Water

14 pages, 1302 KiB

Open AccessArticle

Effects of Salinity Level on Microplastic Removal in Simulated Waters Using Agglomeration–Micro-Flotation

by Theerayut Phengsaart, Palot Srichonphaisarn, Worada Khwathichak, Chanatip Bumrungsak, Ilhwan Park, Mayumi Ito, Mylah Villacorte-Tabelin, Carlito Baltazar Tabelin, Sanghee Jeon, Kazutoshi Haga and Onchanok Juntarasakul

Water 2025, 17(9), 1264; https://doi.org/10.3390/w17091264 - 23 Apr 2025

Abstract

This study investigates the removal of microplastics (MPs) from simulated freshwater, brackish water, and seawater using a novel agglomeration–micro-flotation technique. This method combines particle size enlargement, facilitated by kerosene as a bridging agent, with bubble size reduction through column flotation to enhance the [...] Read more.

This study investigates the removal of microplastics (MPs) from simulated freshwater, brackish water, and seawater using a novel agglomeration–micro-flotation technique. This method combines particle size enlargement, facilitated by kerosene as a bridging agent, with bubble size reduction through column flotation to enhance the removal rate. Six common MP types—polypropylene (PP), polyethylene (PE), acrylonitrile butadiene styrene (ABS), polystyrene (PS), polyethylene terephthalate (PET), and polyvinyl chloride (PVC)—were evaluated under varying salinity levels and kerosene dosages. Results showed that increasing kerosene dosage significantly improved removal rates, achieving up to ~99% recovery at 10 µL for low- and medium-density MPs (PP, PE, ABS, and PS), while a higher dosage of 30 µL was required for high-density MPs (PET and PVC). Elevated salinity levels (50–100%) promoted bubble stabilization and reduced coalescence, enhancing particle–bubble collisions and the overall flotation performance. This work addresses a key research gap in flotation-based MP removal under saline conditions and highlights the dual benefits of using kerosene—not only to enhance the removal rate but also to enable energy recovery, as both kerosene and plastics are combustible. The proposed technique presents a promising approach for microplastic remediation in aquatic environments, supporting sustainable water treatment and circular resource utilization. Full article

(This article belongs to the Special Issue Trends in Effective Removal of Emerging Organic Pollutants from Drinking Water and Wastewater)

20 pages, 8397 KiB

Open AccessArticle

Advancing Sea Ice Thickness Hindcast with Deep Learning: A WGAN-LSTM Approach

by Bingyan Gao, Yang Liu, Peng Lu, Lei Wang and Hui Liao

Water 2025, 17(9), 1263; https://doi.org/10.3390/w17091263 - 23 Apr 2025

Abstract

The thickness of the Arctic sea ice constitutes one of the crucial indicators of global climate change, and while deep learning has shown promise in predicting sea ice thickness (SIT), the field continues to grapple with the challenge of limited data availability. In [...] Read more.

The thickness of the Arctic sea ice constitutes one of the crucial indicators of global climate change, and while deep learning has shown promise in predicting sea ice thickness (SIT), the field continues to grapple with the challenge of limited data availability. In this study, we introduce a Wasserstein Generative Adversarial Network–Long Short-Term Memory (WGAN-LSTM) model, which leverages the data generation capabilities of WGAN and the temporal prediction strengths of LSTM to perform single-step SIT prediction. During model training, the mean square error (MSE) and a novel comprehensive index, the Distance between Indices of Simulation and Observation (DISO), are used as two metrics of the loss function to compare. To thoroughly assess the model’s performance, we integrate the WGAN-LSTM model with the Monte Carlo (MC) dropout uncertainty estimation method, thereby validating the model’s enhanced generalization capabilities. Experimental results demonstrate that the WGAN-LSTM model, utilizing MSE and DISO as loss functions, improves comprehensive performance by 51.9% and 75.2%, respectively, compared to the traditional LSTM model. Furthermore, the MC estimates of the WGAN-LSTM model align with the distribution of actual observations. These findings indicate that the WGAN-LSTM model effectively captures nonlinear changes and surpasses the traditional LSTM model in prediction accuracy. The demonstrated effectiveness and reliability of the WGAN-LSTM model significantly advance short-term SIT prediction research in the Arctic region, particularly under conditions of data scarcity. Additionally, this model offers an innovative approach for identifying other physical features in the sea ice field based on sparse data. Full article

(This article belongs to the Special Issue Mathematical, Physical, Chemical, and Biological Methods for Ice and Water Problems)

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17 pages, 9958 KiB

Open AccessArticle

Intermittent Rainfed Rice var. INIA 516 LM1: A Sustainable Alternative for the Huallaga River Basin

by Ricardo Flores-Marquez, Rita de Cássia Bahia, Yuri Arévalo-Aranda, Edson Esmith Torres-Chávez, Jonathan Guevara, Abner Antezana, Antoni Carranza, Ceila Lao and Richard Solórzano-Acosta

Water 2025, 17(9), 1262; https://doi.org/10.3390/w17091262 - 23 Apr 2025

Abstract

Climate change is projected to increase global temperatures and alter rainfall patterns. In Peru, these changes could adversely affect the central basin of the Huallaga River by increasing pest and disease incidence, evapotranspiration, and water consumption. This basin is one of the country’s [...] Read more.

Climate change is projected to increase global temperatures and alter rainfall patterns. In Peru, these changes could adversely affect the central basin of the Huallaga River by increasing pest and disease incidence, evapotranspiration, and water consumption. This basin is one of the country’s main rice-producing regions, where the crop is traditionally cultivated using inefficient practices, such as continuous flood irrigation. This study evaluated the effects of different irrigation management strategies on the growth and yield of rice (Oryza sativa var. INIA 516 LM1-La Unión 23), the water footprint as an indicator of water use efficiency, and the incidence of pests and diseases associated with irrigation regimes. Three irrigation treatments were implemented: Traditional flooding T1 (maintenance of a 0.15 m water layer with replenishment every 4 days), Optimized flooding T2 (replenishment every 7 days), and Intermittent rainfed irrigation T3 (replenishment every 14 days). Although no significant differences were observed in biometric parameters, yield, or pest and disease incidence, a trend of decreasing yield with longer irrigation intervals was noted: traditional flooding (7.91 t∙ha⁻¹) > reduced flooding (7.82 t∙ha⁻¹) > intermittent rainfed (7.14 t∙ha⁻¹). The incidence of white leaf virus and Burkholderia glumae was highest in the intermittent rainfed treatment, followed by optimized flooding, with the lowest incidence in traditional flooding. Yield reduction and the use of rainwater to cover water requirements resulted in a lower total water footprint for traditional flooding (834.0 m³∙t⁻¹), followed by optimized flooding (843.6 m³∙t⁻¹) and intermittent rainfed (923.9 m³∙t⁻¹). This reflects an improvement in rainwater use efficiency. The findings suggest intermittent rainfed irrigation enhances water use efficiency without significantly compromising rice yield or increasing disease incidence in rice var. INIA 516 LM1-La Unión 23 in the central basin of the Huallaga River. Full article

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

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18 pages, 5098 KiB

Open AccessArticle

Waterway Regulation Effects on River Hydrodynamics and Hydrological Regimes: A Numerical Investigation

by Chuanjie Quan, Dasheng Wang, Xian Li, Zhenxing Yao, Panpan Guo, Chen Jiang, Haodong Xing, Jianyang Ren, Fang Tong and Yixian Wang

Water 2025, 17(9), 1261; https://doi.org/10.3390/w17091261 - 23 Apr 2025

Abstract

As a critical intervention for enhancing inland navigation efficiency, waterway regulation projects profoundly modify riverine hydrodynamic conditions while optimizing navigability. This study employs the MIKE21 hydrodynamic model to establish a two-dimensional numerical framework for assessing hydrological alterations induced by channel regulation in the [...] Read more.

As a critical intervention for enhancing inland navigation efficiency, waterway regulation projects profoundly modify riverine hydrodynamic conditions while optimizing navigability. This study employs the MIKE21 hydrodynamic model to establish a two-dimensional numerical framework for assessing hydrological alterations induced by channel regulation in the Hui River, China. Through comparative simulations of pre- and post-project scenarios across dry, normal, and wet hydrological years, the research quantifies impacts on water levels, flow velocity distribution, and geomorphic stability. Results reveal that channel dredging and realignment reduced upstream water levels by up to 0.26 m during drought conditions, while concentrating flow velocities in the main channel by 0.5 m/s. However, localized hydrodynamic restructuring triggered bank erosion risks at cut-off bends and sedimentation in anchorage basins. The integrated analysis demonstrates that although regulation measures enhance flood conveyance and navigation capacity, they disrupt sediment transport equilibrium, destabilize riparian ecosystems, and compromise hydrological monitoring consistency. To mitigate these trade-offs, the study proposes design optimizations—including ecological revetments and adaptive dredging strategies—coupled with enhanced hydrodynamic monitoring and riparian habitat restoration. These findings provide a scientific foundation for balancing navigation improvements with the sustainable management of fluvial systems. Full article

(This article belongs to the Special Issue Advances in Surface Water and Groundwater Simulation in River Basin)

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23 pages, 1419 KiB

Open AccessArticle

Evaluating Wildfire-Induced Changes in a Water-Yield Ecosystem Service at the Local Scale Using the InVEST Model

by Ye Inn Kim, Bernie Engel, Won Seok Jang and Young Jo Yun

Water 2025, 17(9), 1260; https://doi.org/10.3390/w17091260 - 23 Apr 2025

Abstract

This study evaluates the applicability of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model for assessing wildfire-induced changes in water-related ecosystem services at a localized scale. Wildfires significantly alter hydrological processes by reducing vegetation cover, which in turn affects water-yield dynamics. [...] Read more.

This study evaluates the applicability of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model for assessing wildfire-induced changes in water-related ecosystem services at a localized scale. Wildfires significantly alter hydrological processes by reducing vegetation cover, which in turn affects water-yield dynamics. To quantify these changes, we applied the InVEST annual water-yield model to a 4.95 km² wildfire-affected area and validated its outputs against the physically based SWAT model. The study utilized Sentinel-2 imagery to create pre- and post-wildfire land cover maps, which served as key inputs for the InVEST model. The results showed a 7.05% increase in water yield after the wildfire. Validation using SWAT confirmed that InVEST could capture localized hydrological changes with accuracy. While InVEST simplifies hydrological processes by relying primarily on land cover data, it remains a valuable tool for rapid and low-resource assessments in wildfire-prone regions. This study highlights the potential of InVEST for rapid post-fire evaluations, offering a practical decision-support model for post-fire land and water resource management in the context of climate change. Full article

(This article belongs to the Special Issue Application of Various Hydrological Modeling Techniques and Methods in River Basin Management, 2nd Edition)

16 pages, 4814 KiB

Open AccessArticle

Geomorphological Characteristics and Evolutionary Process of a Typical Isolated Carbonate Platform Slope in the Xisha Sea: A Case Study of the Northwestern Dongdao Platform

by Xudong Guo, Dongyu Lu, Xuelin Li, Xiaochen Fang, Fei Tian, Changfa Xia, Lei Huang, Mei Chen, Luyi Wang and Zhongyu Sun

Water 2025, 17(9), 1259; https://doi.org/10.3390/w17091259 - 23 Apr 2025

Abstract

The northwestern slope of the Dongdao Platform in the Xisha Sea exhibits a complex geomorphological structure. Utilizing high-resolution multibeam bathymetric data and 2D seismic profiles, this study systematically reconstructs the slope morphology and its evolutionary processes. The study area displays a distinct threefold [...] Read more.

The northwestern slope of the Dongdao Platform in the Xisha Sea exhibits a complex geomorphological structure. Utilizing high-resolution multibeam bathymetric data and 2D seismic profiles, this study systematically reconstructs the slope morphology and its evolutionary processes. The study area displays a distinct threefold zonation: the upper slope (160–700 m water depth) has a steep gradient of 15°–25°, characterized by deeply incised V-shaped channels and slump deposits, primarily shaped by gravity-driven erosion; the middle slope (700–1200 m water depth) features a gentler gradient of 10°–15°, where channels stabilize, adopting U-shaped cross-sections with the development of lateral accretion deposits; the lower slope (1200–1500 m water depth) exhibits a milder gradient of 5°–10°, dominated by a mixture of fine-grained carbonate sediments and hemipelagic mud–marine sediments originating partly from the open ocean and partly from the nearby continental margin. The slope extends from 160 m to 1500 m water depth, hosting the C1–C4 channel system. Seismic facies analysis reveals mass-transport deposits, channel-fill facies, and facies modified by bottom currents—currents near the seafloor that redistribute sediments laterally—highlighting the interplay between fluid activity and gravity-driven processes. The slope evolution follows a four-stage model: (1) the pockmark formation stage, where overpressured gas migrates vertically through chimneys, inducing localized sediment instability and forming discrete pockmarks; (2) the initial channel development stage, during which gravity flows exploit the pockmark chains as preferential erosional pathways, establishing nascent incised channels; (3) the channel expansion and maturation stage, marked by intensified erosion from high-density debris flows, resulting in a stepped longitudinal profile, while bottom-current reworking enhances lateral sediment differentiation; (4) the stable transport stage, wherein the channels fully integrate with the Sansha Canyon, forming a well-connected “platform-to-canyon” sediment transport system. Full article

(This article belongs to the Special Issue Regional Geomorphological Characteristics and Sedimentary Processes)

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22 pages, 6999 KiB

Open AccessArticle

Contrasting the Contributions of Climate Change and Greening to Hydrological Processes in Humid Karst and Non-Karst Areas

by Xiaoyu Tan, Yan Deng, Yehao Wang, Linyan Pan, Yuanyuan Chen and Junjie Cai

Water 2025, 17(9), 1258; https://doi.org/10.3390/w17091258 - 23 Apr 2025

Abstract

A quantitative assessment of the responses of hydrological processes to environmental change is vital for the sustainable utilization of groundwater and sustainable development under the dual influences of climate change and global greening. However, few studies have investigated the differences in hydrologic responses [...] Read more.

A quantitative assessment of the responses of hydrological processes to environmental change is vital for the sustainable utilization of groundwater and sustainable development under the dual influences of climate change and global greening. However, few studies have investigated the differences in hydrologic responses between karst and non-karst regions. Thus, we analyzed the spatiotemporal changes in potential groundwater recharge (PGR), potential groundwater recharge as a proportion of precipitation (PGR/P), and actual evapotranspiration (AET) in karst and non-karst regions for 1982–2020 using the V2karst model. The analysis revealed the following results: (1) The V2karst model efficiently monitored variations in the AET and groundwater depth (GWD), which indicated its suitability for use in karst areas. (2) The PGR, PGR/P, and AET increased at rates of 4.9 mm/y, 0.0011, and 1.4 mm/y in karst areas, and 3.8 mm/y, 0.00053, and 1.6 mm/y in non-karst areas, respectively, with the increasing trend in AET being significant in karst and non-karst regions. (3) The precipitation (P) and AET were significantly correlated with the PGR and PGR/P, while the minimum temperature (TMN) was strongly related to the AET. The Normalized Difference Vegetation Index (NDVI) moderately affected the PGR, PGR/P, and AET changes in humid catchments. Climate change is a primary factor for hydrological processes, whereas vegetation restoration has a relatively minor impact. The results of this study are beneficial toward the adoption of strategic groundwater utilization programs and ecological restoration measures for regions with a diverse geological setting. Full article

(This article belongs to the Section Hydrology)

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6 pages, 561 KiB

Open AccessEditorial

Contaminants in the Water Environment: Significance from the Perspective of the Global Environment and Health

by Xia Jiang, Kelly L. Kirsten and Abdul Qadeer

Water 2025, 17(9), 1257; https://doi.org/10.3390/w17091257 - 23 Apr 2025

Abstract

Water is essential for all life, yet it faces increasing threats from contamination due to various human activities and natural processes [...] Full article

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

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20 pages, 3831 KiB

Open AccessArticle

A Highly Effective Method for Simultaneous Determination of 103 Veterinary Drugs in Sediment Using Liquid Chromatography–Tandem Mass Spectrometry

by Henan Li, Kunde Lin, Yuncong Ge, Qian Wang and Meng Chen

Water 2025, 17(9), 1256; https://doi.org/10.3390/w17091256 - 23 Apr 2025

Abstract

Hundreds of veterinary drugs are widely used in agricultural activities and continuously enter aquatic environments through various pathways, posing potential risks to ecosystem. Considering that sediments function both as sinks and sources of these contaminants, it is crucial to promptly and accurately acquire [...] Read more.

Hundreds of veterinary drugs are widely used in agricultural activities and continuously enter aquatic environments through various pathways, posing potential risks to ecosystem. Considering that sediments function both as sinks and sources of these contaminants, it is crucial to promptly and accurately acquire veterinary drug residue level in sediments. In this study, a highly effective analytical method for simultaneous determination of 103 veterinary drugs from 16 classes in sediments was developed using high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS). The extraction procedure was performed twice by ultrasound-assisted extraction with an acetonitrile-buffer mixture consisting of Na₂EDTA, Na₃PO₄·12H₂O, and Na₃C₆H₅O₇·2H₂O. The supernatant was cleaned using 500 mg/6 mL Oasis HLB solid-phase cartridges. The elution solutions were concentrated and redissolved in formic acid–methanol–water (0.1/20/79.9, v/v, FA-MeOH-H₂O) for detection. Results showed that all 103 target drugs exhibited good linearity with R² > 0.990 over a concentration range of 0.010 to 1000 μg·L⁻¹, and method detection limits (MDLs) ranged from 0.025 to 5 μg·kg⁻¹. The recoveries at three spiking levels (2, 5, and 10 times of the method quantification limits, MQLs) varied from 33% to 150%, 32% to 140%, and 40% to 140%, respectively, with relative standard deviations (RSDs, n = 3) of 0.7%~29%, 0.8%~23%, and 0.5%~20%. The matrix effects for all compounds ranged from –85% to 84% with 32 targets negligible, 51 moderate, and 20 significant. An isotope-labeled surrogate method was proposed for quantitation to effectively overcome matrix effects and improve accuracy with better recoveries of 60%~120% for 93 target drugs and RSDs (n = 3) all below 20%. This method was applied to determine 12 sediment samples collected from the Jiulong River, and 16 target drugs were detected in the concentrations range of 0.1~7.6 μg·kg⁻¹. The method is accurate, sensitive, and efficient, providing a powerful analytical tool for behavior and effect studies of multi-classed veterinary drug residue in sediment environments. Full article

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

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20 pages, 3522 KiB

Open AccessArticle

Microbially Mediated Arsenic-Nitrogen Biogeochemical Coupling Across Vertical Distribution in Coastal Wetlands

by Yang Zou, Lili Xue, Ting Luo, Sheng Kong, Zirui Zhao, Liang Ding, Kexin Liu, Huaxin Gao and Hao Wu

Water 2025, 17(9), 1255; https://doi.org/10.3390/w17091255 - 23 Apr 2025

Abstract

Few studies have addressed the coupling of arsenic (As) and nitrogen (N) geochemistry in natural soil. This research focused on the vertical distribution and coupling behavior of As and N in coastal wetland sediments. Pore water and sediment from barren wetlands and coastal [...] Read more.

Few studies have addressed the coupling of arsenic (As) and nitrogen (N) geochemistry in natural soil. This research focused on the vertical distribution and coupling behavior of As and N in coastal wetland sediments. Pore water and sediment from barren wetlands and coastal wetlands near three estuaries (Guanhe River, Sheyang River, and Liangduo River) in central Jiangsu Province of China with Spartina alterniflora (S. alterniflora) were sampled, which were analyzed for total As content and speciation and N inorganic fractions. The bacterial community was investigated through 16s rDNA sequencing; diversity indices were calculated. The As change trend in pore water of surface sediment with increasing depth was opposite to that of NO₃⁻, possibly because NO₃⁻ promoted arsenite (As(III)) oxidation to arsenate (As(V)). Increased NO₃⁻ contents seemed to mitigate As toxicity. The vertical distribution of NH₄⁺ indicated anaerobic ammonium oxidation and iron (Fe) ammonium oxidation to reduce Fe oxides, resulting in As release, especially in the deeper sediment. High-throughput sequencing analysis revealed some potential bacteria possibly involved in As-N geochemical coupling, such as Bacillus and Psychrobacter, which can couple denitrification with As oxidation, and Sva1033, which may favor ammonium oxidation-induced As release. Our results suggest that the N-driven oxidation of As(III) and the ammonium oxidation-induced As release can be relevant to As-N coupling processes in the coastal wetland and emphasize the importance of microorganisms in such processes. This research deepens our understanding of As-N coupling in natural coastal wetlands, providing a theoretical basis for controlling As pollution. Full article

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

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23 pages, 6638 KiB

Open AccessArticle

Influencing Factors and Prediction of Turbine Sediment Concentration in Pure Pumped-Storage Power Stations on Sediment-Laden Rivers

by Lei Liu, Zhandi Dong and Zhiguo Wang

Water 2025, 17(9), 1254; https://doi.org/10.3390/w17091254 - 23 Apr 2025

Abstract

This study investigates the sediment transport characteristics in the lower reservoir area of a pure pumped-storage power station (Pure-PSPS) to address the sediment abrasion issue under high sediment-laden conditions. By establishing a physical model and employing multivariate statistical analysis methods, we systematically reveal [...] Read more.

This study investigates the sediment transport characteristics in the lower reservoir area of a pure pumped-storage power station (Pure-PSPS) to address the sediment abrasion issue under high sediment-laden conditions. By establishing a physical model and employing multivariate statistical analysis methods, we systematically reveal the multifactorial coupled influence mechanism of key parameters in the lower reservoir area on turbine sediment concentration (TSC), while developing a predictive TSC formula applicable to high-sediment Pure-PSPS based on sediment-carrying capacity theory and sediment mass conservation principles. The study indicates the following: (1) Under consistent basic parameters such as reservoir length, the decay rate of sediment concentration along the path from the reservoir inlet to the power station’s intake and outlet decreases to 30~80% under high inflow conditions, while under medium and low inflow conditions, the decay rate exceeds 80%. (2) The lower boundary of the median particle size adjustment range for suspended sediment gradually increases from 0.006 mm for 30- and 40-year flood recurrence intervals to 0.009 mm for an 80-year recurrence interval, and under the 80-year recurrence interval, the particle size fluctuation range converges to a high and narrow distribution of 0.009~0.011 mm. (3) The constructed linear regression model has an R² value of 0.8. The inflow sediment concentration (standardized coefficient β = 0.36) exhibits the strongest explanatory power for the dependent variable, followed by inflow discharge (β = 0.345) and the height difference between the intake/outlet and the silted bed surface (β = 0.319). (4) By optimizing the Adomian decomposition method, dimensional analysis, and multiple regression techniques, and based on sediment-carrying capacity theory and sediment mass conservation principles, this study derived and fitted a predictive formula for TSC in high-sediment-laden Pure-PSPS environments with favorable validation results. The research not only clarifies the interactive relationship between high-sediment-laden flow and turbine sediment concentration in Pure-PSPS but also fills the methodological gap in predicting operational conditions for pure pumped-storage power stations under extreme sediment scenarios. The established regular patterns provide a scientific foundation for the design and feasibility assessment of similar Pure-PSPS projects in sediment-rich rivers. Full article

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

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14 pages, 2718 KiB

Open AccessArticle

Mining-Influenced Water from the Abandoned Hausham Colliery in Southern Germany—A Case of Unmonitored Natural Attenuation

by Sylke Hilberg, Nicola Yousefi and Thomas Rinder

Water 2025, 17(9), 1253; https://doi.org/10.3390/w17091253 - 23 Apr 2025

Abstract

Coal mining in Upper Bavaria ended in the 1960s and the mines were flooded. This study investigates the mining-influenced water and its environmental implications in the Hausham Mine, one of many unmonitored coal mines in the region and along the northern edge of [...] Read more.

Coal mining in Upper Bavaria ended in the 1960s and the mines were flooded. This study investigates the mining-influenced water and its environmental implications in the Hausham Mine, one of many unmonitored coal mines in the region and along the northern edge of the Molasse zone in Austria, Germany and Switzerland. Water and solid samples were collected in the vicinity of the discharge area within a waste rock pile and downstream of a nearby lake. The samples were subjected to chemical and isotopic analysis, with a focus on the potential for natural attenuation. The mine waste discharge has high initial concentrations of calcium, sulfate, and iron, and elevated concentrations of nickel, zinc, and strontium. These element concentrations are significantly reduced along the flow path so that the water is environmentally safe for discharge into the Loidlsee. The reduced contaminant levels are related to the formation of secondary iron precipitates and associated sorption processes, the formation of secondary calcium carbonates, and mixing with another groundwater source. The results indicate that the carbonate-dominated sediments of the Molasse zone contribute substantially to the natural remediation of a potential environmental problem. Full article

(This article belongs to the Special Issue Groundwater Evolution and Hydrochemical Processes in Mining Environments)

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20 pages, 505 KiB

Open AccessReview

Problems, Effects, and Methods of Monitoring and Sensing Oil Pollution in Water: A Review

by Nur Nazifa Che Samsuria, Wan Zakiah Wan Ismail, Muhammad Nurullah Waliyullah Mohamed Nazli, Nor Azlina Ab Aziz and Anith Khairunnisa Ghazali

Water 2025, 17(9), 1252; https://doi.org/10.3390/w17091252 - 23 Apr 2025

Abstract

Oil pollution in water bodies is a substantial environmental concern that poses severe risks to human health, aquatic ecosystems, and economic activities. Rising energy consumption and industrial activity have resulted in more oil spills, damaging long-term ecology. The aim of the review is [...] Read more.

Oil pollution in water bodies is a substantial environmental concern that poses severe risks to human health, aquatic ecosystems, and economic activities. Rising energy consumption and industrial activity have resulted in more oil spills, damaging long-term ecology. The aim of the review is to discuss problems, effects, and methods of monitoring and sensing oil pollution in water. Oil can destroy the aquatic habitat. Once oil gets into aquatic habitats, it changes both physically and chemically, depending on temperature, wind, and wave currents. If not promptly addressed, these processes have severe repercussions on the spread, persistence, and toxicity of oil. Effective monitoring and early identification of oil pollution are vital to limit environmental harm and permit timely reaction and cleanup activities. Three main categories define the three main methodologies of oil spill detection. Remote sensing utilizes satellite imaging and airborne surveillance to monitor large-scale oil spills and trace their migration across aquatic bodies. Accurate real-time detection is made possible by optical sensing, which uses fluorescence and infrared methods to identify and measure oil contamination based on its particular optical characteristics. Using sensor networks and Internet of Things (IoT) technologies, wireless sensing improves early detection and response capacity by the continuous automated monitoring of oil pollution in aquatic settings. In addition, the effectiveness of advanced artificial intelligence (AI) techniques, such as deep learning (DL) and machine learning (ML), in enhancing detection accuracy, predicting leak patterns, and optimizing response strategies, is investigated. This review assesses the advantages and limits of these detection technologies and offers future research directions to advance oil spill monitoring. The results help create more sustainable and efficient plans for controlling oil pollution and safeguarding aquatic habitats. Full article

(This article belongs to the Topic Advanced Processes and Technologies for Wastewater: Collection, Treatment, and Resource)

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25 pages, 10113 KiB

Open AccessArticle

The Effects of Reduced Wastewater Load in the Marine Area off Turku in the Archipelago Sea During the Period 1965–2025

by Harri Helminen

Water 2025, 17(9), 1251; https://doi.org/10.3390/w17091251 - 23 Apr 2025

Abstract

In Finland, municipal wastewater treatment has significantly improved in recent decades, leading to a substantial reduction in nutrient loads from wastewater discharged into water bodies. For example, in the marine area off Turku in the Archipelago Sea, located in the northern Baltic Sea, [...] Read more.

In Finland, municipal wastewater treatment has significantly improved in recent decades, leading to a substantial reduction in nutrient loads from wastewater discharged into water bodies. For example, in the marine area off Turku in the Archipelago Sea, located in the northern Baltic Sea, the total phosphorus load from wastewater has decreased to approximately one-eighth of its level in the early 1990s. Simultaneously, the total nitrogen load has been reduced to one-fifth, and the ammonium nitrogen load is now less than 5% of its peak in 1994. This study examines in detail how water quality parameters and phytoplankton indicators in wastewater-affected areas have changed during the same period in which wastewater loads have significantly decreased. This reduction has contributed to positive developments in the marine area off Turku, although the goal of achieving good ecological status remains unmet. In Raisio Bay, chlorophyll a concentrations decreased by 68% following the relocation of wastewater discharge. In Rauvola Bay, the reduction was estimated to be 36%. Over the past 15 years, the biomass of nitrogen-fixing cyanobacteria has increased in northern Airisto. This trend appears to be driven by a decrease in external nitrogen loading in combination with increased internal phosphorus loading. Water bodies in the inner archipelago continue to receive excessive nutrient inputs from the surrounding catchment area, while internal loading significantly delays the restoration process. Full article

(This article belongs to the Special Issue Research on the Dynamics of Phytoplankton in Eutrophic Water)

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21 pages, 11640 KiB

Open AccessArticle

Biofouling Community Dynamics on Nylon and Polyethylene Aquaculture Nets in the North Yellow Sea: Colonization Patterns and Mytilus edulis Mechanical Properties

by Sai He, Qingsong Xue, Zhixuan Fu, Lei Bao, Kuo Li, Guochen Zhang, Hanbing Zhang and Tianlong Qiu

Water 2025, 17(9), 1250; https://doi.org/10.3390/w17091250 - 23 Apr 2025

Abstract

A hanging net test was conducted from May to November 2022 on Takifugu rubripes culture nets at Wang Jia Island in the North Yellow Sea, China. The study identified 21 species of fouling organisms, with Mytilus edulis emerging as the dominant fouling organism [...] Read more.

A hanging net test was conducted from May to November 2022 on Takifugu rubripes culture nets at Wang Jia Island in the North Yellow Sea, China. The study identified 21 species of fouling organisms, with Mytilus edulis emerging as the dominant fouling organism colonizing aquaculture net cages. Coverage rates varied temporally, with water depth, and by net material, exhibiting a unimodal pattern that peaked between June and October (38.46–98.45%). At different depths, the coverage rates were highest at −0.5 m (75.14% to 98.65%). Additionally, nets made of nylon (29.41% to 98.65%) had an average coverage rate 8.2% higher than those made of PE mesh (26.34% to 90.45%). To assess the growth and mechanical properties of M. edulis, we analyzed its morphological relationships. A strong positive linear correlation was observed between shell length, width, and thickness, while body weight followed a power function relationship with shell dimensions. Growth curve analysis indicated that M. edulis reached maturity in late August. Compression tests revealed a defined yield point, with crack propagation varying by force direction. The maximum compressive force occurred in the thickness direction (195.95 N), with resistance increasing progressively from length to width to thickness. These findings elucidate biofouling dynamics on aquaculture nets and support the development of improved antifouling technologies. Full article

(This article belongs to the Special Issue Aquaculture, Fisheries, Ecology and Environment)

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24 pages, 6110 KiB

Open AccessArticle

Nitrogen and Phosphorus Loss via Surface Flow and Interflow in Subtropical Chinese Tea Plantations: A Comparative Analysis Under Two Slope Gradients

by Haitao Wang, Shuang He, Kamel Mohamed Eltohamy, Weidong Feng, Xiangtian Yang, Hekang Xiao, Yucheng Wang, Zhirong Wang and Xinqiang Liang

Water 2025, 17(9), 1249; https://doi.org/10.3390/w17091249 - 23 Apr 2025

Abstract

Nitrogen (N) and phosphorus (P) losses from sloping agricultural lands through runoff are a significant environmental concern, yet their transport mechanisms across different slope gradients are not well understood. Therefore, we built an experimental site in a subtropical hilly region of China to [...] Read more.

Nitrogen (N) and phosphorus (P) losses from sloping agricultural lands through runoff are a significant environmental concern, yet their transport mechanisms across different slope gradients are not well understood. Therefore, we built an experimental site in a subtropical hilly region of China to explore the patterns of nitrogen and phosphorus loss in tea plantations under typical slopes. We set two slope gradients of 20° and 30°, with three plots for each gradient. We quantified the loss of nitrogen (N) and phosphorus (P) through surface flow and interflow on these two slope gradients. We also collected meteorological data through the meteorological station we built. A total of 17 rainfall events were recorded. Results showed that total nitrogen (TN) and phosphorus (TP) concentrations in surface flow on the 30° slope were 8.9% and 31.6% higher, respectively, than on the 20° slope. In interflow, the differences were even more pronounced, with TN and TP concentrations 68.5% and 218.1% higher on the 30° slope. Overall nutrient loss loads (combining surface and interflow pathways) were significantly greater on the steeper slope, with TN and TP loss loads being 2.58 and 3.43 times higher on the 30° slope than on the 20° slope. The composition analysis revealed that dissolved nitrogen (DN) dominated nitrogen transport, accounting for 68.6% of TN in surface flow and 97.8% in interflow, while dissolved phosphorus (DP) represented 35.0% of TP in surface flow and 57.0% in interflow. Initially, TN and TP concentrations in surface flow were high and decreased as runoff generation time increased. Correlation analysis showed that higher temperatures increased TN and TP concentrations in surface flow. On the 30° slope, increased soil moisture promoted higher concentrations of soluble P. Instantaneous rainfall intensity was significantly correlated with TN and TP concentrations in surface flow under both slope gradients. This study revealed N and P loss patterns in tea gardens on steeper slopes, offering guidance for controlling nutrient loss in sloping farmland. Full article

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

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19 pages, 1079 KiB

Open AccessArticle

Research on Dynamic Trend Prediction Method for Flow Discharge Through Harbor Gates in Tidal Reaches

by Tianshu Zhang, Jie Jin, Yixiao Qian, Chuanhai Wang and Gang Chen

Water 2025, 17(9), 1248; https://doi.org/10.3390/w17091248 - 22 Apr 2025

Abstract

The outflow via the weir gate in coastal estuaries is affected by factors, including channel shape, upstream inputs, sluice gate operations, and tidal variations, leading to nonlinear and transitory correlations between the water stage and discharge. The most common technique utilized to calculate [...] Read more.

The outflow via the weir gate in coastal estuaries is affected by factors, including channel shape, upstream inputs, sluice gate operations, and tidal variations, leading to nonlinear and transitory correlations between the water stage and discharge. The most common technique utilized to calculate discharge is the weir gate overflow equation. Nonetheless, the significant dynamic fluctuations in upstream and downstream water level differentials during the opening or closing of the gate render the exclusive use of static water level differences inadequate for formulating a connection equation that satisfies accuracy standards. This research proposes a dynamic trend prediction approach that utilizes time-series data of water levels and discharge, accounting for temporal trend variations, as input for simulation with a three-layer backpropagation neural network. In the tidal portions of the Lixia River basin, the correlation coefficients for the discharge of four harbor gates surpassed 0.8, and the mean error diminished to 3.00%. It significantly boosts the fitting accuracy of the results and improves data precision during the transition between gate opening and closure. The novel approach employs intelligent algorithm theory to analyze harbor gate flow, offering a more scientific and accurate representation of the gate’s overflow capacity. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

26 pages, 9957 KiB

Open AccessArticle

The Role of High Water Temperature in the Context of Low-Flow Risk Analysis

by Udo Satzinger and Daniel Bachmann

Water 2025, 17(9), 1247; https://doi.org/10.3390/w17091247 - 22 Apr 2025

Abstract

Low-flow events significantly impact water users and ecosystems due to reduced flow rates and deteriorating water quality. Elevated water temperatures during these periods have led to economic and ecological consequences. Therefore, water temperature is a key aspect in the context of low-flow risk [...] Read more.

Low-flow events significantly impact water users and ecosystems due to reduced flow rates and deteriorating water quality. Elevated water temperatures during these periods have led to economic and ecological consequences. Therefore, water temperature is a key aspect in the context of low-flow risk analysis, and it is essential to model it accurately. This study introduces a one-dimensional water temperature model optimized for integration into low-flow risk analysis frameworks. Results demonstrate good performance in simulating water temperatures for both rivers, with Nash–Sutcliffe efficiency values of 0.85–0.98 and root mean square errors of 0.96–1.96 K. The model was evaluated on two contrasting river systems: the small Selke River and the large Elbe River. The model effectively captures anthropogenic influences and altered environmental conditions. Key factors influencing water temperature varied by river size, with tributaries and shading having more impact on smaller rivers, while air temperature was the primary driver for larger rivers. The model’s computational efficiency enables the practical implementation of long-term risk assessments. This temperature model fulfills the requirements for integration into low-flow risk management frameworks, providing a valuable tool for assessing temperature-related impacts and evaluating mitigation strategies across diverse river systems. Full article

(This article belongs to the Special Issue Research on River Environmental Flows and Habitat Restoration)

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28 pages, 1245 KiB

Open AccessArticle

A Multi-Dimensional Contribution-Based Framework for Evaluating Urban Stormwater Management Efficiency

by Kun Mao, Junqi Li and Jiawei Li

Water 2025, 17(9), 1246; https://doi.org/10.3390/w17091246 - 22 Apr 2025

Abstract

Urbanization and climate change amplify urban flooding risks, demanding efficient, data-minimal tools to strengthen flood resilience. This study presents a pioneering multi-dimensional framework that quantifies the contributions of source reduction, stormwater pipes, and drainage/flood control systems, circumventing the need for intricate hydrological models. [...] Read more.

Urbanization and climate change amplify urban flooding risks, demanding efficient, data-minimal tools to strengthen flood resilience. This study presents a pioneering multi-dimensional framework that quantifies the contributions of source reduction, stormwater pipes, and drainage/flood control systems, circumventing the need for intricate hydrological models. Leveraging rainfall depth (mm), runoff volume (m³), and peak flow rate (m³/h) provides a comprehensive evaluation of stormwater management efficacy. Applied to a hypothetical city, City A, under 30- and 50-year rainfall scenarios, the framework reveals efficiencies of 91.0% for rainfall depth and runoff volume, and 90.8% for peak flow in the 30-year case (9% shortfall), declining to 75.7% peak flow efficiency with a 24.3% deficit in the 50-year scenario, underscoring constraints in extreme-event response. Contributions analysis shows stormwater pipes (42.8–47.6%, mean: 46.0%) and drainage/flood control (40.8–43.2%, mean: 41.6%) predominate, while source reduction adds 11.6–14.0% (mean: 12.4%). A primary contribution lies in reducing data demands by approximately 70% compared to traditional approaches, rendering this framework a practical, scalable solution for flood management and sponge city design in data-limited settings. These findings elucidate system vulnerabilities and offer actionable strategies, advancing urban flood resilience both theoretically and practically. Full article

(This article belongs to the Section Urban Water Management)

23 pages, 2317 KiB

Open AccessArticle

Improved Resolution of Drought Monitoring in the Yellow River Basin Based on a Daily Drought Index Using GRACE Data

by Yingying Li, Wei Zheng, Wenjie Yin, Shengkun Nie, Hanwei Zhang and Weiwei Lei

Water 2025, 17(9), 1245; https://doi.org/10.3390/w17091245 - 22 Apr 2025

Abstract

Frequent droughts significantly threaten economic development, necessitating effective long-term drought monitoring. The Gravity Recovery and Climate Experiment (GRACE) satellite and its follow-on mission along with Global Navigation Satellite System (GNSS) inversion technologies provide long-term terrestrial water storage signals. However, their limitations in temporal [...] Read more.

Frequent droughts significantly threaten economic development, necessitating effective long-term drought monitoring. The Gravity Recovery and Climate Experiment (GRACE) satellite and its follow-on mission along with Global Navigation Satellite System (GNSS) inversion technologies provide long-term terrestrial water storage signals. However, their limitations in temporal resolution and spatial continuity are inadequate for current requirements. To solve this problem, this study combines a daily terrestrial water storage anomaly (TWSA) reconstruction method with the GNSS inversion technique to explore daily, spatially continuous TWSA in China’s Yellow River Basin (YRB). Furthermore, the Daily Drought Severity Index (DDSI) is employed to analyze drought dynamics in the YRB. Finally, by reconstructing the climate-driven water storage anomalies model, this study explores the influence of climate and human factors on drought. The results indicate the following: (1) The reconstructed daily TWSA product demonstrates superior quality compared to other available products and exhibits a discernible correlation with GNSS-derived daily TWSA data, while REC_TWSA is closer to the GRACE-based TWSA dataset. (2) The DDSI demonstrates superior drought monitoring capabilities compared to conventional drought indices. During the observation period from 2004 to 2021, the DDSI detected the most severe drought event occurring between 30 October 2010 and 10 September 2011. (3) Human activities become the primary driver of drought in the YRB. The high correlation of 0.81 between human-driven water storage anomalies and groundwater storage anomalies suggests that the depletion of TWSA is due to excessive groundwater extraction by humans. This study aims to provide novel evidence and methodologies for understanding drought dynamics and quantifying human factors in the YRB. Full article

(This article belongs to the Special Issue Enhancing the Understanding of the Water Cycle and Climate Change Using Satellite Geodesy)

20 pages, 6973 KiB

Open AccessArticle

Research on Water Quality Prediction Model Based on Spatiotemporal Weighted Fusion and Hierarchical Cross-Attention Mechanisms

by Jiaming Zhou, Ke Wei, Jiahuan Huang, Lin Yang and Junzhe Shi

Water 2025, 17(9), 1244; https://doi.org/10.3390/w17091244 (registering DOI) - 22 Apr 2025

Abstract

In the context of drinking water safety assurance, water quality prediction faces challenges due to temporal fluctuations, seasonal cycles, and the impacts of sudden events. To address the issue of cumulative prediction bias caused by the simplistic feature fusion of traditional methods, this [...] Read more.

In the context of drinking water safety assurance, water quality prediction faces challenges due to temporal fluctuations, seasonal cycles, and the impacts of sudden events. To address the issue of cumulative prediction bias caused by the simplistic feature fusion of traditional methods, this study proposes a neural network architecture that integrates spatiotemporal features with a hierarchical cross-attention mechanism. Innovatively, the model constructs a parallel feature extraction framework, integrating BiGRUs (Bidirectional Gated Recurrent Units) and BiTCNs (Bidirectional Temporal Convolutional Networks). By incorporating a bidirectional spatiotemporal interaction mechanism, the model effectively captures long-term dependencies in time series and local associations in spatial topology. During the feature fusion phase, layer-by-layer weighting through learnable parameters enables adaptive spatiotemporal feature processing. A hierarchical cross-attention module is designed to achieve deep feature integration, enhancing the discriminative expression of spatial features while preserving the dynamics of time series. The experimental results demonstrate that when predicting water quality monitoring data from the Xidong Water Plant, this model excels in forecasting key indicators such as total phosphorus and total nitrogen. Compared to traditional hybrid models, it reduces the MSE (Mean Squared Error) by 33.35%, the MAE (Mean Absolute Error) by 38.05%, and the RMSE (Root Mean Square Error, RMSE) by 19.35%, and increases the R² (coefficient of determination, R²) by 2.15 percentage points. These achievements break the limitations of traditional methods’ rigid and simplistic feature fusion, fully demonstrating the model’s superiority in prediction accuracy and generalization capabilities. Full article

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

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18 pages, 3956 KiB

Open AccessArticle

Identification of Gully-Type Debris Flow Shapes Based on Point Cloud Local Curvature Extrema

by Ruoyu Tan and Bohan Zhang

Water 2025, 17(9), 1243; https://doi.org/10.3390/w17091243 - 22 Apr 2025

Abstract

The identification of gully-type debris flow remains a challenging task due to the irregularity of terrain, which causes significant fluctuations in local curvature and hinders accurate feature extraction using traditional methods. To address this issue, this study proposes a novel identification approach based [...] Read more.

The identification of gully-type debris flow remains a challenging task due to the irregularity of terrain, which causes significant fluctuations in local curvature and hinders accurate feature extraction using traditional methods. To address this issue, this study proposes a novel identification approach based on point cloud local curvature extrema. The methodology involves collecting image data of debris flow and landslide areas using DJI Matrice 300 RTK (M300RTK), planning control points and flight routes, and generating three-dimensional point cloud data through image matching and point cloud reconstruction techniques. A quadratic surface fitting method was employed to calculate the curvature of each point in the point cloud, while a topological k-neighborhood algorithm was introduced to establish spatial relationships and extract extreme curvature features. These features were subsequently used as inputs to a convolutional neural network (CNN) for landslide identification. Experimental results demonstrated that the CNN architecture used in this method achieved rapid convergence, with the loss value decreasing to 0.0032 (cross-entropy loss) during training, verifying the model’s effectiveness. The introduction of early stopping and learning rate decay strategies effectively prevented overfitting. Receiver-operating characteristic (ROC) curve analysis revealed that the proposed method achieved an area under the ROC curve (AUC) of 0.92, significantly outperforming comparative methods (0.78–0.85). Full article

(This article belongs to the Special Issue Advances in Machine Learning and Artificial Intelligence Technologies for Hydrological Processes and Hydrologic Disasters)

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2 pages, 126 KiB

Open AccessCorrection

Correction: Datta et al. Rethinking Indigenous Community-Led Water Sustainability: Decolonial and Relational Approaches in Western Canada. Water 2025, 17, 334

by Ranjan Datta, Jebunnessa Chapola and Kevin Lewis

Water 2025, 17(9), 1242; https://doi.org/10.3390/w17091242 - 22 Apr 2025

Abstract

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

21 pages, 4854 KiB

Open AccessArticle

Impact of Iron Minerals on Nitrate Reduction in the Lake–Groundwater Interaction Zone of High-Salinity Environment

by Zhen Wang, Yuyu Wan, Zhe Ma, Luwen Xu, Yuanzheng Zhai and Xiaosi Su

Water 2025, 17(9), 1241; https://doi.org/10.3390/w17091241 - 22 Apr 2025

Abstract

Nitrate is the most prevalent inorganic pollutant in aquatic environments, posing a significant threat to human health and the ecological environment, especially in lakes and groundwater, which are located in the high agricultural activity intensity areas. In order to reveal the sources of [...] Read more.

Nitrate is the most prevalent inorganic pollutant in aquatic environments, posing a significant threat to human health and the ecological environment, especially in lakes and groundwater, which are located in the high agricultural activity intensity areas. In order to reveal the sources of nitrogen pollution in lakes and groundwater, this study of the transformation mechanism of nitrogen in the interaction zone between lakes and groundwater has become an important foundation for pollution prevention and control. The coupling effect between the biogeochemical processes of nitrate and iron has been pointed out to be widely present in various water environments in recent years. However, the impact of iron minerals on nitrate reduction in the lake–groundwater interaction zone of a high-salinity environment still remains uncertain. Based on the sediment and water chemistry characteristics of the Chagan Lake–groundwater interaction zone in northeastern China (groundwater TDS: 420~530 mg/L, Na⁺: 180~200 mg/L, and Cl⁻: 15~20 mg/L and lake water TDS: 470~500 mg/L, Na⁺: 210~240 mg/L, and Cl⁻: 71.40~87.09 mg/L), this study simulated relative oxidizing open system conditions and relative reducing closed conditions to investigate hematite and siderite effects on nitrate reduction and microbial behavior. The results indicated that both hematite and siderite promoted nitrate reduction in the closed system, whereas only siderite promoted nitrate reduction in the open system. Microbial community analysis indicated that iron minerals significantly promoted functional bacterial proliferation and restructured community composition by serving as electron donors/acceptors. In closed systems, hematite addition preferentially enriched Geobacter (denitrification, +15% abundance) and Burkholderiales (DNRA, +12% abundance), while in open systems, siderite addition fostered a distinct iron-carbon coupled metabolic network through Sphingomonas enrichment (+48% abundance), which secretes organic acids to enhance iron dissolution. These microbial shifts accelerated Fe(II)/Fe(III) cycling rates by 37% and achieved efficient nitrogen removal via combined denitrification and DNRA pathways. Notably, the open system with siderite amendment demonstrated the highest nitrate removal efficiency (80.6%). This study reveals that iron minerals play a critical role in regulating microbial metabolic pathways within salinized lake–groundwater interfaces, thereby influencing nitrogen biogeochemical cycling through microbially mediated iron redox processes. Full article

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

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Water, Volume 17, Issue 9 (May-1 2025) – 24 articles

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