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Volume 17
Issue 24
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Water, Volume 17, Issue 24 (December-2 2025) – 152 articles

Cover Story (view full-size image): Identifying the key drivers of water and soil salinization in arid regions is crucial for managing basin-scale water–salt balance. Although mineral dissolution, evaporation, and transpiration collectively drive salinization processes, distinguishing their individual contributions remains challenging. This study innovatively combined deuterium excess with hydrochemical analyses. Results show that mineral dissolution is the dominant salinity source in the Barkol Basin's groundwater, rivers, and lake. However, sustained evapotranspiration of shallow groundwater drives surface salt accumulation, making wetlands and lakeshores the ultimate salt sinks. Effective management should therefore focus on regulating groundwater flow paths and water-table depths to control salt mobilization. View this paper
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19 pages, 5159 KB  
Article
Hydrogeochemical Characteristics and Groundwater Quality in Chengde Bashang Area, China
by Wei Xu, Yan Dong, Xiaohua Tian, Zizhao Cai, Hao Zhai and Siyang Qin
Water 2025, 17(24), 3598; https://doi.org/10.3390/w17243598 - 18 Dec 2025
Viewed by 410
Abstract
This study aims to investigate hydrogeochemical characteristics and groundwater quality in the Bashang Area in Chengde and to discuss factors controlling the groundwater quality. A total of 91 groundwater samples were collected and a fuzzy synthetic evaluation (FSE) method was used for assessing [...] Read more.
This study aims to investigate hydrogeochemical characteristics and groundwater quality in the Bashang Area in Chengde and to discuss factors controlling the groundwater quality. A total of 91 groundwater samples were collected and a fuzzy synthetic evaluation (FSE) method was used for assessing groundwater quality. Results show the groundwater chemistry in the study area is predominantly characterized by HCO3−-Ca type waters. Rock weathering processes dominate the hydrogeochemical processes within the study area, while also being influenced by evaporation and concentration effects. The results of the fuzzy evaluation indicate that 94.5% of groundwater samples are of good quality and suitable for drinking (Classes I, II, and III), while 5.5% are of poor quality and unsuitable for drinking (Class IV). Among these, bedrock fissure water exhibited superior quality. Within clastic rock pore water, elevated levels of NO3− and F− ions were observed in certain localized areas. The exceedance of NO3− concentrations stems from agricultural expansion, where the application of nitrogen fertilizers constitutes the primary driver of local nitrate pollution. Excessive F− levels correlate with the region’s indigenous geological background. Fluoride-bearing minerals such as fluorite and biotite are widely distributed throughout the study area. Intensive evaporation concentrates groundwater, while the region’s slow groundwater flow facilitates the accumulation and enrichment of F− within aquifers. Full article
(This article belongs to the Special Issue Assessment of Groundwater Quality and Pollution Remediation)
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22 pages, 4626 KB  
Article
CFD Study on the Influence of Oblique Underflow Baffles on Bedload Transport in Rectangular Channels
by Tino Kostić, Subhojit Kadia and Nils Rüther
Water 2025, 17(24), 3597; https://doi.org/10.3390/w17243597 - 18 Dec 2025
Viewed by 379
Abstract
Hydraulic structures, particularly water intakes, are often affected by undesirable bedload depositions that can significantly reduce their operational efficiency and lifespan. Based on three-dimensional computational fluid dynamics, this study presents the potential of oblique vertical underflow baffles to redistribute the bedload and mitigate [...] Read more.
Hydraulic structures, particularly water intakes, are often affected by undesirable bedload depositions that can significantly reduce their operational efficiency and lifespan. Based on three-dimensional computational fluid dynamics, this study presents the potential of oblique vertical underflow baffles to redistribute the bedload and mitigate bedload accumulation at critical locations. A straight rectangular channel containing a baffle submerged up to 20% of the flow depth was analyzed under varying discharge rates, baffle alignments, and channel width coverages. The specific flow conditions induced by oblique baffles lead to the generation of a vortex along the trailing edge of the baffle, forming a bedload-free zone on one side of the channel—an effect not observed with an orthogonal baffle. This phenomenon offers a potential strategy for managing bedload movement in channels and sluices, providing a means to prevent undesirable bedload depositions. As discharge increases, the bedload-free zone expands, resulting in greater effectiveness at higher flows—an effect not observed with conventional near-bed bedload control structures. The oblique baffle also remained effective even at a channel width coverage of just 25%, indicating the potential for developing cost-effective designs with minimal structural support. Overall, oblique underflow baffles show potential as a practical and efficient solution for managing bedload transport and deposition, thus protecting critical hydraulic structures. Full article
(This article belongs to the Special Issue Numerical Modeling of Hydrodynamics and Sediment Transport)
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20 pages, 5861 KB  
Article
Three-Dimensional Field Investigation of Mixing Dynamics in a River Confluence Using a Mixing Proximity Index (MPI)
by Suin Choi, Seogyeong Lee, Dongsu Kim, Ilwon Seo, Yongmuk Kang and Boseong Jeong
Water 2025, 17(24), 3596; https://doi.org/10.3390/w17243596 - 18 Dec 2025
Viewed by 422
Abstract
High-resolution in situ field measurements capturing seasonal 3D mixing dynamics at river confluences are scarce, yet this understanding is essential for effective water-quality management and pollutant-transport prediction in river–lake systems. To address this gap, this study investigates the confluence of the North and [...] Read more.
High-resolution in situ field measurements capturing seasonal 3D mixing dynamics at river confluences are scarce, yet this understanding is essential for effective water-quality management and pollutant-transport prediction in river–lake systems. To address this gap, this study investigates the confluence of the North and South Han Rivers in the Paldang Reservoir. We introduce and apply a novel mixing proximity index (MPI) to quantify the degree of mixing and water-mass origin based on 3D electrical conductivity and temperature data. Seasonal field campaigns, conducted with an acoustic Doppler current profiler and multi-parameter sensors, revealed distinct hydrodynamic behaviors: strong summer stratification suppressed vertical mixing; winter momentum asymmetry induced persistent flow separation despite minimal temperature differences; and spring conditions fostered rapid mixing, barring some residual unmixed deep layers. The MPI effectively delineated shear layers and identified unmixed water zones, providing an enhanced understanding of mixing dynamics beyond the capabilities of traditional tracer- or statistics-based metrics. These findings highlight the combined influence of density differences, tributary momentum, and dam operations on confluence mixing, offering practical insights for water-resource management and improving 3D hydrodynamic model validation. Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
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14 pages, 2398 KB  
Article
Intelligent Assessment of Landslide Impact Force Considering the Uncertainty of Strength Parameters
by Xinyi Hong, Weijie Zhang, Xin Wang, Hongxin Chen and Yongqi Xue
Water 2025, 17(24), 3595; https://doi.org/10.3390/w17243595 - 18 Dec 2025
Viewed by 315
Abstract
Accurately predicting the peak impact force exerted by landslides on bridge piers is crucial for evaluating structural safety. However, the reliability of such predictions is frequently undermined by the spatial variability and uncertainty inherent in soil and rock strength parameters. To quantify the [...] Read more.
Accurately predicting the peak impact force exerted by landslides on bridge piers is crucial for evaluating structural safety. However, the reliability of such predictions is frequently undermined by the spatial variability and uncertainty inherent in soil and rock strength parameters. To quantify the influence of this uncertainty, in this study, a three-dimensional numerical model of a landslide impacting bridge piers was developed using LS-DYNA software (version R11.0.0). A neural network was then trained on the peak impact forces simulated by the numerical model. Based on the neural network predictions, the impact mechanisms were categorized into two distinct modes, namely, a low-impact mode and a high-impact mode, for a comparative analysis. The results revealed statistically significant differences in soil parameters between these modes. Specifically, low-impact forces (F < 467 kN) were found to correlate with higher cohesion (18.5–24.9 kPa) and lower internal friction angles (15–22.4°). Conversely, high-impact forces (F ≥ 467 kN) were associated with lower cohesion (14.0–21.6 kPa) and higher internal friction angles (18.1–25.3°). This negative correlation highlights the decisive role that the combined uncertainty of strength parameters plays in predicting the peak impact force. Moreover, the surrogate model developed in this study effectively addresses the computational inefficiencies commonly associated with Monte Carlo simulations. This methodology provides a valuable tool for evaluating the vulnerability of infrastructure systems exposed to landslide hazards. Full article
(This article belongs to the Special Issue Intelligent Analysis, Monitoring and Assessment of Debris Flow)
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22 pages, 4565 KB  
Article
Removal of Cr(VI) from an Aqueous Solution via a Metal Organic Framework (Ce-MOF-808)
by Hongfei Zhang, Ming Zou, Haixin Zhang, Naoto Miyamoto and Naoki Kano
Water 2025, 17(24), 3594; https://doi.org/10.3390/w17243594 - 18 Dec 2025
Viewed by 443
Abstract
Hexavalent chromium (Cr(VI)) is a carcinogenic and highly mobile pollutant in aquatic environments. In this study, three cerium-based metal–organic frameworks (Ce-UiO-66, Ce-UiO-66-NO2, and Ce-MOF-808) were synthesized and evaluated for their ability to remove Cr(VI) from aqueous solutions. Among the frameworks studied, [...] Read more.
Hexavalent chromium (Cr(VI)) is a carcinogenic and highly mobile pollutant in aquatic environments. In this study, three cerium-based metal–organic frameworks (Ce-UiO-66, Ce-UiO-66-NO2, and Ce-MOF-808) were synthesized and evaluated for their ability to remove Cr(VI) from aqueous solutions. Among the frameworks studied, Ce-MOF-808 exhibited the highest adsorption capacity and was selected for detailed investigation. To elucidate its structure and adsorption behavior, Ce-MOF-808 was characterized using XRD, FT-IR, SEM-EDS, TG-DTA, XPS, and Zeta potential analyses. The zeta potential results showed that the adsorbent surface remained positively charged in the pH range of 2.8–8.6, enabling electrostatic attraction toward anionic chromate species. XPS further revealed valence transitions between Ce3+/Ce4+ and Cr(VI)/Cr(III), demonstrating the occurrence of partial redox transformation during adsorption. Batch experiments showed that the adsorption was strongly pH-dependent and favored acidic conditions (pH 2). The kinetics followed the pseudo-second-order model, whereas the isotherm data were better described by the Langmuir model, yielding a maximum adsorption capacity of 42.74 mg/g. Thermodynamic analysis indicated a spontaneous and exothermic process. Moreover, Ce-MOF-808 maintained high Cr(VI) uptake in real water samples, demonstrating its environmental applicability. Overall, Ce-MOF-808 is a promising redox-active adsorbent for efficient Cr(VI) removal in water treatment applications. Full article
(This article belongs to the Special Issue Water Quality Engineering and Wastewater Treatment, 4th Edition)
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20 pages, 18938 KB  
Article
Hydrological Analysis of the 2024 Flood in the Upper Biała Lądecka Sub-Basin in South Poland
by Jakub Izydorski and Oscar Herrera-Granados
Water 2025, 17(24), 3593; https://doi.org/10.3390/w17243593 - 18 Dec 2025
Viewed by 476
Abstract
The SCS-CN (Soil Conservation Service Curve Number) model is important for flood forecasting as it provides a relatively simple and widely used methodology for estimating the amount of surface runoff from a rainfall event, which is a crucial input in predicting flood volumes [...] Read more.
The SCS-CN (Soil Conservation Service Curve Number) model is important for flood forecasting as it provides a relatively simple and widely used methodology for estimating the amount of surface runoff from a rainfall event, which is a crucial input in predicting flood volumes and peaks in ungauged or data-scarce watersheds. Thus, the authors developed a hydrological model based on the SCS-CN curve methodology and GIS (Geographic Information Systems) to estimate the flood hydrograph in the upper parts of the Biała Lądecka River basin in Poland. The numerical model was calibrated based on the data available from the Polish Institute of Meteorology and Water Management (IMGW). The output of the model demonstrates the effect in the flood hydrograph at the town of Lądek-Zdrój. Additionally, hydraulic routing calculations were included to analyze the possible causes of the dam failure of the Stronie Śląskie reservoir in the year 2024. The main purpose of this study is to corroborate the influence of climate change on flood events and their consequences, as well as to assist in forecasting future catastrophic hydrological events and thus earlier adaptation and reinforce the infrastructure in our territories against future flooding. Full article
(This article belongs to the Special Issue Climate Change Adaptation in Water Resource Management)
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23 pages, 7300 KB  
Article
Advancing Hydrological Prediction with Hybrid Quantum Neural Networks: A Comparative Study for Mile Mughan Dam
by Erfan Abdi, Mohammad Taghi Sattari, Saeed Samadianfard and Sajjad Ahmad
Water 2025, 17(24), 3592; https://doi.org/10.3390/w17243592 - 18 Dec 2025
Viewed by 543
Abstract
Predicting dam inflow is critical for human life safety, water resource management, and hydroelectric power generation. While machine learning (ML) models address complex, nonlinear hydrological problems, quantum machine learning (QML) offers greater potential to overcome classical computational limits. This study compares a hybrid [...] Read more.
Predicting dam inflow is critical for human life safety, water resource management, and hydroelectric power generation. While machine learning (ML) models address complex, nonlinear hydrological problems, quantum machine learning (QML) offers greater potential to overcome classical computational limits. This study compares a hybrid quantum neural network (HQNN) with the following two classical models: bidirectional CNN-LSTM and support vector regression (SVR). These models were evaluated to predict monthly inflow to the Mile Mughan Dam, a transboundary hydroelectric and irrigation dam located on the Aras River between Azerbaijan and Iran, using a 14-year dataset (2010–2023) under two scenarios. In total, 70% of data was used for training and 30% for testing. The first scenario encompassed meteorological variables plus three months of inflow lags, and the second included inflow lags only. Model performance was assessed using Coefficient of Determination (R2), Root Mean Squared Error (RMSE), Nash–Sutcliffe efficiency (NSE), Mean Absolute Percentage Error (MAPE), and graphical plots. HQNN showed superior performance across all metrics. In Scenario 1, HQNN achieved R2 = 0.915, RMSE = 37.318 MCM, NSE = 0.908, MAPE = 8.343%; CNN-BiLSTM had R2 = 0.867, RMSE = 46.506 MCM, NSE = 0.858, MAPE = 10.795%; SVR had R2 = 0.846, RMSE = 52.372 MCM, NSE = 0.821, MAPE = 12.772%. In Scenario 2, HQNN maintained strong performance (R2 = 0.855, RMSE = 48.56 MCM, NSE = 0.845, MAPE = 9.979%) and outperformed CNN-BiLSTM (R2 = 0.810, RMSE = 56.126 MCM, NSE = 0.793, MAPE = 11.456%) and SVR (R2 = 0.801, RMSE = 60.336 MCM, NSE = 0.761, MAPE = 12.901%). In Scenario 1 and Scenario 2, HQNN increased the prediction accuracy by 19.76% and 13.47%, respectively, compared to the CNN-BiLSTM model. These results confirm HQNN’s reliability in both multivariate and univariate modeling. Full article
(This article belongs to the Special Issue Advances in AI, Numerical, and Experimental Approaches for Water Resources Applications)
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22 pages, 4820 KB  
Article
Iron-Coated Pine Bark as Biosorbents for Textile Wastewater Treatment: A Sustainable Approach
by Pedro Gonçalves, Ariana Pintor, Olivia S. G. P. Soares, Manuel F. R. Pereira, Cidália M. S. Botelho and Ricardo M. Ferreira
Water 2025, 17(24), 3591; https://doi.org/10.3390/w17243591 - 18 Dec 2025
Viewed by 358
Abstract
Dyes are widely used in textile processing and are frequently discharged without adequate treatment, posing risks to aquatic ecosystems through reduced water quality, toxicity to organisms, and long-term environmental degradation. To address the need for sustainable remediation solutions, this study investigated the use [...] Read more.
Dyes are widely used in textile processing and are frequently discharged without adequate treatment, posing risks to aquatic ecosystems through reduced water quality, toxicity to organisms, and long-term environmental degradation. To address the need for sustainable remediation solutions, this study investigated the use of pine bark (Pinus pinaster), an abundant forestry byproduct, as a low-cost biosorbent for textile dye removal. Powdered (<0.5 mm) and granular (>1 mm) bark fractions were washed, dried, and modified through iron impregnation (10 wt.% Fe) via sonication in an FeCl3·6H2O solution, with one iron-coated variant subsequently subjected to thermal treatment at 400 °C under nitrogen (1 h) and hydrogen (3 h). Adsorption performance was evaluated using synthetic effluents containing Sirius Blue, Astrazon Red, and Sirius Yellow, individually and as a ternary mixture (80 mg/L each), with added NaCl and NaHCO3 to simulate realistic conditions. Thermally treated granular iron-coated bark showed the highest removal efficiency, achieving >90% dye elimination within 24 h without detectable iron leaching, along with strong iron retention (~80%) and a 53% thermal-treatment yield. Maximum adsorption reached 15.51 mg/g at 5.0 g/L, while lower adsorbent doses increased capacity (26.8 mg/g) but reduced overall removal (~83%). Kinetic analysis was dose-dependent: the pseudo-first-order model provided the best fit at 5.0 g/L, reflecting the rapid approach to equilibrium, whereas the Elovich model fitted best at 2.5 g/L (R > 0.99), consistent with heterogeneous surface interactions under limited adsorbent availability. These results demonstrate the potential of thermally treated iron-coated pine bark as an efficient and sustainable biosorbent for textile wastewater treatment. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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22 pages, 3171 KB  
Article
Integrated Hydrogeochemical, Isotopic, and Geophysical Assessment of Groundwater Salinization Processes in the Samba Dia Coastal Aquifer (Senegal)
by Amadou Sarr, Seyni Ndoye, Axel L. Tcheheumeni Djanni, Mathias Diedhiou, Mapathe Ndiaye, Serigne Faye, Corinne Sabine Corbau, Arnaud Gauthier and Philippe Le Coustumer
Water 2025, 17(24), 3590; https://doi.org/10.3390/w17243590 - 18 Dec 2025
Viewed by 481
Abstract
This study provides a detailed assessment of groundwater salinization in the Quaternary aquifer of the Samba Dia region, Senegal, using an integrated approach that combines hydrochemical, stable isotopic (δ2H, δ18O), and electrical resistivity tomography (ERT) techniques. Fourteen high-resolution ERT [...] Read more.
This study provides a detailed assessment of groundwater salinization in the Quaternary aquifer of the Samba Dia region, Senegal, using an integrated approach that combines hydrochemical, stable isotopic (δ2H, δ18O), and electrical resistivity tomography (ERT) techniques. Fourteen high-resolution ERT profiles, along with comprehensive chemical and isotopic analyses, were performed to identify the main causes of salinity and their spatial distribution. Results show that groundwater salinization in the area is primarily driven by three mechanisms: seawater intrusion, surface salt leaching, and ion exchange. Hydrochemical facies evolution diagrams, ionic ratios, and isotopic signatures helped differentiate marine-influenced zones from inland salinization areas. ERT imaging also mapped the three-dimensional extent and geometry of saline interfaces, confirming zone-specific mixing of seawater and freshwater. The findings indicate that salinization of the coastal aquifer has worsened over the past twenty years, mainly due to human activities and climate variability. This study recommends a sustainable monitoring strategy to support aquifer management, focusing on accurately identifying vulnerable zones and enabling adaptive resource planning in semi-arid Senegal. Full article
(This article belongs to the Special Issue Research on Hydrogeology and Hydrochemistry: Challenges and Prospects)
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28 pages, 6649 KB  
Article
Resettlement Governance in Large-Scale Urban Water Projects: A Policy Lifecycle Perspective from the Danjiangkou Reservoir Case in China
by Xiaocao Ge, Qian Li, Shaojun Chen and Ziheng Shangguan
Water 2025, 17(24), 3589; https://doi.org/10.3390/w17243589 - 18 Dec 2025
Viewed by 448
Abstract
Using the Danjiangkou Reservoir resettlement as a case study, this research adopts a policy lifecycle perspective to examine the evolutionary mechanisms of livelihood transformation and institutional adaptation under large-scale hydraulic development. The findings reveal that China’s resettlement governance is not merely an economic [...] Read more.
Using the Danjiangkou Reservoir resettlement as a case study, this research adopts a policy lifecycle perspective to examine the evolutionary mechanisms of livelihood transformation and institutional adaptation under large-scale hydraulic development. The findings reveal that China’s resettlement governance is not merely an economic practice of resource redistribution and livelihood reconstruction but a deeper process of institutional learning and social reconfiguration. The transformation of Danjiangkou migrants—from administrative dependence to self-organized recovery and finally to development empowerment—reflects a structural shift in governance logic from control-oriented mobilization to collaborative and inclusive modernization. The study elucidates the dynamic interaction between institutional supply and social agency, arguing that the state acts not only as a resource provider but as an institutional recalibrator that fosters endogenous governance capacity through social self-organization. The identity transformation of migrants—from excluded subjects to integrated citizens—demonstrates that recognition, participation, and social capital are central to achieving social justice and sustainable governance. Practically, sustainable resettlement requires institutional flexibility and social empowerment, emphasizing long-term capacity building over short-term relief. The Danjiangkou experience reveals the deeper logic of Chinese modernization—a transition from control to collaboration, from survival to development, and from outsiders to citizens—offering valuable insights for equitable and resilient resettlement governance. Full article
(This article belongs to the Special Issue Policy Innovation and Integrated Governance for Sustainable Urban Water Management)
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20 pages, 5145 KB  
Article
Mechanisms of Karst Ground Collapse Under Groundwater Fluctuations: Insights from Physical Model Test and Numerical Simulation
by Yongchun Luo, Ling Yang and Yujian Xing
Water 2025, 17(24), 3588; https://doi.org/10.3390/w17243588 - 18 Dec 2025
Viewed by 424
Abstract
Karst ground collapses triggered by groundwater fluctuations pose a significant threat to the safety and stability of tunnel engineering. In this study, taking the Yakouzai Tunnel as a case, a combination of physical model tests and numerical simulations was employed to investigate the [...] Read more.
Karst ground collapses triggered by groundwater fluctuations pose a significant threat to the safety and stability of tunnel engineering. In this study, taking the Yakouzai Tunnel as a case, a combination of physical model tests and numerical simulations was employed to investigate the mechanisms of groundwater-induced karst collapse. A self-designed physical model device reproduced the full process of soil cavity initiation, expansion, and roof failure. Numerical simulations were further conducted to analyze the evolution of pore water pressure, stress distribution, and displacement under both groundwater drawdown and rise conditions. The results indicate that concentrated seepage erosion at the cavity arch foot is the primary driver of cavity initiation, with cyclic suffusion promoting its progressive expansion. Rapid groundwater drawdown generates vacuum suction that markedly reduces roof stability and may induce sudden collapse, whereas groundwater rise, although providing partial support to the roof, intensifies shear stress concentration and leaves the cavity in an unstable state. The findings highlight that karst collapse is governed by the coupled effects of seepage erosion, arching degradation, differential settlement, and vacuum suction, providing a scientific basis for monitoring, prediction, and mitigation of karst hazards. Full article
(This article belongs to the Special Issue Effects of Groundwater and Surface Water on the Natural Geo-Hazards, 2nd Edition)
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14 pages, 4164 KB  
Article
Quantifying Moisture Source Contributions to Diverse Precipitation Events over the Tibetan Plateau
by Beiming Kang, Yan Ren, Yang Shi, Xiaomei Zhu, Jingjing Huang and Wenwen Bai
Water 2025, 17(24), 3587; https://doi.org/10.3390/w17243587 - 17 Dec 2025
Viewed by 500
Abstract
The Tibetan Plateau (TP), known as the “Asian Water Tower,” plays a critical role in regional and global climate systems. However, water resource sustainability is increasingly threatened under climate change and growing demand. While moisture transport mechanisms for summer monsoon and extreme precipitation [...] Read more.
The Tibetan Plateau (TP), known as the “Asian Water Tower,” plays a critical role in regional and global climate systems. However, water resource sustainability is increasingly threatened under climate change and growing demand. While moisture transport mechanisms for summer monsoon and extreme precipitation events have been widely studied, the understanding of moisture sources for different precipitation intensities remains limited. This study employs the Lagrangian-based HYSPLIT model to quantify moisture source contributions to three types of precipitation events—extreme precipitation (EP), moderate precipitation (MP), and light precipitation (LP)—over the TP from 1979 to 2020. Using trajectory clustering and moisture source diagnostics, we identify dominant transport pathways and their relative contributions. Results show that EP and MP events are primarily influenced by the Indian monsoon, with the Bay of Bengal and Arabian Sea as key sources, while LP events are dominated by westerlies. The western pathway contributes 15.55%, 36.28%, and 59.59% to EP, MP, and LP events, respectively, whereas the monsoon pathway accounts for 40.56%, 28.23%, and 31.21%. External moisture sources dominate across all event types (average 87.7%), with local recycling contributions decreasing from LP (12.90%) to EP (11.55%). These findings enhance the understanding of moisture–precipitation coupling mechanisms over the TP and provide a scientific basis for water resource management under changing climate conditions. Full article
(This article belongs to the Section Hydrology)
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18 pages, 3083 KB  
Article
Optical Analysis Based on UV Absorption Spectrum for Monitoring Total Organic Carbon and Nitrate Nitrogen in River Water
by Minhan Kim, Seongwook Park, Byoungsun Park, Hongseok Kim, Taeyong Woo, Sangyoun Kim, Junghee Jang and Changkyoo Yoo
Water 2025, 17(24), 3586; https://doi.org/10.3390/w17243586 - 17 Dec 2025
Viewed by 630
Abstract
The global deterioration of water quality due to climate change and industrialization has intensified the need for real-time monitoring systems. In South Korea’s automated water quality monitoring networks, measuring total organic carbon (TOC) and nitrate nitrogen (NO3-N) as a proxy for [...] Read more.
The global deterioration of water quality due to climate change and industrialization has intensified the need for real-time monitoring systems. In South Korea’s automated water quality monitoring networks, measuring total organic carbon (TOC) and nitrate nitrogen (NO3-N) as a proxy for total nitrogen (TN) is critical; however, conventional analytical instruments face limitations such as high costs, long analysis times, and the need for chemical reagents. In this study, we developed and evaluated a simultaneous TOC and NO3-N measurement method using HASM-4000, a domestically developed optical sensor based on ultraviolet (UV) absorption spectroscopy. The sensor measures absorbance at 254 nm (TOC) and 220 nm (NO3-N) based on the Beer–Lambert law, with signal processing techniques including optical power compensation (OPC) and Binning–Interpolation (BinInterp) applied to enhance measurement accuracy. Calibration using standard solutions demonstrated excellent linear correlations (R2 > 0.99) between actual and estimated concentrations for both TOC and NO3-N, with accuracy and reproducibility validated against standard methods under laboratory conditions. However, performance degradation was observed in turbid mixed samples due to the optical limitations of the 10 mm pathlength, suggesting the need for future improvements such as adopting a 5 mm pathlength and upgrading optical components. The HASM-4000 sensor enables real-time measurement without a reagent, and preliminary testing with river water samples demonstrates its potential to advance Korea’s water quality monitoring infrastructure by reducing dependence on foreign technologies and facilitating network expansion with cost-effective domestic solutions. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
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20 pages, 8586 KB  
Article
Multi-Objective Optimization for Irrigation Canal Water Allocation and Intelligent Gate Control Under Water Supply Uncertainty
by Qingtong Cai, Xianghui Xu, Mo Li, Xingru Ye, Wuyuan Liu, Hongda Lian and Yan Zhou
Water 2025, 17(24), 3585; https://doi.org/10.3390/w17243585 - 17 Dec 2025
Viewed by 473
Abstract
Open-channel irrigation systems often face constraints due to water supply uncertainty and insufficient gate control precision. This study proposes an integrated framework for canal water allocation and gate control that combines interval-based uncertainty analysis with intelligent optimization to address these challenges. First, we [...] Read more.
Open-channel irrigation systems often face constraints due to water supply uncertainty and insufficient gate control precision. This study proposes an integrated framework for canal water allocation and gate control that combines interval-based uncertainty analysis with intelligent optimization to address these challenges. First, we predict the inflow process using an Auto-Regressive Integrated Moving Average (ARIMA) model and quantify the range of water supply uncertainty through Maximum Likelihood Estimation (MLE). Based on these results, we formulate a bi-objective optimization model to minimize both main canal flow fluctuations and canal network seepage losses. We solve the model using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to obtain Pareto-optimal water allocation schemes under uncertain inflow conditions. This study also designs a Fuzzy Proportional–Integral–Derivative (Fuzzy PID) controller. We adaptively tune its parameters using the Particle Swarm Optimization (PSO) algorithm, which enhances the dynamic response and operational stability of open-channel gate control. We apply this framework to the Chahayang irrigation district. The results show that total canal seepage decreases by 1.21 × 107 m3, accounting for 3.9% of the district’s annual water supply, and the irrigation cycle is shortened from 45 days to 40.54 days, improving efficiency by 9.91%. Compared with conventional PID control, the PSO-optimized Fuzzy PID controller reduces overshoot by 4.84%, and shortens regulation time by 39.51%. These findings indicate that the proposed method can significantly improve irrigation water allocation efficiency and gate control performance under uncertain and variable water supply conditions. Full article
(This article belongs to the Section Water, Agriculture and Aquaculture)
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18 pages, 4452 KB  
Article
Identification of Nitrate Sources in the Upper Reaches of Xin’an River Basin Based on the MixSIAR Model
by Benjie Luan, Ai Wang, Zhiguo Huo, Xuqing Lin and Man Zhang
Water 2025, 17(24), 3584; https://doi.org/10.3390/w17243584 - 17 Dec 2025
Viewed by 539
Abstract
The upper Xin’an River basin serves as a critical ecological barrier and water-conservation area for the Yangtze River Delta. However, with rapid economic development, nitrogen pollution in the surface waters of this region has become increasingly pronounced. This study analyzed river water samples [...] Read more.
The upper Xin’an River basin serves as a critical ecological barrier and water-conservation area for the Yangtze River Delta. However, with rapid economic development, nitrogen pollution in the surface waters of this region has become increasingly pronounced. This study analyzed river water samples collected on four occasions from the upper Xin’an River basin for ammonium (NH4+–N), nitrate-nitrogen (NO3−–N), total nitrogen (TN), and nitrate isotopic (δ15N–NO3− and δ18O–NO3−). The sources of nitrate (NO3−) were apportioned using the MixSIAR stable-isotope mixing model, and the spatial distribution of these sources across the basin was characterized. Across the four sampling rounds, the mean TN concentration exceeded 1.3 mg/L, with NO3−–N accounting for over 45% of TN, indicating that nitrate was the dominant inorganic nitrogen species. The δ15N–NO3− values ranged from 2.17‰ to 13.0‰, with mean values following the order summer > winter > autumn > spring. The δ18O–NO3− values varied from −5.20‰ to −3.48‰, and the average value showed a completely opposite seasonal variation pattern to that of δ15N–NO3−. Process-based analysis of nitrogen transformations revealed that nitrification predominates during nitrate transport and transformation, whereas denitrification is comparatively weak. MixSIAR-based estimates indicate marked seasonal differences in the source composition of nitrate pollution in the upper Xin’an River basin; NO3− derives primarily from soil nitrogen (SN) and livestock/sewage manure nitrogen (LSN). LSN was the dominant contributor in spring and summer (49.2% and 59.9%, respectively). SN dominated in autumn (49.2%) and winter (54.1%). Fertilizer nitrogen (FN) contributed more during summer and autumn, when fertilization is concentrated and rainfall is higher. Atmospheric deposition (AN) contributed approximately 1% across all seasons and was thus considered negligible. These findings provide a scientific basis for source control of nitrogen pollution and water-quality management in the upper Xin’an River. Full article
(This article belongs to the Section Water Quality and Contamination)
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23 pages, 4771 KB  
Article
Physics-Assisted Deep Learning Model for Improved Construction Performance Monitoring of Cutter Suction Dredger
by Ruizhe Liu, Guoqing Yu, Kunpeng Shi, Yong Chen and Qiubing Ren
Water 2025, 17(24), 3583; https://doi.org/10.3390/w17243583 - 17 Dec 2025
Viewed by 297
Abstract
Construction monitoring of cutter suction dredgers (CSD) is of great significance in ensuring dredging efficiency. However, existing models have not taken into account the physical constraints in the physical system of a CSD, which limits further improvements in prediction accuracy. To this end, [...] Read more.
Construction monitoring of cutter suction dredgers (CSD) is of great significance in ensuring dredging efficiency. However, existing models have not taken into account the physical constraints in the physical system of a CSD, which limits further improvements in prediction accuracy. To this end, this paper proposes a physics-assisted deep learning model for improved construction performance monitoring of CSD. The data-driven Lossu and the physics-driven Lossr are combined to form an improved physics-assisted loss function (PALF). And then, a physics-assisted deep learning (PADL) model incorporating PALF is developed to predict the construction productivity. In the case application, evaluation across three deep learning models confirms the feasibility and effectiveness of PALF for productivity prediction. The results show that the PALF-based PADL model achieves markedly improved prediction accuracy, reducing the mean absolute error by 20.33–54.33%. Across six training-set sizes (1000–11,000 samples), the improvement is larger in small-data scenarios, highlighting PADL’s strong low-sample robustness. The proposed model can effectively complement physical sensors in monitoring construction parameters and provide reliable decision support for assessing the operational state of CSDs. Full article
(This article belongs to the Special Issue Water Engineering Safety and Management, 2nd Edition)
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25 pages, 6352 KB  
Article
Integrated Stochastic Framework for Drought Assessment and Forecasting Using Climate Indices, Remote Sensing, and ARIMA Modelling
by Majed Alsubih, Javed Mallick, Hoang Thi Hang, Mansour S. Almatawa and Vijay P. Singh
Water 2025, 17(24), 3582; https://doi.org/10.3390/w17243582 - 17 Dec 2025
Viewed by 392
Abstract
This study presents an integrated stochastic framework for assessing and forecasting drought dynamics in the western Bhagirathi–Hooghly River Basin, encompassing the districts of Bankura, Birbhum, Burdwan, Medinipur, and Purulia. Employing multiple probabilistic and statistical techniques, including the gamma-based standardized precipitation index (SPI), effective [...] Read more.
This study presents an integrated stochastic framework for assessing and forecasting drought dynamics in the western Bhagirathi–Hooghly River Basin, encompassing the districts of Bankura, Birbhum, Burdwan, Medinipur, and Purulia. Employing multiple probabilistic and statistical techniques, including the gamma-based standardized precipitation index (SPI), effective drought index (EDI), rainfall anomaly index (RAI), and the auto-regressive integrated moving average (ARIMA) model, the research quantifies spatio-temporal variability and projects drought risk under non-stationary climatic conditions. The analysis of century-long rainfall records (1905–2023), coupled with LANDSAT-derived vegetation and moisture indices, reveals escalating drought frequency and severity, particularly in Purulia, where recurrent droughts occur at roughly four-year intervals. Stochastic evaluation of rainfall anomalies and SPI distributions indicates significant inter-annual variability and complex temporal dependencies across all districts. ARIMA-based forecasts (2025–2045) suggest persistent negative SPI trends, with Bankura and Purulia exhibiting heightened drought probability and reduced predictability at longer timescales. The integration of remote sensing and time-series modelling enhances the robustness of drought prediction by combining climatic stochasticity with land-surface responses. The findings demonstrate that a hybrid stochastic modelling approach effectively captures uncertainty in drought evolution and supports climate-resilient water resource management. This research contributes a novel, region-specific stochastic framework that advances risk-based drought assessment, aligning with the broader goal of developing adaptive and probabilistic environmental management strategies under changing climatic regimes. Full article
(This article belongs to the Special Issue Drought Evaluation Under Climate Change Condition)
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22 pages, 6429 KB  
Article
Multi-Scale Experiments and Mechanistic Insights into Hydro-Physical Properties of Saturated Deep-Sea Sediments in the South China Sea
by Yan Feng, Qiunan Chen, Guangping Liu, Xiaocheng Huang, Zengliang Wang, Wei Hu, Bingchu Chen, Shunkai Liu and Xiaodi Xu
Water 2025, 17(24), 3581; https://doi.org/10.3390/w17243581 - 17 Dec 2025
Viewed by 467
Abstract
Deep-sea-resource development and marine engineering represent cutting-edge global research priorities. As a typical deep-sea region in the Western Pacific, the physical–mechanical properties of the South China Sea’s deep-sea sediments have critical implications for regional and global deep-sea engineering design and the safety assessments [...] Read more.
Deep-sea-resource development and marine engineering represent cutting-edge global research priorities. As a typical deep-sea region in the Western Pacific, the physical–mechanical properties of the South China Sea’s deep-sea sediments have critical implications for regional and global deep-sea engineering design and the safety assessments of resource exploitation. However, due to extreme environmental conditions and sampling technology limitations, studies on the mechanical behavior and microstructural control mechanisms of sediments in complex marine environments exceeding 2000 m in depth remain insufficient worldwide, hindering precise engineering design and risk management. This study systematically investigates the physical–mechanical properties, microstructure, and mechanical behavior of intact sediments acquired at a depth of 2060 m in the South China Sea. Through physical property tests, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), one-dimensional consolidation, and triaxial shear tests, combined with comparisons with nearshore soft soils and other deep-sea sediments, we acquired the following results: The sediments primarily consist of muscovite, quartz, and calcite. Triaxial shear tests revealed initial dilation followed by shear consolidation, reaching critical conditions with an effective cohesion of 19.58 kPa and an effective internal friction angle of 27.32°. One-dimensional consolidation tests indicated a short principal consolidation time, wherein the consolidation coefficient first decreased under loading before slowly increasing, while the secondary consolidation coefficient stabilized after vertical pressure exceeded 400 kPa. The research results not only provide a direct reference for designing deep-sea engineering projects in the South China Sea, calculating the penetration resistance of deep-sea drilling rigs, and predicting the foundation settlement of offshore wind power but also furnish typical cases and key data support for the study of the mechanical properties of global deep-sea high-organic-matter sediments and engineering applications. Full article
(This article belongs to the Special Issue Advances in Water Related Geotechnical Engineering)
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16 pages, 1514 KB  
Article
IoT-Controlled Upflow Filtration Achieves High Removal of Fine Particles and Phosphorus in Stormwater
by Kyungjin Han, Dongyoung Choi, Jeongdong Choi and Junho Lee
Water 2025, 17(24), 3580; https://doi.org/10.3390/w17243580 - 17 Dec 2025
Viewed by 431
Abstract
Urban stormwater runoff, particularly during first-flush events, carries high loads of fine suspended solids and phosphorus that are difficult to remove with conventional best management practices (BMPs). This study developed and evaluated a laboratory-scale high-efficiency up-flow filtration system with Internet of Things (IoT)-based [...] Read more.
Urban stormwater runoff, particularly during first-flush events, carries high loads of fine suspended solids and phosphorus that are difficult to remove with conventional best management practices (BMPs). This study developed and evaluated a laboratory-scale high-efficiency up-flow filtration system with Internet of Things (IoT)-based autonomous control. The system employed 20 mm fiber-ball media in a modular dual-stage up-flow configuration with optimized coagulant dosing to target fine particles (<3 μm) and total phosphorus (TP). Real-time turbidity and pressure monitoring via sensor networks connected to a microcontroller enabled wireless data logging and automated backwash initiation when thresholds were exceeded. Under manual operation, the two-stage filter achieved removals of 96.6% turbidity, 98.8% suspended solids (SS), and 85.6% TP while maintaining head loss below 10 cm. In IoT-controlled single-stage runs with highly polluted influent (turbidity ~400 NTU, SS > 1000 mg/L, TP ~1.6 mg/L), the system maintained >90% SS and ~58% TP removal with stable head loss (~8 cm) and no manual intervention. Turbidity correlated strongly with SS (R2 ≈ 0.94) and TP (R2 ≈ 0.87), validating its use as a surrogate control parameter. Compared with conventional BMPs, the developed filter demonstrated superior solids capture, competitive phosphorus removal, and the novel capability of real-time autonomous operation, providing proof-of-concept for next-generation smart BMPs capable of meeting regulatory standards while reducing maintenance. Full article
(This article belongs to the Section Urban Water Management)
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30 pages, 12551 KB  
Article
Numerical Groundwater Flow Modeling in a Tropical Aquifer Under Anthropogenic Pressures: A Case Study in the Middle Magdalena Valley, Colombia
by Boris Lora-Ariza, Luis Silva Vargas, Juan Pescador, Mónica Vaca, Juan Landinez, Adriana Piña and Leonardo David Donado
Water 2025, 17(24), 3579; https://doi.org/10.3390/w17243579 - 17 Dec 2025
Viewed by 750
Abstract
Groundwater is one of the main sources of water supply in tropical developing countries; however, its integrated management is often constrained by limited hydrogeological information and increasing anthropogenic pressures on aquifer systems. This study presents the numerical modeling of groundwater flow in the [...] Read more.
Groundwater is one of the main sources of water supply in tropical developing countries; however, its integrated management is often constrained by limited hydrogeological information and increasing anthropogenic pressures on aquifer systems. This study presents the numerical modeling of groundwater flow in the Neogene–Quaternary aquifer system of the Middle Magdalena Valley (Colombia), focusing on the rural area of Puerto Wilches, which is characterized by strong surface–groundwater interactions, particularly with the Yarirí wetland and the Magdalena River. A three-dimensional model was implemented and calibrated in FEFLOW v.8.1 under steady-state and transient conditions, integrating both primary and secondary data. The dataset included piezometric levels measured with water level meters and automatic loggers, hydrometeorological records, 21 physicochemical and microbiological parameters analyzed in 45 samples collected during three field campaigns under contrasting hydrological conditions, 79 pumping tests, detailed lithological columns from drilled wells, and complementary geological and geophysical models. The results indicate a predominant east–west groundwater flow from the Eastern Cordillera toward the Magdalena River, with seasonal recharge and discharge patterns controlled by the bimodal rainfall regime. Microbiological contamination (total coliforms in 69% of groundwater samples) and nitrate concentrations above 10 mg/L in 21% of wells were detected, mainly due to agricultural fertilizers and domestic wastewater infiltration. Particle tracking revealed predominantly horizontal flow paths, with transit times of up to 800 years in intermediate units of the Real Group and around 60 years in shallow Quaternary deposits, highlighting the differential vulnerability of the system to contamination. These findings provide scientific foundations for strengthening integrated groundwater management in tropical regions under agroindustrial and hydrocarbon pressures and emphasize the need to consolidate monitoring networks, promote sustainable agricultural practices, and establish preventive measures to protect groundwater quality. Full article
(This article belongs to the Special Issue Groundwater Flow and Contaminant Transport Modeling)
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3 pages, 125 KB  
Editorial
Hydro-Economic Models for Managing Sustainable Water Resources
by Joaquín Melgarejo and Borja Montano
Water 2025, 17(24), 3578; https://doi.org/10.3390/w17243578 - 17 Dec 2025
Viewed by 300
Abstract
Understanding water in the twenty-first century requires acknowledging that it can no longer be analysed from a single disciplinary perspective [...] Full article
(This article belongs to the Special Issue Hydro-Economic Models for Sustainable Water Resources Management)
20 pages, 3036 KB  
Article
Optimization of Auxenochlorella pyrenoidosa Photobioreactor Parameters for Low Carbon-to-Nitrogen Ratio Wastewater Treatment: Effects of Inoculum Density, Aeration, Light Intensity, and Photoperiod
by Lin Zhao, Yuwei Xu, Tian Tian, Yifan Zhang, Guanqin Huang and Jun Tang
Water 2025, 17(24), 3577; https://doi.org/10.3390/w17243577 - 17 Dec 2025
Viewed by 463
Abstract
Treating wastewater with a low carbon-to-nitrogen (C/N) ratio remains a major challenge for conventional biological processes because insufficient organic carbon limits heterotrophic denitrification. To address this issue, microalgae-based photobioreactors offer a sustainable alternative that couples nutrient removal with biomass valorization. This study systematically [...] Read more.
Treating wastewater with a low carbon-to-nitrogen (C/N) ratio remains a major challenge for conventional biological processes because insufficient organic carbon limits heterotrophic denitrification. To address this issue, microalgae-based photobioreactors offer a sustainable alternative that couples nutrient removal with biomass valorization. This study systematically evaluated the effects of four key operational parameters—initial inoculum density, aeration rate, light intensity, and photoperiod—on nutrient removal, biomass productivity, and metabolite accumulation of Auxenochlorella pyrenoidosa (A. pyrenoidosa) treating synthetic low C/N wastewater. Optimal operating conditions were identified as an initial OD680 of 0.1, aeration rate of 2 L air min−1, light intensity of 112 μmol m−2 s−1, and a 16L:8D photoperiod. Under these conditions, the photobioreactor achieved 86.35% total nitrogen and 98.43% total phosphorus removal within 11 days while producing biomass rich in proteins, polysaccharides, and lipids. Metagenomic analysis revealed a metabolic transition from denitrification-driven pathways during early operation to assimilation-dominated nitrogen metabolism under optimized conditions, emphasizing the synergistic interactions within algal–bacterial consortia. These findings demonstrate that optimized A. pyrenoidosa-based photobioreactors can effectively recover nutrients and produce valuable biomass, offering a viable and sustainable solution for the treatment of low C/N wastewater. Full article
(This article belongs to the Topic Advanced Processes and Technologies for Wastewater: Collection, Treatment, and Resource)
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27 pages, 6816 KB  
Article
Experimental Evaluation of the Performance of a Flat Sheet Reverse Osmosis Membrane Under Variable and Intermittent Operation Emulating a Photovoltaic-Driven Desalination System
by Evangelos Dimitriou, Dimitrios Loukatos, Konstantinos G. Arvanitis and George Papadakis
Water 2025, 17(24), 3576; https://doi.org/10.3390/w17243576 - 16 Dec 2025
Viewed by 516
Abstract
The integration of Reverse Osmosis (RO) desalination with Renewable Energy (RE) sources offers a sustainable approach to freshwater production, particularly in remote and off-grid regions. However, the variable and intermittent output of RE power can cause operational instability that affects membrane performance and [...] Read more.
The integration of Reverse Osmosis (RO) desalination with Renewable Energy (RE) sources offers a sustainable approach to freshwater production, particularly in remote and off-grid regions. However, the variable and intermittent output of RE power can cause operational instability that affects membrane performance and system reliability. This study experimentally evaluated a flat sheet seawater RO membrane under variable conditions emulating a Photovoltaic (PV)-powered system over three days. Three scenarios were examined: (i) steady full-load operation representing PV with battery storage, (ii) variable operation representing sunny-day PV output, and (iii) highly variable operation representing cloudy-day PV output. A Variable Frequency Drive (VFD) regulated by an Arduino microcontroller adjusted high-pressure pump operation in real time to replicate power fluctuations without energy storage. Each scenario operated for eight hours per day and was tested with and without end-of-day rinsing. Under the highly variable cloudy-day scenario without rinsing, water permeability decreased by 37%, salt rejection decreased by 18%, and membrane resistance increased by 37%, indicating compaction and fouling effects. Fourier Transform Infrared Spectroscopy with Attenuated Total Reflectance (FTIR-ATR) confirmed structural changes in membranes exposed to fluctuating conditions. These results highlight the need for improved operational strategies to protect membrane longevity in RE-powered desalination systems. Full article
(This article belongs to the Special Issue The Future of Desalination: Sustainable and Energy-Efficient Solutions Through Membrane Innovation)
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17 pages, 3983 KB  
Article
Applicability of the HC-SURF Dual Drainage Model for Urban Flood Forecasting: A Quantitative Comparison with PC-SWMM and InfoWorks ICM
by Sang-Bo Sim and Hyung-Jun Kim
Water 2025, 17(24), 3575; https://doi.org/10.3390/w17243575 - 16 Dec 2025
Viewed by 352
Abstract
This study evaluated the applicability of the dual drainage model, Hyper Connected–Solution for Urban Flood (HC-SURF), for real-time urban flood forecasting. The model was applied to the extreme rainfall event of August 2022 in the Sillim and Daerim drainage basins in Seoul. Its [...] Read more.
This study evaluated the applicability of the dual drainage model, Hyper Connected–Solution for Urban Flood (HC-SURF), for real-time urban flood forecasting. The model was applied to the extreme rainfall event of August 2022 in the Sillim and Daerim drainage basins in Seoul. Its accuracy and computational efficiency were quantitatively compared with those of two widely used commercial models, the Personal Computer Storm Water Management Model (PC-SWMM) and InfoWorks Integrated Catchment Modelling (ICM). Accuracy was assessed by measuring spatial agreement with observed inundation trace maps using binary indicators, including the Critical Success Index (CSI), Probability of Detection (POD), and False Alarm Ratio (FAR). Computational efficiency was evaluated by comparing simulation times under identical conditions. In terms of accuracy against observations, HC-SURF achieved CSI values ranging from 0.26 to 0.45, with POD values from 0.37 to 0.81 and FAR values from 0.49 to 0.53 across the two basins. In inter-model comparisons, the model showed high hydraulic consistency, demonstrating CSI values between 0.72 and 0.88, POD between 0.82 and 0.99, and FAR between 0.08 and 0.15. In terms of computational efficiency, HC-SURF reduced calculation times by approximately 9% and 44% compared with InfoWorks ICM and PC-SWMM, respectively, for a 48 h simulation. The model also completed a 6 h rainfall simulation in approximately 8 min, meeting the lead time requirements for rapid urban flood forecasting. Overall, these findings show that HC-SURF effectively balances simulation accuracy with computational efficiency, demonstrating its suitability for real-time urban flood forecasting. Full article
(This article belongs to the Section Urban Water Management)
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21 pages, 2101 KB  
Article
Probabilistic Prediction of Local Scour at Bridge Piers with Interpretable Machine Learning
by Jaemyeong Choi, Jongyeong Kim, Soonchul Kwon and Taeyoon Kim
Water 2025, 17(24), 3574; https://doi.org/10.3390/w17243574 - 16 Dec 2025
Viewed by 410
Abstract
Local pier scour remains one of the leading causes of bridge failure, calling for predictions that are both accurate and uncertainty-aware. This study develops an interpretable data-driven framework that couples CatBoost (Categorial Gradient Boosting) for deterministic point prediction with NGBoost (Natural Gradient Boosting) [...] Read more.
Local pier scour remains one of the leading causes of bridge failure, calling for predictions that are both accurate and uncertainty-aware. This study develops an interpretable data-driven framework that couples CatBoost (Categorial Gradient Boosting) for deterministic point prediction with NGBoost (Natural Gradient Boosting) for probabilistic prediction. Both models are trained on a laboratory dataset of 552 measurements of local scour at bridge piers using non-dimensional inputs (y/b, V/Vc, b/d50, Fr). Model performance was quantitatively evaluated using standard regression metrics, and interpretability was provided through SHAP (Shapley Additive Explanations) analysis. Monte Carlo–based reliability analysis linked the predicted scour depths to a reliability index β and exceedance probability through a simple multiplicative correction factor. On the held-out test set, CatBoost offers slightly higher point-prediction accuracy, while NGBoost yields well-calibrated prediction intervals with empirical coverages close to the nominal 68% and 95% levels. This framework delivers accurate, interpretable, and uncertainty-aware scour estimates for target-reliability, risk-informed bridge design. Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
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17 pages, 5950 KB  
Article
Nonlinear Water Waves Induced by Vertical Disturbances Through a Navier–Stokes Solver with the Implementation of the Immersed Boundary Method
by Hai-Ping Ma and Hong-Xia Zhang
Water 2025, 17(24), 3573; https://doi.org/10.3390/w17243573 - 16 Dec 2025
Viewed by 428
Abstract
Nonlinear water waves (NWWs) can be generated by the vertical bottom disturbance, which represents the conceptual processes of the rise of seabed rupture under seismic loads. To explore the correlation between the disturbance parameters and the wave features, a Reynolds-averaged Navier–Stokes (RANS) model [...] Read more.
Nonlinear water waves (NWWs) can be generated by the vertical bottom disturbance, which represents the conceptual processes of the rise of seabed rupture under seismic loads. To explore the correlation between the disturbance parameters and the wave features, a Reynolds-averaged Navier–Stokes (RANS) model is applied, with the flow turbulence and fluid–structure interaction (FSI) being resolved by the k–ɛ model and the immersed boundary method (IBM), respectively. The free surface is tracked using the volume of fluid (VOF) method. After validating against the theoretical solutions and experimental results, the effects of disturbance duration and bulk on the wave features at the source region (the generation stage) and offshore direction (the propagation stage) are systematically discussed. The fixed maximal vertical displacement is considered, with four moving durations and five disturbance widths being simulated, resulting in four disturbance velocities and five disturbance bulks. The results indicate that the proposed RANS model can accurately create various wave patterns (including the linear, solitary, and tsunami-like waves) generated by bottom disturbances. Special attentions are paid to the tsunami-like wave. The wave evolution exhibits strong dependence on disturbance duration and width, with shorter durations triggering earlier soliton fission and longer widths accelerating phase celerity. These findings highlight the critical role of disturbance parameters in governing soliton formation and energy propagation patterns, which are vital in disaster forecasting. Full article
(This article belongs to the Special Issue Coastal Engineering and Fluid–Structure Interactions)
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16 pages, 5009 KB  
Article
Groundwater Storage Changes Derived from GRACE-FO Using In Situ Data for Practical Management
by Hongbo Liu, Jianchong Sun, Litang Hu, Shinan Tang, Fei Chen, Junchao Zhang and Zhenyuan Zhu
Water 2025, 17(24), 3572; https://doi.org/10.3390/w17243572 - 16 Dec 2025
Viewed by 515
Abstract
The ongoing global decline in groundwater levels poses significant challenges for sustainable water management. Satellite gravity missions, such as the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), provide valuable estimates of groundwater storage changes at regional scales. However, the relatively coarse spatial resolution [...] Read more.
The ongoing global decline in groundwater levels poses significant challenges for sustainable water management. Satellite gravity missions, such as the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), provide valuable estimates of groundwater storage changes at regional scales. However, the relatively coarse spatial resolution of these satellite data limits their direct applicability to local groundwater management. In this study, we address this limitation for China by analyzing groundwater monitoring data from 108 cities with shallow groundwater use and 37 cities with deep groundwater use from the period 2019–2022, integrating in situ groundwater level records, official monitoring reports, monthly dynamic data, and GRACE-FO-derived groundwater storage estimates. Our findings reveal rapid groundwater depletion in northern China, especially in Xinjiang and Hebei Provinces. Fluctuations in shallow groundwater levels in Beijing and Jiangsu are closely related to precipitation variability. For deep aquifer regions, GRACE-FO-derived groundwater storage changes show a moderate Pearson correlation coefficient of 0.45 and groundwater level variations. Regional analysis for 2019–2021 in the Northeast Plain and the Huang–Huai–Hai Basin indicates better agreement between satellite-derived storage and groundwater levels, with a Pearson correlation coefficient of 0.58 in the Huang–Huai–Hai Basin. Groundwater level dynamics are strongly influenced by both precipitation and pumping, with an approximate three-month lag between precipitation events and groundwater storage responses. Overall, satellite gravity data are suitable for use in regional groundwater assessment and could serve as valuable indicators in areas with intensive deep groundwater exploitation. To enable fine-scale groundwater management, future work should focus on improving the spatial resolution through downscaling and other advanced techniques. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
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32 pages, 7211 KB  
Article
Risk Assessment of Roof Water Inrush in Shallow Buried Thick Coal Seam Using FAHP-CV Comprehensive Weighting Method: A Case Study of Guojiawan Coal Mine
by Chao Liu, Xiaoyan Chen, Zekun Li, Jun Hou, Jinjin Tian and Dongjing Xu
Water 2025, 17(24), 3571; https://doi.org/10.3390/w17243571 - 16 Dec 2025
Viewed by 339
Abstract
Roof water inrush is a major hazard threatening coal mine safety. This paper addresses the risk of roof water inrush during mining in the shallow-buried Jurassic coalfield of Northern Shaanxi, taking the Guojiawan Coal Mine as a case study. A systematic framework of [...] Read more.
Roof water inrush is a major hazard threatening coal mine safety. This paper addresses the risk of roof water inrush during mining in the shallow-buried Jurassic coalfield of Northern Shaanxi, taking the Guojiawan Coal Mine as a case study. A systematic framework of “identification of main controlling factors–coupling of subjective and objective weighting–GIS-based spatial evaluation” is proposed. An integrated weighting system combining the Fuzzy Analytic Hierarchy Process (FAHP) and the Coefficient of Variation (CV) method is innovatively adopted. Four weight optimization models, including Linear Weighted Method, Multiplicative Synthesis Normalization Method, Minimum Information Entropy Method, and Game Theory Method, are introduced to evaluate 10 main controlling factors, including the fault strength index and sand–mud ratio. The results indicate that the GIS-based vulnerability evaluation model using the Multiplicative Synthesis Normalization Method achieves the highest accuracy, with a Spearman correlation coefficient of 0.9961. This model effectively enables five-level risk zoning and accurately identifies high-risk areas. The evaluation system and zoning results developed in this paper can provide a direct scientific basis for the design of water prevention engineering and precise countermeasures in the Guojiawan Coal Mine and other mining areas with similar geological conditions. Full article
(This article belongs to the Special Issue Evaluation and Monitoring of Hydrogeological Hazards in Underground Engineering)
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23 pages, 12592 KB  
Article
MesoHydraulics: Modelling Spatiotemporal Hydraulic Distributions at the Mesoscale
by Piotr Parasiewicz, Jura Sabolek, Adam Kiczko, Dorota Mirosław-Świątek and Jan Wójtowicz
Water 2025, 17(24), 3570; https://doi.org/10.3390/w17243570 - 16 Dec 2025
Viewed by 441
Abstract
The purpose of this study is to enhance the performance of the mesohabitat model MesoHABSIM by lowering the necessary hydraulic modelling effort. This proof-of-concept study tests an application of the MesoHydraulics model to simulate the hydraulic characteristics of hydromorphological units (HMUs) occurring in [...] Read more.
The purpose of this study is to enhance the performance of the mesohabitat model MesoHABSIM by lowering the necessary hydraulic modelling effort. This proof-of-concept study tests an application of the MesoHydraulics model to simulate the hydraulic characteristics of hydromorphological units (HMUs) occurring in a regulated river at different low discharges. In this quantitative approach, hydraulic patterns are transferred from a source site, where depth and velocity distributions were derived from field measurements and a 2D hydrodynamic model, to a target site, where only a single field hydrometric survey was conducted. Instead of modelling changes in individual hydraulic measurement values to estimate hydraulic responses to discharge, the model relies on statistical distributions of these values within HMUs. We were testing whether changes in the distribution of HMU’s and their hydraulics can be transferred between morphologically comparable river sections to serve as a sufficient hydraulic input for mesoscale habitat modelling. The hydrodynamic component of the River2D software (V.0.95a), routinely used in MesoHABSIM, served as a baseline for testing the MesoHydraulic model’s performance and for producing source data for deriving distribution functions. The test was conducted using data from two one-kilometre sites on the upper Oder River (Poland). The model transfers the HMU area distributions, along with corresponding depth and velocity frequency distributions, for a number of flows from one site (the source) to another (the target). The hydraulics at both sites were surveyed under single-discharge conditions. For the source site, the hydrodynamic model was applied to classify the HMU mosaic at three additional discharge stages. At the target reach, the HMU mapping was conducted based on survey data, and statistical frequency functions were used to model distributions of hydraulic patterns at discharges modelled for the source. The hydraulic model’s performance was evaluated at the target reach by comparing simulated hydraulics and HMU patterns with those modelled using River2D. Finally, both models were used to calculate habitat availability for the fish communities, and dissimilarities were observed. The resulting hydraulic distributions were similar, with an average affinity index of 90%. Higher affinity indices were reached at flows close to the measured value, with increasing model disagreement toward flow extremes, most notably for Run and Backwater units. Regardless, habitat models for the fish community were also highly correlated with R2 = 0.98 for amounts of suitable habitat and almost identical habitat distribution among the species. Yet, the MesoHydraulics-based model slightly, but consistently, overestimated habitat availability. While the model was tested in a large and regulated river system, its accuracy may vary depending on the natural river morphology. Further research should evaluate modelling uncertainties and their applicability in less-modified water bodies. Full article
(This article belongs to the Topic Advances in Environmental Hydraulics, 2nd Edition)
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18 pages, 2448 KB  
Article
Integrated Numerical Approach to Glyphosate Transport in Soil Profiles Under Farming Conditions
by Jesús García-Gallego, Sebastian Fuentes, Teobaldis Mercado-Fernández, Eusebio Ventura-Ramos, José Treviño-Reséndez, Josué D. García-Espinoza, Carlos Fuentes and Carlos Chávez
Water 2025, 17(24), 3569; https://doi.org/10.3390/w17243569 - 16 Dec 2025
Viewed by 498
Abstract
Glyphosate is the most widely used herbicide in the world for weed control; however, due to lixiviation, wind and runoff effects, an important fraction can reach the soil, aquifers and surface waters, affecting environmental and human health. The behavior of glyphosate in two [...] Read more.
Glyphosate is the most widely used herbicide in the world for weed control; however, due to lixiviation, wind and runoff effects, an important fraction can reach the soil, aquifers and surface waters, affecting environmental and human health. The behavior of glyphosate in two agricultural soils (C1: silty clay texture, and C2: silty loam texture) was analyzed in this study using a laboratory-scale model. Water transfer was modeled with the Richards equation, while glyphosate transport was modeled using the advection–dispersion equation, with both solved using finite difference methods. The glyphosate dispersion coefficient was obtained from laboratory concentration data derived from the soil profile via inverse modeling using a non-linear optimization algorithm. The goals of this study were to (i) quantify glyphosate retention in soils with different physical and chemical properties, (ii) calibrate a numerical model for the estimation of dispersivity and simulation of short- and long-term scenarios, and (iii) assess vulnerability to groundwater contamination. The results showed that C1 retained a greater amount of glyphosate in the soil profile, while C2 was considered more vulnerable as it liberated the contaminant more easily. The model accurately reproduced the measured concentrations, as evidenced by the RMSE and R2 statistics, thus supporting further scenario simulations allowing for prediction of the fate of the herbicide in soils. The approach utilized in this study may be useful as a tool for authorities in environmental fields, enabling better control and monitoring of soil contamination. These findings highlight potential risks of contamination and reinforce the importance of agricultural management strategies. Full article
(This article belongs to the Special Issue Soil and Groundwater Quality and Resources Assessment, 2nd Edition)
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