This session invites interdisciplinary and transdisciplinary contributions that investigate or support freshwater resilience and risk assessments through the integrated representation of hydrological, social, and ecological processes. Examples of contributions that we hope to receive include, but are not limited to:
[•] Analysis of empirical Earth observations, such as remote sensing, or field-collected social and ecological data to evaluate and track resilience and risk across catchments, regions, and global freshwater systems.
[•] Development or use of process-based models to assess interactions and feedbacks between hydrological, ecological, and societal dynamics.
[•] Applications of machine learning or artificial intelligence techniques to detect, model, and forecast freshwater resilience and/or risk.
[•] Transdisciplinary case studies that work with practitioners, communities, or policy-makers to define system boundaries, support knowledge co-production, or advance frameworks that strengthen freshwater resilience in practice.
[•] Any other studies that work to build a more holistic and actionable understanding of freshwater resilience and risk with insights that may inform strategies to safeguard freshwater’s role in sustaining ecosystems, societies, and Earth systems.
By bringing together researchers across hydrology, ecology, climate science, governance, and social-ecological systems research, this session is motivated to bridge methods and perspectives that are often fragmented and would benefit from greater integration and collaboration.
Orals: Wed, 6 May, 16:15–18:00 | Room -2.62
In the published IPBES Nexus Assessment on the interactions and interlinkages between biodiversity, water, food, health and climate, a set of water response options that deliver solutions to water system challenges were reviewed. Yet this selection emerged from a stepwise procedure that identified 136 response options, globally that deliver across ten water challenges: (i) water and ecosystems, (ii) water and climate, (iii) water quantity, (iv) water quality, (v) water supply and sanitation, (vi) water and culture, (vii) water and equity, (viii) water and governance, (ix) marine, and (x) cross-cutting. Across these water challenges, a minority of response options focused on water alone (n=32), while a large fraction focused on interactions between water and other nexus elements (with one other nexus element n=39, and several nexus n=39). In this presentation, we will show (i) how the response options were identified, (ii) which water challenge was most studied to date, and (iii) what is the current understanding that these response options deliver in relation to freshwater availability. The major findings of the assessment are that a large fraction of humanity’s freshwater demand is used to meet food production, and is dependent on forest for accessible freshwater. Thus a nexus approach to freshwater challenges is fundamental and already being up-took across water challenges, yet few cross across all nexus elements. Further, trade-offs emerge across nexus elements, either when focusing on water or on other elements, and resilience of freshwater therefore depends upon and affects resilience of the whole system, thus would benefit from a more integrated perspective rather than single element approaches.
IPBES Nexus Assessment Water team:
Maria J. Santos, A.A. Kouame, M. Lalika, C.M. Minaverry, S. Oinonen, L. Sandin, M.D. Simatele, N. Rafa, H.S. Embke, A. Gupta, D. Mason-D’Croz, S.C. Phang, T. L. van Huysen, R. Kumar, C. Paukert
How to cite: Santos, M. J. and the IPBES Nexus Assessment Water team: Nexus approaches to freshwater resilience: an overview from the IPBES Nexus assessment water chapter, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19765, https://doi.org/10.5194/egusphere-egu26-19765, 2026.
As global water demand is projected to increase, it remains unclear how and where this demand will be met, or whether it will create new water-crisis hotspots. Projections of meteorological and hydrological droughts already suggest the emergence of new zero-day events. Yet groundwater, a vital buffer for meeting water needs and, at times, the only available freshwater resource, remains underrepresented in current assessments and global models. Groundwater faces substantial threats from overextraction, changes in recharge, and salinization caused by sea-level rise. Unfortunately, models that account for groundwater face significant uncertainties in simulating water table depth, interactions with surface waters, groundwater withdrawals, and groundwater recharge, and are challenging to evaluate. At the same time, these models are not yet capable of simulating water quality processes that may increase water scarcity and are only beginning to represent megacities. In this talk, I will address current uncertainties in global water modeling, examine the implications for water scarcity assessments and risk projections, and outline ideas for further model improvements. Specifically, I will highlight how community approaches to developing a groundwater sector within a model intercomparison project can enhance models and datasets, resulting in improved predictions of future water scarcity hotspots.
How to cite: Reinecke, R.: Uncertainties in modelling global groundwater availability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6248, https://doi.org/10.5194/egusphere-egu26-6248, 2026.
The green water components of the terrestrial water cycle - transpiration, surface soil moisture, and land precipitation - are critical for Earth system stability and ecosystem productivity. However, complex and accelerating human pressures are altering the land surface and water cycle at vast spatial scales. Changes to the terrestrial water cycle can have wide-reaching impacts on ecological (e.g., affecting biodiversity, ecosystem structure and function), and social systems (e.g., affecting crop yields). Despite evidence of considerable and widespread change globally, the resilience of green water variables, or their ability to absorb and recover from disturbances, is not yet well understood. Here, we assess green water resilience using early warning signals (EWS) applied to global satellite-derived time series of green water variables. We map where and how green water resilience is changing, and empirically evaluate these estimates against past abrupt changes to understand where and when EWS are effective.
We show that EWS provide limited but non-negligible additional skill in anticipating abrupt transitions when combined with environmental context. We also find that a wider portfolio of context-appropriate EWS is needed to capture heterogeneous water-vegetation dynamics across eco-hydrological systems. For example, Critical Slowing Down suggests transpiration resilience loss in arid to sub-humid ecosystems, while signals of Critical Speeding Up and flickering are more common in high-latitude and sub-humid systems. Our results highlight emerging risks to terrestrial water cycle dynamics under ongoing anthropogenic pressures.
How to cite: Lotcheris, R., Knecht, N., Wang-Erlandsson, L., and Rocha, J.: Assessing the resilience of the terrestrial water cycle, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6657, https://doi.org/10.5194/egusphere-egu26-6657, 2026.
Assessing freshwater resilience requires understanding how hydrological resources are embedded within coupled social and ecological systems. Global food production and trade play a central role in redistributing freshwater resources across regions, linking local water availability, ecosystem pressures, and societal demand through virtual water flows. Robust, long-term, and transparent datasets are therefore essential to support integrated assessments of freshwater resilience across scales.
Here we present the CWASI 2.0 dataset, an updated open-access database of global agricultural water footprints and virtual water trade. The database provides country-level, annually resolved estimates for over 300 food products over the 1961–2023 period, thereby enabling the analysis of long-term dynamics in freshwater use and redistribution through global food systems.
As in the original CWASI framework, time-varying unit water footprints are applied to FAO-derived production and reconciled bilateral trade data to compute annual virtual water trade matrices and export volumes, but with CWASI 2.0 several significant advancements have been introduced. Firstly, the temporal coverage of the original open-access database has been extended, from 2016 to 2023, providing the most up-to-date publicly accessible dataset of its kind. Secondly, the modelling framework has been enhanced by refining the description of food value chains: re-exports are now modelled with an updated tracing algorithm, food loss and waste material flows are described, and crops are dynamically allocated to animal diets according to historical trends. Thirdly, unit water footprints are now explicitly decomposed into green water (rainwater) and blue water (surface and groundwater) components, allowing for differentiated assessments.
Collectively, these advancements lead to greater consistency and finer granularity in the estimation of both water footprints and virtual water flows, offering a robust data foundation which is able to capture recent shifts in global trade patterns and climate variability, allowing to study emerging vulnerabilities and adaptive responses within the freshwater–society–ecology nexus.
How to cite: Semeria, F., De Petrillo, E., Giordano, V., Tamea, S., Tuninetti, M., and Laio, F.: Tracking agricultural water footprint and virtual water trade across global food systems over the period 1961–2023, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20618, https://doi.org/10.5194/egusphere-egu26-20618, 2026.
The Axarquía region in southern Spain is a hotspot of avocado and mango production in Europe. The region underwent a severe water crisis in 2019-2024 that caused the near-depletion of its large reservoir, a drop of groundwater to sea-level in many parts of the main aquifer, and large socio-economic impacts. Our work examines the causes of this crisis and contrasts the dynamics and management lessons in Axarquía with other regions facing similar challenges. We also reflect on the process and challenges associated with conducting multidisciplinary research on droughts.
Central to our analysis was the examination of water use, demand, availability, accuracy of official estimates, and water management during normal vs. drought periods. We analyzed hydro-meteorological time series (dam inflows and outflows, reservoir and groundwater levels, pluviometry) to identify the duration and intensity of droughts in 1996–2024 and trends and temporal relations between variables. We conducted an in-depth review of drought management plans, land-use regulations, and all water management plans since 1998, verifying the water balance with own estimates based on irrigated area and water permits.
We show that the Axarquía water crisis was caused by a confluence of shorter and long-term dynamics. An unusually severe multi-year meteorological drought directly impacted reservoir and aquifer levels. At the same time, water demand for irrigation has steadily increased over the last two decades because of expanding irrigated avocado and mango plantations, diminishing the resilience to meteorological drought and exacerbating drought propagation. We present evidence of significant management shortcomings, including large uncertainties around water use and availability, lack of extraction metering, permit overallocation, and likely significant irregular freshwater extraction.
We conclude that water management must go beyond traditional supply-side (increase water availability) and demand-side (increase efficiency) measures and impose stricter limits on demand (e.g., caps on irrigated area) combined with a more accurate assessment of water availability (improved models and monitoring) and use (real-time metering at all extraction points), flexible permits based on available water resources, and effective enforcement. These measures combined would reduce the likelihood of future crises under meteorological drought conditions.
Water crises and other extreme events (e.g. floods, wildfires, famines) are almost always the combined result of human–environment interactions and responses. This makes it important to analyze them from a multidisciplinary perspective. In our work, we adopted an explanation-oriented methodology that entails constructing causal histories of interrelated social and biophysical events through abductive reasoning, which seeks to identify the best or most plausible explanations (e.g., Walters & Vayda, 2020).
The challenge of such an analysis is that it is difficult to know a priori what variables are relevant among the many processes involved. Data gathering and analysis were iterative processes, as new insights generated new lines of investigation. Another challenge is that the resulting work does not fit neatly in existing disciplines and journals’ ontological stances. We argue that a causal explanation of the “why” and “how” of social-ecological crises necessarily must adopt a historical and systemic perspective such as a causal-history methodology.
How to cite: Junquera, V., Rubenstein, D. I., Levin, S. A., Hormaza, J. I., Vadillo Pérez, I., and Jiménez Gavilán, P.: Severe water crisis in southern Spain under expanding irrigated agriculture: A multidimensional drought analysis and ontological & epistemological reflections , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10697, https://doi.org/10.5194/egusphere-egu26-10697, 2026.
Agricultural areas are expected to experience more intense rainfall variability in the coming decades, with critical implications for global food production and climate resilience. In Brazil, the world's largest producer of soybean, more than 90% of cropland is rain-fed, making the nation susceptible to shortening rainy seasons, drought and intensifying climate extremes. The Brazilian government plans to expand irrigation to mitigate these risks to its large agricultural sector. Simultaneously, Brazil is incentivizing farmers to grow multiple crops per year in the same tract (multicropping) to ostensibly increase national agricultural output without additional land conversion or deforestation.
Here, we use remote sensing and a crop water model to evaluate how these land-use changes affect evapotranspiration (ET), green water scarcity (an imbalance between rainfall-derived water availability and crop water demand ), and blue water requirements (BWR, the additional water required via irrigation to fulfill crop water requirements not met rainfall) across Brazilian soybean-safrinha maize systems. We find that increasing cropping intensity substantially increases annual ET and irrigation requirements relative to single-cropped, rain-fed systems. As a result, precipitation alone is increasingly insufficient to meet crop water demand, particularly under intensified production and future climate change. We further identify regions where irrigation is most frequently needed and evaluate water resource sustainability under CMIP6 climate projections by estimating monthly blue water scarcity (when human consumption exceeds renewable blue water availability after accounting for environmental flow requirements). The largest increases in BWR and BWS occur in MATOPIBA, an agricultural frontier where agricultural conversion is resulting in rapid biodiversity loss, which may be exaggerated by unsustainable irrigation practices.
Our results highlight a fundamental trade-off between intensification-driven productivity gains and growing pressure on regional water resources. Quantifying these interactions is essential for evaluating the sustainability of irrigation expansion and multicropping as climate adaptation strategies in Brazil’s major agricultural regions.
How to cite: Ruehr, S., Citrini, A., Wendland, E., Dukes, J. S., and Rosa, L.: Multicropping increases water scarcity and irrigation demand in Brazilian croplands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14882, https://doi.org/10.5194/egusphere-egu26-14882, 2026.
Irrigation expansion in Peru represents a complex coupled human-water system where political and economic decisions have reshaped the hydrological landscape. While crucial for food security, this expansion has concentrated water demand in the hyper-arid Pacific coast, creating a path dependency that is increasingly vulnerable to climate variability. This study bridges socio-hydrology and hydro-climatic risk modelling to assess how historically expanded irrigation areas are exposed to future climate change scenarios. We first reconstruct the spatial evolution of irrigated areas from 1950 to 2015, attributing growth to three distinct phases: early global market demands, state-led hydraulic megaprojects (1960–1990), and the recent neoliberal agro-export boom. This historical analysis reveals a strong coastal bias, where infrastructure was developed to conquer the desert for high-value crops. We then assess the future exposure of these established zones using bias-adjusted CMIP6 climate projections (SSP5-8.5) and hydrological simulations from the ISIMIP3b ensemble for the mid-century period (2036–2065). Results reveal a complex seasonal trade-off that heightens the exposure of irrigated systems. While the wet season (NDJFM) is projected to experience increased precipitation and river discharge, particularly in northern regions with increases up to 30%, the dry season (MJJAS) shows a robust drying trend. Of a particular concern, the central and southern coastal valleys, which host the most capital-intensive export agriculture, are identified as "High Drying Exposure" zones, with projected discharge reductions exceeding 20% during peak demand months. This spatial mismatch highlights a severe socio-meteorological risk: the infrastructure built during the historical expansion is now spatially locked into regions facing imminent hydrological scarcity. We conclude that adaptation strategies must urgently pivot from supply-side expansion to demand management to mitigate the collision between anthropogenic water dependency and projected hydro-climatic drying.
How to cite: De la Cruz Montalvo, G. and Pokhrel, Y.: Drivers of Historical Irrigation Expansion in Peru and its Exposure to Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7553, https://doi.org/10.5194/egusphere-egu26-7553, 2026.
Building damage is the primary component of economic damage resulting from flood disasters. Understanding flood damage enables effective disaster risk reduction strategies and community resilience planning. In this study, a comprehensive framework for quantifying flood-induced damage to individual building properties (structural and content) is developed. This methodology combines geospatial data with machine learning and hydrodynamic modeling, as demonstrated through the 2023 flood event in the Dongdian flood storage and detention area (FSDA), Hebei Province, China. The main findings are as follows: (1) building-type classification using random forest algorithms achieved 98.4% accuracy in distinguishing residential, commercial, and industrial structures; (2) two-dimensional hydrodynamic simulations revealed maximum inundation depths predominantly ranging from 1.5 to 2.5 m, with structural damage ratios of 0.2–0.3 and interior property damage ratios of 0.9–1.0; (3) total direct economic damage to building properties in the Dongdian FSDA reached CNY 10.00–11.91 billion (approximately USD 1.42–1.69 billion), with industrial buildings accounting for 68.74% of damage, representing the dominant damage category. This framework delivers a precise flood damage assessment of building properties, transcends traditional survey limitations and offers a globally transferable approach for enhancing disaster resilience and reducing property risks in flood-vulnerable regions, subject to appropriate data availability and parameter adaptation.
How to cite: Jiang, W., pang, Z., Luo, G., Yan, D., Kawasaki, A., and Wu, B.: Development of a building-scale integrated flood damage quantifying framework using a hydrodynamic model and multisource geospatial data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11467, https://doi.org/10.5194/egusphere-egu26-11467, 2026.
More than a billion people around the world experience intermittence in their water supply, where water is delivered for only a few hours per day or a few days per week. This prompts water users to adapt by installing storage tanks or accessing alternative water services to balance service deficits. Adaptation and its resulting costs and impacts are unequally distributed across urban households and have shown to be largely unaccounted for by local water managers. Most studies on household adaptation to intermittent water supply (IWS), which are typically conducted through survey or interview methods, assume income-based heterogeneity to determine adaptive behaviours and do not account for the multiple factors that influence household adaptation. However, our recent research has demonstrated the multiple factors that shape various household responses to IWS in Amman, Jordan, using hierarchical clustering analysis (HCA). Different clusters of households are distinguished by a set of characteristics, including income, water social network, supply duration, relocation, and water quality problems, and related group-specific adaptive strategies such as contacting the water utility or relying on private water services.
Building on this work, we develop a computational model that reproduces piped water use and deficits over time across representative agents from each cluster. We test the model across scenarios of increasing intermittence and population growth, while reproducing trajectories across parameters of pressure and total water availability, giving insights into the inequality and parameters of the system, creating different regimes of water deficit caused by the municipal water supply regime across clusters. We then add the adaptive behaviours of households as recorded in the empirical survey data, to show how adaptation changes water supply resilience across heterogeneous households.
This forms a crucial step towards an equitable and resilience-oriented water management as it reduces several epistemic uncertainties within the system by strengthening the feedback between household adaptation efforts and local water management.
How to cite: Gadge, S., Krueger, E., Vasconcelos, V., and de Roos, A.: Understanding Heterogeneity in Household Adaptation to Intermittent Water Supply: From data to model., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14509, https://doi.org/10.5194/egusphere-egu26-14509, 2026.
Source water protection is one of the most critical barriers in the multi-barrier approach to ensure safe drinking water. However, identifying and prioritizing upstream hazards are still significant challenges for utilities. Several methods, including machine learning, deep learning, and process-based models, have been applied to risk assessment. These approaches are typically developed using numerical scientific measurements. Despite their high analytical precision, traditional monitoring programs are often expensive and difficult to implement in remote regions. They also frequently miss short-term pollution events such as Combined Sewer Overflows (CSOs). Given the uncertainty this discrepancy creates in risk assessment, independent sources of evidence are required to verify assessment results. In such cases, observations from residents and local users of a water body could represent a valuable data source for water quality monitoring and offer essential reference data to validate models where scientific records are limited. To make these qualitative observations comparable with quantitative scientific data, a structured modeling framework is required. Bayesian Networks can address this challenge by quantifying uncertainty and by integrating non-scientific inputs, such as local knowledge, into a structured risk assessment framework.
Using scientific datasets, including municipal CSO records, meteorological observations, and water quality measurements, together with local knowledge from surveys of watercourse users, this study develops a causal top-down Bayesian Network. In this approach, the network structure is constructed a priori based on theoretical causal mechanisms and expert knowledge rather than being learned computationally from data, ensuring physical interpretability. A fuzzy algorithm was used to quantify subjective expert knowledge into the numerical probabilities required for conditional probability tables. The proposed framework compares the capabilities of these distinct data sources in assessing microbial risk levels at selected drinking-water intakes in southern Quebec, Canada. This research investigates the assessment capacity of non-scientific data sources for microbial risk level estimation at drinking-water intakes, comparing their reliability relative to available scientific monitoring records. Compared with findings from previous studies and reports in the same area, this study shows that information reported by water body users can produce realistic and rational estimates of microbial risk levels. The proposed approach offers a lower-cost data source suitable for remote areas and capturing event-based pollution episodes.
How to cite: Mofidi Neyestani, R., Adhav, P., Collado, M., Kammoun, R., McQuaid, N., He, J., Burnet, J.-B., and Dorner, S.: From Local Knowledge to Decision Support: A Causal Top-Down Bayesian Network for Drinking-Water Intake Risk Assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13881, https://doi.org/10.5194/egusphere-egu26-13881, 2026.
Water utilities around the world are faced with escalating climate change impacts. In poorer countries, they are also faced with limited financing, ageing infrastructure and shocks and stresses resulting from rapid urbanization and land use change. This study explores how Ghana’s water utility, Ghana Water Limited (GWL) navigates the pressures imposed by climate change impacts such as floods, drought, and raw water quality deterioration. Using a qualitative case study approach, we employ concepts of resilience, pragmatism and capital portfolio analysis to examine how GWL practices resilience and sustains service delivery under climatic stresses.
Pragmatism is discussed using the four P’s framework (practicality, positionality, pluralism, and provisionality) developed by Brendel (2006) and Shields (2008), and adapted by Schwartz and Boakye-Ansah (2023). Water utilities with resource constraints practice resilience by mobilizing their available capitals (natural, financial, human, physical/infrastructural, institutional and social capital) to address challenges they consider most problematic. Resilience is assumed to stem from the mobilization of resources or capitals that most water utilities in the Global South don’t have access to. So we ask: How does GWL practice and enhances its resilience in a resource-constrained environment where large-scale idealized resilience concepts do not seem applicable? Using interview data from several field visits at the water utility, in which we investigated how different actors in the system recall specific crisis events (pollution caused by gold-mining in the catchment and an episode of drought, both of which led to the shutdown of the water treatment plant for one month, each). The findings highlight that water utilities practice resilience by mobilizing different capitals that they have access to in a pragmatic manner. Interventions that are more resilient are often imperfect and temporary in nature, but in the prevailing contextual realities represent the most suitable option for the utility. The four P’s discussed here highlight that being resilient for water utilities in developing countries requires more than just technical and infrastructure fixes. Rather the degree of resilience depends on capitals that the utility has at its disposal coupled with the experience and adaptability to replace strategies with more effective and impactful ones. For a water utility like GWL, pragmatism appears as both a survival strategy as well as a means of building resilience in situations where permanent, ‘best-practice’ solutions remain elusive.
REFERENCES
Brendel, D. H. (2006). Healing psychiatry : bridging the science/humanism divide. MIT Press. http://site.ebrary.com/id/10173550
Schwartz, K., & Boakye-Ansah, A. (2023, 2023). Pragmatism as an approach for decision-making: Why two Kenyan water utilities opted for pre-paid water dispensers. Utilities Policy, 84, 101623. https://doi.org/https://doi.org/10.1016/j.jup.2023.101623
Shields, P. M. (2008, Mar-Apr). Rediscovering the taproot: Is classical pragmatism the route to renew public administration? Public Administration Review, 68(2), 205-221. https://doi.org/10.1111/j.1540-6210.2007.00856.x
How to cite: Ephraim-Armoo, B. B. A.: Practicing Resilience: How Ghana’s Water Utility Adapts to Climate Change Impacts through Pragmatism, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21571, https://doi.org/10.5194/egusphere-egu26-21571, 2026.
Flood early warning systems are vital for mitigating flood damage, yet limitations in forecasting technologies lead to false alarms and missed events. Repeated occurrences of these issues may cause people to hesitate to take appropriate action (e.g., evacuating or moving assets to safer places) during subsequent warnings, potentially exacerbating flood damage, including both human and economic losses. However, the impact of warning performance on flood damage in Japan has not been examined in the context of actual flood events.
This study empirically examined these effects by applying Bayesian regression analyses to open data on the 2018 Japan Floods in 127 municipalities in four prefectures (i.e., Okayama, Hiroshima, Ehime, and Fukuoka) for which data were available on the real-time flood warning map (Kouzui Kikikuru in Japanese) during the 2018 Japan Floods, which provides limited open data on warning performance. Based on these data, the false alarm ratio (FAR) and missed event ratio (MER) for each municipality before the 2018 Japan Floods were calculated and used as explanatory variables. The outcome variables were (1) fatalities, (2) injuries, (3) economic losses to general assets, and (4) economic losses to crops during the floods.
The results indicate that a higher FAR was associated with an increase in fatalities, injuries, and economic losses to general assets. By contrast, no prominent positive effect of MER was found for any outcome variable. These findings provide valuable insights for improving warning systems and guiding future research.
This presentation is based on our recent publication in Journal of the Meteorological Society of Japan. Ser. II (DOI: 10.2151/jmsj.2025-025).
How to cite: Kotani, H., Ogawa, W., and Matsushima, K.: Does flood early warning performance affect flood damage? Evidence from the 2018 Japan Floods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3271, https://doi.org/10.5194/egusphere-egu26-3271, 2026.
The ongoing intensification of extreme climate events poses an increasing threat to the Amazon River and its floodplains, significantly impacting the riverine Indigenous communities whose livelihoods, mobility, and health are closely linked to the dynamics of the freshwater environment. These increasing hydroclimatic changes highlight the need for a thorough understanding of freshwater systems within a social-ecological nexus in order to develop co-designed strategies and support locally grounded resilience planning.
The study presents an initial insight into the research activities of the NAÃNE project (New Strategies for Environmental Adaptation for Communities and Ecosystems, funded by the Italian Agency for Development Cooperation), which objective is to support community resilience to climatic change by conducting socio-morphodynamic investigations in the Colombian Amazon River corridor, which shall support the development of adaptation strategies including early warning systems.
The study is based on three months of field-campaign conducted among communities living along the Amazon River between the municipalities of Puerto Nariño and Leticia in the Colombian Amazon. By integrating hydrological and morphological perspectives with local knowledge, this project attempts to develop a transdisciplinary methodology of the case study area's freshwater systems resilience. The field methodology is based on preliminary context analysis, which reveals droughts and river contraction as the main challenge faced by the communities. Thus, field data collection comprised qualitative, semi-structured interviews combined with spatially explicit participatory mapping techniques. Field data collected were then compared and integrated with the available hydrological data (water levels) and remote sensing analysis of medium-resolution satellite images to evaluate the local morphodynamics. A total of seventeen interviews were conducted with representative members of four indigenous communities in the study area: Macedonia and Mocagua, located along the main channel, and San Martín de Amacayacu and San Francisco, located on the tributaries. The combination of interviews and participatory mapping enabled the collection of community perceptions of changes in hydrological seasonality across space and time, from both a graphical and a qualitative perspective. The resulting maps identified historically and currently perceived seasonal water level changes, seasonal navigation points, and cultivated areas, integrated with available hydrological and morphodynamic evaluation. The findings highlighted the impacts of past drought events on community livelihoods, including fishing, agriculture, and local trade, as well as on navigation, access to drinking water, and human health.
Overall, this study emphasises the importance of a transdisciplinary and inclusive methodology to have a thorough understanding of the local riverine communities and develop effective strategies for riverine systems resilience, setting the basis for knowledge co-production within the NAÃNE project, where local communities, policy makers and water resources managers collaborate to inform decision-making processes.
How to cite: Usai, C., Crivellaro, M., Cantoni, A., Castelletti, M., Vargas Luna, A., Zortea, M., and Zolezzi, G.: Exploring community adaptation to changes the Amazon River dynamics through a transdisciplinary approach and knowledge co-production, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20794, https://doi.org/10.5194/egusphere-egu26-20794, 2026.
Public demand for ecologically healthy rivers and water-friendly spaces has grown over time, increasing the need for planning and application at the regional scale. Accordingly, incorporating citizens’ needs into management plans has become increasingly important. This study aimed to identify citizens’ preferences for the ecological and spatial features of stream waterfronts. We conducted a survey using 30 images of stream waterfronts that are open access, asking respondents to rate each image on a 7-point scale (1 = very low to 7 = very high). A total of 235 responses were collected. The evaluation features were selected based on findings from previous monitoring studies. In addition, generative AI (ChatGPT 5.2) was used to generate representative stream waterfront images reflecting the observed feature preferences (e.g., best case vs. worst case). Further studies for enhancing the training process by revising the criteria and adding more images are required. The results are expected to support stream waterfront design and discharge management by linking these preferences with holistic planning approaches.
How to cite: Shim, T., Jee, H. W., and Seo, S. B.: Identification of Citizen Preferences for Ecological and Spatial Features of Stream Waterfronts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4615, https://doi.org/10.5194/egusphere-egu26-4615, 2026.
Global mega-river deltas host a disproportionate share of the world’s population and economic activity, yet they are increasingly exposed to compounded water security risks arising from climate change, upstream regulation, and rapid socioeconomic transformation. Despite their global importance, a consistent and comparative assessment of water security sustainability across deltas remains limited.
Here, we develop an integrated assessment framework to evaluate the sustainable water security of major global river deltas by jointly considering hydrological availability, climate extremes, water demand, and socioeconomic pressure. Using multi-source datasets on river discharge, precipitation and temperature, population distribution, economic activity, and land use, we quantify spatial and temporal patterns of water stress across representative deltas in Asia, Africa, Europe, and North America. Trend analysis and attribution methods are applied to disentangle the relative contributions of climatic variability and human drivers to observed changes in water security.
Our results reveal pronounced regional heterogeneity. Many Asian and African deltas exhibit increasing water insecurity driven by the combined effects of declining upstream inflows, intensifying drought extremes, and rapidly growing domestic water demand. In contrast, deltas in developed regions show relatively stable water availability but remain vulnerable due to high exposure and dependence on engineered water systems. The analysis further highlights critical hotspots where climate change amplifies existing socioeconomic pressures, posing challenges to long-term sustainability.
This study provides a global, delta-scale perspective on water security sustainability and identifies priority regions for adaptive management. The framework offers a transferable tool to support policy-relevant assessments and inform integrated water governance strategies for vulnerable delta systems under future change.
How to cite: Cheng, Q.: Assessing resilience of water security in global megadeltas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8981, https://doi.org/10.5194/egusphere-egu26-8981, 2026.
Artisanal and small-scale gold mining (ASGM) has become a major driver of land degradation and river system disturbance in Ghana, yet its spatial dynamics remain poorly quantified. In our study, we assessed the spatio-temporal dynamics of ASGM and associated land use and land cover (LULC) changes in the Pra (23,202 km2), Ankobra (8,442 km2), and Tano (21,465 km2) river catchments in Ghana, with emphasis on ASGM encroachment into riparian zones. We performed a supervised object based image analysis (OBIA) on sentinel-2 images for the catchments for 2020, 2022, and 2024 using a Random Forest classifier trained on four LULC classes (mining, built-up, water, vegetation). Results indicate consistent ASGM expansion across all catchments, resulting in substantial vegetation loss and increase in surface water, likely reflecting the formation of mine-pit ponds. The Pra catchment experienced the most expansion in ASGM (1,155 km²), followed by the Ankobra (347.8 km²) and Tano (192.3 km²) catchments, alongside increasing encroachment into a100m buffer riparian zones of these river channels, where ASGM increased from 72.65 to 133.97 km² in the Pra (299 km2), from 51.36 to 70.57 km² in the Ankobra (114 km2), and from 25.75 to 44.43 km² in the Tano (292 km2) river channels within this period. To complement these findings, field data collection is currently ongoing to assess the impacts of ASGM expansion on ecosystem health. The findings of this study demonstrate intensifying ASGM pressure on Ghana’s river systems and associated ecosystems, highlighting the need for targeted riparian zone protection and catchment-scale management interventions.
How to cite: Agyapong, D., Krueger, E., Cammeraat, E., Jansen, B., and Jacobs, L.: Mapping spatio-temporal expansion and ecological impacts of Artisanal and Small-Scale Gold Mining in River Catchments Using Multi-Temporal Satellite Imagery and field data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15044, https://doi.org/10.5194/egusphere-egu26-15044, 2026.
Posters virtual: Wed, 6 May, 14:00–18:00 | vPoster spot 4
EGU26-18945 | Posters virtual | VPS32
A System Dynamics Model to Assess Water Resilience in the North China PlainWed, 06 May, 14:36–14:39 (CEST) vPoster spot 4
In the context of escalating global population, rapid economic development, and ongoing climate change, water resource management is confronted with a multitude of challenges. The North China Plain (NCP), as the economic powerhouse of China, is facing a multifaceted set of water-related issues, including inefficient water use under persistent scarcity, complex virtual water trade flows, and the increasing pressure on allocating water resource among cities through water diversion projects. Traditional water resource models often overlook the two-way feedbacks between water supply sources and demand sectors, therefore may not adequately represent the real-world water resilience dynamics. To address these challenges, this study constructs a System Dynamic (SD) model in NCP, building on water supply and demand statistics from local governmental reports. Different from previous SD-based water models for this region, we explicitly consider the roles of different water supply sources and municipal emergency water reserves. This provides a unique advantage for assessing urban water system resilience under extreme climate conditions. In this presentation, we will first show the validation of our model in the historical period (2000-2020) compared to water agency statistics. We will also illustrate how the interactions between each urban water system components may change under different future climate scenarios. By investigating the dynamic feedbacks between the natural and anthropogenic water cycles, our model is set to provide a scientific reference for governments to plan flexible and adaptive water resource management strategies.
Key word: Water Management; System Dynamic Model; North China Plain.
How to cite: Junkun, L., Qing, H., Xizhu, H., Hui, L., and Taikan, O.: A System Dynamics Model to Assess Water Resilience in the North China Plain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18945, https://doi.org/10.5194/egusphere-egu26-18945, 2026.
EGU26-16979 | ECS | Posters virtual | VPS32
Integrating drought indices and socio-ecological theory to analyze long-term drought impacts: A review of South Africa’s rural communities.Wed, 06 May, 14:39–14:42 (CEST) vPoster spot 4
Drought remains a pervasive environmental and socio-economic challenge across developing countries, with rural and semi-arid regions such as South Africa’s particularly vulnerable. In recent decades, climate variability has exacerbated the frequency, severity, and duration of droughts, prompting an expanding body of literature on resilience and adaptation. Traditional monitoring tools such as the Standardized Precipitation Index, Standardized Streamflow Index, and NDVI provide valuable biophysical insights but often fail to capture the socio-economic dimensions that shape community vulnerability and response. This review explores the evolution and application of the socio-ecological systems (SES) framework in drought resilience research within developing contexts. The SES approach offers a holistic lens to understand the complex interplay between environmental stressors, livelihoods, governance, and social systems. Emerging literature highlights the growing use of SES yet also reveals persistent gaps including weak integration between quantitative climate data and qualitative social insights, limited longitudinal studies, and inadequate incorporation of local knowledge. Drawing on studies from sub-Saharan Africa and other Global South regions, this review synthesizes key trends, methodological advancements, and research gaps in SES-informed drought resilience. It underscores the need for interdisciplinary, participatory, and context-sensitive approaches to support equitable and sustainable adaptation strategies aligned with global frameworks such as SDG 13 and the Sendai Framework.
How to cite: Mothapo, K., Mathivha, F., Chikoore, H., and Krueger, E.: Integrating drought indices and socio-ecological theory to analyze long-term drought impacts: A review of South Africa’s rural communities., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16979, https://doi.org/10.5194/egusphere-egu26-16979, 2026.
EGU26-16078 | ECS | Posters virtual | VPS32
Constraining irrigation simulation in Global Hydrological Model H08 using satellite-derived dynamic targetsWed, 06 May, 14:42–14:45 (CEST) vPoster spot 4
Accurate simulation of irrigation water use is essential for quantifying human impacts on the global water cycle. Given that continuous large-scale in situ monitoring of irrigation is scarce, the fidelity of irrigation estimates relies heavily on how models represent soil-moisture deficits and management targets. In many global hydrological models (e.g., H08), irrigation demand is commonly computed using a soil-moisture deficit approach: water is applied to refill the soil when moisture levels fall below a prescribed target. However, this target is typically implemented as a static, empirically specified parameter. While computationally efficient, this practice introduces substantial uncertainty into simulated irrigation water use.
Here, we develop a satellite-based framework that utilizes observed surface soil moisture to constrain irrigation demand in hydrological models. We first construct a day-of-year climatology of satellite-derived surface soil moisture to capture multi-year mean irrigation conditions and management requirements. Subsequently, we employ a vertical extrapolation strategy to translate satellite-derived surface targets into a root-zone proxy compatible with the H08 model. We validate this strategy in non-irrigated regions before applying it to irrigated areas to enable dynamic, observation-constrained irrigation targets. Preliminary diagnostics indicate that this framework offers a practical pathway for integrating satellite soil-moisture data into H08, improving the spatial realism of irrigation demand and facilitating more consistent evaluations against independent benchmarks.
How to cite: Huang, X., He, Q., Hanasaki, N., and Oki, T.: Constraining irrigation simulation in Global Hydrological Model H08 using satellite-derived dynamic targets, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16078, https://doi.org/10.5194/egusphere-egu26-16078, 2026.
EGU26-16183 | Posters virtual | VPS32
Projecting bilateral virtual water trade of rice and wheat toward 2100 under different SSP scenariosWed, 06 May, 14:45–14:48 (CEST) vPoster spot 4
Virtual water trade (VWT) redistributes water embodied in agricultural commodities across borders and thereby shapes global interdependence between water resources and food security. Recent studies have increasingly used integrated assessment models (IAMs)—including GCAM, a partial-equilibrium IAM—to project future agricultural production and trade balances under future climate and socio-economic change and to infer virtual water transfer flows(e.g., Graham et al., 2020). However, such approaches assume that commodities are traded in a single global markets, making it difficult to explicitly quantify bilateral exporter–importer dependency structures.
In this study, we develop a scenario-based framework to estimate bilateral virtual water trade of rice and wheat toward 2100 by combining projections of harvested area (land-use), climate-driven yield changes, and population dynamics with an extrapolation of current trade structures. Using baseline bilateral trade matrices from FAOSTAT, we assume that (i) exporter-specific allocation to destination countries and (ii) national export-to-production ratios remain fixed, and we scale bilateral trade volumes in accordance with scenario-driven changes in production and demand. We then compute bilateral VWT by linking projected crop flows with crop- and location-specific water-use coefficients. The analysis focuses on SSP2 as the primary scenario, with additional SSP comparison(SSP126 and SSP585). This framework enables assessment of how future VWT magnitude and bilateral dependency patterns may evolve differently between rice—characterized by relatively thin international markets—and wheat, which is traded in thicker global markets, providing insights for water–food security assessment under future climate and socio-economic change.
How to cite: Tsuda, K., Sano, T., Oki, T., and Iizumi, T.: Projecting bilateral virtual water trade of rice and wheat toward 2100 under different SSP scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16183, https://doi.org/10.5194/egusphere-egu26-16183, 2026.
