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Water, Volume 17, Issue 15 (August-1 2025) – 38 articles

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19 pages, 1710 KiB  
Article
Application of Empirical Mode Decomposition to Land Surface Temperature Projection Under a Changing Climate
by Che-Wei Chang and Wen-Cheng Huang
Water 2025, 17(15), 2204; https://doi.org/10.3390/w17152204 - 23 Jul 2025
Abstract
This study takes the daily temperature series of Taipei City as an example and proposes a data projection method based on Empirical Mode Decomposition (EMD), which effectively resolves the challenge of modeling non-stationary sequences. According to the daily mean temperature records from 1971 [...] Read more.
This study takes the daily temperature series of Taipei City as an example and proposes a data projection method based on Empirical Mode Decomposition (EMD), which effectively resolves the challenge of modeling non-stationary sequences. According to the daily mean temperature records from 1971 to 2023, Taipei has experienced an average warming rate of 0.02 °C per year. After applying EMD, the data were decomposed into 12 intrinsic mode functions (IMFs) and one residual trend. Among them, IMF5, with a period of 352 days (approximately one year), contributes 78% of the total energy, representing the dominant climatic cycle component. In this study, daily temperatures were categorized into five thermal levels: Cold (<12 °C), Cool (12–18 °C), Moderate (18–27 °C), Warm (27–32 °C), and Hot (>32 °C). In addition, using a 5-year moving process based on the annual EMD results, the IMFs and residuals were recombined to generate 390,625 synthetic sequences per year. Results show that the monthly mean temperatures of each year’s simulations closely match the observations, capturing the non-stationary characteristics of temperature variations. The overall classification accuracy of simulated versus observed daily temperature categories ranges from 60% to 71%, with an average of 65.1%. In summary, the EMD combined with the 5-year moving process developed in this study demonstrates a helpful data projection approach with effective reconstruction of periodic structures and stable simulation accuracy. It offers practical value for reconstructing urban climate variability, conducting risk assessments, and analyzing long-term warming trends. Moreover, it serves as a vital tool for modeling non-stationary climate data and supporting future projections. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
18 pages, 1502 KiB  
Article
Evaluation of Wake Structure Induced by Helical Hydrokinetic Turbine
by Erkan Alkan, Mehmet Ishak Yuce and Gökmen Öztürkmen
Water 2025, 17(15), 2203; https://doi.org/10.3390/w17152203 - 23 Jul 2025
Abstract
This study investigates the downstream wake characteristics of a helical hydrokinetic turbine through combined experimental and numerical analyses. A four-bladed helical turbine with a 20 cm rotor diameter and blockage ratio of 53.57% was tested in an open water channel under a flow [...] Read more.
This study investigates the downstream wake characteristics of a helical hydrokinetic turbine through combined experimental and numerical analyses. A four-bladed helical turbine with a 20 cm rotor diameter and blockage ratio of 53.57% was tested in an open water channel under a flow rate of 180 m3/h, corresponding to a Reynolds number of approximately 90 × 103. Velocity measurements were collected at 13 downstream cross-sections using an Acoustic Doppler Velocimeter, with each point sampled repeatedly. Standard error analysis was applied to quantify measurement uncertainty. Complementary numerical simulations were conducted in ANSYS Fluent using a steady-state k-ω Shear Stress Transport (SST) turbulence model, with a mesh of 4.7 million elements and mesh independence confirmed. Velocity deficit and turbulence intensity were employed as primary parameters to characterize the wake structure, while the analysis also focused on the recovery of cross-sectional velocity profiles to validate the extent of wake influence. Experimental results revealed a maximum velocity deficit of over 40% in the near-wake region, which gradually decreased with downstream distance, while turbulence intensity exceeded 50% near the rotor and dropped below 10% beyond 4 m. In comparison, numerical findings showed a similar trend but with lower peak velocity deficits of 16.6%. The root mean square error (RMSE) and mean absolute error (MAE) between experimental and numerical mean velocity profiles were calculated as 0.04486 and 0.03241, respectively, demonstrating reasonable agreement between the datasets. Extended simulations up to 30 m indicated that flow profiles began to resemble ambient conditions around 18–20 m. The findings highlight the importance of accurately identifying the downstream distance at which the wake effect fully dissipates, as this is crucial for determining appropriate inter-turbine spacing. The study also discusses potential sources of discrepancies between experimental and numerical results, as well as the limitations of the modeling approach. Full article
(This article belongs to the Special Issue Optimization-Simulation Modeling of Sustainable Water Resource)
28 pages, 23588 KiB  
Article
An Extensive Italian Database of River Embankment Breaches and Damages
by Michela Marchi, Ilaria Bertolini, Laura Tonni, Luca Morreale, Andrea Colombo, Tommaso Simonelli and Guido Gottardi
Water 2025, 17(15), 2202; https://doi.org/10.3390/w17152202 - 23 Jul 2025
Abstract
River embankments are critical flood defense structures, stretching for thousands of kilometers across alluvial plains. They often originated as natural levees resulting from overbank flows and were later enlarged using locally available soils yet rarely designed according to modern engineering standards. Substantially under-characterized, [...] Read more.
River embankments are critical flood defense structures, stretching for thousands of kilometers across alluvial plains. They often originated as natural levees resulting from overbank flows and were later enlarged using locally available soils yet rarely designed according to modern engineering standards. Substantially under-characterized, their performance to extreme events provides an invaluable opportunity to highlight their vulnerability and then to improve monitoring, management, and reinforcement strategies. In May 2023, two extreme meteorological events hit the Emilia-Romagna region in rapid succession, causing numerous breaches along river embankments and therefore widespread flooding of cities and territories. These were followed by two additional intense events in September and October 2024, marking an unprecedented frequency of extreme precipitation episodes in the history of the region. This study presents the methodology adopted to create a regional database of 66 major breaches and damages that occurred during May 2023 extensive floods. The database integrates multi-source information, including field surveys; remote sensing data; and eyewitness documentation collected before, during, and after the events. Preliminary interpretation enabled the identification of the most likely failure mechanisms—primarily external erosion, internal erosion, and slope instability—often acting in combination. The database, unprecedented in Italy and with few parallels worldwide, also supported a statistical analysis of breach widths in relation to failure mechanisms, crucial for improving flood hazard models, which often rely on generalized assumptions about breach development. By offering insights into the real-scale behavior of a regional river defense system, the dataset provides an important tool to support river embankments risk assessment and future resilience strategies. Full article
(This article belongs to the Special Issue Recent Advances in Flood Risk Assessment and Management)
16 pages, 4204 KiB  
Article
Assessment of the Source and Dynamics of Water Inrush Based on Hydrochemical Mixing Model in Zhaxikang Mining Area, Tibet, China
by Hongyu Gu, Yujie Liu, Huizhong Liu, Xinyu Cen, Jinxian Zhong, Dewei Wang and Lei Yi
Water 2025, 17(15), 2201; https://doi.org/10.3390/w17152201 - 23 Jul 2025
Abstract
Water source identification and dynamic assessment are critical for mining safety, particularly in mines governed by complex geological structures. The hydrochemical mixing model demonstrates a natural advantage for early warning of water intrusion compared to geophysical monitoring techniques. This study discusses core issues [...] Read more.
Water source identification and dynamic assessment are critical for mining safety, particularly in mines governed by complex geological structures. The hydrochemical mixing model demonstrates a natural advantage for early warning of water intrusion compared to geophysical monitoring techniques. This study discusses core issues related to the mixing model, including the conceptual framework, selection of end-members, and choice of tracers, and formulates principles for general applicability. In this study, three sources were identified using the conceptual model and hydrochemical analysis: water in F7 (main fault), shallow fracture water, and river water. A correlation analysis and variability analysis were applied to determine the tracers, and the 18O, D, Cl, B, and Li were determined. The end-members of the three sources are time-dependent in July and September, especially the shallow fracture water’s end-members. The dynamics of the mixing ratios of the three sources suggest that river water contributes only to the inrush (1–4%), with this being especially low in September, as the increasing hydraulic gradient from south to north prevents recharge. The water in F7 accounts for at least 70% of the inrush water. Shallow fracture water accounts for the rest and increases slightly in September as the precipitation increases in mining-disturbed areas. Finally, this work makes the later water control work more targeted. Full article
(This article belongs to the Section Hydrogeology)
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15 pages, 1787 KiB  
Article
Flow Regime Impacts on Chemical Pollution in the Water and Sediments of the Moopetsi River and Human Health Risk in South Africa
by Abraham Addo-Bediako, Thato Matita and Wilmien Luus-Powell
Water 2025, 17(15), 2200; https://doi.org/10.3390/w17152200 - 23 Jul 2025
Abstract
Many effluents from human activities discharged into freshwater ecosystems cause chemical pollution. Chemical pollution in rivers is a serious threat to freshwater ecosystems due to the associated potential human health risks. This study determined the extent of chemical pollution, identified potential sources of [...] Read more.
Many effluents from human activities discharged into freshwater ecosystems cause chemical pollution. Chemical pollution in rivers is a serious threat to freshwater ecosystems due to the associated potential human health risks. This study determined the extent of chemical pollution, identified potential sources of pollution and assessed human health risk in the Moopetsi River, an intermittent river in the Limpopo Province of South Africa. Chemical analyses were conducted on water and sediment samples collected during high-flow, low-flow and intermittent-flow regimes. The findings showed seasonal variations in the chemical pollution levels in the sediments and the highest contamination was measured during intermittent flow. The enrichment factor and geoaccumulation index values identified chromium and nickel as major contributors to sediment contamination. The mean arsenic, chromium and nickel levels exceeded the established guideline values. An evaluation of human health risk was conducted using ingestion and dermal absorption pathways. The results showed that ingestion has greater non-carcinogenic and carcinogenic risks than dermal exposure, especially for children during intermittent flow. The elements of great concern for non-carcinogenic risk were chromium, manganese and nickel and for carcinogenic risk, they were arsenic, chromium, nickel and lead. The outcome of this study is useful for waste management and conservation to reduce environmental degradation and human health risk. Full article
(This article belongs to the Special Issue Advances in Metal Removal and Recovery from Water)
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35 pages, 7193 KiB  
Article
Macrozoobenthos Response to Sediment Contamination near the S/s Stuttgart Wreck: A Biological and Chemical Assessment in the Gulf of Gdańsk, Southern Baltic Sea
by Anna Tarała, Diana Dziaduch, Katarzyna Galer-Tatarowicz, Aleksandra Bojke, Maria Kubacka and Marcin Kalarus
Water 2025, 17(15), 2199; https://doi.org/10.3390/w17152199 - 23 Jul 2025
Abstract
This study provides an up-to-date assessment of the environmental status in the area of the S/s Stuttgart wreck in the southern Baltic Sea, focusing on macrozoobenthos, sediment chemistry, and contamination in Mytilus trossulus soft tissues. Comparative analyses from 2016 and 2023 revealed increased [...] Read more.
This study provides an up-to-date assessment of the environmental status in the area of the S/s Stuttgart wreck in the southern Baltic Sea, focusing on macrozoobenthos, sediment chemistry, and contamination in Mytilus trossulus soft tissues. Comparative analyses from 2016 and 2023 revealed increased species richness and distinct benthic assemblages, shaped primarily by depth and distance from the wreck. Among macrozoobenthos, there dominated opportunistic species, characterized by a high degree of resistance to the unfavorable state of the environment, suggesting adaptation to local conditions. Elevated concentrations of heavy metals were detected in sediments, with maximum values of Cd—0.85 mg·kg−1, Cu—34 mg·kg−1, Zn—119 mg·kg−1, and Ni—32.3 mg·kg−1. However, no significant correlations between sediment contamination and macrozoobenthos composition were found. In Mytilus trossulus, contaminant levels were mostly within regulatory limits; however, mercury concentrations reached 0.069 mg·kg−1 wet weight near the wreck and 0.493 mg·kg−1 at the reference station, both exceeding the threshold defined in national legislation (0.02 mg·kg−1) (Journal of Laws of 2021, item 568). Condition indices for Macoma balthica were lower in the wreck area, suggesting sublethal stress. Ecotoxicological tests showed no acute toxicity in most sediment samples, emphasizing the complexity of pollutant effects. The data presented here not only enrich the existing literature on marine pollution but also contribute to the development of more effective environmental protection strategies for marine ecosystems under international protection. Full article
(This article belongs to the Special Issue Emerging Contaminants in Natural and Engineered Water Environments: Environmental Behavior, Ecological Effects and Control Strategies, 2nd Edition)
14 pages, 4489 KiB  
Article
Modifying Design Standards: The 2023 Extreme Flood’s Impact on Design Discharges in Slovenia
by Mojca Šraj and Nejc Bezak
Water 2025, 17(15), 2198; https://doi.org/10.3390/w17152198 - 23 Jul 2025
Abstract
An extreme flood event occurred in Slovenia in August 2023. This study evaluated the influence of this extreme flood on the design discharges in Slovenia. This evaluation was based on flood frequency analysis for the data from 33 gauging stations. Analyses were conducted [...] Read more.
An extreme flood event occurred in Slovenia in August 2023. This study evaluated the influence of this extreme flood on the design discharges in Slovenia. This evaluation was based on flood frequency analysis for the data from 33 gauging stations. Analyses were conducted with and without the 2023 peak discharge, i.e., for the periods 1961–2022 and 1961–2023, using eight different theoretical distribution functions. In addition, specific discharge values for the 2023 flood event were analyzed and compared with regional envelope curves for Europe. The findings of the study indicate that the impact of a single flood event on the design discharge values can be substantial. Moreover, an analysis of the specific discharges resulting from the 2023 flood event in Slovenia reveals that the values for all gauging stations considered are below the regional envelopes. Concurrently, the analysis indicates that a flood event larger than the 2023 event may occur in the future. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: The Impact of Climate Change on Water Resources)
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20 pages, 2336 KiB  
Article
Microbial DNA-Based Monitoring of Underground Crude Oil Storage Bases Using Water-Sealed Rock-Cavern Tanks
by Ayae Goto, Shunichi Watanabe, Katsumasa Uruma, Yuki Momoi, Takuji Oomukai and Hajime Kobayashi
Water 2025, 17(15), 2197; https://doi.org/10.3390/w17152197 - 23 Jul 2025
Abstract
Strategic petroleum reserves are critical for energy security. In Japan, 0.5 million kiloliters of crude oil (12% of the state-owned reserves) is stored using underground rock-cavern tanks, which comprise unlined horizontal tunnels bored into bedrock. Crude oil is held within the tank by [...] Read more.
Strategic petroleum reserves are critical for energy security. In Japan, 0.5 million kiloliters of crude oil (12% of the state-owned reserves) is stored using underground rock-cavern tanks, which comprise unlined horizontal tunnels bored into bedrock. Crude oil is held within the tank by water inside the tank, the pressure of which is kept higher than that of the crude oil by natural groundwater and irrigation water. This study applied microbial DNA-based monitoring to assess the water environments in and around national petroleum-stockpiling bases (the Kuji, Kikuma, and Kushikino bases) using the rock-cavern tanks. Forty-five water samples were collected from the rock-cavern tanks, water-supply tunnels, and observation wells. Principal-component analysis and hierarchical clustering indicated that microbial profiles of the water samples reflect the local environments of their origins. Particularly, the microbial profiles of water inside the rock-cavern tanks were distinct from other samples, revealing biological conditions and hence environmental characteristics within the tanks. Moreover, the clustering analysis indicated distinct features of water samples that have not been detected by other monitoring methods. Thus, microbial DNA-based monitoring provides valuable information on the in situ environments of rock-cavern tanks and can serve as an extremely sensitive measurement to monitor the underground oil storage. Full article
(This article belongs to the Section Hydrogeology)
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15 pages, 2209 KiB  
Article
Exploration of Phosphorus Release Characteristics in Sediments from the Plains River Network: Vertical Distribution and the Response of Phosphorus and Microorganisms
by Xiaoshuang Dong, Haojie Chen, Yongsheng Chang, Xixi Yang, Haoran Yang and Wei Huang
Water 2025, 17(15), 2196; https://doi.org/10.3390/w17152196 - 23 Jul 2025
Abstract
Plains River networks are important natural ecosystems that play a vital role in storing, draining, conserving, and purifying water. This study selected the river network in the northern plain of Jiaxing as the research area. Samples were collected in October 2023. Sediments were [...] Read more.
Plains River networks are important natural ecosystems that play a vital role in storing, draining, conserving, and purifying water. This study selected the river network in the northern plain of Jiaxing as the research area. Samples were collected in October 2023. Sediments were collected using a sampler and divided into five layers according to the collection depth, namely the surface layer (5 cm), the second layer (15 cm), the third layer (25 cm), the fourth layer (35 cm), and the bottom layer (45 cm). This study analyzed the vertical distribution of each form of phosphorus, the vertical distribution of the microbial community, and the response between the two in the sediments of this plain river network. The results showed high sediment TP concentrations (633.9–2534.7 mg/kg) in this plain river network. The vertical distribution trend of Fe-P was almost the same as that of TP and had the highest concentration (134.9–1860.1 mg/kg). Ca-P is the second highest phosphorus content, which is also an inert phosphorus component, as well as Al-P, and both exhibit a relatively low percentage of surface layers. Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria showed heterogeneity in the vertical distribution of sediments. The river network sediments in the Plains River have a high potential for phosphorus release, with most sites acting as phosphorus “sources”. The sediments in the second of these layers show a strong tendency to release phosphorus. Bottom sediments have a low capacity to both adsorb and release phosphorus. The findings of this study will provide a theoretical foundation for the prevention and management of river networks in this plain. Full article
(This article belongs to the Special Issue Sediment Pollution Process and Microbial Responses in Aquatic Environment)
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36 pages, 10270 KiB  
Article
Spatiotemporal Analysis of Water Quality and Optical Changes Induced by Contaminants in Lake Chinchaycocha Using Sentinel-2 and in Situ Data
by Emerson Espinoza, Analy Baltodano and Norvin Requena
Water 2025, 17(15), 2195; https://doi.org/10.3390/w17152195 - 23 Jul 2025
Abstract
Lake Chinchaycocha, Peru’s second-largest high-altitude lake and a Ramsar-designated wetland of international importance, is increasingly threatened by anthropogenic pollution and hydroclimatic shifts. This study integrates Sentinel-2 multispectral imagery with in situ water quality data from Peru’s National Water Observatory to assess spatiotemporal dynamics [...] Read more.
Lake Chinchaycocha, Peru’s second-largest high-altitude lake and a Ramsar-designated wetland of international importance, is increasingly threatened by anthropogenic pollution and hydroclimatic shifts. This study integrates Sentinel-2 multispectral imagery with in situ water quality data from Peru’s National Water Observatory to assess spatiotemporal dynamics in 31 physicochemical parameters between 2018 and 2024. We evaluated 40 empirical algorithms developed globally for Sentinel-2 and tested their transferability to this ultraoligotrophic Andean system. The results revealed limited predictive accuracy, underscoring the need for localized calibration. Subsequently, we developed and validated site-specific models for ammoniacal nitrogen, electrical conductivity, major ions, and trace metals, achieving high predictive performance during the rainy season (R2 up to 0.95). Notably, the study identifies consistent seasonal correlations—such as between total copper and ammoniacal nitrogen—and strong spectral responses in Band 1, linked to runoff dynamics. These findings highlight the potential of combining public monitoring data with remote sensing to enable scalable, cost-effective assessment of water quality in optically complex, high-Andean lakes. The study provides a replicable framework for integrating national datasets into operational monitoring and environmental policy. Full article
(This article belongs to the Special Issue Water Pollution Monitoring, Modelling and Management)
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21 pages, 3469 KiB  
Article
Monitoring Phosphorus During High Flows: Critical for Implementing Surrogacy Models
by Elliot S. Anderson, Keith E. Schilling and Larry J. Weber
Water 2025, 17(15), 2194; https://doi.org/10.3390/w17152194 - 23 Jul 2025
Abstract
Phosphorus (P) is a problematic waterborne pollutant, and considerable efforts have been taken to monitor its presence and transport in locales struggling with eutrophication. Most historical P datasets consist of intermittent grab samples, necessitating the construction of surrogacy models to explore P at [...] Read more.
Phosphorus (P) is a problematic waterborne pollutant, and considerable efforts have been taken to monitor its presence and transport in locales struggling with eutrophication. Most historical P datasets consist of intermittent grab samples, necessitating the construction of surrogacy models to explore P at high resolutions. In Iowa, models using historical data to relate turbidity to particulate P (PartP) have successfully been created. However, it is unknown how comprehensively historical datasets reflect Iowa’s hydrologic conditions and how well these models perform during flows not well represented within the existing data. In this study, we analyzed historical P datasets from 16 major Iowa rivers to determine how well they captured the rivers’ full range of streamflow conditions. While these datasets contained sufficient samples during low and average flows, they typically under-sampled high flows—containing few values above the 85–95th percentiles. Therefore, we collected new data in each river during wet conditions, with ~300 samples taken from 2021 to 2024. These new sampling results largely aligned with the existing surrogacy models and slightly improved model performance, suggesting that utilizing turbidity to predict PartP is appropriate in nearly all streamflow conditions. These findings may prove consequential for robustly modeling PartP due to its dynamic nature and disproportionately high transport during wet weather events. Full article
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23 pages, 2274 KiB  
Review
Nature-Based Solutions for Water Management in Europe: What Works, What Does Not, and What’s Next?
by Eleonora Santos
Water 2025, 17(15), 2193; https://doi.org/10.3390/w17152193 - 23 Jul 2025
Abstract
Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European [...] Read more.
Nature-based solutions (NbS) are increasingly recognized as strategic alternatives and complements to grey infrastructure for addressing water-related challenges in the context of climate change, urbanization, and biodiversity decline. This article presents a critical, theory-informed review of the state of NbS implementation in European water management, drawing on a structured synthesis of empirical evidence from regional case studies and policy frameworks. The analysis found that while NbS are effective in reducing surface runoff, mitigating floods, and improving water quality under low- to moderate-intensity events, their performance remains uncertain under extreme climate scenarios. Key gaps identified include the lack of long-term monitoring data, limited assessment of NbS under future climate conditions, and weak integration into mainstream planning and financing systems. Existing evaluation frameworks are critiqued for treating NbS as static interventions, overlooking their ecological dynamics and temporal variability. In response, a dynamic, climate-resilient assessment model is proposed—grounded in systems thinking, backcasting, and participatory scenario planning—to evaluate NbS adaptively. Emerging innovations, such as hybrid green–grey infrastructure, adaptive governance models, and novel financing mechanisms, are highlighted as key enablers for scaling NbS. The article contributes to the scientific literature by bridging theoretical and empirical insights, offering region-specific findings and recommendations based on a comparative analysis across diverse European contexts. These findings provide conceptual and methodological tools to better design, evaluate, and scale NbS for transformative, equitable, and climate-resilient water governance. Full article
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18 pages, 6088 KiB  
Article
Hydrochemical Characteristics and Evolution of Underground Brine During Mining Process in Luobei Mining Area of Lop Nur, Northwestern China
by Xu Han, Yufei Deng, Hao Geng, Liangliang Zhao, Ji Zhang, Lingfen Wang, Lei Wang, Xiaohong Sun, Zihao Zhou, Meng Wang and Zhongjian Liu
Water 2025, 17(15), 2192; https://doi.org/10.3390/w17152192 - 23 Jul 2025
Abstract
Underground brine as a liquid mineral resource available for development and utilization has attracted widespread attention. However, how the mining process affects the hydrochemical characteristics and evolution of underground brine has yet to be fully understood. Herein, 207 underground brine samples were collected [...] Read more.
Underground brine as a liquid mineral resource available for development and utilization has attracted widespread attention. However, how the mining process affects the hydrochemical characteristics and evolution of underground brine has yet to be fully understood. Herein, 207 underground brine samples were collected from the Luobei mining area of the Lop Nur region during pre-exploitation (2006), exploitation (2019), and late exploitation (2023) to explore the dynamic change characteristics and evolution mechanisms of the underground brine hydrochemistry using the combination of statistical analysis, spatial interpolation, correlation analysis, and ion ratio analysis. The results indicated that Na+ and Cl− were the dominant ionic components in the brine, and their concentrations remained relatively stable throughout the mining process. However, the content of Mg2+ increased gradually during the mining process (increased by 45.08% in the middle stage and 3.09% in the later stage). The elevation in Mg2+ concentration during the mining process could be attributed to the dissolution of Mg-bearing minerals, reverse cation exchange, and mixed recharge. This research furnishes a scientific foundation for a more in-depth comprehension of the disturbance mechanism of brine-mining activities on the groundwater chemical system in the mining area and for the sustainable exploitation of brine resources. Full article
(This article belongs to the Topic The Hydrosphere in Crisis: Human Impact, Climate Change, and Pathways to Resilience, 2nd Edition)
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25 pages, 1882 KiB  
Article
An Assessment of Collector-Drainage Water and Groundwater—An Application of CCME WQI Model
by Nilufar Rajabova, Vafabay Sherimbetov, Rehan Sadiq and Alaa Farouk Aboukila
Water 2025, 17(15), 2191; https://doi.org/10.3390/w17152191 - 23 Jul 2025
Abstract
According to Victor Ernest Shelford’s ‘Law of Tolerance,’ organisms within ecosystems thrive optimally when environmental conditions are favorable. Applying this principle to ecosystems and agro-ecosystems facing water scarcity or environmental challenges can significantly enhance their productivity. In these ecosystems, phytocenosis adjusts its conditions [...] Read more.
According to Victor Ernest Shelford’s ‘Law of Tolerance,’ organisms within ecosystems thrive optimally when environmental conditions are favorable. Applying this principle to ecosystems and agro-ecosystems facing water scarcity or environmental challenges can significantly enhance their productivity. In these ecosystems, phytocenosis adjusts its conditions by utilizing water with varying salinity levels. Moreover, establishing optimal drinking water conditions for human populations within an ecosystem can help mitigate future negative succession processes. The purpose of this study is to evaluate the quality of two distinct water sources in the Amudarya district of the Republic of Karakalpakstan, Uzbekistan: collector-drainage water and groundwater at depths of 10 to 25 m. This research is highly relevant in the context of climate change, as improper management of water salinity, particularly in collector-drainage water, may exacerbate soil salinization and degrade drinking water quality. The primary methodology of this study is as follows: The Food and Agriculture Organization of the United Nations (FAO) standard for collector-drainage water is applied, and the water quality index is assessed using the CCME WQI model. The Canadian Council of Ministers of the Environment (CCME) model is adapted to assess groundwater quality using Uzbekistan’s national drinking water quality standards. The results of two years of collected data, i.e., 2021 and 2023, show that the water quality index of collector-drainage water indicates that it has limited potential for use as secondary water for the irrigation of sensitive crops and has been classified as ‘Poor’. As a result, salinity increased by 8.33% by 2023. In contrast, groundwater quality was rated as ‘Fair’ in 2021, showing a slight deterioration by 2023. Moreover, a comparative analysis of CCME WQI values for collector-drainage and groundwater in the region, in conjunction with findings from Ethiopia, India, Iraq, and Turkey, indicates a consistent decline in water quality, primarily due to agriculture and various other anthropogenic pollution sources, underscoring the critical need for sustainable water resource management. This study highlights the need to use organic fertilizers in agriculture to protect drinking water quality, improve crop yields, and promote soil health, while reducing reliance on chemical inputs. Furthermore, adopting WQI models under changing climatic conditions can improve agricultural productivity, enhance groundwater quality, and provide better environmental monitoring systems. Full article
(This article belongs to the Topic Hydrology and Water Resources in Agriculture and Ecology—2nd Edition)
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15 pages, 12546 KiB  
Article
Retrieval of Chlorophyll-a Concentration in Nanyi Lake Using the AutoGluon Framework
by Weibin Gu, Ji Liang, Lian Yang, Shanshan Guo and Ruixin Jia
Water 2025, 17(15), 2190; https://doi.org/10.3390/w17152190 - 23 Jul 2025
Abstract
The chlorophyll-a (Chl-a) concentration in lakes is a crucial parameter for monitoring water quality and assessing phytoplankton abundance. However, accurately retrieving Chl-a concentrations remains a significant challenge in remote sensing. To address the limitations of existing methods in terms of modeling efficiency and [...] Read more.
The chlorophyll-a (Chl-a) concentration in lakes is a crucial parameter for monitoring water quality and assessing phytoplankton abundance. However, accurately retrieving Chl-a concentrations remains a significant challenge in remote sensing. To address the limitations of existing methods in terms of modeling efficiency and adaptability, this study focuses on Lake Nanyi in Anhui Province. By integrating Sentinel-2 satellite imagery with in situ water quality measurements and employing the AutoML framework AutoGluon, a Chl-a inversion model based on narrow-band spectral features is developed. Feature selection and model ensembling identify bands B6 (740 nm) and B7 (783 nm) as the optimal combination, which are then applied to multi-temporal imagery from October 2022 to generate spatial mean distributions of Chl-a in Lake Nanyi. The results demonstrate that the AutoGluon framework significantly outperforms traditional methods in both model accuracy (R2: 0.94, RMSE: 1.67 μg/L) and development efficiency. The retrieval results reveal spatial heterogeneity in Chl-a concentration, with higher concentrations observed in the southern part of the western lake and the western side of the eastern lake, while the central lake area exhibits relatively lower concentrations, ranging from 3.66 to 21.39 μg/L. This study presents an efficient and reliable approach for lake ecological monitoring and underscores the potential of AutoML in water color remote sensing applications. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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25 pages, 6316 KiB  
Article
Integration of Remote Sensing and Machine Learning Approaches for Operational Flood Monitoring Along the Coastlines of Bangladesh Under Extreme Weather Events
by Shampa, Nusaiba Nueri Nasir, Mushrufa Mushreen Winey, Sujoy Dey, S. M. Tasin Zahid, Zarin Tasnim, A. K. M. Saiful Islam, Mohammad Asad Hussain, Md. Parvez Hossain and Hussain Muhammad Muktadir
Water 2025, 17(15), 2189; https://doi.org/10.3390/w17152189 - 23 Jul 2025
Abstract
The Ganges–Brahmaputra–Meghna (GBM) delta, characterized by complex topography and hydrological conditions, is highly susceptible to recurrent flooding, particularly in its coastal regions where tidal dynamics hinder floodwater discharge. This study integrates Synthetic Aperture Radar (SAR) imagery with machine learning (ML) techniques to assess [...] Read more.
The Ganges–Brahmaputra–Meghna (GBM) delta, characterized by complex topography and hydrological conditions, is highly susceptible to recurrent flooding, particularly in its coastal regions where tidal dynamics hinder floodwater discharge. This study integrates Synthetic Aperture Radar (SAR) imagery with machine learning (ML) techniques to assess near real-time flood inundation patterns associated with extreme weather events, including recent cyclones between 2017 to 2024 (namely, Mora, Titli, Fani, Amphan, Yaas, Sitrang, Midhili, and Remal) as well as intense monsoonal rainfall during the same period, across a large spatial scale, to support disaster risk management efforts. Three machine learning algorithms, namely, random forest (RF), support vector machine (SVM), and K-nearest neighbors (KNN), were applied to flood extent data derived from SAR imagery to enhance flood detection accuracy. Among these, the SVM algorithm demonstrated the highest classification accuracy (75%) and exhibited superior robustness in delineating flood-affected areas. The analysis reveals that both cyclone intensity and rainfall magnitude significantly influence flood extent, with the western coastal zone (e.g., Morrelganj and Kaliganj) being most consistently affected. The peak inundation extent was observed during the 2023 monsoon (10,333 sq. km), while interannual variability in rainfall intensity directly influenced the spatial extent of flood-affected zones. In parallel, eight major cyclones, including Amphan (2020) and Remal (2024), triggered substantial flooding, with the most severe inundation recorded during Cyclone Remal with an area of 9243 sq. km. Morrelganj and Chakaria were consistently identified as flood hotspots during both monsoonal and cyclonic events. Comparative analysis indicates that cyclones result in larger areas with low-level inundation (19,085 sq. km) compared to monsoons (13,829 sq. km). However, monsoon events result in a larger area impacted by frequent inundation, underscoring the critical role of rainfall intensity. These findings underscore the utility of SAR-ML integration in operational flood monitoring and highlight the urgent need for localized, event-specific flood risk management strategies to enhance flood resilience in the GBM delta. Full article
(This article belongs to the Special Issue Flood Inundation Modeling and Mapping: Application of Hydrodynamic Models, Remote Sensing and Machine Learning Tools)
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15 pages, 4484 KiB  
Article
Effects of Lanthanum-Modified Bentonite on Antibiotic Resistance Genes and Bacterial Communities in Tetracycline-Contaminated Water Environments
by Wanzhong Wang, Sijia Liang, Shuai Zhang, Daming Wei, Xueting Xu and Peng Zhang
Water 2025, 17(15), 2188; https://doi.org/10.3390/w17152188 - 22 Jul 2025
Abstract
Water environments and sediments are important reservoirs for antibiotic resistance genes (ARGs). Under the pressure of antibiotics, ARGs can transform between microorganisms. Lanthanum-modified bentonite (LMB) is a phosphorus passivation material with good prospects in water environment restoration. After a treatment with LMB, the [...] Read more.
Water environments and sediments are important reservoirs for antibiotic resistance genes (ARGs). Under the pressure of antibiotics, ARGs can transform between microorganisms. Lanthanum-modified bentonite (LMB) is a phosphorus passivation material with good prospects in water environment restoration. After a treatment with LMB, the phosphorus forms in water and sediments will change, which may have an impact on microorganisms and the transmission of ARGs. To investigate the effects of LMB and antibiotics on ARGs and bacterial communities in sediment and aquatic environments, LMB and tetracycline (Tet) were added individually and in combination to mixed samples of sediment and water. The results showed that the addition of either LMB or Tet increased the abundance of intI1 and tetA genes in both the sediment and water, with the Tet addition increasing ARGs to more than 1.5 times the abundance in the control group. However, when LMB and Tet were present simultaneously, the abundance of ARGs showed no significant difference compared to the control group. Tet and LMB also affected the bacterial community structure and function in the samples and had different effects on the sediment and water. A correlation analysis revealed that the potential host bacteria of the intI1 and tetA genes were unclassified_Geobacteraceae, Geothrix, Flavobacterium, Anaeromyxobacter, and Geothermobacter. These findings indicate that Tet or LMB may increase the dissemination of ARGs by affecting microbial communities, while LMB may reduce the impact of Tet through adsorption, providing a reference for the safety of the LMB application in the environment and its other effects (alleviating antibiotic pollution) in addition to phosphorus removal. Full article
(This article belongs to the Section Water Quality and Contamination)
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16 pages, 2683 KiB  
Article
The Effect of Herbaceous and Shrub Combination with Different Root Configurations on Soil Saturated Hydraulic Conductivity
by Zeyu Zhang, Chenguang Wang, Bo Ma, Zhanbin Li, Jianye Ma and Beilei Liu
Water 2025, 17(15), 2187; https://doi.org/10.3390/w17152187 - 22 Jul 2025
Abstract
Information on the effects of differences in root and soil properties on Saturated hydraulic conductivity (Ks) is crucial for estimating rainfall infiltration and evaluating sustainable ecological development. This study selected typical grass shrub composite plots widely distributed in hilly and [...] Read more.
Information on the effects of differences in root and soil properties on Saturated hydraulic conductivity (Ks) is crucial for estimating rainfall infiltration and evaluating sustainable ecological development. This study selected typical grass shrub composite plots widely distributed in hilly and gully areas of the Loess Plateau: Caragana korshinskii, Caragana korshinskii and Agropyron cristatum (fibrous root), and Caragana korshinskii and Artemisia gmelinii (taproot). Samples were collected at different distances from the base of the shrub (0 cm, 50 cm), with a sampling depth of 0–30 cm. The constant head method is used to measure the Ks. The Ks decreased with increasing soil depth. Due to the influence of shrub growth, there was significant spatial heterogeneity in the distribution of Ks at different positions from the base of the shrub. Compared to the sample location situated 50 cm from the base of the shrub, it was observed that in a single shrub plot, the Ks at the base were higher, while in a grass shrub composite plot, the Ks at the base were lower. Root length density, >0.25 mm aggregates, and organic matter were the main driving factors affecting Ks. The empirical equation established by using principal component analysis to reduce the dimensions of these three factors and calculate the comprehensive score was more accurate than the empirical equation established by previous researchers, who considered only root or soil properties. Root length density and organic matter had significant indirect effects on Ks, reaching 52.87% and 78.19% of the direct effects, respectively. Overall, the composite plot of taproot herbaceous and shrub (Caragana korshinskii and Artemisia gmelinii) had the highest Ks, which was 82.98 cm·d−1. The ability of taproot herbaceous plants to improve Ks was higher than that of fibrous root herbaceous plants. The research results have certain significance in revealing the influence mechanism of the grass shrub composite on Ks. Full article
(This article belongs to the Special Issue Soil Erosion and Soil and Water Conservation)
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14 pages, 4599 KiB  
Article
Predictive Flood Uncertainty Associated with the Overtopping Rates of Vertical Seawall on Coral Reef Topography
by Hongqian Zhang, Bin Lu, Yumei Geng and Ye Liu
Water 2025, 17(15), 2186; https://doi.org/10.3390/w17152186 - 22 Jul 2025
Abstract
Accurate prediction of wave overtopping rates is essential for flood risk assessment along coral reef coastlines. This study quantifies the uncertainty sources affecting overtopping rates for vertical seawalls on reef flats, using ensemble simulations with a validated non-hydrostatic SWASH model. By generating extensive [...] Read more.
Accurate prediction of wave overtopping rates is essential for flood risk assessment along coral reef coastlines. This study quantifies the uncertainty sources affecting overtopping rates for vertical seawalls on reef flats, using ensemble simulations with a validated non-hydrostatic SWASH model. By generating extensive random wave sequences, we identify spectral resolution, wave spectral width, and wave groupiness as the dominant controls on the uncertainty. Statistical metrics, including the Coefficient of Variation (CV) and Range Uncertainty Level (RUL), demonstrate that overtopping rates exhibit substantial variability under randomized wave conditions, with CV exceeding 40% for low spectral resolutions (50–100 bins), while achieving statistical convergence (CV around 20%) requires at least 700 frequency bins, far surpassing conventional standards. The RUL, which describes the ratio of extreme to minimal overtopping rates, also decreases markedly as the number of frequency bins increases from 50 to 700. It is found that the overtopping rate follows a normal distribution with 700 frequency bins in wave generation. Simulations further demonstrate that overtopping rates increase by a factor of 2–4 as the JONSWAP spectrum peak enhancement factor (γ) increases from 1 to 7. The wave groupiness factor (GF) emerges as a predictor of overtopping variability, enabling a more efficient experimental design through reduction in groupiness-guided replication. These findings establish practical thresholds for experimental design and highlight the critical role of spectral parameters in hazard assessment. Full article
(This article belongs to the Special Issue Study on Environmental Hydrology and Hydrodynamic Characteristics of Basins, Estuaries and Offshore)
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16 pages, 4829 KiB  
Article
A New Monitoring Method for the Water-Filled Status of Check Dams Using Remote Sensing and Deep Learning Techniques
by Zhaohui Xia, Shu Yu, Naichang Zhang, Jianqin Wang, Yongxiang Cao, Fan Yue and Heng Zhang
Water 2025, 17(15), 2185; https://doi.org/10.3390/w17152185 - 22 Jul 2025
Abstract
China’s Loess Plateau is characterized by dense and widely distributed check dams. However, there has been a lack of large-scale and high-temporal-resolution monitoring for the water-filled status of check dams, which is strongly related to their safe operation. In this study, a deep [...] Read more.
China’s Loess Plateau is characterized by dense and widely distributed check dams. However, there has been a lack of large-scale and high-temporal-resolution monitoring for the water-filled status of check dams, which is strongly related to their safe operation. In this study, a deep learning-based remote sensing image interpretation technique was developed, which enables long-term, large-scale, and high-frequency monitoring of the water-filled status of check dams. Using object detection algorithms based on deep learning and YOLOv3, an object-detection model was constructed and optimized. Leveraging high spatial resolution optical remote sensing images, the water-filled status of check dams can be identified. The model prediction indicates that the average precision for the check dam and water-filled check dam detection models reached 90.27% and 91.89%, respectively. Case studies were conducted on the check dams in the Jiuyuangou and Xiwuselang small watersheds. The monitoring result based on remote sensing images in the year 2021 shows a good agreement with the actual number of check dams. The proposed monitoring method for the water-filled status of check dams was proven feasible. This provides a reliable and efficient technical approach for monitoring the water-filled status of check dams, which is promising for their daily management and safe operation. Full article
(This article belongs to the Section Soil and Water)
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29 pages, 1900 KiB  
Review
A Review of Biochar-Industrial Waste Composites for Sustainable Soil Amendment: Mechanisms and Perspectives
by Feng Tian, Yiwen Wang, Yawen Zhao, Ruyu Sun, Man Qi, Suqing Wu and Li Wang
Water 2025, 17(15), 2184; https://doi.org/10.3390/w17152184 - 22 Jul 2025
Abstract
Soil acidification, salinization, and heavy metal pollution pose serious threats to global food security and sustainable agricultural development. Biochar, with its high porosity, large surface area, and abundant functional groups, can effectively improve soil properties. However, due to variations in feedstocks and pyrolysis [...] Read more.
Soil acidification, salinization, and heavy metal pollution pose serious threats to global food security and sustainable agricultural development. Biochar, with its high porosity, large surface area, and abundant functional groups, can effectively improve soil properties. However, due to variations in feedstocks and pyrolysis conditions, it may contain potentially harmful substances. Industrial wastes such as fly ash, steel slag, red mud, and phosphogypsum are rich in minerals and show potential for soil improvement, but direct application may pose environmental risks. The co-application of biochar with these wastes can produce composite amendments that enhance pH buffering capacity, nutrient availability, and pollutant immobilization. Therefore, a review of biochar-industrial waste composites as soil amendments is crucial for addressing soil degradation and promoting resource utilization of wastes. In this study, the literature was retrieved from Web of Science, Scopus, and Google Scholar using keywords including biochar, fly ash, steel slag, red mud, phosphogypsum, combined application, and soil amendment. A total of 144 articles from 2000 to 2025 were analyzed. This review summarizes the physicochemical properties of biochar and representative industrial wastes, including pH, electrical conductivity, surface area, and elemental composition. It examines their synergistic mechanisms in reducing heavy metal release through adsorption, complexation, and ion exchange. Furthermore, it evaluates the effects of these composites on soil health and crop productivity, showing improvements in soil structure, nutrient balance, enzyme activity, and metal immobilization. Finally, it identifies knowledge gaps as well as future prospects and recommends long-term field trials and digital agriculture technologies to support the sustainable application of these composites in soil management. Full article
(This article belongs to the Special Issue Sustainable Water Treatment Systems: Green Infrastructure and Bioremediation)
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13 pages, 785 KiB  
Article
Selective Lactic Acid Production via Thermophilic Anaerobic Fermentation
by Claudia Chao-Reyes, Rudolphus Antonius Timmers, Ahmed Mahdy, Silvia Greses and Cristina González-Fernández
Water 2025, 17(15), 2183; https://doi.org/10.3390/w17152183 - 22 Jul 2025
Abstract
The combined effect of temperature-adapted inocula and anaerobic fermentation (AF) settings (pH 5.1 and 50 °C) were assessed to produce short-chain carboxylates (SCCs). In this study, the AF of carrot pulp was investigated using inocula adapted at different temperatures (25, 35, and 55 [...] Read more.
The combined effect of temperature-adapted inocula and anaerobic fermentation (AF) settings (pH 5.1 and 50 °C) were assessed to produce short-chain carboxylates (SCCs). In this study, the AF of carrot pulp was investigated using inocula adapted at different temperatures (25, 35, and 55 °C) with the aim of shifting the microbiome activity from biogas to SCC production. The highest SCC content (17.2 g COD L−1), and bioconversion (26.1%) and acidification efficiency (56.3%) were achieved with 35 °C-adapted inoculum. Lactic acid production prevailed in all reactors, demonstrating a high selectivity in SCC production. Both the microbial richness and diversity sharply diminished in the 35 °C and 55 °C operated reactors, with Firmicutes phylum identified as key players of the lactic acid production in AF. The results demonstrated that the operating temperature played a key role in shaping the microbial structure of inocula, leading to different process performances and highlighting thermophilic AF as a feasible process to produce lactic acid. Full article
(This article belongs to the Special Issue Innovations in Anaerobic Digestion Technology)
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16 pages, 2024 KiB  
Article
Spatiotemporal Dynamics and Driving Factors of Phytoplankton Community Structure in the Liaoning Section of the Liao River Basin in 2010, 2015, and 2020
by Kang Peng, Zhixiong Hu, Rui Pang, Mingyue Li and Li Liu
Water 2025, 17(15), 2182; https://doi.org/10.3390/w17152182 - 22 Jul 2025
Abstract
This study aimed to analyse the spatiotemporal evolution of phytoplankton community dynamics and its underlying mechanisms in the Liaoning section of the Liao River Basin in 2010, 2015, and 2020. Phytoplankton species diversity increased significantly, with an increase from three phyla and 31 [...] Read more.
This study aimed to analyse the spatiotemporal evolution of phytoplankton community dynamics and its underlying mechanisms in the Liaoning section of the Liao River Basin in 2010, 2015, and 2020. Phytoplankton species diversity increased significantly, with an increase from three phyla and 31 species in 2010 to six phyla and 74 species in 2020. Concurrent increases in α-diversity indicated continuous improvements in habitat heterogeneity. The community structure shifted from a diatom-dominated assemblage to a green algae–diatom co-dominated configuration, contributing to an enhanced water purification capacity. The upstream agricultural zone (Tieling section) had elevated biomass and low diversity, indicating persistent non-point-source pollution stress. The midstream urban–industrial zone (Shenyang–Anshan section) emerged as a phytoplankton diversity hotspot, likely due to expanding niche availability in response to point-source pollution control. The downstream wetland zone (Panjin section) exhibited significant biomass decline and delayed diversity recovery, shaped by the dual pressures of resource competition and habitat filtering. The driving mechanism of community succession shifted from nutrient-dominated factors (NH3-N, TN) to redox-sensitive factors (DO, pH). These findings support a ‘zoned–graded–staged’ ecological restoration strategy for the Liao River Basin and inform the use of phytoplankton as bioindicators in watershed monitoring networks. Full article
(This article belongs to the Special Issue Water Environment Pollution and Control, 4th Edition)
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36 pages, 2334 KiB  
Article
Identification of Critical Exposed Elements and Strategies for Mitigating Secondary Hazards in Flood-Induced Coal Mine Accidents
by Xue Yang, Chen Liu, Langxuan Pan, Xiaona Su, Ke He and Ziyu Mao
Water 2025, 17(15), 2181; https://doi.org/10.3390/w17152181 - 22 Jul 2025
Abstract
Natech events, involving multi-hazard coupling and cascading effects, pose serious threats to coal mine safety. This paper addresses flood-induced Natech scenarios in coal mining and introduces a two-stage cascading analysis framework based on hazard systems theory. A tri-layered network—comprising natural hazards, exposed elements, [...] Read more.
Natech events, involving multi-hazard coupling and cascading effects, pose serious threats to coal mine safety. This paper addresses flood-induced Natech scenarios in coal mining and introduces a two-stage cascading analysis framework based on hazard systems theory. A tri-layered network—comprising natural hazards, exposed elements, and secondary hazards—models hazard propagation. In Stage 1, an improved adjacency information entropy algorithm with multi-hazard coupling coefficients identifies critical exposed elements. In Stage 2, Dijkstra’s algorithm extracts key risk transmission paths. A dual-dimensional classification method, based on entropy and transmission risk, is then applied to prioritize emergency responses. This method integrates the criticality of exposed elements with the risk levels associated with secondary disaster propagation paths. Case studies validate the framework, revealing: (1) Hierarchical heterogeneity in the network, with surface facilities and surrounding hydrological systems as central hubs; shaft and tunnel systems and surrounding geological systems are significantly affected by propagation from these core nodes, exhibiting marked instability. (2) Strong risk polarization in secondary hazard propagation, with core-node-originated paths being more efficient and urgent. (3) The entropy-risk classification enables targeted hazard control, improving efficiency. The study proposes chain-breaking strategies for precise, hierarchical, and timely emergency management, enhancing coal mine resilience to flood-induced Natech events. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)
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7 pages, 186 KiB  
Editorial
Recent Advances in Karstic Hydrogeology, 2nd Edition
by Francesco Maria De Filippi and Giuseppe Sappa
Water 2025, 17(15), 2180; https://doi.org/10.3390/w17152180 - 22 Jul 2025
Abstract
Karst hydrogeology is the branch of hydrogeology that studies how groundwater flows and behaves in karst systems, characterized by the presence of soluble rocks (mainly limestone and dolomite) that favour chemical dissolution by meteoric water [...] Full article
(This article belongs to the Special Issue Recent Advances in Karstic Hydrogeology, 2nd Edition)
19 pages, 8896 KiB  
Article
Future Residential Water Use and Management Under Climate Change Using Bayesian Neural Networks
by Young-Ho Seo, Jang Hyun Sung, Joon-Seok Park, Byung-Sik Kim and Junehyeong Park
Water 2025, 17(15), 2179; https://doi.org/10.3390/w17152179 - 22 Jul 2025
Abstract
This study projects future Residential Water Use (RWU) under climate change scenarios using a Bayesian Neural Network (BNN) model that quantifies the relationship between observed temperatures and RWU. Eighteen Global Climate Models (GCMs) under the Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) scenario were used [...] Read more.
This study projects future Residential Water Use (RWU) under climate change scenarios using a Bayesian Neural Network (BNN) model that quantifies the relationship between observed temperatures and RWU. Eighteen Global Climate Models (GCMs) under the Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) scenario were used to assess the uncertainties across these models. The findings indicate that RWU in Republic of Korea (ROK) is closely linked to temperature changes, with significant increases projected in the distant future (F3), especially during summer. Under the SSP5–8.5 scenario, RWU is expected to increase by up to 10.3% by the late 21st century (2081–2100) compared to the historical baseline. The model achieved a root mean square error (RMSE) of 11,400 m3/month, demonstrating reliable predictive performance. Unlike conventional deep learning models, the BNN provides probabilistic forecasts with uncertainty bounds, enhancing its suitability for climate-sensitive resource planning. This study also projects inflows to the Paldang Dam, revealing an overall increase in future water availability. However, winter water security may decline due to decreased inflow and minimal changes in RWU. This study suggests enhancing summer precipitation storage while considering downstream flood risks. Demand management strategies are recommended for addressing future winter water security challenges. This research highlights the importance of projecting RWU under climate change scenarios and emphasizes the need for strategic water resource management in ROK. Full article
(This article belongs to the Section Water and Climate Change)
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20 pages, 1716 KiB  
Article
Research on the Comprehensive Evaluation Model of Risk in Flood Disaster Environments
by Yan Yu and Tianhua Zhou
Water 2025, 17(15), 2178; https://doi.org/10.3390/w17152178 - 22 Jul 2025
Abstract
Losses from floods and the wide range of impacts have been at the forefront of hazard-triggered disasters in China. Affected by large-scale human activities and the environmental evolution, China’s defense flood situation is undergoing significant changes. This paper constructs a comprehensive flood disaster [...] Read more.
Losses from floods and the wide range of impacts have been at the forefront of hazard-triggered disasters in China. Affected by large-scale human activities and the environmental evolution, China’s defense flood situation is undergoing significant changes. This paper constructs a comprehensive flood disaster risk assessment model through systematic analysis of four key factors—hazard (H), exposure (E), susceptibility/sensitivity (S), and disaster prevention capabilities (C)—and establishes an evaluation index system. Using the Analytic Hierarchy Process (AHP), we determined indicator weights and quantified flood risk via the following formula R = H × E × V × C. After we applied this model to 16 towns in coastal Zhejiang Province, the results reveal three distinct risk tiers: low (R < 0.04), medium (0.04 ≤ R ≤ 0.1), and high (R > 0.1). High-risk areas (e.g., Longxi and Shitang towns) are primarily constrained by natural hazards and socioeconomic vulnerability, while low-risk towns benefit from a robust disaster mitigation capacity. Risk typology analysis further classifies towns into natural, social–structural, capacity-driven, or mixed profiles, providing granular insights for targeted flood management. The spatial risk distribution offers a scientific basis for optimizing flood control planning and resource allocation in the district. Full article
(This article belongs to the Special Issue Causes and Reconstruction of Catastrophic Flash Flood Disasters: Investigation, Analysis, Modelling and Risk Management, 2nd Edition)
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21 pages, 2048 KiB  
Article
Photocatalytic Degradation of Oxytetracycline and Imidacloprid Under Visible Light with Sr0.95Bi0.05TiO3: Influence of Aqueous Matrix
by Maria J. Nunes, Ana Lopes, Maria J. Pacheco, Paulo T. Fiadeiro, Guilherme J. Inacio, Jefferson E. Silveira, Alyson R. Ribeiro, Wendel S. Paz and Lurdes Ciríaco
Water 2025, 17(15), 2177; https://doi.org/10.3390/w17152177 - 22 Jul 2025
Abstract
In this study, Sr0.95Bi0.05TiO3 was synthesized via solid state reaction, characterized, and applied as a visible-light-active photocatalyst for the degradation of oxytetracycline, imidacloprid, and their mixture. To evaluate the influence of the aqueous matrix on pollutant degradation, photocatalytic [...] Read more.
In this study, Sr0.95Bi0.05TiO3 was synthesized via solid state reaction, characterized, and applied as a visible-light-active photocatalyst for the degradation of oxytetracycline, imidacloprid, and their mixture. To evaluate the influence of the aqueous matrix on pollutant degradation, photocatalytic experiments were carried out in both distilled water and a real environmental sample (surface water). The Sr0.95Bi0.05TiO3 perovskite showed high photocatalytic performance under visible light, achieving nearly complete degradation of oxytetracycline after 2 h, and significant removal of imidacloprid in river water (60% after 3 h). Enhanced degradation in surface water was attributed to favorable ionic composition and pH. The perovskite oxide maintained its photocatalytic performance over five consecutive cycles, with no significant loss in photocatalytic activity or structural and morphological stability. Ecotoxicological assessment using Daphnia magna confirmed that the treated water was non-toxic, indicating that no harmful byproducts were formed. Complementary Density Functional Theory calculations were conducted to complement experimental findings, providing insights into the structural, electronic, and optical properties of the photocatalyst, enhancing the understanding of the degradation mechanisms involved. This integrated approach, combining experimental photocatalytic performance evaluation in different matrices, ecotoxicity testing, and theoretical modeling, highlights Sr0.95Bi0.05TiO3 as a promising, stable, and environmentally safe photocatalyst for practical wastewater treatment applications. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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18 pages, 5682 KiB  
Article
Predicting Channel Water Depth: A Multi-Coupling Deep Ensemble Model Approach
by Yiwen Chen, Hangling Ma, Zongkui Guan, Haipeng Lu, Xin Huang, Cheng Bo and Shuliang Zhang
Water 2025, 17(15), 2176; https://doi.org/10.3390/w17152176 - 22 Jul 2025
Abstract
With global warming and accelerated urbanization, urban flooding became one of the top ten international natural disasters in 2024. In order to accurately and efficiently simulate the impact of upstream river water transport on downstream river inundation under heavy rainfall scenarios, this study [...] Read more.
With global warming and accelerated urbanization, urban flooding became one of the top ten international natural disasters in 2024. In order to accurately and efficiently simulate the impact of upstream river water transport on downstream river inundation under heavy rainfall scenarios, this study proposes a river inundation water depth calculation model based on a deep ensemble learning approach. The model integrates flood inundation data from hydrodynamic models with machine learning techniques, introducing a matrix-based deep ensemble learning method. The results demonstrate superior prediction accuracy, with an RMSE of 0.04 and R2 of 0.95. Validation using typical rainfall data from 6 July 2022 shows that the model achieves a prediction error of less than 0.15 m across 99.8% of the domain, outperforming standalone models. These findings confirm that the deep ensemble model effectively captures the complex relationships between rainfall, terrain, and flow dynamics, providing reliable water depth predictions in data-scarce regions through multi-coupling modeling based on river characteristics. Full article
(This article belongs to the Section Hydrology)
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12 pages, 2793 KiB  
Article
Toxicological Efficiency Evaluation of the ASEC Technology for Contaminated Mining Water Using Lemna minor
by Mercedes Conradi, J. Emilio Sánchez-Moyano, Estefanía Bonnail, T. Ángel DelValls and Inmaculada Riba
Water 2025, 17(15), 2175; https://doi.org/10.3390/w17152175 - 22 Jul 2025
Abstract
The Adiabatic Sonic Evaporation and Crystallization (ASEC) technology was developed as a disruptive zero-liquid discharge system to treat contaminated mining effluents. This study evaluates its ecotoxicological efficacy using Lemna minor, a freshwater macrophyte, as a sensitive bioindicator. Acute growth inhibition tests were [...] Read more.
The Adiabatic Sonic Evaporation and Crystallization (ASEC) technology was developed as a disruptive zero-liquid discharge system to treat contaminated mining effluents. This study evaluates its ecotoxicological efficacy using Lemna minor, a freshwater macrophyte, as a sensitive bioindicator. Acute growth inhibition tests were conducted using OECD Guideline 221. Lemna minor was exposed for 7 days to untreated and treated effluents from the Tharsis mine and the Tinto River in southern Spain. The results revealed 100% inhibition of frond growth and biomass in untreated samples (pH < 2.6), indicating acute toxicity. In contrast, effluents treated with ASEC showed growth and biomass accumulation statistically indistinguishable from the control, confirming the system’s efficiency in reducing toxicity and restoring water quality. These findings support the environmental viability of ASEC technology for mine and port effluent treatment. Full article
(This article belongs to the Special Issue Studies on Toxic Effects in Aquatic Organisms and Ecosystems)
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