Water

20 pages, 26018 KiB

Open AccessArticle

An Accuracy Assessment of the ESTARFM Data-Fusion Model in Monitoring Lake Dynamics

by Can Peng, Yuanyuan Liu, Liwen Chen, Yanfeng Wu, Jingxuan Sun, Yingna Sun, Guangxin Zhang, Yuxuan Zhang, Yangguang Wang, Min Du and Peng Qi

Water 2025, 17(14), 2057; https://doi.org/10.3390/w17142057 (registering DOI) - 9 Jul 2025

Abstract

High-spatiotemporal-resolution remote sensing data are of great significance for surface monitoring. However, existing remote sensing data cannot simultaneously meet the demands for high temporal and spatial resolution. Spatiotemporal fusion algorithms are effective solutions to this problem. Among these, the ESTARFM (Enhanced Spatiotemporal Adaptive [...] Read more.

High-spatiotemporal-resolution remote sensing data are of great significance for surface monitoring. However, existing remote sensing data cannot simultaneously meet the demands for high temporal and spatial resolution. Spatiotemporal fusion algorithms are effective solutions to this problem. Among these, the ESTARFM (Enhanced Spatiotemporal Adaptive Reflection Fusion Model) algorithm has been widely used for the fusion of multi-source remote sensing data to generate high spatiotemporal resolution remote sensing data, owing to its robustness. However, most existing studies have been limited to applying ESTARFM for the fusion of single-surface-element data and have paid less attention to the effects of multi-band remote sensing data fusion and its accuracy analysis. For this reason, this study selects Chagan Lake as the study area and conducts a detailed evaluation of the performance of the ESTARFM in fusing six bands—visible, near-infrared, infrared, and far-infrared—using metrics such as the correlation coefficient and Root Mean Square Error (RMSE). The results show that (1) the ESTARFM fusion image is highly consistent with the clear-sky Landsat image, with the coefficients of determination (R²) for all six bands exceeding 0.8; (2) the Normalized Difference Vegetation Index (NDVI) (R² = 0.87, RMSE = 0.023) and the Normalized Difference Water Index (NDWI) (R² = 0.93, RMSE = 0.022), derived from the ESTARFM fusion data, are closely aligned with the real values; (3) the evaluation and analysis of different bands for various land-use types reveal that R² generally exhibits a favorable trend. This study extends the application of the ESTARFM to inland water monitoring and can be applied to scenarios similar to Chagan Lake, facilitating the acquisition of high-frequency water-quality information. Full article

(This article belongs to the Special Issue Drought Evaluation Under Climate Change Condition)

► Show Figures

Figure 1

19 pages, 1943 KiB

Open AccessReview

A Bibliometric Analysis and Visualization of the Assessment of Non-Point Source Pollution Control

by Qijie Geng, Changkun Lin, Shan Li and Fei Guo

Water 2025, 17(14), 2056; https://doi.org/10.3390/w17142056 (registering DOI) - 9 Jul 2025

Abstract

Non-point source (NPS) pollution continues to pose threats to ecosystems and NPS pollution control represents a significant global challenge. This study presents a bibliometric analysis of 1328 studies on the assessment of NPS pollution control, collected from the Web of Science (WOS) Core [...] Read more.

Non-point source (NPS) pollution continues to pose threats to ecosystems and NPS pollution control represents a significant global challenge. This study presents a bibliometric analysis of 1328 studies on the assessment of NPS pollution control, collected from the Web of Science (WOS) Core Collection database for the period between January 1993 and April 2025. The analysis encompassed multiple dimensions, including annual publication volume, most prolific authors and journals, top funding organizations, and keyword co-occurrence. Results reveal a consistently accelerating publication trend, with China and the United States emerging as the most prominent contributors. The findings highlight a distinct evolution in research focus—from early efforts centered on pollutant source tracing and model-based simulations of best management practices (BMPs), such as SWAT and AnnAGNPS, to more holistic, multidimensional assessments that integrate economic, environmental, ecological, and social dimensions to support multi-objective optimization. Future directions are expected to emphasize non-structural measures and promote the development of globally standardized evaluation frameworks for NPS control strategies, thereby enhancing cross-regional comparability and aligning with the United Nations Sustainable Development Goals (UNSDGs). Full article

(This article belongs to the Special Issue Non-Point Source Pollution and Water Resource Protection)

► Show Figures

Figure 1

23 pages, 11464 KiB

Open AccessArticle

Characterization of Water Quality and the Relationship Between WQI and Benthic Macroinvertebrate Communities as Ecological Indicators in the Ghris Watershed, Southeast Morocco

by Ali El Mansour, Saida Ait Boughrous, Ismail Mansouri, Abdellali Abdaoui, Wafae Squalli, Asmae Nouayti, Mohamed Abdellaoui, El Mahdi Beyouda, Christophe Piscart and Ali Ait Boughrous

Water 2025, 17(14), 2055; https://doi.org/10.3390/w17142055 (registering DOI) - 9 Jul 2025

Abstract

The Ghris watershed in southern Morocco is a significant ecological and agricultural area. However, due to the current impacts of climate change, farming activities, and pollution, data on its quality and biological importance need to be updated. Therefore, this study aimed to evaluate [...] Read more.

The Ghris watershed in southern Morocco is a significant ecological and agricultural area. However, due to the current impacts of climate change, farming activities, and pollution, data on its quality and biological importance need to be updated. Therefore, this study aimed to evaluate the physico-chemical and biological quality of surface water in the Ghris River. The Water Quality Index (WQI) and the Iberian Biological Monitoring Working Group (IBMWP) index were used to assess water quality along four sampling sites in 2024. The collected data were analyzed with descriptive and multivariate statistics. In total, 424 benthic macroinvertebrates belonging to seven orders were identified in the surface waters of the Ghris basin. These microfauna were significantly variable among the studied sites (p < 0.05). Station S4 is significantly rich in species, including seven orders and nine families of macroinvertebrates, followed by Station S2, with seven orders and eight families. Stations S3 and S1 showed less species diversity, with three orders and one family, respectively. The Insecta comprised 95.9% of the abundance, while the Crustacea constituted just 4.1%. The physico-chemical parameters significantly surpassed (p < 0.05) the specified norms of surface water in Morocco. This indicates a decline in the water quality of the studied sites. The findings of the principal component analysis (PCA) demonstrate that the top two axes explain 87% of the cumulative variation in the data. Stations 2 and 3 are closely associated with high concentrations of pollutants, notably Cl⁻, SO₄²⁻, NO₃⁻, and K⁺ ions. Dissolved oxygen (DO) showed a slight correlation with S2 and S3, while S4 was characterized by high COD and PO₄ concentrations, low levels of mineral components (except Cl⁻), and average temperature conditions. Bioindication scores for macroinvertebrate groups ranging from 1 to 10 enabled the assessment of pollution’s influence on aquatic biodiversity. The IBMWP biotic index indicated discrepancies in water quality across the sites. This study gives the first insight and updated data on the biological and chemical quality of surface water in the Ghris River and the entire aquatic ecosystem in southeast Morocco. These data are proposed as a reference for North African and Southern European rivers. However, more investigations are needed to evaluate the impacts of farming, mining, and urbanization on the surface and ground waters in the study zone. Similarly, it is vital to carry out additional research in arid and semi-arid zones since there is a paucity of understanding regarding taxonomic and functional diversity, as well as the physico-chemical factors impacting water quality. Full article

(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)

► Show Figures

Figure 1

36 pages, 5746 KiB

Open AccessSystematic Review

Decentralized Renewable-Energy Desalination: Emerging Trends and Global Research Frontiers—A Comprehensive Bibliometric Review

by Roger Pimienta Barros, Arturo Fajardo and Jaime Lara-Borrero

Water 2025, 17(14), 2054; https://doi.org/10.3390/w17142054 (registering DOI) - 9 Jul 2025

Abstract

Decentralized desalination systems driven by renewable energy sources have surfaced as a feasible way to alleviate water scarcity in arid and rural areas. This bibliometric study aims to clarify the research trends, conceptual frameworks, and cooperative dynamics in the scientific literature on decentralized [...] Read more.

Decentralized desalination systems driven by renewable energy sources have surfaced as a feasible way to alleviate water scarcity in arid and rural areas. This bibliometric study aims to clarify the research trends, conceptual frameworks, and cooperative dynamics in the scientific literature on decentralized renewable-powered desalination techniques. Using a thorough search approach, 1354 papers were found. Duplicates, thematically unrelated works, and entries with poor information were removed using the PRISMA 2020 framework. A selected 832 relevant papers from a filtered dataset were chosen for in-depth analysis. Quantitative measures were obtained by means of Bibliometrix; network visualisation was obtained by means of VOSviewer (version 1.6.19) and covered co-authorship, keyword co-occurrence, and citation structures. Over the previous 20 years, the data show a steady rise in academic production, especially in the fields of environmental science, renewable energy engineering, and water treatment technologies. Author keyword co-occurrence mapping revealed strong theme clusters centred on solar stills, thermoelectric modules, reverse osmosis, and off-grid systems. Emphasizing current research paths and emerging subject borders, this paper clarifies the intellectual and social structure of the field. The outcomes are expected to help policy creation, cooperative projects, and strategic planning meant to hasten innovation in sustainable and decentralized water desalination. Full article

(This article belongs to the Section Water-Energy Nexus)

► Show Figures

Figure 1

1 pages, 119 KiB

Open AccessCorrection

Correction: Ramadan et al. Evaluation and Mitigation of Flash Flood Risks in Arid Regions: A Case Study of Wadi Sudr in Egypt. Water 2022, 14, 2945

by Elsayed M. Ramadan, Hossny A. Shahin, Hany F. Abd-Elhamid, Martina Zelenakova and Hazem M. Eldeeb

Water 2025, 17(14), 2053; https://doi.org/10.3390/w17142053 (registering DOI) - 9 Jul 2025

Abstract

In the original publication [...] Full article

(This article belongs to the Special Issue Water Supply System (WSS) Reliability, Safety and Risk Modelling & Assessment)

15 pages, 2302 KiB

Open AccessArticle

Investigation of TiO₂ Nanoparticles Added to Extended Filamentous Aerobic Granular Sludge System: Performance and Mechanism

by Jun Liu, Songbo Li, Shunchang Yin, Zhongquan Chang, Xiao Ma and Baoshan Xing

Water 2025, 17(14), 2052; https://doi.org/10.3390/w17142052 (registering DOI) - 9 Jul 2025

Abstract

The widely utilized TiO₂ nanoparticles (NPs) tend to accumulate in wastewater and affect microbial growth. This work investigated the impacts of prolonged TiO₂ NP addition to filamentous aerobic granular sludge (AGS) using two identical sequencing batch reactors (SBRs, R1 and R2). [...] Read more.

The widely utilized TiO₂ nanoparticles (NPs) tend to accumulate in wastewater and affect microbial growth. This work investigated the impacts of prolonged TiO₂ NP addition to filamentous aerobic granular sludge (AGS) using two identical sequencing batch reactors (SBRs, R1 and R2). R1 (the control) had no TiO₂ NP addition. In this reactor, filamentous bacteria from large AGS grew rapidly and extended outward, the sludge volume index (SVI₃₀) quickly increased from 41.2 to 236.8 mL/g, mixed liquid suspended solids (MLSS) decreased from 4.72 to 0.9 g/L, and AGS disintegrated on day 40. Meanwhile, the removal rates of COD and NH₄⁺-N both exhibited significant declines. In contrast, 5–30 mg/L TiO₂ NPs was added to R2 from day 21 to 100, and the extended filamentous bacteria were effectively controlled on day 90 under a 30 mg/L NP dosage, leading to significant reductions in COD and NH₄⁺-N capabilities, particularly the latter. Therefore, NP addition was stopped on day 101, and AGS became dominant in R2, with an SVI₃₀ and MLSS of 48.5 mL/g and 5.67 g/L on day 130. COD and NH₄⁺-N capabilities both increased to 100%. Microbial analysis suggested that the dominant filamentous bacteria—Proteobacteria, Bacteroidetes, and Acidobacteria—were effectively controlled by adding 30 mg/L TiO₂ NPs. XRF analysis indicated that 11.7% TiO₂ NP accumulation made the filamentous bacteria a framework for AGS recovery and operation without NPs. Functional analysis revealed that TiO₂ NPs had stronger inhibitory effects on nitrogen metabolism compared to carbon metabolism, and both metabolic pathways recovered when NP addition was discontinued in a timely manner. These findings offer critical operational guidance for maintaining the stable performance of filamentous AGS systems treating TiO₂ NP wastewater in the future. Full article

(This article belongs to the Topic Towards Energy-Positive and Carbon-Neutral Technology for Wastewater Treatment and Reclamation)

► Show Figures

Figure 1

20 pages, 2942 KiB

Open AccessArticle

Zooplankton Community Responses to Eutrophication and TOC: Network Clustering in Regionally Similar Reservoirs

by Yerim Choi, Hye-Ji Oh, Geun-Hyeok Hong, Dae-Hee Lee, Jeong-Hui Kim, Sang-Hyeon Park, Jung-Ho Yun and Kwang-Hyeon Chang

Water 2025, 17(14), 2051; https://doi.org/10.3390/w17142051 (registering DOI) - 9 Jul 2025

Abstract

This study analyzed the relationship between zooplankton communities and water quality characteristics, with a focus on total organic carbon (TOC), in 22 reservoirs within the Geum River basin that share similar climatic conditions but exhibit varying levels of pollution. Across all reservoirs, zooplankton [...] Read more.

This study analyzed the relationship between zooplankton communities and water quality characteristics, with a focus on total organic carbon (TOC), in 22 reservoirs within the Geum River basin that share similar climatic conditions but exhibit varying levels of pollution. Across all reservoirs, zooplankton community structures showed the highest correlations with TOC, suspended solids (SS), chlorophyll-a (Chl-a), and Secchi depth (SD), with stronger associations observed for rotifers and cladocerans compared to copepods. The classification of zooplankton community composition patterns, followed by an analysis of their associations with TOC concentrations, revealed relatively distinct differences between high-TOC and low-TOC reservoirs, indicating that TOC functions as a key determinant of community composition. Meanwhile, network analysis based on overall water quality characteristics indicated that patterns of water quality similarity among zooplankton-based communities differed somewhat from those based solely on TOC concentrations, suggesting that TOC may exert an independent influence on zooplankton community structure. In high-TOC reservoirs, typical eutrophic characteristics—such as elevated chlorophyll-a, total phosphorus, and suspended solids, along with reduced water transparency—were observed, accompanied by higher zooplankton abundance and a greater proportion of rotifers within the community. In contrast, low-TOC reservoirs, despite exhibiting no marked differences in other water quality variables, showed higher diversity of cladocerans alongside rotifers, further supporting the independent role of TOC in shaping zooplankton community structures. These findings highlight TOC not only as a general indicator of pollution but also as an ecologically significant factor influencing zooplankton community composition and carbon dynamics in reservoir ecosystems. They suggest that TOC should be considered a key variable in future assessments and management of lentic ecosystems. Full article

(This article belongs to the Special Issue Impacts of Environmental Change and Human Activities on Aquatic Ecosystems, 2nd Edition)

► Show Figures

Figure 1

19 pages, 5852 KiB

Open AccessArticle

Spatial Distribution of Heavy Metals in the Water of Tequesquitengo Lake, Morelos, Mexico, and Their Biosorption by Pectin

by S. Viridiana Vargas-Solano, Y. Yelitza Lizcano-Delgado, Francisco Rodríguez-González, Julio A. Saldivar-Calvo, Rita Martínez-Velarde, Alex Osorio-Ruiz, María Luisa Corona Rangel and Sandra S. Morales-García

Water 2025, 17(14), 2050; https://doi.org/10.3390/w17142050 - 8 Jul 2025

Abstract

In this study, the presence of heavy metals (HMs) is determined to assess surface water contamination; biosorbent materials are also used to remove them and thus improve their quality. The objective of this work was to study the spatial distribution of HMs in [...] Read more.

In this study, the presence of heavy metals (HMs) is determined to assess surface water contamination; biosorbent materials are also used to remove them and thus improve their quality. The objective of this work was to study the spatial distribution of HMs in water samples from Tequesquitengo Lake, Morelos, Mexico; pectin was also used for HM biosorption. For this, fifteen water samples were collected from the central and peripheral zones of the lake; HMs such as Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Zn, As, and Hg were identified and quantified by atomic absorption spectroscopy (AAS). The metal evaluation index (HEI) was calculated, as well as the percentage of HM removal with pectin. The water samples presented high concentrations of Pb, Cr, and Mn in contrast to the other HMs studied. Furthermore, these showed high concentrations (161.2, 85.2, and 65.6 µg/L, respectively) in the peripheral zone. Therefore, these values exceed the permissible limit for human consumption, except for Mn. The HEI value indicated that the lake water exhibits low contamination. After the adsorption of HMs with pectin, Cr (100%), Ni (83%) and Cd (37%) were removed, reducing the total concentration of HMs in the water in all samples. Full article

(This article belongs to the Special Issue Development of New Wastewater Treatments for the Efficient Removal of Micropollutants)

► Show Figures

Figure 1

19 pages, 566 KiB

Open AccessArticle

Energy Audits and Energy Efficiency of Urban Wastewater Systems, Following UWWTP Directive 2024/3019

by Andrea G. Capodaglio

Water 2025, 17(14), 2049; https://doi.org/10.3390/w17142049 - 8 Jul 2025

Abstract

The recent Directive EU/2024/3019, a recast of the previous 1991 Directive 91/271/EEC concerning urban wastewater treatment, introduces new obligations concerning effluents requirements and overall energy management in urban wastewater systems. In addition to increased levels of treatment (including extended tertiary and quaternary pollutants [...] Read more.

The recent Directive EU/2024/3019, a recast of the previous 1991 Directive 91/271/EEC concerning urban wastewater treatment, introduces new obligations concerning effluents requirements and overall energy management in urban wastewater systems. In addition to increased levels of treatment (including extended tertiary and quaternary pollutants removal), the Directive introduces the obligation for treatment facilities to become “energy neutral” at the national sectoral level, increasing reliance on energy optimization and recovery from internal processes and external renewable energy sources. In order to achieve this objective, an obligation to periodically conduct energy audits is introduced; however, while this practice is commonly carried out in residential and industrial buildings, guidelines for its implementation in treatment facilities are currently not precisely defined. The paper summarizes current issues on wastewater sector energy audits, discussing the current state-of-the-art and the expected requirements to conduct such audits. It then discusses the causes of possible facility inefficiencies and their possible solutions from both permanent and transient perspectives. Finally, it addresses the issue of energy neutrality requirement, and the role of renewable energy sources contribution, both natural and internal (process-related) to the sector’s energy efficiency. Full article

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

► Show Figures

Figure 1

20 pages, 11079 KiB

Open AccessArticle

A Bayesian Ensemble Learning-Based Scheme for Real-Time Error Correction of Flood Forecasting

by Liyao Peng, Jiemin Fu, Yanbin Yuan, Xiang Wang, Yangyong Zhao and Jian Tong

Water 2025, 17(14), 2048; https://doi.org/10.3390/w17142048 (registering DOI) - 8 Jul 2025

Abstract

To address the critical demand for high-precision forecasts in flood management, real-time error correction techniques are increasingly implemented to improve the accuracy and operational reliability of the hydrological prediction framework. However, developing a robust error correction scheme remains a significant challenge due to [...] Read more.

To address the critical demand for high-precision forecasts in flood management, real-time error correction techniques are increasingly implemented to improve the accuracy and operational reliability of the hydrological prediction framework. However, developing a robust error correction scheme remains a significant challenge due to the compounded errors inherent in hydrological modeling frameworks. In this study, a Bayesian ensemble learning-based correction (BELC) scheme is proposed which integrates hydrological modeling with multiple machine learning methods to enhance real-time error correction for flood forecasting. The Xin’anjiang (XAJ) model is selected as the hydrological model for this study, given its proven effectiveness in flood forecasting across humid and semi-humid regions, combining structural simplicity with demonstrated predictive accuracy. The BELC scheme straightforwardly post-processes the output of the XAJ model under the Bayesian ensemble learning framework. Four machine learning methods are implemented as base learners: long short-term memory (LSTM) networks, a light gradient-boosting machine (LGBM), temporal convolutional networks (TCN), and random forest (RF). Optimal weights for all base learners are determined by the K-means clustering technique and Bayesian optimization in the BELC scheme. Four baseline schemes constructed by base learners and three ensemble learning-based schemes are also built for comparison purposes. The performance of the BELC scheme is systematically evaluated in the Hengshan Reservoir watershed (Fenghua City, China). Results indicate the following: (1) The BELC scheme achieves better performance in both accuracy and robustness compared to the four baseline schemes and three ensemble learning-based schemes. The average performance metrics for 1–3 h lead times are 0.95 (NSE), 0.92 (KGE), 24.25

m^{3} / s

(RMSE), and 8.71% (RPE), with a PTE consistently below 1 h in advance. (2) The K-means clustering technique proves particularly effective with the ensemble learning framework for high flow ranges, where the correction performance exhibits an increment of 62%, 100%, and 100% for 1 h, 2 h, and 3 h lead hours, respectively. Overall, the BELC scheme demonstrates the potential of a Bayesian ensemble learning framework in improving real-time error correction of flood forecasting systems. Full article

(This article belongs to the Special Issue Innovations in Hydrology: Streamflow and Flood Prediction)

► Show Figures

Figure 1

18 pages, 704 KiB

Open AccessArticle

Water Rights Trading and Agricultural Water Use Efficiency: Evidence from China

by Yi Deng and Lezhu Zhang

Water 2025, 17(14), 2047; https://doi.org/10.3390/w17142047 - 8 Jul 2025

Abstract

Inefficient agricultural water use is a significant factor exacerbating global water scarcity. Water rights trading (WRT) offers a new governance paradigm to address this issue. Initiated by China in 2014, the WRT policy provides a case for researching formal water markets in developing [...] Read more.

Inefficient agricultural water use is a significant factor exacerbating global water scarcity. Water rights trading (WRT) offers a new governance paradigm to address this issue. Initiated by China in 2014, the WRT policy provides a case for researching formal water markets in developing countries. This paper uses a sample of 30 Chinese provinces from 2007 to 2022 and employs the difference-in-differences method to evaluate the impact of WRT on agricultural water use efficiency (AWUE). The findings suggest that AWUE in pilot areas increased by an average of 48.1% compared to non-pilot areas. Heterogeneity analysis reveals a stronger WRT impact on AWUE in regions with developed markets, abundant water, and high agricultural dependence. Subsequent analysis identifies that WRT enhances AWUE mainly by incentivizing water-saving innovation, promoting cross-industry factor mobility, and optimizing crop structures. This study thus offers empirical evidence supporting China’s water marketization reform and explores WRT policy as a pathway to enhance AWUE. Full article

(This article belongs to the Special Issue Economic Approaches to Sustainable Water Management: Policy, Innovation, and Global Challenges)

27 pages, 5832 KiB

Open AccessArticle

Incorporation of Horizontal Aquifer Flow into a Vertical Vadose Zone Model to Simulate Natural Groundwater Table Fluctuations

by Vipin Kumar Oad, Adam Szymkiewicz, Tomasz Berezowski, Anna Gumuła-Kawęcka, Jirka Šimůnek, Beata Jaworska-Szulc and René Therrien

Water 2025, 17(14), 2046; https://doi.org/10.3390/w17142046 - 8 Jul 2025

Viewed by 9

Abstract

The main goal of our work was to evaluate approaches for modeling lateral outflow from shallow unconfined aquifers in a one-dimensional model of vertical variably-saturated flow. The HYDRUS-1D model was modified by implementing formulas representing lateral flow in an aquifer, with linear or [...] Read more.

The main goal of our work was to evaluate approaches for modeling lateral outflow from shallow unconfined aquifers in a one-dimensional model of vertical variably-saturated flow. The HYDRUS-1D model was modified by implementing formulas representing lateral flow in an aquifer, with linear or quadratic drainage functions describing the relationship between groundwater head and flux. The results obtained by the modified HYDRUS-1D model were compared to the reference simulations with HydroGeoSphere (HGS), with explicit representation of 2D flow in unsaturated and saturated zones in a vertical cross-section of a strip aquifer, including evapotranspiration and plant water uptake. Four series of simulations were conducted for sand and loamy sand soil profiles with deep (6 m) and shallow (2 m) water tables. The results indicate that both linear and quadratic drainage functions can effectively capture groundwater table fluctuations and soil water dynamics. HYDRUS-1D demonstrates notable accuracy in simulating transient fluctuations but shows higher variability near the surface. The study concludes that both quadratic and linear drainage boundary conditions can effectively represent horizontal aquifer flow in 1D models, enhancing the ability of such models to simulate groundwater table fluctuations. Full article

(This article belongs to the Section Hydrology)

► Show Figures

Figure 1

25 pages, 2721 KiB

Open AccessArticle

GIS-Based Assessment of Stormwater Harvesting Potentials: A Sustainable Approach to Alleviate Water Scarcity in Rwanda’s Eastern Savanna Agroecological Zone

by Herve Christian Tuyishime and Kyung Sook Choi

Water 2025, 17(14), 2045; https://doi.org/10.3390/w17142045 - 8 Jul 2025

Viewed by 43

Abstract

Water scarcity remains critical in Rwanda’s Eastern Savanna Agroecological Zone due to erratic rainfall, prolonged dry seasons, and rising water demands. This challenge threatens agricultural productivity, food security, and livelihoods. Stormwater harvesting presents a sustainable solution that increases water availability and mitigates the [...] Read more.

Water scarcity remains critical in Rwanda’s Eastern Savanna Agroecological Zone due to erratic rainfall, prolonged dry seasons, and rising water demands. This challenge threatens agricultural productivity, food security, and livelihoods. Stormwater harvesting presents a sustainable solution that increases water availability and mitigates the impacts of climate variability. This study utilizes Geographic Information System (GIS) tools and SCS-CN to assess stormwater harvesting potential in the region. The methodology includes analyzing land use, soil type, rainfall data (30 years, from 1994 to 2023), and topography. Key research steps involve delineating catchment areas, estimating runoff volumes, and selecting optimal storage sites using multi-criteria decision analysis. Findings include eight main water reservoirs, each with a unique code (W_R1 to W_R8), geographic coordinates (X and Y), and 10 million cubic meters storage volumes. W_R1 has the smallest volume at 0.242 × 10⁶ m³, while W_R2 has the largest volume at 8.51 × 10⁶ m³. W_R3, W_R5, and W_R7 are additional noteworthy reservoirs with sizable capacities. The findings contribute to policy formulation and Sustainable Development Goals (SDGs) related to clean water, food security, and climate action. This research provides a replicable framework for addressing water scarcity and enhancing long-term resilience in water-stressed regions. Full article

(This article belongs to the Topic Hydrology and Water Resources in Agriculture and Ecology—2nd Edition)

► Show Figures

Figure 1

19 pages, 1654 KiB

Open AccessArticle

Groundwater Impacts and Sustainability in Italian Quarrying: Evaluating the Effectiveness of Existing Technical Standards

by Matteo Paoletti

Water 2025, 17(14), 2044; https://doi.org/10.3390/w17142044 - 8 Jul 2025

Viewed by 45

Abstract

Quarrying is a key driver in economic growth but also poses significant environmental impacts, particularly on groundwater resources. With approximately 4000 active quarries and diverse hydrological and hydrogeological conditions across Italy, the need for effective regulations that ensure both sustainable extraction and groundwater [...] Read more.

Quarrying is a key driver in economic growth but also poses significant environmental impacts, particularly on groundwater resources. With approximately 4000 active quarries and diverse hydrological and hydrogeological conditions across Italy, the need for effective regulations that ensure both sustainable extraction and groundwater protection is paramount. This study analyzed the European directives, national legislation, and regional quarrying plans governing extractive activities, with a particular focus on groundwater protection. By analyzing the Italian quarries and their main hydrogeological characteristics, the most prevalent hydrogeological scenarios associated with quarrying activities across the country have been identified. The findings reveal significant gaps in the current regulatory framework, characterized by fragmentation and inconsistency across regions. Critical concerns across the quarry lifecycle (planning, excavation, and reclamation) are not comprehensively addressed, and mandatory monitoring and safeguard requirements are lacking. A more structured regulatory approach could incorporate key parameters identified in this study, particularly quarry size and groundwater level depth relative to the excavation plan. Additionally, hydrogeological vulnerability must be considered to guide risk assessment, particularly for alluvial and limestone hydrogeological complexes, which host a substantial number of Italian quarries and require stricter safeguards due to their high susceptibility to contamination and hydrodynamic alterations. Full article

(This article belongs to the Section Hydrogeology)

► Show Figures

Figure 1

17 pages, 18340 KiB

Open AccessArticle

Physics-Informed Deep Learning for Karst Spring Prediction: Integrating Variational Mode Decomposition and Long Short-Term Memory with Attention

by Liangjie Zhao, Stefano Fazi, Song Luan, Zhe Wang, Cheng Li, Yu Fan and Yang Yang

Water 2025, 17(14), 2043; https://doi.org/10.3390/w17142043 - 8 Jul 2025

Viewed by 44

Abstract

Accurately forecasting karst spring discharge remains a significant challenge due to the inherent nonstationarity and multi-scale hydrological dynamics of karst hydrological systems. This study presents a physics-informed variational mode decomposition long short-term memory (VMD-LSTM) model, enhanced with an attention mechanism and Monte Carlo [...] Read more.

Accurately forecasting karst spring discharge remains a significant challenge due to the inherent nonstationarity and multi-scale hydrological dynamics of karst hydrological systems. This study presents a physics-informed variational mode decomposition long short-term memory (VMD-LSTM) model, enhanced with an attention mechanism and Monte Carlo dropout for uncertainty quantification. Hourly discharge data (2013–2018) from the Zhaidi karst spring in southern China were decomposed using VMD to extract physically interpretable temporal modes. These decomposed modes, alongside precipitation data, were input into an attention-augmented LSTM incorporating physics-informed constraints. The model was rigorously evaluated against a baseline standalone LSTM using an 80% training, 15% validation, and 5% testing data partitioning strategy. The results demonstrate substantial improvements in prediction accuracy for the proposed framework compared to the standard LSTM model. Compared to the baseline LSTM, the RMSE during testing decreased dramatically from 0.726 to 0.220, and the NSE improved from 0.867 to 0.988. The performance gains were most significant during periods of rapid conduit flow (the peak RMSE decreased by 67%) and prolonged recession phases. Additionally, Monte Carlo dropout, using 100 stochastic realizations, effectively quantified predictive uncertainty, achieving over 96% coverage in the 95% confidence interval (CI). The developed framework provides robust, accurate, and reliable predictions under complex hydrological conditions, highlighting substantial potential for supporting karst groundwater resource management and enhancing flood early-warning capabilities. Full article

(This article belongs to the Special Issue Advances in Machine Learning and Artificial Intelligence Technologies for Hydrological Processes and Hydrologic Disasters)

► Show Figures

Figure 1

24 pages, 2126 KiB

Open AccessArticle

Contaminant Assessment and Potential Ecological Risk Evaluation of Lake Shore Surface Sediments

by Audrey Maria Noemi Martellotta and Daniel Levacher

Water 2025, 17(14), 2042; https://doi.org/10.3390/w17142042 - 8 Jul 2025

Viewed by 67

Abstract

The interruption of solid transport causes sediment deposition, compromising the useful storage capacity. Therefore, it is essential to remove these materials, currently labelled as waste and disposed of in landfills, by identifying alternatives for recovery and valorization, after assessing their compatibility for reuse [...] Read more.

The interruption of solid transport causes sediment deposition, compromising the useful storage capacity. Therefore, it is essential to remove these materials, currently labelled as waste and disposed of in landfills, by identifying alternatives for recovery and valorization, after assessing their compatibility for reuse through characterization, in a circular economy view. This study analyses the potential contamination of shore surface sediments collected at the Camastra and the San Giuliano lakes, located in the Basilicata region. It defines their potential ecological risk, assesses the contamination level status of the sediments, and verifies whether they are polluted and, consequently, suitable for reuse. Analyses carried out using several pollution indices show a slight Arsenic pollution (with values above the regulatory threshold between 55% and 175%) for the San Giuliano sediments and slight Cobalt pollution (with exceedances between 30% and 58.5%) for the Camastra sediments. Subsequently, through statistical analysis, it was possible to make hypotheses on the possible pollutant sources, depending on the geological characteristics of the sampling area and the type of land use, and to identify the potential ecological risk linked to the exceedance of As and Co in San Giuliano and Camastra reservoirs, respectively. In conclusion, this study ascertained the low pollution content in the sampled sediments, so they could be reused in various application fields, from construction to agriculture, significantly reducing landfill disposal. Full article

(This article belongs to the Special Issue Soil Erosion and Sedimentation by Water)

► Show Figures

Figure 1

25 pages, 11595 KiB

Open AccessArticle

Flood Susceptibility Assessment Using Multi-Tier Feature Selection and Ensemble Boosting Machine Learning Models

by Rajendran Shobha Ajin, Romulus Costache, Alina Bărbulescu, Riccardo Fanti and Samuele Segoni

Water 2025, 17(14), 2041; https://doi.org/10.3390/w17142041 - 8 Jul 2025

Viewed by 44

Abstract

Flood susceptibility modeling (FSM) plays a key role in advancing proactive disaster risk reduction and spatial planning. This research developed FSM for the Buzău River catchment in Romania—a region historically vulnerable to recurrent flood events—using four state-of-the-art ensemble boosting algorithms: AdaBoost, CatBoost, LightGBM, [...] Read more.

Flood susceptibility modeling (FSM) plays a key role in advancing proactive disaster risk reduction and spatial planning. This research developed FSM for the Buzău River catchment in Romania—a region historically vulnerable to recurrent flood events—using four state-of-the-art ensemble boosting algorithms: AdaBoost, CatBoost, LightGBM, and XGBoost. Initially, a comprehensive set of 13 flood conditioning factors was assessed, which was subsequently narrowed down to 9 essential factors through multi-tier feature selection strategies. Analysis of performance via receiver operating characteristic (ROC) andprecision–recall curves showed only marginal differences between the models; however, CatBoost excelled with an area under the ROC curve (AUC) of 0.972 and an average precision (AP) of 0.971, with XGBoost following closely behind. The SHAP (SHapley Additive exPlanations) analysis of the CatBoost model indicated that the Slope, Distance from Rivers, Topographic Wetness Index (TWI), and Land Use/Land Cover (LULC) are the key contributing factors. The novelty of this research is found in its comparative analysis of AdaBoost alongside three gradient boosting algorithms—CatBoost, LightGBM, and XGBoost—while utilizing explainable artificial intelligence (XAI) and a multi-tier feature selection strategy to create FSM that are precise and comprehensible. These strategies deliver robust tools for managing flood risks and reinforce the viability of data-driven modeling in the various catchments of Europe. Full article

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

► Show Figures

Figure 1

Journal Menu

Journal Browser

Water, Volume 17, Issue 14 (July-2 2025) – 17 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI