Water

23 pages, 5624 KB

Open AccessArticle

Numerical Simulation of Sloshing Tanks with Shallow Water Model Using Low Numerical Diffusion Schemes and Its Application to Tuned Liquid Dampers

by Mahdiyar Khanpour, Abdolmajid Mohammadian, Hamidreza Shirkhani and Reza Kianoush

Water 2025, 17(18), 2703; https://doi.org/10.3390/w17182703 (registering DOI) - 12 Sep 2025

Abstract

The initial part of this study fills a notable research gap by investigating the substantial impact of numerical diffusion errors from different schemes on sloshing tank models. Multiple numerical models were developed: first- and higher-order upwind schemes equipped with precise wall treatment using [...] Read more.

The initial part of this study fills a notable research gap by investigating the substantial impact of numerical diffusion errors from different schemes on sloshing tank models. Multiple numerical models were developed: first- and higher-order upwind schemes equipped with precise wall treatment using ghost nodes, MacCormack and central methods that are explicit second-order finite difference methods, and Preissmann and staggered methods employed in full-implicit and semi-implicit modes. Furthermore, the separation of variables technique was proposed for simulating sloshing tanks and deriving an analytical equation for the tank’s natural period. An analytical solution to the perturbation was employed to examine the numerical diffusion of the schemes. Subsequently, two sloshing tests, resonant and near-resonant excitations, were employed to determine the numerical diffusion and calibrate the physical diffusion coefficients, respectively. Finally, an efficient and accurate numerical scheme was applied to a linear shallow water model including physical diffusion and coupled with a single degree of freedom (SDOF), to simulate tuned liquid dampers (TLDs). It shows that the efficiency of TLD is associated with a compact domain around resonance excitation. Contrary to SDOF alone, when SDOF interacts with TLD the impact of structural damping on reducing the response is minimal in resonance excitation. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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26 pages, 2055 KB

Open AccessReview

Evapotranspiration Estimation in the Arab Region: Methodological Advances and Multi-Sensor Integration Framework

by Shamseddin M. Ahmed, Khalid G. Biro Turk, Adam E. Ahmed, Azharia A. Elbushra, Anwar A. Aldhafeeri and Hossam M. Darrag

Water 2025, 17(18), 2702; https://doi.org/10.3390/w17182702 (registering DOI) - 12 Sep 2025

Abstract

Evapotranspiration (ET) estimation is crucial for sustainable water resource management in arid and semi-arid regions, particularly in the Arab world, where water scarcity remains a significant challenge. The objectives of this study were to map dominant ET estimation techniques and their geographic distribution, [...] Read more.

Evapotranspiration (ET) estimation is crucial for sustainable water resource management in arid and semi-arid regions, particularly in the Arab world, where water scarcity remains a significant challenge. The objectives of this study were to map dominant ET estimation techniques and their geographic distribution, demonstrate fusion-based ET estimation under data-scarce conditions, and examine their alignment with climate change and food security priorities. The study reviewed 1279 ET-related articles indexed in the Web of Science, highlighting methodological trends, regional disparities, and the emergence of data-driven techniques. The results showed that traditional methods—primarily the Penman-Monteith model—dominate nearly 70% of the literature. In contrast, machine learning (ML), remote sensing (RS), and artificial intelligence (AI) collectively account for approximately 30%, with hybrid fusion frameworks appearing in only 2% of studies. ML applications are concentrated in Morocco, Egypt, and Iraq, while 50% of Arab countries lack any ML or AI-based research on energy transition (ET). Complementing the bibliometric analysis, this study demonstrates the practical potential of ML-based ET fusion using Landsat and the FAO Water Productivity (WaPOR) data within Saudi Arabia. A random forest model outperformed traditional averaging, reducing the mean absolute error (MAE) to 215.08 mm/year and the root mean square error (RMSE) to 531.34 mm/year, with a Pearson correlation coefficient of 0.86. The findings advocate for greater support and regional collaboration to advance ET monitoring and integrate ML-based modelling into climate resilience frameworks. Full article

(This article belongs to the Special Issue Applied Remote Sensing in Irrigated Agriculture)

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19 pages, 1990 KB

Open AccessReview

Research Progress on the Application of Electrodialysis Technology for Clean Discharge Water Treatment from Power Plants

by Zhiwei Kang, Guifeng Zhao, Haoyang Xiong, Kai Zhang and Peidong Su

Water 2025, 17(18), 2701; https://doi.org/10.3390/w17182701 (registering DOI) - 12 Sep 2025

Abstract

The increasing global demand for sustainable water management in coal-fired power plants highlights the critical challenges of high-salinity wastewater treatment, where electrodialysis technology emerges as a promising technology for salinity removal. This paper systematically investigates the application status, technical principles, advantages, and challenges [...] Read more.

The increasing global demand for sustainable water management in coal-fired power plants highlights the critical challenges of high-salinity wastewater treatment, where electrodialysis technology emerges as a promising technology for salinity removal. This paper systematically investigates the application status, technical principles, advantages, and challenges of electrodialysis (ED) in clean water treatment for coal-fired power plants, and its future development potential is also discussed. As an efficient membrane-based desalination technology, ED could effectively remove chloride ions, sulfate ions, and other dissolved salts from clean water, significantly reducing conductivity and enabling both water reuse and salt recovery. Studies indicate that through optimized operational parameters and system design, ED systems can achieve over 90% desalination efficiency and concentrate salts to levels exceeding 12%, delivering notable economic and environmental benefits. However, practical implementation still faces challenges such as membrane fouling and high energy consumption. Advances in novel membrane materials, system integration, and intelligent control technologies are expected to broaden ED’s applicability in power plant water treatment. This study serves as a valuable technical reference for advancing clean water purification and resource recovery in the energy sector, and the findings will contribute to informed decision-making for sustainable water treatment solutions. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

16 pages, 1666 KB

Open AccessArticle

Extraction and Characterization of Microplastics in Soil: A Case Study from the Hetao Irrigation District

by Chia Min Ho, Weiying Feng, Yuxin Deng, Xiaofeng Li and Su Kong Ngien

Water 2025, 17(18), 2700; https://doi.org/10.3390/w17182700 - 12 Sep 2025

Abstract

Microplastics (MPs) pollution has become a global environmental issue. Soil, as a key environmental medium, serves as an important sink and carrier of MPs. Accurate and efficient extraction of MPs from soil matrices is essential for understanding their distribution, composition, and environmental behavior. [...] Read more.

Microplastics (MPs) pollution has become a global environmental issue. Soil, as a key environmental medium, serves as an important sink and carrier of MPs. Accurate and efficient extraction of MPs from soil matrices is essential for understanding their distribution, composition, and environmental behavior. This study presents a refined extraction method that combines two-step density separation with sodium chloride (NaCl, 1.20 g/cm³), hydrogen peroxide (H₂O₂) digestion for organic matter removal and a Fractionated Filtration Method (FFM) to capture MPs across multiple particle size ranges. Polymer identification and size characterization were performed using the high-throughput Agilent 8700 Laser Direct Infrared (LDIR) imaging system. Method validation demonstrated a recovery rate of 85% based on 100 μm MPs standards spiked into soil and minimal background contamination of 5–8 particles in blank controls, confirming the reliability of the workflow. Applying this method to agricultural soils from the Hetao Irrigation District revealed widespread MP contamination, with concentrations ranging from 5778 to 31,489 particles/kg and an average of 16,461 ± 8097 particles/kg. More than 99% of MPs were smaller than 500 μm, with the 10–30 μm fraction dominating the distribution. Polypropylene (PP), polyamide (PA), and polyethylene (PE) accounted for over 90% of detected MPs. This refined method enables reproducible extraction and accurate characterization of fine MPs in complex soil environments and provides a practical foundation for advancing standardized soil MP monitoring protocols. Full article

(This article belongs to the Special Issue Water Environment Pollution and Control, 4th Edition)

20 pages, 4456 KB

Open AccessArticle

Phosphate Recovery from Wastewater Using Red Mud-Modified Biochar Beads: Performance and Mechanism Study

by Feng Tian, Yiwen Wang, Man Qi, Ruyu Sun, Yawen Zhao, Li Wang and Suqing Wu

Water 2025, 17(18), 2699; https://doi.org/10.3390/w17182699 - 12 Sep 2025

Abstract

In this study, red mud (RM) was utilized as an iron and aluminum source, and reed biomass served as a carbon precursor to prepare red mud-modified biochar beads (RM/CSBC) via the gel-calcination method. Under a pyrolysis temperature of 900 °C and an RM/biomass [...] Read more.

In this study, red mud (RM) was utilized as an iron and aluminum source, and reed biomass served as a carbon precursor to prepare red mud-modified biochar beads (RM/CSBC) via the gel-calcination method. Under a pyrolysis temperature of 900 °C and an RM/biomass dosage of 3 g each, RM/CSBC exhibited an optimal balance between adsorption performance and cost. Within typical pH range of 6–9 in wastewater, RM/CSBC maintained effective adsorption performance, while metal ion leaching (Fe ≤ 0.3 mg·L⁻¹, Al ≤ 0.2 mg·L⁻¹) complied with Class II surface water standards in China. Kinetic data were well fitted by the pseudo second-order model, supported by the Elovich model, indicating the involvement of both chemical and physical adsorption mechanisms. Isotherm results showed that the Langmuir model provided the best fit, indicating monolayer adsorption, with a maximum capacity of 85.16 mg·g⁻¹ at 25 °C. XPS analysis revealed the formation of AlPO₄ and FePO₄ precipitates, confirming chemical precipitation as a key mechanism, along with electrostatic attraction and physical sorption. This study highlights the feasibility of RM/CSBC as an efficient and low-cost phosphate adsorbent and provides a theoretical basis for phosphorus removal and recovery from wastewater using waste-derived materials. Full article

(This article belongs to the Special Issue Ecological Wastewater Treatment and Resource Utilization)

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27 pages, 1588 KB

Open AccessArticle

Representing Small Shallow Water Estuary Hydrodynamics to Uncover Litter Transport Patterns

by Lubna Benchama Ahnouch, Frans Buschman, Helene Boisgontier, Ana Bio, Luis R. Vieira, Sara C. Antunes, Gary F. Kett, Isabel Sousa-Pinto and Isabel Iglesias

Water 2025, 17(18), 2698; https://doi.org/10.3390/w17182698 - 12 Sep 2025

Abstract

Plastic pollution is an increasing global concern, with estuaries being especially vulnerable as transition zones between freshwater and marine systems. These ecosystems often accumulate large amounts of waste, affecting wildlife and water quality. This study focuses on analysing the circulation patterns of the [...] Read more.

Plastic pollution is an increasing global concern, with estuaries being especially vulnerable as transition zones between freshwater and marine systems. These ecosystems often accumulate large amounts of waste, affecting wildlife and water quality. This study focuses on analysing the circulation patterns of the Ave Estuary, a small, shallow system on Portugal’s north-western coast, and their influence on litter transport and distribution. This site was selected for installing an aquatic litter removal technology under the EU-funded MAELSTROM project. A 2DH hydrodynamic model using Delft3D FM, coupled with the Wflow hydrological model, was implemented and validated. Various scenarios were simulated to assess estuarine dynamics and pinpoint zones prone to litter accumulation and flood risk. The results show that tidal action and river discharge mainly drive the estuary’s behaviour. Under low discharge, floating litter should be mostly transported toward the ocean, while high discharge conditions should result in litter movement at all depths due to stronger currents. High water levels and flooding occur mainly upstream and in specific low-lying areas near the mouth. Low-velocity zones, which can favour litter accumulation, were found around the main channel and on the western margin near the estuary’s mouth, even during high flows. These findings highlight persistent accumulation zones, even under extreme event conditions. Full article

(This article belongs to the Special Issue Marine Plastic Pollution: Recent Advances and Future Challenges)

24 pages, 5195 KB

Open AccessArticle

Multi-Scenario Optimization of PID Controllers for Hydro-Wind-Solar Complementary Systems Based on the DEAGNG Algorithm

by Jun Yan, Zhi Wang, Yuye Li, An Yan, Shaoyong Liu, Jinwen Luo, Chu Zhang and Chaoshun Li

Water 2025, 17(18), 2697; https://doi.org/10.3390/w17182697 - 12 Sep 2025

Abstract

This paper focuses on the hydro–solar–wind complementary system, targeting two typical scenarios (both include PV output fluctuations driven by solar radiation intensity: wind power not participating in frequency regulation and wind power participating in frequency regulation) to conduct research on system frequency characteristic [...] Read more.

This paper focuses on the hydro–solar–wind complementary system, targeting two typical scenarios (both include PV output fluctuations driven by solar radiation intensity: wind power not participating in frequency regulation and wind power participating in frequency regulation) to conduct research on system frequency characteristic analysis and Proportional-Integral-Derivative (PID) controller parameter (K_P, K_I) optimization. By constructing a frequency response model that accounts for wind power penetration and output fluctuations, the dynamic regulation characteristics of the system under different scenarios are quantitatively analyzed. Given the limitations of single-objective optimization algorithms in balancing multiple performance indicators, the Decomposition-based Evolutionary Algorithm Guided by Growing Neural Gas (DEAGNG) multi-objective algorithm is introduced, with the Integral Time Absolute Error (ITAE) and the Integral Time Squared Error (ITSE) as the objective functions for parameter collaborative optimization. The results show that the optimization method based on DEAGNG can effectively improve the frequency stability of the system, reduce the mean value and maximum deviation of frequency fluctuations, and exhibit good adaptability in both scenarios. This study provides a multi-scenario-adapted PID parameter optimization scheme for hydro–solar–wind complementary systems, offering theoretical and technical support for achieving high-precision frequency control and enhancing the operational reliability of the system. Full article

(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)

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18 pages, 3589 KB

Open AccessArticle

Study on Hydraulic Safety Control Strategies for Gravity Flow Water Supply Project with Long-Distance and Multi-Fluctuation Pressure Tunnels

by Jinke Mao, Jianyong Hu, Yichen Wang, Haijing Gao, Puxi Li, Yu Zhou, Feng Xie, Jingyuan Cui and Wenjing Hu

Water 2025, 17(18), 2696; https://doi.org/10.3390/w17182696 (registering DOI) - 12 Sep 2025

Abstract

During the sudden closure of gates in long-distance gravity flow water supply projects, intense water hammer waves are generated. These waves can cause severe damage to the water supply tunnel structure, posing a significant threat to project safety. To develop an economical and [...] Read more.

During the sudden closure of gates in long-distance gravity flow water supply projects, intense water hammer waves are generated. These waves can cause severe damage to the water supply tunnel structure, posing a significant threat to project safety. To develop an economical and effective hydraulic safety control strategy, this study uses the example of a specific gravity flow water supply project with long-distance and multi-fluctuation pressure tunnels in Zhejiang Province. A novel combined protection strategy was investigated, involving the conversion of construction branch tunnels into branch tunnel surge tanks combined with an overflow surge tank. Numerical simulations of gate closure-induced water hammer pressures were conducted using the method of characteristics. Additionally, the effectiveness of the overflow surge tank on controlling the surge water level in the branch tunnels was analyzed with respect to variations in its height, diameter, and impedance hole diameter. The results indicate that a 300 s linear gate closure without any protective measures induces severe water hammer pressure. Extending the closure time to 1200 s still results in pressures far exceeding the safety threshold. Converting construction branch tunnels into surge tanks effectively controlled the water hammer pressure; however, overflow issues emerged in some branch tunnels. The subsequent addition of an overflow surge tank at the end of the water supply system successfully eliminated the risk of overflow in the branch tunnels. Building upon this, multi-parameter optimization analysis was used to determine the optimal configuration for the overflow surge tank. This solution ensures hydraulic safety while maintaining cost-effectiveness. Both the maximum pressure and the minimum pressure along the water supply tunnel, as well as the surge water levels in all branch tunnels, meet the code requirements. Furthermore, the reduced size of the surge tank significantly lowered construction costs. The findings of this research provide theoretical foundations and technical support for similar long-distance gravity flow water supply projects. Full article

(This article belongs to the Special Issue Risk Assessment and Mitigation for Water Conservancy Projects)

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24 pages, 4793 KB

Open AccessArticle

Developing Rainfall Spatial Distribution for Using Geostatistical Gap-Filled Terrestrial Gauge Records in the Mountainous Region of Oman

by Mahmoud A. Abd El-Basir, Yasser Hamed, Tarek Selim, Ronny Berndtsson and Ahmed M. Helmi

Water 2025, 17(18), 2695; https://doi.org/10.3390/w17182695 - 12 Sep 2025

Abstract

Arid mountainous regions are vulnerable to extreme hydrological events such as floods and droughts. Providing accurate and continuous rainfall records with no gaps is crucial for effective flood mitigation and water resource management in these and downstream areas. Satellite data and geospatial interpolation [...] Read more.

Arid mountainous regions are vulnerable to extreme hydrological events such as floods and droughts. Providing accurate and continuous rainfall records with no gaps is crucial for effective flood mitigation and water resource management in these and downstream areas. Satellite data and geospatial interpolation can be employed for this purpose and to provide continuous data series. However, it is essential to thoroughly assess these methods to avoid an increase in errors and uncertainties in the design of flood protection and water resource management systems. The current study focuses on the mountainous region in northern Oman, which covers approximately 50,000 square kilometers, accounting for 16% of Oman’s total area. The study utilizes data from 279 rain gauges spanning from 1975 to 2009, with varying annual data gaps. Due to the limited accuracy of satellite data in arid and mountainous regions, 51 geospatial interpolations were used to fill data gaps to yield maximum annual and total yearly precipitation data records. The root mean square error (RMSE) and correlation coefficient (R) were used to assess the most suitable geospatial interpolation technique. The selected geospatial interpolation technique was utilized to generate the spatial distribution of annual maxima and total yearly precipitation over the study area for the period from 1975 to 2009. Furthermore, gamma, normal, and extreme value families of probability density functions (PDFs) were evaluated to fit the rain gauge gap-filled datasets. Finally, maximum annual precipitation values for return periods of 2, 5, 10, 25, 50, and 100 years were generated for each rain gauge. The results show that the geostatistical interpolation techniques outperformed the deterministic interpolation techniques in generating the spatial distribution of maximum and total yearly records over the study area. Full article

(This article belongs to the Section Hydrology)

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11 pages, 750 KB

Open AccessArticle

Analysis of Risk Factors for Tunnel Flooding Disasters Based on DEMATEL

by Yongxiang Fang, Yanmei Zhang, Yanchang Zhu, Yingying Tao, Rui Zhang and Qikai Wang

Water 2025, 17(18), 2694; https://doi.org/10.3390/w17182694 - 12 Sep 2025

Abstract

The growing frequency of extreme rainstorms has increasingly exposed tunnels to flooding risks, underscoring the urgent need for effective flood prevention and drainage measures. In this context, an evaluation framework for tunnel flood hazards was developed based on three criteria—hazard-inducing factors, hazard-formative environment, [...] Read more.

The growing frequency of extreme rainstorms has increasingly exposed tunnels to flooding risks, underscoring the urgent need for effective flood prevention and drainage measures. In this context, an evaluation framework for tunnel flood hazards was developed based on three criteria—hazard-inducing factors, hazard-formative environment, and disaster-bearing body—encompassing nine specific indicators. This study employs the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to construct a causal analysis model and assess the interrelationships and influence levels of risk factors associated with tunnel flooding disasters. Rainfall intensity (C1), rainfall duration (C2), ground elevation (C4), road slope (C5), and impervious surface area (C6) exhibit high causal values, acting as external input factors that drive the occurrence of tunnel flooding incidents. Conversely, water depth (C3), tunnel drainage capacity (C7), emergency flood control measures (C8), and infrastructure aging (C9) display high centrality values, serving as internal factors that reflect the tunnel’s flood prevention capability and determine the extent of disaster losses. Simply enhancing tunnel drainage capacity from the perspective of internal factors alone is insufficient; optimizing the tunnel’s flood resilience requires a combined consideration of both internal and external factors. Full article

(This article belongs to the Section Urban Water Management)

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21 pages, 2556 KB

Open AccessArticle

Scour Control in a 90° Bend by Means of an Air Bubble Screen

by Pari Maleki, Javad Ahadiyan, Rui Aleixo, Hossein Azizi Nadian, Zeinab Tamoradi, Seyed Mahmood Kashefipour, Anton J. Schleiss and Manouchehr Fathi Moghadam

Water 2025, 17(18), 2693; https://doi.org/10.3390/w17182693 - 12 Sep 2025

Abstract

Scouring is an erosional process driven by the water motion over a sediment bed. Scour can lead to structural safety risks of built structures and to riverbanks’ instabilities and collapse. In particular, scouring in river bends is a known phenomenon caused by secondary [...] Read more.

Scouring is an erosional process driven by the water motion over a sediment bed. Scour can lead to structural safety risks of built structures and to riverbanks’ instabilities and collapse. In particular, scouring in river bends is a known phenomenon caused by secondary flow currents. This scouring can result in negative impacts on the economic and social activities that occur on the riverbanks. On the other hand, the erosion and scouring processes of riverbeds are often addressed by means of heavy civil engineering construction works. Aiming at looking for different solutions for the scour in river bends, this research investigates the use of an air bubble screen system to minimize the scouring in river bends by providing detailed measurements of sedimentation patterns and velocity fields in a mild 90-degree bend where an air screen bubble was installed. The air bubble screen is generated by injecting compressed air through a perforated pipe placed on the bed along the outer bend. Different parameters were tested, including the water flow rate in the channel, the air flow rate, the angle of attack between the air bubble screen and the secondary flow, and flow direction. The air bubble screen opposes the direction of the bend’s induced secondary flows, altering the velocity pattern such that the maximum velocity at cross-sections of 45°, 65°, 80°, and 90° were displaced from the outer wall as much as 53%, 68%, 89%, and 84% of the width, respectively. The air bubble screen system also reduced the secondary flow power in the maximum scour zone by 35%. Hence, the maximum scour depth was reduced by 59% to 79.8% for the maximum flow rate by increasing the air bubbles’ angle of attack relative to the primary flow from 0° to 90°. Finally, the limitations of this study and its applicability to real cases is discussed. Full article

(This article belongs to the Special Issue Numerical Modeling of Hydrodynamics and Sediment Transport)

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22 pages, 2358 KB

Open AccessArticle

Shifts in Precipitation Variability near the Danube Delta Biosphere Reserve (1965–2019)

by Alina Bărbulescu and Cristian Ștefan Dumitriu

Water 2025, 17(18), 2692; https://doi.org/10.3390/w17182692 - 11 Sep 2025

Abstract

Nowadays, climate change is one of the significant threats humanity faces. Many researchers have documented its effects on water availability and vulnerable systems. This study examines the long-term precipitation record (1965–2019) from the Tulcea station, located just 4 km from the Danube Delta [...] Read more.

Nowadays, climate change is one of the significant threats humanity faces. Many researchers have documented its effects on water availability and vulnerable systems. This study examines the long-term precipitation record (1965–2019) from the Tulcea station, located just 4 km from the Danube Delta Biosphere Reserve (DDBR), to evaluate the impact of climate change on precipitation variability, which can significantly affect biodiversity in this protected area. We integrated change point detection (CPD), stationarity tests, trend analysis, and series decomposition to characterize shifts and patterns in the time series. The Lee & Heghinian test detected a change point (CP) in all data series, whereas the Hubert segmentation methods and Cumulative Sum Method (CUSUM) found fewer series that present at least a CP. The Mann–Kendall (MK) trend test and Innovative Trend Analysis (ITA) indicated an increasing trend in the annual, monthly, and October precipitation series. The Seasonal-Trend decomposition using Loess STL decomposition found the highest seasonality indices in June and July. The Ensemble Empirical Mode Decomposition (EEMD) emphasizes a substantial difference in the seasonal cycle. The results indicate a high variability in the precipitation pattern, with periods of high precipitation followed by dry periods. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

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18 pages, 3503 KB

Open AccessArticle

MLP-Optimized Duct Design for Enhanced Hydrodynamic Performance in Tidal Turbines

by Zhijie Liu, Yuan Zheng, Yuquan Zhang and Junhui Xu

Water 2025, 17(18), 2691; https://doi.org/10.3390/w17182691 - 11 Sep 2025

Abstract

The duct, a crucial component of tidal energy power generation devices, is designed to enhance the environmental benefits of tidal energy by optimizing water flow paths and improving energy conversion efficiency. Traditional duct design methods are often considered overly complex, lacking precision, and [...] Read more.

The duct, a crucial component of tidal energy power generation devices, is designed to enhance the environmental benefits of tidal energy by optimizing water flow paths and improving energy conversion efficiency. Traditional duct design methods are often considered overly complex, lacking precision, and exhibiting poor optimization efficiency and accuracy. In this study, computational fluid dynamics (CFD) and multi-layer perceptron (MLP) models are employed to investigate the impact of various duct designs on turbine power output and thrust. The MLP model is trained using numerical simulation results, which are then validated by comparing them with experimental data from the literature. Under optimized conditions—specifically, an attack angle of 20°, a blade tip distance of 8 mm, and a cubic curve X_m = 0.796—the power coefficient is found to increase by approximately 11.14% compared to the conventional duct 1, while thrust is reduced by about 52.11% compared to the conventional duct 2. Furthermore, energy loss in the wake vortex is minimized. Flow field analysis is conducted to further confirm the effectiveness of the optimized design, with the high-speed zone area being expanded and pressure extremes reduced by approximately 31.71%. These results demonstrate that machine learning methods can effectively be used to extract nonlinear relationships between complex parameters, offering more design options for duct development and facilitating the engineering application of tidal energy generation technology. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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21 pages, 2339 KB

Open AccessArticle

Flood Frequency Analysis and Trend Detection in the Brisbane River Basin, Australia

by S M Anwar Hossain, Sadia T. Mim, Mohammad A. Alim and Ataur Rahman

Water 2025, 17(18), 2690; https://doi.org/10.3390/w17182690 - 11 Sep 2025

Abstract

This study presents a comprehensive flood frequency analysis for Australia’s Brisbane River basin using annual maximum flood (AMF) data from 26 stream gauging stations. This evaluates five different probability distributions in fitting the AMF data of the selected stations, which are the Lognormal, [...] Read more.

This study presents a comprehensive flood frequency analysis for Australia’s Brisbane River basin using annual maximum flood (AMF) data from 26 stream gauging stations. This evaluates five different probability distributions in fitting the AMF data of the selected stations, which are the Lognormal, Log Pearson Type III (LP3), Gumbel, Generalized Extreme Value (GEV), and Generalized Pareto (GP) distributions (the recommended distributions in FLIKE software (School of Civil Engineering, University of Newcastle Australia, Australia, Release_x86_5.0.306.0). Three different goodness-of-fit tests (Chi-Squared, Anderson–Darling, and Kolmogorov–Smirnov) are adopted. This study also examines trends in the observed AMF data using several trend tests. It is found that the LP3 is the best-fit probability distribution at majority of the selected stations, followed by the GP distribution. Although the AMF data at most of the stations show an increasing linear trend, these trends are generally statistically non-significant. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: The Impact of Climate Change on Water Resources)

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20 pages, 2051 KB

Open AccessArticle

Prediction of Dam Inflow in the River Basin Through Representative Hydrographs and Auto-Setting Artificial Neural Network

by Yong Min Ryu and Eui Hoon Lee

Water 2025, 17(18), 2689; https://doi.org/10.3390/w17182689 - 11 Sep 2025

Abstract

Hydrological prediction under climate change requires representative data selection and adaptable model architecture. This study proposes a two-part methodology to improve deep learning performance in hydrological prediction. The first component, the representative hydrograph extraction technique (RHET), identifies representative inflow patterns from historical records [...] Read more.

Hydrological prediction under climate change requires representative data selection and adaptable model architecture. This study proposes a two-part methodology to improve deep learning performance in hydrological prediction. The first component, the representative hydrograph extraction technique (RHET), identifies representative inflow patterns from historical records using dynamic time warping (DTW) and K-medoids clustering. Inflow data are segmented by year, annual DTW distances are calculated, and central events are selected. Representative hydrographs serve as training input. The second component is the auto-setting artificial neural network (AS-ANN). The AS-ANN automatically determines its structural parameters by performing pre-training to evaluate performance across different configurations. The proposed approach was applied to the Daecheong Dam basin in South Korea and compared against an artificial neural network (ANN). Results show that the proposed model reduced the minimum root mean squared error (Min RMSE) by approximately 267.51 m³/day in the validation results and by approximately 53.04 m³/day in the prediction results compared to the ANN. Furthermore, the proposed model reduced the root mean square error by 57.28% and improved peak inflow prediction accuracy by 54.00%. The proposed RHET-based AS-ANN is expected to show good performance in learning and predicting hydrological data, including the data used in this study, by replacing existing ANNs. Full article

(This article belongs to the Special Issue Application of Machine Learning Models for Flood Forecasting)

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23 pages, 3006 KB

Open AccessArticle

Evaluation of Water Resource Carrying Capacity in Taizhou City, Southeast China

by Chuyu Xu, Jiandong Ye, Yijing Chen, Yukun Wang, Haodong Qiu, Jiaqi Tan, Wencheng Wei, Zhishao Li, Tongtong Yu and Hao Chen

Water 2025, 17(18), 2688; https://doi.org/10.3390/w17182688 - 11 Sep 2025

Abstract

Water resource carrying capacity is a key measure of sustainability, commonly employed to evaluate how well water resources can sustain economic and social growth. With China’s rapid economic growth and modernization, water resources in certain regions are now being used at or beyond [...] Read more.

Water resource carrying capacity is a key measure of sustainability, commonly employed to evaluate how well water resources can sustain economic and social growth. With China’s rapid economic growth and modernization, water resources in certain regions are now being used at or beyond their sustainable threshold. This study evaluates the present state of water resource carrying capacity in Taizhou City, located in southeastern China. Using relevant data from 2012 to 2022 on society, economy, water resources, and ecology, the weights of the evaluation indicators were determined using both the entropy weight method and principal component analysis. Subsequently, a comprehensive evaluation model for water resource carrying capacity was developed by applying the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. The comprehensive proximity index for water resource carrying capacity in Taizhou City averaged 0.4864 between 2012 and 2022, indicating a moderate level overall but exhibiting a declining trend, suggesting an approaching threshold of utilization limits. The range was between 0.3461 and 0.7143. In 2017, the comprehensive proximity index was 0.3461 (low water resource carrying capacity level, with water resources already suffering damage and various subsystems developing uncoordinatedly). However, the comprehensive proximity index for water resource carrying capacity improved significantly from 2018 to 2022. A combination of rising industrial water demand and a decrease in both the absolute volume and proportional allocation of water for ecological purposes drove the overall decline in the progress rate in 2017. Taizhou City has formulated strict water resource management policies and measures, resulting in a decrease in indicators such as industrial water consumption, residential water consumption, and industrial wastewater discharge, as well as an increase in indicators such as ecological water consumption and ecological water utilization rate. As a result, the comprehensive water resource carrying capacity saw a notable rise during 2018–2019. The study results provide a reference for the rational use of water resources in Taizhou City and are of certain significance for promoting the coordinated economic and social development of Taizhou City. Full article

(This article belongs to the Section Water Resources Management, Policy and Governance)

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30 pages, 9156 KB

Open AccessArticle

Integrating Loose Layer Drainage into Mining Subsidence Prediction: A Mathematical Model Validated by Field Measurements and Numerical Simulations

by Bang Zhou, Yueguan Yan, Ming Li, Shengcai Li, Chuanwu Zhao, Jianrong Kang and Jinman Zhang

Water 2025, 17(18), 2687; https://doi.org/10.3390/w17182687 - 11 Sep 2025

Abstract

Mining-induced surface subsidence is a typical geological hazard. Loose layer drainage disturbed by coal mining can exacerbate surface subsidence in terms of both the extent and amount, thereby increasing the risk of building deformation and environmental degradation in mining areas. However, currently the [...] Read more.

Mining-induced surface subsidence is a typical geological hazard. Loose layer drainage disturbed by coal mining can exacerbate surface subsidence in terms of both the extent and amount, thereby increasing the risk of building deformation and environmental degradation in mining areas. However, currently the prediction results of surface subsidence considering these two factors are not precise enough, which contradicts the principles of green coal mining. Firstly, this paper introduces the probability integral method, which predicts mining-induced surface subsidence. Subsequently, based on the soil–water coupled theory and the derived characteristic curve of groundwater level decline, a surface subsidence prediction model that considers loose layer drainage is constructed using triple integral transformation. Finally, a more precise surface subsidence prediction model considering both factors is proposed based on the principle of superposition. The model is applied to the mining of working panel 1309 in Shanxi province, China, an area rich in coal yet scarce in water resources. When compared with the measured subsidence data, the proposed model achieves a root mean square error (RMSE) of 27 mm, while the RMSEs of existing models are 78 mm and 123 mm, respectively. The prediction accuracy has been significantly improved. In addition, the proposed model is further validated through fluid–solid coupling numerical calculations in FLAC3D. The subsidence results considering the single effect of each factor also demonstrated good validation accuracy. Overall, the proposed model can accurately describe the surface subsidence considering both factors. This research can provide a theoretical guide for assessing the environmental impact and building damage, while contributing to the sustainable development of land use and groundwater resource in mining areas. Full article

(This article belongs to the Special Issue Groundwater Evolution and Hydrochemical Processes in Mining Environments)

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17 pages, 2810 KB

Open AccessArticle

Magnetic Intensification of Fenton Processes Using Superconducting Technology for Enhanced Treatment of Printing and Dyeing Wastewater: Mechanisms and Applications

by Qian Luo, Zhenchang Yin, Zhengfeng Hu, Wei Zhang, Yu Zhang, Huimin Huang, Zhihui Chen, Junjie Xu and Rongwu Mei

Water 2025, 17(18), 2686; https://doi.org/10.3390/w17182686 - 11 Sep 2025

Abstract

The rapid industrial development in recent years has led to severe pollution of aquatic environments. It is necessary to develop green and highly efficient treatment technologies for addressing environmental pollution and realizing carbon peaking and carbon neutrality goals. This study aims to explore [...] Read more.

The rapid industrial development in recent years has led to severe pollution of aquatic environments. It is necessary to develop green and highly efficient treatment technologies for addressing environmental pollution and realizing carbon peaking and carbon neutrality goals. This study aims to explore the effect of magnetic fields on chemical oxygen demand (COD) degradation by Fenton reaction. The experimental results demonstrated the following: (1) Magnetic fields convert macromolecular organic compounds into low-molecular-weight organic compounds, promoting the attack of radicals on organic pollutants. (2) The magnetic Fenton process achieved COD removal efficiency of 60.0%. (magnetic field intensity: 1.5 T, magnetization duration: 5 min, pH = 5.0, Fe²⁺ = 2.0 mmol/L, H₂O₂ = 2.0 mmol/L, reaction time: 40 min). (3) The magnetic Fenton process consumes less acidic reagent. Notably, it achieves a 33.3% reduction in both catalyst and oxidant usage under the same COD removal efficiency. This study verifies the feasibility of applying the method in real sewage treatment plants, demonstrating promising application prospects. Full article

(This article belongs to the Special Issue Fate and Transport of Contaminants in Soil and Water)

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24 pages, 348 KB

Open AccessArticle

Muddling Through Water Governance and Water Quality—Comparative Lessons from Three Governance Regimes

by Geir Inge Orderud, Rolf David Vogt, Josef Hejzlar, Hongze Tan, Ståle Haaland, Petr Porcal and Jing Luo

Water 2025, 17(18), 2685; https://doi.org/10.3390/w17182685 - 11 Sep 2025

Abstract

This paper addresses water governance in the context of dissolved organic matter emissions into water bodies and cultural eutrophication. Through a comparative interdisciplinary analysis of cases from Norway, the Czech Republic, and China, it seeks to identify core principals of effective water governance [...] Read more.

This paper addresses water governance in the context of dissolved organic matter emissions into water bodies and cultural eutrophication. Through a comparative interdisciplinary analysis of cases from Norway, the Czech Republic, and China, it seeks to identify core principals of effective water governance and suggest strategies for achieving good ecological and chemical status of raw water. The analysis presents each case by exploring natural and societal processes, emphasising the interdependence between society and nature, and applying a theoretical framework. In this way, the paper contributes to the broader field of water governance studies. The central conclusion is that raw water quality results from “muddling through” processes involving stakeholders with diverse and sometimes conflicting interests. Building the capabilities to manage such contingencies is essential for successful governance. Four critical dimensions are identified as key to this capability: (i) robust environmental knowledge and literacy; (ii) stronger representation of non-human interest; (iii) regulatory measures and economic incentives to enhance raw water quality; and (iv) integrated multi-level governance combining top-down and bottom-up approaches. Strengthening these dimensions can also help mitigate the structural economic pressure driving the exploitation of “cheap nature”. Full article

(This article belongs to the Special Issue Water Governance: Current Status and Future Trends)

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