Real-time modelling frameworks face several challenges, including the integration of diverse data streams and practical constraints on modelling, as well as the need to deliver timely and reliable outputs. Addressing these challenges is key to improve how water and environmental systems are managed under growing pressures from climate change and human activities. This session invites contributions on innovative approaches, tools, and case studies that demonstrate how observations and models can be combined to support operational and strategic decisions.
Topics of interest include, but are not limited to:
1) Integration of modelling with ground-based and satellite observations
2) Real-time data assimilation and forecasting for decision support
3) Conceptual, numerical, and data-driven approaches for decision-relevant modelling
4) Optimised monitoring, site characterisation, and data processing
5) Real-world case studies showing how modelling informs operational water and environmental management
PICO: Tue, 5 May, 16:15–18:00 | PICO spot A
The appropriate management of the water system requires a holistic consideration of the inland waters, the marine ecosystems and their interactions. However, these two systems are monitored, analysed and modelled separately and managed with often non connected policies. This is in part due to the intrinsic characteristics of the two systems and to the complex processes occurring between them, usually understudied. Nowadays modelling offers new opportunities for integrating land-sea interactions, as we show in this study. At the same time, such models are expanding their capabilities in cloud computing environments. However, many existing modelling tools remain fragmented and are limited to either inland or marine components, such as Digital Twin Earth (DTE) Hydrology Next or European Digital Twin Ocean (EDITO). To overcome this limitation, the current work presents a virtual research environment (VRE)-based workflow with a single interface for the whole water continuum: from inland water, through coastal water to open oceans. We present a seamlessly connected inland surface hydrological model with a modular ocean circulation modelling system, available into the AquaINFRA VRE in compliance with FAIR principles. It is provided on the web-based Galaxy platform https://aqua.usegalaxy.eu/ to facilitate the integration with the European Open Science Cloud (EOSC) system.
The developed solution allows to execute the modelling workflow in a pre-prepared specific region with a chain of three components:
- Surface inland model: it allows different scenario simulations at daily or monthly responses through parameterised SWAT+ executions with a previous watershed delineation.
- Inland-marine connector: transform the output in hydrological response units in the neighbouring of the mouth in the sea of the catchment area to needed inputs for the marine model.
- Ocean circulation model: it takes as input for the rivers and computes with the MITgcm modelling code the coastal ocean dynamics.
This workflow is initially developed for a Mediterranean use case but is designed to be reproducible and scalable to other European and global regions. The first study area tested is the Tordera catchment and its neighbouring coastal zone, located on the central Catalan coast in the NW Mediterranean. The Tordera basin features a diverse landscape, including croplands, shrublands, forests, urban areas, and industrial zones. Associated human activities, together with the high variability of climatic events, directly affect the quantity and quality of water in both inland and marine ecosystems. Therefore, integrated information through the water continuum is key for its management.
The proposed system aims to 1) reduce the technical complexity of hydrological and marine model executions, 2) show an innovative connection tool between fresh and ocean water environments, and 3) display clear and useful information of the results. The AquaINFRA project will make this system accessible to a broader research community beyond SWAT and MITgcm experts. Thus, scientists, decision-makers and other stakeholders will be able to simulate and assess different future scenarios and better understand past extreme events with an improved representation of land–sea interactions.
Acknowledgments
The AquaINFRA project received funding from the European Commission’s Horizon Europe Research and Innovation programme under grant agreement No 101094434
How to cite: Pesquer, L., Batlle, A., Galiana, S., Garcia, X., Otsu, K., Flo, E., Prat, E., Berdalet, E., and Ballabrera, J.: A web-based integrated Hydrosphere modeling system for scientists and decision-makers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5184, https://doi.org/10.5194/egusphere-egu26-5184, 2026.
A groundwater model of the Tarn-et-Garonne department in southern France was updated and recalibrated using an ensemble-based approach to support short- to medium-term groundwater level forecasting. The model uses the MARTHE finite-difference groundwater modeling software (developed by the BRGM) to simulate groundwater flow, stream-aquifer interactions and groundwater and surface water withdrawals in a Quaternary alluvial aquifer system. The model was originally developed to support local groundwater management and define allowable groundwater abstraction volumes. It was later coupled with the SURFEX land surface model (developed by the CNRM) and integrated into Aqui-FR, a French hydrometeorological modeling platform that provides groundwater level forecasts at a national scale. The model was last calibrated using data through 2015 and a trial-and-error approach. The update incorporated ten additional years of groundwater level, stream flow and pumping data, along with the latest recharge and surface runoff estimates generated by the SURFEX model. History matching then was performed using an iterative ensemble smoother to generate an ensemble of posterior parameter realizations that honor both expert knowledge and observed groundwater levels and stream flows. Using the posterior parameter ensemble, the uncertainty in various predictions of interest, including groundwater levels and standardized piezometric level indices, was evaluated at multiple locations across the study area. All analyses were implemented using a fully scripted workflow to facilitate future model updates and deployment of the workflow in other areas.
How to cite: Coulon, C., Le Cointe, P., Amraoui, N., and Audigane, P.: Update of a regional groundwater model using an ensemble-based approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20395, https://doi.org/10.5194/egusphere-egu26-20395, 2026.
The planning and management of multiple dams within a river basin are critically important for the effective use of water resources and energy generation. Under the growing pressures of climate change, Türkiye, classified as a water-stressed region, faces significant challenges in balancing water availability with population growth, environmental sustainability, and energy demands. The sustainable operation of multiple dams is a vital step toward ensuring the efficient utilisation of water resources for the country's future, while addressing environmental considerations and climate resilience.
The Euphrates-Tigris Basin spans a semi-arid area of 762,000 km², covering six countries: Türkiye, Iran, Iraq, Jordan, Syria, and Saudi Arabia. The two major rivers in the basin, the Tigris and Euphrates, originate from the mountains in eastern Türkiye. These rivers are primarily fed by snowmelt stored during the winter, while during the dry summer months, they rely heavily on groundwater, making the region particularly vulnerable to climate change. Approximately 60 million people depend on these rivers for irrigation, energy production, and other water-related needs. This study focuses on the portion of the Euphrates-Tigris Basin located within Türkiye, covering an area of 18,500 km² (Esit et al., 2023; Rateb et al., 2021).
Türkiye has built 19 hydropower plants and 22 dams in this region over recent decades to store water for irrigation, energy generation, and flood control (SAPRDA, 2009). However, the basin faces increasing challenges due to climate change, including reduced precipitation, rising temperatures, and greater variability in seasonal water availability. These changes exacerbate flood risks during extreme rainfall events while also intensifying drought conditions in dry seasons. The stored water in dams is essential for hydropower production, contributing to Türkiye’s renewable energy targets, yet evaporation losses and reduced inflows pose threats to long-term sustainability. Addressing these interconnected issues is critical for maintaining water security, energy production, and ecosystem stability in the region.
Currently, dams in Türkiye are operated individually, often without coordination or consideration for downstream interdependencies, population growth, or the effects of a changing climate. Using the Euphrates- Tigris basin as a case study, this study seeks to explore the impacts of multiple dam operations in water management. The research will analyse the implications of uncoordinated dam operations on water allocation, seasonal water availability, and hydropower production. Furthermore, it will assess the potential benefits of integrated dam management strategies for improving water resource efficiency. By identifying key challenges and opportunities, this study aims to contribute to the sustainable management of the Euphrates-Tigris Basin in the face of evolving climatic and socio-economic pressures.
How to cite: Sarışen, D. and Yılmaz, D.: Managing Water Resources in the Euphrates -Tigris Basin: Impacts of Multipurpose Dam Operations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4546, https://doi.org/10.5194/egusphere-egu26-4546, 2026.
With the increasing impacts of climate change in recent decades, numerous studies have reported a rising frequency of extreme rainfall events worldwide, accompanied by intensified droughts and floods. Consequently, traditional hydrological analyses require further consideration of climate change effects.This study analyzes more than 125-year record of daily rainfall observations (1900–2025) from the Taipei and Tainan meteorological stations in Taiwan. The dataset is divided into a historical period (1900–1990) and a recent period (1991–2025) to investigate long-term variations in extreme rainfall and drought characteristics. Three hydrological indicators are examined: (1) changes in return periods of extreme rainfall, (2) trends in the number of non-rainy days, and (3) months of extreme precipitation occurrence.In the return period analysis, the Annual Maximum Series (AMS) method combined with the Weibull plotting position formula was applied. The results reveal a decreasing trend in return periods at both the Taipei and Tainan stations, indicating an increased frequency of extreme rainfall events.In terms of drought characteristics, long-term variations in non-rainy days were examined based on the concept of an accelerated hydrological cycles. The results show that the number of non-rainy days has increased at a rate of approximately 0.3 days per year in both northern and southern Taiwan. Furthermore, the average annual number of non-rainy days in the recent period increased by approximately 23 days compared to the historical period, reflecting climate characteristics associated with reduced light rainfall and intensified drought–flood extremes.Regarding seasonal variability, the probability distribution of extreme precipitation occurrence by month was analyzed. The Taipei station exhibits an expansion of the flood season, with extreme precipitation events primarily occurring in June and October, forming a bimodal distribution. In contrast, the Tainan station shows a pronounced concentration of extreme precipitation during the wet season, with approximately 43.8% of events occurring in August.Based on these findings, it is recommended that flood control design standards be upgraded to account for shortened return periods of extreme rainfall. In addition, water resource allocation and management strategies should be strengthened to mitigate the increasing risk of water shortages associated with the rise in non-rainy days. Flood warning systems and construction planning should also be dynamically adjusted in response to shifts in the occurrence months of extreme precipitation.
How to cite: Yang, C.-L. and Lin, Y.-C.: Investigating Trends in Regional Hydrological Characteristics Under Climate Change Using Long-term Rainfall Observation Data: A Case Study of Taipei and Tainan, Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6106, https://doi.org/10.5194/egusphere-egu26-6106, 2026.
Abstract: Under the increasing pressure of water scarcity, irrigation decision-making plays a critical role in achieving efficient agricultural water use while maintaining stable and increased crop yields. With the continuous advancement of crop water information sensing technologies, irrigation decisions based on multi-source farmland information monitoring have become an important development direction for precision irrigation. Targeting salinized farmland in arid regions with shallow groundwater tables, this study proposes an irrigation decision-making method based on in situ measured farmland evapotranspiration, which effectively avoids the adverse effects of soil salinity on the measurement accuracy of soil moisture sensors and enables precise irrigation regulation under saline conditions. Based on two consecutive years of comparative irrigation decision experiments conducted on tomato and maize, the results indicate that, compared with conventional soil-moisture-based irrigation decision methods, the proposed approach can reduce irrigation water use by 7.69%–14.29% while increasing crop yield by 19.6%–24.2%, leading to a significant improvement in crop water productivity. Furthermore, under the same decision-making framework, the use of plastic mulching combined with a moderate reduction in irrigation level (irrigation adjustment coefficient reduced from 0.9 to 0.7) further saved approximately 3.6%–9.8% of irrigation water and enhanced water productivity by 4.6%–33.5%. These results confirm the feasibility and advantages of the proposed irrigation decision method for salinized farmland and provide reliable theoretical support and empirical evidence for irrigation management and the development of smart irrigation technologies in arid salinized agricultural regions, with practical significance for advancing precision agriculture.
Keywords: irrigation decision-making; evapotranspiration
How to cite: Bingbing, J. and Zailin, H.: Research on Irrigation Decision-making Method for Salinized Farmland Based on Actual Farmland Water Consumption Monitoring , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9361, https://doi.org/10.5194/egusphere-egu26-9361, 2026.
Climate change has intensified drought conditions, and various approaches have been developed to ensure stable water supply using reservoirs. In South Korea, many agricultural reservoirs are monitored only in terms of storage (water level), while inflow data are not available. This limitation poses a challenge for developing drought response strategies, highlighting the need for methods to estimate reservoir inflow under data-scarce conditions.
In this study, we propose a methodology for estimating inflow scenarios for agricultural reservoirs using a physically based hydrological model constrained by observed storage (water level) data. As a case study, the Donghwa Reservoir, an agricultural reservoir located in the Seomjin River basin, was selected, and the Dynamic Water Resources Assessment Tool (DWAT) was applied. DWAT is a physically based hydrological model that represents surface water and groundwater processes and is widely used for water resources planning and management.
In the model setup, a prescribed time series of agricultural water withdrawals from May to September was applied, and catchment parameters were adjusted using observed reservoir storage data. The comparison between observed and simulated storage indicates that the model reasonably reproduces the overall variability and statistical characteristics of reservoir storage. However, there are limitations in directly representing artificial operational elements considered in actual reservoir management, such as flood control storage and water intake restrictions. Consequently, larger deviations between observed and simulated storage occurred during periods of extreme drought and flood between 2017 and 2020.
The proposed approach demonstrates the feasibility of estimating inflow scenarios for reservoirs without inflow measurements using a physically based hydrological model and provides a methodological basis for future drought analysis and the development of operational strategies for agricultural reservoirs.
Keyword: DWAT(Dynamic Water resources Assessment Tool), drought, agricultural reservoir, inflow estimation, storage-based calibration
Acknowledgement: This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Aquatic Ecosystem Conservation Research Program, funded by Korea Ministry of Climate, Energy and Environment(MCEE) (RS-2025-02304832).
How to cite: Lee, S., Jang, C., Kim, D., Jang, W., Jeon, M.-G., and Kim, H.: Application of DWAT for inflow estimation in a data-scarce agricultural reservoir, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15137, https://doi.org/10.5194/egusphere-egu26-15137, 2026.
In September 2025, Obong Reservoir(supplying ~87% of the city’s domestic water) in Gangneung-si, South Korea experienced a severe drawdown that triggered citywide rationing. Reported effective storage fell to about 11% on 12 Sep 2025, with the water level near 99.5 m, only 7 m above the implied dead-water line. This case study applies the Dynamic Water Resources Assessment Tool (DWAT) to (i) reproduce the observed 09/2025 drawdown, (ii) diagnose dominant drivers of the low-water crisis, and (iii) quantify the rainfall threshold required for short-term recovery. DWAT is a hydrological modeling framework designed for water-resources assessment across diverse regions worldwide. It allowing detailed characterization of both short- and long-term hydrologic behavior. DWAT represents key processes such as surface runoff, groundwater flow, and human water use (e.g., irrigation and municipal withdrawals), supporting integrated evaluation of water availability and its movement through a watershed.
For reservoir operation, simulations incorporated spillway/outlet/intake characteristics, the stage–area–storage relationship, and time-varying withdrawal data reflecting operational conditions. The simulation period spanned from January 2023 to September 2025, including a one-year warm-up period and the major drought period affecting Gangneung. Results confirm that DWAT accurately reproduces the progressive water-level decline over multiple seasons, the sharp drawdown in late summer 2025, and the transition into the near dead-storage zone in both timing and magnitude. Water-balance diagnostics indicate that the Obong watershed is strongly storage-dependent (surface runoff is less than 3.4%), such that prolonged drought markedly reduces event-driven inflow, depletion of soil moisture and groundwater weakens baseflow support, and continued pumping accelerates reservoir water-level decline. Recovery experiments using the calibrated model show that reservoir stage can return to the normal operating range and that restoration of soil moisture and groundwater storage requires at least ~200 mm of rainfall.
Overall, the DWAT-based drought simulation demonstrates that DWAT is well suited for integrated drought assessment and reservoir operation analysis, providing a practical tool for diagnosing low-water crises and for identifying actionable recovery thresholds that can support emergency response planning and adaptive water-supply management under increasing hydroclimatic variability.
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Water Management Program for Drought Project, funded by Korea Ministry of Climate, Energy and Environment(MCEE).(2022003610002)
How to cite: Jang, W., Kim, H., Jang, C., Lee, S., Jeon, M.-G., and Kim, D.: Quantifying Drought Impacts on Reservoir Operations with DWAT: The Obong Reservoir Water Crisis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15611, https://doi.org/10.5194/egusphere-egu26-15611, 2026.
Soil moisture is widely used to describe catchment wetness conditions and to support drought-related hydrological interpretation. However, runoff responses under apparently similar soil moisture conditions can differ substantially across catchments and events, suggesting that soil moisture alone may not fully capture the processes controlling runoff generation. This study aims to diagnose the hydrological mechanisms associated with contrasting runoff responses under comparable soil moisture states using the process-based DWAT model. The analysis will use daily catchment-scale DWAT outputs including soil moisture, precipitation, total runoff, baseflow (groundwater flow), recharge, infiltration, and actual evapotranspiration for multiple catchments with contrasting hydrological characteristics. To enable consistent comparison across time, daily soil moisture will be transformed into percentile-based indicators to classify relative soil moisture states without directly implying absolute drought impacts. Runoff response will be quantified using event-based runoff ratios derived from simulated precipitation and discharge, and associated process indicators will be evaluated to interpret differences in runoff behavior. By separating soil moisture state from runoff response and leveraging internal model process variables, this work provides a structured framework to investigate why hydrological responses may diverge under similar dry conditions. The proposed approach is expected to support process understanding relevant for drought analysis and catchment-scale hydrological modeling.
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Aquatic Ecosystem Conservation Research Program, funded by Korea Ministry of Climate, Energy and Environment(MCEE). (RS-2025-02304832)
How to cite: Jeon, M.-G., Kim, H., Jang, C., Kim, D., Jang, W., and Lee, S.: Diagnosing contrasting runoff responses under similar soil moisture conditions using the DWAT model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15934, https://doi.org/10.5194/egusphere-egu26-15934, 2026.
In paddy fields, both rainfall and irrigation water from reservoirs contribute interactively to the hydrological cycle. Quantitative decomposition of return flow based on its source is essential for efficient management of agricultural water. In this study, we employed the Dynamic Water Resources Assessment Tool (DWAT), a physically based semi-distributed model, to simulate major hydrological components in paddy fields including surface runoff, interflow, baseflow, infiltration, evapotranspiration, and water storage and separated them into rainfall and irrigation origin contributions.
The proposed component-wise decomposition framework enables spatio-temporal analysis of each hydrological process and uniquely allows monthly tracking of water storage by origin across soil and groundwater layers, providing a novel approach not explored in previous studies.
This framework can offer diagnostic insight into irrigation efficiency. For example, rapid conversion of irrigation water to surface runoff may indicate hydrological inefficiency, while effective utilization of rainfall implies potential for optimized supply operations. Such source-based decomposition provides a qualitative understanding of irrigation performance that cannot be inferred from return flow ratios alone.
This study can contribute to optimizing the operation of agricultural reservoirs and improving irrigation allocation policies, ultimately enhancing the sustainability of agricultural water use and supporting adaptive water resource management under increasing uncertainties driven by climate change.
This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Aquatic Ecosystem Conservation Research Program, funded by Korea Ministry of Climate, Energy and Environment(MCEE). (RS-2025-02304832)
How to cite: Kim, D., Jang, W., Jeon, M.-G., Lee, S., Jang, C., and Kim, H.: Component-wise Decomposition of Return Flow in Paddy Fields Based on DWAT Simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15973, https://doi.org/10.5194/egusphere-egu26-15973, 2026.
According to the standard CSN 75 1400 "Hydrological data of surface waters", M-day discharges are among the basic hydrological data. The Czech Hydrometeorological Institute is responsible for deriving and providing these basic hydrological data.
The objective of the research was to derive basic hydrological data of low flows for description of the hydrological regime, to propose new methodological procedures for deriving basic hydrological data, which include the long-term average discharge Qa and M-day discharges. These data are, among other things, the basis for decision-making of water authorities. Updated information of the hydrological regime will serve to improve planning in the water sector and will contribute to maintain and improve water management as a key commodity for preserving and increasing the quality of life.
The paper presents methodical approaches used to derive basic hydrological data of low flows in the network of water gauging stations in the Czech Republic. Statistical processing used a five-parameter log-normal distribution (LN5), which is essential for accurate representation of extreme values in hydrology. Furthermore, the paper shows the input data that went into the derivation and presents the resulting database of basic hydrological data for unobserved catchments.
How to cite: Kukla, P. and Kourková, H.: Derivation of basic hydrological data (M-day discharges) for the reference period 1991–2020 in the Czech Republic, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16389, https://doi.org/10.5194/egusphere-egu26-16389, 2026.
Lake water quality monitoring in India faces a critical paradox—one where sub-daily or daily data needs are only met with sparse, annually available information. The largest publicly available water quality dataset in India is hosted by the Central Pollution Control Board (CPCB), which only provides annual maxima and minima for a few monitored quality parameters, providing no details on their intra-annual variability. To bridge this critical data gap, this analysis attempts to build a Satellite-based Monitoring approach, demonstrated for two India lakes- Lake Nainital, a source water body in Uttarakhand (0.438 km2 area) and Lake Sukhna, a wastewater receiving water body in Chandigarh (1.38 km2 area). Using Sentinel-2 imagery from 2016-2023, we reconstructed water quality values for 11 parameters of interest, including optically active (chlorophyll-a, turbidity, TSS, etc.) and optically inactive (electrical conductivity, fecal bacteria, BOD, etc.), derived on 3 separate grid sizes: 10m*10m, 20m*20m and 30m*30m. For Lake Nainital, lake quality was analysed for a 100m buffer zone around the water intake point and the following analyses were performed
(i) Seasonal Random Forest models were trained with CPCB ground-truth data, achieving promising predictive accuracy. In that, for Lake Nainital, winter served as the optimal period for nutritional monitoring with R2 values exceeding 0.9, whereas temperature prediction was most accurate in the monsoon (R2=0.93). Fecal coliform demonstrated remarkable accuracy in summer (R2=0.90), in stark contrast to its diminished performance during the monsoon (R2=0.80). Sukhna exhibited contrasting seasonal dependencies: temperatures peaked in summer (R2=0.81), while electrical conductivity spiked in winter (R2=0.90). Also, BOD prediction enhanced significantly from summer (R2=0.66) to winter (R2=0.91).
(ii) Using Modified Robust Principal Component Analysis (MRPCA) Lake Naintial successfully diagnosed a single-factor dominance to multi-stressor complexity, e.g., during the COVID-19 pandemic in 2020 anthropogenic pressures temporarily eased then resurged with altered patterns. Further, the chronic nutrient impairment of Lake Sukhna was also diagnosed using this approach.
The advantages of the proposed satellite-based lake monitoring approach are significant- allowing water treatment plant operators to seasonally forecast coagulant demand fluctuations. This novel satellite-to-tap approach demonstrates an alternative future for water quality monitoring-one which need not rely on extensive grab sampling or sensor-based data as inputs. It also allows regulatory monitoring of chronically impaired lakes of the country and monitoring the upkeep of restored and rejuvenated lakes.
How to cite: Suchetana, B. and Nag, S.: Development of a Satellite-based Monitoring Approach for Augmenting Open-source Indian Lake Water Quality Datasets with Seasonal Information, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17803, https://doi.org/10.5194/egusphere-egu26-17803, 2026.
This study analyzes the hydrological conditions of the downstream of Kapulukaya Dam on the Kızılırmak River, comparing the pre-construction natural period (1970–1989) with the post-operation-controlled period (1989–2013). Using the Flow Health Software, the nine different hydrological sub-indicators, such as High Flow, Low Flow, and Seasonal Flow Shift were employed to determine the ecological and functional integrity of the river on a scale of 0 to 1. The results show a moderate deviation from natural processes; the most significant changes were observed in the Flood Flow Interval (FFI) and Seasonal Flow Shift (SFS) indices, indicating the suppression of natural flood cycles. Even during periods of extreme drought between 2006 and 2008, the Kapulukaya Dam has a high Persistently Very Low (PVL) rating of 0.95, preventing the complete drying up of the riverbed. However, the facility failed to reach its design energy production target of 190 GWh annually due to climatic pressures and upstream water conditioning. Furthermore, factors such as increase in drinking water demand in Kırıkkale and the lack of a central irrigation union negatively affected operational efficiency. The results obtained demonstrate that the dam achieved its flood control objective but experienced increased seasonal pressures on the river flow. In conclusion, the study highlights the need for an efficient water management strategy in the Kızılırmak Basin, encompassing climate change and water demand scenarios to achieve long-term sustainability.
How to cite: Yıldırım, A. E. and Sarışen, D.: Impacts of the Kapulukaya Dam on the Hydrological Health of the Kızılırmak River, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5116, https://doi.org/10.5194/egusphere-egu26-5116, 2026.
