Water

20 pages, 2682 KB

Open AccessArticle

Monolayer or Multilayer Snow Model: Implications for the HYDROTEL Hydrological Model for Flow Modeling

by Julien Augas, Alain N. Rousseau and Etienne Foulon

Water 2026, 18(7), 884; https://doi.org/10.3390/w18070884 - 7 Apr 2026

Viewed by 541

The snow module of the HYDROTEL (version 2.8.x-078-00-4.1.15.5551) hydrological model was modified to incorporate a multilayer structure composed of ice and air layers within the snowpack, as well as to account for the impact of freezing rain on snow cover. This study examines [...] Read more.

The snow module of the HYDROTEL (version 2.8.x-078-00-4.1.15.5551) hydrological model was modified to incorporate a multilayer structure composed of ice and air layers within the snowpack, as well as to account for the impact of freezing rain on snow cover. This study examines whether this enhanced physical representation of snow processes improves the accuracy of streamflow simulations. The analysis was conducted across ten watersheds in Quebec, Canada. The multilayer snow model consistently improved low-flow simulations during both calibration and validation periods and enhanced the representation of the falling limb during the calibration period. However, the monolayer snow model performs slightly better during the rising limb of the freshet season for the calibration phase. In addition, the multilayer configuration reduced the bias of the cumulative freshet volumes and annual maximum freshet discharge. Overall, the multilayer snow model achieved comparable performance to the monolayer model for high-flow simulations while outperforming it for low-flow conditions, leading to a more accurate representation of freshet volumes and falling limb dynamics. Full article

(This article belongs to the Section Hydrology)

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21 pages, 5619 KB

Open AccessArticle

Influence of Riparian Vegetation on River Morphodynamics: A Numerical Modeling Framework

by Ricardo Gutiérrez, Alejandro Mendoza and Moisés Berezowsky

Water 2026, 18(7), 883; https://doi.org/10.3390/w18070883 - 7 Apr 2026

Viewed by 867

Abstract

Riparian vegetation plays an important role in the morphological evolution of rivers; here, an alternative numerical methodology for modeling river morphodynamics influenced by vegetation is presented. The approach integrates a vegetation growth and flow-resistance submodule coupled with the TELEMAC–MASCARET system. Vegetation is represented [...] Read more.

Riparian vegetation plays an important role in the morphological evolution of rivers; here, an alternative numerical methodology for modeling river morphodynamics influenced by vegetation is presented. The approach integrates a vegetation growth and flow-resistance submodule coupled with the TELEMAC–MASCARET system. Vegetation is represented at the patch scale, and its hydraulic effect is incorporated through an additional drag force in the momentum equation, while stem obstruction is accounted for using the porosity formulation in TELEMAC-2D. Vegetation dynamics consider water depth variability, interspecific competition, and nutrient availability. The model is applied to a braided river reach in southeastern Mexico. The results indicate that riparian vegetation promotes more organized flow paths, enhances bar development, and plays a significant role in modulating bar stability. These findings highlight the importance of explicitly representing flow–sediment–vegetation feedback in river hydro-morphological modeling. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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34 pages, 8819 KB

Open AccessArticle

Mitigating Overfitting and Physical Inconsistency in Flood Susceptibility Mapping: A Physics-Constrained Evolutionary Machine Learning Framework for Ungauged Alpine Basins

by Chuanjie Yan, Lingling Wu, Peng Huang, Jiajia Yue, Haowen Li, Chun Zhou, Congxiang Fan, Yinan Guo and Li Zhou

Water 2026, 18(7), 882; https://doi.org/10.3390/w18070882 - 7 Apr 2026

Viewed by 758

Abstract

Flood susceptibility mapping in high-altitude ungauged basins faces a structural dichotomy: physically based models often suffer from systematic biases due to uncertain satellite precipitation, whereas data-driven models are prone to overfitting and lack physical consistency in data-scarce regions. To resolve this, this study [...] Read more.

Flood susceptibility mapping in high-altitude ungauged basins faces a structural dichotomy: physically based models often suffer from systematic biases due to uncertain satellite precipitation, whereas data-driven models are prone to overfitting and lack physical consistency in data-scarce regions. To resolve this, this study proposes a Physically constrained Particle Swarm Optimization–Random Forest (P-PDRF) framework, validated in the Lhasa River Basin. The core innovation lies in coupling a hydrological model with statistical learning by utilizing the maximum daily runoff depth as a “Relative Hydraulic Intensity Index.” This approach leverages the topological correctness of physical simulations to circumvent absolute forcing errors. Furthermore, a Physiographically Constrained Negative Sampling (PCNS) strategy and a PSO-optimized “Shallow Tree” configuration are introduced to enforce structural regularization against stochastic noise. Empirical results demonstrate that P-PDRF achieves superior generalization (AUC = 0.942), significantly outperforming standard Random Forest, Support Vector Machine, and Analytic Hierarchy Process models. Ablation studies confirm that the dynamic index outweighs the static Topographic Wetness Index in feature importance, effectively correcting topographic artifacts where static models misclassify arid depressions as high-risk zones. This study offers a scalable Physics-Informed Machine Learning solution for the global “Prediction in Ungauged Basins” initiative. Full article

(This article belongs to the Special Issue Urban Flood Risk Assessment and Management)

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19 pages, 2241 KB

Open AccessArticle

Multi-Objective Optimization and Adaptive Control for Frequency Regulation of Hydropower Units Under Variable Operating Conditions

by Dong Liu, Chen Li, Yanbo Xue, Xiaoqiang Tan and Xiaoyuan Zhang

Water 2026, 18(7), 881; https://doi.org/10.3390/w18070881 - 7 Apr 2026

Viewed by 672

Abstract

As a key part of the new power system, hydropower units (HPUs) are capable of maintaining the stability of system frequency through the flexible conversion of operating conditions. Fixed control parameters are generally adopted by existing HPU governors, which cannot meet the requirements [...] Read more.

As a key part of the new power system, hydropower units (HPUs) are capable of maintaining the stability of system frequency through the flexible conversion of operating conditions. Fixed control parameters are generally adopted by existing HPU governors, which cannot meet the requirements of variable operating conditions, and the flexibility of hydropower regulation is thus restricted. Therefore, an adaptive optimal control strategy for units in frequency regulation mode is proposed for a large hydropower station in this paper. Firstly, a segmented linearized mathematical model for HPU frequency regulation is established. On this basis, objective functions under frequency and load perturbation are constructed. Control parameters under each operating condition are optimized via an improved multi-objective particle swarm optimization based on the objective functions. The nonlinear relationship between optimal control parameters and operating conditions is fitted to obtain the adaptive adjustment strategy. Comparative verification with the fixed-parameter strategy shows that the proposed strategy improves comprehensive performance (frequency adjustment and recovery time) under 48 operating conditions. The improvement rate exceeds 50% under large opening conditions, with an overall average of 51.01%, fully proving its superiority. Full article

(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station, 2nd Edition)

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23 pages, 8119 KB

Open AccessArticle

A Detailed Simulation of Overtopping-Induced Breach Processes and Breach Evolution in Non-Cohesive Earth Dams

by Shengyao Mei, Yu Li, Jianjun Xu, Qiming Zhong, Yibo Shan and Lingchun Chen

Water 2026, 18(7), 880; https://doi.org/10.3390/w18070880 - 7 Apr 2026

Viewed by 676

Abstract

Non-cohesive earth dams are widely distributed in natural and semi-engineering scenarios, and overtopping-induced breaches are their most catastrophic failure mode. Accurate prediction of the overtopping failure process and breach evolution is critical for risk assessment, emergency management, and dam design optimization. In this [...] Read more.

Non-cohesive earth dams are widely distributed in natural and semi-engineering scenarios, and overtopping-induced breaches are their most catastrophic failure mode. Accurate prediction of the overtopping failure process and breach evolution is critical for risk assessment, emergency management, and dam design optimization. In this study, an improved 3D numerical method is developed to simulate the coupled hydrodynamic–erosion–breach evolution processes of non-cohesive earth dams. The model based on the finite volume method integrates three core modules: a hydrodynamic module based on the Reynolds-Averaged Navier–Stokes equations with the Volume of Fluid method for free surface tracking, a dam material erosion module considering particle entrainment and transport mechanisms of non-cohesive soils, and a breach development module coupling erosion and gravitational collapse. To validate the model, two levels of verification are conducted: first, a classic benchmark dam break case is employed to confirm the feasibility of the hydrodynamic and breach evolution algorithms; second, published flume experimental data of non-cohesive earth dam overtopping failures are adopted to evaluate the model accuracy in predicting breach hydrographs and spatiotemporal evolution of breach geometry. The results demonstrate that the proposed model accurately reproduces the key characteristics of overtopping failure with high fidelity. The predicted breach flow rates and flow depths are in excellent agreement with experimental observations, with relative errors less than 5% for both peak discharge and time to peak. Consequently, this study provides a reliable numerical tool for detailed simulation of non-cohesive earth dam breaches and offers scientific support for emergency management. Full article

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

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20 pages, 2158 KB

Open AccessArticle

Determination of Octanol–Water Partition Coefficients for Corticosteroids and Its Application in a Screening-Level In Silico Environmental Risk Prioritization for Aquaculture Systems

by Guofeng Cheng, Shimin Wu, Shikun Liu, Yu Liu, Zhaojun Gu, Jiahua Zhang and Yanan Liu

Water 2026, 18(7), 879; https://doi.org/10.3390/w18070879 - 7 Apr 2026

Viewed by 877

Abstract

The presence of corticosteroids (CSs) in aquaculture wastewater poses risks to ecological health and food safety, yet data on their lipophilicity (logK_ow) remain scarce. This study determined the logK_ow of CSs to perform a screening-level in silico environmental [...] Read more.

The presence of corticosteroids (CSs) in aquaculture wastewater poses risks to ecological health and food safety, yet data on their lipophilicity (logK_ow) remain scarce. This study determined the logK_ow of CSs to perform a screening-level in silico environmental risk prioritization. We evaluated nine computational programs (ACD/LogP, ALOGPS 2.1, CLOGP, JChem, KOWWIN, MiLogP, MolLogP, MOSES.logP, and XLOGP3) against experimental data for 50 steroid hormones. Results showed that XLOGP3 demonstrated the highest accuracy (Adjusted R² = 0.9872; SSE = 0.1004), followed by MiLogP, ACD/LogP, and KOWWIN. Structure–lipophilicity analysis revealed that esterification and acetonide formation significantly increase logK_ow, while hydroxylation decreases it. Using the validated XLOGP3, we predicted logK_ow for 32 synthetic CSs and estimated their bioconcentration factor (BCF) and soil organic carbon–water partition coefficient (K_oc). Because experimental logK_ow data for these 32 synthetic compounds are largely unavailable, these estimates should be interpreted as preliminary prioritization indicators rather than experimentally confirmed endpoints. Heavily modified CSs like Ciclesonide and Fluocortolone 21-hexanoate exhibited high logK_ow (>4.5), log BCF (>3.0), and logK_oc (>4.0), indicating their high potential for bioaccumulation and persistent sediment adsorption. This study provides a prioritized list of high-risk CSs, serving as a preliminary tool to identify potential compounds of concern in aquaculture environments. Full article

(This article belongs to the Special Issue Aquaculture Tailwater Treatment: Theoretical Foundations and Applied Techniques)

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13 pages, 3293 KB

Open AccessArticle

From Wastewater Reuse to Natural Wetland Degradation Under Regulatory Mirage

by Amir Gholipour

Water 2026, 18(7), 878; https://doi.org/10.3390/w18070878 - 6 Apr 2026

Cited by 2 | Viewed by 574

Abstract

Water scarcity compels wastewater reuse, but lax discharge standards generate a regulatory mirage, misleading the public about safety. Here, “regulatory mirage” refers to situations where formal compliance with discharge standards creates a false perception of safety while ecological risks and degradation persist. Despite [...] Read more.

Water scarcity compels wastewater reuse, but lax discharge standards generate a regulatory mirage, misleading the public about safety. Here, “regulatory mirage” refers to situations where formal compliance with discharge standards creates a false perception of safety while ecological risks and degradation persist. Despite formal compliance, treated effluent severely harms Iran’s effluent-dependent Kashaf River, driving eutrophication, salinization, and the downstream transport of unregulated contaminants of emerging concern, including fluorinated substances (PFAS) and pharmaceuticals. These pressures extend beyond the river channel to adjacent natural wetlands, which act as de facto nature-based treatment systems yet are progressively transformed into sacrificial sinks for excess nutrients, salts, heavy metals, and micropollutants. By benchmarking the Iranian Wastewater Discharge Standards (IWDS) against international guidelines (WHO, EU, FAO), this study quantifies a “Permissibility Gap” frequently greater than 10 for key parameters such as BOD₅, nutrients, and trace metals, revealing how concentration-based limits ignore cumulative mass load and mixture toxicity at the basin scale. The Kashaf River case demonstrates that current end-of-pipe regulation undermines both natural wetlands and planned nature-based solutions, including constructed wetlands, in arid regions where effluent reuse is unavoidable. The study argues that aligning discharge standards with global benchmarks, adopting mass-based permits, and explicitly regulating contaminants of emerging concern are prerequisites for truly safe wastewater reuse and for protecting wetland ecosystems in effluent-dependent basins. This study shows that permissive, concentration-based discharge standards in effluent-dependent basins create a regulatory mirage that accelerates river and wetland degradation, and that stricter, mass-based limits are essential for safe wastewater reuse. Full article

(This article belongs to the Special Issue Constructed Wetlands for Wastewater Treatment: Recent Advances and Future Challenges)

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21 pages, 3530 KB

Open AccessArticle

Multi-Regional Input–Output Analysis of Water–Energy–Food Nexus Consumption and Transfer in the Yangtze River Delta in China

by Jue Wang, Keyi Ju and Bei Xie

Water 2026, 18(7), 877; https://doi.org/10.3390/w18070877 - 6 Apr 2026

Cited by 1 | Viewed by 684

Abstract

Water, energy, and food (WEF) are intricately linked through economic activities in the Yangtze River Delta, creating increasingly strong interdependencies. Tracking the consumption and transfer of the water–energy–food (WEF) nexus across regions and sectors is essential for the synergetic management of these critical [...] Read more.

Water, energy, and food (WEF) are intricately linked through economic activities in the Yangtze River Delta, creating increasingly strong interdependencies. Tracking the consumption and transfer of the water–energy–food (WEF) nexus across regions and sectors is essential for the synergetic management of these critical resources. To characterize the WEF nexus from both consumption and production ends, this study develops a quantitative accounting framework based on a multi-regional input–output model. The proposed framework integrates direct WEF nexus consumption with embodied consumption driven by final demand and further investigates transfer patterns induced by intermediate inputs. The results indicate that the nexus-oriented consumption between water, energy, and food exceeds individual resource consumption. In particular, food-related water resource consumption in the Service sector in Jiangsu is 28 times that of individual water consumption. The embodied consumption of WEF accounts for 42%, 31%, and 47% of the total consumption, respectively. In particular, the embodied consumption of the WEF nexus caused by urban household consumption in Shanghai is much higher than that in other regions. Manufacturing is the resource-exporting sector, while Agriculture and Construction are the resource-importing sectors. Shanghai is a major resource-importing city, while Zhejiang is a typical resource-exporting city. The results also suggest that Jiangsu–Shanghai and Jiangsu–Anhui are regions with strong connections of WEF nexus transfer, while Agriculture–Manufacturing, Manufacturing–Construction, and Service–Construction are sectors with strong connections. These results highlight the complex interplay between water, energy, and food across the Yangtze River Delta. Given this, this study recommends enhancing resource regulation capabilities and paying attention to strongly correlated regions or sectors. Full article

(This article belongs to the Section Water-Energy Nexus)

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22 pages, 9866 KB

Open AccessArticle

Analysis of Driving Factors and Trend Prediction of Groundwater Levels in the West Liao River Basin Based on the STL-LSTM Model

by Sutong Fu, Liangping Yang, Junting Liu, Pengfei Hao, Fan Wang and Jianmin Bian

Water 2026, 18(7), 876; https://doi.org/10.3390/w18070876 - 6 Apr 2026

Cited by 1 | Viewed by 753

Abstract

In the ecologically fragile West Liao River Basin, characterizing groundwater dynamics is crucial for sustainable water management. Using 2000–2016 groundwater level data, this study applies Seasonal-Trend decomposition using Loess (STL) and change-point detection to analyse trends. Driving factors are quantified via random forest [...] Read more.

In the ecologically fragile West Liao River Basin, characterizing groundwater dynamics is crucial for sustainable water management. Using 2000–2016 groundwater level data, this study applies Seasonal-Trend decomposition using Loess (STL) and change-point detection to analyse trends. Driving factors are quantified via random forest combined with SHapley Additive exPlanations (SHAP) analysis, and a novel STL–Long Short-Term Memory (STL-LSTM) hybrid model is developed for forecasting. Key findings include: (1) Groundwater levels declined persistently, with a significant change point in 2009. The post-2009 decline rate accelerated to −0.749 m/yr, a 55.7% increase. (2) Statistical attribution reveals that soil moisture (43.5%) and climatic factors (29.0%) are the primary predictors of groundwater variability. The dominance of soil moisture highlights the key role of agricultural irrigation, which strongly modifies soil water dynamics during the growing season. (3) The STL-LSTM model achieves optimal predictive performance (R² = 0.8805, RMSE = 0.7081 m), demonstrating enhanced accuracy for non-stationary sequences. This integrated framework combines trend diagnosis, driver interpretation, and hybrid modelling, offering scientific support for precise groundwater management in semi-arid agricultural basins. Full article

(This article belongs to the Section Hydrology)

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19 pages, 3599 KB

Open AccessArticle

Metagenomic Insights into Host-Associated Enrichment of Antibiotic Resistance Genes Under Oxygen-Limited Conditions Induced by PET Microplastics

by Yinhe Zhao, Jun Li, Kunpeng Jiang, Zhaoming Zheng and Zehao Zhang

Water 2026, 18(7), 875; https://doi.org/10.3390/w18070875 - 6 Apr 2026

Cited by 1 | Viewed by 705

Abstract

Antibiotic resistance genes (ARGs) are increasingly recognized as emerging contaminants in wastewater treatment systems; however, their responses to dissolved oxygen (DO)-limited conditions caused by insufficient aeration, particularly in the presence of microplastics, remain poorly understood. In this study, three sequencing batch reactors (SBRs) [...] Read more.

Antibiotic resistance genes (ARGs) are increasingly recognized as emerging contaminants in wastewater treatment systems; however, their responses to dissolved oxygen (DO)-limited conditions caused by insufficient aeration, particularly in the presence of microplastics, remain poorly understood. In this study, three sequencing batch reactors (SBRs) were operated for 31 days under progressively oxygen-limited conditions with different concentrations of polyethylene terephthalate (PET) microplastics to investigate their combined effects on treatment performance, microbial communities, ARGs, mobile genetic elements (MGEs), and PET degradation-related genes using metagenomic analysis. Prolonged oxygen limitation maintained relatively stable organic matter removal but progressively deteriorated ammonium removal and sludge settleability, while PET addition significantly aggravated these effects. PET exposure markedly increased the absolute abundance of ARGs without substantially altering resistome composition or dominant resistance mechanisms, suggesting an amplification rather than restructuring of the resistome. Correlation analyses indicated that ARGs enrichment was primarily host-associated and driven by the proliferation of a limited number of microbial taxa. Several potential ARG hosts were also strongly associated with PET degradation-related genes, indicating shared microbial populations linking PET-associated functions and antibiotic resistance. In addition, strong positive correlations between ARGs and MGEs suggested an important role of gene mobility in resistome dynamics under oxygen-limited conditions. Overall, these results demonstrate that oxygen limitation combined with PET microplastics promotes host-associated ARG enrichment in wastewater systems, highlighting potential environmental and public health risks and emphasizing the importance of maintaining operational stability to mitigate antibiotic resistance dissemination. Full article

(This article belongs to the Special Issue Emerging Contaminants in the Water Environment)

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21 pages, 5239 KB

Open AccessArticle

Spatiotemporal Distribution in Rainfall and Temperature from CMIP6 Models: A Downscaling and Correction Study in a Semi-Arid Region of Mexico

by Ricardo Robles Ortiz, Julián González Trinidad, Carlos Bautista Capetillo, Hugo Enrique Júnez Ferreira, Cruz Octavio Robles Rovelo, Ana Isabel Veyna Gomez, Sandra Dávila Hernández and Misael Del Rio Torres

Water 2026, 18(7), 874; https://doi.org/10.3390/w18070874 - 6 Apr 2026

Viewed by 1110

Abstract

Water planning in semi-arid regions depends on climate information that resolves both seasonal timing and topographic gradients. This study evaluated 15 CMIP6 models over Zacatecas, Mexico, and produced a 1 km historical dataset for 1985–2014 by statistically refining bias-corrected daily fields from NEX-GDDP-CMIP6. [...] Read more.

Water planning in semi-arid regions depends on climate information that resolves both seasonal timing and topographic gradients. This study evaluated 15 CMIP6 models over Zacatecas, Mexico, and produced a 1 km historical dataset for 1985–2014 by statistically refining bias-corrected daily fields from NEX-GDDP-CMIP6. Downscaling was referenced to the CHELSA climatology: temperature was refined using an elevation-informed hybrid spline approach, whereas rainfall was downscaled with geographically weighted regression (GWR) to represent orographic gradients. The resulting fields were assessed against two independent observational baselines: an automated INIFAP network (2004–2014) and a conventional CONAGUA network (1985–2014). For temperature, BCC-CSM2-MR showed the highest performance, with a Pearson correlation of R = 0.94 for both T_max and T_min. A consistent network-dependent bias pattern was identified: the downscaled models overestimated the diurnal temperature range relative to INIFAP but underestimated it relative to CONAGUA, highlighting the influence of instrumentation and observational protocols on model evaluation. For rainfall, ACCESS-ESM1-5 reproduced the seasonal cycle and dominant orographic patterns, with a correlation of R = 0.611 despite the intrinsic stochasticity of semi-arid rainfall. The resulting 1 km fields provide a spatially consistent baseline for regional applications, including stochastic weather generation and impact models in complex semi-arid regions. Full article

(This article belongs to the Section Water and Climate Change)

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15 pages, 3722 KB

Open AccessArticle

Mapping Water Scarcity and Aridity Trends in U.S. Drought Hotspots: Observed Patterns and CMIP6 Projections

by Mario Escobar, Vinay Kumar and Margaret Hurwitz

Water 2026, 18(7), 873; https://doi.org/10.3390/w18070873 - 5 Apr 2026

Viewed by 759

Abstract

Persistent droughts and shifting precipitation regimes continue to threaten water security across the United States, with arid and semi-arid regions remaining the most vulnerable. This study examines the spatial and temporal patterns of aridity and water scarcity across drought-prone stations (111) and regions [...] Read more.

Persistent droughts and shifting precipitation regimes continue to threaten water security across the United States, with arid and semi-arid regions remaining the most vulnerable. This study examines the spatial and temporal patterns of aridity and water scarcity across drought-prone stations (111) and regions of the U.S. using 30 years (1991–2020) of precipitation records from xmACIS II. Weather stations were categorized into arid (<10 inches/year), semi-arid (10–20 inches/year), and non-arid (>20 inches/year) zones, revealing a distinct west–east gradient: arid and semi-arid conditions prevail across the western and central U.S., while the eastern regions remain largely non-arid. Drought frequency analysis spanning 2000–2019 indicates that certain regions experienced exceptional drought conditions (D3 or higher) for more than 50% of the study period, with localized areas enduring over 300 weeks of extreme drought. Long-term precipitation trends (1920–2020) in Texas, Washington, and South Dakota reflect a modest increase in precipitation; however, CMIP6 multi-model ensemble projections under a 2 °C and 4 °C warming scenario point to divergent future trajectories, with some regions experiencing increased wetness while others face progressive drying. These findings offer actionable insights for drought monitoring and climate adaptation strategies, underscoring the heightened vulnerability of arid and semi-arid zones to intensify water scarcity. Full article

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19 pages, 7223 KB

Open AccessArticle

Assessing Climate Change Impacts on Precipitation Volume and Drought Characteristics Across Basin and Sub-Basin Scales in Greece

by Ioannis Zarikos, Nadia Politi, Nikolaos Gounaris, Diamando Vlachogiannis and Athanasios Sfetsos

Water 2026, 18(7), 872; https://doi.org/10.3390/w18070872 - 5 Apr 2026

Cited by 1 | Viewed by 924

Abstract

This study examines the effects of climate change on precipitation and drought conditions in Greece, focusing on basin-level hydrological analysis. It builds on existing evidence that the Mediterranean region is highly vulnerable to global warming, experiencing reduced rainfall, extended droughts, and increased hydro-climatic [...] Read more.

This study examines the effects of climate change on precipitation and drought conditions in Greece, focusing on basin-level hydrological analysis. It builds on existing evidence that the Mediterranean region is highly vulnerable to global warming, experiencing reduced rainfall, extended droughts, and increased hydro-climatic extremes. Using high-resolution down-scaled climate projections under multiple RCP scenarios, the research quantifies precipitation volume within specific hydrological basins, incorporating detailed basin geometries and spatial statistical methods. Alongside precipitation estimates, consecutive dry days and drought frequency, assessed via the Standardised Precipitation Index, offer a multi-indicator view of climate stress. This basin-specific framework connects climate modelling with water resource management, supporting more targeted adaptation strategies. The findings provide new spatial insights into how precipitation redistributes across basins under future climate conditions, with implications for drought-prone regions in Greece. Full article

(This article belongs to the Section Hydrology)

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15 pages, 3700 KB

Open AccessArticle

Determination of Nitrogen in Water by Multi-Pulse Laser-Induced Breakdown Spectroscopy

by Yao Chen, Qian Wang and Zhaoshuo Tian

Water 2026, 18(7), 871; https://doi.org/10.3390/w18070871 - 4 Apr 2026

Viewed by 717

Abstract

Total nitrogen (TN) is a critical indicator of water eutrophication. Conventional detection methods (e.g., alkaline potassium persulfate digestion and the Kjeldahl method) suffer from complex sample preparation, time-consuming operations, and reagent-induced pollution. Laser-induced breakdown spectroscopy (LIBS) offers unique advantages for rapid water quality [...] Read more.

Total nitrogen (TN) is a critical indicator of water eutrophication. Conventional detection methods (e.g., alkaline potassium persulfate digestion and the Kjeldahl method) suffer from complex sample preparation, time-consuming operations, and reagent-induced pollution. Laser-induced breakdown spectroscopy (LIBS) offers unique advantages for rapid water quality analysis, yet it predominantly relies on costly actively Q-switched lasers, with passive Q-switching rarely explored due to multi-pulse output instability. This study employed a passively Q-switched laser as the excitation source for water TN measurement. By optimizing the multi-pulse trigger position, the signal-to-background ratio (SBR) was effectively enhanced. Combined with the substrate liquid–solid conversion method, key parameters (trigger delay, laser energy, argon flow rate) were optimized. Laboratory measurements of KNO₃ standard solutions (0–25 mg/L) using cyanogen (CN) molecular spectral lines yielded a coefficient of determination (R²) of 0.98, and a limit of detection (LoD) of 2.19 mg/L. Tests on actual water samples showed relative deviations ranging from 3.93% to 6.39%. These results demonstrate that passively Q-switched LIBS is a viable, cost-effective solution for rapid water nitrogen detection. Full article

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

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21 pages, 2566 KB

Open AccessArticle

Hydrogeochemical Signature of Cretaceous Geothermal Waters of the Zharkunak Zone, Eastern Ili Depression

by Balnur Kismelyeva, Aisulu Kalitova, Dulat Kalitov, Vyachaslav Zavaley, Yergali Auyelkhan, Rinat Akpanbayev, Raushan Koizhaiganova, Murat Kalitov and Zaure Atabekova

Water 2026, 18(7), 870; https://doi.org/10.3390/w18070870 - 4 Apr 2026

Viewed by 679

Abstract

This study characterizes the hydrochemistry and geochemical signature of the Upper Cretaceous geothermal aquifer in the Zharkunak zone (Eastern Ili Depression, SE Kazakhstan) using certified analytical datasets from five deep wells (5539, 1-RT, 3-T, 1-TP, and 2-TP). The waters are hyperthermal (89–103 °C), [...] Read more.

This study characterizes the hydrochemistry and geochemical signature of the Upper Cretaceous geothermal aquifer in the Zharkunak zone (Eastern Ili Depression, SE Kazakhstan) using certified analytical datasets from five deep wells (5539, 1-RT, 3-T, 1-TP, and 2-TP). The waters are hyperthermal (89–103 °C), alkaline (pH 8.1–9.0), and weakly mineralized (TDS 0.3–1.0 g/L), with sodium-dominated facies ranging from Na–HCO₃–SO₄ to Na–SO₄–Cl. Hydrochemical analysis indicates that water–rock interaction and cation exchange are the primary controls on fluid evolution, with limited influence from evaporation or external salinity sources. Elevated fluoride (up to ~10 mg/L) and dissolved silica (H₂SiO₃, often >50 mg/L) reflect prolonged high-temperature interaction with silicate-rich lithologies under low Ca²⁺ conditions. Trace elements and radon activity (up to 0.32 nCi/L) further support deep, fault-controlled circulation pathways. PHREEQC modeling indicates near-equilibrium to slight supersaturation with respect to silica phases, suggesting a potential risk of silica scaling during cooling, while carbonate scaling remains limited. Although the dataset is based on discharge conditions from a limited number of wells, the results demonstrate that the Zharkunak system has strong geothermal utilization potential, with management considerations related to fluoride, radon, and silica scaling. Future work should focus on integrating isotopic analyses and reactive transport modeling to better constrain subsurface processes and long-term system behavior. Full article

(This article belongs to the Section Hydrogeology)

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22 pages, 3632 KB

Open AccessArticle

Non-Stationarity of Hydroclimatic Memory—Is Hydrological Memory Changing Under Climate Warming?

by Monika Birylo

Water 2026, 18(7), 869; https://doi.org/10.3390/w18070869 - 4 Apr 2026

Cited by 1 | Viewed by 812

Abstract

Hydrological memory reflects the persistence of hydrological processes and plays an important role in understanding basin regime dynamics under changing climatic conditions. This study investigates the temporal stability of hydrological memory in the ten largest European basins: Volga, Danube, Dnieper, Don, Northern Dvina, [...] Read more.

Hydrological memory reflects the persistence of hydrological processes and plays an important role in understanding basin regime dynamics under changing climatic conditions. This study investigates the temporal stability of hydrological memory in the ten largest European basins: Volga, Danube, Dnieper, Don, Northern Dvina, Pechora, Neva, Rhine, Vistula, and Elbe. The analysis used rolling cross-correlation (CCF) and auto-correlation (ACF) functions calculated with a 50-month moving window to assess temporal changes in hydrological dependence structures. Additionally, an Instability Index was applied to quantify the variability of hydrological memory over time. The results indicate that the strongest correlations occur mainly at lag 0 and ±1, suggesting a relatively short hydrological memory in most basins. The lowest Instability Index was observed in the Volga basin, whereas the highest values were recorded in the Danube and Rhine basins. Full article

(This article belongs to the Section Hydrology)

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18 pages, 4378 KB

Open AccessArticle

Comparative Investigation on Flow Behavior and Energy Dissipation of a Novel Cylindrical Asteroid-Shaped Emitter and a Conventional Emitter

by Xingchang Han, Xianying Feng, Yanfei Li, Yitian Sun and Qingsong Lei

Water 2026, 18(7), 868; https://doi.org/10.3390/w18070868 - 4 Apr 2026

Viewed by 568

Abstract

Drip irrigation system performance is largely governed by emitter hydraulic characteristics. This study systematically compares the hydraulic performance of a novel cylindrical asteroid-shaped channel emitter against a conventional toothed labyrinth design. Standardized specimens were produced using precision molds and integrated into drip tapes [...] Read more.

Drip irrigation system performance is largely governed by emitter hydraulic characteristics. This study systematically compares the hydraulic performance of a novel cylindrical asteroid-shaped channel emitter against a conventional toothed labyrinth design. Standardized specimens were produced using precision molds and integrated into drip tapes at 300 mm spacing. To comprehensively analyze flow behavior, pressure–discharge relationships, flow indices, and internal flow fields, a combination of physical experiments and CFD simulations was employed. Experimental results showed that across 20–200 kPa, the cylindrical asteroid-shaped emitter delivered flow rates 24–28% higher than the labyrinth type while maintaining a lower flow index, demonstrating enhanced hydraulic stability. Flow field analysis at 100 kPa revealed that the divergent asteroid geometry generates more intense and sustained turbulent kinetic energy throughout the channel units, resulting in superior energy dissipation. The cylindrical asteroid-shaped unit achieved a pressure drop of 17.5 kPa, exceeding the 15.3 kPa observed in the labyrinth channel, with outlet velocities of 1.6 m/s versus 1.76 m/s. Additionally, the flow pattern promotes comprehensive wall scouring through large-scale vortices, indicating improved resistance to clogging. These findings validate the design superiority of the cylindrical asteroid-shaped emitter and offer a theoretical reference for developing high-uniformity, water-saving irrigation devices. Full article

(This article belongs to the Special Issue Water-Saving and Energy-Efficient Irrigation Technologies and Equipment)

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17 pages, 1597 KB

Open AccessArticle

Chlorine-Enhanced UV-Activated Persulfate System Controls Ammonia Oxidation Product Formation: Contribution of Active Chlorine Species

by Ying Lu, Wenqiang Yang, Linyi Wang, Yinghao Qin, Baomin Chen, Zhenfang Huang, Qingge Feng, Wangye Lu, Chenhong Liu and Dongbo Wang

Water 2026, 18(7), 867; https://doi.org/10.3390/w18070867 - 4 Apr 2026

Viewed by 657

Abstract

The removal of ammonia nitrogen (NH₄⁺-N) using advanced oxidation processes (AOPs) has garnered increasing attention in wastewater purification. However, the application of the UV-activated persulfate (PS) system for treating NH₄⁺-N wastewater is limited by the low reaction [...] Read more.

The removal of ammonia nitrogen (NH₄⁺-N) using advanced oxidation processes (AOPs) has garnered increasing attention in wastewater purification. However, the application of the UV-activated persulfate (PS) system for treating NH₄⁺-N wastewater is limited by the low reaction rate between NH₄⁺-N and the reactive species (·OH and SO₄·⁻) generated in the system. In this study, common chloride ions (Cl⁻) were employed to enhance the removal of NH₄⁺-N in the UV/PS process; when the system conditions were pH = 7, [PS]₀ = 10mM, [Cl⁻]₀ = 35 mM, 30 mg/L NH₄⁺-N was completely degraded within 40 min. The total nitrogen removal rate was 75.50%, and the reaction rate constant increased from 0.0026 min⁻¹ to 0.0801 min⁻¹. The introduction of Cl⁻ led to the generation of reactive chlorine species (RCS) in the system that could efficiently oxidize NH₄⁺-N over a wide pH range (3–9), and the RCS, which efficiently oxidized NH₄⁺-N across a wide pH range (3–9). Quenching experiments confirmed that these RCS were gradually produced through the activation of Cl⁻ by ·OH and SO₄·⁻. The common anions present in water bodies had little impact on the degradation performance of NH₄⁺-N in the UV/PS/Cl⁻ system. Overall, the UV/PS/Cl⁻ system proposed in this study offers an effective approach for the efficient removal of NH₄⁺-N. Full article

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

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22 pages, 3905 KB

Open AccessArticle

Three-Layer Model of Gas–Liquid–Solid Multiphase Transient Flow After Rock Plug Blast

by Gaohui Li, Yiheng Jia, Jian Zhang, Weiwei Pu, Tianchi Zhou and Fulin Zhang

Water 2026, 18(7), 866; https://doi.org/10.3390/w18070866 - 3 Apr 2026

Viewed by 599

Abstract

Underwater rock plug blasting involves a highly complex, transient gas–liquid–solid multiphase flow that is difficult to simulate accurately with conventional single-phase models. To address this gap, a novel three-phase three-layer mathematical model is presented in this study. This model represents the stratified flow [...] Read more.

Underwater rock plug blasting involves a highly complex, transient gas–liquid–solid multiphase flow that is difficult to simulate accurately with conventional single-phase models. To address this gap, a novel three-phase three-layer mathematical model is presented in this study. This model represents the stratified flow behavior by decomposing the conduit into an upper gas layer, a middle gas–liquid–solid mixture layer, and a lower consolidated bed layer. Governing equations for mass, momentum, and energy conservation are derived and solved using the finite volume method. The model is validated against physical model tests, showing a maximum gate shaft surge deviation of only 0.27%, a Pearson correlation coefficient of 0.965, and a relative RMSE of 4.2%. A sensitivity analysis is performed to quantify the influence of key operational water levels, including the reservoir, gate shaft, and slag pit, on critical transient loads. The results demonstrate that a decrease in the reservoir water level from 106 m to 86 m concurrently reduces both surge height and impact pressure. A smaller reservoir–shaft water level difference (5–15 m) increases the initial cushion pressure and amplifies the surge. In contrast, a larger level difference (20–30 m) suppresses surge but increases impact pressure. Furthermore, an excessively high water level in the slag pit (exceeding 47.8 m) weakens the cushioning effect, thereby lowering the impact pressure. The proposed multiphase model provides an improved approach for predicting hydraulic transients during underwater rock plug blasting. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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21 pages, 5069 KB

Open AccessArticle

Numerical Hydrodynamic and Mooring Optimization of a Wave Energy Converter for the Mexican Coast

by Paulino Meneses Gonzalez, Efrain Carpintero Moreno, Peter Troch and Edgar Mendoza

Water 2026, 18(7), 865; https://doi.org/10.3390/w18070865 - 3 Apr 2026

Viewed by 570

Abstract

This study presents a hydrodynamic assessment of a toroidal wave energy converter (WEC) operating under low-energy conditions of the west coast of Mexico. Performance analysis incorporates the coupling surge, heave, and pitch motions. To investigate mooring–device interaction, two mooring configurations were examined: (A) [...] Read more.

This study presents a hydrodynamic assessment of a toroidal wave energy converter (WEC) operating under low-energy conditions of the west coast of Mexico. Performance analysis incorporates the coupling surge, heave, and pitch motions. To investigate mooring–device interaction, two mooring configurations were examined: (A) a single catenary system and (B) a catenary system with a surface-floating buoy. The WEC was evaluated under operational conditions, operational conditions with a constant surface current, and extreme seas. The results show that under operational conditions, the WEC-mooring B configuration achieves higher energy capture than the WEC-mooring A configuration, with performance peaks at 13 s and 11 s, respectively. The presence of a surface current does not significantly influence absorbed power. Under extreme conditions, mooring B reduces mooring-line stresses but causes greater horizontal foundation forces and increased floater drift compared to mooring A. When mooring effects are included, mooring A’s performance is advantageous because it shifts peak energy capture toward the dominant sea states at the study site. This maintains better station-keeping capability and achieves a maximum capture width ratio (CWR) of approximately 0.5. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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13 pages, 2239 KB

Open AccessArticle

Efficient Removal of Dissolved Organic Matter via a Hybrid UV/O₃ Micro-Nano Bubble Process

by Haijun Ma, Quan Zhang, Tao Zhou, Nongcun Wang, Shulei Hou, Jun Liu and Zhanghao Chen

Water 2026, 18(7), 864; https://doi.org/10.3390/w18070864 - 3 Apr 2026

Cited by 1 | Viewed by 692

Abstract

Removing trace amounts of dissolved organic matter (DOM) has always been a significant issue in the field of environmental science and engineering. Herein, a UV-coupled O₃ micro-nano bubble (O₃-MNB) system was constructed, demonstrating superior efficiency in eliminating DOM compared to [...] Read more.

Removing trace amounts of dissolved organic matter (DOM) has always been a significant issue in the field of environmental science and engineering. Herein, a UV-coupled O₃ micro-nano bubble (O₃-MNB) system was constructed, demonstrating superior efficiency in eliminating DOM compared to bulk O₃-MNB oxidation and direct UV photolysis. Various advanced analytical techniques, including in situ electron paramagnetic resonance, Fourier transform infrared spectroscopy and three-dimensional excitation–emission matrix, were employed to reveal the mechanism of the reaction process. Benefiting from the abundant interfacial area and enhanced mass transfer efficiency provided by the micro-nano bubbles, along with the simultaneous generation of reactive oxygen species such as •OH through UV activation, the UV/O₃-MNB system demonstrates excellent performance in removing DOM, and more than 90% of the mineralization rate was achieved after 1 h reaction. Furthermore, the findings were verified using both municipal water and natural surface water, and the proposed system also shows advantages in energy consumption compared to direct UV irradiation and conventional O₃ treatment, with an energy consumption of 25 kWh/mg dissolved organic carbon. This study innovatively integrates UV light with O₃-MNB technology, offering novel insights for advanced water purification and providing valuable references for practical engineering applications. Full article

(This article belongs to the Special Issue Advanced Chemical and Biological Technologies for Water Purification and Contaminant Degradation)

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19 pages, 2757 KB

Open AccessArticle

Data-Driven Modeling and Optimization of a Modified Ludzack–Ettinger Process Using ML and DL for Effluent Quality Prediction

by Fengshi Guo, Shiyu Sun, Mingcan Cui and Daeyeon Yang

Water 2026, 18(7), 863; https://doi.org/10.3390/w18070863 - 3 Apr 2026

Viewed by 844

Abstract

Accurate prediction and optimization of effluent quality are essential for the stable operation of wastewater treatment plants under increasing influent variability and stringent discharge regulations. This study presents an integrated data-driven framework that combines machine learning, deep learning, model interpretability, and optimization to [...] Read more.

Accurate prediction and optimization of effluent quality are essential for the stable operation of wastewater treatment plants under increasing influent variability and stringent discharge regulations. This study presents an integrated data-driven framework that combines machine learning, deep learning, model interpretability, and optimization to enhance the performance of a full-scale Modified Ludzack–Ettinger (MLE) process. Three years of operational data from a municipal wastewater treatment plant were used to develop and compare random forest (RF), k-nearest neighbors (K-NN), multilayer perceptron (MLP), and deep neural network (DNN) models for the simultaneous prediction of effluent total organic carbon (TOC), biochemical oxygen demand (BOD), and total nitrogen (TN). Model performance was evaluated using the coefficient of determination (R²) and root mean square error (RMSE), and generalization capability was validated using independent field data. The results show that deep learning models, particularly DNN, outperform conventional machine learning approaches by effectively capturing complex nonlinear and multivariate process dynamics. To improve model interpretability, SHapley Additive exPlanations (SHAP) were applied to identify key operational variables affecting effluent quality. In addition, particle swarm optimization (PSO) was integrated with the trained models to determine optimal operating conditions that minimize effluent pollutant concentrations without requiring structural modifications. Overall, the proposed framework provides an interpretable and practical decision-support tool for proactive wastewater treatment plant operation, contributing to improved operational efficiency and environmental sustainability. Full article

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

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21 pages, 1798 KB

Open AccessArticle

Evolutionary Characteristics of Water Resource Governance Policies in China: Based on a Quantitative Textual Analysis

by Min Wu, Xiang’an Shen and Zihan Hu

Water 2026, 18(7), 862; https://doi.org/10.3390/w18070862 - 3 Apr 2026

Cited by 1 | Viewed by 702

Abstract

Water governance faces growing challenges from climate change, pollution, and increasing demand, rendering policy evolution a critical research focus. This study analyzes the evolutionary characteristics of China’s national water resources governance policies from 1988 to 2025 through an integrated quantitative textual analysis. Based [...] Read more.

Water governance faces growing challenges from climate change, pollution, and increasing demand, rendering policy evolution a critical research focus. This study analyzes the evolutionary characteristics of China’s national water resources governance policies from 1988 to 2025 through an integrated quantitative textual analysis. Based on 154 authoritative policy documents, the study employs Latent Dirichlet Allocation topic modeling, semantic network analysis, and a tripartite policy instrument coding scheme (command-and-control, market-based, and public participation instruments). The results reveal three key findings: a significant shift in policy attention from early administrative control toward system-oriented governance emphasizing watershed/ecological protection, conservation, and technology; a persistently imbalanced instrument mix with command-and-control tools remaining dominant, despite gradual diversification after 2000; and a three-stage evolutionary trajectory from administrative framework building (1988–1999), through comprehensive management and diversification (2000–2015), to collaborative innovation and basin/ecology integration (2016–2025). This study contributes a long-term empirical perspective on water policy evolution in an emerging economy, demonstrates an integrated textual-analytic approach, and provides actionable insights for optimizing policy mixes through strengthened incentive compatibility, substantive participation mechanisms, and coherent governance-aligned instrument portfolios. Full article

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

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27 pages, 1854 KB

Open AccessArticle

“There Is No Governance”: Drinking Water Governance in Coastal Areas of Bangladesh

by Afsana Afrin Esha, C. Isabella Bovolo, Hanna A. Ruszczyk and Andrew Baldwin

Water 2026, 18(7), 861; https://doi.org/10.3390/w18070861 - 3 Apr 2026

Cited by 1 | Viewed by 1333

Abstract

Most empirical research on drinking water governance and regional transformations in Bangladesh has focused on developed and urban regions. We focus on coastal rural areas to address this gap and employ a three-step methodology for the systematic analysis of the broader and site-specific [...] Read more.

Most empirical research on drinking water governance and regional transformations in Bangladesh has focused on developed and urban regions. We focus on coastal rural areas to address this gap and employ a three-step methodology for the systematic analysis of the broader and site-specific drinking water landscape, involving (i) stakeholder analysis and mapping to identify key actors and characteristics, (ii) field work to identify case study sites, meet stakeholders and identify local water technologies, and (iii) in-depth analysis, triangulating stakeholders, drinking water technologies and governance structures, to identify synergies, differences, gaps and overlaps within them. Taking four different but illustrative case study areas in the Southwestern coastal region of Bangladesh, we identify key stakeholders and capture the multiplicity and dynamism of governance models. We provide the first in-depth mapping of the drinking water landscape in coastal rural Bangladesh. Results reveal a fragmented rural water governance landscape, marked by failed or non-functional technologies due to disputes, poor maintenance, high costs, and lack of accountability after project completion, leaving communities to seek alternative water resources for themselves. We argue that informal water provision currently needs to exist beyond well-known governance models due to system inefficiencies and short legacies of implemented technologies. As the water deficit is predicted to increase, it is imperative to identify the complexities and inefficiencies in governance structures to construct collaborative, sustainable approaches to ensuring drinking water security. Full article

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

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23 pages, 1467 KB

Open AccessReview

Emerging Contaminants in Wastewater: Mitigation Approaches for Environmental Management and Future Sustainability

by Podila Sujan Sai, Kokkanti Hemanth Kumar, Alapati Nidhi Sri, Ranaprathap Katakojwala, Jagiri Shanthi Sravan and Manupati Hemalatha

Water 2026, 18(7), 860; https://doi.org/10.3390/w18070860 - 3 Apr 2026

Cited by 4 | Viewed by 3284

Abstract

Emerging contaminants (ECs) are a diversely mounting group of chemicals and biological compounds found in air, water, and soil, which include pharmaceuticals, personal care products, per- and poly-fluoroalkyl substances (PFASs), microplastics, endocrine-disrupting chemicals, and various other industrial compounds. Unlike conventional pollutants, ECs are [...] Read more.

Emerging contaminants (ECs) are a diversely mounting group of chemicals and biological compounds found in air, water, and soil, which include pharmaceuticals, personal care products, per- and poly-fluoroalkyl substances (PFASs), microplastics, endocrine-disrupting chemicals, and various other industrial compounds. Unlike conventional pollutants, ECs are usually unregulated, found in very small amounts, and can persist and build up in living organisms, resulting in toxic risks for both ecosystems and human health. These contaminants originate from various anthropogenic activities and enter the environment through wastewater, stormwater, landfill leaching, and atmospheric deposition. This article documents a holistic literature review of ECs available from the last five years, covering classification, sources and pathways of contamination, and environmental behavior, while assessing their ecological, human health, and socioeconomic impacts. Advances in detection, including high-resolution mass spectrometry, non-target screening, real-time sensors, and AI-assisted monitoring, are addressed. Management strategies including advanced oxidation, membrane filtration, electrochemical treatments, and nature-based solutions are explored. It also analyses global and regional policy frameworks, highlighting regulatory gaps and the need for standardized monitoring. The study emphasizes integrated, multidisciplinary approaches combining scientific innovation, sustainable chemical design, predictive modeling, and public engagement. Synergizing technology, governance, and prevention could reduce the risks related to ECs and protect the environment. The novel contribution is an end-to-end, decision-oriented synthesis that links what monitoring can reliably infer to be feasible, integrated control strategies and sustainability outcomes, supporting risk-based prioritization, targeted pollution treatment, and prevention-focused management. Full article

(This article belongs to the Special Issue Rethinking Wastewater: Microbial Solutions for a Sustainable Future)

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1 pages, 125 KB

Open AccessCorrection

Correction: Nhu et al. Mapping of Groundwater Spring Potential in Karst Aquifer System Using Novel Ensemble Bivariate and Multivariate Models. Water 2020, 12, 985

by Viet-Ha Nhu, Omid Rahmati, Fatemeh Falah, Saeed Shojaei, Nadhir Al-Ansari, Himan Shahabi, Ataollah Shirzadi, Krzysztof Górski, Hoang Nguyen and Baharin Bin Ahmad

Water 2026, 18(7), 859; https://doi.org/10.3390/w18070859 - 3 Apr 2026

Viewed by 329

Abstract

There was an error in the original publication [...] Full article

(This article belongs to the Section Hydrology)

19 pages, 11722 KB

Open AccessArticle

Modeling Spatiotemporal Streamflow Patterns in the Missouri River Basin Under Future Climate Scenarios

by Benjamin Donkor, Zhulu Lin and Siew Hoon Lim

Water 2026, 18(7), 858; https://doi.org/10.3390/w18070858 - 2 Apr 2026

Viewed by 1088

Abstract

Understanding the spatiotemporal streamflow patterns under future climate scenarios is critical for sustainable water resource management in large river basins. This study applied the Soil and Water Assessment Tool (SWAT), forced by five downscaled and bias-corrected CMIP6 global climate models, to evaluate historical [...] Read more.

Understanding the spatiotemporal streamflow patterns under future climate scenarios is critical for sustainable water resource management in large river basins. This study applied the Soil and Water Assessment Tool (SWAT), forced by five downscaled and bias-corrected CMIP6 global climate models, to evaluate historical (2008–2024) and future (2025–2049) streamflow patterns in the Missouri River Basin in the continental United States. Model calibration and validation were satisfactory, with NSE > 0.5, KGE ≥ 0.5, R² > 0.5, and PBIAS within ±25% at most USGS gauge stations. Future projections indicate spatially and temporally variable hydrological responses: The upper basin (Bismarck, North Dakota) is projected to experience lower flows across most percentiles and reduced extreme events, whereas the lower basin (Hermann, Missouri) shows decreased median flows but higher extremes. Recurrence interval analysis of 2-, 5-, 10-, 50-, 100-, and 500-year flows suggests that 100-year flows may decline by 11% at Bismarck and increase by 37.4% at Hermann. These results highlight the importance of integrating percentile-based and extreme event streamflow analyses with hydrologic modeling for assessing the spatiotemporal streamflow patterns under future climate scenarios in large-scale basins. Quantitative insights into future streamflow variability and its implications for flood risk mitigation, water resources management, and adaptive strategies were gained for one of North America’s largest river systems. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling, 3rd Edition)

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49 pages, 7199 KB

Open AccessArticle

Machine Learning-Enhanced Modeling of Heavy Metal Adsorption onto Coal Fly Ash-Derived Zeolite P

by Benito A. Hernández-Guerrero, Lorena Martínez, Gabriel Peña-Rodríguez and Fernando Trejo

Water 2026, 18(7), 857; https://doi.org/10.3390/w18070857 - 2 Apr 2026

Cited by 1 | Viewed by 918

Abstract

Zeolite P was synthesized by hydrothermal treatment of coal fly ash and applied to the individual removal of six heavy metals (Pb²⁺, Ni²⁺, Cu²⁺, Cr³⁺, Hg²⁺, Cd²⁺) from aqueous solutions. Characterization [...] Read more.

Zeolite P was synthesized by hydrothermal treatment of coal fly ash and applied to the individual removal of six heavy metals (Pb²⁺, Ni²⁺, Cu²⁺, Cr³⁺, Hg²⁺, Cd²⁺) from aqueous solutions. Characterization by SEM-EDS, FTIR, BET, XRD, zeta potential, and XPS revealed a BET surface area of 30 m²/g, Si/Al ratio of 1.63, and pH_pzc of 3.2. Batch experiments at the natural solution pH of 3.9 in all cases (C₀ = 10, 100, 200 mg/L; t = 1–60 min) yielded an apparent selectivity sequence at C₀ = 200 mg/L of Hg²⁺ (10.47 mg/g) > Pb²⁺ (9.12) > Ni²⁺ (2.18) > Cr³⁺ (2.05) > Cu²⁺ (1.82) > Cd²⁺ (1.26), where Hg²⁺ and Pb²⁺ reached near-equilibrium while the remaining metals were still approaching it at t = 60 min. Weber–Morris and Boyd analyses confirmed three sequential diffusion stages with a concentration-dependent shift from film to intraparticle diffusion control through the narrow GIS channels (3.1 × 4.5 Å). Ion exchange was identified as the dominant mechanism based on convergent kinetic, diffusion, XPS, and selectivity–electronegativity evidence (r = +0.76). A leakage-free machine learning framework combining physicochemical descriptors with experimental variables was tested under three cross-validation strategies of increasing stringency. Gradient Boosting achieved R² = 0.979 ± 0.043 (repeated K-Fold) and R² = 0.880 on six completely held-out kinetic curves. An ablation study confirmed that physicochemical descriptors are essential (experimental-only models yielded negative R²). SHAP feature importance rankings were consistent with established ion exchange selectivity theory. This work demonstrates that group-level validation, physics-informed descriptors, and systematic ablation testing are able to identify both the capabilities and the boundaries of small-dataset ML when testing for metal kinetics prediction. Full article

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

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23 pages, 11366 KB

Open AccessArticle

A Process-Based DEM-Pore-Network Framework for Linking Granular Deposition and Particle Irregularity to Directional Permeability

by Yurou Hu, Yinger Deng, Lin Chen, Ning Wang and Pengjie Li

Water 2026, 18(7), 856; https://doi.org/10.3390/w18070856 - 2 Apr 2026

Viewed by 700

Abstract

Granular deposition and grading strongly influence pore-space topology and hence hydraulic conductivity in natural and engineered porous media, yet quantitative links between deposition sequence, particle-scale morphology, pore-network descriptors, and permeability anisotropy remain incomplete. Here, we develop a process-based digital porous-media framework that couples [...] Read more.

Granular deposition and grading strongly influence pore-space topology and hence hydraulic conductivity in natural and engineered porous media, yet quantitative links between deposition sequence, particle-scale morphology, pore-network descriptors, and permeability anisotropy remain incomplete. Here, we develop a process-based digital porous-media framework that couples discrete element method (DEM) deposition with pore-network characterization and Darcy-scale permeability evaluation. Two deposition sequences—normal grading (coarse-to-fine) and reverse grading (fine-to-coarse)—are simulated using bi-disperse particle sets with controlled size ratios. To further isolate the role of particle morphology, particle irregularity is parameterized by a Perlin-noise-based shape perturbation factor and incorporated into the DEM-generated packings. For each packing, pore networks are extracted and quantified in terms of pore/throat size distributions and connectivity, while pore-space complexity is measured via box-counting fractal dimension. Single-phase flow is solved under imposed pressure gradient, and intrinsic permeability is computed along three orthogonal directions to evaluate anisotropy. Results show that increasing size contrast reduces porosity, shifts pore and throat distributions toward smaller characteristic radii, increases pore-space fractal dimension, and yields a monotonic permeability reduction. For identical size ratios, reverse grading consistently yields higher permeability than normal grading, suggesting that deposition sequence exerts a strong control on the continuity and efficiency of effective flow pathways at the sample scale. Increasing particle irregularity decreases permeability and systematically modifies permeability anisotropy, transitioning from weak horizontal anisotropy toward near-isotropy and, at strong irregularity, toward preferential vertical permeability. The proposed framework provides a reproducible route to relate depositional history and particle morphology to pore-network structure and directional permeability, offering implications for filtration, packed-bed design, and sedimentary reservoir characterization. Full article

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

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16 pages, 3190 KB

Open AccessArticle

Spatio-Environmental Drivers of Water Scarcity in Semi-Arid Catchments: Insights from NDWI and LULC

by Andrew Ikingura and Ryszard Staniszewski

Water 2026, 18(7), 855; https://doi.org/10.3390/w18070855 - 2 Apr 2026

Cited by 1 | Viewed by 683

Abstract

Water scarcity in semi-arid closed-basin systems is increasingly driven by hydrological and land transformation processes. This study integrates multi-temporal remote sensing and physicochemical data to examine spatio-environmental drivers of surface water decline in Lake Manyara. Normalized Difference Water Index (NDWI) maps derived from [...] Read more.

Water scarcity in semi-arid closed-basin systems is increasingly driven by hydrological and land transformation processes. This study integrates multi-temporal remote sensing and physicochemical data to examine spatio-environmental drivers of surface water decline in Lake Manyara. Normalized Difference Water Index (NDWI) maps derived from dry-season Landsat imagery (July 2015 and July 2025) were used to quantify surface water dynamics, while supervised Maximum Likelihood land use/land cover (LULC) classification provided a characterized existing spatial context of the study area. Physicochemical parameters derived from recent field observations were evaluated using Carlson’s Trophic State Index (TSI). Results indicate a 31.7% reduction in dry-season surface water extent, from 232.4 km² in 2015 to 158.7 km² in 2025, accompanied by a marked spectral shift toward more negative NDWI values, reflecting extensive lakebed exposure. Agricultural expansion and bare land surfaces were spatially associated with stronger negative NDWI patterns (r ≈ −0.64, p < 0.05). Water quality assessment revealed extreme hypereutrophic conditions (TSI = 98.07), characterized by elevated phosphorus, nitrate, and chlorophyll-a, and high ionic concentrations. The findings demonstrate that hydrological contraction, eutrophication, and catchment land transformation are interconnected processes intensifying water scarcity in semi-arid lake systems. Full article

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

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