Water

25 pages, 46333 KiB

Open AccessArticle

Integrating Rainfall Distribution Patterns and Slope Stability Analysis in Determining Rainfall Thresholds for Landslide Occurrences: A Case Study

by Meen-Wah Gui, Hsin-An Chu, Ming-Chien Chung and Lan-Sheng Chih

Water 2025, 17(8), 1240; https://doi.org/10.3390/w17081240 - 21 Apr 2025

Abstract

After a series of rainfall-related slope incidents that threatened immediately protected entities, the Taipei City government initiated a slope deformation monitoring and investigation program for potential landslides in its administrative districts and a review of its current rainfall thresholds for landslide occurrences, which [...] Read more.

After a series of rainfall-related slope incidents that threatened immediately protected entities, the Taipei City government initiated a slope deformation monitoring and investigation program for potential landslides in its administrative districts and a review of its current rainfall thresholds for landslide occurrences, which is the aim of this study, in 2021 for better preparedness in facing the extreme weather- and climate-related natural hazards. Due to the limited availability of historical data, this study employed a physically based method to derive rainfall thresholds for landslide occurrences by integrating different rainfall distribution patterns into infiltration and slope stability analyses. The study examined four rainfall patterns—uniform, intermediate, advanced, and delayed—to assess their impact on slope failure mechanisms. Results indicate that advanced rainfall patterns (where peak rainfall occurs early) trigger the fastest failures, while delayed rainfall patterns lead to gradual groundwater accumulation, causing slope destabilization over longer durations. The study also found that short-duration rainfall (24 h) mainly triggers shallow landslides, whereas prolonged rainfall (72 h) leads to deep landslides. The study’s findings are crucial for early landslide warning systems, which provide different mitigation strategies based on the expected rainfall duration and provide a scientific basis for authorities to revise and integrate new rainfall thresholds into their real-time landslide warning systems. Full article

(This article belongs to the Special Issue Slope Stability Analyses and Risk Assessment for Rainfall-Induced Landslides)

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20 pages, 30643 KiB

Open AccessArticle

Physics-Guided Deep Learning for Spatiotemporal Evolution of Urban Pluvial Flooding

by Hyuna Woo, Hyeonjin Choi, Minyoung Kim and Seong Jin Noh

Water 2025, 17(8), 1239; https://doi.org/10.3390/w17081239 - 21 Apr 2025

Abstract

Climate change and rapid urbanization have increased the risk of urban flooding, making timely and accurate flood prediction crucial for disaster response. However, conventional physics-based models are limited in real-time applications due to their high computational costs. Recent advances in deep learning have [...] Read more.

Climate change and rapid urbanization have increased the risk of urban flooding, making timely and accurate flood prediction crucial for disaster response. However, conventional physics-based models are limited in real-time applications due to their high computational costs. Recent advances in deep learning have enabled the development of efficient surrogate models that capture complex nonlinear relationships in hydrological processes. This study presents a deep learning-based surrogate model designed to efficiently reproduce the spatiotemporal evolution of urban pluvial flooding using data from physics-based models. For the Oncheon-cheon catchment in Busan, the spatiotemporal evolution of inundation at a 10 m spatial resolution was simulated using the physics-based model for various synthetic inundation scenarios to train the deep learning model based on a Convolutional Neural Network (CNN). The training dataset was constructed using synthetic rainfall scenarios based on probabilistic rainfall data, while the model was validated using both a synthetic flood event and a historical flood event from July 2020 with observed ground-based rainfall measurements. The model’s performance was evaluated using quantitative metrics, including the Hit Rate (HR), False Alarm Ratio (FAR), and Critical Success Index (CSI), by comparing results against both synthetic and real (historical) flood events. Validation results demonstrated high reproducibility, with a CSI of 0.79 and 0.73 for the synthetic and real experiments, respectively. In terms of computational efficiency, the deep learning model achieved a speedup 16.4 times the parallel version and 82.2 times the sequential version of the physics-based model, demonstrating its applicability for near real-time flood prediction. The findings of this study contribute to the advancement of urban flood prediction and early warning systems by offering a cost-effective, computationally efficient alternative to conventional physics-based flood modeling, enabling faster and more adaptive flood risk management. Full article

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

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29 pages, 10523 KiB

Open AccessArticle

Simulated Effects of Future Water Availability and Protected Species Habitat in a Perennial Wetland, Santa Barbara County, California

by Geoffrey Cromwell, Daniel P. Culling, Matthew J. Young and Joshua D. Larsen

Water 2025, 17(8), 1238; https://doi.org/10.3390/w17081238 - 21 Apr 2025

Abstract

This study evaluates the potential water availability in Barka Slough and the effects of changing hydrological conditions on the aquatic habitat of five protected species. Barka Slough is a historically perennial wetland at the downstream western end of the San Antonio Creek Valley [...] Read more.

This study evaluates the potential water availability in Barka Slough and the effects of changing hydrological conditions on the aquatic habitat of five protected species. Barka Slough is a historically perennial wetland at the downstream western end of the San Antonio Creek Valley watershed (SACVW). A previously published hydrologic model of the SACVW for 1948–2018 was extended to include 2019–2021 and then modified to simulate the future years of 2022–2051. Two models simulating the future years of 2022–2051 were constructed, each with different climate inputs: (1) a repeated historical climate and (2) a 2070-centered Drier Extreme Warming climate (2070 DEW). The model with the 2070 DEW climate had warmer temperatures and an increase in average annual precipitation driven by larger, albeit more infrequent, precipitation events than the model with the historical climate. Simulated groundwater pumpage resulted in cumulative groundwater storage depletion and groundwater-level decline in Barka Slough in both future models. The simulations indicate that Barka Slough may transition from a perennial to an ephemeral wetland. Streamflow, stream disconnection, and depth to groundwater are key habitat metrics for federally listed species in Barka Slough. Future seasonal conditions for each metric are more likely to affect federally listed species’ habitats under 2070 DEW climatic conditions. Future seasonal streamflow volume may negatively impact unarmored threespine stickleback (Gasterosteus aculeatus williamsoni) and tidewater goby (Eucyclogobis newberryi) habitats. Future seasonal stream disconnection may negatively impact the unarmored threespine stickleback habitat. Future groundwater-level decline may negatively impact Gambel’s watercress (Nasturtium gambelii) and La Graciosa thistle (Cirsium scariosum var. loncholepis) habitats and could influence the ability to use Barka Slough as a restoration or reintroduction site for these species. Results from this study can be used to inform water management decisions to sustain future groundwater availability in the SACVW. Full article

(This article belongs to the Special Issue Integrated Approaches to Water Resources and Environmental Management: Innovations in Simulation and Impact Assessment)

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11 pages, 2741 KiB

Open AccessArticle

Lanthanum and Sludge Extracellular Polymeric Substances Coprecipitation-Modified Ceramic for Treating Low Phosphorus-Bearing Wastewater

by Yao-Yao Lu, Chao-Xi Yang, Ke-Yu Chen, Jiao-Jiao Wang, Bao-Cheng Huang and Ren-Cun Jin

Water 2025, 17(8), 1237; https://doi.org/10.3390/w17081237 - 21 Apr 2025

Abstract

Excessive phosphorus discharge from fertilizers and detergents has caused severe eutrophication in water bodies, necessitating the upgrading of efficient and cost-effective adsorbents for phosphorus removal. In this study, a novel lanthanum and extracellular polymeric substance (EPS) coprecipitation-modified ceramic (La-EPS-C-450) was developed to address [...] Read more.

Excessive phosphorus discharge from fertilizers and detergents has caused severe eutrophication in water bodies, necessitating the upgrading of efficient and cost-effective adsorbents for phosphorus removal. In this study, a novel lanthanum and extracellular polymeric substance (EPS) coprecipitation-modified ceramic (La-EPS-C-450) was developed to address the limitations of existing adsorbents. The ceramic filler served as a robust and scalable matrix for lanthanum loading, while EPS introduced functional groups and carbonate components that enhanced adsorption efficiency. The prepared adsorbent manifested a maximum phosphorus adsorption capacity of 83.5 mg P/g-La at 25 °C, with its performance well expressed by the Freundlich isotherm model, indicating that it was a multilayer adsorption process. The adsorption mechanism was driven by electrostatic attraction and ligand exchange between lanthanum and phosphate ions, forming inner-sphere complexes. The material demonstrated unfluctuating‌ performance across a pH range of 3–7 and retained high selectivity in the presence of competing anions. In practical applications, La-EPS-C-450 effectively removed phosphorus from actual river water, achieving a treatment capacity of 1800 bed volumes in a continuous-flow fixed column system. This work provides valuable insights into the progress of advanced ceramic-based adsorbents and demonstrates the potential of La-EPS-C-450 as a cost-efficient and effective material for phosphorus removal in water treatment applications. Full article

(This article belongs to the Special Issue Metal Elements and Wastewater Treatment: Adsorption, Catalysis and Oxidation)

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35 pages, 8487 KiB

Open AccessReview

A Review of the Sources, Monitoring, Detection, and Removal of Typical Olfactory Substances Geosmin and 2-Methylisoborneol

by Mingyang Wang, Yufeng Xu, Yiping Xie, Liu Yang and Jun Zhang

Water 2025, 17(8), 1236; https://doi.org/10.3390/w17081236 - 21 Apr 2025

Abstract

As the key sensory indicators for drinking water quality evaluation, the odor problems caused by geosmin (GSM) and dimethylisobornyl alcohol (2-MIB) have led to several major water supply crises around the world. In this paper, the theoretical framework of the whole process control [...] Read more.

As the key sensory indicators for drinking water quality evaluation, the odor problems caused by geosmin (GSM) and dimethylisobornyl alcohol (2-MIB) have led to several major water supply crises around the world. In this paper, the theoretical framework of the whole process control of olfactory substances is systematically constructed through innovative research from multiple perspectives, and the main contributions are as follows: a comprehensive analysis of the sources of GSM and 2-MIB; an innovative summary of the monitoring methods of cyanobacteria and elaboration on the ways of controlling cyanobacteria in the water source; a comprehensive combing of the methods of olfactory substance detection technology, mainly the application of the new sensor technology; an in-depth summary of the techniques of olfactory removal; an analysis of the problems of the traditional water treatment technology; an analysis of the development and application of the new sensor technology, analyzing the advantages and disadvantages of traditional water treatment technology and classifying and elaborating on advanced oxidation processes (AOPs); and suggestions for the future research direction of each segment. Full article

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

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27 pages, 4858 KiB

Open AccessArticle

Appraisal of Groundwater Potential Zones at Melur in Madurai District (Tamil Nadu State) in India for Sustainable Water Resource Management

by Selvam Sekar, Subin Surendran, Priyadarsi D. Roy, Farooq A. Dar, Akhila V. Nath, Muralitharan Jothimani and Muthukumar Perumal

Water 2025, 17(8), 1235; https://doi.org/10.3390/w17081235 - 21 Apr 2025

Abstract

Overextraction of groundwater, as well as rapidly changing land use patterns, climatic change, and anthropogenic activities, in the densely populated Melur of Tamil Nadu state in India, has led to aquifer degradation. This study maps the groundwater potential (GWPZ) by evaluating 678 km [...] Read more.

Overextraction of groundwater, as well as rapidly changing land use patterns, climatic change, and anthropogenic activities, in the densely populated Melur of Tamil Nadu state in India, has led to aquifer degradation. This study maps the groundwater potential (GWPZ) by evaluating 678 km² of this region in the Analytical Hierarchy Processes (AHP) and by using remote sensing and GIS tools as part of SDG 6 for the sustainable management of drinking, irrigation, and industrial uses for future generations. Data information layers, such as aquifer (a), topography (t), lineaments (l), land-use/land-cover (LuLc), soil (s), rainfall (r), and drainage (d) characteristics, separated the study area between poor and excellent groundwater potential zones with 361 km² or 53% of the study area remaining as low GWP and the prospective excellent groundwater potential zone covering only 9 km² (1.3% of total area). The integrated approach of the GWPZ and Water Quality Index (WQI) can effectively identify different zones based on their suitability for extraction and consumption for better understanding. This study also evaluates the performance of three machine learning models, such as Random Forest (RF), Gradient Boosting, and Support Vector Machine (SVM), based on a classification method using the same layers that govern the groundwater potential. The results indicate that both the RF model and Gradient Boosting achieved 100% accuracy, while SVM had a lower accuracy of 50%. Performance metrics such as precision, recall, and F1-score were analyzed to assess classification effectiveness. The findings highlight the importance of model selection, dataset size, and feature importance in achieving optimal classification performance. Results of this study highlight that the aquifer system of Melur has a low groundwater reserve, and it requires adequate water resource management strategies such as artificial recharge, pumping restriction, and implementation of groundwater tariffs for sustainability. Full article

(This article belongs to the Section Hydrogeology)

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15 pages, 10318 KiB

Open AccessArticle

Study on the Complex Erosion Characteristics and Specific Influencing Factor Mechanism in a Francis Hydraulic Turbine

by Jinliang Wang, Xijie Song, Jiabing Wang and Zhengwei Wang

Water 2025, 17(8), 1234; https://doi.org/10.3390/w17081234 - 21 Apr 2025

Abstract

Sediment erosion of hydraulic turbines has gradually become a key factor affecting their long-term stable operation. There are many different factors that can cause erosion in the Francis hydraulic turbine; among them, the vortex occurs in the turbine, which is also a negative [...] Read more.

Sediment erosion of hydraulic turbines has gradually become a key factor affecting their long-term stable operation. There are many different factors that can cause erosion in the Francis hydraulic turbine; among them, the vortex occurs in the turbine, which is also a negative factor for the unit. In this paper, the purpose is to study the complex erosion characteristics and specific influencing factor mechanism. The method is based on numerical simulation, combined with the verification data on site. Research results show that the differences in flow patterns among various components correspond to the erosion distribution of the unit at the same location, indicating that local flow patterns affect the unit’s erosion. The highest total erosion rate is on the surface of the runner at 1.08 × 10⁻³ kg·s⁻¹·m⁻². The erosion rate on the guide vane wall is second highest, also at 9.8 × 10⁻⁴ kg·s⁻¹·m⁻². The total erosion rate in the clearance is lower than that on the guide vane wall at 7.03 × 10⁻⁴ kg·s⁻¹·m⁻². The lowest total erosion rate is found in the draft tube at 2.57 × 10⁻⁴ kg·s⁻¹·m⁻². The effect of local vortices not only exacerbate the microscopic damage on the blade surface but also leads to a more obvious nonuniform erosion distribution, especially at the clearance, where erosion is more severe. The vortex in the guide vane passage alters the particle trajectory at the guide vane outlet, increasing the erosion in the guide vane clearance. Similarly, the vortex in the draft tube increases particle rotation, enhancing erosion on the draft tube wall. Research indicates that eliminating vortices is beneficial for reducing sediment erosion within the unit. The research results provide a theoretical basis for the optimization design of Francis hydraulic turbine. Full article

(This article belongs to the Special Issue Hydrodynamic Science Experiments and Simulations)

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21 pages, 286 KiB

Open AccessReview

Membrane-Based Persulfate Activation for Wastewater Treatment: A Critical Review of Materials, Mechanisms and Expectation

by Wenye Li, Lin Guo, Binghan Xie, Weijia Gong, Guoyu Zhang, Zhipeng Li, Hong You, Fengwei Jia and Jinlong Wang

Water 2025, 17(8), 1233; https://doi.org/10.3390/w17081233 - 21 Apr 2025

Abstract

Membrane-based persulfate catalysis technology offers a dual approach to wastewater treatment by facilitating both physical separation and chemical oxidation. This innovative method significantly enhances pollutant removal efficiency while mitigating membrane fouling, positioning it as a promising advanced oxidation technology for wastewater management. This [...] Read more.

Membrane-based persulfate catalysis technology offers a dual approach to wastewater treatment by facilitating both physical separation and chemical oxidation. This innovative method significantly enhances pollutant removal efficiency while mitigating membrane fouling, positioning it as a promising advanced oxidation technology for wastewater management. This review comprehensively examines the critical aspects of material design, activation mechanisms, and technological challenges. Membrane materials and structures are crucial for enhancing the overall efficiency of the technology. By analyzing various catalytic materials and modification strategies, the study reveals the intricate interactions between membrane structures, catalytic performance, and pollutant degradation. The clear mechanism of pollutant degradation is the key to achieve accurate degradation. The research highlights three primary activation pathways: free radical, non-radical, and hybrid mechanisms, each offering unique advantages in addressing complex water contamination. Finally, the future challenges and research directions are put forward. Despite remarkable progress, challenges remain in membrane stability, economic feasibility, and large-scale implementation. Therefore, this study outlines the latest materials, mechanisms, and prospects of membrane-based persulfate technology, which are expected to promote its widespread application in environmental governance. Full article

(This article belongs to the Special Issue Membrane Technology for Desalination and Wastewater Treatment)

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Graphical abstract

37 pages, 9663 KiB

Open AccessArticle

Integrated Assessment of Groundwater Quality for Water-Saving Irrigation Technology (Western Kazakhstan)

by Yermek Murtazin, Vitaly Kulagin, Vladimir Mirlas, Yaakov Anker, Timur Rakhimov, Zhyldyzbek Onglassynov and Valentina Rakhimova

Water 2025, 17(8), 1232; https://doi.org/10.3390/w17081232 - 21 Apr 2025

Abstract

Western Kazakhstan is susceptible to desertification, with surface water resource scarcity constraining agricultural development. Groundwater has substantial potential as a reliable and secure alternative to other water resources, particularly for irrigation, which is required to ensure food security. Eight aquifer segments with an [...] Read more.

Western Kazakhstan is susceptible to desertification, with surface water resource scarcity constraining agricultural development. Groundwater has substantial potential as a reliable and secure alternative to other water resources, particularly for irrigation, which is required to ensure food security. Eight aquifer segments with an exploitable potential of 0.24 km³/year have been identified for the integrated assessment of groundwater’s suitability for irrigation. The assessment criteria included hydro-chemical groundwater characteristics and irrigated land soil-reclamation conditions. The primary objectives of this study were to assess the groundwater quality for irrigation and to develop a practical operation scheme for rational groundwater use in water-saving irrigation technologies and optimize agricultural crop cultivation. Approximately 90% of the groundwater in these aquifer segments was found to be suitable for irrigation, with a total amount of 6520 thousand m³/day and a salinity of up to 1 g/L, and an additional 12,971 thousand m³/day had a water salinity of up to 3 g/L. Only approximately 10% had TDS values above 3 g/L and up to 6.5 g/L, categorized as conditionally suitable for restricted customized agricultural crop irrigation. Irrigated land development by complex soil desalination agro-reclamation operations enabled the use of brackish water for irrigation. The integrated analysis allowed the development of drip irrigation and sprinkling system irrigation schemes that gradually replaced wasteful surface irrigation. The irrigated land prospective area recommended for groundwater irrigation development is 653 km², with the further restructuring of cultivated areas, reducing the number of annual grasses and grain crops and increasing the number of vegetables, potatoes, and perennial grasses. Full article

(This article belongs to the Special Issue Study of the Soil Water Movement in Irrigated Agriculture III)

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27 pages, 3161 KiB

Open AccessArticle

A 21-Year Study of Virtual Water Trade in Ukraine’s Agricultural Sector: Crop Production and Water Use

by Ahmed S. Afifi and Albert S. Kim

Water 2025, 17(8), 1231; https://doi.org/10.3390/w17081231 - 21 Apr 2025

Abstract

This study quantitatively evaluates Ukraine’s agricultural virtual water footprint over two decades (2001–2021), focusing on ten representative crops with varying water demands. We assess the environmental and economic implications of virtual water flows and emphasize the need for more sustainable agricultural water management. [...] Read more.

This study quantitatively evaluates Ukraine’s agricultural virtual water footprint over two decades (2001–2021), focusing on ten representative crops with varying water demands. We assess the environmental and economic implications of virtual water flows and emphasize the need for more sustainable agricultural water management. Our findings reveal a shift in Ukraine toward water-intensive crops despite their high-water requirements, highlighting critical trends in production and trade. While crops like sunflowers and maize generate higher economic returns per unit of weight, less water-intensive crops such as wheat and barley exhibit greater profitability per unit of water consumed, albeit with lower trade volumes. These insights challenge prevailing agricultural practices and underscore the necessity for a more strategic approach that balances economic productivity with responsible water stewardship. Our study provides a data-oriented framework for optimizing water use in Ukrainian agriculture, offering essential guidance for policy interventions and sustainable development. Full article

(This article belongs to the Special Issue Balancing Competing Demands for Sustainable Water Development)

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24 pages, 7733 KiB

Open AccessArticle

Multi-Objective Model for Efficient, Equitable, and Sustainable Water Allocation Under Uncertainty: A Case Study of Namhan River Basin, South Korea

by Flavia D. Frederick and Doosun Kang

Water 2025, 17(8), 1230; https://doi.org/10.3390/w17081230 - 20 Apr 2025

Abstract

Water allocation under uncertainty remains a critical challenge in water-scarce regions. This study presents an integrated water allocation model that explicitly incorporates uncertainty through stochastic streamflow simulations and addresses multiple objectives—efficiency, equity, and sustainability—within a unified framework. The model uses historical inflow data, [...] Read more.

Water allocation under uncertainty remains a critical challenge in water-scarce regions. This study presents an integrated water allocation model that explicitly incorporates uncertainty through stochastic streamflow simulations and addresses multiple objectives—efficiency, equity, and sustainability—within a unified framework. The model uses historical inflow data, future demand projections, and a multi-objective optimization approach based on the NSGA-II to generate trade-off solutions. To support decision-making, TOPSIS is applied to identify the most balanced allocation strategies from the Pareto-optimal sets. The model is applied to the Namhan River Basin in South Korea, with two key applications: (1) developing adaptive water allocation strategies under dry, normal, and wet hydrological conditions, and (2) proposing targeted infrastructure enhancements—including new dams, transmission lines, and intake points—to address vulnerabilities in dry years. The results demonstrate that the proposed model improves supply reliability, economic efficiency, equity across regions, and sustainability through river maintenance and reservoir storage compliance. This study provides a generalizable and practical decision-support tool for long-term water planning under climate and demand uncertainties, offering actionable insights for water-deficient basins. Full article

(This article belongs to the Special Issue Optimization-Simulation Modeling of Sustainable Water Resource)

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17 pages, 3454 KiB

Open AccessArticle

Enhanced Adsorption of Aqueous Ciprofloxacin Hydrochloride by a Manganese-Modified Magnetic Dual-Sludge Biochar

by Jingxi Tie, Mengjia Yan, Sihao Shao and Xiaohan Duan

Water 2025, 17(8), 1229; https://doi.org/10.3390/w17081229 - 20 Apr 2025

Abstract

In this study, an effective composite material, manganese-modified magnetic dual-sludge biochar (Mn@MDSBC), was developed for the adsorption of ciprofloxacin hydrochloride (CIP). This composite was prepared by means of a simple one-pot method, which involved the pyrolysis of iron-based waterworks sludge (IBWS) and paper [...] Read more.

In this study, an effective composite material, manganese-modified magnetic dual-sludge biochar (Mn@MDSBC), was developed for the adsorption of ciprofloxacin hydrochloride (CIP). This composite was prepared by means of a simple one-pot method, which involved the pyrolysis of iron-based waterworks sludge (IBWS) and paper mill sludge (PMS) loaded with manganese (Mn) under controlled conditions in a nitrogen atmosphere. The synthesized Mn@MDSBC was subjected to a comprehensive suite of characterization approaches, which included N₂ adsorption–desorption, X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Subsequently, static adsorption tests were conducted to investigate how different factors, including the initial solution pH, reaction time and temperature, CIP concentration, and ionic strength influence the adsorption of CIP by Mn@MDSBC. Mn@MDSBC had the maximum CIP adsorption capacity of 75.86 mg/g at pH 5, among the pH values ranging from 3 to 9. The pseudo-second order model provided the best description of the adsorption process, while the experimental data aligned more closely with the Langmuir equation than with the Freundlich model, indicating monolayer adsorption. The adsorption process was found to be non-spontaneous and exothermic according to thermodynamic analysis. The presence of Cl⁻ and SO₄²⁻ enhanced CIP adsorption, while PO₄³⁻ weakened it. After five cycles of reuse, Mn@MDSBC experienced a 17.17% loss in CIP adsorption capacity. The primary mechanisms for CIP removal by Mn@MDSBC were identified as physical and chemical adsorption, hydrogen bonding, and π-π stacking interactions. In summary, the study underscores the high efficiency of Mn@MDSBC as a composite material for CIP adsorption, highlighting its potential for application in wastewater treatment processes. Full article

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

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17 pages, 3828 KiB

Open AccessArticle

A Five-Dimensional Comprehensive Evaluation of the Yellow River Basin’s Water Environment Using Entropy–Catastrophe Progression Method: Implications for Differentiated Governance Strategies

by Yaqun Zhang and Yangan Ren

Water 2025, 17(8), 1228; https://doi.org/10.3390/w17081228 - 20 Apr 2025

Abstract

The systematic evaluation of the water environment in the Yellow River basin is a critical scientific basis for achieving the goals of ecological protection and high-quality development. In this study, a five-dimensional comprehensive evaluation framework (“quality–quantity–space–flow–biota”) consisting of 19 indicators was constructed. The [...] Read more.

The systematic evaluation of the water environment in the Yellow River basin is a critical scientific basis for achieving the goals of ecological protection and high-quality development. In this study, a five-dimensional comprehensive evaluation framework (“quality–quantity–space–flow–biota”) consisting of 19 indicators was constructed. The entropy method and the catastrophe progression method were innovatively combined to solve the limitations of traditional evaluation models in characterizing the nonlinear relationships within water environment systems. The results indicated that the Yellow River basin’s overall comprehensive water environment index was 0.032, classified as “good”. However, the spatial differentiation is significant, showing a step-by-step degradation characteristic of “upstream > downstream > midstream”. Gansu Province (0.028), Ningxia Hui Autonomous Region (0.026), Shaanxi (0.024), and Shanxi (0.020) were rated as “poor” and urgently need to be regulated. The core problems are water shortage (Gansu, Ningxia), water quality deterioration (Shaanxi, Shanxi), and fragmentation of aquatic space (Shanxi, Shaanxi). The findings of this study provided a quantitative tool for differentiated governance in the Yellow River basin which could directly support the decision-making needs of “zoning control and precise policy implementation” in the “Outline of the Plan for Ecological Protection and High-quality Development of the Yellow River Basin”. Full article

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

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16 pages, 6897 KiB

Open AccessArticle

Investigating the Spatiotemporal Variation in Extreme Precipitation Indices in Iran from 1990 to 2020

by Ebrahim Fattahi, Saeedeh Kamali, Ebrahim Asadi Oskouei and Maral Habibi

Water 2025, 17(8), 1227; https://doi.org/10.3390/w17081227 - 20 Apr 2025

Abstract

This study examines the spatiotemporal characteristics of extreme precipitation indices in Iran. It analyzes data from 38 synoptic stations across the country, covering the period from 1990 to 2020, focusing on the 11 most common extreme precipitation indices defined by the Expert Team [...] Read more.

This study examines the spatiotemporal characteristics of extreme precipitation indices in Iran. It analyzes data from 38 synoptic stations across the country, covering the period from 1990 to 2020, focusing on the 11 most common extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis employs the Mann–Kendall (M–K) trend test. The findings indicate that the indices PRCPTOT (annual total precipitation), R20 mm (very heavy precipitation days), R10 mm (heavy precipitation days), R25 mm (number of wet days), Rx1 day (maximum 1-day precipitation), Rx5 day (maximum 5-day precipitation), SDII (simple daily intensity index), R95p (very wet day precipitation), R99p (extremely wet day precipitation), and CWDs (consecutive wet days) showed the highest values in the northern and western regions of the country, particularly at stations like Ramsar, Hamedan, Ilam, Kermanshah, and Yasouj. Conversely, the eastern and southeastern parts of the country showed the lowest values for these indices. The Consecutive Dry Day (CDD) index exhibited the highest values at Zabol station (228 days) and Abadan station (193 days) in the southern region of the country. Generally, precipitation extremes in the western, northwestern, and Caspian Sea coasts showed an increasing trend, while the eastern, southeastern, and central parts of the country demonstrated a decreasing trend. The trend test results indicate significant mutations in all precipitation indices, except for SDII, with mutation points primarily occurring during the decade from 2000 to 2010. The magnitude of mutation for each index post-mutation is generally greater than before. This study provides valuable information for decision-makers in agriculture, food security, water, and the environment. It also serves as a resource for natural disaster prevention and mitigation. Full article

(This article belongs to the Special Issue Analysis of Extreme Precipitation Under Climate Change)

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17 pages, 2831 KiB

Open AccessArticle

The Use of Membrane Processes in Manganese Removal from Drinking Water

by Ján Ilavský, Danka Barloková and Michal Prosňanský

Water 2025, 17(8), 1226; https://doi.org/10.3390/w17081226 - 20 Apr 2025

Abstract

This article deals with the removal of manganese from water via ultrafiltration and the oxidation of manganese with chlorine dioxide or potassium permanganate before ultrafiltration. The dose of oxidizing agents, time of contact with water, and manganese concentration in raw and treated water [...] Read more.

This article deals with the removal of manganese from water via ultrafiltration and the oxidation of manganese with chlorine dioxide or potassium permanganate before ultrafiltration. The dose of oxidizing agents, time of contact with water, and manganese concentration in raw and treated water were monitored. A fully automated ultrafiltration device with membrane module UA-640 (Microdyn-Nadir) was used. A tubular reactor with a static mixer was used to reach a sufficient contact time for water with an oxidizing agent, enabling the oxidation of manganese in water. The concentration of Mn in the water source ranged from 0.150 to 0.250 mg/L Mn. The results of the experiments showed that in the case of chlorine dioxide, the efficiency of removing Mn from water of 74.31% was achieved at a flow rate of 60 L/h, a dose of 0.4 mg/L ClO₂ and a retention time of 30.5 min; the concentration of Mn in the treated water was 0.037 mg/L, while in the case of KMnO₄ the efficiency was up to 100% at a flow rate of 650 L/h, a dose of 0.3 mg/L Mn (determined after adding KMnO₄) and a retention time of 2.8 min; the concentration of Mn in the treated water was below the detection limit of 0.005 mg/L of the measuring device. Pilot plant experiments confirmed the efficiency of ultrafiltration, demonstrating the possibility of decreasing the manganese concentration below the limit for drinking water using the considered method. Full article

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

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17 pages, 5459 KiB

Open AccessArticle

Water-Quality Spatiotemporal Characteristics and Their Drivers for Two Urban Streams in Indianapolis

by Rui Li, Gabriel Filippelli, Jeffrey Wilson, Na Qiao and Lixin Wang

Water 2025, 17(8), 1225; https://doi.org/10.3390/w17081225 - 20 Apr 2025

Abstract

Water quality in urban streams is critical for the health of aquatic and human life, as it impacts both the environment and water availability. The strong impacts of changing climate and land use on water quality necessitate a better understanding of how stream [...] Read more.

Water quality in urban streams is critical for the health of aquatic and human life, as it impacts both the environment and water availability. The strong impacts of changing climate and land use on water quality necessitate a better understanding of how stream water quality changes over space and time. To this end, four key water-quality parameters—Escherichia coli (E. coli), nitrate (NO₃⁻), sulfate (SO₄²⁻), and chloride (Cl⁻)—were collected at 12 sites along Fall Creek and Pleasant Run streams in Indianapolis, Indiana USA from 2003 to 2021 on a seasonal basis: March, July, and October each year. Two-way ANOVA tests were used to determine the impacts of seasonality and location on these parameters. Correlation and RDA (redundancy analysis) were used to determine the importance of climatic drivers. Linear regressions were used to quantify the impacts of land-use types on water quality integrating buffer zone size and sub-watershed analysis. Strong seasonal variations of the water-quality parameters were found. March had higher levels of NO₃⁻, SO₄²⁻, and Cl⁻ than other months. July had the highest E. coli concentrations compared to March and October. Seven-days antecedent snow and precipitation were found to be significantly related to Cl⁻ and log₁₀(E. coli) and can explain up to 53% and 31% of their variations, respectively. Spatially, urban built-up land in a 1000 m buffer around the sampling sites was positively correlated with the log₁₀(E. coli) variation, while lawn cover was positively related to NO₃⁻ concentrations within 500 m buffers. Conversely, NDVI (Normalized Difference Vegetation Index) values were negatively related to all variables. In conclusion, E. coli is more impacted by higher precipitation and urban land coverage, which could be related to more combined sewer overflow events in July. Cl⁻ peaking in March and its relationship with snow indicate salt runoff during snow melting events. NO₃⁻ and SO₄²⁻ increases are likely due to fertilizer input from residential lawns near streams. This suggests that Indianapolis stream water-quality changes are influenced by both changing climate and land-cover/-muse types. Full article

(This article belongs to the Special Issue Modeling and Monitoring Water Quality Management in Support of Public Health)

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32 pages, 17827 KiB

Open AccessArticle

Trends in Coral Reef Habitats over Two Decades: Lessons Learned from Nha Trang Bay Marine Protected Area, Vietnam

by Nguyen Trinh Duc Hieu, Nguyen Hao Quang, Tran Duc Dien, Vo Thi Ha, Nguyen Dang Huyen Tran, Tong Phuoc Hoang Son, Tri Nguyen-Quang, Tran Thi Thuy Hang and Ha Nam Thang

Water 2025, 17(8), 1224; https://doi.org/10.3390/w17081224 - 19 Apr 2025

Viewed by 170

Abstract

Coral reefs are well known for their diversity and value, providing habitats for a third of marine species within just 0.2% of the ocean. However, these natural habitats face significant threats and degradation, leading to unresolved issues related to coral loss inventory, coral [...] Read more.

Coral reefs are well known for their diversity and value, providing habitats for a third of marine species within just 0.2% of the ocean. However, these natural habitats face significant threats and degradation, leading to unresolved issues related to coral loss inventory, coral protection, and the implementation of long-term conservation policies. In this study, we examined two decades of changes in coral spatial distribution within the Nha Trang Bay Marine Protected Area (MPA) using remote sensing and machine learning (ML) approaches. We identified various factors contributing to coral reef loss and analyzed the effectiveness of management policies over the past 20 years. By employing the Light Gradient Boosting Machine (LGBM) and Deep Forest (DF) models on Landsat (2002, κ = 0.83, F₁ = 0.85) and Planet (2016, κ = 0.89, F₁ = 0.82; 2024, κ = 0.92, F₁ = 0.86) images, we achieved high confidence in our inventory of coral changes. Our findings revealed that 191.38 hectares of coral disappeared from Nha Trang Bay MPA between 2002 and 2024. The 8-year period from 2016 to 2024 saw a loss of 66.32 hectares, which is in linear approximation to the 125.06 hectares lost during the 14-year period from 2002 to 2016. It is concluded that the key factors contributing to coral loss include land-use dynamics, global warming, and the impact of starfish. To address these challenges, we propose next a modern community-based management paradigm to enhance the conservation of existing coral reefs and protect potential habitats within Nha Trang Bay MPA. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence (AI) in Water Quality Monitoring)

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18 pages, 4330 KiB

Open AccessArticle

Per- and Polyfluoroalkyl Substances in Surface Water of Fuyang River (Handan Section): Occurrence, Source Apportionment, and Risk Assessment

by Xiaoying Pan, Lifeng Wu and Dong Wang

Water 2025, 17(8), 1223; https://doi.org/10.3390/w17081223 - 19 Apr 2025

Viewed by 43

Abstract

Perfluorinated and polyfluoroalkyl substances (PFASs), as an emerging type of pollutant, always pollute water quality to a certain extent. The occurrence, source, and risk of PFASs in the Fuyang River are not well understood. For the first time, the state of PFASs in [...] Read more.

Perfluorinated and polyfluoroalkyl substances (PFASs), as an emerging type of pollutant, always pollute water quality to a certain extent. The occurrence, source, and risk of PFASs in the Fuyang River are not well understood. For the first time, the state of PFASs in the upper Fuyang River (Handan section) was investigated. The results showed that there were 10 types of PFASs with concentrations higher than the limit of quantitation in the surface water of the Fuyang River. The surface water

ρ

(∑PFASs) ranges from 13.80 to 22.88

ng \cdot L^{- 1}

. The highest quality score is perfluorooctane sulfonate (PFOS), which is 59.40%. PFASs are mainly composed of long-chain substances. PFASs generally show a trend of gradually increasing downstream. PFASs have the same source, mainly from industrial activities around rivers and rainfall inputs. Principal component analysis shows that PFASs mainly come from the leather and textile manufacturing industries, fluoropolymer production, and electroplating metal industries. The concentration of PFASs in the Fuyang River has not yet affected ecology and health. Full article

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

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17 pages, 1212 KiB

Open AccessArticle

Combining Fluorescent Organic Substances, Ions, and Oxygen-18 to Trace Diverse Water Sources of River Flow in a Hilly Catchment

by Zhi-Xiang Sun, Yan-Ting Ao, Jun-Fang Cui, Xiao-Yu Li, Xiang-Yu Tang, Jian-Hua Cheng and Lu Chen

Water 2025, 17(8), 1222; https://doi.org/10.3390/w17081222 - 19 Apr 2025

Viewed by 68

Abstract

Reliable identification of river hydrograph separation is crucial for prioritizing water source areas to be protected from pollution. A field study was carried out in a hilly catchment with diverse land uses, located in Southwest China. A novel water-tracing method, combining the ratio [...] Read more.

Reliable identification of river hydrograph separation is crucial for prioritizing water source areas to be protected from pollution. A field study was carried out in a hilly catchment with diverse land uses, located in Southwest China. A novel water-tracing method, combining the ratio of two conservative fluorescent components of dissolved organic matter, two ion ratios, and oxygen-18, was proposed for river hydrograph separation with MixSIAR. During a rain event with the longest preceding no-rain period, a set of four tracers were found to be applicable to drainage areas with diverse land uses. Notably, a drier antecedent soil moisture condition could favor the occurrence of more tracers qualified for distinguishing multiple water sources of river flow. Full article

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

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20 pages, 3700 KiB

Open AccessArticle

A Single-Objective Optimization of Water Quality Sensors in Water Distribution Networks Using Advanced Metaheuristic Techniques

by Seyed Amir Saman Siadatpour, Zohre Aghamolaei, Jafar Jafari-Asl and Abolfazl Baniasadi Moghadam

Water 2025, 17(8), 1221; https://doi.org/10.3390/w17081221 - 19 Apr 2025

Viewed by 173

Abstract

This paper explores the intersection of water quality management and advanced metaheuristic algorithms (MAs) by optimizing the location of water quality sensors in urban water networks. A comparative analysis of ten cutting-edge MAs, Harris Hawk Optimization (HHO), Artemisinin Optimization (AO), Educational Competition Optimizer [...] Read more.

This paper explores the intersection of water quality management and advanced metaheuristic algorithms (MAs) by optimizing the location of water quality sensors in urban water networks. A comparative analysis of ten cutting-edge MAs, Harris Hawk Optimization (HHO), Artemisinin Optimization (AO), Educational Competition Optimizer (ECO), Fata Morgana Algorithm (FATA), Moss Growth Optimization (MGO), Parrot Optimizer (PO), Polar Lights Optimizer (PLO), Rime Optimization Algorithm (RIME), Runge Kutta Optimization (RUN), and Weighted Mean of Vectors (INFO), was conducted to determine their effectiveness in minimizing the risk of contaminated water consumption. Both benchmark and real-world water network serve as case studies to assess algorithmic performance. The optimization process focuses on reducing the volume of contaminated water by treating sensor placement as a critical design variable. EPANET 2.2 software was integrated with the optimization algorithms to simulate water quality and hydraulic behavior within the networks. The obtained results from analysis of two urban water networks revealed that the newer algorithms, such as the RIME and FATA, exhibit superior convergence rates and stability compared to traditional methods. While all tested algorithms demonstrated satisfactory performance, this study provides foundational insights for future research, paving the way for more effective algorithmic solutions in water quality management. Full article

(This article belongs to the Special Issue Machine Learning in Water Distribution Systems and Sewage Systems)

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18 pages, 2268 KiB

Open AccessArticle

Study of the Hydrological and Erosion Characteristics of Typical Spoil Heaps in the Yangtze River Delta of China

by Yanzi He, Jing Du, Zhujun Gu, Yunhao Li, Jin Ni, Jiasheng Wu, Guanghui Liao and Maimai Zeng

Water 2025, 17(8), 1220; https://doi.org/10.3390/w17081220 - 18 Apr 2025

Viewed by 89

Abstract

Spoil heaps have become a major source of anthropogenic soil erosion, but the hydrological responses and erosion mechanisms of in situ slopes under rainstorms remain poorly understood. We performed simulated rainfall experiments at real estate (Site A), railway (Site B), and railway station [...] Read more.

Spoil heaps have become a major source of anthropogenic soil erosion, but the hydrological responses and erosion mechanisms of in situ slopes under rainstorms remain poorly understood. We performed simulated rainfall experiments at real estate (Site A), railway (Site B), and railway station (Site C) construction sites, as well as spoil sites (Site D) in China’s Yangtze River Delta. Rainfall parameters, surface runoff, interflow, vertical soil moisture profiles, and sediment yield were monitored: (1) Hydrological responses differed significantly across the sites due to soil structure complexity; stable erosion after the first rainfall event was not achieved at any site except Site C. Soil erosion was the strongest at Site C, followed by Sites D, B, and A. After the second rainfall event, erosion was stable, increasing, and decreasing at Sites A, B and C, and D, respectively. (2) Runoff and the soil loss rate were positively correlated (R² > 0.7), and the slopes of the fitted regression lines were highest for Sites B and C, followed by Sites D and A. (3) Soil erodibility values based on field data were 0.0029, 0.1164, 0.1974, and 0.0989 t·hm²·h·hm⁻²·MJ⁻¹·mm⁻¹ for Sites A, B, C, and D, respectively. (4) The soil bulk density, gravel content, and silt content were key factors contributing to the severe erosion of field spoil heaps. Spoil heaps from different project types exhibited distinct hydrological and erosional behaviors, which necessitates targeted mitigation strategies to reduce severe erosion and landslide risks. Full article

(This article belongs to the Special Issue Effects of Hydrology on Soil Erosion and Soil Water Conservation)

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20 pages, 6307 KiB

Open AccessArticle

Machine Learning Models for Chlorophyll-a Forecasting in a Freshwater Lake: Case Study of Lake Taihu

by Guojin Sun, Weitang Zhu, Xiaoyan Qian, Chunlei Wei, Pengfei Xie, Yao Shi, Xiaoyong Cao and Yi He

Water 2025, 17(8), 1219; https://doi.org/10.3390/w17081219 - 18 Apr 2025

Viewed by 99

Abstract

Cyanobacteria harmful blooms (Cyano-HABs) have become a globally critical environmental issue, threatening freshwater ecosystems by degrading water quality and posing risks to human and aquatic life. Chlorophyll-a (Chl-a), a key biomarker of bloom intensity, offers crucial insights into algal bloom dynamics. However, predicting [...] Read more.

Cyanobacteria harmful blooms (Cyano-HABs) have become a globally critical environmental issue, threatening freshwater ecosystems by degrading water quality and posing risks to human and aquatic life. Chlorophyll-a (Chl-a), a key biomarker of bloom intensity, offers crucial insights into algal bloom dynamics. However, predicting Chl-a concentrations remains challenging due to the complex interactions between various environmental factors. This study utilizes machine learning (ML) models to predict Chl-a concentrations, focusing on Lake Taihu in China, a large eutrophic lake that serves as an example of numerous freshwater lakes suffering from Cyano-HABs. The research leverages nine critical water quality parameters—water temperature, pH, dissolved oxygen, turbidity, electrical conductivity permanganate index, ammonia nitrogen, total phosphorus, and total nitrogen—to develop an ensemble ML model using XGBoost, known for its ability to handle nonlinear relationships and integrate multiple variables. The XGBoost model achieved superior predictive accuracy with an R² value of 0.78 and RMSE of 8.97 mg/m³ on the test set, outperforming traditional models like linear regression, decision trees, multi-layer perceptrons, support vector regression, and random forests. Feature importance analysis identified electrical conductivity, turbidity, and water temperature as the most significant predictors of Chl-a levels. This study further enhances model interpretability through Pearson correlation analysis, which quantifies the relationships between Chl-a concentrations and other water quality factors. Additionally, we employed principal component analysis (PCA), mutual information, Spearman rank correlation coefficients, and SHAP models to analyze feature importance and model interpretability in ML. The model’s robustness was tested across multiple monitoring sites in Lake Taihu, demonstrating its potential for broader application in other eutrophic lakes facing similar environmental challenges. By providing a reliable tool for forecasting Chl-a concentrations, this research contributes to the development of early warning systems that can help mitigate the impacts of Cyano-HABs, aiding in more effective water resource management. Full article

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

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15 pages, 1145 KiB

Open AccessPerspective

Killing Two Crises with One Spark: Cold Plasma for Antimicrobial Resistance Mitigation and Wastewater Reuse

by José Gonçalves, João Pequeno, Israel Diaz, Davor Kržišnik, Jure Žigon and Tom Koritnik

Water 2025, 17(8), 1218; https://doi.org/10.3390/w17081218 - 18 Apr 2025

Viewed by 163

Abstract

Global water scarcity and antimicrobial resistance (AMR) represent two escalating crises that urgently demand integrated and effective solutions. While wastewater reuse is increasingly promoted as a strategy to alleviate water scarcity, conventional treatment processes often fail to eliminate persistent contaminants and antibiotic-resistant microorganisms. [...] Read more.

Global water scarcity and antimicrobial resistance (AMR) represent two escalating crises that urgently demand integrated and effective solutions. While wastewater reuse is increasingly promoted as a strategy to alleviate water scarcity, conventional treatment processes often fail to eliminate persistent contaminants and antibiotic-resistant microorganisms. Cold plasma (CP), a non-thermal advanced oxidation process, has demonstrated the strong potential to simultaneously inactivate pathogens and degrade micropollutants. CP generates a diverse mix of reactive oxygen and nitrogen species (ROS and RNS), as well as UV photons and charged particles, capable of breaking down complex contaminants and inducing irreversible damage to microbial cells. Laboratory studies have reported bacterial log reductions ranging from 1 to >8–9 log₁₀, with Gram-negative species such as E. coli and Pseudomonas aeruginosa showing higher susceptibility than Gram-positive bacteria. The inactivation of endospores and mixed-species biofilms has also been achieved under optimized CP conditions. Viral inactivation studies, including MS2 bacteriophage and norovirus surrogates, have demonstrated reductions >99.99%, with exposure times as short as 0.12 s. CP has further shown the capacity to degrade antibiotic residues such as ciprofloxacin and sulfamethoxazole by >90% and to reduce ARGs (e.g., bla, sul, and tet) in hospital wastewater. This perspective critically examines the mechanisms and current applications of CP in wastewater treatment, identifies the operational and scalability challenges, and outlines a research agenda for integrating CP into future water reuse frameworks targeting AMR mitigation and sustainable water management. Full article

(This article belongs to the Special Issue Wastewater Treatment and Public Health Surveillance: Advances and Challenges in the One Health Era)

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17 pages, 2039 KiB

Open AccessArticle

Simulating Water Application Efficiency in Pressurized Irrigation Systems: A Computational Approach

by Nelson Carriço, Diogo Felícissimo, André Antunes and Paulo Brito da Luz

Water 2025, 17(8), 1217; https://doi.org/10.3390/w17081217 (registering DOI) - 18 Apr 2025

Viewed by 115

Abstract

The agricultural sector faces growing environmental and societal pressures to balance natural resource use with food security, particularly within the Water-Energy-Food-Ecosystems Nexus (WEFE). Increasing water demand, competition, and challenges like droughts and desertification are driving the need for innovative irrigation practices. Pressurized irrigation [...] Read more.

The agricultural sector faces growing environmental and societal pressures to balance natural resource use with food security, particularly within the Water-Energy-Food-Ecosystems Nexus (WEFE). Increasing water demand, competition, and challenges like droughts and desertification are driving the need for innovative irrigation practices. Pressurized irrigation systems, such as sprinkler and micro-irrigation, are gaining prominence due to their automation, labor savings, and increased water application efficiency. To support farmers in designing and managing these systems, the R&D project AGIR developed a computational tool that simulates water application efficiency under site-specific conditions. The tool integrates key parameters, including system design, scheduling, soil properties, topography, meteorological data, and vegetation cover, providing a robust methodological framework with classification criteria for evaluating irrigation options. Validated using data from six case studies, the tool achieved simulated irrigation efficiencies of 73% to 90%, which are consistent with field observations. By simplifying complex irrigation requirement calculations, the model offers a user-friendly alternative while maintaining accuracy at the farm level. This innovative tool enables stakeholders to optimize irrigation systems, reduce water losses, and establish standardized recommendations for design, management, performance, and socio-economic considerations. It represents a significant step forward in supporting sustainable water management and advancing the goals of Agriculture 4.0. Full article

(This article belongs to the Special Issue Methods and Tools for Sustainable Agricultural Water Management)

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16 pages, 1921 KiB

Open AccessArticle

Ecological Shifts and Functional Adaptations of Soil Microbial Communities Under Petroleum Hydrocarbon Contamination

by Lei Ren, Jie Zhang, Bao Geng, Jie Zhao, Wenjuan Jia and Lirong Cheng

Water 2025, 17(8), 1216; https://doi.org/10.3390/w17081216 - 18 Apr 2025

Viewed by 94

Abstract

Petroleum hydrocarbon contamination has emerged as a significant global environmental issue, severely impacting soil microbial communities and their functions. This study employed high-throughput sequencing to systematically analyze the bacterial community structure and functional genes in soils with varying levels of petroleum hydrocarbon contamination. [...] Read more.

Petroleum hydrocarbon contamination has emerged as a significant global environmental issue, severely impacting soil microbial communities and their functions. This study employed high-throughput sequencing to systematically analyze the bacterial community structure and functional genes in soils with varying levels of petroleum hydrocarbon contamination. The results demonstrated that petroleum contamination led to a significant decline in microbial diversity, while enhancing the abundance of specific functional genes, such as those involved in polycyclic aromatic hydrocarbon (PAH) degradation, methane production, and denitrification. Phylogenetic analysis further revealed that microbial communities in highly contaminated soils tended to form highly clustered and specialized groups, while simultaneously promoting the coexistence of phylogenetically distant microorganisms. The Mantel test identified significant correlations between ammonium ion concentration, soil moisture content, and microbial metabolic pathways, particularly those related to petroleum hydrocarbon degradation and denitrification. These findings suggest that petroleum contamination not only disrupts the carbon and nitrogen metabolism balance but also has profound implications for greenhouse gas emissions and nitrogen cycling, potentially destabilizing the ecosystem. This study provides novel insights into the ecological functions of microbial communities in petroleum-contaminated soils and highlights potential key factors for pollution management and ecological restoration. Full article

(This article belongs to the Special Issue Water Safety, Ecological Risk and Public Health)

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22 pages, 8841 KiB

Open AccessArticle

Seaweed-Derived Biochar for Effective Treatment of Dye-Contaminated Wastewater

by Ana Paula Soares Dias, Francisco Ascenção Santos, Bruna Rijo, Dina Costa Simes, Leonel Pereira and Manuel Francisco Costa Pereira

Water 2025, 17(8), 1215; https://doi.org/10.3390/w17081215 - 18 Apr 2025

Viewed by 324

Abstract

Freshwater scarcity is a growing concern, exacerbated by industrial effluents containing dyes and other pollutants that endanger aquatic ecosystems. This study explores the potential of biochar sorbents, derived from renewable seaweed biomass, as a sustainable solution for water decontamination. Seaweed biomass (sargaço [...] Read more.

Freshwater scarcity is a growing concern, exacerbated by industrial effluents containing dyes and other pollutants that endanger aquatic ecosystems. This study explores the potential of biochar sorbents, derived from renewable seaweed biomass, as a sustainable solution for water decontamination. Seaweed biomass (sargaço), collected from Portuguese seashores, was carbonized at 300 °C and 400 °C to produce biochar. Adsorption experiments with methylene blue (MB) revealed that carbonization at 400 °C, followed by ball milling, significantly enhanced adsorption performance. Langmuir isotherm analysis demonstrated a maximum adsorption capacity of 500 mg MB/g sorbent for the optimized biochar (400 °C, ball milled), with adsorption efficiency improving at elevated temperatures and pH levels up to 12. Infrared reflectance spectra of fresh and post-adsorption biochars confirmed the involvement of π–π interactions and hydrogen bonding in the adsorption mechanism. These findings highlight the potential of seaweed-derived biochar as an effective and eco-friendly solution for water purification. Full article

(This article belongs to the Special Issue The Application of Novel Biotechnologies for Removal of Emerging Contaminants)

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22 pages, 1076 KiB

Open AccessArticle

Resilience Assessment of Irrigation District Infrastructure: Indicators, Modeling, and Empirical Application

by Shuqing Wei, Laizheng Zhai, Chunlu Liu, Keke Wang and Junjie Li

Water 2025, 17(8), 1214; https://doi.org/10.3390/w17081214 - 18 Apr 2025

Viewed by 104

Abstract

In the context of intensifying climate and environmental changes, the high resilience of irrigation district infrastructure is of crucial importance for sustainable agriculture and water security. This paper proposes a resilience assessment indicator system for irrigation district infrastructure, comprising 23 indicators from the [...] Read more.

In the context of intensifying climate and environmental changes, the high resilience of irrigation district infrastructure is of crucial importance for sustainable agriculture and water security. This paper proposes a resilience assessment indicator system for irrigation district infrastructure, comprising 23 indicators from the four dimensions of foresight capacity, absorption capacity, restoration capacity, and adaptive and learning capacity. This system is constructed by combining the research status quo at home and abroad with the change process of the resilience function. The model was constructed using the DEMATEL-ANP-Cloud method, and the Zhaokou Irrigation District in China was used as a case study to demonstrate the model’s application. The resilience analysis was conducted, and targeted strategies for enhancing resilience were proposed. The resilience assessment model constructed in this study provides a scientific basis for the resilience assessment of irrigation district infrastructure and a reference point for similar projects in terms of risk reduction and system resilience improvement. This is of great significance for guaranteeing sustainable agriculture and water security. Full article

(This article belongs to the Special Issue Sustainable Water Management in Agricultural Irrigation)

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20 pages, 10537 KiB

Open AccessArticle

Research on Performance Prediction of Elbow Inline Pump Based on MSCSO-BP Neural Network

by Chao Wang, Zhenhua Shen, Yin Luo, Xin Wu, Guoyou Wen and Shijun Qiu

Water 2025, 17(8), 1213; https://doi.org/10.3390/w17081213 - 18 Apr 2025

Viewed by 101

Abstract

The vertical inline pump, a single-stage centrifugal pump with a bent elbow inlet, is widely used in marine engineering. The unique water inlet passage combined with uneven inflow at the impeller inlet tends to form an inlet vortex and secondary flow area, which [...] Read more.

The vertical inline pump, a single-stage centrifugal pump with a bent elbow inlet, is widely used in marine engineering. The unique water inlet passage combined with uneven inflow at the impeller inlet tends to form an inlet vortex and secondary flow area, which reduces performance and causes vibration. To predict the performance of the elbow inline pump, this study uses spline curve fitting for the centerline and cross-sectional shape of the elbow passage. With four elbow inlet variables from experimental design as the input layer and targeting efficiency under pump operating conditions, a pump performance prediction model based on an improved sand cat swarm optimization algorithm combined with a BP neural network (MSCSO-BP) is proposed. Six test functions are used to effectively test the improved sand cat swarm optimization algorithm. The results show that compared to the unimproved algorithm, the improved algorithm has significantly faster convergence speed, shorter parameter optimization time, and higher accuracy. For more demanding multidimensional test functions, the improved optimization algorithm can more accurately find the optimal solution, enhancing the prediction accuracy and generalization ability of inline pump performance. This provides a more effective engineering solution for the design and optimization of inline pumps. Full article

(This article belongs to the Special Issue Design and Optimization of Fluid Machinery, 3rd Edition)

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31 pages, 13223 KiB

Open AccessArticle

An Integrated Approach for Groundwater Potential Prediction Using Multi-Criteria and Heuristic Methods

by Aslı Bozdağ, Zeynep Ünal, Ahmet Emin Karkınlı, Arjumand Bano Soomro, Mohammad Shuaib Mir and Yonis Gulzar

Water 2025, 17(8), 1212; https://doi.org/10.3390/w17081212 - 18 Apr 2025

Viewed by 70

Abstract

This research focuses on groundwater mapping for the Çumra and Beyşehir Basins in Konya, a semi-arid region in Turkey that plays a crucial role in agriculture and the food industry. Geographic information systems (GIS), the analytical hierarchical process (AHP), and the multi-population-based differential [...] Read more.

This research focuses on groundwater mapping for the Çumra and Beyşehir Basins in Konya, a semi-arid region in Turkey that plays a crucial role in agriculture and the food industry. Geographic information systems (GIS), the analytical hierarchical process (AHP), and the multi-population-based differential evolution algorithm (MDE) were combined to identify potential groundwater zones. Since direct data on groundwater presence are costly to obtain, thematic maps created from groundwater conditioning factors (such as aquifer, slope, permeability, alluvial soil, soil quality, lithology, precipitation, temperature, salinity, and stone density) can be used to estimate groundwater potential. In this study, these factors were assigned weights using the AHP technique in Model 1 and the MDE technique in Model 2. The TOPSIS (technique for order preference by similarity to ideal solution) method was then employed to simulate groundwater potential, using weights from both techniques. The performance metrics of both models were as follows: Model 1 (RMSE: 114.219, MSE: 13,046.091, and MAE: 99.663) and Model 2 (RMSE: 114.209, MSE: 13,043.785, and MAE: 99.652). The proposed method addresses issues of consistency and bias that might arise from relying on expert opinions through the use of heuristic techniques. Moreover, this approach, which does not require direct data on groundwater availability, enables the creation of accurate predictions while overcoming the challenges of obtaining expensive data in underdeveloped and developing countries. It provides a scientifically sound way to identify and conserve water resources, reducing drilling and other related costs in watershed management and planning. Full article

(This article belongs to the Special Issue Spatial Analysis of Flooding Phenomena: Challenges and Case Studies)

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21 pages, 5460 KiB

Open AccessArticle

Analysis of Response Surface and Artificial Neural Network for Cr(Ⅵ) Removal Column Experiment

by Zhongyu Ren, Zhicong Li, Haokai Tang, Lin Yang, Jinrun Zhu and Qi Jing

Water 2025, 17(8), 1211; https://doi.org/10.3390/w17081211 - 18 Apr 2025

Viewed by 146

Abstract

In this study, inexpensive, environmentally friendly, and biodegradable cellulose filter paper was used to load nano zero-valent iron (nZVI), effectively improving the dispersibility of nZVI and successfully preparing the supported modified cellulose filter paper (FP-nZVI). Subsequently, the capacity of FP-nZVI to remove Cr(VI) [...] Read more.

In this study, inexpensive, environmentally friendly, and biodegradable cellulose filter paper was used to load nano zero-valent iron (nZVI), effectively improving the dispersibility of nZVI and successfully preparing the supported modified cellulose filter paper (FP-nZVI). Subsequently, the capacity of FP-nZVI to remove Cr(VI) in a flow system was explored. FP-nZVI was characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Traditional single-factor experiments often require a large number of repeated experiments when analyzing the interactions among multiple variables, resulting in a long experimental cycle and high consumption of experimental materials. This research used the Response Surface Methodology (RSM) based on the Box-Behnken Design (BBD) and the Artificial Neural Network (ANN) to optimize and predict the removal process of Cr(VI). This RSM investigated the interactions between the response variable (Cr(VI) removal rate) and the independent variables (Cr(VI) concentration, pH value, and flow rate). A highly significant quadratic regression model was constructed, which was proven by a high F value (93.92), an extremely low p-value (<0.0001), and a high determination coefficient (R² = 0.9918). An ANN model was established to forecast the correlation between independent variables and the removal rate of Cr(VI). Both models demonstrate remarkable consistency with the experimental data; however, from the perspective of statistical parameters, the ANN model has more significant advantages; the coefficient of determination R² reaches 0.9937, which is higher than that of RSM (0.9918); the values of indicators such as MSE, RMSE, MAE, MAPE, AAD, and SEP are all smaller than those of RSM. The ANN exhibits greater excellence in prediction error, value fluctuation, and closeness to the actual value and has a more excellent prediction ability. The experiment for treating Cr(VI) with FP-nZVI was optimized, achieving good results. Meanwhile, it also provides a valuable reference for similar experimental studies. Full article

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

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