Water

31 pages, 5302 KiB

Open AccessArticle

Multiple Correlation Analysis of Operational Safety of Long-Distance Water Diversion Project Based on Copula Bayesian Network

by Pengyuan Li, Fudong Dong, Guibin Lv, Yuansen Wang, Yongguo Sheng, Feng Cheng and Bo Wang

Water 2025, 17(16), 2389; https://doi.org/10.3390/w17162389 - 12 Aug 2025

Abstract

Based on the Copula theory, a multiple correlation analysis model for the operation safety risks of long-distance water diversion projects was established. Combined with Bayesian network reasoning, a polynomial regression analysis, and other techniques, a dynamic analysis method for the operation safety of [...] Read more.

Based on the Copula theory, a multiple correlation analysis model for the operation safety risks of long-distance water diversion projects was established. Combined with Bayesian network reasoning, a polynomial regression analysis, and other techniques, a dynamic analysis method for the operation safety of long-distance water diversion projects based on a Copula Bayesian network model was proposed, providing decision support for the operation safety risk management of long-distance water diversion projects. We took the Middle Route Project of the South-to-North Water Diversion Project as an example to verify the validity and practicability of the model. The results show that this method can capture the nonlinear mapping relationship when the probability of risk occurrence changes dynamically on the basis of considering the risk correlation, and realize the dynamic analysis of risk correlation. Full article

(This article belongs to the Special Issue Computer Modelling Techniques in Environmental Hydraulics and Water Resource Engineering)

35 pages, 7825 KiB

Open AccessReview

Approaches for Assessment of Soil Moisture with Conventional Methods, Remote Sensing, UAV, and Machine Learning Methods—A Review

by Songthet Chinnunnem Haokip, Yogesh A. Rajwade, K. V. Ramana Rao, Satya Prakash Kumar, Andyco B. Marak and Ankur Srivastava

Water 2025, 17(16), 2388; https://doi.org/10.3390/w17162388 - 12 Aug 2025

Abstract

Soil moisture or moisture content is a fundamental constituent of the hydrological system of the Earth and its ecological systems, playing a pivotal role in the productivity of agricultural produce, climate modeling, and water resource management. This review comprehensively examines conventional and advanced [...] Read more.

Soil moisture or moisture content is a fundamental constituent of the hydrological system of the Earth and its ecological systems, playing a pivotal role in the productivity of agricultural produce, climate modeling, and water resource management. This review comprehensively examines conventional and advanced approaches for estimation or measuring of soil moisture, including in situ methods, remote sensing technologies, UAV-based monitoring, and machine learning-driven models. Emphasis is primarily on the evolution of soil moisture measurement from destructive gravimetric techniques to non-invasive, high-resolution sensing systems. The paper emphasizes how machine learning modules like Random Forest models, support vector machines, and AI-based neural networks are becoming more and more popular for modeling intricate soil moisture dynamics with data from several sources. A bibliometric analysis further underscores the research trends and identifies key contributors, regions, and technologies in this domain. The findings advocate for the integration of physics-based understanding, sensor technologies, and data-driven approaches to enhance prediction accuracy, spatiotemporal coverage, and decision-making capabilities. Full article

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

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22 pages, 793 KiB

Open AccessArticle

Ecotoxicological Risk Assessment and Monitoring of Pesticide Residues in Soil, Surface Water, and Groundwater in Northwestern Tunisia

by Khaoula Toumi, Abir Arbi, Nafissa Soudani, Anastasia Lomadze, Dalila Haouas, Terenzio Bertuzzi, Alessandra Cardinali, Lucrezia Lamastra, Ettore Capri and Nicoleta Alina Suciu

Water 2025, 17(16), 2387; https://doi.org/10.3390/w17162387 - 12 Aug 2025

Abstract

Pesticides play a significant role in agriculture, but their leaching into soil and water poses serious environmental risks. This study examines pesticide contamination in surface and groundwater in northern Tunisia, specifically in Kef governorate, involving a survey of 140 farmers to gather data [...] Read more.

Pesticides play a significant role in agriculture, but their leaching into soil and water poses serious environmental risks. This study examines pesticide contamination in surface and groundwater in northern Tunisia, specifically in Kef governorate, involving a survey of 140 farmers to gather data on agricultural practices and pesticide use. Twenty-four pesticides were monitored and utilized within the Pesticide Environmental Risk Indicator (PERI) model to evaluate environmental risk scores for each substance. Soil and water samples were analyzed using a multi-residue method and liquid chromatography–tandem mass spectrometry. Results showed that 50% of the pesticides assessed had an Environmental Risk Score of 5 or higher. Contamination was identified in water and soil, with 18 and 15 pesticide residues, respectively. Notable concentrations included 7.8 µg/L of linuron and flupyradifurone in water and 1718.4 µg/kg of linuron in soil. Commonly detected substances included the insecticide acetamiprid and fungicides like cyflufenamid and penconazole in water, while soil contamination was linked to fungicides metalaxyl and metalaxyl-m, as well as herbicides linuron and s-metolachlor. Factors such as proximity to treated water points and poor packaging management were discussed as risks. The findings emphasize the need for better monitoring and sustainable agricultural practices to mitigate contamination. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

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Graphical abstract

27 pages, 2893 KiB

Open AccessArticle

How Integrated Are Water and Food Systems in China? Assessing Coupling Mechanisms and Geographic Disparities

by Shan Zhou, Chao Sun and Yihang Hu

Water 2025, 17(16), 2386; https://doi.org/10.3390/w17162386 - 12 Aug 2025

Abstract

Water resources are of vital importance to human survival and development. This study systematically analyzed the coupling coordination mechanism between China’s food security (FS) and water resource management (WRM) from 2010 to 2022 using the TOPSIS model, Dagum Gini coefficient, coupling coordination model, [...] Read more.

Water resources are of vital importance to human survival and development. This study systematically analyzed the coupling coordination mechanism between China’s food security (FS) and water resource management (WRM) from 2010 to 2022 using the TOPSIS model, Dagum Gini coefficient, coupling coordination model, and fixed effects regression model. The results indicate that FS exhibited a “U-shaped” evolution: an average annual decline of 1.4% before 2017 followed by recovery to 2.39% due to policy optimization and technological upgrades, though significant regional disparities persisted with 15 provinces maintaining ecological vulnerability scores below 0.3. WRM showed an average annual increase of 1.33%, later accelerating to 1.76% driven by projects like the South-to-North Water Diversion Project, which significantly improved 28 provinces. The FS-WRM coupling coordination degree escalated from mild imbalance to near imbalance, forming a spatial pattern of “central region leading–northeast following–eastern fluctuation–western catching up”, with 10 provinces reaching barely coordinated levels in 2022. The study reveals that policy support, infrastructure development, technological innovation, and management model transformation are key influencing factors for FS-WRM coupling coordination. Full article

(This article belongs to the Special Issue Urban Water Resources: Sustainable Management and Policy Needs)

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19 pages, 3264 KiB

Open AccessArticle

Urban Geochemical Contamination of Highland Peat Wetlands of Very High Ecological and First Nations Cultural Value

by Ian A. Wright, Holly Nettle, Uncle David King, Michael J. M. Franklin and Amy-Marie Gilpin

Water 2025, 17(16), 2385; https://doi.org/10.3390/w17162385 - 12 Aug 2025

Abstract

Temperate Highland Peat Swamps on Sandstone (THPSS) are wetlands in the Blue Mountains, south-eastern Australia. The wetlands have legislative protection as endangered ecological communities. They have long-standing cultural significance for Gundungurra Traditional Custodians. Previous studies document their degradation by urban development and [...] Read more.

Temperate Highland Peat Swamps on Sandstone (THPSS) are wetlands in the Blue Mountains, south-eastern Australia. The wetlands have legislative protection as endangered ecological communities. They have long-standing cultural significance for Gundungurra Traditional Custodians. Previous studies document their degradation by urban development and vulnerability to extreme weather. Water quality in our study was assessed at wetlands in protected areas and compared with others exposed to urban development. We derived water quality guidelines that are intended to help future water quality assessment at THPSS and, in particular, to detect any impact from urban development on these wetland systems. Water quality in urban swamps was consistent with the freshwater salinisation syndrome despite all the swamps having relatively low electrical conductance (<140 µS cm⁻¹). Urban swamp water had salinity (mean 87.3 µS cm⁻¹) three times that of non-urban swamps (mean 28 µS cm⁻¹). The ionic composition of urban swamp water was dominated by calcium and bicarbonate, consistent with urban alkalisation syndrome. Our guidelines instead recommend limits for pH, salinity, turbidity, dissolved oxygen, and metals detected in greater concentrations that were found in urban swamps (iron, manganese, barium, and strontium). Our results support the theory that the dissolution of urban concrete materials is a degradation process that contributes to the impairment of urban swamp water quality. Full article

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

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23 pages, 3226 KiB

Open AccessArticle

Advanced Flow Detection Cell for SPEs for Enhancing In Situ Water Monitoring of Trace Levels of Cadmium

by Giulia Mossotti, Davide Girelli, Matilde Aronne, Giulio Galfré, Andrea Piscitelli, Luciano Scaltrito, Sergio Ferrero and Valentina Bertana

Water 2025, 17(16), 2384; https://doi.org/10.3390/w17162384 - 12 Aug 2025

Abstract

An advanced anodic stripping voltammetry (ASV)-based Micro Electro Mechanical System (MEMS) sensor for cadmium (Cd) detection is presented in this study, which is cost-effective and efficient for in situ water monitoring, providing a crucial early warning mechanism, streamlining environmental monitoring, and facilitating timely [...] Read more.

An advanced anodic stripping voltammetry (ASV)-based Micro Electro Mechanical System (MEMS) sensor for cadmium (Cd) detection is presented in this study, which is cost-effective and efficient for in situ water monitoring, providing a crucial early warning mechanism, streamlining environmental monitoring, and facilitating timely intervention to safeguard public health and environmental safety. The rationale behind this work is to address the critical need for an in situ monitoring system for cadmium (Cd) in freshwater sources, particularly those adjacent to agricultural fields. Cd(II) is a highly toxic heavy metal that poses a significant threat to agricultural ecosystems and human health due to its rapid bioaccumulation in plants and subsequent entry into the food chain. The developed analytic device is composed of a commercial mercury salt-modified graphite screen-printed electrode (SPE) with a custom-designed innovative polydimethylsiloxane (PDMS) flow detection cell. The flow cell was prototyped using 3D printing and replica moulding, with its design and performance validated through COMSOL Multiphysics simulations to optimize inflow conditions and ensure maximum analyte dispersion on the working electrode surface. Chemical detection was performed using square wave voltammetry, demonstrating a linear response for Cd(II) concentrations of 0 to 20 µg/L. The system exhibited robust analytical performance, enabling 25–30 daily analyses with consistent sensitivity within the Limit of Detection (LoD) set by the law of 3 µg/L. Full article

(This article belongs to the Special Issue Water Quality Monitoring and Prediction Using New Sensors, Machine Learning and Big Data)

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15 pages, 2779 KiB

Open AccessArticle

Groundwater Flow Impact in Complex Karst Regions Considering Tunnel Construction Conditions: A Case Study of the New Construction Project at XLS Tunnel

by Zhou Chen, Hongtu Zhang, Qi Shen, Zihao Chen, Kai Wang and Changsheng Chen

Water 2025, 17(16), 2383; https://doi.org/10.3390/w17162383 - 12 Aug 2025

Abstract

Tunneling in structurally complex, tectonically active regions such as southwest China poses significant environmental risks to groundwater, especially in heterogeneous karst fault systems where conventional prediction methods often fail. This study innovatively coupled MODFLOW’s STREAM package (for simulating karst conduit networks) and DRAIN [...] Read more.

Tunneling in structurally complex, tectonically active regions such as southwest China poses significant environmental risks to groundwater, especially in heterogeneous karst fault systems where conventional prediction methods often fail. This study innovatively coupled MODFLOW’s STREAM package (for simulating karst conduit networks) and DRAIN package (for tunnel inflow prediction) within a 3D groundwater model to assess hydrogeological impacts in complex mountainous terrain. The simulations show that an uncased tunnel lining causes significant groundwater changes under natural conditions, with predicted inflows reaching 34,736 m³/d. Conventional cement grouting (permeability: 1 × 10⁻⁵ cm/s; thickness: 10 m) mitigates the effects considerably and reduces the inflows in the tunnel sections by 27–97%. Microfine cement grouting (5 × 10⁻⁶ cm/s; 10 m thickness) further improves performance by achieving a 49–98% reduction in inflows and limiting the reduction in spring discharge to ≤13.28%. These results establish a valid theoretical framework for predicting groundwater impacts in heterogeneous terrain and demonstrate that targeted seepage control—particularly grouting with microfine cement—effectively protects groundwater-dependent ecosystems during infrastructure development. Full article

(This article belongs to the Section Hydrogeology)

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21 pages, 12605 KiB

Open AccessArticle

Impact of Sharp Soil Interfaces on Solute Transport: Insights from a Reactive Tracer Test in a 2D Intermediate-Scale Experiment

by Guido González-Subiabre, Oriol Bertran and Daniel Fernàndez-Garcia

Water 2025, 17(16), 2382; https://doi.org/10.3390/w17162382 - 12 Aug 2025

Abstract

Understanding solute transport across interfaces between different porous materials is crucial for subsurface applications. Column tracer experiments have suggested solute accumulation at these interfaces. This effect cannot be explained by standard models based on Fickian flux continuity and the advection–dispersion equation. To analyze [...] Read more.

Understanding solute transport across interfaces between different porous materials is crucial for subsurface applications. Column tracer experiments have suggested solute accumulation at these interfaces. This effect cannot be explained by standard models based on Fickian flux continuity and the advection–dispersion equation. To analyze this phenomenon, we present reactive transport experiments in a 2D intermediate-scale horizontal tank to visualize and evaluate the spatiotemporal evolution of a solute plume crossing a sharp interface between coarse and fine materials. The plume results from the reaction of two fluid solutions entering the tank in parallel through inlet ports. The reaction product is analyzed using mixing and reaction metrics. Results show the reaction product encounters anomalous resistance when the plume crosses the coarse-to-fine (CF) interface. This effect is less pronounced in the fine-to-coarse (FC) transition. This asymmetric resistance does not produce solute accumulation behind the interface, a difference from the results obtained with the one-dimensional model. Instead, results show enhanced transverse spread of the reaction product in the coarse-to-fine transition, with slow release in the fine material. A sudden decrease in the longitudinal concentration profile across the interface is observed. Mixing metrics show that as apparent transverse dispersivity increases closer to the interface in the CF transition, the scalar dissipation rate and total mass reacted increase, indicating that the CF configuration promotes greater solute reactivity near the interface compared to the FC configuration. Full article

(This article belongs to the Topic Advances in Groundwater Science and Engineering)

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19 pages, 1033 KiB

Open AccessArticle

Designing Nature-Based Solutions for Sediment Control in Impaired Humid Subtropical Forests: An Approach Based on the Environmental Benefits Assessment

by Águeda Bellver-Domingo, Carme Machí-Castañer and Francesc Hernández-Sancho

Water 2025, 17(16), 2381; https://doi.org/10.3390/w17162381 - 12 Aug 2025

Abstract

Land-use changes cause disturbance to sediment dynamics, increasing downstream sediment loads discharged into ecosystems and provoking impacts on stream quality and damage to current stormwater infrastructures. Wastewater nature-based solutions (NBSWT) are bioretention techniques that alleviate downstream degradation caused by runoff sediment accumulation and [...] Read more.

Land-use changes cause disturbance to sediment dynamics, increasing downstream sediment loads discharged into ecosystems and provoking impacts on stream quality and damage to current stormwater infrastructures. Wastewater nature-based solutions (NBSWT) are bioretention techniques that alleviate downstream degradation caused by runoff sediment accumulation and are projected as an off-line street device that enhances treatment of runoff contaminant loads. This research assesses the economic, social, and environmental benefits from sediment load reduction in runoff by designing a new NBSWT in a selected urban area of the Mantiqueira Mountain Range (São Paulo, Brazil), considered an irreplaceable protected area for biodiversity and urban water supply. To achieve this quantification, the shadow prices methodology has been used. The results obtained here show the adaptive capacity that NBSWT have according to the territory and its climatic particularities, quantified at USD 40,475,255. This value demonstrates that the retention of runoff sediment generates a direct environmental benefit related to the ecosystem improvement of the river system located downstream, preserving its environmental and social importance. Hence, this study demonstrates the potential of using shadow prices methodology as a management tool for quantifying the environmental benefit of removing runoff solids by using NBSWT in developing urban areas. Full article

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

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44 pages, 3756 KiB

Open AccessArticle

Reflection of Intercontinental Freshwater Resources on Geopolitical Risks: Time Series Analysis

by Sabiha Oltulular

Water 2025, 17(16), 2380; https://doi.org/10.3390/w17162380 - 12 Aug 2025

Abstract

Water, an indispensable resource for life and not a complete substitute, is indispensable for energy production, industry, agriculture, and ecosystem sustainability. In particular, the limited and unequal distribution of freshwater reserves makes water a strategic power element on a global scale, making competition [...] Read more.

Water, an indispensable resource for life and not a complete substitute, is indispensable for energy production, industry, agriculture, and ecosystem sustainability. In particular, the limited and unequal distribution of freshwater reserves makes water a strategic power element on a global scale, making competition inevitable. Increasing water demand and decreasing water resources increase regional and global security risks, causing water to go beyond being a vital natural resource and become a determining factor in diplomacy, conflict, and the balance of power. This study aimed to examine the relationship between freshwater resources and geopolitical risk between 1961 and 2021 using the ARDL model. All models had long-run relationships between water resources and geopolitical risk. In the long-run, a 1% decrease in water resources increased geopolitical risk by 0.37% in Chile, 0.30% in Colombia, 0.46% in the Netherlands, 0.42% in Thailand, 0.44% in Ukraine, and 0.29% in Venezuela. The adjustment rates for the prior period imbalances were estimated to be 0.75% in Switzerland, 0.68% in Chile, 0.28% in Colombia, 0.45% in the Netherlands, 0.86% in Thailand, 0.14% in Ukraine, and 0.59% in Venezuela. Full article

(This article belongs to the Special Issue Water Resources, Economic Development and Environment Carrying Capacity)

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32 pages, 4113 KiB

Open AccessArticle

A Novel Deep Learning-Based Soil Moisture Prediction Model Using Adaptive Group Radial Lasso Regularized Basis Function Networks (AGRL-RBFN) Optimized by Hierarchical Correlated Spider Wasp Optimizer (HCSWO) and Incremental Learning (IL)

by Claudia Cherubini and Muthu Bala Anand

Water 2025, 17(16), 2379; https://doi.org/10.3390/w17162379 - 11 Aug 2025

Abstract

Soil moisture serves as a critical factor in the hydrological cycle, affecting plant growth, ecosystem health, and groundwater reserves. Current methods for monitoring and predicting it fail to account for the complexities introduced by climatic variations and other influencing factors, such as the [...] Read more.

Soil moisture serves as a critical factor in the hydrological cycle, affecting plant growth, ecosystem health, and groundwater reserves. Current methods for monitoring and predicting it fail to account for the complexities introduced by climatic variations and other influencing factors, such as the effects of atmospheric interference and data gaps, leading to reduced prediction accuracy. To address these challenges, this study introduces a novel soil moisture prediction model based on remote sensing and deep learning, utilizing the Adaptive Group Radial Lasso Regularized Basis Function Networks (AGRL-RBFN) optimized by the Hierarchical Correlated Spider Wasp Optimizer (HCSWO) and incremental learning (IL) techniques. The proposed method for monitoring soil moisture utilizes hyperspectral and soil moisture data from a 2017 campaign in Karlsruhe, encompassing variables such as datetime, soil moisture percentage, soil temperature, and remote sensing spectral bands. The proposed methodology begins with comprehensive preprocessing of historical remote sensing data to fill gaps, reduce noise, and correct atmospheric disturbances. It then employs a unique seasonal mapping and grouping technique, enhanced by the AdaK-MCC method, to analyze the impact of climatic changes on soil moisture patterns. The model’s innovative feature selection approach, using HCSWO, identifies the most significant predictors, ensuring optimal data input for the AGRL-RBFN model. The model achieves an impressive accuracy of 98.09%, a precision of 98.17%, a recall of 97.24%, and an F1-score of 98.95%, outperforming existing methods. Furthermore, it attains a mean absolute error (MAE) of 0.047 in gap filling and a Dunn Index of 4.897 for clustering. Although successful in many aspects, the study did not investigate the relationship between soil moisture levels and specific crops, which presents an opportunity for future research aimed at enhancing smart agricultural practices. Furthermore, the model can be refined by integrating a wider range of datasets and improving its resilience to extreme weather conditions, thereby providing a reliable tool for climate-responsive agricultural management and water conservation strategies. Full article

(This article belongs to the Special Issue Artificial Intelligence for Sustainable Management of Groundwater Resources: New Developments, Challenges and Untapped Potentials)

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18 pages, 5592 KiB

Open AccessArticle

Influence of a Diversion Pier on the Hydraulic Characteristics of an Inverted Siphon in a Long-Distance Water Conveyance Channel

by Jian Wang, Jingyu Hu, Xiaoli Yang, Lifang Lou, Tong Mu, Dongsheng Wang and Tengfei Hu

Water 2025, 17(16), 2378; https://doi.org/10.3390/w17162378 - 11 Aug 2025

Abstract

Since large-flow water diversion began in the middle route of the South-to-North Water Diversion Project, inverted siphons have experienced varying degrees of local flow pattern disorder at their inlets and outlets, resulting in a significant decline in hydraulic performance. Taking the Kuhe inverted [...] Read more.

Since large-flow water diversion began in the middle route of the South-to-North Water Diversion Project, inverted siphons have experienced varying degrees of local flow pattern disorder at their inlets and outlets, resulting in a significant decline in hydraulic performance. Taking the Kuhe inverted siphon as a case study, a combination of numerical simulation and on-site testing was used to explore the causes of flow pattern disorder at the outlet of the inverted siphon. Meanwhile, based on the actual engineering situation, the influence of the flow pattern optimization measure of installing a 5D (five times the diameter of the pier) diversion pier at the outlet of the inverted siphon on its hydraulic characteristics was studied. Research findings indicated that before the implementation of flow pattern optimization measures, the Karman vortex street phenomenon was found to occur when water flowed through the piers; the interaction of the vortex streets behind each pier led to flow pattern disorder and affected the flow capacity. After implementation of the flow pattern optimization measures, the diversion piers had a significant inhibitory effect on the formation and development of the Karman vortex street behind the piers under the dispatching and design flow conditions. The flow velocities in each vertical layer were adjusted, with a significant improvement in the flow pattern. The hydraulic loss of the Kuhe inverted siphon was reduced by 11.5 mm, or approximately 7.8%. Under the dispatching flow condition, the water diversion flow of the Kuhe inverted siphon increased by approximately 4.11%. The water diversion capacity of the structure could be effectively enhanced by adding diversion piers to the tails of the piers. This method can be widely applied in similar open-channel long-distance water diversion projects. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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14 pages, 1446 KiB

Open AccessArticle

Factors Influencing the Spatial Distribution of Microplastics in Lakes with the Example of Dianchi Lake

by Chunnuan Deng, Yuejiao Huang, Yao Hu, Quan Zhang and Hui Zhao

Water 2025, 17(16), 2377; https://doi.org/10.3390/w17162377 - 11 Aug 2025

Abstract

The spatial law and influencing factors of microplastics in lakes are an important part of microplastic research. This study focused on exploring the influences of factors such as the underwater slope, water depth, and pollution source/shore distance of a lake on the spatial [...] Read more.

The spatial law and influencing factors of microplastics in lakes are an important part of microplastic research. This study focused on exploring the influences of factors such as the underwater slope, water depth, and pollution source/shore distance of a lake on the spatial distribution of lake MPs (microplastics). The relationships between the underwater slope, other factors, and the concentration of MPs were analyzed. The results showed that the average abundance of MPs in Dianchi Lake was 129 n/m³, and the spatial distribution pattern was higher in the lake center and lower in the lake shore. The correlation analysis showed that MP abundance was not significantly associated with distance to pollution sources or water depth, but it was significantly correlated with slope (p < 0.05) and offshore distance (p < 0.01). There was a significant negative correlation between the abundance of MPs and the underwater slope. The greater the underwater slope, the lower the abundance of MPs; the smaller the underwater slope, the higher the abundance of MPs. There was a significant positive correlation between the abundance of MPs and offshore distance. The abundance of MPs increased with increasing offshore distance. These new discoveries will help us better understand the spatial patterns of MPs in lakes. Full article

(This article belongs to the Special Issue Research on Microplastic Pollution in Water and Soil Environment)

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25 pages, 1040 KiB

Open AccessReview

Establishing a Sea Level Rise-Adjusted Design Flood Elevation for Buildings: A Comparative Study of Methods

by Wendy Meguro, Josephine I. Briones, Eric Teeples and Charles H. Fletcher

Water 2025, 17(16), 2376; https://doi.org/10.3390/w17162376 - 11 Aug 2025

Abstract

Coastal high tide flooding doubled in the U.S. between 2000 and 2022 and sea level rise (SLR) due to climate change will dramatically increase exposure and vulnerability to flooding in the future. However, standards for elevating buildings in flood hazard areas, such as [...] Read more.

Coastal high tide flooding doubled in the U.S. between 2000 and 2022 and sea level rise (SLR) due to climate change will dramatically increase exposure and vulnerability to flooding in the future. However, standards for elevating buildings in flood hazard areas, such as base flood elevations set by the Federal Emergency Management Agency, are based on historical flood data and do not account for future SLR. To increase flood resilience in flood hazard areas, federal, state, regional, and municipal planning initiatives are developing guidance to increase elevation requirements for occupied spaces in buildings. However, methods to establish a flood elevation that specifically accounts for rising sea levels (or sea level rise-adjusted design flood elevation (SLR-DFE)) are not standardized. Many municipalities or designers lack clear guidance on developing or incorporating SLR-DFEs. This study compares guidance documents, policies, and methods for establishing an SLR-DFE. The authors found that the initiatives vary in author, water level measurement starting point, SLR scenario and timeframe, SLR adjustment, freeboard, design flood elevation, application (geography and building type), and whether it is required or recommended. The tables and graph compare the different initiatives, providing a useful summary for policymakers and practitioners to develop SLR-DFE standards. Full article

(This article belongs to the Special Issue Climate Risk Management, Sea Level Rise and Coastal Impacts)

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24 pages, 1395 KiB

Open AccessReview

A Systematic Literature Review of MODFLOW Combined with Artificial Neural Networks (ANNs) for Groundwater Flow Modelling

by Kunal Kishor, Ashish Aggarwal, Pankaj Kumar Srivastava, Yaggesh Kumar Sharma, Jungmin Lee and Fatemeh Ghobadi

Water 2025, 17(16), 2375; https://doi.org/10.3390/w17162375 - 11 Aug 2025

Abstract

The sustainable management of global groundwater resources is increasingly challenged by climatic uncertainty and escalating anthropogenic stress. Thus, there is a need for simulation tools that are more robust and flexible. This systematic review addresses the integration of two dominant modeling paradigms: the [...] Read more.

The sustainable management of global groundwater resources is increasingly challenged by climatic uncertainty and escalating anthropogenic stress. Thus, there is a need for simulation tools that are more robust and flexible. This systematic review addresses the integration of two dominant modeling paradigms: the physically grounded Modular Finite-Difference Flow (MODFLOW) model and the data-agile Artificial Neural Network (ANN). While the MODFLOW model provides deep process-based understanding, it is often limited by extensive data requirements and computational intensity. In contrast, an ANN offers remarkable predictive accuracy and computational efficiency, particularly in complex, non-linear systems, but traditionally lacks physical interpretability. This review synthesizes existing research to present a functional classification framework for MODFLOW–ANN integration, providing a systematic analysis of the literature within this structure. Our analysis of the literature, sourced from Scopus, Web of Science, and Google Scholar reveals a clear trend of the strategic integration of these models, representing a new trend in hydrogeological simulation. The literature reveals a classification framework that categorizes the primary integration strategies into three distinct approaches: (1) training an ANN on MODFLOW model outputs to create computationally efficient surrogate models; (2) using an ANN to estimate physical parameters for improved MODFLOW model calibration; and (3) applying ANNs as post-processors to correct systematic errors in MODFLOW model simulations. Our analysis reveals that these hybrid methods consistently outperform standalone approaches by leveraging ANNs for computational acceleration through surrogate modeling, for enhanced model calibration via intelligent parameter estimation, and for improved accuracy through systematic error correction. Full article

(This article belongs to the Special Issue Application of Hydrological Modelling to Water Resources Management)

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16 pages, 5156 KiB

Open AccessArticle

Deformation and Stress of a Runner in Large Francis Turbines Under Wide-Load Operating Conditions

by Xin Deng, Hong Hua, Chaoshun Li, Shuman Wei, Zhu Yan, Wanquan Deng, Jiayang Pang, Yufan Xiong, Lihao Li and Xiaobing Liu

Water 2025, 17(16), 2374; https://doi.org/10.3390/w17162374 - 11 Aug 2025

Abstract

During partial-load operation, hydroelectric units are frequently subjected to hydraulic vibrations caused by pressure fluctuations within the turbine. These vibrations can result in deformation of the runner blades and, in severe instances, lead to crack formation. Over the years, research efforts have primarily [...] Read more.

During partial-load operation, hydroelectric units are frequently subjected to hydraulic vibrations caused by pressure fluctuations within the turbine. These vibrations can result in deformation of the runner blades and, in severe instances, lead to crack formation. Over the years, research efforts have primarily focused on specific operating conditions, with relatively insufficient attention paid to the study of operational stability under broad-load operation. This study investigates the recurrent occurrence of crack damage in the runner blades of a Francis turbine installed at a major hydropower station. The issue emerges in response to the operational requirements of a modern power system, which mandates wide-load operation across varying heads (154.6 m, 197 m, 229.4 m) and guide vane openings (10%, 25%, 50%, 70%, 100%). To inform the development of optimized operational control strategies, this work examines the deformation and von Mises stress distribution patterns on the runner blades under these wide-load conditions. The findings reveal that the maximum blade deformation predominantly occurs in the mid-section of the trailing edge under most operating scenarios, while the peak von Mises stress consistently appears near the band at the trailing edge. Both peak deformation (1.99 mm) and peak von Mises stress (170.92 MPa) were observed at the maximum head (229.4 m) under 100% guide vane opening. Notably, significant deformation and stress levels were also encountered at openings below 25% under low-head conditions. On the basis of the research results, suggestions for ensuring the safe and stable operation of power station units under wide-load conditions were proposed. Full article

(This article belongs to the Special Issue Advanced Numerical Approaches for Multiphase and Cavitating Flows)

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33 pages, 6805 KiB

Open AccessReview

Diatom Biosilica: A Useful Natural Material for Biomedical Engineering

by Daehyeon Yoo, Minyoung Lee, Yoseph Seo, Jinwook Yoon, Eunseok Jang, Gaeun Lee, Daeryul Kwon, Sang Deuk Lee, Junhong Min and Taek Lee

Water 2025, 17(16), 2373; https://doi.org/10.3390/w17162373 - 11 Aug 2025

Abstract

Silica-based materials are recognized as effective functional materials across diverse industrial fields, including biomedicine (e.g., drug delivery systems (DDS), biosensors, and tissue engineering), owing to their excellent stability and physicochemical characteristics. Among them, diatom biosilica (DB), which constitutes a major part of aquatic [...] Read more.

Silica-based materials are recognized as effective functional materials across diverse industrial fields, including biomedicine (e.g., drug delivery systems (DDS), biosensors, and tissue engineering), owing to their excellent stability and physicochemical characteristics. Among them, diatom biosilica (DB), which constitutes a major part of aquatic biomass, recently gained significant attention as a valuable biomaterial following breakthroughs in its innovative surface structure, superior biocompatibility and multifunctionality. Therefore, DB is emerging as an alternative to synthetic materials used in the biomedical field. This review comprehensively examines the diverse biological properties of DB, followed by an analysis of harvesting and purification strategies. Then, the current application status of DB in two principal biomedical domains, DDS and biosensors, is evaluated. Furthermore, the convergence of these domains into theragnostic applications addresses a significant unmet clinical need for simultaneous therapeutic intervention and diagnostic monitoring, positioning DB as a transformative biomaterial solution. The unique combination of natural hierarchical architecture, tunable surface properties, and excellent biocompatibility make DB promising candidates for next-generation integrated biomedical platforms to address the growing demand of personalized medicine and precision healthcare solutions. Full article

(This article belongs to the Special Issue Advances in Diatom Research in Freshwater)

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16 pages, 2020 KiB

Open AccessArticle

Environmental Drivers of Aquatic Community Structures in a Shallow Eutrophic Lake of the Taihu Lake Basin

by Zishu Ye, Qinghuan Zhang, Chunhua Li, Chun Ye and Yang Wang

Water 2025, 17(16), 2372; https://doi.org/10.3390/w17162372 - 10 Aug 2025

Abstract

Gehu Lake in the lower reaches of the Taihu Lake Basin has experienced water quality degradation due to increasing human activities, pollutant discharge, and non-point source pollution, which requires ecosystem restoration. Currently, the community structure of aquatic organisms and their influencing environmental factors [...] Read more.

Gehu Lake in the lower reaches of the Taihu Lake Basin has experienced water quality degradation due to increasing human activities, pollutant discharge, and non-point source pollution, which requires ecosystem restoration. Currently, the community structure of aquatic organisms and their influencing environmental factors remain poorly understood. Thus, in this study, we conducted comprehensive fieldwork in June 2024 and analyzed the community structures of plankton (i.e., phytoplankton and zooplankton) and macroinvertebrates, and their influencing environmental factors in Gehu Lake and the inflowing river. The trophic level index (TLI) and biodiversity indices (Shannon–Wiener, Pielou, and Margalef) were utilized to assess water quality status. Pearson correlation analysis and redundancy analysis (RDA) were applied to identify key factors influencing plankton and macroinvertebrate community structures. The dominant phytoplankton species included Merismopedia punctata, Microcystis aeruginosa, Aphanizomenon flos-aquae, Aphanocapsa elachista, and Melosira granulata. The dominant zooplankton species were mainly Brachionus diversicornis, Brachionus calyciflorus, and Asplanchna priodonta. The dominant macroinvertebrate species were Microchironomus tabarui and Chironomusflaviplumus. The findings suggest that Gehu Lake exhibited moderate pollution levels, while the diversity indices were significantly correlated with environmental factors. The Shannon–Wiener index of zooplankton displayed a markedly negative correlation with Chl-a (p < 0.05). The results from redundancy analysis showed that TP, TN, SD, COD_Mn, and Chl-a were key environmental factors shaping the aquatic community structure in the lake. Full article

(This article belongs to the Special Issue NBS for Watershed Management: From Ecological Health Assessment to Ecosystem Restoration)

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24 pages, 14222 KiB

Open AccessArticle

Integrated Assessment of Groundwater Quality Using Water Quality Indices, Geospatial Analysis, and Neural Networks in a Rural Hungarian Settlement

by Dániel Balla, Levente Tari, András Hajdu, Emőke Kiss, Marianna Zichar and Tamás Mester

Water 2025, 17(16), 2371; https://doi.org/10.3390/w17162371 - 10 Aug 2025

Abstract

In the present study, the changes in the groundwater quality in a Hungarian settlement, Báránd, were examined, nine years after the construction of a sewerage network. The sewerage network in the study area was completed in 2014, with a household connection rate exceeding [...] Read more.

In the present study, the changes in the groundwater quality in a Hungarian settlement, Báránd, were examined, nine years after the construction of a sewerage network. The sewerage network in the study area was completed in 2014, with a household connection rate exceeding 97% in 2023. In the summer of 2023, water samples were taken from 37 dug groundwater wells. Changes in the water quality were assessed using three water quality indicators (the Water Quality Index (WQI), Contamination degree (Cd), and Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI)) and geographic information (GIS), data visualization systems, and artificial intelligence (AI). During the evaluation of the quality of the groundwater, eight water chemical parameters were used (pH, EC, NH₄⁺, NO₂⁻, NO₃⁻, PO₄³⁻, COD, Na⁺). Based on interpolated maps and water quality indices, it was established that while an increasing portion of the area exhibits adequate or good water quality compared to the pre-sewerage period, a deterioration has occurred relative to recent years. Even nine years after the sewerage network construction, elevated concentrations of inorganic nitrogen forms and organic matter persist, indicating the continued presence of accumulated pollutants, as confirmed by all three water quality indicators to varying degrees and spatial patterns. The interactive data visualization and cloud-based sharing of the data of the water quality geodatabase were made freely available with the help of Tableau Public. A Feed-Forward Neural Network (FFNN) was developed to predict the groundwater quality, estimating the water quality statuses of three water quality indicators based on water chemistry parameters. The results showed that the applied training algorithms and activation functions proved to be the most effective in the case of different network structures. The most accurate prediction of the WQI and CCME WQI indicators was provided by the Bayesian control algorithm (trainbr), which achieved the lowest mean-squared error (RMSE_WQI = 0.1205, RMSE_{CCME WQI} = 0.1305) and the highest determination coefficient (R²_WQI = 0.9916, R²_{CCME WQI} = 0.9838). For the Cd index, the accuracy of the model was lower (RMSE = 0.1621, R² = 0.9714), suggesting that this indicator is more difficult to predict. With regard to our study, it should be emphasized that data visualization is a particularly practical tool for the post-processing of spatial monitoring data, as it is suitable for displaying information in an intuitive, visual form, for discovering spatial patterns and relationships, and for performing real-time analyses. AI is expected to further increase visualization efficiency in the future, enabling the rapid processing of large amounts of data and spatial databases, as well as the identification of complex patterns. Full article

(This article belongs to the Special Issue Urban Water Pollution Control: Theory and Technology)

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