Water

35 pages, 2479 KB

Open AccessEditor’s ChoiceArticle

Cost–Benefit and Market Viability Analysis of Metals and Salts Recovery from SWRO Brine Compared with Terrestrial Mining and Traditional Chemical Production Methods

by Olufisayo E. Ojo and Olanrewaju A. Oludolapo

Water 2025, 17(19), 2855; https://doi.org/10.3390/w17192855 - 30 Sep 2025

Cited by 7 | Viewed by 8884

Abstract

Seawater reverse osmosis (SWRO) desalination generates a concentrated brine byproduct rich in dissolved salts and minerals. This study presents an extensive economic and technical analysis of recovering all major ions from SWRO brine, which includes Na, Cl, Mg, Ca, SO₄, K, [...] Read more.

Seawater reverse osmosis (SWRO) desalination generates a concentrated brine byproduct rich in dissolved salts and minerals. This study presents an extensive economic and technical analysis of recovering all major ions from SWRO brine, which includes Na, Cl, Mg, Ca, SO₄, K, Br, B, Li, Rb, and Sr in comparison to conventional mining and chemical production of these commodities. Data from recent literature and case studies are compiled to quantify the composition of a typical SWRO brine and the potential yield of valuable products. A life-cycle cost framework is applied, incorporating capital expenditure (CAPEX), operational expenditure (OPEX), and total water cost (TWC) impacts. A representative simulation for a large 100,000 m³/day SWRO plant shows that integrated “brine mining” systems could recover on the order of 3.8 million tons of salts per year. At optimistic recovery efficiencies, the gross annual revenue from products (NaCl, Mg(OH)₂/MgO, CaCO₃, KCl, Br₂, Li₂CO₃, etc.) can reach a few hundred million USD. This revenue is comparable to or exceeds the added costs of recovery processes under favorable conditions, potentially offsetting desalination costs by USD 0.5/m³ or more. We compare these projections with the economics of obtaining the same materials through conventional mining and chemical processes worldwide. Major findings indicate that recovery of abundant low-value salts (especially NaCl) can supply bulk revenue to cover processing costs, while extraction of scarce high-value elements (Li, Rb, Sr, etc.) can provide significant additional profit if efficient separation is achieved. The energy requirements and unit costs for brine recovery are analyzed against those of terrestrial or conventional mining; in many cases, brine-derived production is competitive due to avoided raw material extraction and potential use of waste or renewable energy. CAPEX for adding mineral recovery to a desalination plant is significant but can be justified by revenue and by strategic benefits such as reduced brine disposal. Our analysis, drawing on global data and case studies (e.g., projects in Europe and the Middle East), suggests that metals and salts recovery from SWRO brine is technically feasible and, at sufficient scale, economically viable in many regions. We provide detailed comparisons of cost, yield, and market value for each target element, along with empirical models and formulas for profitability. The results offer a roadmap for integrating brine mining into desalination operations and highlight key factors such as commodity prices, scale economies, energy integration, and policy incentives that influence the competitiveness of brine recovery against traditional mining. Full article

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

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48 pages, 4222 KB

Open AccessEditor’s ChoiceReview

Machine Learning Models of the Geospatial Distribution of Groundwater Quality: A Systematic Review

by Mohammad Mehrabi, David A. Polya and Yang Han

Water 2025, 17(19), 2861; https://doi.org/10.3390/w17192861 - 30 Sep 2025

Cited by 10 | Viewed by 4307

Abstract

Assessing the quality of groundwater, a primary source of water in many sectors, is of paramount importance. To this end, modeling the geospatial distribution of chemical contaminants in groundwater can be of great utility. Machine learning (ML) models are being increasingly used to [...] Read more.

Assessing the quality of groundwater, a primary source of water in many sectors, is of paramount importance. To this end, modeling the geospatial distribution of chemical contaminants in groundwater can be of great utility. Machine learning (ML) models are being increasingly used to overcome the shortcomings of conventional predictive techniques. We report here a systematic review of the nature and utility of various supervised and unsupervised ML models during the past two decades of machine learning groundwater hazard mapping (MLGHM). We identified and reviewed 284 relevant MLGHM journal articles that met our inclusion criteria. Firstly, trend analysis showed (i) an exponential increase in the number of MLGHM studies published between 2004 and 2025, with geographical distribution outlining Iran, India, the US, and China as the countries with the most extensively studied areas; (ii) nitrate as the most studied target, and groundwater chemicals as the most frequently considered category of predictive variables; (iii) that tree-based ML was the most popular model for feature selection; (iv) that supervised ML was far more favored than unsupervised ML (94% vs. 6% of models) with tree-based category—mostly random forest (RF)—as the most popular supervised ML. Secondly, compiling accuracy-based comparisons of ML models from the explored literature revealed that RF, deep learning, and ensembles (mostly meta-model ensembles and boosting ensembles) were frequently reported as the most accurate models. Thirdly, a critical evaluation of MLGHM models in terms of predictive accuracy, along with several other factors such as models’ computational efficiency and predictive power—which have often been overlooked in earlier review studies—resulted in considering the relative merits of commonly used MLGHM models. Accordingly, a flowchart was designed by integrating several MLGHM key criteria (i.e., accuracy, transparency, training speed, number of hyperparameters, intended scale of modeling, and required user’s expertise) to assist in informed model selection, recognising that the weighting of criteria for model selection may vary from problem to problem. Lastly, potential challenges that may arise during different stages of MLGHM efforts are discussed along with ideas for optimizing MLGHM models. Full article

(This article belongs to the Section Hydrogeology)

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35 pages, 7061 KB

Open AccessEditor’s ChoiceArticle

Monitoring Surface Water Dynamics in Mining Areas Using Remote Sensing Indices: A Review and Cross-Case Analysis

by Aleksandra Smentek, Aleksandra Kaczmarek, Pinar Eksert and Jan Blachowski

Water 2025, 17(19), 2826; https://doi.org/10.3390/w17192826 - 26 Sep 2025

Cited by 8 | Viewed by 5240

Abstract

Mining affects groundwater and surface water both during an active mining operation and after its termination. Continuous monitoring and both quantitative and qualitative assessment of water dynamics are crucial for the sustainable management of the mining and post-mining environment. This paper provides an [...] Read more.

Mining affects groundwater and surface water both during an active mining operation and after its termination. Continuous monitoring and both quantitative and qualitative assessment of water dynamics are crucial for the sustainable management of the mining and post-mining environment. This paper provides an extensive overview of water in the mining industry and of remote sensing methods for surface water monitoring. Moreover, selected spectral water indices are compared to assess their performance and usefulness in surface water monitoring. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Modified Normalized Difference Water Index (MNDWI) are applied to different case study areas affected by mining-induced multitemporal surface water changes. All the selected indices were found useful as proxies for surface water identification; however, their effectiveness and accuracy varied in subsequent case studies. Full article

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

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29 pages, 1446 KB

Open AccessEditor’s ChoiceReview

Review of Water Use Assessment in Livestock Production Systems and Supply Chains

by Katrin Drastig and Ranvir Singh

Water 2025, 17(19), 2819; https://doi.org/10.3390/w17192819 - 25 Sep 2025

Cited by 4 | Viewed by 2554

Abstract

Improving the water productivity and sustainability of global food supplies and reducing water stress worldwide requires a comprehensive and consistent assessment of water use in global food production systems, including livestock production and supply chains. Presented here is a systematic review of relevant [...] Read more.

Improving the water productivity and sustainability of global food supplies and reducing water stress worldwide requires a comprehensive and consistent assessment of water use in global food production systems, including livestock production and supply chains. Presented here is a systematic review of relevant livestock water use studies, published over two periods: “Period 1993–2017” and “Period 2018–2024”, assessing consistency in their approaches and identifying opportunities for advancing and harmonizing the assessment of livestock water use worldwide. However, the review highlights that a comprehensive and consistent assessment of livestock water use remains a challenge. The reviewed studies (a total of 317) differ in terms of their accounting of different water flows, setting the system boundaries, and quantification of water productivity and impact metrics. This makes it difficult to compare potential water productivity and environmental impacts of livestock production systems at different scales and locations. Case studies are required to further develop and implement a robust and consistent methodological approach, based on locally calibrated models and databases, of different livestock production systems in different agroclimatic conditions. Also, further communication and training are required to help build the capability to apply a comprehensive and consistent assessment of livestock water use locally and globally. The adoption of a scientifically robust and practically applicable methodological framework will support researchers, policy managers, farmers, and business leaders in sound decision-making to improve the productivity and sustainability of water use in livestock production systems locally and globally. Full article

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

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28 pages, 1509 KB

Open AccessEditor’s ChoiceReview

Life After Adsorption: Regeneration, Management, and Sustainability of PFAS Adsorbents in Water Treatment

by Magdalena Andrunik and Marzena Smol

Water 2025, 17(19), 2813; https://doi.org/10.3390/w17192813 - 25 Sep 2025

Cited by 21 | Viewed by 6738

Abstract

Per- and polyfluoroalkyl substances (PFASs) represent one of the most challenging classes of persistent organic pollutants, and adsorption is currently one of the most widely deployed method for their removal from water. However, the long-term sustainability of adsorption-based treatment depends on how adsorbents [...] Read more.

Per- and polyfluoroalkyl substances (PFASs) represent one of the most challenging classes of persistent organic pollutants, and adsorption is currently one of the most widely deployed method for their removal from water. However, the long-term sustainability of adsorption-based treatment depends on how adsorbents are regenerated, managed after exhaustion, and integrated into broader environmental and regulatory frameworks. This review synthesises recent advances in regeneration strategies for PFAS-saturated adsorbents, including thermal, solvent-based, chemical, hybrid, and emerging methods, and provides a targeted analysis of policy and regulatory frameworks governing PFAS management in water. Evidence from the literature is critically assessed with attention to regeneration efficiencies, adsorbent stability, secondary waste generation, and long-term reuse potential. Life cycle assessment (LCA) studies are also examined to evaluate the environmental and cost implications of different management options. The analysis highlights that while solvent and chemical regeneration achieve high short-term recovery, thermal processes offer partial destructive potential, and electrochemical methods are emerging as promising but unproven alternatives. Persistent challenges include incomplete PFAS desorption, performance decline over multiple cycles, energy intensity, and secondary waste burdens. Advancing sustainable PFAS treatment requires integrated evaluation frameworks linking technical performance with environmental impact and cost, supported by policy drivers that incentivize regeneration and safe end-of-life management. Full article

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

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21 pages, 2064 KB

Open AccessEditor’s ChoiceReview

Status and Progress of Determining the Variability and Controls on Chemical Denudation Rates in Glacierized Basins Around the World

by Maya P. Bhatt, Ganesh B. Malla and Jacob C. Yde

Water 2025, 17(19), 2811; https://doi.org/10.3390/w17192811 - 24 Sep 2025

Cited by 2 | Viewed by 924

Abstract

Glaciers play a crucial role in shaping global hydrology and biogeochemical cycles, yet their climate-forced dynamic impact on chemical denudation and solute yields remain poorly understood. This study compiled data on 40 well-documented cationic denudation rates (CDR) from glaciers across Northwest America, the [...] Read more.

Glaciers play a crucial role in shaping global hydrology and biogeochemical cycles, yet their climate-forced dynamic impact on chemical denudation and solute yields remain poorly understood. This study compiled data on 40 well-documented cationic denudation rates (CDR) from glaciers across Northwest America, the Svalbard/Arctic Canada, Iceland, Greenland, Europe, China-Tibet, Antarctica, and the Himalayas, revealing substantial spatial variability. CDRs ranged from 46 to 4160 meq m⁻² yr⁻¹. Northwest American and Himalayan glaciers exhibited the highest CDRs, with the Himalayan denudation rate exceeding the global average by more than fourfold. The exceptionally high mean chemical weathering intensity (CWI) of 801 meq m⁻³ from the Himalayan glaciers indicate a wide range of geochemical and climatic conditions within the region, while Northwest American and Greenland glaciers show comparatively lower mean intensities (273 and 247 meq m⁻³, respectively) suggesting a consistent geochemical regime. Northwest American glaciers had the highest specific discharge rates, while Svalbard/Arctic Canada glaciers had the lowest, reflecting regional disparities influenced by climatic and geological factors. A Bonferroni post hoc test highlighted significant differences in specific discharge between Northwest American glaciers and two other basins, emphasizing their distinct hydrological behavior. Predictive modeling revealed a statistically significant but weak relationship between CDR and specific discharge (R² = 57%), suggesting that much of the variability in CDR cannot be explained by specific discharge alone. A regression coefficient of 382 meq m⁻² yr⁻¹ indicates that CDR increases with glacier discharge, although basin-specific analyses showed minimal variation in this relationship across regions. Svalbard/Arctic Canada, Antarctic, Greenlandic, Icelandic, and European Alpine glaciers displayed lower CDRs, which varied depending on underlying lithology, with higher rates observed in carbonate and basaltic terrains compared to other lithologies. We hypothesize that glacier retreat enhances the downward progression of the weathering reaction front, increasing CDR, particularly in rapidly retreating glaciers. Full article

(This article belongs to the Special Issue Climate Change Impacts on Water Resources and Ecosystem Dynamics in Mountainous and Cold-Region Ecosystems)

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22 pages, 7906 KB

Open AccessEditor’s ChoiceArticle

Analysis of Flood Risk in Ulsan Metropolitan City, South Korea, Considering Urban Development and Changes in Weather Factors

by Changjae Kwak, Junbeom Jo, Jihye Han, Jungsoo Kim and Sungho Lee

Water 2025, 17(19), 2800; https://doi.org/10.3390/w17192800 - 23 Sep 2025

Cited by 3 | Viewed by 1888

Abstract

Urban flood damage is increasing globally, particularly in major cities. Factors contributing to flood risk include urban environmental changes, such as watershed development and precipitation variations caused by climate change. Rapid urbanization and weather anomalies further complicate flood management and damage mitigation. Additionally, [...] Read more.

Urban flood damage is increasing globally, particularly in major cities. Factors contributing to flood risk include urban environmental changes, such as watershed development and precipitation variations caused by climate change. Rapid urbanization and weather anomalies further complicate flood management and damage mitigation. Additionally, detailed analyses at small spatial units (e.g., roads, buildings) remain insufficient. Hence, urban flood analysis considering such spatial variations is required. This study analyzed flood risk in Ulsan, Korea, under a severe flood scenario. Land cover changes from the 1980s to 2010s were examined in 10-year intervals, along with the frequency of heavy rainfall and high river water levels that trigger severe floods. Flood risk was structured as a matrix of likelihood and impact. The results revealed that land cover changes, influenced by development policies or regulations, had a minimal impact on urban flood risk, which is likely because effective drainage systems and stringent urban planning regulations mitigated their effects. However, the frequency and intensity of extreme precipitation events had a substantial effect. These findings were validated using a comparative analysis of an inundation damage trace map and flood range simulated by a physical model. The 10 m grid resolution and time-series likelihood-and-impact framework used in this study can inform budget allocation, resource mobilization, disaster prevention planning, and decision-making during disaster response efforts in major cities. Full article

(This article belongs to the Section Urban Water Management)

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31 pages, 5355 KB

Open AccessEditor’s ChoiceArticle

A Semi-Automated Framework for Flood Ontology Construction with an Application in Risk Communication

by Shenglin Li, Caleb Erickson, Michal Zajac, Xiaoming Guo, Qiuhua Duan and Jiaqi Gong

Water 2025, 17(19), 2801; https://doi.org/10.3390/w17192801 - 23 Sep 2025

Cited by 4 | Viewed by 2285

Abstract

Flash floods are increasingly frequent and severe, yet standard risk communication messages are often too generic and lack actionable guidance, causing them to be ignored. This research aims to enhance flood risk communication by first, developing a robust flood ontology using a novel [...] Read more.

Flash floods are increasingly frequent and severe, yet standard risk communication messages are often too generic and lack actionable guidance, causing them to be ignored. This research aims to enhance flood risk communication by first, developing a robust flood ontology using a novel semi-automated approach, and second, demonstrating its potential as a semantic foundation for translating complex data into clear, personalized public alerts. We introduce a semi-automated, human-in-the-loop ontology engineering strategy that integrates expert-defined schemas with Large Language Model (LLM)-driven expansion and refinement from authoritative sources. Evaluation results are twofold: (1) Technical metrics confirm our LLM-constructed ontology achieves superior relationship richness and expressiveness compared with existing disaster ontologies. (2) A proof-of-concept case study demonstrates the ontology’s potential by showing how its specific classes and relations (e.g., ‘neededForElderly’ relation linking the class ‘SpecialConsideration’ to ‘ElderlyCommunityMember’) can be used to generate targeted advice like “check on elderly neighbors”, transforming a generic alert into a clear and actionable message. Consequently, this research delivers two key contributions: a replicable and domain-adaptable methodology for semi-automated ontology construction and a practical demonstration of how such an ontology can bridge the critical gap between flood data and public understanding, empowering communities to respond more effectively. Full article

(This article belongs to the Special Issue Recent Advances in Flood Risk Assessment and Management)

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22 pages, 3169 KB

Open AccessEditor’s ChoiceArticle

Optimal Water Quality Sensor Placement in Water Distribution Systems: A Computationally Cost-Effective Genetic Algorithm Framework

by Elia Zanelli, Matteo Nicolini and Daniele Goi

Water 2025, 17(18), 2786; https://doi.org/10.3390/w17182786 - 21 Sep 2025

Cited by 4 | Viewed by 1599

Abstract

Despite advances in water treatment technologies and monitoring systems, contamination events in drinking water supply systems (DWSSs) still pose a threat to public health. Since timing is crucial in effectively mitigating impacts, the implementation of an early warning system (EWS) represents an optimal [...] Read more.

Despite advances in water treatment technologies and monitoring systems, contamination events in drinking water supply systems (DWSSs) still pose a threat to public health. Since timing is crucial in effectively mitigating impacts, the implementation of an early warning system (EWS) represents an optimal solution for securing the entire network. In this paper, we present a novel multi-objective approach based on the NSGA-II Genetic Algorithm (GA) for solving the sensor placement optimization (SPO) problem, aiming at defining the optimal water quality sensor system (WQSS) design. We start from the original formulation of the objective functions most commonly used in the literature, which aim, on the one hand, to reduce the impact and, on the other, to maximize the network coverage; such objective functions are rewritten in order to enable a comprehensive perspective of all potential contamination scenarios, including those that remain undetected by the WQSS. Furthermore, we address the issue of computational complexity, increasing with the size of the water distribution system (WDS), and we show that the proposed methodology is computationally cost-effective. Finally, we apply the methodology to two well-known benchmarking water distribution networks (WDNs), showcasing the capabilities and potential advantages it offers. Full article

(This article belongs to the Special Issue Monitoring and Assessment of Water Quality in Drinking Water Distribution Systems)

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18 pages, 2624 KB

Open AccessEditor’s ChoiceArticle

Comparative Assessment of Different Electrode Combinations for Phosphate Removal from Onsite Wastewater via Electrocoagulation

by Arif Reza, Xiumei Jian, Fanjian Zeng and Xinwei Mao

Water 2025, 17(18), 2764; https://doi.org/10.3390/w17182764 - 18 Sep 2025

Cited by 6 | Viewed by 1530

Abstract

Phosphorus (P) discharge from onsite wastewater treatment systems (OWTSs) poses a significant threat to water quality, contributing to eutrophication in nutrient-sensitive aquatic environments. In treated effluents, P predominantly exists as orthophosphate (PO₄³⁻), a highly bioavailable and reactive form that requires [...] Read more.

Phosphorus (P) discharge from onsite wastewater treatment systems (OWTSs) poses a significant threat to water quality, contributing to eutrophication in nutrient-sensitive aquatic environments. In treated effluents, P predominantly exists as orthophosphate (PO₄³⁻), a highly bioavailable and reactive form that requires targeted removal. This study evaluates the performance of electrocoagulation (EC) as a polishing step for PO₄³⁻ removal from OWTS effluents using 12 anode/cathode combinations comprising aluminum (Al), iron (Fe), magnesium (Mg), and stainless steel (SS). Key operational parameters, including treatment time, mixing speed, current density, pH, and initial PO₄³⁻ concentration, were systematically investigated when synthetic denitrified effluent (20 mg P/L) was treated. Based on the performance, the four most effective electrode combinations (Al/Al, Al/Mg, Fe/Al, and Mg/Mg), along with a commercial benchmark (Fe/Fe), were further tested under extended hydraulic retention times (up to 48 h) in both synthetic and real (denitrified) wastewater. To date, none of the studies have systematically evaluated all possible anode/cathode combinations involving multiple electrode materials under uniform operational conditions. The Al/Al and Mg/Mg EC systems achieved rapid and high PO₄³⁻ removal efficiencies (>95%), while Mg-based systems demonstrated sustained performance over prolonged treatment durations, especially in real wastewater. Bimetallic pairs such as Al/Mg and Fe/Al exhibited synergistic effects through enhanced coagulant generation and pH stabilization. The results indicated that PO₄³⁻ removal efficiency was strongly influenced by electrode material selection, hydrodynamic conditions, and wastewater compositions, underscoring the need to design EC systems based on site-specific water quality conditions in OWTSs. Full article

(This article belongs to the Special Issue Application of Electrochemical Technologies in Wastewater Treatment)

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22 pages, 4329 KB

Open AccessEditor’s ChoiceArticle

Fractal-Based Approach to Simultaneous Layout Routing and Pipe Sizing of Water Supply Networks

by Paweł Suchorab, Dariusz Kowalski and Małgorzata Iwanek

Water 2025, 17(18), 2745; https://doi.org/10.3390/w17182745 - 17 Sep 2025

Cited by 2 | Viewed by 1384

Abstract

The process of designing water distribution networks is divided into two main stages: network layout routing and pipe sizing. However, routing and sizing are not separate tasks—the shape of the network affects the diameters of the pipes, and vice versa. This paper presents [...] Read more.

The process of designing water distribution networks is divided into two main stages: network layout routing and pipe sizing. However, routing and sizing are not separate tasks—the shape of the network affects the diameters of the pipes, and vice versa. This paper presents an innovative fractal-based method, which enables the simultaneous layout routing and pipe sizing of water supply networks. The developed pipe routes and diameters selected according to the method are mathematically justified; the selection considers the total length of the pipes, the number of rotation angles of the base section, the cost of the water supply system construction and the priority of water supply to individual customers. The novelty of the method lies in the possibility of carrying out the processes of routing and sizing of the network in a recursive manner by the adoption of the principles of fractal geometry and Murray’s law. The method was tested under the conditions of a synthetic settlement. The obtained results enable us to conclude that the method is universal and suitable for shaping water supply networks, while determining the pipes’ diameters, both under the conditions of a single- and multi-sided water supply source. Full article

(This article belongs to the Special Issue Advances in Management and Optimization of Urban Water Networks)

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23 pages, 1282 KB

Open AccessEditor’s ChoiceArticle

An Integrated Water Resources Solution for a Wide Arid to Semi-Arid Urbanized Coastal Tropical Region with Several Topographic Challenges—A Case Study

by António Freire Diogo and António Luís Oliveira

Water 2025, 17(18), 2750; https://doi.org/10.3390/w17182750 - 17 Sep 2025

Cited by 4 | Viewed by 1983

Abstract

Pressure on fresh water resources has been aggravated in recent decades, basically due to population growth, rapid urbanization, and global warming. Integrated engineering solutions and the circular economy, considering the urban water cycle as a whole, are becoming fundamental, particularly in arid and [...] Read more.

Pressure on fresh water resources has been aggravated in recent decades, basically due to population growth, rapid urbanization, and global warming. Integrated engineering solutions and the circular economy, considering the urban water cycle as a whole, are becoming fundamental, particularly in arid and semi-arid regions under permanent or recurrent hydric deficit. This study aims to develop and present an integrated engineering solution for water supply, wastewater collection, and treated wastewater reuse for landscape irrigation in a large, topographically complex, and arid to semi-arid coastal urban region at the south of Santiago Island, Cape Verde. The region is one of the driest and most arid of the Island, with a current average annual precipitation between about 100 and 200 mm, and has very limited underground water resources. The main study area, with about 600 ha, has altitudes ranging from values close to sea level up to about 115 m and has several topographic difficulties, including several relatively rugged zones. The devised water supply system considers four altimetric distribution levels, three main reservoirs connected to each other by a serial system of pipelines with successive pumping, a fourth downstream reservoir for pressure balance in one of the levels, and desalinated water as the source. The sanitary sewer pipes of the urbanizations drain to an interceptor system that operates predominantly in open channel flow in a closed pipe. The long interceptor crosses laterally along the coast several very dug valleys in the path to the Praia Wastewater Treatment Plant in the east, and requires several conduits working under pressure for the crossings, either lifting or governed by gravity. The under-pressure pipeline system of recycled water is partially forced and partially ruled by gravity and transports the treated wastewater from the plant in the opposite direction of the interceptor to a natural reservoir or lake located in the region of urbanizations and the main green spaces to be irrigated. The conceived design of the interceptor and recycled water pipeline minimizes the construction and operation costs, maximizing their hydraulic performance. Full article

(This article belongs to the Special Issue Research on Water Supply Systems and on the Treatment and Recovery of Wastewater and Stormwater)

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19 pages, 5419 KB

Open AccessEditor’s ChoiceArticle

Runoff Forecast Model Integrating Time Series Decomposition and Deep Learning for the Short Term: A Case Study in the Weihe River Basin, China

by Ruijia Ma, Qiang An, Liu Liu, Yongming Cheng and Xingcai Liu

Water 2025, 17(18), 2718; https://doi.org/10.3390/w17182718 - 14 Sep 2025

Cited by 4 | Viewed by 2118

Abstract

Accurate prediction of river runoff is significant for flood control, water resource allocation, and basin ecological management. Despite the promise of integrating signal decomposition with deep learning, current decomposition-based hybrid models face critical forward data contamination: decomposition algorithms improperly access future test data [...] Read more.

Accurate prediction of river runoff is significant for flood control, water resource allocation, and basin ecological management. Despite the promise of integrating signal decomposition with deep learning, current decomposition-based hybrid models face critical forward data contamination: decomposition algorithms improperly access future test data in full-series applications, artificially inflating prediction accuracy. In contrast, the stepwise decomposition method currently proposed leads to high computational costs. To address this limitation, we introduce a novel framework integrating segmented decomposition sampling with a multi-input neural network. Specifically, a hybrid forecasting model combining Seasonal-Trend decomposition using Loess (STL) and Convolutional Long Short-Term Memory (CNN-LSTM) networks was implemented for daily runoff estimation. Method reliability was evaluated using historical runoff data from Huaxian Station in China’s Weihe River Basin, with comparative experiments conducted against established single and hybrid models. The results showed that the proposed framework can effectively avoid future information leakage and simultaneously improve prediction accuracy. For 1–3-day-ahead Nash-Sutcliffe efficiency (NSE) at Huaxian Station, the STL-CNN-LSTM model achieved values of 0.96, 0.83, and 0.80, respectively—representing improvements of 5.49%, 5.06%, and 12.68% over the VMD-CNN-LSTM model. This STL-based configuration outperformed the standalone LSTM counterpart by 23.08%, 9.21%, and 17.65% in NSE, respectively. Therefore, the proposed framework, which incorporates the segmented decomposition sampling method and a multi-input neural network, proves to be both practical and reliable. Full article

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

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22 pages, 5102 KB

Open AccessEditor’s ChoiceArticle

Spatio–Temporal Dynamics of Groundwater Levels in the Piedmont Po Plain (NW Italy): Impacts of Climate Change and Land Use

by Elena Egidio, Domenico Antonio De Luca, Daniele Cocca and Manuela Lasagna

Water 2025, 17(18), 2712; https://doi.org/10.3390/w17182712 - 13 Sep 2025

Cited by 1 | Viewed by 1571

Abstract

This study analyses spatio–temporal trends in groundwater level (GWL) across the Piedmont Po Plain (NW Italy), aiming to assess the impacts of climate change (CC) and human drivers on regional groundwater systems. Data were collected from a network of automated monitoring wells over [...] Read more.

This study analyses spatio–temporal trends in groundwater level (GWL) across the Piedmont Po Plain (NW Italy), aiming to assess the impacts of climate change (CC) and human drivers on regional groundwater systems. Data were collected from a network of automated monitoring wells over the period 2010–2022, supported by meteorological records from regional weather stations. Results indicate a widespread decline in GWL, with an average of −4.32 cm/y and a maximum of −16.74 cm/y in the time period observed, particularly in recent years. These trends align with decreasing precipitation patterns observed in the region. However, deviations from this general behaviour are also identified. More specifically, local land use practices—specifically rice field and irrigation—may be artificially maintaining GWL. Moreover, hydrometric level data from the main rivers of the region were analysed to evaluate potential interactions with GWL variations. This comparison showed that, in general, no clear correspondence exists between river level fluctuations and groundwater dynamics, except in cases where monitoring wells are located within 50 m of a river channel. In addition, this study was compared with a previous study on the same area concerning temperature variations in groundwater, which allowed for an understanding of both the qualitative and quantitative impacts of CC on the groundwater in the area. The combined analysis highlights the interplay between CC and anthropogenic influences, emphasising the need for integrated groundwater management strategies that account for both climate variability and land use dynamics. Furthermore, the seasonal analysis of GWL revealed a clear hydrological cycle shaped by irrigation activity. In particular, the occurrence of GWL peaks during summer (irrigation season) confirms the role of irrigation in controlling aquifer behaviour in agricultural areas. The absence of a general correlation with river stage, combined with the occurrence of GWL peaks during summer (irrigation season), confirms that irrigation is the main driver of GWL fluctuations over the study period. This finding is critical for the accurate interpretation of groundwater responses and for developing effective and sustainable water management strategies in intensively cultivated regions. Full article

(This article belongs to the Section Hydrogeology)

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17 pages, 3001 KB

Open AccessEditor’s ChoiceArticle

Possible Effects of Pesticide Washout on Microalgae Growth

by Agnes Nadudvari, Michael Schagerl and Shiela Mae Ancheta

Water 2025, 17(18), 2716; https://doi.org/10.3390/w17182716 - 13 Sep 2025

Cited by 2 | Viewed by 2674

Abstract

Aquatic ecosystems are threatened by various anthropogenic activities, including those exacerbated by pesticides leaching from agricultural lands. Although legislation and regulations regarding pesticides aim to eliminate the risk of eutrophication and pollution, only a few studies have examined the impact of these substances [...] Read more.

Aquatic ecosystems are threatened by various anthropogenic activities, including those exacerbated by pesticides leaching from agricultural lands. Although legislation and regulations regarding pesticides aim to eliminate the risk of eutrophication and pollution, only a few studies have examined the impact of these substances on non-target organisms, such as microalgae, which are highly involved in biogeochemical cycles and critical for ecosystem integrity. We studied the effect of the agricultural insecticide Teppeki based on flonicamid, the fungicide Ortiva with azoxystrobin, and the herbicide Basar with (S)-metolachlor on the green microalga Chlorella vulgaris and the cyanobacterium Synechococcus leopoliensis. Ortiva and Basar were more toxic at lower doses than Teppeki, with (S)-metolachlor demonstrating the most instantaneous and potent inhibition. Half maximum effective concentration (EC₅₀) values confirmed the strong inhibitory effect of the herbicide on both strains on days 3 and 8, and highlight the differing temporal responses, especially for Ortiva. This observed pattern of toxicity is consistent with pulse-amplitude-modulated fluorescence measurements of photosystem II, which indicate that both species are more sensitive to (S)-metolachlor and azoxystrobin than to flonicamid. We claim that the side effects of pesticides on non-target organisms must be given more attention. It is well established that herbicides can impair photosynthetic organisms such as microalgae, but pesticides targeting other pests can also cause adverse effects on these communities. Such unwanted side effects are directly related not only to the reduction of biodiversity, but also to human health. Full article

(This article belongs to the Special Issue The Toxicology and Risk Assessment of Agricultural Runoff and Aquaculture Pollution)

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15 pages, 1918 KB

Open AccessEditor’s ChoiceArticle

Efficiency and Mechanism of a Hollow Carbon-Based Single-Atom Iron Catalyst in Activating Periodate for Bisphenol a Degradation

by Chen Ling, Mengyue Yuan, Shang Gao, Yuzhu Xue and Yuwei Pan

Water 2025, 17(18), 2705; https://doi.org/10.3390/w17182705 - 13 Sep 2025

Cited by 2 | Viewed by 1401

Abstract

Developing efficient and recyclable periodate (PI)-based advanced oxidation processes (AOPs) for the removal of emerging organic pollutants (EOPs) has attracted considerable attention. However, the structure–activity relationship of single-atom catalyst in PI-AOP systems remains poorly understood. In this study, a hollow carbon-supported single-Fe atom [...] Read more.

Developing efficient and recyclable periodate (PI)-based advanced oxidation processes (AOPs) for the removal of emerging organic pollutants (EOPs) has attracted considerable attention. However, the structure–activity relationship of single-atom catalyst in PI-AOP systems remains poorly understood. In this study, a hollow carbon-supported single-Fe atom catalyst (HCFe800) was synthesized and applied for PI activation toward bisphenol A (BPA) degradation. Under neutral pH and ambient temperature, HCFe800 enabled complete removal of BPA within 1 min, achieving a degradation rate constant (k) of 5.094 min⁻¹—approximately 3 and 10 times higher than that of Fe-free and solid control catalysts, respectively. After normalization, the apparent degradation rate constant was 1–3 orders of magnitude greater than those of previously reported catalysts. The optimized Fe doping amount and pyrolysis temperature facilitated the formation of atomically dispersed FeN₄ sites, which outperformed Fe clusters and iron oxides in catalytic activity. The hollow porous structure further enhanced the exposure of active sites, contributing to the exceptional performance. The HCFe800/PI system remained highly effective across broad pH (3–7) and temperature (5–35 °C) ranges and in the presence of 100-fold concentrations of common inorganic ions. Mechanistic studies revealed that the main reactive species were ¹O₂, O₂^•−, and IO₃^•, with negligible involvement of high-valent Fe species. Eight less-toxic BPA degradation products were identified. Moreover, the system was extendable to various other EOPs and exhibited excellent recyclability via thermal regeneration. This work provided fundamental insights into designing and applying single-atom catalysts for PI-based advanced treatment of EOPs. Full article

(This article belongs to the Special Issue The Occurrence, Fate and Removal of Emerging Contaminants in Wastewater, 2nd Edition)

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25 pages, 6532 KB

Open AccessEditor’s ChoiceArticle

Representing Small Shallow Water Estuary Hydrodynamics to Uncover Litter Transport Patterns

by Lubna Benchama Ahnouch, Frans Buschman, Helene Boisgontier, Ana Bio, Luis R. Vieira, Sara C. Antunes, Gary F. Kett, Isabel Sousa-Pinto and Isabel Iglesias

Water 2025, 17(18), 2698; https://doi.org/10.3390/w17182698 - 12 Sep 2025

Cited by 3 | Viewed by 1830

Abstract

Plastic pollution is an increasing global concern, with estuaries being especially vulnerable as transition zones between freshwater and marine systems. These ecosystems often accumulate large amounts of waste, affecting wildlife and water quality. This study focuses on analysing the circulation patterns of the [...] Read more.

Plastic pollution is an increasing global concern, with estuaries being especially vulnerable as transition zones between freshwater and marine systems. These ecosystems often accumulate large amounts of waste, affecting wildlife and water quality. This study focuses on analysing the circulation patterns of the Ave Estuary, a small, shallow system on Portugal’s north-western coast, and their influence on litter transport and distribution. This site was selected for installing an aquatic litter removal technology under the EU-funded MAELSTROM project. A 2DH hydrodynamic model using Delft3D FM, coupled with the Wflow hydrological model, was implemented and validated. Various scenarios were simulated to assess estuarine dynamics and pinpoint zones prone to litter accumulation and flood risk. The results show that tidal action and river discharge mainly drive the estuary’s behaviour. Under low discharge, floating litter should be mostly transported toward the ocean, while high discharge conditions should result in litter movement at all depths due to stronger currents. High water levels and flooding occur mainly upstream and in specific low-lying areas near the mouth. Low-velocity zones, which can favour litter accumulation, were found around the main channel and on the western margin near the estuary’s mouth, even during high flows. These findings highlight persistent accumulation zones, even under extreme event conditions. Full article

(This article belongs to the Special Issue Marine Plastic Pollution: Recent Advances and Future Challenges)

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17 pages, 6228 KB

Open AccessEditor’s ChoiceArticle

Three-Dimensional Numerical Simulation of Flow Through an Inclined Bar Rack with Surface Bypasses: Influence of Inlet Velocity Conditions and Comparison with Field Measurements

by Fatma Lemkecher, Guillaume Bon, Ludovic Chatellier, Laurent David and Dominique Courret

Water 2025, 17(18), 2704; https://doi.org/10.3390/w17182704 - 12 Sep 2025

Cited by 2 | Viewed by 865

Abstract

To mitigate the impact of hydroelectric power plants on downstream fish migration, fish-friendly intakes, combining a low bar spacing rack and several bypasses, are implemented. There are still sites that can be improved thanks to a better bypass design. For this purpose, Computational [...] Read more.

To mitigate the impact of hydroelectric power plants on downstream fish migration, fish-friendly intakes, combining a low bar spacing rack and several bypasses, are implemented. There are still sites that can be improved thanks to a better bypass design. For this purpose, Computational Fluid Dynamics (CFD) can be a useful tool, even if such devices are still uncommon. This paper investigates the use of a 3D model based on the Reynolds-Averaged Navier–Stokes (RANS) equation for a single phase to simulate the flow in a real-scale water intake equipped with an inclined bar rack and three surface bypasses. The results of numerical simulations are compared to in situ measurements of flow velocities at four cross-sections along the rack, gauging the discharge flowing into the bypasses. The simulated velocities are in accordance with the velocities measured in situ, with a mean square error for the longitudinal velocity (

v_{x}

) of 0.034 (m²/s²) for the initial simulation and 0.021 (m²/s²) for the improved simulation. The split of the total bypass discharge between the three bypass entrances was satisfyingly predicted by the simulation with the true inlet velocity condition, showing the significant influence of upstream flow non-uniformity. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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22 pages, 2358 KB

Open AccessEditor’s ChoiceArticle

Shifts in Precipitation Variability near the Danube Delta Biosphere Reserve (1965–2019)

by Alina Bărbulescu and Cristian Ștefan Dumitriu

Water 2025, 17(18), 2692; https://doi.org/10.3390/w17182692 - 11 Sep 2025

Cited by 3 | Viewed by 1172

Abstract

Nowadays, climate change is one of the significant threats humanity faces. Many researchers have documented its effects on water availability and vulnerable systems. This study examines the long-term precipitation record (1965–2019) from the Tulcea station, located just 4 km from the Danube Delta [...] Read more.

Nowadays, climate change is one of the significant threats humanity faces. Many researchers have documented its effects on water availability and vulnerable systems. This study examines the long-term precipitation record (1965–2019) from the Tulcea station, located just 4 km from the Danube Delta Biosphere Reserve (DDBR), to evaluate the impact of climate change on precipitation variability, which can significantly affect biodiversity in this protected area. We integrated change point detection (CPD), stationarity tests, trend analysis, and series decomposition to characterize shifts and patterns in the time series. The Lee & Heghinian test detected a change point (CP) in all data series, whereas the Hubert segmentation methods and Cumulative Sum Method (CUSUM) found fewer series that present at least a CP. The Mann–Kendall (MK) trend test and Innovative Trend Analysis (ITA) indicated an increasing trend in the annual, monthly, and October precipitation series. The Seasonal-Trend decomposition using Loess STL decomposition found the highest seasonality indices in June and July. The Ensemble Empirical Mode Decomposition (EEMD) emphasizes a substantial difference in the seasonal cycle. The results indicate a high variability in the precipitation pattern, with periods of high precipitation followed by dry periods. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

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18 pages, 2146 KB

Open AccessEditor’s ChoiceArticle

Effect of Carbon Dioxide on the Growth and Nutrient Uptake of the Microalgae Chlorella sorokiniana from Digestate

by Thomas L. Palikrousis, Sotirios D. Kalamaras and Petros Samaras

Water 2025, 17(18), 2674; https://doi.org/10.3390/w17182674 - 10 Sep 2025

Cited by 7 | Viewed by 3632

Abstract

Microalgae are photosynthetic microorganisms capable of capturing CO₂ from both the atmosphere and industrial emissions while producing valuable biomass. Among the various factors influencing microalgal growth, CO₂ availability plays a critical role. This study examined how different CO₂ flow rates [...] Read more.

Microalgae are photosynthetic microorganisms capable of capturing CO₂ from both the atmosphere and industrial emissions while producing valuable biomass. Among the various factors influencing microalgal growth, CO₂ availability plays a critical role. This study examined how different CO₂ flow rates affect the growth and nutrient assimilation of Chlorella sorokiniana cultivated in diluted digestate from a biogas plant with nitrogen concentrations up to 5 g/L. Results showed that biomass productivity increased with CO₂ supply up to a threshold, beyond which it declined. The highest mean productivity was observed at a CO₂ flow rate of 0.025 LPM, which did not differ significantly from the 0.050 LPM treatment, indicating comparable performance. In contrast, the highest flow rate (0.100 LPM) led to reduced productivity, although still higher than the control (no CO₂). A similar trend was observed in ammonium removal, whereas phosphorus uptake remained relatively unaffected by CO₂ supply. Overall, elevated CO₂ levels appeared to shift microalgal metabolism towards biomass with lower nitrogen content and increased lipid and carbohydrate accumulation. Full article

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24 pages, 17194 KB

Open AccessEditor’s ChoiceArticle

Assessing the Distribution and Stability of Groundwater Climatic Refugia: Cliff-Face Seeps in the Pacific Northwest

by Sky T. Button and Jonah Piovia-Scott

Water 2025, 17(18), 2659; https://doi.org/10.3390/w17182659 - 9 Sep 2025

Cited by 1 | Viewed by 1490

Abstract

Microrefugia can be critical in mediating biological responses to climate change, but the location and characteristics of these habitats are often poorly understood. Groundwater-dependent ecosystems (GDEs) represent critical microrefugia for species dependent on cool, moist habitats. However, knowledge of the distribution and stability [...] Read more.

Microrefugia can be critical in mediating biological responses to climate change, but the location and characteristics of these habitats are often poorly understood. Groundwater-dependent ecosystems (GDEs) represent critical microrefugia for species dependent on cool, moist habitats. However, knowledge of the distribution and stability of GDE microrefugia remains limited. This challenge is typified in the Pacific Northwest, where poorly studied cliff-face seeps harbor exceptional biodiversity despite their diminutive size (e.g., ~1–10 m width). To improve knowledge about these microrefugia, we regionally modeled their distribution and stability. We searched for cliff-face seeps across 1608 km of roads, trails, and watercourses in Washington and Idaho, while monitoring water availability plus air and water temperatures at selected sites. We detected 457 seeps through an iterative process of surveying, modeling, ground-truthing, and then remodeling the spatial distribution of seeps using boosted regression trees. Additionally, we used linear and generalized linear models to identify factors linked to seep thermal and hydrologic stability. Seeps were generally most concentrated in steep and low-lying areas (e.g., edges of canyon bottoms), and were also positively associated with glacial drift, basalt or graywacke bedrock types, high average slope within 300 m, and low average vapor pressure deficit. North-facing slopes were the best predictor of stable air and water temperatures and perennial seep discharge; low-lying areas also predicted stable seep water temperatures. These findings improve possibilities to manage seep microrefugia in the Pacific Northwest and safeguard their associated biodiversity under climate change. Lastly, our iterative method adapts techniques commonly used in species distribution modeling to provide an innovative framework for identifying inconspicuous microrefugia. Full article

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

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16 pages, 6026 KB

Open AccessEditor’s ChoiceArticle

Interannual Variations in Water Budget and Vegetation Coverage Dynamics in Desert Ecosystems of Heihe River Basin

by Jiayin Liu, Wenyang Cao, Yuan Yuan, Siying Li and Pei Wang

Water 2025, 17(18), 2660; https://doi.org/10.3390/w17182660 - 9 Sep 2025

Cited by 2 | Viewed by 1154

Abstract

Climate change intensifies the challenges surrounding water cycling and vegetation dynamics in arid desert ecosystems, calling for detailed observations to decode adaptive plant strategies and support restoration efforts. This study analyzes interannual variations in water budgets and vegetation coverage in two distinct desert [...] Read more.

Climate change intensifies the challenges surrounding water cycling and vegetation dynamics in arid desert ecosystems, calling for detailed observations to decode adaptive plant strategies and support restoration efforts. This study analyzes interannual variations in water budgets and vegetation coverage in two distinct desert systems—K. foliatum (midstream) and R. songarica (downstream)—within the Heihe River Basin from 2016 to 2021. We uncover a pronounced ecohydrological contrast: the K. foliatum ecosystem displays substantial soil moisture variability alongside high precipitation and evapotranspiration rates, leading to a soil water deficit. In contrast, the R. songarica ecosystem maintains minimal moisture fluctuation under extreme aridity, yet records a slight water surplus. Notably, vegetation coverage in K. foliatum closely correlates with soil water storage, precipitation, and evapotranspiration, whereas R. songarica exhibits no significant hydrological coupling, implying a pulsed response to episodic rainfall. Groundwater recharge emerges as a key compensatory mechanism against rainfall shortages in midstream regions. These findings underscore the need for region-specific management—prioritizing groundwater conservation downstream and intelligent irrigation regulation midstream—offering a science-backed pathway for restoring and managing water resources in arid inland basins under climate change. Full article

(This article belongs to the Section Ecohydrology)

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20 pages, 8416 KB

Open AccessEditor’s ChoiceArticle

Extreme Short-Duration Rainfall and Urban Flood Hazard: Case Studies of Convective Events in Warsaw and Zamość, Poland

by Bartłomiej Pietras and Robert Pyrc

Water 2025, 17(18), 2671; https://doi.org/10.3390/w17182671 - 9 Sep 2025

Cited by 3 | Viewed by 3153

Abstract

This study investigates two extreme convective rainfall events that struck Poland in August 2024, affecting Warsaw (Okęcie) on 19 August and Zamość on 21 August. The aim is to evaluate the meteorological background, intensity, and spatial characteristics of these short-duration storms. We used [...] Read more.

This study investigates two extreme convective rainfall events that struck Poland in August 2024, affecting Warsaw (Okęcie) on 19 August and Zamość on 21 August. The aim is to evaluate the meteorological background, intensity, and spatial characteristics of these short-duration storms. We used high-resolution meteorological observations, radar imagery, and satellite data provided by the Institute of Meteorology and Water Management (IMGW-PIB). The storms were analyzed using temporal rainfall profiles, Chomicz α index classification, and comparison with World Meteorological Organization (WMO) thresholds for extreme precipitation. Both events exceeded national and international criteria for torrential rainfall. In Zamość, over 88.3 mm of rain fell within one hour, and 131.3 mm within three hours—ranking this episode among the most intense short-duration rainfall events in the region. Convective organization patterns, including multicellular clustering and convective training, were identified as key factors enhancing rainfall intensity. The results demonstrate the diagnostic value of combining national indices with global benchmarks in rainfall assessment. These findings support further integration of convection-permitting models and real-time nowcasting into urban hydrometeorological warning systems. Full article

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22 pages, 2881 KB

Open AccessEditor’s ChoiceReview

Water, Sanitation, and Hygiene in Urban Areas: A Review

by Gabriela Souza, Cristina Santos and Érico Lisboa

Water 2025, 17(17), 2634; https://doi.org/10.3390/w17172634 - 6 Sep 2025

Cited by 6 | Viewed by 6167

Abstract

This paper provides a comprehensive bibliographic and bibliometric review of water, sanitation, and hygiene (WASH) in global urban areas, employing the Proknow-C methodology. The study categorizes WASH into four main themes: sustainability, urban areas, indicators and index, and urban planning, allowing for a [...] Read more.

This paper provides a comprehensive bibliographic and bibliometric review of water, sanitation, and hygiene (WASH) in global urban areas, employing the Proknow-C methodology. The study categorizes WASH into four main themes: sustainability, urban areas, indicators and index, and urban planning, allowing for a detailed analysis of several multidimensional aspects. The review underscores the importance of providing basic infrastructure to adopt an integrated, sustainable, and socially inclusive approach, showcasing the resilience and adaptability of the WASH sector in tackling the dynamic challenges of urbanization. It is noticeable that the WASH area has undergone significant development, moving from a focus primarily on infrastructure to a more holistic approach. In general, the WASH framework is globally characterized by high irregularity/inequality in provision and access. The relationship between urban vulnerabilities and WASH is very clear, but also multifaceted and complex, and there is a crucial need to combine behavior change with infrastructure development while addressing economic challenges and prioritizing investments in WASH. The improvement of WASH conditions in urban areas should focus the interplay between urban development policies and the provision of WASH services, while focusing also on the role of multi-sectoral collaboration, stakeholder engagement, and policy implementation in overcoming barriers to effective WASH delivery. Full article

(This article belongs to the Section Water and One Health)

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30 pages, 2870 KB

Open AccessEditor’s ChoiceArticle

Hybrid Explainable AI Framework for Predictive Maintenance of Aeration Systems in Wastewater Treatment Plants

by Daniel Voipan, Andreea Elena Voipan and Marian Barbu

Water 2025, 17(17), 2636; https://doi.org/10.3390/w17172636 - 6 Sep 2025

Cited by 4 | Viewed by 3798

Abstract

Aeration systems are among the most energy-intensive components of wastewater treatment plants (WWTPs), consuming up to 75% of total electricity while being prone to performance degradation caused by diffuser fouling and pressure losses. Traditional maintenance strategies are largely reactive or preventive, leading to [...] Read more.

Aeration systems are among the most energy-intensive components of wastewater treatment plants (WWTPs), consuming up to 75% of total electricity while being prone to performance degradation caused by diffuser fouling and pressure losses. Traditional maintenance strategies are largely reactive or preventive, leading to inefficient interventions, higher operational costs, and limited fault anticipation. This study addresses the need for an advanced predictive maintenance framework capable of early detection and differentiation of multiple aeration system faults. Using the Benchmark Simulation Model No. 2 (BSM2), two representative degradation scenarios—acute airflow pressure loss and chronic diffuser fouling—were simulated to generate a labeled dataset. A hybrid machine learning approach was developed, combining Random Forest-based feature selection with Long Short-Term Memory (LSTM) neural networks for temporal, multi-label fault classification. To enhance interpretability and operator trust, SHapley Additive exPlanations (SHAP) were applied to quantify feature contributions and provide transparent model predictions. The results show that the proposed framework achieves over 94% detection accuracy and provides early warnings compared to static threshold-based methods. The integration of explainable AI ensures actionable insights for maintenance planning. This approach supports more energy-efficient, reliable, and sustainable operation of WWTP aeration systems and offers a benchmark methodology for future predictive maintenance research. Full article

(This article belongs to the Special Issue AI, Machine Learning and Digital Twin Applications in Water)

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22 pages, 2756 KB

Open AccessEditor’s ChoiceArticle

Integrating Ecotoxicological Assessment to Evaluate Agricultural Impacts on Aquatic Ecosystems: A Case Study of the Lage Reservoir (Mediterranean Region)

by Adriana Catarino, Clarisse Mourinha, Mariana Custódio, Pedro Anastácio and Patrícia Palma

Water 2025, 17(17), 2642; https://doi.org/10.3390/w17172642 - 6 Sep 2025

Cited by 2 | Viewed by 1931

Abstract

This study analyzed the use of a toolbox to evaluate the impact of agricultural activity on the water quality/status classification of a hydro-agricultural reservoir (Lage reservoir, Southern Portugal). The framework integrated the quantification of a group of 51 pesticides and ecotoxicological endpoints with [...] Read more.

This study analyzed the use of a toolbox to evaluate the impact of agricultural activity on the water quality/status classification of a hydro-agricultural reservoir (Lage reservoir, Southern Portugal). The framework integrated the quantification of a group of 51 pesticides and ecotoxicological endpoints with organisms from different trophic categories (the bacterium Aliivibrio fischeri, the microalga Pseudokirchneriella subcapitata, and the crustaceans Daphnia magna and Thamnocephalus platyurus) at two sampling points in the reservoir (Lage (L) and Lage S (LS)) between 2018 and 2020. Over the three-year study, we quantified 36 of the 51 pesticides analyzed in the Lage reservoir. Total concentrations increased successively from 0.95 µg L⁻¹ to 1.99 and 2.66 µg L⁻¹. Among these, the pesticides most frequently detected were terbuthylazine (100% of detection) and metolachlor (83% of detection), with maximum concentrations of 115.6 and 85.5 µg L⁻¹, respectively. Samples from the LS site showed higher toxicity, where A. fischeri presented 30 min EC₅₀ values of 39–51%. Microalgae growth was consistently inhibited, correlating with agricultural activity, mainly the application of herbicides and insecticides, while D. magna feeding rates revealed no inhibitory effects in the Lage samples. The results highlight that although the detected pesticide levels were below regulatory limits, they still induced toxic effects in the tested organisms. The potential ecological status of the reservoir was classified as moderate, and the integration of the proposal toolbox allowed refinement of the classification of water status. The results demonstrated that this integrated approach, combining multiple assessment methods, establishes a more robust water quality evaluation methodology, allowing it to be used as a tool complementary to the WFD methodology. This proposal not only identified existing pollution impacts but also enabled (1) early detection of the toxic effects of emerging contaminants to prevent ecological damage; (2) proactive management through specific actions to restore water status; and (3) improved sustainable water use. Full article

(This article belongs to the Special Issue Pesticides in Water and Health)

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16 pages, 3525 KB

Open AccessEditor’s ChoiceArticle

A Decade of Change in the Floodplain Lake: Does Zooplankton Yield or Resist?

by Anita Galir, Filip Stević, Karla Čmelar, Dubravka Špoljarić Maronić, Tanja Žuna Pfeiffer and Nikolina Bek

Water 2025, 17(17), 2638; https://doi.org/10.3390/w17172638 - 6 Sep 2025

Cited by 1 | Viewed by 1671

Abstract

Natural ecosystems, especially those regulated by floods, are sensitive to prolonged temperature fluctuations that affect hydrology and the lateral connection between the river and its floodplain. Here, we analyzed a series of zooplankton data collected monthly from 2007 to 2016 during the ice-free [...] Read more.

Natural ecosystems, especially those regulated by floods, are sensitive to prolonged temperature fluctuations that affect hydrology and the lateral connection between the river and its floodplain. Here, we analyzed a series of zooplankton data collected monthly from 2007 to 2016 during the ice-free period in Kopački Rit Nature Park in the Middle Danube, an area important as a food source and nursery area for fish stocks in the Danube. The aim was to find out how the long-term change in temperature and fluctuating environmental parameters affect the succession of zooplankton in the warmer (from April to September) and colder parts of the year (from October to March). Throughout the decade, total nitrogen concentrations showed significant differences between years, with an increase since 2012. Despite the increase in nitrogen levels and the expected increase in primary production, the higher nitrogen levels were accompanied by lower zooplankton biomass. A significant difference was found between the values of the zooplankton geometric mean index, with 73% of the variance explained by the difference between groups. In general, a trend toward a significant decrease in zooplankton biomass, with a simultaneous increase in the number of species and high turnover rates, was observed throughout the decade. Full article

(This article belongs to the Special Issue Freshwater Ecosystems—Biodiversity and Protection: 2nd Edition)

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25 pages, 2306 KB

Open AccessEditor’s ChoiceArticle

A Deterministic Combinatorial Approach to Investigate Interactions of Soil Hydraulic Parameters on River Flow Modelling

by Dhiego da Silva Sales, David de Andrade Costa, Jader Lugon Junior, Ramiro Joaquim Neves and Antônio José da Silva Neto

Water 2025, 17(17), 2627; https://doi.org/10.3390/w17172627 - 5 Sep 2025

Cited by 2 | Viewed by 1469

Abstract

Hydrological modeling is essential for the sustainable management of watershed systems. Physically based models like MOHID-Land simulate soil water dynamics using Richards’ equation, parameterized through the van Genuchten–Mualem (VGM) model. Although the sensitivity of individual VGM parameters—residual water content (

θ_{r}

), [...] Read more.

Hydrological modeling is essential for the sustainable management of watershed systems. Physically based models like MOHID-Land simulate soil water dynamics using Richards’ equation, parameterized through the van Genuchten–Mualem (VGM) model. Although the sensitivity of individual VGM parameters—residual water content (

θ_{r}

), saturated water content (

θ_{s}

), pore size distribution (

n

), inverse of air entry pressure (

α

), and saturated hydraulic conductivity (

K_{s a t}

)—is well documented, their combined effects remain underexplored. This study assessed both isolated and joint impacts of these parameters through a deterministic ±10% perturbation scheme, resulting in 31 unique parameter combinations. Model performance was evaluated using the Nash–Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS). Full-parameter interaction achieved the best results (NSE = 0.50, PBIAS = 25.32), compared to the uncalibrated baseline (NSE = 0.01, PBIAS = 34.06). The pair

θ_{s}

and

n

emerged as the most influential. Adding secondary parameters to this core pair yielded only marginal performance gains, while removing them from the full set caused similarly marginal declines. These findings reveal a hierarchical sensitivity structure, emphasizing

θ_{s}

and

n

as key targets for calibration. Prioritizing this pair enables a more efficient soil calibration process, preserving model accuracy while reducing computational cost by limiting parameter space exploration. Full article

(This article belongs to the Special Issue Soil–Water Interaction and Management)

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28 pages, 1495 KB

Open AccessEditor’s ChoiceReview

Low-Cost Adsorbents for the Removal of Pharmaceuticals from Surface Waters

by Erwin Onyekachukwu, Heather Nesbitt, Svetlana Tretsiakova-McNally and Heather Coleman

Water 2025, 17(17), 2619; https://doi.org/10.3390/w17172619 - 4 Sep 2025

Cited by 10 | Viewed by 4566

Abstract

For decades, there has been increasing interest in pharmaceuticals’ prevalence in water bodies. This represents a major challenge in providing clean water, free from pharmaceutical contaminants, in different parts of the world. The misuse and overuse of pharmaceuticals, their elevated concentrations in surface [...] Read more.

For decades, there has been increasing interest in pharmaceuticals’ prevalence in water bodies. This represents a major challenge in providing clean water, free from pharmaceutical contaminants, in different parts of the world. The misuse and overuse of pharmaceuticals, their elevated concentrations in surface waters, and their negative impacts on humans, aquatic organisms, and ecosystems cannot be ignored. Significant efforts have been made toward the discovery of efficient water treatment techniques. Various technologies have been researched and applied, including co-precipitation, membrane separation, ion-exchange, oxidation, adsorption, and biochemical processes. Amidst these technologies, adsorption is considered a promising due to its unique advantages. This review discusses the pharmaceuticals that have been detected in surface waters in concentrations ranging from ng/L to μg/L. It also offers insights into the diverse applications of low-cost adsorbents to deal with pharmaceutical water pollutants and various parameters influencing the adsorption process. This article will assist in promoting the utilization of sustainable, low-cost adsorbents with high adsorption efficiencies in the water treatment process, and it will aid environmentalists in devising strategies for anticipated challenges and provide policymakers with valuable guidance. Full article

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

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20 pages, 2084 KB

Open AccessEditor’s ChoiceArticle

Unravelling the Effect of Sediment Properties on As(V) and As(III) Adsorption/Desorption Processes: Implications for Groundwater Geochemistry

by Sara Trotta, Gilberto Binda, Andrea Pozzi and Alessandro Maria Michetti

Water 2025, 17(17), 2616; https://doi.org/10.3390/w17172616 - 4 Sep 2025

Cited by 2 | Viewed by 1714

Abstract

Arsenic (As) mobility in aquifer systems is mainly governed by its adsorption and desorption behaviour at the sediment-water interface, directly influencing its environmental availability and risks to water quality. This study explores the adsorption-desorption behaviour of inorganic As species through batch experiments on [...] Read more.

Arsenic (As) mobility in aquifer systems is mainly governed by its adsorption and desorption behaviour at the sediment-water interface, directly influencing its environmental availability and risks to water quality. This study explores the adsorption-desorption behaviour of inorganic As species through batch experiments on environmental sediments collected from three representative depths, selected to reflect local contrasting geochemical, mineralogical, and granulometric characteristics of the Como basin aquifer (Northern Italy). This setting was selected as a case study owing to its notable gradient in As concentration in groundwater: the shallow aquifers host concentrations typically below 10 µg/L, while the deep aquifer reaches concentrations of about 250 µg/L. Statistical analyses (ANOVA and simple linear regression) identified Mn- and Al-(hydr)oxide content, grain size, and mineralogy as strong predictors of As(V) retention, whereas As(III) showed no significant correlation with individual sediment properties within the tested conditions. Shallow, Mn- and Al-rich sediments exhibited higher adsorption capacity and corresponded to lower dissolved As in groundwater, while deeper, finer-grained sediments with lower oxide content coincided with elevated groundwater As concentrations. Desorption experiments indicated that As(III) dominated the released fraction, reflecting its greater mobility under variable pH and redox aquifer conditions. These results provide mechanistic insight into sediment-water interactions controlling As distribution in multilayer aquifers, supporting improved risk assessment and management of As in complex groundwater systems. Full article

(This article belongs to the Section Hydrogeology)

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18 pages, 8435 KB

Open AccessEditor’s ChoiceArticle

Modeling Sentiment–Hydrology Interaction Using LLM: Insights for Adaptive Governance in Ceará’s Water Management

by Tatiane Lima Batista, Ticiana Marinho de Carvalho Studart, Marlon Gonçalves Duarte and Francisco de Assis de Souza Filho

Water 2025, 17(17), 2615; https://doi.org/10.3390/w17172615 - 4 Sep 2025

Cited by 2 | Viewed by 2085

Abstract

This study aims to analyze the relationships between concerns and sentiments of stakeholders and the drought stage in a semi-arid region of Ceará from Language Technologies based on Artificial Intelligence. The dataset comprises 36 meeting minutes of water management bodies (2007–2024), of which [...] Read more.

This study aims to analyze the relationships between concerns and sentiments of stakeholders and the drought stage in a semi-arid region of Ceará from Language Technologies based on Artificial Intelligence. The dataset comprises 36 meeting minutes of water management bodies (2007–2024), of which 17 correspond to dry periods and 19 to normal periods (reservoir volume > 50%). Natural Language Processing (NLP) techniques were applied to generate word clouds, and sentiment analysis was performed using a Large Language Model (Llama 3.2, 3B). Sentiment scores were compared with reservoir volume data. Results show that both perceptions and themes differed between drought and normal phases, with higher water availability coinciding with more positive sentiments. A moderate positive correlation was found between sentiment and reservoir volume (r = 0.53, p = 0.00095, 95% CI [0.24, 0.73]). Statistical tests confirmed differences between periods (Welch’s t-test, p = 0.0018; Mann-Whitney, p = 0.0039). Box-plot analyses indicated that over 75% of sentiments were positive in normal phases, while about 65% were negative in drought phases. These findings highlight the sensitivity of human perceptions to hydrological conditions and point to the potential of LLMs as innovative instruments for integrating qualitative data into complex socio-environmental analyses. Full article

(This article belongs to the Special Issue Application of Hydrological Modelling to Water Resources Management)

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21 pages, 2881 KB

Open AccessEditor’s ChoiceReview

Understanding South Africa’s Flood Vulnerabilities and Resilience Pathways: A Comprehensive Overview

by Nicholas Byaruhanga, Daniel Kibirige and Glen Mkhonta

Water 2025, 17(17), 2608; https://doi.org/10.3390/w17172608 - 3 Sep 2025

Cited by 11 | Viewed by 21612

Abstract

This review examines South Africa’s escalating flood vulnerability through a synthesis of over 80 peer-reviewed articles, historical records, policy reports, and case studies. Using a PRISMA-guided analysis, the study identifies key climatic drivers, including extreme rainfall from tropical–temperate interactions, cut-off lows, and La [...] Read more.

This review examines South Africa’s escalating flood vulnerability through a synthesis of over 80 peer-reviewed articles, historical records, policy reports, and case studies. Using a PRISMA-guided analysis, the study identifies key climatic drivers, including extreme rainfall from tropical–temperate interactions, cut-off lows, and La Niña conditions that interact with structural weaknesses such as inadequate drainage, poorly maintained stormwater systems, and rapid urban expansion. Apartheid-era spatial planning has further entrenched risk by locating marginalised communities in floodplains. Governance failures like weak disaster risk reduction (DRR) policies, fragmented institutional coordination, and insufficient early warning systems intensify flood vulnerabilities. Catastrophic events in KwaZulu-Natal (KZN) and the Western Cape (WC) illustrate the consequences exemplified by the April 2022 KZN floods alone, which caused over 450 deaths, displaced more than 40,000 people, and generated damages exceeding ZAR 17 billion. Nationally, more than 1500 flood-related fatalities have been documented in the past two decades. Emerging resilience pathways include ecosystem-based adaptation, green infrastructure, participatory governance, integration of Indigenous knowledge, improved hydrological forecasting, and stricter land-use enforcement. These approaches can simultaneously reduce physical risks and address entrenched socio-economic inequalities. However, significant gaps remain in spatial flood modelling, gender-sensitive responses, urban–rural disparities, and policy implementation. The review concludes that South Africa urgently requires integrated, multi-scalar strategies that combine scientific innovation, policy reform, and community-based action. Embedding these insights into disaster management policy and planning is essential to curb escalating losses and build long-term resilience in the face of climate change. Full article

(This article belongs to the Special Issue Innovative Approaches in Flood Forecasting and Modeling for Risk Mitigation)

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19 pages, 3509 KB

Open AccessEditor’s ChoiceArticle

Agricultural Activities and Hydrological Processes Drive Nitrogen Pollution and Transport in Polder Waters: Evidence from Hydrochemical and Isotopic Analysis

by Yalan Luo, Bo Peng, Tingting Li, Mengmeng Chang, Yinghui Guo, Yaojun Liu and Xiaodong Nie

Water 2025, 17(17), 2601; https://doi.org/10.3390/w17172601 - 3 Sep 2025

Cited by 2 | Viewed by 1795

Abstract

Excessive nitrogen export from lowland polders is a key contributor to cultural eutrophication in downstream aquatic ecosystems. This study investigated the spatiotemporal characteristics, migration pathways, and sources of nitrogen pollution in a typical polder system. Eight surface water sampling campaigns were conducted at [...] Read more.

Excessive nitrogen export from lowland polders is a key contributor to cultural eutrophication in downstream aquatic ecosystems. This study investigated the spatiotemporal characteristics, migration pathways, and sources of nitrogen pollution in a typical polder system. Eight surface water sampling campaigns were conducted at 13 sites in Quyuan Polder, Dongting Lake, from 2022 to 2023, combining ArcGIS spatial analysis, multivariate statistics, and dual-isotope (δ¹⁵N-NO⁻), δ¹⁸O-NO₃⁻) techniques. Nitrate and ammonium nitrogen dominated the nitrogen pool, accounting for ~76% of total nitrogen. Concentrations were higher in the dry season (2.48 mg/L) than in the wet season (1.89 mg/L) and differed significantly among hydrological periods (p < 0.05). Within the polder, total nitrogen and ammonium nitrogen were elevated, whereas nitrate nitrogen was higher at the outlet, reflecting distinct nitrogen profiles along the hydrological gradient. Nitrogen transport patterns were largely consistent with flow direction, driven by both upstream inputs and in situ generation. Isotopic signatures indicated that nitrate originated mainly from ammonium fertilizer and soil nitrogen, with contributions from manure and sewage. These findings enhance understanding of nitrogen dynamics in lowland catchments and provide a scientific basis for targeted pollution control in polder waters. Full article

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

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24 pages, 5572 KB

Open AccessEditor’s ChoiceArticle

Enhanced Biosorption of Triarylmethane Dyes by Immobilized Trametes versicolor and Pleurotus ostreatus: Optimization, Kinetics, and Reusability

by Ruchi Upadhyay, Wioletta Przystaś, Roman Turczyn and Marcelina Jureczko

Water 2025, 17(17), 2600; https://doi.org/10.3390/w17172600 - 2 Sep 2025

Cited by 4 | Viewed by 2101

Abstract

The discharge of synthetic dyes from industries poses severe environmental challenges, necessitating eco-friendly remediation strategies. This study investigated the biosorption of triarylmethane dyes Crystal Violet (CV), and Brilliant Green (BG) using self-immobilized and sponge-immobilized biosorbents of Trametes versicolor (strain CB8, CB8/S2) and Pleurotus [...] Read more.

The discharge of synthetic dyes from industries poses severe environmental challenges, necessitating eco-friendly remediation strategies. This study investigated the biosorption of triarylmethane dyes Crystal Violet (CV), and Brilliant Green (BG) using self-immobilized and sponge-immobilized biosorbents of Trametes versicolor (strain CB8, CB8/S2) and Pleurotus ostreatus (strain BWPH, BWPH/S2). Tests were conducted with live and autoclaved biomass under varying conditions of dye concentration (100–400 mg/L), temperature (15–55 °C), and pH (2–10). Sponge-immobilized live biomass (CB8/S2 and BWPH/S2) showed superior performance, removing up to 90.3% and 81.7% of BG and 43.9% and 39.3% of CV, respectively, within 6 h, demonstrating 3–5 times higher efficiency than self-immobilized biomass for both dyes. Maximum sorption of 379.4 mg/g of BG and 48.9 mg/g of CV was achieved by CB8/S2 at 400 mg/L. Principal Component Analysis biplot confirmed immobilization efficacy, where Dim1 (85.9–91.8% variance) dominated dye concentration and contact time. The optimized conditions for BG removal by CB8/S2 was 20.85–32.17 °C and pH 3.4–6, and for CV, at pH 6.5–7.5 and 30 °C. The percentage of dye sorption data fitted well with the quadratic model (p < 0.05). Fourier transform infrared spectroscopy (FT-IR) analysis indicated that hydrogen bonding and electrostatic interactions facilitated dye binding onto fungal mycelium. Notably, sponge-immobilized biosorbents were reusable without additional treatment. The findings support fungal biomass immobilization as a viable strategy to augment the bioremediation potential in treating dye-laden wastewater. Full article

(This article belongs to the Special Issue Biodegradation Strategies for Sustainable Removal of Persistent Pollutants and Xenobiotics in Wastewater Treatment)

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15 pages, 1110 KB

Open AccessEditor’s ChoiceArticle

Natural Radionuclides ²²²Rn and ²²⁶Ra in Shallow Groundwater of Nysa County (SW Poland): Concentrations, Background, and Radiological Risk

by Piotr Maciejewski and Jakub Ładziński

Water 2025, 17(17), 2596; https://doi.org/10.3390/w17172596 - 2 Sep 2025

Cited by 1 | Viewed by 1771

Abstract

Natural radionuclides may occur in groundwater and pose health risks when present in elevated concentrations. This study evaluates the quality of shallow groundwater in Nysa County (SW Poland) based on the activity concentrations of natural radionuclides radon (²²²Rn) and radium ( [...] Read more.

Natural radionuclides may occur in groundwater and pose health risks when present in elevated concentrations. This study evaluates the quality of shallow groundwater in Nysa County (SW Poland) based on the activity concentrations of natural radionuclides radon (²²²Rn) and radium (²²⁶Ra) and estimates the associated radiological risk from water ingestion. Twenty-three groundwater samples were collected from private wells located within two distinct geological units: the Fore-Sudetic Block and the Opole Trough. Activity concentrations of ²²²Rn and ²²⁶Ra were measured using the liquid scintillation counting method. A spatial distribution model for ²²²Rn was developed using inverse distance weighting in QGIS. Local hydrogeochemical background levels were determined using the Q-Dixon test, interquartile range, and Shapiro–Wilk normality test. The background ranged from 2.6 to 3.9 Bq·L⁻¹ in the Opole Trough and from 0 to 10.7 Bq·L⁻¹ in the Fore-Sudetic Block. The lower detection limit (0.05 Bq·L⁻¹) for ²²⁶Ra activity concentration measurements was not exceeded. Effective dose rates were calculated in accordance with the recommendations of the International Commission on Radiological Protection and United Nations Scientific Committee on the Effects of Atomic Radiation. Doses ranged from <1 µSv to over 120 µSv·y⁻¹. Although all samples met national regulatory standards (≤1 mSv·y⁻¹), the World Health Organization reference level (0.1 mSv·y⁻¹) was exceeded in two cases. The results support the need for the radiological monitoring of unregulated private wells and provide a scientific basis for the refinement of legal frameworks and health protection strategies. Full article

(This article belongs to the Section Hydrogeology)

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20 pages, 4280 KB

Open AccessEditor’s ChoiceArticle

Application of Positive Mathematical Programming (PMP) in Sustainable Water Resource Management: A Case Study of Hetao Irrigation District, China

by Jingwei Yao, Julio Berbel, Zhiyuan Yang, Huiyong Wang and Javier Martínez-Dalmau

Water 2025, 17(17), 2598; https://doi.org/10.3390/w17172598 - 2 Sep 2025

Cited by 2 | Viewed by 1964

Abstract

Water scarcity and soil salinization pose significant challenges to sustainable agricultural development in arid and semi-arid regions globally. This study applies Positive Mathematical Programming (PMP) to analyze agricultural water resource management in the Hetao Irrigation District (HID), China. The research constructs a comprehensive [...] Read more.

Water scarcity and soil salinization pose significant challenges to sustainable agricultural development in arid and semi-arid regions globally. This study applies Positive Mathematical Programming (PMP) to analyze agricultural water resource management in the Hetao Irrigation District (HID), China. The research constructs a comprehensive multi-stress-factor integrated PMP model to evaluate the compound impacts of water resource constraints, pricing policies, and environmental stress on agricultural production systems. The model incorporates crop-specific salinity tolerance thresholds and simulates farmer decision-making behaviors under various scenarios including water supply reduction (0–100%), water pricing increases (0.2–1.0 CNY/m³), and soil salinity stress (0–10 dS/m). The results reveal that the agricultural system exhibits significant vulnerability characteristics with critical thresholds concentrated in the 60–70% water resource utilization interval. Water pricing policies show limited effectiveness in low-price ranges, with wheat demonstrating the highest price sensitivity (−23.8% elasticity). Crop salinity tolerance analysis indicates that wheat–sunflower rotation systems maintain an 85% planting proportion even under extreme salinity conditions (10 dS/m), significantly outperforming individual crops. The study proposes a hierarchical water resource quota allocation system based on vulnerability thresholds and recommends promoting salt-tolerant rotation systems to enhance agricultural resilience. These findings provide scientific evidence for sustainable water resource management and agricultural adaptation strategies in water-stressed regions, contributing to both theoretical advancement of the PMP methodology and practical policy formulation for irrigation districts facing similar challenges. Full article

(This article belongs to the Special Issue Challenges and Innovations in Resilience of the Water-Energy-Food Nexus)

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19 pages, 9454 KB

Open AccessEditor’s ChoiceArticle

Peroxymonosulfate Activation by Sludge-Derived Biochar via One-Step Pyrolysis: Pollutant Degradation Performance and Mechanism

by Yi Wang, Liqiang Li, Hao Zhou and Jingjing Zhan

Water 2025, 17(17), 2588; https://doi.org/10.3390/w17172588 - 1 Sep 2025

Cited by 2 | Viewed by 2526

Abstract

Municipal wastewater treatment relies primarily on biological methods, yet effective disposal of residual sludge remains a major challenge. Converting sludge into biochar via oxygen-limited pyrolysis presents a novel approach for waste resource recovery. This study prepared sludge-based biochar (SBC) through one-step pyrolysis of [...] Read more.

Municipal wastewater treatment relies primarily on biological methods, yet effective disposal of residual sludge remains a major challenge. Converting sludge into biochar via oxygen-limited pyrolysis presents a novel approach for waste resource recovery. This study prepared sludge-based biochar (SBC) through one-step pyrolysis of sewage sludge and applied it to activate peroxymonosulfate (PMS) for degrading diverse contaminants. Characterization (SEM, XPS, FTIR) revealed abundant pore structures and diverse surface functional groups on SBC. Using Acid Orange 7 (AO7) as the target pollutant, SBC effectively degraded AO7 across pH 3.0–9.0 and catalyst dosages (0.2–2.0 g·L⁻¹), achieving a maximum observed rate constant (k_obs) of 0.3108 min^–1. Salinity and common anions showed negligible inhibition on AO7 degradation. SBC maintained 95% degradation efficiency after four reuse cycles and effectively degraded sulfamethoxazole, sulfamethazine, and rhodamine B besides AO7. Mechanistic studies (chemical quenching and ESR) identified singlet oxygen (¹O₂) and superoxide radicals (O₂^•− ) as the dominant reactive oxygen species for AO7 degradation. XPS indicated a 39% reduction in surface carbonyl group content after cycling, contributing to activity decline. LC-MS identified five intermediates, suggesting a potential degradation pathway driven by SBC/PMS system. ECOSAR model predictions indicated significantly reduced biotoxicity of the degradation products compared to AO7. This work provides a strategy for preparing sludge-derived catalysts for PMS activation and pollutant degradation, enabling effective solid waste resource utilization. Full article

(This article belongs to the Special Issue Application of Advanced Oxidation Processes (AOPs) for Wastewater Treatment)

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21 pages, 5495 KB

Open AccessEditor’s ChoiceArticle

Assessing the Accuracy of Gridded Precipitation Products in the Campania Region, Italy

by Muhammad Shareef Shazil, Muhammad Aleem, Sheharyar Ahmad, Abdullah Abdullah and Roberto Greco

Water 2025, 17(17), 2585; https://doi.org/10.3390/w17172585 - 1 Sep 2025

Cited by 4 | Viewed by 2347

Abstract

Accurate precipitation data are essential for hydrological modeling, climate studies, and water resource management. Indeed, there is an increasing focus on understanding shifts in precipitation events to monitor the risks of floods and droughts, as well as to ensure sustainable water resource management. [...] Read more.

Accurate precipitation data are essential for hydrological modeling, climate studies, and water resource management. Indeed, there is an increasing focus on understanding shifts in precipitation events to monitor the risks of floods and droughts, as well as to ensure sustainable water resource management. This study compares four reanalysis and satellite precipitation products (ERA5-Land, CHIRPS, PERSIANN, and TerraClimate) with ground data from 2003 to 2022. Among the datasets evaluated, ERA5-Land has the best performance (overall) in reproducing ground data, with a minimal mean bias error (MBE) of 1.91 mm, the highest correlation coefficient (R² = 0.93), and the most favorable Nash–Sutcliffe efficiency (NSE = 0.93). In contrast, CHIRPS, PERSIANN, and TerraClimate significantly underestimate precipitation as compared to ground data. The categorical metrics also highlight ERA5-Land’s superior performance in identifying wet months. Spatial analysis shows that ERA5-Land and other datasets generally exhibit agreement regarding precipitation patterns. However, PERSIANN displays notable variances, particularly in northern regions, where it overestimates precipitation. To investigate possible changes in precipitation patterns, a longer period (1983–2022) is selected for trend analysis based on gridded precipitation products. Sen’s slope analysis does not reveal any significant annual precipitation trend. In autumn, the PERSIANN dataset indicates a significant increasing trend of +1.81 mm/year, which is also confirmed by ERA5-Land (+2.68 mm/year) and CHIRPS (+1.34 mm/year), although without statistical significance. The findings emphasize the need for more sophisticated satellite algorithms and integration with ground observations to improve precipitation accuracy. Full article

(This article belongs to the Section Hydrology)

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26 pages, 12809 KB

Open AccessEditor’s ChoiceArticle

Integrated Statistical Modeling for Regional Landslide Hazard Mapping in 0-Order Basins

by Ahmad Qasim Akbar, Yasuhiro Mitani, Ryunosuke Nakanishi, Hiroyuki Honda, Hisatoshi Taniguchi and Ibrahim Djamaluddin

Water 2025, 17(17), 2577; https://doi.org/10.3390/w17172577 - 1 Sep 2025

Cited by 1 | Viewed by 1769

Abstract

Rainfall-induced slope failures are among the most frequent and destructive natural hazards in Japan’s mountainous regions, often causing severe loss of life and damage to infrastructure. This study presents an integrated statistical framework for regional-scale landslide hazard mapping, with a focus on 0-order [...] Read more.

Rainfall-induced slope failures are among the most frequent and destructive natural hazards in Japan’s mountainous regions, often causing severe loss of life and damage to infrastructure. This study presents an integrated statistical framework for regional-scale landslide hazard mapping, with a focus on 0-order basins. To enhance spatial prediction accuracy, both bivariate and multivariate statistical models are employed. Bivariate models efficiently assess the relationship between individual conditioning factors and landslide occurrences but assume variable independence. Conversely, multivariate models account for multicollinearity and the combined effects of interacting factors, although they often require more complex data processing and may lack spatial clarity. To leverage the strengths of both approaches, two hybrid models were developed and applied to a 242.94 km² area in Fukuoka Prefecture, Japan. Model validation was performed using a matrix-based evaluation supported by a threshold optimization algorithm. Among the models tested, the hybrid Frequency Ratio–Logistic Regression (FR + LR) model demonstrated the highest predictive performance, achieving a success rate of 84.30%, a false alarm rate of 17.88%, and a miss rate of 12.30%. It effectively identified critical slip surfaces within zones classified as ‘High’ to ‘Very High’ susceptibility. This integrated approach offers a statistically robust, scalable, and interpretable solution for landslide hazard assessment in geomorphologically complex terrains. It provides valuable support for regional disaster risk reduction and contributes directly to achieving the Sustainable Development Goals (SDGs). Full article

(This article belongs to the Special Issue Applications of GIS and Remote Sensing in Hydrology and Hydrogeology)

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17 pages, 2666 KB

Open AccessEditor’s ChoiceArticle

Effluent Dissolved Carbon Discharge from Two Municipal Wastewater Treatment Plants to the Mississippi River

by Anamika Dristi and Yijun Xu

Water 2025, 17(17), 2589; https://doi.org/10.3390/w17172589 - 1 Sep 2025

Cited by 3 | Viewed by 2061

Abstract

Nutrient and carbon transport from the Mississippi River to the Gulf of Mexico have been investigated intensively. However, little is known about the direct human contribution of carbon from wastewater treatment plants (WWTPs) to this large river, a source that can be termed [...] Read more.

Nutrient and carbon transport from the Mississippi River to the Gulf of Mexico have been investigated intensively. However, little is known about the direct human contribution of carbon from wastewater treatment plants (WWTPs) to this large river, a source that can be termed as Cultural Carbon. This study analyzed dissolved carbon in effluents from two municipal WWTPs on the bank of the Mississippi River in Baton Rouge, South Louisiana, USA. One of the WWTPs (WWTP North) is a conventional wastewater treatment facility with a treatment capacity of 40 million gallons per day (MGD), while the other (WWTP South) is a recently upgraded facility with a treatment capacity of 200 MGD. From September 2022 to November 2024, river water and effluent samples were collected monthly to analyze dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) concentrations and their mass transport. The study found significantly higher monthly average DIC (56.80 ± 16.51 mg/L) and DOC (29.52 ± 8.68 mg/L) concentrations in the effluent of WWTP North than in the effluent of WWTP South (DIC: 42.64 ± 10.50 mg/L and DOC: 12.93 ± 3.68 mg/L). Effluents from both WWTPs had substantially greater DOC and DIC levels than the Mississippi River water (DIC: 28.92 ± 4.91 mg/L and DOC: 5.47 ± 2.35 mg/L). WWTP North discharged, on average, 3.80 MT of DIC and 1.95 MT of DOC per day, whereas WWTP South discharged 6.27 MT of DIC and 1.92 MT of DOC per day, resulting in a total annual load of 3808 MT of DIC and 1459 MT of DOC entering the Mississippi River. Considering the large number of WWTPs within the Mississippi River Basin, these findings highlight a significant contribution of effluents to riverine carbon, suggesting that basin-wide carbon budgets and regional climate assessments must take them into account. The findings from this study can be useful for federal and state policymakers, as well as researchers and engineers involved in carbon science, climate change, and water quality assessment of the Mississippi River Basin and beyond. Full article

(This article belongs to the Special Issue Biogeochemical Processes in Lakes, Ponds and Reservoirs of Urban Environments)

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28 pages, 3888 KB

Open AccessEditor’s ChoiceSystematic Review

On Smart Water System Developments: A Systematic Review

by Daniel Quintana, Luis C. Felix-Herran, Juan C. Tudon-Martinez and Jorge de J. Lozoya-Santos

Water 2025, 17(17), 2571; https://doi.org/10.3390/w17172571 - 31 Aug 2025

Cited by 9 | Viewed by 7395

Abstract

Water is an essential resource for life and is also a necessary resource for the sustainable economic competitiveness of any country. In recent decades, climate change, economic development, and rising population have led to water scarcity in certain regions. In response, new technologies [...] Read more.

Water is an essential resource for life and is also a necessary resource for the sustainable economic competitiveness of any country. In recent decades, climate change, economic development, and rising population have led to water scarcity in certain regions. In response, new technologies and water management techniques have been researched and developed, which are now incorporated into the concept of smart cities. These innovations, called smart water systems, aim to enhance water management by monitoring consumption, quality, reservoir levels, leaks, and asset conditions, and optimizing water processes to maximize water system resilience. The first systems were based on smart meters and have advanced to so-called digital twins for water systems. This review aims to present a comprehensive review of smart water system developments, the geographic distribution of the works, their technological readiness level, and their implementation challenges. Full article

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

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23 pages, 5960 KB

Open AccessEditor’s ChoiceArticle

Comprehensive Evaluation of Urban Storm Flooding Resilience by Integrating AHP–Entropy Weight Method and Cloud Model

by Zhangao Huang and Cuimin Feng

Water 2025, 17(17), 2576; https://doi.org/10.3390/w17172576 - 31 Aug 2025

Cited by 11 | Viewed by 3238

Abstract

To address urban flooding challenges exacerbated by climate change and urbanization, this study develops an integrated assessment framework combining the analytic hierarchy process (AHP), entropy weight method, and cloud model to quantify urban flood resilience. Resilience is deconstructed into resistance, adaptability, and recovery [...] Read more.

To address urban flooding challenges exacerbated by climate change and urbanization, this study develops an integrated assessment framework combining the analytic hierarchy process (AHP), entropy weight method, and cloud model to quantify urban flood resilience. Resilience is deconstructed into resistance, adaptability, and recovery and evaluated through 24 indicators spanning water resources, socio-economic systems, and ecological systems. Subjective (AHP) and objective (entropy) weights are optimized via minimum information entropy, with the cloud model enabling qualitative–quantitative resilience mapping. Analyzing 2014–2024 data from 27 Chinese sponge city pilots, the results show resilience improved from “poor to average” to “good to average”, with a 2.89% annual growth rate. Megacities like Beijing and Shanghai excel in resistance and recovery due to infrastructure and economic strengths, while cities like Sanya enhance resilience via ecological restoration. Key drivers include water allocation (27.38%), economic system (18.41%), and social system (17.94%), with critical indicators being population density, secondary industry GDP ratio, and sewage treatment rate. Recommendations emphasize upgrading rainwater storage, intelligent monitoring networks, and resilience-oriented planning. The model offers a scientific foundation for urban disaster risk management, supporting sustainable development. This approach enables systematic improvements in adaptive capacity and recovery potential, providing actionable insights for global flood-resilient urban planning. Full article

(This article belongs to the Special Issue Advances in Water and Stormwater Networks: Modelling and Pollutant Degradation, 2nd Edition)

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18 pages, 3600 KB

Open AccessEditor’s ChoiceArticle

Spatial Distribution, Key Influencing Factors, and Ecological Risk of Microplastics in Pearl River Estuary Water and Sediments

by Jiyuan Hu, Chengliang Li, Lichi Deng, Ziyan Yan and Xing Gong

Water 2025, 17(17), 2572; https://doi.org/10.3390/w17172572 - 31 Aug 2025

Cited by 7 | Viewed by 2330

Abstract

Microplastic (MP) pollution in aquatic ecosystems poses significant ecological and public health risks. A comprehensive understanding of estuarine MP pollution, influenced by multiple anthropogenic and environmental factors, remains elusive in current research. This study investigated the spatial distribution patterns and dominant factors influencing [...] Read more.

Microplastic (MP) pollution in aquatic ecosystems poses significant ecological and public health risks. A comprehensive understanding of estuarine MP pollution, influenced by multiple anthropogenic and environmental factors, remains elusive in current research. This study investigated the spatial distribution patterns and dominant factors influencing MP abundance (MPA) and physicochemical diversity in the river water and sediments of the Pearl River Estuary (PRE), while also assessing the associated ecological risks. The dominant MP categories in river water and sediments were fibers, clear in color, <1 mm in length, and composed of polyethylene terephthalate and polypropylene. Whereas inland regions showed higher MPA, nearshore regions exhibited marginally greater physicochemical diversity. Multivariate statistical analysis identified population density as the primary driver of both MPA in river water and MP physicochemical diversity in sediments. MP physicochemical diversity in river water was predominantly governed by the synergistic effect of salinity and the vegetation land. MPA in sediments depended on the synergistic effect of flow rate and watershed area. Ecological risk assessment identified elevated risks in the eastern study area driven by the presence of polymethyl methacrylate. This study establishes a scientific basis for PRE region MP management and provides global comparative data for estuarine MP research. Full article

(This article belongs to the Topic Aquatic Emerging Contaminants and Their Ecotoxicological Consequences, 2nd Edition)

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19 pages, 1338 KB

Open AccessEditor’s ChoiceArticle

From Raw Water to Pipeline Water: Correlation Analysis of Dynamic Changes in Water Quality Parameters and Microbial Community Succession

by Xiaolong Jiang, Weiying Li, Xin Song and Yu Zhou

Water 2025, 17(17), 2555; https://doi.org/10.3390/w17172555 - 28 Aug 2025

Cited by 5 | Viewed by 1979

Abstract

Understanding the spatiotemporal dynamics of water quality parameters and microbial communities in drinking water distribution systems (DWDS) and their interrelationships is critical for ensuring the safety of tap water supply. This study investigated the diurnal, monthly, and annual variation patterns of water quality [...] Read more.

Understanding the spatiotemporal dynamics of water quality parameters and microbial communities in drinking water distribution systems (DWDS) and their interrelationships is critical for ensuring the safety of tap water supply. This study investigated the diurnal, monthly, and annual variation patterns of water quality and the stage-specific succession behaviors of microbial communities in a DWDS located in southeastern China. Results indicated that hydraulic shear stress during peak usage periods drove biofilm detachment and particle resuspension. This process led to significant diurnal fluctuations in total cell counts (TCC) and metal ions, with coefficients of variation ranging from 0.44 to 1.89. Monthly analyses revealed the synergistic risks of disinfection by-products (e.g., 24.5 μg/L of trichloromethane) under conditions of low chlorine residual (<0.2 mg/L) and high organic loading. Annual trends suggested seasonal coupling: winter pH reductions correlated with organic acid accumulation, while summer microbial blooms associated with chlorine decay and temperature increase. Nonlinear interactions indicated weakened metal–organic complexation but enhanced turbidity–sulfate adsorption, suggesting altered contaminant mobility in pipe scales. Microbial analysis demonstrated persistent dominance of oligotrophic Phreatobacter and prevalence of Pseudomonas in biofilms, highlighting hydrodynamic conditions, nutrient availability, and disinfection pressure as key drivers of community succession. These findings reveal DWDS complexity and inform targeted operational and microbial risk control strategies. Full article

(This article belongs to the Special Issue Monitoring and Assessment of Water Quality in Drinking Water Distribution Systems)

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20 pages, 3712 KB

Open AccessEditor’s ChoiceArticle

Mussels as Bioindicators for the Rapid Detection of Heavy Metal Fluctuations in Marine Coastal Waters: A Case Study of Seasonal Bioaccumulation Monitoring and Assessment of Perna viridis from the Gulf of Tonkin Coastline, Hai Phong, Vietnam

by Hue Nguyen Thanh Kim, Van-Hao Duong, Trung-Tien Chu, Thanh-Xuan Pham-Thi, Xuan-Quang Nguyen, Sang Van Vu, Thin Pham Van, Duc-Thinh Ta, Duc-Thang Duong, Obid Tursunov, Marckasagayam Priyadharshini, Mohamed Saiyad Musthafa, Miklós Hegedűs, Amin Shahrokhi and Tibor Kovács

Water 2025, 17(17), 2552; https://doi.org/10.3390/w17172552 - 28 Aug 2025

Cited by 5 | Viewed by 3865

Abstract

This study aims to evaluate the feasibility of using the mussel as a bioindicator for the rapid detection of heavy metal (such as Cd, Pb, Hg, Ni, Cr, Cu, As, and Zn) fluctuations in aquatic environments and the sensitivity of the bioaccumulation of [...] Read more.

This study aims to evaluate the feasibility of using the mussel as a bioindicator for the rapid detection of heavy metal (such as Cd, Pb, Hg, Ni, Cr, Cu, As, and Zn) fluctuations in aquatic environments and the sensitivity of the bioaccumulation of heavy metals in muscle tissues over time. The seasonal bioaccumulation patterns of heavy metals within Asian green mussels (Perna viridis), from Vietnamese coastal waters of Hai Phong were investigated using inductively coupled plasma mass spectrometry (ICP-MS). Additionally, the health risks from the consumption of P. viridis by local people were assessed. Mussels of varying sizes were sampled on a monthly basis between March (dry season) and July 2024 (wet season). The results revealed that the hepatopancreas had substantially higher concentrations of metals at all times relative to their corresponding muscle tissues, confirming its appropriateness as a bioindicator organ. The concentrations of heavy metals in mussels were recorded as significantly lower than the guideline levels, except for arsenic (As). Zinc (Zn) showed the highest concentrations, while mercury (Hg) had the lowest concentrations. There were strong seasonal and monthly differences, with peak levels of Pb, Cr, and As during the dry season, and high levels of Cs and Cu during the rainy season. It was found that the condition index, physiological factors, and shell size all had major impacts on the absorption of specific heavy metals. It was indicated that Pb, Cr, As, Cs, and Cu bioaccumulation are both biologically and environmentally responsive and can be used as proxies for environmental contamination, while the accumulation of these metals correlated with biological traits (shell length, weight, and CI), which is useful in modeling efforts. Health risk assessments using target hazard quotients (THQs) and the total hazard index (THI) identified Pb in the hepatopancreas as a primary contributor to the non-carcinogenic risk (THQ > 1), particularly during the dry season. The findings revealed the suitability of P. viridis, particularly hepatopancreatic tissue, as a short-term biomonitoring tool for detecting spikes and rapid fluctuations of certain heavy metals and assessing related human health risks in coastal aquatic systems. Full article

(This article belongs to the Special Issue Water Pollutants and Human Health: Challenges and Perspectives)

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16 pages, 9579 KB

Open AccessEditor’s ChoiceArticle

Video-Based Deep Learning Approach for Water Level Monitoring in Reservoirs

by Wallpyo Jung, Jongchan Kim, Hyeontak Jo, Seungyub Lee and Byunghyun Kim

Water 2025, 17(17), 2525; https://doi.org/10.3390/w17172525 - 25 Aug 2025

Cited by 3 | Viewed by 3048

Abstract

This study developed a deep learning–based water level recognition model using Closed-Circuit Television (CCTV) footage. The model focuses on real-time water level recognition in agricultural reservoirs that lack automated water level gauges, with the potential for future extension to flood forecasting applications. Video [...] Read more.

This study developed a deep learning–based water level recognition model using Closed-Circuit Television (CCTV) footage. The model focuses on real-time water level recognition in agricultural reservoirs that lack automated water level gauges, with the potential for future extension to flood forecasting applications. Video data collected over approximately two years at the Myeonggyeong Reservoir in Chungcheongbuk-do, South Korea, were utilized. A semantic segmentation approach using the U-Net model was employed to extract water surface areas, followed by the classification of water levels using Convolutional Neural Network (CNN), ResNet, and EfficientNet models. To improve learning efficiency, water level intervals were defined using both equal spacing and the Jenks natural breaks classification method. Among the models, EfficientNet achieved the highest performance with an accuracy of approximately 99%, while ResNet also demonstrated stable learning outcomes. In contrast, CNN showed faster initial convergence but lower accuracy in classifying complex intervals. This study confirms the feasibility of applying vision-based water level prediction technology to flood-prone agricultural reservoirs. Future work will focus on enhancing system performance through low-light video correction, multi-sensor integration, and model optimization using AutoML, thereby contributing to the development of an intelligent, flood-resilient water resource management system. Full article

(This article belongs to the Special Issue Machine Learning Methods for Flood Computation)

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13 pages, 1614 KB

Open AccessEditor’s ChoiceArticle

Simultaneous Heterotrophic Nitrification and Aerobic Denitrification of High C/N Wastewater in a Sequencing Batch Reactor

by Tao Tao and Sheng Chang

Water 2025, 17(17), 2515; https://doi.org/10.3390/w17172515 - 23 Aug 2025

Cited by 5 | Viewed by 3482

Abstract

Heterotrophic nitrification and aerobic denitrification (HN–AD) is an emerging biological process capable of achieving efficient nitrogen removal in a single reactor. This study investigates the HN–AD performance of a sequencing batch reactor (SBR) operated with a simple anaerobic–aerobic cycle for treating high C/N [...] Read more.

Heterotrophic nitrification and aerobic denitrification (HN–AD) is an emerging biological process capable of achieving efficient nitrogen removal in a single reactor. This study investigates the HN–AD performance of a sequencing batch reactor (SBR) operated with a simple anaerobic–aerobic cycle for treating high C/N wastewater. Over a 220-day operation, the system achieved average removal efficiencies of 98.6% for COD, 93.3% for NH₄⁺-N, and 87.1% for total nitrogen. Effluent concentrations of NO₂⁻-N and NO₃⁻-N remained negligible at the end of each aerobic phase. Concentration profiles of NH₄⁺-N, NO₂⁻-N, and NO₃⁻-N throughout the operation cycles confirmed the occurrence of simultaneous nitrification and aerobic denitrification. The consistently high COD removal and robust nitrogen reduction highlight the stability of the HN–AD microbial consortia enriched from activated sludge. Phosphorus removal (average removal efficiency 66.3%) may be enhanced by increasing the activity of phosphate-accumulating organisms (PAOs) through process optimization. This study demonstrated effective HN–AD using activated sludge in SBRs. Future work will focus on evaluating the system with real wastewater and continuous-flow setups to further refine operational parameters for sustained HN–AD performance. Full article

(This article belongs to the Special Issue Advances in Biological Technologies for Wastewater Treatment)

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17 pages, 779 KB

Open AccessEditor’s ChoiceReview

Multi-Scale Drought Resilience in Terrestrial Plants: From Molecular Mechanisms to Ecosystem Sustainability

by Weiwei Lu, Bo Wu, Lili Wang and Ying Gao

Water 2025, 17(17), 2516; https://doi.org/10.3390/w17172516 - 23 Aug 2025

Cited by 2 | Viewed by 2389

Abstract

Global climate change has intensified the frequency, intensity, and spatial heterogeneity of drought events, posing severe threats to the stability of terrestrial ecosystems. Plant drought resilience, which encompasses a plant’s capacity for drought resistance, post-stress recovery, and long-term adaptation and transformation to sustain [...] Read more.

Global climate change has intensified the frequency, intensity, and spatial heterogeneity of drought events, posing severe threats to the stability of terrestrial ecosystems. Plant drought resilience, which encompasses a plant’s capacity for drought resistance, post-stress recovery, and long-term adaptation and transformation to sustain ecosystem functionality, has emerged as a central focus in botanical and ecological research. This review synthesizes the conceptual evolution of plant drought resilience, from early emphasis on resistance and recovery to the current multi-dimensional framework integrating adaptation and transformation, and synthesizes advances in understanding multi-scale drought resilience in terrestrial plants—spanning molecular, physiological, individual, community, and ecosystem levels. Key mechanisms include molecular/physiological adaptations (osmotic adjustment, antioxidant defense, hydraulic regulation, carbon–water reallocation via gene networks and aquaporins), morpho-anatomical traits (root architectural plasticity, leaf structural modifications, and hydraulic vulnerability segmentation), community/ecosystem drivers (biodiversity effects, microbial symbioses, and soil–plant–feedback dynamics). We critically evaluate quantitative metrics and expose critical gaps, including neglect of stress legacy effects, oversimplified spatiotemporal heterogeneity, and limited integration of concurrent stressors. Future research should prioritize multi-scale and multi-dimensional integrated analysis, long-term multi-scenario simulations with field validation, and harnessing plant–microbe interactions to enhance drought resilience, providing a theoretical basis for ecosystem sustainability and agricultural production under climate change. Full article

(This article belongs to the Special Issue Wetland Conservation and Ecological Restoration)

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19 pages, 706 KB

Open AccessEditor’s ChoiceReview

Simulation and Prediction of Soil–Groundwater Pollution: Current Status and Challenges

by Chengyu Zhang, Xiaojuan Qiao, Xinyu Chai and Wenjin Yu

Water 2025, 17(17), 2500; https://doi.org/10.3390/w17172500 - 22 Aug 2025

Cited by 4 | Viewed by 2723

Abstract

Soil–groundwater pollution is a complex environmental phenomenon formed by the coupling of multiple processes. Due to the concealment of pollution, the persistence of harm, and the complexity of the system, soil–groundwater pollution has become a major environmental issue of increasing concern. The simulation [...] Read more.

Soil–groundwater pollution is a complex environmental phenomenon formed by the coupling of multiple processes. Due to the concealment of pollution, the persistence of harm, and the complexity of the system, soil–groundwater pollution has become a major environmental issue of increasing concern. The simulation and prediction of different types of models, different pollutants, and different scales in soil and groundwater have always been the research hotspots for pollution prevention and control. Starting from the mathematical mechanism of pollutant transport in soil and groundwater, this study reviews the method models represented by empirical models, analytical models, statistical models, numerical models, and machine learning, and expounds the characteristics and applications of the various representative models. Our Web of Science analysis (2015–2025) identifies 3425 relevant studies on soil–groundwater pollution models. Statistical models dominated (n = 1155), followed by numerical models (n = 878) and machine learning (n = 703). Soil pollution studies (n = 1919) outnumber groundwater research (n = 1506), with statistical models being most prevalent for soil and equally common as numerical models for groundwater. Then this study summarizes the research status of soil–groundwater pollution simulation and prediction at the level of multi-scale numerical simulation and the pollutant transport mechanism. It also discusses the development trend of artificial intelligence innovation applications such as machine learning in soil–groundwater pollution, looks forward to the challenges and measures to cope with them, and proposes to systematically respond to core challenges in soil and groundwater pollution simulation and remediation through new technology development, multi-scale and multi-interface coupling, intelligent optimization algorithms, and pollution control collaborative optimization methods for pollution management, so as to provide references for the future simulation, prediction, and remediation of soil–groundwater pollution. Full article

(This article belongs to the Topic Advances in Hydrogeological Research)

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22 pages, 9268 KB

Open AccessEditor’s ChoiceArticle

Carbon Reduction Strategies for Typical Wastewater Treatment Processes (A²/O): Response Surface Optimization, Mechanism, and Application Analysis

by Siqi Tong, Guangbing Liu, Xi Meng, Chunkai Huang, Siwen Chen, Zhiquan Xiang, Weijing Liu, Jinyou Shen and Yi Wang

Water 2025, 17(17), 2505; https://doi.org/10.3390/w17172505 - 22 Aug 2025

Cited by 2 | Viewed by 3270

Abstract

With increasing wastewater treatment demands and decarbonization goals, synergistic reduction in pollutants and green house gas (GHG) emissions is crucial. High process emissions like N₂O pose significant challenges, yet optimized carbon reduction strategies for conventional plants are lacking. This study developed [...] Read more.

With increasing wastewater treatment demands and decarbonization goals, synergistic reduction in pollutants and green house gas (GHG) emissions is crucial. High process emissions like N₂O pose significant challenges, yet optimized carbon reduction strategies for conventional plants are lacking. This study developed three mathematical models to quantify the impact of dissolved oxygen (DO), influent salinity, and C/N ratio on direct emissions (CH₄, N₂O) and indirect emissions. Response Surface Methodology (RSM) optimized these factors to minimize GHG emissions under three accounting scenarios: (1) plants with CH₄ reuse systems: salinity = 0.5 g L⁻¹, DO = 3.67 mg L⁻¹, C/N = 12.75; (2) plants focusing solely on direct emissions: salinity = 0.5 g L⁻¹, DO = 3.35 mg L⁻¹, C/N = 3; and (3) plants assessing total emissions: salinity = 0.5 g L⁻¹, DO = 2.5 mg L⁻¹, C/N = 7.18. Key findings indicated that increasing salinity exacerbated greenhouse gas emissions. Elevated DO levels in the aerobic stage reduced N₂O emissions but increased indirect emissions in the A²/O process. Higher C/N ratios promoted anaerobic CH₄ production, but sufficient carbon reduced N₂O by enabling complete heterotrophic denitrification. A 60−day continuous GHG emissions monitoring campaign was conducted at a WWTP to validate the actual emission reductions achievable under the identified optimal control conditions. An analysis and comparison of operational and economic costs were also performed. The findings provide practical insights into sustainable GHG emission management and offer potential solutions to advance the synergistic reduction in GHG emissions and pollutants. Full article

(This article belongs to the Special Issue Low-Carbon Technologies and Digital Solutions for Wastewater Treatment)

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