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Water, Volume 17, Issue 18 (September-2 2025) – 135 articles

Cover Story (view full-size image): Thermal discharges from power plants pose significant risks to aquatic ecosystems by altering water temperatures. This study investigates how river mouth morphodynamics, especially spit formation and erosion, control thermal plume dispersion. Using field data from a coastal site in southwest Türkiye and numerical modeling, we reveal that spit development redirects plumes, reducing mixing efficiency by over 75% and elevating temperatures to 4–5 °C. Spit removal enhances dispersion, dropping excesses to 0–1 °C for regulatory compliance. These insights underscore the need for ongoing monitoring and interventions like dredging to mitigate environmental impacts. View this paper
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21 pages, 2466 KB  
Review
Experimental Modeling of Three-Dimensional (3D) Partial Dam-Break Flows: A Review
by Chuke Meng, Weiyang Zhao, Zhipan Niu and Pengzhi Lin
Water 2025, 17(18), 2792; https://doi.org/10.3390/w17182792 - 22 Sep 2025
Viewed by 172
Abstract
The growing threat of dam-break events, fueled by aging infrastructure and climate change, necessitates comprehensive risk management and mitigation strategies. Experimental studies on partial dam-break flows are pivotal for understanding the complex dynamics of these events, particularly in assessing flood risk and refining [...] Read more.
The growing threat of dam-break events, fueled by aging infrastructure and climate change, necessitates comprehensive risk management and mitigation strategies. Experimental studies on partial dam-break flows are pivotal for understanding the complex dynamics of these events, particularly in assessing flood risk and refining predictive models. This review synthesizes current experimental investigations on three-dimensional (3D) partial dam-break flows, with an emphasis on breach dynamics, wave impacts, and the role of urban structures. It highlights the challenges in capturing high-resolution 3D flow characteristics and the advancements in measurement techniques such as particle tracking velocimetry and ultrasonic distance meters. The paper discusses the integration of experimental data with numerical models to validate and improve predictive capabilities, stressing the need for continuous refinement of experimental setups and computational approaches. Gaps in the current literature, including the under-representation of irregular breach geometries and complex terrain, are identified, and future research directions are proposed to address these shortcomings. This work underscores the importance of hybrid measurement techniques and interdisciplinary collaboration to enhance dam-break modeling accuracy and flood risk mitigation. Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
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22 pages, 6778 KB  
Article
Detection of Antibiotic-Resistant Escherichia coli in the Upper Citarum River Using a β-D-Glucuronidase Method
by Siska Widya Dewi Kusumah, Mochinaga Katsuya, Rifky Rizkullah Fahmi, Peni Astrini Notodarmojo, Ahmad Soleh Setiyawan, Hisashi Satoh and Herto Dwi Ariesyady
Water 2025, 17(18), 2791; https://doi.org/10.3390/w17182791 - 22 Sep 2025
Viewed by 146
Abstract
Background: Polluted rivers may become reservoirs of antibiotic-resistant Escherichia coli (AREc), raising concerns about environmental health. While monitoring is crucial for recognizing their incidence and evaluating mitigation solutions, current approaches are limited due to high costs, labor-intensive methods, and a lack of standardized [...] Read more.
Background: Polluted rivers may become reservoirs of antibiotic-resistant Escherichia coli (AREc), raising concerns about environmental health. While monitoring is crucial for recognizing their incidence and evaluating mitigation solutions, current approaches are limited due to high costs, labor-intensive methods, and a lack of standardized indicators. This study aims to identify the priority AREc as the monitoring target and evaluate the applicability of the β-glucuronidase enzyme detection method (MPR Method) as an alternative rapid method for profiling AREc in the Upper Citarum River. Methods: River water sampling was conducted along the river during two periods with varying rainfall levels. Total Escherichia coli (TEc) and twelve types of antibiotic-resistant Escherichia coli (AREc) were measured simultaneously by the Agar Method and the β-D-Glucuronidase detection (MPR Method). Results: Statistical data analyses indicate that Total Escherichia coli (TEc) concentrations in the Upper Citarum River increase during periods of higher rainfall (𝓍 = 2558 ± 360 CFU/mL). Erythromycin-resistant Escherichia coli dominates in both periods (Period I 𝓍 = 57.6 ± 25.9%, Period II 𝓍 = 49.96 ± 29.5%). However, tetracycline-resistant Escherichia coli and Extended-Spectrum β-lactamase-producing Escherichia coli (ESBL-Ec) are the most suitable indicators for AREc concentration due to their consistency and correlation with other AREc types. The MPR method achieved an accuracy of up to 87.2%, a sensitivity of 67.4%, and a specificity of 94%. Conclusion: The MPR Method was considered a better alternative for the AREc screening method, particularly in a high bacterial load aquatic environment. Full article
(This article belongs to the Section Water Quality and Contamination)
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19 pages, 8159 KB  
Article
Photoelectrocatalysis as an Effective Treatment for Removing Perfluoroalkyl Substances from Contaminated Groundwaters: The Real Case of the Veneto Region (Italy)
by Alessandro Pietro Tucci, Sapia Murgolo, Cristina De Ceglie, Giuseppe Mascolo, Massimo Carmagnani, Andrea Lucchini Huspek, Massimiliano Bestetti and Silvia Franz
Water 2025, 17(18), 2790; https://doi.org/10.3390/w17182790 - 22 Sep 2025
Viewed by 148
Abstract
Per-polyfluoroalkyl substances (PFASs) are a class of persistent organic pollutants that have been detected in several environmental matrices. Photoelectrocatalysis (PEC) was employed to remove PFASs contained in natural groundwater collected in the Veneto region (Italy), where a massive PFAS contamination was present. Nine [...] Read more.
Per-polyfluoroalkyl substances (PFASs) are a class of persistent organic pollutants that have been detected in several environmental matrices. Photoelectrocatalysis (PEC) was employed to remove PFASs contained in natural groundwater collected in the Veneto region (Italy), where a massive PFAS contamination was present. Nine PFASs were detected and monitored throughout the process. By varying the magnitude of the applied cell voltage (no bias and 4, 6, and 8 V) the optimal condition was assessed to be 4 V, resulting in a total PFAS removal of about 87%. The presence of H2O2 was ineffective on the reaction kinetic, while NaCl inhibited the oxidation of PFASs. The EEO (Electrical Energy per Order of Magnitude) analysis revealed that PEC is more energy-efficient than both traditional photolysis and most advanced oxidation techniques discussed in published research. Full article
(This article belongs to the Special Issue The PFAS (Perfluoroalkyl and Polyfluoroalkyl Substances) Challenges: Environmental Impact and Alternative Treatments)
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21 pages, 3697 KB  
Article
Heavy Metal Removal from Produced Water Using Waste Materials: A Comparative Study
by Neetu Bansal, Md Maruf Mortula and Sameer Al-Asheh
Water 2025, 17(18), 2789; https://doi.org/10.3390/w17182789 - 22 Sep 2025
Viewed by 280
Abstract
Produced water, a typical byproduct of oil and gas extraction, is considered a significant environmental and health problem due to its heavy metals content. The objective of this study is to evaluate and compare the efficiency of seven low-cost, waste-derived adsorbents in removing [...] Read more.
Produced water, a typical byproduct of oil and gas extraction, is considered a significant environmental and health problem due to its heavy metals content. The objective of this study is to evaluate and compare the efficiency of seven low-cost, waste-derived adsorbents in removing Cr3+, Cu2+, Fe2+, Zn2+, and Pb2+ from simulated produced water. The sorbents include gypsum, neem leaves, mandarin peels, pistachio shells, date seed powder, date seed ash, and activated carbon from date seeds. Adsorption experiments were performed using 2.5 and 5 g/L of the adsorbent. SEM and EDX analyses were used to confirm morphological changes and metal deposition after adsorption. Results showed that date seed ash exhibited the highest efficiency (85–100% across all metals), followed by activated carbon (25–98%), with strong Fe and Cu removal but a lower Pb uptake. Neem leaves, mandarin peels, and date seed powder showed moderate efficiencies (30–97%), while gypsum and pistachio shells were the least effective (0–81%). Lignocellulosic peels also showed good results due to the abundance of –OH and –COOH functional groups. Gypsum performed poorly across most metals. Integrating these waste-based adsorbents into secondary or tertiary treatment stages is an economical and sustainable solution for oil wastewater treatment. The results revealed the potential for valorizing agro-industrial and construction waste for circular economic applications in heavy metal pollution control. Full article
(This article belongs to the Special Issue Adsorption Technologies in Wastewater Treatment Processes—2nd Edition)
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14 pages, 1733 KB  
Article
Occurrence and Seasonal Variation of Picoplankton at Saiysad Freshwater in Taif City, Saudi Arabia
by Najwa Al-Otaibi
Water 2025, 17(18), 2788; https://doi.org/10.3390/w17182788 - 22 Sep 2025
Viewed by 212
Abstract
A wadi ecosystem, a wetland characterized by seasonal water flow, is a unique freshwater environment typically found in semi-arid and arid regions. This study investigates the seasonal and spatial dynamics of environmental properties and microbial plankton communities at Wadi Saiysad in Taif City, [...] Read more.
A wadi ecosystem, a wetland characterized by seasonal water flow, is a unique freshwater environment typically found in semi-arid and arid regions. This study investigates the seasonal and spatial dynamics of environmental properties and microbial plankton communities at Wadi Saiysad in Taif City, Saudi Arabia. Using flow cytometry, three distinct picoplankton populations were observed: Synechococcus and heterotrophic prokaryotes classified as low (LNA) or high (HNA) nucleic acid content. Surface freshwater samples were collected from three distinct sites, representing habitats with actively flowing water, biodiverse communities, and human-influenced areas. Interestingly, no significant differences among stations were observed, suggesting that the sampled stretch of Wadi Saiysad receives similar nutrient inputs. Seasonal water temperature reached 24.5 ± 0.57 °C in summer and the pH ranged from neutral to slightly alkaline. Nutrient analyses revealed that Wadi Saiysad is eutrophic and limited by phosphorus. Phytoplankton biomass was dominated by nanoplankton, particularly in summer (46.60 ± 5.33%), while Synechococcus increased significantly with a maximum abundance of 1.32 × 104 cells mL−1 during the cooler months. HNA prokaryotes displayed marked seasonal variation (1.95 × 104–1.78 × 105 cells mL−1) compared to LNA prokaryotes (2.05–8.17 × 104 cells mL−1). This study highlights the urgent need for monitoring and managing the nutrient inputs in Wadi Saiysad to protect its biodiversity and support sustainable use. Full article
(This article belongs to the Special Issue Freshwater Ecosystems—Biodiversity and Protection: 2nd Edition)
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21 pages, 10257 KB  
Article
Assessing Recent Changes in the Contribution of Rainfall and Air Temperature Effects to Mean Flow and Runoff in Two Slovenian–Croatian Basins Using MLR and MLLR
by Ognjen Bonacci, Ana Žaknić-Ćatović and Tanja Roje-Bonacci
Water 2025, 17(18), 2787; https://doi.org/10.3390/w17182787 - 22 Sep 2025
Viewed by 242
Abstract
This study investigates the recent changes in the relationship between annual precipitation, mean annual air temperature, mean annual river discharge, and annual runoff coefficients in two small, neighboring continental catchments in Slovenia and Croatia: the Sutla/Sotla and Krapina River basins. Analyses of discharge, [...] Read more.
This study investigates the recent changes in the relationship between annual precipitation, mean annual air temperature, mean annual river discharge, and annual runoff coefficients in two small, neighboring continental catchments in Slovenia and Croatia: the Sutla/Sotla and Krapina River basins. Analyses of discharge, precipitation, and temperature time series were conducted on an annual scale using simple linear regression, multiple linear regression (MLR), and multiple log-linear regression (MLLR). Despite their geographical proximity and similar climatic conditions, the two basins exhibit markedly different runoff coefficients. Lower values observed in the Krapina River at Kupljenovo likely reflect gentle slopes, permeable soils, dense vegetation, and significant infiltration losses, while higher runoff coefficients at the Sutla River near Rakovec suggest more rapid surface runoff, reduced infiltration, and potentially distinct land use. In both basins, a pronounced rise in mean annual air temperatures has been evident since 1992, followed approximately eight years later by a sharp decline in mean annual flows and annual runoff coefficients. Our results show that the influence of air temperature on both discharge and runoff coefficients has become significantly stronger in recent decades, especially since the year 2000, contributing to a notable decline in mean annual discharges as well as annual runoff coefficients. Mean annual discharges have decreased by 19% in the Sutla and 15% in the Krapina basin, coinciding with temperature increases. Regression analyses confirm that air temperature has become a dominant negative predictor of discharge and runoff, with its influence intensifying over the past two decades. The runoff coefficient declined from 0.483 to 0.394 in the Sutla basin and from 0.325 to 0.270 in the Krapina basin during the same period. These findings highlight the importance of catchment-specific assessments for understanding and managing the localized impacts of climate change on hydrological processes. However, future work should incorporate evaporation as a key variable to better attribute the observed runoff reductions. Full article
(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources—an Issue of Environmental Global Safety)
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22 pages, 3169 KB  
Article
Optimal Water Quality Sensor Placement in Water Distribution Systems: A Computationally Cost-Effective Genetic Algorithm Framework
by Elia Zanelli, Matteo Nicolini and Daniele Goi
Water 2025, 17(18), 2786; https://doi.org/10.3390/w17182786 - 21 Sep 2025
Viewed by 204
Abstract
Despite advances in water treatment technologies and monitoring systems, contamination events in drinking water supply systems (DWSSs) still pose a threat to public health. Since timing is crucial in effectively mitigating impacts, the implementation of an early warning system (EWS) represents an optimal [...] Read more.
Despite advances in water treatment technologies and monitoring systems, contamination events in drinking water supply systems (DWSSs) still pose a threat to public health. Since timing is crucial in effectively mitigating impacts, the implementation of an early warning system (EWS) represents an optimal solution for securing the entire network. In this paper, we present a novel multi-objective approach based on the NSGA-II Genetic Algorithm (GA) for solving the sensor placement optimization (SPO) problem, aiming at defining the optimal water quality sensor system (WQSS) design. We start from the original formulation of the objective functions most commonly used in the literature, which aim, on the one hand, to reduce the impact and, on the other, to maximize the network coverage; such objective functions are rewritten in order to enable a comprehensive perspective of all potential contamination scenarios, including those that remain undetected by the WQSS. Furthermore, we address the issue of computational complexity, increasing with the size of the water distribution system (WDS), and we show that the proposed methodology is computationally cost-effective. Finally, we apply the methodology to two well-known benchmarking water distribution networks (WDNs), showcasing the capabilities and potential advantages it offers. Full article
(This article belongs to the Special Issue Monitoring and Assessment of Water Quality in Drinking Water Distribution Systems)
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25 pages, 10729 KB  
Article
Water Demand and Water Application for Plants Based on Plant Coefficient Method: Model Development and Verification on Sites of Green Saudi Arabia
by A A Alazba, M.N. Elnesr, Ahmed Elkatoury, Nasser Alrdyan, Farid Radwan and Mahmoud Ezzeldin
Water 2025, 17(18), 2785; https://doi.org/10.3390/w17182785 - 21 Sep 2025
Viewed by 254
Abstract
A GIS-based Plant Coefficient Method (PCM), termed the Plant Coefficient Method Tool (PCMT), is presented and validated through this research. It is designed for sustainable irrigation management within arid urban environments, exemplified by Riyadh, Saudi Arabia. The study integrates remote sensing data, including [...] Read more.
A GIS-based Plant Coefficient Method (PCM), termed the Plant Coefficient Method Tool (PCMT), is presented and validated through this research. It is designed for sustainable irrigation management within arid urban environments, exemplified by Riyadh, Saudi Arabia. The study integrates remote sensing data, including Landsat 8 satellite imagery, vegetation indices (NDVI, LAI), and climatic parameters to estimate daily and seasonal plant water demand for diverse landscape species. Results demonstrate that plant-specific coefficients (Kpl) fluctuate seasonally, ranging from 0.1 to 1.4, with average water demand (ETpl) reaching up to 25 L per square meter during the summer months and decreasing to around 6 L in winter. It may be found by good management based on PCMT that average daily projected ETpl rates can be lowered to as low as 3 mm/day, resulting in a significant decrease in water needs, by around 70% to 50%, when compared to higher categories. Validation across three sites (urban trees, date palms, and turf grass), showed strong correlations (R2 > 0.8) between satellite-derived vegetation indices and modeled water needs. The volumetric water demand estimates closely aligned with actual irrigation practices, albeit with some over- and under-irrigation episodes. Spatial analysis indicated that high-demand zones predominantly occur in summer, emphasizing the necessity of adaptive irrigation scheduling. Overall, the PCMT presents a scalable, accurate tool for optimizing water use, supporting sustainable landscape management aligned with Saudi Arabia’s green initiatives. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
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18 pages, 8295 KB  
Article
Evolution Mechanism of Flow Patterns and Pressure Fluctuations During Runaway Processes of Three Pump–Turbines with Different Blade Lean Angles
by Zhiyan Yang, Jie Fang, Baoyong Zhang, Chengjun Li, Tang Qian and Chunze Zhang
Water 2025, 17(18), 2784; https://doi.org/10.3390/w17182784 - 21 Sep 2025
Viewed by 260
Abstract
Pumped storage power stations are effective stabilizers and regulators of the power grids. However, during the transient process, especially the operating point entering the S-shaped region, the internal flow patterns and pressure pulsations in the pump–turbine unit change violently, seriously affecting the safety [...] Read more.
Pumped storage power stations are effective stabilizers and regulators of the power grids. However, during the transient process, especially the operating point entering the S-shaped region, the internal flow patterns and pressure pulsations in the pump–turbine unit change violently, seriously affecting the safety of the power stations, which requires enough optimizations in the design stage of the pump–turbine. In this paper, to explore the key factors which influence the evolutions of flow patterns and pressure pulsations during the runaway process, three pump–turbine runners with different inlet blade lean, including positive angle, no angle and negative angle, were selected to simulate by using the three-dimensional method. The results show that the changes in the inlet blade lean angles have significant effects on the variation periods and maximum values of the macro parameters during the runaway process, and especially the runner with no lean angle results in the smallest oscillation periods and pressure pulsations but enlarges the runner radial forces. In addition, backflows generate from the hub side under the cases with positive or no blade lean angle, while those occur from the shroud side due to the negative angle. The results provide a basic reference for the design of the pump–turbine. Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
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17 pages, 4314 KB  
Article
Oceanography and Culture Shape Morphometric Divergence in Portunus pelagicus: Defining Actionable Management Units for Climate-Resilient Recreational Fisheries in Asia
by Po-Cheng Chen, Chun-Han Shih, Tzong-Der Tzeng, Chi-Hui Huang and Gui-Mei Zhang
Water 2025, 17(18), 2783; https://doi.org/10.3390/w17182783 - 21 Sep 2025
Viewed by 278
Abstract
Sustainable management of Portunus pelagicus is hindered by uncertain stock boundaries across rapidly changing marginal seas and culturally diverse markets. We measured 12 size-adjusted morphometrics in 525 adults from five sites (Kyushu, Xiamen, Tainan, Hong Kong, and Singapore). Canonical variate analysis resolved three [...] Read more.
Sustainable management of Portunus pelagicus is hindered by uncertain stock boundaries across rapidly changing marginal seas and culturally diverse markets. We measured 12 size-adjusted morphometrics in 525 adults from five sites (Kyushu, Xiamen, Tainan, Hong Kong, and Singapore). Canonical variate analysis resolved three robust groups that mirror oceanographic regimes: a Kuroshio–China group (Kyushu, Xiamen, and Hong Kong), a Taiwan Strait subgroup (Tainan), and a Southeast Asia group (Singapore). Permutation tests (1000 runs) showed near-zero probabilities of observing the low misclassification rates by chance (p < 0.001). A reproductive trait (female AB3W) displayed group-specific allometric slopes, consistent with local functional demands. We integrate these results with a cultural ecology lens—linking ornamental carapace valuation to selective harvest—to propose morphological management units (MMUs) and region-specific rules that can be implemented immediately and refined with genomics. This work reframes a descriptive morphometric study into a socio-ecological mechanism for climate-ready, actionable fisheries governance. Full article
(This article belongs to the Special Issue Marine Biodiversity and Its Relationship with Climate/Environment)
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16 pages, 3060 KB  
Article
Abnormal Adsorption Characteristics of Copper, Zinc, and Manganese Ions on Natural Diatomite in a Liquid/Solid Heterogeneous System
by Jieying Wang, Qihao He, Mingjing Lei, Jing Han, Jiacheng Wang, Wenmin Li, Ying Xiao, Hongchun Huang, Xindeng Huang and Jian Zhu
Water 2025, 17(18), 2782; https://doi.org/10.3390/w17182782 - 20 Sep 2025
Viewed by 210
Abstract
In order to investigate the adsorption characteristics of Cu2+, Zn2+, and Mn2+ on natural diatomite in liquid/solid systems and to provide reliable theoretical support for the application of these materials, we conducted a series of adsorption studies. The [...] Read more.
In order to investigate the adsorption characteristics of Cu2+, Zn2+, and Mn2+ on natural diatomite in liquid/solid systems and to provide reliable theoretical support for the application of these materials, we conducted a series of adsorption studies. The results revealed a non-monotonic relationship between the adsorption capacity of natural diatomite and ion concentration. The maximum adsorption capacities for Cu2+, Zn2+, and Mn2+ were found to be 3.56, 6.23, and 3.82 mg·g−1, at concentrations of 200, 500, and 300 mg·L−1. Optimal adsorption conditions were determined by investigating environmental factors such as pH and temperature: pH 6, temperature 30 °C, and contact time 40 min. The adsorption kinetics were found to be in accordance with the pseudo-second-order model (R2 > 0.997). Fitting adsorption isotherms for Cu2+, Zn2+, and Mn2+ using various models revealed that the Langmuir (R2 > 0.993), Temkin (R2 > 0.953), and Freundlich (R2 > 0.997) models most accurately describe their adsorption behaviour. Thermodynamic analysis confirmed that adsorption is a spontaneous, endothermic, physical process (ΔG° < 0, ΔH° > 0, ΔS° > 0) and that the overall adsorption rate is limited by micropore adsorption. Consequently, natural diatomaceous earth can serve as an efficient, low-cost adsorbent for removing heavy metals from contaminated water. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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24 pages, 6470 KB  
Article
A Method for Improving the Efficiency and Effectiveness of Automatic Image Analysis of Water Pipes
by Qiuping Wang, Lei Lu, Shuguang Liu, Qunfang Hu, Guihui Zhong, Zhan Su and Shengxin Xu
Water 2025, 17(18), 2781; https://doi.org/10.3390/w17182781 - 20 Sep 2025
Viewed by 325
Abstract
The integrity of urban water supply pipelines, an essential element of municipal infrastructure, is frequently undermined by internal defects such as corrosion, tuberculation, and foreign matter. Traditional inspection methods relying on CCTV are time-consuming, labor-intensive, and prone to subjective interpretation, which hinders the [...] Read more.
The integrity of urban water supply pipelines, an essential element of municipal infrastructure, is frequently undermined by internal defects such as corrosion, tuberculation, and foreign matter. Traditional inspection methods relying on CCTV are time-consuming, labor-intensive, and prone to subjective interpretation, which hinders the timely and accurate assessment of pipeline conditions. This study proposes YOLOv8-VSW, a systematically optimized and lightweight model based on YOLOv8 for automated defect detection in in-service pipelines. The framework is twofold: First, to overcome data limitations, a specialized defect dataset was constructed and augmented using photometric transformation, affine transformation, and noise injection. Second, the model architecture was improved on three levels: a VanillaNet backbone was adopted for lightweighting, a C2f-Star module was introduced to enhance multi-scale feature fusion, and the WIoUv3 dynamic loss function was employed to improve robustness under complex imaging conditions. Experimental results demonstrate the superior performance of the proposed YOLOv8-VSW model. This study validates the framework on a curated, real-world image dataset, where YOLOv8-VSW achieved mAP@50 of 83.5%, a 4.0% improvement over the baseline. Concurrently, GFLOPs were reduced by approximately 38.9%, while the inference speed was increased to 603.8 FPS. The findings validate the effectiveness of the proposed method, delivering a solution that effectively balances detection accuracy, computational efficiency, and model size. The results establish a strong technical basis for the intelligent and automated control of safety in urban water supply systems. Full article
(This article belongs to the Section Urban Water Management)
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25 pages, 5293 KB  
Article
Evaluating Droughts and Trends in Data-Scarce Regions: A Case Study of Palestine Using ERA5, Standardized Precipitation Index, Bias Correction, Classical and Innovative Trend Approaches
by Ahmad Abu Arra and Eyüp Şişman
Water 2025, 17(18), 2780; https://doi.org/10.3390/w17182780 - 20 Sep 2025
Viewed by 181
Abstract
The increasing droughts and climate change effects and their frequencies worldwide are a critical threat, especially to regions facing water scarcity and wars. Therefore, comprehensive drought evaluation and trend analysis are crucial for water resources management, climate change, and drought mitigation plans. Classical [...] Read more.
The increasing droughts and climate change effects and their frequencies worldwide are a critical threat, especially to regions facing water scarcity and wars. Therefore, comprehensive drought evaluation and trend analysis are crucial for water resources management, climate change, and drought mitigation plans. Classical drought evaluation methods predominantly rely on in situ observations, often limited or unavailable in many regions, particularly in developing countries such as Palestine. This study investigates the temporal and spatial characteristics and trends of drought across Palestine between 1940 and 2025. To the best of our knowledge, for the first time in the literature, bias-corrected ERA5 precipitation data are employed alongside ground-based observations to assess drought using the Standardized Precipitation Index (SPI) at multiple timescales (1-, 6-, and 12-month). Trend detection was performed through conventional statistical approaches, including the Mann–Kendall test, Spearman’s Rho, and Sen’s slope (SS), as well as the Frequency-Innovative Trend Analysis (F-ITA) method. Furthermore, the performance of the original and bias-corrected ERA5 precipitation datasets was evaluated against observational data using statistical metrics. The main findings indicated that the bias correction significantly improves the accuracy of the ERA5 precipitation data. Also, droughts in SPI-1 and SPI-6 ranged from 4 to 5 months, the minimum at which a drought can be classified. In addition, the average drought duration at a 12-month timescale ranged between 14 and 16 months. At short (SPI-1) and medium (SPI-6) timescales, no significant trends were found, whereas at the long timescale (SPI-12) all stations showed a significant decreasing SPI trend, such as −5.611 in Jenin, reflecting intensifying drought conditions. For F-ITA, the frequencies of extreme drought classification increased from 0.4% in the first period to 2.18% in the second period. The findings of this research have important implications for drought management, water policy planning, and climate adaptation in Palestine. Full article
(This article belongs to the Special Issue Drought Evaluation Under Climate Change Condition)
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17 pages, 1864 KB  
Article
Application of Electrodialysis for Concentration and Desalination of Monovalent Salts
by Jinmei Yang, Qijin Geng, Xinxin Hao, Linna Chen and Wenyu Lian
Water 2025, 17(18), 2779; https://doi.org/10.3390/w17182779 - 20 Sep 2025
Viewed by 326
Abstract
This study investigates electrodialysis (ED) performance for desalination and concentration of monovalent salts (NaCl, NH4Cl, KCl, and NaNO3) at varying mass concentrations. Systematic comparisons of current efficiency (η), energy consumption, water loss, desalination rate ηsalt, [...] Read more.
This study investigates electrodialysis (ED) performance for desalination and concentration of monovalent salts (NaCl, NH4Cl, KCl, and NaNO3) at varying mass concentrations. Systematic comparisons of current efficiency (η), energy consumption, water loss, desalination rate ηsalt, and other key parameters reveal salt-specific behaviors and process determinants. Experimental results show distinct performance hierarchies across operational phases. In the 1% desalination phase, KCl achieved optimal performance with 95.3% salt removal, a dilute η of 99.96%, a production capacity (Q) of 54.95 L/(h·m2), and a unit energy consumption (Eu) of 3.24 kWh/t. This performance outshone that of NaCl (ηsalt = 95.2%) and NaNO3 (ηsalt = 89.5%), with NH4Cl showing the lowest value (80.6%) in this phase. This trend inversely correlated with cation hydration energies. On the other hand, in the 3% concentration phase, NH4Cl demonstrated superior performance with a concentrate η of 83.49%, a flux of 35.71 L/(h·m2), and the lowest Eu (5.30 kWh/t), despite a lower concentration factor (5.33) than NaNO3 (6.48). These findings highlight that KCl is ideal for energy-efficient brine treatment (<3% salinity), while NH4Cl is better suited to high-purity recovery. Although NaNO3 has a high Eu during concentration, it is favorable for applications where minimizing energy usage is critical. Full article
(This article belongs to the Special Issue Advanced Treatment Technologies for Emerging Contaminants in Wastewater)
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14 pages, 2438 KB  
Article
Micro-Nano Aeration Oxygenation Irrigation Has Increased Soil Nitrogen and Cotton Yield in Arid Areas
by Jiayue Wang, Qiqi Chai, Ze Wang, Yanbo Fu, Zhiguo Wang, Qingyong Bian, Junhui Cheng, Yupeng Zhao, Jinquan Zhu and Yanhong Wei
Water 2025, 17(18), 2778; https://doi.org/10.3390/w17182778 - 19 Sep 2025
Viewed by 200
Abstract
To explore the effects of micro-nano aeration and oxygenation irrigation on soil characteristics and cotton growth in cotton fields in arid areas, this study was conducted at the National Soil Quality Aksu Observation and Experiment Station in Baicheng County, Xinjiang. “Xinluzao 78” cotton [...] Read more.
To explore the effects of micro-nano aeration and oxygenation irrigation on soil characteristics and cotton growth in cotton fields in arid areas, this study was conducted at the National Soil Quality Aksu Observation and Experiment Station in Baicheng County, Xinjiang. “Xinluzao 78” cotton was used as the experimental material, and the soil column cultivation method was adopted. Four nitrogen concentration gradients (N0: 0 kg·hm−2, NL: 112.5 kg·hm−2, NM: 225 kg·hm−2, and NH: 337.5 kg·hm−2) and two irrigation methods (micro-nano aeration and oxygenation irrigation Y: DO15 mg/L, conventional irrigation C: DO7.6 mg/L) were set up to systematically analyze the total nitrogen content of the soil, enzyme activity, microbial community structure, and the response characteristics of cotton growth and yield. The results show that aeration treatment significantly increases the total nitrogen content in the soil. The total nitrogen content in the 0–15 cm and 15–30 cm soil layers treated with YNM (aeration + local conventional nitrogen application rate) increased by 9.14% and 8.53%, respectively, compared with CNM. YNM treatment significantly increased the activities of soil urease, sucrase, and β-glucosidase, among which total nitrogen had the strongest correlation with the activity of β-glucosidase. Oxygenation significantly increased the richness of soil microorganisms. The Chao1 index of YNM-treated bacteria was 75.7% higher than that of CNM-treated bacteria. YNM treatment increased cotton yield by 26.73% compared with CNM treatment. Moreover, the number of bells formed per plant and the weight of the bells increased by 44.44% and 29.6%, respectively. In conclusion, micro-nano aeration and oxygenation irrigation effectively increase cotton yield. By optimizing the activities of soil enzymes and microorganisms, micro-nano aeration and oxygenation irrigation enhance the ability of cotton to utilize and transform nitrogen, and alleviate the impact of insufficient nitrogen utilization by cotton in arid areas. Full article
(This article belongs to the Special Issue Impact of Biochar Additions on Soil Hydraulic Properties)
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15 pages, 3333 KB  
Article
The Research on H2O Adsorption Characteristics of Lunar Regolith Simulants: Implications for the Development and Utilization of Lunar Water Resources
by Yanan Zhang, Ziheng Liu, Rongji Li, Xinyu Huang, Jiannan Li, Ye Tian, Junyue Tang, Fei Su and Huaiyu He
Water 2025, 17(18), 2777; https://doi.org/10.3390/w17182777 - 19 Sep 2025
Viewed by 210
Abstract
This study prepared an adsorption-based water-containing lunar regolith simulant under low-temperature conditions to investigate H2O behavior in simulated lunar environments. Experiments established that water binds to regolith particles via adsorption rather than existing in liquid/solid states, with critical initial pressure thresholds [...] Read more.
This study prepared an adsorption-based water-containing lunar regolith simulant under low-temperature conditions to investigate H2O behavior in simulated lunar environments. Experiments established that water binds to regolith particles via adsorption rather than existing in liquid/solid states, with critical initial pressure thresholds identified at various temperatures to ensure pure adsorption conditions. Crucially, coexisting substances extend H2O preservation to −100 °C, suggesting substantial water retention in lunar polar regolith even under extreme cold. Sublimation modeling further revealed phase transition boundaries, indicating water ice likely persists in both permanently shadowed regions and illuminated polar areas. These findings provide fundamental insights into: adsorption-driven enrichment/preservation mechanisms of lunar water, thermodynamic stability thresholds at ultralow temperatures, and water ice distribution patterns across lunar polar terrains. The data advance understanding of lunar water’s stability and extractability, offering critical scientific support for future in situ resource utilization and sustained lunar exploration. Full article
(This article belongs to the Section Hydrogeology)
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29 pages, 17179 KB  
Article
Spatiotemporal Cavitation Dynamics and Acoustic Responses of a Hydrofoil
by Ding Tian, Xin Xia, Yu Lu, Jianping Yuan and Qiaorui Si
Water 2025, 17(18), 2776; https://doi.org/10.3390/w17182776 - 19 Sep 2025
Viewed by 172
Abstract
This study aims to investigate the spatiotemporal evolution of cavitating flow and the associated acoustic responses around a NACA0015 hydrofoil. A coupled fluid–acoustic interaction model is developed by integrating a nonlinear cavitation model with vortex–sound coupling theory. Numerical simulations are conducted within a [...] Read more.
This study aims to investigate the spatiotemporal evolution of cavitating flow and the associated acoustic responses around a NACA0015 hydrofoil. A coupled fluid–acoustic interaction model is developed by integrating a nonlinear cavitation model with vortex–sound coupling theory. Numerical simulations are conducted within a computational domain established for the hydrofoil to capture the interactions between cavitation dynamics and acoustic radiation. The results indicate that the temporal variations in cavity evolution and pressure fluctuations agree well with experimental observations. The simulations predict a dominant pressure fluctuation frequency of 30.15 Hz, consistent with the cavitation shedding frequency, revealing that the evolution of leading-edge vortex structures governs the periodic variations in the lift-to-drag ratio. Cavitation significantly modifies the development of vortex structures, with vortex stretching effects mainly concentrated near cavitation regions. The dilation–contraction term is closely associated with cavity formation, while the pressure–torque tilting term predominantly affects cloud cavitation collapse. Dynamic mode decomposition (DMD) shows that the coherent structures of the leading modes exhibit morphological similarity to multiscale cavitation and vortex structures. Furthermore, hydrofoil cavitation noise consists mainly of loading noise and cavitation-induced pulsating radiation noise, with surface acoustic sources concentrated in cloud cavitation shedding regions. The dominant frequency of cavitation-induced radiation noise is highly consistent with experimental measurements. Full article
(This article belongs to the Special Issue Advances in Hydrodynamics for Pumping Systems: Modeling, Optimization, and Applications)
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28 pages, 5028 KB  
Article
Daily Runoff Prediction Method Based on Secondary Decomposition and the GTO-Informer-GRU Model
by Haixin Yu, Yi Ma, Aijun Hu, Yifan Wang, Hai Tian, Luping Dong and Wenjie Zhu
Water 2025, 17(18), 2775; https://doi.org/10.3390/w17182775 - 19 Sep 2025
Viewed by 297
Abstract
Hydrological runoff prediction serves as the core technological foundation for water resource management and flood/drought mitigation. However, the nonlinear, non-stationary, and multi-temporal scale characteristics of runoff data result in insufficient accuracy of traditional prediction methods. To address the challenges of single decomposition methods’ [...] Read more.
Hydrological runoff prediction serves as the core technological foundation for water resource management and flood/drought mitigation. However, the nonlinear, non-stationary, and multi-temporal scale characteristics of runoff data result in insufficient accuracy of traditional prediction methods. To address the challenges of single decomposition methods’ inability to effectively separate multi-scale components and single deep learning models’ limitations in capturing long-range dependencies or extracting local features, this study proposes an Informer-GRU runoff prediction model based on STL-CEEMDAN secondary decomposition and Gorilla Troops Optimizer (GTO). The model extracts trend, seasonal, and residual components through STL decomposition, then performs fine decomposition of the residual components using CEEMDAN to achieve effective separation of multi-scale features. By combining Informer’s ProbSparse attention mechanism with GRU’s temporal memory capability, the model captures both global dependencies and local features. GTO is introduced to optimize model architecture and training hyperparameters, while a multi-objective loss function is designed to ensure the physical reasonableness of predictions. Using daily runoff data from the Liyuan Basin in Yunnan Province (2015–2023) as a case study, the results show that the model achieves a coefficient of determination (R2) and Nash-Sutcliffe efficiency coefficient (NSE) of 0.9469 on the test set, with a Kling-Gupta efficiency coefficient (KGE) of 0.9582, significantly outperforming comparison models such as LSTM, GRU, and Transformer. Ablation experiments demonstrate that components such as STL-CEEMDAN secondary decomposition and GTO optimization enhance model performance by 31.72% compared to the baseline. SHAP analysis reveals that seasonal components and local precipitation station data are the core driving factors for prediction. This study demonstrates exceptional performance in practical applications within the Liyuan Basin, providing valuable insights for water resource management and prediction research in this region. Full article
(This article belongs to the Special Issue Application of Big Data and Machine Learning in Hydrological Forecasting and Water Resource Management)
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28 pages, 6848 KB  
Article
GIS-Based Multi-Criteria Assessment of Managed Aquifer Recharge (MAR) Zones Using the Analytic Hierarchy Process (AHP) Method in Southern Kazakhstan
by Zhuldyzbek Onglassynov, Ronny Berndtsson, Valentina Rakhimova, Timur Rakhimov, Abai Jabassov, Issa Rakhmetov, Mira Muratova and Kamshat Tussupova
Water 2025, 17(18), 2774; https://doi.org/10.3390/w17182774 - 19 Sep 2025
Viewed by 216
Abstract
Southern Kazakhstan, particularly the Zhambyl Region, is facing increasing groundwater stress due to climate change, degradation of irrigation infrastructure, and unsustainable water use. Despite substantial renewable groundwater reserves (8.33 km3/year), irrigation still relies on ephemeral surface flow. This study delineates priority [...] Read more.
Southern Kazakhstan, particularly the Zhambyl Region, is facing increasing groundwater stress due to climate change, degradation of irrigation infrastructure, and unsustainable water use. Despite substantial renewable groundwater reserves (8.33 km3/year), irrigation still relies on ephemeral surface flow. This study delineates priority zones for Managed Aquifer Recharge (MAR) using a GIS-based Multi-Criteria Decision Analysis framework integrated with the Analytic Hierarchy Process (AHP). Nine hydrogeological criteria were incorporated: shallow aquifer depth, groundwater salinity, precipitation, terrain slope, soil texture, land use/land cover, Normalized Difference Vegetation Index (NDVI), drainage density, and lineament density. Each parameter was normalized to a five-class suitability scale and weighted through expert-informed pairwise comparisons. The MAR suitability map identifies about 19% of the region (27,060 km2) as highly favorable for implementation. Field investigations at eleven groundwater sites in 2024 corroborate model results, providing aquifer depth, quality, and infiltration data. The most suitable areas are concentrated on Quaternary alluvial–proluvial fans near the Kyrgyz Alatau foothills and the Talas-Assa interfluve. Three hydrostratigraphic settings were identified: unconfined alluvial aquifers, Neogene–Quaternary unconsolidated sediments, and fractured Carboniferous carbonates. Recommended MAR methods include infiltration galleries, check dams, and injection wells. The proposed approach, validated through consistency analysis (Consistency Ratio ≤ 0.1), demonstrates the applicability of integrated geospatial and field methods for site-specific MAR planning. Strategic MAR deployment could restore productivity to 37,500 ha of degraded irrigated lands and improve groundwater resilience. These findings provide a practical framework for policymakers and water management authorities to optimize groundwater use and enhance agricultural sustainability under changing climatic conditions. Full article
(This article belongs to the Section Water Use and Scarcity)
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27 pages, 11366 KB  
Article
Evaluating Infiltration Methods for the Assessment of Flooding in Urban Areas
by Paola Bianucci, Javier Fernández-Fidalgo, Kay Khaing Kyaw, Enrique Soriano and Luis Mediero
Water 2025, 17(18), 2773; https://doi.org/10.3390/w17182773 - 19 Sep 2025
Viewed by 555
Abstract
Urban flooding caused by short and high-intensity rainfall events presents increasing challenges for cities, threatening infrastructure, public safety and economic activity. Accurately representing infiltration processes in hydrodynamic models is critical, as oversimplifying infiltration can lead to significant errors in predicted flood extents and [...] Read more.
Urban flooding caused by short and high-intensity rainfall events presents increasing challenges for cities, threatening infrastructure, public safety and economic activity. Accurately representing infiltration processes in hydrodynamic models is critical, as oversimplifying infiltration can lead to significant errors in predicted flood extents and water depths. This study systematically compares two widely used infiltration models—Green-Ampt and Curve Number—implemented within two leading 2D hydraulic models, HEC-RAS and IBER, to assess their influence on urban flood predictions. Simulations were conducted for 26 rainfall events, including both observed and synthetic hyetographs, across two urban neighbourhoods in Pamplona metropolitan area, Spain. Model performance was evaluated using root mean square error, mean absolute error and confusion matrix-derived metrics such as precision, accuracy, specificity, sensitivity and negative predictive value. Results indicate that the choice of infiltration method significantly affects both water depths and inundation extents: while Green-Ampt yields more conservative water depth estimates, Curve Number tends to underestimate flood extents. The comparison between the two hydraulic models has shown that IBER simulates broader flood extents and lower water depth errors compared to HEC-RAS. The findings highlight the importance of selecting appropriate infiltration methods and hydraulic models for reliable urban flood risk assessment, as well as providing guidance for model selection in urban inundation studies. Full article
(This article belongs to the Special Issue Urban Flood Frequency Analysis and Risk Assessment, 2nd Edition)
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19 pages, 2867 KB  
Article
Inorganic Constituents in Shale Gas Wastewater: Full-Scale Fate and Regulatory Implications
by Yunyan Ni, Ye Zhang, Chun Meng, Limiao Yao, Jianli Sui, Jinchuan Zhang, Quan Zheng, Mingxuan Di and Jianping Chen
Water 2025, 17(18), 2772; https://doi.org/10.3390/w17182772 - 19 Sep 2025
Viewed by 272
Abstract
Shale gas wastewater from hydraulic fracturing poses significant environmental risks due to its high salinity and complex inorganic composition. This study investigates the behavior of major and trace inorganic constituents across a full-scale treatment train in the Sichuan Basin, China. Despite multi-stage processes [...] Read more.
Shale gas wastewater from hydraulic fracturing poses significant environmental risks due to its high salinity and complex inorganic composition. This study investigates the behavior of major and trace inorganic constituents across a full-scale treatment train in the Sichuan Basin, China. Despite multi-stage processes including equalization, flocculation, flotation, biological reactors, membrane filtration, and clarification, key inorganic species such as Cl, Na, Br, Sr, Li, and B remained largely persistent in the final effluent with values of 13,760, 8811, 70, 95.9, 26.6, and 60.2 mg/L, respectively. Geochemical tracers including Br/Cl (average: 0.0022 mM/mM), Na/Br (average: 125 mg/mg), and Sr/Ca (average: 0.15 mM/mM) ratios, combined with halide endmember mixing models, revealed that salinity primarily originated from highly evaporated formation brines, with limited evidence for halite dissolution or external contamination. Elevated Sr (average: 89.3 mg/L) and Ca (average: 274 mg/L) levels relative to Mg (average: 32 mg/L) suggest significant water–rock interaction. Environmental risk assessments showed that concentrations of several elements in treated effluent greatly exceeded national and international discharge or reuse standards. These findings underscore the limitations of conventional treatment technologies and highlight the urgent need for advanced processes and regulatory frameworks that address the unique challenges of high-TDS (total dissolved solids) unconventional wastewater. Full article
(This article belongs to the Section Water Quality and Contamination)
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17 pages, 2930 KB  
Article
Phosphorus Loss Risk in the Ju River Basin, China, Under Urbanization and Climate Change: Insights from the Hydrological Simulation Program—FORTRAN (HSPF) Model
by Chaozhong Deng, Qian Xiang, Qinxue Xiong, Shunyao Jiang, Fuli Xu, Liman Li, Jianqiang Zhu and Yuan Zhou
Water 2025, 17(18), 2771; https://doi.org/10.3390/w17182771 - 19 Sep 2025
Viewed by 289
Abstract
Despite increasing concerns over recurrent phosphorus (P) pollution, the Ju River—a small tributary of the Yangtze River—has received limited scientific attention. To correct this, the present study integrates field-based observations with the Hydrological Simulation Program—FORTRAN (HSPF) model to comprehensively assess the conjunct effects [...] Read more.
Despite increasing concerns over recurrent phosphorus (P) pollution, the Ju River—a small tributary of the Yangtze River—has received limited scientific attention. To correct this, the present study integrates field-based observations with the Hydrological Simulation Program—FORTRAN (HSPF) model to comprehensively assess the conjunct effects of urban expansion and changing precipitation patterns on watershed hydrology and phosphorus dynamics at the small-catchment scale. A total of five urban expansion scenarios and three precipitation enhancement scenarios were simulated to capture both seasonal and event-driven variations in daily discharge and total phosphorus (TP) concentrations. The model was calibrated and validated using in situ water quality data, ensuring high reliability of the simulations. The results indicate that agricultural non-point sources are the primary contributor to total phosphorus (TP) loads. During the overlapping period of intensive farming and heavy rainfall (June–July), TP concentrations more than doubled compared to other months, with these two months accounting for over 70% of the annual TP load. Urban expansion significantly amplified hydrological extremes, increasing peak discharge by up to 224% under extreme rainfall, thereby intensifying flood risks. Although increased precipitation diluted TP concentrations, it simultaneously accelerated overall phosphorus export. This study offers a novel modeling–monitoring framework tailored for small watersheds and provides critical insights into how land use transitions and climate change jointly reshape nutrient cycling. The findings support the development of targeted, scenario-based strategies to mitigate eutrophication risks in vulnerable river systems. Full article
(This article belongs to the Topic Water-Soil Pollution Control and Environmental Management)
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18 pages, 5619 KB  
Article
Composition and Abundance Distribution of Filamentous Bacteria During the Variable- and Low-Temperature Operation Periods of Wastewater Treatment Plants
by Xiaoling Wang, Lu Niu, Wenbo Pan, Xu Zhang and Hai Lu
Water 2025, 17(18), 2770; https://doi.org/10.3390/w17182770 - 18 Sep 2025
Viewed by 325
Abstract
Activated sludge microorganisms in sewage treatment plants are crucial for controlling water pollution and protecting public health and the ecological environment. Activated sludge must have biodegradation, easy sedimentation, and separation functions. Filamentous bacteria play an essential role in floc formation and structure. However, [...] Read more.
Activated sludge microorganisms in sewage treatment plants are crucial for controlling water pollution and protecting public health and the ecological environment. Activated sludge must have biodegradation, easy sedimentation, and separation functions. Filamentous bacteria play an essential role in floc formation and structure. However, low temperature, low load and low dissolved oxygen (DO) will destroy the balance between beneficial structural action and harmful overgrowth. In this study, the high-throughput sequencing (HTS) dataset of 16s rRNA gene sequence V3–V4 amplicons from 30 activated sludge samples from the Chuanhu Sewage Treatment Plant in Changchun was analyzed to investigate the abundance distribution of filamentous bacteria and further determine the main operating parameters and environmental factors. The experimental results showed that the filamentous bacterial community accounted for a large part of the entire microbial community, with the total filamentous bacterial percentage in each sample ranging from 7.32% to 56.81%, with large fluctuations in abundance and consistent with the SVI value. Although most of them were in flocs, they occasionally caused sedimentation problems when the water temperature was low. With 14 species of filamentous bacteria detected, the population structure of filamentous bacteria in the thermophilic, variable-temperature and low-temperature periods was universal and specific. The groups with a detection frequency of 100%, high abundance, and significant fluctuations in distribution were Microthrix parvicella and Nostocoida limicola I. The Pearson correlation analysis showed that the total abundance of filamentous bacteria and the fluctuation distribution of dominant filamentous bacteria abundance were significantly correlated with water temperature, sludge load, sludge age, and mixed liquid suspended solids (MLSS). Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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30 pages, 16884 KB  
Article
Evaluating the Long-Term Effectiveness of Marsh Terracing for Conservation with Integrated Geospatial and Wetland Simulation Modeling
by Nick Carpenter, Laura Costadone and Thomas R. Allen
Water 2025, 17(18), 2769; https://doi.org/10.3390/w17182769 - 18 Sep 2025
Viewed by 336
Abstract
Coastal marshes provide essential ecosystem services, yet they are vulnerable to anthropogenic stressors and climate change, particularly sea level rise (SLR). Restoration approaches like marsh terracing have emerged as nature-based strategies to enhance resilience and reduce habitat loss. This study applies the Sea [...] Read more.
Coastal marshes provide essential ecosystem services, yet they are vulnerable to anthropogenic stressors and climate change, particularly sea level rise (SLR). Restoration approaches like marsh terracing have emerged as nature-based strategies to enhance resilience and reduce habitat loss. This study applies the Sea Level Affecting Marshes Model (SLAMM) to assess the potential of marsh terraces to mitigate future losses, while also examining the model’s limitations, including its assumptions and capacity to reflect complex marsh processes. A geospatial approach was used to generate 3D representations of terraces through morphostatic modeling within digital elevation models (DEMs). Under a no-restoration scenario, SLAMM projections show that all marshes analyzed are at risk of total loss by 2100. In contrast, scenarios including terracing demonstrate a delay in net marsh loss, extending the persistence of key marsh habitats by approximately a decade. Although marsh degradation remains likely under high SLR conditions, the results underscore the utility of marsh terraces in prolonging habitat stability. Additionally, the study demonstrates the feasibility of integrating restoration features like terraces into DEMs and wetland models. Despite SLAMM’s simplified erosion and accretion assumptions, the model yields important insights into restoration effectiveness and long-term marsh dynamics, informing more adaptive, forward-looking coastal management strategies. Full article
(This article belongs to the Special Issue New Insights into Sea Level Dynamics and Coastal Erosion)
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19 pages, 1545 KB  
Article
Study on an Evaluation Model for Regional Water Resource Stress Based on Water Scarcity Footprint
by Lu Qiao, Xue Bai, Yan Bai, Jialin Liu, Lingsi Kong and Lan Zhang
Water 2025, 17(18), 2768; https://doi.org/10.3390/w17182768 - 18 Sep 2025
Viewed by 242
Abstract
Under the multiple pressures of intensifying global climate change disruption and rapid economic growth, China has become one of the countries facing the most serious water scarcity problems. Based on the ISO 14046 standard and the framework of water scarcity footprint theory, this [...] Read more.
Under the multiple pressures of intensifying global climate change disruption and rapid economic growth, China has become one of the countries facing the most serious water scarcity problems. Based on the ISO 14046 standard and the framework of water scarcity footprint theory, this study will break through the static limitations and lack of dimensions of traditional characteristic factors (i.e., water stress) and construct a water stress evaluation index system that combines nature, economy, and society. The results indicate that in recent years, regional water stress in China has exhibited significant spatiotemporal variations and spatial clustering, primarily driven by composite factors, with an overall decreasing trend. Among them, Shanghai is the highest-pressure area and Shaanxi is the lowest-pressure area, which is mainly due to the spatial projection of the coupling effect of multi-dimensional factors. In addition, the obstacle degree analysis method shows that indicators such as the utilization rate of water resource development constitute cross-regional constraints. To this end, all regions should make efforts to regulate and control the water use structure, introduce water-saving technologies, and strengthen water-saving publicity according to their needs. Therefore, this study not only provides a scientific basis for in-depth understanding of the distribution law and influencing mechanism of water stress but also provides an important reference for the rational allocation and sustainable use of water resources by upgrading the characteristic factors to system control signals. Full article
(This article belongs to the Section Water Use and Scarcity)
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15 pages, 881 KB  
Article
Prevalence and Resistance Patterns of Campylobacter spp. and Arcobacter spp. in Portuguese Water Bodies
by Igor Venâncio, Inês Martins, Rodrigo M. Martins, Mónica Oleastro and Susana Ferreira
Water 2025, 17(18), 2767; https://doi.org/10.3390/w17182767 - 18 Sep 2025
Viewed by 208
Abstract
Campylobacter spp. and Arcobacter spp. are recognized etiological agents of gastroenteritis worldwide. While poultry is their best-known reservoir, human exposure can also occur via environmental pathways, particularly through contaminated water sources, which play a significant role in their transmission dynamics. In addition to [...] Read more.
Campylobacter spp. and Arcobacter spp. are recognized etiological agents of gastroenteritis worldwide. While poultry is their best-known reservoir, human exposure can also occur via environmental pathways, particularly through contaminated water sources, which play a significant role in their transmission dynamics. In addition to their pathogenicity and widespread environmental prevalence, increasing antibiotic resistance has contributed to the global emergence of multidrug-resistant strains, hindering effective treatment. Here, the distribution and antibiotic resistance potential of Campylobacter spp. and Arcobacter spp. isolates collected from water bodies in Portugal were investigated. Water samples were collected from rivers, their tributaries, and springs, at 25 sites over a six-month period. Campylobacter spp. were isolated from 13.3% of the samples, whereas Arcobacter spp. were detected in 57.6% of the samples. Of the 27 isolated Campylobacter isolates, 44.0% were resistant to at least one antibiotic, while only one strain exhibited a multidrug-resistant (MDR) phenotype. In contrast, 98.9% of the 177 Arcobacter isolates were resistant to at least one antibiotic, with 15.8% classified as MDR. These findings contribute to the surveillance of Campylobacter spp. and Arcobacter spp., highlighting the critical role of aquatic environments in their epidemiology and supporting the need to incorporate waterborne transmission pathways into integrated surveillance and control strategies within the One Health framework. Full article
(This article belongs to the Special Issue Evaluation of Microbiological Indicators for Water and Wastewater Treatment and Reuse)
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21 pages, 4834 KB  
Article
A Displacement Monitoring Model for High-Arch Dams Based on SHAP-Driven Ensemble Learning Optimized by the Gray Wolf Algorithm
by Shasha Li, Kai Jiang, Shunqun Yang, Zuxiu Lan, Yining Qi and Huaizhi Su
Water 2025, 17(18), 2766; https://doi.org/10.3390/w17182766 - 18 Sep 2025
Viewed by 275
Abstract
Displacement monitoring data is essential for assessing the structural safety of high-arch dams. Existing models, predominantly based on single-model architectures, often lack the ability to effectively integrate multiple algorithms, leading to limited predictive performance and poor interpretability. This study proposes an ensemble learning [...] Read more.
Displacement monitoring data is essential for assessing the structural safety of high-arch dams. Existing models, predominantly based on single-model architectures, often lack the ability to effectively integrate multiple algorithms, leading to limited predictive performance and poor interpretability. This study proposes an ensemble learning framework for dam displacement prediction, combining Hydraulic–Seasonal–Temporal model (HST), Random Forest (RF), and Bidirectional Gated Recurrent Unit (BiGRU) models as base learners. A stacking strategy is employed to enhance predictive accuracy, and the Grey Wolf Optimizer (GWO) is used for hyperparameter optimization. To improve model transparency, the Shapley Additive Explanations (SHAP) algorithm is applied for interpretability analysis. Extensive experiments demonstrate that the proposed ensemble model outperforms individual models, achieving a Root Mean Squared Error (RMSE) of 0.2241 and a Coefficient of Determination (R2) of 0.9993 on the test set. The SHAP analysis further elucidates the contribution of key variables, providing valuable insights into the displacement prediction process and offering a robust technical foundation for arch dam safety monitoring and early risk warning. Full article
(This article belongs to the Special Issue Hydraulic Engineering Applications of Artificial Intelligence, Deep Learning, and Digital Twin Technology)
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26 pages, 4714 KB  
Article
Impacts of the Degree of Heterogeneity on Design Flood Estimates: Region of Influence vs. Fixed Region Approaches
by Ali Ahmed, Mohammad A. Morshed, Sadia T. Mim, Ridwan S. M. H. Rafi, Zaved Khan, Rajib Maity and Ataur Rahman
Water 2025, 17(18), 2765; https://doi.org/10.3390/w17182765 - 18 Sep 2025
Viewed by 463
Abstract
In regional flood frequency analysis (RFFA), the formation of homogeneous regions is commonly regarded as a necessary condition for reliable regional flood estimation. However, achieving true homogeneity is often challenging in practice. This study investigates the formation of homogeneous regions by applying two [...] Read more.
In regional flood frequency analysis (RFFA), the formation of homogeneous regions is commonly regarded as a necessary condition for reliable regional flood estimation. However, achieving true homogeneity is often challenging in practice. This study investigates the formation of homogeneous regions by applying two region delineation approaches—fixed regions and the region-of-influence (ROI) method—accompanied by the widely used heterogeneity measure (H1) proposed by Hosking and Wallis. The analysis utilizes data from 201 stream gauging stations across southeast Australia, evaluating a total of 1211 candidate regions. The computed H1-statistics range from 13 to 30 for fixed regions and from 6 to 30 for ROI-based regions, indicating a consistently high level of heterogeneity across the study area. This suggests that the assumption of homogeneity may not be realistic for many parts of southeast Australia. Moreover, regression equations developed for regional flood estimation yield absolute median relative errors between 29% and 56%, with a median of 39% across return periods from 2 to 100 years. These findings underscore the limitations of relying solely on homogeneity in regional flood modelling and highlight the need for more flexible and robust approaches in RFFA. The outcomes of this research have significant implications for improving flood estimation practices and are expected to contribute to future enhancements of the Australian Rainfall and Runoff (ARR) national guidelines. Full article
(This article belongs to the Special Issue Urban Flood Mitigation and Sustainable Stormwater Management—2nd Edition)
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18 pages, 2624 KB  
Article
Comparative Assessment of Different Electrode Combinations for Phosphate Removal from Onsite Wastewater via Electrocoagulation
by Arif Reza, Xiumei Jian, Fanjian Zeng and Xinwei Mao
Water 2025, 17(18), 2764; https://doi.org/10.3390/w17182764 - 18 Sep 2025
Viewed by 295
Abstract
Phosphorus (P) discharge from onsite wastewater treatment systems (OWTSs) poses a significant threat to water quality, contributing to eutrophication in nutrient-sensitive aquatic environments. In treated effluents, P predominantly exists as orthophosphate (PO43−), a highly bioavailable and reactive form that requires [...] Read more.
Phosphorus (P) discharge from onsite wastewater treatment systems (OWTSs) poses a significant threat to water quality, contributing to eutrophication in nutrient-sensitive aquatic environments. In treated effluents, P predominantly exists as orthophosphate (PO43−), a highly bioavailable and reactive form that requires targeted removal. This study evaluates the performance of electrocoagulation (EC) as a polishing step for PO43− removal from OWTS effluents using 12 anode/cathode combinations comprising aluminum (Al), iron (Fe), magnesium (Mg), and stainless steel (SS). Key operational parameters, including treatment time, mixing speed, current density, pH, and initial PO43− concentration, were systematically investigated when synthetic denitrified effluent (20 mg P/L) was treated. Based on the performance, the four most effective electrode combinations (Al/Al, Al/Mg, Fe/Al, and Mg/Mg), along with a commercial benchmark (Fe/Fe), were further tested under extended hydraulic retention times (up to 48 h) in both synthetic and real (denitrified) wastewater. To date, none of the studies have systematically evaluated all possible anode/cathode combinations involving multiple electrode materials under uniform operational conditions. The Al/Al and Mg/Mg EC systems achieved rapid and high PO43− removal efficiencies (>95%), while Mg-based systems demonstrated sustained performance over prolonged treatment durations, especially in real wastewater. Bimetallic pairs such as Al/Mg and Fe/Al exhibited synergistic effects through enhanced coagulant generation and pH stabilization. The results indicated that PO43− removal efficiency was strongly influenced by electrode material selection, hydrodynamic conditions, and wastewater compositions, underscoring the need to design EC systems based on site-specific water quality conditions in OWTSs. Full article
(This article belongs to the Special Issue Application of Electrochemical Technologies in Wastewater Treatment)
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22 pages, 6378 KB  
Article
LU-Net: Lightweight U-Shaped Network for Water Body Extraction of Remote Sensing Images
by Chengzhi Deng, Ruqiang He, Zhaoming Wu, Xiaowei Sun and Shengqian Wang
Water 2025, 17(18), 2763; https://doi.org/10.3390/w17182763 - 18 Sep 2025
Viewed by 257
Abstract
Deep learning-based water body extraction methods generally focus on maximizing accuracy while neglecting inference speed, which can make them challenging to apply in real-time applications. To address this problem, this paper proposes a lightweight u-shaped network (LU-Net), which improves inference speed while maintaining [...] Read more.
Deep learning-based water body extraction methods generally focus on maximizing accuracy while neglecting inference speed, which can make them challenging to apply in real-time applications. To address this problem, this paper proposes a lightweight u-shaped network (LU-Net), which improves inference speed while maintaining comparable accuracy. To reduce inference latency, a lightweight decoder block (LDB) is designed, which employs a depthwise separable convolution structure to accelerate the decoding process. To enhance accuracy, a lightweight convolutional block attention module (LCBAM) is designed, which effectively captures water-specific spectral and spatial characteristics through a dual-attention mechanism. To improve multi-scale water boundary extraction, a structurally re-parameterized multi-scale fusion prediction module (SRMFPM) is designed, which integrates multi-scale water boundary information through convolutions of different sizes. Comparative experiments are conducted on the GID and LoveDA datasets, with model performance assessed using the MIoU metric and inference latency. The results demonstrate that LU-Net achieves the lowest GPU latency of 3.1 MS and the second-lowest CPU latency of 36 MS in the experiments. On the GID, LU-Net achieves the MIoU of 91.36%, outperforming other tested methods. On the LoveDA datasets, LU-Net achieves the second-highest MIoU of 86.32% among the evaluated models, which is 0.08% lower than the top-performing CGNet. Considering both latency and MIoU, LU-Net demonstrates commendable efficiency on the GID and LoveDA datasets across all compared networks. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
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