Water

18 pages, 6148 KB

Open AccessEditor’s ChoiceArticle

Impact of Drought on the Aquatic Ecosystem of the Cascade Dam Reservoir in South Korea

by Youn Bo Sim, Jong Kwon Im, Chae Hong Park, Jeong Hwan Byun and Soon-Jin Hwang

Water 2025, 17(7), 1023; https://doi.org/10.3390/w17071023 - 31 Mar 2025

Cited by 2 | Viewed by 2306

Climate change has increased the frequency and intensity of extreme weather events worldwide. In South Korea, annual precipitation in 2014–2015 was only 50% of the long-term average, resulting in severe drought conditions. This drought extended water residence time in dam reservoirs, enhancing internal [...] Read more.

Climate change has increased the frequency and intensity of extreme weather events worldwide. In South Korea, annual precipitation in 2014–2015 was only 50% of the long-term average, resulting in severe drought conditions. This drought extended water residence time in dam reservoirs, enhancing internal nutrient recycling, degrading water quality, and promoting harmful cyanophyta blooms in downstream reservoirs. Using the Standardized Precipitation Index—for drought assessment, and monthly water sampling—for environmental factors and phytoplankton analyses, this study examined the impacts of drought on water quality and phytoplankton communities in a series of interconnected dam reservoirs (Uiam, Cheongpyeong, Sambong-ri, and Paldang Lakes) within the Bukhan River system from 2013 to 2016. The prolonged residence time during drought facilitated nutrient accumulation and recycling within the reservoirs, intensifying eutrophication and water quality deterioration, alongside a pronounced cyanobacterial dominance and harmful algal blooms. These findings suggest that changes in upstream dam discharges directly influence water quality and ecosystem health in downstream reservoirs and that diverse hydrological changes associated with drought pose a significant threat to water source management. These findings may inform the development of integrated water management strategies for maintaining water quality and protecting water sources during droughts and extreme climatic events. Full article

(This article belongs to the Special Issue Impacts of Environmental Change and Human Activities on Aquatic Ecosystems)

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17 pages, 1992 KB

Open AccessEditor’s ChoiceArticle

Molecular Dynamics Simulation of the Impact of Functional Head Groups and Chain Lengths of PFAS Degradation Using Ultrasound Technology

by Bruno Bezerra de Souza, Jitendra A. Kewalramani, Richard W. Marsh and Jay Meegoda

Water 2025, 17(7), 1025; https://doi.org/10.3390/w17071025 - 31 Mar 2025

Cited by 6 | Viewed by 2965

Abstract

PFASs, or per- and polyfluoroalkyl substances, comprise a diverse group of synthetic chemicals known for their widespread use, persistence, and potential environmental and health risks. The sonolytic treatment of PFASs is one of the technologies with the ability to complete destruction without harmful [...] Read more.

PFASs, or per- and polyfluoroalkyl substances, comprise a diverse group of synthetic chemicals known for their widespread use, persistence, and potential environmental and health risks. The sonolytic treatment of PFASs is one of the technologies with the ability to complete destruction without harmful byproducts. This study aims to provide a theoretical explanation for the sonolytic treatment of PFAS. Combining insights from molecular dynamics simulations with experimental data, the influence of chain length and functional headgroups on the PFAS destruction mechanism was investigated. The findings revealed that the impact on functional head groups and chain length on PFAS degradation via sonolysis treatment is complex and multifaceted. The preliminary degradation step is attributed to be headgroup cleavage, while differences in degradation rates between perfluorocarboxylic acids (PFCAs) and perfluorosulfonic acids (PFSAs) are primarily influenced by adsorption at the air–water interface of micro/nanobubbles created by ultrasound and dictated by compound hydrophobicity characteristics. Moreover, longer-chain PFAS compounds tend to degrade faster than shorter-chain counterparts due to their enhanced hydrophobic characteristics, facilitating adsorption and subsequent mineralization. The sonolytic environment significantly influences PFAS degradation, with aqueous sonolysis proving the most effective compared to dry pyrolysis or thermal combustion, highlighting the importance of considering environmental factors in remediation strategies. These insights provide valuable guidance for designing effective PFAS remediation strategies, emphasizing the need to consider molecular structure and environmental conditions. Further research and technological innovation are essential for developing sustainable approaches to mitigate PFAS pollution’s adverse impacts on human health and the environment. Full article

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

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39 pages, 15097 KB

Open AccessEditor’s ChoiceReview

Metal Pollution and Health–Ecological Risk Assessment in an Intensely Burdened Coastal Environment of Greece, the Saronikos Gulf: A 50-Year Critical Review

by Anastasia Gkaragkouni, Xenophon Dimas, Spyros Sergiou, Dimitris Christodoulou, Loukas Anastasopoulos, Maria Geraga, Hrissi K. Karapanagioti and George Papatheodorou

Water 2025, 17(7), 1029; https://doi.org/10.3390/w17071029 - 31 Mar 2025

Cited by 3 | Viewed by 2180

Abstract

Among Greece’s coastal areas, the Saronikos Gulf encounters the highest environmental challenges due to heavy metal contamination, caused by extensive urbanization and industrialization. In the present study, online databases were used to identify research articles focusing on the levels, patterns, and origins of [...] Read more.

Among Greece’s coastal areas, the Saronikos Gulf encounters the highest environmental challenges due to heavy metal contamination, caused by extensive urbanization and industrialization. In the present study, online databases were used to identify research articles focusing on the levels, patterns, and origins of the heavy metals on the gulf’s seafloor published from 1974 to 2024. Thirty-three scientific papers were chosen to review the status of heavy metal pollution, set background values, and summarize the analytical methods used. Additionally, fourteen of them were used for a meta-analysis review. Geographic Information System (GIS) techniques were employed to map the sampling locations and heavy metal distribution per decade of the collected data, while the ecological status of the area was estimated via the application of indices such as the Pollution Loading Index (PLI), Potential and Ecological Risk Index (PERI), and Human Health Risk Assessment (HHRA) to the previously collected data. The review revealed that the Saronikos Gulf has mostly been studied in specific regions due to existent point sources. Additionally, the reassessment of the data referenced in the literature permitted integrative comparisons that could improve the management and sustainable development of the Saronikos Gulf. Full article

(This article belongs to the Special Issue Source, Occurrence, Pathway, and Fate of Heavy Metals in the Water Environment)

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22 pages, 4464 KB

Open AccessEditor’s ChoiceArticle

Microtopography Affects the Diversity and Stability of Vegetation Communities by Regulating Soil Moisture

by Lei Han, Yang Liu, Jie Liu, Hongliang Kang, Zhao Liu, Fengwei Tuo, Shaoan Gan, Yuxuan Ren, Changhua Yi and Guiming Hu

Water 2025, 17(7), 1012; https://doi.org/10.3390/w17071012 - 29 Mar 2025

Cited by 5 | Viewed by 1780

Abstract

Microtopography plays a crucial role in regulating soil moisture in arid and semi-arid regions, thereby significantly influencing vegetation growth and distribution. The Loess Plateau, characterized by a deeply incised and fragmented landscape, necessitates an in-depth understanding of the microtopograph–soil moisture–vegetation relationship to guide [...] Read more.

Microtopography plays a crucial role in regulating soil moisture in arid and semi-arid regions, thereby significantly influencing vegetation growth and distribution. The Loess Plateau, characterized by a deeply incised and fragmented landscape, necessitates an in-depth understanding of the microtopograph–soil moisture–vegetation relationship to guide effective vegetation restoration. This study, based on field investigations and laboratory analyses in the hilly-gully region of the Loess Plateau, employed one-way ANOVA, Duncan’s multiple range test, and structural equation modeling to examine the effects of microtopography on vegetation community characteristics. The results revealed that microtopography significantly affects vegetation diversity and stability. Vegetation diversity and stability were higher on shady slopes than on sunny slopes, with diversity indices increasing by approximately 38% in certain regions. Additionally, downslope positions exhibited greater vegetation diversity than upslopes, with richness indices increasing by approximately 33% and the M. Godron index decreasing by 8.49, indicating enhanced stability. However, the effects of gullies varied significantly across different regions. Soil moisture content was higher on shaded slopes than on sunny slopes and greater at downslope positions than at upslopes, reaching up to 12.89% in gullies. Slope position exerted a direct and significant positive effect on soil moisture, which, in turn, indirectly influenced vegetation diversity and stability. This study reveals the dominant regulatory role of slope position in soil moisture, vegetation diversity, and stability, providing new perspectives and evidence for developing vegetation restoration strategies on the Loess Plateau and promoting the sustainable growth of regional vegetation. Full article

(This article belongs to the Section Soil and Water)

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18 pages, 10601 KB

Open AccessEditor’s ChoiceArticle

Impact of Drainage Network Structure on Urban Inundation Within a Coupled Hydrodynamic Model

by Pan Wu, Tao Wang, Zhaoli Wang, Chao Song and Xiaohong Chen

Water 2025, 17(7), 990; https://doi.org/10.3390/w17070990 - 28 Mar 2025

Cited by 4 | Viewed by 2501

Abstract

Currently, one of the major threats to cities is the escalating risk of flooding, which is attributed to the alteration of climate and hastened urbanization. The purpose of this study was to introduce the Strahler ordering method for simplifying drainage networks and to [...] Read more.

Currently, one of the major threats to cities is the escalating risk of flooding, which is attributed to the alteration of climate and hastened urbanization. The purpose of this study was to introduce the Strahler ordering method for simplifying drainage networks and to avoid randomness in developing flooding models. A coupled hydrodynamic model that combines SWMM and LISFLOOD-FP was developed to simulate urban inundation. Results showed that the coupled model had satisfactory applicability for waterlogging simulation. The Strahler ordering method could construct clear topological relations of the drainage network and showed good performance in drainage network simplification. Higher-density drainage networks could increase peak discharge and total volume of discharge, while decreasing the maximum water depth and the total inundation area. Taking “5.29” rainstorm events as an example, compared to Level 3, the relative rates of change in the total flow and peak flow of Level 2 and Level 1 networks are −33.18% and −23.29%. The total inundation area was decreased from 14.14 ha to 1.43 ha when the level of drainage network hierarchy was increased from Level 1 to Level 3. This study highlights the importance of re-assessment of current and future urban drainage networks for coping with the changes in urban floods induced by local and large-scale changes. Full article

(This article belongs to the Section Urban Water Management)

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15 pages, 6484 KB

Open AccessEditor’s ChoiceArticle

Multivariate Statistics and Hydrochemistry Combined to Reveal the Factors Affecting Shallow Groundwater Evolution in a Typical Area of the Huaibei Plain, China

by Xi Qin, Hesheng Wang, Jianshi Gong, Yonghong Ye, Kaie Zhou, Naizheng Xu, Liang Li and Jie Li

Water 2025, 17(7), 962; https://doi.org/10.3390/w17070962 - 26 Mar 2025

Cited by 4 | Viewed by 817

Abstract

Understanding the characteristics of groundwater chemistry is essential for water resource development and utilization. However, few studies have focused on the chemical evolution processes of shallow groundwater in typical areas of the Huaibei Plain. We analyzed 28 water samples from the study area [...] Read more.

Understanding the characteristics of groundwater chemistry is essential for water resource development and utilization. However, few studies have focused on the chemical evolution processes of shallow groundwater in typical areas of the Huaibei Plain. We analyzed 28 water samples from the study area using hydrogeochemical mapping, multivariate statistical analysis, and other approaches. The study found that the hydrogeochemical facies of groundwater are mainly HCO₃-Ca·Mg (64.3%), mixed SO₄·Cl-Ca·Mg, and SO₄·Cl-Na. The hydrochemical composition is primarily controlled by natural water–rock interactions, including carbonate weathering and cation exchange processes. Correlation analysis and principal component analysis (PCA) revealed that mineral dissolution was the predominant source of Na⁺, Mg²⁺, Cl⁻, and SO₄²⁻ in shallow groundwater, significantly contributing to total dissolved solids (TDS) accumulation. Hierarchical cluster analysis (HCA) identified three characteristic zones: (1) agricultural/urban-influenced areas, (2) high-F⁻/low-hardness zones, and (3) nitrate-contaminated regions. These findings provide critical insights for assessing the geochemical status of groundwater in the Huaibei Plain and formulating targeted resource management strategies. Full article

(This article belongs to the Special Issue Assessment of Groundwater Quality and Pollution Remediation)

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27 pages, 1239 KB

Open AccessEditor’s ChoiceArticle

The Impact of Water Resources Tax Reform on Corporate ESG Performance: Patent Evidence from China

by Jiachun Wen, Xiang Ji and Xue Wu

Water 2025, 17(7), 959; https://doi.org/10.3390/w17070959 - 25 Mar 2025

Cited by 3 | Viewed by 1471

Abstract

This paper uses a difference-in-differences approach to investigate how China’s water resources tax reform influences corporate Environmental, Social and Governance (ESG) performance. Drawing on a panel dataset of A-share listed companies from 2013 to 2023, we find that the reform significantly improves firms’ [...] Read more.

This paper uses a difference-in-differences approach to investigate how China’s water resources tax reform influences corporate Environmental, Social and Governance (ESG) performance. Drawing on a panel dataset of A-share listed companies from 2013 to 2023, we find that the reform significantly improves firms’ ESG ratings, a result that holds under multiple robustness checks. Mechanism tests reveal that this positive effect operates through enhanced green technological innovation, increased environmental investment, and heightened pressure from capital markets, with media attention further reinforcing these pathways. Heterogeneity analyses indicate that state-owned enterprises and larger firms experience particularly strong ESG improvements following the tax reform. These findings provide empirical evidence of the effectiveness of government-led environmental governance policies and offer practical insights for promoting green transformation in the corporate sector. Full article

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

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23 pages, 29128 KB

Open AccessEditor’s ChoiceArticle

Flood Susceptibility Analysis with Integrated Geographic Information System and Analytical Hierarchy Process: A Multi-Criteria Framework for Risk Assessment and Mitigation

by Sujan Shrestha, Dewasis Dahal, Bishal Poudel, Mandip Banjara and Ajay Kalra

Water 2025, 17(7), 937; https://doi.org/10.3390/w17070937 - 23 Mar 2025

Cited by 12 | Viewed by 8179

Abstract

Flooding is among the most destructive natural disasters globally, and it inflicts severe damage on both natural environments and human-made structures. The frequency of floods has been increasing due to unplanned urbanization, climate change, and changes in land use. Flood susceptibility maps help [...] Read more.

Flooding is among the most destructive natural disasters globally, and it inflicts severe damage on both natural environments and human-made structures. The frequency of floods has been increasing due to unplanned urbanization, climate change, and changes in land use. Flood susceptibility maps help identify at-risk areas, supporting informed decisions in disaster preparedness, risk management, and mitigation. This study aims to generate a flood susceptibility map for Davidson County of Tennessee using an integrated geographic information system (GIS) and analytical hierarchical process (AHP). In this study, ten flood causative factors are employed to generate flood-prone zones. AHP, a form of weighted multi-criteria decision analysis, is applied to assess the relative impact weights of these flood causative factors. Subsequently, these factors are integrated into ArcGIS Pro (Version 3.3) to create a flood susceptibility map for the study area using a weighted overlay approach. The resulting flood susceptibility map classified the county into five susceptibility zones: very low (17.48%), low (41.89%), moderate (37.53%), high (2.93%), and very high (0.17%). The FEMA flood hazard map of Davidson County is used to validate the flood susceptibility map created from this approach. Ultimately, this comparison reinforced the accuracy and reliability of the flood susceptibility assessment for the study area using integrated GIS and AHP approach. Full article

(This article belongs to the Special Issue Advancing the Monitoring and Modelling of Freshwater Systems with New Remote Sensing Technologies)

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14 pages, 2961 KB

Open AccessEditor’s ChoiceArticle

Research on the Features and Driving Factors of Shallow Groundwater Quality in Arid Areas, Northwest China

by Long Wang, Nan Yang, Yang Zhao and Qianqian Zhang

Water 2025, 17(7), 934; https://doi.org/10.3390/w17070934 - 22 Mar 2025

Cited by 6 | Viewed by 903

Abstract

Given the increasing threat of groundwater pollution, comprehending the trends and influencing factors of groundwater quality variation is essential for effective mitigation strategies. This study addresses groundwater quality variations in the Beichuan River, a critical area in China’s arid region. Using hydrochemical analysis [...] Read more.

Given the increasing threat of groundwater pollution, comprehending the trends and influencing factors of groundwater quality variation is essential for effective mitigation strategies. This study addresses groundwater quality variations in the Beichuan River, a critical area in China’s arid region. Using hydrochemical analysis and multivariate statistics, we identified key factors influencing groundwater quality. Groundwater is mildly alkaline, with HCO₃⁻-Ca as the dominant hydrochemical type. The concentrations of major ions increase during the high-flow period due to rainfall effects. The dissolution of rock salt primarily contributes to the presence of Na⁺ and Cl⁻ ions. Meanwhile, the weathering of silicate and carbonate rocks is the main origin of Ca²⁺, Mg²⁺, and HCO₃⁻ ions. Additionally, the dissolution of evaporite rocks is identified as the principal source of SO₄²⁻. Human activities, particularly sewage discharge and fertilization, significantly contribute to nitrate contamination. Principal component analysis revealed that the weathering of rocks and industrial activities are the main controlling factors during the high-flow season, while the hydrochemistry of groundwater during the low-flow season is mainly influenced by the weathering of silicate rocks, evaporite rocks, and rock salt. Our findings provide a scientific basis for preventing groundwater quality deterioration and ecological environmental protection in arid regions. Full article

(This article belongs to the Special Issue Water Quality Assessment of River Basins)

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13 pages, 2709 KB

Open AccessEditor’s ChoiceArticle

Study on Large-Scale Geomechanical Experiments on Tunnel External Water Pressure

by Wei Huang, Mingtao Hu, Rubin Wang, Jianping Zhang and Weiya Xu

Water 2025, 17(7), 913; https://doi.org/10.3390/w17070913 - 21 Mar 2025

Cited by 3 | Viewed by 1282

Abstract

High external water pressure poses significant challenges to the construction of long-distance water diversion tunnels under complex geological conditions. This study developed a large-scale geomechanics model to explore the effects of tunnel depth, water head, and drained conditions on external water pressure, focusing [...] Read more.

High external water pressure poses significant challenges to the construction of long-distance water diversion tunnels under complex geological conditions. This study developed a large-scale geomechanics model to explore the effects of tunnel depth, water head, and drained conditions on external water pressure, focusing on the Songlin Tunnel in the Central Yunnan Water Diversion Project. The results show that external water pressure is most affected by water head and tunnel depth, particularly under undrained conditions. At water heads over 160 m, the external water pressure significantly decreases with an increasing tunnel depth. The suggested coefficients are 0.65–0.80 for shallowly buried tunnels with high water heads and 0.50–0.65 for deeply buried tunnels with low water heads. For drained conditions, the recommended reduction coefficients are 0.30–0.55 for the arch vault and spandrels. For the haunch, arch springing, and arch bottom, the suggested coefficients are 0.50 to 0.60 under the low water head and 0.40 to 0.60 under the high water head. These findings offer practical guidance for the design and safety of hydraulic tunnels under high external water pressure. Full article

(This article belongs to the Topic Carbon-Energy-Water Nexus in Global Energy Transition)

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27 pages, 9632 KB

Open AccessEditor’s ChoiceArticle

Investigating Sedimentation Patterns and Fluid Movement in Drip Irrigation Emitters in the Yellow River Basin

by Mengyang Wang, Mengyun Xue, Hao Sun, Hui Li, Rui Li and Qibiao Han

Water 2025, 17(7), 910; https://doi.org/10.3390/w17070910 - 21 Mar 2025

Cited by 2 | Viewed by 1157

Abstract

Developing efficient water-saving irrigation technologies that utilize high sand-laden water is an important approach to alleviating agricultural water scarcity in the Yellow River Basin. This study aims to investigate sedimentation patterns and fluid movement characteristics in drip irrigation emitters under such challenging water [...] Read more.

Developing efficient water-saving irrigation technologies that utilize high sand-laden water is an important approach to alleviating agricultural water scarcity in the Yellow River Basin. This study aims to investigate sedimentation patterns and fluid movement characteristics in drip irrigation emitters under such challenging water conditions. The dynamic changes in Dra and Cu were determined through short-period intermittent clogging tests to evaluate the anti-clogging performance of four different emitter types. The distribution and particle size composition of the deposited sediments inside the emitters were analyzed using a high-resolution electron microscope and a laser particle size analyzer. Additionally, the RNG k-ε turbulence model was used to simulate the fluid movement inside the emitters. The results showed that the B drip irrigation belt had better sediment tolerance and operational stability. The anti-clogging capacity of drip irrigation can be improved by optimizing the combination of emitter channel structure and sediment content. The fluid in the channel was divided into mainstream zone and vortex zone. Sediment particles increased in the backing-water zone and vortex center, where particles of 0.05–0.1 mm were more prone to settling due to reduced transport capacity. Energy dissipation primarily took place at the curvature of the emitter channel, and within each channel unit, gradually decreasing along the vortex flow direction, with the lowest dissipation aligning with sediment deposition zones. These findings provide a theoretical basis for mitigating clogging in high sand-laden water drip irrigation systems, offering valuable insights for improving the effective utilization of water resources in the Yellow River Basin. Full article

(This article belongs to the Special Issue Advances in Agricultural Irrigation Management and Technology)

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27 pages, 9731 KB

Open AccessEditor’s ChoiceArticle

Interpretable Machine Learning Based Quantification of the Impact of Water Quality Indicators on Groundwater Under Multiple Pollution Sources

by Tianyi Zhang, Jin Wu, Haibo Chu, Jing Liu and Guoqiang Wang

Water 2025, 17(6), 905; https://doi.org/10.3390/w17060905 - 20 Mar 2025

Cited by 5 | Viewed by 2592

Abstract

Accurate evaluation of groundwater quality and identification of key characteristics are essential for maintaining groundwater resources. The purpose of this study is to strengthen water quality evaluation through the SHAP and XGBoost algorithms, analyze the key indicators affecting water quality in depth, and [...] Read more.

Accurate evaluation of groundwater quality and identification of key characteristics are essential for maintaining groundwater resources. The purpose of this study is to strengthen water quality evaluation through the SHAP and XGBoost algorithms, analyze the key indicators affecting water quality in depth, and quantify their impact on groundwater quality through interpretable tools. The XGBoost algorithm shows that zinc (0.183), nitrate (0.159), and chloride (0.136) are the three indicators with the highest weight. The SHAP algorithm shows that zinc (34.62%), nitrate (17.65%), and chloride (16.98%) have higher contribution values, which explains the output results of XGBoost. According to the calculation scores and classification standards of the water quality model, 49% of the groundwater samples in the study area have excellent water quality, 33% of the samples are better, and 18% of the samples are polluted. The results of positive matrix factorization (PMF) show that natural conditions, metal processing, metal smelting and mining, and agricultural activities all cause pollution to groundwater. Zinc, chloride, nitrate, and manganese were the key variables determined by the SHAP algorithm to explain the vast majority of human health risk sources. These findings indicate that interpretable machine learning not only improves the correlation of water quality assessment but also quantifies the judgment basis of each sample and helps to track key pollution indicators. Full article

(This article belongs to the Special Issue Groundwater Environmental Risk Perception)

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19 pages, 4387 KB

Open AccessEditor’s ChoiceArticle

Hydroxyapatite-Modified Zeolite for Fluoride Removal from Drinking Water: Adsorption Mechanism Investigation and Column Study

by Rajinda Boteju, Libing Zheng, Hewa M. S. Wasana, Qiyang Wu, Yuansong Wei, Hui Zhong, Yawei Wang and Ajith de Alwis

Water 2025, 17(6), 908; https://doi.org/10.3390/w17060908 - 20 Mar 2025

Cited by 2 | Viewed by 2277

Abstract

This study investigates the synthesis and application of hydroxyapatite (HAp)-modified zeolite materials for efficient fluoride removal from groundwater-based drinking water. Characterization confirmed the successful incorporation of HAp onto the zeolite surface and the formation of a stable composite. EDS analysis revealed the presence [...] Read more.

This study investigates the synthesis and application of hydroxyapatite (HAp)-modified zeolite materials for efficient fluoride removal from groundwater-based drinking water. Characterization confirmed the successful incorporation of HAp onto the zeolite surface and the formation of a stable composite. EDS analysis revealed the presence of Ca and P after modification, while FTIR and XRD confirmed the structural integrity of HAp during adsorption. ZH8 exhibited the highest F-removal efficiency of 92.23% at pH 3, 30 °C, [F⁻] = 6 ppm and dose = 10 g/L. Meanwhile, HAp-modified zeolite showed high F-selectivity, and the competing ions had limited interference. The Langmuir model best described the adsorption process, suggesting monolayer adsorption with a maximum capacity of 39.38 mg/g for ZH8. The process followed pseudo-first-order kinetics, with equilibrium achieved within 4 h. Regeneration studies demonstrated that ZH8 maintained over 85% efficiency for three cycles, highlighting its reusability. Column studies validated the material’s practical applicability, with breakthrough times of up to 23 h under optimal conditions (flow rate: 8 cm³ min⁻¹, bed depth: 30 cm, feed concentration: 7.5 ppm) and a maximum yield of 99% at [F⁻] = 5 ppm with V_b = 10.8 L. The Thomas model best described the column adsorption process, indicating chemical adsorption as the dominant mechanism. These findings demonstrate the potential of HAp-modified zeolite, particularly ZH8, as an effective adsorbent for fluoride removal in real-world applications. Full article

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

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24 pages, 6891 KB

Open AccessEditor’s ChoiceArticle

Assessment of Future Rainfall Quantile Changes in South Korea Based on a CMIP6 Multi-Model Ensemble

by Sunghun Kim, Ju-Young Shin and Jun-Haeng Heo

Water 2025, 17(6), 894; https://doi.org/10.3390/w17060894 - 20 Mar 2025

Cited by 10 | Viewed by 4293

Abstract

Climate change presents considerable challenges to hydrological stability by modifying precipitation patterns and exacerbating the frequency and intensity of extreme rainfall events. This research evaluates the prospective alterations in rainfall quantiles in South Korea by employing a multi-model ensemble (MME) derived from 23 [...] Read more.

Climate change presents considerable challenges to hydrological stability by modifying precipitation patterns and exacerbating the frequency and intensity of extreme rainfall events. This research evaluates the prospective alterations in rainfall quantiles in South Korea by employing a multi-model ensemble (MME) derived from 23 Global Climate Models (GCMs) associated with the Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). Historical rainfall data from simulations (1985–2014) and future projections (2015–2044, 2043–2072, and 2071–2100) were analyzed across a total of 615 sites. Statistical Quantile Mapping (SQM) bias correction significantly enhanced the accuracy of projections (RMSE reduction of 63.0–85.3%, Pbias reduction of 93.6%, and R² increase of 0.73). An uncertainty analysis revealed model uncertainty to be the dominant factor (approximately 71.87–70.49%) in the near- to mid-term periods, and scenario uncertainty increased notably (up to 5.94%) by the end of the century. The results indicate substantial temporal and spatial changes, notably including increased precipitation in central inland and eastern coastal regions, with peak monthly increases exceeding 40 mm under high-emission scenarios. Under the SSP2-4.5 and SSP5-8.5 scenarios, the 100-year rainfall quantile is projected to increase by over 40% across significant portions of the country, emphasizing growing challenges for water resource management and infrastructure planning. These findings provide critical insights for water resource management, disaster mitigation, and climate adaptation strategies in South Korea. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling, 2nd Edition)

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13 pages, 1519 KB

Open AccessEditor’s ChoiceReview

Reviewing Water Wars and Water Weaponisation Literatures: Is There an Unnoticed Link?

by Paula Duarte Lopes and Margarida Gama

Water 2025, 17(6), 897; https://doi.org/10.3390/w17060897 - 20 Mar 2025

Cited by 2 | Viewed by 3674

Abstract

The prediction made by former Vice President of the World Bank, Ismail Serageldin, that the wars of the 21st century will be about water, remains on the international political agenda. Yet, there is enough evidence corroborating that water wars have not occurred in [...] Read more.

The prediction made by former Vice President of the World Bank, Ismail Serageldin, that the wars of the 21st century will be about water, remains on the international political agenda. Yet, there is enough evidence corroborating that water wars have not occurred in the past and that there are sufficient mechanisms in place to prevent them in the future. Simultaneously, domestic water violent conflicts have been taking place, usually as immediate reactions to localised disputes. More importantly, water weaponisation has been gaining visibility during violent conflicts, violating international humanitarian law without any consequences so far. This paper reviews the water wars and water weaponisation literatures, arguing that there is an under-researched link between these two literatures and practices. This review suggests that the water weaponisation discourse and practice may facilitate the context for the water wars prophecy to become true. Full article

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14 pages, 11569 KB

Open AccessEditor’s ChoiceArticle

Machine Learning Models for Mapping Groundwater Pollution Risk: Advancing Water Security and Sustainable Development Goals in Georgia, USA

by Shivank Pandey, Srimanti Duttagupta and Avishek Dutta

Water 2025, 17(6), 879; https://doi.org/10.3390/w17060879 - 19 Mar 2025

Cited by 2 | Viewed by 1906

Abstract

The widespread use of pesticides, such as atrazine and malathion, in agricultural systems raises significant concerns regarding the contamination of groundwater, which serves as a critical resource for drinking water. This study applies machine learning techniques to predict the concentrations of atrazine and [...] Read more.

The widespread use of pesticides, such as atrazine and malathion, in agricultural systems raises significant concerns regarding the contamination of groundwater, which serves as a critical resource for drinking water. This study applies machine learning techniques to predict the concentrations of atrazine and malathion in groundwater across Georgia, USA, using 2019 data. A Random Forest classifier was employed to integrate various environmental and demographic factors, including pesticide application rates, precipitation, lithology, and population density, to predict pesticide contamination in groundwater. The models demonstrated high training accuracies of 100% and moderate average testing accuracy of 55% for atrazine and 60% for malathion across five iterations. The low test accuracy of the model, ranging from 50% to 75%, is likely due to overfitting, which can be attributed to the small dataset size and the complex nature of pesticide-contamination patterns, making it challenging for the model to generalize to unseen data. Feature importance analysis revealed that average pesticide usage emerged as the most influential factor for atrazine, while aquifer lithology and precipitation played crucial roles in both models. These results provide valuable insights into the dynamics of pesticide contamination, highlighting areas at greater risk of contamination. The findings underscore the importance of integrating environmental, geological, and agricultural variables for more effective groundwater management and sustainable agricultural practices, contributing to the protection of water resources and public health. Full article

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11 pages, 1048 KB

Open AccessEditor’s ChoiceArticle

Evolution of Water Governance for Climate Resilience: Lessons from Japan’s Experience

by Mikio Ishiwatari, Kenji Nagata and Miho Matsubayashi

Water 2025, 17(6), 893; https://doi.org/10.3390/w17060893 - 19 Mar 2025

Cited by 7 | Viewed by 2832

Abstract

Water resources management needs to be strengthened to address increasing flood and drought risks exacerbated by climate change and socio-economic development. This requires effective water governance mechanisms that can reduce vulnerability in disasters while managing complex stakeholder relationships. This paper analyzes the evolution [...] Read more.

Water resources management needs to be strengthened to address increasing flood and drought risks exacerbated by climate change and socio-economic development. This requires effective water governance mechanisms that can reduce vulnerability in disasters while managing complex stakeholder relationships. This paper analyzes the evolution of water governance in Japan over more than half a century, examining how the country transformed from a centralized, top-down approach to a more collaborative model of water management. Through an analysis of three significant water infrastructure projects, this study identifies key drivers of governance change and evaluates the effectiveness of various stakeholder engagement mechanisms. The findings reveal how catalytic events prompted institutional innovations in addressing social impacts, environmental concerns, and climate resilience. Challenges remain in balancing diverse interests, managing implementation timeframes, and incorporating climate change uncertainties into decision-making processes. This paper offers important lessons for developing countries working to strengthen their water governance frameworks, particularly regarding stakeholder engagement, social impact mitigation, and the development of flexible institutional arrangements that can adapt to emerging climate risks. This research contributes to governance theory by demonstrating how institutional evolution occurs through the interaction of formal mechanisms and informal processes in response to changing social, environmental, and climatic conditions. Full article

(This article belongs to the Special Issue Water-Related Disasters in Adaptation to Climate Change)

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16 pages, 9459 KB

Open AccessEditor’s ChoiceArticle

Key Calibration Strategies for Mitigation of Water Scarcity in the Water Supply Macrosystem of a Brazilian City

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

Water 2025, 17(6), 883; https://doi.org/10.3390/w17060883 - 19 Mar 2025

Cited by 4 | Viewed by 1286

Abstract

This study focuses on Fortaleza, the largest metropolis in Brazil’s semi-arid region. Due to recurrent droughts, massive infrastructure like high-density reservoir networks, inter-municipal and interstate water transfer systems, and a seawater desalination plant have been implemented to ensure the city’s water security. To [...] Read more.

This study focuses on Fortaleza, the largest metropolis in Brazil’s semi-arid region. Due to recurrent droughts, massive infrastructure like high-density reservoir networks, inter-municipal and interstate water transfer systems, and a seawater desalination plant have been implemented to ensure the city’s water security. To evaluate the quantitative and qualitative impact of introducing these diverse water sources into Fortaleza’s water supply macrosystem, adequate calibration of the operating and demand parameters is required. In this study, the macrosystem was calibrated using the Particle Swarm Optimization (PSO) method based on hourly data from 50 pressure head monitoring points and 40 flow rate monitoring points over two typical operational days. The calibration process involved adjusting the operational rules of typical valves in large-scale Water Distribution Systems (WDS). After parameterization, the calibration presented the following results: R² of 88% for pressure head and 96% for flow rate, with average relative errors of 13% for the pressure head and flow rate. In addition, with NSE values above 0.80 after calibration for the flow rate and pressure head, the PSO method suggests a significant improvement in the simulation model’s performance. These results offer a methodology for calibrating real WDS to simulate various water injection scenarios in the Fortaleza macrosystem. Full article

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

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20 pages, 6067 KB

Open AccessEditor’s ChoiceArticle

Shallow Subsurface Soil Moisture Estimation in Coal Mining Area Using GPR Signal Features and BP Neural Network

by Chaoqi Qiu, Wenfeng Du, Shuaiji Zhang, Xuewen Ru, Wei Liu and Chuanxing Zhong

Water 2025, 17(6), 873; https://doi.org/10.3390/w17060873 - 18 Mar 2025

Cited by 6 | Viewed by 999

Abstract

Coal mining disrupts soil structure and causes water loss, thereby affecting the ecological environment of mining areas. Rapid, accurate, and non-destructive detection of surface soil moisture is crucial for advancing ecological restoration in these regions. This study focuses on the mined and unmined [...] Read more.

Coal mining disrupts soil structure and causes water loss, thereby affecting the ecological environment of mining areas. Rapid, accurate, and non-destructive detection of surface soil moisture is crucial for advancing ecological restoration in these regions. This study focuses on the mined and unmined areas of the Yushuquan coal mine, located on the southern slope of the Tianshan Mountains in Xinjiang, China. The soil volumetric water content (SVWC) was measured using time-domain reflectometry (TDR), while the shallow subsurface soil was investigated using ground-penetrating radar (GPR). Various features were extracted from GPR signals in both the time- and frequency-domains, and their relationships with SVWC were analyzed. Multiple features were selected and optimized to determine the optimal feature combination for building a multi-feature backpropagation neural network model for soil volumetric water content prediction (Muti-BP-SVWC). The performance of this model was compared with two single-feature-based methods for SVWC prediction: the average envelope amplitude (AEA) method and the frequency shift method. The application results of the Muti-BP-SVWC model in different regions demonstrated significant improvements in accuracy and stability compared to the AEA method and the frequency shift method. In the mined area validation set, the model achieved an determination coefficient (R²) of 0.77 and the root mean square error (RMSE) of 0.0091 cm³/cm³, while in the unmined area validation set, the R² of 0.84 and an RMSE of 0.0059 cm³/cm³. These results indicate that incorporating multiple features into the BP neural network can better capture the complex relationship between GPR signals and SVWC. This approach effectively inverts the shallow subsurface soil moisture in mining areas and provides valuable guidance for ecological restoration in these regions. Full article

(This article belongs to the Section Soil and Water)

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13 pages, 1447 KB

Open AccessEditor’s ChoiceReview

Rice Fields and Aquatic Insect Biodiversity in Italy: State of Knowledge and Perspectives in the Context of Global Change

by Tiziano Bo, Anna Marino, Simone Guareschi, Alex Laini and Stefano Fenoglio

Water 2025, 17(6), 845; https://doi.org/10.3390/w17060845 - 15 Mar 2025

Cited by 2 | Viewed by 2285

Abstract

Rice fields are one of the most important and extensive agro-ecosystems in the world. Italy is a major non-Asian rice producer, with a significant proportion of its yield originating from a vast area within the Po Valley, a region nourished by the waters [...] Read more.

Rice fields are one of the most important and extensive agro-ecosystems in the world. Italy is a major non-Asian rice producer, with a significant proportion of its yield originating from a vast area within the Po Valley, a region nourished by the waters of the Alps. While the biodiversity of these rice fields has been extensively documented for certain faunal groups, such as birds, there remains a paucity of research on the biodiversity of aquatic insects. A further challenge is the limited dissemination of findings, which have been primarily published in “gray” literature (local journals, newsletters and similar). Moreover, rice fields are of particular significance in the field of invasion biology, given their role in the arrival and spread of alien species. While the efficacy of rice fields as a substitute for the now-disappeared lowland natural environments is well documented, it is equally evident that traditional rice-growing techniques can require an unsustainable use of water resources, which threatens the biodiversity of the surrounding lotic systems. Here, we summarize and review multiple sources of entomological information from Italian rice fields, analyzing both publications in ISI journals and papers published in local journals (gray literature). In the near future, strategies that reduce the demand for irrigation, promote the cultivation of drought-tolerant crops, and utilize precision farming techniques will be implemented. The challenge will be balancing the need to reduce water withdrawal from rivers with the maintenance of wetlands where possible to support this pivotal component of regional biodiversity. Full article

(This article belongs to the Special Issue Impacts of Environmental Change and Human Activities on Aquatic Ecosystems)

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24 pages, 5197 KB

Open AccessEditor’s ChoiceArticle

Evaluating Pretreatment Strategies with Modeling for Reducing Scaling Potential of Reverse Osmosis Concentrate: Insights from Ion Exchange and Activated Alumina

by Carolina Mejía-Saucedo, Zachary Stoll, Punhasa S. Senanayake, Pei Xu and Huiyao Wang

Water 2025, 17(6), 828; https://doi.org/10.3390/w17060828 - 13 Mar 2025

Cited by 2 | Viewed by 2487

Abstract

Reverse osmosis concentrate (ROC) treatment is critical for enhancing water recovery and minimizing concentrate volume for disposal, especially in regions facing water scarcity. This study investigates the application of ion exchange (IX) resins and activated alumina (AA) as pretreatment strategies to mitigate scaling [...] Read more.

Reverse osmosis concentrate (ROC) treatment is critical for enhancing water recovery and minimizing concentrate volume for disposal, especially in regions facing water scarcity. This study investigates the application of ion exchange (IX) resins and activated alumina (AA) as pretreatment strategies to mitigate scaling in ROC due to high concentrations of total dissolved solids, hardness (Ca²⁺ and Mg²⁺), and silica. Through a series of Langmuir isotherms, continuous column experiments, and model simulation, two types of strong acid cation IX resins and three types of strong base anion IX resins alongside three types of AA were evaluated. Results indicate that AA exhibits superior performance in silica removal, achieving up to a 65% reduction and maintaining performance for up to 800 bed volume without reaching saturation. Model simulation of a secondary reverse osmosis treating ROC after the IX and AA pretreatment indicated an additional water recovery of ~70% using antiscalants. This study demonstrates the potential for achieving higher water recovery while also identifying opportunities for pretreatment improvement. Challenges such as the limited IX capacity treating ROC, which requires frequent regeneration and increases operational costs, along with the restricted regeneration capacity of AA, underscore the importance of innovation. These findings emphasize the critical need for developing advanced materials and optimized strategies to further enhance the efficiency of ROC treatment processes. Full article

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

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18 pages, 1981 KB

Open AccessEditor’s ChoiceArticle

Impact of Freeze–Thaw Action on Soil Erodibility in the Permafrost Regions of the Sanjiangyuan Area Affected by Thermokarst Landslides

by Bihui Wang, Yidong Gu, Kexin Zhou, Shengnan Li, Ce Zheng and Yudong Lu

Water 2025, 17(6), 818; https://doi.org/10.3390/w17060818 - 12 Mar 2025

Cited by 2 | Viewed by 1238

Abstract

The Sanjiangyuan region, known as the “Chinese Water Tower”, serves as a crucial ecological zone that is highly sensitive to climate change. In recent years, rising temperatures and increased precipitation have led to permafrost melt and frequent occurrences of thermokarst landslides, exacerbating soil [...] Read more.

The Sanjiangyuan region, known as the “Chinese Water Tower”, serves as a crucial ecological zone that is highly sensitive to climate change. In recent years, rising temperatures and increased precipitation have led to permafrost melt and frequent occurrences of thermokarst landslides, exacerbating soil erosion issues. Although studies have explored the impact of freeze–thaw action (FTA) on soil properties, research on this phenomenon within the unique geomorphological unit of thermokarst landslides, formed from degrading permafrost, remains sparse. This study, set against the backdrop of temperature-induced soil landslides, combines field investigations and controlled laboratory experiments on typical thermokarst landslide bodies within the permafrost region of Sanjiangyuan to systematically investigate the effects of FTA on the properties of soils within thermokarst landslides. Furthermore, this study employs the EPIC model to establish an empirical formula for the soil erodibility (SE) factor before and after freeze–thaw cycles (FTCs). The results indicate that: (1) FTCs significantly alter soil particle composition, reducing the content of clay particles in the surface soil while increasing the content of sand particles and the median particle size, thus compromising soil structure and enhancing erodibility. (2) FTA initially significantly increases soil organic matter content (OMC); however, as the number of FTCs increases, the magnitude of these changes diminishes. The initial moisture content of the soil significantly influences the effects of FTA, with more pronounced changes in particle composition and OMC in soils with higher moisture content. (3) With an increasing number of FTCs, the SE K-value first significantly increases and then tends to stabilize, showing significant differences across the cycles (1 to 15) (p < 0.05). This study reveals that FTCs, by altering the physicochemical properties of the soil, significantly increase SE, providing a scientific basis for soil erosion control and ecological environmental protection in the Sanjiangyuan area. Full article

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22 pages, 834 KB

Open AccessEditor’s ChoiceArticle

Toxicity of the Antiretrovirals Tenofovir Disoproxil Fumarate, Lamivudine, and Dolutegravir on Cyanobacterium Microcystis novacekii

by Gabriel Souza-Silva, Mariângela Domingos Alcantara, Cléssius Ribeiro de Souza, Carolina Paula de Souza Moreira, Kenia Pedrosa Nunes, Cíntia Aparecida de Jesus Pereira, Marcos Paulo Gomes Mol and Micheline Rosa Silveira

Water 2025, 17(6), 815; https://doi.org/10.3390/w17060815 - 12 Mar 2025

Cited by 4 | Viewed by 2381

Abstract

Antiretrovirals (ARVs) have become one of the most prescribed groups of drugs, and these residues are found in the environment. Among them, the most widely used in HIV treatment are tenofovir (TDF), lamivudine (3TC), and dolutegravir (DTG). This study aimed to evaluate the [...] Read more.

Antiretrovirals (ARVs) have become one of the most prescribed groups of drugs, and these residues are found in the environment. Among them, the most widely used in HIV treatment are tenofovir (TDF), lamivudine (3TC), and dolutegravir (DTG). This study aimed to evaluate the toxicity of ARVs TDF, 3TC, and DTG on the cyanobacterium Microcystis novacekii and estimate their environmental risk. DTG showed the highest toxicity among the drugs tested, inhibiting cyanobacteria cell growth and metabolic activity at low concentrations. TDF and 3TC alone were less toxic, with more pronounced adverse effects in long time exposures at high concentrations. However, the combination of ARVs, especially TDF and 3TC, showed a synergistic effect, significantly increasing toxicity compared to the drugs alone. Excipients found in commercial formulations of ARVs, such as sodium lauryl sulfate, also influenced toxicity. Although DTG showed the highest risk to cyanobacteria, the environmental risk assessment indicated that TDF and 3TC, although less toxic to M. novacekii, may pose moderate-to-high environmental risks at typical environmental concentrations. These results reinforce the need for strict regulation and monitoring of the release of ARVs into the environment, and the development of effective treatments for removing these residues in sewage treatment plants. This study contributes to understanding the ecotoxicological impacts of ARVs and highlights the importance of long-term assessments to adequately estimate the environmental risks of ARVs and their commercial formulations. Full article

(This article belongs to the Special Issue Fate, Transport, Removal and Modeling of Pollutants in Water)

15 pages, 3474 KB

Open AccessEditor’s ChoiceArticle

New Underwater Image Enhancement Algorithm Based on Improved U-Net

by Sisi Zhu, Zaiming Geng, Yingjuan Xie, Zhuo Zhang, Hexiong Yan, Xuan Zhou, Hao Jin and Xinnan Fan

Water 2025, 17(6), 808; https://doi.org/10.3390/w17060808 - 12 Mar 2025

Cited by 5 | Viewed by 3852

Abstract

(1) Objective: As light propagates through water, it undergoes significant attenuation and scattering, causing underwater images to experience color distortion and exhibit a bluish or greenish tint. Additionally, suspended particles in the water further degrade image quality. This paper proposes an improved U-Net [...] Read more.

(1) Objective: As light propagates through water, it undergoes significant attenuation and scattering, causing underwater images to experience color distortion and exhibit a bluish or greenish tint. Additionally, suspended particles in the water further degrade image quality. This paper proposes an improved U-Net network model for underwater image enhancement to generate high-quality images. (2) Method: Instead of incorporating additional complex modules into enhancement networks, we opted to simplify the classic U-Net architecture. Specifically, we replaced the standard convolutions in U-Net with our self-designed efficient basic block, which integrates a simplified channel attention mechanism. Moreover, we employed Layer Normalization to enhance the capability of training with a small number of samples and used the GELU activation function to achieve additional benefits in image denoising. Furthermore, we introduced the SK fusion module into the network to aggregate feature information, replacing traditional concatenation operations. In the experimental section, we used the “Underwater ImageNet” dataset from “Enhancing Underwater Visual Perception (EUVP)” for training and testing. EUVP, established by Islam et al., is a large-scale dataset comprising paired images (high-quality clear images and low-quality blurry images) as well as unpaired underwater images. (3) Results: We compared our proposed method with several high-performing traditional algorithms and deep learning-based methods. The traditional algorithms include He, UDCP, ICM, and ULAP, while the deep learning-based methods include CycleGAN, UGAN, UGAN-P, and FUnIEGAN. The results demonstrate that our algorithm exhibits outstanding competitiveness on the underwater imagenet-dataset. Compared to the currently optimal lightweight model, FUnIE-GAN, our method reduces the number of parameters by 0.969 times and decreases Floating-Point Operations Per Second (FLOPS) by more than half. In terms of image quality, our approach achieves a minimal UCIQE reduction of only 0.008 while improving the NIQE by 0.019 compared to state-of-the-art (SOTA) methods. Finally, extensive ablation experiments validate the feasibility of our designed network. (4) Conclusions: The underwater image enhancement algorithm proposed in this paper significantly reduces model size and accelerates inference speed while maintaining high processing performance, demonstrating strong potential for practical applications. Full article

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25 pages, 4326 KB

Open AccessEditor’s ChoiceArticle

Spatial Distribution, Temporal Behaviour, and Trends of Rainfall Erosivity in Central Italy Using Coarse Data

by Francesca Todisco, Alessio Massimi Alunno and Lorenzo Vergni

Water 2025, 17(6), 801; https://doi.org/10.3390/w17060801 - 11 Mar 2025

Cited by 5 | Viewed by 1325

Abstract

This study examines the spatio-temporal dynamics of rainfall erosivity, R, in the Umbria region (central Italy), based on a 20-year dataset of 30 min precipitation records from 54 stations. Using the RUSLE2 framework, models of varying complexity were evaluated to estimate the R-factor: [...] Read more.

This study examines the spatio-temporal dynamics of rainfall erosivity, R, in the Umbria region (central Italy), based on a 20-year dataset of 30 min precipitation records from 54 stations. Using the RUSLE2 framework, models of varying complexity were evaluated to estimate the R-factor: the original model (Model A), and models based solely on event rainfall depth h_e or daily rainfall depth h_d. All the models show consistency in the spatial and temporal patterns of the R-factor: higher erosivity is observed in the southern and northwestern areas, while summer contributes the most to annual erosivity due to the high average intensity of rainfall events. Trend analyses indicate stationarity across most stations. Compared to Model A (mean R-factor: 1840 MJ mm ha⁻¹ h⁻¹ y⁻¹), the models based on h_e underestimate the R-factor by about 15%, whereas the R-factor derived from the h_d-dependent model is almost equivalent. The estimate from Model A is also approximately 20% higher than that of a previous study conducted on a more limited dataset. The most likely reason for this difference appears to be the formula used for estimating the R-factor. The study highlights the practicality of simplified models, which offer a viable alternative in contexts where high-resolution precipitation data are unavailable. It also demonstrates the benefits of denser station networks and longer observation periods, particularly in regions characterised by complex terrains. Full article

(This article belongs to the Special Issue Soil Erosion Measurement Techniques and Field Experiments, 2nd Edition)

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32 pages, 5862 KB

Open AccessEditor’s ChoiceReview

Advances in Hydrothermal Carbonization for Biomass Wastewater Valorization: Optimizing Nitrogen and Phosphorus Nutrient Management to Enhance Agricultural and Ecological Outcomes

by Guoqing Liu and Tao Zhang

Water 2025, 17(6), 800; https://doi.org/10.3390/w17060800 - 11 Mar 2025

Cited by 11 | Viewed by 5718

Abstract

This study presents a novel approach that integrates hydrothermal carbonization (HTC) technology with circular economy principles to optimize the management of nitrogen and phosphorus in agricultural wastewater. Given the increasing global resource scarcity and continuous ecological degradation, the valorization of biomass wastewater has [...] Read more.

This study presents a novel approach that integrates hydrothermal carbonization (HTC) technology with circular economy principles to optimize the management of nitrogen and phosphorus in agricultural wastewater. Given the increasing global resource scarcity and continuous ecological degradation, the valorization of biomass wastewater has become a critical pathway for the promotion of sustainable development. Biomass wastewater, which contains crop residues, forestry leftovers, and food processing byproducts, has long been regarded as useless waste. However, this wastewater contains abundant organic matter and possesses significant renewable energy potential. The valorization of biomass wastewater can significantly reduce environmental pollution. Through the optimization of the HTC process parameters, we achieved an improvement in the quality and yield of carbonized products, facilitating the efficient recycling and utilization of resources. This research demonstrates that HTC technology can transform agricultural wastewater into valuable biofertilizers, biomass energy, and organic feed, while simultaneously reducing the reliance on fossil fuels, decreasing greenhouse gas emissions, and mitigating the environmental impact of agricultural activities. This paper provides a comprehensive exploration of the application of HTC technology in agricultural ecosystems, highlighting its beneficial role in nitrogen and phosphorus management, resource utilization efficiency, and environmental pollution reduction. The findings of this study suggest that HTC technology holds significant potential in optimizing agricultural wastewater treatment, promoting resource recycling, and advancing sustainable agricultural development. Furthermore, this research offers theoretical support and practical guidance for the implementation of HTC technology in agricultural ecosystems, which is of paramount importance in fostering circular economic development and achieving sustainable agriculture. Full article

(This article belongs to the Special Issue Sustainable Wastewater Treatment and the Circular Economy—2nd Edition)

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22 pages, 9859 KB

Open AccessEditor’s ChoiceArticle

Analysis of Interactions and Driving Factors in Subsystems of Regional Water Resource Carrying Capacity: A Case Study of Ningxia Hui Autonomous Region

by Heyuan Zhou, Suzhen Dang and Chengpeng Lu

Water 2025, 17(6), 792; https://doi.org/10.3390/w17060792 - 10 Mar 2025

Cited by 4 | Viewed by 1116

Abstract

The sustainable utilization of water resources plays a crucial strategic role in regional economic development. The water resources carrying capacity (WRCC) is a multifaceted system influenced by diverse factors, where the interplay among water resources, societal factors, economic conditions, and ecological elements collectively [...] Read more.

The sustainable utilization of water resources plays a crucial strategic role in regional economic development. The water resources carrying capacity (WRCC) is a multifaceted system influenced by diverse factors, where the interplay among water resources, societal factors, economic conditions, and ecological elements collectively determines the overall WRCC. Combining relevant research results, this paper utilized an improved TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) and GRA (grey relational analysis)-based WRCC evaluation model, introduced the panel vector autoregressive (PVAR) model to analyze the effects of interactions among subsystems, and applied the geographically and temporally weighted regression (GTWR) model for the driving analysis of WRCC. Using Ningxia Hui Autonomous Region as a case study, this paper discusses the internal dynamic relationships and driving mechanisms of the WRCC system. It also provides a new perspective for discussing WRCC in water-scarce areas and provides novel approaches for optimizing water resource management and enhancing ecological protection. The results indicate that the water resources subsystem is central to the WRCC in Ningxia, with significant interconnections among the four subsystems. However, significant spatial and temporal heterogeneity is evident across different regions. The water resources system contributes significantly, with ecological development having a positive impact on water resources. However, social and economic development has a restrictive impact on water resources. Full article

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

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15 pages, 3352 KB

Open AccessEditor’s ChoiceArticle

Synthesis of a Novel Modified Zeolite (ZeoPhos) for the Adsorption of Ammonium and Orthophosphate Ions from Eutrophic Waters

by Irene Biliani and Ierotheos Zacharias

Water 2025, 17(6), 786; https://doi.org/10.3390/w17060786 - 8 Mar 2025

Cited by 3 | Viewed by 1608

Abstract

Intensified human activities such as urbanization, agricultural production, industrialization, mining, and fish farming have led to high concentrations of nutrients in water bodies, resulting in eutrophication. Eutrophication has become a global problem that threatens water ecosystems globally. The present study examines the efficiency [...] Read more.

Intensified human activities such as urbanization, agricultural production, industrialization, mining, and fish farming have led to high concentrations of nutrients in water bodies, resulting in eutrophication. Eutrophication has become a global problem that threatens water ecosystems globally. The present study examines the efficiency of applying a novel modified material as an adsorbent for phosphate and ammonium uptake from natural eutrophic freshwater, called ‘ZeoPhos’. The novel material consists of natural zeolite and the addition of iron, calcium, and humic ions, which have been reported for their high adsorption capacity and nutrient-binding properties. Morphological and chemical composition analysis by SEM/EDS and TEM microscopic analysis results are included for natural and modified zeolite. Ammonium and orthophosphate kinetic adsorption results are aligned with pseudo-second kinetic models and reveal 78% and 70% adsorption removal efficiency for solutions of 1 mg NH₄⁺-N/L and 1 mg PO₄³⁻-P/L, respectively. Finally, ‘ZeoPhos’ ammonium and orthophosphate ions adsorption capacity reached up to 28.61 mg/g ± 0.32 and 27.13 mg/g ± 0.57, respectively, after Langmuir fitting isotherm experiments. Full article

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

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18 pages, 6047 KB

Open AccessEditor’s ChoiceArticle

Satellite Retrieval and Spatiotemporal Variability in Chlorophyll-a for Marine Ranching: An Example from Daya Bay, Guangdong Province, China

by Junying Yang, Ruru Deng, Yiwei Ma, Jiayi Li, Yu Guo and Cong Lei

Water 2025, 17(6), 780; https://doi.org/10.3390/w17060780 - 7 Mar 2025

Cited by 6 | Viewed by 1704

Abstract

With the planning and construction of marine ranching in China, water quality has become one of the critical limiting factors for the development of marine ranching. Due to geographical differences, marine ranches exhibit varying water quality conditions under the influence of the continental [...] Read more.

With the planning and construction of marine ranching in China, water quality has become one of the critical limiting factors for the development of marine ranching. Due to geographical differences, marine ranches exhibit varying water quality conditions under the influence of the continental shelf. To the best of our knowledge, there is limited research on satellite-based water quality monitoring for marine ranching and the spatiotemporal variations in marine ranches in different geographical locations. Chlorophyll-a (Chl-a) is a key indicator of the ecological health and disaster prevention capacity of marine ranching, as it reflects the conditions of eutrophication and is crucial for the high-quality, sustainable operation of marine ranching. Using a physically based model, this study focuses on the retrieval of Chl-a concentration in Daya Bay. The coefficient of determination (R²) between the model retrieval values and the in situ Chl-a data is 0.69, with a root mean square error (RMSE) of 1.52 μg/L and a mean absolute percentage error (MAPE) of 44.25%. Seasonal variations in Chl-a concentration are observed in Daya Bay and are higher in spring–summer and lower in autumn–winter. In the YangMeikeng waters, Chl-a concentration shows a declining trend with the development of marine ranching. A comparison between the YangMeikeng (nearshore) and XiaoXingshan (offshore) marine ranches suggests that offshore ranching may be less impacted by terrestrial pollutants. The primary sources of Chl-a input in Daya Bay are the Dan’ao River and the aquaculture areas in the northeastern part of the bay. This study can provide valuable information for the protection and management of marine ranching. Full article

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20 pages, 6538 KB

Open AccessEditor’s ChoiceArticle

The Influence of Wind on the Spatial Distribution of Pelagic Sargassum Aggregations in the Tropical Atlantic

by Marine Laval, Yamina Aimene, Jacques Descloitres, Luc Courtrai, Paulo Duarte-Neto, Adán Salazar-Garibay, Alex Costa da Silva, Pascal Zongo, René Dorville and Cristèle Chevalier

Water 2025, 17(6), 776; https://doi.org/10.3390/w17060776 - 7 Mar 2025

Cited by 2 | Viewed by 1481

Abstract

Since 2011, Sargassum seaweed has spread widely outside the Sargasso Sea, causing massive strandings on the coasts of the West Indies and Mexico, causing serious economic, ecological, and health problems. This Atlantic pelagic alga has the characteristic of moving in rafts. According to [...] Read more.

Since 2011, Sargassum seaweed has spread widely outside the Sargasso Sea, causing massive strandings on the coasts of the West Indies and Mexico, causing serious economic, ecological, and health problems. This Atlantic pelagic alga has the characteristic of moving in rafts. According to in situ observations, their size and shape can vary with the wind. To better understand the effect of wind on Sargassum coverage and aggregation size, we conducted a large temporal (2019–2022) and spatial scale study in the West Indies using OLCI/Sentinel-3 satellite imagery. During this period, a database of nearly 1 million Sentinel-3 aggregations, including their geometric and wind characteristics, was established. Analysis of the size distribution showed that wind has a dual effect on disaggregation and agglomeration depending on wind speed and aggregation size: (1) low winds favor agglomeration for the smallest aggregations and disaggregation for the largest aggregations; (2) high winds favor disaggregation for all aggregation sizes. In addition, topography also plays a role in size distribution: the Caribbean arc favors agglomeration over offshore zones, and coastal areas favor disaggregation over offshore zones. Full article

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

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26 pages, 8108 KB

Open AccessEditor’s ChoiceArticle

Investigating Groundwater–Surface Water Interactions and Transformations in a Typical Dry–Hot Valley Through Environmental Isotopes Analysis

by Jun Li, Honghao Liu, Yizhi Sheng, Duo Han, Keqiang Shan, Zhiping Zhu and Xuejian Dai

Water 2025, 17(6), 775; https://doi.org/10.3390/w17060775 - 7 Mar 2025

Cited by 5 | Viewed by 1689

Abstract

This study investigates the hydrological processes and water body transformation mechanisms in the Yuanmou dry–hot valley, focusing on precipitation, well water, spring water, river water, and reservoir water, during both wet and dry seasons. The spatiotemporal characteristics and significance of the hydrogen and [...] Read more.

This study investigates the hydrological processes and water body transformation mechanisms in the Yuanmou dry–hot valley, focusing on precipitation, well water, spring water, river water, and reservoir water, during both wet and dry seasons. The spatiotemporal characteristics and significance of the hydrogen and oxygen stable isotopes across these water bodies were analyzed. Key findings included the following: (i) Seasonal variations in precipitation, river water, and shallow groundwater were minimal, and were primarily driven by differences in water vapor sources and transport distances during wet and dry seasons. The seasonal effects of mid-deep groundwater and reservoir water were influenced by leakage recharge from deep aquifers and temperature variations, respectively. (ii) The groundwater line-conditioned excess (lc-excess) deviated significantly from the Local Meteoric Water Line, indicating that precipitation recharge occurred primarily through slow infiltration piston flow with significant isotopic fractionation. (iii) River water was recharged by precipitation, deep groundwater, and spring water; well water by precipitation and lateral groundwater inflow; spring water by deep groundwater; and reservoir water by precipitation, groundwater, and water transfer, with strong evaporation effects. (iv) Using a binary isotope mass balance model, the recharge ratios of precipitation and groundwater to surface water were calculated to be 40% and 60%, respectively. Additionally, during the wet season, the proportion of groundwater recharge to river water increased. This study provides valuable insights into hydrological cycle processes in dry–hot valleys and offers a scientific basis for the sustainable development and management of water resources in arid regions. Full article

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18 pages, 18373 KB

Open AccessEditor’s ChoiceArticle

Visual Satisfaction of Urban Park Waterfront Environment and Its Landscape Element Characteristics

by Mei Lyu, Shujiao Wang, Jiaxuan Shi, Dong Sun, Kangting Cong and Yi Tian

Water 2025, 17(6), 772; https://doi.org/10.3390/w17060772 - 7 Mar 2025

Cited by 6 | Viewed by 2794

Abstract

Close contact with nature helps moderate public emotions and enhance happiness. As an important space for the public to connect with nature, the urban park waterfront environment plays a significant role. Studying the characteristics of landscape elements contributes to the optimization of the [...] Read more.

Close contact with nature helps moderate public emotions and enhance happiness. As an important space for the public to connect with nature, the urban park waterfront environment plays a significant role. Studying the characteristics of landscape elements contributes to the optimization of the urban park natural environment. In this study, the waterfront spaces of 23 urban parks in Shenyang were selected in order to categorize urban park waterfront spaces from the perspective of landscape elements and to explore the relationship between the characteristics of landscape elements in different types of waterfront spaces and public visual satisfaction. Using qualitative analysis, typical spatial types were identified based on differences in landscape elements. Content analysis was used to extract and quantify the characteristics of landscape elements for various waterfront spaces. Through orthogonal experimental design, virtual scenarios were created to evaluate public satisfaction. Methods such as the least significant difference multiple comparison analysis (LSD) were applied to explore the effects of landscape element characteristics on satisfaction in different types and differences within groups. Among the four types of waterfront spaces identified in the experiment, the landscape elements that influenced spatial satisfaction were primarily concentrated in plant characteristics and pavement characteristics. In different types of spaces, the impact of landscape element factors at different levels varied. The study introduced virtual experiments to analyze the characteristics of landscape elements in waterfront spaces, which provided a new method for the satisfaction research of waterfront spaces. The results are a valuable guidance for the scientific classification of urban park waterfront spaces. A new perspective for enhancing the urban park waterfront landscape was supplied. Full article

(This article belongs to the Special Issue Ecohydrological Processes, Environmental Effects, and Integrated Regulation of Wetland Ecosystems, 3rd Edition)

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18 pages, 5543 KB

Open AccessEditor’s ChoiceArticle

Deformation and Failure Mechanism of Bedding Rock Landslides Based on Stability Analysis and Kinematics Characteristics: A Case Study of the Xing’an Village Landslide, Chongqing

by Jingyi Zeng, Zhenwei Dai, Xuedong Luo, Weizhi Jiao, Zhe Yang, Zixuan Li, Nan Zhang and Qihui Xiong

Water 2025, 17(5), 767; https://doi.org/10.3390/w17050767 - 6 Mar 2025

Cited by 4 | Viewed by 1608

Abstract

Bedding rock landslides, characterized by their distinct geological structure, are widely distributed and highly susceptible to sliding under external disturbances, resulting in catastrophic events. This study aims to unravel the geomechanical mechanisms governing rainfall-induced instability through an integrated investigation of a representative landslide [...] Read more.

Bedding rock landslides, characterized by their distinct geological structure, are widely distributed and highly susceptible to sliding under external disturbances, resulting in catastrophic events. This study aims to unravel the geomechanical mechanisms governing rainfall-induced instability through an integrated investigation of a representative landslide in Xing’an Village, Chongqing. Employing multidisciplinary approaches, including field monitoring, geotechnical testing, and dynamic numerical modeling, we systematically revealed two critical failure zones: a front failure zone and a rear potential instability zone. Under rainstorm conditions, the safety factor for both zones was 1.02, indicating a marginally unstable state. The DAN-W simulations indicate that the potential instability zone at the rear of the landslide experienced complete failure within 12 s under heavy rainfall, with a maximum run-out distance of 20 m, a maximum velocity of 4.32 m/s, and a maximum deposition thickness of 8.3 m, which could potentially bury the buildings at the toe of the landslide. The low strength and permeability of the mudstone-dominated Badong Formation, characterized by interbedded mudstone, siltstone, and sandstone within the Middle Triassic geological system, provides a fundamental prerequisite for the landslide. Rainwater infiltration into the mudstone layers degraded its mechanical properties, and excavation at the slope base ultimately triggered the landslide initiation. These findings can provide theoretical support for preventing and managing similar bedding rock landslides with similar geological backgrounds. Full article

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13 pages, 1727 KB

Open AccessEditor’s ChoiceArticle

Degradation of Phenolic Compounds and Organic Matter from Real Winery Wastewater by Fenton and Photo-Fenton Processes Combined with Ultrasound

by Ricardo Augusto Rodrigues, Mariana Bizari Machado de Campos and Paulo Sergio Tonello

Water 2025, 17(5), 763; https://doi.org/10.3390/w17050763 - 6 Mar 2025

Cited by 2 | Viewed by 1713

Abstract

Real winery wastewater (WW), with a high concentration of organic matter (OM), was treated using Fenton (FP), photo-Fenton (PFP), sono-Fenton (SFP), and sono-photo-Fenton processes (SPFP), with the primary objective of removing phenolic compounds (PhCs). Although beneficial to human health, these compounds are considered [...] Read more.

Real winery wastewater (WW), with a high concentration of organic matter (OM), was treated using Fenton (FP), photo-Fenton (PFP), sono-Fenton (SFP), and sono-photo-Fenton processes (SPFP), with the primary objective of removing phenolic compounds (PhCs). Although beneficial to human health, these compounds are considered recalcitrant and toxic to aquatic organisms, posing significant environmental risks if discharged into water bodies. They can also reduce the efficiency of biological treatment processes. After physicochemical characterization and two hours of treatment, the removal efficiencies achieved by the FP, PFP, SFP, and SPFP processes were 29.35%, 41.30%, 28.82%, and 33.95% for PhCs; 27.88%, 31.51%, 23.19%, and 29.29% for chemical oxygen demand (COD); and 12.53%, 13.92%, 9.28%, and 10.62% for dissolved organic carbon (DOC), respectively. The degradations achieved by SFP and SPFP were lower than those of FP and PFP, respectively, due to reactions that scavenge hydroxyl radicals. Treatment of a gallic acid (GA) solution, used as a model compound for PhCs, exhibited similar trends, indicating that the lower efficiency in processes involving ultrasound is not due to the OM in the effluent, but rather the interaction between ultrasound (US) and H₂O₂, which reduces hydroxyl radical concentration. However, under the conditions of the wastewater used, the technologies applied did not completely reduce the parameters analyzed, being recommended as pre- or post-treatment, and combined with other processes. Full article

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

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19 pages, 2233 KB

Open AccessEditor’s ChoiceArticle

Quantifying Temporal Dynamics of E. coli Concentration and Quantitative Microbial Risk Assessment of Pathogen in a Karst Basin

by Shishir K. Sarker, Ryan T. Dapkus, Diana M. Byrne, Alan E. Fryar and Justin M. Hutchison

Water 2025, 17(5), 745; https://doi.org/10.3390/w17050745 - 4 Mar 2025

Cited by 4 | Viewed by 2129

Abstract

Karst aquifers can be highly productive water sources but are vulnerable to contamination by pathogens because of integrated surface and subsurface drainage. Our study focuses on the karstic Royal Spring basin in Kentucky, encompassing urban and agricultural land uses. The city of Georgetown [...] Read more.

Karst aquifers can be highly productive water sources but are vulnerable to contamination by pathogens because of integrated surface and subsurface drainage. Our study focuses on the karstic Royal Spring basin in Kentucky, encompassing urban and agricultural land uses. The city of Georgetown distributes treated water from Royal Spring to over 33,000 customers. We examined E. coli dynamics at Royal Spring from June 2021 through June 2022, assessing variability under wet versus dry weather conditions. We also used quantitative microbial risk assessment (QMRA) to estimate potential health risks from the pathogenic bacterium E. coli O157:H7. E. coli concentrations in weekly water samples varied from 12 to 1732.8 MPN/100 mL, with a geometric mean of 117.2 MPN/100 mL. The mean concentration in wet periods was approximately double that during dry conditions. Because the pathogen was not detected by quantitative PCR (qPCR), we conducted QMRA based on literature data for water treatment plant operations (occupational) and recreational activities near the spring. The median probability of annual infection was 5.11 × 10⁻³ for occupational exposure and 1.45 × 10⁻² for recreational exposure. Uncertainty and sensitivity analyses revealed that health risks were most sensitive to the pathogen/E. coli ratio and ingestion rate. Although the pathogen was not detected by qPCR, the presence of E. coli suggests potential fecal contamination. This highlights the importance of continued monitoring and investigation of different detection methods to better understand potential health risks in karst systems. Full article

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

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16 pages, 10090 KB

Open AccessEditor’s ChoiceArticle

Hybrid System of Fenton Process and Sequencing Batch Reactor for Coking Wastewater Treatment

by Anna Grosser, Ewa Neczaj, Dorota Krzemińska and Izabela Ratman-Kłosińska

Water 2025, 17(5), 751; https://doi.org/10.3390/w17050751 - 4 Mar 2025

Cited by 4 | Viewed by 1627

Abstract

The aim of the work was to investigate the treatment efficiency of coking wastewater in a hybrid system combining the Fenton process with an SBR reactor. The Fenton reaction was optimised using variable reagent doses of 0.75, 1.0, 1.25 and 1.5 g/L for [...] Read more.

The aim of the work was to investigate the treatment efficiency of coking wastewater in a hybrid system combining the Fenton process with an SBR reactor. The Fenton reaction was optimised using variable reagent doses of 0.75, 1.0, 1.25 and 1.5 g/L for iron ions and 750, 1000, 1250, and 1500 mg/L for H₂O₂. The effects of Fe²⁺ and H₂O₂ concentration on BOD, COD, TOC, TN N-NH₄⁺ and BOD/COD ratio were studied in detail to optimise the pretreatment performance. The selection of the most favourable parameters for the Fenton reaction was based on the frequency of occurrence of a different combination of the chemical reagents. The most beneficial doses were found to be 0.75 g/L of iron (II) ion and 1000 mg/L of hydrogen peroxide, at which the COD reduction rate was about 40% and a high increase in the BOD₅/COD ratio from 0.1 to 0.31 was observed. Moreover, the obtained results showed that the efficiency of removing organic pollutants and nitrogen compounds was higher in the SBR reactor fed with pretreated wastewater. However, the relatively low efficiency of removing TKN (25%) and NH₄⁺ (21%) indicates the presence of toxic substances in them that may inhibit the removal of nitrogen compounds. Full article

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15 pages, 3129 KB

Open AccessEditor’s ChoiceArticle

Evaluating Modeling Approaches for Phytoplankton Productivity in Estuaries

by Reed Hoshovsky, Frances Wilkerson, Alexander Parker and Richard Dugdale

Water 2025, 17(5), 747; https://doi.org/10.3390/w17050747 - 4 Mar 2025

Cited by 2 | Viewed by 1464

Abstract

Phytoplankton comprise the base of the food web in estuaries and their biomass and rates of growth (productivity) exert a bottom-up control in pelagic ecosystems. Reliable means to quantify biomass and productivity are crucial for managing estuarine ecosystems. In many estuaries, direct productivity [...] Read more.

Phytoplankton comprise the base of the food web in estuaries and their biomass and rates of growth (productivity) exert a bottom-up control in pelagic ecosystems. Reliable means to quantify biomass and productivity are crucial for managing estuarine ecosystems. In many estuaries, direct productivity measurements are rare and instead are estimated with biomass-based models. A seminal example of this is a light utilization model (LUM) used to predict productivity in the San Francisco Estuary and Delta (SFED) from long timeseries data using an efficiency factor, ψ. Applications of the LUM in the SFED, Chesapeake Bay, and the Dutch Scheldt Estuary highlight significant interannual and regional variability, indicating the model must be recalibrated often. The objectives of this study are to revisit the LUM approach in the SFED and assess a chlorophyll-a to carbon model (CCM) that produces a tuning parameter, Ω. To assess the estimates of primary productivity resulting from the models, productivity was directly measured with a ¹³C-tracer at nine locations during 22 surveys using field-derived phytoplankton incubations between March and November of 2023. For this study, ψ was determined to be 0.42 ± 0.02 (r² = 0.89, p < 0.001, CI₉₅ = 319). Modeling productivity using an alternative CCM approach (Ω = 3.47 × 10⁴ ± 1.7 × 10³, r² = 0.84, p < 0.001, CI₉₅ = 375) compared well to the LUM approach, expanding the toolbox for estuarine researchers to cross-examine productivity models. One practical application of this study is that it confirms an observed decline in ψ, suggesting a decline in light utilization by phytoplankton in the SFED. This highlights the importance of occasionally recalibrating productivity models in estuaries and leveraging multiple modeling approaches to validate estimations before application in ecological management decision making. Full article

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

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18 pages, 5447 KB

Open AccessEditor’s ChoiceArticle

Coupling Interpretable Feature Selection with Machine Learning for Evapotranspiration Gap Filling

by Lizheng Wang, Lixin Dong and Qiutong Zhang

Water 2025, 17(5), 748; https://doi.org/10.3390/w17050748 - 4 Mar 2025

Cited by 2 | Viewed by 1887

Abstract

Evapotranspiration (ET) plays a pivotal role in linking the water and carbon cycles between the land and atmosphere, with latent heat flux (LE) representing the energy manifestation of ET. Due to adverse meteorological conditions, data quality filtering, and instrument malfunctions, LE measured by [...] Read more.

Evapotranspiration (ET) plays a pivotal role in linking the water and carbon cycles between the land and atmosphere, with latent heat flux (LE) representing the energy manifestation of ET. Due to adverse meteorological conditions, data quality filtering, and instrument malfunctions, LE measured by the eddy covariance (EC) is temporally discontinuous at the hourly and daily scales. Machine-learning (ML) models effectively capture the complex relationships between LE and its influencing factors, demonstrating superior performance in filling LE data gaps. However, the selection of features in ML models often relies on empirical knowledge, with identical features frequently used across stations, leading to reduced modeling accuracy. Therefore, this study proposes an LE gap-filling model (SHAP-AWF-BO-LightGBM) that combines the Shapley additive explanations adaptive weighted fusion method with the Bayesian optimization light gradient-boosting machine algorithm. This is tested using data from three stations in the Heihe River Basin, China, representing different plant functional types. For 30 min interval missing LE data, the RMSE ranges from 17.90 W/m² to 20.17 W/m², while the MAE ranges from 10.74 W/m² to 14.04 W/m². The SHAP-AWF method is used for feature selection. First, the importance of SHAP features from multiple ensemble-learning models is adaptively weighted as the basis for feature input into the BO-LightGBM algorithm, which enhances the interpretability and transparency of the model. Second, data redundancy and the cost of collecting other feature data during model training are reduced, improving model calculation efficiency (reducing the initial number of features of different stations from 42, 46, and 48 to 10, 15, and 8, respectively). Third, under the premise of ensuring accuracy as much as possible, the gap-filling ratio for missing LE data at different stations is improved, and the adaptability of using only automatic weather station observation is enhanced (the improvement range is between 7.46% and 11.67%). Simultaneously, the hyperparameters of the LightGBM algorithm are optimized using a Bayesian algorithm, further enhancing the accuracy of the model. This study provides a new approach and perspective to fill the missing LE in EC measurement. Full article

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

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23 pages, 4130 KB

Open AccessEditor’s ChoiceArticle

Machine Learning-Based Early Warning of Algal Blooms: A Case Study of Key Environmental Factors in the Anzhaoxin River Basin

by Yuyin Ao, Juntao Fan, Fen Guo, Mingyue Li, Aopu Li, Yue Shi and Jian Wei

Water 2025, 17(5), 725; https://doi.org/10.3390/w17050725 - 1 Mar 2025

Cited by 4 | Viewed by 2277

Abstract

Algal blooms are a major risk to aquatic ecosystem health and potable water safety. Traditional statistical models often fail to accurately predict algal bloom dynamics due to their complexity. Machine learning, adept at managing high-dimensional and non-linear data, provides a superior predictive approach [...] Read more.

Algal blooms are a major risk to aquatic ecosystem health and potable water safety. Traditional statistical models often fail to accurately predict algal bloom dynamics due to their complexity. Machine learning, adept at managing high-dimensional and non-linear data, provides a superior predictive approach to this challenge. In this study, we employed support vector machine (SVM), random forest (RF), and backpropagation neural network (BPNN) models to predict the severity of algal blooms in the Anzhaoxin River Basin based on an algal density-based grading standard. The SVM model demonstrated the highest accuracy with training and test set accuracies of 0.96 and 0.92, highlighting its superiority in small-sample learning. The Shapley Additive Explanations (SHAP) technique was utilized to evaluate the contribution of environmental variables in various predictive models. The results show that TP is the most significant environmental factor affecting the algal bloom outbreak in Anzhaoxin River, and the phosphorus management strategy is more suitable for the management of the artificial water body in northeast China. This study contributes to exploring the potential application of machine learning models in diagnosing and predicting riverine ecological issues, providing valuable insights and support for the protection and management of aquatic ecosystems in the Anzhaoxin River Basin. Full article

(This article belongs to the Special Issue Microalgae Control and Utilization: Challenges and Perspectives)

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21 pages, 6979 KB

Open AccessEditor’s ChoiceArticle

Nitrogen and Gray Water Footprints of Various Cropping Systems in Irrigation Districts: A Case from Ningxia, China

by Huan Liu, Xiaotong Liu, Tianpeng Zhang, Xinzhong Du, Ying Zhao, Jiafa Luo, Weiwen Qiu, Shuxia Wu and Hongbin Liu

Water 2025, 17(5), 717; https://doi.org/10.3390/w17050717 - 1 Mar 2025

Cited by 3 | Viewed by 1643

Abstract

Under the influence of water resource conservation policies, the annual water diversion volumes in irrigation areas have been steadily decreasing, leading to substantial changes in regional cropping systems. These shifts have profoundly impacted agricultural reactive nitrogen (Nr) emissions and surface water quality. This [...] Read more.

Under the influence of water resource conservation policies, the annual water diversion volumes in irrigation areas have been steadily decreasing, leading to substantial changes in regional cropping systems. These shifts have profoundly impacted agricultural reactive nitrogen (Nr) emissions and surface water quality. This study focuses on the Yellow River Irrigation area of Ningxia, China, and employs a life cycle assessment method to quantitatively analyze fluctuations in the nitrogen footprint (NF) and gray water footprint (GWF) across three cropping systems—rice-maize intercropping, rice monoculture, and maize monoculture—during 2021–2023. The results indicate that rice monoculture exhibited significant variability in NF values (197.89–497.57 kg Neq·ha⁻¹), with NO₃⁻ leaching identified as the primary loss pathway (102.33–269.48 kg Neq·ha⁻¹). The GWF analysis revealed that in 2021, the region’s GWF peaked at 23.18 × 10⁴ m³·ha⁻¹, with water pollution predominantly concentrated in Pingluo County (8 × 10⁴ m³·ha⁻¹). LMDI analysis identified nitrogen fertilizer application as the main contributor to variations in NF, while surface water pollution was indirectly influenced by crop yield. Furthermore, gray correlation analysis highlighted a significant coupling relationship between NF and GWF, with nitrogen fertilizer application having the most pronounced impact on GWF. Therefore, in the face of the gradual tightening of water resources in the irrigation areas, the current situation of reduced water diversion should be adopted as early as possible, and initiatives such as the reduction of nitrogen fertilizer application and the adjustment of the planting area of dryland crops should be accelerated to cope with the problem of nitrogen pollution brought about by changes in the cropping system. Full article

(This article belongs to the Special Issue Basin Non-Point Source Pollution)

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23 pages, 2010 KB

Open AccessEditor’s ChoiceArticle

Technical, Economic, Energetic, and Environmental Evaluation of Pretreatment Strategies for Scaling Control in Brackish Water Desalination Brine Treatment

by Abdiel Lugo, Carolina Mejía-Saucedo, Punhasa S. Senanayake, Zachary Stoll, Kurban Sitterley, Huiyao Wang, Krishna Kota, Sarada Kuravi, Vasilis Fthenakis, Parthiv Kurup and Pei Xu

Water 2025, 17(5), 708; https://doi.org/10.3390/w17050708 - 28 Feb 2025

Cited by 9 | Viewed by 2940

Abstract

Effective pretreatment is essential for achieving long-term stable operation and high water recovery during the desalination of alternative waters. This study developed a process modeling approach for technical, economic, energetic, and environmental assessments of pretreatment technologies to identify the impacts of each technology [...] Read more.

Effective pretreatment is essential for achieving long-term stable operation and high water recovery during the desalination of alternative waters. This study developed a process modeling approach for technical, economic, energetic, and environmental assessments of pretreatment technologies to identify the impacts of each technology treating brackish water desalination brine with high scaling propensity. The model simulations evaluated individual pretreatment technologies, including chemical softening (CS), chemical coagulation (CC), electrocoagulation (EC), and ion exchange (IX). In addition, combinations of these pretreatment technologies aiming at the effective reduction of key scaling constituents such as hardness and silica were investigated. The three evaluation parameters in this assessment consist of levelized cost of water (LCOW, $/m³), specific energy consumption and cumulative energy demand (SEC|CED, kWh/m³), and carbon dioxide emissions (CO₂, kg CO_2-eq/m³). The case study evaluated in this work was the desalination brine from the Kay Bailey Hutchison Desalination Plant (KBHDP) with a total dissolved solids (TDS) concentration of 11,000 mg/L and rich in hardness and silica. The evaluation of individual pretreatment units from the highest to lowest LCOW, SEC|CED, and CO₂ emissions in the KBHDP brine was IX > CS > EC > CC, CS > IX > EC > CC, and CC > CS > EC > IX, respectively. In the case of pretreatment combinations for the KBHDP, the EC + IX treatment combination was shown to be the best in terms of the LCOW and CO₂ emissions. The modeling and evaluation of these pretreatment units provide valuable guidance on the selection of cost-effective, energy-efficient, and environmentally sustainable pretreatment technologies tailored to desalination brine applications for minimal- or zero-liquid discharge. Full article

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

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14 pages, 4168 KB

Open AccessEditor’s ChoiceArticle

Comparative Long-Term Monitoring of Microplastics in the Effluent of Three Different Wastewater Treatment Plants with Two, Three, and Four Treatment Stages

by Michael Toni Sturm, Daphne Argyropoulou, Erika Myers, Anika Korzin, Pieter Ronsse, Oleg Zernikel, Dennis Schober and Katrin Schuhen

Water 2025, 17(5), 711; https://doi.org/10.3390/w17050711 - 28 Feb 2025

Cited by 2 | Viewed by 2133

Abstract

Wastewater treatment plants (WWTPs) are important point sources for microplastics (MPs) in the environment. For effective mitigation measures and regulations, it is important to monitor their release into the environment and understand the level of MPs in the WWTP effluents based on different [...] Read more.

Wastewater treatment plants (WWTPs) are important point sources for microplastics (MPs) in the environment. For effective mitigation measures and regulations, it is important to monitor their release into the environment and understand the level of MPs in the WWTP effluents based on different treatment technologies. In this study, we compare the MP levels in the effluents of three different municipal WWTPs which each use a different treatment concept: a conventional three-stage WWTP, one with an additional fourth cleaning stage using powdered activated carbon, and a two-stage WWTP utilizing a membrane bioreactor (MBR). Long-term monitoring was performed on the WWTP effluents using the same standardized methods for sample collection, preparation, and detection, based on fluorescent staining. Despite the various advanced treatment processes, there are no significant differences in the resulting MP contamination in the investigation of WWTP effluents. The average MP concentrations in the effluents were 21.8 MPs/L for the conventional three-stage WWTP, 15.1 MPs/L for the four-stage WWTP, and 15.1 MPs/L for the MBR. Further, the MP contamination in all effluents shows a strong fluctuation over time. These findings highlight the need for standard MP monitoring at WWTPs, to gain a better understanding of the MP emission in different treatment processes. Further, it highlights the need for a fourth treatment stage that specifically targets MP removal to effectively prevent the MP release from WWTPs into the environment. Full article

(This article belongs to the Special Issue Microplastics Pollution in Aquatic Environments)

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14 pages, 15721 KB

Open AccessEditor’s ChoiceArticle

Performance of Emitters in Drip Irrigation Systems Using Computational Fluid Dynamic Analysis

by Mauro De Marchis, Federica Bruno, Domenico Saccone and Enrico Napoli

Water 2025, 17(5), 689; https://doi.org/10.3390/w17050689 - 27 Feb 2025

Cited by 4 | Viewed by 2916

Abstract

Flat drippers are widely used in agricultural irrigation systems to ensure precise water distribution. This study investigates the optimization of flat drippers through Computational Fluid Dynamics (CFDs) simulations, focusing on the channel geometry. These emitters have a particular configuration of the labyrinth channel [...] Read more.

Flat drippers are widely used in agricultural irrigation systems to ensure precise water distribution. This study investigates the optimization of flat drippers through Computational Fluid Dynamics (CFDs) simulations, focusing on the channel geometry. These emitters have a particular configuration of the labyrinth channel appropriately shaped to ensure high turbulence and dissipation of the hydraulic load. CFDs techniques are particularly suitable to investigate the labyrinth design and optimization. Here, by analyzing seven different dripper models with varying dissipation channel sizes, the relationship between flow rate (liters per hour) and pipe pressure (kPa) was studied. Simulations were performed for six inlet pressures in the range between 50 and 175 kPa, with steps of 25 kPa, allowing for the derivation of the pressure–flow curve and the optimization of the emitter exponent. The value of the exponent is closely linked to the conformation of the channel and is standardized by the International Organization for Standardization (ISO) 9261:2004. Additionally, the influence of the labyrinth channel’s cross-sectional area on flow rate was examined, providing insights into design improvements for enhanced hydraulic performance. The proposed optimization could lead to significant water savings and enhanced agricultural productivity by improving the efficiency of irrigation systems. Full article

(This article belongs to the Special Issue Advances in Agricultural Irrigation Management and Technology)

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19 pages, 3546 KB

Open AccessEditor’s ChoiceArticle

A Comparative Assessment of Reynolds Averaged Navier–Stokes and Large-Eddy Simulation Models: Choosing the Best for Pool-Type Fishway Flow Simulations

by Ana L. Quaresma, Filipe Romão and António N. Pinheiro

Water 2025, 17(5), 686; https://doi.org/10.3390/w17050686 - 27 Feb 2025

Cited by 7 | Viewed by 1432

Abstract

Fishways are an important solution for mitigating the ecological impacts of river barriers, with their hydrodynamics playing a key role in their effectiveness. Computational fluid dynamics (CFD) is now one of the main tools to predict and characterize flow hydrodynamics, but choosing the [...] Read more.

Fishways are an important solution for mitigating the ecological impacts of river barriers, with their hydrodynamics playing a key role in their effectiveness. Computational fluid dynamics (CFD) is now one of the main tools to predict and characterize flow hydrodynamics, but choosing the most suitable turbulence model is considered one of its main challenges. Although substantial research has been carried out on vertical slot fishways, where the flow is predominantly two-dimensional, studies on pool-type fishways with bottom orifices remain scarce. In this study, three Reynolds averaged Navier–Stokes (RANS) turbulence models (the standard k-ε model, the renormalized group k-ε (RNG) model, and the standard k-ω model) and the large-eddy simulation (LES) model performances were compared to simulating the flow in a pool-type fishway with bottom orifices. ADV and PIV experimental data were used to assess model performance. While all the turbulence models accurately predicted the discharges and flow depths, the LES model outperformed the others in reproducing flow patterns, velocities, and turbulent kinetic energy. The RNG model also showed reasonable agreement with the experimental data. By contrast, the k-ε model delivered the poorest performance, failing to accurately predict the sizes of the recirculation zones and the locations of the recirculation axis and presenting the weakest agreement with the experimental observations. The value of the LES model in studying and characterizing fishway hydrodynamics, particularly concerning turbulence parameters, is highlighted. Full article

(This article belongs to the Special Issue Fishway Design and Development: New Challenges, Tools and Applications)

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26 pages, 5578 KB

Open AccessEditor’s ChoiceArticle

Predicting Harmful Algal Blooms Using Explainable Deep Learning Models: A Comparative Study

by Bekir Zahit Demiray, Omer Mermer, Özlem Baydaroğlu and Ibrahim Demir

Water 2025, 17(5), 676; https://doi.org/10.3390/w17050676 - 26 Feb 2025

Cited by 13 | Viewed by 5781

Abstract

Harmful algal blooms (HABs) have emerged as a significant environmental challenge, impacting aquatic ecosystems, drinking water supply systems, and human health due to the combined effects of human activities and climate change. This study investigates the performance of deep learning models, particularly the [...] Read more.

Harmful algal blooms (HABs) have emerged as a significant environmental challenge, impacting aquatic ecosystems, drinking water supply systems, and human health due to the combined effects of human activities and climate change. This study investigates the performance of deep learning models, particularly the Transformer model, as there are limited studies exploring its effectiveness in HAB prediction. The chlorophyll-a (Chl-a) concentration, a commonly used indicator of phytoplankton biomass and a proxy for HAB occurrences, is used as the target variable. We consider multiple influencing parameters—including physical, chemical, and biological water quality monitoring data from multiple stations located west of Lake Erie—and employ SHapley Additive exPlanations (SHAP) values as an explainable artificial intelligence (XAI) tool to identify key input features affecting HABs. Our findings highlight the superiority of deep learning models, especially the Transformer, in capturing the complex dynamics of water quality parameters and providing actionable insights for ecological management. The SHAP analysis identifies Particulate Organic Carbon, Particulate Organic Nitrogen, and total phosphorus as critical factors influencing HAB predictions. This study contributes to the development of advanced predictive models for HABs, aiding in early detection and proactive management strategies. Full article

(This article belongs to the Special Issue Aquatic Ecosystems: Biodiversity and Conservation)

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20 pages, 10353 KB

Open AccessEditor’s ChoiceArticle

Numerical Modelling of Coupled Thermal–Hydraulic–Mechanical Processes in Unsaturated Soils During Freezing and Thawing

by Sara Soltanpour and Adolfo Foriero

Water 2025, 17(5), 677; https://doi.org/10.3390/w17050677 - 26 Feb 2025

Cited by 4 | Viewed by 1674

Abstract

Most existing studies investigate the effect of the overburden pressure and external temperature on the freezing process in unsaturated soils. However, the hydraulic and thermal properties of soil have a significant outcome as well. For this purpose, a coupled Thermal–Hydraulic–Mechanical theory, to investigate [...] Read more.

Most existing studies investigate the effect of the overburden pressure and external temperature on the freezing process in unsaturated soils. However, the hydraulic and thermal properties of soil have a significant outcome as well. For this purpose, a coupled Thermal–Hydraulic–Mechanical theory, to investigate unsaturated fine sands, is developed and deployed in a finite element method simulation with COMSOL Multiphysics. Validation of the model’s accuracy is achieved by comparing the numerical to the experimental soil freezing and thawing results published in the literature. After validating the model’s reliability, five cases are simulated to examine the impact of soil particle thermal conductivity and saturated hydraulic conductivity on the freezing and thawing processes. Results indicate that the saturated hydraulic conductivity has a slightly greater effect on the position of the freezing front and on the amount of heave than particle thermal conductivity. Finally, this study shows the effect inflicted by the temperature gradient, water flux, and vertical stress build-up on both thermal and hydraulic properties during the freeze–thaw cycles. Full article

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22 pages, 8381 KB

Open AccessEditor’s ChoiceArticle

Assessing the Use of Alternative Soil Data in Hydrological and Water Quality Modeling with SWAT+: SSURGO and POLARIS at Sub-Basin and Field Scales

by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Michael J. White, Jungang Gao and Jeffrey G. Arnold

Water 2025, 17(5), 670; https://doi.org/10.3390/w17050670 - 25 Feb 2025

Cited by 3 | Viewed by 1499

Abstract

The accuracy of soil databases is essential in hydrological modeling, yet limited studies have evaluated the implications of using emerging soil datasets like POLARIS compared to traditional ones such as SSURGO. This study evaluates the performance of POLARIS soil data for simulating the [...] Read more.

The accuracy of soil databases is essential in hydrological modeling, yet limited studies have evaluated the implications of using emerging soil datasets like POLARIS compared to traditional ones such as SSURGO. This study evaluates the performance of POLARIS soil data for simulating the streamflow and sediment yield at both the sub-basin and field scales within the Big Muddy Watershed (BMW), Illinois, U.S.A., using a soft-calibrated SWAT+ model. The field-scale analysis focused on cropland-dominated HRUs from two sub-basins with contrasting POLARIS-SSURGO similarities at the sub-basin scale, optimizing computational efficiency. POLARIS results were compared to those derived from the widely used SSURGO soil database using a soft-calibrated SWAT+ model. At the sub-basin scale, the two datasets showed strong overall agreement for the streamflow and sediment yield over the 81 BMW sub-basins, with minor discrepancies, especially in sediment yield predictions, which exhibited more variability. At the field scale, the agreement between POLARIS and SSURGO was good for both variables, streamflow and sediment yield, though the sediment yield showed greater variability as shown at the sub-basin level. At both scales, the POLARIS and SSURGO outcomes for the streamflow and sediment yield did not always follow the same trend, with discrepancies observed in some sub-basins and HRUs. This suggested that while POLARIS can replicate SSURGO’s streamflow outcomes, this similarity does not always extend to sediment yield predictions and vice versa. At the sub-basin scale, the POLARIS and SSURGO outcomes showed strong alignment (88.9% in “very good” agreement). However, at the field scale, this alignment decreased to 42.9% and 33.3% in specific sub-basins. This indicates that sub-basin aggregation reduces local variability, while finer scales reveal greater sensitivity to soil and hydrological differences. This study highlights POLARIS as a robust alternative to SSURGO for hydrological modeling. Future research should explore its broader application across diverse conditions. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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21 pages, 1736 KB

Open AccessEditor’s ChoiceArticle

When Technology Meets Sustainability: Microplastic Removal from Industrial Wastewater, Including Impact Analysis and Life Cycle Assessment

by Jan Puhar, Michael Toni Sturm, Erika Myers, Dennis Schober, Anika Korzin, Annamaria Vujanović and Katrin Schuhen

Water 2025, 17(5), 671; https://doi.org/10.3390/w17050671 - 25 Feb 2025

Cited by 3 | Viewed by 2534

Abstract

Microplastics (MPs) that are ubiquitous in aquatic environments and industrial wastewater streams have been identified as key hotspots of MP contamination. It is significantly more effective to remove MPs at these points before they enter municipal wastewater streams. This study is an environmental [...] Read more.

Microplastics (MPs) that are ubiquitous in aquatic environments and industrial wastewater streams have been identified as key hotspots of MP contamination. It is significantly more effective to remove MPs at these points before they enter municipal wastewater streams. This study is an environmental assessment of a novel pilot plant for the removal of MPs and the chemical oxygen demand (COD) from wastewater with a high MP contamination from a plastics manufacturer in Germany. MP removal is based on physical–chemical agglomeration–fixation by organosilanes. Formed agglomerates are separated using a belt filter. The COD is removed by an adsorption process. The resulting MP removal was 98.0 ± 1.1% by mass and 99.9987 ± 0.0007% by particle count, while the COD was reduced by 96 ± 2.7%. The system’s sustainability is evaluated using the Life Cycle Assessment methodology, evaluating system construction, operation, and end-of-life considerations. The current pilot plant is also compared to an optimized circular and sustainable upgrade, where drivers of environmental burdens are eliminated and collected MPs are reused. Significant reductions in environmental impact categories are achieved and the global warming potential is reduced by 96%. This study provides a sustainability assessment of a novel technology and circular solution to remove MPs from highly polluted industrial wastewater. Full article

(This article belongs to the Special Issue Microplastic Removal and Assessment in Wastewater Treatment Plants)

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17 pages, 12714 KB

Open AccessEditor’s ChoiceArticle

Novel Oscillatory Flocculation System for Colloids Removal from Water

by Inbar Shlomo Bendory and Eran Friedler

Water 2025, 17(5), 665; https://doi.org/10.3390/w17050665 - 25 Feb 2025

Cited by 2 | Viewed by 975

Abstract

According to a novel “grouping” methodology, applying sinusoidal oscillatory linear mixing enhances the aggregation of colloid particles in water. To verify this concept, an oscillatory mixing system was constructed. The methodology was tested on simulative synthetic surface water containing fine kaolin clay, with [...] Read more.

According to a novel “grouping” methodology, applying sinusoidal oscillatory linear mixing enhances the aggregation of colloid particles in water. To verify this concept, an oscillatory mixing system was constructed. The methodology was tested on simulative synthetic surface water containing fine kaolin clay, with alum as a coagulant. The system was examined under various operational and configurational conditions. Process efficiency was assessed by turbidity removal. The hydrodynamic properties of the created oscillatory waves, flow patterns, and obtained vortices were evaluated. At the optimal conditions, the oscillatory system created the theoretically predicted “moon shape” sedimentation pattern, removing turbidity at a higher rate than conventional coagulation. Both the configurational and operational conditions had considerable effects on aggregate size thus changing the turbidity removal rate. The methodology appeared to be efficient, as significant sedimentation had already occurred during the oscillatory mixing. Hence, the method has a high potential to contribute to the coagulation–flocculation process. Full article

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

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34 pages, 8695 KB

Open AccessEditor’s ChoiceArticle

Cost-Effective Strategies for Assessing CO₂ Water-Alternating-Gas (WAG) Injection for Enhanced Oil Recovery (EOR) in a Heterogeneous Reservoir

by Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Dung Bui, Jonathan Asante, Irma Primasari, Adewale Amosu, Son Nguyen, Samuel Appiah Acheampong, Anthony Hama, William Ampomah and Angus Eastwood-Anaba

Water 2025, 17(5), 651; https://doi.org/10.3390/w17050651 - 23 Feb 2025

Cited by 2 | Viewed by 2907

Abstract

This study evaluates the feasibility of CO₂ Water-Alternating-Gas (WAG) injection for enhanced oil recovery (EOR) in a highly heterogeneous reservoir using cost-effective and efficient tools. The Rule of Thumb method was initially used to screen the reservoir, confirming its suitability for CO [...] Read more.

This study evaluates the feasibility of CO₂ Water-Alternating-Gas (WAG) injection for enhanced oil recovery (EOR) in a highly heterogeneous reservoir using cost-effective and efficient tools. The Rule of Thumb method was initially used to screen the reservoir, confirming its suitability for CO₂-WAG injection. A fluid model was constructed by comparing several component lumping methods, selecting the approach with the least deviation from experimental data to ensure accuracy. The minimum miscibility pressure (MMP), a critical parameter for CO₂-EOR, was estimated using three methodologies: 1D simulation based on the slim tube test, semi-empirical analytical correlations, and fluid modeling. These techniques provided complementary insights into the reservoir’s miscibility conditions. The CO₂ Prophet software version 1 was employed to history-match production data and evaluate different development strategies. The Kinder Morgan CO₂ Scoping Model was used to perform production forecasting and assess the economic viability of implementing CO₂-WAG. Quantitative comparisons showed that the CO₂ Prophet version 1 model revealed minimal deviations from the history match results: oil production estimates differed by only 3.5%, and water production estimates differed by −4.11%. Cumulative oil recovery was projected to reach approximately 20.26 MMSTB over a 25-year production period. The results indicate that CO₂-WAG injection could enhance oil recovery significantly compared to water flooding while maintaining economic feasibility. This study demonstrates the practical integration of analytical tools and inexpensive models to evaluate and optimize CO₂-EOR strategies in complex reservoirs. The findings provide a systematic workflow for deploying CO₂-WAG in heterogeneous reservoirs, balancing technical and economic considerations. Full article

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