Forecasting Future Groundwater Recharge from Rainfall Under Different Climate Change Scenarios Using Comparative Analysis of Deep Learning and Ensemble Learning Techniques - Dolon Banerjee; Sayantan Ganguly; Shashwat Kushwaha (Water Resources Management, 2024)

Enhancing Flood Routing Accuracy: A Fuzzified Approach to Nonlinear Variable-Parameter Muskingum Model - Amirfarhad Aletaha; Masoud-Reza Hessami-Kermani; Reyhaneh Akbari (Water Resources Management, 2024)

Study of Water Resource System Adaptability Based on the Connection Number and Three-Dimensional Risk Matrix - Pan Zhengwei; Cui Yunhui; Zhou Yuliang; Zhou Ping; Wang Jing (Water Resources Management, 2024)

Development of A Distributed Modeling Framework Considering Spatiotemporally Varying Hydrological Processes for Sub-Daily Flood Forecasting in Semi-Humid and Semi-Arid Watersheds - Xiaoyang Li; Lei Ye; Xuezhi Gu; Jinggang Chu; Jin Wang; Chi Zhang; Huicheng Zhou (Water Resources Management, 2024)

Single-Objective and Multi-Objective Flood Interval Forecasting Considering Interval Fitting Coefficients - Xinyu Chang; Jun Guo; Hui Qin; Jingwei Huang; Xinying Wang; Pingan Ren (Water Resources Management, 2024)

Integrated Sustainability Index for Assessing the Performance of Water Distribution Network - Jyotsna Pandey; Vemavarapu V. Srinivas (Water Resources Management, 2024)

Navigating Reservoir Deposition Challenges: Evaluation of Reservoir Desilting Strategy Through a 4-Stage Life Cycle Assessment Approach - Cheng-Chia Huang (Water Resources Management, 2024)

Impact of Climate Change on Regional Water Availability and Demand for Agricultural Production: Application of Water Footprint Concept - T. R. Sreeshna; P. Athira; B. Soundharajan (Water Resources Management, 2024)

Spatiotemporal Assessment Model for Manual Operation Systems' Technical Performance in Surface Water Distribution Under Water Scarcity Scenarios - Dorsa Rahparast; Seied Mehdy Hashemy Shahdany (Water Resources Management, 2024)

Improving Water Efficiencies in Rural Agriculture for Sustainability of Water Resources: A Review - Manish Yadav; B. B. Vashisht; S. K. Jalota; T. Jyolsna; Samar Pal Singh; Arun Kumar; Amit Kumar; Gurjeet Singh (Water Resources Management, 2024)

Assessment of Climate Change-Induced Water Scarcity Risk by Using a Coupled System Dynamics and Bayesian Network Modeling Approaches - Sara Dehghani; Alireza Massah Bavani; Abbas Roozbahani; Oz Sahin (Water Resources Management, 2024)
The water scarcity risk induced by climate change is contributing to a sequence of hydrological and socioeconomic impacts. Certain numbers of related impacts are locked in already and are expected to be much greater in the future. So, there is still a lack of understanding of its dynamics, origin, propagation, and the mutual interaction of its drivers. In recent years, several model-based approaches have been introduced to tackle the complexity, dynamics, and uncertainty of water scarcity specifically. However, the coupled modeling while addressing different aspects of the risk of water scarcity under the climate change scenarios has been rarely done. For bridging this gap, in this research, the combination of complementary System Dynamics modeling and Bayesian Network was applied to Qazvin Plain in Iran with five AOGCM models under two Shared Socioeconomic Pathways (SSP) scenarios (126 and 585). Key findings of this research show: 1) Baseline risk assessment indicates a low probability of water scarcity; however, in the future 30-year time horizon with continuous change in hazard, vulnerability, and exposure for SSP126, the risk fell in the extreme category with an average probability of 41%. Under SSP585, the risk varies between extreme and high categories with an average probability of 47%. 2) Economic development, particularly regional gross domestic product (RGDP) in 2045–2054 in SSP585 can diminish the negative projected consequences of climate change and therefore investments in adaptation policies could offset negative consequences, highlighting the role of economic growth in climate resilience. 3) It is projected that crop yield and income will receive the largest negative effects due to cutting back the agriculture area. 4) Considering the interplay of climate change, economic development, and water extraction policies is essential for the design, operation, and management of water-related activities. The proposed integrated methodology provides a comprehensive framework for understanding climate change-induced water scarcity risks, their drivers, and potential consequences. This approach facilitates adaptive decision-making to address the evolving challenges posed by climate change.

The Potential of Stormwater Management Strategies and Artificial Intelligence Modeling Tools to Improve Water Quality: A Review - Ndivhuwo Ramovha; Martha Chadyiwa; Freeman Ntuli; Thandiwe Sithole (Water Resources Management, 2024)
Stormwater management modeling tools have been utilized to enhance stormwater operating systems, assess modeling system efficiency, and evaluate the impacts of urban growth on stormwater runoff and water quality. This review explores the potential of stormwater management strategies and Artificial Intelligence modeling tools in enhancing water quality. The study focuses on evaluating stormwater modeling tools for planning and improving stormwater systems, assessing modeling efficiency, and understanding the impacts of new development on stormwater runoff and water quality. Various stormwater modeling tools are compared to aid in water management in urban and rural settings, which is crucial due to increasing storm intensity from climate change. The review debates the advantages and limitations of different modeling tools, particularly in modeling stormwater quantity and quality under different scenarios. It also examines tools used for predicting and analysing stormwater runoff during storm events in diverse locations. The assessment of modeling tools is centred on their support for Green Infrastructure (GI) practices, considering factors like modeling accuracy, data availability, and requirements. The study highlights the importance of these tools in managing water in urban areas and safeguarding water sources during stormwater events. Notably, the accuracy and efficacy of stormwater modeling tools are influenced by input data quality, calibration methods, and standardization metrics, with the widely used Stormwater Management Model (SWMM) being a common modeling tool.

Simultaneous Minimization of Water Age and Pressure in Water Distribution Systems by Pressure Reducing Valves - Kristina Korder; Hao Cao; Elad Salomons; Avi Ostfeld; Pu Li (Water Resources Management, 2024)
Pressure reducing valves (PRVs) are essentially used to reduce operational pressures in water distribution systems (WDSs) to minimize water leakage. However, water age in a WDS is an important variable describing the water quality and should be kept as low as possible. Therefore, the aim of this study is to investigate the possibility and potential of simultaneously minimizing both pressure and water age by using PRVs. To determine the optimal location and setting of PRVs, a mixed-integer nonlinear programming (MINLP) problem is formulated with minimization of the sum of the weighted total water age and pressure as the objective function, where the weighting factor can be defined by the user’s preference. The equality constraints consist of the hydraulic equations and water age functions to describe pressure and water age in the distribution network, while the inequality constraints ensure them in the defined operating ranges, respectively. Applying the proposed approach to two case studies, the results show that both water age and pressure can indeed be significantly reduced by the optimized position and setting of the PRVs.

Investigating the Economic Impacts of Inter-Basin Water Transfer Projects with a Water- Embedded Multi - Regional Computable General Equilibrium Approach - Shahrbanoo Bagheri; Mortaza Baky-Haskuee; Saeed Yazdani; Babolla Hayati (Water Resources Management, 2024)

Comparison of Hybrid LSTAR-GARCH Model with Conventional Stochastic and Artificial-Intelligence Models to Estimate Monthly Streamflow - Priyanka Sharma; Farshad Fathian; Deepesh Machiwal; S. R. Bhakar; Survey D. Sharma (Water Resources Management, 2024)

A Flood Season Division Model Considering Uncertainty and New Information Priority - Jun Li (Water Resources Management, 2024)

Use of Artificial Intelligence Modelling for the Dynamic Simulation of Urban Catchment Runoff - Harshanth Balacumaresan; Monzur Alam Imteaz; Md Abdul Aziz; Tanveer Choudhury (Water Resources Management, 2024)
The complex topography and inherent nonlinearity affiliated with influential hydrological processes of urban catchments, coupled with limited availability of measured data, limits the prediction accuracy of conventional models. Artificial Neural Network models (ANNs) have displayed commendable progress in recognising and simulating highly complex, non-linear associations allied with input-output variables, with limited comprehension of the underlying physical processes. Therefore, this paper investigates the effectiveness and accuracy of ANN models, in estimating the urban catchment runoff, employing minimal and commonly available hydrological data variables – rainfall and upstream catchment flow data, employing two powerful supervised-learning-algorithms, Bayesian-Regularization (BR) and Levenberg-Marquardt (LM). Gardiners Creek catchment, encompassed in Melbourne, Australia, with more than thirty years of quality-checked rainfall and streamflow data was chosen as the study location. Two significant storm events that transpired within the last fifteen years - the 4th of February 2011 and the 6th of November 2018, were nominated for calibration and validation of the ANN model. The study results advocate that the use of the LM-ANN model stipulates accurate estimates of the historical storm events, with a stronger correlation and lower generalisation error, in contrast to the BR-ANN model, while the integration of upstream catchment flow alongside rainfall, vindicate for their collective impact upon the dynamics of the flow being spawned at the downstream catchment locations, significantly enhancing the model performance and providing a more cost-effective and near-realistic modelling approach that can be considered for application in studies of urban catchment responses, with limited data availability.

Modeling the Role of Novel Ecosystems in Runoff and Soil Protection: Native and Non-native Subtropical Montane Forests - Yohana G. Jimenez; Ezequiel Aráoz (Water Resources Management, 2024)

Strategic Placement of In-line Turbines for Optimum Power Generation and Leakage Reduction in Water Supply Networks - Priyanshu Jain; Ruchi Khare (Water Resources Management, 2024)

Uncertain Benefits of Using Remotely Sensed Evapotranspiration for Streamflow Estimation—Insights From a Randomized, Large-Sample Experiment - Hong Xuan Do; Hung T.T. Nguyen; Vinh Ngoc Tran; Manh-Hung Le; Binh Quang Nguyen; Hung T. Pham; Tu Hoang Le; Doan Van Binh; Thanh Duc Dang; Hoang Tran; Tam V. Nguyen (Water Resources Management, 2024)
Remotely sensed evapotranspiration (ET RS ) shows promise for enhancing hydrological models, especially in regions lacking in situ streamflow observations. However, model calibration studies showed conflicting results regarding the ability of ET RS products to improve streamflow simulation. Rather than relying on model calibration, here we produce the first randomized experiment that explores the full streamflow–ET skill distribution, and also the first probabilistic assessment of the value of different global ET RS products for streamflow simulation. Using 280,000 randomized SWAT (Soil and Water Assessment Tool) model runs across seven catchments and four ET RS products, we show that the relationship between ET and streamflow skills is complex, and simultaneous improvement in both skills is only possible in a limited range. Parameter sensitivity analysis indicates that the most sensitive parameters can have opposite contributions to ET and streamflow skills, leading to skill trade-offs. Conditional probability assessment reveals that models with good ET skills are likely to produce good streamflow skills, but not vice versa. We suggest that randomized experiments such as ours should be performed before model calibration to determine whether using ET RS is worthwhile, and to help in interpreting the calibration results.

Multifractal Description of the Agricultural and Meteorological Drought Propagation Process - Lailei Gu; Sajad Jamshidi; Mingjun Zhang; Xiufen Gu; Zhilan Wang (Water Resources Management, 2024)

Developing a National-Scale Hybrid System Dynamics, Agent-Based, Model to Evaluate the Effects of Dietary Changes on the Water, Food, and Energy Nexus - Shima Kheirinejad; Omid Bozorg-Haddad; Dragan Savic; Vijay P. Singh; Hugo A. Loáiciga (Water Resources Management, 2024)

Artificial Intelligence for Water Consumption Assessment: State of the Art Review - Almando Morain; Nivedita Ilangovan; Christopher Delhom; Aavudai Anandhi (Water Resources Management, 2024)
In recent decades, demand for freshwater resources has increased the risk of severe water stress. With the growing prevalence of artificial intelligence (AI), many researchers have turned to it as an alternative to linear methods to assess water consumption (WC). Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, this study utilized 229 screened publications identified through database searches and snowball sampling. This study introduces novel aspects of AI's role in water consumption assessment by focusing on innovation, application sectors, sustainability, and machine learning applications. It also categorizes existing models, such as standalone and hybrid, based on input, output variables, and time horizons. Additionally, it classifies learnable parameters and performance indexes while discussing AI models' advantages, disadvantages, and challenges. The study translates this information into a guide for selecting AI models for WC assessment. As no one-size-fits-all AI model exists, this study suggests utilizing hybrid AI models as alternatives. These models offer flexibility regarding efficiency, accuracy, interpretability, adaptability, and data requirements. They can address the limitations of individual models, leverage the strengths of different approaches, and provide a better understanding of the relationships between variables. Several knowledge gaps were identified, resulting in suggestions for future research.

Numerical Investigation of Confluence Flow in a Degraded Bed under Different Hydraulic Parameters, Using SSIIM 2.0 - Milad Pourvahedi; Khosrow Hosseini; Sayed-Farhad Mousavi; Kiarash Geranmayeh (Water Resources Management, 2024)

Nonlinear Segmental Runoff Ensemble Prediction Model Using BMA - Xiaoxuan Zhang; Songbai Song; Tianli Guo (Water Resources Management, 2024)

Analysis of Flow and Ambient Sound Data to Identify the Microcomponents of Domestic Water Consumption for Large Households - Amjad Aliewi; John Ewen; Mark Dutton; Asim Al-Khalid; Jasim Al-Kandari; Dalal Sadeqi; Enda O’Connell (Water Resources Management, 2024)

On the Evolution and Determinants of Water Efficiency in the Regions of Spain - Asensio Buendía Hernández; Francisco Javier André; Francisco Javier Santos-Arteaga (Water Resources Management, 2024)
Economic growth in Spain has largely relied on certain water-intensive sectors including construction, leisure, and agriculture; but considerable heterogeneity is found across the country’s regions, both in terms of water stress and economic structure. Using Data Envelopment Analysis and a panel Tobit model, we analyze the determinants of water efficiency in Spain, differentiating by groups of agents (companies, households, and municipalities) and paying particular attention to inter-regional differences and specifically the sectoral structure of the various regions. To the best of our knowledge, such an analysis has never before been conducted with a focus on Spain’s economy. Moreover, we emphasize the importance of considering the circular aspects of water management by including treated wastewater and recycled water in our analysis. We argue that this approach provides more credible and accurate measures of efficiency as well as more robust results around the key driving and explanatory factors. Our analysis reveals that water efficiency has a very significant inertia component with respect to one-year and even two-year lags, and this is found to react positively to water scarcity. Moreover, water efficiency depends on income in a nonlinear way, and it is sensitive to the economic structures of the diverse regions, with more efficient regions tending to export more at the national level. In terms of policy implications, our results provide an empirical basis from which to advocate for water tariffication as a means to spur efficiency.

Enhancing Water Cycle Restoration through LID Practices Considering Climate Change: A Study on Permeable Pavement Planning by an Iterative MCDM Model - Seung Taek Chae; Eun-Sung Chung; Jiping Jiang (Water Resources Management, 2024)

Prioritization of Sub-Watersheds Susceptible to Soil Erosion using Different Combinations of Objective Weighting and MCDM Techniques in an Ungauged River Basin - Vinoth Kumar Sampath; Nisha Radhakrishnan (Water Resources Management, 2024)

Correlation Between Water Erosion and Hydraulics of Slope–Gully Systems According to Check Dam Siltation Depth - Lulu Bai; Peng Shi; Zhanbin Li; Peng Li; Zhun Zhao; Jingbin Dong; Tanbao Li; Jingmei Sun; Dejun Wang (Water Resources Management, 2024)

A Multi-step Data Assimilation Framework to Investigate the Effect of Measurement Uncertainty in the Reduction of Water Distribution Network Model Errors - Ibrahim Miflal Fayaz; Mario Castro-Gama; Leonardo Alfonso (Water Resources Management, 2024)
Water distribution network (WDN) models are a common decision support tool for understanding the behavior and performance of WDNs, aiding in the planning and management of WDN systems. The increasing availability of real-time data has recently promoted the exploration of Data Assimilation (DA) techniques to improve these models. However, flow, pressure and demand data are uncertain, particularly due to sensor characteristics such as precision and noise. An open question is to what extent DA can still improve hydraulic models when the data used to this end is uncertain. This paper proposes a three-step Ensemble Kalman Filter based DA approach for WDNs (3-EnKF-WDN), building on previous approaches, and advancing in two main fronts: the use of extended period simulation, and the use of pressure-dependent demand (PDD) analysis. Different scenarios considering uncertain sensor data, with varied precision and noise, are applied to two networks of different sizes, representative of real-world WDNs. The computational demand of the 3-EnKF-WDN method is also assessed. Results show that increasing sensor’s precision and decreasing the noise in state measurements reduce model error, as expected. However, we also found that model errors: 1) are reduced more effectively by using 3-EnKF-WDN than by increasing sensors’ precision; 2) are not reduced if certain noise thresholds are surpassed; 3) can be reduced without assimilating demand data if the WDNs are fully monitored with head sensors in all the nodes and flow sensors in all the links.

Reservoir Risk Operation of 'Domestic-Production-Ecology' Water Supply Based on Runoff Forecast Uncertainty - Tao Bai; Qianglong Feng; Dong Liu; Chi Ju (Water Resources Management, 2024)

A Qualitative-Risk-Based Model to Assess Group Decisions for Planning the Maintenance-Renewal Works of Water Pipelines with Unreliable Operational Data - Sattar Salehi; Seyed Payam Salamati Nia (Water Resources Management, 2024)

Incorporating Spatio-Temporal Changes of Well Irrigation into a Distributed Hydrologic Model to Improve Groundwater Anomaly Estimations for Basins with Expanding Agricultural Lands - Cihangir Koycegiz; Mehmet Cuneyd Demirel; Omer Lutfi Sen; Meral Buyukyildiz (Water Resources Management, 2024)
This paper seeks to address the deficiency of utilizing satellite-based GRACE observations and model-based GLDAS water budget components in estimating the changes in the groundwater storage in Konya Endorheic Basin (KEB), a basin experiencing considerable land use land cover (LULC) change, primarily agricultural expansion. Cereal cultivation in the basin has a slight decreasing trend, however, the cultivation of crops with high water consumption, such as maize and sunflower, is increasing substantially. And total agricultural areas are increasing. GRACE-GLDAS approach does not accurately give the long-term groundwater decline in the basin, mainly because the land surface models employed in GLDAS cannot realistically simulate variations in water budget components as they do not consider the changes in LULC and do not possess an elaborated irrigation scheme. Here, we used a fully-distributed mesoscale hydrologic model, mHM, that can handle multiple LULC maps from different years. The model was modified to incorporate the spatio-temporal changes of agricultural fields in KEB and an explicit irrigation scheme since we hypothesized that the groundwater depletion is mainly caused by well irrigation. mHM was calibrated against streamflow observations for the period 2004–2019. The simulations show that the use of mHM with the incorporated features gives groundwater storage changes that are more consistent with the well-based observations than those obtained from the GRACE-GLDAS approach. On the other hand, the mHM simulation with a static LULC map, as in GLDAS models but with a better representation of irrigated fields, provides groundwater anomaly changes that are more consistent with the GRACE-GLDAS results, a further justification of insufficiency of the GLDAS-based approach in estimating groundwater variations for basins with considerable landscape change.

Effective Hydraulic Head Control Rule Identification for Unrecoverable Subsidence Mitigation - Tatas; Hone-Jay Chu (Water Resources Management, 2024)

Investigating the Impacts of Seasonal Temperature Variations on the Hysteresis Response of Groundwater in the Aquitard in a Plain Reservoir area - Kehan Miao; Yong Huang; Zhi Dou; Huan Shen; Yan Zhu; Yue Su; Yin Jiang; Chaoqi Wang (Water Resources Management, 2024)

A Novel Coupled Model for Monthly Rainfall Prediction Based on ESMD-EWT-SVD-LSTM - Ziyu Li; Xianqi Zhang (Water Resources Management, 2024)

Analyzing the Role of Changing Climate on the Variability of Intensity-Duration-Frequency Curve Using Wavelet Analysis - Syed Adnan Shah; Hamza Farooq Gabriel; Muhammad Waqar Saleem; Nuaman Ejaz; Songhao Shang; Deqiang Mao; Khalil Ur Rahman (Water Resources Management, 2024)

D-vine Copula Quantile Regression for a Multidimensional Water Expenditures Analysis: Social and Regional Impacts - El Hannoun Wafaa; Zoglat Abdelhak; Ezzahid ElHadj; El Adlouni Salah-Eddine (Water Resources Management, 2024)

Generalized Structure of Group Method of Data Handling: Novel Technique for Flash Flood Forecasting - Isa Ebtehaj; Hossein Bonakdari (Water Resources Management, 2024)

Regional Water Environmental Carrying Capacity: Changing Trends and Direction, Obstacle Factors, and Implications - Xi Yang; Zhihe Chen; Zhen Li (Water Resources Management, 2024)

Evaluating the Performance of Several Data Preprocessing Methods Based on GRU in Forecasting Monthly Runoff Time Series - Wen-chuan Wang; Yu-jin Du; Kwok-wing Chau; Chun-Tian Cheng; Dong-mei Xu; Wen-Tao Zhuang (Water Resources Management, 2024)

A Systematic Feedback Assessment Framework to Identify the Impact of Climate Change and Ecological Restoration on Water Yield Patterns - Yongwei Zhu; Shanhu Jiang; Liliang Ren; Denghua Yan; Hao Cui; Menghao Wang; Chong-Yu Xu (Water Resources Management, 2024)

Agricultural Water Resource Management in the Socio-Hydrology: A Framework for Using System Dynamics Simulation - Fatemeh Javanbakht-Sheikhahmad; Farahnaz Rostami; Hossein Azadi; Hadi Veisi; Farzad Amiri; Frank Witlox (Water Resources Management, 2024)

Impact of Climate Change on Water Diversion Risk of Inter‑Basin Water Diversion Project - Linhui Mu; Tao Bai; Dong Liu; Lei Li (Water Resources Management, 2024)

Modeling Predictors of Water Conservation-Friendly Behavior Among the General Public: Structural Equation Modeling - Anthony Coetzer-Liversage; Azadeh Fatehpanah; Elham Maraghi; Mahmood Karimy; Amir H. Pakpour; Majed Maripour; Nematollah Jaafarzadeh Haghighi Fard; Marzieh Araban (Water Resources Management, 2024)

Enhancing Equitable Water Distribution in Agriculture: A Novel Optimal Framework for Irrigation Equity Index Improvement Under Diverse Adaptation Strategies - Moudi Mahdi; Song Xueqian; He Yuan; Majid Amani-Beni (Water Resources Management, 2024)

Study on the Influence of Temporal and Spatial Resolution of Rainfall Data on Watershed Flood Simulation Performance - Xinxin Pan; Jingming Hou; Tian Wang; Xinyi Li; Jing Jing; Guangzhao Chen; Juan Qiao; Qingyuan Guo (Water Resources Management, 2024)

Application of Machine Learning Approaches in Particle Tracking Model to Estimate Sediment Transport in Natural Streams - Saman Baharvand; Habib Ahmari (Water Resources Management, 2024)

Enhancing Flood Susceptibility Modeling: a Hybrid Deep Neural Network with Statistical Learning Algorithms for Predicting Flood Prone Areas - Motrza Ghobadi; Masumeh Ahmadipari (Water Resources Management, 2024)

Relevance of Intuitionistic Fuzzy Optimization Approach in Planning of a Multi–Objective Water Resource System - Sangita Pawar; Premlal Patel; Ashwini B. Mirajkar (Water Resources Management, 2024)

Bivariate Assessment of Hydrological Drought of a Semi-Arid Basin and Investigation of Drought Propagation Using a Novel Cross Wavelet Transform Based Technique - Suvro Aon; Sujata Biswas (Water Resources Management, 2024)

Dynamic Effects of a Regulating Valve in the Assessment of Water Leakages in Single Pipelines - Oscar E. Coronado-Hernández; Modesto Pérez-Sánchez; Alfonso Arrieta-Pastrana; Vicente S. Fuertes-Miquel; Jairo R. Coronado-Hernández; Edgar Quiñones-Bolaños; Helena M. Ramos (Water Resources Management, 2024)
Water losses in water distribution systems are typically analysed using extended period simulations, where its numerical resolution is commonly achieved using the gradient method. These models assume that adjustments to regulating valves occur, either manually or automatically, over an extended period of time, then the system inertia can be neglected. This research introduces the development of a rigid water column model for analysing water leakages in single pipelines, which can be employed to account for regulation valve adjustments in shorter time periods, thereby providing greater accuracy when assessing water losses. The application to a case study is presented to analyse pressure variations and leakage flow patterns over 30, 60, and 180 s. A comparison between the extended period simulation and rigid water column model is presented in order to note the order of magnitude on leakages when the system inertia is not considered. The results confirm that is crucial for water utilities the consideration of inertial system to simulate adequately opening and closure manoeuvres in water distribution systems, since according to the case study the extended period simulation can overestimated or underestimated the total leakage volume in percentages of 37.1 and 55.2 $$%$$ % , respectively.

Identifying Risk Components Using a Sewer-Road Integrated Urban Stormwater Model - Chen Shen; Haishan Xia; Xin Fu; Xinhao Wang; Weiping Wang (Water Resources Management, 2024)

Variance-based Global Sensitivity Analysis of Surface Runoff Parameters for Hydrological Modeling of a Real Peri-urban Ungauged Basin - C. Giudicianni; I. Di Cicco; A. Di Nardo; R. Greco (Water Resources Management, 2024)

Effective Management of Water Resources Problems in Irrigated Agriculture Through Simulation Modeling - Ajay Singh (Water Resources Management, 2024)

Study on Watershed Ecological Water Replenishment Coupling Hydrodynamic and Reservoir Operation - Tao Bai; Yu Kang; Dong Liu; Shaojie Gou (Water Resources Management, 2024)

Innovative Drought Classification Matrix and Acceptable Time Period for Temporal Drought Evaluation - Ahmad Abu Arra; Eyüp Şişman (Water Resources Management, 2024)
Evaluating drought is paramount in water resources management and drought mitigation plans. Drought indices are essential tools in this evaluation, which mainly depends on the time period of the original datasets. Investigating the effects of time periods is critical for a comprehensive understanding and evaluation of drought. Also, It holds particular significance for regions facing data availability challenges. The existing literature reveals a gap in drought assessment and comparison analysis using conventional methods based on drought indices only. This research proposes an innovative drought classification matrix to compare drought indices and spatial and temporal scenarios; the proposed matrix depends on any drought classification for comparison procedure. Furthermore, it aims to investigate the differences between several time period scenarios based on the proposed matrix and several statistical metrics (R 2 , CC, RMSE, HH, and RB) and determine the acceptable/minimum time period. The application of the proposed matrix and selection of an acceptable/minimum time period is presented to three different climates: Durham station in the United Kingdom, Florya station in Türkiye, and Karapinar station in Türkiye. The results show that the time period scenarios are able to catch the reference time period (RTP) scenario reasonably, with strong correlation and negative relative bias. The 10-year time period is sufficient as an acceptable/minimum time period for short timescales, such as meteorological drought. Conversely, for longer timescales, such as hydrological drought, a 20-year time period is the acceptable/minimum time period. The proposed matrix demonstrates a robust and powerful framework for comparison, making it applicable to various drought assessment scenarios globally.

Developing Extended and Unscented Kalman Filter-Based Neural Networks to Predict Cluster-Induced Roughness in Gravel Bed Rivers - Masoud Karbasi; Mohammad Ghasemian; Mehdi Jamei; Anurag Malik; Ozgur Kisi (Water Resources Management, 2024)

Potential of Soil Conditioners to Mitigate Deficit Irrigation Impacts on Agricultural Crops: A Review - Ahmed Abdelfattah; Harby Mostafa (Water Resources Management, 2024)
In light of the current water scarcity, one strategy for reducing water consumption in irrigated agriculture is to reduce the amount of irrigation water compared to full crop irrigation or in other words deficit irrigation. Deficit irrigation management may be a critical issue due to climate change. Incorporation of different soil conditioners can improve soil hydro-physical properties and mitigate negative effects in water-stressed conditions. Recent review articles either addressed specific crop behavior under water deficit or covered a single type of soil conditioners. This manuscript represents an inclusive review providing insight into deficit irrigation methods incorporated with different soil conditioners. Crop response to deficit irrigation is discussed in the light of some mathematical models. Three main types of soil conditioners are covered: bentonite, biochar, and super-absorbent polymers. Mechanisms associated with effects of each conditioner to enhance soil water retention is highlighted as well. Previous study findings were discussed comparatively and future prospective, recommendations and challenges were addressed.

Uncertainty and Sensitivity Analysis in Reservoir Modeling: a Monte Carlo Simulation Approach - Adelena Gonçalves Maia; Miller Alonso Camargo-Valero; Mark A. Trigg; Amirul Khan (Water Resources Management, 2024)

Relationships between River and Groundwater Flow in an Alluvial Plain by Time Series Analysis and Numerical Modeling - Guido Leone; Michele Ginolfi; Libera Esposito; Francesco Fiorillo (Water Resources Management, 2024)

Enhanced Methods for Evaluating Aquifer Susceptibility: Incorporating Static and Dynamic Vulnerability Assessments - Sofia Ourarhi; Alae-Eddine Barkaoui; Yassine Zarhloule (Water Resources Management, 2024)

Digital Twin-Based Pump Station Dynamic Scheduling for Energy-Saving Optimization in Water Supply System - Sheng-Wen Zhou; Shun-Sheng Guo; Wen-Xiang Xu; Bai-Gang Du; Jun-Yong Liang; Lei Wang; Yi-Bing Li (Water Resources Management, 2024)

Rainfall Extreme Indicators Trend and Meteorological Drought Changes Under Climate Change Scenarios - Mohammad Tavosi; Mehdi Vafakhah; Hengameh Shekohideh; Seyed Hamidreza Sadeghi; Vahid Moosavi; Ziyan Zheng; Qing Yang (Water Resources Management, 2024)

Graph Convolutional Neural Network for Pressure Prediction in Water Distribution Network Sites - Dan Liu; Pei Ma; Shixuan Li; Wei Lv; Danhui Fang (Water Resources Management, 2024)

Effect of Air Vessel Configuration on Transient Pressure - Moustafa S. Darweesh; Anwar A. Ahmed (Water Resources Management, 2024)

Slope Stability Analysis under Heavy Rainfall Conditions Based on a Modified Green-Ampt Model - Yunxin Zheng; Zhiping Hu; Rui Wang; Xin Wen; Xiang Ren; Rui Pan (Water Resources Management, 2024)

Analyzing Urban Drinking Water System Vulnerabilities and Locating Relief Points for Urban Drinking Water Emergencies - Mohammad Kazemi Garajeh; Bakhtiar Feizizadeh; Behnam Salmani; Mohammad Ghasemi (Water Resources Management, 2024)
Urban water is known as a critical sector of urban environments which significantly impacts the life quality and wellbeing of reinstates. In the context of developing sustainable urban drinking system it is critical to analyze network events and develop sufficient systems of water supply. To the best of our knowledge, fewer studies have examined the potential of automated-based approaches such as deep learning convolutional neural network (DL-CNN) for analyzing urban water network events and identifying the optimal location of urban drinking water relief posts. Therefore, the current study aims to propose an efficient approach for Geospatial based urban water network events analyze and determine the optimal location of urban drinking water relief posts in Zanjan. For this goal, first, we prepared and preprocessed various predisposing variables for analyzing the urban water network events and determining the optimal location of urban drinking water relief posts. We then applied an integrated approach of analytical network process (ANP) and DL-CNN methods to locate the best location of urban drinking water relief posts. Finally, intersection over union and accuracy assessment were employed to evaluate the performance of the results. Our findings show that the DL-CNN performed well with an accuracy of 0.942 compared to the ANP (0.895) for determining the optimal location of urban drinking water relief posts. According to the results, the best place to build a relief post is in the city center, and the surrounding areas may not be suitable, which is in accordance with field work analysis. The results of the study also reveal that areas 5 and 3 are at high risk from the number of urban water network events perspective, which requires the construction of urban water relief stations.

Meteorological Drought Prediction Based on Evaluating the Efficacy of Several Prediction Models - Abdol Rassoul Zarei; Mohammad Reza Mahmoudi; Alireza Pourbagheri (Water Resources Management, 2024)

A Simulation–Optimization System to Assess Dam Construction with a Focus on Environmental Degradation at Downstream - Mahdi Sedighkia; Asghar Abdoli (Water Resources Management, 2024)
The present study proposes and evaluates an integrated framework to assess dam construction and removal, encompassing the simulation of downstream river habitats and reservoir operation in three distinct statuses: conventional reservoir operation optimization, optimal release considering environmental aspects within the optimization model, and natural flow conditions. Fuzzy physical habitat simulation was employed to assess physical habitats, while an ANFIS-based model was utilized to simulate thermal tension and dissolved oxygen tension at downstream habitats. Particle swarm optimization was applied in the optimization models. To evaluate the effectiveness of the proposed framework, results from the optimization system as well as habitat suitability models in the natural flow and current condition were compared using various measurement indices, including the reliability index, vulnerability index, the Nash–Sutcliffe model efficiency coefficient (NSE), and root mean square error (RMSE). The case study results suggest that the reliability of water supply may be diminished under optimal release for environmental and demand considerations. Additionally, optimal release for the environment may not adequately protect downstream aquatic habitats. Therefore, in cases where the preservation of downstream habitats is a priority, dam removal may be a logical solution. Moreover, it is essential to acknowledge that the main limitation of the proposed method is its high computational complexity.

Advancing Sponge City Implementation in China: The Quest for a Strategy Model - Faiza CHIKHI; Chuancheng LI; Qunfeng JI; Xilin ZHOU (Water Resources Management, 2024)

An Agent-based Framework for Transition from Traditional to Advanced Water Supply Systems in Arid Regions - Mohammad Sadegh Khorshidi; Azizallah Izady; Mohammad Reza Nikoo; Ali Al-Maktoumi; Mingjie Chen; Amir H. Gandomi (Water Resources Management, 2024)

Development, Application, and Validation of the Urban Flood Susceptibility Index - Rafael Brandão Ferreira de Moraes; Fábio Veríssimo Gonçalves (Water Resources Management, 2024)

Water Quality Prediction in Urban Waterways Based on Wavelet Packet Denoising and LSTM - Jiafeng Pang; Wei Luo; Zeyu Yao; Jing Chen; Chunyu Dong; Kairong Lin (Water Resources Management, 2024)

Aadhaar Enabled Water Distribution System - D. Giridhar Reddy; Darshan V; N. S. Girish Rao Salanke; Shobha G.; Manas M.N (Water Resources Management, 2024)

Real-Time Evaluation of the Uncertainty in Weather Forecasts Through Machine Learning-Based Models - Carmen Calvo-Olivera; Ángel Manuel Guerrero-Higueras; Jesús Lorenzana; Eduardo García-Ortega (Water Resources Management, 2024)
Meteorological events have always been of great interest because they have influenced everyday activities in critical areas, such as water resource management systems. Weather forecasts are solved with numerical weather prediction models. However, it sometimes leads to unsatisfactory performance due to the inappropriate setting of the initial state. Precipitation forecasting is essential for water resource management in semi-arid climate and seasonal rainfall areas such as the Ebro basin. This research aims to improve the estimation of the uncertainty associated with real-time precipitation predictions presenting a machine learning-based method to evaluate the uncertainty of a weather forecast obtained by the Weather Research and Forecasting model. We use a model trained with ground-truth data from the Confederación Hidrográfica del Ebro, and WRF forecast results to compute uncertainty. Experimental results show that Decision Tree-based ensemble methods get the lowest generalization error. Prediction models studied have above 90% accuracy, and root mean square error has similar results compared to those obtained with the ground truth data. Random Forest presents a difference of -0.001 concerning the 0.535 obtained with the ground truth data. Generally, using the ML-based model offers good results with robust performance over more traditional forms for uncertainty calculation and an effective alternative for real-time computation.

Research on Ecological Protection Mechanisms in Watersheds Based on Evolutionary Games-Inter-provincial and Intra-provincial Perspectives - Fugui Dong; Mingxia Shi; Wanying Li (Water Resources Management, 2024)

The Effect of Discounting on the Formulation of an Aquifer Management Policy Based on Groundwater Trading - Athanasios Tsiarapas; Zisis Mallios (Water Resources Management, 2024)
Optimal groundwater management is a necessary condition for achieving the objective of sustainable development, which is directly linked to issues of intergenerational equity. Thus, groundwater management policy shaping has to consider such issues, in particular through the implementation of appropriate discounting methods. The existing literature in the field of groundwater management focuses on a single discount function (DF), the exponential one, without considering the impact of different DFs on the results obtained. At the same time, tradable water rights (TWR) systems have been suggested as policy instruments for more efficient and sustainable water use. This paper focuses on the impact that different DFs have on the formulation of groundwater management policies based on TWR. To this end, a dynamic model is formulated, which concerns groundwater pumping from an aquifer by two groups of users participating in a TWR system and four different DFs are considered to calculate the present value of social welfare: no discounting, exponential, hyperbolic and Gamma discounting. The results of simulations based on data for an aquifer in Northern Greece show that there is a high sensitivity of the results to the DF, which has a direct effect on social welfare from groundwater consumption, aquifer’s hydrological behavior and TWR system intertemporal economic efficiency.

Critical View of Overland Flow Estimation in Semi-arid Catchments Under Land Subsidence with Long-term Field Measurements - O. Bakhshi Rad; A. R. Vaezi; R. Khatibi (Water Resources Management, 2024)

Improving Multivariate Runoff Prediction Through Multistage Novel Hybrid Models - Muhammad Sibtain; Xianshan Li; Fei Li; Qiang Shi; Hassan Bashir; Muhammad Imran Azam; Muhammad Yaseen; Snoober Saleem; Qurat-ul-Ain (Water Resources Management, 2024)

Improving Hydrological Modeling with Hybrid Models: A Comparative Study of Different Mechanisms for Coupling Deep Learning Models with Process-based Models - Yiming Wei; Renchao Wang; Ping Feng (Water Resources Management, 2024)

A Comparative Assessment of Decision Tree Algorithms for Index of Sediment Connectivity Modelling - Haniyeh Asadi; Mohammad T. Dastorani; Roy C. Sidle; Afshin Jahanshahi (Water Resources Management, 2024)

Discovering the Perception Differences of Stakeholders on the Sustainable and Innovative Stormwater Management Practices - Ömer Ekmekcioğlu (Water Resources Management, 2024)
The overarching aim of the present work is to explore the perception differences of stakeholders, i.e., municipalities (MN), water administrations (WS), non-governmental organizations (NGO), and universities (UN), playing vital roles in the decision mechanisms regarding one of the sustainable flood mitigation techniques, i.e., low impact development (LID) practices. As being rewarding alternative to conventional drainage techniques, four different LID strategies, i.e., green roof (GR), bioretention cells (BC), permeable pavement (PP), and infiltration trench (IT), and three of their combinations were adopted to the densely urbanized Ayamama River basin, Istanbul, Turkey. The performances of the LIDs were comprehensively evaluated based on three pillars of sustainability (i.e., social, economic, and environmental) using a hybrid multi-criteria decision-making (MCDM) framework containing the implementation of fuzzy analytical hierarchy process (fuzzy AHP) and the VIKOR (VIse KriterijumsaOptimiz acija I Kompromisno Resenje) for finding the weights of constraining criteria and prioritizing the LID scenarios, respectively. The major outcomes of this research showed that experts from MN, WS, and UN put forward the environmental dimension of sustainability, whereas respondents from NGO concentrated on the social aspect. Furthermore, MN and WS highlighted initial investment cost as the most determining criterion in optimal LID selection. On the other hand, criteria weights regarding the judgments of the experts attended from NGO revealed the significance of community resistance in specifying the optimal LID practices, while aesthetic appearance was the major concern of the academia. Hence, the present study, as an initial attempt, enabled critical standpoints for discovering perceptions of stakeholders.

Application and Uncertainty Analysis of Data-Driven and Process-Based Evapotranspiration Models Across Various Ecosystems - Qinghe Wang; Na Liu; Shunqing Zhong; Wulin Jiang (Water Resources Management, 2024)

On the Occurrence of Extreme Rainfall Events Across Italy: Should We Update the Probability of Failure of Existing Hydraulic Works? - Benedetta Moccia; Elena Ridolfi; Claudio Mineo; Fabio Russo; Francesco Napolitano (Water Resources Management, 2024)
Every year, extreme rainfall events cause human deaths and economic losses around the world. Risk reduction strategies may involve the implementation of structural measures that are widely extended and financial relevant. Despite the high reliance on these mitigation measures, there might occur instances of overload, i.e. events with intensities exceeding the design value of these structures, that may have catastrophic consequences. In this framework, it is crucial to improve hydraulic works management, thus, we introduce a procedure at rain gauge scale for revising design variables throughout their operational lifespan. This enables us to enhance the assessment of the probability of failure of these works. Finally, we investigate instances where design variables experience overload during the recording period, thus assessing the occurrence of rare yet possible events. To this aim we find the most-suitable probability distribution to describe daily rainfall maxima in Italy. Specifically, we test the performance of four widely used bi-parametrical distributions with different tail behaviour, by analysing an impressive dataset consisting of 2282 rain gauges observations from 1860 to 2022. Our results show that: (1) 78% of the empirical samples exhibits heavy-tail behaviour; (2) when the update procedure is applied, 64% of the samples shows a higher-than-expected probability of failure; (3) at least one case of overload associated to a 100-years return period is recorded in almost all regions. Based on our results, existing hydraulic works designed to safeguard populations and their activities from catastrophic events may face a higher risk of failure than initially expected.

Optimizing Control of Secondary Water Supply Tanks for Demand Peak Staggering - Jian Wang; Bangwu Deng; Shuai Jiang; Zhuozhi Deng; Wei Wang; Guowei Chen; Li Liu (Water Resources Management, 2024)

Uncertainty Analysis of Optimal Instruction for WDN Pipes Repair and Replacement Using Fuzzy α-cut - hydraulic Simulation Approach - S. M. Jafari; A. R. Zahiri; O. Bozorg Haddad; M. Mohammad Rezapour Tabari (Water Resources Management, 2024)

Predicting the Water Inflow Into the Dam Reservoir Using the Hybrid Intelligent GP-ANN- NSGA-II Method - Ramtin Moeini; Kamran Nasiri; Seyed Hossein Hosseini (Water Resources Management, 2024)

Groundwater Resource Assessment by Applying Long-Term Trend Analysis of Spring Discharge, Water Level, and Hydroclimatic Parameters - Zhi-Qiang Yu; Takahiro Hosono; Hiroki Amano; Ronny Berndtsson; Kei Nakagawa (Water Resources Management, 2024)

Assessing Water Management Strategies in Data-Scarce Mountain Regions under Uncertain Climate and Socio-Economic Changes - R. Muñoz; S. A. Vaghefi; F. Drenkhan; M. J. Santos; D. Viviroli; V. Muccione; C. Huggel (Water Resources Management, 2024)
Water management in mountainous regions faces significant challenges due to deep uncertainties arising from data scarcity, knowledge gaps, and the complex interplay of climate and socio-economic changes. While existing approaches focused on uncertainty reduction and water system optimization contribute to managing uncertainties, they often require probability distributions that can be difficult to obtain in data-scarce mountain regions. To address these challenges, we demonstrate the effectiveness of Exploratory Modeling and Analysis (EMA) in assessing water management strategies and identifying operational ranges that avoid future water scarcity. Through a case study in the complex and data-scarce Peruvian Andes, we employed EMA to run 12,000 simulations by 2050, incorporating deep uncertainties from climate and socio-economic scenarios, and hydrological modeling parameters. This analysis identified specific policy combinations demonstrating greater robustness across diverse scenarios and uncertainties. EMA explicitly identifies operational ranges of policies to avoid water scarcity but also highlights the conditions that might trigger policy failure. We also delve into the roles of the different factors used in EMA and their significance in water management applications. Our research illustrates that an exploratory hydrological modeling approach based on robust decision-making can foster a more informed decision-making process for long-term water adaptation in rapidly changing mountain regions under data scarcity and deep uncertainties.

Improving Evapotranspiration Estimation in SWAT-Based Hydrologic Simulation through Data Assimilation in the SEBAL Algorithm - Omidreza Mikaeili; Mojtaba Shourian (Water Resources Management, 2024)

Times Series Forecasting of Monthly Rainfall using Seasonal Auto Regressive Integrated Moving Average with EXogenous Variables (SARIMAX) Model - Shahenaz Mulla; Chaitanya B. Pande; Sudhir K. Singh (Water Resources Management, 2024)

Application of Multi-Strategy Based Improved DBO Algorithm in Optimal Scheduling of Reservoir Groups - Ji He; Wen Guo; Songlin Wang; Haitao Chen; Xiaoqi Guo; Shumin Li (Water Resources Management, 2024)

A Rapid Forecast Method for the Process of Flash Flood Based on Hydrodynamic Model and KNN Algorithm - Nie Zhou; Jingming Hou; Hua Chen; Guangzhao Chen; Bingyi Liu (Water Resources Management, 2024)

Evaluation and Interpretation of Runoff Forecasting Models Based on Hybrid Deep Neural Networks - Xin Yang; Jianzhong Zhou; Qianyi Zhang; Zhanxin Xu; Jianyun Zhang (Water Resources Management, 2024)

Nature-Based Disaster Risk Reduction of Floods in Urban Areas - Poulomee Ghosh; Jeyaraman Sethuraman Sudarsan; Subramanian Nithiyanantham (Water Resources Management, 2024)

A Fuzzy Multicriteria Approach to Estimate the Water Quality Index of Hydroelectric Reservoirs - José Roberto Ribas; Juliana Crenitte Ribas Severo; Letícia Correa Gonçalves (Water Resources Management, 2024)

A Systematic Review of Crop Planning Optimisation Under Climate Change - Marcus Randall; Karin Schiller; Andrew Lewis; James Montgomery; Muhammad Shahinur Alam (Water Resources Management, 2024)
Optimising the use of natural resources for food production in the context of changing climate is an increasingly important issue. Optimisation techniques have been shown to be remarkably effective for planning problems, and tools regional planners and farmers can use to determine the viability of agricultural land use planning into the future. This paper systematically reviews the recent literature in this area and draws out the key emerging themes: few studies to date have explicitly incorporated climate projections into optimisation models; increased tension for water resources between stakeholders; and various agricultural production systems of complex versions of crop planning. From this review it can be seen that increasing concentration on the use of climate projection models within agriculturally-oriented optimisation processes is a necessity.

An adaptable participatory modelling framework to anticipate needs for securing regional drinking water supply systems under global changes - Noémie Neverre (Water Resources Management, 2024)

An Objective Framework for Bivariate Risk Analysis of Flash Floods Under the Compound Effect of Rainfall Characteristics - Tao Jiang; Qiulian Wei; Ming Zhong; Jianfeng Li (Water Resources Management, 2024)

Research on Urban Storm Flood Simulation by Coupling K-means Machine Learning Algorithm and GIS Spatial Analysis Technology into SWMM Model - Chengshuai Liu; Caihong Hu; Chenchen Zhao; Yue Sun; Tianning Xie; Huiliang Wang (Water Resources Management, 2024)

Suspended Load Modeling of River Using Soft Computing Techniques - Amir Moradinejad (Water Resources Management, 2024)

Optimization of Integrated Operation of Surface and Groundwater Resources using Multi-Objective Grey Wolf Optimizer (MOGWO) Algorithm - Ali Torabi; Fariborz Yosefvand; Saeid Shabanlou; Ahmad Rajabi; Behrouz Yaghoubi (Water Resources Management, 2024)

Global Sensitivity Analysis of Crop Parameters Based on AquaCrop Model - Wei Li; Rui Song; Muhammad Awais; Leilei Ji; Shuo Li; Mingjiang Liu; Tao Lang; Handong Qi (Water Resources Management, 2024)

Pricing of Drinking Water under Dynamic Supply and Demand based on Government Role: A Game-Theoretic Approach - Mobin Zarreh; Saeed Yaghoubi; Hamideh Bahrami (Water Resources Management, 2024)

Research on Water Price and Quantity to Meet the Basic Living Needs of Urban Residents Based on Water Conservation - Shujing Zhang; Yanrong Wang (Water Resources Management, 2024)

A Hybrid Particle Swarm Optimization-Genetic Algorithm for Multiobjective Reservoir Ecological Dispatching - Xu Wu; Xiaojing Shen; Chuanjiang Wei; Xinmin Xie; Jianshe Li (Water Resources Management, 2024)

Hydropower Reservoir Optimization with Solar Generation-Changed Energy Prices in California - Mustafa Sahin Dogan; Josue Medellin-Azuara; Jay R. Lund (Water Resources Management, 2024)
Growing solar photovoltaic supply has significantly reshaped energy prices, lowering them during solar generating hours. Large-scale hydropower reservoir operations need to adapt to changes in energy prices to maximize hydropower revenue. This paper evaluates effects of solar generation-changed energy prices on hydropower generation for five multipurpose reservoirs in California using a hydroeconomic optimization model. In California, major solar generation began in 2013, so years 2010–2012 are a pre-solar period, and years 2013–2018 are post-solar. Reservoir operations, hydropower generation and revenue between these periods are compared. Operations in the wet season (January to June), and the dry season (July to December) are evaluated. Results show that releases are more profitable when hydropower is generated twice a day during on-peak hours in the morning and evening in the wet season. When water is scarce, energy is generated only during the higher-price evening peak. Hydropower generation is mostly curtailed between 10am and 6pm due to large solar supplies, and increase during morning and evening peaks when solar generation is unavailable. However, by optimizing hydropower scheduling hours, the new energy price pattern can be more profitable. With increased energy price variability and adaptation, overall daily revenue can increase by about 14% in the wet season and 30% in the dry season.

A Novel Stochastic Tree Model for Daily Streamflow Prediction Based on A Noise Suppression Hybridization Algorithm and Efficient Uncertainty Quantification - Nasrin Fathollahzadeh Attar; Mohammad Taghi Sattari; Halit Apaydin (Water Resources Management, 2024)

Investigation of Clean Energy Production in Drinking Water Networks - Veli Süme; Rasoul Daneshfaraz; Ali Kerim; Hamidreza Abbaszadeh; John Abraham (Water Resources Management, 2024)
Viable renewable energy sources must be low-cost, easy to install, clean, and reliable if they are to meet the energy demand of urban or rural areas. Water is able to provide efficient sources of electrical energy among alternative renewable energy sources. Using modern hydraulic techniques, drinking water can be transported to the areas where it is needed. Studies on obtaining energy from drinking water networks are quite limited. Although not as necessary as water in terms or human health, electrical power is still critically important in many applications (lighting, heating, cooling, etc.). Consequently, many countries are developing energy using various renewable energy sources. In this study, a water distribution network in the Armağan Village of Maçka district of Trabzon province were used to obtain electrical energy. There are 47 pressure breaking valves (PBVs) in this network and the broken energy height is 236.35 m. The same energy loss can be achieved by installing microturbines instead of PBVs, and electricity generation can thus be achieved with a clean energy source. It was found that 84.12kWh of energy was obtained from each PBV, with a total of 3950kWh. The most suitable microturbine was selected according to sound microturbine selection criteria. From this study, it is revealed that electricity can be produced by using a Microturbine instead of Pressure Breaker Valves (PBVs).

Utilizing Machine Learning Models with Limited Meteorological Data as Alternatives for the FAO-56PM Model in Estimating Reference Evapotranspiration - Shima Amani; Hossein Shafizadeh-Moghadam; Saeid Morid (Water Resources Management, 2024)

Acknowledgement of Reviewers for 2023 - George Tsakiris (Water Resources Management, 2024)

Analysing Coastal Flood Risk: Assessing the Impact on Critical Water Infrastructures - Estefanía Couñago; Adela García-Pintos; Gloria Caballero; Fernando León-Mateos (Water Resources Management, 2024)
There is a need to enhance the resilience of critical infrastructures. The effects of climate change have already led to increased flooding of critical water infrastructure. Furthermore, predictions indicate that more infrastructures will be affected in the future. Currently, methods for accurately quantifying the economic losses resulting from sea level rise and extreme weather events are lacking. This article proposes a risk assessment methodology for coastal flooding in the Galicia region of Spain. The method estimates the losses incurred by water infrastructure and indirect industry losses due to the interruption of water infrastructure services. The results indicate that losses currently exceed 90 million euros due to extreme weather events. In the most pessimistic scenario, these losses increase to 127 million euros in 2050 and 451 million euros in 2100. In both cases, indirect industry losses account for more than 80% of the total losses.

A Novel Runoff Prediction Model Based on Support Vector Machine and Gate Recurrent unit with Secondary Mode Decomposition - Jinghan Dong; Zhaocai Wang; Junhao Wu; Xuefei Cui; Renlin Pei (Water Resources Management, 2024)

Investigating the Non-Linear Effects of Breach Parameters on a Dam Break Study - Hasan Oğulcan Marangoz; Tuğce Anılan; Servet Karasu (Water Resources Management, 2024)
When settlements are located close to a dam, it is important to accurately predict the breach peak flow and the time to reach the peak. Therefore, the prediction of dam breach properties is essential in dam break studies. Dam breach parameters such as the breach side slope, final bottom width, final bottom elevation, weir coefficient, breach formation time, and initial elevation of reservoirs are the key variables for estimating the peak discharge during a dam break scenario. In this study, these six breach parameters were analyzed to investigate the impact of breach parameters on breach peak flow and the time to reach the peak. Thus, several scenarios were calculated and compared for Atasu Dam. The results revealed that the role of the initial water elevation, final bottom elevation, and breach development time had more of an impact on the breach peak flow and the time to reach the peak. In addition, the study indicated that the final bottom width and breach weir coefficient were less sensitive to both the peak discharge and peak discharge time. Furthermore, the analysis indicated that the breach side slope parameter had no major influence on the time to peak while also having an insignificant impact on the peak discharge. Understanding this breach mechanism provides a basis for relevant research in designating key parameters for dam break analysis. Thus, the results can contribute to decision making toward the design of flood mitigation and dam emergency action planning.

Prediction of Depth-Averaged Velocity for Flow Though Submerged Vegetation Using Least Squares Support Vector Machine with Bayesian Optimization - Yangyu Deng; Yakun Liu (Water Resources Management, 2024)

Study on Multi-Time Scale Hydrodynamic Model Based on Local Time Stepping Scheme and GPUs and its Application in Urban Inundation - Junhui Wang; Shaowu Li; Jingming Hou; Ye Liu; Wenli Hu; Xueli Shi; Jiaohang Yao (Water Resources Management, 2024)

Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms - Mohammad Abdullah Almubaidin; Ali Najah Ahmed; Lariyah Mohd Sidek; Khlaif Abdul Hakim AL-Assifeh; Ahmed El-Shafie (Water Resources Management, 2024)

How Do Structural Safety, Ecological Functions and Social Development Influence Construction of Ecological Seawalls for Coastal Protection and Sustainability? - Peng Qin; Yong Jiang; Chunmei Cheng (Water Resources Management, 2024)

Development of a Long-Range Hydrological Drought Prediction Framework Using Deep Learning - Mohd Imran Khan; Rajib Maity (Water Resources Management, 2024)

The Implementation of a New Optimization Method for Hydropower Generation and Multi-Reservoir Systems - Abbas Moghani; Hojat Karami (Water Resources Management, 2024)

System Thinking for Sustainable Water Management: The Use of System Tools in Sustainability Transitions - Wan Izar Haizan Wan Rosely; Nikolaos Voulvoulis (Water Resources Management, 2024)
Managing water resources to meet current social, economic, and environmental needs without compromising the ability to meet those needs in the future, requires water managers to look beyond jurisdictional boundaries and their immediate supply operations, protect shared water and marine environments, resources and ecosystems from pollution and over-abstraction and deliver structural changes and resilient solutions to make the provision of water services sustainable. With a plethora of system tools increasingly available to support the sustainability transformation of water systems, sorting through their breadth and diversity to determine what is useful and what is not can be challenging. From a selection of 40 popular system tools grouped in terms of how they function, we review those most commonly used in water management through 35 water-related studies from the literature. Findings demonstrate that system tools are not a substitute for systems thinking and applying them alone does not qualify the development of systemic solutions. Systems thinking offers a powerful approach to first improving collective understanding of sustainability challenges related to water and then, in collaboration with a diverse group of stakeholders and the public, defining desired goals for water management and working together to make them a reality. System tools in that context can play an important role in facilitating the process and here we propose an overarching framework of how to select and apply available tools to facilitate a holistic, integrated, and interdisciplinary systems approach for water management and wider urban sustainability transitions.

Managing Potable Water in Southeastern Spain, Los Angeles, and Sydney: Transcontinental Approaches to Overcome Water Scarcity - Miguel Borja Bernabé-Crespo; Hugo Loáiciga (Water Resources Management, 2024)
Climate change and the increase of population pose challenges to ensuring suitable water supply in water-scarce regions. This work presents a comparative analysis of the water-supply approaches adopted in Los Angeles, Southeastern Spain, and Sydney. Results show a decrease in per-capita water use in the period 2000–2020, which reflects an improvement in water conservation. Social factors in the domain of hydropolitics and economic efficiency explain the divergence of water policies adopted. The adaptation to water scarcity and growing population in three regions of developed countries located in different continents sheds light on challenges facing the achievement of water security worldwide.

Combined Systematic Review and Meta-Analysis of Ground-Level Impacts of Management Transfer to Poor Farmers in Developing Countries - Éva Pék; Imre Fertő; Stefania Giusti; Maher Salman (Water Resources Management, 2024)

Multiple Risk Trend Identification with Seesaw Methodology in Hydrometeorology Time Series - Zekâi Şen (Water Resources Management, 2024)

A Machine Learning-Based Probabilistic Approach for Irrigation Scheduling - Shivendra Srivastava; Nishant Kumar; Arindam Malakar; Sruti Das Choudhury; Chittaranjan Ray; Tirthankar Roy (Water Resources Management, 2024)

Analytical Solution of the Linearized Boussinesq Equation Considering Time-Dependent Downslope Boundary, Variable Recharge and Bedrock Seepage - Ratan Sarmah; Sagar Rohidas Chavan; Ickkshaanshu Sonkar (Water Resources Management, 2024)

A Novel Strategic Water Loss Management Model and Its Optimization with Harris Hawk Algorithm - Cansu Bozkurt; Abdullah Ates; Mahmut Fırat; Salih Yılmaz; Özgür Özdemir (Water Resources Management, 2024)
Water loss management (WLM) in water distribution systems (WDSs) is generally time consuming, costly and difficult. Therefore, the most appropriate methodology should be defined based on the current status, requirements and technical capacity of the utilities. In this study, a novel WLM model was developed to improve the WLM practices, to define the most appropriate and applicable targets and to determine the components that need to be improved primarily using the Harris Hawk Optimization (HHO) algorithm. Firstly, a total of 144 components in the CSAS proposed by Bozkurt et al. (Welcome Sigma J Eng Natural Sci 40:1–13, 2022b) are scored in three utilities. The averages of current scores in utilities are 3.4167, 2.9792 and 1.1597, respectively. Then the most appropriate targets were defined with the optimization algorithm by considering the current situation and the dynamic structure of utility. The target scores defined by optimization model in utilities are 4.4097, 4.3958 and 3.2292, respectively. This novel model will contribute to the prevention of time-consuming and costly processes by determining the most appropriate progress. It is thought that this study will provide significant benefits for creating a road map for practitioners in WLM.

A Rapid Assessment Method for Flood Risk Mapping Integrating Aerial Point Clouds and Deep Learning - Xin Fang; Jie Wu; Peiqi Jiang; Kang Liu; Xiaohua Wang; Sherong Zhang; Chao Wang; Heng Li; Yishu Lai (Water Resources Management, 2024)

Future Climatic Projections and Hydrological Responses with a Data Driven Method: A Regional Climate Model Perspective - Haitao Yang; Hao Sun; Chao Jia; Tian Yang; Xiao Yang (Water Resources Management, 2024)

Pressure Sampling Design for Estimating Nodal Water Demand in Water Distribution Systems - Yu Shao; Kun Li; Tuqiao Zhang; Weilin Ao; Shipeng Chu (Water Resources Management, 2024)

Research on Hydrodynamic and Water Quality Optimization Scheduling Based on Optimization Technology for Complex of River Network Structures - Guangxue Luan; Jingming Hou; Tian Wang; Jiahao Lv; Yuzhe Li; Xujun Gao; Xueliang Sun; Yuan Liu (Water Resources Management, 2024)

Water Distribution Networks Optimization Considering Uncertainties in the Demand Nodes - Gustavo H. B. Cassiolato; Jose Ruben Ruiz-Femenia; Raquel Salcedo-Diaz; Mauro A. S. S. Ravagnani (Water Resources Management, 2024)

Automatic Generation of Water Distribution Networks Using Central Street Lines - Artemisa Fontinele Frota; Luis Henrique Magalhães Costa; José Nilton de Abreu Costa; Marco Aurélio Holanda de Castro (Water Resources Management, 2024)

Simulation of Flood Inundation Extent by Integration of HEC-HMS, GA-based Rating Curve and Cost Distance Analysis - Sagar Debbarma; Subhajit Dey; Arnab Bandyopadhyay; Aditi Bhadra (Water Resources Management, 2024)

Quantifying the Infiltration Capacity of High-Turbidity Rivers Under the Conditions of Fine Particle Clogging and Resuspension - Congmin Liu; Chengzhong Pan (Water Resources Management, 2024)

A Bayesian Based Multi-stage Type-2-fuzzy Game and Interval-stochastic Programming Method for Planning Basin Energy-water-climate Nexus System - Danyang Di; Hao Hu; Hexiang Zhang (Water Resources Management, 2024)

A New Whole Life Cycle Index System for Evaluation of Runoff Forecasting - Xiaohui Yuan; Wenbin Hu; Chao Wang; Yuxin Mao (Water Resources Management, 2024)

Quantitative Morphometric Analysis and Prioritization of Sub-Watersheds for Soil Erosion Susceptibility: A Comparison between Fuzzy Analytical Hierarchy Process and Compound Parameter Analysis Method - Shantha Kumar Dhanush; M. Mahadeva Murthy; A. Sathish (Water Resources Management, 2024)

Comparison of Classical and Machine Learning Methods in Estimation of Missing Streamflow Data - A. B. Dariane; M. I. Borhan (Water Resources Management, 2024)

Enhancing Flooding Depth Forecasting Accuracy in an Urban Area Using a Novel Trend Forecasting Method - Song-Yue Yang; You-Da Jhong; Bing-Chen Jhong; Yun-Yang Lin (Water Resources Management, 2024)

Assessing Climate Vulnerability of Ramsar Wetlands through CMIP6 Projections - Shivam Singh; Manish Kumar Goyal; Erumalla Saikumar (Water Resources Management, 2024)

SC.HAWQS: A User-Friendly Web-Based Decision Support System for Regional Water Resources Management Under a Changing Climate - Qiong Su; Raghavan Srinivasan; R. Karthikeyan (Water Resources Management, 2024)

Detailed Audit of the Energy Efficiency in Water Systems: New Performance Indices - Maria Cristina Morani; Armando Carravetta; Oreste Fecarotta; Renato Montillo (Water Resources Management, 2024)

Correction to: Design Optimization of Water Distribution Networks with Dynamic Search Space Reduction GA - Laxmi Gangwani; Shilpa Dongre; Rajesh Gupta; Mohd Abbas H. Abdy Sayyed; Tiku Tanyimboh (Water Resources Management, 2024)

Assessing Impact of Nature Based Solutions on Peak Flow Using HEC-HMS - Divya S. Agarwal; Alka Bharat; Thomas Rodding Kjeldsen; Kemi Adeyeye (Water Resources Management, 2024)

Enhancing Rainfall Data Consistency and Completeness: A Spatiotemporal Quality Control Approach and Missing Data Reconstruction Using MICE on Large Precipitation Datasets - Nafiseh Seyyed Nezhad Golkhatmi; Mahboobeh Farzandi (Water Resources Management, 2024)

Modeling Transient Mixed Flows in Drainage Networks With Smoothed Particle Hydrodynamics - Wenke Song; Hexiang Yan; Tao Tao; Mingfu Guan; Fei Li; Kunlun Xin (Water Resources Management, 2024)

Territorial Decision Support System Based on IDF Curves’ Parameters Regionalization - Moulay Driss Hasnaoui; Oumaima Rami; Driss Ouazar (Water Resources Management, 2024)

Estimation of River High Flow Discharges Using Friction-Slope Method and Hybrid Models - Fatemeh Shirazi; Abdolreza Zahiri; Jamshid Piri; Amir Ahmad Dehghani (Water Resources Management, 2024)

A Two-Stage Stochastic Water Resources Planning Approach with Fuzzy Boundary Interval Based on Risk Control and Balanced Development - Tao Wang; Jiaqi Zhai; Haihong Li; Yifei Zhao; Longlong Zhang; Kuan Liu (Water Resources Management, 2024)

Multi—Objective Reservoir Operation Optimization by Considering Ecosystem Sustainability and Ecological Targets - Hamed Yazdian; Banafsheh Zahraie; Neamatollah Jaafarzadeh (Water Resources Management, 2024)

Optimization of LSTM Parameters for Flash Flood Forecasting Using Genetic Algorithm - You-Da Jhong; Chang-Shian Chen; Bing-Chen Jhong; Cheng-Han Tsai; Song-Yue Yang (Water Resources Management, 2024)

The Impacts of Agricultural Water Pricing on Sustainable Agricultural Production - Lan Mu; Yuan Wang; Binrui Xue (Water Resources Management, 2024)

How do Multi-Scale Virtual Water Flows of Large River Economic Belts Impact Regional Water Distribution: Based on a Nested Input-Output Model - Mingdong Jiang; Xinxin Yu; Mengyuan Dai; Xiaomei Shen; Guanyu Zhong; Chunlai Yuan (Water Resources Management, 2024)

A Method For Estimating Excess Rainfall Intensity (ERI) of Combined Sewer Overflow (CSO) Based on Peak Over Threshold (POT) Sampling And The Generalized Pareto Distribution (GPD) - Xingpo Liu; Wenke Zang; Yuwen Zhou (Water Resources Management, 2024)

Sustainable Groundwater Recharge Potential Zone Identification: An AHP-OWA Approach Integrating Future Rainfall and Land-Use Projections - Shweta Kodihal; M. P. Akhtar (Water Resources Management, 2024)

Uncertainty Analysis of River Water Quality Based on Stochastic Optimization of Waste Load Allocation Using the Generalized Likelihood Uncertainty Estimation Method - Omid Babamiri; Yagob Dinpashoh (Water Resources Management, 2024)

Deep Learning to Recognize Water Level for Agriculture Reservoir Using CCTV Imagery - Soon Ho Kwon; Seungyub Lee (Water Resources Management, 2024)

Meteorological to Agricultural Drought Propagation Time Analysis and Driving Factors Recognition Considering Time-Variant Characteristics - Chengguo Wu; Yin Xu; Juliang Jin; Yuliang Zhou; Boyu Nie; Rui Li; Yi Cui; Fei Tong; Libing Zhang (Water Resources Management, 2024)

Experimental Study to Estimate Hyporheic Velocity Using Wavelet-Hybrid Soft-Computing Model - Fazeleh Kabiri; Mohammad Reza Majdzadeh Tabatabai; Sevda Mozaffari; Mohammad Shayannejad (Water Resources Management, 2024)

Integration of Exponential Weighted Moving Average Chart in Ensemble of Precipitation of Multiple Global Climate Models (GCMs) - Muhammad Shakeel; Zulfiqar Ali (Water Resources Management, 2024)

Climate Change and Multi-Reservoirs Impacts on Extreme Flood: Nonstationary Regional Frequency Analysis and Uncertainty Estimation - Hong Du; Jun Xia; Sidong Zeng; Yike Tu (Water Resources Management, 2024)

Water Microturbines for Sustainable Applications: Optimization Analysis and Experimental Validation - A. M. Rodríguez-Pérez; C. A. Rodríguez-Gonzalez; R. López; J. A. Hernández-Torres; J. J. Caparrós-Mancera (Water Resources Management, 2024)
The use of microturbines in irrigation applications represents a great opportunity for increasing sustainable energy generation. Irrigation systems have water flow that can be used to generate electricity based on microturbines that are acceptably configure such, that efficiency in crop irrigation is not affected. This research validates this use of microturbines through a system designed specifically for the characterization of microturbine generation technology. This system includes a closed water pumping circuit capable of working under, different water flow settings, as well as flow, pressure, and electricity generation sensors. For this system, the production range of the microturbines and the pressure loss associated with the various proposed configurations are characterized and specifically quantified for the best performance. After design and characterization of a scalable microturbine system, the feasibility and benefits of this application to supporting most relevant crops supplied by localized irrigation are analysed. The experiments demonstrate the greatest benefit with the implementation of 15 series microturbines each at 80 V, alongside non-Citrus fruit, where a favourable balance is achieved for the amortization period in vineyards and citrus fruit. The results validate a profitable and sustainable design for electricity generation, with return on investment rates of up to 53%. Therefore, this research offers real and extensive applications, while being scalable to rural, residential, urban and industrial settings.

A Multi-Criteria Combination Approach to Determine Spatial Intervention Prioritization of Urban Flood Based on Source Tracking Analysis - Xinghua Wang; Jingming Hou; Guangyao Hu; Xujun Gao; Ruozhu Shen (Water Resources Management, 2024)

A Rule Based Water Quality Sensor Placement Method for Water Supply Systems Using Network Topology - M. Shahsavandi; J. Yazdi; M. Jalili-Ghazizadeh; A. Rashidi Mehrabadi (Water Resources Management, 2024)

Investigating the Impact of Cumulative Pressure-Induced Stress on Machine Learning Models for Pipe Breaks - Charalampos Konstantinou; Carlos Jara-Arriagada; Ivan Stoianov (Water Resources Management, 2024)
Significant financial resources are needed for the maintenance and rehabilitation of water supply networks (WSNs) to prevent pipe breaks. The causes and mechanisms for pipe breaks vary between different WSNs. However, it is commonly acknowledged that the operational management and water pressure influence significantly the frequency of pipe breaks. Pipe breaks occur when the water pressure exceeds the tensile strength of a pipe, or due to repetitive pressure cycles that result in fatigue-related failures. Considering these pipe failure modes, a new metric known as cumulative pressure-induced stress has been introduced. This metric takes into account both static and dynamic pressure components that contribute to pipe breaks, including mean pressure and the magnitude and frequency of pressure fluctuations, respectively. The impact of CPIS on pipe breaks has not been extensively investigated. Consequently, this study investigates and evaluates the impact of this metric when incorporated as an explanatory variable in Random Forest (RF) models that analyse the key causes of pipe breaks in two WSNs. Different RF models were developed both with and without incorporating pressure components. Subsequently, the performance of these models and the significance of each input variable were assessed. The results of this study suggest that CPIS is an important variable, especially in cases where pressure-related factors play a significant role in pipe breaks. Consequently, incorporating CPIS has shown a notable improvement in the accuracy of pipe break models.

Water Resources Allocation: Interactions Between Equity/Justice and Allocation Strategies - Elmira Valipour; Hamed Ketabchi; Reza Safari shali; Saeed Morid (Water Resources Management, 2024)

Streamflow Data Infilling Using Machine Learning Techniques with Gamma Test - Saad Dahmani; Sarmad Dashti Latif (Water Resources Management, 2024)

A Laboratory Investigation on the Effects of Intermittent Water Supply in a Branched System - Marco Ferrante (Water Resources Management, 2024)

A GPU-Accelerated Full 2D Shallow Water Model Using an Edge Loop Method on Unstructured Meshes: Implementation and Performance Analysis - Liping Ma; Jijian Lian; Jingming Hou; Dawei Zhang; Xiaoqun Wang (Water Resources Management, 2024)

Multi-Risk Interaction Analysis of Cascade Hydropower Stations Based on System Dynamics Simulation - Boran Zhu; Junqiang Lin; Yi Liu; Di Zhang; Qidong Peng; Yufeng Ren; Jiejie Chen; Yi Xu (Water Resources Management, 2024)

Different Infiltration Methods for Swat Model Seasonal Calibration of Flow and Sediment Production - Priscila Pacheco Mariani; Nilza Maria dos Reis Castro; Vanessa Sari; Taís Carine Schmitt; Olavo Correa Pedrollo (Water Resources Management, 2024)

A Set Pair Analysis Method for Assessing and Forecasting Water Conflict Risk in Transboundary River Basins - Liang Yuan; Chenyuan Liu; Xia Wu; Weijun He; Yang Kong; Dagmawi Mulugeta Degefu; Thomas Stephen Ramsey (Water Resources Management, 2024)

Water Resources Allocation in a Transboundary River Based on a Rubinstein Bargaining Model - Jisi Fu; Tianwei Lu; Bin Xu; Jieyu Li; Junwei Zhou; Bin Xiong; Zhongzheng He (Water Resources Management, 2024)

A Systematic Review of Methods for Investigating Climate Change Impacts on Water-Energy-Food Nexus - Danyang Gao; Albert S. Chen; Fayyaz Ali Memon (Water Resources Management, 2024)
Water, energy and food are important for human survival and sustainable development. With climate change, investigating climate change impacts on Water-Energy-Food nexus has been a topic of growing interest in recent years. However, there is a lack of a systematic review of the current state and methodologies of Water-Energy-Food nexus studies under climate change. Here, we review research articles investigating climate change impacts on Water-Food, Water-Energy and Water-Energy-Food nexus over last seven years. The existing methods and tools, spatial scales, and future climate scenarios setting in these articles are summarised and analysed. We found that the analyses methods could be divided into four categories (physics-based modelling, statistical methods, supervised learning and operation optimisation), among them, physics-based modelling accounts for the largest proportion. The reviewed studies cover a range of scales from site scale to global, with most studies focusing on the regional scale. Models used for small to middle scale are mainly related to hydrology and water resource, while large-scale modelling is based on interdisciplinary models. Future climate scenarios setting include emission scenarios and global warming scenarios based on Global Climate Models (GCMs). A number of future research challenges have been identified. These include spatial scale and resolution, internal physical mechanism, application of novel artificial intelligence models, extreme climate events, potential competition in nexus systems as well as data and model uncertainty.

Evaluation of the Complementary Characteristics for Wind-Photovoltaic-Hydro Hybrid System Considering Multiple Uncertainties in the Medium and Long Term - Lu Lu; Wenlin Yuan; Hongshi Xu; Chengguo Su; Denghua Yan; Zening Wu (Water Resources Management, 2024)

Uberizing Agriculture in Drylands: A Few Enriched, Everyone Endangered - Jaime Martínez-Valderrama; Rolando Gartzia; Jorge Olcina; Emilio Guirado; Javier Ibáñez; Fernando T. Maestre (Water Resources Management, 2024)
The future of water resources relies heavily on food production. Large-scale agriculture, driven by irrigation technology and cost reduction, has transformed traditional dryland croplands into a very profitable but environmentally and socially impactful agribusiness. The study of groundwater-dependent food systems is fragmented. Hydrology, on one hand, concentrates on water resources while overlooking surface agricultural processes. Meanwhile, the agro-economic sector is fixated on optimizing resource utilization for short-term profit maximization. Consequently, numerous adverse environmental and social consequences are overlooked by these conventional approaches. To steer resource usage and our food systems in a new direction, prioritizing the integration of this collective knowledge is imperative. Here, we analyze the impacts of greenhouse agriculture in SE Spain, one of the global hotspots of fruit and vegetable production. Through the lens of the treadmill of production theory we uncover the model’s significant profitability and its environmental and social effects, which include unequal wealth distribution, precarious working conditions, and the depletion and pollution of belowground water reserves. Reducing water use and limiting the development of new irrigated areas, using crop species adapted to available water resources, and empowering farmers against large distributors are key measures to avoid the social and economic collapse of this region, and of other dryland areas that have followed a similar unsustainable development model. The need for these changes becomes more pressing as the impacts of climate change continue to escalate. Within this context, groundwater reserves represent vital strategic resources that must not be wasted.

Optimization Operation of Water Resources Using Game Theory and Marine Predator Algorithm - Shirin Moradi Far; Parisa-Sadat Ashofteh (Water Resources Management, 2024)

A Gradient Smoothing Technique-Based S-FEM for Simulating the Full Impacts of Anomalies on Seepage Solutions and its Application in Multi-Parameter Seepage Inversion - Yi Lei; Qianwei Dai; Bin Zhang; Chongyang Kong; Junsheng Yang (Water Resources Management, 2024)

Analyzing the Subsurface Consequences of Dam Removal on Groundwater Storage and Hydrologic Niches in a Mountain Meadow Ecosystem - Theodore D. Eyster; Mark S. Johnson; Sarah M. Yarnell; Christopher S. Lowry (Water Resources Management, 2024)

Analogy Between SCS-CN and Muskingum Methods - Esmatullah Sangin; S. K. Mishra; Pravin R. Patil (Water Resources Management, 2024)

Machine Learning For Groundwater Quality Classification: A Step Towards Economic and Sustainable Groundwater Quality Assessment Process - Aymen Zegaar; Samira Ounoki; Abdelmoutia Telli (Water Resources Management, 2024)

Research on the Degree of Non-Stationarity in Extreme Precipitation in the Continental United States - Junbo Shao; Jingcai Wang; Wenyue Wang; Fan Li; Chen Wu (Water Resources Management, 2024)

Integrating Support Vector Machines with Different Ensemble Learners for Improving Streamflow Simulation in an Ungauged Watershed - Yahi Takai Eddine; Marouf Nadir; Sehtal Sabah; Abolfazl Jaafari (Water Resources Management, 2024)

Prediction of Irrigation Water Quality Indices Using Random Committee, Discretization Regression, REPTree, and Additive Regression - Mustafa Al-Mukhtar; Aman Srivastava; Leena Khadke; Tariq Al-Musawi; Ahmed Elbeltagi (Water Resources Management, 2024)

Application of Hydraulic Sensitivity Indicators in Improving Canal Control Capabilities for Irrigation Systems - Yumiao Fan; Xiaohui Jin; Haorui Chen; Yawei Hu; Zhanyi Gao (Water Resources Management, 2024)

Design Optimization of Water Distribution Networks with Dynamic Search Space Reduction GA - Laxmi Gangwani; Shilpa Dongre; Rajesh Gupta; Mohd Abbas H. Abdy Sayyed; Tiku Tanyimboh (Water Resources Management, 2024)

Identifying Potential Locations of Hydrologic Monitoring Stations Based on Topographical and Hydrological Information - Akshay Singhal; Muhammed Jaseem; Divya; Shiblu Sarker; Pragati Prajapati; Ankit Singh; Sanjeev K. Jha (Water Resources Management, 2024)

Cluster Analysis and Predictive Modeling of Urban Water Distribution System Leaks with Socioeconomic and Engineering Factors - Qing Shuang; Rui Ting Zhao; Erik Porse (Water Resources Management, 2024)

Detection of Urban Flood Inundation from Traffic Images Using Deep Learning Methods - Pengcheng Zhong; Yueyi Liu; Hang Zheng; Jianshi Zhao (Water Resources Management, 2024)
Urban hydrological monitoring is essential for analyzing urban hydrology and controlling storm floods. However, runoff monitoring in urban areas, including flood inundation depth, is often inadequate. This inadequacy hampers the calibration of hydrological models and limits their capacity for early flood warning. To address this limitation, this study established a method for evaluating the depth of urban floods using image recognition and deep learning. This method utilizes the object recognition model YOLOv4 to identify submerged objects in images, such as the legs of pedestrians or the exhaust pipes of vehicles. In a dataset of 1,177 flood images, the mean average precision for water depth recognition reached 89.29%. The study also found that the accuracy of flood depth recognition by YOLOv4 is influenced by the type of reference object submerged by the flood; the use of a vehicle as the reference object yielded higher accuracy than using a person. Furthermore, image augmentation with Mosaic technology effectively enhanced the accuracy of recognition. The developed method extracts on-site, real-time, and continuous water depth data from images or video data provided by existing traffic cameras. This system eliminates the need for installing additional water gauges, offering a cost-effective and immediately deployable solution.

Monthly Runoff Prediction Via Mode Decomposition-Recombination Technique - Xi Yang; Zhihe Chen; Min Qin (Water Resources Management, 2024)

Data-Driven Dam Outflow Prediction Using Deep Learning with Simultaneous Selection of Input Predictors and Hyperparameters Using the Bayesian Optimization Algorithm - Vinh Ngoc Tran; Duc Dang Dinh; Binh Duy Huy Pham; Kha Dinh Dang; Tran Ngoc Anh; Ha Nguyen Ngoc; Giang Tien Nguyen (Water Resources Management, 2024)

Assessing the Effect of Future Climate Change on Drought Characteristics and Propagation from Meteorological to Hydrological Droughts—A Comparison of Three Indices - Kashish Sadhwani; T. I. Eldho (Water Resources Management, 2024)

Recent Advances in Surface Water Quality Prediction Using Artificial Intelligence Models - Qingqing Zhang; Xue-yi You (Water Resources Management, 2024)

A Multi-Task Learning Based Runoff Forecasting Model for Multi-Scale Chaotic Hydrological Time Series - Hui Zuo; Gaowei Yan; Ruochen Lu; Rong Li; Shuyi Xiao; Yusong Pang (Water Resources Management, 2024)

How to Choose the Most Proper Representative Climate Model Over a Study Region? a Case Study of Precipitation Simulations in Ireland with NEX-GDDP-CMIP6 Data - Sogol Moradian; Liz Coleman; Bartosz Kazmierczak; Agnieszka I. Olbert (Water Resources Management, 2024)

Novel Approaches for Regionalising SWAT Parameters Based on Machine Learning Clustering for Estimating Streamflow in Ungauged Basins - Javier Senent-Aparicio; Patricia Jimeno-Sáez; Raquel Martínez-España; Julio Pérez-Sánchez (Water Resources Management, 2024)

River Flash Flood Economical Loss and its Uncertainty in Developing Countries - Kimiya Amirmoradi; Alireza Shokoohi (Water Resources Management, 2024)