1. Better understanding of hydrological and/or biophysical processes that govern hydrological response to multi-annual or longer climate shifts;
2. Studies of hydrological regularities (e.g. the Budyko hypothesis) for predictions under changing conditions;
3. Characterizations of catchment multi-annual “memory” and its representation in models;
4. Efforts to improve the realism and robustness of hydrological simulations under climatic variability and change;
5. So-called “bottom-up” approaches to decision making under deep uncertainty, novel modelling paradigms, innovative risk assessment frameworks, or characterisations of multiple (compound) sources of risk in future scenarios.
Orals: Fri, 8 May, 08:30–10:15 | Room 2.15
Droughts can substantially alter catchment hydrological behaviour by modifying vegetation productivity and composition, soil hydraulic properties, surface water-groundwater interactions, and water storage. These changes can persist beyond the drought period, shaping catchment response to precipitation and subsequent flood dynamics. Yet, the influence of drought characteristics on catchment response remains unclear.
Here, we present a global-scale analysis of drought influence on catchment response to precipitation, using long-term satellite and in-situ observations from thousands of catchments worldwide. By employing multivariate statistical analysis, our analysis shows that drought events generally lead to significantly lower streamflow than expected from the historical norm. While arid and semi-arid regions show lower resilience to drought-induced changes in the streamflow-precipitation relationship, wet catchments, such as those in snow-influenced climates, show greater resilience due to their water-buffering mechanisms. In catchments with non-stationary streamflow-precipitation relationships, severe and prolonged droughts can lead to both positive and negative shifts in catchment response. These shifts can have implications for subsequent flood severity and flood timing.
Overall, our findings highlight the importance of accounting for drought characteristics and regional hydroclimatic differences when assessing catchment responses to precipitation and flood risk under and following drought conditions.
How to cite: Matano, A., van Loon, A., Irene Brunner, M., and Berghuijs, W.: How do droughts influence catchment response and flood dynamics?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17044, https://doi.org/10.5194/egusphere-egu26-17044, 2026.
Evapotranspiration (ET) is a central component of the water and energy cycle, jointly affected by climate and vegetation. Under ongoing climate change and large-scale greening, a key challenge is to quantify how much of observed ET change is driven by vegetation, rather than by co-varying precipitation and atmospheric demand. Strong multicollinearity among climate, ET, and leaf area index (LAI) in observations hinders robust estimation of ET’s sensitivity to vegetation. Even though the classical Budyko framework can separate climatic and vegetation controls, it relies on fixed functional forms, limiting its ability to represent the strongly state-dependent and region-specific ET responses across climate and vegetation regimes. Therefore, we incorporate the Budyko framework within a data-driven model. This enables us to disentangle the influence of climate and LAI on ET, by combining global observations and established water-energy balance constraints. Using local derivatives and counterfactual experiments, we estimate the sensitivities of ET to climatic factors and LAI, and decompose ET changes into contributions from climate and vegetation. Our results show that ET sensitivity to LAI increases and then decreases with rising LAI, peaking in transitional regimes where neither water nor energy fully dominate. At the global scale, climatic contributions to ET change are spatially diverse, whereas LAI increases almost everywhere enhance ET. Even though climatic effects are typically stronger locally, their opposing signs across regions cancel out when aggregated globally. Therefore, during 2001-2020, the global ET increases correspond mainly to LAI trends. By leveraging this Budyko-informed model, which reduces the influence of multicollinearity, we can obtain a more robust separation of climatic and vegetation drivers of ET. These findings highlight the dynamic role of vegetation in regulating terrestrial water loss, which directly affects how reforestation and greening impacts on water resources are interpreted.
How to cite: Li, Y., Jiang, S., Blougouras, G., Zhang, B., and Winkler, A.: Global Climate and Vegetation Controls on Evapotranspiration Change Revealed by Budyko-informed Machine Learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1067, https://doi.org/10.5194/egusphere-egu26-1067, 2026.
The choice of potential evapotranspiration (PET) methods in hydrological modelling can result in contrasting estimates of meteorological drought and low flows in the context of climate change, but their effects on other drought types and the associated hydrological components are still unknown. This study aims to systematically assess the effects of a temperature-based (T-based) method and a Penman-Monteith (PM) method on 1) historical hydrological simulations, and 2) projected changes in hydrological components, meteorological, agricultural and hydrological droughts under climate scenarios in mainland Norway. The distributed version of the hydrological model HBV with two PET methods was driven by six regional climate projections under three emission scenarios. The results show that the PET methods provide similar historical discharge simulations but different spatial distribution of hydrological components. The T-based method always estimates higher PET and evapotranspiration, lower soil moisture and runoff and longer severe droughts than the PM method under climate scenarios, especially in Eastern, Central and Northern Norway. The discrepancies of projected changes between the two PET methods generally increase linearly with temperature change. Among various drought types, agricultural drought projections are the most sensitive to the choice of PET method.
How to cite: Huang, S., Wong, W. K., Tveito, O. E., and Haddeland, I.: Impacts of empirical and physical evaporation methods on changes in hydrological components and drought indices under climate change scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18815, https://doi.org/10.5194/egusphere-egu26-18815, 2026.
The increasing intensity and frequency of Extreme Hydrological Events (EHEs), such as floods and droughts, underscores the urgent need to understand how the water cycle is changing. To project what lies ahead, it is essential to investigate the past by identifying when, where, and how EHEs occur and how they shape current land–atmosphere interactions. Land surface models (LSMs) are widely used for this purpose, yet their accuracy is often limited by region-specific observations, structural simplifications, and challenges in model calibration. In many data-scarce regions, such as the Ganges River Basin, uncalibrated LSMs are frequently applied to reconstruct past hydrological conditions and to estimate potential future changes. However, the extent to which model calibration improves such projections remains poorly understood, particularly given strong spatial and seasonal variability.
In this study, we investigate how model calibration influences projections of EHEs using the Variable Infiltration Capacity (VIC) model. We compare three VIC model setups: an uncalibrated model to establish the baseline for our investigations; a single-site calibration against monthly in-situ streamflow observations at the basin outlet, Farakka; and a sequential multi-site calibration using available monthly in-situ streamflow observations at 12 stations across the basin to constrain basin-scale water balance, seasonal streamflow patterns, and interannual variability. The three model versions are then forced with precipitation and temperature from multiple Global Climate Models (GCMs) under different Shared Socioeconomic Pathway (SSP) scenarios. Historical simulations are used to define high- and low-flow thresholds and baseline variability, providing a reference for interpreting future projections. The resulting simulated streamflow is analyzed at monthly, seasonal, and annual scales to identify dominant drivers and regional contrasts, providing a basis for interpreting future changes relative to historical conditions.
The findings aim to support the development of hydrological monitoring frameworks with improved representation of regional- to large-scale processes, particularly in data-scarce basins, to strengthen disaster mitigation and climate risk assessment strategies.
How to cite: Tiwari, S., Forootan, E., and Schumacher, M.: The Impact of Model Parameter Calibration on Future Extreme Event Predictions in the Ganges Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20543, https://doi.org/10.5194/egusphere-egu26-20543, 2026.
Climate change is altering the hydrological cycle, with implications for riverine ecosystems that are expected to vary over space and time. This study assesses projected changes in streamflow regimes for 27 Irish rivers across three future periods (2006–2035, 2036–2065, and 2066–2095) relative to a baseline period (1976–2005). Changes in hydrological behaviour are quantified using seven flow regime metrics that represent the magnitude, variability, frequency, and duration of the flow. These metrics include the 5th percentile daily streamflow (Q5), 99th percentile daily streamflow (Q99), maximum monthly mean streamflow (MaxMonthQ), Richards–Baker Flashiness Index (RBI), interdecile range ratio (QmaxIDR), low-flow event duration (LowDur), and the number of high-flow events (HighNum), capturing changes in both low- and high-flow conditions. The metrics are derived from daily streamflow simulated using the SMART model driven by five regional climate models under both RCP4.5 and RCP8.5 scenarios.
The results, based on the ensemble median, indicate a consistent decline in low flow magnitude across all catchments and periods, with larger reductions under RCP8.5. In contrast, LowDur exhibits both increases and decreases depending on catchment and period relative to the baseline. High-flow magnitude increases at all but two stations, while changes in the frequency of high-flow events (HighNum) are mixed across periods and catchments. MaxMonthQ shows an overall increasing trend. QmaxIDR increases across most rivers indicating greater flow variability. The result show a widespread moderate increase in RBI, suggesting a progressively flashier flow regimes across Irish rivers under future climate scenarios. These findings help identify rivers and future periods that are the most vulnerable to alternation of the hydrological, highlighting the increased risks of both drying and flooding and their potential effects on aquatic ecosystems under climate change.
How to cite: O'Loughlin, F. and Khan, S.: Variability of the hydrological regime in Irish Rivers under Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3328, https://doi.org/10.5194/egusphere-egu26-3328, 2026.
Climate change is expected to substantially alter the hydrological cycle in temperate regions. Denmark, where groundwater and surface water are tightly coupled, provides an ideal test case to investigate the propagation of climate change signals through the hydrological system, due to good data availability and an existing well-established national-scale hydrological model. The Danish National Hydrological Model (DK-model) is a physically based, distributed model that has previously been shown to reproduce the observed propagation of drought and hydrological anomalies throughout the hydrological cycle.
Here, we analyse the climate change impact on the Danish hydrology, as simulated by the DK-model forced by an ensemble of 17 downscaled and bias-corrected climate models (RCP8.5) until the end of the 21st century. The climate projections indicate an increase in net precipitation at the annual scale, driven primarily by wetter winters, while summers experience increased net precipitation deficits. The resulting climate change signals across the hydrological cycle are assessed using both absolute values and standardized indices for soil moisture, streamflow, and shallow and deep groundwater.
Model results show that increased net precipitation and increased seasonality are translated into different hydrological responses. Fast reacting, surface-near compartments (soil moisture) shift towards drier conditions during summer and wetter conditions during winter. In contrast, deep groundwater shows a consistent rise across all seasons, reflecting the overall increase in precipitation. Shallow groundwater and streamflow show intermediate behaviour dominated by large increases in winter and a mixed signal for summer. Despite these differences, all compartments experience an increase in seasonality, expressed as larger amplitudes between annual minimum and maximum states. Notably, climate models show stronger agreement on increasing seasonality than on the direction of absolute changes.
Moreover, the increased seasonality is also reflected in the hydrological drought indices which indicate increased soil moisture droughts during summer and, at the same time, an increase in wet anomalies during winter. The development of streamflow and groundwater droughts is more complex due to the partial buffering of drier summers by wetter winters. Yet, results clearly indicate a similar trend towards increased seasonality. Overall, the results demonstrate that, despite significant precipitation increases, climate change in Denmark is projected to amplify seasonal extremes rather than uniformly shift hydrological states towards wetter conditions, with important implications for water resources management, agriculture, ecosystems, and infrastructure.
How to cite: Schneider, R., Stisen, S., Troldborg, L., and Seidenfaden, I. K.: Climate change projections with the National Hydrological Model of Denmark reveal an intensified seasonality of the hydrological cycle, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6662, https://doi.org/10.5194/egusphere-egu26-6662, 2026.
Climate change is expected to alter the frequency, duration, timing and severity of droughts. Traditional top-down approaches to assessing the performance of water supply systems under different climatic conditions can miss drought vulnerabilities, particularly where drought characteristics may be altered under climate change. Stress-tests under a bottom-up framework offer a way of identifying water supply system vulnerabilities to droughts more severe and extreme, and with different characteristics, to those experienced historically.
An inverse stochastic approach was developed to elicit weather type transitions that cause severe and extreme droughts for a water supply system in mid-west Wales, United Kingdom. Droughts are defined at the start of the process by the end-user, focussing on drought characteristics where consequences are decision-relevant. The inverse stochastic approach (using a Markov Chain stochastic model trained on historical synoptic weather types) then perturbs the likelihood of weather type transitions to produce the user-specified droughts.
The approach provides actionable insights for water managers by identifying water supply system vulnerabilities to different drought dynamics, as well as indicating how implausible the droughts would need to be in order to reach the targeted drought definitions. The impacts of climate change can be included by incorporating changes in weather types from validated climate models, using a range of methods from simple changes in future occurrence, to more complex stochastic models trained on future weather types.
How to cite: Durant, M., Counsell, C., Fung, F., and Wilby, R.: Searching for extremes: A framework for decision-relevant stress tests using weather types, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19469, https://doi.org/10.5194/egusphere-egu26-19469, 2026.
Hydrological extremes (floods and low flows) are an important societal issue in Mediterranean areas. Dry summers limit the available water resource, while flash floods cause material and human damage. Both extremes are expected to intensify under future climate. There are strong links between changes in the water cycle and changes in human activity in both directions: on the one hand, limitations of water resources constrain societies to adapt their activities and, on the other hand, changes in human activity can further change the pressure on water resources.
It is therefore essential to anticipate how territories should adapt and transform their land uses in response to increasing pressures on water resources. We uniquely combine land use and land cover (LULC) scenarios co-constructed with local stakeholders, hourly climate projections and a spatially distributed hydrological model in order to evaluate the impact of management choices on hydrological variables and the societal implications of these changes.
An interdisciplinary prospective study at 2050 horizon was conducted in the Mediterranean Claduègne catchment (43 km²; Ardèche, France), characterized by rural mixed land use (extensive agriculture, forests, small towns and tourism). This study was based on surveys with 16 key local stakeholders (farmers, elected officials, planners, residents, etc.). Semi-structured interviews and focus groups were used to identify past and current drivers of change, and to explore plausible futures. Three contrasting scenarios were established. These LULC scenarios contain modeled future land cover maps, as well as descriptions of changes in agricultural practices and water management strategies.
The scenarios were fed into a hydrological model along with two contrasting climatic projections, in order to establish six potential future pathways for the middle of the century. We used the spatially distributed process-based hydrological model J2000P at hourly resolution. Besides natural hydrology, the model represents human activity, such as irrigation, livestock farming, and drinking and waste water fluxes, as well as specific water resource management strategies like hillslope reservoirs and external water importations.
We assessed the territorial impact of the three LULC scenarios under climate change, on low flows and contributions of the main hydrological components (overland flow and groundwater). We discuss the capacity of each scenario to sustain diversified agricultural activities with or without external water input to the catchment, and the ability to supply the catchment with drinking water, particularly during critical periods.
The climatic conditions determined the future change of high flow extremes and groundwater contributions, while both climate and LULC significantly impacted low flow extremes, overland flow contribution and the streamflow during the driest period of the year. The capability to sustain agricultural activity in the future depends on additional solutions such as hillslope reservoirs. The extent of this dependency varies across LULC scenarios and climate projections. Additional water importations may be needed some summers in order to sustain drinking water supply for the population. However, these additional solutions rely on management choices that raise economic issues, dependency on infrastructure, and questions of social acceptability.
How to cite: Hachgenei, N., Créti, I., Branger, F., Robinet, N., Nord, G., Coquery, M., Pellerin, N., and Dusseux, P.: Combining climate, land use and water use scenarios to project possible futures of a meso-scale Mediterranean catchment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11924, https://doi.org/10.5194/egusphere-egu26-11924, 2026.
Abstract
Understanding the significant influence of climate and landscape changes is essential for managing water resources; however, the individual effects of climate and landscape on surface and subsurface runoff are not well understood. In this study, we quantified the contributions of precipitation (P), potential evapotranspiration (PET), and landscape parameter (n) changes to the elasticity of surface and subsurface runoff using a modified Budyko Framework (e.g., Choudhury–Yang equation) across six Ethiopian sub-basins. Trend and breakpoint analyses (Mann–Kendall and Pettitt tests) divided the long-term runoff data (1964–2023) into two distinct periods for attribution. We examined runoff elasticity, as the percentage change in mean annual runoff for a given percentage change in P, PET, and n. The results revealed that, on average, P decreased by 1.33 mm/year, and PET increased by 1.72 mm/year, resulting in a decline in the long-term total, surface, and subsurface runoff by 19.7 mm, 7.6 mm, and 12.4 mm, respectively, between the two periods. Crucially, the runoff components exhibited distinct hydrological responses; surface runoff elasticity was primarily governed by change in P (49.3%), followed by PET (26.2%) and n (24.5%), emphasizing its dominant link to water availability, particularly in arid sub-basins. The subsurface runoff elasticity showed greater sensitivity to landscape change and energy balance, being predominantly influenced by change in PET (33.6%) and n (39.7%). Large positive deviations in ∆n (n2-n1) rapidly shift runoff sensitivity from climate control to landscape domination. Overall, climate forcing (changes in P and PET) accounted for 66.7% of the runoff elasticity, confirming its primary role. These findings provide fundamental new insights into catchment partitioning behaviors, mandating that water management strategies adopt a component-specific approach tailored to the differential elasticities of surface and subsurface flow systems in complex catchments.
Keywords
Budyko framework, Climate change, landscape parameter, Runoff components, Runoff elasticity
How to cite: Demeke, G. G., Huang, J.-C., and Chen, Y.-Y.: Differentiating Surface and Subsurface Runoff Elasticity to Climate and Landscape Changes Using a Modified Budyko Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1771, https://doi.org/10.5194/egusphere-egu26-1771, 2026.
As the impacts of climate change intensify and water demand continues to increase, assessing future water resources has become an important issue. In Taiwan, the precipitation–runoff relationship exhibits a decoupled behavior. Although annual precipitation has increased in most catchments, the corresponding increase in runoff has been smaller than expected or has even declined.
A parametric Budyko framework was employed to quantify the temporal evolution of 54 catchments across Taiwan in Budyko space from 1970 to the present. The results indicate that Budyko curves constructed using 11-year moving windows provide a robust representation of long-term catchment water balance behavior. Moreover, the catchment landscape parameter (m value) shows an increasing trend over time in most Taiwan’s catchments, implying a gradual enhancement of catchment water storage capacity. This finding suggests that assuming a fixed m value for future runoff may lead to overestimation.
To better understand the drivers of changes in m, this study explores the relationships between variations in m and changes in soil moisture, land use, groundwater levels, and streamflow. By capturing the temporal dynamics of the catchment landscape, this approach aims to improve the robustness of future water resource assessments based on the Budyko framework.
How to cite: Chen, Y.-C., Lee, T.-Y., and Chen, S.-E.: Quantifying Temporal Shifts in Catchment Water Storage Using a Time-Varying Budyko Framework in Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5105, https://doi.org/10.5194/egusphere-egu26-5105, 2026.
The Budyko framework is widely used in hydrology to describe how long-term catchment behaviour is constrained by the balance between annual precipitation (the water budget) and the evapotranspiration capacity (the energy budget). These two factors jointly determine a catchment’s position on the Budyko diagram. Under a stationary climate, this position is expected to fluctuate around an equilibrium state; under climate warming, this equilibrium may shift.
Combining experimental and operational stream gauge networks with remote-sensing products, we analyse the positions of 61 catchments in Luxembourg on the Budyko diagram over the period 1995–2025. Owing to its relatively homogeneous climate, Luxembourg provides a particularly suitable case study for isolating the influence of non-climatic controls on these positions, such as geology and its underlying contribution to storage capacity.
Our results show that departures from the Budyko curve are explained by differences in active catchment storage, which are closely linked to geologic variations. Catchments with higher active storage capacities tend to plot above the Budyko curve, remain closer to an energy-limited regime, and are therefore less exposed to drying. This analysis highlights the role of catchment geology, and more specifically its capacity to store and release water over multiple years, as a key resilience factor of the water cycle under a warming and increasingly arid climate.
How to cite: Courtois, S., Zoccatelli, D., Vincenot, C., and Pfister, L.: Active subsurface storage as a resilience factor of Luxembourgish catchments under a changing climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9764, https://doi.org/10.5194/egusphere-egu26-9764, 2026.
Evapotranspiration (ET ) in irrigation districts is a key proxy of actual water consumption, reflecting the shifting agricultural water demand under the combined pressures of climate change and human activities. Accurate attribution of ET variations is essential for sustainable agricultural water management but remains challenging due to the complex interplay of hydrological drivers. The Budyko framework provides a physically-based approach to partition these influences. However, the traditional Budyko framework is not applicable the irrigation area.
In this study, we used an extended Fu’s formula within the Budyko framework to explicitly incorporate the impacts of irrigation activities on the water-energy balance. We defined "equivalent precipitation" (Pe) —the sum of irrigation water ( I ) , precipitation (P ) , and groundwater evaporation (𝐸𝑇gw ) , as the water availability. This framework was applied to 364 large irrigation districts across China to quantify ET from 2010 to 2017 and evaluate the extended Budyko framework’s applicability at the irrigation district scale.Then, we calculate the elasticity coefficients for I、P、Pe、ω (the optimal values of Budyko parameter）、potential evaporation (ETo) to quantify the sensitivity of ET to each forcing factor of ET change via a dimensionless elasticity-based attribution method.
Our results indicate that:
- (1) Framework Applicability: We found that the extended Budyko framework demonstrates good applicability in irrigation districts. Compared with the ET results from water balance calculations and the results from the MOD16A3 dataset, the relative error of annual evapotranspiration was less than 10% in 87.91% (320 samples) of the irrigated areas, and the root mean square error was less than 60 mm in 80.77% of the irrigated areas (294 sample points). The calculation error was smallest in the humid region.
- (2) Parameter ω’s distribution: The optimal values of Budyko parameter w in the extended Fu’s formula exhibit significant regional distribution characteristics, showing a pattern different from that of natural watersheds. The more humid the irrigated area, the larger the value of w in the fitted equation, reflecting the impact of human irrigation activities on hydrological conditions.
- (3) Attribution Analysis: In arid and semi-arid regions, evapotranspiration is jointly limited by water and energy, exhibiting the highest sensitivity to parameter ω, with elasticity coefficients of 3.073 and 1.879, respectively. This is followed by sensitivity to energy, with elasticity coefficients of 0.754 and 0.413, and then sensitivity to irrigation, with elasticity coefficients of 0.709 and 0.239, respectively. As the climate becomes wetter, the system transitions to an energy-limited state; therefore, ET becomes more sensitive to ETo, while its sensitivity to ω and irrigation significantly decreases. In humid regions, the elasticity coefficient to irrigation is only 0.091, to potential evapotranspiration is 0.752, and to ω is 0.722.
How to cite: Li, M. and Huo, Z.: Attribution of Evapotranspiration Variations in 364 Large Irrigation Districts across China: Quantifying the effects of irrigation via an extended Budyko Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11862, https://doi.org/10.5194/egusphere-egu26-11862, 2026.
Long-term flow variability in transboundary rivers reflects the combined influence of water availability, management, and usage across space and time. However, integrating historical flow with evolving water-use data remains challenging, as assessments are often conducted within national frameworks despite shared watersheds among at least two nations. Moreover, water discharge and usage data are often fragmented across multiple sources. This study presents a 125-year discharge record (1900–2025) from historical Water Bulletins and modern observations at 12 internationally operated gauging stations, delivering a spatiotemporal assessment of long-term flow evolution and water-budget components in the Lower Rio Grande/Bravo (LRG). Extending from below Falcon Dam Reservoir to the Gulf (~460 river km), the LRG is regulated between the U.S. and Mexico by three major dams (Falcon, Anzaldúas, and Retamal) and eight weirs below Anzaldúas. Supplying ~98% of regional water consumption for more than 2.8 million people at a binational scale, the river has been altered by anthropogenic activities since the late 1800s, with agricultural irrigation accounting for ~85% of current annual withdrawals. To address data discontinuities, flow records were evaluated using four representative 16-year hydrological regimes—natural (1900–1915), pre-dam (1935–1950), post-dam (1974–1989), and modern (2010–2025) —analyzed in conjunction with modern binational usage records across major water sectors (agricultural, municipal, and other uses). Below Falcon Dam, median annual inflow declined by ~64% in the last 125 years, while downstream outflow decreased by ~96%, resulting in a near 100% modern Gulf-delivery deficit relative to natural conditions (i.e., no freshwater delivery to the Gulf from the median basis). While binational water use is dominated by irrigation (~58% U.S., ~26% Mexico), downstream losses exceed what can be attributed to irrigation alone. Findings show upstream delivery reduction as the primary driver of long-term decline, accounting for 54.7% [31.8–91.4%] of total flow reduction relative to natural conditions, while binational water use represents a substantial but secondary contribution, accounting for 33.5% [30.5–43.8%], and unknown losses (e.g., evapotranspiration) follow with minor impacts. Insights from this work aim to inform sustainable, binational water management under increasing urban, agricultural, and climatic pressures across transboundary river systems.
How to cite: Casillas, A., Dong, T., Xu, H., Benavides, J., and Dee, S.: Spatiotemporal Evolution of Flow Decline and Water Consumption in a Highly Regulated Transboundary River: The Lower Rio Grande/Bravo, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15748, https://doi.org/10.5194/egusphere-egu26-15748, 2026.
The case study in Slovakia was based on mean daily discharge records in catchments smaller than 50 km². The objective was to quantify the occurrence, duration, and temporal patterns of zero-flow conditions and to assess their relevance for water management and ecological resilience. An analysis of temporal clustering showed, that zero-flow events often occurred in multi-day episodes. Seasonal analysis indicated that August, September, and October were the months with the highest occurrence of zero-flows. The occurrence of zero-flow events across multiple years implies, that they may become more frequent in the future, as a result of climate change. The study underscores the importance of maintaining long-term hydrological monitoring networks, as such datasets are essential for understanding hydrological processes, evaluating their impacts and development of adaptation strategies.
How to cite: Jeneiova, K., Melova, K., Danacova, Z., and Lovasova, L.: Understanding the occurrence of zero-flow stream gauge observations in Slovakia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3386, https://doi.org/10.5194/egusphere-egu26-3386, 2026.
The Po River Basin represents one of the most socio-economically and environmentally critical regions in Europe, supporting agriculture, hydropower production, ecosystems, and urban water supply. Its hydrological regime is strongly influenced by climate variability and change, particularly through alterations in snow accumulation and melt processes in Alpine headwaters. In this context, improving the quantification and forecasting of water availability is essential to support adaptive water management strategies.
For this reason, since 2021, a collaboration between the Po River Basin District Authority and the University of Trento has focused on the application of the GEOframe modelling system to the entire Po River District. The primary objective is to provide a spatially and temporally consistent assessment of water availability across the basin, supporting planning and decision-making activities of the Basin Authority under current and future climate conditions.
GEOframe is a fully open-source, semi-distributed, conceptual hydrological modelling system capable of simulating the complete water balance, including snow accumulation and melt, evapotranspiration, soil water dynamics, and river discharge. The model was implemented at daily temporal resolution and fine spatial scale across the Po River District, accounting for the region’s complex topography and pronounced climatic gradients. Model calibration was performed using an extensive set of hydrometeorological observations collected by regional and local authorities, primarily through the ARPA monitoring networks, enabling the integration of heterogeneous datasets and the representation of spatial variability across sub-catchments.
Following calibration, the modelling framework was applied to analyse drought periods during the 2010–2020 decade, focusing on the Sesia River catchment as a representative and particularly complex study area within the Po River District. The Sesia basin is indeed characterised by a strong altitudinal gradient, significant Alpine headwaters with glacierised areas, and highly anthropised lowland sectors, making it especially sensitive to both climatic variability and human water use pressures. This complexity provides a robust test case for evaluating model performance across contrasting hydrological regimes.
The analysis focused on the response of the main hydrological components during drought conditions, with particular emphasis on snow-related processes, given their critical role in regulating seasonal water availability. Simulated snow water equivalent (SWE) data were compared against the SWE dataset by Dall’Amico et al., enabling a more precise evaluation of the snow component in the water balance.
Results highlight the strong influence of reduced snow accumulation and earlier snowmelt on water availability during drought conditions, particularly in Alpine subcatchments, with cascading effects on downstream flows in more heavily anthropized areas. The comparison with the reference SWE dataset confirms the ability of GEOframe to reproduce both interannual variability and spatial patterns of snow storage, while also revealing key sensitivities relevant for drought monitoring and seasonal forecasting.
Overall, this study demonstrates the suitability of the open-source GEOframe modelling system not only for detailed basin-scale analyses, but also for consistent, large-scale applications across the entire Po River District. The results provide actionable insights for water management authorities, supporting improved drought preparedness, strategic planning, and adaptive water management under current and future climate variability.
How to cite: Roati, G., Brian, M., Salehi, H., Azimi, S., Formetta, G., Andreis, D., Wani, J. M., Farina, A., Tornatore, F., and Rigon, R.: Assessing Water Availability and Drought Dynamics in the Po River District Using the GEOframe Modelling System - the Sesia River basin case, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21087, https://doi.org/10.5194/egusphere-egu26-21087, 2026.
Water scarcity is a persistent challenge in arid and semi-arid environments, including the southwestern region of Saudi Arabia where water availability is strongly controlled by precipitation variability. This study provides a hydrological assessment of increased precipitation during 2022–2025 relative to a baseline period (2015–2021) using integrated satellite-derived and ground-based observations.
The analysis quantifies changes in precipitation magnitude, frequency, and spatial distribution and evaluates resulting watershed-scale responses through hydrological modeling. Key hydrological outcomes examined include surface runoff generation, streamflow behavior, soil moisture dynamics, and potential groundwater recharge. Model outputs are analyzed to determine how precipitation anomalies propagate through catchment processes and alter water availability across diverse topographic and land-surface conditions.
Results show that the 2022–2025 period is associated with measurable increases in hydrological response where cloud seeding operations occurred, including higher runoff volumes and enhanced streamflow in several catchments, with variability driven by watershed characteristics and antecedent conditions. The study discusses uncertainties related to interannual climate variability, data limitations, and model parameter sensitivity, and identifies implications for water resources planning and flood-risk management in southwestern Saudi Arabia. These findings support evidence-based management by linking precipitation changes to hydrological behavior in a water-stressed region.
How to cite: Alzahrani, A.: Hydrological Assessment of Increased Precipitation in the Southwestern Region of Saudi Arabia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3056, https://doi.org/10.5194/egusphere-egu26-3056, 2026.
A new scenario free method for determining changes of flood peaks considering climate change is developed. Compared to existing methods, it accounts for heavy rainfall changes by a newly developed factor with two seasons and establishes a numerical relationship to a greater number of relevant climate predictors. For easier application, it is based on frequently available daily measurements. A functional test of the factor for heavy rainfall changes and its adjustment algorithm for the precipitation time series is performed. Using a regional AR5 ensemble, for the first time the error and the uncertainty of a new scenario free method are estimated and compared with an existing method. The new method is applied in the Harz Mountains, where the sensitivity of the region to different climate predictors is investigated.
The adjusting algorithm for precipitation is able to adjust the time series while maintaining mass balance. The new method has a lower error than the reference method, with better matches of changes in the median of the climate ensemble as well as the most ensemble members. In general, the uncertainty of the seasonal results is below the climate uncertainty of the AR5 ensemble. Regarding future flood peaks, the regional catchments are most sensitive to mean precipitation changes, followed by heavy rainfall changes especially in the winter season. Mean temperature changes are of minor significance, but the catchments characteristics are important. The new method can be recommended for assessments of climate change impacts on floods in low to average mountain regions in Germany and Europe.
How to cite: Reinstorf, F., Beylich, M., and Haberlandt, U.: A new scenario free procedure to determine flood peak changes in the Harz Mountainsin response to climate change projections, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16814, https://doi.org/10.5194/egusphere-egu26-16814, 2026.
The KliWES 3.0 project investigated the historical and future development of the water balance in Saxony under changing climatic conditions. The simulations covered the reanalysis period 1961–2020 as well as the future up to the year 2100 using 21 climate projections. A comprehensive hydrological modeling was carried out for the entire Free State of Saxony (≈22,200 km²), including the opencast mining areas of Lusatia. The water balance of this region is characterized by decades of lignite mining and the associated intensive groundwater management, which led to a cumulative regional deficit of approximately 4 billion m³ by 2020. By flooding of the former opencast mines and the gradual reduction of groundwater drainage a large-scale recovery of groundwater levels shell be achieved within the coming decades, despite the expected reduction in water availability due to climate change.
The state-wide water balance calculations for Saxony are based on the ArcEGMO model, which was improved by the integration of a floodplain approach. Furthermore, ERA5 land data were used to determine the potential grass reference evaporation. To evaluate the robustness of the model, a comparison between ArcEGMO, BROOK90, Raven 3, and Raven 4 was carried out in the catchment area of the Spree River in Saxony.
BROOK90 is a 1d site model, which was used as validation for actual evaporation due to its detailed description of vertical soil-plant-atmosphere processes. Raven is a modular, object-oriented open-source model that allows flexible combinations of different hydrological process modules – from precipitation-runoff concepts and various snowmelt models to a wide range of evapotranspiration and soil moisture approaches. It can replicate both conceptual and physically based model structures. The current version, Raven 4.1, offers significant enhancements over Raven 3, in particular an integrated optimization module based on a linear solver for water management. This allows operating rules, reservoir target specifications, and water management discharge rules to be embedded directly into the hydrological system model - a functionality that is highly relevant in the context of the Lusatian opencast mining landscape.
The results of the model comparison are examined with regard to structural differences, the sensitivity of the models to climatic changes, and the extent to which the choice of model influences the assessment of future water availability and runoff development. Particular focus is placed on the representation of anthropogenically modified systems in which management measures play a central role. The analysis demonstrates how model structure and process understanding shape the interpretation of future hydrological scenarios, and the resulting uncertainties for water management.
How to cite: Hauffe, C., Hünersen, H., and Schütze, N.: Comparative simulations of past and future water balances with the models ArcEGMO, BROOK90 and Raven in managed catchments – Does the model selection have an influence?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19499, https://doi.org/10.5194/egusphere-egu26-19499, 2026.
Climate change is intensifying hydro-climatic variability in mountainous regions, where complex terrain, limited data availability, and rising anthropogenic pressures already challenge sustainable water-resources management. This research analyses the combined influence of extreme weather, drought variability, water-resource components (blue and green water), and demographic change on the future water security of a mountainous catchment. An integrated framework was applied using downscaled CMIP6 projections to examine future changes in hydro-meteorological extremes under 2°C and 3°C global warming levels (GWLs), as well as near-future (2021-2050) and far-future (2071-2100) periods. A calibrated hydrological model was used to quantify blue water (surface water), green water (soil moisture and evapotranspiration), and the Streamflow Drought Index (SDI). These indicators, combined with future population projections, were incorporated into a Fuzzy Analytic Hierarchy Process (FAHP), enabling identification of sub-catchments that are most vulnerable to future water scarcity. Results indicate a significant increase in hydro-climatic extremes. Under SSP5-8.5, extreme temperature indices (TXx, TNx) rise sharply, and annual rainfall increases by up to 31% by century’s end, accompanied by a 50-77% increase in very heavy precipitation events (R95p, R99p). High flows (Q95) exhibit notable amplification (+30%), while low flows (Q05) decline across most sub-catchments, highlighting increasing hydrological variability. Blue water availability is projected to rise by 22-44%, whereas green water flow increases moderately (+15-28%). In contrast, green water storage shows minimal or negative trends, suggesting declining soil moisture resilience despite higher rainfall. Hydrological drought analysis shows a basin-wide shift toward negative SDI values, indicating the rise of mild to moderate drought conditions even under wetter climates, driven by altered runoff timing, intensified evapotranspiration, and declining low-flow. Integrating eight hydro-climatic, hydrological, and socio-demographic indicators, the fuzzy AHP framework identifies four out of nine sub-catchments as highly vulnerable under SSP2-4.5, driven by rapid population growth (up to +40%), rising drought stress, and limited green-water buffering. Under SSP5-8.5, although higher rainfall reduces vulnerability in some areas, intensified extremes and shifting hydrological regimes expand moderate-risk zones across the basin. Findings reveal rising rainfall yet declining effective water, worsening low flows, and drought, highlighting the need for catchment-specific, climate-resilient water-management strategies.
How to cite: Prakash, P. and Chembolu, V.: Assessing Hydrological Variability and Water Scarcity in a Mountainous River Catchment under Climate and Demographic Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-321, https://doi.org/10.5194/egusphere-egu26-321, 2026.
Water scarcity is emerging as a critical challenge under changing climatic conditions, especially in semi-arid river basins, where rainfall variability governs the balance between blue and green water resources. Achieving the United Nations Sustainable Development Goals - 6 (Clean Water and Sanitation) and 13 (Climate Action) requires a clear understanding of how climate change alters hydrological processes and drives water scarcity. This study presents an integrated, model-based framework to evaluate the influence of climate change on the partitioning of precipitation into blue water (surface runoff and sub-surface runoff) and green water (soil moisture) and the resulting implications for water availability in the Upper–Middle Godavari (UG–MG) basin, India. A physically based SWAT hydrological model was developed, calibrated, and validated for 1979–2020 and forced with climate projections from SSP245 and SSP585 scenarios from CMIP6. The framework quantified blue water resources (BWR), green water resources (GWR), and associated scarcity indices by integrating irrigation, domestic, and industrial demands with environmental flow requirements. The basin receives an average annual precipitation of 770 mm, which is partitioned into 137 mm (17.8 %) of BWR and 629 mm (81.7 %) of GWR. Future projections indicate a 10–40 % increase in rainfall, accompanied by consecutive high-intensity rainfall events that are projected to enhance BWR by 50–100 % in some of the sub-basins. In contrast, GWR declines by up to 30 %, particularly in agricultural regions where rising temperatures (+3.5 °C under SSP585) intensify evapotranspiration and reduce soil-moisture retention. The BWR/PCP ratio is projected to exceed 30 %, signifying a shift toward runoff-dominated hydrological regimes. The results suggest that climate change is transforming the UG–MG basin from a green-water-dominated to a runoff-driven system, simultaneously heightening downstream flood risks and agricultural water deficits. The findings emphasize the urgency of adaptive and integrated water management strategies to restore the blue–green water balance and advance progress toward SDGs 6 and 13.
Keywords: Blue water resources; Green water resources; Climate change; SWAT model; Rainfall partitioning; water scarcity
How to cite: Chakkaralla, M. R. and Vema, Dr. V. K.: How Does Climate Change Alter the Partitioning of Rainfall into Blue and Green Water and Drive Water Scarcity?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-584, https://doi.org/10.5194/egusphere-egu26-584, 2026.
The Indian Subcontinent comprises approximately 5,700 dams, many of which are decades old, to fulfill the water demands of the agricultural, domestic, and industrial sectors. However, hydrological response and water availability in these dam catchments have either significantly changed or are expected to change under global warming. To effectively manage the water resources storage and water supply in the densely populated and agriculturally driven region, here, we assessed the changes in hydrological components and water availability in 5700 dams over India during the observed (1951-2022) and future warming climate (2031-2065: mid period; 2066-2100; end period). Using the Variable Infiltration Capacity (VIC) model, we simulated water budget components across the Indian Subcontinent during both the observed period and the future period to evaluate alterations in hydrological response and water availability. Our results showed that runoff-induced water availability has increased significantly in the Sabarmati, Pennar, Cauvery, and South Coast River basins, and decreased in the Ganga and Brahmaputra River basins, during the observed period. Moreover, we found that the majority of Indian dam catchments (except those in the Ganga and Brahmaputra River Basins) experienced a significant increase in monsoon precipitation and total runoff over the past three decades (1986-2022). Based on future analysis, we also found that nearly half of the dam catchments in the end period under SSP5-8.5 experienced around a 25% increase in monsoon precipitation and total runoff, which affects the reservoir operation and dam functionality in a future warming climate.
How to cite: Tiwari, M. and Aadhar, S.: Altered Hydrological Response and Water Availability of Indian Dams under Observed and Changing Climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1096, https://doi.org/10.5194/egusphere-egu26-1096, 2026.
Climate change is affecting water availability and irrigation management in agricultural systems, particularly where climatic pressures interact with technical and regulatory constraints. This study presents a case study developed through collaboration between academic research and local water management authorities, specifically the Piave land reclamation consortium (Consorzio di Bonifica Piave, northeastern Italy). This study investigates how projected climatic changes may impact hydrological conditions and crop water availability within a complex socio-ecological system. We used climate projections (CMIP6; CMCC-ESM2 model; SSP5-8.5 scenario) to assess changes in temperature, precipitation, potential evapotranspiration, and aridity indicators. These variables were combined with crop-specific coefficients to estimate irrigation water requirements for the main crops cultivated (maize, soybean, wheat, alfalfa, and vineyard) under near-term (2021–2040) and future (2041–2060) climate scenarios. The analysis focuses on relative changes in irrigation demand and their implications for water management. Results indicate a systematic increase in irrigation demand per unit area across all analysed crops. Projected changes show relative increases in specific irrigation requirements of 10–15% for arable crops and over 20% for forage crops, while key crops for the area such as grapevine, historically characterised by very low irrigation requirements (or no irrigation), exhibit the highest relative increases. These trends are mainly driven by increased evaporation rather than changes in total precipitation, leading to a growing imbalance between water demand and effective water availability during the irrigation season. Climatic pressures are also aggravated by technical and regulatory constraints, such as environmental flow requirements defined under historical hydrological conditions, which reduce operational flexibility during drought periods. Despite uncertainties inherent in climate and hydrological modelling, the proposed approach provides a bottom-up framework for informed decision making. The methodology is also transferable to specific sub-areas of the consortium, supporting targeted planning and project design aimed at enhancing irrigation resilience under future climate conditions.
How to cite: Straffelini, E., Ghirardelli, A., Borsato, E., Mirolo, D., and Tarolli, P.: Assessing climate-driven changes in crop water demand using CMIP6 data: implications for water management and decision making, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7481, https://doi.org/10.5194/egusphere-egu26-7481, 2026.
Posters virtual: Wed, 6 May, 14:00–18:00 | vPoster spot A
EGU26-17766 | ECS | Posters virtual | VPS9
Hydrodynamic Changes of Estuarine Islands in the Meghna River under Future Climate ScenariosWed, 06 May, 14:45–14:48 (CEST) vPoster spot A
Hydrodynamic processes strongly influence coastal and estuarine landscapes, especially in low-lying deltaic regions like the Meghna Estuary. Islands in the lower Meghna and at the Padma-Meghna confluence face increased risk of submergence due to sea-level rise and intensified precipitation under future climate scenarios. This study analyzes the long-term hydrodynamic changes in the Meghna Estuary using Delft3D simulations for 2000, 2024, and 2050, focusing on islands such as Nijhum Dwip, Moulovi Char, Domar Char, Char Kukri Mukri, Rajrajeshwar, Hatiya, and Manipura. The model covers the area from Baruriya Transit to the sea, integrating tidal and riverine dynamics. Future discharge for 2050 was generated from MIROC6 climate projections under SSP2-4.5 and SSP5-8.5 scenarios, bias-corrected and simulated via HEC-HMS. HEC-HMS was calibrated using 2022 data and validated with 2023 discharge records from Bhairab Bazar, while Delft3D was calibrated and validated using observed water level data from Daulatkhan over the same period. Results show rising tidal amplitudes and water levels, with high tides near Char Kukri Mukri increasing by 30 to 35 cm by 2050. Tidal inundation is expected to expand during monsoons, increasing flood risk in low-lying areas. Islands like Char Kukri Mukri and Hatiya are losing relative elevation, heightening their vulnerability to flooding and storm surges. Hydrodynamic projections indicate an average increase in water depth of 0.5 to 0.8 m around Rajrajeshwar, Hatiya, and Manipura by 2050, suggesting enhanced tidal energy and flow velocities that are likely to accelerate shoreline erosion and land loss, particularly along their southern and eastern margins. These findings highlight the increasing vulnerability of the Meghna Estuary’s islands to climate change–driven hydrodynamic shifts, emphasizing the urgent need for targeted adaptive management, improved flood risk mitigation, and resilience-building measures to protect the region’s communities and ecosystems from future inundation and erosion risks.
How to cite: Ahmed Dipu, S. U., Gemintang, E., Haque Laskor, Md. A., Bhuiyan, F., Galib Fardin, M. A., Rahman, Md. M., Rabbany, Y., and Islam Fahim, S.: Hydrodynamic Changes of Estuarine Islands in the Meghna River under Future Climate Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17766, https://doi.org/10.5194/egusphere-egu26-17766, 2026.
EGU26-21606 | ECS | Posters virtual | VPS9
The Role of Reservoirs in a Glacierized Basin Under Climate Change: An Analysis Using the WEAP ModelWed, 06 May, 14:48–14:51 (CEST) vPoster spot A
The Syr Darya River Basin is a highly glacierized transboundary system where future water availability is strongly influenced by climate change, reservoir operations, and population growth. This study investigates the role of reservoirs in regulating water supply under future climate scenarios using the Water Evaluation and Planning (WEAP) model. Climate projections from the ISIMIP framework under Shared Socioeconomic Pathways SSP1-2.6, SSP3-7.0, and SSP5-8.5 are used to drive hydrological inputs, including streamflow, precipitation, and temperature, while population growth projections represent evolving water demands.
Results indicate a strong increase in summer unmet demand by 2050, intensifying further by 2090, with peak deficits occurring in July–August. Reservoir refilling remains seasonal across all scenarios but becomes more variable and less reliable by 2090, with deeper drawdowns and reduced buffering capacity under higher-emission pathways.
How to cite: Abdul Jalil, U., D'Haeyer, B., Prakash, S., and Huang, J.: The Role of Reservoirs in a Glacierized Basin Under Climate Change: An Analysis Using the WEAP Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21606, https://doi.org/10.5194/egusphere-egu26-21606, 2026.
