Water

15 pages, 3388 KB

Open AccessArticle

A Leakage Identification Model for Water Distribution Networks Based on Deep Residual and Multi-Scale Feature Extraction

by Yongfeng Zhou, Hele Su, Hanqing Huang, Binghua Xu, Jiasheng Cen and Shipeng Chu

Water 2026, 18(12), 1528; https://doi.org/10.3390/w18121528 (registering DOI) - 22 Jun 2026

Abstract

Leakage detection in water distribution networks is a core component of smart water management. Addressing the limitations of traditional acoustic detection methods, which heavily rely on manual expertise, and the inadequate feature extraction and low recognition rates for minor leaks of existing deep [...] Read more.

Leakage detection in water distribution networks is a core component of smart water management. Addressing the limitations of traditional acoustic detection methods, which heavily rely on manual expertise, and the inadequate feature extraction and low recognition rates for minor leaks of existing deep learning models in complex noise environments, this study proposes a novel hybrid architecture CNN model named Incep-ResNet. The model innovatively integrates multi-scale feature extraction and deep residual learning, incorporating an SE attention mechanism to achieve adaptive recalibration of feature channels. Experimental results demonstrate that the model achieves a leakage identification accuracy of 96.6%, representing improvements of 6.7% and 7% compared to ResNet18 and GoogLeNet, respectively. It exhibits excellent noise resistance and feature extraction capabilities, providing a new technical solution for intelligent leakage detection. Full article

(This article belongs to the Special Issue Smart Design and Management of Water Distribution Systems)

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22 pages, 5863 KB

Open AccessArticle

Modelling the Hydrological and Flooding Behavior of a Caribbean Basin Merging Satellite Rainfall Data and Field Data

by Andrea Gianni Cristoforo Nardini, Giacomo Pellegrini, Luca Mao, Yoiner Ariza, Fayder Herrera, Jairo René Escobar Villanueva and Emirielys Andrea Ospino Navarro

Water 2026, 18(12), 1527; https://doi.org/10.3390/w18121527 (registering DOI) - 21 Jun 2026

Abstract

The Tomarrazón-Camarones Basin (La Guajira, Colombia) is characterized by frequent, widespread flooding and, anthropogenically, by intense instream sediment mining. Mapping flood hazard is hence essential to develop effective flood management plans, and a knowledge of the water regime (duration curves) is also essential [...] Read more.

The Tomarrazón-Camarones Basin (La Guajira, Colombia) is characterized by frequent, widespread flooding and, anthropogenically, by intense instream sediment mining. Mapping flood hazard is hence essential to develop effective flood management plans, and a knowledge of the water regime (duration curves) is also essential to estimate sediment transport and carry out sediment budgets to inform on the impacts and sustainability of the mining activity. However, neither water levels nor discharges are monitored by official gauging stations, and only a few rainfall gauging stations are available in the area, with daily records often affected by data gaps. Therefore, a first challenge is to reconstruct discharge time series by an affordable effort, scaled to the financial-labour resources available in that challenging context. This paper presents an integrated approach that combines satellite-derived rainfall data with ground observations. A semi-distributed hydrological model (HEC-HMS, SCS-CN method) is used to reconstruct the full flow-rate time series once calibrated and validated with data derived from automatic sensors and field measurements. The model is fed with hourly data derived from daily data at ground gauging stations temporally downscaled by adopting the spatially distributed hourly rainfall patterns obtained from satellite records. Before that, observed water levels in three stations equipped with water level sensors were translated into discharge time series using analytical relationships based on field-measured geometric and physical characteristics. Then, these event-based hydrographs were used to calibrate and validate the model. Results show good agreement with observations, with R² = 0.981 and a relative RMSE of 40% for overall hydrograph reproduction, and R² = 0.87 for peak flow estimation, supporting a reasonable confidence in the approach. The calibrated model is then applied to long-term datasets (1973–2024) to retrieve duration curves and return periods of peak discharges. Full article

(This article belongs to the Special Issue Climate Change and Hydrological Processes, 3rd Edition)

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17 pages, 4830 KB

Open AccessArticle

Response of Urban Waterlogging to Short-Duration Precipitation Based on Minute-Resolution Observations in Jinan, China

by Donghan Feng, Can Qiu, Yichen Liu and Guili Feng

Water 2026, 18(12), 1526; https://doi.org/10.3390/w18121526 (registering DOI) - 21 Jun 2026

Abstract

To enhance the meteorological forecasting and early warning service capability for urban waterlogging risks in Jinan, this study aims to investigate the relationship between rainfall and urban waterlogging. Based on minute-scale precipitation observations from 38 automatic weather stations and records from 70 waterlogging [...] Read more.

To enhance the meteorological forecasting and early warning service capability for urban waterlogging risks in Jinan, this study aims to investigate the relationship between rainfall and urban waterlogging. Based on minute-scale precipitation observations from 38 automatic weather stations and records from 70 waterlogging monitoring sites in the urban area of Jinan from 2011 to 2024, this study systematically analyzes the spatiotemporal characteristics of precipitation and waterlogging events and quantifies their response relationship. The main findings are summarized as follows. Heavy precipitation and waterlogging events are strongly temporally coincident, primarily occurring during the main flood season from June to August. Regarding diurnal variation, short-duration heavy rainfall and waterlogging events are concentrated between 14:00 and 20:00. The water depth of most waterlogging events ranges from 0.11 m to 1.04 m, with a median of 0.26 m, and the distribution of waterlogging exhibits a pronounced right-skewed pattern. A moderate positive spatial autocorrelation was observed in waterlogging depth, suggesting that severe urban waterlogging events are more likely to occur in the northern region of Jinan. The precipitation preceding waterlogging events is predominantly short-duration heavy rainfall. A strong temporal relationship exists between peak precipitation and maximum waterlogging depth. In nearly 90% of the waterlogging events, peak precipitation occurs within 2 h before the maximum waterlogging depth, with an average lead time of approximately 55 min. The relationship between antecedent cumulative precipitation and peak waterlogging depth is strongest at the 120 min timescale. About 90% of maximum rainfall over 10 min, 1 h, and 2 h did not exceed the 1-year return period threshold, indicating that the precipitation causing waterlogging events in Jinan is generally non-extreme. Full article

(This article belongs to the Section Urban Water Management)

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17 pages, 9220 KB

Open AccessArticle

Research on River Water Quality Anomaly Early Warning Method Based on LSTM–SOA–DA

by Tianhao Zhao and Dexiu Hu

Water 2026, 18(12), 1525; https://doi.org/10.3390/w18121525 (registering DOI) - 21 Jun 2026

Abstract

River water quality monitoring data are often non-stationary and nonlinear and may contain occasional abnormal values. To support anomaly early warning, this study proposes an LSTM–SOA–DA framework. Water quality monitoring data for six indicators, including pH, DO, COD_Mn, NH₃-N, [...] Read more.

River water quality monitoring data are often non-stationary and nonlinear and may contain occasional abnormal values. To support anomaly early warning, this study proposes an LSTM–SOA–DA framework. Water quality monitoring data for six indicators, including pH, DO, COD_Mn, NH₃-N, TP, and TN, were collected from the Bahekou section in Xi’an at 4 h intervals from 2021 to 2023 and chronologically divided into training and testing sets at an 8:2 ratio. The Seagull Optimization Algorithm (SOA) was used to optimize the L2 regularization coefficient, initial learning rate, and number of hidden units of the Long Short-Term Memory (LSTM) network, establishing an LSTM-SOA forecasting model. Compared with traditional LSTM, BP neural network, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and other optimization-based LSTM models, the proposed model achieved better RMSE and R² performance, indicating improved prediction accuracy. Based on the residuals between observed and predicted values, the DA method was then used to determine indicator-specific anomaly thresholds from the residual distributions. The model identified 193 abnormal points in the test set. After manual rechecking, the Precision, Recall, and F1-score reached 87.6%, 93.9%, and 90.64%, respectively. These results suggest that the LSTM–SOA–DA framework can effectively identify abnormal fluctuations in river water quality data and support timely water environment management. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Hydraulic Engineering, 2nd Edition)

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18 pages, 42492 KB

Open AccessArticle

Metagenomic Insights into Taxonomic Structure, Function of Microbial Community and Antibiotic Resistance Genes in the Whole Baihe Basin

by Yongliang Cui, Yuting Zhang, Yue Wang, Kongping Xie, Huan Xi, Qingsong Chen and Song Lu

Water 2026, 18(12), 1524; https://doi.org/10.3390/w18121524 (registering DOI) - 20 Jun 2026

Abstract

Plateau waters in Northern Sichuan, China, act as critical headwaters of the Yellow River. Microbial communities in water bodies and soil matrices within this region are increasingly pressured by intensive animal rearing; yet few studies have characterized microbial shifts across entire riverine niches. [...] Read more.

Plateau waters in Northern Sichuan, China, act as critical headwaters of the Yellow River. Microbial communities in water bodies and soil matrices within this region are increasingly pressured by intensive animal rearing; yet few studies have characterized microbial shifts across entire riverine niches. In this study, we employed next-generation sequencing based metagenomics to investigate microbial features, community structure and diversity, metabolic potentials, and antibiotic resistance genes (ARGs) in the Baihe River, a tributary in the source region of the Yellow River. Sampling locations covered the main stem and three tributaries of the Baihe River, spanning from its source, through upstream and downstream segments, to the convergence site with the main stem of the Yellow River. Results revealed that Pseudomonadota and Bacteroidota were the most abundant phyla. The relative abundance of most taxa at multiple taxonomic levels exhibited an increasing trend along the river continuum driven by rising total nitrogen (TN) and total phosphorus (TP) concentrations; however, a notable exception occurred at BH1 (the Baihe source), where the abundance of numerous taxa was markedly higher than in downstream samples. We detected abundant ARGs predominantly associated with antibiotic resistance. Furthermore, prevalent viruses affiliated with the phyla Uroviricota and Nucleocytoviricota, together with pathogenic bacteria, were identified as etiological agents of diverse infectious diseases. This study provides novel perspectives for managing aquatic contamination in plateau river ecosystems by linking environmental variables, microbial succession, and resistome distribution. Full article

(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)

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27 pages, 4601 KB

Open AccessArticle

Few-Shot Learning–Based Water Quality Classification Under Limited Data Conditions for Smart Aquaculture Monitoring

by Ashikur Rahman, Gwo Chin Chung, Yin Hoe Ng, Kah Yoong Chan and Soo Fun Tan

Water 2026, 18(12), 1523; https://doi.org/10.3390/w18121523 (registering DOI) - 20 Jun 2026

Abstract

Water quality monitoring is a fundamental element of sustainable aquaculture management, as changes in parameters of physicochemical and biological properties directly affect the health, growth performance, and productivity of the aquaculture systems. Although traditional machine learning (ML) methods have demonstrated effectiveness in water [...] Read more.

Water quality monitoring is a fundamental element of sustainable aquaculture management, as changes in parameters of physicochemical and biological properties directly affect the health, growth performance, and productivity of the aquaculture systems. Although traditional machine learning (ML) methods have demonstrated effectiveness in water quality classification, their performance often depends on large amounts of labeled data, which can be challenging and expensive to collect in real-world aquaculture environments. This study explores a few-shot learning (FSL) framework for data-efficient water quality classification under limited supervision to address this limitation. Several FSL models, including prototypical networks (ProtoNet), Siamese Networks, and Matching Networks were developed and evaluated in a comparative experimental framework against the traditional machine learning classifiers logistic regression, random forest, support vector machine and extreme gradient boosting. Low-data learning scenarios were simulated using a structured episodic evaluation approach. Experimental results demonstrate FSL techniques outperform traditional machine learning methods across all evaluated scenarios. Among the tested methods, ProtoNet achieved the highest performance, attaining an accuracy of 94.46% and an ROC-AUC score of 98.65%, indicating superior discriminative capability and robustness. Siamese Networks also demonstrated competitive performance under highly constrained data conditions. Furthermore, latent-space visualization, confusion matrix analysis, paired t-test statistical analysis, and ablation studies confirmed that episodic meta-learning enables the learning of highly discriminative latent representations with strong generalization capability under limited labeled data conditions. The findings highlight that FSL provides a robust and scalable framework for intelligent water quality classification in aquaculture systems, particularly in scenarios where labeled data are scarce, offering significant potential for sustainable aquaculture monitoring applications. Full article

(This article belongs to the Special Issue Water Quality Management for Sustainable Aquaculture: Integrating Multi-Omics, Digital Technologies, and Climate Resilience)

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19 pages, 13812 KB

Open AccessArticle

Lagged Responses of Vegetation Growth to Hydrometeorological Drivers Across Complex Terrain in Southwest China

by Ting Chen, Guocai Xiong, Zhanxin Gao, Zhijie Song, Jingyi Zhang, Dandan Dong and Hui Chen

Water 2026, 18(12), 1522; https://doi.org/10.3390/w18121522 (registering DOI) - 20 Jun 2026

Abstract

Vegetation is an important component of ecosystems and plays an important role in carbon balance, water balance, and energy conversion. The spatial and temporal changes in the normalized difference vegetation index (NDVI), water resources, and hydrometeorological factors in southwest China between 2003 and [...] Read more.

Vegetation is an important component of ecosystems and plays an important role in carbon balance, water balance, and energy conversion. The spatial and temporal changes in the normalized difference vegetation index (NDVI), water resources, and hydrometeorological factors in southwest China between 2003 and 2020 were investigated using multisource remote sensing data. Correlation analyses were performed to assess the correlation among NDVI, water resource changes, and hydrometeorological factors with different time lags. A stepwise regression model with different lag times was constructed to clarify the effects of four topographic factors and eight climatic factors on NDVI, and the following conclusions were obtained: (1) NDVI increased from 2003 to 2020, and the increase became obvious after 2012. (2) NDVI was considerably affected by alterations in the soil water content caused by natural changes. The correlation of NDVI with evapotranspiration and precipitation was high, followed by NDVI’s correlation with surface temperature. The spatial distribution of the positive correlation between NDVI and evapotranspiration and NDVI and precipitation was relatively consistent, and a positive correlation was observed in most parts of Southwest China. (3) The hydrometeorological factors mainly affected NDVI with a lag of 0–1 month, and the correlation was high in western Sichuan and most of Yunnan. In Yunnan, Available Water Capacity (AWC) affected NDVI with a lag of 0–2 months; the lag was 0–1 month in western Yunnan and 1–2 months in eastern Yunnan. (4) In terms of different vertical heights, the NDVI in the regions with altitudes higher than 3000 m was affected by climate change, especially evapotranspiration and precipitation. (5) Digital Elevation Model (DEM), Latitude (Lat), Evapotranspiration (ET), Precipitation (PRCP), Land Surface Temperature (LST), and NDVI were closely related in the construction of stepwise regression models with different lag times. Full article

(This article belongs to the Section Ecohydrology)

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Graphical abstract

14 pages, 5252 KB

Open AccessArticle

Identification of Testate Amoeba Communities and Their Influencing Factors in Dali Lake

by Biao Sun, Yuying Guo, Chunling Wang and Zhilei Zhen

Water 2026, 18(12), 1521; https://doi.org/10.3390/w18121521 (registering DOI) - 20 Jun 2026

Abstract

The shells of testate amoebae are decay-resistant and well preserved in lake sediments, making them excellent biological indicators of climate change. In this study, the identification method for testate amoebae was initially optimized based on the collection of surface sediments from Dali Lake, [...] Read more.

The shells of testate amoebae are decay-resistant and well preserved in lake sediments, making them excellent biological indicators of climate change. In this study, the identification method for testate amoebae was initially optimized based on the collection of surface sediments from Dali Lake, and statistical analyses were conducted to investigate the community distribution characteristics and key environmental factors driving the testate amoeba species composition. According to the results, the testate amoeba species diversity in the surface sediments of Dali Lake was relatively low. A total of eight species belonging to five genera were identified, and the dominant species were Arcella discoides (35.64% of the total abundance), Phryganella acropodia (24.75%), and Arcella gibbosa (11.39%). All the identified testate amoeba taxa are common in global freshwater sediments, and no new species was discovered in this study. The testate amoeba community composition exhibited strong correlations with the total organic carbon, total nitrogen, dissolved inorganic phosphorus, and total phosphorus and weak correlations with the electrical conductivity and Chlorophyll-a. Full article

(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)

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22 pages, 27018 KB

Open AccessProject Report

Regional Assessment of Groundwater Flow of Natural and Predicted Resources of Fresh and Low-Mineralized Waters in Southern and Western Kazakhstan

by Dinara Adenova, Janay Sagin, Malis Absametov, Yermek Murtazin and Vladimir Smolyar

Water 2026, 18(12), 1520; https://doi.org/10.3390/w18121520 (registering DOI) - 20 Jun 2026

Abstract

Groundwater flow is an integral part of the Earth’s water cycle and plays a key role in assessing groundwater resource potential, characterizing the upper limit of possible groundwater withdrawal over a long period without depletion. The objective of this study is a comprehensive [...] Read more.

Groundwater flow is an integral part of the Earth’s water cycle and plays a key role in assessing groundwater resource potential, characterizing the upper limit of possible groundwater withdrawal over a long period without depletion. The objective of this study is a comprehensive regional assessment of groundwater flow and the natural and predicted resources of fresh and low-mineralized groundwater in Southern and Western Kazakhstan. This assessment is based on an analysis of hydrogeological conditions and water balance, taking into account climate variability and anthropogenic load, to justify sustainable water resources management in arid territories. This article provides a regional assessment and mapping of groundwater flow, taking into account climate and anthropogenic changes in Kazakhstan, to refine the predicted resources of fresh and low-mineralized groundwater. The basin balance calculation results indicate that in arid and semi-arid regions, the decline in groundwater recharge by the 2050s will generally not exceed 10%. The average layer of groundwater flow of renewable groundwater resources in the Kazakhstan part of the Zhaiyk-Caspian water management basin (WMB) is estimated at 33.4 mm/year, and the average modulus of groundwater flow is 1.06 L/s per 1 km². The average layer of groundwater flow of renewable groundwater resources in the Kazakhstan part of the Aral-Surdarya water management basin (WMB) is estimated at 14.8 mm/year, and the average modulus of groundwater flow is 0.47 L/s per 1 km². The average layer of groundwater flow of renewable groundwater resources in the Kazakhstan part of the Shu-Talas water management basin (WMB) is estimated at 26.5 mm/year, and the average modulus of groundwater flow is 0.84 L/s per 1 km². For mountainous and folded regions, the average layer of groundwater flow of renewable groundwater resources in the Balkhash-Alakol water management basin (WMB) system is estimated at 70.7 mm/year, and the average modulus of groundwater flow is 2.24 L/s per 1 km². For intermontane and foothill basins, the average layer of groundwater flow of renewable groundwater resources in the Balkhash-Alakol water management basin (WMB) is estimated at 54.3 mm/year, and the average modulus of groundwater flow is 1.72 L/s per km². Full article

(This article belongs to the Topic Human Impact on Groundwater Environment, 2nd Edition)

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21 pages, 2421 KB

Open AccessArticle

Coastal Water Quality Degradation by Virulent and Antibiotic-Resistant Enteric Pathogens: Seasonal Patterns and Anthropogenic Drivers in the Jaffna Peninsula, Sri Lanka

by Meddage Anjana Kelum Mithurangana Madhura Kumara, Pathmalal Marakkale Manage, Ganepola Arachchilage Pradeep Ruchitha Ganepola, Ponnamperuma Arachchige Kasun Chamara Wijerathna, Weiping Liu and Shanshan Yin

Water 2026, 18(12), 1519; https://doi.org/10.3390/w18121519 (registering DOI) - 20 Jun 2026

Abstract

Tropical coastal waters are increasingly recognized as critical reservoirs for virulent, antibiotic-resistant enteric pathogens, yet seasonal dynamics governing their spatial distribution remain poorly characterized. We hypothesized that hydrological shifts and anthropogenic nutrient enrichment drive the seasonal distribution, virulence profiles, and antimicrobial resistance (AMR) [...] Read more.

Tropical coastal waters are increasingly recognized as critical reservoirs for virulent, antibiotic-resistant enteric pathogens, yet seasonal dynamics governing their spatial distribution remain poorly characterized. We hypothesized that hydrological shifts and anthropogenic nutrient enrichment drive the seasonal distribution, virulence profiles, and antimicrobial resistance (AMR) of Escherichia coli, Salmonella spp., and Shigella spp. in the Jaffna Peninsula, Sri Lanka. Across 25 coastal sites during dry and transitional seasons, we integrated physicochemical water quality assessment, culture-based enumeration, PCR-based virulence gene profiling, Minimum Inhibitory Concentration (MIC) assays, GIS mapping, and statistical analyses. Key water quality parameters, including ammonium, nitrite, and total phosphorus, showed significant seasonal variation (p < 0.05), reflecting distinct hydrological regimes across seasons. A total of 220 E. coli, 200 Salmonella spp., and 100 Shigella spp. isolates were examined for virulence gene profiles and antibiotic tolerance. E. coli was detected at 80–88% of sites, Salmonella spp. at 72–88%, and Shigella spp. at 32–48%. Among E. coli isolates, stx1 was detected at 20–28% of sites and eae at 16% across both seasons. The stn gene was detected in Salmonella spp. at 12–28% of sites seasonally. Virulence profiling confirmed STEC harbouring stx1, stx2, and eae; Salmonella spp. carried stn; and Shigella spp. possessed invasion-associated genes. Trimethoprim–sulfamethoxazole resistance was recorded in 63.2% of E. coli, 33.0% of Salmonella spp., and 31.0% of Shigella spp. isolates at the lowest tested concentration of 4 µg/mL., while ciprofloxacin and piperacillin–tazobactam retained greater efficacy. Correlation analyses revealed significant associations among faecal contamination, nutrient enrichment, and virulence gene prevalence, implicating untreated sewage discharge and eutrophication as likely ecological factors associated with pathogen occurrence. These findings designate the Jaffna coastal zone as a significant reservoir of virulent AMR enteric pathogens, underscoring the urgent need for integrated One Health surveillance and seasonally adaptive coastal water quality management. Full article

(This article belongs to the Special Issue Pollution Mechanisms and Source Apportionment of Typical Pollutants in Aquatic Environments, 2nd Edition)

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14 pages, 1267 KB

Open AccessArticle

Monitoring-Based Assessment of Fluoride Exposure and Health Risks via Drinking Water in the Taruo Lake Region, Tibetan Plateau

by Weimin Xie, Bingyang Wang, Jianghuan Hua, Mingyang Li, Gezi Li, Fan Xia, Tao Zuo and Xiaochen Wang

Water 2026, 18(12), 1518; https://doi.org/10.3390/w18121518 (registering DOI) - 19 Jun 2026

Abstract

Excessive fluoride intake from drinking water remains a public health concern in geogenic high-fluoride regions, yet direct evidence linking environmental fluoride levels to internal exposure in remote high-altitude areas is limited. This study integrated environmental monitoring with human biomonitoring to assess fluoride exposure [...] Read more.

Excessive fluoride intake from drinking water remains a public health concern in geogenic high-fluoride regions, yet direct evidence linking environmental fluoride levels to internal exposure in remote high-altitude areas is limited. This study integrated environmental monitoring with human biomonitoring to assess fluoride exposure and health risks in the Taruo Lake region of the Tibetan Plateau. Surface water (n = 45 for Taruo Lake; n = 8 for its tributaries) and groundwater samples (n = 4) were collected and analyzed for fluoride concentrations, and blood ionic fluoride (BIF) levels were measured in 122 local residents (47 adults, 75 children). The results showed that fluoride concentrations in most surface water tributaries of Taruo Lake and groundwater sources were below China’s drinking water standard, whereas those in Taruo Lake exceeded this limit (routine monitoring mean 2.54 mg/L; multi-site mean 2.79 mg/L). BIF levels were significantly higher in adults (0.126 ± 0.041 mg/L) than in children (0.075 ± 0.032 mg/L) and showed a positive correlation with age (r = 0.533, p < 0.001). Notably, 23.4% of adults and 1.3% of children exceeded 0.15 mg/L, an empirical threshold typical for healthy populations in non-endemic areas. Based on the hazard quotient (HQ) model recommended by the US EPA, most drinking water sources posed acceptable non-carcinogenic risks (HQ < 1). In contrast, Taruo Lake water presented an elevated risk (HQ > 1) in 2024 primarily due to the regional geological background, and although not used for daily drinking, this finding offers an indicative reference for local water management and risk prevention. This preliminary monitoring and biomonitoring assessment provides baseline data for future studies and underscores the necessity of continuous surveillance and evaluation of total dietary fluoride intake to protect the health of this vulnerable high-altitude population. Full article

(This article belongs to the Special Issue Elemental and Isotopic Geochemistry Tracing of Aquatic Pollutants: Source Apportionment and Ecological Health Risk)

13 pages, 1431 KB

Open AccessArticle

A Case Study of the First Known Relocation of an Imperiled Burrowing Crayfish Species, Cambarus pauleyi—Meadow River Mudbug: Results and Implications

by David A. Foltz II and Zachary J. Loughman

Water 2026, 18(12), 1517; https://doi.org/10.3390/w18121517 (registering DOI) - 19 Jun 2026

Abstract

Burrowing crayfish are among the most important keystone species in North American ecosystems, yet they remain poorly understood. The Meadow River Mudbug (Cambarus pauleyi), native to West Virginia, was only recently described and is known from a very limited range in [...] Read more.

Burrowing crayfish are among the most important keystone species in North American ecosystems, yet they remain poorly understood. The Meadow River Mudbug (Cambarus pauleyi), native to West Virginia, was only recently described and is known from a very limited range in the Central Appalachians. During planning for an interstate pipeline, two large populations of C. pauleyi were found in the proposed right-of-way. As part of environmental compliance, salvage, relocation, and monitoring for the species were conducted from 2018 to 2024. All C. pauleyi were moved to the Meadow River Wildlife Management Area, where artificial starter burrows were created, and exclusion baskets were placed over them to prevent predation, the process of which is described herein. Monitoring showed a two-month survival rate of 74.0% to 85.5%. These results are promising for the future restoration of burrowing crayfish and other species that rely on crayfish burrows for habitat. Full article

(This article belongs to the Special Issue Ecology and Management of Crayfish)

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19 pages, 1663 KB

Open AccessReview

Challenges and Development Trends of Crop–Hydro Digital Twin Technology

by Shihan Wang, Jiaqing He, Aidi Huo, Yapeng Li, Yibing Cao, Salah Elsayed and Jahangir Muhammad Ilyas

Water 2026, 18(12), 1516; https://doi.org/10.3390/w18121516 (registering DOI) - 19 Jun 2026

Abstract

Under the dual constraints of global food security and ecological protection, conventional agriculture is hampered by low resource efficiency and sluggish environmental response. Crop digital twin technology establishes a dynamic virtual reality system that integrates crops, environment, and water to enable real-time interaction [...] Read more.

Under the dual constraints of global food security and ecological protection, conventional agriculture is hampered by low resource efficiency and sluggish environmental response. Crop digital twin technology establishes a dynamic virtual reality system that integrates crops, environment, and water to enable real-time interaction and optimization. Based on the existing literature, this paper reviews the concept, architecture, and core modules of this technology and summarizes its applications in precision irrigation and crop monitoring. There are three major bottlenecks that persist, including limited high-frequency multi-source sensing and spatiotemporal fusion, insufficient parameter calibration and dynamic updating, and weak cross-scale integration from plant to watershed. Water is increasingly recognized as the key constraint and control variable and acting as both the central physiological driver of crop growth and the mass-flow link that connects the soil–plant–atmosphere continuum. The spatiotemporal dynamics of crop water deficit, compensatory root water uptake, evapotranspiration feedback, and the hydraulic behavior of irrigation-district canal systems constitute the core hydrological processes that must be simulated within the digital twin. Synchronizing crop water demand, soil moisture dynamics, atmospheric evapotranspiration, and irrigation scheduling within a unified spatiotemporal framework establishes a complete sensing, diagnosis, prediction and regulation technical chain. This chain offers a core pathway for alleviating agricultural water scarcity, improving irrigation efficiency, and ensuring food security. Full article

(This article belongs to the Special Issue Application of Water-Saving Irrigation in Agricultural Development)

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24 pages, 1902 KB

Open AccessArticle

An Empirical Conditional Model for Estimating Wave Characteristics from Wind Speed, Fetch, and Depth: Application to the Red Sea

by Muhnad Almasoudi, Soroosh Sharifi and Hassan Hemida

Water 2026, 18(12), 1515; https://doi.org/10.3390/w18121515 (registering DOI) - 19 Jun 2026

Abstract

An empirical model is developed to predict significant wave height and significant wave period using only wind speed at 10 m height, fetch, and water depth. The model distinguishes between fetch-limited and duration-limited sea states within a conditional empirical framework that incorporates modified [...] Read more.

An empirical model is developed to predict significant wave height and significant wave period using only wind speed at 10 m height, fetch, and water depth. The model distinguishes between fetch-limited and duration-limited sea states within a conditional empirical framework that incorporates modified empirical exponents and corrections into classical wave formulations. Validation was performed using wind and wave data from the Global Forecast System at 26 coastal and offshore stations distributed across eleven different pilot seas and oceans worldwide, encompassing a broad spectrum of marine environments and climatic conditions. The proposed model was benchmarked against established empirical approaches. Results indicate a mean prediction error of 6.6% for the significant wave height and 9.6% for the significant wave period, substantially outperforming conventional formulations whose errors exceed 50% under comparable conditions. Unlike existing empirical models that are restricted to specific regions or sea-state conditions, the proposed model demonstrated strong predictive performance across diverse seas, oceans, and climatic conditions, enabling more reliable wave predictions in data-scarce and dynamically complex marine environments. The developed model was further applied to the Red Sea, where it successfully reproduced the spatial variability of significant wave height and wave period. From the results, it has been found that the developed model provides a practical and transferable tool for wave forecasting, coastal engineering, and offshore renewable energy applications. Full article

(This article belongs to the Special Issue Recent Advances in Hydraulic Machinery and Its Application in Marine Engineering)

20 pages, 1890 KB

Open AccessSystematic Review

Urban Water Insecurity and Public Health in Kathmandu Valley, Nepal: A Systematic Review of Contamination Sources, Health Risks, and Governance Gaps

by Ganga B. Basnet and Samendra Sherchan

Water 2026, 18(12), 1514; https://doi.org/10.3390/w18121514 (registering DOI) - 19 Jun 2026

Abstract

Urban water insecurity is an increasingly critical challenge in rapidly urbanizing regions of the Global South, driven by population growth, environmental degradation, infrastructure limitations, and institutional constraints. Kathmandu Valley, Nepal, exemplifies these interconnected pressures. This study presents a systematic review of 45 peer-reviewed [...] Read more.

Urban water insecurity is an increasingly critical challenge in rapidly urbanizing regions of the Global South, driven by population growth, environmental degradation, infrastructure limitations, and institutional constraints. Kathmandu Valley, Nepal, exemplifies these interconnected pressures. This study presents a systematic review of 45 peer-reviewed and selected grey literature sources published between 2000 and 2025, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were included if they examined drinking water contamination, public health risks, household coping practices, wastewater-related exposure, or governance dynamics in Kathmandu Valley, Nepal. Findings were synthesized using a narrative thematic approach. The review identifies widespread contamination across municipal supply systems, groundwater, tanker water, traditional water sources, and household-stored water. Microbial contamination, particularly total coliforms, fecal coliforms, and Escherichia coli, emerged as the most consistently reported and immediate public health concern. Chemical and physicochemical contaminants, including ammonia, iron, arsenic, nitrate, and turbidity, were also widely reported, especially in shallow and deep groundwater systems. Seasonal dynamics further influenced exposure risks, with increased microbial contamination during monsoon periods and greater dependence on alternative and less regulated water sources during dry seasons. The findings further indicate that unsafe water exposure is associated with a substantial burden of waterborne diseases and emerging risks such as antimicrobial resistance. Although household water treatment practices reduced contamination in some cases, risks often persisted due to recontamination during storage and handling. These burdens disproportionately affected marginalized and peri-urban populations with limited access to safe and reliable water infrastructure. The review also highlights persistent governance challenges, including institutional fragmentation, weak regulatory enforcement, inadequate infrastructure investment, and growing dependence on informal water supply systems. Together, these conditions contribute to a hybrid urban water system in which formal and informal sources coexist without consistent quality control. Overall, the evidence demonstrates that water insecurity in Kathmandu Valley is a systemic condition shaped by the interaction of environmental contamination, unequal exposure, household coping limitations, and fragmented governance. By integrating environmental, public health, and governance evidence, this review advances understanding of urban water insecurity in rapidly urbanizing contexts and highlights the need for integrated, equity-oriented, and governance-informed interventions. These findings have broader relevance for cities across the Global South experiencing similar environmental and infrastructural pressures. Full article

(This article belongs to the Special Issue Water Quality, Pathogens, and Public Health Risks)

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19 pages, 3586 KB

Open AccessArticle

Chemical-Free Regeneration of Scaled Capacitive Deionization Electrodes Using Alternating Polarization

by Yazeed Algurainy

Water 2026, 18(12), 1513; https://doi.org/10.3390/w18121513 (registering DOI) - 19 Jun 2026

Abstract

Mineral scaling on carbon electrodes remains a critical limitation to the long-term performance of capacitive deionization (CDI) systems treating hard and alkaline waters. In this study, alternating polarization (AP) is investigated as an in situ electrochemical regeneration strategy to reverse cathodic scaling in [...] Read more.

Mineral scaling on carbon electrodes remains a critical limitation to the long-term performance of capacitive deionization (CDI) systems treating hard and alkaline waters. In this study, alternating polarization (AP) is investigated as an in situ electrochemical regeneration strategy to reverse cathodic scaling in flow-through CDI treating a feed containing 5 mM NaCl, 5 mM NaHCO₃, and 2.5 mM CaCl₂ under three modes: conventional cycling (control), delayed AP introduced after fouling developed, and immediate AP implemented from the first cycle. Under conventional operation, cathodic scaling reduced the salt adsorption capacity (SAC) to 5.9 ± 0.2 mg/g, increased cathode mass from 0.208 ± 0.004 g (pristine) to 0.353 ± 0.054 g, and decreased specific capacitance to 28 ± 2 F/g, accompanied by extensive pore blockage and carbonate deposition observed by SEM and BET measurements. Application of delayed AP restored electrode functionality, increasing SAC to 8.9 ± 0.6 mg/g and specific capacitance to 56 ± 2 F/g while reducing the cathode mass to 0.212 ± 0.007 g and removing surface precipitates. The immediate AP operation reduced the extent of scale formation from cycle 1, maintaining SAC at 8.4 ± 0.2 mg/g throughout operation, with stable physical and electrochemical properties. These improvements are attributed to periodic polarity reversal, which induces alternating alkaline and acidic microenvironments at the electrode surface and promotes the electrochemical dissolution of carbonate phases during anodic polarization. Overall, this work establishes AP as a simple, chemical-free operational strategy for both preventing and reversing cathodic mineral scaling, thereby enabling sustained CDI performance and mitigating capacity loss over the tested operational periods in complex water matrices. Full article

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

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16 pages, 13758 KB

Open AccessArticle

Bridging the Laboratory–Field Divide: Challenges and Opportunities in the ALPSTREAM Eco-Hydraulic Experimental Outdoor Mesocosm

by Tiziano Bo, Anna Marino, Margherita Abbà, Francesca Bona, Elisa Falasco, Marta Moriondo and Stefano Fenoglio

Water 2026, 18(12), 1512; https://doi.org/10.3390/w18121512 - 19 Jun 2026

Abstract

The use of mesocosms in stream ecology has long attracted the attention of researchers due to the clear advantages these systems offer for manipulative experiments. Despite some limitations, they provide an effective way to create semi-natural conditions in which selected parameters can be [...] Read more.

The use of mesocosms in stream ecology has long attracted the attention of researchers due to the clear advantages these systems offer for manipulative experiments. Despite some limitations, they provide an effective way to create semi-natural conditions in which selected parameters can be artificially controlled. This study presents the ALPSTREAM eco-hydraulic laboratory, a mesocosm system designed to mimic the conditions of an alpine stream (Ostana, NW Italy). The structure of this system is unique and consists of six 25-m-long flumes, fed directly by the Po River and equipped to regulate key hydraulic parameters. The paper describes the structure of this system and presents two case studies to illustrate some potential applications. The first aimed to analyze the impact of different aquatic insects (scrapers) on periphyton dynamics. The second tested the feasibility of the flumes for the ex situ breeding of a threatened fish species, the European bullhead (Cottus gobio L.). The purpose of this paper is to raise awareness of this facility and make it available to researchers interested in eco-hydraulic studies in mountain environments. Full article

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

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16 pages, 1671 KB

Open AccessArticle

Treatment of Novel Pigment Wastewater Using an AAO System: Tolerance, Start-Up and Operation, Toxicity Analysis, and Mitigation Strategies

by Tongzhou Wang, Peipei Li, Yong Li, Lei Chen and Yanqiu Wang

Water 2026, 18(12), 1511; https://doi.org/10.3390/w18121511 - 19 Jun 2026

Abstract

The biological treatment risk associated with wastewater containing the novel pigment intermediate N,N′-(1,4-phenylene)bis(acetoacetamide) has not been previously characterized. This study systematically evaluated the tolerance and performance of a laboratory-scale anaerobic–anoxic–oxic (AAO) system subjected to progressively increasing loadings of high-concentration (COD > 10,000 mg·L [...] Read more.

The biological treatment risk associated with wastewater containing the novel pigment intermediate N,N′-(1,4-phenylene)bis(acetoacetamide) has not been previously characterized. This study systematically evaluated the tolerance and performance of a laboratory-scale anaerobic–anoxic–oxic (AAO) system subjected to progressively increasing loadings of high-concentration (COD > 10,000 mg·L⁻¹) wastewater. During a 39-day trial, the influent proportion was incrementally increased from 0.57% to 52.14% without system collapse. Complete microbial adaptation required approximately seven days. The anaerobic unit exhibited the highest sensitivity to shock loads, followed by the oxic unit, while the anoxic unit remained stable. GC-MS analysis confirmed the degradation of complex organic intermediates throughout the treatment stages, and TEST-based predictions indicated that the effluent exhibited lower predicted toxicity than the influent. Notably, cessation of mother liquor addition resulted in system self-recovery, further demonstrating robust shock resistance. This study provides the first experimental evidence of (i) unit-specific shock sensitivity (anaerobic > oxic > anoxic), (ii) a quantified adaptation period of approximately seven days, (iii) an operational threshold of 52.14% mother liquor without causing system collapse, and (iv) self-recovery following load cessation in an AAO system treating wastewater containing N,N′-(1,4-phenylene)bis(acetoacetamide). These findings extend previous AAO toxicity studies on industrial wastewater and present a practical, cost-effective mitigation strategy for full-scale applications. Full article

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

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17 pages, 2386 KB

Open AccessArticle

Spatio-Temporal Comparison of Springs in the Southern Swiss Alps—Implications for Spring Conservation

by Tania Pedimina, Simone Bontà and Stefanie von Fumetti

Water 2026, 18(12), 1510; https://doi.org/10.3390/w18121510 (registering DOI) - 19 Jun 2026

Abstract

Springs are environmentally stable habitats that are refugia for specialized species. Springs at Monte Generoso, Monte Bar, and Monte Tamaro in the southern Swiss Alps were investigated to understand how they are affected by human activities and environmental changes. We conducted (a) a [...] Read more.

Springs are environmentally stable habitats that are refugia for specialized species. Springs at Monte Generoso, Monte Bar, and Monte Tamaro in the southern Swiss Alps were investigated to understand how they are affected by human activities and environmental changes. We conducted (a) a temporal comparison of five springs at Monte Generoso, which were first sampled in 2011 and re-sampled in 2023 and (b) a spatial comparison of 19 springs of the three mountains. Physical and chemical parameters were measured, ecomorphology and anthropogenic impacts were evaluated, and macroinvertebrates were sampled. Springs at Monte Generoso changed along a temperature gradient. EPT-taxa shifted towards euryoecious taxa owing to environmental changes. The spatial comparison showed differences between the mountain summits driven by electrical conductivity and water temperature. These differences were mainly evident for Crenobia alpina and in the occurrence of Niphargus cf. thuringius in Bar and Tamaro as well as Drusus alpinus in Tamaro. Springs at Monte Generoso were the least diverse and exhibited the highest water temperature, possibly owing to the higher utilization pressure. Spring specialists were present even in heavily modified springs. This spatio-temporal analysis provided insights into the pressure on springs in the southern Swiss Alps, emphasizing the importance of a site-specific protection of these precious habitats. Full article

(This article belongs to the Special Issue Biodiversity of Freshwater Ecosystems: Monitoring and Conservation, 2nd Edition)

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