydrology research in the context of global development agenda, the potential of review papers for achieving the research-practice interface remains unexplored or largely ignored. Hereby, we discuss how review papers in hydrology could contribute to this dialogue and remove barriers around the translation of research into practice. With this objective in mind, we reflect on several principles of writing and communicating review papers, including: 1) effective writing (e.g., language and format), 2) purposeful content design and development (e.g., review context, research synthesis, main findings and implications), 3) high accessibility (e.g., open access publishing), and 4) efficient visibility and dissemination (e.g., meetings with stakeholders and/or users,  social media, artistic material). For each principle, we explore strategies, resources and tools to improve the benefit of review papers to  hydrology practitioners.

How to cite: Dogulu, N., M. Mosquera, G., and Ramos, M.-H.: Review papers in hydrology for linking research to practice: a reflection on the why’s and how’s, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8748, https://doi.org/10.5194/egusphere-egu22-8748, 2022.

The flood events of 13-15 July 2021 in Germany brought the relevance of flood prevention acutely and once again to our attention. As the earth's atmosphere heats up, nature has more and more intense events in store for us, which push our flood protection and management measures to their limits and beyond. For planning purposes, but also in case of an event, it is therefore highly relevant to improve the communication of uncertainties and the assessment of their potential impact, e.g. in the climate or flood forecast, in a target group-oriented manner.

In Germany and in the European Union, the conditions for flood risk management have been improved since 2007 with the implementation of the European Flood Risk Management Directive (FRMD) and the amendments to the Federal Water Act. Many new instruments such as flood hazard and risk maps, building regulations or the category of flood emergence areas were introduced. For example, flood hazard and flood risk maps and corresponding management plans have been prepared on the basis of historical discharge data, water levels and hydrological and hydraulic modelling. However, recent examples have shown that the objective of the FRMD to reduce flood-related risks to human health, the environment, infrastructure and property has only been achieved to a limited extent.

In this paper we discuss why the developed maps and plans do not lead to a sufficient risk perception and why, in case of a flood event, it is often not clear what actions need to be taken when and by whom. For this, we want to highlight three aspects in particular:

1) Data: importance of using measured data and dealing with historical flood events, which are only comparable to a limited extent to today's and future conditions, which are shaped by the influences of climate change.

2) Actors: importance of involving different actors in the flood risk management planning process to strengthen risk perception and responsibility.

3) Communication: Importance of communicating uncertainties target group-specific and visualising uncertainties and their possible impacts context-specific.

For effective and sustainable flood risk management, we therefore believe that we are in need of a communication and dissemination strategy in order to contribute to a transparent description of the roles of the actors and their responsibilities. Consequently, the already developed tools (e.g. flood hazard /risk maps) should be supplemented by involving regional actors, uncertainty information and its effects should be classified and communicated to all decision-making levels in a way that is appropriate for the target group.

How to cite: Höllermann, B., Evers, M., and Johann, G.: The safety paradox in flood protection: the importance of communicating and contextualizing uncertainties, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9160, https://doi.org/10.5194/egusphere-egu22-9160, 2022.

While the added value of green roofs for mitigating rainfall extremes in urban drainage systems has been addressed in numerous studies, the microscale spatial redistribution of rainfall by solar panels (photovoltaic modules) mounted on green roofs and its impact on hydrology has hardly been studied so far. However, considering both green roofs and rooftop photovoltaic installations are emerging topics relevant for decision makers, since their combination supports both climate change adaptation (transforming grey to green infrastructure in order to cope with extreme rainfall in urban areas) and climate change mitigation (energy transformation). In the framework of an experimental study, we shed light on the hydrological and hydrodynamic effects of rooftop photovoltaic installations mounted on green roofs and how this contributes to the development of sustainable solutions in an interdisciplinary setting. Since solar panels redirect rainfall to the “green” fraction of the roof not covered by solar panels, the green roof part is in effect subject to higher rainfall and hence intensified surface runoff generation. Promising results were still obtained in a first investigation, where a photovoltaic green roof has been irrigated by a 100 years design storm with 27 mm over 15 minutes: the runoff coefficient (i.e., the percentage of rainfall that becomes runoff) at the end of the rainfall event amounts to only 23%, even though surface runoff occurred after 13 minutes. Based on this first investigation, a systematic measurement campaign has been launched to scrutinize the impact of the microscale spatial rainfall redistribution by solar panels on the runoff coefficient. In this presentation, we show the results of the first investigation along with results achieved in the systematic measurement campaign, which considers different vertical layer structures as well as various flow lengths and slopes of the photovoltaic green roof. In parallel, green roofs without photovoltaic rooftop installations are investigated alongside as a benchmark. In essence, our results suggest to consider both green roofs and photovoltaic rooftop installations to support both climate change mitigation and adaptation, which are important questions that decision makers are simultaneously confronted with. This way, this presentation highlights how experimental hydrology and interdisciplinary collaboration can contribute to address policy-related emerging research. Given that an obligation to install solar panels is expected in numerous countries, this kind of research might endorse new design approaches in future green roof design guidelines relevant for practitioners.

How to cite: Förster, K., Westerholt, D., and Lösken, G.: Photovoltaic green roofs – On the role of experimental hydrology to feature the acceptance of interdisciplinary and sustainable solutions for both climate change mitigation and adaptation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9498, https://doi.org/10.5194/egusphere-egu22-9498, 2022.

River water quality changes have been shown to follow typical trajectories, often characterized by sequential phases of accelerated degradation, environmental recovery, and responsive management. However, the relationships between anthropogenic mitigation measures such as regulatory interventions and their effects on water quality remain rarely studied and poorly understood.

In this study, we evaluate the effectiveness of three types of regulations: source-control, use-related and end-of-pipe regulations. Using phosphorus (P) as a model substance for water quality, we analyse a 50-year trajectory of measured total phosphorus (TP) concentrations in the river Ruhr, Germany, and link this with a comprehensive analysis of water quality related laws and regulations being enforced at the national and European level over the same time period. We categorized the regulations according to the aforementioned types and re-analysed the infrastructure developments and operation modes in a literature review and based on research in the archives of the responsible river basin management authority.

The strong decline of TP concentrations from a maximum of 0.59mg/l TP in 1977 to around 0.05mg/l TP in the early 21^st century resulted dominantly from source control by banning of P in detergents, the parallel construction of wastewater treatment plants and their sequential upgrade to treatment stages incorporating P removal. Thus, while point source pollution decreased, the share of agricultural and other diffuse sources of riverine TP concentrations increased to around 50%, making them the focus of attention nowadays. As source control and end-of-pipe measures have reached a level at which a further reduction of TP concentration in the river through those means would be marginal, use-related measures gain importance, especially for agricultural practices.

Our results show that source-control was the most effective and fastest way of reducing TP pollution, whereas end-of-pipe measures were a necessary, complementary way to reduce P related water quality impairment. Given the current dominance of diffuse pollution sources resulting from agricultural inputs, where the effectiveness of regulation is likely to be limited, additional measures such as awareness, economic incentives and support for agricultural best management practices need to be addressed. These findings may provide important insights into understanding the effectiveness of different regulatory measures, in particular with regard to the increasing introduction of (new) pollutants and associated impacts on the environment and human health.

How to cite: Hildebrandt, S., Krüger, E. H., Westphal, K., Ruhl, A. S., and Borchardt, D.: Efficacy of source-control, use-related and end-of-pipe regulations on river water quality in a large German river catchment: a 50-year trajectory, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10129, https://doi.org/10.5194/egusphere-egu22-10129, 2022.

The Winter Storm of February 2021 left millions of Americans in Gulf Coast states without access to reliable, clean domestic water during the COVID19 pandemic. In the state of Texas, over 17 million people served by public drinking water systems were placed under boil water advisories for periods ranging from one day to more than one month. We combine public boil water advisory data with demographic information from the 2010 United States Census to understand the affected populations. Additionally, we are conducting a survey of over 350 households in Texas to portray the impact of demographics and family considerations on Texans personal experiences with water access during the Winter Storm of 2021. Statistical analysis shows that the duration of boil water advisories depended partly on the size of the public water system. Large, predominantly urban systems (serving more than 10,000 individuals) tended to issue shorter advisories (median of 6 days and a maximum of 12 days). Smaller systems (serving less than 10,000 individuals) experienced a wide range of advisory lengths with a median of 8 days and a maximum of 36 days. Principal component analysis shows two main dimensions of variability among public water systems based on weather and demographics. Some of the longest boil water advisories exhibit clustering consistent with smaller, more rural systems (which also tend to serve predominantly white communities). Though these communities' benefit from public water service, the systems that serve them may have fewer resources to address problems that arise in extreme weather events. Small, rural or ex-urban communities with a greater portion of non-white residents have historically been excluded from public water service in the US (a problem known as underbounding). Some of these communities lack access to clean drinking water year-round and are more likely to experience more significant barriers to access in extreme weather events such as the Winter Storm of 2021. More studies are needed to understand and address disparities in clean water access throughout the US.  

How to cite: Tomko, B., Sawyer, A. H., Sánchez-Vila, X., and Nittrouer, C.: Public Drinking Water Access in Texas (United States) Communities During The Winter Storm 2021, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10351, https://doi.org/10.5194/egusphere-egu22-10351, 2022.

Recent decades have witnessed an increasing trend of displacement—forced movements of people, e.g., refugee, internal displacement, asylum. The greatest portion of global displaced populations are internally displaced persons (IDP) who travel within a country's boundary. IDPs are relocated due to varying reasons such as conflict, drought, flood, etc. Somalia is particularly renowned for protracted internal displacement due to long-lasting conflicts, extreme droughts, and flooding events. Despite the severity and continuity of the problem, we still lack an understanding of how water (here, droughts and floods) and conflict build IDP networks respectively. This research answers the following questions to solve the gap: (1) What are the underlying push and pull mechanisms in water-induced and conflict-induced IDP networks?; (2) How are water-induced and conflict-induced IDP networks structured and characterized?; (3) How do geographical locations cluster differently in two IDP networks? The analysis was conducted on the yearly IDP flow data at the district level in Somalia. We compared water-induced and conflict-induced IDP networks in Somalia using multiple network metrics, motif analysis, and community detection algorithms. From the analysis, conflict-induced IDP networks followed a power law for both indegree and outdegree. Though the in-degree networks of water-induced IDPs were weakly scale-free, the out-degree case was a random network. Both water-induced and conflict-induced IDP networks shared a similar mesoscopic network structure through the motif analysis. Closed triads were more frequently observed, supporting the importance of social linkages such as social homophily or information/knowledge sharing. Through the community detection, we found that water drove IDPs to move to nearby locations and led neighboring locations to clustered. Conflict, however, facilitated IDP flows between remote locations, building geographically-dispersed clusters. These findings offer an in-depth insight into commonalities and differences between water-induced and conflict-induced IDP networks in Somalia.

How to cite: Oh, W. S., Muneepeerakul, R., Rubenstein, D., Homayounfar, M., and Levin, S.: Water and conflict on internal displacement: network analysis of Somalia case, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10886, https://doi.org/10.5194/egusphere-egu22-10886, 2022.

Recent examples of climate-driven catastrophes both internationally (e.g. US and Australian wildfires in 2020) and nationally in Africa or Europe, as well as climate scenarios highlight that climate change impacts will likely reach dimensions which pose substantive shocks to social, economic and ecological systems in the near future. At some point, this increased number of shocks will overstretch current individual and collective coping capacities. However, on the other side catastrophic shocks may enable the transformation to decarbonisation and resilience of our society, if the rebuilding phase after an event is used for a broad societal transformation process and not only for quickly bouncing back to the pre-shock situation. A rushed return to normality may come at the cost of forgoing lengthy and challenging transformation processes, which may ultimately reorient a system to higher resilience. Fast recovery from shocks typically mobilizes extensive resources but often lacks an integrated perspective on climate change adaptation and mitigation policies (‘adaptigation’) that could leverage synergies and build up for long-term responses to climate impacts. Instead, many policies implemented after shocks act in isolated or even competitive silos, cater to immediate demands by affected citizens and businesses, and have different goals, instruments, financial resources, administrative practices, time perspectives, or lack of imagination how to implement. The aim of the paper is therefore to illustrate how the transformative potential of shocks can be leveraged to lower carbon emissions, higher climate resilience and encompassing adaptigation policy. This contribution presents a conceptual framework that focuses on the interaction between the individual actors affected by a shock, and the policy instruments in place in the aftermath of a shock. We strive to learn from past and current reactions to inform the future with the aim of directing post-shock learning to transformation outcomes and to avoiding maladaptation, backfire or inaction pitfalls. The paper derives guidance how to leverage the transformative potential of shocks by dedicated policy action, in order to promote outcomes congruent with the Sustainable Development Goals and the targets of European and Austrian climate change mitigation and adaptation strategies. The conceptual framework can be expected to apply to a wide range of emerging, novel or familiar shocks.

How to cite: Thaler, T., Posch, E., Seebauer, S., and Winkler, C.: Leveraging the transformative potential of shocks: a conceptual framework to reach the adaptigation goal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11380, https://doi.org/10.5194/egusphere-egu22-11380, 2022.

Over several years, flood management was concentrated on a physical solution such as building flood control structures like levees or dikes. However, with the increasing term of  “socio-hydrology” within the scientific community, the importance of analyzing the feedback between socio and hydrological systems is drawing attention for effective flood management. Many studies(Di Baldassarre, G et al., 2013; Green, C et al., 2011) have warned about the levee effect, which means increasing vulnerability due to non-occurrence of frequent flooding as a result of flood control structure system. Research to understand such interactions from a sociohydrology perspective is mostly conceptual and limited to qualitative analysis. In this study, we quantitively evaluate the dynamic behavior of a system composed of flood-economy-infrastructure. Sociohydrology model based on the differential equation for dynamic analysis system was used to interpret the Yangjae river flood plain numerically. The results confirmed that excessively built flood control structure systems increased flood risk and hindered economic growth.

How to cite: Kang, S., Uranchimeg, S., Cho, H., and Kwon, H.-H.: An Interaction between flood and economy of Yangjae River in socio-hydrology perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11789, https://doi.org/10.5194/egusphere-egu22-11789, 2022.

The World Meteorological Organization (WMO) supports the National Meteorological and Hydrological Services in their mission to deliver operational hydrology services for achieving water security and the water-dependent/water-related Sustainable Development Goals. Operational hydrology is defined as “the real time and regular measurement, collection, processing, archiving and distribution of hydrological, hydrometeorological and cryospheric data, and the generation of analyses, models, forecasts and warnings which inform water resources management and support water-related decisions, across a spectrum of temporal and spatial scales”. The WMO ‘Vision and Strategy for Hydrology and its associated Plan of Action*’, approved by the Extraordinary Congress in October 2021, identifies eight long-term ambitions for operational hydrology in support of the global water agenda: (1) No one is surprised by a flood, (2) Everyone is prepared for drought, (3) Hydro-climate and meteorological data support the food security agenda, (4) High-quality data supports science, (5) Science provides a sound basis for operational hydrology, (6) We have a thorough knowledge of the water resources of our world, (7) Sustainable development is supported by hydrological information, and (8) Water quality is known. The WMO initiatives aim at improving operational hydrology applications by communicating the needs and benefits of hydrological research in support of operational hydrology, and enabling new research partnerships and collaborations with academia and practice communities. In this presentation, we focus on science priorities and knowledge gaps necessary to improve the delivery and the use of hydrologic data, information, and services in operational hydrology. We discuss the WMO Hydrological Research Strategy and how we can strengthen Hydrology/Water topics under the umbrella of the WMO Research Board. We will also report on the main achievements of an expert team, brought together at the end of 2021 to identify complementary and new research areas to strengthen the linkages between water, weather, climate and environment within the existing WMO related programmes, including the Global Atmosphere Watch (GAW) Programme, the World Climate Research Programme (WCRP), and the World Weather Research Programme (WWRP).

* The process was led by the WMO Research Board (RB) with inputs from the WMO Hydrological Coordination Panel (HCP), the International Association of Hydrological Sciences (IAHS), and the Intergovernmental Hydrological Programme (UNESCO-IHP)

How to cite: Ramos, M.-H., Cudennec, C., Cullmann, J., Dogulu, N., Luterbacher, J., Pechlivanidis, I., and Salzberg, A.: WMO Hydrological Research Strategy 2022‑2030: Operational Hydrology and Water Research Priorities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11837, https://doi.org/10.5194/egusphere-egu22-11837, 2022.

We used Natural Language Processing (NLP) to assess topic diversity in the abstracts of all research articles (75,000) from eighteen water science and hydrology journals published between 1991 and 2019 -- these are all water science journals with an SCI h-index > 0.9. We found that individual water science and hydrology research articles are becoming increasingly interdisciplinary in the sense that, on average, the number of sub-topics that are represented in individual articles is increasing. This is true even though the body of water science and hydrology literature as a whole is not becoming more topically diverse. These findings suggest that the National Research Council's (1991) recommendation to increase multidisciplinarity of hydrological research has been followed in the sense that individual researchers are working to make their work more interdisciplinary. Topics with the largest increases in popularity were ‘Forecasting’ and ‘Climate Change Impacts’, and topics with the largest decreases in popularity were ‘Hydraulics’, ‘Solute Transport’, and ‘Aquifers and Abstraction’. Out of the eighteen journals that we tested, Hydrological Processes, Journal of Hydrology, and Water Resources Research are the three most topically diverse journals in the discipline. We also identified topics that are becoming increasingly isolated, and could potentially benefit from integrating more with the wider hydrology discipline.

How to cite: Rahman, M., Frame, J., Lin, J., and Nearing, G.: Hydrology Research Articles Are Becoming More Interdisciplinary, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13024, https://doi.org/10.5194/egusphere-egu22-13024, 2022.

Human activities can have substantial impacts on watersheds, and a dominant, yet understudied, impact on urban watersheds is the inflow and infiltration (I&I) of water into sewage infrastructure. This study uses a water-budget approach to quantify the magnitude of I&I and its effects on streamflow. The analysis is performed over the 2013-2020 period on 90 watersheds in the Atlanta, Georgia USA metropolitan statistical area (MSA), which has a humid subtropical climate. The following annual totals are determined for each watershed: precipitation, water leakage from municipal sources, actual evapotranspiration (AET), water withdrawals, and observed stream discharge. AET is the most difficult component to estimate, therefore, multiple models are used to estimate AET totals, and reference watersheds are used to adjust the totals. Predicted discharge is estimated by subtracting known water outputs from the water inputs, and I&I was the difference between predicted discharge and observed discharge. The most I&I-impacted watersheds are those with the largest I&I to stream discharge ratios. Mean annual totals for precipitation and supply-pipe loss for those watersheds are 1,498 mm and 39 mm, respectively. Mean annual totals for AET, stream discharge, and I&I, are 737 mm, 534 mm, and 267 mm. Therefore, the mean I&I to streamflow ratio for the ten most I&I-impacted watersheds is 0.51 (i.e., I&I is 51% of streamflow). Mean population densities, percent developed, and percent imperviousness for the ten watersheds are as follows: 1,308 people per km², 60%, and 37%, respectively. I&I is strongly positively correlated with the above three urbanization variables. Regression analyses show that population density explains approximately 50% of the variation in I&I and is the best predictor of I&I. The most urbanized watersheds in the Atlanta MSA have relatively low population densities compared to typical urban watersheds globally, so it remains to be seen if the regression model can be used in locales with much higher population densities. Nevertheless, these results are supported by previous findings in the eastern United States and the results should be transferrable to most urban watersheds there, while the general approach for quantifying I&I should be applicable globally.

How to cite: Diem, J., Pangle, L., Milligan, R., and Adams, E.: Using a Water Budget Approach to Quantify Inflow and Infiltration Impacts on Urban Streamflow, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13135, https://doi.org/10.5194/egusphere-egu22-13135, 2022.

Malaria remains a major health problem predominantly in tropical countries and is still being one of the biggest causes of mortality worldwide. It is an ancient vector borne infectious disease caused by parasitic protozoans of the genus Plasmodium and is transmitted by female mosquitos of the Anopheles species. The spatiotemporal distribution of this vector is sensitive to climate conditions and the distribution of hydrometeorological variables, particularly temperature, precipitation, and humidity. We present first results of a joint high resolution hydrometeorological- and subsequent dynamical vector transmission modelling. Our approach uses the couple atmospheric- and terrestrial model system WRF-Hydro, with a 1km grid spacing for the atmospheric part and a 100m grid spacing for the hydrological part. Besides traditional hydrometeorological variables, WRF-Hydro further resolves the surface water, which is potentially a crucial step forward for the grid cell distributed dynamical vector transmission model VECTRI. Our study addresses two Health and Demographic Surveillance Systems (HDSS) site regions at Nouna in Burkina Faso and Kisumu in Kenya. We present an analysis of the performance of the hydrometeorological model system and first results of the VECTRI modeling.

Preliminary results of the WRF-Hydro -VECTRI model system capture the Malaria seasonal variations correctly and show reasonable reproduction of the year-to-year variability of HDSS observed total Malaria cases.

How to cite: Bousso Dieng, M. D., Arnault, J., Tompkins, A., Sié, A., Munga, S., Franke, J., and Kunstmann, H.: High resolution coupled climate-hydrology-dynamical Malaria transmission modeling for regional Malaria transmission in sub-Saharan Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13166, https://doi.org/10.5194/egusphere-egu22-13166, 2022.

The increase in water demand and droughts have exacerbated water inequalities and weakened the economy worldwide. Nonetheless, droughts alone do not justify the severity of water scarcity events, leading to public water rationing and restrictions. It is of paramount importance to obtain a better understanding of how public perceptions of and attitudes towards drought adaptation strategies influence the severity and extent of impacts on water consumption. Furthermore, studies on the general public’s willingness to pay for mitigation and adaptation measures are key for the design and implementation of efficient and effective water management policies. This study aims to inform policy and decision-making by investigating people’s experiences, perceptions, and assessments of past water scarcity events to understand how these past events may have changed their attitudes and behaviour towards water availability and saving. Data were collected by surveying a sample of 800 residents in the Metropolitan Area of São Paulo (MASP) in South-eastern Brazil, and in Campo Grande in Midwestern Brazil. The MASP faced a severe drought from 2014 until and including 2015 due to a decrease in rainfall and human factors, including water resource mismanagement. This vulnerability frame is also observed in Campo Grande, where residents faced serious water rationing in 2016 and 2019. Our results show that more than 80% of the respondents think the frequency of drought periods increased over the last 10 years and will continue to increase in the next 10 years, and 95% of the respondents believe climate change is real. These results also corroborate the fact that 80% of the sample have faced water restrictions or rationing in the past, of which most lasted more than one day. The study provides policy and decision-makers with important information about the future design of payments for watershed services (PWS) to improve water security. However, one in every fifth respondent does not believe that a possible payment for water saving measures in the surrounding watersheds supplying the cities with drinking water would be invested by the responsible authorities to reduce future water restrictions and rationing and, therefore, improve water security. This reveals a considerable mistrust in the local, regional, and state governments responsible for water supply. Our findings provide important insights into relevant feedbacks between hydrological events such as droughts and societal vulnerability and response inserted into the present-day Brazilian cultural, socioeconomic, and political context, and the effectiveness of economic policy instruments like PWS.

How to cite: Sone, J., Gesualdo, G., Schwamback, D., Wendland, E., and Brouwer, R.: Public perception of droughts and water shortages and metropolitan willingness to pay for water saving measures to improve water security, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13392, https://doi.org/10.5194/egusphere-egu22-13392, 2022.

There has been increasing recognition that the global water crisis is due to lack of understanding of wider economic and socio-cultural perspectives, resulted from the intended and/or unintended consequences of co-evolution of coupled human-water systems. In light of such recognition, Panta Rhei Initiative (2013-2022) was proposed to focus on changes in both hydrology and society. Approaching end of this decade, this study present the synthesis of knowledge gained in our understanding of coevolution and prediction of coupled human-water systems. Content include five parts: (I) Motivation and Overview, (II) Theoretical Foundations and Methodological Approaches, (III) Synthesis of Work Done and Understanding Gained in Specific Application Areas, (IV) Panta Rhei Case Studies, (V) Grand Synthesis and Recommendations.

How to cite: Tian, F., Haeffner, M., Kreibich, H., Mukherji, A., Wei, J., Sivapalan, M., and Blöschl, G.: Coevolution and Prediction of Coupled Human-Water Systems: A Synthesis of Change in Hydrology and Society, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-36, https://doi.org/10.5194/egusphere-egu22-36, 2022.

The effectiveness of governmental disaster risk reduction policies in East Africa is influenced by how smallholder farmers react to droughts and adopt drought adaptation measures. In recent research on socio-hydrological feedbacks and the role of farmers’ adaptive behaviour in drought management, agent-based models (ABM) were found to be powerful tools. In this study, we developed an innovative agent-based drought risk model (ADOPT) that explicitly takes into account the two-way relationship between heterogenous individual agricultural adaptation decisions and the agro-hydrological system (modelled using AquacropOS). ADOPT is able to evaluate the effect of drought risk policies on the dynamics of poverty, food security and relief needs, and was applied to a case in Kenya.

First, we conducted a multi-method data survey among stakeholders and households in semiarid Kenya to better understand the drivers and barriers, such as knowledge of adaptation measures, fear of droughts, and perceived vulnerability, that determine the adoption of drought adaptation measures in this context. This information was used to calibrate the decision rules in ADOPT. We then applied ADOPT to simulate how drought policy interventions, such as improving extension services, improving early-warning systems, distributing ex-ante rather than ex-post cash transfers, and widening access to credit markets, influence the drought risk and adaptation of smallholders. We found that a holistic approach, including all these measures combined, can reduce the poverty rate with 66%, food insecurity with 70%, and aid needs with 75%, on average over six potential future climate scenarios.

How to cite: Wens, M., Van Loon, A., Veldkamp, T., Mwangi, M., and Aerts, J.: Assessing smallholder drought risk dynamics under climate change and government policies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-458, https://doi.org/10.5194/egusphere-egu22-458, 2022.

Sea-level rise (SLR) and socioeconomic trends are increasing the population and assets exposed to extreme coastal flood events in the coming decades. People residing in communities experiencing this increase in coastal flood risk may choose to stay, to stay and adapt, or to migrate towards safer areas. However, these migration decisions are influenced by many socio- economic and environmental factors. For example, current assessments of SLR adaptation and migration do often not address risk perceptions of residents related to different environmental risks, such as flooding and erosion. These factors influence adaptation decisions, and thus exposure and vulnerability. In this study, we aim to improve the representation of the dynamics of adaptive behavior of coastal communities in flood risk assessment by including human behavior and its effect on adaptation decisions, in face of SLR. Therefore, we develop an agent-based model grounded in subjective expected utility theory and simulate adaptation- and migration decisions of households facing coastal flood risk in France between 19xx and 2020. The model is empirically calibrated using survey data on flood risk perception and people’s willingness to implement adaptation measures. Then, we use socio-demographic projections to estimate future changes (2020-2080) in demographic composition, and apply the model to simulate coastal adaptation. The agent-based model presented in this study functions as a platform for further development of 1) more realistic decision models and 2) global modelling approaches of both coastal adaptation and migration under projections of future development.

How to cite: Tierolf, L., Haer, T., de Bruijn, J., Botzen, W., Reimann, L., Ton, M., and Aerts, J.: COASTMOVE: A global agent-based model of adaptation and migration decisions in face of sea level rise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-857, https://doi.org/10.5194/egusphere-egu22-857, 2022.

Uncertainties and indeterminate scope, divergent social values and stakeholder interests, and changing hydroclimatology in transboundary river basins are all factors that may complicate sustainable water resource management. To address such complex socio hydrological issues, we present an example of an integrated approach to assessing future sustainability challenges in their social, hydrological, and ecological dimensions using a case study from the Lower Mekong basin. Our study area here is the combined basin of the Se Kong, Se San, and Sre Pok (3S) rivers which deliver approximately 20% of flow to the Mekong River system. We used a mixed methods approach to analyze potential impacts of climate change on regional hydrology, the ability of dam operation rules to keep downstream flow within acceptable limits, and the present state of water governance in Laos, Vietnam, and Cambodia. Our results suggest that future river flows in the 3S river system could move closer to natural (i.e. pre-development) conditions during the dry season and experience increased floods during the wet season. This anticipated new flow regime in the 3S region would require a shift in the current dam operations, from maintaining minimum flows to reducing flood hazards. Moreover, our Governance and Stakeholders survey assessment results revealed that existing water governance systems in Laos, Vietnam, and Cambodia are ill-prepared to address such anticipated future water resource management problems. Our results indicate that the solution space for addressing these complex issues in the 3S river basins will be highly constrained unless major deficiencies in transboundary water governance, strategic planning, financial capacity, information sharing, and law enforcement are remedied in the next decade. This work is part of an ongoing research partnership between the National Aeronautical and Space Agency (NASA) and the Conservation International (CI) dedicated to improving natural resources assessment for conservation and sustainable management.

How to cite: Mohammed, I., Bolten, J., Souter, N., Shaad, K., and Vollmer, D.: Assessment of water resources conservation and sustainable management strategies in the Lower Mekong River Basin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1323, https://doi.org/10.5194/egusphere-egu22-1323, 2022.

The estimation of irrigation amounts and timings is crucial for the design of water management strategies at the regional scale. However, simplified modelling approaches are often preferred even though very complex and high-accuracy crop models or agent-based models exist. In this study, we develop a sensitivity analysis to evaluate the impacts of simplifications and hypotheses in irrigation modelling. For this, different simple modelling approaches based on the CropWat model were compared to a multi-agent based approach (Maelia), which served as a benchmark. To make an in-depth comparison between simulations, several indicators characterizing daily simulated irrigation were calculated and a decomposition of variance was carried out to measure impacts of diverse factors on irrigation. Applied over a downstream portion of the Aveyron River (southern France), the sensitivity analysis shows a high variability between simulations in function of modelling assumptions. It also shows that several simplifying approaches were able to reproduce the high-accuracy model estimation of irrigation. Decisive variation factors we identified are rules of triggering and quantification of daily irrigation, irrigation period definition and evapotranspiration estimation. Recommendations to take into account highlighted variability linked to farmers’ irrigation practices are introduced in this work, consisting in a combining a set of irrigation models. In function of advancement, a complete integrated agro-hydrologic modelling chain might be presented.

How to cite: Soutif--Bellenger, M., Thirel, G., Therond, O., and Villerd, J.: How much can we simplify irrigation in an integrated modelling purpose? A case study in southern France, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1522, https://doi.org/10.5194/egusphere-egu22-1522, 2022.

Calculating the drawdown of groundwater abstractions for drinking water is usually done considering the current land use and regional drainage characteristics. However, many drinking water abstractions already exist for several decades and abstracted volumes have increased over time. In the Netherlands, especially in the more elevated parts of the country, the drainage characteristics were also significantly altered to prevent water logging and to optimize the water management for agricultural use, often after establishment of the groundwater abstraction site. These changes were intended to lower the phreatic groundwater levels to prevent waterlogging, but unintendedly also made the regions more vulnerable to drought. The question is whether groundwater abstractions for groundwater would have a similar impact in the former historic hydrological context and whether restoring the system to this state would ameliorate current drought problems.

In this study we investigated whether a drinking water abstraction would have the same drawdown if the regional drainage characteristics would not have been altered and whether restoring the historic situation would decrease drought impacts. First, a literature study was conducted to understand the changes to the drainage system over time. These changes were then implemented in a regional groundwater model (based on Modflow) for a conceptual region, representative for the eastern part of the Netherlands. Results from both the literature study and the groundwater model indicated that changes in the drainage system lowered the groundwater levels by tens of centimetres (differences ranged from 20 to 100 cm). Drawdown from the drinking water abstraction was larger in the historical situation than in the current situation, even though groundwater levels were higher. In the historical situation less reduction in transpiration occurred, leading to a lower recharge of the groundwater and thus a larger drawdown. However, when irrigation was applied, this effect was not found.  This implied that a correct estimate of groundwater recharge is crucial to calculate drawdown from abstractions. Recharge depends on actual evapotranspiration, of which the conceptualization in regional models could be improved. Returning the drainage system to the historical situation leads to higher groundwater levels, thereby reducing the drought impact, but also increasing the risk of oxygen stress in crops. More research with regard to the impact on crop yields is needed on local scale, before measures to mitigate drought impacts can be taken.

How to cite: van Huijgevoort, M., Cirkel, G., and Bartholomeus, R.: Effects of historic changes in regional drainage characteristics on the drawdown of groundwater abstractions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2333, https://doi.org/10.5194/egusphere-egu22-2333, 2022.

There is a reason why Iceland is frequently called the land of fire and ice. Located on the mid-Atlantic ridge in the North Atlantic Ocean, Iceland is frequently exposed to explosive volcanic eruptions. Furthermore, due to its geographic location cold Arctic winds from the North and the warm humid winds coming from the Gulf of Mexico collide. The particular geographic location is the reason why over 10% of the Island area is covered by glaciers, precipitation can exceed 10´000 mm a-1, and glacial flood can reach several 100’000 m3 s-1. Regardless of the arctic winds, the extreme precipitation, and the frequent eruption, the original Icelandic vegetation has developed a resilience to with sand almost any natural hazard. However, with the arrival of the first settler over a millennium ago Iceland has been subject to dramatic deforestation due to intense sheep and horse farming. These anthropogenic impacts have severely mitigated the resilience of the Icelandic vegetation, altering the erosion patterns and finally also impacting the natural water flow. The Rangárvellir area in southern Iceland is an ideal location to study the interaction of human impacts, natural hazards, and consequences for the natural water cycle. Deforestation and intensive farming have decreased the resilience of the local ecosystems, leading to severe land degradation and extensive soil erosion. Since the beginning of the 20th century, diverse restoration measures have been implemented across Rangárvellir. Long-term monitoring programs demonstrate how restoration can help mitigate hydrometeorological and volcanic risks, providing a representative example of nature-based solutions. For this purpose, we present a metadatabase (http://rangarvellir.ru.is/) providing an overview of previous and ongoing research on land restoration, land management, reforestation, hydro-meteorological monitoring, and vegetation mapping. All relevant past and ongoing research and restoration projects are described in order to demonstrate the importance of an all-inclusive landscape restoration approach. The study concludes by outlining the importance of nature-based solutions and highlights the interaction between research projects in the frame of restoration and land reclamation efforts.

How to cite: Finger, D. C.: Hydrology at its extreme: climate change, societal impacts and natural hazards in the land of fire and ice, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4543, https://doi.org/10.5194/egusphere-egu22-4543, 2022.

The Po Plain (Northern Italy) has largely subsided due to natural processes and human activities. In particular, in order to reduce subsidence, in the Bologna metropolitan area a politic decision in 2010, imposed a significant reduction of civil water supply from groundwater withdrawal wells. The study area is characterized by an excellent monitoring activity which provides a good spatial and temporal distribution of data coming from continuous GNSS sites, piezometers and rain gauges.

In the present work we analyze both GNSS and piezometric data by means of the Principal Component Analysis (PCA). The results of the analysis are then compared with the rainfall time series measured by rain gauges. Thanks to the PCA analysis we can identify: i) a clear increase in the water level following the withdrawal decrease started in 2010 and ii) an anthropic induced surface displacement, which is smaller in magnitude than that induced by rainfall variations. Without the PCA analysis, such a small, but still significant, anthropic effect on vertical displacements would have remained hidden in the raw time series.

Our analysis reveals a decrease of about 4 mm/y of vertical velocity in some GNSS sites closest the withdrawal wells. We also found that on large time scales (> 1 month), the vertical displacement induced by rainfall strongly depends on the geological setting: in the mountains a water level increase causes subsidence (elastic response), whereas in the Po Plain it causes uplift (poro-elastic response). Thanks to the PCA analyses, the combined observations of different kind of instruments (GNSS, piezometers and rain gauges) and a basic knowledge of the geological context, we can correctly identify both the anthropic and natural signals on the data.

How to cite: Nespoli, M., Cenni, N., Belardinelli, M. E., and Marcaccio, M.: Detecting natural and anthropic effects on displacements and water level changes: a combined observation from rain gauges, piezometers and CGNSS, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5096, https://doi.org/10.5194/egusphere-egu22-5096, 2022.

Water quality is an integral part of water security, but water quality itself is complex, due to its multifaceted nature. Measuring the physico-chemical indicators for water quality (e.g. pH, turbidity, heavy metal content) can provide an objective picture of water health, but it does not provide information on how it integrates and expresses the human perspective. Perceptual information and local ecological knowledge on water quality can help to understand the usability of water and support better conservation strategies. Therefore, the aims of the Nuestro Rio project were to investigate local perceptions of water quality in the upper Santa River basin, Peru. Walking interviews (n = 99) were conducted in the field between July-August 2021 to assess community members perceptions of their local rivers and streams. Through qualitative data analysis in two rural communities in the glaciated Santa River basin, we collected local perspectives on good and poor water quality, identified some of the key water concerns of the population, and explored the importance of emotions for determining water quality perceptions. Overall water quality perspectives differed within, and between, the two communities. Yet, it was possible to identify several characteristics and concerns that the population has been perceiving in recent years, as well as their causes, both natural and anthropogenic. Both communities felt the main cause of poor water quality was pollution due to the presence of minerals in the water, “invisible” aspects of water quality. We found that local perceptions on water quality also depend on water use as it has an important effect on local organisation. Emotions, on the other hand, reflect the population’s concern, fear, anger, and even frustration, when perceiving poor water quality, and happiness, trust, and even affection, when perceiving good water quality. More inclusive science that asks people what they observe, think and feel about the quality of their rivers and water can help provide a much deeper contextual understanding (e.g. useability of water, changes over time, traditional ecological knowledge) of local dynamic human-water systems, and improve science communication and policy implementation.

How to cite: Rangecroft, S., Dextre, R. M., Richter, I., Kelly, C., Turin, C., Fuentealba, B., Grados Bueno, C. V., Camacho Hernández, M., Morera, S., Martin, J., Guy, A., and Clason, C.: Exploring local perceptions of water quality in the upper Santa River, Peru, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5520, https://doi.org/10.5194/egusphere-egu22-5520, 2022.

Sustainable development is becoming increasingly urgent in the post-COVID recovery and climate crisis era. Despite this need, the water management scientific community is still deciding how to comprehensively represent and assess the role of humans within the hydrological cycle. An explanation may be found in numerous examples where water managers are often challenged when their decisions, policies, and interventions lead to a range of unintended consequences that cause increased pressures on the environment, which have been described by socio-hydrological paradoxes. If the paradoxes are seen as the main obstacles hindering sustainable development in the context of water management, then investigating their mechanisms and understanding logic may help us to reveal unintended system responses and define guiding principles critical for designing robust and sustainable water management plans. We analyse the socio-hydrological paradoxes from a systems perspective and assume that water management decisions and plans developed adopting a linear thinking and goals-focused approach are likely to neglect consequential effects which occur throughout the wider system. This definition enables us to rename the phenomena into water management paradoxes, which might be fundamentally related to systems’ complexity and unexpected behaviour arising from internal feedbacks along with external driving forces that generate nonlinear outcomes which are inconsistent with the expected results or responses from inputs and actions within the system.

To find solutions for the water management paradoxes, we hypothesise that they can be described in the context of three feedback mechanisms, which define the purpose of systems water management (SYWM) as coordination of development and water infrastructure with environmental management to improve the quality of life. We argue that the lack of consideration, integration and coordination of the SYWM meta-model loops will result in one of the water management paradoxes. As a solution, we propose three paradox archetypes that form the basis for guiding principles for systems water management. We suggest that environmental capacity indicators should be used in whole-system performance evaluation. The meta-model emphasises the need to better understand the baseline and development scenarios in the context of water neutrality, which is crucial for informing development decisions, including trade-offs in resource and infrastructure planning and operation. We encourage the use of a SYWM meta-model and proposed principles as a guide for analysing, modelling, and assessing human-water systems, thus creating an evidence base of case studies to demonstrate the meta-model’s applicability to solving water management paradoxes. In doing so, we hope to move towards the design of water systems that will support post-COVID recovery and enable long-term sustainable development.

How to cite: Mijic, A., Liu, L., O'Keeffe, J., Dobson, B., and Chun, K. P.: Solving water management paradoxes requires a systems meta-model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5577, https://doi.org/10.5194/egusphere-egu22-5577, 2022.

Water scarcity and drought are sustainability issues that cut across borders and different scales and levels of organizations and cannot be designated to one governmental authority. Due to hydrological droughts in semi-arid Northeast Brazil, the region deals with water scarcity. In the case of Ceará state, water is stored in multiple reservoirs as part of a water supply system and is managed from different levels of organization. These are considered governance scales that include state level-, regional level- and municipal level institutions, local level communities, and individual households. Water management in Ceará is an example of how polycentric governance brings a multifold of governmental and non-governmental actors together for the management of public goods in the society, and therefore cross-scale and cross-level interactions are inevitable. However, a variety of multiple challenges of contradictory water policies, diverse and varying levels of water users and multiple overlapping governance systems and organizations in combination with resource depletion make equitable water allocation challenging in Ceará. For this reason, this research aims to examine the scale mismatches in the water management processes and level misalignments of different governance levels and understand the influences of multiple governance systems on collectively managing water for equal water allocation. The following research question is used: What are the scale mismatches in water management and the misalignments of levels in water governance in Ceará state, and how have these affected the equitable access to water by different groups?

A polycentric governance lens is used to understand the interplay and influences of multiple water governance systems with competitive and cooperative relationships over water resources. We analyzed the multiple scale challenges in water management in the Banabuiú basin in the state of Ceará, using minutes from official water committee meetings, and qualitative data from interviews conducted with smallholder farmers, field technicians, civil servants and researchers in November and December 2021.

Literature research and fieldwork interviews in Ceará provided insights into user conflicts and mismatches across varying scales and levels. Our results show that, at river basin levels, e.g., networks of reservoirs and the river basin of Banabuiú, conflicts of prioritization between small-scale farmers and urban water users occur when the metropolitan area of Fortaleza is prioritized. Prioritization of the metropolitan region has been shown to result in limited and non-participatory decision-making, lack of information sharing and restrictions for irrigated farmers at the local scale. At the local scale, state interference in water management is in some cases not appropriate to the local context or in accordance with local knowledge. These scale mismatches occur due to multiple types of local water management, lack of responsibility for the management of monitored and unmonitored reservoirs, and various overlapping assisting agencies at the community level. The cross-scale interactions and conflicts in water management systems highlight the interdependencies between stakeholders and scale challenges in socio-hydrological systems. 

How to cite: van de Ridder, E., Cavalcante, L., van Oel, P., Dewulf, A., Kchouk, S., Ribeiro Neto, G., Walker, D., and Martins, E.: Polycentric governance and scale challenges in water management in the semi-arid river basin of Banabuiú, Ceará, Brazil, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6497, https://doi.org/10.5194/egusphere-egu22-6497, 2022.

The city of Barcelona is severely affected by pluvial floods, for which the risk management can be further improved. To provide essential information about pluvial flood risk we compare two events that occurred in 1995 and 2018 and put these into context of all convective precipitation events between 2013 and 2018 in Barcelona. The objective is to identify the main drivers of pluvial flood impact and the most flood prone areas. These results will help to further improve pluvial flood risk management in Barcelona, e.g. by developing targeted preparedness and empowerment campaigns.

The event comparison followed the paired event approach (Kreibich et al. 2017). In the 1995 event, the surface runoff of the streets caused a fatality in the Eixample quartier, a total of 2,500 calls were registered to the emergency services, 128,000 subscribers suffered cuts of light, 2 blocks of houses were evacuated, and numerous low floors were flooded.  33.6 Million €₂₀₁₈ were paid by the national insurance company, CCS, to compensate insured losses in Barcelona. The 1995 episode marked a turning point in the development of the sewerage in the city. Although the maximum 5-min intensity in the 1995 event was 235 mm/h in front of 211 mm/h in the 2018 event, the maximum rainfall recorded in 20 min (155,4 mm/h versus 169,8 mm/h, respectively) and 60 min (78,6 mm/h versus 88,1 mm/h), as well as the “average water volume precipitated over the city” (376,5 m³ versus 457,1 m³) was superior in the second event. However, in the 2018 event, only 294 emergency phone calls were received, mainly due to flooding of low plants and basements, water leaks or fallen trees; and 3.5 Million €₂₀₁₈ were paid by the CCS. This analysis shows the effectiveness of the mitigation measures taken in the city after the 1995 flood event that have diminished the vulnerability. The analysis of the 207 convective pluvial events registered by the city's drainage network between 2013 and 2018, with a focus on the 58 events for which radar images are available (Esbrí et al., 2021) provides information on the city quartiers which are most endangered by pluvial floods. Conclusion shows that the structural and non-structural improvements applied in Barcelona are a good example for other cities with similar characteristics, although the improvement in awareness, empowerment and communication with the population is still pending, mainly in the most affected quartiers of the city.

This work has been done in the framework of the I-CHANGE (H2020-2020 Prop.101037193) European project and the C3-RiskMed (PID2020-113638RB-C22) research project, funded by the Spanish Ministry of Science and Innovation.

References.

Kreibich, H., S. Vorogushyn, J.C.J.H. et al. 2017. Adaptation to flood risk – results of international paired flood event studies. Special collection “Avoiding Disasters: Strengthening Societal Resilience to Natural Hazards” in the journal Earth’s Future. Earth’s Future,5,953–965, doi:10.1002/2017EF000606.

Esbrí, L.; Rigo, T.; Llasat, M.C.; Aznar, B. Identifying Storm Hotspots and the Most Unsettled Areas in Barcelona by Analysing Significant Rainfall Episodes from 2013 to 2018. Water 2021, 13, 1730. https://doi.org/10.3390/w13131730.

How to cite: Llasat, M. C., Aznar, B., Esbrí, L., Rigo, T., Grima, O., and Kreibich, H.: A comparative analysis between two pluvial flood events in Barcelona (Spain).  An example of a success story, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6604, https://doi.org/10.5194/egusphere-egu22-6604, 2022.

As the longest river in Asia, the Yangtze River has shown its impact on human societies with floods recorded since 12^th century. In 1931, the Yangtze River has manifested its force again with one of the deadliest floods ever recorded in Chinese history, causing 422,499 deaths, damages to more than 25.2 million people and 58.7 billion m² farmland. Similar flood occurred again in 1954, resulting in 31,762 deaths, damages to 18.9 million people and 31.7 billion m² farmland. Researches have shown that 1954 flood being larger and higher compared to 1931 flood. However, it is still unclear for what reason that a more severe flood leading to less damage. Was it because of the change of residents’ interactions and for what extent had it affected the damage? To answer this question, first, we constructed a conceptual framework of 1930s and 1950s agricultural society. From which drastic changes has been detected (e.g., increase of absentee landlords, land reform) and the residents’ interactions with floods have been analyzed. Then, we reconstructed the flood inundation process of 1931 and 1954 floods with gauged rainfall dataset. After referring to the investigation report, the inundation information was applied to re-estimate the flood damage on farmland, houses, and residents. With the simulation and modification, we found that the inundated farmland of 1931 is about 83% more than former, indicating a much more severe influence on residents’ lives than we used to think. On the contrary, the total increase of influence farmland in 1954 is around 50% after modification, suggesting a relative success in reducing flood damage. To quantitatively explain it, the countermeasures during 1954 flood were estimated, showing that the reinforcement of levees in 1950s was more effective in reducing inundation area of 7%, while the construction of detention basins accounted for only 2%. Such results revealed that the countermeasures against 1954 flood being more successful than 1931. Moreover, the changes of agricultural interactions with floods have also been estimated using the potential crop production (PCP), indicating an improvement in disaster mitigation in 1954. Our results demonstrate how society changes are likely to affect the response towards natural hazards, the knowledge and method of which are expected to be applicable to many other regions and times.

How to cite: Liu, C., Kawasaki, A., and Shiroyama, T.: The society interactions with floods in the modern Chinese history: a comparison between 1931 and 1954 floods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6759, https://doi.org/10.5194/egusphere-egu22-6759, 2022.

Irrigated agriculture plays an important role in the continental water and energy cycles of the basins where it is present. Land-Surface models (LSM) can be used to study and quantify the impact of anthropic processes on the continental water cycle. Therefore, it is necessary to have good quality forcing and physiographic data, including a correct representation of agricultural covers, irrigation methods and actual irrigated areas. 

This work presents four datasets, at a spatial resolution of 1 km, that have been prepared to simulate irrigation-related processes using a LSM over the Ebro basin, the largest Mediterranean Spanish basin, where irrigated agriculture has a large impact on the water cycle. These datasets are: (1) a land cover map, (2) an actual irrigated areas map, (3) a map of irrigation methods per area, (4) and a meteorological forcing dataset.

The most recent version of the ISBA LSM, in SURFEX v9, contains an improved irrigation scheme (Druel et al., 2021), which requires the also recent ECOCLIMAP-SG land cover map (Druel et al., 2021). We validated ECOCLIMAP-SG over the Ebro basin, using SIGPAC data (Agricultural Plot Geographic Information System) provided by the Spanish Ministry of Agriculture, Fisheries and Food. The results showed low F1-score values, indicating a poor representation of agricultural covers. The comparison also showed that ECOCLIMAP-SG overestimated the irrigated surface. Therefore, it was decided to improve the ECOCLIMAP-SG Land Cover Map and create a new map of actual irrigated areas over this basin.

For the improved cover map, SIGPAC information was used. Each agricultural plot was classified, assigning to the informed cultivated species its correspondent ECOCLIMAP-SG cover and replacing it in the original map. The actual irrigated areas map was elaborated combining SIGPAC information of plots prepared for irrigation with data from LAI increments computed for two Summer days (20/08/2017 and 10/08/2019) by LDAS-Monde (Albergel et al. 2017). LDAS-Monde is a tool based on SURFEX able to assimilate satellite-derived LAI from the Copernicus Global Land service in ISBA. The irrigation method map was generated using a simple approach. The irrigation districts were classified between traditional and modernized. In traditional areas, the irrigation method was set to surface irrigation. In modernized areas, plots with herbaceous crops and trees were assigned to sprinkler and drip irrigation respectively. 

In addition, a new version of the SAFRAN meteorological forcing (Vidal et al. 2010, Quintana-Seguí et al, 2017), was developed. For this project, observations from two different sources (Spanish Meteorological State Agency and Catalan Meteorological Survey) were obtained, together with ERA5 data, which is used as first guess (for all variables except Precipitation). SAFRAN has been used to generate forcing data for Precipitation, Temperature, Wind Speed and Relative Humidity.  

The forcing dataset sensitivity has been tested by comparing two SURFEX simulations performed using the new SAFRAN forcing dataset, one with the original ECOCLIMAP-SG maps and another one using the new land cover, actual irrigated areas, and irrigation methods maps.

This work is a contribution to the LIAISE campaign, through the IDEWA project (PCI2020-112043).

How to cite: Barella-Ortiz, A., Quintana-Seguí, P., Dari, J., Brocca, L., Altés, V., Villar, J. M., Paolini, G., Escorihuela, M. J., Bonan, B., Calvet, J.-C., and Tzanos, D.: Improved SAFRAN forcing and ECOCLIMAP-SG datasets to simulate irrigation over the Ebro basin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7834, https://doi.org/10.5194/egusphere-egu22-7834, 2022.

Northern Java coasts of Indonesia is dominated by unconsolidated Holocene alluvial deposits. Anthropogenic stresses on the area has lead to land subsidence at various rate relate to the deposition systems. This paper review reports on land subsidence in the area using the formal phrase as well as terms related to the phenomenons appeared in coastal communities. We found the formal phrase appeared decades after coastal communities has considered the impact without knowing the physical phenomenon. In addition to that, research agencies have been focusing on monitoring while national government bodies focused on mitigation infrastructures. To fill in the gap, we suggest flood risk study will help the efforts to bridge both activities. This will help local and national government to prioritize activities in to overcome negative impact of land subsidence.

How to cite: Budiyono, Y., Melati, D. N., Khaerani, P., Yuliana, D. K., Riyandari, R., Riyalda, B. F., and Colombijn, F.: Review on land subsidence and socio-hydrology of northern Java, Indonesia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8170, https://doi.org/10.5194/egusphere-egu22-8170, 2022.

Human pressure on surface water is increasing globally, especially on river systems. Future scenarios of urban population growth anticipate an overexploitation of surface water resources in the proximity of cities, which in turn will produce environmental, social, and economic impacts whose effects are going to influence increasingly larger areas. Therefore, it is crucial to gain a better understanding of the dynamics of interaction between human settlements and surface water, to find a balance between urban planning and water management policies that ensure water conservation and ecosystem protection. In this study we assess the driving role of urban areas in the spatial distribution of surface water losses across the contiguous United States (CONUS). In particular, we analyze the frequency of occurrence of surface water loss as a function of distance from urban areas using remote sensing data and we define a distance decay model that reproduces the observed spatial behavior. We find that the frequency of surface water loss declines as the distance from urban areas increases and we successfully model this spatial trend with an exponential probability distribution function. Moreover, we observe distinct decay patterns of the frequency of occurrence of surface water loss associated to the main climatic conditions of the CONUS, as surface water losses are more concentrated around urban areas in regions with a temperate and continental climate, while they result to be more widespread over greater distances in regions with an arid climate.

How to cite: Palazzoli, I., Montanari, A., and Ceola, S.: Spatial distribution of surface water losses from urban areas across the contiguous United States, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8511, https://doi.org/10.5194/egusphere-egu22-8511, 2022.

At the local and sub-regional levels, human-water systems are bound by regional constraints that are influenced by connected internal politics associated with particular socioeconomic conditions. This implies that any multi-scale scenario framework must account for the many scales at which socioeconomic change will manifest. In this study, we developed a series of localized shared socioeconomic pathways (SSPs) by downscaling global SSPs as boundary conditions integrated with climate change pathways (RCPs) to construct a narrative scenario development process that incorporates both a multi-scale (top-down) and a bottom-up (co-production) approach. To obtain insight into human-water systems in developing countries, the study focused on the extensive irrigated portions of Pakistan's central-northeastern Rechna Doab watershed, which served as a case study for a typical multi-stakeholder system. Our developed localized narrative SSPs served as the basis for evaluating the probable consequences of socioeconomic and climatic change at the local level across a variety of socioeconomic possibilities. These estimates provide information on the likely future consequences of socioeconomic and climatic change and the performance of various adaptation measures. Additionally, the localized narratives are designed as a starting point for downscaling projections of critical processes and variables such as population increase and economic development. By analyzing the localized SSPs narratives using a regional integrated assessment model, significant future changes in these critical socioeconomic and environmental variables are predicted, assisting decision-makers in exploring and developing appropriate policy interventions and adaptation strategies. These estimates are used to model and quantify the local consequences of the human-water system on social and environmental issues (e.g., farm income, crop yields, water demands, and groundwater resource depletion). Our findings show that even with modest socioeconomic advances (e.g., technology, policies, institutions, and environmental consciousness), water security is likely to decline, and environmental degradation (e.g., groundwater depletion) will exacerbate. The suggested framework makes it easier to establish future adaptation plans that take regional and local planning and socioeconomic factors into account.

How to cite: Alizadeh, M. and Adamowski, J.: Multi-scale Scenarios for Local Climate Change Policies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9025, https://doi.org/10.5194/egusphere-egu22-9025, 2022.

Climate change and socio-economic development are putting water resources under increasing pressure, even in what are so far seen as ‘water-rich’ countries. At a regional scale, the water resources present in groundwater, soil water and surface water are often used for various functions, including nature, agriculture and drinking water production. Local changes in water management or land cover can potentially affect all these functions. Therefore, ensuring a sustainable water availability requires an integrated understanding of the interactions in the water system. However, regional water systems, that often include a wide range of water pathways and functions, can be complex to grasp and time-intensive to study in detail. There is therefore a need for exploratory methods that provide a fast and comprehensive overview of the interactions in regional water systems. This provides a valuable first step to direct research and management efforts.  

In this study, we have developed an exploratory water system analysis method using a case study in the south of the Netherlands. The case study area supports groundwater-dependent nature areas, agriculture, drinking water production and urban land use, which may face increasing pressure in the future. Several adaptation measures have been proposed, including restoration of natural brook systems, enhancing groundwater recharge and changing extraction regimes. As a first step, we developed quantitative visual overviews of the water system under both average and dry conditions, using a combination of a groundwater model and field data. Next, we used simplified analytical functions to assess the potential effects of several proposed measures on water stores and fluxes in the water system. Together, these analyses provide an overview of the main system drivers and potential threats to water availability. In addition, they help to identify which potential solutions are promising for further exploration. The results can be used to guide further research and cooperation in the area towards a sustainable water system. In addition, the methods can be easily applied to other regions and scales.

How to cite: Brakkee, E., van Huijgevoort, M., and Stofberg, S.: Grasping water availability at regional scale: development of exploratory methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9413, https://doi.org/10.5194/egusphere-egu22-9413, 2022.

The success of climate adaptation actions relies on the availability and quality of information, especially in climate-sensitive sectors such as tourism, agriculture, and river management. Over the years, researchers have highlighted how climate services providing such key information should focus on end-user needs to bridge the usefulness-usability gap. Thus, overcoming this dichotomy will enable the effective use of climate services in adaptation initiatives, especially at the local scale. In this study, we present the basis for a conceptual framework identifying the balancing and reinforcing feedbacks in a coupled human-climate system, with a focus on hydrological risks, i.e. floods and droughts. The analysis is based on system dynamics conceptualization and builds upon data from various living labs (i.e. case studies) across Europe. The framework is presented as a causal-loop diagram and emerging behaviors of the system are described using system archetypes. The proposed framework highlights the importance of understanding feedbacks between climate information and adaptation options when designing user-centered climate services. Moreover, it sheds a light on usefulness of system dynamics as a tool for informing the planning of effective adaptation actions while building resilience.

How to cite: Biella, R., Di Baldassarre, G., Brandimarte, L., and Mazzoleni, M.: Conceptualizing feedbacks between climate services and adaptation actions across various European contexts., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9459, https://doi.org/10.5194/egusphere-egu22-9459, 2022.

Drought is the natural hazard producing the most significant impacts on the agricultural sector. In the Mediterranean area, drought-related losses were estimated at approximately 9€ billion/year and this value is going to increase in future climate change scenarios. In this context, implementing proper risk reduction strategies and effective water resources management is fundamental in coping with drought-related water crises.

In this study, a survey has been proposed to farmers of the Po Valley (Northern Italy), in order to identify past drought and heatwaves events that hit their cultivations and to know the strategies implemented to cope with those events.

Farmers were asked to answer questions about the use of irrigation during past droughts and heatwaves, the preferred irrigation strategies during water crises (i.e., irrigate at night, irrigate a reduced area to full irrigation, crop prioritization, etc), the decisional criteria they adopted to establish when to start irrigation during a drought and the availability of insurance coverage.

Past droughts have been identified using the Standardized Precipitation and Evaponstrspiration Index (SPEI) and compared with the ones identified through the survey, highlighting two main drought events: the first one occurred in June 2003 and the other one in August 2019. This last event has been analysed in detail. Survey’s results reveal that, even if the 2003 event was more severe than that one in 2019, since all the farmers decided to irrigate their cultures during the 2003 drought, yield reduction was less than in 2019, when half of the farmers decided to not irrigate their crops during the drought event. In particular, the mean yield reduction for farmers who irrigated their crops during drought events was 35% less than for those who decided to not irrigate.

It was also found that droughts occurring in different plant growth stages have caused very different economic damages in terms of yield reduction, the amount of water resources allocated, and thus the irrigation expenses.

Regarding insurance coverage and the corresponding farmers’ grade of satisfaction, the survey’s responses revealed that farmers who applied irrigation didn’t acquire insurance coverages, and farmers who haven’t used irrigation trusted more on insurance.

How to cite: Bonaccorso, B., Borzì, I., Monteleone, B., and Martina, M.: A survey-based evaluation of farmers’ drought risk reduction strategies in the Po Valley (Northern Italy), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11981, https://doi.org/10.5194/egusphere-egu22-11981, 2022.

Impacts and trade-offs between society and hydrological processes cover a wide range of issues, for which climate, geography, environment, cultural context, economy, and society altogether result in largely different coevolution schemes and current scenarios. This work presents a selection of case studies addressing the Panta Rhei Decade’s goals and discussions, that cover representative examples to assess future challenges of sociohydrology to be included in the Panta Rhei Book results. As a follow-up of the work progress presented in previous conferences, we focus now on each storyline to highlight their contribution to the Panta Rhei decade’s work and impact on future reflections, and pathways.

Specifically, some similarities and major divergences are assessed between local cases across geography and topics in a preliminary attempt to identify the key conclusions of this paradigm and the most relevant sectors dealing with socio-hydrological processes now, and in the future. These results pave the line towards the final lessons learnt from this process, to be presented in the XXIst Scientific Assembly of the IAHS.

How to cite: Polo, M. J., Vail, C., Penny, G., Gunda, T., and Montanari, A.: Contribution of local examples of co-evolution of society and hydrology to address current and future challenges of sustainability in the context of the Panta Rhei Book, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12216, https://doi.org/10.5194/egusphere-egu22-12216, 2022.

Linear infrastructure such as roads, bridge crossings, protective dams cause significant changes of the floodplains topography and flow characteristics. To estimate the anthropogenic impact on the changing of inundation characteristics we applied two-dimensional hydrodynamic modeling approach. The study is focused on wide populated floodplains areas of the Ob River near Surgut city (Western Siberia, Russia), Lena River near Yakutsk city (Eastern Siberia), Amur/Zeya Rivers near Blagoveshchensk (Far East). STREAM_2D software (authors V. Belikov et al.), which is based on the numerical solution of two-dimensional Saint-Venant equations on a hybrid curvilinear quadrangular and rectangular mesh, and includes sediment transport and ice modules, was used for the simulations. Detailed topography and bathymetry data, obtained as results of field surveys, were used for model setup. All linear infrastructure in river channels and floodplains, including dams, cities embankments, existing and under construction bridges, road embankments were taken into account in the model grid and relief. Second version of the model relief was constructed excluding infrastructure. Calibration and verification of the model were performed for modern conditions using data of field surveys and data of gauging stations. Additional verification of simulated flooded areas and the water level in ungauged reaches was done using high resolution satellite optical images and satellite altimetry measurements. For impact analysys two modeling scenarios were considered for each key area: modern conditions of flow with all infrastructure and natural conditions without any constructions. More pronounced effect of the infrastructure on the flooding zones was identified for the floodplains of Amur/Zeya Rivers near Blagoveshchensk and Heihe cities: the area of flooding in modern conditions decreased by 10%, which led to an increase in the average depth of flooding by 10%, and the average flow velocity in the modeling area by 2-5%. Significant backwater effects due to linear infrastructure on the floodplains were identified for the Ob River, water levels upstream the existing bridge transect can rise more than 0.5m and observed at a distance of more than 30 km.

The numerical experiments were designed within the framework of the Governmental Order to Water Problems Institute, Russian Academy of Sciences, subject no FMWZ-2022-0001. The Ob River floodplain model was adopted with the financial support of RSF № 22-27-00633.

How to cite: Krylenko, I., Belikov, V., Golovlyov, P., Surkov, V., Zakharova, E., and Zavadskii, A.: Impact of linear infrastructure on floodplains on inundation characteristics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12234, https://doi.org/10.5194/egusphere-egu22-12234, 2022.

How to cite: Jonsson, E., Lindersson, S., and Di Baldassarre, G.: Global impacts of dams and reservoirs on hydrological droughts, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12594, https://doi.org/10.5194/egusphere-egu22-12594, 2022.

Agricultural use of pesticides helps control a range of pests and diseases that threaten crops, thereby avoiding yield losses and improving the quality of the food produced. However, pesticides applied on agricultural fields dissipate with time. The export of pesticides and their transformation products after application from the agricultural fields threatens the water quality of aquatic systems in many world regions.

Climate change is further expected to intensify pest pressures and potential pesticide use by affecting agriculture in many ways. Changing climatic conditions can increase pesticide leaching due to increased and frequent rainfall, higher degradation rates, or higher temperatures or soil moisture contents. The indirect effects are changes in land use, the timing of crop cultivation, selection of other crop types, new pests and changed pest behaviour, etc. Additionally, several socio-economic factors influence pesticide use at the farm and national level, including regulation and legislation, economy, technology and crop characteristics. In order to better understand the pesticide risk to surface waters in the future, we aim to understand the influence of both climate and socio-economic change on pesticide use and fate.

Various catchment-scale models are available to assess pesticides and their impacts on water bodies. However, most modelling approaches solely concentrate on the total amount or concentration of pesticide exported from a catchment and do not necessarily analyse the future change of pesticide and transformation products. We propose an integrated modelling framework to answer the research questions: What are the current significant climate and socio-economic drivers influencing pesticide use and emissions? How can climate change influence pesticide and transformation products emission trends? How will socio-economic change influence pesticide emissions?

The integrated modelling framework helps to include adapting agricultural production to climatic (e.g., temperature, precipitation) and socio-economic drivers (e.g., land use, crop type, pesticide regulation) and quantifying pesticide emissions with the Zin-AgriTRA pesticide fate model. The ZIN-AgriTra is a catchment scale reactive transport model which can simulate agrochemical and transformation products exported from agricultural catchments. We use the Eur-Agri-SSP scenarios that extend and enrich the basic Shared Socio-economic Pathways with a regional and sectoral component on agriculture to explain the socio-economic change and climate projections for Representative concentration pathways to adopt climate change scenarios.

The integrated modelling framework links the future scenario results from independent, standalone models that present crop rotation, land use, pesticide regulation and climate to the pesticide fate model (Zin-AgriTRA). The framework is applied to an agricultural catchment in Burgenland, Austria, to quantify pesticide pollution under future climate and socio-economic change up to 2050.

How to cite: Nagesh, P., Gajraj, R., Eitzinger, J., and C. Dekker, S.: Modelling the impacts of climate and socio-economic changes on pesticide use and fate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12615, https://doi.org/10.5194/egusphere-egu22-12615, 2022.

Water extraction in Bengaluru, India's fastest expanding metropolis, entirely depends on its ~500000 wells in a crystalline rock aquifer, of which an unknown number has been abandoned and the level of others has sunk to depths of 450 meters below surface. Recent research has highlighted the spatial heterogeneity and questioned the reliability of water level data in these settings. To fill existing knowledge gaps on the likely over-extraction of groundwater as a vital resource we used a socio-hydrogeological approach of front-lining local hydrogeologists to collect primary data on the spatio-temporal evolution of well depths across the city. Our data show that over the past 60 years borewell depth has increased significantly while water yields have remained unchanged, indicating that digging deeper wells is unsustainable. Using camera inspections of 56 wells in a 2.1km² catchment of industrial land use in Electronic City of Bengaluru, we noted that water levels in the wells are largely determined by rock fractures, not by well depth. Our data show that increased borewell depths is a good signal of declining water levels in Bengaluru’s aquifers. Analysis of δ¹⁸O and δ²H signatures of groundwater samples across all depths followed the local meteoric water line indicating recent recharge, implying that drilling deeper only increased the borehole volume and did not tap into newer water sources.

How to cite: Kulkarni, T., Gassmann, M., Kulkarni, C., Khed, V., and Buerkert, A.: Assessing the groundwater sustainability of Bengaluru megacity, India, through the lens of socio-hydrogeology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2135, https://doi.org/10.5194/egusphere-egu22-2135, 2022.

Coastal Mediterranean lagoons are very often groundwater-dependent hydrosystems, however their hydrogeological functioning is poorly known, damaging their management. Socio-hydrogeology allows, in an inter-and transdisciplinary way to clarify the relationships linking human activities and groundwater status. Those interactions within the watershed, combined with consumption patterns of the population, and sanitation defects can generate processes leading to pollutant fluxes with impacts on surface water, groundwater and lagoon water quality. This approach integrates both social and economic components into hydrogeological investigations.

The Biguglia lagoon watershed (Northern Corsica, France) has been chosen as a pilot site. Indeed, significant nitrate content, emerging compounds, and pesticides have already been observed in the lagoon waters, but their origin still needs to be specified, both in terms of source and dispersion modalities.

The aim of this study is to (1) assess the link between groundwater quality and the anthropogenic pressures on the watershed, (2) understand water users’ and the stakeholders ‘perception and knowledge of the watershed and the local territory, (3) identify the origin of pollutions detected in the lagoon’s water.

In this purpose, a field sampling was led in spring 2021, combining several tools useful for the knowledge improvement of the hydrogeological functioning and the tracing of anthropic pollutant fluxes. Investigations with structured interviews was administered to 32 water users and 16 local stakeholders involved in the monitoring assessment, to determine the land use evolution since 1950’s to present and aiming at identifying past and present uses of the water resource over the watershed. At the same time, a multi-tracer water sampling, combining physico-chemical parameters, major ions and trace elements as well as, stable isotopes of the water molecule was carried out on 53 points (lagoon, rivers, canals waters, groundwater), of which 21 samples were also analysed for a set of pesticides (screening of 240 molecules).

Pesticide’s analysis show that the study site is affected by agricultural pollution. Indeed, neonicotinoid insecticides, extensively used worldwide, have been found on the sampling points with significant concentrations. Those pesticides are mainly used in fruit, vegetable and cereal crops. The field survey, the questionnaire and the sampling campaign have allowed to identify and confirm the presence of these cultures on the study site. In the same way, benzotriazoles, perfluorinated acids (PFAs) and DEET (insect repellent) have also been detected. They are related to the consumption habits of the population on the watershed.

Geochemical analysis correlated with the social analysis and the land use analysis permitted to better constraint pollution sources, evidencing two main sources: sanitation defect and agriculture activity.

The socio-hydrogeological approach is essential to improve the knowledge of the Biguglia lagoon hydrosystem. The purpose of this work is to offer a new functional diagram of the area, including the space-time continuum of anthropogenic impacts within the watershed. This new knowledge will help local stakeholders towards the recovery of a good geochemical and ecological status for the lagoon brackish water body of Biguglia.

How to cite: Crayol, E., Huneau, F., Garel, E., Re, V., Mattei, A., Santoni, S., and Pasqualini, V.: Socio-hydrogeological approach to identify contaminant fluxes towards groundwater-dependent hydrosystems, case of the Biguglia lagoon (Corsica, France), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3412, https://doi.org/10.5194/egusphere-egu22-3412, 2022.

Developing green infrastructures (GIs) for rainwater harvesting has prevailed in many arid regions, which requires a new water management framework. This paper focuses on a water policy - water trading scheme – design and analysis for integrated green infrastructures and water resource management in a watershed that consists of multiple urban areas. A multiagent model bringing together urban water management and GIs planning models for multiple water managers with hydrological models is proposed to show 1) what the optimized water trading scheme is, 2) how the scheme would affect watershed socio-hydrologic environments, and 3) what the role of GIs in the scheme is. In the model, the water trading scheme design depends not only on the hydrologic dynamics of watershed caused by GIs and but on the social interactions between watershed and multiple urban managers. The proposed model is applied to the Colorado River Lower Basin, which is one of the USA's aridest regions and is planning water trading. Results indicated that a water-trading scheme effectively allocates limited water resources with a minimized system cost in the study area. Results also show that developing GIs to use rainwater resources might further reduce the cost induced by the water trading scheme. However, it might also exacerbate water resource allocation inequity among water users. These findings can help decision-makers design the associated water policy to support sustainable watershed development in arid regions.

How to cite: Zhang, M. and Chui, T. F. M.: Modeling water trading to support integrated green infrastructure and water resources management in an arid watershed, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3487, https://doi.org/10.5194/egusphere-egu22-3487, 2022.

Shallow groundwater is usually more accessible than surface water in remote and rural areas due to the infrastructure cost to collect and allocate surface water on dispersed communities. However, the absence of a proper hydrogeological characterization of the aquifer system added to the lack of groundwater infrastructure and maintenance, technical capacity, and governance has not allowed the development of sustainable use of local groundwater resources in different territories worldwide.

We propose an interdisciplinary approach to determine the risk of a household experiencing water shortage due to depletion of the aquifer, degradation of the water quality, not access to the water point, or sustainable functionality. Three main parameters were defined: Closeness (determined by geographical parameters and easily computed using GIS), Availability (determined by hydrogeological parameters that can be assessed from a groundwater model), and Sustainability (differentiating between software functionality and hardware functionality (Bonsor, MacDonald, Casey, Carter, & Wilson, 2018), the former analyzed through Multiple Factor Analysis. Each of these three factors range between 0 and 1, and their product provides an index that can be used to map the risk of individual households.

An application case in Kwale County, southeast coast of Kenya, is presented, where community handpumps are the main water supply system. The novelty of the index relies on the combination of groundwater model outputs with household data, which allows the generation of time-dependent risk indexes that can be calculated for several scenarios depending on the data available. In this case, we present three scenarios, one involving the potential malfunctioning of a percentage of the existing handpumps, and two other ones dealing with extreme climate scenarios, all of them designed to test the resilience and applicability of the proposed index and their applicability for decision making.

Acknowledgements: This work was funded by the Centre of Cooperation for Development of the Universitat Politècnica de Catalunya. We want to thank UPGRO and Gro For Good projects for their support and collaboration in acquiring available data.

References: Bonsor, H., MacDonald, A., Casey, V., Carter, R., & Wilson, P. (2018). The need for a standard approach to assessing the functionality of rural community water supplies. Hydrogeology Journal, 26(2), 367–370. https://doi.org/10.1007/s10040-017-1711-0

How to cite: Cid Escobar, D., Folch, A., Ferrer, N., and Sanchez-Vila, X.: Combining groundwater numerical modelling and social sciences to assess water access in developing countries rural environments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4065, https://doi.org/10.5194/egusphere-egu22-4065, 2022.

The Galápagos Archipelago (Ecuador) is traditionally considered a living museum and showcase of evolution. The rich biodiversity and distinctive environment attract thousands of visitors every year. However, this tourist flow exerts continuous pressures on the natural environment, and on water resources in particular, to the detriment of the local population who is faced with the challenges of accessing safe and sustainable drinking resources.

For this reason, over the years numerous projects, especially in the context of international cooperation activities, have tried to assess the impact of anthropogenic activities on the water quality and quantity in the islands. Unfortunately, the lack of coordination among all these projects did not allow to carry out continuous monitoring and, above all, to obtain homogenous and consistent time series of the measured hydrogeochemical parameters.

For this reason, in the framework of a joint technical cooperation project (“Health protection and prevention of anthropic pollution risks” in the Island of Santa Cruz” financed by Veneto Region, Italy; CS2012A19) a comprehensive assessment on water quality data (physico-chemical parameters, major elements, trace elements and coliforms) collected since 1985 in the Santa Cruz Island was performed. Results revealed the need of optimizing monitoring efforts to fill knowledge gaps and to better target decision making processes. All data were therefore standardized, homogenized and collected in an open database, accessible to all water stakeholders involved in water control, management and protection in the island. 

The information gathering activity also revealed the lack of coordination between the stakeholders themselves and the presence overlapping interests towards water resources, which represent an obstacle for coordinated actions targeted to sustainable water resources management in such a fragile environment. 

Therefore, under the guidance of the Santa Cruz Municipality, a Water Committee was established to foster the coordinated action among the water stakeholders in the island. The latter range from national to local authorities (e.g. National Water Secretariat, Ministry of Agriculture, Ecuador Naval Oceanographic Institute, National Park Galapagos, Municipality), research institutes (Charles Darwin Foundation), bottled water companies and Santa Cruz Households. Within the committee, shared procedures for data collection, sample analysis, evaluation and data assessment by an open access geodatabase were agreed collectively and tested in the field. Joint monitoring in the island can optimize the efforts for water quality assessment and protection, and improve accountability and outreach towards civil society and water users. Such a coordinated action can also ensure that international cooperation activities carried out in the island will respond to the real needs of the local population, and results will contribute to the long-term protection of the scarce water resources in the island.

Overall, results of the project revealed the high potential of adopting transdisciplinary approaches in complex, multi-stakeholder, framework typical of small island states.

How to cite: Tringali, C., Rizzi, J., Re, V., Tuci, C., Mancin, M., Mendieta, E., and Marcomini, A.: Insights from a transdisciplinary approach for water quality monitoring and multi-stakeholder management in the island of Santa Cruz, Galápagos (Ecuador), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4383, https://doi.org/10.5194/egusphere-egu22-4383, 2022.

Groundwater resources in African drylands are important sources of freshwater but are under pressure due to population growth and climate change. It is therefore increasingly important that groundwater resources are managed in a sustainable way. Development of IWRM plans are ongoing in (semi-)arid African countries with support from national governments, NGOs and consultancies. This presentation aims to highlight two case studies in which bio-geophysical and socio-economic data were combined to assist in the Integrated Water Resources Management (IWRM) process: 1) catchment-scale Water Infrastructure Assessment (WIA) in Sudan and 2) assessment of pathways towards sustainable groundwater use in African drylands. Per case study lessons learned and recommended approaches are provided.

In IWRM intervention planning for semi-arid regions a local increase in available water resources is sought after, which can be found in the better use of excess runoff. A balance between water demand and water resources on community level is key and a prerequisite for implementing durable and inclusive interventions that last. The IWRM process starts with a strong knowledge base. In practice, however, the development of a good knowledge base is not simple. Challenges arise in collecting, processing, and mapping results. With hydrogeology, a 3D situation is translated to 2D maps. Socio-economic data are often stored based on administrative boundaries and need corrections for hydrological source-area delineation and seasonal and interannual variations. Population density and water demand change over seasons, following crop cycles and livestock migration patterns. Looking at local water availability, rainfall and surface water flows are becoming more variable and less reliable. Therefore, assessment of the rainfall regime and corresponding behaviour and movements of people and livestock is key. For WIAs, yields and usage are often averaged, thus disregarding seasonal changes, even though shallow wells and reservoirs regularly become depleted outside the rainy season. The Sudan case study presents an improved approach for a WIA, that is adaptable and can be applied in semi-arid environments in Africa and elsewhere, in which seasonality and socio-economic dynamics were taken into account.

Both hydrogeologic and socio-economic conditions tend to be quite location-specific. This makes developing a simple blueprint for integrated groundwater management impossible. However, by translating local conditions into regional advice, strategic pathways were developed for the drylands of Africa[1] to support IWRM. The zonal hydrogeological and socio-economic setting determined the main groundwater issues and the potential sustainability strategies. The sustainability pathways describe potential sets of strategies that can be effective in moving towards sustainable groundwater resources development and use. While these pathways provide insight into regional differences within the African drylands, these cannot be used at local scales. Tailor-made approaches are necessary. In these assessments, remote sensing provides opportunities. Gridded datasets of population density are of great value in water demand assessments on a larger scale. Participatory stakeholder processes also provide opportunities, including group interviews for development of community calendars providing useful information on the occurrence and frequency of natural hazards and water demand.

How to cite: Van der Heijden, A., Waterloo, M. J., Gevaert, A. I., and Benedicto van Dalen, D.: Integration of hydrogeology and social sciences in practice, two IWRM case studies with challenges and opportunities from semi-arid Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7114, https://doi.org/10.5194/egusphere-egu22-7114, 2022.

Managing groundwater resources is challenging because they are difficult to monitor. The application of remote sensing methods has improved our capacity to monitor variability in groundwater storage, as is the case for the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On (GRACE-FO) missions. While GRACE-based groundwater studies to date have covered many places across the globe, perspectives that link scientific studies to policymaking and practices are still limited. Challenges to applying GRACE data into practice result from their coarse resolution, which limits their utility at the smaller scales at which water management decisions are made. Another reason is that the data and related studies can be difficult to use and understand by policymakers and end-users. However, these challenges offer the GRACE scientific community opportunities to communicate with stakeholders, policymakers, and the public in raising awareness around groundwater sustainability issues. This paper addresses three questions: which GRACE data and GRACE-derived products can be useful for groundwater practices and management; how GRACE-derived groundwater messages can be better communicated with practitioners; and how to better operationalize GRACE-derived products for groundwater practice and management. This paper also aims to provide an agenda for the continued use of GRACE and GRACE-FO for the purpose of sustainable groundwater management. To gain insight into these questions, a policy Delphi survey was conducted to collect opinions of both the scientific and non-scientific communities. We made use of target search and snowballing techniques to identify suitable participants who are experienced groundwater researchers or practitioners, and who are familiar with GRACE. A total of 25 participants from around the world were surveyed (14 scientific and 11 non-scientific), and they provided thoughtful responses. We found that both communities acknowledged the potential of GRACE data and GRACE-derived products for groundwater management, and would be willing to collaborate to develop projects for practical applications. Better communication between researchers and practitioners was recommended as a key for the application of GRACE-derived products into practice. Practitioners noted their high demand for reliable data for their management responsibilities, but are more favorable towards locally observed data. The reliability of GRACE at small scales was an issue, even though some robust downscaling methods have been demonstrated down to local scales. The survey showed a desire for more comparison of GRACE-derived products to local measurements to determine whether GRACE products, e.g. downscaled data, can be useful for informing local decisions. Based on the survey, we proposed an agenda that helps to improve the usefulness of GRACE-derived products for practices. This agenda includes scientific recommendations that help to resolve the resolution and technical barriers for local applications, and professional perspectives that bridge the connection between science and policy, and facilitate communication for groundwater management.

How to cite: Xu, L., Famiglietti, J. S., Ferris, D., Huggins, X., Mohan, C., Sadri, S., Sanyal, P., and Wong, J. S.: From Coarse Resolution to Realistic Resolution: GRACE as a Science Communication and Policymaking Tool for Sustainable Groundwater Management, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10542, https://doi.org/10.5194/egusphere-egu22-10542, 2022.

The Limpopo river basin (LRB) is water-stressed and highly susceptible to floods and droughts. The impacts of floods and droughts on water availability and quality is increasing as a result of their increase in magnitude and frequency. The LRB encompasses a large diversity of physical and socio-economical characteristics spread across four Southern Africa countries (Botswana, Mozambique, South Africa and Zimbabwe). This dictates highly heterogeneous physical and human responses, coping mechanisms, and policy frameworks from local to transboundary scales.

Understanding the multidimensional connections that exist between and within flood and drought events and cycles, between various regions across the basin, between physical and social impacts, and between users and decision-makers, is critical to sustainable water resources management and long-term resilience to hydrological extremes.

The Connect4 Water Resilience project has brought together an international multidisciplinary team of hydrologists and social scientists from academia, policy, and practice to investigate the drivers and impacts of floods and droughts, and to promote solutions towards adaptation. In our research we deployed hydrological and geological investigations alongside community and governance interviews and workshops across the LRB to jointly feed in the application of a large-scale transboundary hydrological model of the LRB. Model assessment and future management scenario definition and analysis were implemented collaboratively with stakeholders across the basin, through iterative workshops at local, national, and transboundary scales.

Results so far revealed: (1) the high complementarity of physical (hydrological and sedimentological) and social (community narrative) data to reconstruct spatiotemporal dynamics and impacts of events, which has been crucial to model application in the basin affected by highly fragmented monitoring; (2) the observed increase in floods and droughts magnitude and frequency is not responsible for significant changes in groundwater recharge, suggesting that the general observed groundwater level decline is to be related to increasing abstraction, which in turn amplifies droughts; (3) flood severity and impacts are higher after droughts regardless of rainfall magnitude; (4) mitigation, through anticipatory action and preparation for floods and droughts at policy, user and community level is uneven and inadequately resourced, with generally some forms of preparation to droughts but little for floods; (5) the uptake of forecast and management recommendations from governments is patchy, while extension officers are playing a key role for communication and NGOs for training; (6) local stakeholder expertise and experience brought in during stakeholder workshops were critical to groundwater model conceptualisation, and management scenario definition and analysis; (7) preferred scenarios of management strategies, as collaboratively defined with stakeholders, were highly variable across the LRB countries and sub-regions, including preference for local water management (e.g. temporary flood water storage for subsequent droughts) in upstream upland regions vs large scale strategies (e.g. storage in dams) in downstream floodplain regions; however, hydrological model outputs showed that local/regional strategies have basin-scale (transboundary) impacts emphasizing the importance of transboundary cooperation and management of water resources and extreme events.

Research outcomes are being translated into tailored guidance for policy and practice including feeding in ongoing early warning system development and sustainable water resource management.

How to cite: Comte, J.-C., Artur, L., Bharucha, Z., Chirindja, F., Day, R., Dube, J., Franchi, F., Geris, J., Hussey, S., Makaya, E., Matano, A., Mustafa, S., Nesamvuni, E., Olabode, O., Rohse, M., Taylor, S., Tirivarombo, S., and Van Loon, A.: Adaptation to floods and droughts in (semi) arid transboundary basins: insights, barriers and opportunities drawn from socio-hydrogeological research in the Limpopo river basin, Southern Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11819, https://doi.org/10.5194/egusphere-egu22-11819, 2022.

Drinking water quality is a key component of water security to ensure clean and safe water supplies to achieve the Global SDG6. Yet frequently there are capacity constraints on the adequacy and sustained water quality monitoring programs in LDC contexts, especially in rural areas where resources are more limited and the resident population is more reliant on scattered independent groundwater supplies. In Malawi, knowledge of the importance of water quality has been developing over recent years, necessitating local capacity development for sufficient and sustained water quality monitoring.

International, transdisciplinary, and interdisciplinary research collaboration and capacity-building efforts in rural water quality monitoring can be a vehicle to improve technology development that supports operational monitoring and data reporting in resource-poor settings. However, in cognate fields, similar international partnership models have drawn some criticism of late, because of their alleged tendency to not translate collaboration agreements into demonstrable local capacity gains. We, therefore, link our consideration of these issues specific to our direct input to efforts to create a new water quality testing program in rural southern Malawi in southern Africa in a collaborative research project between the University of Dundee and Fisherman’s Rest, a local NGO in Malawi. Fisherman’s Rest works with rural communities in Malawi, specifically borehole monitoring under the Madzi Alipo program. However, their work lacked the water quality monitoring component, a key element to water security. Using our reflections, we find that the line of critique on international collaborations has some value in terms of thinking about how to advance ‘genuine’ collaboration and capacity-building in water quality monitoring programs as we look to expand our collaboration efforts with Fisherman’s Rest and other stakeholders in rural water quality monitoring in Malawi.

How to cite: Gomo, F., Halliday, S., Chichlowski, W., Chichloska, S., Zaunda, H., and Geddes, A.: Reflections on collaboration and capacity-building for sustainable groundwater quality monitoring in rural Malawi, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12846, https://doi.org/10.5194/egusphere-egu22-12846, 2022.

With a rapid increase in the use of low-cost DIY Arduino solutions, many companies are providing low cost sensors for practically any environmental applications and new users can also benefit from a rich virtual community proposing diverse solutions and tutorials. Nowadays, these new hardware solutions, as well as more robust communication protocols, allow to design very simple almost plug-and-play automatic dataloggers.

In this talk we will discuss three simple datalogger solutions developed in the framework of a field campaign in a harsh proglacial environment in the Swiss Alps. The first solution consists of a simple autonomous datalogger (based on Seeeduino Stalker board) designed to record piezometric heads in wells, even during the winter cold season. The second station consists of two alternative main boards (SODAQ and CubeCell) that were used to develop a connected LoRaWAN automatic weather station to monitor air temperature and precipitation on the glacier. Connected to a base station LoRaWAN gateway (Dragino), this system successfully allowed for a remote monitoring of those parameters.

In a first step, we will quickly go through the main components of each system and detail the basic LoRaWAN architecture. We will then mostly focus on the practical deployment of these solutions in the field and discuss their potential and challenges. We will try to show a live demonstration of their functioning and will insist on the relative technical simplicity and low-cost of such solutions, which could be replicated for many other environmental applications. We will finally discuss the pros and cons of these solutions compared to professional senor companies.

How to cite: Müller, T., Schaefli, B., and Lane, S. N.: A simple low-cost Arduino based LoRaWAN automatic weather station, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-940, https://doi.org/10.5194/egusphere-egu22-940, 2022.

The role of freshwater ecosystems in the global carbon budget has yet to be accurately quantified. Substantial uncertainties remain in estimation of greenhouse gas (GHG) fluxes to the atmosphere due to heterogeneity, temporal variability and small scale of many systems. Additionally, methods to measure dissolved gases involve expensive equipment and/or are time consuming, making fine scale resolution challenging. We here present a self-made low-cost (~ 250 €) sensor unit which can measure carbon dioxide (CO2) and methane (CH4) in the water phase, allowing inexpensive continuous in-situ logging of GHG concentrations with little manpower.

The electronic hardware of the sensor unit is integrated into a polypropylene tubing with two parts: The sensor body is completely waterproof and houses electrical hardware and battery. The sensor head houses the gas sensors and is separated from the water phase by a semipermeable PTFE membrane that is hydrophobic but permeable to gases, thereby allowing the gaseous phase in the sensor head to equilibrate with the water phase.

For CO2, we use a miniature non-dispersive infrared sensor; data from the factory-calibrated sensor can be read via I2C serial communication. For CH4, we use a semiconductor gas quality sensor from the Figaro sensor family. Originally developed for explosion warning systems, these sensors were shown to detect CH4 near ambient concentration. Incorporated into a voltage divider, sensor output voltage can be measured and translated into CH4 concentration. Electrical resistance of this sensor varies in presence of combustible gases but also with temperature and humidity. Additional sensors provide pressure, temperature and relative humidity; and mathematical models fitted to calibration data allow to adjust for reference output voltage at background concentration levels, thereby allowing measurement of CH4 concentration. As a microprocessor, we use an Arduino mini board in combination with a real-time clock, a voltage regulator and a micro SD-card module. The microprocessor is programmed using Arduino´s integrated development environment. Data is stored on the internal SD card and powered by two Li-Ion 18650 batteries connected in series. The sensor is able to measure continuously for 24 hours.

Our low-cost, yet accurate-enough sensor can help to address the major bottlenecks in better quantification of GHG fluxes: continuous measurements to capture natural temporal variability, as well as spatially replicated measurements to map carbon sources and sinks across heterogeneous ecosystems with little investment costs. 

How to cite: Dalvai Ragnoli, M.: RiverRunner: a low-cost sensor prototype for continuous dissolved GHG measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1617, https://doi.org/10.5194/egusphere-egu22-1617, 2022.

The eigenfrequencies of speleothems are fundamental parameters in the study of their response to earthquakes. To study these, the seismic ambient noise is measured by three-component seismic sensors adapted to the geometry of the speleothems. This method is currently being studied in the Han-sur-Lesse cave (Ardenne, Belgium).

A previous study (Martin et al. 2020) was carried out with a SmartSolo IGU-16HR 3C sensor on an imposing 4.5 m tall stalagmite.  This approach demonstrated the feasibility and interest of studying the eigenfrequencies of stalagmites from ambient noise. However, this sensor was too heavy for use on thin and slender stalagmites. The challenge was to find and adapt a lighter sensor able to record very weak movements while being easily adjustable to the various shapes of the stalagmite and securely attachable on these to reduce the impact of the sensor on frequencies measurements and the risks for the fragile structure.

A solution was found by using a Raspberry Shake 3D Personal Seismograph (RS) that initially integrates three orthogonal velocity sensors (Sunfull PS-4.5B), the digitizer, and the Raspberry Pi computer into a single plexiglass box​. The RS has the advantage of being less heavy while being composed of three weak motion geophones. After a comparison study, this sensor gives similar results for eigenfrequency and polarization analyses. However, the use of this new sensor on thin and slender stalagmites requires the creation of suitable support. The RS was split and distributed around the stalagmite. The geophone wiring was modified and extended to separate the geophones from the acquisition system. A 3D-printed support was created to guarantee the orthogonality of the horizontal sensors while reducing the stresses by distributing the weight of the sensor around the stalagmite.

This new configuration allowed determining the eigenfrequencies of 16 thin and slender stalagmites in the Han-sur-Lesse cave (Ardenne, Belgium) and the polarization of the motions associated with these frequencies. Moreover, a two-week recording period allows to measure the daily and weekly variation of ambient noise and transient events like earthquakes, quarry blasts or flooding events in the cave.

Reference: Martin, A.; Lecocq, T.; Hinzen, K.-G.; Camelbeeck, T.; Quinif, Y.; Fagel, N. Characterizing Stalagmites’ Eigenfrequencies by Combining In Situ Vibration Measurements and Finite Element Modeling Based on 3D Scans. Geosciences 2020, 10, 418. https://doi.org/10.3390/geosciences10100418

How to cite: Martin, A., Lecocq, T., Lannoy, A., Quinif, Y., Camelbeeck, T., and Fagel, N.: Measuring the eigenfrequencies of candlestick stalagmites with a custom 3D-printed sensor modified from a Raspberry Shake 3D, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1657, https://doi.org/10.5194/egusphere-egu22-1657, 2022.

Environmental monitoring programs carried out by expeditions or autonomous stations are expensive and only allow measurements for discrete times and locations. After data acquisition most of the data needs hand-operated validation and evaluation before being stored in databases.

For a higher local and temporal resolution on parameters of marine ecosystems, it is planned to extend monitoring programs by attaching a small-sized module, which combines a microcontroller with multiple sensors, to ships of opportunity or any other suitable platform. The modules design focuses on the usability, reliability and interoperability of the derived data by using metadata information and assessing in-situ which data is relevant to be measured and stored.

Using an ESP32, a popular microcontroller, to collect data from OEM sensors of different manufacturers enables a high flexibility in parameters and sensor types. The use of different OEM sensors also allows to experiment with unconventional hydrological sensors. The proposed open source module attempts to collect data as reliable as with conventional monitoring sensor systems.

This approach allows an event based data acquisition, e.g. by adjusting the sampling rate so that only as much data as necessary is measured. In order to provide precise spatio-temporal referencing, the system contains a real time clock and GPS positioning. Moreover, storing the raw data of the sensors alongside their calibration coefficients enables post-processing of the data. The ESP32 transmits the stored data to a server via WiFi or an external LTE module. From this point on, a machine-based validation, flagging of relevant data and basic visualization can assist the evaluation.

With such a module integrating multiple sensors and focusing on the interpretation and use of data starting at the measurement, reliable and pre-evaluated data from hard to access areas can be obtained and contribute to the assessment of dynamic and heterogeneous ecosystems.

How to cite: Björner, M., Naumann, M., Furkert, F., Stepputtis, D., Hermann, A., Gag, M., Eilek, S., and Wagner, R.: Using an open source approach to remotely collect reliable environmental data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2722, https://doi.org/10.5194/egusphere-egu22-2722, 2022.

Measurements of greenhouse gas (GHG) emissions such as carbon dioxide (CO_­­2) play an important role in finding solutions to mitigate the global climate crises. In case of direct treatment comparisons, dynamic manual closed chamber systems are often used to measure the CO₂ exchange and determine the treatment corresponding net ecosystem C balance (NECB). These measurements are commonly accompanied by records of non-destructive spectral vegetation indices such as RVI and NDVI, which can be used to validate obtained CO₂ flux dynamics, to improve the accuracy and precision of determined CO₂ exchange during gap-filling, and for up-scaling purposes. However, commercially available systems for both measurements of CO₂ exchange and spectral vegetation indices are usually cost-intensive, which resulted in a long-term focus in GHG research on the northern hemisphere and the fact that studies on agroecosystems in sub-Saharan Africa as well as Southeast Asia are still being underrepresented.

We present two portable, inexpensive, open source devices to measure in situ 1) CO₂ fluxes using the manual closed chamber method; and 2) vegetation spectral indices, such as NDVI and RVI. The CO₂ flux measurement device consists of a combination of multiple low-cost sensors, such as a NDIR-based CO­₂ sensor (K30FR; 0-10,000 ppm, ± 30 ppm accuracy), a DHT-22 (humidity and temperature) and a BMP280 (air pressure). Sensors are connected to a bluetooth enabled, battery powered, compact microcontroller based logger unit for data visualization and storage.  The handheld, NDVI measurement device consist of a combination of two faced up and two faced down visible (AS7262) and IR (AS7263) sensors, as well as a CCS811 and BME280 for parallel measurements of relevant environmental parameters (e.g., ambient temperature and relative humidity). Sensor control, data visualization and storage is implemented using again a bluetooth enabled, battery powered, compact microcontroller based logger unit. Here, we present the design, and first results of both low-cost devices. Results were validated against results of customized CO₂ and NDVI measurement systems using regular scientific sensors (LI-COR 850 and SKR 1840(ND) and data logger components (CR1000). 

Keywords: CO₂ exchange measurements, closed chamber, NDVI, low-cost open source DIY device

How to cite: Macagga, R., Antonijevic, D., Monzon, R., Bayot, R., Lueck, M., Asante, M., Sossa, L. G., Sanchez, P., Augustin, J., and Hoffmann, M.: Portable low cost devices for in situ measurements of CO2 exchange and vegetation spectral indices: Design and first results., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3517, https://doi.org/10.5194/egusphere-egu22-3517, 2022.

Analyses of the relationships between climate, air substances and health usually concentrate on urban environments due to increased urban temperatures, high levels of air pollution and the exposure of a large number of people compared to rural environments. Ongoing urbanization, demographic aging and climate change lead to an increased vulnerability with respect to climate-related extremes and air pollution. However, systematic analyses of the specific local-scale characteristics of health-relevant atmospheric conditions and compositions in urban environments are still scarce due to the lack of high-resolution monitoring networks. In recent years low-cost sensors became available, which potentially provide the opportunity to monitor atmospheric conditions with a high spatial resolution and which allow monitoring directly at exposed people.

We develop a measurement system for several air substances like ozone, nitrogen oxides, carbon monoxide and particulate matter as well as meteorological variables like temperature and relative humidity, based on low-cost sensors. This involves the assembly of compact, weatherproof boxes with 3D-printed parts. They contain a control unit based on Arduino hardware to gather the sensor data as well as self-designed printed circuit boards (PCBs). A Pycom microcontroller is used for low-power, high-temporal data transmissions by Long-Term Evolution Cat-M1 (LTE-M). These Atmospheric Exposure Low-cost Monitoring units (AELCM) include digital and analogue sensors for air substances and meteorological variables, LCD display, RTC module, uninterruptible power supply, active ventilation, a SD Module as a data black box in addition to an optional internally running FTP server and optional GPS module. A computational fluid dynamics (CFD) simulation is used to evaluate the air flow inside the AELCM units. Sensors are selected based on own analyses as well as according to evaluation and performance in other projects. The measurement equipment is extensively tested using the high-quality measurement unit for meteorology and air substances (Atmospheric Exposure Monitoring System, AEMS) of our research group, located at the Augsburg University Hospital.

How to cite: Gäbel, P., Koller, C., and Hertig, E.: Development of air quality boxes based on low-cost sensor technology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3719, https://doi.org/10.5194/egusphere-egu22-3719, 2022.

Stable water isotopes (δ¹⁸O, δ²H) are used as tracers in hydrology to study the components of the terrestrial water cycle. The stable water isotopes of precipitation are affected by the passage of rainfall through tree canopy, resulting in a change of the tracer signal. Several processes within the canopy are thought to be responsible for this, including evaporation, liquid-vapor equilibration, redistribution, and legacy effects. However, it is currently not clear which processes dominate under which conditions, and predictions of these changes are not yet possible. This is partly due to a lack of high resolution throughfall data, as previous studies usually sampled throughfall in evaporation-reducing bulk containers placed under canopy. Here we propose to hang commonly available cotton products in tree canopy, let them soak up rainfall water, and subsequently measure the stable water isotopes directly from the wet cotton products using the direct liquid-vapor equilibration method in the laboratory. First, four products (two types of tampons, two types of cotton pads) were evaluated in terms of the minimum amount of water drops necessary for a reliable measurement, their price, and ease of handling. Cotton pads had the overall best rating and were therefor hung in a coniferous tree placed in a rainfall simulator. With a fixed rainfall intensity, we tested how long the cotton pads can be left hanging before significant isotopic changes due to evaporation occurred. While cotton pads that were on the outer edge of the canopy showed significant deviations after only half an hour, cotton pads inside the canopy as well as close to the stem could be left hanging for one hour. As a comparison, throughfall was also collected using a bulk sampler under the canopy, and this sample showed no significant changes even after four hours. It can thus be assumed that due to the comparatively low amount of water in the cotton pads (even if soaking wet), evaporative changes of isotope values had a stronger impact on the remaining water compared to the bulk throughfall sampler. This study presents first laboratory results and further tests, in the laboratory or in the field, are called for.

How to cite: Stockinger, M., Ziesel, G., and Stumpp, C.: Using cotton pads to sample the stable water isotopes of throughfall inside tree canopies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3888, https://doi.org/10.5194/egusphere-egu22-3888, 2022.

How to cite: Diederen, D.: Global surface and groundwater levels - hand measurements with a mobile app., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5446, https://doi.org/10.5194/egusphere-egu22-5446, 2022.

Efficient water use is a must for sustainable agriculture, driving the need for affordable soil moisture sensors to guide irrigation timing. Sensors are limited by cost, maintenance and the need for wires for data capture and charging.  We are developing low-cost, long-life, wireless in-situ soil sensing networks, which can potentially enable a much higher sensor density for large farmland or intense research plot monitoring. This custom soil sensor is made from off-the-shelf electronics and consumes approximately 10x less energy per measurement, compared to commercially available sensors. Here we present our new sensor technology, while also investigating its repeatability and accuracy in controlled conditions and comparing it to that of commercially available soil moisture sensors. The final application of the custom soil moisture sensor is an underground in-situ sensing network, which will be enabled through wireless powering and telemetry systems implemented on autonomous vehicles, both ground and aerial.

How to cite: Marin, M., Elsakloul, F., Sanchez, J., Arteaga Saenz, J. M., Boyle, D., O’Keeffe, J. H., Goel, R., Hallett, P. D., Mitcheson, P. D., Norton, G. J., Yeatman, E., Young, D. J., Zesiger, C., and Roundy, S.: Low energy and cost soil moisture sensor technology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5620, https://doi.org/10.5194/egusphere-egu22-5620, 2022.

Solar panels and batteries are commonly used to power autonomous instrumentation in remote locations. The use of solar power in the polar regions needs a special approach to the system design because of the need to store sufficient energy to cover the period of total darkness in the winter. In this presentation we review the key principles of solar power system design for the polar regions and provide a spreadsheet model to aid the design process. We demonstrate the importance of assessing the power consumption of ancillary electronics (such as solar regulators and low-voltage disconnect units), as this can often be greater or equal to that of the instrument itself. Consequently, the choice of solar regulator (and other ancillary devices) can have a major impact on the size of the battery required for successful operation. Controlled laboratory measurements  of power consumption for fourteen commonly-used models of solar regulator demonstrated that there can be disparity between the manufacturer’s specifications and measured power consumption, so we assess the most suitable  systems for low temperature, long-term deployment at polar latitudes.

How to cite: Prior-Jones, M. R., Bagshaw, E. A., Nylen, T. H., Pettit, J., and Carpenter, P.: Design of solar power systems for autonomous instruments deployed in the polar regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7886, https://doi.org/10.5194/egusphere-egu22-7886, 2022.

The ratio between slow or thermal (<2.2 km/s) and fast (>2.2 km/s) neutrons is known to be a good measure of the amount of water present in a radius of about 300m from the measurement. COSMOS detectors use this principle and measure neutrons by means of the helium isotope ³He. COSMOS has been in use for some time now and its large-scale observations are central to bridging the scaling gap between direct gravimetric observation of soil moisture (<<1m²) and the scale at which soil moisture is represented in hydrological models and satellite observations (>100m²). The main sources of ³He were nuclear warheads. The fortunate demise of nuclear weapons has had the less fortunate consequence that ³He has become expensive, leading to a search for more affordable alternatives.

Here, we present laboratory results of a boron-based neutron detector called BLOSM. About 20% of naturally occurring boron is ¹⁰B, which has a large cross-section for thermal neutrons. When ¹⁰B absorbs a neutron, it decays into lithium and alpha particles. Alpha particles can then be detected by ZnS(Ar), which sends out UV photons. Because real-estate is at a premium for most neutron detection applications, most boron detectors are based on relatively expensive enriched boron with >99% ¹⁰B. In hydrology, space is usually less of an issue, so one innovation here is that we use natural boron in a detector that is simply a bit larger than one based on enriched boron but much cheaper. A second innovation, put forward by Jeroen Plomp of the Delft Reactor Institute, are wavelength shifting fibers that capture UV photons by downshifting the wavelength to green. Green photons have a wider angle of total internal reflection and tend to stay in the fiber until they exit at the end. Here, a third innovation comes into play, inspired by Spencer Axani's $100 muon detector, namely the use of simple electronics and silicon photon multipliers (SiPMs).

Because we want to know the ratio between fast and slow neutrons, we need two detectors, one that just counts the thermal neutrons that continuously zap around and through us, and one covered by a moderator that slows down faster neutrons to thermal levels, so that they can be detected. Presently, we can build two detectors for about EU 1000. We expect that after the development of some custom electronics, this will come down to around EU 500. Ideally, we would like to build a network of these detectors in Africa in conjunction with the TAHMO network (www.tahmo.org).

How to cite: van de Giesen, N. and van Amelrooij, E.: DIY Neutron detection: Boron-based Large-scale Observation of Soil Moisture (BLOSM), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9749, https://doi.org/10.5194/egusphere-egu22-9749, 2022.

Plant physiologists have used microscopy to study how leaf anatomy is related to photosynthetic performance and how this relation is affected by environmental conditions. However, leaf anatomy is not invariant over time: small pores on the leaf surface (stomata) open and close within minutes in response to the availability of water, CO₂ and light. Within tens of minutes following a water deficit, cells in many leaves also shrink significantly in volume and the leaf undergoes structural changes as a result of wilting. Gas-exchange setups can monitor changes in photosynthesis and transpiration under such conditions, but classical microscopy techniques are not well-suited to capture the concomitant changes in leaf anatomy for two main reasons. First, available non-destructive microscopy techniques are limited in resolution and imaging depth, making it difficult to analyze changes in anatomy to the required detail. Second, using sectioned fixated samples is known to be associated with tissue shrinkage, swelling or deformation, making estimates of cellular volumes and surfaces prone to artifacts. Moreover, the destructive nature of these techniques makes it impossible to monitor changes in leaf anatomy during ongoing gas-exchange measurements. These limitations hinder advancing our understanding of the relation between leaf anatomy and photosynthesis or transpiration.

Here, we present a novel gas-exchange setup that combines synchrotron-based high-resolution computed tomography (microCT) with concurrent measurements of gas-exchange using an commercially available infra-red gas analyzer. We designed and constructed a novel gas-exchange cuvette with CO₂ and H₂O control that allows for non-invasive monitoring of leaf anatomy in a microCT setup. Custom-built sensors were used to measure light intensity and leaf temperature. At given time points during gas-exchange measurements, 300-500 X-ray projections (100 ms) were taken while the chamber rotated 180°. From this data, a leaf volume corresponding to 0.5 mm² leaf surface was reconstructed at high resolution (0.325 µm per voxel edge).

The setup provides 3D images that can be used to measure the aperture of multiple stomata and the volumes, shapes and surface areas of cells and airspaces within the leaf. We found that the same leaf section can be scanned several times without measurable radiation damage, allowing for the combination of three spatial dimensions with time to create a 4D analysis of the leaf structure. Using poplar, willow and Arabidopsis leaves we studied how leaf anatomy rapidly adjusts after limiting water availability and show that such effects are not limited to the stomatal pore alone. We discuss the issues and pitfalls with the methodology and suggest avenues for future improvement.

How to cite: Tholen, D., Scheffknecht, S., Voggeneder, K., Weiss, E., and Théroux-Rancourt, G.: Leaf Structure and Function in Four Dimensions: Non-invasive MicroCT Imaging During Gas-exchange Measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9801, https://doi.org/10.5194/egusphere-egu22-9801, 2022.

An unknown source of methane (CH₄) was recently discovered under the Kangerlussuaq sector of the Greenland Ice Sheet (GrIS). CH₄ is transported dissolved in meltwater from the subglacial environment to the margin of the ice sheet, where it rapidly degasses to the atmosphere. Existing knowledge gaps concern the magnitude of emissions, seasonal patterns and spatial variations along the margin of the GrIS, which require long-term monitoring and large-scale measurement campaigns at multiple meltwater outlets. A limiting factor for such studies in remote areas is that CH₄ analysers (laser spectroscopy) are power-hungry, maintenance-intensive, and expensive. To overcome these obstacles, we are developing a low-cost, low power sensor for measuring dissolved CH₄ in subglacial meltwater systems in the MetICE project: the WaterWorm.

The WaterWorm is based on a metal oxide sensor (MOS) designed for CH₄ detection (Figaro TGS2611-E00), which is highly sensitive to variations in relative humidity (RH) and temperature. In the WaterWorm, the MOS is encased in a hydrophobic but gas-permeable silicone tube, ensuring a stable and fully saturated headspace (100% RH) during submergence. We calibrated the analogue output (in mV) of the submerged WaterWorm against a reference CH₄ analyser (μGGA, GLA-331, LGR Research) connected to a dissolved gas extraction system (DGES, LGR Research) in temperature-controlled laboratory experiments by stepwise enrichment of the water with CH4. These calibration tests showed that the sensor output (set at two readings per minute) is proportional to dissolved CH₄ at constant humidity and temperature.

During fieldwork near Kangerlussuaq, Greenland, in summer 2021, a field baseline calibration was performed in a meltwater stream on the surface of the GrIS at ambient CH₄ concentrations. WaterWorms were deployed for ten weeks in the meltwater of a small outlet of the Isunnguata Sermia glacier with known CH₄ export and stable meltwater temperatures (0.0 - 0.1°C) to test the sensor under field conditions. Throughout this period, the WaterWorms measured elevated dissolved CH₄ concentrations with diurnal variations that corresponded to similar diurnal variation in gaseous CH₄ measurements performed with the reference CH₄ analyser.

The WaterWorm is a promising and cost-efficient option for the seasonal monitoring of dissolved CH₄ in glacial meltwater. With material costs of only 150€, the WaterWorm can be left unattended in the field and positioned directly at the ice edge. This makes the sensor suitable for a large-scale CH₄ monitoring network along the margin of the GrIS. The next steps involve material tests to build WaterWorms for applications in other aquatic environments and at different water depths.

How to cite: Sapper, S. E., Christiansen, J. R., and Jørgensen, C. J.: The WaterWorm: a low-cost, low power sensor for the detection of dissolved CH4 in glacial meltwater, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9972, https://doi.org/10.5194/egusphere-egu22-9972, 2022.

How to cite: Vergara Niedermayr, B., Antonijevic, D., Monzón, O., and Hoffmann, M.: A novel, low-cost floating chamber design for semi-automatic measurements of CO2 and CH4 emissions from ponds and ditches, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10102, https://doi.org/10.5194/egusphere-egu22-10102, 2022.

Extended droughts are known to cause severe damage to crops. Short-term droughts of two to three weeks that occur in areas with high evapotranspiration demands and soils with low water-holding capacity can also significantly affect crop yields although their impact has not been well quantified. These short-term droughts are sometimes referred to as flash droughts. The timing of flash droughts likely has a major impact on whether or not they result in significant yield losses. An ongoing project funded by the U.S. National Oceanic and Atmospheric Administration (NOAA) is quantifying the effect of flash drought on rainfed agronomic crops and pasture grasses in the southeastern U.S. The project is also developing tools to forecast when flash drought periods result in significant yield losses. This paper reports on the development of a tool for estimating daily crop water use and soil water content for three commonly used pasture grasses of the southeastern U.S. – Bermudagrasses (Cynodon dactylon and C. dactylon´ C. nlemfuensis), Bahiagrass (Paspalum notatum), and Tall Fescue (Lolium arundinaceum). Five rainfed farmer-managed fields in which these grasses are grown for hay were instrumented with capacitance-type soil moisture sensors to continuously measure volumetric water content in 12 cm increments to a depth of 60 cm. These data are used to estimate daily crop water use / daily crop evapotranspiration (ETc) which in turn is used to estimate daily crop coefficient (Kc) values using Penman-Montieth evapotranspiration (ETo). ETo is calculated from the University of Georgia Weather Station Network weather stations located near the fields. The final product is a decision support tool that helps farmers quantify the duration of periods of low soil moisture content. The effect on the yield of these flash droughts is quantified by using the DSSAT CSM-CROPGRO-Perennial-Forage crop simulation model.

Keywords: remote sensing, evapotranspiration, crop coefficient, smart irrigation.

How to cite: Maktabi, S., Gallios, I., Knox, P., Kukal, S., and Vellidis, G.: Developing a soil moisture Decision Support Tool to quantify the occurrence of flash droughts and saturated soil conditions for pasture grasses in the southeast of the United States, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10381, https://doi.org/10.5194/egusphere-egu22-10381, 2022.

Streamflow measurement is essential in hydraulic engineering to develop and manage water resources and ensure they are managed correctly and adequately. Two primary parameters for discharge measurements in natural rivers, namely, the mean flow velocity and cross-sectional flow area at the measurement site, are requisites. The cross-sectional area of the section could be measured using river bathymetric surveys or by using advanced and modern methods such as Acoustic Doppler Current Profiler (ADCP). For mean velocity, numerous ways and tools are available depending on the fact, whether the measurements are taken from a distance (non-contact) or using a contact method (traditional approach). Nowadays, non-contact velocity measurement approaches are becoming more popular as they are less time-consuming and user‑friendly to deal with high flows and rough weather. In contrast, the entropy-based concepts (such as Shannon entropy, Tsallis entropy and Renyi entropy) are utilized to obtain the discharge from the non-contact measurements, which gives better results than the traditional approaches such as the velocity area method. Entropy-based velocity distribution depends on the crucial parameter called entropy parameter (a function of the mean and maximum velocity), which is linked to the channel characteristics such as channel roughness and bed slope. Due to a lack of concrete evidence regarding its variation with the channel characteristics, the entropy parameter was surmised as constant. In this study, the experimental velocity data was collected from a rectangular flume fitted with a mechanical apparatus to change the bed slope. The obtained velocity data was employed to comment on the actual variation of the Shannon entropy parameter for the one such channel characteristic, i.e., channel bed slope. The velocity data analysis depict only a slight variation in entropy parameter. In addition, the discharge error analysis provided a substantial justification for using a unique constant value of the entropy parameter for the whole cross-section can be utilized instead of individual values for each channel bed slope condition.

How to cite: Singh, G. and Khosa, R.: Effect of Channel Bed Slope on Shannon Entropy-Based Velocity Distribution in Open Channel Flow, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-139, https://doi.org/10.5194/egusphere-egu22-139, 2022.

The understanding of groundwater interactions with riverine systems is of utmost importance for ecosystem assessment and management. Diffuse groundwater born nutrients, such as N, P and C contribute significantly to an increase of algae growth in rivers and eventually in estuaries, leading to eutrophication with severe consequences for water quality and ecosystem health. Thus, knowledge of both location dynamics and temporal dynamics of diffuse groundwater discharge areas, as well as the discharging groundwater quantity are required.

Here we provide a multi-methodological approach to gain this information for a large river in Germany, i.e. the Elbe River. We applied complementary methods to a 450 km long stretch including: i) analysis of daily time series of hydraulic gradients between river- and groundwater levels, ii) a flux balance for river segments spanning between neighboring gauging stations, iii) inverse geochemical modeling of the river water composition for each segment, and iv) a Darcy approach as an additional tool based on the hydraulic conductivity of the upper aquifer. The results are manifold, including a spatiotemporal answer to the dynamics and orientation of groundwater interaction with the Elbe.

Groundwater inflow is variable but occurs along the entire river. Areas of high groundwater contribution are located in the upstream mountainous parts, where groundwater makes up to 11% of the total river flow. Further downstream, groundwater inflow decreases, while inversion of hydraulic gradients indicate an immense infiltration of river water into the river banks. Unexpectedly high input of groundwater-like fluids could be detected in the lowland, where geochemical modeling indicated a massive inflow of water in a magnitude of 10% of the total river flow. Given a missing surface and groundwater contribution, an unidentified but apparently large system of subsurface drainage ditches co-exists, which transports water to the Elbe River efficiently during and due to drought-related low flow conditions.

Gaining insight into such a large-scale setting with interfering surface water contributions, effluents of wastewater treatment plants, and diffuse groundwater in- and outflows was possible only by applying the combination of independent geochemical, hydraulic and balancing approaches. With a similar availability of river and well levels and the physical access to the latter, the presented multi-method approach may provide a blueprint for the assessment of other large river systems.

How to cite: Zill, J., Siebert, C., Rödiger, T., Weitere, M., and Mallast, U.: Revealing unexpected sources and quantities of groundwater discharge into major river systems during drought conditions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2218, https://doi.org/10.5194/egusphere-egu22-2218, 2022.

Long series of river discharge data are essential for developing improved river and water management strategies and for coping with water-related hazards such as floods. However, continuous direct measurement of river discharge is practically infeasible. Recently developed electromagnetic and ultrasonic methods can be used for automated (or direct) river discharge measurements; however, they are not widely used because they are expensive and are prone to damage during high flows.

At most gauging sites around the world, a rating curve is used to convert the measured stage into discharge. However, using rating curves is fraught with difficulties, including (a) hysteresis effect during unsteady flow, (b) extrapolation error during high flows, (c) need for regular updating due to change in hydraulic resistance and channel geometry. More recently, methods have been developed for dynamic river discharge estimation by solving governing equations of river flow i.e., shallow water equations (SWE). However, these methods (a) solve SWE in its conservative form, (b) are most suitable for prismatic channels with no lateral flow, (c) require one flow value, and (d) assume channel roughness or calibrate it by using observed stage data from two or three gauging locations. Although, stage data from two or three gauging locations are theoretically sufficient to calibrate channel roughness, in practice error margins are still high due to sub-optimal positioning of gauging stations, and coarse temporal resolution of existing measurement networks.

Therefore, motivated by a need to surmount the limitations in existing methods, we have developed a non-contact, robust, and cost-effective approach for dynamic river discharge estimation. We use an array of bespoke sensors to monitor the river stage at high resolutions and use these stage data to estimate river discharge. We present a methodology to calibrate a hydraulic model of a river reach by only using stage data from a network of such sensors. We use freely available HEC-RAS software as the solver for SWE. We have developed python scripts to control and automate HEC-RAS simulations and estimate river discharge dynamically.

How to cite: Sah, N., Buytaert, W., D. Paul, J., De Stercke, S., and Paschalis, A.: Non-contact, Low-cost Sensor Network for River Stage Monitoring and Dynamic Discharge Estimation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2867, https://doi.org/10.5194/egusphere-egu22-2867, 2022.

Image-based monitoring of rivers is a growing field of research and is being popularized as a technical alternative for discharge, erosion and flood risk estimation applications. Surface velocimetry can also be a way to characterize the turbulence structure of shallow flows, making possible the remote determination of quantities of interest such as dissipation and integral length scales. To evaluate velocimetry methods and data processing workflows, a laboratory facility emulating a river reach was assembled at IST, and monitored using commercial grade cameras, in field-like conditions. In this work the results of estimates of turbulent dissipation and integral length scales using multiple methods are provided, along with a discussion on the differences among methods and possible applications of the derived data in hydrodynamic model parameter calibration and data assimilation. LSPIV and PTV display similar results with regard to velocity estimation and vortex detection. In the estimation of integral lengths, the longitudinal scales are most affected by limitations in the measurement setup, whereas for the dissipation and turbulent viscosity estimates, spectrum methods seem to be less reliable than simpler methods based on dimensional analysis and integral length scales.

How to cite: Zandonadi Moura, L., Ferreira, R., and Aleixo, R.: Turbulence Metrics from Surface Image Velocimetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3049, https://doi.org/10.5194/egusphere-egu22-3049, 2022.

The handling of natural disasters, especially heavy rainfall and corresponding floods, requires special demands on emergency services. The need to obtain a quick, efficient and real-time estimation of the water level is critical for monitoring a flood event. This is a challenging task and usually requires specially prepared river sections. In addition, in heavy flood events, some classical observation methods may be compromised.

With the technological advances derived from image-based observation methods and segmentation algorithms based on neural networks (NN), it is possible to generate real-time, low-cost monitoring systems. This new approach makes it possible to densify the observation network, improving flood warning and management. In addition, images can be obtained by remotely positioned cameras, preventing data loss during a major event.

The workflow we have developed for real-time monitoring consists of the integration of 3 different techniques. The first step consists of a topographic survey using Structure from Motion (SfM) strategies. In this stage, images of the area of interest are obtained using both terrestrial cameras and UAV images. The survey is completed by obtaining ground control point coordinates with multi-band GNSS equipment. The result is a 3D SfM model georeferenced to centimetre accuracy that allows us to reconstruct not only the river environment but also the riverbed.

The second step consists of segmenting the images obtained with a surveillance camera installed ad hoc to monitor the river. This segmentation is achieved with the use of convolutional neural networks (CNN). The aim is to automatically segment the time-lapse images obtained every 15 minutes. We have carried out this research by testing different CNN to choose the most suitable structure for river segmentation, adapted to each study area and at each time of the day (day and night).

The third step is based on the integration between the automatically segmented images and the 3D model acquired. The CNN-segmented river boundary is projected into the 3D SfM model to obtain a metric result of the water level based on the point of the 3D model closest to the image ray.

The possibility of automating the segmentation and reprojection in the 3D model will allow the generation of a robust centimetre-accurate workflow, capable of estimating the water level in near real time both day and night. This strategy represents the basis for a better understanding of river flooding and for the development of early warning systems.

How to cite: Blanch, X., Wagner, F., Hedel, R., Grundmann, J., and Eltner, A.: Towards automatic real-time water level estimation using surveillance cameras, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3225, https://doi.org/10.5194/egusphere-egu22-3225, 2022.

Stream networks are important flow pathways along which water transports solutes, sediments and affects living communities. Field observations in headwater catchments have shown that the networks of actively flowing channels are not static, but rather expand and contract over time, depending on the intensity and timing of hydro-climatic forcing. Until now, however, flowing stream networks (FSNs) have been mapped only sporadically and environmental tracer data to explore the varying stream-landscape connectivity are lacking. Thus, little is known about how and why these networks change and what the implications are for streamflow, water quality and biodiversity. 

To gain detailed insights into the mechanistic links between FSNs and catchment hydrological processes, we investigated two 4-ha head watersheds in the Alptal valley in central Switzerland. We deployed a wireless sensor network in the field to obtain spatially distributed continuous data of flow occurrence. In addition, we conducted multiple mapping surveys using a self-developed mobile phone application. Our data show that the total flowing stream length increased rapidly by more than a factor of 3 during individual rainfall events. This suggests that different water stores become dynamically connected to the stream network and disconnect again during subsequent dry periods. We test this hypothesis by linking short-term changes in FSN length to variations in subsurface water storage and water chemistry. The results help to broaden our understanding of flow intermittency in pre-Alpine headwater catchments, and thus aids in developing effective strategies to protect ecosystems dependent on temporary flow conditions.

How to cite: von Freyberg, J., Bujak, I., Rinaldo, A., and van Meerveld, I.: Monitoring changes in temporary stream networks during rainfall events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4435, https://doi.org/10.5194/egusphere-egu22-4435, 2022.

The operator effect is a prominent error source in image-based velocimetry methods. Video sampling, ortho-rectification parameters, motion analysis parameters and filters can strongly impact velocity and discharge measurements. This has been reported in the literature (e.g. Detert, 2021) and highlighted by the Video Globe Challenge 2020, a video gauging intercomparison (Le Coz et al., 2021). The parameter choices made by the operator must be assisted to contain errors and to make image analysis methods accessible to non-specialists.

An investigation of the operator effect (or parameter effect) in various situations is proposed. The analysis focuses on the LSPIV measurements carried out during the Video Globe Challenge 2020. This contest involved around 15 participants with varying levels of experience, challenged over 8 videos. All the LSPIV measurements were replayed based on the data submitted by the participants. The objective was to identify the most sensitive parameter(s) for each video, based on an extensive analysis of the replayed velocity and discharge results.

The data retrieved were: video sampling rate, number of frames, ortho-rectification resolution, IA and SA sizes, correlation based and vector based filters, surface velocity coefficient (a.k.a. alpha) and transect interpolation parameters. To ensure valuable comparisons, grid points and video sequencing were fixed the same for all the participants. Replaying LSPIV measurements allowed to play with the parameters methodically and to quantify their impact on the measured discharge deviation from the reference.

Several lessons were learned from these analyses thanks to the variety of conditions offered by the 8 videos. A tendency to under-estimate the discharge in case of inappropriate parameters was observed. The influence of the video sampling rate has been noticed in many cases. It turns out to have more impact than the motion analysis parameters. The dataset was used to evaluate the benefit of automated parameters setting tools, e.g. ensemble correlation, automated time-interval, automated video sequencing.

Detert, M. (2021). How to avoid and correct biased riverine surface image velocimetry. Water Resources Research, 57, e2020WR027833. https://doi.org/10.1029/2020WR027833

Le Coz, J., Hauet, A., and Despax, A. (2021). The Video Globe Challenge 2020, a video streamgauging race during the Covid-19 lockdown, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2116, https://doi.org/10.5194/egusphere-egu21-2116, 2021

How to cite: Bodart, G., Le Coz, J., Jodeau, M., and Hauet, A.: Quantifying the operator effect in LSPIV image-based velocity and discharge measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4457, https://doi.org/10.5194/egusphere-egu22-4457, 2022.

Acoustic Doppler Current Profilers (ADCP) are used a lot all around the world to measure discharge in rivers. These instruments measure most of the vertical velocity profile in rivers, but due to technical and physical limitations they cannot measure all the way to the surface or all the way to the bottom. To calculate discharge, the instruments (or software) need to extrapolate data into the un-measured regions. Previously there was no good and available tools to aid the operators in selecting proper extrapolation. In 2010 USGS released the software Extrap, which plots relative velocity versus relative depth for ADCP measurements, and this tool made it way easier to determine the correct extrapolation of data. (Extrap is now a part of Qrev/QrevInt). Before the introduction of Extrap, 80-90% of the ADCP-measurements at NVE used the default power law extrapolation in the ADCP’s standard software (WinRiver at the time), and around 5% used constant at top and no-slip at the bottom. The first if these assumes a velocity profile that is very similar to the logarithmic velocity profile that comes from classical boundary layer theory. The latter one is much steeper (constant) close to the surface.

After starting to use Extrap regularly, 60% of the measurements use the constant/no-slip extrapolation, while 40 % uses the power law extrapolation. This impacts the reported discharge from the measurements by reducing the reported discharge by on average 4% for the measurements using constant/no-slip extrapolation, and data users must be aware, because these measurements eventually form the foundation for the long time, continuous data series for discharge in our archives.

How will a climate researcher react to a 4% decrease in annual run-off from Norway?

How to cite: Florvaag-Dybvik, K.: Climate change or just new software? The impact of Extrap software on ADCP discharge measurements in Norway, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5037, https://doi.org/10.5194/egusphere-egu22-5037, 2022.

The importance of optical measurement methods in hydrology is increasing in the last years. In contrast to conventional gauging techniques, they can be applied remotely, making the measurement safe for humans and equipment, even under difficult measurement conditions. One important hydrological parameter to measure is discharge. Deriving discharge with remote sensing can be done by applying particle tracking velocimetry (PTV) in combination with the velocity area method (VAM). VAM is a standardized and established method in hydrology. For reliable discharge results with the VAM, surface flow velocity measurements and thus trackable particles in the case of PTV usage are required across the entire width of the river cross section, which is not always the case in natural observation conditions. To fill these data gaps several statistical methods were investigated that incorporate information provided at different measurement times but with similar discharge conditions.

In this study, data were collected over longer time periods with different cameras at a gauging station of a medium scale river in Saxony, Germany. Stationary cameras recorded short videos, which are used to estimate the velocity distribution at the water surface using PTV incorporated in the FlowVelo tool (Eltner, 2020), and afterwards, to estimate the discharge using VAM. The obtained discharge time series from different cameras and camera positions were used to analyse the performance of different gap filling approaches. The results were compared to discharge and water level measurements of the official gauging station maintained by the federal measuring agency. They show, that the adjustment to the data of the reference measurements increases significantly by application of the gap filling methods. Next steps are to enhance the presented methods by using targeted data filtering and deep learning.

Keywords: velocity area method, particle tracking velocimetry, camera based discharge estimation

How to cite: Kutscher, A., Grundmann, J., Eltner, A., Blanch, X., and Hedel, R.: Determination of continuous discharge time series based on the optical Particle Tracking Velocity (PTV), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5967, https://doi.org/10.5194/egusphere-egu22-5967, 2022.

Monitoring volumetric flow in arid and semi-arid regions is a major challenge due to their harsh and continuously changing environment (e.g. extreme temperature, severe sand storms). In these regions, hydrological events such as rainfall storms and flash flood events occur intermittently, time between major events may take years. Drainage water courses in these areas are often referred as Wadis, which are ephemeral drainage courses. Wadis are normally dry except after a rain event, often resulting in flash floods events with flood peak values occurring in the first few minutes of the event.

Monitoring the volumetric flow under these environments requires robust devices which record continuously at relatively short recording intervals, e.g. minutes or less, to be able to capture the steep ramp of the flood peak.

On April 2021 a DischargeKeeper, an image-based system for flow monitoring, with a PTZ camera was installed at the Wadi Naqab located in northern United Arab Emirates. The Wadi is approximately 50m wide and has been dry for most of the time. One event occurred at the beginning of January 2022, reaching a peak discharge of 78 m³/s just 15min after water started flowing. In this session we will show the system, its challenges and the results of the event.

How to cite: Peña-Haro, S., Lüthi, B., Düster, R., Hansen, I., Vogel, K., Gad, M., and Magdy, M.: Non-contact volumetric flow monitoring in a semi-arid regions’ Wadi, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6198, https://doi.org/10.5194/egusphere-egu22-6198, 2022.

The quantification of river bathymetry and its change through time is a primary challenge in fluvial geomorphology. Whilst there has been a very rapid development of methods for measuring exposed river morphology, inundated zones remain a problem. The development of cheap UAV platforms and SfM-MVS photogrammetry have been particularly important as these allow low cost, high resolution, and repeat surveys. Researches have now shown that provided that there is a signal of water depth then it is also possible to map inundated areas by adopting, for example, two media refraction correction if there is sufficient bed texture in the imagery. The main problem arises, however, when the water is so turbid that the river bed is not visible in imagery. This is the case for braided rivers in proglacial margins where high rates of glacial erosion create high suspended sediment concentrations and also morphodynamically active braided rivers. In this paper we test a new and simple hypothesis to predict water depth distribution based upon heuristic reasoning: that our experience of braided river environments allows us to make a series of qualitative statements about where water will be deeper and where it will be shallower; and that if we can quantify them, we can model the water depths associated with inundated zones.

The simplest statement is that water depth increases with distance away from the nearest river bank; and it is likely to do so more rapidly when the total wetted width is lower. A more rapid increase is also likely on the outer bank of curved sections; and conversely, a slower increase is likely on the inner bank. In a braided river, streamline convergence is likely to lead to deeper water; streamline divergence is likely to lead to shallow water. On this basis, we ought to be able to model water depths in a shallow braided river on the basis of: (1) distance from the nearest bank; (2) local channel width; (3) total inundated width (given a braided river is multi-channel); (4) local curvature magnitude and direction; and (5) planform streamline convergence/divergence. We measure these parameters for a shallow braided proglacial stream (Glacier d’Otemma, south-western Swiss Alps) with high suspended sediment concentrations. Over the summers of 2020 and 2021 we acquired high resolution UAV-based imagery, as well as spatially distributed GPS data of water depths. We used resultant ortho-imagery to extract these parameters and to calibrate predictive models of water-depth based upon multivariate statistical modelling. The independent validation data suggest that between 50% and 75% of the variance in water depths can be reconstructed and confidence in estimated depths are of the order of +/- 0.10m. Finally, we integrate these water depths and their uncertainty into elevation data derived using SfM-MVS photogrammetry for the exposed areas to produce digital elevation models with spatially dependent uncertainty. Comparison of these DEMs shows that they can be used to visualize quantitative geomorphological changes and that the associated uncertainties in volume of change estimates are sufficiently low to be used in sediment budget studies.

How to cite: Mancini, D., Roncoroni, M., Antoniazza, G., Ouvry, B., and Lane, S. N.: Heuristic measurement of river bathymetry in proglacial braided streams using SfM-MVS photogrammetry and statistical approaches, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7071, https://doi.org/10.5194/egusphere-egu22-7071, 2022.

A lot of different methods are used to estimate flood risk worldwide. The method that performs better depends on the catchment features and dimension, data time resolution and availability and uncertainty level required. Remote sensing approaches are more and more common, but because of the limited periods covered by time series derived by this new methodology, in-situ data integration is still required. A new methodology is proposed, based on a case-study of different reaches of Basento river, Basilicata (Southern Italy). Starting from hourly rainfall time series (covering not less than 20 years), for each pluviometric station taken into account into the catchment area, Intensity-Duration-Frequency (IDF) curves are computed (fitting a power law), in order to calculate the rainfall maximum at a certain percentile (typically 90° or 95° percentile are used) during the concentration time. Thiessen polygon method is used to divide the catchment area into smaller areas, each one corresponding to a pluviometric station, with the purpose of calculating weighted  rainfall values for each station area. A Digital Terrain Model is used to extract multiple cross sections of the river-bed, spanning different morphologies, from braided to meandering channels. For each cross section, starting from bankful level, it is possible to estimate diverse hydraulic parameters such as river stage, hydraulic radius, section’s surface area (using image analysis) and the mean velocity of the current, using the logarithmic law profile of the turbulent flow. Sediment size analysis is carried out as to estimate the river bed roughness for each cross section. The mean velocity value V can be used to estimate the concentration time t=L/V, where L is equal to the distance between the cross section and the hydraulically further point into the catchment area. The concentration time value t is used into the equation of the IDF curves, in order to link the corresponding rainfall height to the river stage reached at the cross section, eventually to estimate the rainfall value that, if exceeded, can cause flood. A FLO-2D model has been then used to run simulations with the aim to detect flood-prone areas, finding an overall good matching between the values of current mean velocity, discharge and river stage estimated in the cross sections.

How to cite: Roseto, R., Capolongo, D., and Dellino, P.: A new approach for flood risk estimation integrating remote sensing and in-situ data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7229, https://doi.org/10.5194/egusphere-egu22-7229, 2022.

High mountain environments have shown substantial geomorphological changes forced by rising temperatures in recent decades. As such, paraglacial transition zones in catchments with rapidly retreating glaciers and abundant sediments are key elements in high alpine river systems and promise to be revealing, yet challenging, areas of investigation for the quantification of current and future sediment transport. In this study, we explore the potential of semi-automatic image analysis to detect the extent of the inundation area and corresponding inundation frequency in a proglacial outwash plain (Jamtal valley, Austria) from terrestrial time-lapse imagery. We cumulated all available records of the inundated area from 2018-2020 and analysed the spatial and temporal patterns of flood flows. The approach presented here allows semi-automated monitoring of fundamental hydrological/hydraulic processes in an environment of scarce data. The pixel classification based on greyscale values from oblique hourly recordings returned plausible results of the spatial and temporal variability of surface runoff in the investigated glacier forefield. The image sets, processed in ImageJ, allowed geo-rectification to produce inundation frequency maps. Meteorological and discharge data from downstream measuring stations was consulted to interpret our findings. Runoff events and their intensity were quantified and attributed to either pronounced ablation, heavy precipitation, or a combination of both. We also detected an increasing degree of channel concentration within the observation period. The maximum inundation from one event alone took up 35% of the analysed area. About 10% of the observed area presented inundation in 60-70% of the analysed images. In contrast, 60-70% of the observed area was inundated in fewer than 10% of the analysed period. Despite some limitations in terms of image classification, prevailing weather conditions and illumination, the derived inundation frequency maps provide novel insights into the evolution of the proglacial channel network.

How to cite: Hiller, C., Walter, L., Helfricht, K., Weisleitner, K., and Achleitner, S.: Flood flow in a proglacial outwash plain - quantifying spatial extent and frequency of inundation from time-lapse imagery, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7517, https://doi.org/10.5194/egusphere-egu22-7517, 2022.

Since 2015, 13 agencies from all around the world (9 different countries in Europe, North and South America and Oceania) have been working together in an International Hydrometry Group, a loosely organized group of experts in instruments and methods for measuring discharge in rivers that meets virtually once a month to discuss scientific and technical issues relating to river flow measurements.

A main objective of the group is to lead the development and funding of an open-source software package, QRevInt, for postprocessing ADCP discharge measurements. The agencies participate in funding the software developer (Dave Mueller, Genesis HydroTech) or contribute scientific inputs. They define the annual development workplan and its funding, and monitor progress during monthly monitoring meetings.

In this presentation, the latest version of QRevInt is detailed and the main advantages of the software are explained, including processing of measurements from ADCP of different manufacturers (TRDI and SonTek) with the same calculation assumptions, objectification of the computation of unmeasured flow area (top, bottom, edges, invalid cells or ensembles), calculation of uncertainty and advanced graph options.

The workplan of the group for 2022 is presented, including the ongoing developments of QRevInt, and the new project for a software dedicated to mid- or mean-section ADCP measurement, QRevIntMS.

How to cite: Lennermark, M. and Hauet, A.: Developing a post-processing software for ADCP discharge measurement piloted by an international and inter-agency group: a unique, ambitious experience… and one that works!, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9379, https://doi.org/10.5194/egusphere-egu22-9379, 2022.

The annual monsoon inundations are vital in maintaining the fertility and productivity of the delta of the Mekong, Southeast Asia’s largest river. During the inundations, which traditionally last from July until November, nutrient-rich sediments are deposited on the floodplains, groundwater is recharged, and fish populations regenerate in the shallow waters. Consequently, local agriculture and fisheries are keyed to the timing of flood arrival and recession and reliant on overall flood duration. However, in recent years, the hydrological dynamics of the region have shifted. The Mekong’s hydrological regime has been impacted by shifts in land cover, the construction of hydropower infrastructure, and climate change. 

Yet the effects of these changes on the spatio-temporal patterns of inundations in the Mekong Delta remain largely unstudied, especially at local scales. Part of the reason for this is data sparsity: there is a lack of consistent long-term data on spatial inundation dynamics. No concerted in-situ monitoring efforts of flood extents existed until recently, while optical earth observation satellite missions such as Landsat often fail to provide data during the wet season due to cloud cover. Hydrological modelling approaches struggle with insufficiently precise elevation data - due to the flat topography of the Mekong Delta, even high-resolution Digital Elevation Models (DEMs) fail to capture small-scale dykes that determine whether large swaths of land become flooded. 

To cope with this data-scarce environment, we propose an innovative methodology harnessing recent satellite missions and long-term in-situ river water level measurements. This approach uses remote sensing data from the Sentinel-1 and 2 missions operated by the European Space Agency. Since 2017, these satellites provide optical and synthetic aperture radar (SAR) data at a spatial resolution of 10 m and a return frequency of 5-6 days. Furthermore, SAR provides data independent of cloud cover, which makes it particularly well-suited for operational flood monitoring purposes. After deriving inundation maps from available Sentinel images, we link these maps to water levels measured at a local hydrological station through a correlative approach to create a water-level flood link (WAFL). Using this link, we can describe the evolution of inundation patterns in the Mekong Delta since the 1990s. To quantify uncertainties, comparisons with historical inundation maps derived from available Landsat images,  and with a high- resolution DEM were carried out.  

The approach was tested in two study areas in the Cambodian Mekong Delta.  The results indicate that the accuracy of the WAFL for quantifying inundations on a per-pixel basis lies at 87%, reaching up to 93%. The spatio-temporal analysis shows that inundation incidence in the early wet season has declined by 21% since 1991 and that the average duration of inundations has decreased by 19 days. This illustrates that annual monsoon inundations have become an increasingly volatile resource, with significant impacts on agriculture, fisheries, and ecosystems. 

How to cite: Orieschnig, C., Belaud, G., Venot, J.-P., and Massuel, S.: Assessing long-term changes in annual monsoon inundations in the Mekong Delta (Cambodia): Testing an innovative approach linking remote sensing and in-situ measurements to overcome data scarcity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9619, https://doi.org/10.5194/egusphere-egu22-9619, 2022.

The changing climate and corresponding increased variability in weather events globally have made clear the need for accurate measurements of streamflow, and the ability to respond quickly to conditions as they occur.

We present Infrared Quantitative Image Velocimetry (IR-QIV), a nearfield remote sensing method that uses infrared imagery of the surface of a river or other body of water to accurately calculate the surface flow field at high resolution in space (~10cm resolution) and time (>1Hz), accurately and continuously, over large areas (1,000s of m^2), for extended periods of time.

IR-QIV is similar to LSPIV (Large Scale Particle Image Velocimetry) and other image-based velocity measurement methods, however, it does not require any illumination or tracer particles since it uses thermal infrared images. IR-QIV has the advantages of being able to measure instantaneous velocity, in addition to mean velocity, and hence makes it possible to calculate metrics of turbulence, from which additional hydrodynamic properties of the flow can be found, including estimates of local bathymetry and bed stress, which allow estimation of discharge from a single, non-contact, measurement.

Since IR-QIV can be used to measure a wide range of flows, can operate day or night and in most weather conditions, and can continuously and robustly measure at high spatial resolution over large areas, it is particularly of use where high accuracy and resolution measurements are required, such as for fish management applications, near hydraulic structures or at other locations with complex hydrodynamics, or at locations where physical access to the water is restricted or dangerous. Because measurements can be set up relatively quickly and without requiring contact with the water, we expect IR-QIV to increasingly become an important tool in responding to changing environmental conditions.

IR-QIV was developed in a partnership between Cornell University, the California Department of Water Resources (DWR), and the US Geological Survey (USGS) for applications including monitoring flow and discharge, and high resolution hydrodynamic measurements near fish guidance structures and barriers. In this presentation we will present an overview of the method, and discuss its capabilities and applications, including considerations that are relevant for any image-based velocity measurement methods, regardless of the imaged wavelengths (thermal, or visible-light).

Figure 1. IR-QIV example: Velocity calculated by IR-QIV (black arrows), plotted over an infrared image of the water surface at Sutter Slough, Califiornia, USA, superimposed on an aerial image.  From: Schweitzer, S. A., & Cowen, E. A. (2021). Instantaneous river-wide water surface velocity field measurements at centimeter scales using infrared quantitative image velocimetry. Water Resources Research, 57, e2020WR029279. https://doi.org/10.1029/2020WR029279

How to cite: Schweitzer, S. and Cowen, E.: Infrared Quantitative Image Velocimetry (IR-QIV): Instantaneous River-Wide Water Surface Velocity  Measurements at Centimeter Scales, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10350, https://doi.org/10.5194/egusphere-egu22-10350, 2022.

Non-contact and automated flow measurement in open channels is becoming more popular as techniques improve to measure surface velocity, reducing costs and risk to hydrographers.  However, these methods rely on estimates of bulk-to surface ratio estimates, as well as channel wetted area.  This study considers the accuracy and application of paired Up and Downstream Water Quality (WQ) measurements to estimate the Transit Time (TT) and average bulk velocity.  Combined with results from both the Automated Salt Dilution (AutoSalt) and Water Quality Mixing Model (WQMM) systems, we can calibrate the waterway for wetted area at a given water level, and hence estimate discharge from transit time velocity on a continuous basis using only temperature and conductivity insitu sensors.  This low-cost method can used to build or validate rating curves, measure peak and low flow events, and conduct cost-effective hydrological assessments over large regions for any size waterway,  to support climate change study and adaptation.  This method also has application to flood wave propagation and Initial Dilution Zone (IDZ) studies. Results from a large and a small waterway, along with uncertainty, is discussed.

How to cite: Sentlinger, G.: Water Quality Transit Time (WQTT) for Continuous Velocity/Discharge Measurement in Large and Small Waterways, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10795, https://doi.org/10.5194/egusphere-egu22-10795, 2022.

Debris flows and flash floods occur frequently in Chile due to geology, geomorphology and weather, costing human lives and impacting settlements, infrastructure and economic activities. One of the problems relates to the lack of adequate monitoring technology in remote areas with limited connectivity. We have developed a low cost system that processes acquired lidar and image data in-situ with a Raspberry Pi obtaining flow level and velocity and transmits near real time via satellite (or cellular network if available). The low implementation cost allows to replicate the system in the many hazardous sites, as well as advance towards early warning systems in locations with limited communication networks. The velocimetry method consists of two steps: first obtaining the images, and then a brightness filter and normalized cross correlation. To eliminate outliers a flow direction filter is used, and velocities are obtained by tracking of flow surface elements. Also the flow level is measured with a lidar also connected to the R-Pi. We will present both laboratory and field test results.

How to cite: Dussaillant, A., Sepúlveda, N., Aguilar, F., Valencia, J., Ancan, J., Cotroneo, J., Herrera, R., Leiva, N., Peña, C., Alfaro, A., Fernández, J., and Muñoz, A.: In-Situ, Near Real Time and Low Cost Image Velocimetry for Debris Flows and Flash Flood Monitoring in the Chilean Andes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10797, https://doi.org/10.5194/egusphere-egu22-10797, 2022.

The gauging of open channel flows in waterways provides the foundation to monitor, understand and manage the water resources of our built and natural environment. Several methods are available for measuring the flow, with each of these methods having its own advantages and limitations. For a significant economic and environmental cost, hydraulic control structures can be built to measure the flow using analytical relationships with water height often by measuring the pressure head invasively in the water. Another common approach using the proxy measurement of water height without a hydraulic control structure is the expensive development and maintenance of a discharge rating table relating the measured water height to an estimated flow which has been manually measured at a previous time by acoustic instruments with technically proficient operators. Whilst these approaches are typically able to reasonably estimate flow within their measurement range, the safety risks in monitoring high flow events and the ongoing costs involved are prohibitive to increasing the spatial coverage of these approaches. As water resources become increasingly vulnerable to climate variability, modification of waterways, and increased extraction, there is a critical need to develop monitoring tools that can be flexible, cost-effective, and safe.

Much research has been undertaken into optical non-contact methods to estimate flow in waterways by measuring surface velocities without intrusive instruments or structures. However, to date, these surface velocimetry methods are limited to a narrow operational window of certain stream types and flow velocities due to inherent challenging optical variability in stream environments. A cost-effective stereographic camera-based stream gauging device has been developed for rapid stream gauging through the remote sensing of water height and stream velocities to estimate flows and employ the learning of an adaptive discharge rating envelope. The device includes embedded edge computing capabilities, local app connectivity for setup, and online cloud fleet management with a data dashboard for streamlined deployment and ongoing operational monitoring. Automated analysis is performed reconstructing the point cloud of the scene in front of the camera out to 40 m in order to estimate the water level without any instream equipment. An optical flow algorithm is passed over the short videos collected, generating an array of net motion in the scene which is projected out of the image plane onto the assumed water surface plane using the water level estimation combined with the accelerometer and the embedded intrinsic camera properties. The optically measured motions which are out of the plane of the waterway surface are then able to be automatically filtered and integrated into a water level indexed learning surface velocity distribution which generates an updating adaptive discharge rating envelope for the site. With over 100,000 videos recorded and analysed across 20 sites, the computer vision stream gauging approach has achieved discharge measurements within 15% RMSE of traditional acoustic gauging. This work evaluates this innovative approach across sites on the east coast of Australia and demonstrates the potential to improve the operational reliability and performance of surface velocimetry stream gauging.

How to cite: Hutley, N., Wagenaar, D., Beecroft, R., Soutar, J., Pimble, L., Edwards, B., Grinham, A., and Albert, S.: A stereo computer vision approach to automated stream gauging, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11030, https://doi.org/10.5194/egusphere-egu22-11030, 2022.

OpenRiverCam is a fully open-source, user-friendly, low cost and sustainable web-software stack with API to establish and maintain river rating curves (relationships between geometry and river discharge) in small to medium sized streams based on Large Scale Particle Image Velocimetry (LSPIV). The software is co-designed with practitioners from The Netherlands (Waterboard Limburg and KNMI) and Tanzania (Wami - Ruvu Basin Authority and TMA) with the principle that organizations should be able to establish and maintain operational flow monitoring sites and networks at low costs. A user only requires to establish a temporary or permanent camera site; a simple field survey to measure river cross sections and several control points; and feeding operational videos into the dashboard of the software.

In July 2021, a severe flood event hit several Western European countries including parts of Germany, France, The Netherlands and Belgium. Also the Geul river, a tributary to the Meuse river was severely affected. One of our camera setups was operational at the Geul, near the village Hommerich during the event. The camera recorded 10 second videos every 15 minutes. Through the recordings of this single event, we were able to reconstruct flows and prepare a large number of rating points over a wide diversity of flow domains within a period of less than 12 hours. In this presentation we will share the results of our analysis, and validation against formal flow observations of the Waterboard Limburg. We plan to extend the software with improved pre-processing and allow use of less precise smart phone videos.

How to cite: Winsemius, H., Annor, F., Hagenaars, R., Luxemburg, W., Van den Munckhof, G., Heeskens, P., and Van de Giesen, N.: Capturing the Europe July 2021 flood event flows with an IP camera and OpenRiverCam, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11627, https://doi.org/10.5194/egusphere-egu22-11627, 2022.

Climate change, together with other natural and anthropogenic drivers lead to changes in streamflow patterns that are now occurring with increasing frequency. At the same time traditional streamflow monitoring methods are time-consuming and costly so that it typically takes many years of significant field efforts to establish reliable streamflow data for a new location or for stations with major temporal changes to the stage—discharge relation. To provide timely and reliable streamflow data to tackle these changes to the hydrological regime and their impacts on society’s water management requires new cost-effective monitoring methods that can rapidly produce data with low uncertainty. Hydraulically modelled rating curves are a promising alternative to traditional power-law methods as they need much fewer calibration gaugings, but they are associated with additional uncertainty sources in the hydraulic knowledge and these need to be assessed.
We present the Rating curve Uncertainty estimation using Hydraulic Modelling (RUHM) framework which was developed to rapidly estimate rating curves and their uncertainty. The RUHM framework combines a one-dimensional hydraulic model with Bayesian inference to incorporate information from both hydraulic knowledge and the calibration gauging data. In this study we compare RUHM and the Bayesian power-law method BaRatin in application to a Swedish site using nine different gauging strategies associated with different costs. We compare results for the two methods in terms of accuracy, cost and time required for establishing rating curves. 
We found that rating curves with low uncertainty could be modelled with fewer gaugings for RUHM compared to BaRatin. As few as three gaugings were needed with RUHM if these gaugings covered low and medium flows, whereas high flow gaugings were not necessary. This makes the RUHM method both cost effective and time efficient as low and medium flows occur more frequently than high flows. When using all gaugings (i.e., a high-cost gauging strategy), the uncertainty for RUHM and BaRatin was similar. The results for this Swedish site show that hydraulic rating curve uncertainty estimation is a promising tool for quickly estimating rating curves and their uncertainties. Finally, we discuss the potential of using RUHM together with drone-derived data to make field efforts even more efficient.

How to cite: Westerberg, I., Mansanarez, V., Lyon, S., and Lam, N.: The RUHM framework for rapid rating curve uncertainty estimation: comparison to power-law methods and potential using drone-derived data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13348, https://doi.org/10.5194/egusphere-egu22-13348, 2022.

A remote method of measuring surface and near-surface currents in wavy riverine environments
at high spatial and temporal resolution is presented. A two-dimensional power spectral density
technique (2D PSD), which is based on calculating the cross-spectrum between two images is
developed and compared with the established 3D PSD technique. In contrast to the 3D PSD
technique, the 2D PSD algorithm is capable of determining velocity time series and spectra,
thereby facilitating remote measurements of turbulence. Moreover, the 2D PSD algorithm can
accurately determine near-surface flows from fewer images. Results are presented from imagery
collected from an unmanned aerial vehicle and satellite imagery from a number of different
riverine locations.

How to cite: Johnson, E.: Measuring Instantaneous Velocity Fields Remotely using a Two-Dimensional Power Spectral Density Technique, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13487, https://doi.org/10.5194/egusphere-egu22-13487, 2022.

Computer models are frequently used tools in hydrological research. Many decisions related to the model set-up and configuration have to be made before a model can be run, which might influence the results of the model. This study is an empirical investigation of the motivations for certain modeling decisions. Fourteen modelers from three different institutes were interviewed about their modeling decisions. In total, 83 different motivations were identified. Most motivations were related to the team of the modeler and the modelers themselves, `Experience from colleagues' was the most frequently mentioned motivation. Institutionalization and Internalization were observed: a modeler can introduce a concept that subsequently becomes the teams' standard, or a modeler can internalize the default team approach. These processes depend on the experience of the modeler. For model selection, two types of motivations were identified: experience (from colleagues or the modelers themselves), and model vision (the model has assets that align with the modeling vision). Model studies are mainly driven by context, such as time constraints, colleagues, and facilities at the institute, rather than epistemic (such as aligning with the modeling vision). The role of local context in the construction of and the value assigned to models shows that models are social constructs, making model results time and place dependent. To account for this context in the estimation of the robustness of model results, we need diversity of opinions, perspectives, and approaches. This requires transparent modeling procedures and an explicit modeling vision for each model study. 

How to cite: Melsen, L.: It takes a village to run a model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1167, https://doi.org/10.5194/egusphere-egu22-1167, 2022.

Severe flash floods have hit Jordan in recent years, e.g., in 2018 and 2020, leading to fatalities and infrastructure damages. Moreover, even though Jordan is one of the water scarcest countries of the world, extreme rainfall events might occur more frequently under climate change (IPCC Sixth Assessment Report 2021), causing flash floods in wadi systems. Also, the population growth combined with construction and sealing in cities increases the risk of damages, and authorities are under pressure to provide solutions for disaster risk reduction. Few flash flood models have been adopted and developed for wadi systems. Here the scientific community might help by providing tools to understand better, assess, and predict such events to introduce possible adaptation strategies.

The BMBF funded German-Jordanian project “CapTain Rain” studies flash flood risks with a transdisciplinary approach, interacting with local stakeholders. Jordan receives annual precipitation of around 110 mm overall, and hydrological data is not abundant, discontinuous, and of differing quality. Hence, flash flood modelling approaches and available software for humid regions from northern hemisphere industrialized countries cannot be easily transferred. Therefore, we want to review the variety of model options for flash flood modelling in arid and humid areas and give an overview of the selection process.

The model selection is often based on different aspects like application of interest, data requirements and availability, model complexity, code availability and open-source option, user knowledge, and modeling group experience. On the one hand, Beven and Young (2013) strengthen that model selection should not be more complex as necessary and fit-for-purpose. On the other hand, Addor and Melsen (2019) saw a strong social component. They mention the hydrological model selection is stronger influenced by legacy aspects instead of adequacy aspects. Horton et al. (2021) reviewed the hydrological model application for Switzerland. They discuss that not all aspects of model selection are mentioned in the published articles, mainly social elements. In addition, their author survey shows that modeling group experience plays a crucial factor in model selection, and most models used have a strong basis in the country.

By focusing on Jordan or other dry and data-scarce regions worldwide, other aspects need to be considered. For example, modelling knowledge of users might be limited, validation and calibration data are scarce, and financial resources for software are restricted. Therefore, we see an urgent need to analyze the aspects of model selection for flash floods in Wadi systems in a scientific context and to give the stakeholders a fact-based overview about possible model options.  

Literature:

Addor, N.; Melsen, L.A. (2019): Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models. WRR. 55, 378–390

Beven, K.; Young, P. (2013): A guide to good practice in modeling semantics for authors and referees. WRR. 49, 5092–5098

Horton, P; Schaefli, B.; Kauzlaric, M. (2021): Why do we have so many different hydrological models? A review based on the case of Switzerland. Wiley Interdiscip.Rev.-Water, e1574

How to cite: Hohmann, C., Maus, C., Ziegler, D., Kantoush, S., and Abdelal, Q.: Selection of flash flood models in data-scarce regions like Jordan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3905, https://doi.org/10.5194/egusphere-egu22-3905, 2022.

Stringent modelling methods and diagnostic techniques for improving the credibility of model predictions have received a lot of attention in the hydrological literature. However, previous discussions have revolved mainly around theoretical aspects, and arguably lacked persuasive examples. In this work, in order to illustrate the weaknesses of widespread modelling practices, we instead provide an applied perspective. In particular, we present the case of a distributed rainfall-runoff model that evolves in response to progressively more stringent application of model diagnostics. Through this example we demonstrate the usefulness of the following methodological instruments: (i) benchmarking model results against a null-hypothesis model, (ii) testing model predictions in space-time validation, and (iii) carrying out controlled model comparisons. These instruments, arguably still underutilized in the hydrological community, offer important diagnostic capabilities to increase the rigor of hydrological and environmental model applications.  Therefore their more widespread application is encouraged.

How to cite: Fenicia, F. and Kavetski, D.: Behind every robust result is a robust method: Perspectives from a hydrological case study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4802, https://doi.org/10.5194/egusphere-egu22-4802, 2022.

Deep subsurface dynamic models allow simulating the interaction of multiple physical processes at regional and geological scale. In the past three decades, O&G industry developed so called Basin and Petroleum Systems Models to improve the prediction of hydrocarbons accumulation and reduce risks of exploration wells failure. By simulating the geological history of a sedimentary basin from its origin, these thermo-hydro-mechanical and chemical (THMC) models provide at present day a balanced distribution of static and dynamic properties of a huge volume of rocks.

For the last years, one of these THMC simulators has been extended to more generic application, such as geothermal potential assessment of sedimentary basins, large scale aquifers systems appraisal for massive CO₂ sequestration or quantification of present-day methane seepage from shallow biogenic gas production.

At the basin scale, data to describe the subsurface are very diverse and scattered and the uncertainty of representativeness of basin geological models is large, especially if one expects to obtain results in quantitative terms on connected pore volumes, temperatures, pressures, stress or fluid composition.

This scarcity of data requires geoscientists to describe alternative scenarios that are compatible with the observational data.  The description of a 4D model (3D structure through geological time) of a sedimentary basin is a long and complex task and the creation and analysis of multiple digital scenarios is therefore almost impossible in reasonable timeframe.

We have developed and proofed the concept of interactive basin model that allows simulating while interpreting, hence comparing scenarios while interpreting. In the concept implementation, the processes of surface and subsurface data analysis, 3D scenario model building, simulation parameters setup, THMC simulation, results visualisation and analysis and scenario comparison is performed in a single “real-time” loop.

The concept also allows the incremental building of a geological basin model. Therefore, one can start by building a coarse model of the full sedimentary basin that is continuously watertight and consistent. Then by visualising the result of the simulation in terms of present-day temperature, pressure, stress, and fluid chemistry fields compared instantaneously with the available data, it can be improved to a more complete and consistent representation. This interactive loop avoids the need for costly and complex inversion and allows the geologist to quickly explore the consistency of his or her assumptions.

Ultimately, this interactive modelling protocol based on advanced multi-physics simulation tools should become an essential weapon for rapidly defining the basis for assessing the potential, risks and balances between human activity and the nature of an often poorly documented deep underground.

It is complementary to specific tools for data analysis or uncertainty and risk assessment, such as specialised simulators like reservoir or aquifer models.

How to cite: Gout, C. and Cacas-Stentz, M.-C.: An interactive geological basin model: supporting the fast-track assessment of large-scale subsurface potential in the context of the ecological transition, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5215, https://doi.org/10.5194/egusphere-egu22-5215, 2022.

Hydrological models are fundamental tools that play a key role in many areas of hydrological science and climate change impact studies. However, it is well known that the number of models has increased beyond what is necessary. One of the key drivers for model diversity in hydrology is the wide range of model applications, motivated by specific needs and contexts that require suitable models. Yet, a significant part of this diversity is not driven by the context, as different models are applied under analogue circumstances.

To better understand the main drivers of model diversity, a review of hydrological modelling habits was conducted on studies carried out in Switzerland. Despite being a small country, Switzerland has a variety of hydro-climatological regimes, water resource management challenges, and hydrological research institutes, and can thus be representative of other regions. A first observation was that the motivations for selecting a model are rarely stated in scientific articles, and the adequacy of the model for the context or landscape is often not addressed. Thus, a survey was conducted to evaluate some subjective aspects that are otherwise difficult to retrieve from the scientific literature.

Not surprisingly, researchers are very keen on using a model developed at their own institute, which provides the benefit of expertise and efficiency, but at increased risk of context inadequacy and automatism in decisions. Other aspects were considered relevant in the model selection process, such as – indeed – adequacy, access to the code, reuse of existing model setups, collaborations, technical constraints or data availability.

Several hydrological models exist in Switzerland, while the vast majority of the studies were conducted using a single model. To some extent, model diversity is desirable to assess model variability, but multi-model applications to harness this diversity are largely missing. The survey could highlight that most researchers consider multi-model approaches important, but most do not apply them for various practical reasons, such as lack of resources (time and/or money) or lack of expertise in another model. We believe that some barriers can be lowered to facilitate multi-model approaches, requiring efforts from the modelling community and the funding agencies.

How to cite: Horton, P., Schaefli, B., and Kauzlaric, M.: Drivers of hydrological model diversity and model selection factors - The example of Switzerland., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6363, https://doi.org/10.5194/egusphere-egu22-6363, 2022.

A long-standing research issue, in the hydrological sciences and beyond, is that of developing methods to evaluate the predictive/forecasting skill, errors and uncertainties of a model (or model ensembles). Various methods have been proposed for characterising time series residuals, i.e. the differences between observed (or target) and modelled (or estimate) time series. Most notably, the Taylor Diagram summarises model performance via a single plot based on three related metrics: the (linear Pearson) correlation, standard deviation, and root mean squared differences of one or multiple pairs of target and estimate time series. Despite its theoretical elegance and widespread use, the Taylor diagram does not account for bias errors, which is an important summary statistic for evaluating model performance. Further, it is very common to evaluate, compare, and report on model “skill” by use of a single aggregate metric value, even when a vector of metrics is used to calibrate/train the model; most commonly this is a dimensionless efficiency metric such as Nash-Sutcliffe Efficiency (NSE) or Kling-Gupta Efficiency (KGE). Such “efficiency” metrics typically aggregate over multiple types of residual behaviours: for example the most commonly used version of KGE is based on correlation, bias, and variability errors, although the authors recommended that it should be applied in a context-dependent fashion based on which model behaviours are deemed to be important to a given situation. Nevertheless, the use of a single summary value fails to account for the interactions among the error component terms, which can be quite informative for the evaluation and benchmarking of models. In this study, we propose a new diagram that is as easy to use and interpret as the Taylor Diagram, while also accounting for bias. We further suggest a new convention for reporting model skill that is based on foundational error terms. Our vision is that this new diagram and convention will enable researchers and practitioners to better interpret and report model performance. We provide multiple numerical examples to illustrate how this approach can be used for evaluating performance in the context of multi-model and multi-catchment (large-sample) studies.

How to cite: Khatami, S., Di Baldassarre, G., Gupta, H., Moallemi, E. A., and Pool, S.: Suggesting a new diagram and convention for characterising and reporting model performance, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8211, https://doi.org/10.5194/egusphere-egu22-8211, 2022.

As hydrologists, we pride ourselves on being able to identify deficiencies of a hydrologic model by looking at its runoff simulations. Generally, one of the first questions that a practicing hydrologist always asks when presented with a new model is: "show me some hydrographs!". Everyone has an intuition about how a "real" (i.e., observed) hydrograph should behave [1, 2]. Although there exists a large suite of summary metrics that measure differences between simulated and observed hydrographs, those metrics do not always fully account for our professional intuition about what constitutes an adequate hydrological prediction (perhaps because metrics typically aggregate over many aspects of model performance). To us, this suggests that either (a) there is potential to improve existing metrics to conform better with expert intuition, or (b) our expert intuition is overvalued and we should focus more on metrics, or (c) a bit of both.

In the social study proposed here, we aim to address this issue in a data-driven fashion: We will ask experts to access a website where they are tasked to compare two unlabeled hydrographs (at the same time) against an observed hydrograph, and to decide which of the unlabeled ones they think matches the observations better. Together with information about the experts’ background expertise, the collected responses should help paint a more nuanced picture of the aspects of hydrograph behavior that different members of the community consider important. This should provide valuable information that may enable us to derive new (and hopefully better) model performance metrics in a data-driven fashion directly from human ratings.

[1] Crochemore, Louise, et al. "Comparing expert judgement and numerical criteria for hydrograph evaluation." Hydrological sciences journal 60.3 (2015): 402-423.

[2] Wesemann, Johannes, et al. "Man vs. Machine: An interactive poll to evaluate hydrological model performance of a manual and an automatic calibration." EGU General Assembly Conference Abstracts. 2017.

How to cite: Gauch, M., Kratzert, F., Mai, J., Tolson, B., Nearing, G., Gupta, H., Hochreiter, S., and Klotz, D.: Rate my Hydrograph: Evaluating the Conformity of Expert Judgment and Quantitative Metrics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8396, https://doi.org/10.5194/egusphere-egu22-8396, 2022.

Irrigation agriculture is the most important user of the global freshwater resources worldwide, which makes it one of the key actors conditioning sustainable development and water security. The anticipated future climate change, population growth, and rapidly rising global demand for food will likely lead to agricultural expansion by allowing the development of irrigated areas. This together with the fact that irrigated crops are approximately four times more profitable than rainfed crops will place much additional pressure on water resources in the next years. Therefore, it is of vital importance to devise solutions that minimize the negative impacts of agricultural expansion, particularly on biodiversity and water use, so as to help us achieve environmental and economic sustainability. To realize such an ambition, quantifying irrigation water withdrawal at different spatio-temporal scales is essential. Global Hydrological Models (GHM) are often used to produce irrigation water withdrawal estimates. Yet GHMs questionably rely on several uncertain estimates of irrigated areas, crop evapotranspiration processes, precipitation and irrigation efficiency, which are the four main inputs in the structure of GHMs. Here we show that, once basic uncertainties regarding these estimates are properly integrated into the calculations, the point-based irrigation water withdrawal estimates actually correspond to uncertainty intervals that span several orders of magnitude already at the grid cell level. Our approach is based on the concept of “sensitivity auditing”, a practice of process-oriented skepticism towards mathematical models. The numerical results suggest that current estimates of global irrigation water withdrawals are spuriously accurate due to their neglect of several ambiguities/uncertainties, and thus need to be re-assessed. Our analysis highlights that models of global irrigation water demands need to better integrate uncertainties, both technical and epistemological, so as to avoid misguiding the development of strategies intended to help ensure water and food security.

How to cite: Puy, A., Sheikholeslami, R., Gupta, H., Hall, J., Lankford, B., Lo Piano, S., Meier, J., Pappenberger, F., Porporato, A., Vico, G., and Saltelli, A.: How certain are we about the model-based estimations of global irrigation water withdrawal?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8603, https://doi.org/10.5194/egusphere-egu22-8603, 2022.

It has been said that culture eats strategy for breakfast. The effect of legacy over adequacy in modelling practice exemplifies the difficulty in changing behaviours to improve modelling outcomes. Ideally, good modelling practice would be incentivised by the systems in which modellers operate, and moreover, that modelling practice would have a learning orientation that gradually improves over time, seeking an ever closer alignment with organisational and societal needs.

Digital twins institutionalised within organisational operations provide a possible opportunity to incentivise these behaviours. A digital twin is a time-varying representation of a system that brings together observed information and predictive model capabilities. Juxtaposing model predictions with other sources of information forces models to demonstrate their value, in continually changing conditions. Operational use of a digital twin means that models need to be fit for purpose. The need to prioritise investment across a digital twin means that the model suite needs to address a broad range of purposes and model augmentation is more likely to be driven by consideration of value of information and prioritisation of efforts to reduce uncertainty over time.

These theoretical benefits are explored with example use cases in the context of cross-scale catchment water resource, landscape, and irrigation management, drawing on preliminary experiments in Australia.

How to cite: Guillaume, J.: Can digital twins incentivise good modelling practice?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9464, https://doi.org/10.5194/egusphere-egu22-9464, 2022.

Model calibration and validation are critical in hydrological model robustness assessment. Unfortunately, the commonly used split-sample test (SST) framework for data splitting requires modelers to make subjective decisions without clear guidelines.

A massive SST experiment for hydrological modeling is proposed and tested across a large sample of catchments to empirically reveal how data availability and calibration period features (i.e., length and recentness) simultaneously impact model performance in the post-validation period (e.g., forecasting or prediction), thus providing practical guidance on split-sample design. Unlike most SST studies that use two sub-periods (i.e., calibration and validation) to build models, this study incorporates an independent model testing period in addition to calibration and validation periods. Model performance of two lumped conceptual hydrological models (i.e., GR4J and HMETS) are calibrated and tested in 463 CAMELS catchments across the United States using 50 different data splitting schemes. These schemes are established regarding the data availability, length, and data recentness of the continuous calibration sub-periods (CSPs). A full-period CSP is also included in the experiment, which skips model validation entirely. The results are synthesized regarding the large sample of catchments and are comparatively assessed in multiple novel ways, including how model building decisions are framed as a decision tree problem and viewing the model validation process as a formal testing period classification problem, aiming to accurately predict model success/failure in the testing period.

Results span different climate and catchment conditions across a 35-year period with available data, making conclusions generalizable. Strong patterns show that calibrating to older data and then validating models on newer data produces inferior model testing period performance in every single analysis conducted and should hence be avoided. Calibrating to the full available data and skipping model validation entirely is the most robust split-sample decision. Findings have significant implications for SST practice in hydrological modeling. As the next phase of this study, results for discontinuous calibration sub-periods (DCSP) will be evaluated as an alternative SST design choice and contrasted then with the CSP results.

How to cite: Shen, H., Tolson, B., and Mai, J.: Time to Update the Split Sample Approach to Hydrological Model Calibration: A Massive Empirical Study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10846, https://doi.org/10.5194/egusphere-egu22-10846, 2022.

Effective water resources management and mitigation of adverse effects of global warming requires accurate flow projections. These projections are generally focused on statistical changes in hydrologic signatures (e.g., 100-year floods, 30-year or 7-day minimum flows), which are obtained from statistical analyses of simulated flows under baseline and future conditions. However, hydrological models used for these simulations are traditionally calibrated to reproduce entire flow series, rather than statistical properties of the hydrologic signatures. Therefore, there is a dichotomy between criteria for hydrological model evaluation/selection and the actual requirements of climate change impact studies.

Here, we address this dichotomy by providing novel insights into the assessment of model suitability for climate change impact studies. Specifically, we analyse performance of numerous spatially-lumped, bucket-style hydrological models in reproducing observed distributions and trends in the annual series hydrologic signatures relevant for hydrologic impacts studies under climate change. Model performance in reproducing distributions of the signatures is evaluated by applying the Wilcoxon rank sum test. We consider that a model properly reproduces trends in the series of signatures if either series of observed and simulated signatures both exhibit lack of statistically significant trends, or both series exhibit statistically significant trends of the same sign. Statistical significance of the trends is estimated by applying the Man-Kendall test is used, while signs of the trends are obtained from the San slope. Model performance is also quantified in terms of commonly used numerical indicators, such as Nash-Sutcliffe or Kling-Gupta coefficients.

Our results, which are based on streamflow simulations in 50 high-latitude catchments in Sweden, show that high model performance quantified in terms of traditional performance indicators does not necessarily imply that distributions or trends in series of hydrologic signatures are well reproduced, and vice-versa. Therefore, these two aspects of model performance are distinct and complementary, and they require separate evaluation analyses. Accurate reproduction of statistical properties of hydrologic signatures relevant for climate change impact studies is essential for improving the credibility of future flow projections. We, therefore, recommend that the traditional process of selecting hydrological models for the impact studies should be enhanced with assessments of model ability to reproduce distributions and trends in the hydrologic signatures.

How to cite: Todorović, A., Grabs, T., and Teutschbein, C.: Assessment of Suitability of Hydrological Models for Climate Change Impact Studies , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11463, https://doi.org/10.5194/egusphere-egu22-11463, 2022.

The goal of this contribution is to demonstrate deficiencies that we observe in hydrological modelling studies. Our hope is that awareness of potential mistakes, errors, and habits will support accurate communication and analysis — and consequently lead to better modelling practises in our community.

By deficiencies, we broadly mean wrong assumptions, false conclusions, and artificial limitations that impair our modelling efforts. To give some explicit examples:

• Model calibration: Often, only two data splits are used: one for model calibration and one for model validation. To provide a robust estimate of model quality on unseen data, one should, however, involve a three-way split: a calibration set used for parameter adaptation, a validation set used for hyperparameter tuning and intermediate model evaluations, and a test set used only once to derive the final, independent model accuracy.
• Artificial restrictions: Studies often restrict modelling setups to specific settings (e.g., model classes, input data, or objective functions) for comparative reasons. In general, one should use the best available data, inputs, and objective functions for each model, irrespective of the diagnostic metric used for evaluation and irrespective of what other models are (able to) use.
• (Missing) Model rejection: Although benchmarking efforts are not an entirely new concept in our community, we do observe that the results of model comparisons are seemingly without consequences. Models that repeatedly underperform on a specific task continue to be used for the same task they were just proven not to be good for. At some point, these models should be rejected and we as a community should move forward to improve the other models or develop new models.
• Interpretation of intermediate states: Many hydrologic models attempt to represent a variety of internal physical states that are not calibrated (e.g., soil moisture). Unfortunately, these states are often mistaken for true measurements and used as ground truth in downstream studies. We believe that (unless the quality of these states was evaluated successfully), using intermediate model outputs is of high risk, as it may distort subsequent analyses.
• Noise: Albeit it is commonly accepted that hydrological input variables are subject to large uncertainties and imprecisions, the influence of input perturbations is often not explicitly accounted for in models. 
• Model  complexity: We aim to model one of the most complex systems that exists, our nature. In practice, we will only be able to obtain a simplified representation of the system. However, we should not reduce complexity for the wrong reasons. While there is a tradeoff between simplicity and complexity, we should not tend towards the most simple models, such as two- or three-bucket models.

Our belief is that modelling should be a community-wide effort, involving benchmarking, probing, model building, and examination. Being aware of deficiencies will hopefully bring forth a culture that adheres to best practises, rigorous testing, and probing for errors — ultimately benefiting us all by leading to more performant and reliable models.

How to cite: Klotz, D., Gauch, M., Nearing, G., Hochreiter, S., and Kratzert, F.: Deficiencies in Hydrological Modelling Practices, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12403, https://doi.org/10.5194/egusphere-egu22-12403, 2022.

Probabilistic predictions describe the uncertainty in modelled streamflow, which is a critical input for many environmental modelling applications.  A residual error model typically produces the probabilistic predictions in tandem with a hydrological model that predicts the deterministic streamflow. However, many objective functions that are commonly used to calibrate the parameters of the hydrological model make (implicit) assumptions about the errors that do not match the properties (e.g. of heteroscedasticity and skewness) of those errors. The consequence of these assumptions is often low-quality probabilistic predictions of errors, which reduces the practical utility of probabilistic modelling. Our study has two aims:

1. Evaluate the impact of objective function inconsistency on the quality of probabilistic predictions;

2. To demonstrate how a simple enhancement to a residual error model can rectify the issues identified with inconsistent objective functions in Aim 1, and thereby improve probabilistic predictions in a wide range of scenarios.

Our findings show that the enhanced error model enables high-quality probabilistic predictions to be obtained for a range of catchments and objective functions, without requiring any changes to the hydrological modelling or calibration process. This advance has practical benefits that are aimed at increasing the uptake of probabilistic predictions in real-world applications, in that the methods are applicable to existing hydrological models that are already calibrated, simple to implement, easy to use and fast. Finally, these methods are available as an open-source R-shiny application and an R-package function.

How to cite: Thyer, M., Hunter, J., McInerney, D., and Kavetski, D.: High-quality probabilistic predictions for existing hydrological models with common objective functions   , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13083, https://doi.org/10.5194/egusphere-egu22-13083, 2022.

Atmospheric rivers (ARs) are filaments of extensive water vapor transport in the lower troposphere. They are important triggers of heavy rainfall events, contributing to more than 50% of the rainfall sums in some regions along the western coast of North America. ARs play a crucial role in the distribution of water, but can also cause natural and economical damage by facilitating heavy rainfall. Here, we investigate the large-scale spatio-temporal synchronization patterns of heavy rainfall triggered by ARs over the western coast and the continental regions of North America.

For our work, we employ daily ERA5 rainfall estimates at a spatial resolution of 0.25°x0.25° latitude and longitude which we threshold at the 95^th percentile to obtain binary time series indicating the absence or presence of heavy rainfall. Subsequently, we separate periods with ARs and periods without ARs and investigate the differing spatial synchronization pattern of heavy rainfall. To establish that our results are not dependent on the chosen AR catalog, this is conducted in two different ways: first based on a recently published catalog by Gershunov et al. (2017) , and second based on a catalog constructed using the IPART algorithm (Xu et al, 2020). For both approaches, we subsequently utilize event synchronization and a complex network framework to reveal distinct spatial patterns of heavy rainfall events for periods with and without active ARs. Using composites of upper-level meridional wind, we attribute the formation of the rainfall synchronization patterns to well-known atmospheric circulation configurations, whose intensity scales with the strength of the ARs. Furthermore, we demonstrate that enhanced AR activity is going in hand with a suppressed seasonal shift of the characteristic meridional wind pattern. To verify and illustrate how small changes of the high-level meridional wind affect the distribution of heavy rainfall, we, additionally, perform a case study focusing on the boreal winter.

Our results indicate the strong sensitivity of the intensity, location, frequency, and pattern of synchronized heavy rainfall events related to ARs to small changes in the large-scale circulation.

How to cite: Wolf, F., Vallejo-Bernal, S. M., Boers, N., Marwan, N., Traxl, D., and Kurths, J.: Spatio-temporal synchronization of heavy rainfall events triggered by atmospheric rivers in North America, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2993, https://doi.org/10.5194/egusphere-egu22-2993, 2022.

In Denmark, about half of the agricultural land is artificially drained. These drainage systems have a significant effect on the hydrological system. Knowledge about the spatio-temporal distribution of drain flow is crucial to understand aspects such as groundwater recharge, streamflow partitioning and nutrient transport. Still, quantification of drain flow at regional and large scale remains a major challenge: Data on the distribution of the installed subsurface drainage system are scarce, as are measurements of drain flow. Large-scale simulations of drain with physically-based hydrological models are challenged by scale, as drain flow is controlled by small-scale variations in groundwater depth often beyond the model resolution. Purely data-driven models can struggle representing the complex controls behind drain flow.

Here, we suggest a metamodel approach to obtain a more accurate estimate of generated drain flow at high spatial resolution of 10 m, combining physically-based with data-driven models. Our variable of interest is drain fraction, defined as the ratio between drain flow and recharge per grid cell, which is an indicator for flow partitioning between drain and recharge to deeper groundwater.

First, we setup distributed, integrated groundwater models at 10 m grid resolution for 28 Danish field-scale drain catchments with observations of drain flow timeseries. A joint calibration of these field-scale models against observed drain flow resulted in an average KGE of above 0.5. Subsequently, the simulated drain fractions from the field-scale models were used to train a decision tree machine learning algorithm. This metamodel uses various mappable covariates (topography and geology-related) available at high resolution for all of Denmark. The metamodel then is used to predict drain fractions, within its limits of applicability, across relevant areas of Denmark with significant drain flow outside of the field-scale models.

Eventually, the predicted drain fractions are intended to inform national, large-scale physically based hydrological models: An improved representation of drain can, for example, make those models more fit to improve national targeted nitrate regulation.

How to cite: Schneider, R., Mahmood, H., Frederiksen, R. R., Højberg, A. L., and Stisen, S.: Prediction of drain flow fraction at high spatial resolution by combining physically based models and machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3694, https://doi.org/10.5194/egusphere-egu22-3694, 2022.

Soil environments are naturally governed by a multitude of interdependent chemical, biological, and physical processes that define their macro-state. In the context of farming these features are further complemented and affected by anthropogenic activities (ploughing, fertilizing, use of pesticides, etc.) that systematically aim to change soil and plant environments to enhance yield, but often with unforeseen detrimental effects (biodiversity loss, erosion, etc.). Assessing strategies for sustainable environmental management is therefore a highly challenging task that is often accompanied by incomplete knowledge of systemic feedback mechanisms and a lack of continuous and reliable data. 

To address this issue, we investigate the use of complexity metrics from information theory to gain insights about underlying patterns of multivariate soil systems and their potential implications for time series analysis. Here we apply existing methods for the processing and analysis of similar systems, we verify current theories about the dynamics and mechanisms of ecological processes in time and study innate interactions between separate components. Thereby, we will use available agricultural datasets that display a wide range of soil properties and explore several notions of complexity approaches, such as entropy measures (e.g., Permutation entropy, transfer entropy, Shannon entropy) and the Hurst exponent. Characteristic features will be highlighted that can be used to enhance time series prediction accuracy and systemic soil functions understanding.

How to cite: Corpaci, L. C., Raubitzek, S., and Mallinger, K.: Information theory approach for enhancing time series analysis and predictability of soil environments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4076, https://doi.org/10.5194/egusphere-egu22-4076, 2022.

Abstract

Flood frequency curves are usually fitted to short time series of observations, leading to great uncertainties mainly for high return periods. However, reliable estimates are required for designing and assessing safety of hydraulic infrastructure, such as bridges and dams. Therefore, flood frequency analyses based on instrumental data collected at gauging stations can be improved by incorporating available information about historical floods before the beginning of the systematic period. This study presents how to identify and integrate all the information available, in order to improve flood frequency curve estimates. The Cuevas de Almanzora Dam located in southeast Spain is selected as case study.

The Cuevas de Almanzora Dam catchment has an area of 2122 km² with a mean annual precipitation of 316 mm. However, daily precipitation can be higher, such as 600 mm for the 1973 flood event. Flood data are available at a gauging station located in the River Almanzora upstream of the dam, with a draining catchment of 1850 km². The systematic period is 1963-2008 with information about 36 annual maximum floods. The largest flood in the 20^th century was recorded at the gauging station in 1973. A two-dimensional (2D) hydrodynamic model of the River Almanzora was calibrated with such information.

Historical information about floods has been collated from local newspapers, books, chronicles, research papers, photographs, national archives of historical floods, and municipal archives. The three largest floods in the River Almanzora between 1830 and 1963 were identified, extending the systematic period to a total period of 191 years. Information about water depths and flood extensions at different cross sections of the River Almanzora were collected. The 2D hydrodynamic model was used to estimate the peak discharges in such historical flood events.

After the end of the systematic period, the hydrograph of the great 2012 flood event was estimated from the data recorded at the Cuevas de Almanzora reservoir. A rainfall-runoff model was calibrated in the catchment with 1-h precipitation data to estimate the flood hydrograph at the gauging station.

The five historical floods that exceed the perception threshold in the period 1830-2020 were integrated with the annual maximum floods extracted from the systematic data, using five techniques to incorporate historical information in the flood frequency curve. The Generalized Extreme Value (GEV) and the Two-Component Extreme Value (TCEV) distribution functions were considered. The best fit was selected considering the accuracy and the uncertainty of estimates by a stochastic procedure. Flood quantiles for the highest return periods triple the estimates obtained by using only the systematic data.

The methodology proposed can improve the reliability of flood quantile estimates, mainly in arid regions where the lack of information about the rare greatest flood, which can exceed several times the mean magnitude of floods in the systematic period, can lead to strong underestimates for the highest return periods that are needed to design and assess the safety of hydraulic infrastructure.

Acknowledgments: This research has been supported by the project SAFERDAMS (PID2019-107027RB-I00) funded by the Spanish Ministry of Science and Innovation.

How to cite: Fernandez-Palomares, M. A. and Mediero, L.: Integrating historical information, systematic data, and rainfall-runoff modelling to improve flood frequency estimates, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4933, https://doi.org/10.5194/egusphere-egu22-4933, 2022.

Beach cast is a material deposited on beaches after being washed up by storm (or tidal movement). The composition of beach cast usually includes seagrass or algae fragments, wracks of land plants and other materials of natural origin, (anthropogenic) marine litter, including plastic debris and microplastics. Beach casts monitoring is of current interest for beach management and maintenance of the sandy shores for recreational purposes, tracing marine litter transport and dispersion, evaluating environmental contamination by microplastiсs.

Large patches of marine debris appear on beaches after stormy weather. However, little is known about the sea state that precedes the formation of beach casts. From an observer's point of view, beach casts occur at random locations along the coast at unpredictable times. They may even be washed back to the sea at some time later. This work aims to disclose characteristic features of temporal variations of surface wave field parameters, which lead to beach cast formation.

Results of incidental surveys of the northern coast of the Sambia Peninsula, stretching from west to east in the southeastern part of the Baltic Sea, were analyzed. The presence of beach cast (at one or more locations) was observed during 234 days of 2011-2021. Some of the observations were performed during or shortly after the ending of the beaching process. Field information was collated with a freely available re-analysis database on surface waves (http://marine.copernicus.eu). Surface wave spectrum parameters were picked up from the database at the geographical point corresponding to the coastal zone's open-sea limit. Elements of Bayesian analysis were applied to overcome the lack of information on the very time of the beach casts formation and/or the unknown duration of the beaching process.

The analysis shows the values of significant wave height, peak period, and wave direction, which occurred before the beach cast appearance more often than follows from the overall time statistics ("climate"). A separate analysis of only recently formed beach casts made it possible to determine the evolution of wave spectrum parameters during the beaching process. Data suggests that most of the beach cast events on this coast are preceded by waves caused by cyclone passages from the northern direction.

Data analysis is carried out by I.I., with the support of the Russian Science Foundation, grant No 21-77-00027. Beach surveys are carried out by E.E. voluntarily and with partial support from IO RAS state assignment.

How to cite: Isachenko, I. and Esiukova, E.: Analysis of wind wave statistics preceding beach cast events on the southeastern shore of the Baltic Sea (Kaliningrad region): preliminary results, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5690, https://doi.org/10.5194/egusphere-egu22-5690, 2022.

Process-based hydrological models seek to represent the dominant hydrological processes in a catchment. However, due to unavoidable incompleteness of knowledge, the construction of “fidelius” process-based models depends largely on expert judgment. We present a systematic approach that treats models as hierarchical assemblages of hypotheses (conservation principles, system architecture, process parameterization equations, and parameter specification), which enables investigating how the hierarchy of model development decisions impacts model fidelity. Each model development step provides information that progressively changes our uncertainty (increases, decreases, or alters) regarding the input-state-output behavior of the system. Following the principle of maximum entropy, we introduce the concept of “minimally restrictive process parameterization equations—MR-PPEs,” which enables us to enhance the flexibility with which system processes can be represented, and to thereby investigate the important role that the system architectural hypothesis (discretization of the system into subsystem elements) plays in determining model behavior. We illustrate and explore these concepts with synthetic and real-data studies, using models constructed from simple generic buckets as building blocks, thereby paving the way for more-detailed investigations using sophisticated process-based hydrological models. We also discuss how proposed MR-PPEs can bridge the gap between current process-based modeling and machine learning. Finally, we suggest the need for model calibration to evolve from a search over “parameter spaces” to a search over “function spaces.”

How to cite: Gharari, S., Gupta, H., Clark, M., Hrachowitz, M., Fenicia, F., Matgen, P., and Savenije, H.: Understanding the Information Content in the Hierarchy of Model Development Decisions: Learning From Data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6761, https://doi.org/10.5194/egusphere-egu22-6761, 2022.

The consequences of ever-increasing human interference with freshwater systems, e.g., through land-use and climate changes, are already felt in many regions of the world, e.g., by shifts in freshwater availability and partitioning between green (evapotranspiration) and blue (runoff) water fluxes around the world. In this study, we have developed a machine learning (ML) model for the possible prediction of green-blue water flux partitioning (WFP) under different climate, land-use, and other landscape and hydrological catchment conditions around the world. ML models have shown relatively high predictive performance compared to more traditional modelling methods for several tasks in geosciences. However, ML is also rightly criticized for providing theory-free “black-box” models that may fail in predictions under forthcoming non-stationary conditions. We here address the ML model interpretability gap using Shapley values, an explainable artificial intelligence technique. We also assess ML model predictability using a dissimilarity index (DI). For ML model training and testing, we use different parts of a total database compiled for 3482 hydrological catchments with available data for daily runoff over at least 25 years. The target variable of the ML model is the blue-water partitioning ratio between average runoff and average precipitation (and the complementary, water-balance determined green water partitioning ratio) for each catchment. The predictor variables are hydro-climatic, land-cover/use, and other catchment indices derived from precipitation and temperature time series, land cover maps, and topography data. As a basis for the ML modelling, we also investigate and quantify (through data averaging over moving sub-periods of different time lengths) a minimum temporal aggregation scale for water flux averaging (referred to as the flux equilibration time, T_eq) required to reach a stable temporal average runoff (and evapotranspiration) fraction of precipitation in each catchment; for 99% of catchments, T_eq is found to be ≤2 years, with longer T_eq emerging for catchments estimated to have higher ratio R_gw/R_avg, i.e., higher groundwater flow contribution (R_gw) to total average runoff (R_avg). The cubist model used for the ML modelling yields a Kling-Gupta efficiency of 0.86, while the Shapley values analysis indicates mean annual precipitation and temperature as the most important variables in determining the WFP, followed by average slope in each catchment. A DI threshold is further used to label new data points as inside or outside the ML model area of applicability (AoA). Comparison between test data points outside and inside the AoA reveals which catchment characteristics are mostly responsible for ML model loss of predictability. Predictability is lower for catchments with: larger T_eq and R_gw/R_avg; higher phase lag between peak precipitation and peak temperature over the year; lower forest and agricultural land fractions; and aridity index much higher or much lower than 1 (implying major water or energy limitation, respectively). Identifying such predictability limits is crucial for understanding, and facilitating user awareness of the applicability and forecasting ability of such data-driven ML modelling under different prevailing and changing future hydro-climatic, land-use, and groundwater conditions.

How to cite: Althoff, D. and Destouni, G.: Partitioning of green-blue water fluxes around the world: ML model explainability and predictability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8321, https://doi.org/10.5194/egusphere-egu22-8321, 2022.

Discerning the dynamics of complex systems in a mathematically rigorous and physically consistent manner is as fascinating as intimidating of a challenge, stirring deeply and intrinsically with the most fundamental Physics, while at the same time percolating through the deepest meanders of everyday life.

The socio-natural coevolution in hydroclimate dynamics is an example of that, exhibiting a striking articulation between governing principles and free will, in a stochastic-dynamic resonance that goes way beyond a reductionist dichotomy between deterministic and probabilistic approaches and between physical principles and information technologies.

Subjacent to the conceptual and operational interdisciplinarity of that challenge, lies the simple formal elegance of a “lingua franca” for communication with Nature. This emerges from the innermost mathematical core of Information Physics articulating the wealth of insights and flavours from frontier natural, social and technical sciences in a coherent, integrated manner.

Communicating thus with Nature, we equip ourselves by developing formal innovative methodologies and technologies to better appreciate and discern complexity in articulation with expert knowledge. Thereby opening new pathways to assess and predict elusive non-recurrent phenomena such as irreversible geophysical transformations and extreme hydro-meteorological events in a coevolutionary climate.

Our novel advances will be shared across the formal, structural and functional theory of the Information Physics of Coevolutionary Complex Systems, along with the analysis, modelling and decision support in crucial matters afflicting our environment and society, with special emphasis onto hydroclimatic problems.

In an optic of operational empowerment, some of our flagship initiatives will be addressed such as Earth System Dynamic Intelligence and Quantum Information Technologies in the Earth Sciences (QITES) on a synergy among our information physical and quantum technological developments.

The articulation between these flagships leverages our proprietary synergistic quantum gravitational and electrodynamic QITES constellation from deep undersea to outer space to take the pulse of our planet, ranging from high resolution 4D sensing and computation to unveiling early warning signs of critical transitions and extreme events.

How to cite: Perdigão, R. A. P. and Hall, J.: Deciphering Hydroclimatic Complexity with Information Physics and Quantum Technologies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8372, https://doi.org/10.5194/egusphere-egu22-8372, 2022.

The observed retreat of mountain glaciers on a global scale promotes the formation and growth of glacial lakes across newly exposed ice-free areas. In mainland Norway, this process drives the rise in glacial lake outburst floods (GLOFs), posing a considerable threat to people and infrastructure  downstream. Moreover, many glacial lakes are used as reservoirs for hydropower production and thus represent an important energy source, emphasizing the need for continuous monitoring of glacial lake life cycles.

Remote sensing is currently the most efficient technique for tracking changes in glacial lakes, understanding their responses to climate change and observing lakes prone to GLOFs. Recent advances in machine learning techniques have presented new opportunities to automatize glacial lake mapping over large areas. For the first time, this study presents a Norway-wide reconstruction of glacial lake changes through the last three decades using  machine learning algorithms and long-term satellite observations. It contrasts the performance of two classification methods - maximum likelihood  classification (MLC) and support vector machine (SVM) - to outline glacial lakes and study their evolution using the Landsat series and Sentinel-2 images.

This study zooms into the pros and cons of each classification method and satellite product through the prism of glacial lake processes occurring over  disparate temporal and spatial scales - from lake formation, growth and dissociation from the proximal glaciers to the aftermath of rapid GLOF events. Based on this analysis, I conclude that the recognition skills of supervised classification methods largely depend on the quality of satellite images and careful selection of training samples. Some of the factors that adversely affect the classification results are unfavourable weather conditions such as  cloud, snow and ice cover, image disturbances through atmospheric corrections and shadows on slopes that lead to misclassifications. Regardless of higher spatial and temporal resolution, Sentinel imagery has not revealed significant advantages over Landsat but has shown a potential for their  complementary use to continue glacial lake observations in the future. The performance of SVM is clearly superior to MLC, but it is difficult to use over  large spatial scales, at least in the form it is currently implemented in ENVI.

How to cite: Moghaddam, G., Andreassen, L. M., and Rogozhina, I.: Life cycles of glacial lakes in Norway: Insights from machine learning algorithms on Landsat series and Sentinel-2, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10119, https://doi.org/10.5194/egusphere-egu22-10119, 2022.

The fact that both the Lorenz 1963 and 1969 models suggest finite predictability is well-known. However, it is less known that mechanisms (i.e., sensitivities) within both models that lead to finite predictability are different. Additionally, the mathematical and physical relationship between these two models has not been fully documented. New analyses along with literature review are performed here to provide insights on the similarities and differences for these two models. The models represent different physical systems, one for convection and the other for barotropic vorticity. From theperspective of mathematical complexities, the Lorenz 1963 (L63) model is limited-scale and nonlinear; and the Lorenz 1969 (L69) model is closure-based, physically multiscale, mathematically linear, and numerically ill-conditioned. The former possesses a sensitive dependence of solutions on initial conditions, known as the butterfly effect, and the latter contains numerical sensitivities due to an ill-conditioned matrix with a large condition number (i.e., a large variance of growth rates).

Here, we illustrate that the existence of a saddle point at the origin is a common feature that produces instability in both systems. Within the chaotic regime of the L63 nonlinear model, unstable growth is constrained by nonlinearity, as well as dissipation, yielding time varying growth rates along an orbit, and, thus, a dependence of (finite) predictability on initial conditions. Within the L69 linear model, multiple unstable modes at various growth rates appear, and the growth of a specific unstable mode (i.e., the most unstable mode during a finite time interval) is constrained by imposing a saturation assumption, thereby yielding a time varying system growth rate. Both models have been interchangeably applied for qualitatively revealing the nature of finite predictability in weather and climate. However, only single type solutions were examined (i.e., chaotic and linearly unstable solutions for the L63 and L69 models, respectively), and the L69 system is ill-conditioned and easily captures numerical instability. Thus, an estimate of the predictability limit using either of the above models, with or without additional assumptions (e.g., saturation), should be interpreted with caution and should not be generalized as an upper limit for predictability of the atmosphere.

How to cite: Shen, B.-W., Pielke, Sr., R., and Zeng, X.: One Saddle Point and Two Types of Sensitivities Within the Lorenz 1963 and 1969 Models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10890, https://doi.org/10.5194/egusphere-egu22-10890, 2022.

Soil moisture affects gross primary production through two pathways. First, directly through
drought stress and second, indirectly through temperature via evaporative cooling of the near-
surface atmospheric layer. Because it is not possible to disentangle these effects experimentally
at a biome level, Humphrey et al. (2021) has used Earth system model experiments in which soil
moisture is fixed to its seasonal cycle and evaluated the effects on gross primary production. In
contrast, we aim to use causal modeling to infer impacts directly from observation. To predict the
effects of soil moisture anomalies on gross primary production, we extend existing causal mod-
eling frameworks to cover situations where two variables influence one other. A major challenge
in applying causal modeling here lies in the bidirectional relationship between soil moisture and
temperature via evapotranspiration. On one hand, higher temperature leads to higher evapotran-
spiration and thus lower soil moisture. On the other hand, lower soil moisture leads to lower evap-
otranspiration and thus higher temperatures. Therefore, neither soil moisture nor temperature can
be adequately modeled as a function of the other. To address this challenge, we extend existing
causal modeling frameworks to account for these situations where the variables are not functions
of each other but are determined by equilibrium. We show that our method identifies the correct
links between variables in synthetic data. We further evaluate whether our new approach is con-
sistent with the results of Humphrey et al. (2021) based on idealized counterfactual experiments
using Earth system models. To this end, we use the control runs of the models to directly predict
the results of the idealized counterfactual experiment as proof-of-concept. Finally, we apply our
method to observations and determine the direct and indirect effect of soil moisture anomalies on
gross primary production.

References:
Vincent Humphrey, Alexis Berg, Philippe Ciais, Pierre Gentine, Martin Jung, Markus Reichstein,
Sonia I Seneviratne, and Christian Frankenberg. Soil moisture–atmosphere feedback dominates
land carbon uptake variability. Nature, 592(7852):65–69, 2021.

How to cite: Reimers, C., Winkler, A., Humphrey, V., and Reichstein, M.: Disentangling direct and indirect soil moisture effects onecosystem carbon uptake with Causal Modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11148, https://doi.org/10.5194/egusphere-egu22-11148, 2022.

The water environment is an important carrier of material processes, in which a large number of biochemical reactions and energy transmission processes occur. High-frequency water quality observation can help us understand the dynamics of solute transport in the water environment. The information-theoretic approaches to system dynamics are receiving more and more attention that it reveals the new laws and support board applications. Configuration entropy (H^*) is one of the derivative indexes that originated from information entropy, which was first introduced in 1994 to describe the disorder in random morphologies. It can reflect the complexity of the system under different space or time resolutions. Researchers have analyzed the characteristics of configuration entropy in some of the environment scenarios, such as spatial arrangement of rainfall. In this paper, we analyzed the space structure of river basin water quality dynamic system under the network topology of rivers, together with the time structure of water quality dynamic system. We calculated the configuration entropy of six water quality parameter data from four monitoring stations at Potomac River in two dimensions of time and space with topological treatment of river water system map. We arranged the high-frequency water quality time series according to different time slices to form a two-dimensional pixel image for calculating configuration entropy and the variation under different time resolutions. Results show that with the increasing length of time slice (from 1 day to 9 days), except pH and turbidity, the configuration entropy curve of other parameters has only one peak (1 day, 1.5 days, 2 days) to the valley (2.5 days and later), which confirms a hypothesis that the configuration entropy will not have a valley when the length of time grid is significantly greater than the width. When the length of the time slice is more than 2.5 days, even if the length of the time slice is increased, the overall shape of configuration entropy curve does not change significantly, suggesting that the configuration entropy of specific water quality parameters did not show temporal heterogeneity in a long-time period observation. We also assumed that temporal fractal phenomena exist in some water quality parameters consistent with previous studies. More analysis is in progress.

How to cite: Pang, T., Jiang, J., Wang, P., Zheng, Y., and Zheng, T.: Configuration entropy analysis of river water quality dynamics under fine time resolution and network topology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12346, https://doi.org/10.5194/egusphere-egu22-12346, 2022.

Understanding the connections in the dynamics of water quality at different locations in a catchment is important for catchment studies and watershed management. Complex network science provides effective ways to uncover connections and patterns in catchment water quality dynamics. This study  investigates the spatial connections in each of five water quality indexes (Chloride, Dissolved oxygen, pH, Total nitrogen, and Total organic carbon) and flow rate in the Chesapeake Bay basin, USA.High-resolution data (five minutes) from 120 water quality monitoring stations are analyzed. 1) The clustering coefficient (CC) and degree distribution methods are employed to examine the connections and identify the type of the water quality networks. The results indicate that the networks of water quality parameters are  scale-free. The power-law (γ) values of for the networks of Chl, DO, flow rate, pH, TN, TOC are 0.74, 0.67, 0.37, 2.0, 0.57 and 1.2, respectively. 2) Monte Carlo simulation of degree distributions and clustering coefficients (CC) shown that all water quality parameters present a decrease in the CC along with the turn down of the threshold of correlation coefficient (R), but the R threshold for DO and flow rate was 0.9. Other water quality parameters showed a sharp decline in the range of correlation coefficient (R) of 0.3-0.6, show a gentle decrease, and then decrease sharply, with an inverse s-curve. 3) All the WQ parameters show stable patterns of CC versus R, for different sizes of networks, arrived by randomly reducing the number of nodes (i.e. stations) of the networks. This seems to indicate that the pattern is an internal systemically feature of the networks, regardless of the node selected for analysis. The variations of CC values for the different stations in the networks  with different R values also help identify the “heat area” of the whole catchment, which  has some nodes with stable large CC. For the different water quality parameters, the heat area is basically the same, except for pH and TN for which the area is much smaller. The present findings on the characteristics, patterns, and drivers of water quality dynamics in catchments have important implications for water quality studies, especially in large networks of monitoring stations.

How to cite: Wen, Q., Jiang, J., and Sivakumar, B.: A complex network perspective on catchment water quality dynamics: characteristics, pattern, and drivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12588, https://doi.org/10.5194/egusphere-egu22-12588, 2022.

Extreme drought has a strong socio-economic impact on the human environment, especially where surface and ground water supplies are significantly reduced due to reduced stream flow, reduced hydroelectric generation, and increased ground water pumping for agricultural and human consumption. This reduction will likely increase in the future as drought is expected to increase in the United States due to global warming and climate change. However, identifying drought is problematic due to the lack of standardized classification or reliable methods for drought prediction. Recently, machine learning techniques have been applied to drought indices to identify drought features and for risk assessment. For this work, we utilize unsupervised machine learning (ML) computational algorithms to identify drought characteristics with a new drought index based on vapor pressure deficit (VPD). The Standardized VPD Drought Index (SVDI) is used to cluster points with common features to characterize spatial and temporal drought characteristics. The SVDI is calculated with the NASA’s Land Surface Assimilation System (NLDAS) data from 1990-2010. Several ML cluster techniques (e.g. HMM, k_means, BIRCH, DBSCAN) are applied to the SVDI to identify known short and long term drought events. Optimized techniques will be applied to downscaled global climate models (e.g. CCSM4, GFDL-ESM2G, and HadGEM2-ES) based on the 8.5 Representative Concentration Pathway (RCP8.5). From the space-time clustering algorithm, we will extract the spatiotemporal information for each identified event as a means of determining the probability of each type of event under global warming in the future.

How to cite: Gamelin, B., Rao, V., Bessac, J., and Altinakar, M.: Machine Learning Methods with the Standardized VPD Drought Index to Identify and Assess Drought in the United States, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13100, https://doi.org/10.5194/egusphere-egu22-13100, 2022.

Remote sensing is one of the major sources of data for the hydrological sciences. This presentation provides an overview of the contributions of Eric Wood to this field, encompassing studies from the last three decades, across multiple continents and different spatial and temporal scales. The remotely sensed variables include, but are not limited to, surface soil moisture content (through active and passive remote sensing), precipitation, and evapotranspiration. A general overview of the field and satellite campaigns in which these methods and products were developed will be presented. A short overview of the application of these products for different purposes is also provided.

How to cite: Pauwels, V.: Contributions of Eric Wood to hydrologic remote sensing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-416, https://doi.org/10.5194/egusphere-egu22-416, 2022.

This presentation will briefly review the scaling and similarity concepts developed by Eric Wood and evaluate their impact on the development of the hydrological science, in particular distributed hydrological modeling.

Eric Wood was a pioneer in fundamental research on scaling and similarity of catchment hydrologic response. He introduced the “representative elementary area” concept that showed that catchment response could be represented in terms of “building blocks” of some minimum size. This thinking launched him into the era of spatially distributed hydrologic modeling. Eric was the first to develop a distributed modeling framework that accounted for the effects of topography and land ­surface–​­atmosphere interactions involving coupled ­water–​­energy dynamics. Many of the distributed modeling concepts Eric pioneered found their way into the Variable Infiltration Capacity (VIC) macroscale hydrology model, which has become a common land surface parameterization scheme in global circulation models used in global change science.

How to cite: Blöschl, G.: Eric Wood’s contributions to Scaling in Hydrology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1900, https://doi.org/10.5194/egusphere-egu22-1900, 2022.

I will reflect on some of Eric’s major accomplishments, and my own experiences from having worked with him for over 40 years.  This will go back to our first professional meeting, at a meeting of the AGU Committee on Network Design in the late 1970s.  It will also include early consulting work, including Love Canal in particular, his leave at the (then) UK Institute of Hydrology in 1984, and work with the late James R Wallis.  I will focus especially on development of the Variable Infiltration Capacity (VIC) model starting in the early 1990s, and its many applications by his group over the last two plus decades.  I’ll finish with reflections on his approach to hydrologic research, and some messages our younger colleagues can take away from his life and contributions.

How to cite: Lettenmaier, D.: Some reflections on Eric Wood’s career, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3054, https://doi.org/10.5194/egusphere-egu22-3054, 2022.

Eric Wood's contributions to distributed modeling were partially motivated by a desire to test the REA hypothesis as well as by a desire to demonstrate the impact of remotely sensed data on hydrologic prediction.  In this brief talk, I will review the advances in distributed modeling, such as high-resolution terrain, distributed hydrometeorological forcings and soil-vegetation parameters, high performance computing and communications, data assimilation, coupled land-atmosphere modeling, that laid the foundation for macroscale and ultimately "hyperresolution" modeling.  These foundational advances exemplify the 3^rd paradigm in hydrology and are moving us towards embracing a 4^th paradigm in hydrology, where we enable a rigorous confrontation of our hypotheses embodied within our models with a range of data types across many locations and spatial-temporal scales.  

How to cite: Peters-Lidard, C.: Distributed Modeling: from REA to hillslope-resolving, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3084, https://doi.org/10.5194/egusphere-egu22-3084, 2022.

Eric F. Wood was a pioneer in large-domain hydrologic modeling. Building on his work on hydrologic scaling in the 1980s, in the 1990s and 2000s Eric led the community in process-based approaches to hydrologic modeling across large geographical domains. Together with Dennis Lettenmaier, Eric developed the open-source Variable Infiltration Capacity (VIC), which became a leading large-domain hydrologic model used by dozens of research groups around the world. The capabilities of VIC advanced by Eric and Dennis' students and postdocs included improved representation of hydrologic scaling relationships, advanced representation of cold region hydrologic processes, new capabilities for large-domain streamflow forecasting, and understanding the sensitivity of large river basins to climate variability and change. Eric's work in leading community model inter-comparison projects (PILPS) and community large-domain modeling studies (GEWEX/GCIP and GEWEX/GAPP) advanced understanding of the limitations of large-domain hydrologic models and helped identify effective strategies for model improvement. It is clear that most large-domain hydrologic models that are in use today are heavily influenced by the legacy of VIC. As the community continues to advance in developing interdisciplinary approaches to Earth System modeling (integrating advances from terrestrial and aquatic ecology and the social sciences), explicitly representing a broader range of natural and human processes, it is increasingly clear that the community is indebted to the contributions of Eric F. Wood.

How to cite: Clark, M.: Celebrating Eric Wood's advances in large domain hydrologic modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5238, https://doi.org/10.5194/egusphere-egu22-5238, 2022.

Eric F. Wood will be remembered as a visionary scientist and mentor to many hydrologists. As a master student, I had the good fortune to read one of his thought-provoking questions: What modelling experiments need to be performed to resolve the scale question? [1]. Further reading of his scientific contributions led me to appreciate the usefulness of the representative elementary area concept (REA) [2] for developing meso- or macro-scale hydrological models that benefit from the subgrid variability of model paramterizations to derive hydrological fluxes at multiple scales. Eric's scientific writings intrigued us so much that they lead to the development of the multiscale parameter regionalization (MPR) [3] technique originally implemented in the mesoscale hydrological model [4] and now applicable to any land surface model to derive seamless parameter fields at continental or global scales [5].

Eric was an early advocate of hyperresolution global land surface modeling and continental drought monitoring and forecasting initiatives [6,7]. His support and motivation were key to devising a project to demonstrate, for the first time, the feasibility of a high-resolution seasonal forecasting and projection system for Europe using a multi-model approach that use the same hyperresolution physiographic datasets and a common river routing model to reduce the predictive uncertainty of the target variables. We called this project the End to End Demonstrator for Improved Decision Making in Europe (EDgE) [8]. This proof-of-concept constitutes now a blueprint for several follow-up projects at national or global scales [e.g., 9].

Eric F. Wood's scientific legacy will shape future developments in land surface modeling and his contributions will keep guiding generations of hydrologists. I was one of the fortunate ones who had the opportunity to know him as a mentor, project partner and friend. In this presentation, I will attempt to synthesize some of his key contributions that are the cornerstone for developing a Digital Twin [11] of the Earth's water cycle.

References

[1] Wood, E. (Ed.): Land Surface, atmosphere interactions for climate modelling: observations, models, and analysis, Kluwer, 1990.
[2] Wood, E. F. et al. https://doi.org/10.1016/0022-1694(88)90090-X 1988.
[3] Samaniego, L. et al. https://doi.org/10.1029/2008WR007327, 2010b.
[4] mhm-ufz.org
[5] Schweppe, R et al. https://doi.org/10.5194/gmd-2021-103. 2021.
[6] Wood, E.F. et al. https://doi.org/10.1029/2010WR010090 2010.
[7] Sheffield, J., Wood, E. F. et al. https://doi.org/10.1175/BAMS-D-12-00124.1, 2014.
[8] Samaniego, L. et al. https://doi.org/10.1175/BAMS-D-17-0274.1 2019
[9] https://www.ufz.de/ulysses
[10] Bauer, P. et al. https://doi.org/10.1038/s41558-021-00986-y 2021

How to cite: Samaniego, L.: From the REA Concept to a High Resolution Digital Twin of the Earth's Water Cycle, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8072, https://doi.org/10.5194/egusphere-egu22-8072, 2022.

One of Eric Wood’s latest contributions was to set forth the needs and challenges for developing hyper-resolution LSMs in the order of ~100-m to 1-km spatial resolution. This expanded the applicability of land surface models (LSMs), to address critical challenges in monitoring terrestrial water.  Particularly, by representing the spatial variability of physical processes and their interactions with water, energy, and carbon fluxes at the fine-scale that are critical to advance monitoring and understanding of processes linked to freshwater dynamics, hydrologic extremes (floods and droughts), food security, water quality, among others. Over the past 10 years, Eric’s visions on hyper-resolution along with the ever-increasing availability of high-resolution environmental datasets, satellite and in-situ observations, computing resources, and the development of novel modeling frameworks provided a fertile environment for hyper-resolution land surface models to flourish. This presentation will review the community’s efforts towards the development of models, processes representation, and supporting datasets. In particular, it will highlight recent advances on leveraging big environmental datasets and machine learning for developing hyper-resolution LSMs’ sub-grid tiling schemes; the role of data assimilation in hyper-resolution LSMs to bridge spatial scale mismatch between satellite and in-situ observations; and applications of hyper-resolution LSM for understanding soil moisture spatial scaling.

How to cite: Vergopolan, N.: Eric Wood’s contributions and recent advances on hyper-resolution land surface modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9726, https://doi.org/10.5194/egusphere-egu22-9726, 2022.

With climate change, mainly drought, the situation of water stress in most Mediterranean countries is worsening with the high demand for agricultural water and the scarcity of water resources. Forecasts have found that more than 33 countries, including Tunisia and Spain, will face extremely high water stress by 2040, threatening agriculture and food security. In this study, we analyze the potential of different drought indices to identify drought periods for two regions with different climates: Kairouan in Tunisia, and Lleida in Spain, and we identify the indices that give more accuracy for cereal yield prediction.

To achieve the objectives of this study, satellite data was used: MODIS (NDVI and LST) and SMOS. Spatial resolution enhancement algorithms have been applied, such as DISaggregation based on Physical And Theoretical scale Change (DISPATCh), to improve the spatial resolution of SMOS from 40 km to 1 km. In this study, we focus on two principal parameters to identify agricultural drought: Soil Moisture Anomaly Index (SMAI) calculated from soil moisture DISPATCh data, which gives an idea of the soil water status and Vegetation Anomaly Index (VAI) derived from MOD13Q1, which reflects the vegetative activity. 

Over the past 10 years, from the 2010/2011 agricultural year to 2019/2020, we have identified dry periods of agricultural drought based on VAI and SMAI. The results show that SMAI can detect more dry periods in space and time than VAI. For the study area in Tunisia, the strongest correlation obtained between wheat yield and SMAI is in November (R = 0.71). This result highlights the importance of water during this period. The correlation between wheat yield and SMAI decreased slightly in January (R=0.55), February (R=0.57), and March (R=0.63). However, the vegetation cover started to appear in January. A stronger, but later, correlation with VAI in March (R=0.63). For the second study area in Spain, Lleida, the correlation between drought index and yield anomaly of wheat and barley was studied separately. For barley, the increase in the correlation between grain yield and VAI started in February (R= 0.71), March (R=0.73), and then April where it reached its maximum (R=0.87). A more important correlation is noted in March with the SMAI which is about 0.8. Similarly, for wheat, the best correlation between yield and SMAI is recorded in March (R= 0.88) and with a slightly less important correlation with VAI of the order of 0.51 in March.

In conclusion, this study shows the interest in improving the spatial resolution of soil moisture to better study agricultural drought and its effect on cereal yield.

How to cite: Khlif, M., Chahbi Bellakanji, A., Escorihuela, M. J., Stefan, V.-G., and Lili Chabaane, Z.: Potential of remote sensing data to analyze the effect of drought on wheat yields in the Mediterranean region: study area Kairouan Tunisia and Lleida Spain, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-291, https://doi.org/10.5194/egusphere-egu22-291, 2022.

Abstract:

Hydrological modelling in karst environments is a difficult task due to the inherent complexity of the karst system and the usual lack of information about its geometrical description. The hydrological processes of karst systems in Mediterranean semiarid environments are particularly difficult to simulate mathematically due to the pattern of long dry periods and short wet periods. In this study, we tested the ability of the open-source SWAT hydrologic modelling code to simulate the behaviour and hydrologic output of a karstic watershed in a Mediterranean semiarid environment (SE Spain). Calibration and first validation were accomplished using a 20-year and 10-year record of stream water discharge, respectively, at the catchment outlet. Additional testing of the model was accomplished using groundwater discharge data from four natural springs in the watershed and by comparing the results of the SWAT model with the SIMPA model (a hydrological model used by the Spanish national water authority to simulate the water balance among others). Likewise, an adapted form of the Nash-Sutcliffe Efficiency (NSE) index for arid environments, ANSE, is presented. Based on results, the simulated behaviour was good and very good (with ANSE values of 0.96 and 0.78 for the calibration and validation periods respectively). SWAT and SIMPA results provide spatial distributions of the main hydrological processes of the watershed, such as aquifer recharge, actual evapotranspiration, and surface runoff, being verified as useful tools for water policy managers in karstic environments.

Keywords:

Water balance; karst aquifer springs; SWAT; SIMPA; ANSE index; Mediterranean karstic catchment.

How to cite: Jodar, A., Palacios - Cabrera, T., Bailey, R. T., Melgarejo - Moreno, P., Legua - Murcia, P., and Hussein, E. E.: Evaluation of the water response in a Mediterranean karstic catchment (SE Spain) with the SIMPA and SWAT models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1390, https://doi.org/10.5194/egusphere-egu22-1390, 2022.

Irrigated agriculture is the largest consumer of freshwater in the world, particularly in the South Mediterranean region, that already suffers from water shortages. For a rational and sustainable management of water resources, monitoring the water stress status of plants can contribute to an optimal use of irrigation.

C-band radar data have shown great potential for monitoring soil and vegetation hydric conditions. Over forests, several studies have observed a diurnal cycle in the backscattering coefficient that can reach up to 1 dB between morning and evening measurements acquired by sun-synchronous satellites. This cycle is assumed to be related to the physiological functioning of trees, in particular to the diurnal cycle of the vegetation water content. A recent study also identified a diurnal cycle in the temporal coherence measured over tropical forests. The authors hypothesized that transpiration was the main factor in the decrease in coherence at dawn, especially since winds are almost zero at that time of day. While the diurnal cycle of radar data is well documented over trees, the behavior of annual crops is yet to be investigated. In this context, the objective of this work is to present a preliminary study of this behavior over wheat by assuming that water movement in the plant could lead to a daily cycle of the interferometric coherence and backscattering coefficient.

An experiment funded by LMI TREMA and TOSCA/CNES has been conducted over a winter wheat field in Morocco since January 2020. The experimental setup consists of six C-band antennas installed at the top of a 20 m high tower. It allows the full polarization acquisition of the backscattering coefficient and the interferometric coherence with a 15 minutes time step. The field is also equipped with an eddy covariance and weather stations that allow half-hourly measurements of evapotranspiration and wind speed. In addition to automatic measurements, field campaigns are also carried out to measure soil moisture, surface roughness, vegetation above-ground biomass and cover fraction.

The preliminary analysis of in situ radar acquisitions over the 2020 agricultural season reveals the existence of a diurnal cycle of the interferometric coherence whose amplitude increases with the development of vegetation. In particular, a drop in coherence was observed at dawn. This drop is concomitant with the increase in evapotranspiration, which may indicate that it could be due to the sapflow. On the other hand, low coherence values are recorded at the end of the afternoon, which may be related to wind peaks. For the backscattering coefficient, a good agreement is observed between the evolution of its daily average and the evolution of evapotranspiration. These results, which need to be consolidated, demonstrate the existence of important dependencies between the C-band response and the physiological functioning of wheat, which opens insights for the monitoring of crop water status using radar data acquired at sub-daily timescale. This rather highlights the interest of a future geostationary radar mission.

How to cite: Ouaadi, N., Villard, L., Khabba, S., Frison, P.-L., Ezzahar, J., Kasbani, M., Fanise, P., Chakir, A., Le Dantec, V., Zribi, M., Er-Raki, S., and Jarlan, L.: In situ radar measurements for monitoring the physiological functioning of wheat crops in the semi-arid area, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2768, https://doi.org/10.5194/egusphere-egu22-2768, 2022.

Due to the water shortage and poor management of limited water resources in semi-arid region, the improvement of irrigation efficiency became crucial. In this context, the objective of this work is to estimate water content and evapotranspiration using the HYDRUS-1D model. 

The study was carried out over wheat fields of the R3 perimeter (located in the Haouz plain of Marrakesh-Safi region, Morocco) for the growing season of 2003/2004. Four types of data have been used, namely: data related to the soil, data related to the plant, data related climatic parameters (recorded in a station close to the study site), and data related to the local agricultural practice.

We firstly used the inverse method, available in HYDRUS-1D, in order to estimate the hydrodynamic parameters of cultivated soil. The analysis of the convergence and consistency of this method showed that for correct calibration of the model, it is necessary to take into account the vertical heterogeneity of the soil. Therefore, we proceeded to the manual calibration of the model by testing different choices of initial parameters and taking into account the soil  vertical heterogeneity. The calibration carried out concerned mainly the water content of the soil and the evapotranspiration of the surface.

The simulations of the real evapotranspiration (ET) were carried out using the inputs obtained for the manual calibration. The results obtained by the HYDRUS-1D model gave an overestimation of the soil water content. This underestimation can be explained either by an underestimation of the LAI inputs or by the root extraction module that needs to be readjusted.

In the present work, the HYDRUS-1D model was tested, for the first time, over an area of Haouz plain in central Morocco.  The obtained results are not yet final. The model needs to be tested sufficiently over a wide spatio-temporal range. The HYDRUS-1D model is widely used in different regions of the world and the extensive literature reports a good score on the consistency and robustness of the model. Thus we are convinced that, overall, HYDRUS-1D seems to be an adequate model to estimate with acceptable accuracy the water content and the real ET under semi-arid conditions. It is also a promising tool for planning and decision support in the field of water and agro-environmental research.

How to cite: Moumni, A. and Lahrouni, A.: Towards a calibration of the HYDRUS-1D model on a wheat crop in the semi-arid conditions of Haouz region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3121, https://doi.org/10.5194/egusphere-egu22-3121, 2022.

The hydraulic basin of Tensift is a concrete example of diversification and increase of pollutants discharged without treatment into the natural environment. This issue strongly threatens the water resources of this basin and makes it extremely sensitive to pollution, including groundwater that is a strategic resource in this area. The purpose of this study is to simulate two phenomena, which are hydrodynamic operation and leaching of solute in the conditions of the Haouz region.

The study was conducted on the R3 perimeter. It is an irrigated agricultural sector in the region of Sidi Rahal, about 40 km east of Marrakech city, Morocco. To carry out this work, the VS2DI model was chosen for the following reasons: accessibility, reliability, and free of charge. This model popularly uses Cartesian or radial coordinates and allows solving the Richards equation to model the water transfer and the convection-dispersion equation to model the transport of solutes and heat in a porous and variably saturated medium. Our research team collects the data needed for the VS2DI model during the agricultural season of 2002/2003. The collected data is related to climatic conditions, soil, plant, and cultivation practice. 

The results obtained showed that for the scenarios studied the moisture of the upper layers increases and tends towards saturation depending on the value of the flux imposed on the surface. However, the deep layers remain unsaturated for a long time because of drainage. Thus, after one day and for a flux of 12 cm/d, the first 40cm of the soil is saturated. For the 4 cm/d flow, the saturation, during 24h, did not exceed the 30 cm depth. Knowing that these upper layers are subject to strong thermal gradients and root extractions. On the other hand, in the simulations of solute transport, we try to describe the evolution of the degree of contamination of a layer after a period of one day as a function of the imposed water flow and the concentration of solute on the surface.

The results obtained by these simulations show that at 20cm depth the solute concentration starts to change only after a period of 4h and that the rate of change of the concentration is almost linear with time for each given water flux. Beyond 4h, the rate of change of the solute at this depth decreases in a non-linear way with the increase of the water flux imposed on the surface. From these first tests, we can say that this model performs water balances in an acceptable way. It has also been proved that the saturation rate of the soil increases with the increase of the imposed flux and of the moisture of this layer. Finally, it was found that the rate of change of the solute at a given depth decreases non-linearly with the imposed water flux at the surface.

How to cite: el moussaoui, E. H., Moumni, A., and Lahrouni, A.: Simulation study of water balance and solute transport in agricultural soil in Haouz region, Morocco, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3201, https://doi.org/10.5194/egusphere-egu22-3201, 2022.

Mediterranean mountainous regions are strongly affected by flash flood events causing many damages. The vulnerability to flooding in the Moroccan High Atlas, especially in the Tensift basin, has been increasing over the last decades. Rainfall-runoff models can be very useful for flash flood forecasting. However, event-based models require a reduction of their uncertainties related to the estimation of initial moisture conditions before a flood event. Soil moisture may strongly modulate the magnitude of floods and is thus a critical parameter to be considered in flood modeling.

Indeed, several studies have assimilated satellite soil moisture observations into rainfall-runoff models to improve their flood forecasting capabilities.

In order to have a better representation of the watershed states which leads to a better estimation of the streamflow. By exploiting the strong physical connection between soil moisture dynamics and precipitation, it has been shown that satellite soil moisture observations can also be used to improve the quality of precipitation observations.

The aim of this study is to compare daily soil moisture measurements obtained by time domain reflectometry (TDR) at Sidi Rahal station with satellite soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI), in order to estimate the initial soil moisture conditions for each event. The systematic bias between soil moisture products and in situ measurements was corrected using a bias correction method. The correlations between soil moisture products and in situ observations are about 0.77 after the correction.  

However, a modeling approach based on rainfall-runoff observations of 30 sample flood events have been applied, from (2011 to 2018), in the Ghdat basin were extracted and modeled by an event-based rainfall-runoff model (HEC-HMS) which is based on the Soil Conservation Service (SCS-CN), loss model, and a Clark unit hydrograph was developed for simulation and calibration of the 10-minute rainfall runoff.

A similar approach could be implemented in other watersheds in this region for further operational purposes. This method is very satisfactory for reproducing rainfall-runoff events in this small Mediterranean mountainous watershed, the same approach could be implemented in other watersheds in this region. The results of this study indicate that the remote sensing data are theoretically useful for estimating soil moisture conditions in data-sparse watersheds in arid Mediterranean regions.

Keywords: Soil moisture; Floods; Remote sensing; Hydrological modelling, CN method, Mediterranean basin.

How to cite: Benkirane, M., Laftouhi, N.-E., and Khabba, S.: Impact of initial soil moisture on the hydrological response: Application for flood forecasting in the Mediterranean mountainous watershed., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3786, https://doi.org/10.5194/egusphere-egu22-3786, 2022.

In the Atlas Mountains range, streamflow is largely generated from meltwater supplied by the snowpack during spring and early summer. In this manner, snow is considered an important factor which determining water availability in semi-arid and arid mountains. This substantial part of freshwater stored in the form of snow contributes significantly to mountainous runoff. However, the contribution of snow and rain to the annual and multi-annual water balance remain largely unknown. Hydrological modeling is needed to support water resource assessment and management in the Atlas range. As meteorological data is often scarce, the models must be able to simulate the spatiotemporal heterogeneity of forcing variables while maintaining a low data input requirement.

In this study, the performance of the snowmelt runoff model (SRM) is assessed to simulate and forecast daily runoff essentially from snowmelt and rainfall at the Rheraya watershed in the Moroccan High Atlas range over the 2010 - 2016 period. The SRM runoff simulation is tested under two forcing inputs: (i) four snowmelt rates previously estimated by a classical temperature-index model (TI) and three enhanced temperature index models that respectively include the potential clear-sky direct radiation (HTI), the incoming solar radiation (ETI-A), and net solar radiation (ETI-B); (ii) calculated snowmelt from the snow cover area (SCA) products of Moderate-Resolution Imaging Spectroradiometer (MODIS).

All SRM simulated runoff were subjected to calibration and validation through the measured runoff in the Tahanaout weather station. The sensibility of recession coefficients was also evaluated. The SRM simulations results over the validation period show an acceptable performance.

Keywords: Runoff, SRM, snowmelt, SCA, temperature index model; enhanced degree-day models, MODIS, semi-arid climate, Rheraya, High Atlas, Morocco.

How to cite: Bouamri, H., Boudhar, A., and Kinnard, C.: A comparative study of snowmelt runoff modelling at Rheraya watershed in the Moroccan High Atlas Mountains, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3894, https://doi.org/10.5194/egusphere-egu22-3894, 2022.

To ensure food security, the irrigation water demand is increasing with the growth of the population. Therefore, the optimization of irrigation scheduling is compulsory to improve water resources management where soil moisture estimation is an essential component. Over the last decades, remote sensing demonstrated its potential to retrieve soil water content. In this work, we investigate the potential of the Synthetic Aperture Radar (SAR) data in L-band acquired by Advanced Land Observing Satellite-2 (ALOS-2) and C-band data acquired by Sentinel-1 sensor, to estimate soil moisture in heterogenous row crop fields locally irrigated with drips in a semi-arid area in the center of Tunisia.

During SAR data acquisitions, ground data gathering campaigns were carried out over irrigated pepper fields. The in-situ measurements included soil surface parameters such as soil roughness and soil moisture, and pepper biophysical parameters such as vegetation height (H), Leaf Area Index (LAI), and cover fraction (Fc) measurements. Based on the pepper field’s organization and ground observations, we calculated an average soil moisture value per field as the sum of 15% of vegetation row soil moisture and 85% bare soil moisture.

In this context, we suggested the modification of the Water Cloud Model (WCM) to simulate the L-band signal in Horizontal-Horizontal polarization (L-HH) and C-band signal in Vertical-Vertical polarization (C-VV). The total backscattering is simulated as the sum of vegetation row cover contribution weighted by Fc and bare soil contribution weighted by (1-Fc). The vegetation row contribution is calculated as the sum of the scattered signal from pepper seedlings described by vegetation height and bare soil part contribution attenuated by vegetation. The bare soil part is considered as the contribution of two parts where the first is irrigated directly by drips and the second separates two successive pepper seedlings relatively far from water emitters namely the non-irrigated part. The bare soil signal simulations are performed using the Integral Equation model modified by Baghdadi (IEM-B).  

After calibration and validation of the modified WCM using three-folds cross-validation, we investigate the potential of the proposed model by various simulations under constant roughness parameters and different conditions of pepper biophysical parameters and bare soil moisture values. The examination of linear slopes between modeled backscattering and soil moisture measurements highlights that model sensitivity decreases as a function of the increase of pepper vegetation parameters (Fc and H). The sensitivity of the modified WCM is limited where Fc and pepper height are less than 0.4 and 0.5 m, respectively, using L-HH data and lower than 0.3 and 0.3 m using C-VV data. The aforementioned findings revealed the potential of the proposed WCM to simulate SAR signal in heterogeneous context of soil moisture.

How to cite: Ayari, E., Kassouk, Z., Lili-Chabaane, Z., Baghdadi, N., and Zribi, M.: Estimation of soil moisture within drip irrigation context in pepper fields using ALOS-2 and Sentinel-1 data., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3937, https://doi.org/10.5194/egusphere-egu22-3937, 2022.

Droughts can be defined as a climatic phenomenon in which periods of low precipitation may generate water shortages in various parts of the whole of the hydrological cycle. Droughts are natural hazards that usually have severe negative impacts on the economy, society, and environment. Meteorological drought is generally described by the magnitude and duration of the precipitation deficit. Therefore, precipitation is the primary variable often used in the calculation of drought indices, such as the Standardized Precipitation Index (SPI). The SPI is particularly useful for drought monitoring, allowing the identification of different drought types and their impacts on different systems.

Nevertheless, the sparse network of observation stations data-scarce regions, especially in developing countries, is often an obstacle to drought monitoring. To overcome this limitation, remote sensing observations of precipitation are increasingly used over large-scale regions. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data are of particular interest. The CHIRPS monthly precipitation product at 0.05° spatial resolution, for the period 1981 to 2020, and the SPI have been used to study the intensity, duration, and spatial extent of meteorological droughts in Morocco at different time-scales (monthly, seasonal, and annual). The use of several time scales allowed us to highlight the spatial occurrence, temporal characteristics, and impacts of drought on different hydrological and agricultural landscapes of Morocco. Based on a threshold level of SPI, drought event statistics (number of events, duration, severity, and magnitude) over 39 years were derived at the watershed scale to highlight regional differences at multiple time scales. The results of this study allow existing water and agricultural strategies to be adapted to different types of drought. The results will also open perspectives for the development of drought monitoring and early warning systems in Morocco and over Africa.

How to cite: Oukaddour, K., Fakir, Y., and Le Page, M.: Analysis and assessment of meteorological droughts in Morocco using CHIRPS data., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4049, https://doi.org/10.5194/egusphere-egu22-4049, 2022.