Water

17 pages, 4574 KiB

Open AccessArticle

A Multi-Source Object-Oriented Framework for Extracting Aquaculture Ponds: A Case Study from the Chaohu Lake Basin, China

by Lingyan Qi, Zhengxin Wang, Liuyi Dai, Fengwen Wu, Han Yin, Kejia Zhang, Mingzhu Guo, Liangtao Ye and Shanshan Zhang

Water 2025, 17(9), 1406; https://doi.org/10.3390/w17091406 - 7 May 2025

Viewed by 224

Abstract

Quantifying the extent and distribution of aquaculture ponds has become the key to management in the aquaculture industry, thereby contributing to the sustainable development of the region. However, accurate extraction of individual aquaculture pond boundaries from mesoscale remote sensing images remains a significant [...] Read more.

Quantifying the extent and distribution of aquaculture ponds has become the key to management in the aquaculture industry, thereby contributing to the sustainable development of the region. However, accurate extraction of individual aquaculture pond boundaries from mesoscale remote sensing images remains a significant challenge. In this work, we developed the Multi-source Object-oriented Framework for extracting Aquaculture ponds (MOFA) to address mapping challenges in the Chaohu Lake basin, China. The MOFA combined Sentinel-1 synthetic aperture radar (SAR) with Sentinel-2 data, applying an object-oriented approach with adaptive threshold segmentation for robust and automated aquaculture pond delineation. Our performance evaluation results showed that the overall accuracy is as high as 90.75%. The MOFA is thus capable of distinguishing seasonal water bodies, lakes, reservoirs, and rivers from individual (non-centralized, contiguous) aquaculture ponds. Our results showed that the central and south sections of the Chaohu Lake basin are characterized by denser aquaculture pond distributions, relative to those in the western basin. The total area of aquaculture ponds across the entire basin decreased from 19,297.86 hm² in 2016 to 18,262.77 hm² in 2023, which is likely attributed to local policy adjustments, resource optimization, shifting market demands, or natural environmental changes. The abandonment and unregulated expansion of aquaculture ponds threaten sustainable development. Local governments must implement adaptive governance strategies to balance ecological preservation with economic growth. Overall, the MOFA can quickly and accurately extract and map aquaculture ponds, and further support the scientific planning of sustainable aquaculture development. Full article

(This article belongs to the Special Issue Wetland Water Quality Monitoring and Assessment)

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21 pages, 2147 KiB

Open AccessArticle

Runoff Prediction Method Based on Pangu-Weather

by Wentao Yang, Hui Qin, Yongsheng Jie, Yuhua Qu, Taiheng Zhang, Chenghong Li and Li Tan

Water 2025, 17(9), 1405; https://doi.org/10.3390/w17091405 - 7 May 2025

Viewed by 182

Abstract

Runoff prediction is a complex hydrological, nonlinear time-series problem. Many machine learning methods have been put forth in recent years to predict runoff. A sliding window method is typically used to preprocess the data in order to rebuild the time series of runoff [...] Read more.

Runoff prediction is a complex hydrological, nonlinear time-series problem. Many machine learning methods have been put forth in recent years to predict runoff. A sliding window method is typically used to preprocess the data in order to rebuild the time series of runoff data into a standard machine learning dataset. The size of the window is a variable parameter that is commonly referred to as the time step. With developments in computer and AI technology, data-driven models have demonstrated tremendous potential for runoff prediction. And AI technology has opened up a new avenue for weather prediction, with Pangu-Weather demonstrating considerable improvements in both accuracy and processing efficiency. This study creates two novel prediction models, LSTM-Pangu and GRU-Pangu, by combining Pangu with Long Short-Term Memory (LSTM) and the Gate Recurrent Unit (GRU). We concentrated on the Beipanjiang River Basin in China, using Guizhou Qianyuan Power Company Limited’s daily runoff data and meteorological satellite data from the Climate Data Store platform to forecast daily runoff. These models were used to anticipate runoff on various future days (known as the lead time). The results show that regardless of time step, both LSTM-Pangu and GRU-Pangu outperform the LSTM and GRU models. Furthermore, this advantage is more evident as the advance time increases. When the time step is 7 and the lead time is 5, the Nash–Sutcliffe Efficiency (NSE) of the LSTM-Pangu model improves by 8.1% compared to the LSTM model, while the NSE of the GRU-Pangu model improves by 11.7% compared to the GRU model. Furthermore, LSTM-Pangu and GRU-Pangu outperform LSTM and GRU models in terms of the predictive accuracy under high-flow conditions, highlighting their significant advantages in flood forecasting. This integration strategy displays great transferability and may be expanded to other typical data-driven models. Full article

(This article belongs to the Section Hydrology)

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21 pages, 20296 KiB

Open AccessArticle

Urban Flood Prediction Model Based on Transformer-LSTM-Sparrow Search Algorithm

by Zixuan Fan, Jinping Zhang, Yanpo Chen and Hongshi Xu

Water 2025, 17(9), 1404; https://doi.org/10.3390/w17091404 - 7 May 2025

Viewed by 263

Abstract

Global climate change and accelerated urbanization have intensified extreme rainfall events, exacerbating urban flood risks. Although data-driven models have shown potential in urban flood prediction, the ability of single models to capture complex nonlinear relationships and their sensitivity to hyperparameters still limit prediction [...] Read more.

Global climate change and accelerated urbanization have intensified extreme rainfall events, exacerbating urban flood risks. Although data-driven models have shown potential in urban flood prediction, the ability of single models to capture complex nonlinear relationships and their sensitivity to hyperparameters still limit prediction accuracy. To address these challenges, this study proposes an urban flood prediction model by integrating Transformer, Long Short-Term Memory (LSTM), and Sparrow Search Algorithm (SSA), combining Transformer’s global feature extraction with LSTM’s temporal modeling. The SSA was adopted to optimize hyperparameters for the Transformer-LSTM model. Dropout and early stopping techniques were adopted to mitigate overfitting. Applied to Zhengzhou city of Henan province, China, the model achieves a Nash-Sutcliffe Efficiency (NSE) of 0.971, indicating that the proposed model has high prediction performance for urban flooding. The experimental results demonstrate that the Transformer-LSTM-SSA model outperforms the standalone Transformer, LSTM, and Transformer-LSTM models by 12.9%, 10.1%, and 2.9% in NSE accuracy, respectively, while reducing MAE by 62.12%, 56.9%, and 34.21%, respectively, and MAPE by 21.69%, 22.2%, and 10.89%, respectively. Furthermore, the proposed model exhibits enhanced stability and superior generalization capability. The Transformer-LSTM-SSA model exhibits superior performance among the comparative methods, thereby demonstrating the model’s viability for providing a reliable solution for real-time flood prediction and early warning. Full article

(This article belongs to the Special Issue Urban Flood Frequency Analysis and Risk Assessment)

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22 pages, 6938 KiB

Open AccessArticle

Assessing the Effects of Climate Change on the Hydrology of a Small Catchment: The Krapina River near Kupljenovo

by Ognjen Bonacci, Ana Žaknić-Ćatović, Tanja Roje-Bonacci and Duje Bonacci

Water 2025, 17(9), 1403; https://doi.org/10.3390/w17091403 - 7 May 2025

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Abstract

The aim of this study was to examine variations in the hydrological regime of the Krapina River from 1964 to 2023. The river basin spans 1263 km² and is characterized by a temperate, humid continental climate with warm summers. Hydrological data from [...] Read more.

The aim of this study was to examine variations in the hydrological regime of the Krapina River from 1964 to 2023. The river basin spans 1263 km² and is characterized by a temperate, humid continental climate with warm summers. Hydrological data from the Kupljenovo gauging station, which monitors 91.1% of the basin (1150 km²), indicate an average annual discharge of 11.2 m³/s, ranging from 3.25 m³/s to 18.3 m³/s. Over the 60-year study period, the minimum mean daily discharges show a statistically insignificant increasing trend, while the mean annual and maximum annual mean daily discharges exhibit statistically insignificant declines. Annual precipitation averages 1037 mm, varying between 606 mm and 1459 mm, with a non-significant decreasing trend. In contrast, the mean annual air temperatures demonstrate a statistically significant increasing trend, with a pronounced intensification beginning in 1986. The annual runoff coefficients series exhibits a statistically insignificant downward trend, with an average value of 0.293 (range: 0.145–0.399). Application of the New Drought Index (NDI) revealed a marked increase in the frequency of strong and extreme droughts since 2000. Full article

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

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30 pages, 2340 KiB

Open AccessReview

A Systematic Literature Review on the Use of Clays for Arsenic Removal

by Lorenzo Reyes-Bozo, Eduardo Vyhmeister, Gabriel G. Castane, Juan Chirinos, Jeannette Zárraga, Claudia Sandoval-Yáñez and Héctor Valdés-González

Water 2025, 17(9), 1402; https://doi.org/10.3390/w17091402 - 7 May 2025

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Abstract

Arsenic contamination in water remains a critical global challenge, particularly in rural and resource-limited regions. Clays have been widely studied as cost-effective and efficient adsorbents for arsenic removal. This systematic review provides a comprehensive analysis of the application of clays in arsenic adsorption, [...] Read more.

Arsenic contamination in water remains a critical global challenge, particularly in rural and resource-limited regions. Clays have been widely studied as cost-effective and efficient adsorbents for arsenic removal. This systematic review provides a comprehensive analysis of the application of clays in arsenic adsorption, focusing on clay types, operational units, and study methodologies. The review classifies the adsorption mechanisms, highlights key factors influencing adsorption performance—such as pH, ionic strength, and surface modifications—and examines the effectiveness of various modifications. Furthermore, the study categorizes adsorption research into kinetic, iso-thermal, thermodynamic, and efficiency studies, providing insights into the state of the art and the experimental conditions that govern arsenic removal. It also discusses the scalability and practical application of clay-based adsorption technologies, emphasizing gaps in field validation, regeneration studies, and large-scale implementation. The findings highlight the potential of natural and modified clays in arsenic remediation, while underscoring the need for further research to optimize adsorption conditions and enhance sustainability in water treatment systems. Full article

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

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28 pages, 2946 KiB

Open AccessReview

Perfluorooctanoic Acid (PFOA) and Perfluorooctanesulfonic Acid (PFOS) Adsorption onto Different Adsorbents: A Critical Review of the Impact of Their Chemical Structure and Retention Mechanisms in Soil and Groundwater

by Mehak Fatima, Celine Kelso and Faisal Hai

Water 2025, 17(9), 1401; https://doi.org/10.3390/w17091401 - 7 May 2025

Viewed by 349

Abstract

Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are emerging contaminants of concern as they persist in natural environments due to their unique chemical structures. This paper critically reviewed the adsorption of PFOA and PFOS, depending on their chemical structure, by different adsorbents as [...] Read more.

Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are emerging contaminants of concern as they persist in natural environments due to their unique chemical structures. This paper critically reviewed the adsorption of PFOA and PFOS, depending on their chemical structure, by different adsorbents as well as soil. Adsorption of PFOS generally surpasses that of PFOA across various adsorbents. Despite having the same number of carbons, PFOS exhibits greater hydrophobicity due to two major structural differences: firstly, it has one extra CF₂ unit and secondly, the sulfonate group in PFOS, being a relatively hard base, readily adsorbs on oxide surfaces, enhancing its adsorption compared to the carboxylate group in PFOA. While comparing activated carbon (AC) adsorption performance, powdered activated carbon (PAC) demonstrates higher adsorption capacity than granular activated carbon (GAC) for PFOS and PFOA. Anion exchange resin (AER) outperforms other adsorbents, with a maximum adsorption capacity for PFOS twice that of PFOA. Carbon nanotubes (CNTs) exhibit two-fold higher adsorption for PFOS compared to PFOA, with single-walled CNTs showing a distinct advantage. Overall, the removal of PFOS and PFOA under similar conditions on different adsorbents is observed to be in the following order: AER > single-walled CNTs > AC. Moreover, AER, single-walled CNTs, and AC exhibited higher adsorption capacities for PFOS than PFOA. In situ remediation studies of PFOA/S-contaminated soil using colloidal activated carbon show a reduction in concentration to below acceptable limits within 12–24 months. The theoretical and experimental studies cited in this review highlight the role of air–water interfacial adsorption in retaining PFOA and PFOS as a function of their charged head groups during their transport in unsaturated porous media. Full article

(This article belongs to the Special Issue The PFAS (Perfluoroalkyl and Polyfluoroalkyl Substances) Challenges: Environmental Impact and Alternative Treatments)

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22 pages, 2869 KiB

Open AccessReview

A Review on Uses of Lemna minor, a Beneficial Plant for Sustainable Water Treatments, in Relation to Bioeconomy Aspects

by Constantina-Bianca Vulpe, Ioana-Maria Toplicean, Bianca-Vanesa Agachi and Adina-Daniela Datcu

Water 2025, 17(9), 1400; https://doi.org/10.3390/w17091400 - 7 May 2025

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Abstract

This review seeks to highlight the issue of utilizing a widely distributed aquatic species within the broader context of the transition from a linear to a circular economy and the growing emphasis on environmental sustainability. To promote a cleaner aquatic environment and ensure [...] Read more.

This review seeks to highlight the issue of utilizing a widely distributed aquatic species within the broader context of the transition from a linear to a circular economy and the growing emphasis on environmental sustainability. To promote a cleaner aquatic environment and ensure compliance with current regulations, the use of bioindicators and plant bioaccumulators presents a viable alternative. Lemna minor, a small aquatic species, serves as a noteworthy example that warrants greater consideration. A review of specialized literature was conducted to provide a comprehensive overview of these issues, drawing from the most relevant sources. This paper offers a broad discussion on bioeconomy and water management, along with an in-depth examination of L. minor, its characteristics, and its practical applications. The biological characteristics, ecological significance, and useful applications of L. minor in wastewater treatment, bioenergy, and bioproduct production are summarized in this research. The analysis also identifies research gaps for further investigation and looks at how this plant fits into new frameworks for the circular economy. Full article

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

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14 pages, 3107 KiB

Open AccessArticle

Modeling Dependence Structures in Hydrodynamic Landslide Deformation via Hierarchical Archimedean Copula Framework: Case Study of the Donglinxin Landslide

by Rubin Wang, Luyun Tang, Yue Yang, Ning Sun and Yunzi Wang

Water 2025, 17(9), 1399; https://doi.org/10.3390/w17091399 - 7 May 2025

Viewed by 132

Abstract

This study proposes a hierarchical Archimedean copula (HAC) framework to model the complex dependence structures in hydrodynamic landslide deformations, with a focus on the Donglinxin (DLX) landslide. Hierarchical Archimedean copulas, compared to elliptical copulas, offer greater flexibility by requiring fewer parameters while maintaining [...] Read more.

This study proposes a hierarchical Archimedean copula (HAC) framework to model the complex dependence structures in hydrodynamic landslide deformations, with a focus on the Donglinxin (DLX) landslide. Hierarchical Archimedean copulas, compared to elliptical copulas, offer greater flexibility by requiring fewer parameters while maintaining broader applicability. The HAC model, combined with pseudo-maximum likelihood estimation (PMLE), is applied to analyze the interdependencies among the landslide-related variables, such as monthly displacement increments, reservoir water level fluctuations, groundwater variations, and precipitation. A case study of the DLX landslide demonstrates the model’s ability to quantify the critical aspects of landslide deformation, including variable correlations, risk thresholds, conditional probabilities, and return periods. The analysis reveals a strong hierarchical dependence between monthly displacement increments and reservoir water level drops. The model also provides valuable insights into the potential risk factors, helping to optimize landslide monitoring and early-warning systems for more effective disaster mitigation. Full article

(This article belongs to the Special Issue Geotechnics and Geostructures Modelling for Hydrodynamic-Driven Landslides: Prediction and Control)

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21 pages, 4923 KiB

Open AccessArticle

Study on the Effect of Water System Connection on the Improvement of Water Quality of Inner Lakes in Town—Taking Seven Lakes in Yangshuo Urban Area of Guilin as an Example

by Huili Liu, Shuhai Huang, Hang Chen, Mingbo Zuo, Guangyan He, Mei Wang, Shaoyuan Bai, Qin Zhang, Dandan Xu, Yanli Ding and Yanan Zhang

Water 2025, 17(9), 1398; https://doi.org/10.3390/w17091398 - 7 May 2025

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Abstract

Urban lake degradation caused by intensive urbanization necessitates systematic solutions, with water connectivity being a crucial ecological restoration strategy. This study evaluates the two-year effects (2020–2022) of connectivity interventions on seven lakes in Yangshuo, Guilin, classified by connectivity: multi-channel (Mc), single-channel (Sc), and [...] Read more.

Urban lake degradation caused by intensive urbanization necessitates systematic solutions, with water connectivity being a crucial ecological restoration strategy. This study evaluates the two-year effects (2020–2022) of connectivity interventions on seven lakes in Yangshuo, Guilin, classified by connectivity: multi-channel (Mc), single-channel (Sc), and non-connected (Nc). Regular monitoring of the physicochemical parameters and microbial communities revealed significant patterns: multi-channel connected lakes exhibited superior water quality improvement, with trophic state downgrading (weak eutrophic → mesotrophic), but the water quality of Sc-BQ was deteriorating. Seasonal variations showed wet season peaks in pH, DO, COD_Mn, and Chl-a, versus dry season elevations in NH₃-N, NO₃-N, TN, and TP. Correlation analysis identified organic matter as the primary driver of eutrophication, with TN strongly linked to NH₃-N, indicating persistent domestic sewage contamination. Microbial community restructuring was accompanied by changes in water quality, and the abundance and diversity of OTUs decreased after restoration. Notably, Limnohabitans dominated Mc lakes (31.82–35.1%), while Pleurocapsa prevailed (37.85%) in Nc-LH under weak eutrophic conditions. These findings demonstrate that multi-channel connectivity effectively enhances hydrodynamic conditions and pollutant dispersion, whereas inadequate connectivity exacerbates nutrient accumulation. The study provides critical empirical evidence for optimizing urban lake management, emphasizing the necessity of multi-dimensional connectivity designs and targeted control of untreated sewage inputs in water system rehabilitation projects. Full article

(This article belongs to the Topic Sustainable River and Lake Restoration: From Challenges to Solutions)

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24 pages, 6710 KiB

Open AccessArticle

Extreme Precipitation Dynamics and El Niño–Southern Oscillation Influences in Kathmandu Valley, Nepal

by Deepak Chaulagain, Ram Lakhan Ray, Abdulfati Olatunji Yakub, Noel Ngando Same, Jaebum Park, Anthony Fon Tangoh, Jong Wook Roh, Dongjun Suh, Jeong-Ok Lim and Jeung-Soo Huh

Water 2025, 17(9), 1397; https://doi.org/10.3390/w17091397 - 6 May 2025

Viewed by 218

Abstract

Understanding historical climatic extremes and variability is crucial for effective climate change adaptation, particularly for urban flood management in developing countries. This study investigates historical precipitation trends in the Kathmandu Valley, Nepal, focusing on precipitation frequency, intensity, and the influence of the El [...] Read more.

Understanding historical climatic extremes and variability is crucial for effective climate change adaptation, particularly for urban flood management in developing countries. This study investigates historical precipitation trends in the Kathmandu Valley, Nepal, focusing on precipitation frequency, intensity, and the influence of the El Niño–Southern Oscillation (ENSO), using extreme precipitation indices and the precipitation concentration index (PCI). The results reveal sharply fluctuating short-term precipitation from 1980 to 2022, with the exception of an increasing trend during spring (1.17 mm/year) and a decreasing trend in November and December. Trends in extreme precipitation indices are mixed: RX7day shows an increasing trend of 0.1 mm/year, with decadal analysis (1980–2001 and 2002–2022) indicating similar upward patterns. In contrast, RX1day, RX3day, RX5day, and R95pTOT exhibit inconsistent trends, while R99pTOT demonstrates a decreasing trend over the full period (1980–2022). Although the number of days with precipitation ≥ 35 mm has declined, the increasing trend in 7-day maximum precipitation, coupled with no significant change in total annual precipitation and highly variable short-term rainfall, points to a rising risk of unexpected extreme precipitation events. Precipitation patterns in the Kathmandu Valley remain highly irregular across seasons, except during summer. ENSO exhibits a negative correlation with annual precipitation, extreme precipitation indices, and the PCI but shows a positive correlation with the annual and summer PCI as well as 1-day maximum precipitation, emphasizing its significant influence on precipitation variability. These findings highlight the urgent need for targeted climate adaptation strategies and provide valuable insights for hydrologists, meteorologists, policymakers, and urban planners to enhance climate resilience and improve flood management in the Kathmandu Valley. Full article

(This article belongs to the Special Issue Advances in Extreme Hydrological Events Modeling)

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20 pages, 6380 KiB

Open AccessArticle

Mapping and Assessing Groundwater Quality in Bourgogne-Franche-Comté (France): Toward Optimized Monitoring and Management of Groundwater Resource

by Abderrahim Bousouis, Meryem Ayach, Youssouf El Jarjini, Ismail Mohsine, Laurence Ravung, Saïd Chakiri, Abdelhak Bouabdli, Vincent Valles and Laurent Barbiero

Water 2025, 17(9), 1396; https://doi.org/10.3390/w17091396 - 6 May 2025

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Abstract

To optimize the management of groundwater resources in the Bourgogne-Franche-Comté (BFC, France) region, data from the Size-Eaux database were cross-referenced with the French Reference Framework for Groundwater Bodies (GWB). The information contained in this dataset was synthesized using Principal Component Analysis (PCA), followed [...] Read more.

To optimize the management of groundwater resources in the Bourgogne-Franche-Comté (BFC, France) region, data from the Size-Eaux database were cross-referenced with the French Reference Framework for Groundwater Bodies (GWB). The information contained in this dataset was synthesized using Principal Component Analysis (PCA), followed by Agglomerative Hierarchical Clustering (AHC) of GWBs based on their average coordinates along the main factorial axes. The results reveal 11 distinct GWB groups, each internally homogeneous in terms of chemical composition and ongoing processes responsible for intra-group variability. The distribution of the groups aligns with the region’s structural geology, lithology, and agricultural activity patterns. Livestock farming areas, prone to fecal contamination, and cereal-growing areas, characterized by high nitrate concentrations, stand out distinctly. Furthermore, the analysis of GWB groups highlights regional processes such as denitrification, confirming the existence of spatial structuring of these mechanisms beyond local specificities. The major physicochemical and bacteriological zones show strong contrasts between groups while maintaining significant internal homogeneity. Despite the region’s vast size and diversity, spanning three major watersheds, further subdivision was not necessary to obtain applicable results. These findings confirm observations made in other regions and pave the way for an optimized monitoring and surveillance strategy. Full article

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

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21 pages, 504 KiB

Open AccessArticle

Biomimicry-Inspired Automated Machine Learning Fit-for-Purpose Wastewater Treatment for Sustainable Water Reuse

by Vasileios Alevizos, Zongliang Yue, Sabrina Edralin, Clark Xu, Nikitas Georlimos and George A. Papakostas

Water 2025, 17(9), 1395; https://doi.org/10.3390/w17091395 - 6 May 2025

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Abstract

The growing global freshwater scarcity urgently requires innovative wastewater treatment technologies. This study hypothesized that biomimicry-inspired automated machine learning (AML) could effectively manage wastewater variability through adaptive processing techniques. Utilizing decentralized swarm intelligence, specifically the Respected Parametric Insecta Swarm (RPIS), the system demonstrated [...] Read more.

The growing global freshwater scarcity urgently requires innovative wastewater treatment technologies. This study hypothesized that biomimicry-inspired automated machine learning (AML) could effectively manage wastewater variability through adaptive processing techniques. Utilizing decentralized swarm intelligence, specifically the Respected Parametric Insecta Swarm (RPIS), the system demonstrated robust adaptability to fluctuating influent conditions, maintaining stable effluent quality without centralized control. Bio-inspired oscillatory control algorithms maintained stability under dynamic influent scenarios, while adaptive sensor feedback enhanced real-time responsiveness. Machine learning (ML) methods inspired by biological morphological evolution accurately classified influent characteristics (F1 score of 0.91), optimizing resource allocation dynamically. Significant reductions were observed, with chemical consumption decreasing by approximately 11% and additional energy usage declining by 14%. Furthermore, bio-inspired membranes with selective permeability substantially reduced fouling, maintaining minimal fouling for up to 30 days. Polynomial chaos expansions efficiently approximated complex nonlinear interactions, reducing computational overhead by approximately 35% through parallel processing. Decentralized swarm algorithms allowed the rapid recalibration of system parameters, achieving stable pathogen removal and maintaining effluent turbidity near 3.2 NTU (Nephelometric Turbidity Units), with total suspended solids consistently below 8 mg/L. Integrating biomimicry with AML thus significantly advances sustainable wastewater reclamation practices, offering quantifiable improvements critical for resource-efficient water management. Full article

(This article belongs to the Special Issue Driving Water Reuse by New Technologies, Land Use and Infrastructure Planning, and Legislation Policies)

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15 pages, 6813 KiB

Open AccessArticle

Bedload Dynamics in a Partially Glaciated Catchment: Insights from over One Decade of Measuring Bedload Transport Processes and Future Perspectives Under Climate Change

by Sabrina Schwarz, Michael Paster, Andrea Lammer, Dorian Shire-Peterlechner, Michael Tritthart, Helmut Habersack and Rolf Rindler

Water 2025, 17(9), 1394; https://doi.org/10.3390/w17091394 - 6 May 2025

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Abstract

Glacial retreat is a widely recognised phenomenon, and yet the processes of glaciofluvial bedload in high-alpine river systems remain largely unobserved. This study investigates the impact of hydrological and climatic changes on bedload and water discharge dynamics in the Rofenache catchment in the [...] Read more.

Glacial retreat is a widely recognised phenomenon, and yet the processes of glaciofluvial bedload in high-alpine river systems remain largely unobserved. This study investigates the impact of hydrological and climatic changes on bedload and water discharge dynamics in the Rofenache catchment in the Ötztal Alps over a 14-year period. Utilising high-resolution bedload data from plate geophones and direct calibration measurements, we analyse water discharge and bedload transport, focusing on hysteresis events influenced by temperature and precipitation. Our findings reveal that water discharge and bedload transport processes are non-linear, with counterclockwise hysteresis dominating; this is consistent with previous studies in glaciated catchment areas. The inclusion of temperature and precipitation data further highlights the significant influence of temperature on hysteresis events in the catchment area. This research provides insights into the bedload dynamics of a high-alpine river under the effects of climate change, emphasising the need for continued monitoring and analysis to understand the evolving interactions between hydrological and sedimentological processes and climatic factors in partially glaciated catchments. Full article

(This article belongs to the Special Issue Advances in River Restoration and Sediment Transport Management)

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15 pages, 9822 KiB

Open AccessArticle

Suitability Evaluation of Ecological Restoration Relying on Water Resources in an Agro-Pastoral Transition Zone: A Case Study of Zhangbei, Zhangjiakou, Northern China

by Jin-Jie Miao, Yi-Hang Gao, Ying Zhang, Xue-Sheng Gao, Dan-Hong Xu, Jun-Quan Yang, Wei Wang and Hong-Wei Liu

Water 2025, 17(9), 1393; https://doi.org/10.3390/w17091393 - 6 May 2025

Viewed by 162

Abstract

(1) Background: Ecological restoration is crucial to improve ecological functions and optimize its security patterns. The Zhangbei of Zhangjiakou, a typical agro-pastoral transition zone, was studied as an example to conduct ecological restoration suitability evaluation in northern China. (2) Methods: suitability of ecological [...] Read more.

(1) Background: Ecological restoration is crucial to improve ecological functions and optimize its security patterns. The Zhangbei of Zhangjiakou, a typical agro-pastoral transition zone, was studied as an example to conduct ecological restoration suitability evaluation in northern China. (2) Methods: suitability of ecological restoration in Zhangbei was assessed by both single factor analysis and comprehensive factor analysis, which were based on the data of regional water resources, ecosystem service function, and ecosystem sensitivity obtained from a high-precision environmental survey. (3) Results and conclusions: The results show that in Zhangbei County, areas classified as important and extremely important for ecosystem service functions account for 50.32%, ecologically sensitive and highly sensitive areas represent 5.95%, and regions designated as important and extremely important for ecological protection cover 52.70%. Furthermore, ecological restoration of Zhangbei was divided into four ecological restoration zones: agro-forest–wetland ecological restoration and soil erosion control zone, agro-forest–wetland ecological restoration and water conservation zone, forest–grassland soil erosion and soil–water conservation zone, and mountain forest conservation and biodiversity maintenance zone. The study can be a scientific case study for local ecosystem restoration and conservation. In the future, this study will further explore multi-source data fusion, the establishment of a multi-scale evaluation system, and the trade-off analysis between conservation and development. Full article

(This article belongs to the Special Issue Wetland Conservation and Ecological Restoration)

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15 pages, 3811 KiB

Open AccessArticle

Rainfall-Induced Slope Instability in Tropical Regions Under Climate Change Scenarios

by Rajendra Kumar P, Kasinathan Muthukkumaran, Chetan Sharma, Anoop Kumar Shukla and Surendra Kumar Sharma

Water 2025, 17(9), 1392; https://doi.org/10.3390/w17091392 - 6 May 2025

Viewed by 233

Abstract

The reduction in the stability of rock slopes due to rainfall is a significant issue in tropical regions. Unsaturated soil, commonly found on hill slopes, provides higher shear strength compared to saturated soil due to matric suction. Soil moisture plays a crucial role [...] Read more.

The reduction in the stability of rock slopes due to rainfall is a significant issue in tropical regions. Unsaturated soil, commonly found on hill slopes, provides higher shear strength compared to saturated soil due to matric suction. Soil moisture plays a crucial role in determining slope stability during rainfall events, yet it is often overlooked in geotechnical engineering projects. This study integrates both steady-state and transient analyses to examine how rainfall intensity affects the stability of a rock slope near a tunnel portal. Transient seepage analysis was conducted using SEEP/W to simulate changes in pore water pressure (PWP) resulting from rainfall infiltration under historical and future precipitation conditions. The analysis considers medium (SSP245) and worst-case (SSP585) climate change scenarios as per Coupled Model Intercomparison Project Phase 6 (CMIP6). The findings underscore the significant impact of rainfall-induced infiltration on slope stability and highlight the importance of incorporating soil moisture dynamics in slope stability assessments. The safety factor, initially 1.54 before accounting for rainfall effects, decreases to 1.34 when the effects of rainfall are included. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources—an Issue of Environmental Global Safety)

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12 pages, 737 KiB

Open AccessTechnical Note

Limited Time Resolution of Event Data Loggers Can Bias Intensity Measurements from Tipping-Bucket Rain Gauges

by David Dunkerley

Water 2025, 17(9), 1391; https://doi.org/10.3390/w17091391 - 6 May 2025

Viewed by 153

Abstract

Event data loggers are frequently used to record the date and time of tip events in tipping-bucket rain gauges. The HOBO^® pendant event data logger is one such commercially available device commonly used for this purpose. It can record the contact closure [...] Read more.

Event data loggers are frequently used to record the date and time of tip events in tipping-bucket rain gauges. The HOBO^® pendant event data logger is one such commercially available device commonly used for this purpose. It can record the contact closure of a TBGR reed switch at a maximum timing resolution of 1 s, tied to the timing of the logger clock, which is set each time the logger is launched. These event loggers are ideal for the routine recording of rainfall. This paper addresses the issue of whether they can also be relied upon when estimating short-term intensities, for which they were not designed. New experiments show that for a series of switch closures at fixed intervals other than exact multiples of 1 s, the HOBO^® logger fails to record evenly spaced tip events. Thus, for example, with pulses at fixed 2.75 s intervals, the logger records some events as occurring at 2 s intervals and others at 3 s intervals. This quantization error means that there can be large errors in the logged time between bucket tip events. In natural rainfall, tip events can occur at any time, and inter-tip times, from which intensity can be estimated, will generally not be an integral number of seconds. Consequently, particularly in intense rain, the logger behaviour just described can lead to erroneous estimates of the rainfall rate estimated from the duration of individual inter-tip times. Possible solutions are discussed. Full article

(This article belongs to the Special Issue Urban Flood Mitigation and Sustainable Stormwater Management—2nd Edition)

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21 pages, 8888 KiB

Open AccessArticle

A Study on the Deformation Mechanism of a Landslide Reinforced with an Anti-Slip Pile Under the Effect of Reservoir Water Level Decline

by Gang Yang, Zhuolin Wu, Lin Zhang, Jingfeng Hou, Shen Tong, Fei Liu and Yong Zheng

Water 2025, 17(9), 1390; https://doi.org/10.3390/w17091390 - 6 May 2025

Viewed by 243

Abstract

The fluctuation of reservoir water levels is a critical factor influencing the evolution of reservoir landslide–anti-slide pile systems. To investigate the reinforcement mechanism of anti-slide piles in reservoir landslides under the effect of reservoir water level fluctuations, this study employs numerical simulation methods [...] Read more.

The fluctuation of reservoir water levels is a critical factor influencing the evolution of reservoir landslide–anti-slide pile systems. To investigate the reinforcement mechanism of anti-slide piles in reservoir landslides under the effect of reservoir water level fluctuations, this study employs numerical simulation methods to establish a three-dimensional slope model, simulating the drawdown process of the reservoir water level from 175 m to 145 m. The displacement and strain fields of the reservoir landslide during the water level drawdown are analyzed. Furthermore, the strain characteristics of the anti-slide pile-reinforced reservoir landslide under stress–seepage coupling are studied, and the prevention effectiveness of the landslide–anti-slide pile interaction system is explored. The results indicate that the drawdown of the reservoir water level can lead to the gradual expansion of the strain and displacement zones in the landslide, as well as a reduction in the safety factor. Under the effect of anti-slide piles, the maximum deformation of the reservoir landslide is significantly reduced. The optimal reinforcement effect is achieved when the anti-slide piles are arranged in the middle of the reservoir landslide, with a pile spacing of four times the pile diameter and an embedded depth reaching the critical depth. The findings of this study can provide a scientific basis for analyzing the instability mechanisms and mitigation of reservoir landslides. Full article

(This article belongs to the Special Issue Theory and Technology of Water-Induced Geological Disaster Prevention and Water Resource Utilization in Mines)

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18 pages, 4012 KiB

Open AccessArticle

Synthesis of Hydroxyapatite Mulberry Stem Biochar Composites for Efficient Pb(II) Adsorption from Aqueous Solutions

by Dunqiu Wang, Xinyu Zhou, Meina Liang and Zimeng Wu

Water 2025, 17(9), 1389; https://doi.org/10.3390/w17091389 - 5 May 2025

Viewed by 274

Abstract

In this study, two biochar composites, namely hydroxyapatite/mulberry stem biochar (HMp) and magnesium-doped HMp (Mg0.1-HMp), were prepared using mulberry stem as the major raw material using the sol–gel process. Characterization and batch experiments were carried out on HMp and Mg0.1-HMp to investigate the [...] Read more.

In this study, two biochar composites, namely hydroxyapatite/mulberry stem biochar (HMp) and magnesium-doped HMp (Mg0.1-HMp), were prepared using mulberry stem as the major raw material using the sol–gel process. Characterization and batch experiments were carried out on HMp and Mg0.1-HMp to investigate the Pb(II) adsorption mechanism and the factors affecting the adsorption, respectively. The results indicated that carboxylic compounds, phenols, and carbonyl functional groups were formed on the surfaces of HMp and Mg0.1-HMp. At an optimal pH of 5, an adsorption period of 6 h was achieved at an initial Pb(II) concentration of 100 mg/L and adsorbent quantity of 2 g/L. The maximum Pb(II) adsorption capacities of the HMp and Mg0.1-HMp were 303.03 and 312.50 mg/g, respectively, at 25 °C. The maximum Pb(II) adsorption capacity of Mg0.1-HMp was 2.55 times more than that of mulberry stem biochar (MBC). The adsorption of Pb(II) by HMp and Mg0.1-HMp is consistent with the Langmuir isotherm and pseudo-second-order kinetic models, demonstrating a spontaneous, endothermic, and irreversible process dominated by monolayer chemical adsorption. These results show that the mechanisms of Pb(II) by Mg0.1-HMp mainly involved electrostatic interaction, complexation, precipitation, and ion exchange. Full article

(This article belongs to the Special Issue Adsorption Technologies in Wastewater Treatment Processes)

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18 pages, 12080 KiB

Open AccessArticle

Synergistic Regulation of Soil Salinity and Ion Transport in Arid Agroecosystems: A Field Study on Drip Irrigation and Subsurface Drainage in Xinjiang, China

by Qianqian Zhu, Hui Wang, Honghong Ma, Feng Ding, Wanli Xu, Xiaopeng Ma and Yanbo Fu

Water 2025, 17(9), 1388; https://doi.org/10.3390/w17091388 - 5 May 2025

Viewed by 275

Abstract

The salinization of cultivated soil in arid zones is a core obstacle restricting the sustainable development of agriculture, particularly in regions like Xinjiang, China, where extreme aridity and intensive irrigation practices exacerbate salt accumulation through evaporation–crystallization cycles. Conventional drip irrigation, while temporarily mitigating [...] Read more.

The salinization of cultivated soil in arid zones is a core obstacle restricting the sustainable development of agriculture, particularly in regions like Xinjiang, China, where extreme aridity and intensive irrigation practices exacerbate salt accumulation through evaporation–crystallization cycles. Conventional drip irrigation, while temporarily mitigating surface salinity, often leads to secondary salinization due to elevated water tables and inefficient leaching. Recent studies highlight the potential of integrating drip irrigation with subsurface drainage systems to address these challenges, yet the synergistic mechanisms governing ion transport dynamics, hydrochemical thresholds, and their interaction with crop physiology remain poorly understood. In this study, we analyzed the effects of spring irrigation during the non-fertile period, soil hydrochemistry variations, and salt ion dynamics across three arid agroecosystems in Xinjiang. By coupling drip irrigation with optimized subsurface drainage configurations (burial depths: 1.4–1.6 m; lateral spacing: 20–40 m), we reveal a layer-domain differentiation in salt migration, Cl⁻ and Na⁺ were leached to 40–60 cm depths, while SO₄²⁻ formed a “stagnant salt layer” at 20–40 cm due to soil colloid adsorption. Post-irrigation hydrochemical shifts included a 40% decline in conductivity, emphasizing the risk of adsorbed ion retention. Subsurface drainage systems suppressed capillary-driven salinity resurgence, maintaining salinity at 8–12 g·kg⁻¹ in root zones during critical growth stages. This study establishes a “surface suppression–middle blocking–deep leaching” three-dimensional salinity control model, providing actionable insights for mitigating secondary salinization in arid agroecosystems. Full article

(This article belongs to the Special Issue Advanced Technologies in Agricultural Water-Saving Irrigation)

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14 pages, 3426 KiB

Open AccessArticle

The Application of an Infrared-Based ECG Acquisitor in an Online Healthy Assessment System: The Effect of Temperature on Cardiac Function in Carp (Cyprinus carpio)

by Miao Yu and Zongming Ren

Water 2025, 17(9), 1387; https://doi.org/10.3390/w17091387 - 5 May 2025

Viewed by 260

Abstract

Carp (Cyprinus carpio) is one of the major farmed fish species in China. In recent years, the increasing water temperature caused by global warming has caused physiological stress in fish, which in turn affects the heart function and health of the [...] Read more.

Carp (Cyprinus carpio) is one of the major farmed fish species in China. In recent years, the increasing water temperature caused by global warming has caused physiological stress in fish, which in turn affects the heart function and health of the fish. Therefore, we hypothesized that the electrocardiogram (ECG) parameters of carp could reflect the temperature-induced stress. To test this hypothesis, in this study, the real-time online cardiac function assessment system (OCFAS) was used to monitor the electrocardiogram signals (heart rate, P wave, R wave, T wave, P-R interval, QRS complex, Q-T interval) of carp at different temperatures. The results showed that the heart rate of the fish increased with the temperature within a certain range. However, when the temperature exceeded this range, the cardiac function of the fish was significantly impaired. The P-R interval was shortened with the increase in the body temperature, and there was a negative correlation between them. This study emphasizes the importance of using real-time online fish ECG assessments to evaluate cardiac health, and it further improves the evaluation index system for ECG in fish. At the same time, the temperature in aquaculture and water environments requires special attention to avoid its adverse effects on the health of aquatic populations. Full article

(This article belongs to the Special Issue Studies on Toxic Effects in Aquatic Organisms and Ecosystems)

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16 pages, 3245 KiB

Open AccessArticle

Nutrient Monitoring and Comparison of On-Site Community Science Data Collection Methods for Indigenous Water Protection

by Jaclyn D. Porter, Lori Bradford, Tim D. Jardine, Myron Neapetung, Lalita A. Bharadwaj, Graham Strickert and Justin Burns

Water 2025, 17(9), 1386; https://doi.org/10.3390/w17091386 - 5 May 2025

Viewed by 244

Abstract

Excessive nutrient loading in freshwater is a water quality and safety concern for Indigenous communities, especially those with inadequate water treatment. Continuous nutrient monitoring efforts in collaboration with community members require cost-effective but information-rich methods. Data gathered through community-science approaches could enhance source [...] Read more.

Excessive nutrient loading in freshwater is a water quality and safety concern for Indigenous communities, especially those with inadequate water treatment. Continuous nutrient monitoring efforts in collaboration with community members require cost-effective but information-rich methods. Data gathered through community-science approaches could enhance source water protection programs and can provide first-hand knowledge and expertise through reciprocal information exchange with local community members. Yet, there are still misconceptions about the validity of data gathered by community scientists. This study validates the use of two inexpensive nutrient monitoring devices (YSI 9500 Photometer and the Nutrient Smartphone App) for community-based environmental research by testing the accuracy of each device, identifying nutrient hotspots, and determining if nutrient concentrations relate to precipitation patterns in a drought-prone region of Saskatchewan within the Lake Winnipeg Basin in Canada. We found that the measurement accuracy of these devices varied depending on the compound tested, with the poorest results for nitrate (r² = 0.07) and the best results for phosphate (r² = 0.89) when using the photometer. Seasonal nutrient concentration patterns differed between the years of moderate (2019) and low (2021) precipitation, but there was no correlation between rainfall amounts and nutrient concentrations, suggesting other drivers. This study identifies the strengths and weaknesses of cost-effective nutrient testing devices, guiding continuous monitoring efforts with communities. Full article

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

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27 pages, 17175 KiB

Open AccessArticle

Study on the Coordinated Regulation of Storage and Discharge Mode in Plain Cities Under Extreme Rainfall: A Case Study of a Southern Plain City

by Zhe Wang, Zhiming Zhang, Qianting Liu and Liangrui Yang

Water 2025, 17(9), 1385; https://doi.org/10.3390/w17091385 - 4 May 2025

Viewed by 321

Abstract

Under the influence of climate change, extreme rainfall events (EREs) have become increasingly frequent. The urban waterlogging caused by these events has a particularly significant impact on cities with flat terrain and inadequate surface runoff dynamics. This study proposes a Coordinated Regulation of [...] Read more.

Under the influence of climate change, extreme rainfall events (EREs) have become increasingly frequent. The urban waterlogging caused by these events has a particularly significant impact on cities with flat terrain and inadequate surface runoff dynamics. This study proposes a Coordinated Regulation of Storage and Discharge Mode (CRSD) tailored for plain cities. It establishes an evaluation system for CRSD based on regional rainwater flood carrying capacity, drainage capacity, and regional value, thereby assigning customized storage and drainage strategies to different urban areas. The model optimizes the relationship between storage and drainage across regions based on the fundamental principles of CRSD and establishes dynamic cross-regional water distribution rules according to optimization objectives. Finally, CRSD is validated using the MIKE models. The results indicate that as the rainfall return period increases, the area affected by urban waterlogging expands, though the proportion of waterlogging across various severity levels remains stable. CRSD can effectively alleviate urban waterlogging caused by EREs, with waterlogging reduction percentages ranging from 12.21% to 18.50%. Among the optimization schemes, Safe Consumption (SC) delivers the best overall performance, reducing waterlogging by up to 1.80 km² under 500 yr. The Average Pressure (AP) performs best in high-value areas, reducing waterlogging by up to 1.96 km² under the same return period. This study advances urban flood management by integrating cross-regional coordination mechanisms with blue–green–grey infrastructure, providing a replicable strategy for flatland cities to cope with the increasing challenges of EREs. Full article

(This article belongs to the Section Urban Water Management)

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53 pages, 1194 KiB

Open AccessReview

An Overview of Evapotranspiration Estimation Models Utilizing Artificial Intelligence

by Mercedeh Taheri, Mostafa Bigdeli, Hanifeh Imanian and Abdolmajid Mohammadian

Water 2025, 17(9), 1384; https://doi.org/10.3390/w17091384 - 4 May 2025

Viewed by 511

Abstract

Evapotranspiration (ET) has a significant role in various natural and human systems, such as water cycle balance, climate regulation, ecosystem health, agriculture, hydrological cycle, water resource management, and climate studies. Among various approaches that are employed for estimating ET, the Penman–Monteith equation is [...] Read more.

Evapotranspiration (ET) has a significant role in various natural and human systems, such as water cycle balance, climate regulation, ecosystem health, agriculture, hydrological cycle, water resource management, and climate studies. Among various approaches that are employed for estimating ET, the Penman–Monteith equation is known as the widely accepted reference approach. However, the extensive data requirement of this method is a crucial challenge that limits its usage, particularly in data-scarce regions. Therefore, as an alternative approach, artificial intelligence (AI) models have gained prominence for estimating evapotranspiration because of their capacity to handle complicated relationships between meteorological variables and water loss processes. These models leverage large datasets and advanced algorithms to provide accurate and timely ET predictions. The current research aims to review previous studies addressing the application of the AI model in ET modeling under four main categories: neuron-based, tree-based, kernel-based, and hybrid models. The results of this study indicated that traditional models like the Penman–Monteith (PM) require extensive input data, while AI-based approaches offer promising alternatives due to their ability to model complex nonlinear relationships. Despite their potential, AI models face challenges such as overfitting, interpretability, inconsistent input variable selection, and lack of integration with physical ET processes, highlighting the need for standardized input configurations, better pre-processing techniques, and incorporation of hydrological and remote sensing data. Full article

(This article belongs to the Special Issue Climate Change and Hydrological Processes, 2nd Edition)

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17 pages, 3023 KiB

Open AccessArticle

Towards More Accurate Risk Assessment of Sediment Trace Metals: Integrating Sedimentary Background Determination and Probabilistic Evaluation in Chaohu Lake, China

by Wenguang Luo, Jiantao Zhang, Mian Wang and Jinxiao Zhao

Water 2025, 17(9), 1383; https://doi.org/10.3390/w17091383 - 4 May 2025

Viewed by 282

Abstract

Accurate ecological risk assessment of trace metals in lake sediments remains a significant challenge due to the widespread use of generalized regional background values, which often fail to capture the spatial and historical heterogeneity of sedimentary environments. This study addresses this gap by [...] Read more.

Accurate ecological risk assessment of trace metals in lake sediments remains a significant challenge due to the widespread use of generalized regional background values, which often fail to capture the spatial and historical heterogeneity of sedimentary environments. This study addresses this gap by establishing sediment-specific background values of heavy metals through high-resolution core sampling from three representative zones (western, central, and eastern) of Chaohu Lake, China. The determined variation depths (36.60 cm, 21.35 cm, and 47.58 cm) allowed for the reconstruction of pre-contamination baselines for key trace metals. These refined background values were then incorporated into enhanced ecological risk assessment frameworks, including the geo-accumulation index (I_geo) and a modified potential ecological risk index (RI), which integrates chemical accumulation with toxicity units (∑TU). A probabilistic risk assessment based on the refined RI was further conducted using a large sediment dataset. The results revealed that 67.0% of the samples posed low ecological risk, while 33.0% fell into the moderate-risk category, with mercury (Hg), arsenic (As), and nickel (Ni) identified as the primary contributors. This study demonstrates that sediment-specific background values, when combined with probabilistic risk modeling, offer a more accurate, site-relevant, and scientifically grounded approach for assessing and managing trace metal contamination in lake systems. Full article

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

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15 pages, 4816 KiB

Open AccessArticle

Numerical Investigation on the Hydrodynamic Coefficients of Subsea Suspended Pipelines Under Unidirectional Currents

by Xiaowei Huang, Deping Zhao, Ganqing Zuo, Jianfeng Ren and Guoqiang Tang

Water 2025, 17(9), 1382; https://doi.org/10.3390/w17091382 - 4 May 2025

Viewed by 220

Abstract

Hydrodynamic coefficients of subsea suspended pipelines are crucial for fatigue and stability assessments. The effect of the gap height to diameter ratio e/D (0.1 ≤ e/D ≤ 2.0) and boundary layer thickness to diameter ratio δ/D (0.5 [...] Read more.

Hydrodynamic coefficients of subsea suspended pipelines are crucial for fatigue and stability assessments. The effect of the gap height to diameter ratio e/D (0.1 ≤ e/D ≤ 2.0) and boundary layer thickness to diameter ratio δ/D (0.5 ≤ δ/D ≤ 3.0) on the force coefficients under unidirectional current conditions with the Reynolds numbers Re in the range of 1 × 10⁴ ≤ Re ≤ 1 × 10⁵ are investigated via numerical simulations. The results show that the average drag coefficient increases, whereas the average lift coefficient decreases gradually with the increasing e/D. The vortex shedding is inhibited by the wall for e/D < 0.24, starts at e/D = 0.24, becomes stronger with the increase in e/D in the range from 0.24 to 0.5, and approximates to that behind a wall-free cylinder for e/D > 0.5. The effect of δ/D can be eliminated if the coefficients are normalized by the undisturbed flow velocity at the height of the center of the pipeline. Moreover, empirical prediction formulas are proposed describing the drag and lift coefficients as the function of e/D, which can be applied to engineering designs related to free spans. Full article

(This article belongs to the Special Issue Hydrodynamics and Sediment Transport in Ocean Engineering—Second Edition)

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20 pages, 9678 KiB

Open AccessArticle

Precipitation Spatio-Temporal Forecasting in China via DC-CNN-BiLSTM

by Peng Shu, Xiaoqi Duan, Chenming Shao, Jie Liu, Youliang Tian and Sheng Li

Water 2025, 17(9), 1381; https://doi.org/10.3390/w17091381 - 4 May 2025

Viewed by 329

Abstract

Accurate and reliable precipitation prediction remains a significant challenge due to an incomplete understanding of regional meteorological dynamics and limitations in forecasting routine weather events. To overcome these challenges, we propose a novel model, DC-CNN-BiLSTM, which integrates a dilation causal convolutional neural network [...] Read more.

Accurate and reliable precipitation prediction remains a significant challenge due to an incomplete understanding of regional meteorological dynamics and limitations in forecasting routine weather events. To overcome these challenges, we propose a novel model, DC-CNN-BiLSTM, which integrates a dilation causal convolutional neural network (DC-CNN) with a Bidirectional Long Short-Term Memory (BiLSTM) network. The DC-CNN component, by fusing causal and dilated convolutions, extracts multi-scale spatial features from time series data. In parallel, the BiLSTM module leverages bidirectional memory cells to capture long-term temporal dependencies. This integrated approach effectively links localized meteorological inputs with broader hydrological responses. Experimental evaluation demonstrates that the DC-CNN-BiLSTM model significantly outperforms traditional models. Specifically, the model improves the Root Mean Square Error (RMSE) by 9.05% compared to ConvLSTM and by 32.3% compared to ConvGRU, particularly in forecasting medium- to long-term precipitation. In conclusion, our results validate the benefits of incorporating advanced spatio-temporal feature extraction techniques for precipitation forecasting, ultimately improving disaster preparedness and resource management. Full article

(This article belongs to the Special Issue Advances in Crop Evapotranspiration and Soil Water Content)

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22 pages, 31214 KiB

Open AccessArticle

A Comparative Study of a Two-Dimensional Slope Hydrodynamic Model (TDSHM), Long Short-Term Memory (LSTM), and Convolutional Neural Network (CNN) Models for Runoff Prediction

by Yuhao Zhou, Jing Pan and Guangcheng Shao

Water 2025, 17(9), 1380; https://doi.org/10.3390/w17091380 - 3 May 2025

Viewed by 216

Abstract

Accurate runoff prediction in complex slope catchments remains challenging due to terrain heterogeneity and dynamic rainfall interactions. This study conducts a systematic comparison between a physics-based Two-Dimensional Slope Hydrodynamic Model (TDSHM) and data-driven deep learning models (LSTM and CNN) for runoff forecasting under [...] Read more.

Accurate runoff prediction in complex slope catchments remains challenging due to terrain heterogeneity and dynamic rainfall interactions. This study conducts a systematic comparison between a physics-based Two-Dimensional Slope Hydrodynamic Model (TDSHM) and data-driven deep learning models (LSTM and CNN) for runoff forecasting under variable rainfall conditions. Using 214 rainfall–runoff events (2013–2023) from the Qiaotou watershed in Nanjing, China, the TDSHM integrates rainfall momentum, wind effects, and hydrodynamic principles to resolve spatiotemporal flow dynamics, while LSTM and CNN models leverage seven hydrological features for data-driven predictions. Results demonstrate that the TDSHM achieved superior accuracy, with a mean relative error of 10.77%, Nash–Sutcliffe Efficiency (NSE) of 0.801, and Mean Absolute Error (MAE) of 3.17 mm, outperforming LSTM (24.38% error, NSE = 0.751, MAE = 4.61 mm) and CNN (28.10% error, NSE = 0.506, MAE = 6.82 mm). The TDSHM’s explicit physical interpretability enabled precise simulation of vegetation-modulated runoff processes, validated against field observations (92% predictions within ±15% error). While LSTM captured temporal dependencies effectively, CNN exhibited limitations in sequential data processing. This study highlights the TDSHM’s robustness for scenarios requiring mechanistic insights and the complementary role of LSTM in data-rich environments. The findings provide critical guidance for flood risk management, soil conservation, and model selection trade-offs between physical fidelity and computational efficiency. Full article

(This article belongs to the Section Hydrology)

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22 pages, 8377 KiB

Open AccessArticle

Numerical Modeling and Sea Trial Studies of Oil Spills in the Sea Area from Haikou to Danzhou

by Weihang Wang, Bijin Liu, Zhen Guo, Zhenwei Zhang and Chao Chen

Water 2025, 17(9), 1379; https://doi.org/10.3390/w17091379 - 3 May 2025

Viewed by 252

Abstract

This study utilized the FVCOM model to establish a hydrodynamic model for the waters from Haikou to Danzhou. Based on this framework, a numerical model for oil spill drift and diffusion was developed using the Lagrangian particle method, incorporating processes such as advection, [...] Read more.

This study utilized the FVCOM model to establish a hydrodynamic model for the waters from Haikou to Danzhou. Based on this framework, a numerical model for oil spill drift and diffusion was developed using the Lagrangian particle method, incorporating processes such as advection, diffusion, spreading, emulsification, dissolution, volatilization, and shoreline adsorption. Sea experiments involving drifters and dye were conducted to validate the oil spill model. The model was subsequently applied to analyze the impacts of tidal phases and wind fields on oil spill trajectories, predict affected areas, and assess risks to environmentally sensitive zones. The results demonstrate that the hydrodynamic model accurately reproduces the tidal current characteristics of the study area. Validation using drifter and dye experiments confirmed that the model’s predictive error remains within 20%, meeting operational forecasting standards. Potential sources of error include uncertainties in wind–wave–current interactions and discrepancies in windage coefficients between oil spills and drifters. Tidal currents and wind fields were identified as the dominant drivers of oil spill drift and diffusion. Under southerly wind conditions, the oil spill exhibited the largest spatial extent, covering 995.25 km² with a trajectory length of 226.92 km. A sensitivity analysis highlighted the Lingao Silverlip Pearl Oyster Marine Protected Area and Shatu Bay Beach as high-risk regions. The developed model provides critical technical support for oil spill emergency response under diverse environmental conditions, enabling proactive pathway forecasting and preventive measures to mitigate ecological damage. Full article

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

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17 pages, 2988 KiB

Open AccessArticle

Comparative Analysis of Nonlinear Models from Different Domains: A Case Study on the Quality of Groundwater in an Alluvial Aquifer in Northwestern Croatia

by Ivan Kovač, Marko Šrajbek, Nikola Sakač and Jasna Nemčić-Jurec

Water 2025, 17(9), 1378; https://doi.org/10.3390/w17091378 - 2 May 2025

Viewed by 289

Abstract

In groundwater quality analysis, nonlinear models are typically used, with domains spanning the entire real number line. In this study, alongside these models (Logistic, Gompertz and Richards), nonlinear models defined based on functions whose domain is only the positive part of the real [...] Read more.

In groundwater quality analysis, nonlinear models are typically used, with domains spanning the entire real number line. In this study, alongside these models (Logistic, Gompertz and Richards), nonlinear models defined based on functions whose domain is only the positive part of the real number line are presented (Michaelis–Menten, Hill 1 and 2 and Rosin–Rammler 1 and 2). Two case studies were observed in the paper: (i) the dependence of nitrate concentration on the pumping rate in the Bartolovec wellfield, and (ii) the dependence of nitrate concentration on the distance from the source of pollution in the Varaždin wellfield. Both wellfields are located in the alluvial aquifer in northwestern Croatia. In this way, the curves obtained on the basis of the mentioned mathematical functions were fitted to the experimental data. The results show a good fit, so that the values of the coefficients of determination R² are greater than 0.82 for the case study (i) and greater than 0.96 for the case study (ii). Since the models differ in the number of parameters (e.g., three parameters for Michaelis–Menten and five parameters for Rosin–Rammler), the corrected Akaike information criterion (AIC_c) was used for their comparison. In this way, the best fit for the case study (i) was obtained for the Rosin–Rammler 1 model, while for the case study (ii), it was for the Hill 1 model. A t-test was performed for all models, and they can be considered reliable at a significance level of 0.05. However, t-values and p-values were also calculated for each parameter of each model. Based on these results, it is concluded that all model parameters can be considered reliable at a significance level of 0.05 only for the Hill 1 and Rosin–Rammler 1 models in both case studies. For this reason, these models can generally be considered the best fit to the experimental data. The study demonstrates the superiority of nonlinear models with domains restricted to positive real numbers (e.g., Hill 1, Rosin–Rammler 1) over traditional models (e.g., Logistic, Richards) in groundwater quality analysis. These findings offer practical tools for predicting contaminant extremes (e.g., maximum/minimum concentrations) and optimizing groundwater management strategies. Full article

(This article belongs to the Special Issue Advances in Hydrogeological Investigations: Field Monitoring, GIS, AI, Remote Sensing, Geophysical Techniques, and Hydrochemical Analysis)

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15 pages, 3448 KiB

Open AccessArticle

Experimental Study on the Influence of Rising Water Levels on the Buoyancy of Building Structure

by Zhisong Fan, Changjie Xu, Kelang Yang, Xiuli Xue and Chaofeng Zeng

Water 2025, 17(9), 1377; https://doi.org/10.3390/w17091377 - 2 May 2025

Viewed by 214

Abstract

This study investigates the complete process of water level elevation’s impact on structural buoyancy under varying environmental conditions (with/without surrounding barriers) using model testing. The experiments simulated the buoyancy response patterns in sandy soil layers under different hydraulic heads. Dynamic variations of structural [...] Read more.

This study investigates the complete process of water level elevation’s impact on structural buoyancy under varying environmental conditions (with/without surrounding barriers) using model testing. The experiments simulated the buoyancy response patterns in sandy soil layers under different hydraulic heads. Dynamic variations of structural buoyancy over time were systematically analyzed, revealing distinct differences across the working conditions. The key findings demonstrate: (1) in the presence of the barrier effect, the growth of structure buoyancy is significantly slower than that without a barrier, but the measured value of structure buoyancy in sand is basically consistent with the theoretical value of Archimedes’ law, and the reduction coefficient is between 0.78 and 0.96; (2) the influence rate of water level rise under high water head pressure on structure buoyancy is significantly higher than that under low water head pressure. Therefore, special attention should be paid to monitoring structure buoyancy when the water level rises under high water levels. Full article

(This article belongs to the Section Hydrology)

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