Determining the Sensitivity of Performance Indicators in Doroodzan Irrigation and Drainage Network Using a Flow Hydraulic Simulation Model - Mohammad Ali Shahrokhnia (Water Resources Management, 2024)

Enhancing the EPANET Hydraulic Model through Genetic Algorithm Optimization of Pipe Roughness Coefficients - Chia-Cheng Shiu; Chih-Chung Chung; Tzuping Chiang (Water Resources Management, 2024)

A Framework for Algorithmic Improvement to Mitigate the Effects of Equifinality in the Calibration of High-dimensional Parameters for Hydrological Models - Xiaoyang Tang; Deshan Tang; Fulin Zhang (Water Resources Management, 2024)

A Fast Local Search Strategy Based on the Principle of Optimality for the Long-Term Scheduling of Large Cascade Hydropower Stations - Chao Wang; Zhiqiang Jiang; Pengfei Wang; Yichao Xu (Water Resources Management, 2024)

Multiple Conceptual Model Approach for Assessing Groundwater Resources Sustainability Under Multiple Stresses - Sandow Mark Yidana; Elikplim Abla Dzikunoo; Jacob Doku Tetteh; Richard Adam Mejida (Water Resources Management, 2024)

Multi-Objective Optimization and Coordination of Power Generation, Ecological Needs, and Carbon Emissions in Reservoir Operation - Shiwei Yang; Yuanqin Wei; Junguang Chen; Yuanming Wang; Ruifeng Liang; Kefeng Li (Water Resources Management, 2024)

Evaluation of Feature Selection Methods in Estimation of Precipitation Based on Deep Learning Artificial Neural Networks - Mohammad Taghi Sattari; Anca Avram; Halit Apaydin; Oliviu Matei (Water Resources Management, 2023)
Precipitation is the most important element of the water cycle and an indispensable element of water resources management. This paper’s aim is to model the monthly precipitation in 8 precipitation observation stations in the province of Hamadan, Iran. The effects and role of different feature weights pre-processing methods (Weight by deviation, Weight by PCA, Weight by correlation and Weight by Support Vector Machine) on artificial intelligence modeling were investigated. Deep learning method based on a multi-layer feed-forward artificial neural network that is trained with Stochastic Gradient Descent using back-propagation (DL-SGD) and Convolutional Neural Networks (CNN) modelling were applied. The precipitation of each station is modeled using the precipitation values of the other stations. The best result, among all scenarios, at the Vasaj station according to the DL-SGD method (CC = 0.9845, NS = 0.9543 and RMSE = 10.4169 mm) and at the Varayineh station according to the CNN method (CC = 0.9679, NS = 0.9362 and RMSE = 16.0988 mm) were estimated.

Reservoir Inflow Prediction: A Comparison between Semi Distributed Numerical and Artificial Neural Network Modelling - Mahesh Shelke; S. N. Londhe; P. R. Dixit; Pravin Kolhe (Water Resources Management, 2023)

Evaluating Mesh Geometry and Shade Coefficient for Fog Harvesting Collectors - Abdullah A. Elshennawy; Magdy Y. Abdelaal; Ahmed M. Hamed; Mohamed M. Awad (Water Resources Management, 2023)
The most valuable resource for sustaining life on earth is water. In dry and semi-arid areas, the problem of water scarcity can be resolved with the aid of fog collection techniques employing fog collectors. Fog collection is greatly influenced by a variety of factors. Some are design parameters, while others depend on ambient circumstances. Geometry and the mesh’s shade coefficient are important design factors that can be modified and have an impact on the rate at which fog collects in fog collectors. The shape of the mesh holes and the process used to create the mesh serve to identify geometry and measure the shade coefficient. In this paper, a straightforward mathematical technique is proposed to make it easier to calculate the shade coefficient of various mesh shapes used in fog harvesting and to provide an approximation of the mesh volume and cost. Five alternative geometries were used: the rectangular mesh, square mesh, Raschel mesh, triangular mesh, and hexagonal mesh. The current simple method will facilitate the design of the fog mesh collector and can assist in achieving the ideal shade coefficient and most effective mesh geometry for fog harvesting. Rectangular meshes were solely used as an example to evaluate the results. Stainless steel rectangular meshes with various shade coefficients were tested for fog collection, and the amount of water collected by each mesh varied. It was concluded that the optimum shade coefficient ranged 50–60% for fog collection.

Flood Attenuation Potential of Italian Dams: Sensitivity on Geomorphic and Climatological Factors - Giulia Evangelista; Daniele Ganora; Paola Mazzoglio; Francesca Pianigiani; Pierluigi Claps (Water Resources Management, 2023)
In this work the attenuation potential of flood peaks of 265 large reservoirs all over Italy is analysed, considering a flood management that excludes gates opening and then configures strictly unsupervised attenuation effects. Key factors of dams and related basins are considered to develop a ranking method that can emphasize the interplay between dam geometry and the hydrological processes acting in the upstream watershed. To maintain a homogeneous approach in such a wide geographic area, the attenuation index is computed applying the numerical solution of the differential equation of lakes and only two different standardized hydrograph shapes have been used. An index design flood from the rational method is used as the incoming peak value for each dam, enhancing the use of the results of a recent analysis of all Italian rainfall extremes. Even with a very simple approach, twenty-four different design incoming floods are derived, by varying the shape of the incoming hydrograph and the parameters of the rational method. Exploring the ranking results in all the alternatives, the attenuation potential obtained for all dams demonstrates to be strongly sensitive to the assumptions on the time of concentration and to some rainfall features. On the other hand, the hydrograph shape seems to exert much less influence on the ranking outcome. Results obtained can be useful to studies of wide-area flood frequency analyses, as we highlighted the sensitivity of the rank of attenuation efficiency to hydrologic parameters widely used in the assessment of the design flood peaks in ungauged basins.

An Integrated Modeling Approach to Assess Best Management Practices (BMPs) for Improving Stream Water Quality Using the MapShed and WASP8 Models - Ayse Muhammetoglu; Pelin Orhan; Ozgun Akdegirmen; Secil Tuzun Dugan; Habib Muhammetoglu (Water Resources Management, 2023)

Characterization and Classification of River Network Types - Li Fawen; Luo Qingyang; Zhao Yong (Water Resources Management, 2023)

Determinants of Farmers’ Decision-Making Processes under Socio-Political Stressors exacerbated by Water Scarcity and Climate Change Adaptation - G. Harik; R. Zurayk; I. Alameddine; M. El Fadel (Water Resources Management, 2023)

Towards Sustainable Cities: Studying Evaluation Index of Water Environment Carrying Capacity - Jiaxi Chen; Xiaonan Tang (Water Resources Management, 2023)

Holistic Framework for Canal Modernization: Operation Optimization, and Economic and Environmental Analyses - Kazem Shahverdi; Jose Maria Maestre (Water Resources Management, 2023)

Artificial Intelligence Generated Synthetic Datasets as the Remedy for Data Scarcity in Water Quality Index Estimation - Min Yan Chia; Chai Hoon Koo; Yuk Feng Huang; Wei Di Chan; Jia Yin Pang (Water Resources Management, 2023)

Resolving Trans-Boundary Water Conflicts: Third-Party Mediation Using an Inverse Approach of GMCR Under Incomplete Preference Environments - Xiufen Gu; Lailei Gu; Dayong Wang; Sajad Jamshidi (Water Resources Management, 2023)

Futuristic Streamflow Prediction Based on CMIP6 Scenarios Using Machine Learning Models - Basir Ullah; Muhammad Fawad; Afed Ullah Khan; Sikander Khan Mohamand; Mehran Khan; Muhammad Junaid Iqbal; Jehanzeb Khan (Water Resources Management, 2023)

Developing a New Artificial Intelligence Framework to Estimate the Thalweg of Rivers - Zohre Aghamolaei; Masoud-Reza Hessami-Kermani (Water Resources Management, 2023)

Comparative Analysis of Drought Modeling and Forecasting Using Soft Computing Techniques - K. A. Jariwala; P. G. Agnihotri (Water Resources Management, 2023)

Evaluating the Impact of Inclined Cutoff-Wall to Control Seawater Intrusion in Heterogeneous Coastal Aquifers - Sobhy R. Emara; Tamer A. Gado; Bakenaz A. Zeidan; Asaad M. Armanuos (Water Resources Management, 2023)
Subsurface physical barriers have been effectively used to mitigate seawater intrusion (SWI). Traditionally, the primary emphasis in both numerical studies and practical implementations has been on vertical barriers. The current research aims to explore the dynamics of SWI under various cutoff-wall inclination angles and depths, as well as aquifer heterogeneity using both experimental and numerical simulations. The impact of aquifer characteristics was assessed by utilizing a low hydraulic conductivity (K) aquifer (case L), a high hydraulic conductivity aquifer (case H), and two stratified aquifers. The stratified aquifers were created by grouping different hydraulic conductivity layers into two cases: high K above low K (case H/L) and low K above high K (case L/H). The model simulations covered seven different cutoff-wall inclination angles: 45.0°, 63.4°, 76.0°, 90.0°, 104.0°, 116.6°, and 135.0°. The maximum repulsion ratio of SWI wedge length was observed at an inclination angle of 76.0° for cutoff-wall depth ratios up to 0.623. However, as the depth ratio increased to 0.811, the maximum repulsion ratio shifted to an angle of 63.4° for all aquifers studied. At an inclined cutoff depth ratio of 0.811, the cutoff-wall inclination angle of 45.0° had the most significant impact on the saltwater wedge area. This results in SWI area reductions of 74.9%, 79.8%, 74.7%, and 62.6% for case L, case H, case H/L, and case L/H, respectively. This study provides practical insights into the prevention of SWI. Nevertheless, a thorough cost–benefit analysis is necessary to assess the feasibility of constructing inclined cutoff-walls.

Evaluation of Optimal Energy Productıon Usıng Deterministic, Probabilistic and Risky Cases In a Multi-Reservoir System - Efsun Bacaksız; Mücahit Opan; Zuhal Elif Kara Dilek; Murat Karadeniz (Water Resources Management, 2023)

Leveraging Transfer Learning in LSTM Neural Networks for Data-Efficient Burst Detection in Water Distribution Systems - Konstantinos Glynis; Zoran Kapelan; Martijn Bakker; Riccardo Taormina (Water Resources Management, 2023)
Researchers and engineers employ machine learning (ML) tools to detect pipe bursts and prevent significant non-revenue water losses in water distribution systems (WDS). Nonetheless, many approaches developed so far consider a fixed number of sensors, which requires the ML model redevelopment and collection of sufficient data with the new sensor configuration for training. To overcome these issues, this study presents a novel approach based on Long Short-Term Memory neural networks (NNs) that leverages transfer learning to manage a varying number of sensors and retain good detection performance with limited training data. The proposed detection model first learns to reproduce the normal behavior of the system on a dataset obtained in burst-free conditions. The training process involves predicting flow and pressure one-time step ahead using historical data and time-related features as inputs. During testing, a post-prediction step flags potential bursts based on the comparison between the observations and model predictions using a time-varied error threshold. When adding new sensors, we implement transfer learning by replicating the weights of existing channels and then fine-tune the augmented NN. We evaluate the robustness of the methodology on simulated fire hydrant bursts and real-bursts in 10 district metered areas (DMAs) of the UK. For real bursts, we perform a sensitivity analysis to understand the impact of data resolution and error threshold on burst detection performance. The results obtained demonstrate that this ML-based methodology can achieve Precision of up to 98.1% in real-life settings and can identify bursts, even in data scarce conditions.

A Technology-Organization-Environment (TOE) Framework Based on Scientometry for Understanding The Risk Factors in Sustainable Water Resources Management - Chih-Hsien Lin; Wei-Hsiang Chen (Water Resources Management, 2023)

A Scenario-based Interval Multi-objective Mixed-integer Programming Model for a Water Supply Problem: An Integrated AHP Technique - Nadire Ucler; Hale Gonce Kocken (Water Resources Management, 2023)

The Construction and Migration of a Multi-source Integrated Drought Index Based on Different Machine Learning - Hui Yue; Xiangyu Yu; Ying Liu; Xu Wang (Water Resources Management, 2023)

Experimental Investigation on Flow Configuration in Flexible and Rigid Vegetated Streams - Binit Kumar; Swagat Patra; Manish Pandey (Water Resources Management, 2023)

Dimensional Analysis and Stage-Discharge Relationships for Vegetated Weirs - Alessio Nicosia; Costanza Di Stefano; Maria Angela Serio; Vito Ferro (Water Resources Management, 2023)
The deduction of the weir flow stage-discharge relationship is a hydraulic problem generally solved by energy considerations and using the discharge coefficient to correct the gap between theoretical results and experimental measurements. In this context, the dimensional analysis represents an alternative to find simple and reliable equations to obtain the rating curve. In this study, the outflow process of vegetated weirs is investigated applying the Π-Theorem of dimensional analysis and the incomplete self-similarity theory. The aim of this paper is to propose a new theoretically-based stage-discharge relationship, and test its applicability by measurements recently published in the literature. The results showed that the errors in discharge estimate obtained by the proposed stage-discharge relationship are always less than or equal to ± 10% and less than or equal to ± 5% for 97–100% of cases. The main advantage of the proposed relationships is providing a single stage-discharge relationship, which has better performances than the equations reported in the literature and excludes the use of discharge coefficient.

Regional Groundwater Flow Modeling Using Improved Isogeometric Analysis: Application and Implications in Unconfined Aquifer Systems - Farhang Daneshmand; Jan Adamowski; Richard Martel; Rahim Barzegar; Shadi Hatami (Water Resources Management, 2023)

A Web-Enabled Tool for Site Suitability Mapping for Managed Aquifer Recharge (MAR) Using Google Earth Engine (GEE) and Multi-Criteria Decision Analysis (MCDA) - Nitesh Patidar; Basant Yadav; Sumit Kumar; Abhay Raj; Gopal Krishan; Surjeet Singh; Bhaskar Jyoti Deka; Sanghyun Jeong; Ashish Pandey; Yutaka Matsuno; R. D. Singh (Water Resources Management, 2023)

Development of Advanced Data-Intelligence Models for Radial Gate Discharge Coefficient Prediction: Modeling Different Flow Scenarios - Zaher Mundher Yaseen; Omer A. Alawi; Ammar Mohammed Alshammari; Ali Alsuwaiyan; Mojeed Opeyemi Oyedeji; Atheer Y. Oudah (Water Resources Management, 2023)

A Contract Period Optimization Model for Water Saving Management Contract Project Based on Equipment Replacement - Wei Li; Xiaosheng Wang; Qian Zhang (Water Resources Management, 2023)

Hybrid Extreme Gradient Boosting and Nonlinear Ensemble Models for Suspended Sediment Load Prediction in an Agricultural Catchment - Gebre Gelete (Water Resources Management, 2023)

Optimization of the Low-Impact Development Facility Area Based on a Surrogate Model - Jing Feng; Yuanyuan Yang; Jianzhu Li (Water Resources Management, 2023)

Detecting Background Leakages in Water Infrastructure With Fiber Optic Distributed Temperature Sensing: Insights From a Heat Transfer-Unsaturated Flow Model - Andrea D’Aniello (Water Resources Management, 2023)
The use of fiber optic distributed temperature sensing (DTS) to detect and locate leaks is still in its infancy in water infrastructure, despite its promising capabilities. Only few experiments tested this technology, and none of these studies focused on small but persistent leaks, like background leakages, which are ubiquitous and generally go undetected with the technology currently available, thus posing a serious threat to the available water resource. To test the feasibility of detecting and locating background leakages with fiber optic DTS, this study provides a detailed analysis on flow and temperature alterations around leaking water pipelines in presence of small leaks (5, 25, and 125 L/d) with small to moderate temperature differences with the surrounding soil, under 3 different pipe defect configurations, either in absence or in presence of pipe thermal insulation. Transient 3D heat transfer-unsaturated flow numerical simulations showed that there is potential to use temperature alterations to detect and locate incredibly small leaks with fiber optic DTS, like background leakages, despite the influence of pipe temperature on the surrounding soil. The analysis showed that extent, distribution, and magnitude of these alterations are convection dominated at a given temperature difference between leaked water and undisturbed soil, and that it may not be strictly necessary to place the optical fiber directly below the pipe. Indeed, optical fibers located within the utility trench at the sides of the pipe and below its bottom showed comparable or even better performance, thus giving new opportunities to retrofit existing pipelines as well.

Time of Concentration Model for Non-Urban Tropical Basins Based on Physiographic Characteristics and Observed Rainfall Responses - Aleska Kaufmann Almeida; Isabel Kaufmann de Almeida; José Antonio Guarienti; Luiz Felipe Finck; Sandra Garcia Gabas (Water Resources Management, 2023)

Stable Improved Dynamic Programming Method: An Efficient and Accurate Method for Optimization of Reservoir Flood Control Operation - Fuxin Chai; Feng Peng; Hongping Zhang; Wenbin Zang (Water Resources Management, 2023)

Analytical Solution for Linearized Saint-Venant Equations with a Uniformly Distributed Lateral Inflow in a Finite Rectangular Channel - Shiva Kandpal; Swaroop Nandan Bora (Water Resources Management, 2023)

Potential Impacts of Climate Change on Water Management in the Aral Sea Basin - Zafarjon Sultonov; Hari K. Pant (Water Resources Management, 2023)

Improving Linear Interpolation of Missing Hydrological Data by Applying Integrated Autoregressive Models - Tomasz Niedzielski; Michał Halicki (Water Resources Management, 2023)
The application of linear interpolation for handling missing hydrological data is unequivocal. On one hand, such an approach offers good reconstruction in the vicinity of last observation before a no-data gap and first measurement after the gap. On the other hand, it omits irregular variability of hydrological data. Such an irregularity can be described by time series models, such as for instance the autoregressive integrated moving average (ARIMA) model. Herein, we propose a method which combines linear interpolation with autoregressive integrated model (ARI, i.e. ARIMA without a moving average part), named LinAR (available at GitHub), as a tool for inputing hydrological data. Linear interpolation is combined with the ARI model through linear scaling the ARI-based prediction issued for the no-data gap. Such an approach contributes to the current state of art in gap-filling methods since it removes artificial jumps between last stochastic prediction and first known observation after the gap, also introducing some irregular variability in the first part of the no-data gap. The LinAR method is applied and evaluated on hourly water level data collected between 2016 and 2021 (52,608 hourly steps) from 28 gauges strategically located within the Odra/Oder River basin in southwestern and western Poland. The data was sourced from Institute of Meteorology and Water Management (Poland). Evaluating the performance with over 100 million assessments in the validation experiment, the study demonstrates that the LinAR approach outperforms the purely linear method, especially for short no-data gaps (up to 12 hourly steps) and for rivers of considerable size. Based on rigorous statistical analysis of root mean square error (RMSE) – expressed (1) absolutely, (2) as percentages and (3) using RMSE error bars – the percentage improvement, understood as percentage difference between RMSE of linear and LinAR interpolations, was found to reach up to 10%.

Developing the Regional Nonstationary IDF Curves Using NGN-ProNEVA Framework - Mohammad Reza Mahmoudi; Moein Tahanian; Alireza Gohari; Saeid Eslamian (Water Resources Management, 2023)

Benchmarking the Performance of Productive Units Using Cross-Efficiency Techniques: An Empirical Approach for Water Companies - Ramon Sala-Garrido; Manuel Mocholi-Arce; Maria Molinos-Senante; Michail Smyrnakis; Alexandros Maziotis (Water Resources Management, 2023)

A Multi-stage Stochastic Approach for Statistical Downscaling of Rainfall - Jose George; Athira P. (Water Resources Management, 2023)

A Probability Model for Short-Term Streamflow Prediction Based on Multi-Resolution Data - Lili Wang; Zexia Li; Fuqiang Ye; Tongyang Liu (Water Resources Management, 2023)

Estimation of Mean Velocity Upstream and Downstream of a Bridge Model Using Metaheuristic Regression Methods - Ozgur Kisi; Mehmet Ardiçlioğlu; Arzu M. W. Hadi; Alban Kuriqi; Christoph Kulls (Water Resources Management, 2023)
This study compares four data-driven methods, Gaussian process regression (GPR), multivariate adaptive regression spline (MARS), M5 model tree (M5Tree), and multilinear regression (MLR), in estimating mean velocity upstream and downstream of bridges. Data were obtained through multiple experiments in a rectangular laboratory flume with glass walls 9.5 m long, 0.6 m wide, and 0.6 m deep. Four different bridge models were placed at the 6th meter of the channel to determine the average velocities upstream and downstream. Different data-driven models were implemented with different combinations of effective parameters as input. They were evaluated and compared using root mean square error (RMSE), mean absolute relative error (MARE), and Nash–Sutcliffe efficiency (NSE). The results showed that the MARS had the best efficiency in estimating the mean velocity upstream of the bridge model. At the same time, the M5Tree provided the highest performance in estimating the mean velocity downstream. The MARS method improved the estimation accuracy of GPR, M5Tree, and MLR in the test phase by 23.8%, 45.1%, and 47.4% concerning the RMSE at the upstream. The M5Tree provided better RMSE accuracy of 31.8%, 70.4%, and 75.5% at the downstream compared to MARS, GPR, and MLR, respectively. The study recommends the MARS and M5Tree for estimating mean velocities upstream and downstream of the bridge.

Hybrid Iterative and Tree-Based Machine Learning Algorithms for Lake Water Level Forecasting - Elham Fijani; Khabat Khosravi (Water Resources Management, 2023)

Application of Copulas in Hydrometeorological Drought Risk Analysis Under Climate Change Scenarios- a Case Study - Jincy Rose M.A; Chithra N.R (Water Resources Management, 2023)

A Long-Term Operational Scheme for Hybrid Hydro-Photovoltaic (PV) Systems that Considers the Uncertainties in Reservoir Inflow and Solar Radiation Based on Scenario Trees - Han Cao; Jun Qiu; Hui-Min Zuo; Fang-Fang Li (Water Resources Management, 2023)

Simulation of Urban Flood Process Based on a Hybrid LSTM-SWMM Model - Chenchen Zhao; Chengshuai Liu; Wenzhong Li; Yehai Tang; Fan Yang; Yingying Xu; Liyu Quan; Caihong Hu (Water Resources Management, 2023)

Water-Saving Revenue Guarantee Optimization in Water Saving Management Contract Based on Simulation Method - Wei Li; Xiaosheng Wang; Ran Li (Water Resources Management, 2023)

The Influence of Industrial Pulling Effect on the Coordinated Development of China’s Water Resources and Economic System - Jingwei Zheng; Caizhi Sun (Water Resources Management, 2023)

Investigating the Effect of Spatial and Temporal Variabilities of Rainfall on Catchment Response - Pardis Ziaee; Mohammad Javad Abedini (Water Resources Management, 2023)

Rainwater and Greywater as Alternative Water Resources: Public Perception and Acceptability. Case Study in Twelve Countries in the World - Agnieszka Stec (Water Resources Management, 2023)
The aim of the paper was to identify factors that influence the public perception of the possibility of replacing tap water with rainwater or greywater. In order to check whether a geographical location and water resources of a region affect the public's attitude toward alternative water systems, the surveys were carried out among respondents from twelve countries. The surveys identified the level of awareness among respondents about their country's water resources, ways to save water at home, and their attitudes to rainwater and greywater as additional sources of water in a building. The results showed that only 39% of respondents would not be afraid to use treated greywater in their household. The situation was better in case of replacement of tap water with rainwater, where more than 54% of the respondents were not concerned. The use of alternative sources of water for body washing and cleaning works was the biggest concern among the respondents. In case of greywater recycling, this was indicated by 56% (personal hygiene) and 34% (cleaning works) of respondents. People in the countries with low water resources view alternative water sources more favourably. They are also more aware of, and more likely to accept the use of rainwater or greywater even in uses where they will come into contact with the human body. The research also showed that for more than 3/4 of respondents, funding to install these systems would encourage their use in their household.

Initial Investigation of Wave Interactions During Simultaneous Valve Closures in Hydraulic Piping Systems - Kamil Urbanowicz; Igor Haluch; Anton Bergant; Adam Deptuła; Paweł Śliwiński (Water Resources Management, 2023)
The effects of interference of pressure waves in simple piping systems were studied. A freeware computer code Allievi developed at the University of Valencia was used to simulate dynamic waveforms in simple and complex networks. The tests were carried out according to three scenarios. No pressure increases significantly exceeding the Joukowsky pressure in simple cases were noticed. When the effects of the simultaneous closing of three valves located at the three pressure reservoirs with pipes of the same diameter connected at "Y" junction were tested, it was shown that wave interference (between primary and reflected waves) is influenced strongly by the length of the analyzed pipes. Additionally, when a change of diameter was assumed at the "Y" junction, secondary waves appear, which are responsible for increased pressure in this type of the system (even when the lengths of the lines are identical). Water supply pipe systems are subject to cyclical loads and wave interference of similar types even during standard operations, that’s why the understanding of this issue is crucial to effectively protect the systems from the risk of possible cracks, bursts, and leaks.

Effects of Precipitation Concentration and Human Activities On City Runoff Changes - Cuimei Lv; Xinrui Wang; Minhua Ling; Wenjing Xu; Denghua Yan (Water Resources Management, 2023)

An Efficient Approach for Partitioning Water Distribution Networks Using Multi-Objective Optimization and Graph Theory - Mohammad Reza Shekofteh; Ehsan Yousefi-Khoshqalb; Kalyan R. Piratla (Water Resources Management, 2023)

Experimental Study of Variation Sediments and Effective Hydraulic Parameters on Scour Downstream of Stepped Spillway - Arman Dah-Mardeh; Gholamreza Azizyan; Mahmood Shafai Bejestan; Abbas Parsaie; Seyed Hossein Rajaei (Water Resources Management, 2023)

Importance of Aquitard Response Time for Groundwater Management in Multi-Aquifer Systems Subject to Land Subsidence - Juan José Díaz-Nigenda; Eric Morales-Casique; Mauricio Carrillo-García; Mario Alberto Vázquez-Peña; Oscar Escolero-Fuentes (Water Resources Management, 2023)
Groundwater management models have been widely applied to obtain optimal pumping strategies for land subsidence control, but most of them do not explicitly incorporate land subsidence variables (such as cumulative settlement and land subsidence rates) within the model constraints and neglect the transient effect due to aquitard storage. Here, three operating scenarios of a hypothetical multi-aquifer system, which include a highly compressible aquitard, were implemented with the aim of evaluating land subsidence and identifying management schemes with the support of an optimization model for groundwater management. In a 50-year management period, maximizing pumping while restricting drawdown to 10 m after year 25 stabilizes groundwater levels within the aquifer, but land subsidence continues to reach 4.8 m at year 50. The effect of reducing pumping rates and how early in the management period this is implemented is also analyzed. Restricting the pumping rate as early as year 6 leads to reduced land subsidence at year 50 by 17%. If pumping reduction is delayed, larger land subsidence rates occurred in the system (7.9, 8.3 and 9.6 cm/year in the tested cases); however, if the total settlement is evaluated as a proportion of the thickness of the aquitard, values of the order of 10% are presented. Our results highlight the importance of timely decisions for groundwater management based on the response time of the aquitards in multi-aquifer systems.

Integration of Three Standardized Drought Indices utilizing Modified Triple Collocation and Scaled Triple Collocation relative to Triple Collocation - Zanib Badar; Mohammed M. A. Almazah; Ijaz Hussain; Fuad S. Al-Duais; A. Y. Al-Rezami; Muhammad Sulaman Ijaz (Water Resources Management, 2023)

Flood Subsidence Susceptibility Mapping using Elastic-net Classifier: New Approach - Ahmed M. Al-Areeq; S. I. Abba; Bijay Halder; Iman Ahmadianfar; Salim Heddam; Vahdettin Demir; Huseyin Cagan Kilinc; Aitazaz Ahsan Farooque; Mou Leong Tan; Zaher Mundher Yaseen (Water Resources Management, 2023)

Identification of Best CMIP6 Global Climate Model for Rainfall by Ensemble Implementation of MCDM Methods and Statistical Inference - Gaurav Patel; Subhasish Das; Rajib Das (Water Resources Management, 2023)

Drought Risk Assessment for Surface Water Distribution Systems in Irrigation Districts - Javad Pourmahmoud; Seied Mehdy Hashemy Shahdany; Abbas Roozbahani (Water Resources Management, 2023)

Assessment of XGBoost to Estimate Total Sediment Loads in Rivers - Reza Piraei; Seied Hosein Afzali; Majid Niazkar (Water Resources Management, 2023)

Modeling Hydrological Responses of Watershed Under Climate Change Scenarios Using Machine Learning Techniques - Keivan Karimizadeh; Jaeeung Yi (Water Resources Management, 2023)

Urban Water Consumption Prediction Based on CPMBNIP - Jun Li; Songbai Song (Water Resources Management, 2023)

Three-Dimensional Numerical Simulation Research on Discharge Characteristics of Storm-Drain Inlet in Low-Lying Areas - Ke Zhang; Jiake Li; Lizhong Ning; Weifeng Xie; Yafang Li; Zakir ullah; Kai Peng (Water Resources Management, 2023)

Rainfall Assessment and Water Harvesting Potential in an Urban area for Artificial Groundwater Recharge with Land Use and Land Cover Approach - Ali Reza Noori; S.K. Singh (Water Resources Management, 2023)

Global Sustainable Water Management: A Systematic Qualitative Review - Nuru Hasan; Raji Pushpalatha; V. S. Manivasagam; Sudha Arlikatti; Raj Cibin (Water Resources Management, 2023)

Simultaneous Optimization of SWMM Parameters by the Dynamic System Response Curve with Multi-Objective Function - Yao Du; Qiongfang Li; Pengfei He; Zhenhua Zou; Zhengmo Zhou; Shuhong Xu; Xingye Han; Tianshan Zeng (Water Resources Management, 2023)

Optimization of Roof Coverage and Tank Size for Integrated Green Roof Rainwater Harvesting Systems-a Case Study - Haowen Xie; Mark Randall; Sylvana Melo dos Santos (Water Resources Management, 2023)

Interannual Variabilities in the Onset and Demise of Rainy Season: Implications for Water Management - Yuannan Long; Moruo Zheng; Huaiguang He; Shixiong Yan (Water Resources Management, 2023)

Optimal Placement and Settings of Valves for Leakage Reduction in Real Life Water Distribution Networks - Tamás Huzsvár; Richárd Wéber; Marcell Szabó; Csaba Hős (Water Resources Management, 2023)
Nowadays, the rapid growth of operational costs and human resource shortages increase the importance of the leakage reduction, and the pressure management. This paper presents an optimisation procedure placing pressure-reducing valves (PRVs) to minimise the water losses of real-life water distribution networks (WDNs). The number and placement of the valves are optimised from clustering perspective with the Leiden algorithm. The optimal settings of the valves are determined with a differential evolution algorithm, where a compound fitness function is applied. On the one hand, it minimises the leakages, on the other hand, evades the pressure-dependent consumer outages, i.e. it keeps the pressure above the desired. Seven real-life water distribution networks were analysed from the region of Western Hungary using the techniques. Moreover, three of them are analysed in details. The robustness of the achieved leakage reduction with the optimised PRV placement is analysed to the uncertainty of the leakage exponent.

Assessment and Analysis of Crop Irrigation by the Combination of Modelling and Remote Sensing Techniques - Fabio Maselli; Luca Fibbi; Bernardo Rapi; Luca Angeli; Piero Battista; Marta Chiesi; Bernardo Gozzini (Water Resources Management, 2023)

Estimation of Unconfined Aquifer Transmissivity Using a Comparative Study of Machine Learning Models - Zahra Dashti; Mohammad Nakhaei; Meysam Vadiati; Gholam Hossein Karami; Ozgur Kisi (Water Resources Management, 2023)

An Uncertainty-Based Random Boundary Interval Multi-Stage Stochastic Programming for Water Resources Planning - Mehri Raei; Javad Hossienzad; Mohammad Ali Ghorbani (Water Resources Management, 2023)

A Comparative Study on Forecasting of Long-term Daily Streamflow using ANN, ANFIS, BiLSTM and CNN-GRU-LSTM - Sajjad M. Vatanchi; Hossein Etemadfard; Mahmoud F. Maghrebi; Rouzbeh Shad (Water Resources Management, 2023)

Univariate and Bivariate Hydrological Drought Frequency Analysis by Copula Functions - Ibrahim Halil Deger; Musa Esıt; Mehmet Ishak Yuce (Water Resources Management, 2023)

A Hybrid Model Combining the Cama-Flood Model and Deep Learning Methods for Streamflow Prediction - Ming Zhong; Hongrui Zhang; Tao Jiang; Jun Guo; Jinxin Zhu; Dagang Wang; Xiaohong Chen (Water Resources Management, 2023)

A Common Factor Analysis Based Data Mining Procedure for Effective Assessment of 21st Century Drought under Multiple Global Climate Models - Muhammad Ahmad; Zulfiqar Ali; Maryam Ilyas; Muhammad Mohsin; Rizwan Niaz (Water Resources Management, 2023)

Novel Hybrid Machine Learning Algorithms for Lakes Evaporation and Power Production using Floating Semitransparent Polymer Solar Cells - Ismail Abd-Elaty; N. L. Kushwaha; Abhishek Patel (Water Resources Management, 2023)
The present study predicts the future evaporation losses by applying novel hybrid Machine Learning Algorithms (MLA). Water resources management is achieved by covering the reservoir water surface with floating semitransparent polymer solar cells. The energy produced by these panels will be used in the irrigation activities. The study is applied for the mass water body of Nasser Lake, Egypt and Sudan. Five MLAs namely additive regression (AR), AR-random subspace (AR-RSS), AR-M5Pruned (AR-M5P), AR-reduced error pruning tree (AR-REPTree), and AR- support vector machine (AR-SVM) were developed and evaluated for predicting future evaporation losses in the years 2030, 2050, and 2070. The study concludes that the hybrid AR-M5P ML model was not only superior to the AR model alone but also outperformed other hybrid models such as AR-RSS and AR-REPTree. The expected total annual water saving are projected to reach 3.47 billion cubic meters (BCM), 3.68 and 3.90 BCM, while the total annual power production is observed to be 1389 × 10 9 Megawatt (MW), 1535 × 10 9 MW and 1795 × 10 9 MW in the years 2030, 2050 and 2070, respectively. These results were achieved by covering the shallow water depths from contour level 0 m to 10 m below the surface water level. Additionally, this study shows the ability of using MLAs in the estimation of reservoir evaporation and addressing the water shortages in high stress regions. Graphical Abstract

A Novel Compromise Approach for Risk-Based Selective Water Withdrawal from Reservoirs Considering Qualitative-Quantitative Aspects - Sadegh Vanda; Mohammad Reza Nikoo; Narges Taravatrooy; Ghazi Ali Al-Rawas; Seyed M. K. Sadr; Fayyaz A. Memon; Banafsheh Nematollahi (Water Resources Management, 2023)

A Complementary Streamflow Attribution Framework Coupled Climate, Vegetation and Water Withdrawal - Shanhu Jiang; Yongwei Zhu; Liliang Ren; Denghua Yan; Ying Liu; Hao Cui; Menghao Wang; Chong-Yu Xu (Water Resources Management, 2023)

A Real Time Optimization Based Sequential Convex Program for Pressure Management in Water Distribution Systems - Pham Duc Dai (Water Resources Management, 2023)

Influence of Various Accessories Upstream Large Water Meters - Iñigo Albaina; Iñigo Bidaguren; Urko Izquierdo; G. A. Esteban (Water Resources Management, 2023)
The focus of this study is on large flow meters, for which there is limited information due to their large size, making testing and research challenging. This research was conducted to quantify the effects of various accessories located upstream of these meters. Even a small percentage of variation in error can correspond to a significant volume of water. Accurate meters are crucial in many applications that involve large volumes of water as precise flow measurements are necessary for smooth and efficient processes while avoiding costly errors and downtime. Inaccurate large water meters can have far-reaching implications, such as overbilling or underbilling and production inefficiencies, which result in wasted resources and energy. Furthermore, inaccurate flow measurements can lead to environmental consequences as industries must comply with strict regulations regarding wastewater discharge limits. Uncertainty about the economic impact of an accessory installed upstream of a medium-sized water meter leads many water utilities to oversize the meter chambers to mitigate potential negative errors. In this study, six types of elements were tested upstream of ten brand-new water meters from six different manufacturers, constructed using four different metering technologies: single-jet, Woltmann, electromagnetic, and ultrasonic. Each meter unit was tested at five flow rates, ranging from the minimum to overload. The tests were conducted with accessories set in different orientations and distances upstream of the water meters under study. The research shows that the accessories used can cause significant deviations in measuring errors compared to the regular errors found under undisturbed working conditions.

Development of a Comprehensive Water Simulation Model for Water, Food, and Energy Nexus Analysis in Basin Scale - Elham Soleimanian; Abbas Afshar; Amir Molajou; Mahdi Ghasemi (Water Resources Management, 2023)

Ecological Risk Identification and Ecological Security Pattern Construction of Productive Wetland Landscape - Lihua Chen; Yuan Ma (Water Resources Management, 2023)

A Decision Making Approach for Water Transfer Systems by Analytical Hierarchy Process (AHP) and GIS - Homayoun Motiee; Reza khalili; Behrooz Gholami; Soroush Motiee (Water Resources Management, 2023)

Farm-level Hydroeconomic Analysis of Alternative Water Tariff Charges Using a Hybrid Solution Method - Bennie Grové; Johannes Jacobus Bezuidenhout; Nicolette Matthews (Water Resources Management, 2023)
This paper's main objective is to develop a farm-level water programming model to realistically model extensive margin and intensive margin responses resulting from deficit irrigation to the implementation of volumetric water charges. The highly complex programming model that uses the FAO56 water budget calculations to simulate crop water use while using relative evapotranspiration to estimate crop yield is solved using a hybrid procedure. The hybrid solution procedure uses a genetic algorithm to simplify the optimization model by fixing the irrigation schedule of each crop and then solving for the optimal water allocation amongst crops subject to water constraints. The area-based charges results showed that when irrigation application efficiency is low, irrigators could apply more water per hectare to sustain high crop yields without being held accountable if water quotas are exceeded. In contrast, irrigators with higher application efficiency could use less water than the area-based estimated water use. The results also showed that volumetric water charges cause both intensive margin and extensive margin responses. The conclusion of whether a volumetric-based water charging system will be better than area-based water charges is not straightforward because of differentiated impacts on profitability and hydrology. While irrigators will use irrigation water more efficiently and adopt more efficient irrigation technologies, their changed behavior could impact the hydrology of the water system through reduced return flows.

Energy Recovery Optimization by Means of a Turbine in a Pressure Regulation Node of a Real Water Network Through a Data-Driven Digital Twin - Marco Sinagra; Enrico Creaco; Gabriele Morreale; Tullio Tucciarelli (Water Resources Management, 2023)
In recent years, various devices have been proposed for pressure regulation and energy recovery in water distribution and transport networks. To provide a real net benefit, they require a dedicated long-distance management system in order to carry on both hydraulic regulation and electricity production without direct human manual operations. This work presents a new proposal for the management of a pressure regulation system based on the PRS turbine. The proposal is applied to a real water distribution network, named Montescuro Ovest pipeline, at the San Giovannello station. The Real Time Control (RTC) logic currently applied at San Giovannello station is first presented and discussed. A new Advanced Real Time Control (ARTC) logic is then proposed, based on direct configuration of the turbine and the surrounding valves as computed by the solution of an optimization problem. In ARTC a digital twin, including the hydraulic model of the surrounding network, provides a one-to-one relationship between the configuration parameters and the state variables, i.e. flow rates and pressures. The digital twin model equations are continuously updated on the basis of the recorded measures. Besides providing almost identical performance to the current RTC logic in the current operational scenario, the improved ARTC is more robust, in that it guarantees better hydropower generation in modified operational scenarios, as shown in specific tests. The proposed methodology constitutes a new approach to regulating the valves in hydroelectric plants which are currently regulated with traditional automation algorithms.

Runoff Forecasting of Machine Learning Model Based on Selective Ensemble - Shuai Liu; Hui Qin; Guanjun Liu; Yang Xu; Xin Zhu; Xinliang Qi (Water Resources Management, 2023)

Short-term Prediction Method of Reservoir Downstream Water Level Under Complicated Hydraulic Influence - Jingwei Huang; Hui Qin; Yongchuan Zhang; Dongkai Hou; Sipeng Zhu; Pingan Ren (Water Resources Management, 2023)

Modelling Stormwater Runoff Changes Induced by Ground-Mounted Photovoltaic Solar Parks: A Conceptualization in EPA-SWMM - Aurora Gullotta; Tagele Mossie Aschale; David J. Peres; Guido Sciuto; Antonino Cancelliere (Water Resources Management, 2023)
A modelling framework for the simulation of stormwater runoff in ground-mounted photovoltaic solar parks is proposed. Elements in the solar park and their mutual interactions during precipitation events are conceptualized in EPA-SWMM. We demonstrate the potential of the framework by exploring how different factors influence runoff formation. Specifically, we carry out simulations for different sizes of the installation, soil types and input hyetographs. We also show the effect of ground cover, by changing the surface roughness. Outflow discharge from the park is compared to that from a reference catchment to evaluate variations of peak flow and runoff volume. Results highlight no practical changes in runoff in the short term after installation. However, in the long term, modifications in soil cover may lead to some potential increase of runoff. For instance, increments of the peak flow from the solar park up to 21% and 35% are obtained for roughness coefficient reductions of 10% and 20%, respectively. The proposed modelling approach can be beneficial for studying hydrological impacts of solar parks and thus for planning measures for their mitigation.

The Dynamics of the Relationship Between Water Availability, Water Equity, Economic Benefits and Water User Associations’ Performance: A PLS-SEM Approach - Mohsin Riaz; Muhammad Ashfaq; Ismet Boz; Pomi Shahbaz (Water Resources Management, 2023)

Handling Large Decision Variables in Multi-Objective Groundwater Optimization Problems: Aquifer Parameter-Based Clustering Approach - Shreyansh Mishra; Lilian Bosc; Shishir Gaur; Mariem Kacem; Anurag Ohri (Water Resources Management, 2023)

Experimental Exploration of Flow Hydraulics and Discharge Coefficient for an Inclined Circular Labyrinth Weir - Hossain Zare; Mohammad Vaghefi; Amin Mahmoudi; Abdol Mahdi Behroozi (Water Resources Management, 2023)

Analysing the Impact of Land Subsidence on the Flooding Risk: Evaluation Through InSAR and Modelling - María I. Navarro-Hernández; Javier Valdes-Abellan; Roberto Tomás; Serena Tessitore; Pablo Ezquerro; Gerardo Herrera (Water Resources Management, 2023)
Floods greatly impact human settlements in flood risk areas, such as floodplains and coastal lowlands, following heavy rainfall. The Alto Guadalentin valley, an orogenic tectonic depression, experiences extreme flash floods and land subsidence due to groundwater withdrawal, rendering it one of Europe's fastest subsiding regions. In this study, we compared two 2D flood event models representing different land subsidence scenarios for 1992 and 2016. To determine the flooded area and water depth variations due to land subsidence, the Hydrologic Engineering Centre River Analysis System 2D (HEC-RAS 2D) model was used to simulate flood inundation by the Alto Guadalentin River and its tributaries. Synthetic aperture radar (SAR) satellite (ERS, ENVISAT, and Cosmo-SkyMED) images were employed, along with the interferometric SAR (InSAR) technique, to calculate the magnitude and spatial distribution of land subsidence. By analysing the accumulated subsidence distributions obtained from InSAR, the original topography of the valley in 1992 and 2016 was reconstructed. These digital surface models (DSMs) were then used to generate 2D hydraulic models, simulating flood scenarios in the unsteady mode. The results demonstrated significant changes in the water surface elevation over the 14-year period, with a 2.04 km2 increase in areas with water depths exceeding 0.7 m. These findings were utilized to create a flood risk map and assess the economic flood risk. The data highlight the crucial role of land subsidence in determining the inundation risk in the Alto Guadalentin valley, providing valuable insights for emergency management and civil protection against future potential flooding events.

Energy Dissipation Potentials of Grouped Spur Dikes in an Open Channel - Ali Emre Ulu; M. Cihan Aydin; Fevzi Önen (Water Resources Management, 2023)

Farmers’ Water Poverty Measurement and Analysis of Endogenous Drivers - Jinlong Shen; Jiafen Li; Yu Zhang; Jianfeng Song (Water Resources Management, 2023)

Application of Multi-Criteria Decision-Making of CODAS and SWARA in Reservoir Optimal Operation Using Marine Predator Algorithm Based on Game Theory - Parisa-Sadat Ashofteh; Shirin Moradi Far; Parvin Golfam (Water Resources Management, 2023)

Development of the Multi-Objective Invasive Weed Optimization Algorithm in the Integrated Water Resources Allocation Problem - Mahdieh Kalhori; Parisa-Sadat Ashofteh; Seyedeh Hadis Moghadam (Water Resources Management, 2023)

Ensemble Learning Paradigms for Flow Rate Prediction Boosting - Kouao Laurent Kouadio; Jianxin Liu; Serge Kouamelan Kouamelan; Rong Liu (Water Resources Management, 2023)

Drought Assessment Using Gridded Data Sources in Data-Poor Areas with Different Aridity Conditions - Milad Nouri (Water Resources Management, 2023)

A Novel Smoothing-Based Deep Learning Time-Series Approach for Daily Suspended Sediment Load Prediction - Bibhuti Bhusan Sahoo; Sovan Sankalp; Ozgur Kisi (Water Resources Management, 2023)

Climate Change Impacts on Rainwater Tank’s Potential Water Savings, Efficiency and Reliability Presenting Relationship Between ‘Seasonality Index’ and Water Savings Efficiency - Monzur A. Imteaz; Mohammad S. Khan; Abdullah G. Yilmaz; Abdallah Shanableh (Water Resources Management, 2023)
The paper presents potential impacts of climate change on rainwater tanks outcomes such as water savings, reliability and water savings efficiency under two projected climate change scenarios; RCP4.5 and RCP8.5 utilising a case study using rainfall data from four stations within the city of Brisbane, Australia. Historical rainfall data were collected from the Australian Bureau of Meteorology website for the selected stations. Projected daily rainfall data were collected from Australian government data portal for the same stations within Brisbane. Using an earlier developed daily water balance model, eTank potential annual water savings were calculated for several weather and climate change scenarios with varied roof areas and rainwater demandValues of ‘Seasonality Index (SI)’, a commonly used factor representing rainfall variability within a year, were explored to validate earlier developed relationships between SI and water savings efficiency through rainwater tanks. It is found that in most cases water savings in future periods are expected to decrease and such decrease is not necessarily attributed to the expected decrease in rainfall amounts in future, rather also affected by future reductions in rainwater tank reliability. Linear relationships between potential future water savings and reliabilities for all the stations are found. Relationship between SI and water savings efficiency was established, and it is found that the relationship slightly varies with an earlier developed relationship using historical data. Compared to earlier established relationship, for lower SI values water savings efficiency is expected to become better, while for higher SI values the water savings efficiency is expected to become worse. Also, an increase of roof area from 100 m 2 to 200 m 2 will cause an average increase of water savings efficiency by 25% and an increase of rainwater usage from 200 L/day to 300 L/day will cause an average increase of water savings efficiency by 20%.

On the Role of Hydrological Losses in Estimating Event Runoff Coefficients Using the NRCS Method - Zahra Eslami; Khodayar Abdollahi; Ataollah Ebrahimi‬ (Water Resources Management, 2023)

Improved Treatment of Model Prediction Uncertainty: Estimating Rainfall using Discrete Wavelet Transform and Principal Component Analysis - Mahrouz Nourali (Water Resources Management, 2023)

Dam Health Diagnosis Model Based on Cumulative Distribution Function - Zhenxiang Jiang; Bo Wu; Hui Chen (Water Resources Management, 2023)

Impact of Institutional Pressures on Socially Responsible Collective Action Behaviors for Major Water Transfer Projects - Wujuan Zhai; Florence Yean Yng Ling; Jiyong Ding; Zhuofu Wang (Water Resources Management, 2023)

Retraction Note: Predicting the Impacts of Optimal Residential Development Scenario on Soil Loss Caused by Surface Runoff and Raindrops Using TOPSIS and WetSpa Models - Mahtab Forootan Danesh; Mohammad Reza Dahmardeh Ghaleno; Ehsan Alvandi; Sarita Gajbhiye Meshram; Ercan Kahya (Water Resources Management, 2023)

Comparative Analyses on Disaggregation Methods for the Rainfall Projection - Wan Amirul Syahmi Wan Mazlan; Nurul Nadrah Aqilah Tukimat (Water Resources Management, 2023)

An Alternative Approach for Computing the Standardized Precipitation-Evapotranspiration Index (SPEI) - Tayeb Raziei; Morteza Miri (Water Resources Management, 2023)

Assessment of Crop-Drought Relationship: A Climate Change Perspective - Soumyashree Dixit; V. Neethin; K. V. Jayakumar (Water Resources Management, 2023)

Efficient Segmentation Algorithm for Estimation of Revised Reservoir Capacities in Google Earth Engine - Rahul Kumar Jaiswal; Gunja Dhruw; Sukant Jain; Ravi V. Galkate; Anil Kumar Lohani; Akhilesh Verma (Water Resources Management, 2023)

Assessing the Impact of Land-Use Dynamics to Predict the Changes in Hydrological Variables Using Effective Impervious Area (EIA) - Akanksha Balha; Amit Singh; Suneel Pandey; Reetesh Kumar; Javed Mallick; Chander Kumar Singh (Water Resources Management, 2023)

Evaluation of an Adaptation Strategy for Flood Damage Mitigation Under Climate Change Through the Use of Irrigation Reservoirs in Japan - Atsuya Ikemoto; So Kazama; Takeo Yoshida; Hayata Yanagihara (Water Resources Management, 2023)
This study performed flood analysis, considering the water storage of irrigation reservoirs, to realize flood control by reservoirs, which are traditional irrigation facilities. The effect on flood control was determined through flood analysis performed by varying the reservoir storage rates. Based on the flood analysis results, Japan’s flood damage costs were estimated. Using three Shared Socioeconomic Pathways (SSPs) (SSP1-2.6, SSP2-4.5, and SSP5-8.5), we evaluated the flood control potential of reservoirs under future climate conditions. When the reservoirs were empty, the damage cost reduction rate resulting from the use of reservoirs across Japan was small, ranging from 1.1% to 2.3%, but as the damage cost reduction rate did not change under all future scenarios, reductions in flood damage were not affected by changes in rainfall under future climate conditions. Moreover, some prefectures showed high damage cost reduction effects. In northern part of Japan and numerous prefectures in western Japan, the potential to reduce damage through flood control by irrigation reservoirs was high. Some prefectures experienced similar reduction levels as those under alternative adaptation strategies. In the Kanto region, flood control by irrigation reservoirs had low potential for reducing damages. Even among prefectures with low water storage capacities of irrigation reservoirs, the potential to mitigate the effect of damage was high.

Promoting Climate Resilient Sustainable Agriculture Through Participatory System Dynamics with Crop-Water-Income Dynamics - Ravi Gorripati; Mainak Thakur; Nagesh Kolagani (Water Resources Management, 2023)

Monthly River Discharge Forecasting Using Hybrid Models Based on Extreme Gradient Boosting Coupled with Wavelet Theory and Lévy–Jaya Optimization Algorithm - Jincheng Zhou; Dan Wang; Shahab S. Band; Changhyun Jun; Sayed M. Bateni; M. Moslehpour; Hao-Ting Pai; Chung-Chian Hsu; Rasoul Ameri (Water Resources Management, 2023)

Adoption and shift of water-saving strategies to policy shock: based on social-ecological system analysis - Linjing Ren; Xiaojun Yang (Water Resources Management, 2023)

Classification and applicable conditions of water rights systems - Yuanyuan Sun; Shaofeng Jia; Ru Jia (Water Resources Management, 2023)

Artificial Roughness Dimensions and their Influence on Bed Topography Variations Downstream of a Culvert: An Experimental Study - Mohammad Sadeghpour; Mohammad Vaghefi; Seyed Hamed Meraji (Water Resources Management, 2023)

Modeling Future Hydrological Characteristics Based on Land Use/Land Cover and Climate Changes Using the SWAT Model - Maryam Abbaszadeh; Ommolbanin Bazrafshan; Rasool Mahdavi; Elham Rafiei Sardooi; Sajad Jamshidi (Water Resources Management, 2023)

What Socio-Technical and Institutional Determinants Explain the Farm-Level Economic Divergence? - Muhammad Arfan; Kamran Ansari; Asmat Ullah (Water Resources Management, 2023)

A Hybrid CNN-LSTM Approach for Monthly Reservoir Inflow Forecasting - S. Khorram; N. Jehbez (Water Resources Management, 2023)

An Improved Fineness Flood Risk Analysis Method Based on Digital Terrain Acquisition - Yichao Xu; Xinying Wang; Zhiqiang Jiang; Yi Liu; Li Zhang; Yukun Li (Water Resources Management, 2023)

Improving Hybrid Models for Precipitation Forecasting by Combining Nonlinear Machine Learning Methods - Laleh Parviz; Kabir Rasouli; Ali Torabi Haghighi (Water Resources Management, 2023)
Precipitation forecast is key for water resources management in semi-arid climates. The traditional hybrid models simulate linear and nonlinear components of precipitation series separately. But they do not still provide accurate forecasts. This research aims to improve hybrid models by using an ensemble of linear and nonlinear models. Preprocessing configurations and each of the Gene Expression Programming (GEP), Support Vector Regression (SVR), and Group Method of Data Handling (GMDH) models were used as in the traditional hybrid models. They were compared against the proposed hybrid models with a combination of all these three models. The performance of the hybrid models was improved by different methods. Two weather stations of Tabriz and Rasht in Iran with respectively annual and monthly time steps were selected to test the improved models. The results showed that Theil’s coefficient, which measures the inequality degree to which forecasts differ from observations, improved by 9% and 15% for SVR and GMDH relative to GEP for the Tabriz station. The applied error criteria indicated that the proposed hybrid models have a better representation of observations than the traditional hybrid models. Mean square error decreased by 67% and Nash Sutcliffe increased by 5% in the Rasht station when we combined the three machine learning models using genetic algorithm instead of SVR. Generally, the representation of the nonlinear models within the improved hybrid models showed better performance than the traditional hybrid models. The improved models have implications for modeling highly nonlinear systems using the full advantages of machine learning methods.

River Flow Modeling in Semi-Arid and Humid Regions Using an Integrated Method Based on LARS-WG and LSTM Models - Kiyoumars Roushangar; Sadegh Abdelzad (Water Resources Management, 2023)

Three-Dimensional Numerical Study of Dam-Break Flood Impacting Problem with VOF Method and Different Turbulence Closures - Ling Peng; Ting Zhang; Jianzhu Li; Ping Feng (Water Resources Management, 2023)

Addressing Water Meter Inaccuracies Caused By Intermittent Water Supply: A Laboratory Investigation of Remedial Measures - Marco Ferrante; Dewi Rogers; Josses Mugabi; Francesco Casinini (Water Resources Management, 2023)
The interruption of supply in water distribution systems is a common management practice particularly prevalent in developing countries. Upon reopening, the air is expelled through user service pipes, which causes over-reading and seriously impacts the water meter reliability. This paper aims to assess by laboratory tests the effects of air flow on water meter performance by laboratory tests, using a set-up with diameters comparable to those of real water systems. The improvements introduced by applying unmeasured-flow reducer and air valves at different locations are also tested. The relevance of the results of the laboratory activity for practical applications is discussed, both for reducing the over-reading and improving the reliability of the water meters.

Assessing Sustainable Development of Deep Aquifers - Annette Dietmaier; Thomas Baumann (Water Resources Management, 2023)
Deep groundwater aquifers are exploited for a variety of purposes. In general, impermeable rock layers protect these aquifers from anthropogenic influences. As such, they are a last resort for groundwater in a pre-industrial state, and a crucial resource in cases of emergency, such as floods contaminating shallow groundwater. The EU Water Framework Directive (WFD) provides the regulatory framework to protect its quality and quantity. Recent monitoring of the hydrochemical state of Upper Jurassic wells in Bavaria and Austria has shown fluctuations that were connected to new exploitation activities and might indicate an unsustainable development of the aquifer. We propose a new workflow in accordance with the WFD which uses clustering algorithms to assess these fluctuations. Our data consists of 5 to 42 hydrochemical analyses per well with yearly sampling intervals spanning up to 30 years. From the cluster analysis we derived thresholds for two corridors: Natural Range Corridor (NC) and Action Corridor (AC). While the NC represents a well-specific natural variation range, the AC hints towards unsustainable development and should trigger a detailed (re)assessment. To show the potential of the new method, the workflow was applied to two wells with different geological characteristics. Distinct fluctuation events were clearly recognized and can be used in the context of an early warning system, such that malign hydrochemical variations can be detected before they become legally problematic to well operators. Our workflow thus provides a novel, robust, and reproducible method to assess the grade of sustainability at which a well is exploited and ensures a good status of a unique and important resource.

Hybrid Decentralized Systems of Non-potable Water Supply: Performance and Effectiveness Analysis - A Ferreira; C. Santos; M. A. Imteaz; C. Matos (Water Resources Management, 2023)
This article presents a study of Hybrid Rainwater/Greywater Systems (HRGS), with the objective of perceiving the main factors that influence their performance and how they can be optimized. For this goal, a decision support tool, that makes their dimensioning and performs an economic and performance analysis, was used for four different types of buildings: a single-family house, a multifamily building and two service buildings. For each case, distinct scenarios were defined, considering different end-uses of non-potable water, in order to evaluate the performance of the systems using effectiveness and performance indicators. Results show that the effectiveness of “non-potable water consumption” is influenced by two main factors: the final uses considered for non-potable water and the storage volume. In most of the study cases, values of effectiveness (ratio between the volume of non-potable water used and non-potable water demand for the final uses considered) greater than 50% were obtained. In the case of domestic buildings, such as single-family house and multifamily building effectiveness values above 67%, were obtained. And for the case of service buildings, the effectiveness was between 42.8 and 65.6% in one case, and between 12.9 and 93.6% for the other. The best performance of the studied hybrid systems is achieved when the volume of non-potable water used in the building is maximized, resulting in greater savings of potable water. In addition, the larger the fraction of greywater reused, the lower the volume of wastewater produced and sent directly to the sanitation network.

Correction to: Optimization of Meteorological Monitoring Network of New South Wales, Australia - Shahid Khan; Mohammed M. A. Almazah; Ataur Rahman; Ijaz Hussain (Water Resources Management, 2023)

Integrated SUSTAIN-SWMM-MCDM Approach for Optimal Selection of LID Practices in Urban Stormwater Systems - Amirhossein Nazari; Abbas Roozbahani; Seied Mehdy Hashemy Shahdany (Water Resources Management, 2023)
Rapid urbanization has increased impervious areas, leading to a higher flood hazard across cities worldwide. Low Impact Development (LID) practices have shown efficacy in reducing urban runoff; nevertheless, choosing the best combinations in terms of implementation cost and performance is of great importance. The present study introduces a framework based on green infrastructure, multi-objective optimization, and decision support tools to determine the most cost-effective LID solutions. The Storm Water Management Model (SWMM) was employed for rainfall-runoff and hydraulic modeling in Region 1, District 11 of Tehran, Iran. Six scenarios of different combinations of LID practices were developed. The system for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) was used to optimize and evaluate each scenario. The selected solutions were imported to the SWMM to evaluate the stormwater system performance. Then, two multi criteria decision making (MCDM) models, including TOPSIS and COPRAS, were employed to rank the scenarios based on four technical and economic criteria. Results showed that scenario 4, consisting of rain barrels, porous pavements, and vegetated swales, had the best performance under TOPSIS with a 7.68 million USD and reduced the runoff volume and peak flow by 20.77% and 19.2%, respectively. However, Under the COPRAS method, Scenario 2 with a combination of rain barrels, bio-retention cells, and vegetated swales showed higher performance than the other scenarios with 3.25 million USD and led to a 15% reduction in the runoff volume and 4.30% in the peak flow. The COPRAS method was more sensitive to cost weights and chose the most economical scenario as the ideal. However, Scenario 4 concluded to be more feasible due to spatial limitations in the study area. The proposed SWMM—SUSTAIN—MCDM framework could be helpful to decision-makers in the design, performance evaluation, cost estimation, and selection of optimal scenarios.

A Comprehensive Experimental and Computational Investigation on Estimation of Scour Depth at Bridge Abutment: Emerging Ensemble Intelligent Systems - Manish Pandey; Masoud Karbasi; Mehdi Jamei; Anurag Malik; Jaan H. Pu (Water Resources Management, 2023)

Convolutional Neural Network for Burst Detection in Smart Water Distribution Systems - Sanghoon Jun; Kevin E. Lansey (Water Resources Management, 2023)

Convolutional Neural Network -Support Vector Machine Model-Gaussian Process Regression: A New Machine Model for Predicting Monthly and Daily Rainfall - Mohammad Ehteram; Ali Najah Ahmed; Zohreh Sheikh Khozani; Ahmed El-Shafie (Water Resources Management, 2023)

Predicting Hydropower Production Using Deep Learning CNN-ANN Hybridized with Gaussian Process Regression and Salp Algorithm - Mohammad Ehtearm; Hossein Ghayoumi Zadeh; Akram Seifi; Ali Fayazi; Majid Dehghani (Water Resources Management, 2023)

Daily Scale River Flow Forecasting Using Hybrid Gradient Boosting Model with Genetic Algorithm Optimization - Huseyin Cagan Kilinc; Iman Ahmadianfar; Vahdettin Demir; Salim Heddam; Ahmed M. Al-Areeq; Sani I. Abba; Mou Leong Tan; Bijay Halder; Haydar Abdulameer Marhoon; Zaher Mundher Yaseen (Water Resources Management, 2023)

Numerical Investigation of Modified Semi-Cylindrical Weirs - Ehsan Afaridegan; Nosratollah Amanian; AmirHamzeh Haghiabi; Abbas Parsaie; Alireza Goodarzi-Mohammadi (Water Resources Management, 2023)

Study on Reservoir Operation Model Based on Ecological Flow Calculation - Guanjun Lei; Junxian Yin; Wenchuan Wang; Changshun Liu; Hao Wang (Water Resources Management, 2023)

Two-Stage and Three-Party Transboundary Watershed Management Based on Valuation Adjustment Mechanism (VAM) Agreement - Jingxin Gao; Changzan Duan; Jinbo Song; Xianrui Ma; Yuanping Wang (Water Resources Management, 2023)

Bi-Attempted Base Optimization Algorithm on Optimization of Hydrosystems - Burhan Yildiz; Mehtap Kose Ulukok; Vali Bashiry (Water Resources Management, 2023)

Assessing the Anthropogenic and Climatic Components in Runoff Changes of the São Francisco River Catchment - Larissa S. Melo; Veber A. F. Costa; Wilson S. Fernandes (Water Resources Management, 2023)

Investigation of the Different Models of Elliptical-Lopac Gate Performance under Submerged Flow Conditions - Ashkan Pilbala; Mahmood Shafai Bejestan; Seyed Mohsen Sajjadi; Luigi Fraccarollo (Water Resources Management, 2023)
The effect of the elliptic ratio on the hydraulic performance of the LOPAC gate has been investigated using experimental and Computational Fluid Dynamics $$CFD$$ CFD simulations (Flow- $$3D$$ 3 D Hydro). Experiments and simulations were carried out at three different flow discharges, three different submerged ratios, and five different elliptic ratios. In this context, the $$CFD$$ CFD model was first calibrated and verified using the measured data, and then $$CFD$$ CFD simulation was performed. The ratio of upstream/downstream flow depth, the flow discharge coefficient, and the energy dissipation through the gate have been calculated and analyzed, and the three-dimensional features of the flow have been described. Based on the results, the elliptical LOPAC gates with circular weirs determine extreme values of the controlled flow parameters. Asymmetric recirculation downstream of the gate is sometimes observed in the model predictions. The use of Coriolis coefficients relevant to the entire cross-section, here deployed just for the circular and the traditional rectangular Lopac gates, has allowed a concise way to report and compare complex flows for any experimental condition.

Prediction of Hydrological Drought in Semi-arid Regions Using a Novel Hybrid Model - Anas Mahmood Al-Juboori (Water Resources Management, 2023)

A Systematic Review of Optimization of Dams Reservoir Operation Using the Meta-heuristic Algorithms - Behrang Beiranvand; Parisa-Sadat Ashofteh (Water Resources Management, 2023)

Estimation of Manning Roughness Coefficient in Alluvial Rivers with Bed Forms Using Soft Computing Models - Mohammad Bahrami Yarahmadi; Abbas Parsaie; Mahmood Shafai-Bejestan; Mostafa Heydari; Marzieh Badzanchin (Water Resources Management, 2023)

Investigating the Local-scale Fluctuations of Groundwater Storage by Using Downscaled GRACE/GRACE-FO JPL Mascon Product Based on Machine Learning (ML) Algorithm - Behnam Khorrami; Shoaib Ali; Orhan Gündüz (Water Resources Management, 2023)

Multi-timescale Performance of Groundwater Drought in Connection with Climate - Ruirui Zhu; Hongxing Zheng; Anthony J. Jakeman; Francis H.S. Chiew (Water Resources Management, 2023)

Optimizing Reservoir Water Management in a Changing Climate - Pedro Beça; António C. Rodrigues; João P. Nunes; Paulo Diogo; Babar Mujtaba (Water Resources Management, 2023)
One of the UN agenda 2030 Sustainable Development goals is associated with water availability and its sustainable management. The present study intends to improve multipurpose reservoir management under climate change scenarios in water scarce regions such as the Mediterranean. Implemented methods include the sequential use of climate model results, hydrological modelling, and reservoir water balance simulation, which are used to estimate future water availability. This work focuses on developing an innovative reservoir management approach based on rule curves and a dynamic assessment of water needs, to improve the management of reservoirs that are dependent on a water transfer system. The proposed methods are implemented in two reservoirs located in a typical Mediterranean river basin and assessed under long-term climate change scenarios up to the year 2100. The results show that the proposed approach can ensure 100% of the urban water supply, improve the reliability of the irrigation supply from 75% to 86–91%, and provide 92–98% of the river ecological flow. It is also demonstrated that this management approach is beneficial, particularly in the case of multipurpose reservoirs in watersheds facing water scarcity risks, to optimize the balance between supply reliability, water transfer volumes, and costs.

Optimization of Meteorological Monitoring Network of New South Wales, Australia - Shahid Khan; Mohammed M. A. Almazah; Ataur Rahman; Ijaz Hussain (Water Resources Management, 2023)

Runoff Prediction Under Extreme Precipitation and Corresponding Meteorological Conditions - Jinping Zhang; Dong Wang; Yuhao Wang; Honglin Xiao; Muxiang Zeng (Water Resources Management, 2023)

Climate Informed Non-stationary Modeling of Extreme Precipitation in China - Chi Zhang; Xuezhi Gu; Lei Ye; Qian Xin; Xiaoyang Li; Hairong Zhang (Water Resources Management, 2023)

A Procedure for Assessment of Environmental Flows Incorporating Inter- and Intra-Annual Variability in Dam-Regulated Watersheds - Ravindra Kumar Verma; Ashish Pandey; Surendra Kumar Mishra; Vijay P. Singh (Water Resources Management, 2023)

Evaluation of Flow Resistance using Multi-Gene Genetic Programming for Bed-load Transport in Gravel-bed Channels - Satish Kumar; Arpan Pradhan; Jnana Ranjan Khuntia; Kishanjit Kumar Khatua (Water Resources Management, 2023)

An Innovative Approach to Predicting the Financial Prospects of a Rainwater Harvesting System - Shiguang Chen; Hongwei Sun; Qiuli Chen; Song Liu; Xuebin Chen (Water Resources Management, 2023)

Optimizing Soil Moisture in Subsurface Irrigation System Based on Porous Clay Capsule Technique - Hojjat Ghorbani Vaghei; Hossein Ali Bahrami; Farzin Nasiri Saleh (Water Resources Management, 2023)

Influence of Initial Abstraction Ratios in NRCS-CN Model on Runoff Estimation of Permeable Brick Pavement Affected by Clogging - Xiaoli Du; Mingzhe Yang; Zijie Yin; Xing Fang (Water Resources Management, 2023)

Forecasting Short-term Water Demands with an Ensemble Deep Learning Model for a Water Supply System - Jing Liu; Xin-Lei Zhou; Lu-Qi Zhang; Yue-Ping Xu (Water Resources Management, 2023)

Influence of Land Surface Temperature and Rainfall on Surface Water Change: An Innovative Machine Learning Approach - Vanita Jain; Aarushi Dhingra; Eeshita Gupta; Ish Takkar; Rachna Jain; Sardar M. N. Islam (Water Resources Management, 2023)
The largest reservoir of drinkable water on Earth is surface water. It is crucial for maintaining ecosystems and enabling people to adapt to diverse climate changes. Despite surface freshwater is essential for life, the current research shows a striking lack of understanding in its spatial and temporal dynamics of variations in outflow and storage across a sizable country: India. Numerous restrictions apply to current research, including the use of insufficient machine learning techniques and limited data series. This work uses cutting-edge and SOTA-method to use the available data and machine learning to accurately understand spatial and temporal dynamics of variations in surface freshwater outflow and storage using extended data series. The authors did the examination of thematic maps produced using ArcMap 10.8 from June’2005 to June’2020 using JRC dataset to track changes in the intensity of surface water. Google Earth Engine in Python API has been devised to detect changes in surface water levels and quantifying shifting map trends. Raster image viewing, editing, and calculation are done with ArcMap. For determining the relationship between declines in Surface water levels, changes in rainfall intensity and land surface temperature, variables were averaged over 13 rivers for 15 years. The change in surface water is reliant on independent variables of change in land surface temperature and rainfall intensity. The authors use the correlation between these parameters to achieve an average R-squared adjusted value of 0.402. The study's findings contribute to a better understanding of the matter and can be used across the world.

Analytic Element-Finite Volume Based Coupled Groundwater-Surface Water Interaction model for Canal Command Systems - Komal Kumari; Anirban Dhar (Water Resources Management, 2023)

High-Resolution Flood Numerical Model and Dijkstra Algorithm Based Risk Avoidance Routes Planning - Bingyao Li; Jingming Hou; Xinghua Wang; Yongyong Ma; Donglai Li; Tian Wang; Guangzhao Chen (Water Resources Management, 2023)

Does the Ownership of Water Utilities Influence Water-Saving Advice Provided to Service Users? An Analysis of the Spanish Water Sector - Samara López-Ruiz; Nazaret Ibáñez-Rueda; Jorge Guardiola; Francisco González-Gómez (Water Resources Management, 2023)
This paper addresses the need to ensure the sustainable use of water, in line with the United Nations’ Sustainable Development Goals. Using statistical methods, this paper analyses whether the ownership of the water utility is an explanatory factor for (1) the provision of water conservation advice on utilities’ websites; and (2) how comprehensive this advice is in terms of tips on (i) installing efficient technology and (ii) adopting sustainable habits and behaviours. The paper focuses on the Spanish water industry, which is considered particularly appropriate for the analysis due to the coexistence of utilities with different ownership structures. The results reveal statistically significant differences according to the ownership of the operator and the size of the population served. For example, more private companies provide some advice on their websites, while public companies offer more tips per online advice section. The evidence should encourage national governments and regulatory authorities to pass a regulation that establishes guidelines on how these companies, both public and private, should provide water conservation advice on their websites.

A Hybrid Model for Predicting the Energy Dissipation on the Block Ramp Hydraulic Structures - Mostafa Rahmanshahi; Jafar Jafari-Asl; Mahmood Shafai Bejestan; Seyedali Mirjalili (Water Resources Management, 2023)

Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management - Sarmad Dashti Latif; Ali Najah Ahmed (Water Resources Management, 2023)

Evaluation of Remote Sensing Rainfall Products, Bias Correction and Temporal Disaggregation Approaches, for Improved Accuracy in Hydrologic Simulations - P. Yaswanth; B. Arul Malar Kannan; V. M. Bindhu; C. Balaji; Balaji Narasimhan (Water Resources Management, 2023)

Muskingum Models’ Development and their Parameter Estimation: A State-of-the-art Review - Wen-chuan Wang; Wei-can Tian; Dong-mei Xu; Kwok-wing Chau; Qiang Ma; Chang-jun Liu (Water Resources Management, 2023)

Cascade Hydropower System Operation Considering Ecological Flow Based on Different Multi-Objective Genetic Algorithms - Yubin Chen; Manlin Wang; Yu Zhang; Yan Lu; Bin Xu; Lei Yu (Water Resources Management, 2023)

Equity, Social Welfare, and Economic Benefit Efficiency in the Optimal Allocation of Coastal Groundwater Resources - Elmira Valipour; Hamed Ketabchi; Reza Safari shali; Saeed Morid (Water Resources Management, 2023)

Performance Improvement of LSTM-based Deep Learning Model for Streamflow Forecasting Using Kalman Filtering - Fatemeh Bakhshi Ostadkalayeh; Saba Moradi; Ali Asadi; Alireza Moghaddam Nia; Somayeh Taheri (Water Resources Management, 2023)

Numerical Simulation of Water Hammer in Pipeline System Using Efficient Wave Tracking Method - Qianping Zhang; Zhaofei Tian; Shuaijie Lu; Huilun Kang (Water Resources Management, 2023)

The Effect of Meteorological and Hydrological Drought on Groundwater Storage Under Climate Change Scenarios - Shima Kamali; Keyvan Asghari (Water Resources Management, 2023)

Optimal Implementation of Climate Change Adaptation Measures to Ensure Long-term Sustainability on Large Irrigation Systems - David Haro-Monteagudo; Leticia Palazón; Christos Zoumides; Santiago Beguería (Water Resources Management, 2023)
Observed and projected consequences of climate change on streamflow generated in the Pyrenees threatens the long-term sustainability of water resources systems downstream, especially those with high irrigation demands. To tackle this challenge, the participation of stakeholders in defining potential adaptation strategies is crucial to building awareness and capacity for the community, providing agreed solutions, and reducing conflict. However, there is also a need for a top-down approach to incorporate other, large-scale, or innovative adaptation strategies. This article describes a bottom-up-meets-top-down approach to estimate the optimal implementation intensity of adaptation strategies under different climate scenarios on a complex water resources system. Future streamflow projections were used in a water allocation model combined with a Markov Chain Monte Carlo sampling process to obtain optimal combinations of measures to meet different sustainability objectives. The methodology was applied to the Gállego-Cinca River system in NE Spain, which relies on water from the Pyrenees. A stakeholder workshop identified storage development and irrigation modernisation as the preferred adaptation options. However, the modelling results show that more storage in the basin, especially on-farm reservoirs, is not enough to maintain current sustainability levels. This will enable the adoption of demand management measures that optimise water use despite not being among stakeholder preferences.

Estimation of Runoff Under Changed Climatic Scenario of a Meso Scale River by Neural Network Based Gridded Model Approach - Debajit Das; Tilottama Chakraborty; Mrinmoy Majumder; Tarun Kanti Bandyopadhyay (Water Resources Management, 2023)

Adaptive Water Resources Management Under Climate Change: An Introduction - G. P. Tsakiris; D. P. Loucks (Water Resources Management, 2023)

Climate Change Impacts on Blue and Green Water of Meki River Sub-Basin - Aster Tesfaye Hordofa; Olkeba Tolessa Leta; Tena Alamirew; Abebe Demissie Chukalla (Water Resources Management, 2023)

Climate Change Impact on Water Resources of Tank Cascade Systems in the Godavari Sub-Basin, India - Koppuravuri Ramabrahmam; Venkata Reddy Keesara; Raghavan Srinivasan; Deva Pratap; Venkataramana Sridhar (Water Resources Management, 2023)

Evaluation Climate Change Impacts on Water Resources Over the Upper Reach of the Yellow River Basin - Xiaowen Zhuang; Yurui Fan; Yongping Li; Chuanbao Wu (Water Resources Management, 2023)

Integrated Water Resources Management in Cities in the World: Global Challenges - Chloé Grison; Stef Koop; Steven Eisenreich; Jan Hofman; I-Shin Chang; Jing Wu; Dragan Savic; Kees van Leeuwen (Water Resources Management, 2023)
Water scarcity and accessibility remain persistently amongst the most prominent global challenges. Although there is a wide agreement among international organizations that Integrated Water Resources Management (IWRM) and water governance are key to overcome water-related challenges, global assessments of the progress made by cities is lacking. This paper for the first time analyses the challenges of water, wastewater, municipal solid waste and climate change in cities. We used empirical studies (125 cities) based on the City Blueprint Approach and developed a statistical estimation model to estimate IWRM performances of another 75 cities. These 200 cities in total represent more than 95% of the global urban population. This comprehensive global picture enables us to evaluate the existing gaps in achieving water-related Sustainable Development Goals (SDGs), in particular SDG 6 (clean water and sanitation) and SDG 11 (sustainable cities and communities). The best performing cities were Amsterdam and Singapore. Unfortunately, most cities do not yet manage their water resources wisely and are far from achieving the SDGs. For instance, targets regarding drinking water supply are still a challenge for many cities in Africa and Asia and challenges regarding sanitation are high in cities in Africa, Asia and Latin America. The same holds for solid waste management, climate adaptation, and people living in informal settlements. In another paper we will address the solution pathways to these global challenges.

Multi-objective Optimisation Framework for Assessment of Trade-Offs between Benefits and Co-benefits of Nature-based Solutions - Shengnan Yang; Laddaporn Ruangpan; Arlex Sanchez Torres; Zoran Vojinovic (Water Resources Management, 2023)
Urbanization and climate change are producing an escalation in the prevalence of urban problems, particularly those connected to flooding, prompting authorities and stakeholders to recognize the need for sustainable solutions. Nature-Based Solutions are progressively replacing traditional engineering solutions as an alternative since they are more eco-friendly. By re-activating the urban hydrological cycle processes, NBS intends to increase the natural water storage capacity to help decrease urban flooding. The work described here outlines a framework for optimising the efficacy of NBS for flood risk reduction and its co-benefits, as well as defining the trade-offs among these co-benefits. The framework integrates 1D hydrodynamic models with multi-objective optimisation techniques. To demonstrate the applicability of the framework and its methods it has been used in Sint Maarten, which is an island located in the Caribbean Sea. Four NBS measure were identified as having good potential to be applied in the case study, namely: green roof, permeable pavement, bio-retention pond, and open detention basin. The results showed that the developed framework has the ability to represent the link between benefits and costs when evaluating various NBS, hence aiding the decision-making process to select and implement NBS.

Complex Policy Mixes are Needed to Cope with Agricultural Water Demands Under Climate Change - Jaime Martínez-Valderrama; Jorge Olcina; Gonzalo Delacámara; Emilio Guirado; Fernando T. Maestre (Water Resources Management, 2023)
The divergence between agricultural water use and the annual supply of water resources (water gap) has been increasing for decades. The forecast is that this water gap will continue to widen, compromising the water security of a large share of the global population. On the one hand, the increase in demand is attributed to an ever-growing population that, in addition, is adopting a high-water consumption per capita lifestyle (e.g., meat-rich diet, increased use of biofuels and of irrigated agriculture). On the other hand, climate change is increasing aridification and the spatio-temporal heterogeneity of precipitation worldwide. The water gap is particularly acute in drylands, where development and food security has been based on the massive exploitation of water resources, particularly groundwater. Here we analyze the mechanisms underlying this water gap, which is mainly driven by water use in agriculture, and suggest suitable solutions that can help to close it. Using causal diagrams, we show how population generates different demands that create a water gap that prevailing supply-side solutions cannot close. Indeed, it has been widening over the years because water consumption has grown exponentially. This behaviour is explained by a series of mechanisms that it is necessary to understand to realize the complexity of water scarcity problems. For solving the water gap, we propose and exemplify eight lines of action that can be combined and tailored to each territory. Our analyses corroborate the urgent need to plan an integral management of water resources to avoid widespread scenarios of water scarcity under future climatic conditions.

Climate Change Risks on Mediterranean River Ecosystems and Adaptation Measures (Spain) - Clara Estrela-Segrelles; Gabriel Gómez-Martínez; Miguel Ángel Pérez-Martín (Water Resources Management, 2023)
The Mediterranean is one of the most vulnerable regions to climate change impacts. Climate change scenarios predict that water temperature will increase up to 2.2–2.9ºC by the end of the century in Mediterranean rivers. This will cause an impact on water quality (oxygen dissolved reduction), reduce the available habitat of cold-water fish species and affect macroinvertebrates. Risk assessment methodology develops indicators that integrate hazard, exposure and vulnerability. Risk maps are key tools to prioritize the areas in which adaptation measures should be implemented in order to improve the adaptive capacity of ecosystems. The risk of habitat loss and ecosystem damage is very high in Mediterranean rivers. For RCP8.5, the 80% of the waterbodies that currently have brown trout presence are in High Risk (HR) or Very High Risk (VHR) of disappearing in the long term future (2070–2100) and the 35% in the short term (2010–2040). It will affect the middle sections first and the headwaters of the rivers later. The 92% of the waterbodies are in HR-VHR of macroinvertebrate family’s affection (2070–2100) and dissolved oxygen may be reduced by 0.5–0.75 mgO 2 /l (2070–2100). The restoration of the riverside vegetation is the main adaptation measure. This reduces significantly the stream temperature. Other measures are the groundwater protection and cold-water discharge from the reservoirs.

Business As Usual Versus Climate-responsive, Optimised Crop Plans – A Predictive Model for Irrigated Agriculture in Australia in 2060 - Andrew Lewis; James Montgomery; Max Lewis; Marcus Randall; Karin Schiller (Water Resources Management, 2023)
Climate change is impacting people’s lives, with management of water resources and food security being major concerns for the future of many countries. In this paper, future water availability, crop water needs, yields, market costs and returns of current crops in a case study area in Australia are evaluated under future climatic conditions. The predictive methods on which the work is based have the advantage of being robust—they are able to simultaneously consider many climate change models—giving greater confidence in determining what the future will hold in this regard. The results indicate business as usual, in terms of the quantity and types of crops that can be grown presently, will not be sustainable in the medium and long term future. Instead, modelling indicates that changes in production and land use to maximise revenue per megalitre of water will be needed to adapt to future conditions and deliver climate-smart agriculture.

Climate Change Impacts on Water Resources and Sustainable Water Management Strategies in North America - Zunaira Asif; Zhi Chen; Rehan Sadiq; Yinying Zhu (Water Resources Management, 2023)

Climate Change in the Mediterranean Basin (Part II): A Review of Challenges and Uncertainties in Climate Change Modeling and Impact Analyses - L. V. Noto; G. Cipolla; D. Pumo; A. Francipane (Water Resources Management, 2023)
The Mediterranean basin is particularly prone to climate change and vulnerable to its impacts. One of the most relevant consequences of climate change, especially for the southern Mediterranean regions, is certainly water scarcity as result of a reduction of surface runoff and groundwater levels. Despite the progress achieved in recent years in the field of climate change and its impact on water resources, results and outcomes should be treated with due caution since any future climate projection and derived implications are inevitably affected by a certain degree of uncertainty arising from each different stage of the entire modeling chain. This work offers a comprehensive overview of recent works on climate change in the Mediterranean basin, mainly focusing on the last ten years of research. Past and future trends on different components of the hydrological balance are discussed in a companion paper (Noto et al. 2022), while the present paper focuses on the problem of water availability and water scarcity. In addition, the work aims to discuss the most relevant sources of uncertainty related to climate change with the aim to gain awareness of climate change impact studies interpretation and reliability.

Climatic and Other Global Changes as Current Challenges in Improving Water Systems Management: Lessons from the Case of Italy - Giuseppe Rossi; David J. Peres (Water Resources Management, 2023)
Climate change linked to human activities is affecting natural systems, increasing frequency and severity of water-related hazards. The issue of climate change pushes to tackle the expected risks in the water sector through a comprehensive and global view, with a revision of the paradigms considered as drivers of water resources development. Based on the evolution of these paradigms in Italy the main characteristics of an adaptive approach to climate change and other global changes are discussed relatively to water infrastructures, legislative and institutional frameworks. The objective of adaptation strategies is the increase of resilience of water systems, emphasizing the capability of reducing both physical and socio-political vulnerability, improving the governance of water services. Starting from the analysis of the evolution of water management, priorities for coping with future challenges are discussed with reference to the reduction of the risk of water shortage due to drought, to the mitigation of flood risk, and to the issues concerning the water-food-energy nexus.

Effectiveness of Adaptive Operating Rules for Reservoirs - Luis Garrote; Alfredo Granados; Mike Spiliotis; Francisco Martin-Carrasco (Water Resources Management, 2023)
In this paper, a methodological proposal is made to develop an adaptive decision support system for reservoir management. The system is based on an optimization model that determines operating rules that meet certain optimality conditions based on the state of the reservoir at a certain time and on a streamflow forecast, if available. The model is based on Spiliotis et al. in Water Resour Manage 30:5759-5778, where a general methodology was developed to specify static operating rules for reservoir systems. The proposed methodology consists of modifying the optimization procedure developed in the previous work to dynamically update operating rules to adapt management to the changing situation. To evaluate its effectiveness, the methodology was applied to the Pisuerga-Carrión reservoir system, in the Spanish part of the Duero basin. The results obtained with adaptive rules were compared with those obtained applying the same static operating rule for the entire analysis period. Adaptive rules were found to lead to better operating results, particularly if a successful streamflow forecast method is available.

Water and Environmental Systems Management Under Uncertainty: From Scenario Construction to Robust Solutions and Adaptation - Maria da Conceição Cunha (Water Resources Management, 2023)
This paper presents and discusses concepts, models, and methods for defining strategies, plans, and actions to achieve the sustainable development of water and environmental systems in a context of uncertainty. The complexity of such systems, including human and natural landscapes and their interactions, is a tremendous challenge with regard to decision-making processes. The future that is now being designed involves a myriad of uncertainties, climate and non-climate related, that request comprehensive decision frameworks involving multiple processes (institutional, political, social, economic, biophysical, etc.) to prevent disagreements and barriers from impeding the achievement of sustainable decisions. When it comes to assessing responses to future scenarios (or different states of the world), the idea of ​​robustness can include introducing the concept of adaptation. New terms such as “multiple plausible futures” and “deep uncertainty” have been emerging. How past frameworks should give rise to new frameworks so that decisions to be taken on water and environmental systems management and infrastructure planning are adapted to uncertain future conditions are the main issues tackled. The limitations on predicting the future and controlling and managing water and environmental systems mean that policy makers and society in general, especially knowledge-producing centres, need to shift from rhetoric to intervention, to tackle the many changing tendencies of today. Deciding now, at the present time, which has already been the future, the future of the next generations is an intricate and demanding task.

Future Climate Change Impact on the Streamflow of Mahi River Basin Under Different General Circulation Model Scenarios - Swati Maurya; Prashant K. Srivastava; Lu Zhuo; Aradhana Yaduvanshi; R. K. Mall (Water Resources Management, 2023)

Adaptive Water Management: On the Need for Using the Post-WWII Science in Water Governance - Peder Hjorth; Kaveh Madani (Water Resources Management, 2023)
Although the UN concluded, already in 1997, that water would be the most contentious issue of the 21st century, water governance is still confused, nearly everywhere. Even the severe impacts of escalating water bankruptcy and global warming have so far failed to incur a marked improvement in governance systems. The global community has adopted sustainable development as a common vision and guide for the future. Yet, the adoption of the underlying principles of sustainable development has been slow in the water sector and elsewhere. Despite the realization that water governance is a political issue, the near-universal neoliberal agenda tends to only employ technologic and economic solutions to address water problems. This paper presents a historical overview, from the end of the Second World War (WWII) and onwards, of events that could, or should, have had an impact on water management frameworks. It evidences some important consequences of the institutional rigidity exposed during that period. The paper also turns to the fields of science, policy, and management, to pinpoint failures in the translation of political rhetoric as well as new scientific findings into change at the operational level. It explores how an updated knowledge base could serve a quest for sustainable water governance strategies. It is argued that a persistent failure to learn is an important reason behind the dire state that we are now in. As a result, water management is still based on century-old, technocratic, and instrumental methodologies that fail to take advantage of important scientific advancements since WWII and remain unable to properly deal with real-world complexities and uncertainties. The paper concludes that when it is linked to a transformation of the institutional superstructure, adaptive water management (AWM), a framework rooted in systems thinking, emerges as a prominent way to embark on a needed, radical transformation of the water governance systems.

The Great Salt Lake Water Level is Becoming Less Resilient to Climate Change - Daniyal Hassan; Steven J. Burian; Ryan C. Johnson; Sangmin Shin; Michael E. Barber (Water Resources Management, 2023)

Impact of Climate Change on Water Transfer Scale of Inter-basin Water Diversion Project - Tao Bai; Lei Li; Peng-fei Mu; Bao-zhu Pan; Jin Liu (Water Resources Management, 2023)

Climate Change in the Mediterranean Basin (Part I): Induced Alterations on Climate Forcings and Hydrological Processes - Leonardo V. Noto; Giuseppe Cipolla; Antonio Francipane; Dario Pumo (Water Resources Management, 2023)

Systemic Management of Water Resources with Environmental and Climate Change Considerations - Behnam Sadeghi; Mahmoud Ahmadpour Borazjani; Mostafa Mardani; Saman Ziaee; Hamid Mohammadi (Water Resources Management, 2023)

Simulation and Evaluation of Water Resources Management Scenarios Under Climate Change for Adaptive Management of Coastal Agricultural Watersheds - Aikaterini Lyra; Athanasios Loukas (Water Resources Management, 2023)
The main objective of this paper is to analyze the impact of climate change on water resources management and groundwater quantity and quality in the coastal agricultural Almyros Basin, in Greece. Intensive groundwater abstractions for irrigation and nitrogen fertilization for crop production maximization, have caused a large water deficit, nitrate pollution, as well as seawater intrusion in the Almyros aquifer system. Multi-model climate projections for Representative Concentration Pathways (RCPs 4.5 and 8.5) from the Med-CORDEX database for precipitation and temperature have been used to evaluate the impacts of climate change on the study area. The multi-model climate projections have been bias-corrected with Delta, Delta change of Mean and Variance, Quantile Delta Change, Quantile Empirical Mapping, and Quantile Gamma Mapping methods, and statistically tested to find the best GCM/RCM multi-model ensemble. Simulation of coastal water resources has been performed using an Integrated Modelling System (IMS) that contains connected models of surface hydrology (UTHBAL), groundwater hydrology (MODFLOW), nitrate leaching/crop growth (REPIC), nitrate pollution (MT3DMS), and seawater intrusion (SEAWAT). The results indicate that the best climate multi-model ensemble consists of three (3) climate models for both RCP4.5 and RCP8.5 using the Quantile Empirical Mapping bias-correction method. The IMS was applied for historical and future periods with observed and simulated meteorological inputs (e.g. precipitation and temperature) and various irrigation and agronomic scenarios and water storage works development (i.e. reservoirs). The results indicate that at least deficit irrigation and deficit irrigation along with rain-fed cultivation schemes, combined with or without the development and operation of reservoirs, should be applied to overcome the degradation of groundwater quality and quantity in the study basin. Based on the findings of this work, the water resources management should be adaptive to tackle the water resources problems of the Almyros Basin.

Reservoir Evaporation Forecasting Based on Climate Change Scenarios Using Artificial Neural Network Model - Yeşim Ahi; Çiğdem Coşkun Dilcan; Daniyal Durmuş Köksal; Hüseyin Tevfik Gültaş (Water Resources Management, 2023)

Application of a Distributed Hydrologic Model to Assess the Impact of Climate and Land-use Change on Surface Runoff from a Small Urbanizing Watershed - N. M. Sabitha; Santosh G. Thampi; D. Sathish Kumar (Water Resources Management, 2023)

Adapting Irrigation Strategies to Mitigate Climate Change Impacts: A Value Engineering Approach - Walaa El-Nashar; Ahmed Elyamany (Water Resources Management, 2023)
Water scarcity and climate change are posing new challenges to irrigation management. Climate change increases water demand and decreases crop yields. The aim of this paper is to propose a framework to select the most efficient irrigation strategy to mitigate the impacts of climate change and achieve food security. Value engineering (VE) methodology is utilized to assure the functionality of the strategy and add an element of creativity while creating the value alternatives. The life cycle cost (LCC) technique is utilized to provide the optimum irrigation strategy from an economic perspective. The findings showed three different value alternatives for different crops, soil types, and irrigation systems. This paper contributes to the current state of knowledge by a) utilizing the Value Engineering methodology in irrigation management studies; b) evaluating irrigation strategies to ensure efficient irrigation water management; and c) providing policymakers with a tool to incorporate the added value and functionality into their policies regarding irrigation water.

How Do Sustainable Development-Induced Land Use Change and Climate Change Affect Water Balance? A Case Study of the Mun River Basin, NE Thailand - Arika Bridhikitti; Arocha Ketuthong; Thayukorn Prabamroong; Renzhi Li; Jing Li; Gaohuan Liu (Water Resources Management, 2023)

Assessment of the Analytic and Hydrologic Methods in Separation of Watershed Response to Climate and Land Use Changes - Omidreza Mikaeili; Mojtaba Shourian (Water Resources Management, 2023)

Climate Change Impacts on ‘Seasonality Index’ and its Potential Implications on Rainwater Savings - Monzur A. Imteaz; Iqbal Hossain (Water Resources Management, 2023)
Seasonality Index (SI) is commonly used to define rainfall variability within a year for a locality, which has got significant impact on the water resources planning and management. Both the longer periods of dry and wet conditions are reflected by SI value. As SI is calculated using historical rainfall data, a historical average value is represented for a locality. However, with the emerging impacts of climate change SI values based on historical data are likely to change. This paper presents expected changes in future SI values for the largest city of Australia (Sydney) based on projected future rainfall scenarios for the city. The paper further illustrates potential water savings through rainwater tanks under projected climate change scenarios using an earlier developed daily water balance model, eTank. For the simulations of potential water savings through rainwater tanks, projected daily rainfall data was collected from Australian government data portal for four stations within Sydney. Future potential rainwater savings efficiencies were correlated with the corresponding SI values. It is found that such correlation closely matches with an earlier developed correlation using past historical data, however the future water savings efficiency will be slightly lower than the past water savings efficiency.