Water

18 pages, 2770 KB

Open AccessArticle

Distribution Characteristics and Enrichment Mechanisms of Fluoride in Alluvial–Lacustrine Facies Clayey Sediments in the Land Subsidence Area of Cangzhou Plain, China

by Juyan Zhu, Rui Liu, Haipeng Guo, Juan Chen, Di Ning and Xisheng Zang

Water 2025, 17(19), 2887; https://doi.org/10.3390/w17192887 - 3 Oct 2025

Abstract

Compression of clayey sediments not only causes land subsidence but also results in geogenic high fluoride groundwater. The distribution characteristics and enrichment mechanisms of fluoride in alluvial−lacustrine facies clayey sediments in the land subsidence area of Cangzhou Plain, China, were investigated using sample [...] Read more.

Compression of clayey sediments not only causes land subsidence but also results in geogenic high fluoride groundwater. The distribution characteristics and enrichment mechanisms of fluoride in alluvial−lacustrine facies clayey sediments in the land subsidence area of Cangzhou Plain, China, were investigated using sample collection, mineralogical research, and hydrogeochemical and isotopic analysis. The results show that F⁻ concentration of groundwater samples ranged from 0.31 to 5.54 mg/L in aquifers. The total fluoride content of clayey sediments ranged from 440 to 792 mg/kg and porewater F⁻ concentration ranged from 0.77 to 4.18 mg/L. Clay minerals containing fine particles, such as muscovite, facilitate the enrichment of fluoride in clayey sediments, resulting in higher total fluoride levels than those in sandy sediments. The clay porewater F⁻ predominantly originated from the dissolution of water-soluble F and the desorption of exchangeable F from sediments. The F⁻ concentration in porewater was further influenced by ionic interactions such as cation exchange. The stable sedimentary environment and intense compression promoted the dissolution of F–bearing minerals and the desorption of adsorbed F in deep clayey sediments. The similar composition feature of δ²H−δ¹⁸O in deep groundwater and clay porewater samples suggests a significant mixing effect. These findings highlight the joint effects of hydrogeochemical and mineralogical processes on F behavior in clayey sediments. Full article

(This article belongs to the Special Issue Advancing Knowledge of the Impacts of Contaminants in Aquatic Environments)

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15 pages, 2076 KB

Open AccessArticle

Forecasting Urban Water Demand Using Multi-Scale Artificial Neural Networks with Temporal Lag Optimization

by Elias Farah and Isam Shahrour

Water 2025, 17(19), 2886; https://doi.org/10.3390/w17192886 - 3 Oct 2025

Abstract

Accurate short-term forecasting of urban water demand is a persistent challenge for utilities seeking to optimize operations, reduce energy costs, and enhance resilience in smart distribution systems. This study presents a multi-scale Artificial Neural Network (ANN) modeling approach that integrates temporal lag optimization [...] Read more.

Accurate short-term forecasting of urban water demand is a persistent challenge for utilities seeking to optimize operations, reduce energy costs, and enhance resilience in smart distribution systems. This study presents a multi-scale Artificial Neural Network (ANN) modeling approach that integrates temporal lag optimization to predict daily and hourly water consumption across heterogeneous user profiles. Using high-resolution smart metering data from the SunRise Smart City Project in Lille, France, four demand nodes were analyzed: a District Metered Area (DMA), a student residence, a university restaurant, and an engineering school. Results demonstrate that incorporating lagged consumption variables substantially improves prediction accuracy, with daily R² values increasing from 0.490 to 0.827 at the DMA and from 0.420 to 0.806 at the student residence. At the hourly scale, the 1-h lag model consistently outperformed other configurations, achieving R² up to 0.944 at the DMA, thus capturing both peak and off-peak consumption dynamics. The findings confirm that short-term autocorrelation is a dominant driver of demand variability, and that ANN-based forecasting enhanced by temporal lag features provides a robust, computationally efficient tool for real-time water network management. Beyond improving forecasting performance, the proposed methodology supports operational applications such as leakage detection, anomaly identification, and demand-responsive planning, contributing to more sustainable and resilient urban water systems. Full article

(This article belongs to the Section Urban Water Management)

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11 pages, 1669 KB

Open AccessArticle

From Filamentous Bulking to Utilization: Formation Mechanisms of Filamentous Biofilms and Construction of Stabilized Systems

by Tao Song, Ji Li and Xiaolei Zhang

Water 2025, 17(19), 2885; https://doi.org/10.3390/w17192885 - 3 Oct 2025

Abstract

Sludge bulking in wastewater treatment is often caused by massive filamentous bacteria. This study aimed to turn such bacteria into a stable system dominated by filamentous biofilms (FBs) by using a continuous flow reactor (CFR) fed with simulated domestic wastewater; to address FBs’ [...] Read more.

Sludge bulking in wastewater treatment is often caused by massive filamentous bacteria. This study aimed to turn such bacteria into a stable system dominated by filamentous biofilms (FBs) by using a continuous flow reactor (CFR) fed with simulated domestic wastewater; to address FBs’ poor solid–liquid separation and uncontrollable sludge retention time (SRT), string carriers were added, SRT was controlled at 30 days, and parameters like mixed liquid suspended solids (MLSS) and sludge volume index (SVI) were monitored. Results showed filamentous Sphaerotilus (68–93% of FBs) self-aggregated as FBs’ reticular skeleton (loose, porous, stable, max 8 cm) with non-filamentous bacteria anchoring; FBs achieved >80% COD/NH₄⁺-N removal despite low MLSS (<1000 mg/L) and SVI > 350 mL/g. The application of carriers increased the proportion of non-filamentous microorganisms to over 80%, reduced SVI to 150–400 mL/g, and increased MLSS to over 2700 mg/L, enabling stable operation. This study challenges the traditional negative perception of filamentous bacteria and opens new prospects for wastewater treatment technology. Full article

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

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21 pages, 3155 KB

Open AccessArticle

Human Impacts on Heavy Metals in Lake Sediments of Northern China: History, Sources, and Trend Prediction

by Ruifeng Xie, Shuying Zang, Li Sun and Hongwei Ni

Water 2025, 17(19), 2884; https://doi.org/10.3390/w17192884 - 2 Oct 2025

Abstract

Lake sediments are important indicators of human activities and environmental changes, while lakes in northern China receive little attention. Heavy metal elements in core sediments from Bosten Lake (BST) in the arid area, Wuliangsuhai Lake (WLS) in the semi-arid area, and Chagan Lake [...] Read more.

Lake sediments are important indicators of human activities and environmental changes, while lakes in northern China receive little attention. Heavy metal elements in core sediments from Bosten Lake (BST) in the arid area, Wuliangsuhai Lake (WLS) in the semi-arid area, and Chagan Lake (CG) in the semi-humid area of northern China, based on the precise dating of ²¹⁰Pb and ¹³⁷Cs, were analyzed to evaluate the characteristics and sources of heavy metal pollution, analyze the influence of different types and intensities of human activities on heavy metals, and predict the development trend of heavy metal content in lake sediments in the future. The content of heavy metals in the sediments of the three lakes has gradually increased over time, with a decreasing trend of CG > WLS > BST, which is in accordance with the intensity of human activities. Co, Cu, Zn, Cd, As, and Pb are greatly influenced by human activities and mainly come from wastewater, waste residue, and waste gas produced by industrial activities, pesticide residues from agricultural activities, and pollution from domestic sewage, while, Cr and Ni come from both natural sources and human activities. Mn and Fe are relatively stable and mainly come from natural sources. The development trend of heavy metal content in the sediments of various lakes in the future is predicted by regression analysis. Fe and As in WLS and Cr, Mn, Ni, and Cu in BST show upward trends, indicating that the influences of industrial activities, agricultural activities, domestic emissions, and air pollutants on heavy metal pollution in lake sediments have a continuous effect. The results can provide a scientific basis for the effective control and environmental governance of heavy metal pollution in lakes. Full article

(This article belongs to the Section Water Quality and Contamination)

19 pages, 3846 KB

Open AccessArticle

Impact of the Tigray War on Water Infrastructures and Essential Hydrosystems in Selected Battle Corridors

by Gebremedhin Berhane, Tesfamichael Gebreyohannes, Miruts Hagos, Abdelwassie Huessien, Aregawi Gebrekirstos, Kaleab Adhena Abera, Thomas Hermans and Kristine Walraevens

Water 2025, 17(19), 2883; https://doi.org/10.3390/w17192883 - 2 Oct 2025

Abstract

Armed conflicts continue to severely impact human populations and essential infrastructure, particularly water supply systems. This study examines the Yechilla area, a high-intensity battle corridor during the Tigray (between 12°15′26″ 14°57′49″ N latitude; and 36°20′57″–39°58′54″ E longitude) war (2020–2022). Using Cochran’s formula, a [...] Read more.

Armed conflicts continue to severely impact human populations and essential infrastructure, particularly water supply systems. This study examines the Yechilla area, a high-intensity battle corridor during the Tigray (between 12°15′26″ 14°57′49″ N latitude; and 36°20′57″–39°58′54″ E longitude) war (2020–2022). Using Cochran’s formula, a representative sample of 89 water schemes was selected for onsite assessment. Additional data on damages to water offices, personnel, equipment, and related infrastructure were gathered through face-to-face interviews with local officials and water professionals, onsite visits, and reviews of governmental and non-governmental archives, and previous studies. The findings reveal that 48.3% of water schemes in the study area are non-functional (does not deliver water), which is a significant increase from pre-war non-functionality rates of approximately 7.1% regionally and 21.1% nationally. Despite the Pretoria peace agreement, non-functionality levels remain critically high two years after conflict. Damage includes partial impairments, lack of technical and spare part support, complete destruction, and looting of water scheme components. The widespread destruction of civilian water infrastructure during the Tigray conflict underscores the insufficiency of existing international legal frameworks, such as the International Humanitarian Law and International Water Law, which are inadequately protecting civilians and their property. Understanding the broader consequences of armed conflicts requires examining the indirect effects and the complex interactions within and between social, economic, and environmental systems. These interconnected impacts are essential to fully grasp how conflict affects livelihoods and human security on a wider scale. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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22 pages, 1567 KB

Open AccessArticle

Short-Term Displacement Prediction of Rainfall-Induced Landslides Through the Integration of Static and Dynamic Factors: A Case Study of China

by Chuyun Cheng, Wenyi Zhao, Lun Wu, Xiaoyin Chang, Bronte Scheuer, Jianxue Zhang, Ruhao Huang and Yuan Tian

Water 2025, 17(19), 2882; https://doi.org/10.3390/w17192882 - 2 Oct 2025

Abstract

Rainfall-induced landslide deformation is governed by both intrinsic geological conditions and external dynamic triggers. However, many existing predictive models rely primarily on rainfall inputs, which limits their interpretability and robustness. To address these shortcomings, this study introduces a group-based data augmentation method informed [...] Read more.

Rainfall-induced landslide deformation is governed by both intrinsic geological conditions and external dynamic triggers. However, many existing predictive models rely primarily on rainfall inputs, which limits their interpretability and robustness. To address these shortcomings, this study introduces a group-based data augmentation method informed by displacement curve morphology and proposes a multi-slope predictive framework that integrates static geological attributes with dynamic triggering factors. Using monitoring data from 274 sites across China, the framework was implemented with a Temporal Fusion Transformer (TFT) and benchmarked against baseline models, including SVR, XGBoost, and LSTM models. The results demonstrate that group-based augmentation enhances the stability and accuracy of predictions, while the integrated dynamic–static TFT framework delivers superior accuracy and improved interpretability. Statistical significance testing further confirms consistent performance improvements across all groups. Collectively, these findings highlight the framework’s effectiveness for short-term landslide forecasting and underscore its potential to advance early warning systems. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

21 pages, 5141 KB

Open AccessArticle

Groundwater Pollution Source Identification Based on a Coupled PCA–PMF–Mantel Framework: A Case Study of the Qujiang River Basin

by Xiao Li, Ying Zhang, Liangliang Xu, Jiyi Jiang, Chaoyu Zhang, Guanghao Wang, Huan Huan, Dengke Tian and Jiawei Guo

Water 2025, 17(19), 2881; https://doi.org/10.3390/w17192881 - 2 Oct 2025

Abstract

This study develops an integrated framework for groundwater pollution source identification by coupling Principal Component Analysis (PCA), Positive Matrix Factorization (PMF), and the Mantel test, with the Qujiang River Basin as a case study. The framework enables a full-process assessment, encompassing qualitative identification, [...] Read more.

This study develops an integrated framework for groundwater pollution source identification by coupling Principal Component Analysis (PCA), Positive Matrix Factorization (PMF), and the Mantel test, with the Qujiang River Basin as a case study. The framework enables a full-process assessment, encompassing qualitative identification, quantitative apportionment, and spatial validation of pollution drivers. Results indicate that groundwater chemistry is primarily influenced by three categories of sources: natural rock weathering, agricultural and domestic activities, and industrial wastewater discharge. Anthropogenic sources account for 73.7% of the total contribution, with mixed agricultural and domestic inputs dominating (38.5%), followed by industrial effluents (35.2%), while natural weathering contributes 26.3%. Mantel test analysis further shows that agricultural and domestic pollution correlates strongly with intensive farmland distribution in the midstream area, natural sources correspond to carbonate outcrops and higher elevations in the upstream, and industrial contributions cluster in downstream industrial zones. By integrating PCA, PMF, and Mantel analysis, this study offers a robust and transferable framework that improves both the accuracy and spatial interpretability of groundwater pollution source identification. The proposed approach provides scientific support for regionalized groundwater pollution prevention and control under complex hydrogeological settings. Full article

(This article belongs to the Special Issue Advance in Hydrology and Hydraulics of the River System Research 2025)

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19 pages, 1316 KB

Open AccessArticle

A Comprehensive Model for Predicting Water Advance and Determining Infiltration Coefficients in Surface Irrigation Systems Using Beta Cumulative Distribution Function

by Amir Panahi, Amin Seyedzadeh, Miguel Ángel Campo-Bescós and Javier Casalí

Water 2025, 17(19), 2880; https://doi.org/10.3390/w17192880 - 2 Oct 2025

Abstract

Surface irrigation systems are among the most common yet often inefficient methods due to poor design and management. A key factor in optimizing their design is the accurate prediction of the water advance and infiltration relationships’ coefficients. This study introduces a novel model [...] Read more.

Surface irrigation systems are among the most common yet often inefficient methods due to poor design and management. A key factor in optimizing their design is the accurate prediction of the water advance and infiltration relationships’ coefficients. This study introduces a novel model based on the Beta cumulative distribution function for predicting water advance and estimating infiltration coefficients in surface irrigation systems. Traditional methods, such as the two-point approach, rely on limited data from only the midpoint and endpoint of the field, often resulting in insufficient accuracy and non-physical outcomes under heterogeneous soil conditions. The proposed model enhances predictive flexibility by incorporating the entire advance dataset and integrating the midpoint as a constraint during optimization, thereby improving the accuracy of advance curve estimation and subsequent infiltration coefficient determination. Evaluation using field data from three distinct sites (FS, HF, WP) across 10 irrigation events demonstrated the superiority of the proposed model over the conventional power advance method. The new model achieved average RMSE, MAPE, and R² values of 0.790, 0.109, and 0.997, respectively, for advance estimation. For infiltration prediction, it yielded an average error of 12.9% in total infiltrated volume—outperforming the two-point method—and also showed higher accuracy during the advance phase, with average RMSE, MAPE, and R² values of 0.427, 0.075, and 0.990, respectively. These results confirm that the Beta-based model offers a more robust, precise, and reliable tool for optimizing the design and management of surface irrigation systems. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

20 pages, 2655 KB

Open AccessArticle

Experimental Assessment of Vegetation Density and Orientation Effects on Flood-Induced Pressure Forces and Structural Accelerations

by Imran Qadir, Afzal Ahmed, Abdul Razzaq Ghumman, Manousos Valyrakis, Syed Saqib Mehboob, Ghufran Ahmed Pasha, Fakhar Muhammad Abbas and Irfan Qadir

Water 2025, 17(19), 2879; https://doi.org/10.3390/w17192879 - 2 Oct 2025

Abstract

This study aims to assess the effect of vegetation angle and density on hydrostatic pressure and acceleration of a downstream house model experimentally. The vegetation cylinders were positioned at angles 30°, 45°, 60° and 90° with respect to the flow and two densities [...] Read more.

This study aims to assess the effect of vegetation angle and density on hydrostatic pressure and acceleration of a downstream house model experimentally. The vegetation cylinders were positioned at angles 30°, 45°, 60° and 90° with respect to the flow and two densities of vegetation conditions, i.e., sparse (G/d = 2.13) and intermediate (G/d = 1.09), where G is the spacing between the model vegetation elements in the cross-stream di-rection and d is the vegetation diameter. The streamwise acceleration of the house model was measured by an X2-2 accelerometer that was located downstream from the vegetation patches. Results show that the perpendicular orientation of the vegetation patch (90°) most effectively reduces hydrodynamic loads, with intermediate density (I90) achieving the highest reductions, i.e., 22.1% for acceleration and 7.4% for pressure impacts. Even sparse vegetation (S90) provided substantial protection, reducing acceleration by 21.9% and pressure by 5.8%. These findings highlight the importance of integrating vegetation density and orientation into flood management designs to enhance both their performance and reliability under varying hydraulic conditions. Full article

(This article belongs to the Special Issue Advancing Hydro-Environmental Research and Practice: Integrating Ecohydrology, Remote Sensing and Hydroinformatics)

22 pages, 1280 KB

Open AccessArticle

Mechanism and Measurement of Coordinated Development in the Mariculture Ecological–Economic–Social Complex System: A Case Study of China

by Runsheng Pei, Hongzhi Zhang, Yongtong Mu, Md. Hashmi Sakib, Yingxue Zhang, Xin Liu, Xia Huang, Aiqin Ge, Runfeng Pei and Ruohan Wang

Water 2025, 17(19), 2878; https://doi.org/10.3390/w17192878 - 2 Oct 2025

Abstract

The coordinated development of a complex system refers to the harmonious and coherent evolution of its subsystems. From the perspective of the coordinated development of ecological–economic–social complex systems, this paper analyzes the coordinated development mechanism (CDM) of the mariculture ecological–economic–social (MEES) complex system, [...] Read more.

The coordinated development of a complex system refers to the harmonious and coherent evolution of its subsystems. From the perspective of the coordinated development of ecological–economic–social complex systems, this paper analyzes the coordinated development mechanism (CDM) of the mariculture ecological–economic–social (MEES) complex system, constructs a coordinated development evaluation indicator system for the MEES complex system, and adopts the comprehensive evaluation model and the coupling coordination degree (CCD) model to empirically analyze the coordinated development level of the MEES complex system in China from 2009 to 2020. The results show that the comprehensive development level of China’s MEES complex system has improved significantly during this period, with the comprehensive development index increasing from 0.25 in 2009 to 0.76 in 2020, transitioning from a poor to an excellent status. Simultaneously, the CCD of the system increased progressively, experiencing phases of near dissonance, barely coupling coordination, primary coordination, and intermediate coordination, before finally reaching a stage of good coordination. Based on these findings, we further discuss and propose countermeasures to promote the coordinated development of China’s MEES complex system. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

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26 pages, 12966 KB

Open AccessArticle

Dynamic Co-Optimization of Features and Hyperparameters in Object-Oriented Ensemble Methods for Wetland Mapping Using Sentinel-1/2 Data

by Yue Ma, Yongchao Ma, Qiang Zheng and Qiuyue Chen

Water 2025, 17(19), 2877; https://doi.org/10.3390/w17192877 - 2 Oct 2025

Abstract

Wetland mapping plays a crucial role in monitoring wetland ecosystems, water resource management, and habitat suitability assessment. Wetland classification remains significantly challenging due to the diverse types, intricate spatial patterns, and highly dynamic nature. This study proposed a dynamic hybrid method that integrated [...] Read more.

Wetland mapping plays a crucial role in monitoring wetland ecosystems, water resource management, and habitat suitability assessment. Wetland classification remains significantly challenging due to the diverse types, intricate spatial patterns, and highly dynamic nature. This study proposed a dynamic hybrid method that integrated feature selection and object-oriented ensemble model construction to improve wetland mapping using Sentinel-1 and Sentinel-2 data. The proposed feature selection approach integrates the ReliefF and recursive feature elimination (RFE) algorithms with a feature evaluation criterion based on Shapley additive explanations (SHAP) values, aiming to optimize the feature set composed of various variables. During the construction of ensemble models (i.e., RF, XGBoost, and LightGBM) with features selected by RFE, hyperparameter tuning is subsequently conducted using Bayesian optimization (BO), ensuring that the selected optimal features and hyperparameters significantly enhance the accuracy and performance of the classifiers. The accuracy assessment demonstrates that the BO-LightGBM model with ReliefF-RFE-SHAP-selected features achieves superior performance to the RF and XGBoost models, achieving the highest overall accuracy of 89.4% and a kappa coefficient of 0.875. The object-oriented classification maps accurately depict the spatial distribution patterns of different wetland types. Furthermore, SHAP values offer global and local interpretations of the model to better understand the contribution of various features to wetland classification. The proposed dynamic hybrid method offers an effective tool for wetland mapping and contributes to wetland environmental monitoring and management. Full article

(This article belongs to the Special Issue Remote Sensing of Spatial-Temporal Variation in Surface Water)

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23 pages, 6028 KB

Open AccessArticle

Bayesian Analysis of Stormwater Pump Failures and Flood Inundation Extents

by Sebastian Ramsauer, Felix Schmid, Georg Johann, Daniela Falter, Hannah Eckers and Jorge Leandro

Water 2025, 17(19), 2876; https://doi.org/10.3390/w17192876 - 2 Oct 2025

Abstract

Former coal mining in the Ruhr area of North Rhine-Westphalia, Germany, leads to significant challenges in flood management due to drainless sinks in urban areas caused by ground depression. Consequently, pumping stations have been constructed to enable the drainage of incoming river discharge, [...] Read more.

Former coal mining in the Ruhr area of North Rhine-Westphalia, Germany, leads to significant challenges in flood management due to drainless sinks in urban areas caused by ground depression. Consequently, pumping stations have been constructed to enable the drainage of incoming river discharge, preventing overland flooding. However, in the event of the failure of pumping stations, these areas are exposed to a higher flood risk. To address this issue, a methodology has been developed to assess the probability of pumping failures by identifying the most significant failure mechanisms and integrating them into a Bayesian network. To evaluate the impact on the flood inundation probability, a new approach is applied that defines pump failure scenarios depending on available pump discharge capacity and integrates them into a flood inundation probability map. The result is a method to estimate the flood inundation probability stemming from pumping failure, which allows the integration of internal failure mechanisms (e.g., technical or electronic failure) as well as external failure mechanisms (e.g., sedimentation or heavy rainfall). Therefore, authorities can assess the most probable pumping failures and their impact on flood risk management strategies. Full article

(This article belongs to the Section Hydrology)

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27 pages, 8550 KB

Open AccessArticle

Relationship Between Runoff and Sediment Transfer in a Slope–Gully Cascade System During Extreme Hydrological Events in the Lublin Upland, East Poland

by Grzegorz Janicki, Jan Rodzik and Waldemar Kociuba

Water 2025, 17(19), 2875; https://doi.org/10.3390/w17192875 - 2 Oct 2025

Abstract

Erosion monitoring was carried out between 2003 and 2022 using a hydrological station with a Thomson overflow, a water gauge, and a limnigraph installed at the outlet of the Kolonia Celejów gully system. The study area is located in the north-western part of [...] Read more.

Erosion monitoring was carried out between 2003 and 2022 using a hydrological station with a Thomson overflow, a water gauge, and a limnigraph installed at the outlet of the Kolonia Celejów gully system. The study area is located in the north-western part of the Lublin Upland in the Nałęczów Plateau mesoregion (SE Poland). The total amount and intensity of precipitation were measured using an automatic station and water runoff and suspended sediment yield (SST) were also continuously measured. High variability in water runoff was observed during this period (max. of about 76,000 m³ and mean > 26,000 m³), and as a result of numerous heavy rains, a significant increase in SST (max. of about 95 Mg to about 1200 Mg and mean of 24 Mg to about 215 Mg) was noted in the second half of the measurement period. Most of the material removed at that time came from the cutting of the gully bottom and from the redeposition of material transported from the catchment used for agricultural purposes. In order to determine the volume of material delivered to the slope–gully cascade system in November 2012, a second station was installed at the gully head, which only operated until June 2013. However, the measurements covered all snowmelts and summer runoffs, as well as the June downpours. At the same time, these measurements represent the first unique attempt to quantify the delivery of material from the slope subcatchment to the gully system. The year 2013 was also important in terms of water runoff from the loess gully catchment area (about 40,000 m³) and was a record year (SST > 1197 Mg) for the total amount of suspended material runoff (7.6% and 33.5% of the 20-year total, respectively). During the cool half of the year, 16,490 m³ of water (i.e., 42% of the annual total) flowed out of the gully catchment area, and during the warm half of the year, 23,742 m³ of water (59% of the annual total) flowed out. In contrast, 24,076.7 m³ of water flowed out of the slope subcatchment area during the year, with slightly more flowing out in the cool half of the year (12,395.9 m³ or 51.5% of the annual total). In the slope and gully subcatchment areas, the suspended sediment discharge clearly dominated in the warm half of the year (98% and 97%). The record-breaking SST amount in June was over 1100 Mg of suspended sediment, which accounted for 93% of the annual SST from the gully catchment area and over 94% in the case of the slope subcatchment area. The relationships in the slope–gully cascade system in 2013 were considered representative of the entire measurement series, which were used to determine the degree of connectivity between the slope and gully subsystems. During summer downpours, the delivery of slope material from agricultural fields accounted for approx. 15% of the material removed from the catchment area, which confirms the predominance of transverse transport in the slope catchment area and longitudinal transport in the gully. The opposite situation occurs during thaws, with as much as 90% of the material removed coming from the slope catchment area. At that time, longitudinal transport dominates on the slope and transverse transport dominates in the gully. Full article

(This article belongs to the Special Issue Soil Erosion and Sedimentation by Water)

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37 pages, 11728 KB

Open AccessArticle

Damage Analysis of the Eifel Route Railroad Infrastructure After the Flash Flood Event in July 2021 in Western Germany

by Eva-Lotte Schriewer, Julian Hofmann, Stefanie Stenger-Wolf, Sonja Szymczak, Tobias Vaitl and Holger Schüttrumpf

Water 2025, 17(19), 2874; https://doi.org/10.3390/w17192874 - 2 Oct 2025

Abstract

Extreme rainfall events characterized by small catchments with high-velocity flows pose critical challenges to infrastructure resilience, particularly the rail infrastructure, due to its partial location near rivers and in mountainous regions, and the limited availability of alternative routes. This can lead to severe [...] Read more.

Extreme rainfall events characterized by small catchments with high-velocity flows pose critical challenges to infrastructure resilience, particularly the rail infrastructure, due to its partial location near rivers and in mountainous regions, and the limited availability of alternative routes. This can lead to severe damages, often resulting in long-term route closures. To mitigate flash flood damage, detailed information about affected structures and damage processes is necessary. Therefore, this study presents a newly developed multi-criteria flash flood damage assessment framework for the rail infrastructure and a QGIS-based analysis of the most frequent damages. Applying the framework to Eifel route damages in Western Germany after the July 2021 flood disaster shows that nearly 45% of the damages affected the track superstructure, especially tracks and bedding. Additionally, power supply systems, sealing and drainage systems, as well as railway overpasses or bridges, were impacted. Approximately 30% of the railway section showed washout of ballast, gravel and soil. In addition, deposit of wood or stones occurred. Most damages were classified as minor (47%) or moderate (34%). Furthermore, damaged track sections were predominantly located within a 50 m distance to the Urft river, whereas undamaged track sections are often located at a greater distance to the Urft river. These findings indicate that the proposed framework is highly applicable to assess and classify damages. Critical elements and relations could be identified and can help to adapt standards and regulations, as well as to develop preventive measures in the next step. Full article

(This article belongs to the Special Issue Causes and Reconstruction of Catastrophic Flash Flood Disasters: Investigation, Analysis, Modelling and Risk Management, 2nd Edition)

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18 pages, 2532 KB

Open AccessArticle

Occurrence and Risk Assessment of Metals and Metalloids in Surface Drinking Water Sources of the Pearl River Basin

by Bin Li, Yang Hu, Yinying Zhu, Yubo Yang, Xiang Tu, Shouliang Huo, Qing Fu, Sheng Chang and Kunfeng Zhang

Water 2025, 17(19), 2873; https://doi.org/10.3390/w17192873 - 2 Oct 2025

Abstract

Based on monitoring data from 2019 to 2024 at 270 typical surface drinking water sources (SDWS) in the Pearl River Basin (PRB), the occurrence and health risks of metal and metalloid pollutants (MMPs) were analyzed from a large watershed scale and long-term evolution. [...] Read more.

Based on monitoring data from 2019 to 2024 at 270 typical surface drinking water sources (SDWS) in the Pearl River Basin (PRB), the occurrence and health risks of metal and metalloid pollutants (MMPs) were analyzed from a large watershed scale and long-term evolution. The results indicated that the overall pollution status of 8 MMPs (As, Cd, Pb, Mn, Sb, Ni, Ba, V) were at a low level and the concentrations of Cd, Pb, Ni, Ba, and V exhibited downward trends from 2019 to 2024. The distribution of MMPs exhibited significant regional differences with the main influencing factors including geological conditions, industrial activities, and urban development. River-type drinking water sources might be more affected by pollution from human activities such as industrial wastewater discharge, and the concentration levels of MMPs were generally higher than those in lake-type drinking water sources. Monte Carlo simulation revealed that 33.08% and 12.90% of total carcinogenic risks (TCR) exceeded the threshold of 10⁻⁶ for adults and children, respectively. Ba and Ni were the main contributors to the TCR, while As posed a certain non-carcinogenic risk to children. Sensitivity analysis indicated that concentrations of As and Ba were the main factors contributing to health risks. Although highly stringent water pollution control and a water resource protection policy have been implemented, it is still suggested to strengthen the control of As, Ba, and Ni in industrial-intensive areas and river-type water sources in the PRB. Full article

(This article belongs to the Special Issue Legacy and Emerging Contaminants in the Water Environment Under Contemporary Global Changes)

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4 pages, 126 KB

Open AccessEditorial

Spatial–Temporal Variation and Risk Assessment of Water Quality

by Yonggui Wang

Water 2025, 17(19), 2872; https://doi.org/10.3390/w17192872 - 2 Oct 2025

Abstract

Water is a fundamental resource for ecosystem health and sustainable societal development [...] Full article

(This article belongs to the Special Issue Spatial–Temporal Variation and Risk Assessment of Water Quality)

24 pages, 4495 KB

Open AccessArticle

Longitudinal Calculation of Water Poverty Index in the Middle East: Potential to Expedite Progress

by Ashraf Isayed, Juan M. Menendez-Aguado, Hatem Jemmali and Nidal Mahmoud

Water 2025, 17(19), 2871; https://doi.org/10.3390/w17192871 - 1 Oct 2025

Abstract

This study examines the longitudinal relationship and interactions among comprehensive water management, human development, and fragility. The seventeen Middle Eastern countries were examined for the period from 1996 to 2023. The Human Development Index (HDI) and Fragile States Index (FSI) were considered as [...] Read more.

This study examines the longitudinal relationship and interactions among comprehensive water management, human development, and fragility. The seventeen Middle Eastern countries were examined for the period from 1996 to 2023. The Human Development Index (HDI) and Fragile States Index (FSI) were considered as a proxy for human development and fragility. In addition, the Water Poverty Index (WPI) was thoroughly assessed using classical and improved methods to measure multidisciplinary water management. Findings highlight that “Resources” and “Environment” are the most critical components of WPI. Iran performed the most consistently across WPI versions, whereas Palestine performed the worst. “Capacity,” “Environment,” and “Access” are the most influential components of HDI. FSI was found to be the most sensitive to “Capacity” and “Environment”, which contribute to both human development and stability. This study provides empirical evidence to inform SDG 6 implementation by demonstrating the linkage between WPI components and progress in human development. Full article

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

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29 pages, 3020 KB

Open AccessArticle

Water Supply Management Index

by Mayra Mendoza Gómez, Daniel Tagle-Zamora, Jorge Luis Morales Martínez, Alex Caldera Ortega, Jesús Mora Rodríguez, Helena M. Ramos and Xitlali Delgado-Galván

Water 2025, 17(19), 2870; https://doi.org/10.3390/w17192870 - 1 Oct 2025

Abstract

One of the limiting factors in the implementation of water resource management is the absence of tools that help water programs evaluate processes and progress. This is because, until now, the indicators that have been developed have not addressed specific local characteristics and [...] Read more.

One of the limiting factors in the implementation of water resource management is the absence of tools that help water programs evaluate processes and progress. This is because, until now, the indicators that have been developed have not addressed specific local characteristics and issues. Therefore, in this research, a set of indicators has been proposed, with the purpose of developing a management index for urban public water supply, which will consider the Drinking Water and Sewer System of León (SAPAL), in the Mexican state of Guanajuato, as case study. This index will be useful to measure progress toward sustainable development, monitor the impact of public policies, and foster citizen participation. In order to propose a methodology that aligns with the changing environments, where proper decision-making is key to the current water management requirements, the combination of the Analytic Hierarchy Process (AHP) and Fuzzy Logic (FL) methodologies will be helpful for proper decision-making. All this will foster a paradigm shift towards appropriate water management actions that allow for the conditions and availability of human and natural resources, which the municipality has control of, for a long-term improvement that guarantees the well-being of the population. Full article

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26 pages, 7079 KB

Open AccessArticle

Hydrological Response Analysis Using Remote Sensing and Cloud Computing: Insights from the Chalakudy River Basin, Kerala

by Gudihalli Munivenkatappa Rajesh, Sajeena Shaharudeen, Fahdah Falah Ben Hasher and Mohamed Zhran

Water 2025, 17(19), 2869; https://doi.org/10.3390/w17192869 - 1 Oct 2025

Abstract

Hydrological modeling is critical for assessing water availability and guiding sustainable resource management, particularly in monsoon-dependent, data-scarce basins such as the Chalakudy River Basin (CRB) in Kerala, India. This study integrated the Soil Conservation Service Curve Number (SCS-CN) method within the Google Earth [...] Read more.

Hydrological modeling is critical for assessing water availability and guiding sustainable resource management, particularly in monsoon-dependent, data-scarce basins such as the Chalakudy River Basin (CRB) in Kerala, India. This study integrated the Soil Conservation Service Curve Number (SCS-CN) method within the Google Earth Engine (GEE) platform, making novel use of multi-source, open access datasets (CHIRPS precipitation, MODIS land cover and evapotranspiration, and OpenLand soil data) to estimate spatially distributed long-term runoff (2001–2023). Model calibration against observed runoff showed strong performance (NSE = 0.86, KGE = 0.81, R² = 0.83, RMSE = 29.37 mm and ME = 13.48 mm), validating the approach. Over 75% of annual runoff occurs during the southwest monsoon (June–September), with July alone contributing 220.7 mm. Seasonal assessments highlighted monsoonal excesses and dry-season deficits, while water balance correlated strongly with rainfall (r = 0.93) and runoff (r = 0.94) but negatively with evapotranspiration (r = –0.87). Time-series analysis indicated a slight rise in rainfall, a decline in evapotranspiration, and a marginal improvement in water balance, implying gradual enhancement of regional water availability. Spatial analysis revealed a west–east gradient in precipitation, evapotranspiration, and water balance, producing surpluses in lowlands and deficits in highlands. These findings underscore the potential of cloud-based hydrological modeling to capture spatiotemporal dynamics of hydrological variables and support climate-resilient water management in monsoon-driven and data-scarce river basins. Full article

(This article belongs to the Section Hydrology)

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