This session invites theoretical, experimental, and applied studies that explore the management of both natural and human-made water storages under different local and global change scenarios, identifying the associated risks to sustainable water reservoir management. The goal is to unite diverse contributions including (but not limited to) remote sensing, in situ observations, AI-based methods, and hydrological modeling to enhance the sustainable management and implementation of freshwater storage systems.
Key topics include:
• Impacts of climate variability and change on reservoir performance and water availability
• Sedimentation, water quality, and ecological consequences of reservoir operation
• Role of digital tools, such as digital twins, in monitoring and optimizing reservoir management
• Governance, policy, and socio-economic dimensions of sustainable reservoir use
• Case studies highlighting innovative adaptation strategies and restoration initiatives
Water reservoirs play a crucial role in water resources management, providing a range of benefits that contribute to societal, economic, and environmental well-being. One of the primary functions of reservoirs is to provide water for agriculture, which is essential for irrigating crops and sustaining agricultural productivity. About 70% of global freshwater withdrawals are used for irrigation, creating substantial demand and alterations for regional hydrology. A study conducted by the World Commission on Dams revealed that irrigation dams frequently fail to deliver the projected water supply for their command areas (i.e., the irrigated area extent and location associated with each individual irrigation reservoir), underscoring inefficiencies in reservoir management.
Several additional challenges are expected to affect reservoir management in the future. For example, climate change can alter the volume of stored water in the reservoirs, whereas land cover change can increase sediment delivery, reducing reservoir storage capacity. Pollution may trigger harmful algal blooms, and conflicting objectives such as balancing domestic water supply, hydropower generation, and irrigation demands can make reservoir operation even more complex. Therefore, reservoir management is inherently a multi-objective task that must account for future storage conditions while balancing various water demands to ensure their sustainable supply.
Many researchers have tried to map irrigated areas and the crops produced therein, but no current global dataset provides command areas and crop production information at the resolution of individual irrigation reservoirs at a global scale. As a result, there is a clear global need for continuous, high-resolution information on command areas and crop production linked to individual water reservoirs.
This study proposes a new framework to cope with the complexity of irrigation reservoir management through two different steps, including (i) the identification of command areas and (ii) the determination of crop production and water demand for each command area for all large irrigation reservoirs worldwide, totaling more than 21,000. Command areas are estimated based on different criteria such as proximity to the reservoir, gravity-based water transfer (i.e., only downhill movement is allowed), irrigation and crop maps, exclusion of water bodies and urban areas, and slope considerations. Then, using crop production maps alongside the estimated command areas, geospatial analyses are applied to extract the total crop production within each command area. For each command area, the first step is to identify the different crop types harvested during the target year. Once the crop types are identified, the water requirements for all crops within the command area can be calculated. The annual water requirement for each command area then represents the sum of the water needed for all crop types grown within the command area during the target year.
Integrating crop production data with command area mapping allows for improved optimization of reservoir operations to balance irrigation needs with other competing uses such as hydropower generation, flood control, and environmental flows, as well as a better management of downstream irrigation production.
How to cite: Soleimanian, E. and Lehner, B.: Calculating crop production within the command areas of irrigation reservoirs at a global scale to support sustainable water management under climate change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5561, https://doi.org/10.5194/egusphere-egu26-5561, 2026.
The intense hydrological variability and the increased frequency of drought events in Mediterranean basins entail major challenges for achieving an effective balance between water-supply reliability and ecological conservation in regulated river systems. Within this context, this study examines the performance of an adaptive minimum environmental flow (MEF) regime aimed at enhancing drought resilience in a three reservoirs system of the Rivera de Huelva catchment (southern Spain), which constitute a critical component of the water-supply infrastructure for the metropolitan area of Seville.
An adaptive MEF regime, that reflects the natural hydrological variability, is defined based on a statistical approach and using historical streamflow data. This adaptive MEF regime was also variable between meteorological drought and no-drought situations using the Standardized Precipitation Index (SPI). To evaluate the impact of this new MEF regime, reservoir operation was simulated for the 2001/02–2024/05 period under two management scenarios: (1) the MEF regime currently implemented, and (2) the new proposed adaptive MEF regime. Based on observed daily inflows and operational releases, the analysis quantifies the individual impact of each flow regime on reservoir storage dynamics. Reservoir-specific water scarcity situations - pre-alert, alert, emergency - were established fixing different threshold to the normalization of observed storage volume. This procedure is consistent with the framework of the River Basin Drought Management Plan, and therefore it enables standardized characterization of water scarcity at the reservoir scale. Finally, a comparative analysis, based on the fraction of months allocated to each state was carried out.
The adaptive regime resulted in consistently higher storage levels across the three reservoirs, with mean increases which may vary from 5 to 10 hm³, depending on the specific reservoir. The effects are particularly notable in the smallest reservoir, where the incidence of alert and emergency states is reduced to approximately one third of that observed under the current regime, which indicates a substantial reduction in the frequency of emergency conditions under the adaptive regime.
Overall, the results demonstrate that the implementation of adaptive environmental flows can simultaneously reinforce supply-security outcomes and strengthen ecological resilience, thereby offering a robust and scalable strategy for reservoir management under increasing drought pressure.
Acknowledgments: This work has been funded by the project CONV 39-27 UCO-EMASESA, in the framework of the TED/934/2022-PCAU00006, funded by MITECO and by European Union NextGenerationEU/PTR.
How to cite: Contreras, E., Pimentel, R., Gómez-Beas, R., Puerto, A., Escot, C., and Polo, M. J.: Enhanced reservoir system management using adaptive environmental flows, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1352, https://doi.org/10.5194/egusphere-egu26-1352, 2026.
The increased frequency and intensity of hydrological extremes, including drought, due to anthropogenic climate change will drive the need for enhanced water supply resilience, even in water-rich countries. Previous studies have shown that small reservoirs have considerable potential for expanding water supply for various purposes, including when repurposed from flood-only reservoirs for both flood and drought protection. However, whether these repurposed reservoirs retain the same flood protection ability when operating under forecasts is still unclear, as reservoir operation under forecasts has primarily been researched in the context of large reservoirs. In this study, we investigated potential operating rules under forecasts for 30 small-to-midsize flood reservoirs to a) determine if the uncertainty introduced by forecasts degrades the performance of repurposed reservoirs so significantly as to render the concept unusable, b) identify patterns in the relationship between forecast accuracy and optimal reservoir performance, and c) identify patterns in optimal reservoir operation rules, under the constraint that flood protection should not be compromised. Performance is determined by the modelled ability to either supplement streamflow to avoid low flows or to provide water for irrigation purposes in the area of the reservoir. 1000 combinations of three operation parameters—the warning threshold at which flood pre-release begins, the rate at which water is released from the reservoir for flood pre-release, and the inflow at which the reservoir begins storing water—were tested for maintenance of flood protection (viability) and benefit for the reservoir’s additional uses. While some reservoirs indeed were no longer beneficial when optimized to operate under forecasts, many still maintained benefits above 40%, with a couple even surpassing their performance under perfect knowledge. Comparing changes in benefit from the perfect-knowledge operation to forecast accuracy indicated that high rates of hits, false alarms and misses, and misses (HFM) could explain the largest decreases in performance, while other forecast accuracy metrics were less impactful. However, even if HFM were low but nonzero, a poorly-timed false alarm could drain a reservoir’s storage before a spike in demand, causing a noticeable loss in performance. Investigation of reservoirs’ potential benefits under forecasts should therefore be done via simulation rather than approximated via characterizing indices. Optimal operation rules tended to be those that most closely mimicked the perfect knowledge operation, i.e. aggressive storage thresholds and a tendency to hold onto the water storage for as long as is safe, but more conservative operating rules were also able to provide benefits as well. The models for forecast operation and optimization produced for this study can be used by water managers to assess if existing small flood reservoirs can feasibly be used to increase water supply resilience in a changing world.
How to cite: Ho, S., Ehret, U., and Lang, R.: Forecast-based operation of re-purposed small reservoirs for floods, farms, and (low) flows, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7812, https://doi.org/10.5194/egusphere-egu26-7812, 2026.
Small farm reservoirs are human-made storage systems (from few hundreds m3 to 1Mm³) used all around the world to store water for agricultural uses (crop irrigation, livestock watering) . They are usually built directly across the stream (small dams) or in local depressions to store surface runoff water (hill reservoirs). In the absence of regulation from authorities, small dams can intercept and store upstream water throughout the year without any restrictions. This may have downstream impacts on streamflow and aquatic ecosystem, particularly during the dry season. Many countries, such as Spain and South-Africa, have incorporated the concept of environmental flow in their regulations to protect downstream water uses.
In France, since 2014, all dams irrespective of their size or construction date are required to maintain a downstream flow whenever upstream flow occurs. Reservoirs can only be filled if the upstream flow exceeds a minimum flow, which must be transmitted downstream. This minimum flow is set at 10 % of the inter-annual mean discharge at the location of the reservoir.
This study aims to evaluate the effect of the minimum flow on streamflow, especially low-flow, and water availability in small reservoirs. From a water management perspective, it addresses the question of the mitigation of the hydrological impacts of small reservoirs. We used the spatially-distributed agro-hydrological model MHYDAS-small-reservoirs (Lebon et al., 2022¹) to test four minimum flow values: 0%, 5%, 10%, and 20% of inter-annual mean discharge. The study site was the Gélon catchment (20 km²) located in South-Western France, characterized by hilly terrain, clay loam soils, and a groundwater dominated hydrology. The four values of minimum flow were tested with three different hypothetical 14-reservoirs networks to consider the effect of reservoir distribution (Lechevallier et al., 2025²), and with two values for total reservoir capacity. This results in a total of 24 simulations, in addition to the reference simulation without reservoirs or irrigation. The agronomic context involved intensive reservoir use to irrigate maize and soybeans crops. Simulations were run on 20 years at a hourly time step.
The impact on low-flows was assessed spatially as the change in the number in low-flow days compared to the reference situation without reservoirs. Our on-going research reveals that the greatest impact occurs at 0% of minimum flow, and the effect diminishes with increasing minimum flow, reaching a no-impact situation at 20% of minimum flow. Additionally, withdrawals and water availability are little impacted by the implementation of minimum flows, except for upstream reservoirs. These findings demonstrate that minimum flows effectively mitigate the impacts of small farm reservoirs on low-flows. Future analysis will explore the effects of minimum flows on crop yields and simulate alternative management strategies with restrictions on reservoir refill during the dry season.
¹ https://doi.org/10.1016/j.envsoft.2022.105409
² https://doi.org/10.5194/egusphere-egu25-6876
How to cite: Lechevallier, H., Dagès, C., Burger-Leenhardt, D., and Molénat, J.: Exploring the potential of minimum flows to mitigate the impacts of small farm reservoirs on low-flows, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11155, https://doi.org/10.5194/egusphere-egu26-11155, 2026.
Mediterranean river basins are characterized by high hydroclimatic variability and the recurrence of drought episodes that strongly condition water resources availability and management. In these systems, water scarcity situations are not only triggered by a reduction in water quantity but, may also be conditioned by a bad water quality that compromises multiple uses. This was the case of the water crisis experienced in the northern part of the Córdoba province during 2023, when, more than 80,000 people did not have running water at home for more than a year. The main reservoir supplying water to the population, Sierra Boyera Dam, was dried out and the safeguard water coming from La Colada reservoir did not fulfill the requirements for their consumption due to high rates of arsenic, TOC, and nitrogen. Therefore, early detection of these situations is particularly relevant in regulated basins, where drought develops progressively and with non-simultaneous responses across the system components due to storage effects and management practices.
This work uses this water crisis as case study to propose to include water quality in the definition of droughts. For that a Combined Water Scarcity Index (CWSI) that combines meteorological, agricultural and hydrological drought with a fourth component explicitly linked to water quality is proposed. Conventional drought indexes (i.e., Standardized Precipitation Index – SPI -, Standardize Soil Moisture Index – SSMI – and Standardized Streamflow Index – SSI) are used to account for the different types of droughts. In the case of water quality, the potential non-point pollution index modified monthly by precipitation patterns is adapted to be used as a fourth component of the combined drought index. The period 1960-2024 has been used for defining this new combined index. A comparative analysis has been carried out to assess the impact of including the potential affection of water quality in water scarcity definition and some specific cases know in the area were used as validation datasets for the methodology proposed.
The results show that the inclusion of water quality in drought assessment increases the number of water scarcity situations identified. Therefore, CWSI enables the early identification of alert states and tipping points relevant for decision-making to deal with water scarcity situations, highlighting its potential as a tool for foreseeing water scarcity episodes. In addition, our results showed that those areas with high water pollution potential risk, predominantly associated with zones of intensive agriculture, livestock farming, and urban development, had to face more frequent water scarcity situations and water shortages due to poor water quality in reservoirs.
Acknowledgements: This study has been funded by the call “Grants to develop innovative solutions to address drought, within the framework of the PLAnd Drought Andalusia. 2023 Call” through the project PLSQ-00172-F – “Service for the early detection of alert states in water management under scarcity conditions” (SEGA)
How to cite: Santos, L., Herrera, F., Contreras, E., Andreu, A., Gómez-Beas, R., Aguilar, C., Polo, M. J., and Pimentel, R.: Including water quality in drought definition for a better assessment of water scarcity situation in Mediterranean highly human modified catchments., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10912, https://doi.org/10.5194/egusphere-egu26-10912, 2026.
Amid global warming and expanding high-altitude hydropower development, characterizing the carbon source-sink dynamics of cryospheric waters is pivotal for sustainable water resource management. However, water-carbon coupling across natural and artificial water bodies in the Third Pole remains poorly understood. This study deeply explored the coupling influence mechanism of hydrological, climate, biogeochemical, land cover, and human factors on water-air carbon dioxide (CO2) flux across lakes, reservoirs, and rivers in the Yarlung Tsangpo basin (YL). Results indicate that compared with inland waters, lakes and reservoirs in the YL were obvious carbon sinks (4.91 ± 86.92 and 21.23 ± 95.67 mmol m-2 d-1, respectively), especially during normal and flood periods, whereas rivers predominantly acted as CO2 sources (103.04 ± 194.88 mmol m-2 d-1). The key drivers of CO2 flux were pH, air temperature, and runoff etc. Runoff showed obvious spatial heterogeneity that correlated negatively with CO2 flux in upstream lakes/reservoirs but positively in downstream rivers. Structural equation modeling identified pCO2water (pH-controlled), climate (rainfall, temperature), and runoff as direct drivers for CO2 flux. Increased rainfall and temperature facilitate CO2 uptake of YL waters, further retained by lentic systems but re-released by rivers via runoff. Runoff effects on carbon sequestration in reservoirs were weaker than in lakes, indicating that while damming converts rivers from sources to sinks, operations may weaken the sink capacity. Operation ratios range from -0.24 ~ 0.56, and less than -0.36 might be an ideal regulation range. Our findings highlight the critical role of lentic systems in CO2 uptake within the YL. While impoundment can reduce carbon emissions from rivers, careful operational regulation is essential.
How to cite: Chen, Y., Sun, J., and Liu, P.: Water-Carbon Coupling Processes on the Third Pole: Differential Carbon Source-Sink Effects and Mechanisms in Lakes, Reservoirs, and Rivers of The Yarlung Tsangpo River Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11900, https://doi.org/10.5194/egusphere-egu26-11900, 2026.
This study develops and applies a deficit‑based approach to estimate the minimum buffering of water deficits (summer drought) required so that potatoes in Finland avoid specified levels of water shortage under two future CMIP6 scenarios of SSP2‑4.5 and SSP5‑8.5. Using an ensemble‑based daily water‑balance model, future changes in precipitation and crop evapotranspiration are translated into spatially explicit indices of deficit severity, duration of consecutive deficit days, and the associated deficit buffering needed to keep water stress within chosen tolerance levels. The results indicate an increasing mismatch between water supply and crop water demand under high‑emission conditions, leading to more frequent and persistent dry spells and a strong rise in required deficit buffering, particularly in southern agricultural regions. In contrast, the intermediate‑emission pathway produces more moderate increases and a more limited spatial expansion of high-risk areas. Increasing the tolerated length of consecutive deficit days reduces the average deficit buffering needed but increases relative spatial variability, highlighting a trade‑off between acceptable crop stress and the scale of buffering measures. Overall, the deficit‑based indices provide a practical framework to support adaptive decision-making across Finland for climate‑resilient planning of irrigation, soil‑water management, and on‑farm buffering strategies for potatoes and other water‑sensitive crops in northern European agriculture.
How to cite: Naghdyzadegan Jahromi, M., Gohari, A., Nakigudde, C. K., and Torabi Haghighi, A.: Deficit Buffering Indices for Climate-Resilient Potato Water Management in Finland under CMIP6 SSPs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18378, https://doi.org/10.5194/egusphere-egu26-18378, 2026.
Small agricultural reservoirs are a critical, yet poorly documented component of managed water storage systems, supporting irrigation and livestock water demands (Aminzadeh et al., 2025). Due to small size (often <0.1 km²) and strong temporal variability of agricultural reservoirs driven by evaporative losses and frequent withdrawals (Aminzadeh et al., 2024, 2018), they are commonly overlooked in the existing global inventories of inland water bodies. We present the first comprehensive global, seasonally resolved dataset of small agricultural reservoirs derived by integrating Sentinel-2 optical indices and Sentinel-1 radar backscatter. The product includes four seasonal layers for March 2024-February 2025 (MAM, JJA, SON, DJF). Water bodies are detected independently in optical and radar imagery using an edge-aware, locally adaptive dynamic thresholding approach. We identified more than 5 million reservoirs globally, with the highest density in China, the United States, and India. Validation against ~2,000 independently delineated reservoirs shows strong area agreement (R² = 0.92), enabling forward updates and retrospective back-casting toward a multiyear global record.
References
Aminzadeh, M., Friedrich, N., Narayanaswamy, S., Madani, K., Shokri, N., 2024. Evaporation Loss From Small Agricultural Reservoirs in a Warming Climate: An Overlooked Component of Water Accounting. Earth’s Future 12, e2023EF004050. https://doi.org/10.1029/2023EF004050
Aminzadeh, M., Lehmann, P., Or, D., 2018. Evaporation suppression and energy balance of water reservoirs covered with self-assembling floating elements. Hydrology and Earth System Sciences 22, 4015–4032. https://doi.org/10.5194/hess-22-4015-2018
Aminzadeh, M., Narayanaswamy, S., Nevermann, H., Zampieri, M., Hoteit, I., D’Odorico, P., AghaKouchak, A., Madani, K., Shokri, N., 2025. Water storage paradox of reservoir expansion and evaporative losses in the MENA region. Sci Rep 15, 34297. https://doi.org/10.1038/s41598-025-21859-w
How to cite: Govindaiah Narayanaswamy, S., Aminzadeh, M., Alemohammad, H., and Shokri, N.: Global distribution of small agricultural reservoirs and their seasonal dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22569, https://doi.org/10.5194/egusphere-egu26-22569, 2026.
Water evaporation represents a major source of water loss in agricultural systems, particularly in arid and semi-arid regions. Developing innovative, data-driven approaches to quantify and manage evaporation is therefore essential for sustainable water resource management. This study proposes an original experimental protocol combined with machine learning techniques to support smart evaporation management at the plot scale.
The experimental setup consists of two identical artificial basins exposed to the same climatic conditions: one partially covered by a photovoltaic panel, while the other remains uncovered. Continuous high-resolution measurements of water level variations, along with other climatic parameters (humidity, air temperature, water temperature, TDS, etc.), are collected using sensors, enabling a precise characterization of evaporation dynamics under contrasting surface conditions.
The acquired experimental data constitute a dedicated database for training machine learning models, including Support Vector Machines (SVM), Gradient Boosting, and Random Forest, aimed at predicting evaporation rates and identifying the main controlling factors. According to the results, the Gradient Boosting model performed best, achieving an R² of 0.993 and RMSE of 0.245 for the open basin, and an R² of 0.996 and RMSE of 0.158 for the covered basin, indicating highly accurate predictions. Random Forest and SVM were also tested, showing good and poor predictive performance, respectively.These findings demonstrate the reliability of ensemble models, particularly Gradient Boosting, for modeling evaporation from measured climatic parameters. The models support adaptive irrigation strategies and contribute to the development of an intelligent agricultural plot, where water losses can be anticipated and minimized.
This work highlights the potential of coupling experimental hydrological observations with machine learning to reduce evaporation losses while promoting the integration of renewable energy solutions in agricultural water management.
key words: Water evaporation,Climate Change,Machine Learning,Experimental protocol,Photovoltaic covering, Smart agricultural plot
How to cite: ouchkir, I., Arioua, A., Arioua, B., Karaoui, I., Nait-taleb, O., El Kamouni, F. E., and Bimouhen, M.: An Experimental Protocol Combined with machine mearning for Smart Evaporation Management under Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4527, https://doi.org/10.5194/egusphere-egu26-4527, 2026.
Saline lakes play a critical role in ecosystem functioning and are highly sensitive to both
climatic variability and human-induced pressures. Rising global water demand and intensified
water extraction coupled with shifts in precipitation regimes and increasing temperatures
have altered the hydrological stability of many saline lakes across the world. This study
integrates satellite remote sensing and multi-decadal historical observations to assess the
spatial extent and long-term dynamics of more than 24,000 saline lakes (> 10 ha) worldwide
from 1985 to 2021. Our preliminary results reveal that approximately 15% of these lakes have
undergone notable shrinkage, about 31% have experienced expansion, and the rest have
remained largely unchanged during the study period. Linking spatial trends to climatic regimes
indicates that lake shrinkage is primarily concentrated in arid and semi-arid regions which
often experience acute water stress problems. In contrast, accelerated snow and glacier melt
with global warming has been a primary driver of lake expansion. These findings underscore
the need for region-specific water management strategies, especially in water-stressed
regions where lake desiccation enhances ecosystem degradation and dust emissions with
significant human health implications (Hassani et al., 2020).
Hassani, A., Azapagic, A., D'Odorico, P., Keshmiri, A., Shokri, N. (2020). Desiccation crisis of
saline lakes: A new decision-support framework for building resilience to climate change.
Science of the Total Environment, 703, 134718,
https://doi.org/10.1016/j.scitotenv.2019.134718
How to cite: Kumaraswamy, I., Aminzadeh, M., and Shokri, N.: A global assessment of saline lake dynamics from 1985 to 2021, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6863, https://doi.org/10.5194/egusphere-egu26-6863, 2026.
Lakes and reservoirs support rich biodiversity and are essential for the natural production of over 12% of Germany's drinking water. Their biodiversity is crucial for maintaining water quality but is increasingly threatened by climate change, pollution and the spread of invasive species. In the context of the IQ Water project, a multifaceted approach is employed to assess water quality, encompassing conventional parameters such as physical, chemical, and hygienic metrics, as well as assessments of the planktonic community, in conjunction with innovative molecular methodologies (e.g., eDNA analyses). This integrated strategy enables the exploration of reservoir behavior across multiple dimensions, including physicochemical aspects, in addition to the often-overlooked domain of microbial biodiversity, encompassing bacteria, viruses, protozoa, and fungi. The focus of this research is on water quality parameters, including, but not limited to blooms of potentially toxic cyanobacteria or hygienic relevant bacteria, antibiotic resistance genes (ARG), viruses, and invasive species. The overarching objective of the project is to develop biodiversity models for drinking water reservoirs by integrating complex biological, chemical, and physical data with machine learning (ML) technologies. These ML models aim to enable the prediction of important hygienic challenges like cyanobacterial blooms and the distribution of pathogens and ARGs, thereby contributing to the advancement of understanding of aquatic freshwater ecosystem dynamics.
In this contribution, we present preliminary findings regarding the efficacy of molecular methodologies in analyzing reservoir biodiversity. We also offer insights from a data-centric perspective, including the necessity of a unified data schema for the collection of highly heterogeneous data and the support of machine learning (ML)-based modeling. We showcase ML-based cross-reservoir assessments for ecosystem monitoring based on the proposed framework by modeling biochemical and physicochemical fingerprints. Furthermore, we propose a neural network–based multi‑resolution modelling approach that explicitly accounts for strongly variable sampling intervals (hours to months) within a single model. The architecture treats meteorological and physicochemical time series as primary sequential inputs and uses sparsely sampled molecular profiles as contextual information via learned embeddings and cross‑attention.
How to cite: Wunsch, A., Kühnert, C., Holzer, C., Ho, J., and Hügler, M.: IQ Water: AI-supported modeling and forecasting of biodiversity and water quality in drinking water reservoirs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7826, https://doi.org/10.5194/egusphere-egu26-7826, 2026.
This paper proposes the Neural Evolution-Enhanced Differential Evolution (NEDE), a novel meta-heuristic algorithm designed to optimize the operations of complex, high-dimensional reservoir clusters—a critical task for efficient hydropower utilization and global carbon reduction. Integrating Differential Evolution (DE) with Deep Reinforcement Learning (DRL) and the concept of "evolutionary paths," NEDE features a novel neural network-based architecture comprising a population encoder, policy selector, and parameter controller. By leveraging the adaptive capabilities of DRL to dynamically adjust DE parameters and mutation strategies, the algorithm effectively addresses the challenges of hydraulic coupling and hydrological uncertainty inherent in high-dimensional systems. The neural network is trained within a reinforcement learning framework utilizing fitness rewards and entropy regularization. Comparative analyses on the IEEE CEC 2020 benchmark functions and the real-world downstream Jinsha River - Three Gorges cascade system demonstrate that NEDE delivers superior solution accuracy and faster convergence than conventional algorithms. Specifically, compared to LSHADE, NEDE increases average and maximum power generation by 0.4% and 0.9% in wet years, 1.0% and 0.9% in normal years, and 1.0% and 1.2% in dry years, respectively, validating its robustness and effectiveness in dynamic reservoir scheduling.
How to cite: Yang, L., Qin, H., Li, C., and Xu, X.: Deep Reinforcement Learning Aided Differential Evolution for High-Dimensional Reservoir Optimization: The Case of Jinsha River - Three Gorges Cascade , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8537, https://doi.org/10.5194/egusphere-egu26-8537, 2026.
Climate change, population growth, and water source pollution present significant challenges for water resource managers, who often face limited resources and scarce in-situ data in the arid and semi-arid regions of Sub-Saharan Africa. In Kenya, about 80% of the country’s land area falls within these arid and semi-arid regions. These areas support 36% of the human population and 70% of the livestock population, contributing roughly 50% of agricultural GDP and 15% of national GDP. Water pans, which are small, shallow reservoirs that fill with surface runoff, sustain local livelihoods by supplying water for livestock, wildlife, and small-scale agropastoral irrigation. However, water pans are becoming increasingly susceptible to climate change, highlighting the need for continuous monitoring to ensure water availability for communities. Remote sensing provides a valuable complement to traditional water monitoring techniques by offering spatially extensive and repeatable observations that enhance our understanding of water dynamics. In this context, our primary aims were to evaluate the potential of Sentinel-2 imagery for detecting water presence and assessing physicochemical parameters, specifically turbidity and specific conductivity, in water pans in Taita Taveta County, Kenya. We employed mid-point and receiver operating characteristic (ROC) curve-based threshold methods for water presence detection, alongside generalized additive models for estimating turbidity and specific conductivity. We achieved an F1 score greater than 95% for water presence detection using the Normalized Difference Moisture Index and the two thresholds. The B8A/B4 predictor for specific conductivity yielded a coefficient of determination (R²) of less than 0.5 with both standard and group leave-one-out cross-validation (LOOCV). In contrast, the B8/B4 and B8/B5 predictors for turbidity recorded R² values greater than 0.8 with standard LOOCV and greater than 0.6 with group LOOCV. Overall, this study demonstrates the potential of remote sensing-based approaches for water monitoring, even under conditions of limited data availability.
How to cite: Ogola, P., Heiskanen, J., Too, A., Mundia, C., Gettel, G., and Pellikka, P.: Remote sensing of water presence and physicochemical parameters in water pans in semi-arid Kenya using Sentinel-2 imagery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9551, https://doi.org/10.5194/egusphere-egu26-9551, 2026.
Reservoirs are a cornerstone of global water management, providing critical buffering capacity for irrigation, municipal supply, energy production, and environmental flows. However, intensifying drought under warming climate is increasingly challenging the reliability of reservoir storage worldwide. Unlike meteorological or hydrological droughts, reservoir droughts emerge from nonlinear and lagged interactions between climate forcings, catchment processes, and storage dynamics, and therefore remain poorly characterized in global drought assessments. In particular, consistent metrics that capture the intensity, spatial extent, and frequency of reservoir storage deficits across regions are lacking.
Here, we present a global assessment of reservoir drought patterns using a storage-centric framework based on standardized reservoir storage anomalies (SRSA). We analyze monthly storage variations for approximately 7,000 large reservoirs worldwide over the period 1999–2018, spanning 44 IPCC reference regions. SRSA is computed using long-term, month-specific climatologies for each reservoir. Trends in SRSA are evaluated using Mann–Kendall tests at the reservoir scale and aggregated to assess field-significant regional patterns. To characterize the spatiotemporal structure of reservoir droughts, we extend the Intensity–Extent–Frequency (IEF) framework to reservoir storage. Drought intensity is defined as the normalized storage deficit within affected reservoirs, extent as the fraction of regional storage capacity impacted, and frequency as the return interval of such events. Capacity-weighted metrics are used to quantify regional drought behavior and distinguish localized from system-wide storage failures.
Results reveal a pronounced latitudinal divide in global reservoir drought behavior. Northern regions generally exhibit stable or increasing storage trends and experience frequent but low-severity fluctuations that are spatially coherent across reservoirs. In contrast, tropical and subtropical regions show declining storage trends and are dominated by episodic, high-intensity droughts that affect a limited fraction of regional capacity. IEF curves further demonstrate that extreme reservoir drought risk is primarily driven by localized storage failures in lower-latitude regions, whereas droughts in northern regions tend to expand more uniformly across systems. These findings highlight substantial regional heterogeneity in reservoir drought dynamics and emphasize the importance of storage-based diagnostics for understanding drought risk in managed water systems. This study provides a global, capacity-weighted assessment of reservoir drought intensity, extent, and frequency and establishes a transferable framework for evaluating reservoir vulnerability under ongoing and future climate change.
How to cite: Upadhyay, S. and Marshall, A.: Global Assessment of Reservoir Drought Patterns, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14976, https://doi.org/10.5194/egusphere-egu26-14976, 2026.
Human-driven nutrient enrichment is accelerating the spread of invasive aquatic macrophytes, generating substantial ecological and socio-economic impacts in freshwater ecosystems, including biodiversity loss, deterioration of drinking water quality, reduced fisheries productivity, constraints on recreational use as well as impaired waterborne transport. Consequently, the management of invasive aquatic weeds is now widely regarded as a priority for the conservation and sustainable use of freshwater lakes.
This study critically reviews the main control strategies currently adopted to limit the expansion of highly invasive species such as Salvinia molesta, Eichhornia crassipes, Egeria densa, Pistia stratiotes, and Elodea nuttallii. Starting from 30,659 academic and grey literature articles matching our search criteria across multiple browsers (i.e. Google Scholar, ProQuest, Web of Science, and Scopus), we critically analysed 155 fully relevant articles, focusing on lake morphology, infestation details (year of detection and species involved), strategy characteristics and their effectiveness (reduction in surface coverage and containment in the event of reappearance), as well as the qualitative and quantitative advantages and disadvantages of each method.
Our work also examines the global distribution of such management practices and integrates satellite-based remote sensing data to quantify macrophyte surface coverage in lake environments pre‑ and post‑control. Our results to date have identified three dominant approaches: mechanical removal (in 15.6% of the cases), chemical herbicide application (19.5%), and biological control (28.6%), alongside integrated management combining the former approaches (28.6%) and other treatments (7.8%).
Mechanical harvesting and chemical treatments can rapidly reduce biomass, yet their long-term application is often constrained by high operational costs and, in the case of herbicides, potential environmental risks. Biological control, typically involving specialist insects or herbivorous fish, appears to offer a more sustainable and self-maintaining option (with a recurrence rate of 11.4% of the cases, compared with 33.3% for chemical approaches and 41.7% for mechanical treatments), although its effectiveness depends on predator–prey specificity and the suitability of local climatic conditions.
In terms of geographical distribution, the case studies were unevenly distributed, with 40.8% located in North America (which shows a predominance of chemical treatment accounting for 36.7% of the total, particularly in the United States), 25.0% in Africa (where 70.0% of the cases involved biocontrol), and a smaller share in Oceania and Asia (representing 20.0% and 10.8% of the total, respectively), with an even smaller proportion in Europe and South America.
By comparing the strengths, limitations, and context-dependent requirements of each method, this study supports the selection of appropriate management strategies for future case studies, taking into account ecological characteristics, invasion dynamics, geographic setting, and available economic resources.
How to cite: Reboldi, M., Bertone, E., Valerio, G., O'Halloran, K., and Purcell, M.: Comparative Assessment of Management Strategies for Invasive Aquatic Macrophytes in Freshwater Lakes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15870, https://doi.org/10.5194/egusphere-egu26-15870, 2026.
Artificial reservoirs with meandering planforms and tributary junctions often exhibit complex three-dimensional flow structures that vary depending on hydrologic conditions. In such systems, interactions between inflow regimes and water-intake facilities can influence both hydraulic behavior and water-supply stability. This study examines the flow-regime-dependent hydrodynamic characteristics of Lake Paldang, a large regulated reservoir that serves as a primary drinking-water source for approximately 25 million people in the Seoul metropolitan area, Korea.
Field measurements were conducted under contrasting hydrologic conditions, including flood and normal-flow periods, focusing on major bend sections downstream of tributary confluences. Three-dimensional velocity fields were obtained using an Acoustic Doppler Current Profiler (ADCP), while vertical profiles of water-quality parameters were measured using multi-parameter sondes (YSI-EXO2). Spatial patterns of flow and mixing were analyzed by integrating cross-sectional velocity distributions, electrical conductivity fields, and the positions of maximum-velocity lines (MVL). These datasets were used to examine secondary-flow structures, lateral mixing behavior, and transport pathways of distinct water masses.
The results indicate that during flood conditions, increased discharge from main tributaries enhances curvature-induced momentum, leading to a pronounced lateral separation of the MVL and the development of a dominant single secondary-circulation cell. Under these conditions, the flow field exhibits river-like characteristics, suggesting an increased potential for asymmetric sediment transport and bank-related hydraulic stresses. In contrast, during normal-flow periods, overall flow velocities decrease and multiple smaller secondary cells emerge across the channel section, reflecting more lacustrine hydraulic behavior with reduced lateral momentum and weaker organized circulation.
In addition, under specific hydrologic regimes, tributary inflows characterized by relatively high electrical conductivity were observed to migrate along near-surface pathways toward water-intake zones. This behavior suggests that seasonal flow conditions may influence not only mixing efficiency but also the potential exposure of intake facilities to pollutant-rich inflows.
Overall, the findings suggest that regulated artificial lakes can alternate between riverine and lacustrine hydrodynamic states depending on flow regimes, with direct implications for mixing processes, sediment dynamics, and intake management. The study highlights the value of high-resolution field measurements for understanding regime-dependent hydraulic behavior and supports the need for adaptive monitoring and operational strategies to enhance the resilience of reservoir-based water-supply systems.
How to cite: Kang, Y., Choi, S., Lee, S., and jeong, B.: Field-Based Investigation of Flow-Regime-Dependent Hydrodynamic Characteristics in a Complex Artificial Lake, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16555, https://doi.org/10.5194/egusphere-egu26-16555, 2026.
Endorheic lakes, terminal basins without surface outflows, are among the most sensitive indicators of hydroclimatic change. While recent global analyses have highlighted widespread shrinkage driven by a combination of anthropogenic and climatic factors, many endorheic lakes have remained stable or even expanded over the past two decades. We hypothesize that understanding the mechanisms behind their resilience can help adaptive water management and conservation strategies in closed basins. Building on our global assessment of 635 endorheic lakes (Nevermann et al., 2025), which identified 130 lakes exhibiting significant shrinkage, here we focus on the remaining non-shrinking systems to determine how they persist under increasing hydroclimatic stress. Using multi-decadal satellite records, land-use data, and climate reanalysis, we aim to quantify decadal hydrological stability trends (for 2000 to 2021). A comparison of stable versus shrinking lakes across climate zones, water-stress categories, and basin-level anthropogenic activity will help disentangle resilience mechanisms such as increased glacial melt contributions, climatic water surpluses, effective basin management, and limited irrigation pressures. Preliminary findings indicate that many stable lakes occur in high-elevation basins (e.g., Tibetan Plateau, Andes), where increased cryospheric water input offsets evaporative losses, while others in semi-arid regions exhibit stability linked to strong governance or reduced agricultural intensity. These contrasting hydrological trajectories provide valuable insights into how natural and managed systems maintain equilibrium under global change.
Nevermann, H., Aminzadeh, M., Madani, K., D’Odorico, P., AghaKouchak, A., & Shokri, N. (2025). A global perspective on endorheic lake shrinkage: Impacts of anthropogenic and atmospheric factors. EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8774. https://doi.org/10.5194/egusphere-egu25-8774
How to cite: Nevermann, H., Aminzadeh, M., Or, D., and Shokri, N.: Why some terminal lakes remain stable while others shrink under hydroclimatic stresses?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18717, https://doi.org/10.5194/egusphere-egu26-18717, 2026.
The “Kefalari Agios Ioannis” spring, situated at approximately 871 m elevation and about 1,650 m south-southeast of the picturesque village of Dimitsana (Peloponnesus, Greece), is used for both drinking water supply and irrigation.
The spring is a contact spring, discharging the karst aquifer developed in the Upper Cretaceous platy limestones of the Pindos Unit, at their contact with the underlying impermeable red cherts, siltstones, and “First Flysch” (Upper Jurassic – Lower Cretaceous) of the same unit.
The recession coefficient of the “Kefalari Agios Ioannis” spring, calculated from flow measurements conducted between 14 July 2024 (711.1 m³/h) and 27 October 2024 (69.4 m³/h), is 8.69 × 10-³ days-¹. This value indicates that groundwater flow occurs mainly through fractures and intra-stratigraphic voids within the Upper Cretaceous platy limestones of the Pindos Unit. The calculated recession coefficient is consistent with values reported in the literature for karst aquifers developed in the Pindos Unit and equivalent formations, which are on the order of 10-³ days-¹ (Soulios, 1985; Giannatos, 1999; Karalemas, 2010).
The hydrological year 2023-2024 was particularly dry (1,109.2 mm), and the calculated recession coefficient should therefore be interpreted with caution, as it reflects flow conditions under prolonged drought and water scarcity. Such conditions may alter groundwater circulation, which is not uniform across the hydrogeological basin and becomes more evident under extreme hydrological conditions—either surplus (wet years) or deficit (dry years)—when different sections and levels of the recharge area are activated or operate differently. Notably, the recession period lasted at least 105 days. The following hydrological year, 2024-2025, was also dry (1,135.6 mm), in contrast to the wetter years 2021-2022 and 2022-2023, which recorded precipitation totals of 1,436.4 mm and 1,426.6 mm, respectively. For the ongoing 2025-2026 hydrological year, a total of 602.4 mm of precipitation has been recorded as of 14 January, indicating that dry conditions persist.
Effective water resources management should prioritize the protection and zoning of the karst aquifer, include systematic monitoring of spring discharge and groundwater quality, regulated and sustainable planning of groundwater abstraction through controlled boreholes, and the enhancement of natural and artificial recharge where feasible. Such adaptation measures are essential to mitigate the impacts of extreme hydrological events and prolonged droughts, ensuring the long-term availability of water for both human consumption and downstream cultural heritage sites.
Under the currently observed low-discharge conditions (98.2 m³/h as of 7 August 2024), the operation of the Open-Air Water Power Museum of the Piraeus Cultural Foundation, which is located immediately downstream, is significantly affected, as the available spring flow becomes insufficient during the summer months. Consequently, the museum is periodically forced to suspend its operation, highlighting the direct dependence of cultural and touristic activities on the hydrological regime of the “Kefalari Agios Ioannis” spring.
In conclusion, the sustainable management of water resources in the Dimitsana area, and particularly of the karst aquifer discharged by the “Kefalari Agios Ioannis” spring, is imperative given the combined pressures of ongoing tourism development and climate variability.
How to cite: Korovesai, A., Filis, C., Skourtsos, E., Andreadakis, E., Kapourani, E., Karalemas, N., and Alexopoulos, A.: Water Resources Management of the “Kefalari Agios Ioannis” Spring, Dimitsana, Greece, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20614, https://doi.org/10.5194/egusphere-egu26-20614, 2026.
Three main aquifer systems have developed on Kythira Island (Greece) (Pagounis, 1981; Pagounis & Gertsos, 1984; Danamos, 1991; Koumantakis et al., 2006; Filis et al., 2019):
- The porous aquifer system within Neogene and Quaternary formations.
- The karst aquifer system developed in the carbonate formations of the Pindos and Tripolitza Units.
- The aquifer system, both shallow and deep, within fractured hard rocks, mainly associated with the Phyllites – Quartzites Unit.
The main discharge of the aquifer systems takes place in coastal and submarine brackish springs around the island, except for its northern part where the Phyllites – Quartzites Unit outcrops and its central part where springs of small capacity discharge the carbonate formations of the Pindos Unit.
Precipitation is the direct recharge of the three aforementioned aquifer systems while indirectly lateral discharge occurs in places between adjacent and tangential aquifer systems and from the streams runoff as well.
The municipal water supply of Kythira has been reinforced by a series of projects and interventions, focusing on the summer touristic period, mainly consisting of new deep boreholes and low-capacity desalination plants.
The climate crisis has led to increasingly frequent high-intensity hydro-meteorological events, particularly in summer, with heavy rainfall over short periods. Consequently:
- Surface runoff dominates, limiting groundwater recharge.
- Evapotranspiration increases due to high temperatures and longer daylight hours.
Taking the above into consideration, the following conclusions can be drawn regarding the water resources of Kythira:
- The coverage of water supply needs during the summer months faces severe challenges, with frequent interruptions in water distribution.
- Overexploitation of available water resources occurs during the summer months, due to the significant increase in population and the inability to meet water demand, as a result of the substantial tourism development in recent years.
- During the period of maximum water demand (summer months), the available water supply is at its minimum.
- The climate crisis has adversely affected the recharge of individual aquifers.
- The drilling of new water-supply boreholes does not always yield the desired results, due to the area’s particular hydrogeological structure.
- Water resources management in Kythira presents a pessimistic outlook, as the projected changes in mean seasonal and average climatic parameters are negative, indicating decreased precipitation accompanied by increased temperatures.
In conclusion, there is an urgent need to implement actions and interventions for the sustainable management of the water resources of Kythira, which, depending on local conditions, may include the following:
- Proposals/measures for the rational management of groundwater resources at the Community level (environmental awareness, drilling of water-supply boreholes, desalination plant locations, protection zones for municipal water abstraction works, etc.).
- Siting of small check dams along watercourses to regulate downstream flow and promote artificial recharge.
- Siting of small reservoirs within and/or outside watercourses for the storage of winter runoff, as well as identification of locations for drilling boreholes for the implementation of artificial recharge, under specific conditions.
How to cite: Zoumbourlis, G., Filis, C., Skourtsos, E., Megalokonomou, E., Ketsetsioglou, V., and Trianti, N.: Water Resources Management in Kythira Island (Greece) under High Tourism Pressure and Climate Crisis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20903, https://doi.org/10.5194/egusphere-egu26-20903, 2026.
