Water

29 pages, 4061 KB

Open AccessReview

A Review of Assessment Methods for Coastal Hydro-Environmental Processes: Research Trends and Challenges

by Qian Xuan Lee, Fang Yenn Teo, Anurita Selvarajoo, Sin Poh Lim, Hooi Bein Goh and Roger A. Falconer

Water 2025, 17(22), 3278; https://doi.org/10.3390/w17223278 (registering DOI) - 16 Nov 2025

Abstract

Coastal regions face escalating challenges, including climate change, rapid urbanisation, ocean pollution, habitat degradation, and nutrient enrichment, which threaten coastal ecosystem health, biodiversity, and human livelihoods. A comprehensive understanding of coastal hydro-environmental processes, encompassing hydrodynamics, sediment transport driven by waves and currents, and [...] Read more.

Coastal regions face escalating challenges, including climate change, rapid urbanisation, ocean pollution, habitat degradation, and nutrient enrichment, which threaten coastal ecosystem health, biodiversity, and human livelihoods. A comprehensive understanding of coastal hydro-environmental processes, encompassing hydrodynamics, sediment transport driven by waves and currents, and biogeochemical dynamics influencing water quality, is essential for sustainable coastal management. This study presents a global systematic review of assessment methods for these processes, focusing on field data collection, laboratory experiments, numerical modelling, and artificial intelligence techniques. A bibliometric analysis was conducted on 165 peer-reviewed articles from Scopus and Web of Science, adhering to PRISMA 2020 guidelines. The findings reveal a significant shift from conventional standalone methods to integrated approaches, with 31.5% of studies combining field data with numerical models and 20% incorporating AI with field data, emphasising the need for real-time data integration and interdisciplinary strategies to enhance model reliability. This study also introduces a novel process–method–time classification framework that functionally aligns various assessment methods with specific coastal processes. However, challenges such as limited long-term datasets, high computational costs, and data resolution constraints persist. By synthesising global research trends and methodological advancements, this study offers critical insights to support more resilient, adaptive, and data-driven coastal management strategies. Full article

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

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35 pages, 12053 KB

Open AccessArticle

A Moving-Window Based Method for Floor Water Inrush Risk Assessment in Coal Mines

by Xiang Si, Dangliang Wang, Chengyue Gao, Jin Ma, Weizhuo Xu and Zhiheng Zhu

Water 2025, 17(22), 3277; https://doi.org/10.3390/w17223277 (registering DOI) - 16 Nov 2025

Abstract

In recent years, with the continuous increase in coal mining depth and intensity, hydrogeological conditions in coal mines have become increasingly complex, and the risk of floor water inrush has risen significantly. To address the limitations of the global weighting pattern in traditional [...] Read more.

In recent years, with the continuous increase in coal mining depth and intensity, hydrogeological conditions in coal mines have become increasingly complex, and the risk of floor water inrush has risen significantly. To address the limitations of the global weighting pattern in traditional floor water inrush risk evaluation systems, this study, taking a coal mine in Shaanxi Province as a case, develops a local water inrush risk evaluation method based on the Monte Carlo Analytic Hierarchy Process (MAHP) combined with a circular moving window, and compares it with the water inrush coefficient method and the global evaluation method. The results demonstrate that the proposed local evaluation model achieves higher accuracy, provides a more refined delineation of high-risk zones, and shows stronger consistency with actual mining conditions. Further comparison of window radii of 100 m, 500 m, and 900 m indicates that the 500 m radius performs best in terms of spatial morphology, area proportion, and water inrush point identification rate (89.3%). Moreover, its application in Yangcheng Coal Mine further confirms that this method can accurately identify high-risk zones, thereby offering reliable scientific support for the prevention and control of coal seam floor water inrush. Full article

(This article belongs to the Section Hydrogeology)

24 pages, 1087 KB

Open AccessArticle

Impact of Wastewater Treatment Plant Discharge on Water Quality of a Heavily Urbanized River in Milan Metropolitan Area: Traditional and Emerging Contaminant Analysis

by Stefano Tasselli, Laura Marziali, Licia Guzzella, Lucia Valsecchi, Maria Teresa Palumbo, Franco Salerno and Diego Copetti

Water 2025, 17(22), 3276; https://doi.org/10.3390/w17223276 (registering DOI) - 16 Nov 2025

Abstract

Wastewater treatment plants (WWTPs) can still be considered point sources of contamination into receiving aquatic ecosystems, especially for many emerging contaminants, which require additional treatments for their removal. In this study, the impact of a WWTP on the water quality of a river [...] Read more.

Wastewater treatment plants (WWTPs) can still be considered point sources of contamination into receiving aquatic ecosystems, especially for many emerging contaminants, which require additional treatments for their removal. In this study, the impact of a WWTP on the water quality of a river located in the metropolitan area of Milan, Northern Italy, was investigated. A wide range of emerging contaminants (i.e., perfluorinated compounds, pharmaceuticals, and synthetic fragrances) and traditional contaminants (i.e., heavy metals, nutrients, and microbiological parameters) were analyzed, both in the river water and in the wastewater at the inlet and outlet of the WWTP, with the aim of evaluating removal efficiency and the risk for the riverine ecosystem. The results showed that wastewater treatment acts differently on the analyzed compounds, effectively removing nutrients, bacteria, few pharmaceuticals, and most heavy metals, but leaving others unchanged such as perfluorinated compounds and synthetic fragrances, that are thus discharged into the receiving river, especially during rain events due to the activation of sewer overflows. The calculation of the Risk Quotient for organic compounds confirmed the negative impact of the WWTP effluent on the chemical quality of the river water, with a consequent potential ecological risk for riverine biota. This study also verified that certain traditional contaminants (i.e., total nitrogen (TN), total phosphorous (TP), thermotolerant coliforms, Escherichia coli), and contamination tracer (i.e., chloride (Cl), boron (B), and MBAS (Methylene Blue Active Substances) could be effectively measured in real time rather than through classical laboratory analysis and could support timely risk assessment. Full article

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

21 pages, 760 KB

Open AccessReview

China’s South-to-North Water Diversion Project: A Review and Reach Beyond China’s Borders

by Yi Jia, Linus Zhang, Jianzhi Niu and Ronny Berndtsson

Water 2025, 17(22), 3275; https://doi.org/10.3390/w17223275 (registering DOI) - 16 Nov 2025

Abstract

The South-to-North Water Diversion Project (SNWDP), the world’s largest water transfer initiative, is designed to address northern China’s acute water scarcity by diverting approximately 45 km³ of water annually from the south through three major routes, with completion targeted for 2050. This [...] Read more.

The South-to-North Water Diversion Project (SNWDP), the world’s largest water transfer initiative, is designed to address northern China’s acute water scarcity by diverting approximately 45 km³ of water annually from the south through three major routes, with completion targeted for 2050. This review demonstrates that the SNWDP has already improved water security for over 150 million people, stabilized groundwater, and supported agricultural and urban development, but also presents significant challenges, including escalating costs, large-scale resettlement, and substantial environmental concerns such as ecosystem alteration, salinity intrusion, pollutant transfer, and risks to biodiversity and water quality. While mitigation and adaptive management efforts are ongoing, their long-term effectiveness remains uncertain. Notably, the SNWDP’s influence extends beyond China: by enhancing food production self-sufficiency, it can help stabilize global food markets during concurrent droughts and serves as a model—albeit a debated one—for large-scale water management and governance. The project’s hydropolitical and geopolitical dimensions, especially regarding the planned western route and potential transboundary impacts, underscore the need for international dialog and monitoring. Overall, the SNWDP exemplifies both the opportunities and dilemmas of 21st-century megaprojects, with its legacy dependent on balancing economic, environmental, and social trade-offs and on transparent, participatory governance to ensure sustainable outcomes for China and the global community. Full article

(This article belongs to the Special Issue China Water Forum, 4th Edition)

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15 pages, 1251 KB

Open AccessArticle

Application of a Box-Cox Transformed LSTAR-GARCH Model for Point and Interval Forecasting of Monthly Rainfall in Hainan, China

by Xiaoxuan Zhang, Yu Liu and Jun Li

Water 2025, 17(22), 3274; https://doi.org/10.3390/w17223274 (registering DOI) - 16 Nov 2025

Abstract

To improve the accuracy of monthly rainfall forecasting and reasonably quantify its uncertainty, this study developed a hybrid LSTAR-GARCH model incorporating a Box–Cox transformation. Using monthly rainfall data from 1999 to 2019 from four meteorological stations in Hainan Province (Haikou, Dongfang, Danzhou, and [...] Read more.

To improve the accuracy of monthly rainfall forecasting and reasonably quantify its uncertainty, this study developed a hybrid LSTAR-GARCH model incorporating a Box–Cox transformation. Using monthly rainfall data from 1999 to 2019 from four meteorological stations in Hainan Province (Haikou, Dongfang, Danzhou, and Qiongzhong), the non-stationarity and nonlinearity of the series were first verified using KPSS and BDS tests, and the Box–Cox transformation was applied to reduce skewness. A Logistic Smooth Transition Autoregressive (LSTAR) model was then established to capture nonlinear dynamics, followed by a GARCH(1,1) model to address heteroskedasticity in the residuals. The results indicate that: (1) The LSTAR model effectively captured the nonlinear characteristics of monthly rainfall, with Nash-Sutcliffe efficiency (NSE) values ranging from 0.565 to 0.802, though some bias remained in predicting extreme values; (2) While the GARCH component did not improve point forecast accuracy, it significantly enhanced interval forecasting performance. At the 95% confidence level, the average interval width (RIW) of the LSTAR-GARCH model was reduced to 0.065–0.130, substantially narrower than that of the LSTAR-ARCH model (RIW: 4.548–8.240), while maintaining high coverage rates (CR) between 93.8% and 97.9%; (3) The LSTAR-GARCH model effectively characterizes both the nonlinear mean process and time-varying volatility in rainfall series, proving to be an efficient and reliable tool for interval rainfall forecasting, particularly in tropical monsoon regions with high rainfall variability. This study provides a scientific basis for regional water resource management and climate change adaptation. Full article

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

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39 pages, 8925 KB

Open AccessReview

Rainfall-Induced Landslide Prediction Models, Part I: Empirical–Statistical and Physically Based Causative Thresholds

by Kyrillos Ebrahim, Sherif M. M. H. Gomaa, Tarek Zayed and Ghasan Alfalah

Water 2025, 17(22), 3273; https://doi.org/10.3390/w17223273 (registering DOI) - 16 Nov 2025

Abstract

Introduction and Problem Statement: Landslides represent a significant geological hazard worldwide. One of the primary triggers for these landslides is rainfall, which is becoming more intense as a result of climate change. The available literature has produced extensive research. However, this largely [...] Read more.

Introduction and Problem Statement: Landslides represent a significant geological hazard worldwide. One of the primary triggers for these landslides is rainfall, which is becoming more intense as a result of climate change. The available literature has produced extensive research. However, this largely overlooks the use of mixed methodologies. Furthermore, a comprehensive review combining empirical, physically based, deterministic, and phenomenological models is still rare. Objective and Method: This study (Part I of a two-part review) addresses this gap by employing a mixed review that integrates quantitative scientometric analysis with a qualitative systematic review. The primary objective of Part I is to deliver a critical assessment, focusing on empirical and physically based causative threshold models. Main Results and Validation: Macroscopically, our analysis reveals that antecedent rainfall is a more robust indicator than classical intensity–duration (I-D) thresholds, though the latter remains widely used due to its simplicity. Physically based models provide a critical bridge when geotechnical data is scarce, correlating rainfall with internal slope responses like displacement. At a microscopic level, hybrid artificial intelligence (AI) models consistently demonstrate superior predictive accuracy by capturing complex, nonlinear relationships missed by simpler models. These findings are validated through a systematic evaluation of performance metrics across the reviewed literature. Main Conclusions and Significance: We conclude that while empirical thresholds offer operational simplicity, the future of accurate prediction lies in sophisticated hybrid AI models trained on extensive monitoring data. This review synthesizes fragmented knowledge into a unified framework, providing a clear roadmap for model selection. Full article

(This article belongs to the Special Issue Rainfall-Induced Landslides: Influencing, Modelling and Hazard Assessment: 2nd Edition)

17 pages, 2392 KB

Open AccessArticle

Spatial and Temporal Distribution and Risk Assessment of Dissolved and Particulate Heavy Metals in the Middle and Lower Reaches of the Yellow River During the Water and Sediment Regulation Period

by Yimei Ying, Xinrui Cui, Xu Wang, Ruijie Huang, Bing Han, Yun Zhang, Jinglei Hou, Meng Shang and Yu Bai

Water 2025, 17(22), 3272; https://doi.org/10.3390/w17223272 (registering DOI) - 16 Nov 2025

Abstract

Water-sediment regulation Scheme (WSRS) is a crucial artificial control method for water and sediment in the lower reaches of the Yellow River (YR). During this period, the impact of high flow discharge and high sediment concentration on the distribution and transport of heavy [...] Read more.

Water-sediment regulation Scheme (WSRS) is a crucial artificial control method for water and sediment in the lower reaches of the Yellow River (YR). During this period, the impact of high flow discharge and high sediment concentration on the distribution and transport of heavy metals in the Yellow River warrants particular attention. This study analyzes heavy metals in water and suspended sediments across different phases of the WSRS. During the WSRS, the lower Yellow River showed decreased levels of dissolved heavy metals. Evaluations of the ecological risk posed by Cd, Cu, Ni, Pb, Zn, and Cr in suspended sediments suggested an absence of risk or minimal risk levels. A greater percentage of Cd and Pb was found in bioavailable forms. And RAC analysis further revealed that Cd poses a relatively higher migration risk. Compared to the water regulation stage (WRS), the sediment regulation stage (SRS) was characterized by lower dissolved heavy metal concentrations but higher particulate heavy metal contents. Over 85% of heavy metals were transported by SPM in WSRS. During the sediment regulation phase, the mean particulate transport proportion for heavy metals surpassed 96%. This phase accounted for more than 50% of the total heavy metal flux delivered to the sea throughout the entire regulation period. These findings offer valuable insights into controlling and managing heavy metal risks during WSRS in the YR. Full article

(This article belongs to the Section Hydrology)

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21 pages, 14137 KB

Open AccessArticle

Stability Analysis of Loess Slope Under Heavy Rainfall Considering Joint Effect—Case Study of Jianxi Landslide, China

by Jiahao Wang, Lei Zhang, Shi Zhao, Guoji Li and Haipeng Guo

Water 2025, 17(22), 3271; https://doi.org/10.3390/w17223271 (registering DOI) - 15 Nov 2025

Abstract

Loess exhibits a pronounced reduction in strength under rainfall infiltration, making loess slopes highly susceptible to instability and failure during rainfall events. Although numerous studies have investigated the failure mechanisms of loess slopes under rainfall, most have overlooked the role of joints, which [...] Read more.

Loess exhibits a pronounced reduction in strength under rainfall infiltration, making loess slopes highly susceptible to instability and failure during rainfall events. Although numerous studies have investigated the failure mechanisms of loess slopes under rainfall, most have overlooked the role of joints, which are intrinsic structural features of loess. To address this gap, this study selected the Jianxi landslide, located in Lingbao city of Henan province, as a representative case and employed a numerical simulation method to examine the influence of joints on the moisture fields and stability conditions of the Jianxi landslide. The results elucidate that the safety factor of the Jianxi landslide considering joints is 15.7% lower than the one measured without considering joints and identify the critical rainfall threshold leading to landslide instability to be 100 mm/d. Furthermore, when joints are considered, the sliding zone becomes deeper, indicating a larger landslide volume and more severe potential damage. This work provides new insights into the failure mechanism of loess landslides and offers a scientific basis for early warning. Full article

(This article belongs to the Special Issue Landslide on Hydrological Response)

23 pages, 14113 KB

Open AccessArticle

Groundwater Flow Fields and Patterns in Heterogeneous Aquifer Induced by Mine Water Injection and Storage Under Different Well Configurations

by Ge Chen, Heng Li, Xin Li, Li Zhang, Peishan Yuan, Hewen Ma, Zhimin Xu and Wanghua Sui

Water 2025, 17(22), 3270; https://doi.org/10.3390/w17223270 (registering DOI) - 15 Nov 2025

Abstract

Mine water injection and storage (MWIS) represent a crucial method for the management of unconventional water resource in the mining regions of China. The flow fields and patterns within heterogeneity porous media during the MWIS process are complex and significantly influenced by well [...] Read more.

Mine water injection and storage (MWIS) represent a crucial method for the management of unconventional water resource in the mining regions of China. The flow fields and patterns within heterogeneity porous media during the MWIS process are complex and significantly influenced by well configurations. This study aims to offer a numerical perspective for the evaluation of MWIS flow fields and patterns associated with diverse well configurations in different heterogeneous aquifers. The simulation results of various well configuration scenarios, including vertical, slanted and horizontal wells, demonstrate that well configuration exerts a profound influence on the flow fields and patterns of MWIS. The injected mine water primarily spreads radially and groundwater level gradually diminishes as the distance from the wellbore increases in the vertical well. Conversely, horizontal wells can notably augment the contact area between the injected mine water and the aquifer, leading to a more uniform distribution of the flow field and higher injection efficiency. Slanted wells exhibit a combination of vertical and horizontal flow characteristics, which can be adjusted in accordance with specific geological conditions to optimize the MWIS effect. Overall, both horizontal and slanted wells exhibit water storage capacities that are approximately 1.77 to 2.65 times greater than that of vertical wells. Effective mine water capacity accumulates primarily during the initial phase, followed by a rapid decline in subsequent reserves. The results suggest that appropriate arrangement of well configurations and injection pressure can effectively enhance the MWIS efficiency. Hydraulic fracturing is the fundamental approach to sustaining MWIS capacity. This research provides a theoretical foundation and practical guidance for the design and optimization of MWIS, which is of great significance for the sustainable development of coal mines in the Ordos Basin, China. Full article

(This article belongs to the Special Issue Mine Water Environment and Remediation)

28 pages, 49938 KB

Open AccessArticle

Geothermal Reservoir Parameter Identification by Wellbore–Reservoir Integrated Fluid and Heat Transport Modeling

by Fengyu Li, Xia Guo, Zhenxiang Xing, Haitao Cui and Xi Zhang

Water 2025, 17(22), 3269; https://doi.org/10.3390/w17223269 (registering DOI) - 15 Nov 2025

Abstract

Efficient development of karst geothermal resources relies on the accurate identification of thermophysical and hydrogeological parameters. In this paper, the integrated wellbore–reservoir model of fluid and heat transport is applied to identify hydrothermal parameters of the karst geothermal system in Tianjin, China, based [...] Read more.

Efficient development of karst geothermal resources relies on the accurate identification of thermophysical and hydrogeological parameters. In this paper, the integrated wellbore–reservoir model of fluid and heat transport is applied to identify hydrothermal parameters of the karst geothermal system in Tianjin, China, based on multi-type field test data. A natural state model is conducted by fitting steady-state borehole temperature measurement results to identify formation thermal conductivity, while reservoir permeability is determined via the Gauss–Marquardt–Levenberg optimization algorithm based on dynamic temperature and pressure data from pumping tests. The parameter identification results indicate a reservoir permeability of 5.25 × 10⁻¹⁴ m² and a corrected bottom-hole temperature of 109 °C. Subsequently, productivity optimization for actual heating demands (1.33 × 10⁵ m²) yields an optimal heat extraction efficiency of 6.17 MW, with a flow rate of 80 m³/h, an injection well perforated length of 388 m, and an injection temperature of 30 °C. Additionally, addressing reservoir heterogeneity, the study finds that high-permeability zones between wells significantly shorten the safe operation duration of geothermal doublets, and reducing flow rate can mitigate thermal breakthrough risk to a certain extent. Full article

(This article belongs to the Section Hydrogeology)

60 pages, 7411 KB

Open AccessArticle

An Integrated Methodology for Novel Algorithmic Modeling of Non-Spherical Particle Terminal Settling Velocities and Comprehensive Digital Image Analysis

by Kaan Yetilmezsoy, Fatih Ilhan and Emel Kıyan

Water 2025, 17(22), 3268; https://doi.org/10.3390/w17223268 (registering DOI) - 15 Nov 2025

Abstract

Accurate prediction of settling velocities for irregular particles offers significant advantages in various fields, including more efficient water/wastewater treatment, environmental pollution control, industrial productivity, and sustainable resource utilization. These predictions are essential for advancing sustainable hydraulic engineering and environmental management. In this study, [...] Read more.

Accurate prediction of settling velocities for irregular particles offers significant advantages in various fields, including more efficient water/wastewater treatment, environmental pollution control, industrial productivity, and sustainable resource utilization. These predictions are essential for advancing sustainable hydraulic engineering and environmental management. In this study, a new algorithmic modeling framework was proposed to estimate the terminal settling velocity of irregularly shaped particles/materials. The framework integrates advanced non-linear regression techniques with robust optimization methods. The model successfully incorporated seven key input parameters to construct a comprehensive mathematical representation of the settling process. The proposed explicit model demonstrates superior prediction accuracy compared to existing empirical and drag correlation models. The model’s validity was confirmed using a large and morphologically diverse dataset of 86 irregular materials and rigorously evaluated using an extensive battery of statistical goodness-of-fit parameters. The developed model is a robust and highly accurate tool for predicting the settling behavior of non-spherical particles in the transition flow regime. Beyond its technical merits, the model could offer significant sustainability benefits by enhancing the design and optimization of wastewater treatment systems. More precise predictions of non-spherical particle settling behavior could improve sedimentation or particle removal efficiency, potentially reducing energy consumption and mitigating adverse environmental impacts on industrial waste management and aquatic ecosystem preservation. Full article

(This article belongs to the Special Issue Mathematical Models of Fluid Dynamics)

19 pages, 3333 KB

Open AccessArticle

Spatial Distribution and Environmental Impacts of Soil Nitrogen and Phosphorus in the Downstream Daliao River Basin

by Tianxiang Wang, Yexin Liu, Zixiong Wang, Tianzi Wang, Zipeng Zhang, Runfa Cui, Rongyue Ma and Guangyu Su

Water 2025, 17(22), 3267; https://doi.org/10.3390/w17223267 (registering DOI) - 15 Nov 2025

Abstract

Soil nitrogen (N) and phosphorus (P) loss in watersheds is a critical source of water pollution. This study explores the spatial distribution, release potential, and environmental impacts of soil N and P in the downstream Daliao River basin by integrating field investigations and [...] Read more.

Soil nitrogen (N) and phosphorus (P) loss in watersheds is a critical source of water pollution. This study explores the spatial distribution, release potential, and environmental impacts of soil N and P in the downstream Daliao River basin by integrating field investigations and simulation experiments. Results showed that total nitrogen content in soils ranged from 256.09 to 3362.75 mg/kg, while that in sediments ranged from 114.85 to 1640.54 mg/kg. Total phosphorus content in soils varied from 250.18 to 1142.69 mg/kg, whereas in sediments it ranged from 327.23 to 586.24 mg/kg. The ammonia nitrogen release potentials of soils collected from rice paddies, corn farmlands, roadsides, and reed wetlands were 0.75, 0.86, 0.70, and 8.65 mg/L, respectively, with corresponding total phosphorus release potentials of 0.61, 1.01, 0.31, and 1.52 mg/L. For sediments, ammonia nitrogen and total phosphorus release potentials ranged from 0.96 to 1.21 mg/L and 0.44 to 0.52 mg/L, respectively. Temperature, pH, and dissolved oxygen were important factors influencing nitrogen and phosphorus release from soils and sediments. The export of nitrogen and phosphorus from soil reached 50.50 t/a and 21.63 t/a, respectively. During the soil erosion process in the Daliao River Basin, phosphorus exhibited a high release potential and served as the primary pollutant, whereas the release mechanism of ammonia nitrogen was more complex, showing seasonal variability. Soils in the downstream Daliao River basin have large specific surface areas and may pose a high pollution risk after discharge into water bodies due to prolonged adsorption of pollutants. It is recommended to propose promoting soil testing-based fertilization, constructing ecological engineering projects, developing sponge cities, and conducting environmental dredging to reduce N and P release from agricultural lands, construction areas, natural wastelands, and sediments. Full article

(This article belongs to the Special Issue Application of Smart Technologies in Integrated Water Quality Modeling, 2nd Edition)

30 pages, 11720 KB

Open AccessArticle

Assessment of Groundwater Quality for Irrigation in the Semi-Arid Region of Oum El Bouaghi (Northeastern Algeria) Using Groundwater Quality and Pollution Indices and GIS Techniques

by Norelhouda Messaid, Ramzi Hadjab, Hichem Khammar, Aymen Hadjab, Nadhir Bouchema, Abderrezzeq Chebout, Mourad Aqnouy, Ourania Tzoraki and Lahcen Benaabidate

Water 2025, 17(22), 3266; https://doi.org/10.3390/w17223266 (registering DOI) - 15 Nov 2025

Abstract

Groundwater quality in the semi-arid region of Oum El Bouaghi, Northeastern Algeria, was assessed for irrigation suitability using hydrogeochemical analyses, water quality indices, and GIS techniques. The study analyzed 23 groundwater samples during dry and wet seasons in 2022–2023, several physicochemical parameters were [...] Read more.

Groundwater quality in the semi-arid region of Oum El Bouaghi, Northeastern Algeria, was assessed for irrigation suitability using hydrogeochemical analyses, water quality indices, and GIS techniques. The study analyzed 23 groundwater samples during dry and wet seasons in 2022–2023, several physicochemical parameters were measured. Results revealed neutral to slightly alkaline pH levels, except for one acidic sample, with salinity (EC: 527–5001 µS·cm⁻¹) exceeding WHO guidelines, particularly during the dry season due to evaporation and anthropogenic activities. Hydrogeochemical facies showed dominance of Na⁺-HCO₃⁻ and Ca²⁺-Cl⁻/SO₄²⁻ water types, indicating rock–water interactions and evaporation control, as confirmed by Gibbs plots. The IWQI classified water into five categories, with severe restrictions (IWQI < 40) in 13% of samples during the dry season, improving slightly in the wet season. Indices such as SAR, Na%, and RSC indicated low to moderate sodium hazard, while KR and PS highlighted salinity risks in specific areas. Spatial analysis revealed localized pollution hotspots, with the (GPI) identifying minimal to high contamination levels, linked to agricultural and geogenic sources. These findings underscore needs for sustainable groundwater management, including monitoring, optimized irrigation practices, and mitigation of anthropogenic impacts, to ensure long-term agricultural viability in this water-scarce region. Full article

(This article belongs to the Special Issue Research on Hydrogeology and Hydrochemistry: Challenges and Prospects)

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25 pages, 3960 KB

Open AccessArticle

Spatial Structure and Temporal Dynamics in Clear Lake, CA: The Role of Wind in Promoting and Sustaining Harmful Cyanobacterial Blooms

by David A. Caron, Alle A. Y. Lie, Brittany Stewart, Amanda Tinoco, Isha Kalra, Stephanie A. Smith, Adam L. Willingham, Shawn Sneddon, Jayme Smith, Eric Webb, Kyra Florea and Meredith D. A. Howard

Water 2025, 17(22), 3265; https://doi.org/10.3390/w17223265 (registering DOI) - 15 Nov 2025

Abstract

Clear Lake in Lake County, CA, USA has experienced highly toxic cyanobacterial blooms for more than a decade, with multiple cyanobacterial taxa and cyanotoxins appearing sporadically, typically throughout much of the early-spring to late-fall seasons. Recurring blooms have been attributed to high internal [...] Read more.

Clear Lake in Lake County, CA, USA has experienced highly toxic cyanobacterial blooms for more than a decade, with multiple cyanobacterial taxa and cyanotoxins appearing sporadically, typically throughout much of the early-spring to late-fall seasons. Recurring blooms have been attributed to high internal nutrient loads within the lake, with hydrography and hydrology playing important but still poorly documented roles in controlling the availability of growth-limiting elements to the phytoplankton community. The lake is approximately 180 km² in areal extent and composed of three somewhat disjointed lobes, or ‘Arms’. The large size of the lake presents a formidable task for synoptic lakewide surveys and for understanding the specific features that stimulate the development and magnitude of harmful blooms. We conducted a study in August of 2020 that involved the use of an autonomous underwater vehicle and deployment of a hand-held water column profiler to describe the lakewide status of various biological, chemical, and physical features. Discrete water samples were also collected from ten stations located throughout the lake to produce a near-synoptic depiction of lake status. Additionally, a mechanically driven, continuously monitoring water-column profiler was deployed at a central lake location to document short-term temporal (minutes to months) changes in water-column structure and chemistry. Wind was a dominant feature affecting the lake’s chemistry and biology during the study, resulting in massive concentrations and dramatic spatial heterogeneity of phytoplankton biomass and cyanotoxins in the eastern and southeastern Arms of the lake, and confirmed by the analysis of discrete water samples. Unique insight into the processes leading to or prolonging blooms was revealed by the water column profiler, which demonstrated rapid development (within a few hours) of suboxic conditions during periods of calm winds. We speculate that these quiescent periods are fundamental events in the lake’s ecology, resulting in episodic ‘pulses’ of nutrient release from the sediments, which can stimulate or refuel blooms of cyanobacteria in the water column. Full article

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

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16 pages, 2103 KB

Open AccessArticle

Hydrological and Geochemical Responses to Agricultural Activities in a Karst Catchment: Insights from Spatiotemporal Dynamics and Source Apportionment

by Le Cao, Qianyun Cheng, Shangqing Wang, Shaoqiang Xu, Qirui He, Yanqiu Li, Tao Peng and Shijie Wang

Water 2025, 17(22), 3264; https://doi.org/10.3390/w17223264 (registering DOI) - 15 Nov 2025

Abstract

Karst aquifers, vital freshwater resources, are highly vulnerable to agricultural pollution, yet their hydro-geochemical responses remain poorly understood due to high spatial heterogeneity. This study aimed to unravel these complex responses in a subtropical karst agricultural catchment to provide a basis for its [...] Read more.

Karst aquifers, vital freshwater resources, are highly vulnerable to agricultural pollution, yet their hydro-geochemical responses remain poorly understood due to high spatial heterogeneity. This study aimed to unravel these complex responses in a subtropical karst agricultural catchment to provide a basis for its sustainable management. We employed high-frequency monitoring at a headwater spring (background), a depression well (hotspot), and the catchment outlet (integrated) in Southwest China. Using hydrological and geochemical data from 2017, we applied Principal Component Analysis (PCA) to apportion natural and anthropogenic sources. The main findings revealed significant spatial heterogeneity, with the depression well acting as a contamination hotspot characterized by rapid hydrological responses and elevated SO₄²⁻ and Cl⁻ concentrations. PCA successfully decoupled an “anthropogenic factor” (PC1, 40.5%) from a “natural weathering factor” (PC2, 25.2%). Critically, agricultural SO₄²⁻ at the hotspot was counter-intuitively higher during the wet season than the dry season, opposing the typical dilution pattern of background ions and revealing that depressions act as contaminant-concentrating pathways, whose risks are severely underestimated by traditional outlet monitoring. The anomalous sulfate dynamics reveal a cross-seasonal “storage-and-release” mechanism (legacy effect) within the karst Critical Zone, demonstrating that these systems can buffer and “remember” contaminants. Full article

(This article belongs to the Section Hydrogeology)

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16 pages, 1602 KB

Open AccessArticle

Boosting Denitrification in Pyrite Bioretention Through Biochar-Mediated Electron Transfer

by Ying Xu, Xiaoqin Yang, Fanxiao Luo, Haiyuan Ma, Cong Huang, Zheng Xu, Rui Liu, Lu Qiu and Haifa Zu

Water 2025, 17(22), 3263; https://doi.org/10.3390/w17223263 - 14 Nov 2025

Abstract

The pyrite bioretention system has been increasingly used to control dissolved nutrients in stormwater runoff. However, its low electron supply rate cannot adapt to the demand for denitrification under high nitrogen-loading conditions. To address this limitation, we constructed a mixed biochar–pyrite bioretention system [...] Read more.

The pyrite bioretention system has been increasingly used to control dissolved nutrients in stormwater runoff. However, its low electron supply rate cannot adapt to the demand for denitrification under high nitrogen-loading conditions. To address this limitation, we constructed a mixed biochar–pyrite bioretention system (BP) by optimizing the structural composition of the fill media. Under simulated complex rainfall conditions, the nitrogen removal efficiency, by-product generation, and filler physicochemical properties of system were evaluated. Results demonstrated that the BP system significantly enhanced denitrification performance, achieving average NO_x⁻-N and TN removal rates of 63.3% and 67.8%, respectively. This represented improvements of 79.1% and 45.9% over the conventional pyrite bioretention system. Moreover, the composite system exhibited a sustained and effective denitrification even under low C/N ratio conditions. This enhancement is attributed to biochar’s dual role as an electron shuttle and an electron reservoir, which facilitated microbial nitrate reduction. XPS analysis further confirmed that biochar addition effectively reduced the oxidation degree of pyrite, thereby protecting it from rapid oxidative degradation. Microbial analysis revealed that biochar supplementation in the BP system increased microbial diversity in the saturated zone, which contributed to improved ecosystem function and stability, including the promotion for key denitrification processes. Full article

(This article belongs to the Special Issue Urban Drainage Systems and Stormwater Management)

16 pages, 2704 KB

Open AccessArticle

Study on Operational Stability of the Hydro-Turbine Governing System for Three-Turbine Shared Tailwater Tunnel

by Dong Liu, Yanbo Xue, Jiejie Lv and Xiaoqiang Tan

Water 2025, 17(22), 3262; https://doi.org/10.3390/w17223262 - 14 Nov 2025

Abstract

As a key power source for peak regulation and frequency control, hydropower units frequently adjust their output to maintain grid stability. In shared tailrace tunnel systems, hydraulic coupling between units significantly influences system stability. This study investigates a three-unit system with a common [...] Read more.

As a key power source for peak regulation and frequency control, hydropower units frequently adjust their output to maintain grid stability. In shared tailrace tunnel systems, hydraulic coupling between units significantly influences system stability. This study investigates a three-unit system with a common tailrace tunnel, establishes its mathematical model, and employs linear stability analysis to examine its stability characteristics under small disturbances. The research focuses on the impacts of total power output and power allocation strategies on system stability. Key findings reveal that (1) the stable domain of each unit decreases with greater penstock water inertia, and the instability of any single unit propagates through hydraulic coupling, causing system-wide instability; (2) the control parameters of individual units primarily affect their own stability, with negligible cross-unit impact, and the system’s overall stable domain is determined by the unit with the smallest stability region when uniform parameters are adopted; (3) increasing the total power output reduces system stability, and equally distributing power among units is more conducive to stable operation than concentrating it on a single unit. These results provide a theoretical basis for the optimized dispatch and stability control of multi-unit hydropower systems with shared hydraulic structures. Full article

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

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21 pages, 1858 KB

Open AccessArticle

Delineation Using Multi-Tracer Tests and Hydrochemical Investigation of the Matica River Catchment at Plitvice Lakes, Croatia

by Tihomir Frangen, Ivana Boljat, Hrvoje Meaški and Josip Terzić

Water 2025, 17(22), 3261; https://doi.org/10.3390/w17223261 - 14 Nov 2025

Abstract

In the Plitvice Lakes National Park, several hydrogeological catchments can be distinguished, but their boundaries are not clearly defined. This study focused on the Matica River catchment area, which covers the main contributors to the lake system and its overall water balance. An [...] Read more.

In the Plitvice Lakes National Park, several hydrogeological catchments can be distinguished, but their boundaries are not clearly defined. This study focused on the Matica River catchment area, which covers the main contributors to the lake system and its overall water balance. An initial assessment indicated that the Matica River catchment is among the most vulnerable areas due to the anticipated land-use expansion related to agriculture and tourism. This research provides critical hydrogeological data supporting sustainable management in response to the increasing extremes of floods and droughts induced by climate change. Two separate campaigns (March 2023 and April 2025) were carried out, each involving three simultaneous tracer injections using different fluorescent dyes. The results of earlier tracer tests were evaluated; furthermore, a hydrochemical analysis of the spring water offered valuable insights into subsurface processes and anthropogenic impacts. Tracing in the southwest clarified the boundary between the Plitvice Lakes and Una River catchments. In the Homoljac polje, the tracer responses highlighted a triple junction between the Plitvice Lakes, Gacka, and Una River catchments. In the southeastern Brezovac polje, the boundary between the Crna Rijeka and Bijela Rijeka catchments was delineated in detail. Full article

(This article belongs to the Special Issue Water Management and Geohazard Mitigation in a Changing Climate)

25 pages, 1563 KB

Open AccessArticle

AI-Augmented Water Quality Event Response: The Role of Generative Models for Decision Support

by Stephen Mounce, Richard Mounce and Joby Boxall

Water 2025, 17(22), 3260; https://doi.org/10.3390/w17223260 - 14 Nov 2025

Abstract

The global water sector faces unprecedented challenges from climate change, rapid urbanisation, and ageing infrastructure, necessitating a shift towards proactive, digital strategies. Historically characterised as “data rich but information poor,” the sector struggles with underutilised and siloed operational data. Traditional machine learning (ML) [...] Read more.

The global water sector faces unprecedented challenges from climate change, rapid urbanisation, and ageing infrastructure, necessitating a shift towards proactive, digital strategies. Historically characterised as “data rich but information poor,” the sector struggles with underutilised and siloed operational data. Traditional machine learning (ML) models have provided a foundation for smart water management, and subsequently deep learning (DL) approaches utilising algorithmic breakthroughs and big data have proved to be even more powerful under the right conditions. This paper explores and reviews the transformative potential of Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs), enabling a paradigm shift towards data-centric thinking. GenAI, particularly when augmented with Retrieval-Augmented Generation (RAG) and agentic AI, can create new content, facilitate natural language interaction, synthesise insights from vast unstructured data (of all types including text, images and video) and automate complex, multi-step workflows. Focusing on the critical area of drinking water quality, we demonstrate how these intelligent tools can move beyond reactive systems. A case study is presented which utilises regulatory reports to mine knowledge, providing GenAI-powered chatbots for accessible insights and improved water quality event management. This approach empowers water professionals with dynamic, trustworthy decision support, enhancing the safety and resilience of drinking water supplies by recalling past actions, generating novel insights and simulating response scenarios. Full article

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

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