Water

25 pages, 6228 KB

Open AccessArticle

A Multi-Objective Trade-Off Analysis with NSGA-II and Pareto Strategies for Total Phosphorus Load Allocation and Engineering Configuration in Yangcheng Lake Basin

by Zijiajie Peng, Yingdong Yu and Yongzhou Cheng

Water 2026, 18(12), 1391; https://doi.org/10.3390/w18121391 (registering DOI) - 6 Jun 2026

Abstract

Yangcheng Lake, the third largest freshwater lake in the Taihu Plain (118.68 km²), serves critical functions in drinking water supply, aquaculture, and ecological regulation. This study aims to address the challenge of optimizing total phosphorus load allocation and engineering project configuration [...] Read more.

Yangcheng Lake, the third largest freshwater lake in the Taihu Plain (118.68 km²), serves critical functions in drinking water supply, aquaculture, and ecological regulation. This study aims to address the challenge of optimizing total phosphorus load allocation and engineering project configuration in the Yangcheng Lake basin by developing a multi-objective optimization model that integrates environmental, social, and economic dimensions with the goal of achieving three specific objectives: (1) maximizing ecological benefits, (2) minimizing life-cycle costs, and (3) minimizing the environmental Gini coefficient. The NSGA-II algorithm was used, with hyperparameters calibrated via orthogonal experiments and HV-GD evaluation. Under a normal flow year scenario, total phosphorus (TP) load allocation was optimized for an agricultural watershed where livestock manure contributes 86.5% of TP pollution. Five selection strategies (Economic Priority, Ecological Priority, Equity Priority, Ideal Point Method, Game Theory) were applied to the Pareto front. Results show synergy between ecological and equity objectives, both competing with economic cost. Optimal hyperparameters were a population size of 1000 and 1000 iterations. Among strategies, the Ideal Point Method achieved the best compromise (economic cost: 5772.7; Gini coefficient < 0.30). The proposed framework provides scientific support for pollution load allocation in plain river network regions, helping decision-makers balance economic development, ecological protection, and social equity. Full article

(This article belongs to the Topic Environmental Pollutant Management and Control)

27 pages, 2802 KB

Open AccessArticle

Bulk Decay Coefficient Assessment for Different Water Temperatures: Ensemble Temperature State Estimation Approach

by Elena Cejas, Sarai Díaz and Javier González

Water 2026, 18(12), 1390; https://doi.org/10.3390/w18121390 (registering DOI) - 6 Jun 2026

Abstract

Most water supply systems rely on free chlorine residual to ensure disinfection through the network and at the user’s tap. Temperature increase is known to accelerate the chlorine decay process and is typically associated with water quality deterioration. This is a challenging situation [...] Read more.

Most water supply systems rely on free chlorine residual to ensure disinfection through the network and at the user’s tap. Temperature increase is known to accelerate the chlorine decay process and is typically associated with water quality deterioration. This is a challenging situation under the current climate change scenario, which is bound to increase average temperatures and the intensity and frequency of extreme-temperature events. Moreover, water temperature varies through the supply network due to seasonal changes and thermal interaction, so it is not straightforward to model chlorine evolution through the network considering temperature effects. Previous works have highlighted the importance of considering the Arrhenius formula when accounting for temperature changes in the bulk chlorine decay coefficient (typically characterized through bottle tests), but these studies have never explicitly considered the uncertainty of the bulk decay coefficient itself. Recent studies have identified that the uncertainty of the bulk decay coefficient may be relevant (>15%) and should be considered when cross-comparing bottle test results (e.g., at different temperatures). The aim of this work is to propose a new method that statistically computes the mean and standard deviation of the key parameters in the Arrhenius formula (the reference bulk decay coefficient

k_{b_{0}}

and activation coefficient E/R) from free chlorine residual bottle test results (with replicated measurements over samples from the entrance to the network) at different temperatures. This approach (here called the ensemble temperature state estimation approach) ensures that bottle test measurements at different temperatures are jointly assessed to derive an equation that provides the bulk decay coefficient at any water temperature. Therefore, the new method improves the characterization of the bulk decay component (and its associated uncertainty) and could be crucial for improving the understanding and modeling capabilities of complex chlorine dynamics within supply infrastructure. Full article

(This article belongs to the Section Urban Water Management)

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19 pages, 15571 KB

Open AccessReview

A Review of Water Distribution System Modeling and Calibration: Insights into Desalinated Water Integration

by Jefferson S. Rocha, José Gescilam S. M. Uchôa, Bruno M. Brentan and Iran E. Lima Neto

Water 2026, 18(12), 1389; https://doi.org/10.3390/w18121389 (registering DOI) - 6 Jun 2026

Abstract

The management of water availability in urban areas has become progressively more complex due to adverse climatic conditions and the continuous growth in water demand. These concerns have driven the search for alternative water supply sources, such as desalination, as well as the [...] Read more.

The management of water availability in urban areas has become progressively more complex due to adverse climatic conditions and the continuous growth in water demand. These concerns have driven the search for alternative water supply sources, such as desalination, as well as the need for a deeper understanding of the hydraulic and operational behavior of water distribution systems (WDS) in the face of these challenges. This study presents an exploratory and integrative literature review on the modeling and calibration of WDS, with an emphasis on their application to the analysis of hydraulic and operational impacts associated with the integration of desalinated water into large-scale WDS. The results, supported by bibliometric analysis and a comparative assessment of 28 real-world calibration studies, highlight advances in modeling and calibration techniques and identify engineering-based trends and research gaps related to desalinated water integration in WDS. These include increased pressure heterogeneity associated with desalinated water injection points, challenges related to intermittent operation, and the need for properly managed storage reservoirs. Overall, the findings reinforce hydraulic modeling and calibration as central tools for the integrated assessment of desalination impacts in large-scale water distribution systems. Full article

(This article belongs to the Special Issue The Safety Operations and Intelligent Control of Water Network Engineering Systems)

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16 pages, 922 KB

Open AccessArticle

Genotoxic Effects of River Waters in Northern Armenia Evaluated with Tradescantia Test Systems

by Rimma Avalyan, Alla Khosrovyan, Bardukh Gabrielyan, Rouben Aroutiounian and Anahit Atoyants

Water 2026, 18(12), 1388; https://doi.org/10.3390/w18121388 (registering DOI) - 6 Jun 2026

Abstract

The quality of riverine water is largely influenced by anthropogenic activity; however, worldwide monitoring practices remain largely limited to assessing water physicochemical parameters. To evaluate the potential of river contaminants to cause biological effects, two standard tests with the Tradescantia plant were used: [...] Read more.

The quality of riverine water is largely influenced by anthropogenic activity; however, worldwide monitoring practices remain largely limited to assessing water physicochemical parameters. To evaluate the potential of river contaminants to cause biological effects, two standard tests with the Tradescantia plant were used: Trad-SHM (stamen hair mutations) and Trad-MN (appearance of micronuclei in sporogenic cells). Water samples were collected from nine localities along the two rivers of the Kura basin: before and after the towns of Spitak, Vanadzor, Tumanyan, Alaverdi, and before Akhtala. The sampling locations were impacted by different anthropogenic sources—domestic and agricultural (Spitak and Vanadzor) and domestic and mining (Tumanyan, Alaverdi, and Akhtala). The biological responses were compared to water quality monitoring data based on physicochemical parameters (ions and metals). Monitoring results indicated “good” or “average” water quality, except for the exceedance of Fe, Mn, Cu, and Pb concentrations in the mining-affected areas. However, Tradescantia showed significantly increased frequency of hair cell mutations and micronucleus formation from urban/agricultural to mining-affected samples. The multivariate PCA analysis distinguished between the samples by associating ammonium and nitrate levels with the samples from urban/agricultural areas and the concentrations of Fe, Mn, Co, and Al with the biological responses in mining-affected samples. However, most likely, toxic substances in the riverine waters acted synergistically. The results indicated that compliance with chemical standards does not necessarily equate to biological safety. They emphasize the need to incorporate biological effects into monitoring programs to improve their contribution to informed decision-making regarding environmental impacts. Full article

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

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16 pages, 628 KB

Open AccessArticle

The Water Footprint of Food Loss and Waste in Saudi Arabia: Magnitude, Composition, and Policy Implications

by Fahad Alzahrani and Rady Tawfik

Water 2026, 18(12), 1387; https://doi.org/10.3390/w18121387 (registering DOI) - 6 Jun 2026

Abstract

Food loss and waste (FLW) represent a significant source of resource inefficiency in water-scarce economies. This study quantifies the water footprint (WF) of FLW in Saudi Arabia using product-level blue, green, and grey WF coefficients from the Water Footprint Network database. Our analysis [...] Read more.

Food loss and waste (FLW) represent a significant source of resource inefficiency in water-scarce economies. This study quantifies the water footprint (WF) of FLW in Saudi Arabia using product-level blue, green, and grey WF coefficients from the Water Footprint Network database. Our analysis covers 3.997 million tons of FLW across 19 commodities grouped into cereals, fruits, vegetables, and meat. Results indicate that FLW is associated with a total blue and green WF of 7.3 billion m³, of which 2.1 billion m³ is blue water directly associated with managed water resources. The blue WF is equivalent to approximately 20% of agricultural water withdrawals and 62% of domestic water demand. Despite constituting only 13% of total FLW by mass, meat products account for 53% of the total water footprint, driven by their exceptionally high water intensity (7474 m³/ton). The consumption stage dominates water losses, contributing 56% of the total blue and green WF. Based on alternative water supply cost benchmarks, the blue WF embedded in FLW corresponds to an indicative production-cost equivalent ranging from 1.03 to 6.5 billion SAR. A 25% reduction in FLW could save over 500 million m³ of blue water annually. These findings demonstrate that FLW reduction represents an important supporting strategy for water resource management and provides a quantitative basis for prioritizing intervention across food groups and supply-chain stages. Full article

(This article belongs to the Special Issue Economic Approaches to Sustainable Water Management: Policy, Innovation, and Global Challenges)

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13 pages, 2399 KB

Open AccessArticle

Development of a Conceptual Hydrogeological Model Based on Geological Mapping and Stable Isotopes: A Case Study of Šmarna Gora, Slovenia

by Mitja Janža, Tamara Marković and Brigita Jamnik

Water 2026, 18(12), 1386; https://doi.org/10.3390/w18121386 (registering DOI) - 6 Jun 2026

Abstract

Small decentralized water supply systems are often sensitive to local pollution and require a clear understanding of recharge conditions and the hydrodynamics within the water resource catchment. This study develops a conceptual hydrogeological model for the Šmarna Gora area based on geological mapping, [...] Read more.

Small decentralized water supply systems are often sensitive to local pollution and require a clear understanding of recharge conditions and the hydrodynamics within the water resource catchment. This study develops a conceptual hydrogeological model for the Šmarna Gora area based on geological mapping, long-term monitoring of chemical parameters, and stable isotope analyses (δ¹⁸O, δ²H) of precipitation and groundwater. The study was initiated in response to rising pollutant concentrations in the drinking water. Estimates of transit time (TT) and mean residence time (MRT) were used to characterize recharge, mixing processes, and differences between the SG and ZAVRH wells, the existing and alternative water supply wells. Isotope data show that the aquifer is predominantly recharged during colder periods and that Mediterranean air masses have become an increasingly important source of precipitation, suggesting a shift in precipitation patterns. The results indicate that SG has longer TT (6–8 months) and MRT (up to 1–2 years). In contrast, ZAVRH shows shorter TT and MRT (4–6 months), and lower pollutant concentrations. The hydrogeological regime in the catchment of the ZAVRH well is characterized by a dynamic, fast-flowing system with limited storage and more intensive dilution of contaminants by infiltrating water, whereas the catchment of the SG well functions as a deeper and more buffered aquifer with prolonged groundwater residence and a more direct hydraulic linkage to the contaminant source. The findings distinguish two hydrogeological regimes and provide a basis for planning water supply solutions and protection measures. Full article

(This article belongs to the Special Issue Application of Isotope Geochemistry in Hydrological Research)

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22 pages, 2892 KB

Open AccessArticle

Decomposition–Migration Cooperative Modeling Approach for Forecasting Runoff in Data-Scarce Watershed Areas

by Yiyang Yang, Xiangyu Sun, Siyu Cai, Xuefei Wu and Mingshuo Zhai

Water 2026, 18(12), 1385; https://doi.org/10.3390/w18121385 (registering DOI) - 6 Jun 2026

Abstract

To address runoff forecasting inaccuracies caused by data gaps in reservoir operations, this paper proposes a collaborative modeling framework integrating deep learning, signal decomposition, uncertainty quantification, and transfer learning. Validated on the Wei River (source basin) and Yongding River (target basin) with similar [...] Read more.

To address runoff forecasting inaccuracies caused by data gaps in reservoir operations, this paper proposes a collaborative modeling framework integrating deep learning, signal decomposition, uncertainty quantification, and transfer learning. Validated on the Wei River (source basin) and Yongding River (target basin) with similar hydrological characteristics, the framework first constructs a Pyraformer-BiLSTM-LSS point forecasting model to enhance characterization of non-stationary runoff sequences. Then, the BLSO-VMD optimization decomposition technique filters and reconstructs forecasting noise, improving model robustness. Subsequently, a probabilistic interval forecasting model is developed via multi-task learning to reliably quantify uncertainty. To tackle data scarcity in the target domain, a “decomposition–reconstruction–transfer” learning mechanism transfers model knowledge from the source domain to the target domain. Results show that the framework achieves excellent performance in the source domain and successfully transfers to the data-scarce target domain, significantly enhancing the accuracy and stability of both point and interval forecasts. By establishing a collaborative modeling framework combining transfer learning and multi-task learning, along with an adaptive signal decomposition method based on BLSO and a multi-scale deep learning model, this study effectively addresses the challenges of accuracy and reliability in runoff forecasting for data-scarce basins. It provides a transferable and scalable technical pathway for runoff simulation and reservoir operation in hydrologically underserved regions, supporting sustainable water resource management and ecological protection. Full article

(This article belongs to the Special Issue Managing Water Under a New Hydrological Normal: Innovations for Resilience in the Face of Climate Change)

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22 pages, 1867 KB

Open AccessArticle

Characterization of Heavy Metal Pollution in Urban Wetland Sediments and Evaluation of Human Health Risk

by Tao Tian, Lingyun Mo, Litang Qin, Junfeng Dai, Dunqiu Wang and Qiutong Lu

Water 2026, 18(11), 1384; https://doi.org/10.3390/w18111384 (registering DOI) - 5 Jun 2026

Abstract

Urban wetlands are transitional sub-ecosystems, which have an important part in connecting the city sources of heavy metal pollution with freshwater ecosystems, and numerous studies have studied the nature of heavy metal pollution, though only several have investigated the consequences of heavy metals [...] Read more.

Urban wetlands are transitional sub-ecosystems, which have an important part in connecting the city sources of heavy metal pollution with freshwater ecosystems, and numerous studies have studied the nature of heavy metal pollution, though only several have investigated the consequences of heavy metals on the health of city dwellers residing in urban wetlands. The Monte Carlo simulation-based method of assessing health risks was employed to calculate the health risks related to the population residing within the study site as one of the measures taken within the framework of the present research to identify the health risks faced by the population when using the sediments of Huixian Wetland Mudong Lake, Guilin City, to evaluate health outcomes. The results showed that Cd and As had the highest geoaccumulation index values and were the most seriously polluted metals. The northeastern and northwestern areas of the lake exhibited a strong level of ecological risk, likely due to their proximity to anthropogenic pollution sources and slower water exchange rates. Non-carcinogenic risk indices (HI) for both adults and children were below 1, with children facing higher risk than adults. For carcinogenic risk, As, Cd, Cr, and Pb posed greater risks to children than adults, with 99.96% of the total carcinogenic risk (TCR) values exceeding the USEPA threshold of 1.00 × 10⁻⁴, indicating an unacceptable risk to children. Sensitivity analysis revealed that the hand–oral intake rate (IRing), As, and Cr were the main factors affecting the human health risk. These findings provide clear guidance for targeted risk control; priority should be given to pollution control of Cd and As, as well as protective measures in high-risk zones, to reduce children’s exposure. The results of this study provide a scientific basis for precise risk control and remediation measures in the region. Full article

(This article belongs to the Special Issue Environmental Behavior and Prevention Strategies of Toxic Chemicals in Farmland Soil Within River Basins)

13 pages, 894 KB

Open AccessArticle

Assessment of Production and Potential Use of Microalgal–Bacterial Aggregates for Contaminant Removal in Agro-Industrial Wastewater

by Sandra Bibiana Vargas, Luisa Fernanda Castro Rubio, Alejandro Cardozo Triviño and José Lugo-Arias

Water 2026, 18(11), 1383; https://doi.org/10.3390/w18111383 (registering DOI) - 5 Jun 2026

Abstract

Agro-industrial wastewater, rich in nutrients and organic matter, represents both an environmental challenge and a valuable resource for biomass valorization. This study assessed the formation, functional performance, and compositional quality of microalgal–bacterial aggregates (MBAs) cultivated exclusively in agro-industrial wastewater under different hydrodynamic conditions. [...] Read more.

Agro-industrial wastewater, rich in nutrients and organic matter, represents both an environmental challenge and a valuable resource for biomass valorization. This study assessed the formation, functional performance, and compositional quality of microalgal–bacterial aggregates (MBAs) cultivated exclusively in agro-industrial wastewater under different hydrodynamic conditions. Open photobioreactors operated at 50 and 100 rpm were used to promote aggregate development, followed by closed static and dynamic batch operations to evaluate contaminant removal efficiency. The systems achieved high pollutant removal rates, including 98% ammonium, 95% phosphate, 65–80% Chemical Oxygen Demand (COD), and complete elimination of E. coli, while moderate agitation enhanced aggregation and settleability without compromising treatment efficiency. Dynamic operation maintained more stable removal performance and biomass retention compared to static systems. The recovered biomass exhibited a favorable nutritional profile (12.5% protein, 4.39% lipids, and 31% dietary fiber) and tested negative for cyanotoxins and pathogens, confirming its microbiological safety. Overall, the findings demonstrate that MBAs cultivated from agro-industrial wastewater can effectively couple bioremediation with the production of safe, nutrient-rich biomass, offering a sustainable and circular solution for wastewater management and bioresource recovery. Full article

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

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13 pages, 1949 KB

Open AccessArticle

Study on the Degradation Efficiency and Mechanisms of Propranolol by an Ultraviolet/Peracetic Acid System

by Xusong Zhao, Shuang Liu, Yungang Sun, Zhaoxiang Wu, Zhenbin Chen and Pengchao Xie

Water 2026, 18(11), 1382; https://doi.org/10.3390/w18111382 (registering DOI) - 5 Jun 2026

Abstract

This study investigates the degradation of propranolol, a widely detected beta-blocker in natural water, using an ultraviolet/peracetic acid (UV/PAA) system. The UV/PAA system significantly enhanced the degradation efficiency compared to UV or PAA alone, achieving a 90.67% removal of propranolol after 15 min [...] Read more.

This study investigates the degradation of propranolol, a widely detected beta-blocker in natural water, using an ultraviolet/peracetic acid (UV/PAA) system. The UV/PAA system significantly enhanced the degradation efficiency compared to UV or PAA alone, achieving a 90.67% removal of propranolol after 15 min under optimal conditions. The degradation process was found to follow first-order kinetics, with a rate constant 36 times higher than that of UV. Reactive species such as hydroxyl radicals (^·OH) and organic radicals (RO^·) were identified through quenching experiments and electron paramagnetic resonance (EPR) spectroscopy. The degradation mechanism was further explored using density functional theory (DFT), revealing the molecular sites most susceptible to radical attacks. This study provides new insights into the application of UV/PAA systems for the removal of beta-blockers and contributes to the optimization of advanced oxidation processes in water treatment. Full article

(This article belongs to the Special Issue Distribution and Toxicity of Emerging Contaminants in Aquatic Environments)

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26 pages, 959 KB

Open AccessArticle

A Graph Attention-Enhanced Hybrid Deep Learning Model for Effluent Total Nitrogen and Total Phosphorus Prediction in Municipal WWTPs

by Jiaxun Cai, Shengli Du and Junfei Qiao

Water 2026, 18(11), 1381; https://doi.org/10.3390/w18111381 (registering DOI) - 5 Jun 2026

Abstract

Accurate effluent-quality prediction is essential for improving nitrogen and phosphorus removal performance and reducing energy consumption in wastewater treatment plants (WWTPs). However, the strong coupling, high noise, and time-lag effects in wastewater treatment processes pose significant challenges to existing prediction models. In this [...] Read more.

Accurate effluent-quality prediction is essential for improving nitrogen and phosphorus removal performance and reducing energy consumption in wastewater treatment plants (WWTPs). However, the strong coupling, high noise, and time-lag effects in wastewater treatment processes pose significant challenges to existing prediction models. In this study, we propose a GAT-CNN-LSTM(GCL) model for the prediction of effluent total nitrogen (TN) and total phosphorus (TP). The GCL model first uses a graph attention network (GAT) to adaptively learn inter-variable relationships, and then applies a convolutional neural network (CNN) and long short-term memory (LSTM) network to extract local and long-term temporal features. The GCL model is trained and evaluated using real operational data from a municipal WWTP in northern China. Based on the best run of each model, GCL improves the

R^{2}

by 13.7% and 6.4% over LSTM and Transformer for TN prediction, while reducing MAPE by 39.4% and 30.4%, respectively. For TP prediction, the corresponding improvements in

R^{2}

are 70.7% and 59.1%, with MAPE reductions of 37.1% and 36.0%. Ablation experiments further demonstrate the complementary contributions of the three modules, showing that graph-based feature fusion enhances subsequent temporal modeling. The temporal variation in neighbor attention weights and one-at-a-time (OAT) sensitivity analysis provide interpretability consistent with A²/O process mechanisms. These findings provide a preliminary validation based on a limited dataset from a single WWTP, and broader applicability under more diverse operating conditions warrants further investigation. Full article

(This article belongs to the Special Issue Water Environment Modeling, Simulation, Informatics, and Big Data Mining)

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28 pages, 50253 KB

Open AccessTechnical Note

Limitations of a Low-Cost Camera System for Monitoring Streamflow in an Extremely Small Forested Headwater Stream

by Tyler Wong and Steve W. Lyon

Water 2026, 18(11), 1380; https://doi.org/10.3390/w18111380 (registering DOI) - 5 Jun 2026

Abstract

Headwater stream dynamics are vital for understanding hydrological and ecological processes in watersheds; however, traditional monitoring methods can be costly and time-consuming. This technical note documents the limitations and challenges encountered when deploying a low-cost camera system for continuous streamflow monitoring in a [...] Read more.

Headwater stream dynamics are vital for understanding hydrological and ecological processes in watersheds; however, traditional monitoring methods can be costly and time-consuming. This technical note documents the limitations and challenges encountered when deploying a low-cost camera system for continuous streamflow monitoring in a forested headwater stream in Ohio, USA. The study stream, with a channel width of less than 1 m and watershed of 0.4 km², is much smaller than previously studied streams. The camera system was constructed using inexpensive and easily accessible electronics, and it enabled application of large-scale particle image velocimetry (LSPIV) to videos collected at a frequency of 15 min. The application of LSPIV to much larger streams is well-established in previous studies; however, its application to extremely small headwater streams is understudied. Preliminary testing in a flume showed that this system was capable of providing accurate discharge measurements. In the field, however, a rating curve calibrated based on the LSPIV-derived flow estimates had an R² value of 0.70, which was weaker than relationships previously reported in the literature. The rating curve overestimated flows at lower channel stages and underestimated them at higher stages when compared to physical discharge measurements. Examination of the videos collected during field deployment revealed that unsteady flow conditions introduced significant variability in the rating curve analysis. Environmental noise from raindrops, illumination conditions, and leaf litter also caused erroneous flow measurements in the LSPIV results. This technical note presents a critical evaluation of the performance of LSPIV-based camera system in extremely small streams, and practitioners and researchers are advised to follow several best practices, offered as lessons learned from our study, to minimize specific sources of error during implementation. Full article

(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)

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42 pages, 7321 KB

Open AccessArticle

A Basin-Scale Framework to Reconstruct Reservoir Sedimentation: Long-Term Sediment Dynamics in the Ebro Basin

by Isabel Granados, Álvaro Sordo-Ward, Alfredo Granados and Luis Garrote

Water 2026, 18(11), 1379; https://doi.org/10.3390/w18111379 (registering DOI) - 5 Jun 2026

Abstract

Reservoir sedimentation alters sediment continuity in regulated river basins, affecting both reservoir storage capacity and downstream river and coastal systems. This study presents a basin-scale framework for reconstructing long-term sediment supply and reservoir sedimentation in the Ebro River Basin (Spain) using publicly available [...] Read more.

Reservoir sedimentation alters sediment continuity in regulated river basins, affecting both reservoir storage capacity and downstream river and coastal systems. This study presents a basin-scale framework for reconstructing long-term sediment supply and reservoir sedimentation in the Ebro River Basin (Spain) using publicly available erosion datasets, empirical sediment delivery ratios and reservoir sedimentation observations. Three sediment supply datasets (GloSEM, RUSLE2015 and WaTEM/SEDEM) were combined with sediment delivery ratios and reservoir trapping functions to reconstruct sediment continuity patterns across the basin. Model calibration was performed using reservoir sedimentation records covering approximately 95% of the basin area. The framework reproduces the main spatial and temporal patterns of sediment accumulation observed in the basin and allows the definition of plausible sediment supply scenarios. Results indicate that current sediment fluxes at the basin outlet are reduced by more than 90% relative to natural conditions due to reservoir trapping. Most reservoirs experience moderate storage losses, although several reservoirs are projected to undergo severe long-term sedimentation. The proposed approach provides a transferable basin-scale sediment assessment methodology for supporting sediment management under data-limited conditions. Full article

(This article belongs to the Section Water Erosion and Sediment Transport)

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27 pages, 43457 KB

Open AccessArticle

Evolution Mechanisms of Spatiotemporal Characteristics of Rainfall-Induced Shallow Landslide Scars: Insights from Beijing Mountainous Areas, China

by Qian Mu, Yue Lu and Gang Mei

Water 2026, 18(11), 1378; https://doi.org/10.3390/w18111378 (registering DOI) - 5 Jun 2026

Abstract

Rainfall-induced shallow landslides strongly affect slope stability and hazard potential in mountainous areas. However, the spatiotemporal evolution of landslide scars under repeated rainfall events remains poorly understood. Using Beijing mountainous areas as a case study, we combined remote sensing, time-series NDVI analysis, and [...] Read more.

Rainfall-induced shallow landslides strongly affect slope stability and hazard potential in mountainous areas. However, the spatiotemporal evolution of landslide scars under repeated rainfall events remains poorly understood. Using Beijing mountainous areas as a case study, we combined remote sensing, time-series NDVI analysis, and a visual foundation model to quantify landslide scar evolution and identify its controlling mechanisms. Two typical patterns have been found. Pattern I follows a “decline–outburst–overcompensation–scarring” sequence: pre-event NDVI declines by 25.1%; during the event, NDVI drops to extreme lows and 21.7% of pixels are masked; after the event, surviving vegetation shows 8.5% overcompensatory growth, but permanent scars form. Pattern II follows a “growth–acceleration–stabilization–masking” sequence: pre-event NDVI increases by 13.6%, reducing landslide risk; rainfall drives NDVI to a peak (+23.4%); post-event NDVI remains high, and landslide areas account for only 0.53%, with damage masked within a new, higher steady state. These findings demonstrate that topographic conditions, vegetation type, and phenological stage jointly control landslide scar characteristics. Steep slopes with shallow-rooted vegetation tend toward Pattern I (explicit damage, persistent scars), while gentle slopes with vegetation in active growing seasons tend toward Pattern II (masked damage, rapid recovery). Pre-event NDVI anomalies provide identifiable precursory information and should be incorporated into early warning and risk assessment systems. Full article

(This article belongs to the Special Issue Hydrological Impacts on Geological Hazards: Mechanisms, Modeling, and Early Warning)

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32 pages, 21007 KB

Open AccessArticle

Warming and Reorganization of Sea Surface Temperature Variability in the Western Black Sea: A Multi-Phase Perspective, 2003–2024

by Nadezhda Valcheva, Nikolay Valchev and Violeta Slabakova

Water 2026, 18(11), 1377; https://doi.org/10.3390/w18111377 (registering DOI) - 5 Jun 2026

Abstract

Understanding sea surface temperature (SST) variability is essential for assessing climate-driven changes in semi-enclosed basins such as the Black Sea. This study investigates SST variability in the western Black Sea over 2003–2024 using MODIS Aqua nighttime SST observations. Annual mean SST time series [...] Read more.

Understanding sea surface temperature (SST) variability is essential for assessing climate-driven changes in semi-enclosed basins such as the Black Sea. This study investigates SST variability in the western Black Sea over 2003–2024 using MODIS Aqua nighttime SST observations. Annual mean SST time series were constructed for coastal, shelf, and open-sea subregions and analysed using linear regression, ARIMA modelling, segmented regression, and spectral methods. SST exhibits a persistent warming signal across all subregions, with an overall increase of ~2.0–2.5 °C and a mean trend of 0.64 ± 0.08 °C decade⁻¹. Warming is spatially heterogeneous, with stronger trends in coastal and shelf regions, indicating a pronounced cross-shelf gradient. Temporal evolution reveals a multi-phase structure, with breakpoints around 2006–2008 and ~2022 marking shifts in warming intensity. Extreme anomalies include basin-wide cooling in 2017 and a sustained warming episode during 2019–2020. Statistical analyses indicate that SST variability is dominated by short-term persistence, while the influence of the North Atlantic Oscillation (NAO) is weak at the annual scale. In addition to the warming trend, SST variability undergoes a systematic reorganization, with variability remaining pronounced and spatially differentiated, particularly in coastal and shelf regions. Near-term projections further suggest that SST evolution may be moderated by internal variability, resulting in limited net change relative to recent peak conditions. Overall, SST variability reflects the combined effects of basin-scale warming, stratification, and regional circulation, indicating a transition toward a more stratified and dynamically variable system with implications for regional climate and marine ecosystems. Full article

(This article belongs to the Section Oceans and Coastal Zones)

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5 pages, 150 KB

Open AccessEditorial

Science and Technology for Water Purification (2nd Edition)

by Kai He and Yuanfeng Qi

Water 2026, 18(11), 1376; https://doi.org/10.3390/w18111376 (registering DOI) - 5 Jun 2026

Abstract

Water scarcity, pollution, and increasingly complex contaminant mixtures continue to challenge conventional treatment processes and management paradigms [...] Full article

(This article belongs to the Special Issue Science and Technology for Water Purification, 2nd Edition)

11 pages, 3948 KB

Open AccessArticle

Nationwide Spatial and Temporal Patterns of Trihalomethanes in Drinking Water

by Nitzan Sagie, Ronnie Levin, Irit Hen, Atar Adout, Luda Groisman, Tamar Berman, Noa Cedar, Natalie De Falco, Shimon Rachmilevitch, Denis Gamzin and Lena Novack

Water 2026, 18(11), 1375; https://doi.org/10.3390/w18111375 (registering DOI) - 5 Jun 2026

Abstract

Disinfection of drinking water prevents waterborne diseases but can lead to the formation of trihalomethanes (THMs), which are linked to an increased risk of cancer. This study examined the association between water source allocation and THM levels in Israel. A retrospective analysis of [...] Read more.

Disinfection of drinking water prevents waterborne diseases but can lead to the formation of trihalomethanes (THMs), which are linked to an increased risk of cancer. This study examined the association between water source allocation and THM levels in Israel. A retrospective analysis of water quality reports, published by the Israeli Ministry of Health, was conducted, including only samples collected from the water distribution system between 2015 and 2024. To assess temporal and geographic variability, monthly and annual averages were calculated. Trends were evaluated using interrupted time series regression. Overall, 16,268 samples were included, with a study-wide mean THM level of 30.41 µg/L, mainly due to Bromoform. Elevated THM levels were observed in northern districts, particularly before 2020, with seasonal peaks in the summer months. After 2020, as surface water utilization increased, THM levels also rose in central Israel, with no discernible seasonal pattern. Southern regions, supplied mainly by desalinated water, showed consistently low levels. This analysis indicates that the water source influences THM formation, as increased surface-water use is associated with higher THM concentrations. Mixing surface and groundwater with desalinated water may reduce exposure in areas with high THM levels, highlighting the need for informed water management policies. Full article

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

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34 pages, 50377 KB

Open AccessArticle

Global Precipitation Regimes and Seasonal Dynamics from IMERG Climatology: Focus on Europe and Italy

by Matteo Gentilucci

Water 2026, 18(11), 1374; https://doi.org/10.3390/w18111374 - 4 Jun 2026

Abstract

The accurate characterization of global precipitation regimes, encompassing not only the mean quantities but also the seasonal structure, concentration, and spatial heterogeneity, is essential for understanding the hydroclimatological dynamics and supporting climate-sensitive applications. This study presents a multi-scale precipitation climatology based on the [...] Read more.

The accurate characterization of global precipitation regimes, encompassing not only the mean quantities but also the seasonal structure, concentration, and spatial heterogeneity, is essential for understanding the hydroclimatological dynamics and supporting climate-sensitive applications. This study presents a multi-scale precipitation climatology based on the IMERG Final Run V06B dataset (2001–2021) integrating satellite-derived monthly precipitation fields, unsupervised K-means clustering, Walsh–Lawler concentration metrics, and pixel-scale regime-dynamics indicators. The analysis identifies eight physically interpretable global precipitation regimes and six Italian sub-regional regimes characterized by distinct seasonal structures and precipitation persistence patterns. The resulting classifications exhibit a strong consistency with major atmospheric circulation domains, including monsoonal, mediterranean, continental, and equatorial precipitation regimes. A Hovmöller diagram highlights the seasonal northward migration of the Intertropical Convergence Zone (ITCZ) from approximately 5° S in January to 10° N in August. The K-means classification identifies eight physically interpretable global regimes, including a perhumid equatorial regime, a South-Asian monsoonal regime, a Southern-Hemisphere Mediterranean type, and a transitional autumn-peaked Mediterranean–Atlantic regime covering most of Italy and the broader Mediterranean basin. At the Italian scale, a dedicated K = 6 clustering reveals six distinct precipitation regimes, characterized by contrasting seasonal structures: the Alpine Convective regime, unique to the Alps and pre-Alpine foothills; the Po Valley Padano regime, the least seasonal regime in Italy; the Apennine Hybrid; the Tyrrhenian Mediterranean; the Adriatic Transition; and the Semi-arid Mediterranean regime, dominant across Sicily, Sardinia, and coastal southern Italy. The Walsh–Lawler Concentration Index increases markedly from north to south (~0.58), indicating a pronounced intensification of the temporal concentration of precipitation toward the Mediterranean climatic extreme. Overall, the study demonstrates the capability of high-resolution satellite climatologies to identify dynamically coherent precipitation-regime structures across multiple spatial scales and provides a quantitative baseline for future applications in hydrology, climate-risk assessment, and climate-change impact analysis. Full article

(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence, 2nd Edition)

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22 pages, 2904 KB

Open AccessArticle

Ecofriendly Biosorbent for the Removal of Hexavalent Chromium from Drinking Water

by Ouro T. Koumai, George A. Sorial, Endalkachew Sahle-Demessie and Mallikarjuna Nadagouda

Water 2026, 18(11), 1373; https://doi.org/10.3390/w18111373 - 4 Jun 2026

Abstract

For the removal of hexavalent chromium [Cr(VI)] from drinking water, a hybrid biosorbent designated chitosan–natural diatomaceous earth (CNDE) was developed and thoroughly characterized. The material couples the ion-exchange and chelating capacity of chitosan—applied at an 85% degree of deacetylation—with the high-surface-area mineral framework [...] Read more.

For the removal of hexavalent chromium [Cr(VI)] from drinking water, a hybrid biosorbent designated chitosan–natural diatomaceous earth (CNDE) was developed and thoroughly characterized. The material couples the ion-exchange and chelating capacity of chitosan—applied at an 85% degree of deacetylation—with the high-surface-area mineral framework of natural diatomaceous earth, onto which the polymer was deposited as a conformal coating. Surface morphology and internal microstructure were examined by scanning and transmission electron microscopy (SEM/TEM), while elemental composition across the hybrid matrix was resolved by energy-dispersive X-ray spectroscopy (EDX). Fourier transform infrared (FTIR) spectroscopy was employed to identify the surface functional groups responsible for chromate binding, and streaming current measurements established the pH of zero charge (pH_pzc), which governs the electrostatic environment at the sorbent–solution interface. Specific surface area was quantified by the Brunauer–Emmett–Teller (BET) method, and the balance of surface acidic and basic sites was determined through titrimetric analysis of total acidity and alkalinity. Thermogravimetric analysis (TGA) was conducted to assess thermal stability. Batch equilibrium isotherm experiments were performed to evaluate Cr(VI) uptake from model drinking water prepared using dilute potassium dichromate solutions adjusted to target pH levels. The effects of solution pH and competing anions (chloride and sulfate) were also investigated. Kinetic studies were conducted to determine the rate of Cr(VI) adsorption, and residual metal concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). Results indicated that CNDE containing 30% chitosan (CNDE30) achieved effective Cr(VI) removal at pH 5. Adsorption was strongly pH-dependent, decreasing as pH increased from 5 to 8. Equilibrium data were well described by both Langmuir and Freundlich isotherm models, while kinetic data followed a pseudo-second-order model. The presence of chloride ions (15 mg/L) reduced adsorption capacity by approximately one-third, whereas sulfate at the same concentration significantly inhibited Cr(VI) removal. Overall, the isotherm results suggest that CNDE30 is a promising material for Cr(VI) removal from drinking water. Its cost-effectiveness, ease of synthesis, and potential for reuse make it particularly attractive for small-scale and decentralized water treatment applications. Full article

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

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