Water

22 pages, 2358 KB

Open AccessArticle

Shifts in Precipitation Variability near the Danube Delta Biosphere Reserve (1965–2019)

by Alina Bărbulescu and Cristian Ștefan Dumitriu

Water 2025, 17(18), 2692; https://doi.org/10.3390/w17182692 (registering DOI) - 11 Sep 2025

Nowadays, climate change is one of the significant threats humanity faces. Many researchers have documented its effects on water availability and vulnerable systems. This study examines the long-term precipitation record (1965–2019) from the Tulcea station, located just 4 km from the Danube Delta [...] Read more.

Nowadays, climate change is one of the significant threats humanity faces. Many researchers have documented its effects on water availability and vulnerable systems. This study examines the long-term precipitation record (1965–2019) from the Tulcea station, located just 4 km from the Danube Delta Biosphere Reserve (DDBR), to evaluate the impact of climate change on precipitation variability, which can significantly affect biodiversity in this protected area. We integrated change point detection (CPD), stationarity tests, trend analysis, and series decomposition to characterize shifts and patterns in the time series. The Lee & Heghinian test detected a change point (CP) in all data series, whereas the Hubert segmentation methods and Cumulative Sum Method (CUSUM) found fewer series that present at least a CP. The Mann–Kendall (MK) trend test and Innovative Trend Analysis (ITA) indicated an increasing trend in the annual, monthly, and October precipitation series. The Seasonal-Trend decomposition using Loess STL decomposition found the highest seasonality indices in June and July. The Ensemble Empirical Mode Decomposition (EEMD) emphasizes a substantial difference in the seasonal cycle. The results indicate a high variability in the precipitation pattern, with periods of high precipitation followed by dry periods. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

► Show Figures

Figure 1

18 pages, 3503 KB

Open AccessArticle

MLP-Optimized Duct Design for Enhanced Hydrodynamic Performance in Tidal Turbines

by Zhijie Liu, Yuan Zheng, Yuquan Zhang and Junhui Xu

Water 2025, 17(18), 2691; https://doi.org/10.3390/w17182691 (registering DOI) - 11 Sep 2025

Abstract

The duct, a crucial component of tidal energy power generation devices, is designed to enhance the environmental benefits of tidal energy by optimizing water flow paths and improving energy conversion efficiency. Traditional duct design methods are often considered overly complex, lacking precision, and [...] Read more.

The duct, a crucial component of tidal energy power generation devices, is designed to enhance the environmental benefits of tidal energy by optimizing water flow paths and improving energy conversion efficiency. Traditional duct design methods are often considered overly complex, lacking precision, and exhibiting poor optimization efficiency and accuracy. In this study, computational fluid dynamics (CFD) and multi-layer perceptron (MLP) models are employed to investigate the impact of various duct designs on turbine power output and thrust. The MLP model is trained using numerical simulation results, which are then validated by comparing them with experimental data from the literature. Under optimized conditions—specifically, an attack angle of 20°, a blade tip distance of 8 mm, and a cubic curve X_m = 0.796—the power coefficient is found to increase by approximately 11.14% compared to the conventional duct 1, while thrust is reduced by about 52.11% compared to the conventional duct 2. Furthermore, energy loss in the wake vortex is minimized. Flow field analysis is conducted to further confirm the effectiveness of the optimized design, with the high-speed zone area being expanded and pressure extremes reduced by approximately 31.71%. These results demonstrate that machine learning methods can effectively be used to extract nonlinear relationships between complex parameters, offering more design options for duct development and facilitating the engineering application of tidal energy generation technology. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

► Show Figures

Figure 1

21 pages, 2339 KB

Open AccessArticle

Flood Frequency Analysis and Trend Detection in the Brisbane River Basin, Australia

by S M Anwar Hossain, Sadia T. Mim, Mohammad A. Alim and Ataur Rahman

Water 2025, 17(18), 2690; https://doi.org/10.3390/w17182690 - 11 Sep 2025

Abstract

This study presents a comprehensive flood frequency analysis for Australia’s Brisbane River basin using annual maximum flood (AMF) data from 26 stream gauging stations. This evaluates five different probability distributions in fitting the AMF data of the selected stations, which are the Lognormal, [...] Read more.

This study presents a comprehensive flood frequency analysis for Australia’s Brisbane River basin using annual maximum flood (AMF) data from 26 stream gauging stations. This evaluates five different probability distributions in fitting the AMF data of the selected stations, which are the Lognormal, Log Pearson Type III (LP3), Gumbel, Generalized Extreme Value (GEV), and Generalized Pareto (GP) distributions (the recommended distributions in FLIKE software (School of Civil Engineering, University of Newcastle Australia, Australia, Release_x86_5.0.306.0). Three different goodness-of-fit tests (Chi-Squared, Anderson–Darling, and Kolmogorov–Smirnov) are adopted. This study also examines trends in the observed AMF data using several trend tests. It is found that the LP3 is the best-fit probability distribution at majority of the selected stations, followed by the GP distribution. Although the AMF data at most of the stations show an increasing linear trend, these trends are generally statistically non-significant. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: The Impact of Climate Change on Water Resources)

► Show Figures

Figure 1

20 pages, 1749 KB

Open AccessArticle

Prediction of Dam Inflow in the River Basin Through Representative Hydrographs and Auto-Setting Artificial Neural Network

by Yong Min Ryu and Eui Hoon Lee

Water 2025, 17(18), 2689; https://doi.org/10.3390/w17182689 - 11 Sep 2025

Abstract

Hydrological prediction under climate change requires representative data selection and adaptable model architecture. This study proposes a two-part methodology to improve deep learning performance in hydrological prediction. The first component, the representative hydrograph extraction technique (RHET), identifies representative inflow patterns from historical records [...] Read more.

Hydrological prediction under climate change requires representative data selection and adaptable model architecture. This study proposes a two-part methodology to improve deep learning performance in hydrological prediction. The first component, the representative hydrograph extraction technique (RHET), identifies representative inflow patterns from historical records using dynamic time warping (DTW) and K-medoids clustering. Inflow data are segmented by year, annual DTW distances are calculated, and central events are selected. Representative hydrographs serve as training input. The second component is the auto-setting artificial neural network (AS-ANN). The AS-ANN automatically determines its structural parameters by performing pre-training to evaluate performance across different configurations. The proposed approach was applied to the Daecheong Dam basin in South Korea and compared against an artificial neural network (ANN). Results show that the proposed model reduced the minimum root mean squared error (Min RMSE) by approximately 267.51 m³/day in the validation results and by approximately 53.04 m³/day in the prediction results compared to the ANN. Furthermore, the proposed model reduced the root mean square error by 57.28% and improved peak inflow prediction accuracy by 54.00%. The proposed RHET-based AS-ANN is expected to show good performance in learning and predicting hydrological data, including the data used in this study, by replacing existing ANNs. Full article

(This article belongs to the Special Issue Application of Machine Learning Models for Flood Forecasting)

23 pages, 2530 KB

Open AccessArticle

Evaluation of Water Resource Carrying Capacity in Taizhou City, Southeast China

by Chuyu Xu, Jiandong Ye, Yijing Chen, Yukun Wang, Haodong Qiu, Jiaqi Tan, Wencheng Wei, Zhishao Li, Tongtong Yu and Hao Chen

Water 2025, 17(18), 2688; https://doi.org/10.3390/w17182688 - 11 Sep 2025

Abstract

Water resource carrying capacity is a key measure of sustainability, commonly employed to evaluate how well water resources can sustain economic and social growth. With China’s rapid economic growth and modernization, water resources in certain regions are now being used at or beyond [...] Read more.

Water resource carrying capacity is a key measure of sustainability, commonly employed to evaluate how well water resources can sustain economic and social growth. With China’s rapid economic growth and modernization, water resources in certain regions are now being used at or beyond their sustainable threshold. This study evaluates the present state of water resource carrying capacity in Taizhou City, located in southeastern China. Using relevant data from 2012 to 2022 on society, economy, water resources, and ecology, the weights of the evaluation indicators were determined using both the entropy weight method and principal component analysis. Subsequently, a comprehensive evaluation model for water resource carrying capacity was developed by applying the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. The comprehensive proximity index for water resource carrying capacity in Taizhou City averaged 0.4864 between 2012 and 2022, indicating a moderate level overall but exhibiting a declining trend, suggesting an approaching threshold of utilization limits. The range was between 0.3461 and 0.7143. In 2017, the comprehensive proximity index was 0.3461 (low water resource carrying capacity level, with water resources already suffering damage and various subsystems developing uncoordinatedly). However, the comprehensive proximity index for water resource carrying capacity improved significantly from 2018 to 2022. A combination of rising industrial water demand and a decrease in both the absolute volume and proportional allocation of water for ecological purposes drove the overall decline in the progress rate in 2017. Taizhou City has formulated strict water resource management policies and measures, resulting in a decrease in indicators such as industrial water consumption, residential water consumption, and industrial wastewater discharge, as well as an increase in indicators such as ecological water consumption and ecological water utilization rate. As a result, the comprehensive water resource carrying capacity saw a notable rise during 2018–2019. The study results provide a reference for the rational use of water resources in Taizhou City and are of certain significance for promoting the coordinated economic and social development of Taizhou City. Full article

(This article belongs to the Section Water Resources Management, Policy and Governance)

30 pages, 9156 KB

Open AccessArticle

Integrating Loose Layer Drainage into Mining Subsidence Prediction: A Mathematical Model Validated by Field Measurements and Numerical Simulations

by Bang Zhou, Yueguan Yan, Ming Li, Shengcai Li, Chuanwu Zhao, Jianrong Kang and Jinman Zhang

Water 2025, 17(18), 2687; https://doi.org/10.3390/w17182687 - 11 Sep 2025

Abstract

Mining-induced surface subsidence is a typical geological hazard. Loose layer drainage disturbed by coal mining can exacerbate surface subsidence in terms of both the extent and amount, thereby increasing the risk of building deformation and environmental degradation in mining areas. However, currently the [...] Read more.

Mining-induced surface subsidence is a typical geological hazard. Loose layer drainage disturbed by coal mining can exacerbate surface subsidence in terms of both the extent and amount, thereby increasing the risk of building deformation and environmental degradation in mining areas. However, currently the prediction results of surface subsidence considering these two factors are not precise enough, which contradicts the principles of green coal mining. Firstly, this paper introduces the probability integral method, which predicts mining-induced surface subsidence. Subsequently, based on the soil–water coupled theory and the derived characteristic curve of groundwater level decline, a surface subsidence prediction model that considers loose layer drainage is constructed using triple integral transformation. Finally, a more precise surface subsidence prediction model considering both factors is proposed based on the principle of superposition. The model is applied to the mining of working panel 1309 in Shanxi province, China, an area rich in coal yet scarce in water resources. When compared with the measured subsidence data, the proposed model achieves a root mean square error (RMSE) of 27 mm, while the RMSEs of existing models are 78 mm and 123 mm, respectively. The prediction accuracy has been significantly improved. In addition, the proposed model is further validated through fluid–solid coupling numerical calculations in FLAC3D. The subsidence results considering the single effect of each factor also demonstrated good validation accuracy. Overall, the proposed model can accurately describe the surface subsidence considering both factors. This research can provide a theoretical guide for assessing the environmental impact and building damage, while contributing to the sustainable development of land use and groundwater resource in mining areas. Full article

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

► Show Figures

Figure 1

17 pages, 2810 KB

Open AccessArticle

Magnetic Intensification of Fenton Processes Using Superconducting Technology for Enhanced Treatment of Printing and Dyeing Wastewater: Mechanisms and Applications

by Qian Luo, Zhenchang Yin, Zhengfeng Hu, Wei Zhang, Yu Zhang, Huimin Huang, Zhihui Chen, Junjie Xu and Rongwu Mei

Water 2025, 17(18), 2686; https://doi.org/10.3390/w17182686 - 11 Sep 2025

Abstract

The rapid industrial development in recent years has led to severe pollution of aquatic environments. It is necessary to develop green and highly efficient treatment technologies for addressing environmental pollution and realizing carbon peaking and carbon neutrality goals. This study aims to explore [...] Read more.

The rapid industrial development in recent years has led to severe pollution of aquatic environments. It is necessary to develop green and highly efficient treatment technologies for addressing environmental pollution and realizing carbon peaking and carbon neutrality goals. This study aims to explore the effect of magnetic fields on chemical oxygen demand (COD) degradation by Fenton reaction. The experimental results demonstrated the following: (1) Magnetic fields convert macromolecular organic compounds into low-molecular-weight organic compounds, promoting the attack of radicals on organic pollutants. (2) The magnetic Fenton process achieved COD removal efficiency of 60.0%. (magnetic field intensity: 1.5 T, magnetization duration: 5 min, pH = 5.0, Fe²⁺ = 2.0 mmol/L, H₂O₂ = 2.0 mmol/L, reaction time: 40 min). (3) The magnetic Fenton process consumes less acidic reagent. Notably, it achieves a 33.3% reduction in both catalyst and oxidant usage under the same COD removal efficiency. This study verifies the feasibility of applying the method in real sewage treatment plants, demonstrating promising application prospects. Full article

(This article belongs to the Special Issue Fate and Transport of Contaminants in Soil and Water)

► Show Figures

Figure 1

24 pages, 348 KB

Open AccessArticle

Muddling Through Water Governance and Water Quality—Comparative Lessons from Three Governance Regimes

by Geir Inge Orderud, Rolf David Vogt, Josef Hejzlar, Hongze Tan, Ståle Haaland, Petr Porcal and Jing Luo

Water 2025, 17(18), 2685; https://doi.org/10.3390/w17182685 - 11 Sep 2025

Abstract

This paper addresses water governance in the context of dissolved organic matter emissions into water bodies and cultural eutrophication. Through a comparative interdisciplinary analysis of cases from Norway, the Czech Republic, and China, it seeks to identify core principals of effective water governance [...] Read more.

This paper addresses water governance in the context of dissolved organic matter emissions into water bodies and cultural eutrophication. Through a comparative interdisciplinary analysis of cases from Norway, the Czech Republic, and China, it seeks to identify core principals of effective water governance and suggest strategies for achieving good ecological and chemical status of raw water. The analysis presents each case by exploring natural and societal processes, emphasising the interdependence between society and nature, and applying a theoretical framework. In this way, the paper contributes to the broader field of water governance studies. The central conclusion is that raw water quality results from “muddling through” processes involving stakeholders with diverse and sometimes conflicting interests. Building the capabilities to manage such contingencies is essential for successful governance. Four critical dimensions are identified as key to this capability: (i) robust environmental knowledge and literacy; (ii) stronger representation of non-human interest; (iii) regulatory measures and economic incentives to enhance raw water quality; and (iv) integrated multi-level governance combining top-down and bottom-up approaches. Strengthening these dimensions can also help mitigate the structural economic pressure driving the exploitation of “cheap nature”. Full article

(This article belongs to the Special Issue Water Governance: Current Status and Future Trends)

► Show Figures

Graphical abstract

25 pages, 5082 KB

Open AccessArticle

Mechanisms of Sulfate In Situ Removal Using SRB-PRB Driven by Low-Cost Sustained-Release Carbon Source in Coal Mine Goafs: A Dynamic Column Experiment Study

by Li Zhang, Zhimin Xu, Mingan Xiahou, Liang Gao, Yating Gao, Juan Guo and Chi Li

Water 2025, 17(18), 2684; https://doi.org/10.3390/w17182684 - 11 Sep 2025

Abstract

The proportion of neutral and weakly alkaline high-sulfate mine water in China is over 50%, resulting in the problem of high treatment costs. Low-cost, sustainable, and non-secondary pollution remediation technologies for in situ application in underground coal mines have rarely been reported. Here, [...] Read more.

The proportion of neutral and weakly alkaline high-sulfate mine water in China is over 50%, resulting in the problem of high treatment costs. Low-cost, sustainable, and non-secondary pollution remediation technologies for in situ application in underground coal mines have rarely been reported. Here, the mixed packed and layered packed SRB-PRB (sulfate-reducing bacteria-permeable reactive barrier) column experiments at a flow speed of 300 mL/d using low-cost corncob as a carbon source were conducted to simulate sulfate in situ remediation in goafs. The column experiments utilized the simulated weakly alkaline mine water, with an initial sulfate concentration of 1027.45 mg/L. The results showed that during the 40 d operation, the SO₄²⁻ removal kinetics included three stages: rapid reduction (0–6 d), stable reduction (6–16 d), and reduction attenuation (16–40 d). Corncob could provide a relatively long-term carbon source supply, with the maximum average removal efficiency of 65.5% for the mixed packed column and 56.6% for the layered packed column. A large number of complex organic-degrading bacteria were detected in both the effluent water samples and the solid packed media, while SRB became dominant only in the solid packed media. However, the low-abundance SRB could still maintain a high-efficiency SO₄²⁻ reduction, due to the supply of readily utilizable carbon sources provided by hydrolytic and fermentative bacteria. This indicated that the synergistic effect between SRB and these organic matter-degrading bacteria was the critical limiting factor for SO₄²⁻ removal. The microscopic characterizations of SEM-EDS (scanning electron microscopy and energy-dispersive spectroscopy) and FTIR (Fourier transform infrared spectroscopy) confirmed the damage of functional groups in corncobs and the generation of SO₄²⁻ removal products (i.e., FeS). The engineering application schemes of the SRB-PRB under both in-production and abandoned mining scenarios were proposed. Additionally, the material cost estimate results showed that the SRB-PRB could achieve in situ low-cost remediation (0.2–1.55 USD/m³) of the characteristic pollutant SO₄²⁻. These findings would benefit the engineering application of in situ microbial remediation technology for high-sulfate mine water. Full article

(This article belongs to the Section Hydrogeology)

► Show Figures

Figure 1

18 pages, 2227 KB

Open AccessArticle

Sustaining Grape Yield and Soil Health Under Saline–Sodic Irrigation Through Amendments and Canal Water Application

by Karamjit Singh Sekhon, Anureet Kaur, Sudhir Thaman, Navjot Gupta, Anurag Malik, Chetak Bishnoi, Ozgur Kisi, Ali Salem and Mohamed A. Mattar

Water 2025, 17(18), 2683; https://doi.org/10.3390/w17182683 - 11 Sep 2025

Abstract

The present study was undertaken for six years to appraise the responses of four-year-old established grapevines (Vitis vinifera L., cv. Perlette) to saline–sodic groundwater irrigation in relation to different amendments in a field experiment on non-saline, non-sodic calcareous sandy loam soil under [...] Read more.

The present study was undertaken for six years to appraise the responses of four-year-old established grapevines (Vitis vinifera L., cv. Perlette) to saline–sodic groundwater irrigation in relation to different amendments in a field experiment on non-saline, non-sodic calcareous sandy loam soil under a semi-arid climate at the research farm of Punjab Agricultural University, Regional Research Station, Bathinda, Punjab, India. Different water quality treatments, viz., canal water or good-quality water (GQW), poor-quality saline–sodic groundwater (PQW), alternate irrigation of canal water and groundwater (GQW/PQW), PQW with 50% gypsum (CaSO₄·2H₂O) requirement (PQW + GR₅₀), PQW with 100% gypsum requirement (PQW + GR₁₀₀), and PQW with sulphitation pressmud (by-product of sugar industry) @ 6.6 t ha⁻¹ on a dry weight basis (PQW + SPM), applied in furrows, were imposed in quadruplicate with a randomized block design. PQW with an electrical conductivity (EC) of 2.2–2.4 dS m⁻¹, residual sodium carbonate (RSC) content of 6.21–6.44 mmolc L⁻¹, and a sodium adsorption ratio (SAR) from 23.1 to 24.8 (mmolc L⁻¹)^0.5 was used during the course of experimentation. The pooled mean 6-year data showcased that the treatments GQW/PQW, PQW + GR₅₀, PQW + GR₁₀₀, and PQW + SPM improved the berry yield by 28.3%, 11.3%, 21.2%, and 31.0%, respectively, when compared with PQW. Use of amendments, i.e., gypsum, sulphitation pressmud, and practice of GQW/PQW for irrigation in a cyclic mode, helped in reducing the pH, SAR, and bulk density (BD) of surface soil (0–15 cm) and enhancing the final infiltration rate (FIR) of soil and berry yield. A maximum water use efficiency (WUE) of 3.99 q ha⁻¹-cm was recorded in the GQW treatment, followed by 3.93, 3.72, and 3.68 q ha⁻¹-cm in the PQW + SPM, GQW/PQW, and PQW + GR₁₀₀ treatments, respectively. Application of amendments alongside PQW evidenced a significant enhancement in total soluble solids (TSSs) and a decrease in the acidity of berries as compared to PQW. These results suggest that table grape yield (cv. Perlette) on calcareous sandy loam soil under saline–sodic groundwater irrigation can be sustained with the application of PQW + GR₁₀₀, sulphitation pressmud, and GQW/PQW in already-established grapevines with minimal detrimental effects on soil health. Full article

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

► Show Figures

Figure 1

26 pages, 5803 KB

Open AccessArticle

Spatiotemporal Changes in Yangtze Estuary River Islands Revealed by Landsat Imagery

by Xinjun Wang, Haiyun Shi, Yuhan Cao, Yu Li and Xinman Zhu

Water 2025, 17(18), 2682; https://doi.org/10.3390/w17182682 - 11 Sep 2025

Abstract

As fluvial deposition features, river islands originate from persistently exposed sandbars. Their morphological evolution responds to hydrological dynamics, sediment budgets, and human modifications of river systems. This study conducts a quantitative analysis of the spatiotemporal evolution of four river islands in China’s Yangtze [...] Read more.

As fluvial deposition features, river islands originate from persistently exposed sandbars. Their morphological evolution responds to hydrological dynamics, sediment budgets, and human modifications of river systems. This study conducts a quantitative analysis of the spatiotemporal evolution of four river islands in China’s Yangtze River Estuary (YRE), utilizing multitemporal Landsat imagery (MSS, TM, ETM+, and OLI) at five-year intervals from 1974 to 2024. This analysis employed thresholding, binarization, image registration, cropping, and cluster analysis. Hydrological data (runoff and sediment flux) from Datong Station were concurrently evaluated to explore the driving factors of evolution. The findings suggested the following: (1) MSS/TM/ETM+/OLI images were effective for accurately extracting river island information, and the results were consistent with the accuracy verification. (2) The cumulative area and growth rate of the river islands have exhibited an upward trend over time, with Jiuduansha growing the fastest. (3) Runoff and sediment discharge are the primary natural controls on morphological evolution, with a weak positive correlation (R = 0.293) and a strong negative correlation (R = −0.915) with the area of river islands, respectively. Anthropogenic drivers such as land reclamation, sediment enhancement projects, and the Three Gorges Dam are equally critical. Full article

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

► Show Figures

Figure 1

20 pages, 5554 KB

Open AccessArticle

Sources and Transport of Dissolved Organic Matter (DOM) in Surface and Groundwater Within a Dominated Greenhouse Agriculture Catchment: Insights from Multi-Tracer

by Haoyang Wang, Shuang Song, Wei Xu and Fu-Jun Yue

Water 2025, 17(18), 2681; https://doi.org/10.3390/w17182681 - 10 Sep 2025

Abstract

Intensive greenhouse agriculture significantly alters dissolved organic matter (DOM) dynamics in aquatic ecosystems, but related research remains scarce. To address this knowledge gap, this study employed an integrated approach combining Excitation–Emission Matrix Parallel Factor Analysis (EEM-PARAFAC), Two-Dimensional Correlation Spectroscopy (2D-COS), and Self-Organizing Map [...] Read more.

Intensive greenhouse agriculture significantly alters dissolved organic matter (DOM) dynamics in aquatic ecosystems, but related research remains scarce. To address this knowledge gap, this study employed an integrated approach combining Excitation–Emission Matrix Parallel Factor Analysis (EEM-PARAFAC), Two-Dimensional Correlation Spectroscopy (2D-COS), and Self-Organizing Map (SOM) analyses with hydrochemical and stable water isotopes (δ¹⁸O and δD) to investigate the dynamic characteristics of DOM in surface water and groundwater in an intensive greenhouse agriculture catchment (XER) in northern China. Water chemistry and isotope results consistently demonstrated mixing between surface water and groundwater, which was attributed to irrigation pumping. Four fluorescent components were identified via EEM-PARAFAC (C1 and C4 are humic components, while C2 and C3 are tryptophan components), with microbial decomposition of organic fertilizers and domestic wastewater discharge being important sources. Compared with tryptophan components, terrestrial humic substances in groundwater preferentially change in the parallel river direction, while microbial humic substances are more sensitive in the vertical direction, as confirmed by 2D-COS. SOM analysis validated the EEM-PARAFAC results through component plane visualization, demonstrating both DOM inter-component relationships and their correlations with inorganic ions. These results provide critical scientific support for developing sustainable water resource management strategies and optimizing organic fertilizer use in greenhouse agricultural systems, with important practical implications for protecting groundwater quality in intensively cultivated catchments. Full article

(This article belongs to the Special Issue Pollution Mechanisms and Source Apportionment of Typical Pollutants in Aquatic Environments)

► Show Figures

Graphical abstract

20 pages, 4055 KB

Open AccessArticle

Numerical Study of Hydrodynamics Characteristics of Cylinders with Intermittent Spanwise Arrangements

by Songsong Yu, Erxian Zeng, Yadong Wang, Zhihui Jiao, Shunyu He and Guoqiang Tang

Water 2025, 17(18), 2680; https://doi.org/10.3390/w17182680 - 10 Sep 2025

Abstract

Subsea pipelines with intermittent spanwise arrangements are commonly encountered in offshore engineering, yet their complex hydrodynamic interactions remain insufficiently understood. In this study, three-dimensional numerical simulations were conducted to investigate the hydrodynamics of intermittently spanning cylinders at a Reynolds number of 40,250. The [...] Read more.

Subsea pipelines with intermittent spanwise arrangements are commonly encountered in offshore engineering, yet their complex hydrodynamic interactions remain insufficiently understood. In this study, three-dimensional numerical simulations were conducted to investigate the hydrodynamics of intermittently spanning cylinders at a Reynolds number of 40,250. The hydrodynamic coefficients and flow fields of cylinders with different gap ratios e/D, total spanning ratios L/H, and individual spanning ratios l/D were investigated (where e is the gap height, D is the diameter of the cylinder, L is the total spanning length, H is the length of the cylinder, and l is the individual spanning length). Moreover, this work validates the applicability of existing hydrodynamic prediction formulas for spanning cylinders under complex spanning conditions, as proposed by previous researchers. Numerical results show that the existing formulas can accurately predict the drag coefficient

{\bar{C}}_{D}

of spanning cylinders under different uniform l/D ratios, but it fails to provide reliable predictions for the lift coefficient

{\bar{C}}_{L}

. These findings provide critical insights for optimizing the design of subsea pipelines and marine structures with intermittent spanwise arrangements. Full article

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

► Show Figures

Figure 1

23 pages, 13794 KB

Open AccessArticle

Numerical Simulation Study on Seepage-Stress Coupling Mechanisms of Traction-Type and Translational Landslides Based on Crack Characteristics

by Meng Wu, Guoyu Yuan, Qinglin Yi and Wei Liu

Water 2025, 17(18), 2679; https://doi.org/10.3390/w17182679 - 10 Sep 2025

Abstract

This study examines the deformation and failure mechanisms of two reservoir bank landslides: the traction-type Baijiabao landslide and the translational Baishuihe landslide. Based on long-term monitoring data and a hydro-mechanical coupled numerical model of rainfall infiltration, we investigate the impact of crack depth [...] Read more.

This study examines the deformation and failure mechanisms of two reservoir bank landslides: the traction-type Baijiabao landslide and the translational Baishuihe landslide. Based on long-term monitoring data and a hydro-mechanical coupled numerical model of rainfall infiltration, we investigate the impact of crack depth on landslide stability. Results show that the Baishuihe landslide exhibits translational failure, initiated at the rear by tension cracks and rear subsidence, followed by toe uplift, whereas the Baijiabao landslide displays traction-type progressive failure, starting with toe erosion and later developing rear-edge cracks. Rainfall induces similar seepage patterns in both landslides, with infiltration concentrated at the crest, toe, and convex terrain areas. As crack depth increases, soil saturation near the cracks decreases nonlinearly, while the base remains saturated. However, displacement responses differ: Traction-type landslides exhibit opposing lateral movements with minimal vertical displacement. In contrast, translational landslides show displacement increasing with crack depth, dominated by gravity. These findings guide targeted mitigation: traction-type landslides require crack control and toe protection, while translational landslides need measures to block thrust transfer and monitor deep slip surfaces. This study offers new insights into the effect of crack depth on landslide stability, contributing to improved landslide hazard assessment and management. Full article

(This article belongs to the Special Issue Water-Related Landslide Hazard Process and Its Triggering Events)

31 pages, 48193 KB

Open AccessArticle

Combining Machine Learning Models and Satellite Data of an Extreme Flood Event for Flood Susceptibility Mapping

by Nikos Tepetidis, Ioannis Benekos, Theano Iliopoulou, Panayiotis Dimitriadis and Demetris Koutsoyiannis

Water 2025, 17(18), 2678; https://doi.org/10.3390/w17182678 - 10 Sep 2025

Abstract

Machine learning techniques have been increasingly used in flood management worldwide to enhance the effectiveness of traditional methods for flood susceptibility mapping. Although these models have achieved higher accuracy than traditional ones, their application has not yet reached full maturity. We focus on [...] Read more.

Machine learning techniques have been increasingly used in flood management worldwide to enhance the effectiveness of traditional methods for flood susceptibility mapping. Although these models have achieved higher accuracy than traditional ones, their application has not yet reached full maturity. We focus on applying machine learning models to create flood susceptibility maps (FSMs) for Thessaly, Greece, a flood-prone region with extreme flood events recorded in recent years. This study utilizes 13 explanatory variables derived from topographical, hydrological, hydraulic, environmental and infrastructure data to train the models, using Storm Daniel—one of the most severe recent events in the region—as the primary reference for model training. The most significant of these variables were obtained from satellite data of the affected areas. Four machine learning algorithms were employed in the analysis, i.e., Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost). Accuracy evaluation revealed that tree-based models (RF, XGBoost) outperformed other classifiers. Specifically, the RF model achieved Area Under the Curve (AUC) values of 96.9%, followed by XGBoost, SVM and LR, with 96.8%, 94.0% and 90.7%, respectively. A flood susceptibility map corresponding to a 1000-year return period rainfall scenario at 24 h scale was developed, aiming to support long-term flood risk assessment and planning. The analysis revealed that approximately 20% of the basin is highly prone to flooding. The results demonstrate the potential of machine learning in providing accurate and practical flood risk information to enhance flood management and support decision making for disaster preparedness in the region. Full article

(This article belongs to the Special Issue Machine Learning Models for Flood Hazard Assessment)

► Show Figures

Figure 1

24 pages, 20388 KB

Open AccessArticle

Distribution and Environmental Implications of GDGTs in Sediments from Three Asian Mangrove Wetlands

by Qiunan Li, Yasong Wang, Xinxin Li, Mohammad Abdul Baki, Shilpi Saha, Jiaodi Zhou and Yunping Xu

Water 2025, 17(18), 2677; https://doi.org/10.3390/w17182677 - 10 Sep 2025

Abstract

Glycerol Dialkyl Glycerol Tetraethers (GDGTs) are microbial membrane lipids that can provide crucial information for identifying organic carbon sources and understanding paleoenvironments. Despite numerous studies reporting the presence of GDGTs in various terrestrial and marine environments, there is a paucity of reports concerning [...] Read more.

Glycerol Dialkyl Glycerol Tetraethers (GDGTs) are microbial membrane lipids that can provide crucial information for identifying organic carbon sources and understanding paleoenvironments. Despite numerous studies reporting the presence of GDGTs in various terrestrial and marine environments, there is a paucity of reports concerning GDGTs in mangrove wetlands that are characterized by unique hydrological conditions and disproportionately high accumulation rates of blue carbon (i.e., carbon sequestered in coastal ecosystems, where tidal flooding and anaerobic sediments facilitate exceptional long-term carbon storage). This study investigates GDGTs in 81 sediment samples from 5 sediment cores collected from three Asian mangrove wetlands in Bangladesh, Hong Kong, and Guangxi Province, China. The Hong Kong mangrove sediments had the highest GDGT concentration (370.18 ± 58.00 ng·g⁻¹ dws), followed by Bangladesh mangrove sediments (136.70 ± 41.70 ng·g⁻¹ dws), while Guangxi mangrove sediments had the lowest (100.80 ± 28.71 ng·g⁻¹ dws). All samples demonstrated high BIT index values (>0.8), low IIIa/IIa index values (0.09–0.19) and the predominance of tetramethylated brGDGTs (70.38 ± 2.21%), indicating that terrestrial inputs are the primary source of organic carbon. Despite overall low methylation index (MI) values (0.15–0.35) and GDGT-0/Cren ratios, deeper sediment samples in the lower part of HK exhibited GDGT-0/Cren > 2, likely reflecting enhanced contributions of methanogenic archaea under distinct redox conditions compared to upper sediments. This in situ production may complicate the application of GDGT-based paleo-proxies, as indicated by the substantial deviations between CBT’-pH (MBT’_5ME-temperature) and measured pH (instrumental temperature). The dominant bacterial phyla in the mangrove sediments of Guangxi and Bangladesh were Proteobacteria, Actinobacteriota, Chloroflexi, Acidobacteriota, and Firmicutes (>70% relative abundance). However, correlations between microbial community compositions and brGDGT isomers are different among sampling sites. Our study emphasizes that site- and depth-specific microbial activity may significantly contribute to organic matter cycling and the in situ production of GDGTs in mangrove sediments. These factors should be taken into account for organic carbon sequestration and the validity of GDGT-based paleo-proxies in mangrove wetlands. Full article

(This article belongs to the Section Ecohydrology)

► Show Figures

Figure 1

1 pages, 132 KB

Open AccessCorrection

Correction: Seo et al. Identification of Phytoplankton-Based Production of the Clam Corbicula japonica in a Low-Turbidity Temperate Estuary Using Fatty Acid and Stable Isotope Analyses. Water 2023, 15, 1670

by Dongkyu Seo, Changseong Kim, Jaebin Jang, Dongyoung Kim and Chang-Keun Kang

Water 2025, 17(18), 2676; https://doi.org/10.3390/w17182676 - 10 Sep 2025

Abstract

The journal’s Editorial Office and Editorial Board are jointly issuing a resolution and removal of the Journal Notice linked to this article [...] Full article

18 pages, 3692 KB

Open AccessArticle

Effects of Straw Mulching on Nonpoint Source Pollutant Runoff During Snowmelt in Korean Highland Agricultural Areas

by Seonah Lee, Yoon-Seok Kim, Mingyeong Bak and Eunmi Hong

Water 2025, 17(18), 2675; https://doi.org/10.3390/w17182675 - 10 Sep 2025

Abstract

Nonpoint Source (NPS) pollution refers to water pollution that does not originate from a single identifiable source. In this study, we conducted water-quality monitoring during the snowmelt period from February to March of 2024 and 2025 in Jaun, a highland agricultural area. We [...] Read more.

Nonpoint Source (NPS) pollution refers to water pollution that does not originate from a single identifiable source. In this study, we conducted water-quality monitoring during the snowmelt period from February to March of 2024 and 2025 in Jaun, a highland agricultural area. We analyzed changes in nonpoint source pollutant concentration and evaluated Best Management Practice (BMPs) effectiveness. A year-to-year comparison showed that in 2024, a single intense snowmelt event led to a sharp increase in particulate pollutants, such as TP and SS. In 2025, repeated and gradual thawing resulted in the accumulation and release of dissolved pollutants, including TN and TOC. BMPs such as straw mulching were partially effective in reducing pollutant concentrations. However, in 2025, a lack of proper maintenance led to increased concentration at certain sites. The water quality during the snowmelt period was comparable to that during the summer monsoon season, indicating that snowmelt has a similar potential for generating nonpoint source pollution. The findings provide area-based insights into snowmelt-induced nonpoint source pollution and can form a foundation for developing seasonal water quality management policies. Full article

(This article belongs to the Special Issue Basin Non-Point Source Pollution)

► Show Figures

Figure 1

18 pages, 2146 KB

Open AccessArticle

Effect of Carbon Dioxide on the Growth and Nutrient Uptake of the Microalgae Chlorella sorokiniana from Digestate

by Thomas L. Palikrousis, Sotirios D. Kalamaras and Petros Samaras

Water 2025, 17(18), 2674; https://doi.org/10.3390/w17182674 - 10 Sep 2025

Abstract

Microalgae are photosynthetic microorganisms capable of capturing CO₂ from both the atmosphere and industrial emissions while producing valuable biomass. Among the various factors influencing microalgal growth, CO₂ availability plays a critical role. This study examined how different CO₂ flow rates [...] Read more.

Microalgae are photosynthetic microorganisms capable of capturing CO₂ from both the atmosphere and industrial emissions while producing valuable biomass. Among the various factors influencing microalgal growth, CO₂ availability plays a critical role. This study examined how different CO₂ flow rates affect the growth and nutrient assimilation of Chlorella sorokiniana cultivated in diluted digestate from a biogas plant with nitrogen concentrations up to 5 g/L. Results showed that biomass productivity increased with CO₂ supply up to a threshold, beyond which it declined. The highest mean productivity was observed at a CO₂ flow rate of 0.025 LPM, which did not differ significantly from the 0.050 LPM treatment, indicating comparable performance. In contrast, the highest flow rate (0.100 LPM) led to reduced productivity, although still higher than the control (no CO₂). A similar trend was observed in ammonium removal, whereas phosphorus uptake remained relatively unaffected by CO₂ supply. Overall, elevated CO₂ levels appeared to shift microalgal metabolism towards biomass with lower nitrogen content and increased lipid and carbohydrate accumulation. Full article

► Show Figures

Figure 1

31 pages, 5616 KB

Open AccessArticle

Deep Signals: Enhancing Bottom Temperature Predictions in Norway’s Mjøsa Lake Through VMD- and EMD-Boosted Machine Learning Models

by Sertac Oruc, Mehmet Ali Hınıs, Zeliha Selek and Türker Tuğrul

Water 2025, 17(18), 2673; https://doi.org/10.3390/w17182673 - 10 Sep 2025

Abstract

In this study, we benchmark various machine learning techniques against a synthetic but physically based reference time series (model-simulated (ERA5-Land/FLake) bottom-temperature series) and assess whether decomposition methods (VMD and EMD) improve forecast accuracy using Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Random Forest [...] Read more.

In this study, we benchmark various machine learning techniques against a synthetic but physically based reference time series (model-simulated (ERA5-Land/FLake) bottom-temperature series) and assess whether decomposition methods (VMD and EMD) improve forecast accuracy using Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Random Forest (RF), Gaussian Process Regression (GPR), and Long Short-Term Memory (LSTM) with the monthly average data of Mjøsa, the largest lake in Norway, between 1950 and 2024 from the ERA5-Land FLake model. A total of 70% of the dataset was used for training and 30% was reserved for testing. To assess the performance several metrics, correlation coefficient (r), Nash–Sutcliffe efficiency (NSE), Kling–Gupta efficiency (KGE), Performance Index (PI), RMSE-based RSR, and Root Mean Square Error (RMSE) were used. The results revealed that without decomposition, the GPR-M03 combination outperforms other models (with scores r = 0.9662, NSE = 0.9186, KGE = 0.8786, PI = 0.0231, RSR = 0.2848, and RMSE = 0.2000). Considering decomposition cases, when VMD is applied, the SVM-VMD-M03 combination achieved better results compared to other models (with scores r = 0.9859, NSE = 0.9717, KGE = 0.9755, PI = 0.0135, RSR = 0.1679, and RMSE = 0.1179). Conversely, with decomposition cases, when EMD applied, LSTM-EMD-M03 is explored as the more effective combination than others (with scores r = 0.9562, NSE = 0.9008, KGE = 0.9315, PI = 0.0256, RSR = 0.2978, and RMSE = 0.3143). The results demonstrate that GPR and SVM, coupled with VMD, yield high correlation (e.g., r ≈ 0.986) and low RMSE (~0.12), indicating the ability to reproduce FLake dynamics rather than as accurate predictions of measured bottom temperature. Full article

(This article belongs to the Special Issue Application of Machine Learning in Hydrological Monitoring)

► Show Figures

Graphical abstract

17 pages, 5867 KB

Open AccessArticle

Coupling of SWAT and WEAP Models for Quantifying Water Supply, Demand and Balance Under Dual Impacts of Climate Change and Socio-Economic Development: A Case Study from Cauto River Basin, Cuba

by Bao Chung Tran, Anh Phuong Tran, Dieu Hang Tran, Anh Duc Nguyen, Siliennis Blanco Campbell, Nam Anh Nguyen and Thi Huong Le

Water 2025, 17(18), 2672; https://doi.org/10.3390/w17182672 - 10 Sep 2025

Abstract

The Cauto River Basin (CRB), the heartland of Cuban agriculture, has been hit hard by drought and water shortages. In response to this pressing issue, this study provides a comprehensive assessment of the water supply, demand and balance within the Cauto River Basin, [...] Read more.

The Cauto River Basin (CRB), the heartland of Cuban agriculture, has been hit hard by drought and water shortages. In response to this pressing issue, this study provides a comprehensive assessment of the water supply, demand and balance within the Cauto River Basin, considering the baseline and projected socio-economic and climatic conditions by coupling SWAT and WEAP models. The obtained results revealed that the annual flow in the CRB is projected to slightly decrease (2.5%), in which, the reduction in the rainy season (3.1%) will be higher than that in the dry season (1.3%). The total water demand in the baseline scenario is around 1.194 billion m³, dominated by agriculture (96%), with rice crops requiring nearly half. For the future scenario of 2050, the study showed a 16.6% surge in demand to 1.394 billion m³, driven by climate change and agricultural expansion. However, domestic use will decrease by 10% due to population reduction. The water deficit in the future is projected to increase by 52% from 172.4 to 262.7 million m³ due to a rising water demand and declining water supply. This study shows that integrating a hydrological model into a water allocation model is a promising approach to estimate the water supply, demand and balance, which is a crucial component of water resources management. Full article

(This article belongs to the Special Issue Water Resource Management: Hydrological Modelling, Hydrological Cycles, and Hydrological Prediction)

► Show Figures

Figure 1

20 pages, 8416 KB

Open AccessArticle

Extreme Short-Duration Rainfall and Urban Flood Hazard: Case Studies of Convective Events in Warsaw and Zamość, Poland

by Bartłomiej Pietras and Robert Pyrc

Water 2025, 17(18), 2671; https://doi.org/10.3390/w17182671 - 9 Sep 2025

Abstract

This study investigates two extreme convective rainfall events that struck Poland in August 2024, affecting Warsaw (Okęcie) on 19 August and Zamość on 21 August. The aim is to evaluate the meteorological background, intensity, and spatial characteristics of these short-duration storms. We used [...] Read more.

This study investigates two extreme convective rainfall events that struck Poland in August 2024, affecting Warsaw (Okęcie) on 19 August and Zamość on 21 August. The aim is to evaluate the meteorological background, intensity, and spatial characteristics of these short-duration storms. We used high-resolution meteorological observations, radar imagery, and satellite data provided by the Institute of Meteorology and Water Management (IMGW-PIB). The storms were analyzed using temporal rainfall profiles, Chomicz α index classification, and comparison with World Meteorological Organization (WMO) thresholds for extreme precipitation. Both events exceeded national and international criteria for torrential rainfall. In Zamość, over 88.3 mm of rain fell within one hour, and 131.3 mm within three hours—ranking this episode among the most intense short-duration rainfall events in the region. Convective organization patterns, including multicellular clustering and convective training, were identified as key factors enhancing rainfall intensity. The results demonstrate the diagnostic value of combining national indices with global benchmarks in rainfall assessment. These findings support further integration of convection-permitting models and real-time nowcasting into urban hydrometeorological warning systems. Full article

► Show Figures

Figure 1

15 pages, 1655 KB

Open AccessArticle

Quantitative Prediction of Sediment–Water Partition Coefficients for Tetracycline Antibiotics in a Typical Karst Wetland

by Cong Peng, Jianhong Liang, Xiaodong Pan, Jie Zeng, Kun Ren and Jianwen Cao

Water 2025, 17(18), 2670; https://doi.org/10.3390/w17182670 - 9 Sep 2025

Abstract

The soil–water partition coefficient (Kd) of antibiotics is a critical indicator for assessing their migration potential in the environment. Currently, research on antibiotic Kd values in specific geological settings such as karst wetlands remains relatively limited. This study uniquely integrates partial least squares [...] Read more.

The soil–water partition coefficient (Kd) of antibiotics is a critical indicator for assessing their migration potential in the environment. Currently, research on antibiotic Kd values in specific geological settings such as karst wetlands remains relatively limited. This study uniquely integrates partial least squares (PLS) regression with redundancy analysis (RDA), a hybrid approach that effectively handles complex environmental datasets prone to multicollinearity. The results identified Fe³⁺, NO₃⁻, and PO₄³⁻ in water, as well as clay content, organic matter, bulk density, and pH in sediments, as key factors influencing Kd through redundancy analysis. Using PLS, predictive models were developed for the logKd of four antibiotics: tetracycline (TC), doxycycline (DOX), chlortetracycline (CTC), and demeclocycline (DMC). The models demonstrated strong predictability with Q₂cum values of 0.96, 0.93, 0.99, and 0.83, respectively, indicating excellent model convergence. These findings provide important insights into how soil and water physicochemical properties influence the distribution of antibiotics, support the prediction of antibiotic transport and fate, and contribute to the exposure and risk assessment of these emerging contaminants in aquatic ecosystems. Full article

(This article belongs to the Special Issue Advances in Groundwater Resource Development: Innovative Methods and Technologies)

► Show Figures

Figure 1

24 pages, 3374 KB

Open AccessArticle

Characterization of the Meiobenthic Community Inhabiting the Zwin Coastal Lagoon (Belgium, the Netherlands) and the Role of the Sedimentary Environment

by Elisa Baldrighi, Francesca Alvisi, Carl Van Colen, Eleonora Grassi, Linda Catani, Francesca Ape, Claudio Vasapollo, Elena Manini, Jeffrey G. Baguley and Federica Semprucci

Water 2025, 17(18), 2669; https://doi.org/10.3390/w17182669 - 9 Sep 2025

Abstract

Coastal waters are sensitive habitats that support high biodiversity and provide essential ecosystem goods. Changes in sedimentation regimes due to land-use and engineering activities in the coastal zone affect biodiversity and these habitats’ ecological value. This study aims to characterize the meiobenthic communities [...] Read more.

Coastal waters are sensitive habitats that support high biodiversity and provide essential ecosystem goods. Changes in sedimentation regimes due to land-use and engineering activities in the coastal zone affect biodiversity and these habitats’ ecological value. This study aims to characterize the meiobenthic communities inhabiting the Zwin tidal lagoon, located on the border between Belgium and the Netherlands, and to evaluate to what extent the sedimentological characteristics and the quantity and composition of organic matter influence the composition and distribution of meiofauna. The meiobenthic community showed traits of a well-established population dominated by nematodes, followed by copepods + nauplii. Notably, meiofauna rapidly colonized the area after its opening to the sea in February 2019 (two years before sampling), showing that even very weak tidal currents were sufficient to suspend and transport these animals to the new environment. Our results suggest that the Zwin lagoon is a productive system with high food quality (i.e., PRT/CHO ≥ 1), predominantly of marine origin. Major structural differences in communities were related to the sedimentary environments at the investigated stations and estimations of the quantity of food. The present findings confirm that sedimentary dynamics and depositional processes, through their influence on sediment properties (e.g., grain size) and organic matter’s quantity and composition, shape meiofaunal communities and their vertical and horizontal distributions. Full article

(This article belongs to the Special Issue Marine Biodiversity and Its Relationship with Climate/Environment)

► Show Figures

Figure 1

42 pages, 2723 KB

Open AccessReview

Citizen Science for Monitoring Plastic Pollution from Source to Sea: A Systematic Review of Methodologies, Best Practices, and Challenges

by Corinne Corbau, Alexandre Lazarou, Oliver Bajt, Vlatka Filipović Marijić, Tatjana Simčič, Massimo Coltorti, Elisa Pignoni and Umberto Simeoni

Water 2025, 17(18), 2668; https://doi.org/10.3390/w17182668 - 9 Sep 2025

Abstract

Citizen science provides a valuable approach for tracking plastic pollution; however, its effectiveness is often limited by methodological inconsistencies, concerns about data quality, and a persistent gap between data collection and policy implementation. This systematic review addresses the key question: What constitutes a [...] Read more.

Citizen science provides a valuable approach for tracking plastic pollution; however, its effectiveness is often limited by methodological inconsistencies, concerns about data quality, and a persistent gap between data collection and policy implementation. This systematic review addresses the key question: What constitutes a comprehensive set of best practices for addressing these issues and enhancing the scientific and societal impact of citizen science in monitoring plastic pollution from source to sea? Analyzing 84 studies, from beach cleanups to microplastic sampling, this review synthesizes best practices and identifies remaining gaps. It presents a structured framework designed to enhance data quality and volunteer participation. Key challenges include the ‘microplastic analytical bottleneck,’ the ‘digital divide,’ and notable geographical and demographic disparities that hinder the integration of policies. While citizen science is effective for large-scale data collection, its main challenge is translating data into actionable policies. The main contribution of this review is a series of practical recommendations aimed at improving methodological consistency, ensuring fair volunteer participation, and facilitating the transition from citizen data to evidence-based environmental management, thereby enhancing the effectiveness and impact of citizen science. Full article

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

► Show Figures

Figure 1

19 pages, 4346 KB

Open AccessArticle

Assessment of Stock Enhancement Efficacy for Hypophthalmichthys molitrix and Aristichthys nobilis in the Xixi of Jiulong River Basin

by Hong Li, Ta-Jen Chu, Qing-Min Zeng, Jia-Qiao Wang, Liang-Min Huang, Kai Liu, Fen-Fen Ji, Shao-Peng Guo and Yi-Jia Shih

Water 2025, 17(18), 2667; https://doi.org/10.3390/w17182667 - 9 Sep 2025

Abstract

Stocking and replenishing fish are crucial for the ecological restoration of aquatic biological resources. Since 2017, a long-term stocking program of Hypophthalmichthys molitrix and Aristichthys nobilis has been underway in the Xixi River basin of the Jiulong River. To understand the status of [...] Read more.

Stocking and replenishing fish are crucial for the ecological restoration of aquatic biological resources. Since 2017, a long-term stocking program of Hypophthalmichthys molitrix and Aristichthys nobilis has been underway in the Xixi River basin of the Jiulong River. To understand the status of fishery resources following this long-term stocking program, field surveys were conducted every two months from October 2023 to October 2024. Traditional netting, resource assessment and environmental DNA (eDNA) analysis methods were used to conduct a comprehensive assessment of resource abundance, stocking contribution and ecological adaptability. The research revealed that the annual survival rates for H. molitrix and A. nobilis were 40.25% and 48.19%, respectively. The current numerical ratio of H. molitrix to A. nobilis stands at 1.97:1, indicating that the survival number of H. molitrix is better than that of A. nobilis. No mature gonads were observed in any sampled individuals, demonstrating that the current population is highly dependent on artificial replenishment. This study provides valuable data support for aquatic resource restoration and ecological management in the Jiulong River Basin. Full article

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

► Show Figures

Figure 1

12 pages, 869 KB

Open AccessArticle

Analysis of Soil Salinization Characteristics in Coastal Area of Panjin City, Liaoning Province

by Jiaquan Sun, Wanbing Song, Xiubo Sun, Jian Cui and Hongwei Ma

Water 2025, 17(18), 2666; https://doi.org/10.3390/w17182666 - 9 Sep 2025

Abstract

Soil salinization is one of the major geological environmental issues in the coastal area of Panjin City, Liaoning Province. By collecting soil samples from the upper 0–40 cm and conducting total salt content tests, this study summarizes the statistical characteristics of soil salinity [...] Read more.

Soil salinization is one of the major geological environmental issues in the coastal area of Panjin City, Liaoning Province. By collecting soil samples from the upper 0–40 cm and conducting total salt content tests, this study summarizes the statistical characteristics of soil salinity content, analyzes the correlations between soil salinity ions and total salt content, explores the spatial distribution characteristics of soil salinization in the study area, evaluates soil salinization, and identifies the driving factors of soil salinization in the region. The results show that the total salt content in the study area ranges from 1.3 to 9.0 g kg⁻¹, with Na⁺, Cl⁻, and SO₄²⁻ being the dominant ions. Total salt content is positively correlated with Mg²⁺, Na⁺, Cl⁻, and SO₄²⁻, indicating that the main forms of salinity are sulfates and chlorides. The degree of soil salinization is classified as mild to moderate. The types of soil salinization change from the center to the sides in the following order: sulfate type → chloride–sulfate type → sulfate–chloride type. The degree of soil salinization shows distinct zonality, gradually decreasing from the coastal area to the inland. The main driving factor of soil salinization is the groundwater level, while the evapotranspiration ratio and groundwater salinity are secondary factors that jointly control the process. Full article

(This article belongs to the Special Issue Long-Term Coastal Evolution and Morphodynamics: Ecosystem Protection and Coastal Safety)

► Show Figures

Figure 1

21 pages, 1585 KB

Open AccessArticle

Hybrid ITSP-LSTM Approach for Stochastic Citrus Water Allocation Addressing Trade-Offs Between Hydrological-Economic Factors and Spatial Heterogeneity

by Wen Xu, Rui Hu, Yifei Zheng, Ying Yu, Yanpeng Cai and Shijiang Zhu

Water 2025, 17(18), 2665; https://doi.org/10.3390/w17182665 - 9 Sep 2025

Abstract

This study addresses the critical challenge of optimizing water resource allocation in fragmented citrus cultivation zones, particularly in Anfusi Town, a key citrus production area in China’s middle-lower Yangtze River region. To overcome the limitations of traditional deterministic models and spatially heterogeneous water [...] Read more.

This study addresses the critical challenge of optimizing water resource allocation in fragmented citrus cultivation zones, particularly in Anfusi Town, a key citrus production area in China’s middle-lower Yangtze River region. To overcome the limitations of traditional deterministic models and spatially heterogeneous water supply–demand dynamics, an innovative framework integrating interval two-stage stochastic programming (ITSP) with long short-term memory (LSTM) neural networks is proposed. The LSTM component forecasts irrigation demand and supply under climate variability, while ITSP optimizes dynamic allocation strategies by quantifying uncertainties through interval analysis and balancing economic returns with hydrological risks. Key results demonstrate an 8.67% increase in system-wide benefits compared to baseline practices in the current year scenario. For the planning year (2025), the model identifies optimal water distribution thresholds: an upper limit of 3.85 × 10⁶ m³ for high-availability zone A and lower limits of 1.62 × 10⁶ m³ for moderate-to-low-availability zones B and C. These allocations minimize water scarcity penalties while maximizing net benefits, prioritizing local over external water sources to reduce costs. The study innovates by integrating stochastic-economic analysis with spatial prioritization of high-marginal-benefit zones and uncertainty robustness via interval analysis and two-stage decision making. By bridging a research gap in citrus irrigation optimization, this approach advances sustainable water management in complex agricultural systems, offering a scalable solution for regions facing fragmented landscapes and climate-driven water scarcity. Full article

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

► Show Figures

Figure 1

24 pages, 3996 KB

Open AccessArticle

Exploring the Dynamics of Virtual Water Trade in Crop Products Between Morocco and the European Union

by Mounsif Ridaoui, Aziz Razzouki, Hafsa Ouhbi, Mohamed Oudgou and Abdeslam Boudhar

Water 2025, 17(18), 2664; https://doi.org/10.3390/w17182664 - 9 Sep 2025

Abstract

Morocco, located in an arid region and increasingly affected by climate change, faces chronic water stress. This structural vulnerability places mounting pressure on the country’s water resources. International trade contributes significantly to this pressure, particularly through the export of water-intensive agricultural products. This [...] Read more.

Morocco, located in an arid region and increasingly affected by climate change, faces chronic water stress. This structural vulnerability places mounting pressure on the country’s water resources. International trade contributes significantly to this pressure, particularly through the export of water-intensive agricultural products. This study investigates the virtual water trade flows of the 32 most-traded agricultural products between Morocco and its primary trading partner, the European Union, over the period of 2000–2020. This study adopts a bottom-up approach, employing the FAO’s CROPWAT 8.0 software based on the Penman–Monteith climatic model to estimate crop water requirements. The results indicate that Morocco was a net importer of virtual water in its agricultural trade with EU countries, with a cumulative net virtual water of 51,839.171 million cubic meters (Mm³). During the study period, Morocco exported a total of 3393.791 Mm³ of virtual water to the EU, primarily through fruits (2903.028 Mm³; 85.539%) and vegetables (467.928 Mm³; 13.788%), notably those with high water footprints. The top three EU importers of Moroccan virtual water were France (1138.785 Mm³), the Netherlands (874.323 Mm³), and the United Kingdom (430.872 Mm³). Conversely, virtual water imports by Morocco amounted to 55,232.963 Mm³, overwhelmingly dominated by cereals, which accounted for 99.697% of the total. These imports originated mainly from France (37,154.090 Mm³), Germany (4980.296 Mm³), and Poland (2330.039 Mm³). The analysis of Morocco’s virtual water balance with EU countries revealed that Morocco was a net virtual importer in trade with most of them. Furthermore, the crop-level virtual water trade balance revealed a tendency to export water-intensive crops that offer relatively low economic water productivity. However, four agricultural products recorded a high economic return per unit of Virtual Water Exported: tomatoes returned 19.80 USD/m³, strawberries 16.02 USD/m³, carrots 13.06 USD/m³, and watermelons 8.11 USD/m³. These findings underscore the importance of integrating water footprint analysis into national agricultural policy to maximize the economic productivity of water and ensure the sustainability of resources in a water-stressed country. Full article

(This article belongs to the Special Issue Balancing Competing Demands for Sustainable Water Development)

► Show Figures

Figure 1

20 pages, 1373 KB

Open AccessArticle

Sustainable Water Retention Strategy for Urban Resilience: A Valorization and Action Model for Cities

by Piotr Bujak, Magdalena Grochulska-Salak, Eliza Maciejewska, Kinga Rybak-Niedziółka, Věra Hubačíková, Barbara Francke and Agnieszka Starzyk

Water 2025, 17(18), 2663; https://doi.org/10.3390/w17182663 - 9 Sep 2025

Abstract

The objective of this article is to propose a novel model for evaluating retention solutions in urban areas. This model is designed to serve as a tool to support integrated urban planning in the context of reurbanization and climate change adaptation processes. The [...] Read more.

The objective of this article is to propose a novel model for evaluating retention solutions in urban areas. This model is designed to serve as a tool to support integrated urban planning in the context of reurbanization and climate change adaptation processes. The model is both diagnostic and decision-support in nature, integrating spatial, environmental, and functional data. It analyzes these data based on a spatial dependency matrix. A comprehensive consideration of both physiographic factors (e.g., geomorphological typology and land ownership) and social and institutional factors (e.g., institutional readiness and stakeholder engagement) was undertaken. The modelling employs methodologies that are characteristic of urban and landscape design, including multi-criteria analysis, case studies, expert assessment, and Geographic Information System (GIS) tools. The assessment of the retention potential was conducted with consideration for the typology of buildings, infiltration capacity, soil permeability, and existing infrastructure. The findings of the present study demonstrate that local spatial and social conditions exert a substantial influence on the efficacy of retention implementation. The model enables the prioritization of actions and the selection of suitable solutions (context-sensitive retention strategies), thus making it a valuable instrument for designers, urban planners, and decision-makers. The proposed approach can be used in urban planning as a practical tool to support decisions on resilient city development and urban water management. Full article

(This article belongs to the Special Issue Urban Water Management: Challenges and Prospects)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Water, Volume 17, Issue 18 (September-2 2025) – 35 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI