An Urban Waterlogging Dynamic Vulnerability Assessment Framework Integrating Hydrological-hydrodynamic Model, Multi-agent Modeling, and the Choquet Integral - Weichao Yang; Maomao Li; Xuefeng Jiang; De Hu; Haoyang Liang; Xuelian Jiang; Xiangdong Liu (Water Resources Management, 2026)

Development of Novel Simplified Empirical Equations for the Estimation of Peak Discharge due to Dam Failures - Rasim Temür; Yasin Paşa; Sezar Gülbaz; İsmail Bilal Peker; Abdülbaki Hacı (Water Resources Management, 2026)
This study presents a novel methodology for estimating the peak discharge resulting from the failure of earth-fill dams through the development of simplified empirical equations. The proposed method integrates parametric sensitivity analysis, numerical simulations, and meta-heuristic optimization techniques. The historical failure of the Teton Dam in Idaho, USA, was selected as a reference study area due to the availability of reliable spatial and hydraulic data, and the developed models are therefore mainly applicable to piping-type failures in earth-fill dams. Five critical parameters were initially considered in the dam breach analysis: bottom breach width ( BBW ), breach side slope ( SS ), breach development time ( BDT ), volume of water above breach invert ( V w ), and water height at piping initiation ( H w ). A total of 2000 dam failure scenarios were simulated using the Hydrologic Engineering Center's – River Analysis System (HEC-RAS), and the results were analyzed to derive empirical models. Correlation analysis revealed that while BBW and BDT have strong correlation with Peak Breach Flow ( Q p ) and clear directional influence, SS had a minor direct effect. In contrast, H w and V w exhibited complex and nonlinear behavior due to their interdependence with BDT . Although they physically affect Q p , their influence is non-monotonic and scenario-dependent. For empirical equation development approach, their contribution was found to be minimal compared to BBW and BDT . As a result, simplified empirical equations were developed using the most influential parameters. Multiple empirical equation structures were investigated: (i) single-parameter models, (ii) two- and three-parameter models, and (iii) a novel table-driven model where the coefficients adapt dynamically based on discrete values of the third parameter. Among these, the table-driven empirical equations performed the best, with a maximum absolute percent error ranging from 20.3% to 25.1%, significantly improving the accuracy compared to fixed-coefficient models. Coefficients of the empirical models were optimized using the Teaching–Learning-Based Optimization (TLBO) algorithm, which proved effective in calibrating the nonlinear relationships between breach parameters and peak flow. The proposed empirical equation family, named Simplified Empirical Equation for Dam failure (SEED), provides a rapid and flexible estimation framework that can support early warning systems, dam breach risk assessment, and emergency action planning. The study demonstrates that well-designed empirical equations, when supported by robust simulation and optimization techniques, can offer reliable approximations for complex dam breach hydraulics, especially in data-scarce or time-critical scenarios.

Integrating Revised Intensity-Duration-Frequency Curves with Coupled 1D-2D MIKE+ Modelling for Urban Flood Hazard Assessment Under CMIP6 Projections - Aman Kumar; Renji Remesan (Water Resources Management, 2026)

Subsurface Irrigation in Regional Water Management: a System Dynamics Approach to Support Decision Making - Janine A. de Wit; Jos C. van Dam; Tom H.H. Heijmans; Marjolein H.J. van Huijgevoort; Coen J. Ritsema; Ruud P. Bartholomeus (Water Resources Management, 2026)
Controlled drainage with subirrigation (CDSI) using surface water contributes to freshwater availability by recharging, retaining and discharging water. However, CDSI systems affect regional hydrological fluxes, which requires adequate regional planning and management. This study aims to (i) investigate to what extent regional upscaling of CDSI can be supported in relation to surface water availability, using a system dynamics model (SDM) and (ii) identify how an SDM can support decision making of water management authorities. An SDM was developed to simulate changes in hydrological fluxes and water levels resulting from CDSI upscaling from the local to the regional scale. An SDM was used as it is able to capture key non-linear feedbacks within the water system, such as those between (i) surface water and groundwater, (ii) groundwater and unsaturated zone, (iii) regional water supply and weir management. The model provides insight into changes in hydrological fluxes due to CDSI upscaling, without long computational times and the complexities of spatially distributed models. Simulations show non-linear propagation of hydrological fluxes, where three phases can be identified for different degrees of upscaling: (i) sufficient surface water availability, (ii) surface water availability decreases due to subirrigation, and (iii) insufficient water availability due to overexploitation. These phases are related to regional and local water management strategies controlled by water management authorities and farmers, and to geohydrological characteristics. In conclusion, the SDM can support early-stage strategic planning on the feasibility of CDSI upscaling and facilitate discussions between stakeholders by efficiently visualizing and quantifying associated hydrological effects.

Estimating Financial Flood Damages in Residential and Commercial Regions: A Global Depth-Damage Approach - Sakineh Koohi; Asghar Azizian; Mohammad Saeid Najafi; Chiara Arrighi (Water Resources Management, 2026)

Chaos Theory-Based Downscaling for Future Rainfall Projections from Climate Models - B. Deepthi; Bellie Sivakumar (Water Resources Management, 2026)

Evaluating the Impact of Climate and Land-Use Change on Flood Susceptibility on a Global Scale - Fatemeh Rezaie; Saeid Janizadeh; Sayed M. Bateni; Changhyun Jun; Dongkyun Kim; Zahra Kalantari; Essam Heggy (Water Resources Management, 2026)

The Transboundary Precipitationshed of a Non-Transboundary Watershed: Emerging Challenges for Water Resources Management - José A. Posada-Marín; A.M. Rendón; F. Jaramillo; J.F. Salazar (Water Resources Management, 2026)
Terrestrial moisture recycling (TMR) plays a crucial role in the global distribution of water. This process establishes atmospheric connections between watersheds, which are often overlooked in traditional water management that focuses solely on surface hydrology. Located in northwestern South America, the Magdalena Watershed is a non-transboundary watershed that is essential for Colombia’s water and energy security. However, its water availability depends heavily on evapotranspiration from other watersheds and countries. Using a moisture-tracking simulation, we show that this non-transboundary watershed becomes transboundary when analysed through its precipitationshed. We estimate that around 30% of the watershed’s annual precipitation results from Regional Moisture Recycling (RMR), which is moisture originating in terrestrial areas outside the watershed, primarily the Orinoco and Amazon watersheds that span neighbouring countries. A key difference between watersheds and precipitationsheds lies in their physical nature. While watersheds are generally static, precipitationsheds are inherently dynamic. We illustrate this dynamic nature for the Magdalena’s precipitationshed, showing both its seasonal variability and its sensitivity to the El Niño–Southern Oscillation (ENSO). These transboundary and dynamic atmospheric connections challenge the conventional approach to water management that is based solely on static watershed boundaries.

Hierarchical Framework for Reservoir Co-management: A Cross-scale Reservoir Dispatch Paradigm Balancing Energy and Morphogenic Flow Needs - Hong Zeng; Tian-Yao Zhang; Yi-Ming Liao; Guang-Wen Ma; Ji-Dong Li; Wei-Bin Huang; Yan-Mei Zhu; Shi-Jun Chen (Water Resources Management, 2026)

Optimal Hedging Rules Determination for Dam Reservoir Operation Under Climate Change - Pegah Hoseingholi; Ramtin Moeini; Mehry Akbary (Water Resources Management, 2026)

Explainable Artificial Intelligence in Hydrology: A Review - Mohammad Zounemat-Kermani; Marwan Kheimi (Water Resources Management, 2026)

An Integrated VMD-CNN-GRU Framework for Multi-Horizon Forecasting of Water Quality Dynamics - Mojtaba Sabagh Torkan; Abbas Hekmatiyan; Mohammad Hashemzadeh; Amin Karbasi Ahvazi; Farshad Hesamfar; Mohammad G. Zamani (Water Resources Management, 2026)

Enhancing Streamflow Prediction Using Cutting-edge Deep Learning Models and Seasonal-Trend Decomposition - Yubo Jia; Xiaoling Su; Haijiang Wu; Hanwen Yan; Xingyu Zhu (Water Resources Management, 2026)

Simulating Streamflow Scenarios Using Hydrological Modeling Integrated with Future Land Use and CMIP6 Climate Projections - Preetam Choudhary; C P Devatha; Adani Azhoni (Water Resources Management, 2026)

A New Method for Calculating the Volume Capture Ratio of Annual Rainfall (VCRAR) of the Sponge City - Xingpo Liu; Yiwen Hu; Yingyi Zhang; Yiyi Liu (Water Resources Management, 2026)

Comparative Performance Evaluation of Machine Learning Models for Predicting Water Yields in Desiccant-Driven Water Harvesting System - Mehrdad Ghiyasvand; Elshan Soltani; Mohammad Reza Salimi (Water Resources Management, 2026)

Mapping Urban Water Stress and Human-Water Conflicts: a Climate–Ecosystem Framework for Sustainable Water Management - Fatima Zahra Kherazi; Dongying Sun; Jan Muhammad Sohu; Charafa El Rhadiouini; Sonia Najam Shaikh (Water Resources Management, 2026)

Sustainable Water Management for Agriculture to Mitigate Climate Change Effects - Khamis N. Sayl; Nese Yaman; Isam M. Abdulhameed; Hana H. Khalaf (Water Resources Management, 2026)
Water scarcity, intensified by climate change and anthropogenic accomplishment, poses a critical task to worldwide sustainability. Iraq is one of the countries that has experienced severe water shortages due to the impacts of climate change and lack of water resources management. The most significant impacts of climate change are the availability and contamination of water resources. The main goal of this study is to develop a methodology to mitigate the effects of drought by utilizing saline water from the Main Outfall Drain (MOD) with the integrated WATSUIT model and Geographic Information System (GIS). After assessing the physical and chemical properties (pH, TDS, EC, Na, Mg, and Ca) at five monitoring stations (Baghdad, Hilla, Diwaniyah, Nasiriyah, and Basra) that have been selected along the MOD irrigation according to Iraqi and global criteria, the study determined that the water quality is unsuitable for drinking but adequate for irrigating salt-tolerant crops. The accumulated salinity at a steady state was estimated using the WATSUIT model. The results indicated that Basra’s water could not be used even at the highest washing requirements, while other sites were deemed acceptable with washing needs of (0.1) In comparison with salinity levels, the water in Al-Basra was found to be unusable even at maximum washing needs of 0.4. However, a significant improvement in the salinity levels was observed in Al-Diwaniyah at an LF of (0.2) Nevertheless, salinity levels in Al-Nasiriyah remain high, even at LF values between 0.2 and 0.4. Additionally, the total dissolved salts mostly exceed 2000 ppm, indicating the potential for growing salt-tolerant plants. The study concludes that using rainwater harvesting for soil washing, along with the saline water from the MOD, can help mitigate the impacts of climate change, remove salts from soils, and support the irrigation of salt-resistant crops.

Comparative Analysis of Global DEMs for Dam-Break Flood Modeling and Inundation Mapping - Sérgio Ricardo Toledo Salgado; Elsa Maria da Silva Carvalho; Maria Teresa Viseu; Othon Fialho de Oliveira (Water Resources Management, 2026)
The accuracy of flood hazard mapping in dam-break modeling depends strongly on the quality of the Digital Elevation Model (DEM). This study evaluates six open-access global DEMs (SRTM, ALOS PALSAR, AW3D30, COPERNICUS, FABDEM, and ANADEM) in dam-break simulations for two Brazilian dams (Negreiros and Copiti), using HEC-RAS 2D and high-resolution LiDAR as reference. Four aspects were analyzed: (1) elevation accuracy; (2) flood wave propagation, including peak discharge and time-to-peak; (3) inundation extent, with over- and underestimation indices; and (4) hydrodynamic risk. Results show that AW3D30 consistently produced flood propagation, extent, and risk estimates that are closest to those from LiDAR. In contrast, SRTM and PALSAR systematically underestimated inundation areas, whereas FABDEM and ANADEM tended to overestimate, resulting in conservative risk scenarios. COPERNICUS and FABDEM achieved the highest altimetric accuracy but only moderate hydraulic performance. Across case studies, dam size, geomorphology, and distance downstream significantly affected DEM reliability, with mismatches becoming more pronounced the further downstream. The findings highlight the influence of DEM choice on flood modeling and guide dam-break risk assessment in semi-arid and data-scarce regions, where high-resolution DEMs are often unavailable.

Machine Learning as a Tool to Predict Reference Evapotranspiration - Safa Alkanjo; Kübra Kaya; Veysi Kartal; Veysel Süleyman Yavuz; Michael Nones (Water Resources Management, 2026)
Reference evapotranspiration (ET) is essential for agricultural planning and water management, especially in semi-arid areas like Türkiye’s Siirt province. This study predicted monthly ET using machine learning methods (SVM, XgBoost, KNN, RF) and statistical regression models (Quartile, PLS, LASSO, Ridge, Elastic Net, NonParametric, Linear), as well as a Design of Experiments (DoE) approach. Models used climate variables such as temperature, humidity, wind speed, precipitation, sunshine hours, snow thickness, pressure, cloudiness, and solar radiation. RF was the best-performing machine learning model (R²=0.948), while XgBoost was the lowest (R²=0.776). Among regression methods, NonParametric regression performed best (R²=0.948), and PLS performed weakest (R²=0.901). The DoE model showed the highest accuracy overall (R²=0.987), identifying average temperature as the key variable affecting ET. The findings improve prediction accuracy and offer new insights for hydrological understanding and practical applications in water management, agriculture, and climate adaptation in Siirt.

Hydrological Challenges and Competing Demands in the Mediterranean Region - José Arnáez; Estela Nadal-Romero; Noemí Lana-Renault; José M. García-Ruiz (Water Resources Management, 2026)
The Mediterranean region is facing severe hydrological challenges. Rising temperatures, remarkable fluctuations in precipitation, more frequent and intense droughts, and widespread revegetation in the headwaters due to farmland abandonment explain the observed decreases in river discharge across the region. Particularly, farmland abandonment in mountain areas favors woody encroachment, increasing water consumption by vegetation and rainfall interception. In contrast to the reduction of surface water resources, lowland areas are experiencing a growing water demand, primarily driven by increasing consumption in irrigated agriculture (which accounts for over 80% of total water use), tourism resorts, and urban and industrial areas. This contradictory trend between water resources generation and water demand is responsible for increasingly marked tensions, driving many regions toward environmental and social collapse. This includes inland and coastal wetlands (such as deltas and marshes), which are now under threat of extinction or face severe conflicts between wildlife, vegetation, and agricultural demands. In this review, we examine the conflicts between runoff generation in the highlands and water consumption in the lowlands of the Mediterranean region in order to improve land and water management and to ensure the survival of key ecosystems. The development of socio-hydrological scenarios and adaptive governance strategies will be critical for anticipating future conflicts and designing sustainable pathways for the management of scarce water resources.

Developing a Comprehensive and Spatially Explicit GIS–Fuzzy TOPSIS Framework for Drought Vulnerability Assessment - Vijendra Kumar; Akash Nandkumar Mohite; Saleh Alsulamy (Water Resources Management, 2026)

Towards Water Sensitivity: A Critical Review of Urban Water Management Strategies - Indra Mani Tripathi; Sunil Kumar; Ankit Modi; Aamer Majid Bhat; Chandrasekhar Bhagat; Pranab Kumar Mohapatra; Mitthan Lal Kansal (Water Resources Management, 2026)

Incorporating Ecoregions and Freeze–Thaw Effects Effectively Improves the Accuracy of Machine Learning Models for Baseflow Prediction in Seasonally Frozen Regions - Tingting Deng; Hang Lyu; Rong Zhong; Yunting Zou; Jianan Wang; Yu Li; Yue Guo (Water Resources Management, 2026)

Improving Daily Streamflow Predictions over Large Watersheds: Introducing a Novel Enhanced Long Short-Term Memory (En-LSTM) Model - Purshottam Sharma; Vaibhav Tripathi; Mohit Prakash Mohanty (Water Resources Management, 2026)

Quantitative Estimation of the Effects of Parameter Classification and Optimization Methods on Flood Simulations - Ji Li; Jiao Liu; Zhiqiang Xia; Chenrun Liu; Yuechen Li (Water Resources Management, 2026)

A Percentile-Based Dynamic Threshold Run Theory (pDTRT) for Characterizing Agricultural Drought Using ESACCI Soil Moisture - Hussain Palagiri; Manali Pal (Water Resources Management, 2026)

Modelling Nature-Based Solutions in HEC-RAS - Ramtin Sabeti; Thomas Rodding Kjeldsen; Matt Chambers; Hamed Moftakhari; Luis Partida; Ioanna Stamataki; Solomon Simmonds; Rebecca Lee; Barry Hankin; Melissa Hoskings; Katherine Dixon; James Molloy; et al. (Water Resources Management, 2026)
Nature-based solutions (NBS) are becoming increasingly popular for mitigating flood risk while providing multiple benefits such as enhanced biodiversity, and improved water quality. Hydraulic modelling is an essential tool for evaluating and optimising the flood risk regulating service of NBS. Yet, there is no standardised approach to represent NBS interventions in hydraulic models, leading to inconsistent implementations. This study reports a systematic review of 1,080 publications from Scopus and Web of Science. A final selection of 30 key-studies is identified utilising HEC-RAS to model NBS interventions. By collating and synthesising the various approaches documented in these studies, a consolidated resource for researchers and practitioners is provided. This synthesis offers practical recommendations for the application of different NBS interventions in hydraulic modelling and outlines the corresponding parameter ranges to consider. A critical assessment is undertaken on how these interventions map to specific parameters in the governing hydraulic equations, elucidating the physical mechanisms of flow attenuation and water storage that are broadly applicable to all hydraulic models. To demonstrate the real-world utility of these recommendations, a case study of the River Chew catchment (England) is presented, detailing pre- and post-intervention configurations wherein multiple candidate areas are converted to wetland and woodland using a HEC-RAS 2D model; this section is available in the Supplementary Material. Graphical Abstract

Quantifying Predictability and Information Transfer in Rainfall-Runoff Process - Chongli Di; Shailesh Kumar Singh; Jianzhi Dong; Jianzhu Li; Jun He (Water Resources Management, 2026)

Multi-objective Joint Optimization Operation of Cascade Reservoirs Considering River Hydrological Health Assessment - Chongxun Mo; Zihan Lin; Na Li; Xiaoyu Wan; Gang Tang; Yi Huang (Water Resources Management, 2026)

PRRRGN: A Deep Learning Framework for Bias-corrected Satellite Precipitation Estimation in Complex Terrains - G. Kalyan Kumar; P. Sankar (Water Resources Management, 2026)

Optimal Short-Time Rainfall Time Series for Adapting Rainwater Harvesting System to Climate Change in Urban Runoff Management - Weilun Chen; Zhonghui Liu; Wei Ou; Pengxuan Wang; Xindong Wei; Weijun Gao (Water Resources Management, 2026)

Multialgorithm Fusion Strategy Via Efficient Nondominated Sorting for Optimal Daily Operation of a Multireservoir System - Peisi Yang; Xia Zhang; Tao Feng; Jianyun Zhang; Xingcheng Yan; Ruxiao Qiao; Qiuwen Chen (Water Resources Management, 2026)

A Systematic Literature Review on Machine Learning Techniques for Predicting Household Water Consumption - Diego Canquil; Daniel San Martín; Irene Inoquio-Renteria; Paul Leger (Water Resources Management, 2026)

Urbanization and Water Resource Green Efficiency: Coupling Coordination, Dynamic Interactions, and Driving Forces - Linjie Feng; Yi Shi; Zhenjie Yang; Huangxin Chen; Xieqihua Liu; Junhao Chen (Water Resources Management, 2026)

Development of a Two-Stage LSTM for Multi-Step Runoff Forecasting Using a XAJ Model and EEMD - Zihao Yang; Qianjin Dong; Xu Zhang; Hongyu Zhu; Zhetao Cheng (Water Resources Management, 2026)

Integrating Standardized Climate Indicators Using Triple and Scaled Triple Collocation to Develop an Agricultural Productivity Stress Index - Muhammad Asim Khan; Jianyi Lin; Mohammed M. A. Almazah; Ijaz Hussain; Hanen Louati; Mhassen. E. E. Dalam (Water Resources Management, 2026)

Enhancing Hydrologic Model Performance in a Data-Scarce Basin Using Satellite-Based Soil Moisture Data - Praveen Kalura; Ashish Pandey; Deen Dayal; V. M. Chowdary (Water Resources Management, 2026)

Water Bankruptcy: The Formal Definition - Kaveh Madani (Water Resources Management, 2026)

Assessment of Socio-Economic Damages Consequent To Dam Break Using A Data-Driven Approach - Unni Balakrishnan; Santosh G. Thampi; Aditya Harikumar (Water Resources Management, 2026)

Quantifying Carbon Ecological Compensation Standards for Water-Receiving Areas in Interbasin Transfers - Zhuoyue Peng; Yaming Liu; Mengting Li; Hongyuan Fang; Junxian Yin (Water Resources Management, 2026)

Fine-Tunning Deep Neural Networks for Performance Optimization in Desiccant-Assisted Atmospheric Water Harvesting - Mehrdad Ghiyasvand; Elshan Soltani (Water Resources Management, 2026)

Traceable Risk Evolution Forecasting for Irrigation Districts Driven by Enhanced Spatiotemporal Attention (ESTAM) - Xinjuan Sun; Yongchao Zhu; Hairui Li (Water Resources Management, 2026)

A Novel Evidential Uncertainty Framework for Hybrid Models in Rainfall Simulation - Hamid Ebrahimi (Water Resources Management, 2026)

Assessing Spatiotemporal Variability in Soil Moisture under a Changing Climate Using Hydrological Models in Hilly Landscapes - Muhammad Waseem Rasheed; Junfang Cui; Jialiang Tang; Abid Sarwar; Mostafa Moradzadeh; Muhammad Faheem (Water Resources Management, 2026)

Meteorological to Hydrological Drought Propagation: the Role of Catchment Properties in Contrasting Climatic Regions - Tesfalem Abraham; Yan Liu; Zaher Mundher Yaseen; Andreas Hartmann (Water Resources Management, 2026)

Streamflow Forecasting Using a Hybrid Modelling Coupled with Different Components - Haibo Chu; Yulin Jiang; Wei Zhang; Jiahua Wei (Water Resources Management, 2026)

A Hybrid Multi-Strategy Monthly Runoff Forecasting Model Based on Parallel CNN-GRU Architecture, SSA Optimization, and Error Correction Mechanisms - Liyuan Wang; Xuebin Wang; Jianxia Chang; Xuejiao Meng; Yimin Wang; Chengqing Ren; Junhao Zhang (Water Resources Management, 2026)

Hybrid Ensemble and Quantum Machine Learning Framework for River Water Quality Prediction and Classification - Amine Zeguendry; Zahi Jarir; Mohamed Quafafou (Water Resources Management, 2026)

Rapid Urban Flood Simulation and Prediction Using Integrated Hydrodynamic Modeling and Deep Learning Approaches - Houlin Chen; Jiahu Wang (Water Resources Management, 2026)

Deep Learning Based In-Silico Water Level Prediction and IoT Based Monitoring System - Faruque Aziz; Rudraneel Bhattacharya; Arijit De; Sukanta Ghosh; Debashish Pal; Subhajit Das (Water Resources Management, 2026)

Pareto-Based Multi-Objective Calibration of a Hydrological Model Integrating Streamflow and Snow Cover Area - Jose-David Hidalgo-Hidalgo; David Pulido-Velazquez; Antonio-Juan Collados-Lara; A. Arda Şorman; A. Şensoy (Water Resources Management, 2026)
Accurate hydrological modeling in high-mountainous snow-dominated basins is essential for effective water resource management, particularly in climate change-sensitive regions. To better understand the processes that govern hydrological responses, model calibration against multiple variables offers a valuable approach for reducing parameter uncertainty and model equifinality. In data-scarce environments, simple lumped-parameter hydrological models that account for snow accumulation and melting processes are particularly useful. In this study, we used the Témez lumped hydrological model enhanced by the integration of a new semi-distributed snow module to simulate key snow-related processes. We performed a novel sensitivity analysis of the efficiency of the models depending on the adopted multi-objective functions within an automatic procedure to calibrate and validate the models. We evaluated three calibration approaches by varying the weight of the snow cover objective $$\:{w}_{S}$$ . The first procedure consisted of a single-objective calibration against streamflow alone. The other procedures applied multi-objective calibration against streamflow and snow cover, which differed in the performance metric used for the snow component: Nash-Sutcliffe efficiency and Kling-Gupta efficiency. The results demonstrated that incorporating snow cover data into the calibration process improved snow cover simulation without significantly compromising streamflow efficiency, except when the streamflow weight $$\:{w}_{Q}$$ was reduced to zero. Notably, the KGE-based approach yielded a better-defined Pareto front with a more robust snow cover efficiency and reduced bias. Our findings also revealed that snow-related parameters were highly sensitive to the inclusion of snow cover data. Key parameters exhibited substantial changes, with a reduction in variability of approximately 30%.

Estimation of the Hydrological Regime Variability Risk of a Regulated River - Chenguang Xiang; Wei Huang; Cuixia Yao; Le Luo; Rong Zhang; Jing Wang; Pan Yang (Water Resources Management, 2026)

A Study on Dam Site Suitability Using AHP, Fuzzy Overlay and Machine Learning Techniques - Harishankar Manoharan; Sanat Nalini Sahoo (Water Resources Management, 2026)

SSPP: a Novel Flood Probabilistic Forecasting Model Based on Synergistic Seq2Seq Framework and Peak-Enhanced Loss Function - Chang Chen; Dawei Zhang; Fan Wang; Xin Qi; Kang Zheng; Liyun Xiang (Water Resources Management, 2026)

Probabilistic Risk Assessment of Meteorological and Hydrological Droughts with Copula Functions: A Multivariate Framework - Tolga Barış Terzi; Osman Üçüncü (Water Resources Management, 2026)
Drought is a complex and gradually developing natural hazard with profound impacts on water resources, agriculture, and ecosystems. Its multifaceted nature, coupled with increasing frequency and severity under climate change, requires robust monitoring and risk assessment tools. Traditional univariate indices, such as the Standardized Precipitation Index (SPI), provide essential information on drought occurrence and intensity but cannot capture the interactions among hydroclimatic variables. Multivariate indices, including the Multivariate Standardized Drought Index (MSDI), address this limitation by integrating multiple variables, yet probabilistic characterization of drought characteristics remains limited. This study presents a sequential, copula-based framework to assess drought behavior in the Çoruh River Basin. First, univariate drought indices, Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSFI), are calculated to quantify individual drought characteristics. Then, a copula-based MSDI is developed to integrate meteorological and hydrological drought, capturing compound drought events and their interdependencies. Finally, the dependence between drought duration and severity is modeled using copula functions to estimate joint return periods based on drought characteristics derived from both univariate indices and the MSDI. Results demonstrate that the integrated approach more accurately represents the interdependencies of drought events than univariate methods alone, improving estimates of recurrence and joint risk. The study highlights the potential of combining univariate indices, multivariate indices, and copula-based analysis to advance understanding of compound drought risks, supporting early warning systems, water resources planning, and climate adaptation strategies in regions vulnerable to prolonged hydroclimatic extremes.

Asymmetric Feature Reconstruction and Improved Transformer for Multi-step River Streamflow Prediction - Yinghao Zhang; Zhanying Li; Yu Gao; Wenhao Fu; Mingyu Wang (Water Resources Management, 2026)

C-Vine Copulas Function and Conditional Quantile Regression Coupling Model for Agricultural Drought Prediction Analysis - Chengguo Wu; Chengjie Ren; Juliang Jin; Yuliang Zhou; Boyu Nie; Xia Bai; Yi Cui; Fang Tong; Libing Zhang (Water Resources Management, 2026)

Assessment and Prediction of Jacking Effects On Coastal Cities Under Compound Flooding: A Physics-based Modeling Approach - Kui Xu; Naxin Wen; Yunchao Zhuang; Lingling Bin (Water Resources Management, 2026)

Watershed Health Dividend of Floodwater Spreading: Quantifying Benefits Through Counterfactual Scenarios - Seyed Hamidreza Sadeghi; Fariba Esmaeili; Elham Azizi; Reza Chamani; Masoumeh Havasi; Fatemeh Kateb; Mojtaba Pakparvar; Hamed Beigi; Negin Behnia (Water Resources Management, 2026)

Coupling SWAT and Interpretable Deep Learning to Improve Streamflow Simulation in Arid Regions - Qingyang Zhang; Junhu Wu; Tianle Wang; Chenzhan Tang; Weibin Liu (Water Resources Management, 2026)

Event Mean Concentration-based Modelling Approach for a Large Scale Spatially Heterogenous Catchment using SWMM - Manish Ratna Bhusal; Shobha Muthukumaran (Water Resources Management, 2026)
This study evaluated the suitability of Storm Water Management Model (SWMM) for continuous rainfall-runoff modelling and investigated the Event Mean Concentration (EMC) approach in quantifying total nitrogen (TN) and total phosphorus (TP) wash off to the Maribyrnong river in Australia. The model demonstrated satisfactory performance for stream flow simulation during calibration (R 2 = 0.551, NSE = 0.522, KGE = 0.724, PBIAS = 3.96%) and validation (R 2 = 0.6695, NSE = 0.603, KGE = 0.503, PBIAS = 19.03%). For water quality, only TN concentrations in streamflow were satisfactorily validated (R 2 > 0.30 and PBIAS < ± 70%). Further, correlation analysis revealed the intricate role of land use in nutrient dynamics, highlighting the multi factor interdependency on runoff volume, wash off concentration and land use characteristics. Results suggest that SWMM can be effectively used for large scale, spatially heterogenous catchments, provided careful parametrization and calibration are undertaken. While correlation analysis supports the validity of EMC transferability, validation of TN concentration show less sensitivity to temporal pattern, highlighting the need for development of dynamic EMCs.

Performance Drop Appraisal of a Dual-Fracture Underground Barrier for Mitigating Coastal Aquifer Salinization - Asaad M. Armanuos; Ahmed Shalby; Sobhy R. Emara (Water Resources Management, 2026)
Saltwater intrusion (SI) increasingly jeopardizes coastal aquifers, causing soil and groundwater salinization. Subsurface dams are commonly installed at the aquifer base to counteract SI. They have proven to be highly effective mitigation measures, albeit costly. However, such concrete dams often imply inherent construction defects in addition to cracks that are highly likely due to chemical interaction with dissolved ions. An appraisal of the efficiency of fractured subsurface dams is therefore essential for a comprehensive impact assessment and the planning of proposed countermeasures. Accordingly, the SEAWAT code was applied to simulate the abilities of variant configurations of dam heights and locations with different aperture dimensions to control SI. Application in the Henry problem and the Biscayne Aquifer, USA, permitted a consistent appraisal for benchmark and field-scale groundwater systems. Alteration in invasion length at the aquifer base was the key parameter for assessing the performance drop attributed to fractures. The loss of effectiveness was higher in short, defective dams, which permit the flow of dense saltwater through fractures. Similarly, the closer a dam was located to the shoreline, the higher the loss of efficiency observed. The loss of dual-fractured dam efficiency ranged from 4.70 to 75.96%, and the loss is highly sensitive to the dam location, fracture length, and lower fracture height, while fracture aperture indicated moderate sensitivity, and the upper fracture height indicated a lower sensitivity. Considering the study findings is imperative for the robust management of coastal aquifers. Exploring advanced materials and construction techniques to enhance the durability and reliability of subsurface dams is recommended.

Global Attribution of Anthropogenic Climate Change to Terrestrial Long-Term Droughts - Milad Nouri; Mostafa Khorsandi (Water Resources Management, 2026)

Interpreting Irrigation Decisions: Explainable AI Using SHAP and LIME in Agricultural Water Management Models - Shah Mehmood Wagan; Sidra Sidra (Water Resources Management, 2026)

Simulation Method of Urban Flood Process Based on Dynamic Correction of Stormwater Inlet Capacity - Jiahao Lv; Jingming Hou; Donglai Li; Tian Wang; Yanhong Wang; Guangzhao Chen; Zheng Dang; Xiang Man (Water Resources Management, 2026)

A New Tailored Analytical Method for Estimating Breach Parameters and Peak Discharge in Earthen Ponds - Mónica Delgado; Francisco-Javier Sánchez-Romero; Modesto Pérez-Sánchez; Helena M. Ramos (Water Resources Management, 2026)

Hydrological and Hydraulic Analysis of Hydropower Plants Reservoirs Under the Influence of Climate Change with a Sequential Machine Learning Model - Josias da Silva Cruz; Leonardo Melo de Mendonça; Nelio Moura de Figueiredo; Claudio Blanco; Antonio Cesar Pinho Brasil Junior (Water Resources Management, 2026)

A Novel Approach for the SCS-CN Method by Updating Curve Numbers for the Antecedent Soil Moisture Conditions (ASMCs) and Improving its Performance - Ajith A.V.; Dillip Kumar Barik (Water Resources Management, 2026)

Improved Comprehensive Flood Risk Index Method and Multi-Scenario Flood Simulation for Downstream Area of the Reservoir - Nijuan Yang; Ting Zhang; Jianzhu Li; Ping Feng (Water Resources Management, 2026)

Enhancing Flood Prediction in Mountainous Watersheds across Diverse Climates Using Spatiotemporal Variable Source-Mixed Runoff Model - Xuantao Zhao; Aidi Huo; Changjun Liu; Xia Jia; Lei Wen; Qi Liu (Water Resources Management, 2026)

Assessment of Remote Sensing Precipitation Products for Hydrological Analysis in an Ungauged Watershed - Dibyandu Roy; J. Indu (Water Resources Management, 2026)

Streamflow Forecasting Based on PatchTST, LSTM, and Ensemble Learning Approaches - Hajar Feizi; Mohammad Taghi Sattari (Water Resources Management, 2026)

Applying Interpretable Machine Learning for Hypoxia Mitigation: an Operational Framework Coupling Predictive Modeling and Causal Inference for Urban River Management - Jia-yun Chen; Da-wei Wang; Zu-lin Hua; Ke-jian Chu; Li Gu (Water Resources Management, 2026)

Decomposition of Water Demand Patterns Using Skewed Gaussian Distributions for Behavioral Insights and Operational Planning - Roy Elkayam (Water Resources Management, 2026)

From Fragmented Systems to Transparent Governance: Blockchain-Enabled Water Management with IoT Integration - Andreas Sendros; Periklis Kostamis; Ioannis Zikos; Anastasios Manos; Despina Elisabeth Filippidou; George Drosatos; Pavlos Efraimidis (Water Resources Management, 2026)

An Adaptive Agent-Based Framework for Simulating Farmers’ Behavior in the Face of Drought: Application of Numerical Weather Predictions - Negin Salimi; Mohammad Ferdosian; Najmeh Mahjouri (Water Resources Management, 2026)

Quantifying Individual Contribution of Human Activities on Long-Term Streamflow Change in a Large Climate-Sensitive River Basin - Xiaoya Wang; Fengping Li; Guangxin Zhang; Y. Jun Xu; Yanfeng Wu; Fan Liu; Hongze Wang (Water Resources Management, 2026)

Assessment of the Sustainability of Water Resources Based on Regional Water Quality Parameter Inversion and Water Quality Class Assessment to Support SDG 6.3 and 6.4 - Yuxun Zhang; Wenpeng Lin; Yaojen Tu; Yukun Lin; Jiaxin Gao; Qinping Yu; Yunchun Ye; Yiwen Shi (Water Resources Management, 2026)

A Horizon-Adaptive Benchmarking Framework for Long-Term Reservoir Storage Forecasting Using Physics-Informed Transformers and Machine Learning - Ekinhan Eriskin; Özlem Terzi; Emine Dilek Taylan (Water Resources Management, 2026)

A Novel Algorithm for Optimizing Structure of In-Situ Supplementary Irrigation Device for Afforestation in Dryland - Bokun Jia; Sen Zhai; Lin Zhang; Lijie Liu; Yong Yang; Xufei Liu; Shoujun Wu; Xin Hui (Water Resources Management, 2026)

A Comparative Study of Urban Pluvial Flood Susceptibility Assessment Based on Multi-Machine Learning Algorithm - Yaqi Li; Zhengjie Fang; Jun Liu; Zhengsheng Lu; Hong Zhou; Wenhao Yin; Xiaolan Chen (Water Resources Management, 2026)

A Novel Index for Integrative Drought Assessment in Agricultural Reservoirs - Rahmon Abiodun Salau; Bashir Adelodun; Mirza Junaid Ahmad; Qudus Adeyi; Adisa Hammed Akinsoji; Golden Odey; Kyung Sook Choi (Water Resources Management, 2026)

Anthropogenic Interventions in Diverse Watersheds: Insights for Sustainable Water Resource Management - Maithili Mohanty; Vinod Tare (Water Resources Management, 2026)

An Efficient Data-Driven Leak Detection Strategy by Enhancing a Convolutional Neural Network Approach Using a Gaussian Process Regressor - Elvio Damonti; Giancarlo Bernasconi (Water Resources Management, 2026)

Improving River Flood Mapping with Adaptive Sampling and Artificial Intelligence Techniques for Enhanced Flood Risk Assessment - Kola Yusuff Kareem; Innkyo Choo; Seungoh Lee; Younghun Jung (Water Resources Management, 2026)

Optimizing Irrigation Scheduling with a Hybrid Transformer-GRU Model and Reinforcement Learning in Smart Agriculture - Shriya Sahu; Prerna Verma (Water Resources Management, 2026)

Quantifying the Impact of Rainfall Spatial Heterogeneity and Patterns on Urban Flooding by Integrating Machine Learning Algorithm and Hydrodynamic–Hydrological Modeling - Hongshi Xu; Yongle Guan; Peiyao Li; Wanjie Xue; Yanpo Chen; Xiaoyang Jiao; Jiahao Zhang (Water Resources Management, 2026)

Sustainable Water Management in Arid Regions: Integrating Technological Innovations and Nature-Based Solutions - Vikrant Pachouri; Prafull Kothari; Rajesh Singh; Anita Gehlot; Amit Kumar Thakur (Water Resources Management, 2026)

Ensemble Machine Learning-Based Feature Selection for Flood Susceptibility Mapping Under Climate and Land Use Change Scenarios - Adisa Hammed Akinsoji; Bashir Adelodun; Qudus Adeyi; Rahmon Abiodun Salau; Kyung Sook Choi (Water Resources Management, 2026)

Effectiveness of Machine Learning Methods in Predicting Water Potability: A Comparative Study - Tarik Talan (Water Resources Management, 2026)

An Easy-to-Apply Machine Learning Framework for Hydrologic Evaluation of Ungauged Catchments - Bhaswatee Baishya; Arup Kumar Sarma (Water Resources Management, 2026)

Deep Learning and Remote Sensing for Crop Yield Prediction and Decision Support - Shriya Sahu; Priyank Jain (Water Resources Management, 2026)

Fluvial Flood Inundation Modeling: a Comparative Assessment of 1D and 2D Hydraulic Approach Using MIKE+ - Matej Vojtek; Jana Vojteková (Water Resources Management, 2026)
Fluvial floods are one of the most frequent types of floods worldwide. Fluvial flood inundation modeling focuses on determination of at least flood extent and flows depths in studied domain. In our case, the study area was represented by a short upstream reach of the Gidra River, which is located in western Slovakia. The aim of this study was to compare 1D and 2D hydraulic approaches for fluvial flood modeling of three flood scenarios (Q 1000 , Q 100 , Q 10 ) using the MIKE + model and geographic information systems (GIS). The hydrologic input was represented by the officially determined flood discharges. Hydraulic input data were maintained the same for comparison purposes. Both hydraulic approaches were also compared to 2D benchmark (official) flood hazard maps. To quantify the differences between 1D and 2D flood extents and as respect to the benchmark flood maps, we applied five pixel-to-pixel cross-evaluation metrics. The results showed that 1D hydraulic model did not provide sufficiently reliable and comparable results to 2D hydraulic model as well as to 2D benchmark flood maps. Compared to the flood extent of 2D benchmark flood maps for Q 1000 , Q 100 , and Q 10 , the 1D modeled flood extent was lower by 5.59%, 49.63%, and 56.23%, respectively while in case of the 2D model, it was higher by 22.31% for Q 1000 , lower by 0.71% for Q 100 , and lower by 33.58% for Q 10 . We concluded that 1D model is not suitable for producing fluvial flood inundation maps in similar study areas/geomorphological settings and 2D approach should be used instead for practical purposes.

Multi-Objective Performance Evaluation and Contributing Area Optimization Framework for Urban Green Stormwater Infrastructure - Afiya Narzis; Jessica A. Eisma (Water Resources Management, 2026)

Structure, Development and Effects of Global Water Pricing in the Sustainability Context: A Review - Fengguang Lyu; Hongbo Zhang; Chiheng Dang; Jingru Zhang (Water Resources Management, 2026)

Analyzing Pluvial Flooding Influenced by Urban Road Network Metrics Based on Hydrodynamic Simulation and SHAP Values - Yanfen Geng; Peng Liu; Xiao Huang (Water Resources Management, 2026)

Identifying Hydrological Analogous Year from Magnitude and Temporal Patterns - Shiqi Nie; Ganggang Zuo; Ni Wang; Jiancang Xie (Water Resources Management, 2026)

Exploring the Impact of Optimization Techniques on Streamflow Prediction Using XGBoost: A Comparative Analysis with Satellite and Reanalysis Precipitation Datasets - Nagireddy Masthan Reddy; Roshan Srivastav (Water Resources Management, 2026)

A Novel Approach To Integrate Low Impact Development (LID) Modules into the SWAT Model To Facilitate Sustainable Urban Drainage Planning at River Basin Scales - Sreethu Subrahmanian; Arun Rajasekaran Sankarbalaji; Elanchezhiyan Duraisekaran; S. Murty Bhallamudi; Balaji Narasimhan (Water Resources Management, 2026)

Optimal Sensor Placement for Acoustic Leak Pinpointing in Water Distribution Networks - Pranav Agrawal; Yongjie Zhuang; Rohan Sinha; Sachit Murthy; Sriram Narasimhan (Water Resources Management, 2026)

A Comparative Evaluation of Deep Learning and Machine Learning Models for River Suspended Sediment Concentration Forecasting - Amin Gharehbaghi; Salim Heddam; Saeid Mehdizadeh; Sungwon Kim (Water Resources Management, 2026)

A long-term Areal Flooding Risk Calculation Method Based on the Historical Rainfall Records - Xingpo Liu; Wen Xu; Hongyuan Guo; Minhao Chen (Water Resources Management, 2026)

Model Selection Challenges in Non-Stationary Precipitation Estimation: The Role of AIC, BIC, and Covariate Choice - Murat Yegin; Gulsah Karakaya; Elcin Kentel (Water Resources Management, 2026)

System Dynamics Model for Assessing the Water Dynamics and the Capacity of Large Reservoirs to Supply Multiple Uses - Alisson Lopes Rodrigues; Ricardo Santos Silva Amorim; Pedro Manuel Villa (Water Resources Management, 2026)

Comprehensive Evaluation Approach for Earth-Rock Dam Performance Based on Variable Weight Extension Cloud Model - Hanye Xiong; Zhenzhong Shen; Yongchao Li (Water Resources Management, 2026)

Sustainable Water Governance: Insights from Living Lab Experiences - Anthi-Eirini K. Vozinaki; Ioanna V. Anyfanti; George P. Karatzas; Emmanouil A. Varouchakis; Chiara Ceseracciu; Giampiero Branca; Romina Deriu; Pier Paolo Roggero; Irem Daloglu Cetinkaya; Cem İskender Aydın; Nadim Copty; Seifeddine Jomaa (Water Resources Management, 2026)

From Regional Disputes to Global Solutions: A Fairness-Based Game-Theoretic Model for Sustainable River Water Allocation - Durga Prasad Panday; Vivek Agarwal; Rahul Silori (Water Resources Management, 2026)

Fusion of Multi-Source Evapotranspiration Products Via the Bayesian Three-Cornered Hat Method and its Application in Runoff Simulation for Semi-Arid Basins - Chuqiao Han; Jianghua Zheng; Wanqiang Han; Liang Liu; Congren Li; Wenjie Yu; Juan Yang; Jiale Wu (Water Resources Management, 2026)

A Data-Driven Approach to Dam Infrastructure Monitoring: Enhancing Prediction Accuracy by Systematic Rainfall Event Classification - Ryul Kim; Soon Ho Kwon; Seungyub Lee; Young Hwan Choi (Water Resources Management, 2026)

Capacity Expansion for Urban Drainage Network To Avoid Waterlogging in Cities - Tianze Xu; Xiaoguo Zhang; Baoshun Song; Lunrui Zhang (Water Resources Management, 2026)

A Novel Self-Adaptive, Non-Metaphor-Based FISANET Framework for Pressure Dependent Optimization of Water Distribution Networks - Vishal Jain; Ruchi Khare (Water Resources Management, 2026)

Spatial Optimization of Low-Impact Development Facilities for Sustainable Flood Management in an Industrial Park - Lina Shen; Meihan Lin; Fangyuan Zhang (Water Resources Management, 2026)

Spatial–Temporal Heterogeneity of Ecosystem Service Supply–Demand at the Grid and Watershed Scales - Dongjie Guan; Jiameng Cao; Xiaofeng Fan; Lilei Zhou; Xiujuan He; Xinyu Liu; Xusen Zhu; Kangwen Zhu (Water Resources Management, 2026)

A Multi-Level Data Mining and Blending Framework for Enhanced Accuracy of Satellite-Based Datasets in Hydrological Applications - Mehran Besharatifar; Mohammadnabi Jalali; Keivan Rahsepas (Water Resources Management, 2026)

Quantifying the Urbanization and Vegetation Greening Effect on Spatiotemporal Continuous Drought Risk Via Nonstationary C-Vine Copula Model - Pengcheng Xu; Dong Wang; Yuankun Wang; Vijay P. Singh (Water Resources Management, 2026)

A Holistic Approach to Multi-criteria Decision-Making for Selecting the Sustainable Groundwater Source Protection Management Plan - Dragoljub Bajić; Dragan Pamučar; Milica Stepanović; Dušan Polomčić (Water Resources Management, 2025)

Optimizing Water Allocation and Industry Structure: A Multi-Scenario Comparison by Using Interval Fuzzy Multi-Level Programming Model - Chunxiao Ma; Ruxin Bai; Shifu Wang; Zhiqiang Yan; Haochen Shi (Water Resources Management, 2025)

Ensuring Water Justice and Achieving Sustainable Development Goals in Megacities Through Cooperative Bargaining Solutions - Shahmir Janjua; Kathryn Reardon-Smith; Shahbaz Mushtaq; Duc-Anh An-Vo (Water Resources Management, 2025)
Water scarcity and insecurity remains a critical challenge for the megacities of Global South, disproportionately impacting vulnerable and low-income communities. In Karachi, one of Pakistan’s largest cities, almost 45 percent of domestic water demands are unmet due to governance failures and infrastructural inefficiencies. Our study applies a novel integrated Water Evaluation and Planning (WEAP)-Nash Bargaining Solution (NBS) framework that simulates future water demands and optimizes fair and equitable allocation of water among the seven administrative divisions of the city. Under WEAP, the projected satisfaction ratio with no intervention declined from 60 percent in 2023 to 30 percent in 2040, whereas the integrated strategy improved the demand satisfaction to 100 percent for all seven districts by 2036. Our results also indicate that water allocation under NBS, weighted by the Multidimensional Poverty Index (MPI), would enhance equity at the district level with Karachi East’s allocation increasing from 60 to 96 percent in addition to the allocation improvements for other marginalized areas. These results highlight the importance of embedding socio-economic considerations within technical water allocation models. This would also directly contribute to achieving Sustainable Development Goals (SDGs) 6 and 10, ensuring access to water and reducing inequality, respectively.

Fuzzy Cognitive Mapping of Stakeholders’ Perception of Water Resources Management - Mert Can Gunacti; Cem P. Cetinkaya; Filiz Barbaros; Ali Gul; Gulay Onusluel Gul (Water Resources Management, 2025)

A Methodology for Detecting Existing and Potential Hydrographic Features - Natalia Janczewska; Magdalena Matysik; Damian Absalon; Andrzej Woźnica; Marcin Lipowczan; Łukasz Pieron; Barbara Kalinowska-Wójcik; Wanda Jarosz; Witold Mandrysz; Magdalena Biela; Edyta Sierka (Water Resources Management, 2025)

Fuzzy Membership Based Weighted Modularity Maximization Approach for Sectorization of Water Distribution Network into Dynamic District Metered Areas - Jyotsna Pandey; Vemavarapu V. Srinivas (Water Resources Management, 2025)

Addressing Global Water Challenges in 2025: an Integrated Framework for Research, Policy, and Resource Management - Frank A. Ward (Water Resources Management, 2025)

The Impact of Denoised Data on the Performance of the Hybrid Model (CNN-Qlearning) - Hamid Ebrahimi (Water Resources Management, 2025)

Novel Parameter Calibration Method of WRF-Hydro in Ungauged Areas Combining Satellite-Based Soil Moisture and Multisource Meteorological Data - Qingzhi Zhao; Yatong Li; Hongwu Guo; Zufeng Li; Yibin Yao; Mingxian Hu; Pengfei Geng; Yuan Zhai; Xiaohua Fu; Qiong Wu (Water Resources Management, 2025)

An Evaluation Method of Urban Smart Water Supply System Supported by Fit-For-Purpose Concept and Association Rule - Nan Zhang; Manuel Sebastian Fiallos-Salguero; Yang Liu; Pei Yu; Soon-Thiam Khu; Jia Wang (Water Resources Management, 2025)

Assessment of a Survivability Index for Drought Management in River Basins - Mert Can Gunacti; Cem Polat Cetinkaya (Water Resources Management, 2025)

Preferential Flow in Common Low Impact Development Technologies: A Review - Ruifen Liu; Junqi Zhou; Ting Fong May Chui; Defu Liu; Ying Liu (Water Resources Management, 2025)
Preferential flow, a common phenomenon in natural soils, has received limited attention in low impact development technologies (LIDs), despite its potential impact on stormwater performance. This paper provides a comprehensive review of the effects, detection and modelling of preferential flow in three common LID systems: green roofs, bioretention, and pervious pavements. While preferential flow negatively affects the retention and detention performance of green roofs, it is considered beneficial for mitigating clogging in bioretention systems. Coarse-grained LID media, such as green roof substrates, bioretention media and pavement aggregates, are particularly susceptible to preferential flow, with plant interactions adding complexity to its formation. Several attempts have been made to characterize preferential flow in LID media through detection techniques based on water movement, breakthrough curves, and dye tracing. As an advanced technique, X-ray scanning has also been introduced for the noninvasive identification of preferential flow. The dual-porosity model is a simple and effective tool for accounting for preferential flow in LID; however, determining the required parameters for multilayered systems, such as pervious pavements, remains a significant challenge. Future research should focus on monitoring preferential flow in field-scale LIDs, investigating the factors influencing preferential flow initiation, and optimizing the stormwater performance of LIDs in the presence of preferential flow.

Flood Management with Flood Galleries in a Reservoir Basin - Zuhal Elif Kara Dilek; Mücahit Opan; Efsun Bacaksız (Water Resources Management, 2025)

Long-term Study of Water Resource by Machine Learning: A New Application of Explainable Artificial Intelligence Model Towards Sustainable Development Goals - Mojtaba Poursaeid (Water Resources Management, 2025)

AH-GCAN-LSTM: Adaptive Hybrid-Graph Convolution Attention Network with LSTM and Genetic Optimization for Hydrological time Series Forecasting - Huseyin Cagan Kilinc; Sina Apak; Furkan Ozkan; Adem Yurtsever (Water Resources Management, 2025)

Coupling Hydrus-1d and Epa Swmm to Assess the Multiscale Hydrological Benefits of a Green Infrastructure - Michele Turco; Anna Chiara Brusco; Giuseppe Brunetti; Patrizia Piro (Water Resources Management, 2025)
Urbanization and climate change have intensified the challenges of managing stormwater due to increased impervious surfaces and more frequent extreme weather events. Effective water management strategies are essential to mitigate flood risks, enhance water quality, and improve urban resilience. Green infrastructure (GI) represents a key nature-based solution to address these challenges by integrating natural processes into the built environment. Numerical modelling plays a crucial role in the widespread adoption of GIs at the urban scale. In this study, the hydrological models, HYDRUS-1D and SWMM, are coupled to assess the hydrological performance of GIs in managing urban runoff. The methodology involves characterizing GI components, defining representative hydrological scenarios, and applying stratified models. This integrated approach enables accurate simulation of water flow dynamics within GI systems and their interaction with the urban drainage network. The results of the coupled models highlight the effectiveness of GI in reducing runoff volumes and delaying peak flows, thereby alleviating hydraulic pressure on conventional drainage systems and enhancing urban resilience to extreme weather events. To define the soil hydraulic properties in the HYDRUS model, the evaporation method was used, and the van Genuchten-Mualem model was selected to characterize the Soil Water Retention Curve of the substrate. This model showed a saturated volumetric water content of 0.543 cm³ cm⁻³ and high permeability, ensuring efficient drainage and avoiding ponding. Building-scale modeling demonstrated a 36% reduction in runoff volume, while urban-scale simulations showed decreased surcharge of nodes and conduits, confirming improved stormwater management and flood risk mitigation. By combining the analytical strengths of both models, this study provides a robust tool for evaluating performance under varying environmental conditions. The findings support the broader adoption of nature-based solutions in sustainable urban planning, aligning with global initiatives such as the SDG 11 and SDG 13, which focus on fostering resilient and sustainable cities. This research underscores the importance of integrating advanced modeling tools into the design and management of green infrastructure to effectively address contemporary urban water management challenges.

Effects of Inflow Rate and Channel Bed Slope on Noncohesive Landslide Dams during Overtopping Failure Based on Flume Tests - Danyi Shen; Jiangtao Yang; Zhenming Shi; Jiongchao Wang (Water Resources Management, 2025)

Effects of Multi-Step-Ahead Prediction Strategies on LSTM-Based Runoff Prediction - Jingchao Jiang; Yang Gao; Jiaqi Chen; Jingzhou Huang; Juan Yu; Cong Jiang; Junzhi Liu; Anke Xue (Water Resources Management, 2025)

Comprehensive Hydrologic Modeling for Evaluating Impacts of Future Water Uses and Climate Change on Water Resources Sustainability - Elias Getahun; A. F. Prada; Z. Zhang; L. Keefer; G. Qie (Water Resources Management, 2025)
Climate change and increasing water demand are critical factors influencing water availability and the hydrologic cycle. This study examines their combined impacts on the Kaskaskia River watershed in Illinois, USA, using a comprehensive hydrologic modeling approach. The model integrates key watershed components, including existing reservoirs, multiple water withdrawal sources, and point source discharges, with necessary modifications to the governing algorithms to accurately represent system processes. A daily target release method was implemented for routing water through the watershed’s two main reservoirs, significantly improving the accuracy of storage and outflow simulations. A total of 68 hydrologic scenarios were simulated, combining 17 climate projections with four water demand patterns. Results reveal that climate change exerts a substantial influence on river flows and reservoir storages, while the effects of projected water demand are comparatively minor. Under RCP2.6, RCP4.5, and RCP8.5 scenarios, minimum storage volumes in both reservoirs are projected to decline over the next 25 to 50 years, while maximum storage volumes are expected to increase, indicating greater variability in reservoir levels. Despite these changes, future water yields from both reservoirs are projected to exceed current yields across all scenarios. These findings underscore the importance of adopting sustainable water resource management strategies to address the challenges posed by climate variability and evolving water demands, ensuring long-term water security in the region. Furthermore, as water availability is also constrained by water quality, future enhancements to the model should incorporate water quality simulations to assess the impacts of sediment and nutrient loads on overall water availability.

Spatiotemporal Heterogeneity of Surface Evapotranspiration and its Driving Mechanisms in a Significant Ecological Recovery Area - Suhua Liu; Zhenfeng Zang; Xiangchao Qin; Xudong Huang; Chunying Wang; Hongbo Su; Yuping Han (Water Resources Management, 2025)

Smart Water Quality Monitoring Using a Hybrid Deep Learning Framework with Memory Network and Teaching–Learning-Based Optimization for Accurate LSI Prediction - Milad Sharafi; Javad Behmanesh; Vahid Rezaverdinejad (Water Resources Management, 2025)

Investigating the Dependence Structure of Temperature and Precipitation Concentration with Evapotranspiration in Finland - Rasoul Mirabbasi; Mohammad Nazeri Tahroudi; Alireza Sharifi; Ali Torabi Haghighi (Water Resources Management, 2025)

Baseflow Separation for Improving Dam Inflow Prediction Using Data-Driven Models: A Case Study of Four Dams in South Korea - Heechan Han; Heeseung Park; Donghyun Kim (Water Resources Management, 2025)

Insights into Robustness as a Criterion to Support Cost-Benefit Analysis of Supply-Enhancing Investments under Uncertainty. Part II – Investment Evaluation and Robustness Appraisal - Claudio Arena; Marcella Cannarozzo; Giorgio Gullotti (Water Resources Management, 2025)
After shaping, in the companion paper, an uncertainty environment where to embed investment appraisal, in this paper we intend to demonstrate how robustness criteria can be used to investigate the behaviour of different investment alternatives in this environment, in a cost-benefit analysis framework. The performance indicator is the NPV (Net Present Value) that also accounts for the life-cycle costs of the alternatives. As an example, three supply-enhancing investments to increase water resources availability, in a part of the multi-purpose water supply system of the Southern Apennine River Basin District (Italy), are evaluated. The effect of each of three identified alternatives is assessed through a simulation model of the system, described in the companion paper, that allows the evaluation of the benefits as the difference between scarcity costs with and without the investment in each of the 486 scenarios considered. Robustness is evaluated with reference to various metrics such as maxi-max, maxi-min, regret-related metrics, and satisficing metrics. The application shows that valuable insights can be gained by systematically comparing the alternatives according to the different robustness criteria: for instance, the investment with the seemingly worst NPV in an evaluation framework ignoring uncertainty, due to its high investment and operation costs, proves to be the second-best option when uncertainty surrounding the supply-demand balance is considered, as it turns out to be the best-performing option in a set of critical scenarios that have an overall non-negligible occurrence probability.

Quantifying the Impact of River Levels on Urban Drainage Capacity - Haijia Zhang; Jiahong Liu; Chao Mei; Jia Wang; Tianxu Song (Water Resources Management, 2025)

Efficient Hyperparameter Tuning for Precise Precipitation Prediction Using EHPC Framework - Nivethitha K; Lokeshkumar R (Water Resources Management, 2025)

Assimilating Farmers’ Behaviour in the Development of an ET-Based Irrigation Water-Accounting Model - Ivan Portoghese; Raffaella Matarrese; Laura Mirra; Giacomo Giannoccaro (Water Resources Management, 2025)

A Hybrid Deep Learning Approach for Flood Prediction: Integrating ICENet’s Spatial-Temporal Learning with DRAW Optimizer’s Adaptive Weighting - S. Sathees Babu; J. Jeba Sonia; S. Aarthee; R. Chithambaramani; P. Ganeshkumar (Water Resources Management, 2025)

An Investigation into the Prediction Success of Different Regression-Based Models for Monthly Streamflow Prediction in an Ungauged Watershed - Yahi Takai Eddine; Zeghmar Amer; Marouf Nadir; Abolfazl Jaafari (Water Resources Management, 2025)

Identifying Risk Transition Pattern of Compound Flooding Using the Copula Integrated Markov Chain - Xiaodi Li; Ming Zhong; Xueyou Li; Jiao Wang; Lu Zhuo; Feng Ling; Lixiang Song; Xianwei Wang; Jinhui Li; Xiaohong Chen (Water Resources Management, 2025)

Comparison of Process-Based Hydrological Modeling and Deep Learning Approaches for Streamflow Simulation - Jingyao Wang; Hossein Yousefi; Mojtaba Shourian (Water Resources Management, 2025)

Optimizing a Network of Weather Stations in Arid Regions using a Fuzzy AHP-Based Approach - Forough Mirsadeghi; Saeid Okhravi; Saeed Toghyani; Saeid Eslamian (Water Resources Management, 2025)
Accurate hydrological analyses largely depend on precipitation data from weather stations (WSs). The stations’ density and spatial distribution are essential for ensuring data accuracy. However, in regions with diverse climatic conditions, WS network often fail to meet the World Meteorological Organization (WMO) standards. This study evaluates the WS network in Isfahan Province, an arid to semi-arid region, to develop an optimized system for reliable meteorological data collection. A novel framework is introduced to achieve this goal by integrating statistical analysis with the Fuzzy Analytical Hierarchy Process (Fuzzy AHP). Initially, a correlation equation was fitted to annual precipitation records, and the absolute relative error was distributed using the Kernel Density Function. Next, the Fuzzy AHP algorithm was employed to generate a weighted overlay layer based on seven critical physical and environmental factors: elevation, slope, proximity to existing stations, land use, proximity to roads, distance from streams, and population centers. These two outputs were combined to produce a refined suitability map, identifying 17.9% of the land area as highly or fairly suitable for WS establishment. According to WMO guidelines, an additional 72 WSs are required throughout the province. Results demonstrated that incorporating error-informed weighting from spatial rainfall uncertainty into a GIS-based multi-criteria framework significantly improved the spatial accuracy in data-scarce regions. The scalable framework offers a practical tool for meteorological agencies, planners, and researchers, supporting more resilient networks and accurate hydrological analyses.

How Do decision-tree-based Machine Learning Techniques Compare To Hybrid Approaches for Predicting Fluvial Dike Breach Discharge? - Vincent Schmitz; Renaud Vandeghen; Sébastien Erpicum; Michel Pirotton; Pierre Archambeau; Benjamin Dewals (Water Resources Management, 2025)

Crop Water Footprint Assessment: A Review of Methodological Approaches, Scale Variability, and Data Constraints - Ashish Koradia; Basant Yadav; Ashish Pandey; V. M. Chowdary; K. Chandrasekar (Water Resources Management, 2025)

Dynamic Control of the Flood Limited Water Level in Reservoir Considering the Uncertainty Error Domain of Forecast Information - Qianning Wang; Yong Peng; Min Li; Jinnan Zhang; Yue Sun; Wei Ding; Feilin Zhu (Water Resources Management, 2025)

An IoT Enabled Knowledge Graph Convolutional Radial Basis Deeplabv3+ Model for Flood Disaster Detection - Shashank Shashikant Tolye; Vinayak Ashok Bharadi; Kaushal Kamaleshwar Prasad (Water Resources Management, 2025)

Impact of Different Factors on Changes in Water Resources Availability - Dejan Dimkić; Boris Pokorni; Zoran Simić (Water Resources Management, 2025)

A Novel Multitype Graph Fusion Framework for Short-term Water Demand Forecasting - Chenlei Xie; Jie Wang; Tao Chen; Qiansheng Fang; Xinyin Xu (Water Resources Management, 2025)

Effects of Model Spatial Structure and Basin Characteristics on the Performance of Three Hydrologic Models - F. Sencer Kacar; Kayhan Bayhan; Andreas Gassner; Enes Ergun; Oguzhan Murat Halat; Mustafa Nuri Balov; Mahmud Sami Demirel; Muhammet Bahattin Avcuoglu; Salih Babagiray; Suleyman Selim Calli; Roghayeh Ghasempour; V. S. Ozgur Kirca; et al. (Water Resources Management, 2025)

Developing an Agent-based Water Market Mechanism for Sustainable Groundwater Management in Agricultural Regions - Soroush Sharghi; Pooya Ghorbanpoor Sheikhani; Reza Kerachian (Water Resources Management, 2025)

The Ideal Flow-Based Multi-Model Ensemble Strategy for Projecting Future Runoff with CMIP6 GCMs - Seung Taek Chae; Mohammed Magdy Hamed; Shamsuddin Shahid; Eun-Sung Chung (Water Resources Management, 2025)

A Multi-Agent and GraphRAG-Based Framework for Operation and Management Decision-Making in Hydraulic Projects - Yangrui Yang; Pengfei Wang; Xuemei Liu; Wenyu Luo; Libo Yang (Water Resources Management, 2025)

Impact of Interactions between Different Rainfall Patterns and River Water Levels on Urban Flooding in Inland Plain Cities - Jian Chen; Yaowei Li; Luyao Zhang; Yangyang Tian (Water Resources Management, 2025)

Performance Evaluation of a Substituted Topography-based Model To Forecast Rainfall and tide-induced Lowland Flooding - Pin-Chun Huang (Water Resources Management, 2025)

Rethinking Urban Water Network Design: A Reinforcement Learning Framework for Long-Term Flexible Planning - Lydia Tsiami; Christos Makropoulos; Dragan Savic (Water Resources Management, 2025)
Effectively planning the design of water distribution networks (WDNs) for their whole lifecycle is a complex task for water utilities due to the dynamic nature of WDNs, their long planning horizons, and the deep uncertainty that characterises key design parameters such as future water demand and population growth. Existing flexible design methods, which attempt to address these challenges, rely on static heuristic approaches and predefined decision pathways, requiring re-optimisation whenever new information becomes available. As additional scenarios are introduced, these methods also suffer from exponential increase in complexity, limiting their ability to adapt to emerging information and efficiently explore a wide range of future possibilities. In this work, we introduce a deep reinforcement learning (DRL) framework for the flexible, long-term design of WDNs. By formulating the least-cost staged design problem as a Markov Decision Process and training an agent using Proximal Policy Optimisation, our approach learns cost-effective, sequential interventions across multiple construction stages and future scenarios without relying on predefined decision trees. We evaluate our method on a modified New York Tunnels benchmark across three design tasks, ranging from static single-stage to flexible multi-stage design. Our results show that the DRL agent performs comparably to state-of-the-art heuristics for static and staged deterministic tasks. In the flexible design task, it autonomously devised adaptive strategies, clustered similar scenarios, and maintained high sample efficiency as the number of stages and scenarios increased. These findings highlight DRL as a promising alternative for the lifecycle design of WDNs, establishing a new paradigm for long-term water network planning under deep uncertainty.

A Hybrid Mamba Architecture with Graph Convolution and Convolutional Self-Attention for Multivariate Water Quality Forecasting - Yulong Bai; Xianbao Tan; Xiaoxin Yue (Water Resources Management, 2025)

Applications of Behavioral Simulation Models in Water Resources Management: A Systematic State-of-the-Art Review - Fardin Kamali; Reza Kerachian (Water Resources Management, 2025)

The Role of the Temporal Patterns of Rainfall on the Design and Performance of Rainwater Harvesting Systems: the Italian Case - Matteo Carollo; Ilaria Butera (Water Resources Management, 2025)
Rainwater harvesting (RWH) for indoor use could be a useful practice for a sustainable management of urban water. The impact of the temporal patterns of rainfall on the size of the tank of an RWH system has been analysed in the present work. This analysis was carried out through numerical simulations and was focused on the national Italian territory. Daily rainfall data from 3436 rainfall gauge stations located throughout the Italian territory were considered, and buildings with different catchment areas and numbers of users were considered. The coefficient of variation of the daily rainfall data was used to quantify the temporal variability of the rainfall. Furthermore, analytical expressions have been developed in this work to compute the performance of a rainwater harvesting system (water savings, retention efficiency and overflows) as a function of certain characteristics of the building and of the rainfall regime. The results of the numerical simulations point out the important role of the temporal patterns of rainfall in the design steps of such a system and successfully support the analytical expressions proposed for the performance indicators.

Coordinated Research Among Multiple Stakeholders in Water Diversion Projects Under the Guarantee of Water Quality: Based on the Perspective of Sustainable Supply Chain - Meng Liu; Xiaodan Xi; Hongcheng Gan (Water Resources Management, 2025)

Forecast Scheduling Mode Coupled with Long- and Medium-term Runoff Forecast - Qiang Hui; Jungang Luo; Ganggang Zuo (Water Resources Management, 2025)

Optimizing Flood Susceptibility Detection Using Ensemble Learning Methods - Zihui Dai; Alireza Arabameri; Peyman Yariyan; Hasan Raja Naqvi; Tania Nasrin (Water Resources Management, 2025)

Determination and Application of a New Drought Resistant Control Water Level for Multi-Reservoir Systems Based on a Water Resource Allocation Model - Yaping Cheng; Ziqi Yan; Denghua Yan; Miao Liu; Ruishen Wei (Water Resources Management, 2025)

Correction to: Flood Mitigation and Water Resource Preservation: Hydrodynamic and SWMM Simulations of Nature-Based Solutions Under Climate Change - Maelaynayn El baida; Mimoun Chourak; Farid Boushaba (Water Resources Management, 2025)

Two-stage Adaptive Modelling Framework for Long-term Monthly Operation of a Multi-purpose Reservoir for Regulating Environmental Flows - Ruby Jose; K. Srinivasan (Water Resources Management, 2025)

Bi-level Multi-objective Complex Regional Water Resources Optimal Allocation Model Under Hybrid Uncertainty - Tao Wang; Jingjing Duan; Chenhui Jiang; Zhaohan Zhang; Dangxian Wang; Xing Li; Ziyu Guan; Jing Zhao; Jiaqi Zhai; Jingzhe Liu; Yulong Gao; Peiling Wang (Water Resources Management, 2025)

A Comprehensive Evaluation Framework for the Hydrological Evolution Characteristics of the Yellow River - Wenxian Guo; Xuyang Jiao; Lintong Huang; Baoliang Wang; Hongxiang Wang (Water Resources Management, 2025)

Site Selection and Investment Prioritization for Small Hydropower Plants Using Spatial Multi-Criteria Decision-Making Models - Mohammad Mazlomi Mochani; Ali Moridi; Mojtaba Dadkhah Tehrani; Reza Khalili; Ali Torabi Haghighi (Water Resources Management, 2025)

Strategic Engineering Design in Water Infrastructure: A Game-Theoretic Approach and Network Topology for Flood Irrigation Systems - Mobin Zarreh; Paul T. Grogan (Water Resources Management, 2025)

A Method to Quantify the Negative Impacts of Extreme Floods on the Environment in Monetary Terms - Yadong Zhang; Jianyou Wang; Jingjing Li; Hongyin Xu; Zongkun Li; Hui Qian; Wei Ge (Water Resources Management, 2025)

Assessing Climate Change Impacts on Future Reliability of Water Supply Systems Served by Karst Aquifers - Nunziarita Palazzolo; David J. Peres; Claudio Mineo; Stefania Passaretti; Anna Varriale; Antonino Cancelliere (Water Resources Management, 2025)

Decision Model for Sustainable Urban Drainage Systems: A Technical, Social, and Economic Multicriteria Analysis - Izabel Rodrigues Leite; Sharon Kelly de Melo; Luiz Felipe Finck; Ana Julia Motyczka Finck; Aleska Kaufmann Almeida; Isabel Kaufmann de Almeida (Water Resources Management, 2025)

Assessment of Variability of Rainfall Erosivity Using Different Rainfall Products - R. Akhila; S. K. Pramada (Water Resources Management, 2025)

Impact of Runoff Forecast Errors on the Optimal Operation of Reservoir Power Generation - Chongxun Mo; Yuyi Zhong; Keke Huang; Mengxiang Bao; Yi Huang; Changdi Tao; Huabo Jiang (Water Resources Management, 2025)

A Framework to Evaluate the Performance of Urban Rainwater Harvesting Systems Considering Water and Sanitation Utility Perspectives under Deep Uncertainties - Gabriela Cristina R. Pacheco; Conceição de Maria A. Alves (Water Resources Management, 2025)

Navigating Uncertainties in Quantifying Water Availability Amidst the Climate and Land Use Changes - Nirajan Devkota; Suraj Lamichhane; Pawan Kumar Bhattarai (Water Resources Management, 2025)

Leakage Area Detection in Water Distribution Networks: a Two-Step Algorithm Using Limited Data - Luigi Cimorelli; Andrea D’Aniello; Dina Pirone; Domenico Pianese (Water Resources Management, 2025)

Effect of Attribute Information of Recycled Water on Willingness to Accept: Evidence from an Event-Related Potential (ERP) Experiment - Hanliang Fu; Bo Dong; Zhifang Wu; Caixia Hou; Yanjun Ren (Water Resources Management, 2025)

Fuzzy Logic Inference Modeling (FLIM) of Culvert Design Size and Discharge Calculations - Özay Uslu; Zekâi Şen (Water Resources Management, 2025)
In road construction groundwater especially surface and flows play very important roles, because road paths must cross over narrow or wide drainage basins through culverts, bridges or aqueducts. Under the bridges and aqueducts water problems do not pose very dangerous situations, but culverts as comparatively small-scale engineering structures are subject to most dangerous surface water (runoff) problems and thus need more attention. Culverts under the highways and railways must be designed and constructed in such a way that they pass the upstream runoff without critical problem to downstream area. In the literature there are many reports about the water passage and dimensional design formulations for culvert works that have empirical bases and validity for the region they are planned. In most of the culvert drainage basins, there are no measurements of rainfall and therefore empirical, logical rational approaches are needed. One of such method is the bivalent logic (two-value, crisp) rule-based approach is the Talbot culvert design approach, which does not depend on complex mathematical equations and cannot consider various uncertainties (vague, imprecise, incomplete) effectively. This paper proposes fuzzy logic inference model (FLIM) approach for transformation of Talbot bivalent logic method steps into more meaningful fuzzy logic method. The application of the proposed method is made in a local area where a serious train accident occurred due to a poorly maintained culvert in Tekirdağ province near Istanbul on the European side of Turkey.

Does Non-conventional Water Use Impact the Performance of Irrigation Communities in Water-Scarce Regions? - Mario Ballesteros-Olza; Irene Blanco-Gutiérrez; Almudena Gómez-Ramos; Sarah Stempfle (Water Resources Management, 2025)
Irrigation Communities (ICs) are pivotal to sustainable agricultural water management, especially in water-scarce regions like the Mediterranean. To address increasing water scarcity, many ICs have incorporated Non-Conventional Water (NCW) sources, such as reclaimed and desalinated water, into their strategies. However, their impact on IC performance remains largely unexplored. This study aims to address this knowledge gap by examining the relationship between NCW use and IC performance in 19 communities across the Region of Murcia (southeastern Spain), one of Europe’s driest areas. A benchmarking framework based on eight key performance indicators covering operational, economic-financial, productive, and environmental dimensions was applied. Principal component analysis reduced dimensionality, followed by agglomerative hierarchical cluster analysis to group ICs with similar performance. Finally, multiple regression analysis was applied to identify the main determinants of performance. Results reveal substantial heterogeneity in IC performance. The best-performing ICs excelled in operational and financial indicators but showed low productivity, while the second-best group, comprising the largest and most modernized ICs, achieved high water-use efficiency and productivity despite experiencing water supply variability and applying deficit irrigation. Although NCW improves crop water availability and overall performance, its higher costs (particularly for desalination) negatively impact gross margin. Ensuring the long-term viability of NCW requires advancements in treatment technologies, renewable energy integration, and supportive governance. The study offers valuable insights for ICs and policymakers in other semi-arid regions facing similar water challenges.

Investigating on Trade-offs and Synergies of Ecosystem Services and their Driving Mechanisms Under Different Land Use Scenarios - Xinyang Ma; Zongxue Xu; Depeng Zuo (Water Resources Management, 2025)

Modeling GRACE-Based Groundwater Drought and its Teleconnections with Global Climate Drivers for Water Sustainability in Arid Regions - Javed Mallick; Saeed Alqadhi; Swapan Talukdar; Hoang Thi Hang (Water Resources Management, 2025)

Nonstationary Frequency Analysis of Annual Maximum Flow Series: Climate Change Versus Land Use/Land Cover Change - Murat Yegin; Gulsah Karakaya; Elcin Kentel (Water Resources Management, 2025)
Accurate estimation of flood peak discharges is essential for effective flood risk management. Traditional flood management approaches that assume stationarity may be inadequate due to the dynamic influences of climate change (CC) and land use/land cover (LULC) changes, necessitating nonstationary flood frequency analysis. This study investigates the challenges associated with selecting suitable probability distributions and covariates for nonstationary frequency analysis of annual maximum flow series (AMFS). Six probability distributions (i.e., normal, log-normal, logistic, gamma, Gumbel, and Generalized Extreme Value (GEV)) and seven covariates (i.e., time, reservoir index (RI), annual maximum precipitation, annual average temperature, annual total precipitation, population, and the Normalized Difference Vegetation Index (NDVI)) are evaluated for the Silifke region in Turkey. Based on Akaike Information Criterion (AIC) scores, the GEV distribution performed better than others. However, the 500-year return period flood (Q 500 ) estimated using the best-performing nonstationary GEV model was an outlier, deviating by nearly 19 standard deviations away from the maximum observed discharge. This indicates that reliance solely on AIC scores may result in misleading conclusions. Considering both AIC scores and Q 500 estimates, Gumbel is identified as the best distribution for modeling AMFS in the study area. Results also show that LULC-related covariates more strongly influence nonstationarity than CC-related ones. Among these, RI proves to be the most representative covariate. Notably, NDVI, employed as a covariate in nonstationary frequency analysis for the first time in this study, appears frequently among the most effective models, underscoring its potential relevance in future research.

Developing Resilient Reservoir System Operations: A Simulation Approach Incorporating Rule Curve - Eunkyung Lee; Jungwon Ji; Sooyeon Yi; Seonmi Lee; Jeongin Yoon; Jaeeung Yi (Water Resources Management, 2025)
To manage the growing challenges of water scarcity and variability, especially during prolonged droughts, effective reservoir operation is essential. This study builds on previous research to address the complexities of water allocation under extreme drought conditions. The objectives are to (a) develop a new water supply adjustment standard (Standard) for Hwacheon reservoir for practical application, (b) create a simulation model that integrates this Standard, and (c) establish a reservoir system operation for managing three major reservoirs in the Han River Basin, South Korea. The results demonstrate that the newly developed simulation model effectively minimized water supply reductions for domestic and industrial sectors. The simulation model decreased the water supply reduction by 467.5 MCM for the Hwacheon reservoir and by 1476.0 MCM for the Chungju-Soyanggang reservoirs in the domestic and industrial sectors compared to the historical supply. The number of days spent in the critical emergency stage was reduced across all reservoirs. The emergency stage duration for Hwacheon reservoir dropped from 477 days to 104 days, while the Chungju-Soyanggang reservoirs eliminated emergency stage days, reducing from 86 days to none. Compared to the previously developed optimization model, reservoir storage in June (before the flood season) decreased by 26.6% to allow for greater flood control capacity, while in September (after the flood season), it increased by 5.4% to enhance conservation storage. These findings underscore the potential for enhancing water resource management in diverse regions. The flexible framework developed in this study can be applied globally to similar reservoir systems, enhancing resilience and water management efficiency.

Risk Assessment of Human and Vehicle Stability in Extreme Weather Events in Coastal Cities - Wei Zhu; Xianbao Zha; Pingping Luo; Shuangtao Wang; Chengyi Xv; Yongxing Ji (Water Resources Management, 2025)

Investigation and Evaluation of Hydraulic Parameters of Stepped Spillway Based on ANN Models - Prachi Dharmadhikari; Sumit Gandhi (Water Resources Management, 2025)

Experimental Measurement and Predictive Modelling of Wind-driven Rainwater Collections from Building Facades Towards New Vertical Rainwater Harvesting Systems in Tropical Urban Setting - Mozhgan Samzadeh; Nazli Bin Che Din; Norhayati Mahyuddin; Zunaibi Abdullah (Water Resources Management, 2025)

Adaptive Reservoir Operation Considering Real-time Forecasting: Application of Two-stage Coordinated Control Risk Hedging Principle - Jingzhe Liu; Jiaqi Zhai; Jingjing Duan; Chenhui Jiang; Zhaohan Zhang; Qingming Wang; Jing Zhao; Tao Wang (Water Resources Management, 2025)

Linking Water Technologies with Water Practices: Case Studies from 11 Countries - Lin Gan; Yongping Wei; Shuanglei Wu (Water Resources Management, 2025)
Radical transformations of technology development are required to meet the rapidly increasing global water resource challenges. A systemic understanding of the impacts of water technologies on water practices across countries remains limited. This paper aims to develop an understanding of the linkages between water technologies and water practices in the 11 countries where 95% of the world’s water patents were produced. The water technological development was assessed by both the contents (different types of technologies) and the structure (the technology network). The water practices were presented by country-level indicators representing their water demand, water supply, and water management collected from public databases. It was found that there was an extremely uneven distribution with the top 3 countries (China, Korea, Japan) accounting for over 70% of the total patents, and there were slow growth rates and even a decline of water technologies. All countries demonstrated homogeneous technological development focusing on water supply, and their networks had limited brokerage capacity for knowledge diffusion. Australia, China, Canada, France, and Korea had relatively good links between water technologies and practices, whereas the majority of countries demonstrated unbalanced technological structures with a de-linking to water practices. These findings can assist in developing water technologies for improving water practices in future.

Estimating Potential and Reference Evapotranspiration in the Central European Region: The Challenge of Model Selection - Jitka Toušková; Kristyna Falatkova; Václav Šípek (Water Resources Management, 2025)
An accurate assessment of evapotranspiration (ET) is crucial for determining water balance, particularly in agricultural areas. However, misconceptions surrounding the definition and concept of ET contribute to significant uncertainty in its measurement and estimation. This study focuses on comparing the performance of 25 common models, including mass transfer, radiation-based, temperature-based, and combined methods. The results were compared with observed pan evaporation data from 18 stations across various climatic conditions in the temperate zone of the Czech Republic. The best results were achieved with the combined methods, which performed well in terms of both absolute values and daily patterns. The mean RMSEs between modeled and observed PET/RET were 1.2/18.6/33.3 mm day⁻¹/month⁻¹/season⁻¹, with correlation coefficients of 0.75, 0.94, and 0.75 for daily, monthly, and seasonal analyses, respectively. Individually, the radiation-based Makkink method (J Inst Water Eng 11:277–288, 1957) and the temperature-based approach by Oudin et al. (J Hydrol 303(1-4):290–306, 2005) stood out, both providing reliable results in terms of absolute PET values. The daily course was most accurately simulated by the Penman method (1963) and the WMO method (1966). Overall, model performance indicators such as RMSE and BIAS were more method-specific, whereas the correlation between modeled and observed data varied by station.

Optimal Design of Water Distribution Network Considering the Uncertainty and Correlation of Nodal Demands - Benwei Hou; Baojin Zhou; Shan Wu (Water Resources Management, 2025)

Performance Assessment of LID Techniques to Control Urban Floods Under Historical and Future Rainfall and Land Cover Scenarios - Masoud Borna; Milad Borna; Mehdi Jorabloo (Water Resources Management, 2025)

A CFD-Based Study of Pipe Leakage Dynamics and Water Management Impacts - Magashen Govender; Darlington Chinenye Ikegwuoha; Mohammed Seyam (Water Resources Management, 2025)
This paper investigates pipe leakage using Computational Fluid Dynamics (CFD) simulations to analyse flow behaviour under various conditions, including laminar and turbulent states. Factors such as material, pressure, flow rate, and leak orifice size were examined to understand leakage-induced disruptions, including pressure distribution and velocity profiles. A 3D model was created in AutoCAD 2024 and simulated in Ansys Fluent, with results validated using EPANET and calibrated via Torricelli’s equation. Leak sizes ranging from 10 mm to 200 mm positively correlated with water loss. This study uniquely applies CFD with sensitivity analysis, offering detailed insights for proactive water management.

DEMend: Automating Hydrological Correction of Digital Elevation Models for Enhanced Urban Flood Modeling - Zeeshan Khalid; Andre de Souza de Lima; P. J. Ruess; Arslaan Khalid; Tyler Miesse; Diana Veronez; Celso M. Ferreira; James L. Kinter (Water Resources Management, 2025)
Increasingly frequent and extreme precipitation events are heightening flood hazard exposure, intensifying the need for efficient and reliable flood risk modeling. Such modeling relies critically on accurate Digital Elevation Models (DEMs), yet raw DEMs often contain artificial obstructions—primarily bridges and culverts—that incorrectly disrupt modeled water flow. While high-resolution elevation data from Light Detection and Ranging (LiDAR) helps address some of these challenges, LiDAR cannot resolve elevations beneath bridges and culverts, necessitating further corrections. Traditional manual methods of DEM correction are labor-intensive and impractical at large scales. To address this issue, we introduce DEMend (Digital Elevation Model mender), a streamlined, automated tool designed to efficiently detect and correct hydrological obstructions in DEMs. DEMend leverages widely available stream and road network datasets and employs locally weighted regression techniques to statistically adjust and smooth terrain elevations. Applied to Northern Virginia’s Accotink watershed, DEMend rapidly identified and corrected 119 artificial obstructions, markedly enhancing stream alignment and facilitating efficient flood modeling workflows. Packaged as an ArcGIS toolbox, DEMend significantly reduces manual preprocessing efforts, offering flood modelers a practical and scalable solution to rapidly improve DEM suitability for accurate flood risk assessments.

Integrating DEA and Machine Learning for Sustainable Resource Management in Arid Regions: A Comprehensive Framework for Groundwater Quality Assessment - Ahmed Amin Soltani; Ahmed Ferhati; Amar Oukil; Nour El Houda Belazreg (Water Resources Management, 2025)