Evaluating Impact of Land Use and Land Cover Change Under Climate Change on the Lake Marmara System - Mert Can Gunacti; Gulay Onusluel Gul; Cem P. Cetinkaya; Ali Gul; Filiz Barbaros (Water Resources Management, 2023)

A Non-Stationary Based Approach to Understand the Propagation of Meteorological to Agricultural Droughts - Subhadarsini Das; Jew Das; N. V. Umamahesh (Water Resources Management, 2023)

Updating IDF Curves Under Climate Change: Impact on Rainfall-Induced Runoff in Urban Basins - Ioannis M. Kourtis; Ioannis Nalbantis; George Tsakiris; Basil Ε. Psiloglou; Vassilios A. Tsihrintzis (Water Resources Management, 2023)

Managing Risks of Climate Change on Irrigation Water in Arid Regions - Walaa Elnashar; Ahmed Elyamany (Water Resources Management, 2023)
Abnormal changes in temperature, precipitation, atmospheric carbon dioxide, or solar radiation are examples of climate change that may affect irrigation water demand. Studies show an increasing trend in the earth’s surface temperature, with decreasing trends in rainfall. With most studies focused on predicting the extent of climate change, fewer studies focused on developing appropriate response strategies. This paper aims to propose a systematic approach to identify, analyze, and respond to the risks of climate change on irrigation water in arid regions using the Risk Management process. The compound effect of these risks was analysed using Monte Carlo Simulation, which indicated a 69% loss in crop production due to climate change at a 90% confidence level. The proposed responses to the risks of climate change include strategies to avoid, transfer, mitigate, and/or accept these risks. The study has made three contributions to the state of the art. First, to adopt a well-recognized risk management methodology in climate change studies. Second, to quantify the compound effect of climate change risks on irrigation water in arid regions. Third, to recommend a set of response strategies to help policymakers mitigate the inevitable harmful effect of climate change on irrigation water.

Future Changes in Precipitation Over Northern Europe Based on a Multi-model Ensemble from CMIP6: Focus on Tana River Basin - Sogol Moradian; Ali Torabi Haghighi; Maryam Asadi; Seyed Ahmad Mirbagheri (Water Resources Management, 2023)

Meeting Climate Change Challenges: Searching for More Adaptive and Innovative Decisions - Daniel P. Loucks (Water Resources Management, 2023)

Climate change and local anthropogenic activities have altered river flow regimes across Canterbury, New Zealand - Doug J. Booker; Ton H. Snelder (Water Resources Management, 2023)

Drainage Systems Optimization Under Climate Change Scenarios - Diana Fiorillo; Francesco De Paola; Giuseppe Ascione; Maurizio Giugni (Water Resources Management, 2023)

Efficient Monitoring of Total Suspended Matter in Urban Water Based on UAV Multi-spectral Images - Yi Tang; Yang Pan; Lei Zhang; Hongchen Yi; Yiping Gu; Weihao Sun (Water Resources Management, 2023)

Modified SWAT to Forecast Water Availability in Mediterranean Mountainous Watersheds with Snowmelt Dominated Runoff - G. Harik; I. Alameddine; M. Abou Najm; M. El-Fadel (Water Resources Management, 2023)

System Dynamics-based Carbon Footprint Assessment of Industrial Water and Energy Use - Mohammad Karamouz; Mohammadreza Zare; Elham Ebrahimi (Water Resources Management, 2023)

An Adaptive Ensemble Framework for Flood Forecasting and Its Application in a Small Watershed Using Distinct Rainfall Interpolation Methods - Yichao Xu; Zhiqiang Jiang; Yi Liu; Li Zhang; Jiahao Yang; Hairun Shu (Water Resources Management, 2023)

Burst Analysis of Water Supply Pipe Based on Hydrodynamic Simulation - Wang Pengfei; Jiang Zhiqiang; Duan Jiefeng (Water Resources Management, 2023)

Prediction of Irrigation Water Requirements for Green Beans-Based Machine Learning Algorithm Models in Arid Region - Ali Mokhtar; Nadhir Al-Ansari; Wessam El-Ssawy; Renata Graf; Pouya Aghelpour; Hongming He; Salma M. Hafez; Mohamed Abuarab (Water Resources Management, 2023)
Water scarcity is the most obstacle faced by irrigation water requirements, likewise, limited available meteorological data to calculate reference evapotranspiration. Consequently, the focal aims of the investigation are to assess the potential of machine learning models in forecasting irrigation water requirements (IWR) of snap beans by evolving multi-scenarios of inputs parameters to figure out the impact of meteorological, crop, and soil parameters on IWR. Six models were applied, support vector regressor (SVR), random forest (RF), deep neural networks (DNN), convolutional neural networks (CNN), long short-term memory (LSTM), and Hybrid CNN-LSTM. Ten variables including maximum and minimum temperature, Relative humidity, wind speed, precipitation, root depth, basal crop coefficient, soil evaporation, a fraction of surface wetted and, exposed and soil wetted fraction were used as the input data for models with their combination, 8 input scenarios were designed. Overall models, the best scenario was scenario 4 (relative humidity, wind speed, basal crop coefficient, soil evaporation), however, the best scenario for DNN and RF model was scenario 7 (root depth, basal crop coefficient, soil evaporation, fraction of surface wetted, exposed and soil wetted fraction). While the weakest one was the group of climatic factors in scenario 6 (maximum temperature, minimum temperature, relative humidity, wind speed, and precipitation). Among the models, the hybrid LTSM & CNN was the most accurate and the SVR model had the lowest estimation accuracy. The outcomes of this research work could set up a modeling strategy that would set in motion the improvement of efforts to identify the shortages in IWR forecasting, which sequentially may support alleviation strategies such as policies for sustainable water use and water resources management. The current approach was promising and has research value for other similar regions.

Modelling and Analyzing a Unique Phenomenon of Surface Water Temperature Rise in a Tropical, Large, Riverine Reservoir - Shibo Guo; Dejun Zhu; Yongcan Chen (Water Resources Management, 2023)

Criticality of Isolation Valves in Water Distribution Networks with Hydraulics and Topology - Richárd Wéber; Tamás Huzsvár; Ákos Déllei; Csaba Hős (Water Resources Management, 2023)
Occasional, random pipe bursts are inevitable in water distribution networks; thus, properly operating isolation valves is critical. During a shutdown, the damaged segment is segregated using the neighbouring valves, causing the smallest isolation possible. This study analyses the importance of isolation valves individually from the perspective of the demand shortfall increment. An in-house, open-source software called STACI performs demand-driven simulations to solve the hydraulic equations with pressure-dependent demand determining the nodal pressures, the volumetric flow rates, and the consumption loss. The system has an additional consumption loss if an isolation valve cannot be closed. The criticality of an isolation valve is the increment in the relative demand shortfall caused by its malfunction. Moreover, centrality indices from complex network theory are applied to estimate the criticality without the need for computationally expensive hydraulic simulations. The distribution of criticality values follows a power-law trend, i.e. some of the isolation valves have significantly higher importance during a shutdown. Moreover, Spearman’s rank correlation coefficients between the centrality and criticality values indicate limited applicability. The criticality analysis can highlight which isolation valves have higher importance during reconstruction planning or maintenance. The Katz and the Degree centrality show a moderate positive correlation to the criticality, i.e., if numerous hydraulic simulations are not feasible, these quantities give an acceptable estimate.

An Optimal Operation Method for Parallel Hydropower Systems Combining Reservoir Level Control and Power Distribution - Xinyu Wu; Yuan Lei; Chuntian Cheng; Qilin Ying (Water Resources Management, 2023)

Costs-benefit Analysis for the use of Shallow Groundwater as non-conventional Water Resource - Mariana Marchioni; Anita Raimondi; Maria Gloria Di Chiano; Umberto Sanfilippo; Stefano Mambretti; Gianfranco Becciu (Water Resources Management, 2023)
Encouraging the implementation of non-conventional water resources (NCWR) is a fundamental strategy to face the future challenges due to urban population growth and resource scarcity. The implementation of a systematic process of Cost Benefit Analysis (CBA) offers reliable economic indicators to support decision makers in taking actions shifting towards NCWR. While infrastructure costs are directly estimated, while the benefits depend upon the considered stakeholders and require a tough estimation of the achieved ecosystem services. This research provides a framework for CBA analysis adopting NCWR at municipal level. The framework has been then applied to two case studies in Milan focused on the exploitation of shallow groundwater, where the obtained economic indicators has stressed out the importance of considering a complete benefits analysis that could support incentive policies on shifting part of the financial benefits to direct users leading to benefits for the whole community.

A Comparative Analysis of Rainwater Harvesting System and Conventional Sources of Water - Abdul Salam Khan (Water Resources Management, 2023)

Assessment of the Joint Impact of Rainfall Characteristics on Urban Flooding and Resilience Using the Copula Method - Kun Xie; Yanfeng He; Jong-Suk Kim; Sun-Kwon Yoon; Jie Liu; Hua Chen; Jung Hwan Lee; Xiang Zhang; Chong-Yu Xu (Water Resources Management, 2023)

Acknowledgement of Reviewers for 2022 - George Tsakiris (Water Resources Management, 2023)

Synergetic Water Demand and Sustainable Supply Strategies in GCC Countries: Data-driven Recommendations - Ibrahim Al Khoury; Sophia Ghanimeh; Dima Jawad; Maya Atieh (Water Resources Management, 2023)
The Gulf Cooperation Council (GCC) countries, characterized with limited water resources and high oil/gas revenues, rely heavily on energy-intensive seawater desalination and non-renewable groundwater abstraction. The need to shift solutions to demand-side practices and sustainable supply alternatives has been long advocated; yet this study is the first to “quantify” the impacts of such solutions on the water management system of Qatar – considered a study case of GCC countries. In this research, a scenario-based approach was utilized to predict the impact of water demand control and wastewater reuse (and the resulting synergies) on consumption of desalinated water, extraction of groundwater resources, and development needs of water and wastewater infrastructure. To this effect, country-specific models for Qatar were developed to project annual household water demand, wastewater generation and residential construction growth, up to year 2050. The outcomes showed that tariff reforms and regulated greywater reuse would reduce the annual household demand for desalinated water by up to 27% and 7%, respectively. Also, intensive reuse of Treated Sewage Effluent (TSE) would reduce 40–80% of total groundwater abstraction for irrigation by 2050. Finally, adopting an integrated water strategy, with combined demand and supply management targets, creates synergies that would: (1) limit groundwater abstraction to rates close to the aquifers safe yield; and (2) delay the need for expansion of the water and wastewater infrastructure by more than a decade. Data-driven recommendations were provided accordingly.

Trivariate Probabilistic Assessments of the Compound Flooding Events Using the 3-D Fully Nested Archimedean (FNA) Copula in the Semiparametric Distribution Setting - Shahid Latif; Slobodan P. Simonovic (Water Resources Management, 2023)

Study of Dam-Break Flow Over a Vegetated Channel With and Without a Drop - Alireza Khoshkonesh; Seyed Hossein Sadeghi; Saeed Gohari; Somayyeh Karimpour; Shahin Oodi; Silvia Di Francesco (Water Resources Management, 2023)

Developing Optimal Reservoir Rule Curve for Hydropower Reservoir with an add-on Water Supply Function Using Improved Grey Wolf Optimizer - Youngje Choi; Jungwon Ji; Eunkyung Lee; Sunmi Lee; Sooyeon Yi; Jaeeung Yi (Water Resources Management, 2023)

Effect of Distinct Evaluation Objectives on Different Precipitation Downscaling Methods and the Corresponding Potential Impacts on Catchment Runoff Modelling - Xumin Zhang; Simin Qu; Jijie Shen; Yingbing Chen; Xiaoqiang Yang; Peng Jiang; Peng Shi (Water Resources Management, 2023)

Risk Assessment and Management Method of Urban Flood Disaster - Jiake Li; Jiayu Gao; Ning Li; Yutong Yao; Yishuo Jiang (Water Resources Management, 2023)

Impact of Climate Change on Crop Irrigation Requirements in Arid Regions - Maha Alotaibi; Nawaf S. Alhajeri; Fahad M. Al-Fadhli; Salem Al Jabri; Mohamed Gabr (Water Resources Management, 2023)

Simulation Model to Assess the Water Dynamics in Small Reservoirs - Alisson Lopes Rodrigues; Lineu Neiva Rodrigues; Guilherme Fernandes Marques; Pedro Manuel Villa (Water Resources Management, 2023)

Long-Term Water Management Model for Preserving Sustainable Useful Capacity of Reservoirs - Bruno Molino; Annamaria De Vincenzo; Antonio Minó; Luigi Ambrosone (Water Resources Management, 2023)
In this study, we present a long-term water management model which can be an important tool for the ordinary management of a reservoir. The model can be made simple and applicable in a graphic form. The key point of the model is that the sedimentation rate of solids can be modeled according to a power law. The basic equation of the model is tested using bathymetric surveys of different dams located in different parts of the world. Robustness and predictive power are evaluated both numerically and by comparison with satellite results. Then the model is transformed into the form of a management plot and applied to the real case of the Camastra dam.

Water-Food-Energy Nexus in Global Cities: Addressing Complex Urban Interdependencies - Mohamed Hachaichi; Jafaru Egieya (Water Resources Management, 2023)

The Influence of Deep Uncertainties in the Design and Performance of Residential Rainwater Harvesting Systems - Gabriela Cristina Ribeiro Pacheco; Conceição de Maria Albuquerque Alves (Water Resources Management, 2023)

Convolutional Neural Network- ANN- E (Tanh): A New Deep Learning Model for Predicting Rainfall - Mahdie Afshari Nia; Fatemeh Panahi; Mohammad Ehteram (Water Resources Management, 2023)

Hydraulic Diagnostic Kit for the Automatic Expeditious Survey of in-line Valve Sealing in Long, Large Diameter Transmission Mains - Caterina Capponi; Bruno Brunone; Filomena Maietta; Silvia Meniconi (Water Resources Management, 2023)
In long transmission mains (TMs), maintenance operations and repairs often require the preliminary closure of some of the installed in-line valves. If perfectly sealed, these valves avoid leakage and then the possible emptying of the pipelines, air entry through leaks, and the successive unwanted transients at the filling completion. The poor accessibility of TMs makes the check of the valve sealing quite difficult since in most cases the confined space where they are installed implies the adoption of severe prevention measures. Therefore, expeditious and possibly remote survey procedures are strongly required by pipe system managers. In this paper, an innovative technique based on the execution of safe transient tests is proposed. It is tested on the Dorsale TM – a long, large diameter pipe system – in the northeast of Milan, Italy, where the sealing of three in-line valves had to be checked. The analysis of the test results allows pointing out successfully not only the valves sealing, but also refining a quick and reliable procedure – the so called “diagnostic kit” – that leads the way to automatic and periodic checks of the valve sealing. In the proposed procedure – that can be straightforwardly exported to other TMs – only a single pressure measurement section is required, that significantly simplifies the survey.

Impact of Modern Irrigation Methods on Groundwater Storage and Land Subsidence in High-water Stress Regions - Ismail Abd-Elaty; Ismail Fathy; Alban Kuriqi; Am Pris John; Salvatore Straface; Elsayed M. Ramadan (Water Resources Management, 2023)
Water resources management in high-stress regions is a large-scale problem affecting food and water security. Therefore, modern irrigation systems such as sprinklers, subsurface, and drip irrigations are applied to manage the water shortage in regions of the Nile delta. Because of the increase in population rate and climate change, freshwater supplies are significantly limited and must be efficiently managed. Consequently, Egypt plans to implement MIS in the old land of the Nile delta. The current study aims to investigate and model the recharge from the excess irrigation system that affects groundwater storage and land subsidence unexpectedly. The visual modflow was applied to investigate the groundwater heads and drawdown. At the same time, the analytical solution based on Terzaghi theory, and the surfer software was used to estimate and map the land subsidence. For this reason, we investigated the groundwater drawdown in the high-water shortage of Egypt’s Nile delta. Three scenarios were considered by changing irrigation methods and their Impact on land subsidence in the Nile Delta Aquifer (NDA). Therefore, the results of this study demonstrated that the groundwater drawdown reached 2.60 m, 4.20 m, and 6.50 m, respectively. In contrast, the land subsidence outstretched 26 m, 44 m, and 65 cm for the sprinkle sub-surface. Future design infrastructures such as pipelines, roads, irrigation networks, canals, and water structures should consider land subsidence due to modern irrigation systems (MIS).

NDVI Forecasting Model Based on the Combination of Time Series Decomposition and CNN – LSTM - Peiqiang Gao; Wenfeng Du; Qingwen Lei; Juezhi Li; Shuaiji Zhang; Ning Li (Water Resources Management, 2023)

Attribution of Streamflow Changes Considering Spatial Contributions and Driver Interactions Based on Hydrological Modeling - Yinshan Xu; Yubin Chen; Yufeng Ren; Zhengyang Tang; Xu Yang; Yu Zhang (Water Resources Management, 2023)

A New Regional Drought Index under X-bar Chart Based Weighting Scheme – The Quality Boosted Regional Drought Index (QBRDI) - Zulfiqar Ali; Sadia Qamar; Nasrulla Khan; Muhammad Faisal; Saad Sh. Sammen (Water Resources Management, 2023)

Modeling Soil Water Retention Under Different Pressures Using Adaptive Neuro-Fuzzy Inference System - Ahmed Elbeltagi; R. K. Jaiswal; R. V. Galkate; Manish Kumar; A. K. Lohani; Jaiveer Tyagi (Water Resources Management, 2023)
Soil Water Retention (SWR) is an important process in drainage, surface, and groundwater partitioning, hydrological modeling, water supply for irrigation, etc. Assessment of SWR characteristics is complex and difficult to conduct spatially in varied locations. Therefore, Pedotransfer Functions (PTF) which are empirical relations with easily available physical properties are commonly used. In the present study, the evaluation of soil moisture at different suction pressure using the adaptive neuro-fuzzy inference systems (ANFIS) approach based on soil texture (percentage of gravel, sand, silt, and clay) and compare with the PTF approach. The analysis was conducted for a total of eleven sites of two adjoining commands in India. The pressure plate apparatus along with coarse and fine sieve analysis, titration, and other tests were carried out to determine SWR, texture, organic carbon, and bulk density. The comparative analysis of Nash–Sutcliffe efficiencies of the best-fitted PTF models and ANFIS model confirmed that the ANFIS model can capture all variations of soil texture across all sites with Nash–Sutcliffe efficiency of nearly 1.0 indicative of an exact match, while no single PTF-based model can be used for all the sites. Therefore, the ANFIS model can be used to model soil water retention for the central India region using easily available texture properties of soils.

Climate Change Impacts on Irish River Flows: High Resolution Scenarios and Comparison with CORDEX and CMIP6 Ensembles - Conor Murphy; Anthony Kettle; Hadush Meresa; Saeed Golian; Michael Bruen; Fiachra O’Loughlin; Per-Erik Mellander (Water Resources Management, 2023)
Climate change is likely to impact water quality, resource availability and riverine ecosystems. While large ensembles are available to assess future impacts (e.g., the Coupled Model Intercomparison Projects (CMIP) and/or CORDEX) many countries have developed their own high-resolution ensembles. This poses a selection problem with robust adaptation dependent on plausible ranges of change being adequately quantified. Therefore, it is important to compare projected changes from available ensembles. Here we assess future climate change impacts for 26 Irish catchments. Using a high-resolution national ensemble of climate models projected impacts in mean, low and high flows are assessed and uncertainties in future projections related to catchment size. We then compare future impacts from CORDEX and CMIP6 ensembles for a subset of catchments. Results suggest increases in winter flows (-3.29 to 59.63%), with wide ranges of change simulated for summer (-59.18 to 31.23%), low (-49.30 to 22.37%) and flood (-19.31 to 116.34%) flows across catchments under RCP8.5 by the 2080s. These changes would challenge water management without adaptation. Smaller catchments tend to show the most extreme impacts and widest ranges of change in summer, low and flood flow changes. Both the ensemble mean and range of changes from the national ensemble were more modest and narrower than the CMIP6 and CORDEX ensembles, especially for summer mean and low flows, highlighting the importance of evaluating impacts across ensembles to ensure adaptation decisions are informed by plausible ranges of change.

Optimizing the Cleaning Strategies to Reduce the Flood Risk Increased by Gully Blockages - Jiun-Huei Jang (Water Resources Management, 2023)

Analysis of Water Pricing Policy Effects in a Mediterranean Basin Through a Hydroeconomic Model - Javier Martínez-Dalmau; Carlos Gutiérrez-Martín; Alfonso Expósito; Julio Berbel (Water Resources Management, 2023)
This paper explores the impacts of water pricing as a demand management policy, at a regional level (or basin-sector). To this aim, a hydro-economic model for the Guadalquivir River basin (southern Spain) is proposed here. This basin constitutes a perfect example of a Mediterranean basin subject to frequent and long drought periods, where challenges related to water scarcity are increasing, leading to social conflicts among water users. Moreover, this basin is characterised by a closure state meaning that all available water resources are already allocated among users. In this context, water pricing policy may act as an effective tool to reduce water demand by encouraging changes of behaviour in water users. In particular, those who perform irrigation practices in the agricultural sector. This paper focuses on the irrigation sector since it is the main water user in the basin (87%). Additionally, alternative water-availability scenarios have been used to test the effect of water pricing under drought conditions. The hydro-economic model presented here has been sectorized into four basin sectors with common characteristics (hydro and economic). This enables the analysis of alternative price scenarios in the agricultural sector, in terms of water used, crop patterns and gross margin. Results show that water pricing policy should consider the regional characteristics at the basin-sector scale to gain effectiveness and equity at the river basin scale. Moreover, it has been found that both water availability and the crop pattern at the basin-sector scale have an effect on the reduction of water used (and therefore in gross margin.

An Investigation of the Temporal Interaction of Urban Water Consumption in the Framework of Settlement Characteristics - Volkan Yilmaz; Mehmet Alpars (Water Resources Management, 2023)

Generalized Impedance-based Transient Analysis for Multi-branched Pipeline Systems - Sang Hyun Kim (Water Resources Management, 2023)

Development of a Water Security Conceptual Model by Combining Human-Environmental System (HES) and System Dynamic Approach - Maryam Yazdanparast; Mehdi Ghorbani; Ali Salajegheh; Reza Kerachian (Water Resources Management, 2023)

Runoff Forecast Model Based on an EEMD-ANN and Meteorological Factors Using a Multicore Parallel Algorithm - Shengli Liao; Huan Wang; Benxi Liu; Xiangyu Ma; Binbin Zhou; Huaying Su (Water Resources Management, 2023)

Simultaneous Monitoring of Different Drought Types Using Linear and Nonlinear Combination Approaches - Zahra Sadat Hosseini; Mahnoosh Moghaddasi; Shahla Paimozd (Water Resources Management, 2023)

A Stormwater Management Framework for Predicting First Flush Intensity and Quantifying its Influential Factors - Cosimo Russo; Alberto Castro; Andrea Gioia; Vito Iacobellis; Angela Gorgoglione (Water Resources Management, 2023)

Comparative Assessment of Improved SVM Method under Different Kernel Functions for Predicting Multi-scale Drought Index - Chaitanya B. Pande; N. L. Kushwaha; Israel R. Orimoloye; Rohitashw Kumar; Hazem Ghassan Abdo; Abebe Debele Tolche; Ahmed Elbeltagi (Water Resources Management, 2023)

On the Structure of the Intermittency of Rainfall - Pankaj Dey (Water Resources Management, 2023)

Coupling Time and Non-Time Series Models to Simulate the Flood Depth at Urban Flooded Area - Hongfa Wang; Xinjian Guan; Yu Meng; Zening Wu; Kun Wang; Huiliang Wang (Water Resources Management, 2023)

Study of Optimal and Joint Allocations of Water and land Resources for Multiple Objectives - Jianwei Wang; Tianling Qin; Xizhi Lv; Yongxin Ni; Qiufen Zhang; Li Ma (Water Resources Management, 2023)

Prediction Model for Reference Crop Evapotranspiration Based on the Back-propagation Algorithm with Limited Factors - Long Zhao; Liwen Xing; Yuhang Wang; Ningbo Cui; Hanmi Zhou; Yi Shi; Sudan Chen; Xinbo Zhao; Zhe Li (Water Resources Management, 2023)

A Model Coupling Water Resource Allocation and Canal Optimization for Water Distribution - Yu Fan; Haorui Chen; Zhanyi Gao; Benyan Fang; Xiangkun Liu (Water Resources Management, 2023)

Trimmed L-Moments of the Pearson Type III Distribution for Flood Frequency Analysis - Yifan Jia; Songbai Song; Liting Ge (Water Resources Management, 2023)

Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic - Miloš Milašinović; Damjan Ivetić; Milan Stojković; Dragan Savić (Water Resources Management, 2023)

Analysis of Drought Dynamics over Annual Maximum Drought Severity Series Based on Daily Index Definitions - Ayşegül Kuzucu; Gülay Onuşluel Gül (Water Resources Management, 2023)

Modeling Daily Reference Evapotranspiration from Climate Variables: Assessment of Bagging and Boosting Regression Approaches - Jayashree T R; NV Subba Reddy; U Dinesh Acharya (Water Resources Management, 2023)
The increasing frequency of droughts and floods due to climate change has severely affected water resources across the globe in recent years. An optimal design for the scheduling and management of irrigation is thus urgently needed to adapt agricultural activities to the changing climate. The accurate estimation of reference crop evapotranspiration (ET0), a vital hydrological component of the water balance and crop water need, is a tiresome task if all the relevant climatic variables are unavailable. This study investigates the potential of four ensemble techniques for estimating precise values of the daily ET0 at representative stations in 10 agro-climatic zones in the state of Karnataka, India, from 1979 to 2014. The performance of these models was evaluated by using several combinations of climatic variables as inputs by using tenfold cross-validation. The outcomes indicated that predictions of ET0 by all four ensemble models based on all climatic variables were the most accurate in comparison with other input combinations. The random forest regressor was found to deliver the best performance among the four models on all measures considered (Nash–Sutcliffe efficiency, 1.0, root-mean-squared error, 0.016 mm/day, and mean absolute error, 0.011 mm/day). However, it incurred the highest computational cost, whereas the computational cost of the bagging model for linear regression was the lowest. The extreme gradient-boosting model delivered the most stable performance with a modified training dataset. The work here shows that these models can be recommended for daily ET 0 estimation based on the users’ interests.

Comparative Study of Different Discrete Wavelet Based Neural Network Models for long term Drought Forecasting - Djerbouai Salim; Souag-Gamane Doudja; Ferhati Ahmed; Djoukbala Omar; Dougha Mostafa; Benselama Oussama; Hasbaia Mahmoud (Water Resources Management, 2023)

Risk Management Decision of Reservoir Dams Based on the Improved Life Quality Index - Hexiang Zhang; Wei Ge; Yadong Zhang; Zongkun Li; Wei Li; Junyu Zhu; Wenqi Wang (Water Resources Management, 2023)

A Leader-Follower Framework for Sustainable Water Pricing and Allocation - Sina Jahanshahi; Reza Kerachian; Omid Emamjomehzadeh (Water Resources Management, 2023)

Hydraulic Performance of Sharp-Crested Side Slit Weirs - Veysi Kartal; M. Emin Emiroglu (Water Resources Management, 2023)

Designating Appropriate Areas for Flood Mitigation and Rainwater Harvesting in Arid Region Using a GIS-based Multi-criteria Decision Analysis - Mahmoud M. Abd-el-Kader; Ahmed M. El-Feky; Mohamed Saber; Maged M. AlHarbi; Abed Alataway; Faisal M. Alfaisal (Water Resources Management, 2023)

SSDP Model with Inflow Clustering for Hydropower System Operation - Xinyu Wu; Shuai Yin; Chuntian Cheng; Zhiyong Chen; Huaying Su (Water Resources Management, 2023)

Simulated Investigation on the Impact of Spatial–temporal Variability of Rainstorms on Flash Flood Discharge Process in Small Watershed - Guangzhao Chen; Jingming Hou; Yuan Hu; Tian Wang; Shaoxiong Yang; Xujun Gao (Water Resources Management, 2023)

Multiobjective Intuitionistic Fuzzy Optimization Approach in Optimal Irrigation Planning and Operation of Reservoir - Sangita Pawar; Premlal Patel; Ashwini B. Mirajkar (Water Resources Management, 2023)

Pressure Regulation in a Water Distribution Network Using Pumps as Turbines at Variable Speed for Energy Recovery - Davi Edson Sales e Souza; André Luiz Amarante Mesquita; Claudio José Cavalcante Blanco (Water Resources Management, 2023)

Parameter Estimation for Univariate Hydrological Distribution Using Improved Bootstrap with Small Samples - Hanlin Li; Longxia Qian; Jianhong Yang; Suzhen Dang; Mei Hong (Water Resources Management, 2023)

Automating HEC-RAS and Linking with Particle Swarm Optimizer to Calibrate Manning’s Roughness Coefficient - Kazem Shahverdi; Hossein Talebmorad (Water Resources Management, 2023)

Probabilistic Modeling of the Rainfall Severity and Height for Locating the Surface Artificial Recharge Structure - Junjie Wang; Xiaocui Wang; Yuru Wang; Donghui Yang (Water Resources Management, 2023)

Runoff Forecasting using Convolutional Neural Networks and optimized Bi-directional Long Short-term Memory - Junhao Wu; Zhaocai Wang; Yuan Hu; Sen Tao; Jinghan Dong (Water Resources Management, 2023)

Optimal Design of Groundwater Quality Monitoring Network Using Aquifer Vulnerability Map - Hedi Mahmoudpour; Somaye Janatrostami; Afshin Ashrafzadeh (Water Resources Management, 2023)

Novel Methods for Imputing Missing Values in Water Level Monitoring Data - Thakolpat Khampuengson; Wenjia Wang (Water Resources Management, 2023)
Hydrological data are collected automatically from remote water level monitoring stations and then transmitted to the national water management centre via telemetry system. However, the data received at the centre can be incomplete or anomalous due to some issues with the instruments such as power and sensor failures. Usually, the detected anomalies or missing data are just simply eliminated from the data, which could lead to inaccurate analysis or even false alarms. Therefore, it is very helpful to identify missing values and correct them as accurate as possible. In this paper, we introduced a new approach - Full Subsequence Matching (FSM), for imputing missing values in telemetry water level data. The FSM firstly identifies a sequence of missing values and replaces them with some constant values to create a dummy complete sequence. Then, searching for the most similar subsequence from the historical data. Finally, the identified subsequence will be adapted to fit the missing part based on their similarity. The imputation accuracy of the FSM was evaluated with telemetry water level data and compared to some well-established methods - Interpolation, k-NN, MissForest, and also a leading deep learning method - the Long Short-Term Memory (LSTM) technique. Experimental results show that the FSM technique can produce more precise imputations, particularly for those with strong periodic patterns.

Fingerprinting Sources of Fine-grained Sediment Deposited in a Riverine System by GLUE - Seyed Masoud Soleimanpour; Hamid Gholami; Omid Rahmati; Samad Shadfar (Water Resources Management, 2023)

White Elephant or Golden Goose? An Assessment of Middle Route of the South-to-North Water Diversion Project from the Perspective of Regional Water Use Efficiency - Zhe Cheng; Yuntong Zhao; Tao Song; Le Cheng; Wenbin Wang (Water Resources Management, 2023)

Optimal Inversion of Manning’s Roughness in Unsteady Open Flow Simulations Using Adaptive Parallel Genetic Algorithm - Lishuang Yao; Yang Peng; Xianliang Yu; Zhihong Zhang; Shiqi Luo (Water Resources Management, 2023)

Win–win Strategies for Transboundary Water Management During the GERD Operating Stage - Walaa El-Nashar; Ahmed Elyamany (Water Resources Management, 2023)
The list of challenges associated with the operation of the Grand Ethiopian Resistance Dam (GERD) now includes global concern over climate change. Due to their inability to reach a legally enforceable agreement on how to address watershed degradation and water quality, riparian nations are already experiencing peace and security issues. A win–win strategy seeks to develop collaborative solutions to transboundary water management problems while maximizing the benefits for both parties. This paper aims to develop, evaluate, and analyze win–win transboundary water management strategies during the operating stage of GERD. Using value engineering (VE), functional analysis system technique (FAST), and life cycle cost (LCC), the optimal win–win strategy is determined. The study uncovered four distinct value options for various win–win strategies. According to the study results, the third win–win strategy is the most effective way to help both upstream and downstream nations retain peace, as it seeks to encourage riparian countries to collaborate by: i) developing cooperative regulatory policy; ii) switching to renewable energy supported by GERD; and iii) reducing water loss. This study advances our understanding of the topic by providing policymakers with a tool to: i) evaluate win–win strategies for managing transboundary water; and ii) incorporate the added value and functionality into policies regarding transboundary water management.

Impact of Installing Rainwater Harvesting System on Urban Water Management - Sara Lopes Souto; Ricardo Prado Abreu Reis; Marcus André Siqueira Campos (Water Resources Management, 2023)

Urban Rainwater Harvesting Adoption Potential in a Socio-economically Diverse City Using a GIS-based Multi-criteria Decision Method - Annah Ndeketeya; Morgan Dundu (Water Resources Management, 2023)

Evaluation of the Velocity Parameter Estimation Methods in a Geomorphological Instantaneous Unit Hydrograph (GIUH) Model for Simulating Flood Hydrograph in Ungauged Catchments - B. Grum; B. A. Abebe; A. M. Degu; H. Goitom; K. Woldearegay; R. Hessel; C. J. Ritsema; V. Geissen (Water Resources Management, 2023)

Joint-Probabilistic Double-Sided Random Interval Programming for Booster Optimization in Water Distribution Network - Yumin Wang (Water Resources Management, 2023)

Comparison of the capability of the Meteorological and Remote Sensing Drought Indices - Abdol Rassoul Zarei; Marzieh Mokarram; Mohammad Reza Mahmoudi (Water Resources Management, 2023)

Three-dimensional Reverse Modeling and Hydraulic Analysis of the Intake Structure of Pumping Stations on Sediment-laden Rivers - Cundong Xu; Junjiao Tian; Zijin Liu; Rongrong Wang; Guoxia Wang (Water Resources Management, 2023)

Advanced Machine Learning Model for Prediction of Drought Indices using Hybrid SVR-RSM - Jamshid Piri; Mohammad Abdolahipour; Behrooz Keshtegar (Water Resources Management, 2023)

An Assessment of the Integrated Multi-Criteria and New Models Efficiency in Watershed Flood Mapping - Karim Solaimani; Fatemeh Shokrian; Shadman Darvishi (Water Resources Management, 2023)

Nonstationary Regional Flood Frequency Analysis Based on the Bayesian Method - Shuhui Guo; Lihua Xiong; Jie Chen; Shenglian Guo; Jun Xia; Ling Zeng; Chong-Yu Xu (Water Resources Management, 2023)

Short-term Runoff Prediction Optimization Method Based on BGRU-BP and BLSTM-BP Neural Networks - Sheng He; Xuefeng Sang; Junxian Yin; Yang Zheng; Heting Chen (Water Resources Management, 2023)
Runoff forecasting is one of the important non-engineering measures for flood prevention and disaster reduction. The accurate and reliable runoff forecasting mainly depends on the development of science and technology, many machine learning models have been proposed for runoff forecasting in recent years. Considering the non-linearity and real-time of hourly rainfall and runoff data. In this study, two runoff forecasting models were proposed, which were the combination of the bidirectional gated recurrent unit and backpropagation (BGRU-BP) neural network and the bidirectional long short-term memory and backpropagation (BLSTM-BP) neural network. The two models were compared with the gated recurrent unit (GRU), long short-term memory (LSTM), bidirectional gated recurrent unit (BGRU), and bidirectional long short-term memory (BLSTM) models. The research methods were applied to simulate runoff in the Yanglou hydrological station, Northern Anhui Province, China. The results show that the bidirectional models were superior to the unidirectional model, and the backpropagation (BP) based bidirectional models were superior to the bidirectional models. The bidirectional propagation was conducive to improving the generalization ability of the model, and BP neural network could better guide the model to find the optimal nonlinear relationship. The results also show that the BGRU-BP model performs equally well as the BLSTM-BP model. The BGRU-BP model has few parameters and a short training time, so it may be the preferred method for short-term runoff forecasting.

Hydropower Contribution to the Renewable Energy Transition Under Climate Change - José Pedro Ramião; Cláudia Carvalho-Santos; Rute Pinto; Cláudia Pascoal (Water Resources Management, 2023)

LSTM-AE-WLDL: Unsupervised LSTM Auto-Encoders for Leak Detection and Location in Water Distribution Networks - Maryam Kammoun; Amina Kammoun; Mohamed Abid (Water Resources Management, 2023)

Using AHP-PROMOTHEE for Selection of Best Low-Impact Development Designs for Urban Flood Mitigation - Yashar Dadrasajirlou; Hojat Karami; Seyedali Mirjalili (Water Resources Management, 2023)

Effect of Gradient Descent Optimizers and Dropout Technique on Deep Learning LSTM Performance in Rainfall-runoff Modeling - Duong Tran Anh; Dat Vi Thanh; Hoang Minh Le; Bang Tran Sy; Ahad Hasan Tanim; Quoc Bao Pham; Thanh Duc Dang; Son T. Mai; Nguyen Mai Dang (Water Resources Management, 2023)

Coupling the Causal Inference and Informer Networks for Short-term Forecasting in Irrigation Water Usage - Liangfeng Zou; Yuanyuan Zha; Yuqing Diao; Chi Tang; Wenquan Gu; Dongguo Shao (Water Resources Management, 2023)

Data Decomposition, Seasonal Adjustment Method and Machine Learning Combined for Runoff Prediction: A Case Study - Hao Yang; Weide Li (Water Resources Management, 2023)

Study on Agricultural Drought Risk Assessment Based on Information Entropy and a Cluster Projection Pursuit Model - Wei Pei; Lei Hao; Qiang Fu; Yongtai Ren; Tianxiao Li (Water Resources Management, 2023)

Attribution Analysis of Streamflow Changes Based on Large-scale Hydrological Modeling with Uncertainties - Manlin Wang; Yu Zhang; Yan Lu; Li Gao; Leizhi Wang (Water Resources Management, 2023)

Water Quality Modeling in Atlantic Region: Review, Science Mapping and Future Research Directions - Hanane Rhomad; Karima Khalil; Khalid Elkalay (Water Resources Management, 2023)

Evolutionary Game Analysis of Inter-provincial Diversified Ecological Compensation Collaborative Governance - Yali Lu; Linfang Fan; Luyu Zhai (Water Resources Management, 2023)

Pressure-driven Background Leakage Models and their Application for Leak Localization Using a Multi-population Genetic Algorithm - Yihong Guan; Mou Lv; Shen Dong (Water Resources Management, 2023)

Estimating the Temporal and Spatial Variations in Evapotranspiration with a Nonlinear Evaporation Complementary Relationship Model in Hyper-arid Areas - Liu Yunfei; Gui Dongwei; Yin Changjun; Zhang Lei; Xue Dongping; Liu Yi; Zeng Fanjiang; Zeeshan Ahmed; Chen Xiaoping (Water Resources Management, 2023)

Drought-Stricken U.S. States Have More Comprehensive Water-Related Hazard Planning - Theresa Jedd; Kelly Helm Smith (Water Resources Management, 2023)
Despite the devastating impacts of droughts, the United States lacks a national drought plan. This leaves states to address droughts in water, hazard, and stand-alone plans which are designed to reduce drought vulnerability and to prepare government, industry, and society to cope with the impacts. Yet, there is limited empirical research that evaluates the comprehensiveness of these plans, specifically in terms of whether they include preparedness and mitigation measures or triggers for action and response. To fill this gap, this study’s first aim was to establish an evaluation framework based on principles from the drought mitigation literature. The study then evaluated 171 state-level plans with the framework, and simultaneously collected interview data to contextualize the results. In a final step, the scores were employed in a statistical analysis of whether states with higher physical exposure to drought have more comprehensive planning. The study finds states that have experienced more frequent and severe drought plan more comprehensively, suggesting that the occurrence of drought may be an intrinsic driver for planning. The study concludes that planning and preparing for droughts is a necessary but complex undertaking requiring interdisciplinary, interagency efforts that the U.S.’ decentralized, federalist political system is suited to address. If generalization is warranted, the results suggest that the physical occurrence of drought can act as a policy catalyst.

Is Climate Dominating the Spatiotemporal Patterns of Water Yield? - Lei Wu; Xia Liu; Zhi Yang; Yang Yu; Xiaoyi Ma (Water Resources Management, 2023)

Investigating the Effectiveness of Irrigation Restriction Length on Water Use Behavior - Xiangwen Kong; Chengyan Yue; Eric Watkins; Mike Barnes; Yufeng Lai (Water Resources Management, 2023)

Municipal Water Use Kuznets Curve - Zikun Song; Shaofeng Jia (Water Resources Management, 2023)

Rainfall-Derived Infiltration and Inflow Estimate in a Sanitary Sewer System Using Three Impulse Response Functions Derived from Physics-Based Models - Namjeong Choi; Arthur R. Schmidt (Water Resources Management, 2023)

Generalized Daily Reference Evapotranspiration Models Based on a Hybrid Optimization Algorithm Tuned Fuzzy Tree Approach - Dilip Kumar Roy; Tapash Kumar Sarkar; Sujit Kumar Biswas; Bithin Datta (Water Resources Management, 2023)

Leveraging Unsupervised Learning to Develop a Typology of Residential Water Users’ Attitudes Towards Conservation - Renee Obringer; Dave D. White (Water Resources Management, 2023)

Water Intensity Indicators in the Global Retail Sector - Ana Ferreira; Manuel Duarte Pinheiro; Jorge de Brito; Ricardo Mateus; Vitor Sousa (Water Resources Management, 2023)

Analysis of Identification and Driving Factors of Ecological Base Flow Noncompliance in Major Rivers of China - Pu Zhang; Yinglan A; Jianhua Wang; Huan Liu; Qin Yang; Zefan Yang; Qinghui Zeng; Peng Hu (Water Resources Management, 2023)

A Low-Return-Period Rainfall Intensity Formula for Estimating the Design Return Period of the Combined Interceptor Sewers - Xingpo Liu; Chenmeng Ouyang; Yuwen Zhou (Water Resources Management, 2023)

Optimal Treated Wastewater Allocation Among Stakeholders Based on an Agent-based Approach - Nafiseh Bahrami; Mohammad Reza Nikoo; Ghazi Al-Rawas; Khalifa Al-Jabri; Amir H. Gandomi (Water Resources Management, 2023)

Intelligent Scheduling of Urban Drainage Systems: Effective Local Adaptation Strategies for Increased Climate Variability - Kun Xie; Jong-Suk Kim; Linjuan Hu; Hua Chen; Chong-Yu Xu; Jung Hwan Lee; Jie Chen; Sun-Kwon Yoon; Di Zhu; Shaobo Zhang; Yang Liu (Water Resources Management, 2023)

Comparison of Irrigation Management in Water User Associations of Italy, Spain and Turkey Using Benchmarking Techniques - Firat Arslan; Juan Ignacio Córcoles Tendero; Juan Antonio Rodríguez Díaz; Demetrio Antonio Zema (Water Resources Management, 2023)

Environmental Flows Allocation for a Tropical Reservoir System by Integration of Water Quantity (SWAT) and Quality (GEFC, QUAL2K) Models - Mummidivarapu Satish Kumar; P. N. Chandi Priya; Rehana Shaik; Shailesh Kumar Singh (Water Resources Management, 2023)

Improving Short-range Reservoir Inflow Forecasts with Machine Learning Model Combination - M. Rajesh; Sachdeva Anishka; Pansari Satyam Viksit; Srivastav Arohi; S. Rehana (Water Resources Management, 2023)

Sustainable Management and Environmental Protection for Basin Water Allocation: Differential Game-based Multiobjective Programming - Danyang Di; Qi Shi; Zening Wu; Huiliang Wang (Water Resources Management, 2023)

Refined Scheduling Based on Dynamic Capacity Model for Short-term Hydropower Generation - Rongqi Zhang; Shanghong Zhang; Xiaoxiong Wen; Zhu Jing (Water Resources Management, 2023)

Retraction Note to: Recommendations for Modifying the Standardized Precipitation Index (SPI) for Drought Monitoring in Arid and Semi‑arid Regions - Peyman Mahmoudi; Alireza Ghaemi; Allahbakhsh Rigi; Seyed Mahdi Amir Jahanshahi (Water Resources Management, 2022)

Integrated Water Resources Management Based on Water Governance and Water-food-energy Nexus through System Dynamics and Social Network Analyzing Approaches - Marzieh Samadi-Foroushani; Mohammad Javad Keyhanpour; Seyed Habib Musavi-Jahromi; Hossein Ebrahimi (Water Resources Management, 2022)

Spatial Distributions, Sources and Risk Assessment of Toxic Elements in Waters of a Central Asian Basin - Beibei Shen; Jinglu Wu; Shuie Zhan; Miao Jin (Water Resources Management, 2022)

Correction to: A New Approach for Dam Safety Assessment Using the Extended Cloud Model - Liansheng SangJun; Jun Wang; Jueyi Sui; Mauricio Dziedzic (Water Resources Management, 2022)

Improved Convolutional Neural Network and its Application in Non-Periodical Runoff Prediction - Yichao Xu; Yi Liu; Zhiqiang Jiang; Xin Yang; Xinying Wang; Yunkang Zhang; Yangyang Qin (Water Resources Management, 2022)

On the Effectiveness of Domestic Rainwater Harvesting Systems to Support Urban Flood Resilience - Anna Palla; Ilaria Gnecco (Water Resources Management, 2022)
The effectiveness of domestic rainwater harvesting (DRWH) systems to support urban flood resilience is analysed at the sub-catchment scale, according to a specific DRWH conversion scenario, under 4 degrees of urbanization, 3 drainage network configurations, 4 precipitation regimes and 3 return periods of the rainfall event. At this aim, a suitable modelling framework is implemented: the semi-distributed hydrologic-hydraulic model is undertaken using EPASWMM 5.1.007 where specific tools are developed to simulate DRWH systems at high spatial resolution. The effectiveness of the DRWH systems simulated for the 144 different cases, is analysed at the event scale by using the Volume and Peak Reduction indexes to measure the hydrologic performance. The dimensionless variable, namely the event storage fraction, is defined in order to easily describe the DRWH effectiveness. The event storage fraction is defined as the ratio between the event runoff volume resulting from the impervious surface of the urban catchment in the reference scenario and the storage capacity of the DRWH systems. Modelling results confirm that DRWH catchment-scale applications allow to support specific stormwater control requirements based on peak-flow or volume regulations strategies. Findings of the elaboration reveal for a typical residential catchment in the Italy-France cross-border coastal area, that DRWH effectiveness in supporting the urban flood management becomes significant (i.e. Volume and Peak Reduction indexes greater than 0.2) starting from a storage event fraction of 0.4 that means realizing storage tanks able to contain at least the 40% of runoff volume generated by the targeted event at the sub-catchment scale.

A Model Combination Approach for Improving Streamflow Prediction - Akshay Kadu; Basudev Biswal (Water Resources Management, 2022)

Investigation of Infrastructural and Management Actions to Increase the Resilience of Existing Pressurized Irrigation Networks - Younes Aminpour; Nicola Lamaddalena; Eisa Maroufpoor (Water Resources Management, 2022)

The New Bias Correction Method for Daily Extremes Precipitation over South Korea using CMIP6 GCMs - Young Hoon Song; Eun-Sung Chung; Shamsuddin Shahid (Water Resources Management, 2022)

Extreme Rainfall Variations Under Climate Change Scenarios. Case of Study in an Andean Tropical River Basin - Martín Montenegro; Daniel Mendoza; Diego Mora; Fernando García; Alex Avilés (Water Resources Management, 2022)

Agricultural Drought Characteristics Analysis Using Copula - Ihsan F. Hasan; Rozi Abdullah (Water Resources Management, 2022)

Genetic Algorithm Based Model for Optimal Selection of Open Channel Design Parameters - Aly K. Salem; Yehya E. Imam; Ashraf H. Ghanem; Abdallah S. Bazaraa (Water Resources Management, 2022)
Open channels are one of the most used water conveyance systems for delivering water for different purposes. Existing models for the design of open channels mainly assume uniform flow, focus on cross-section sizing, and generally decouple cross-section sizing from the selection of channel alignment and profile. In this study, we developed an optimization model for a comprehensive design of transmission channels. The model minimizes the sum of costs for earthwork, lining, water losses, and land acquisition; accounts for non-uniform, mixed-regime flow; and considers multiple geometric and hydraulic constraints. The model was validated using several idealized scenarios. The model potential in minimizing the cost of real open channel projects was demonstrated through application to an existing irrigation water transmission canal in Egypt (the Sheikh Zayed Canal). The results of validation scenarios matched the anticipated outcomes for channel profile and alignment and reproduced analytical solutions given in the literature for channel cross-section design. Application of the model to the Sheikh Zayed Canal gave a more optimal design; the OCCD model produced a design alternative with ~27% less cost than the constructed alternative.

Assessment of Long-term Groundwater Use Increase and Forest Growth Impact on Watershed Hydrology - Wonjin Kim; Seongjoon Kim; Jinuk Kim; Jiwan Lee; Soyoung Woo; Sehoon Kim (Water Resources Management, 2022)

Improved Whale Algorithm for Economic Load Dispatch Problem in Hydropower Plants and Comprehensive Performance Evaluation - Kun Yang; Kan Yang (Water Resources Management, 2022)

Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms - Prabal Das; D. A. Sachindra; Kironmala Chanda (Water Resources Management, 2022)

Low-Impact Optimal Operation of a Cascade Sluice-Reservoir System for Water-Society-Ecology Trade-Offs - Xiang Zhang; Liangkun Deng; Bi Wu; Shichun Gao; Yi Xiao (Water Resources Management, 2022)

Towards Linking the Sustainable Development Goals and a Novel-Proposed Snow Avalanche Susceptibility Mapping - Hüseyin Akay (Water Resources Management, 2022)

Global Sensitivity Analysis of a Coupled Hydro-Economic Model and Groundwater Restriction Assessment - José M. Rodríguez-Flores; Jorge A. Valero Fandiño; Spencer A. Cole; Keyvan Malek; Tina Karimi; Harrison B. Zeff; Patrick M. Reed; Alvar Escriva-Bou; Josué Medellín-Azuara (Water Resources Management, 2022)
Assessing impacts on coupled food-water systems that may emerge from water policies, changes in economic drivers and crop productivity requires an understanding of dominant uncertainties. This paper assesses how a candidate groundwater pumping restriction and crop prices, crop yields, surface water price, electricity price, and parametric uncertainties shape economic and groundwater performance metrics from a coupled hydro-economic model (HEM) through a diagnostic global sensitivity analysis (GSA). The HEM used in this study integrates a groundwater depth response, modeled by an Artificial Neural Network (ANN), into a calibrated Positive Mathematical Programming (PMP) agricultural production model. Results show that in addition to a groundwater pumping restriction, performance metrics are highly sensitive to prices and yields of perennial tree crops. These sensitivities become salient during dry years when there is a higher reliance on groundwater. Furthermore, results indicate that performing a GSA for two different water baseline conditions used to calibrate the production model, dry and wet, result in different sensitivity indices magnitudes and factor prioritization. Diagnostic GSA results are used to understand key factors that affect the performance of a groundwater pumping restriction policy. This research is applied to the Wheeler Ridge-Maricopa Water Storage District located in Kern County, California, region reliant on groundwater and vulnerable to surface water shortages.

Hydrological Response and Ecological Flow Optimization in Water Diversion Area of Inter-basin Water Diversion Project - Tao Bai; Xian-Ge Sun; Jian Wei; Lianzhou Wu (Water Resources Management, 2022)

Bi-objective Extraction-injection Optimization Modeling for Saltwater Intrusion Control Considering Surrogate Model Uncertainty - Jina Yin; Frank T.-C. Tsai; Chunhui Lu (Water Resources Management, 2022)

Optimized Model Inputs Selections for Enhancing River Streamflow Forecasting Accuracy Using Different Artificial Intelligence Techniques - Yahia Mutalib Tofiq; Sarmad Dashti Latif; Ali Najah Ahmed; Pavitra Kumar; Ahmed El-Shafie (Water Resources Management, 2022)

Novel Eulerian Approach with Cellular Automata Modelling to Estimate Water Quality in a Drinking Water Network - M. A. Bonora; G. Capano; A. De Rango; Mario Maiolo (Water Resources Management, 2022)
The forecast analysis of the exposure to the contamination risk in a water distribution network requires increasing the quality of the applied input/outputs modeling. This need involves using non-traditional models responding to the increasingly high computation requirements. In this scenario, the Cellular Automata paradigm represents a new frontier with considerable potential. Specifically, this paper describes the Eulerian Water quAlity Modeling—Cellular Automata (EWAM-CA) model, aimed at simulating the sodium hypochlorite (chlorine) injection, transport, and reaction phase in a medium-sized drinking water network. The EWAM-CA accuracy was compared with the Epanet software on a Fossolo water network, in Bologna town (Italy), considering a constant and an impulsive input respectively. Due to CA's intrinsic aptitude for parallel computing, a parallel version of EWAM-CA was developed. Moreover, using the capability of the cellular automata to manage the modeling asynchronously, improving the computational efficiency, we propose a novel approach based on activation/deactivation asynchronous rules, avoiding unnecessary calculations in nodes or pipes where no pollution occurs. The different EWAM-CA versions were compared for the case study, and the parallel EWAM-CA approach coupled with asynchronous functionality significantly improved computational performance.

Comparison of the Performance of a Surrogate Based Gaussian Process, NSGA2 and PSO Multi-objective Optimization of the Operation and Fuzzy Structural Reliability of Water Distribution System: Case Study for the City of Asmara, Eritrea - Ngandu Balekelayi; Haile Woldesellasse; Solomon Tesfamariam (Water Resources Management, 2022)

A New Approach for Dam Safety Assessment Using the Extended Cloud Model - Liansheng Sang; Jun Wang; Jueyi Sui; Mauricio Dziedzic (Water Resources Management, 2022)

Optimal Energy Storage Operation Chart and Output Distribution of Cascade Reservoirs Based on Operating Rules Derivation - Yuxin Zhu; Jianzhong Zhou; Yongchuan Zhang; Zhiqiang Jiang; Benjun Jia; Wei Fang (Water Resources Management, 2022)

Wetting Patterns in a Subsurface Irrigation System Using Reservoirs of Different Permeabilities: Experimental and HYDRUS-2D/3D Modeling - Zahra Jafari; Sayed Hamid Matinkhah; Mohammad Reza Mosaddeghi (Water Resources Management, 2022)

Nonparametric Approach to Copula Estimation in Compounding The Joint Impact of Storm Surge and Rainfall Events in Coastal Flood Analysis - Shahid Latif; Slobodan P. Simonovic (Water Resources Management, 2022)

Research on the Ecological Flow and Water Replenishment Thresholds for Diversion Rivers Based on the MC-LOR Algorithm - Wentong Hu; Wenquan Gu; Donghao Miao; Dongguo Shao (Water Resources Management, 2022)

A Comparison of Model-Based Methods for Leakage Localization in Water Distribution Systems - Irene Marzola; Stefano Alvisi; Marco Franchini (Water Resources Management, 2022)
Model-based methods for leakage localization in water distribution systems have recently been gaining more attention. These methods identify the leakage position by comparing the measured network data with the corresponding values simulated by a hydraulic model. In this study two model-based methods already proposed in literature, one based on the Sensitivity Matrix method and the other one on the Linear Approximation method, are analysed and compared to each other. The methods are applied to the same case study network, exploiting only data provided by pressure sensors. Various analyses are undertaken in order to investigate the main critical issues tied to the two methods, i.e. a) the use of different amounts of data averaged over different time windows, b) the impact of the model’s accuracy in terms of water demands and pipe roughness, and c) the effect of the number of pressure measuring points. The results show that higher efficiency is obtained by considering the hourly averaged data all together. Moreover, the Linear Approximation method is on average 3 times more accurate than the Sensitivity Matrix when a perfect hydraulic model is used, even with a reduced number of pressure sensors. However, when a hydraulic model and/or measured data affected by errors are considered, the Sensitivity Matrix is more accurate, with an average error almost 10% lower than the Linear Approximation.

A Coupled Hydrodynamic and Rainfall-tracking Model for Source-to-impact Analysis in Urban Inundation - Xinghua Wang; Jingming Hou; Donglai Li; Bingyao Li; Xujun Gao; Yuan Liu (Water Resources Management, 2022)

Evaluating Surface Water-groundwater Interactions in Consequence of Changes in Climate and Groundwater Extraction - Chanchai Petpongpan; Chaiwat Ekkawatpanit; Ryan T. Bailey; Duangrudee Kositgittiwong; Phayom Saraphirom (Water Resources Management, 2022)

A Multi-Indicator, Non-Cooperative Game Model to Resolve Conflicts for Aquifer Restoration - Hamid Kardan Moghaddam; Saman Javadi; Timothy O. Randhir; Neda Kavehkar (Water Resources Management, 2022)

Changing Pattern of Intensity–Duration–Frequency Relationship of Precipitation due to Climate Change - Subhra Sekhar Maity; Rajib Maity (Water Resources Management, 2022)

Application of Machine Learning-based Energy Use Forecasting for Inter-basin Water Transfer Project - Sooyeon Yi; G. Mathias Kondolf; Samuel Sandoval-Solis; Larry Dale (Water Resources Management, 2022)
Energy use forecasting is crucial in balancing the electricity supply and demand to reduce the uncertainty inherent in the inter-basin water transfer project. Energy use prediction supports the reliable water-energy supply and encourages cost-effective operation by improving generation scheduling. The objectives are to develop subsequent monthly energy use predictive models for the Mokelumne River Aqueduct in California, US. Partial objectives are to (a) compare the model performance of a baseline model (multiple linear regression (MLR)) to three machine learning-based models (random forest (RF), deep neural network (DNN), support vector regression (SVR)), (b) compare the model performance of the whole system to three subsystems (conveyance, treatment, distribution), and (c) conduct sensitivity analysis. We simulate a total of 64 cases (4 algorithms (MLR, RF, DNN, SVR) x 4 systems (whole, conveyance, treatment, distribution) x 4 scenarios (different combinations of independent variables). We concluded that the three machine learning algorithms showed better model performance than the baseline model as they reflected non-linear energy use characteristics for water transfer systems. Among the three machine learning algorithms, DNN models yielded higher model performance than RF and SVR models. Subsystems performed better than the whole system as the models more closely reflected the unique energy use characteristics of the subsystems. The best case was having water supply (t), water supply (t-1), precipitation (t), temperature (t), and population (y) as independent variables. These models can help water and energy utility managers to understand energy performance better and enhance the energy efficiency of their water transfer systems.

Determining Groundwater Recharge Rate with a Distributed Model and Remote Sensing Techniques - M. Babaei; H. Ketabchi (Water Resources Management, 2022)

Hydraulic jump over an adverse slope controlled by different roughness elements - Parastoo Parsamehr; Alban Kuriqi; Davoud Farsadizadeh; Ali Hosseinzadeh Dalir; Rasoul Daneshfaraz; Rui M. L. Ferreira (Water Resources Management, 2022)

Assessment of Flooding Impact on Water Supply Systems: A Comprehensive Approach Based on DSS - Silvia Barbetta; Bianca Bonaccorsi; Stavroula Tsitsifli; Ivana Boljat; Papakonstantinou Argiris; Jasmina Lukač Reberski; Christian Massari; Emanuele Romano (Water Resources Management, 2022)
The assessment of flood impact on a Water Supply System (WSS) requires a comprehensive approach including several scales of analysis and models and should be managed in the Water Safety Plans (WSP), as recommended in the EU Water Directive 2020/2184. Flooding can affect the quality of groundwater and surface water resources and can cause supply service interruption due to damaged infrastructures. A complete approach to address flood impact on WSS is required but not yet available, while only specific aspects were investigated in details. This work introduces a comprehensive tool named WAter Safety Planning Procedures Decision Support System (WASPP–DSS) developed in the context of MUHA (Multihazard framework for Water Related risks management) project. The tool is mainly addressed to small water utilities (WU) for supporting WSP development and is based on two main premises: 1) a correct approach for WSS risk analysis requires a multi-hazard perspective encompassing all the system components and different hazards; 2) other institutions in addition to WUs have to be involved in WSS risk analyses to harmonize monitoring and response procedures. The tool is here applied on risks associated to flooding and demonstrated for three case studies. The WASPP–DSS, tested by eight WUs, was found a potentially valid support for small WUs that must start drafting the WSP in a comprehensive way and can provide a common shared scheme. Improvements are desirable, as including a specific section to consider the issue of loss of water resources from reservoirs due to overflow.

A Long-term Global Comparison of IMERG and CFSR with Surface Precipitation Stations - Uttam Ghimire; Taimoor Akhtar; Narayan Kumar Shrestha; Pranesh Kumar Paul; Christoph Schürz; Raghavan Srinivasan; Prasad Daggupati (Water Resources Management, 2022)

Impact of Spatial Variation and Uncertainty of Rainfall Intensity on Urban Flooding Assessment - Ruozhou Lin; Feifei Zheng; Yiyi Ma; Huan-Feng Duan; Shipeng Chu; Zhengzhi Deng (Water Resources Management, 2022)

Enhancing the Urban Resilience to Flood Risk Through a Decision Support Tool for the LID-BMPs Optimal Design - Francesco Pugliese; Carlo Gerundo; Francesco De Paola; Gerardo Caroppi; Maurizio Giugni (Water Resources Management, 2022)

Study on Ecological Allocation of Mine Water in Mining Area Based on Long-term Rainfall Forecast - Guan-jun Lei; Chang-shun Liu; Wenchuan Wang; Jun-xian Yin; Hao Wang (Water Resources Management, 2022)

Spatial Prediction of the Groundwater Potential Using Remote Sensing Data and Bivariate Statistical-Based Artificial Intelligence Models - Yong Ye; Wei Chen; Guirong Wang; Weifeng Xue (Water Resources Management, 2022)

Validation of Computational Fluid Dynamics Approach of Lateral Velocity Profile Due to Curvature Effect on Floodplain Levee of Two-stage Meandering Channel - Shriya K. Rathor; Abinash Mohanta; K. C. Patra (Water Resources Management, 2022)

Burst Area Identification of Water Supply Network by Improved DenseNet Algorithm with Attention Mechanism - Jing Cheng; Sen Peng; Rui Cheng; Xingqi Wu; Xu Fang (Water Resources Management, 2022)

A Novel Approach to the Optimization of the Spatial Distribution of the Multiple Crop Pattern on a River Basin Scale - Motahareh Saadatpour; Fardin Kamali (Water Resources Management, 2022)

Forecasting Hourly Intermittent Rainfall by Deep Belief Networks with Simple Exponential Smoothing - Guo-Yu Huang; Chi-Ju Lai; Ping-Feng Pai (Water Resources Management, 2022)

Correction of Reservoir Runoff Forecast Based on Multi-scenario Division and Multi Models - Suiling Wang; Zhiqiang Jiang; Hairong Zhang (Water Resources Management, 2022)

Investigation of Topographical Controls on the Groundwater Potential Zone in a Hilly Watershed Using a Geospatial and Geophysical Approach - Roshani Singh; Aditya Kumar Anand; Pallavi Banerjee Chattopadhyay (Water Resources Management, 2022)

Sensor Partitioning Placements via Random Walk and Water Quality and Leakage Detection Models within Water Distribution Systems - Tianwei Mu; Manhong Huang; Shi Tang; Rui Zhang; Gang Chen; Baiyi Jiang (Water Resources Management, 2022)

System Archetypes Underlying Formal-Informal Urban Water Supply Dynamics - Rakhshinda Bano; Mehdi Khiadani; Yong Sebastian Nyam (Water Resources Management, 2022)
Contrary to developed countries, developing countries have been observed to have an increased reliance on a diversity of water supply options to meet their daily demands, where formal supply systems are incapable of fulfilling the daily needs of consumers. In filling a demand-supply gap, informal supply systems are increasingly being associated with issues of long-term sustainability, higher consumer cost, and inequity. Emerging formal-informal dynamics in developing countries require a thorough understanding of complex human-water interactions for policy direction, in order to best support the advancement of urban water sustainability. Accordingly, system archetypes offer a platform to explain the behaviors of complex systems. This paper identifies common system archetypes that define urban waterscapes in the developing world. In this way, Causal Loop Diagrams (CLDs) are used to present relationships and identify common archetypes that define the complexity of urban water supply systems in Hyderabad, Pakistan. These archetypes include ‘fixes that fail’, ‘shifting the burden’, ‘limits to growth/success’ and ‘growth and underinvestment’. These archetypes demonstrate that increases in formal infrastructure capacity and the number of informal suppliers to increase supply reliability are symptomatic solutions, restrained by financial and technical resources, and thus have unintended consequences. Further, a number of policy instruments are discussed as leverage points to achieve financial sustainability of formal systems. This paper emphasizes the need of a policy framework for informal supply system in national and regional water policies to ensure its service reliability as a short to medium term solution.

A Triple-stage Operation Method for Deriving Operation Rules for Cascade Reservoirs during Catastrophic Flood Events - Di Zhu; Hua Chen; Yanlai Zhou; Yadong Mei; Xinfa Xu; Shenglian Guo (Water Resources Management, 2022)

Assessing Economic Feasibility of Managed Aquifer Recharge Schemes: Evidence from Cost-benefit Analysis in Poland - Olha Halytsia; Maria Vrachioli; Krzysztof Janik; Sławomir Sitek; Grzegorz Wojtal; Anne Imig; Arno Rein; Johannes Sauer (Water Resources Management, 2022)
The accelerated growth of water demand globally calls for promising solutions in the field of water management. Managed aquifer recharge (MAR) systems are among the solutions that are capable of increasing water supply and improving water quality through natural attenuation processes. Along with hydrogeologic considerations and institutional feasibility assessments, economic analysis is essential when evaluating MAR projects. This study is the first one to provide an economic feasibility assessment of a MAR scheme in Poland by performing a cost-benefit analysis (CBA) combined with a contingent valuation study to identify the willingness-to-pay, sensitivity analysis to address uncertainty regarding the realisation of benefits and costs together with expert assessment of socio-economic risks associated with the MAR scheme implementation. The results suggest that the total economic value of the MAR scheme’s extension (which includes both use and non-use benefits) exceeds the costs of putting this system in place and maintaining it. This paper can contribute to the existing literature as a practical example providing the base for economic assessment and policy considerations of future sustainable water management projects.

How Did Balance Loss Occur? A Cross-stakeholder Analysis of Risk Misallocation in a Sponge City PPP Project - Yang Wang; Qingying Li; Jian Zuo; Katharine Bartsch (Water Resources Management, 2022)

Performance Indexes Analysis of the Reservoir-Hydropower Plant System Affected by Climate Change - Parvin Golfam; Parisa-Sadat Ashofteh (Water Resources Management, 2022)

Distribution and Prediction of Boundary Shear in Diverging Compound Channels - B. Sree Sai Prasad; Anurag Sharma; Kishanjit Kumar Khatua (Water Resources Management, 2022)

An Adaptive Dynamic Kriging Surrogate Model for Application to the Optimal Remediation of Contaminated Groundwater - Shuangsheng Zhang; Jing Qiang; Hanhu Liu; Xiaonan Wang; Junjie Zhou; Dongliang Fan (Water Resources Management, 2022)

Past and Future Global Drought Assessment - Mohammad Amin Asadi Zarch (Water Resources Management, 2022)

Methodology to Optimize Rainwater Tank-sizing and Cluster Configuration for a Group of Buildings - Jersain Gómez Núñez; Magdalena García Martínez; Rojacques Mompremier; Beatriz A. González Beltrán; Icela Dagmar Barceló Quintal (Water Resources Management, 2022)

A Pipe Ranking Method for Water Distribution Network Resilience Assessment Based on Graph-Theory Metrics Aggregated Through Bayesian Belief Networks - Alessandro Pagano; Raffaele Giordano; Ivan Portoghese (Water Resources Management, 2022)
The resilience assessment is crucial for many infrastructures, including water supply and distribution networks. In particular, the identification of the ‘critical’ components (nodes or pipes) whose failure may negatively affect network performances and system resilience is a key issue, with a direct relevance for decision-makers involved in planning, management and improvement activities. Among the multiple methods and tools available, the use of graph-theory metrics is a cutting-edge research topic, as the analysis of topological properties may provide simple yet reliable information on the performance of complex networks. In the present work, we aim to overcome the limit associated to the use of individual graph-theory metrics, identifying a subset of relevant metrics that are directly connected to network resilience properties, using them to perform a ‘network degradation analysis’ in case of single pipe failure and finally proposing an aggregation of the results using a Bayesian Belief Network. Ultimately, the proposed methodology provides a ranking of the most critical pipes, i.e. those that contribute most to system resilience. A real water distribution network in Italy is used for model development and validation.

Ensemble CNN Model for Effective Pipe Burst Detection in Water Distribution Systems - Sehyeong Kim; Sanghoon Jun; Donghwi Jung (Water Resources Management, 2022)

Determining The Main Controlling Factors of Nitrogen Diffusion Fluxes at Sediment-water Interface by Grey Correlation Analysis - Han Wang; Yi Gao; Yuping Han (Water Resources Management, 2022)

Improving Daily and Monthly River Discharge Forecasts using Geostatistical Ensemble Modeling - Farshid Rezaei; Rezvane Ghorbani; Najmeh Mahjouri (Water Resources Management, 2022)

Uncertainty Quantification of Rainfall-runoff Simulations Using the Copula-based Bayesian Processor: Impacts of Seasonality, Copula Selection and Correlation Coefficient - Zhangjun Liu; Jingwen Zhang; Tianfu Wen; Jingqing Cheng (Water Resources Management, 2022)

A Novel Approach to Identify the Characteristics of Drought under Future Climate Change Scenario - Jagadish Padhiary; Kanhu Charan Patra; Sonam Sandeep Dash (Water Resources Management, 2022)

Water Transfer Redistributes Sediment in Small Mountain Reservoirs - Tingyu Li; Gregory B. Pasternack (Water Resources Management, 2022)
Reservoir sedimentation management has become an important topic for large dams in the United States due to their historical design, current age, and increased environmental regulation. Less attention has been paid to small dams (hydraulic size < 0.01) in remote mountains with urgent sedimentation problems. In drier climates, such reservoirs may be frequently drained and trans-catchment flows routed over their sediment deposits heading from one mountain tunnel to another. This study asked an unexplored scientific question focusing on this special setting: how do different amounts of water transfers interact with different reservoir stages to affect sediment erosion and its redistribution in the backwater zone? Mindful timing and magnitude adjustment of water transfer, involving water diverted across watersheds by tunnels, through a reservoir were hypothesized to strategically redistribute sediment erosion for sites with water transfer/diversion facilities in the main channel. For a study site in the north-central Sierra Mountains of California, 2D hydrodynamic modeling revealed that sediment erosion within the backwater zone increased by > 100% when water transfer was maximized, involving a flow 12 times higher than mean annual discharge. With reservoir stage drawdown, the increment of sediment erosion was further increased by > 50% compared with water-transfer-only scenarios. The natural upstream inflow with daily flow occurrence of 5–25% was the optimal water transfer to avoid disturbing sediment. These results indicated that water transfer and stage drawdown optimization is a promising strategy to promote or abate redistribution of deposited sediment through a smaller reservoir.

A Multi-criteria Decision-making Optimization Model for Flood Management in Reservoirs - Banafsheh Nematollahi; Mohammad Reza Nikoo; Amir H. Gandomi; Nasser Talebbeydokhti; Gholam Reza Rakhshandehroo (Water Resources Management, 2022)

Simulation of Actual Evapotranspiration and Evaluation of Three Complementary Relationships in Three Parallel River Basins - Yongshan Jiang; Zhaofei Liu (Water Resources Management, 2022)

Facilitation Model for Supporting Integrative Water Resource Management - Vanessa Batista Schramm; Alexandre de Araújo Gomes Júnior; Fernando Schramm (Water Resources Management, 2022)

Developing Strategies for Agricultural Water Management of Large Irrigation and Drainage Networks with Fuzzy MCDM - Ahmad Radmehr; Omid Bozorg-Haddad; Hugo A. Loáiciga (Water Resources Management, 2022)

Reliability-based Operation of Reservoirs Using Combined Monte Carlo Simulation Model and a Novel Nature-inspired Algorithm - Abolfazl Baniasadi Moghadam; Hossein Ebrahimi; Abbas Khashei Siuki; Abolfazl Akbarpour (Water Resources Management, 2022)

Cost Analysis of Water Quality Assessment Using Multi-Criteria Decision-Making Approach - Seyed Farhan Moosavian; Daryoosh Borzuei; Abolfazl Ahmadi (Water Resources Management, 2022)

New Machine Learning Ensemble for Flood Susceptibility Estimation - Romulus Costache; Alireza Arabameri; Iulia Costache; Anca Crăciun; Binh Thai Pham (Water Resources Management, 2022)

Research on Crop Irrigation Schedules Under Deficit Irrigation—A Meta-analysis - Qian Li; Yan Chen; Shikun Sun; Muyuan Zhu; Jing Xue; Zihan Gao; Jinfeng Zhao; Yihe Tang (Water Resources Management, 2022)

A Hierarchical Index System for Analysis of Water Supply-Demand Situation - Ting Wang; Jinjun You; Zhenzhen Ma; Ping Xiao (Water Resources Management, 2022)

Assessment and Improvement of IDF Generation Algorithms Used in the IDF_CC Tool - Fahad Alzahrani; Ousmane Seidou; Abdullah Alodah (Water Resources Management, 2022)

Comparison of Real-time Control Methods for CSO Reduction with Two Evaluation Indices: Computing Load Rate and Double Baseline Normalized Distance - Zhenliang Liao; Zhiyu Zhang; Wenchong Tian; Xianyong Gu; Jiaqiang Xie (Water Resources Management, 2022)

Daily Streamflow Prediction and Uncertainty Using a Long Short-Term Memory (LSTM) Network Coupled with Bootstrap - Zhuoqi Wang; Yuan Si; Haibo Chu (Water Resources Management, 2022)

The Hysteresis Response of Groundwater to Reservoir Water Level Changes in a Plain Reservoir Area - Yong Huang; Kehan Miao; Xiaoguang Liu; Yin Jiang (Water Resources Management, 2022)

A New Precipitation Prediction Method Based on CEEMDAN-IWOA-BP Coupling - Fuping Liu; Ying Liu; Chen Yang; Ruixun Lai (Water Resources Management, 2022)

Analysis of Flow Behavior as Influenced by Reservoir with Flow Regularization - Tarcila Neves Generoso; Demetrius David da Silva; Lineu Neiva Rodrigues; Ricardo Santos Silva Amorim; Laura Thebit de Almeida (Water Resources Management, 2022)

Scientific Mapping of Research on Nature-based Solutions for Sustainable Water Management - Lisa Bunclark; Iván Manuel De La Vega Hernández (Water Resources Management, 2022)

A Hybrid ANFIS-GA Approach for Estimation of Hydrological Time Series - Bulent Haznedar; Huseyin Cagan Kilinc (Water Resources Management, 2022)

Actual Evapotranspiration for Sugarcane Based on Bowen Ratio-Energy Balance and Soil Water Balance Models with Optimized Crop Coefficients - Suelen da Costa Faria Martins; Marcos Alex dos Santos; Gustavo Bastos Lyra; José Leonaldo de Souza; Guilherme Bastos Lyra; Iêdo Teodoro; Fábio Freitas Ferreira; Ricardo Araújo Ferreira Júnior; Alexsandro Claudio dos Santos Almeida; Renan Cantalice de Souza (Water Resources Management, 2022)

Dam-Break Flow on Mobile Bed Through an Idealized City: Numerical Study - Alibek Issakhov; Aliya Borsikbayeva; Assylbek Issakhov (Water Resources Management, 2022)