Water

23 pages, 12254 KiB

Open AccessArticle

Making Sense of Unsustainable Realities: Hydropower and the Sustainable Development Goals

by Emily Benton Hite

Water 2025, 17(13), 1857; https://doi.org/10.3390/w17131857 (registering DOI) - 22 Jun 2025

This paper explores the tensions between hydropower and sustainable development to critically examine how hydropower, often promoted as a strategy for fulfilling the Sustainable Development Goals, may not align with the values and needs of local communities. Research in Costa Rica highlights a [...] Read more.

This paper explores the tensions between hydropower and sustainable development to critically examine how hydropower, often promoted as a strategy for fulfilling the Sustainable Development Goals, may not align with the values and needs of local communities. Research in Costa Rica highlights a key issue: For whom and for what is hydropower sustainable? While hydropower may support global energy and climate goals, it often undermines the autonomy, cultural practices, and ecological relationships of Indigenous peoples. This disconnect raises further questions: what social, economic, and ecological trade-offs are acceptable, and for whom? This paper discusses how these trade-offs—climate mitigation versus the loss of land, resources, and autonomy—are often imposed without meaningful consultation or participation from affected communities. Furthermore, it asks who makes the decisions, and how can these decisions be more just? By analyzing the power dynamics within hydrosocial territories, this paper argues for water governance that applies an environmental justice framework to address power asymmetries and centers marginalized voices to ensure that sustainability efforts do not reproduce the very injustices they seek to solve. Full article

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

18 pages, 1658 KiB

Open AccessArticle

Microbial Quantification Using ATP and Petrifilms for Irrigation Water Treated with Cold Plasma or Ozone

by Dharti Thakulla and Paul R. Fisher

Water 2025, 17(13), 1856; https://doi.org/10.3390/w17131856 (registering DOI) - 22 Jun 2025

Abstract

Traditional methods of microbial quantification of irrigation water using colony counts from agar culture require dedicated laboratory space and trained personnel, limiting their on-site applicability. Dehydrated Petrifilm™ plates are a simpler alternative but still require 2–3 days to culture. Adenosine triphosphate (ATP) tests [...] Read more.

Traditional methods of microbial quantification of irrigation water using colony counts from agar culture require dedicated laboratory space and trained personnel, limiting their on-site applicability. Dehydrated Petrifilm™ plates are a simpler alternative but still require 2–3 days to culture. Adenosine triphosphate (ATP) tests may offer a fast and reliable method for quantifying microbes in water. In this study, we compared a) microbial quantification based on ATP assays with Petrifilm™-based assays, and (b) we evaluated the effectiveness of cold plasma or ozone treatments in controlling microbial growth at various oxidation–reduction potential (ORP) levels. Lake water was recirculated through an ozone or cold plasma treatment system until a target ORP of 700 mV was reached. Samples were collected at various ORP levels and plated for aerobic bacteria and yeast and mold counts using Petrifilm™ plates. The free and total ATP concentrations were measured using the Hygiena EnSURE luminometer and its accompanying free and total ATP swabs. Microbial ATP was calculated by subtracting the free from the total ATP. Cold plasma and ozone showed similar effects on microbial inactivation at 700 mV (p < 0.05). Both treatments achieved complete fungal inactivation at 600–700 mV ORP, bacterial inactivation at 600 mV ORP, and near-complete inactivation of microbial ATP at 600–700 mV. A moderate positive correlation (Pearson’s correlation = 0.39 and Spearman’s rank correlation = 0.39) was observed between the Petrifilm™ bacterial counts and microbial ATP levels, suggesting ATP quantification could complement Petrifilm™ for rapid and non-selective onsite microbial assessment of irrigation water. Full article

(This article belongs to the Special Issue Ecological Wastewater Treatment and Resource Utilization)

32 pages, 10468 KiB

Open AccessArticle

Predictive Analytics and Soft Computing Models for Groundwater Vulnerability Assessment in High-Salinity Regions of the Southeastern Anatolia Project (GAP), Türkiye

by Abdullah Izzeddin Karabulut, Sinan Nacar, Mehmet Irfan Yesilnacar, Mehmet Ali Cullu and Adem Bayram

Water 2025, 17(13), 1855; https://doi.org/10.3390/w17131855 (registering DOI) - 22 Jun 2025

Abstract

This study was conducted in the Harran Plain within the framework of the Southeastern Anatolia Project (GAP) in Türkiye to evaluate the vulnerability of groundwater to contamination, with a special emphasis on the high salinity conditions attributed to agricultural and rural practices. The [...] Read more.

This study was conducted in the Harran Plain within the framework of the Southeastern Anatolia Project (GAP) in Türkiye to evaluate the vulnerability of groundwater to contamination, with a special emphasis on the high salinity conditions attributed to agricultural and rural practices. The region is notably challenged by salinization resulting from intensive irrigation and insufficient drainage systems. The DRASTIC framework was used to assess groundwater contamination vulnerability. The DRASTIC framework parameters were numerically integrated using both the original DRASTIC framework and its modified version, serving as the basis for subsequent predictive analytics and soft computing model development. The primary aim was to determine the most effective predictive model for groundwater contamination vulnerability in salinity-affected areas. In this context, various models were implemented and evaluated, including artificial neural networks (ANNs) with varied hidden layer configurations, four different regression-based methods (MARS, TreeNet, GPS, and CART), and three classical regression analysis approaches. The modeling process utilized 24 adjusted vulnerability indices (AVIs) as target variables, with the dataset partitioned into 58.34% for training, 20.83% for validating, and 20.83% for testing. Model performance was rigorously assessed using various statistical indicators such as mean absolute error, root mean square error, and the Nash–Sutcliffe efficiency coefficient, in addition to evaluating the predictive AVIs through spatial mapping. The findings revealed that the ANNs and TreeNet models offered superior performance in accurately predicting groundwater contamination vulnerability, particularly by delineating the spatial distribution of risk in areas experiencing intensive agricultural pressure. Full article

(This article belongs to the Section Hydrogeology)

15 pages, 5632 KiB

Open AccessArticle

Analysis of the Driving Factors for Land Subsidence in the Northern Anhui Plain: A Case Study of Bozhou City

by Qing He, Hehe Liu, Lu Wei and Zhen Zhang

Water 2025, 17(13), 1854; https://doi.org/10.3390/w17131854 (registering DOI) - 22 Jun 2025

Abstract

In recent years, land subsidence in the Northern Anhui Plain has become increasingly pronounced, posing serious risks to infrastructure and groundwater management. However, quantitative assessments of its driving mechanisms remain limited. This study focuses on Bozhou, a typical resource-based city, and employs 186 [...] Read more.

In recent years, land subsidence in the Northern Anhui Plain has become increasingly pronounced, posing serious risks to infrastructure and groundwater management. However, quantitative assessments of its driving mechanisms remain limited. This study focuses on Bozhou, a typical resource-based city, and employs 186 Sentinel-1 SAR images and SBAS-based interferometric analysis to retrieve the spatiotemporal evolution of land subsidence from 2022 to 2024. Results show that the peak subsidence rate reaches 102 mm/year and has its major distribution in the central and eastern sectors of Bozhou. Temporally, the subsidence pattern shows an initial intensification followed by gradual stabilization. Furthermore, a GeoDetector-based analysis indicates that excessive groundwater extraction and coal mining are the dominant factors, with significant interactive enhancement effects. These findings provide crucial insights for the prevention and mitigation of land subsidence in resource-based cities. Full article

(This article belongs to the Special Issue Sustainable Groundwater Management and Mitigation of Land Subsidence: Evaluating Environmental Impacts and Resilience Strategies)

18 pages, 1021 KiB

Open AccessFeature PaperArticle

Heavy Metal Pollution of the Świder River, Protection Measures and Impact on Tourism Development

by Mariusz Kluska and Joanna Jabłońska

Water 2025, 17(13), 1853; https://doi.org/10.3390/w17131853 (registering DOI) - 22 Jun 2025

Abstract

As a fundamental element of nature, water determines the existence of life on Earth. The physicochemical and biological composition of natural waters is closely correlated with the state of the environment through which they flow. The main threat is municipal wastewater, but also [...] Read more.

As a fundamental element of nature, water determines the existence of life on Earth. The physicochemical and biological composition of natural waters is closely correlated with the state of the environment through which they flow. The main threat is municipal wastewater, but also nonpoint source pollution from agriculture, which has a major impact on the state of the aquatic environment. The main objective of this study was to analyse selected heavy metals in surface waters and bottom sediments of the Świder River. Given the intricate nature of how heavy metals interact and move between water and sediment, the study also aimed to show whether bottom sediments of surface waters may pose an environmental risk—particularly through the potential release of toxic metals and the development of tourism on the Świder River. The obtained values of the concentrations of the analysed metals were below the permissible standards. The highest concentrations were found in the lower reaches of the Świder River, where a tourist and more urbanised area is located. The obtained results allowed us to assess the bioavailability of these metals, and will be used by local government units to improve the management of this area in order to minimise anthropogenic pollution. Full article

(This article belongs to the Special Issue Water and Society: Challenges for Freshwater Quality Under a Climate Change Scenario)

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19 pages, 4551 KiB

Open AccessArticle

Nonlinear Dynamic Analysis on Multi-Fishing Boats Anchored Together Based on Hilbert–Huang Transform

by Yi-Yan Sun, De-Shuang Yu, Yu-Zhang Xiong, Gang Wang, Xing Li and Ding Chen

Water 2025, 17(13), 1852; https://doi.org/10.3390/w17131852 (registering DOI) - 21 Jun 2025

Abstract

Fishing boats anchored away from the wharf or revetment are typically in side-by-side configurations due to their small size. Expanding on previous physical model tests investigating regular wave interactions with multi-boat and bow-and-stern-anchored fishing arrays, this study examines the hydrodynamic effects of irregular [...] Read more.

Fishing boats anchored away from the wharf or revetment are typically in side-by-side configurations due to their small size. Expanding on previous physical model tests investigating regular wave interactions with multi-boat and bow-and-stern-anchored fishing arrays, this study examines the hydrodynamic effects of irregular wave conditions. The Hilbert–Huang transform (HHT), an adaptive time–frequency processing technique, was applied to investigate multi-order nonlinear oscillatory elements in dynamic systems. It is found that the roll and heave motions of each boat are dominated by the wave-frequency components, whereas the sway motion is dominated by the low-frequency components. When multi-boats are anchored side by side, the roll and heave motion of the lee-side boat has a greater wave-frequency response compared with other boats, while for sway motion, the middle boat seems a little higher than others. The nonlinear dynamics of the roll and sway motion for a single boat is very large. An increase in the number of parallel boats has significant effect on reducing these responses. The variation trends of the three motion responses of the boat on the weather and lee sides are obviously different in each form. Full article

(This article belongs to the Special Issue Coastal Management and Nearshore Hydrodynamics, 2nd Edition)

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20 pages, 1492 KiB

Open AccessArticle

Using Hybrid Machine Learning to Predict Wastewater Effluent Quality and Ensure Treatment Plant Stability

by Zhaoyang Xiong, Xingyang Liu, Thomas Igou, Zhanchao Li and Yongsheng Chen

Water 2025, 17(13), 1851; https://doi.org/10.3390/w17131851 (registering DOI) - 21 Jun 2025

Abstract

The accurate prediction of wastewater quality parameters is pivotal for evaluating the treatment stability of processes and for ensuring regulatory compliance in wastewater treatment plants. A singular machine learning model often faces challenges in fully capturing and extracting the complex nonlinear relationships inherent [...] Read more.

The accurate prediction of wastewater quality parameters is pivotal for evaluating the treatment stability of processes and for ensuring regulatory compliance in wastewater treatment plants. A singular machine learning model often faces challenges in fully capturing and extracting the complex nonlinear relationships inherent in multivariate time series data. To overcome this limitation, this study proposes a dual hybrid modeling framework that effectively integrates LSTM and XGBoost models, leveraging their complementary strengths. The first hybrid model refines the residues to utilize the information, whereas the second hybrid model enhances the input features by extracting temporal dependencies. A comparative analysis against three standalone models reveals that the proposed hybrid framework consistently outperforms them in both predictive accuracy and generalization ability across four key effluent indicators—chemical oxygen demand, ammonia nitrogen, total nitrogen, and total phosphorus. These results demonstrate that the proposed hybrid machine learning framework has great potential to be used to evaluate process stability in wastewater treatment plants, paving a way for smarter, more resilient, and more sustainable wastewater management, which will improve ecological integrity and regulatory compliance. Full article

(This article belongs to the Special Issue Risk Characterization, Assessment, and Management Derived from Water for Environmental/Human Health)

25 pages, 4005 KiB

Open AccessArticle

Prediction of Sluice Seepage Based on Impact Factor Screening and the IKOA-BiGRU Model

by Xiaoran Sun, Jianhe Peng, Chunlin Zhang and Sen Zheng

Water 2025, 17(13), 1850; https://doi.org/10.3390/w17131850 (registering DOI) - 21 Jun 2025

Abstract

Sluices play a critical role in flood control, power generation, water supply, etc. With decades of service, sluice safety assurance becomes a structural engineering imperative. Previous investigations have revealed that failures of sluices are often associated with seepage damage. To gain further insight [...] Read more.

Sluices play a critical role in flood control, power generation, water supply, etc. With decades of service, sluice safety assurance becomes a structural engineering imperative. Previous investigations have revealed that failures of sluices are often associated with seepage damage. To gain further insight into sluice seepage and ensure the safety of sluice structures, proposing an effective prediction method for sluice seepage nevertheless remains a challenging fundamental and practical perspective. Therefore, in this paper, a novel prediction model for sluice seepage based on impact factor screening methods, the improved Kepler optimization algorithm (IKOA) and the bidirectional gated recurrent unit (BiGRU), is presented. Primarily, the maximal information coefficient and the correlation-based feature selection (MIC–CFS) are introduced to screen the impact factors of the model, aiming to reduce redundant information and the complexity of the model. Subsequently, the Kepler optimization algorithm (KOA) is enhanced using three strategies: chaotic mapping-based initialization, Runge–Kutta-based position updating, and the enhanced solution quality (ESQ) strategy to optimize the hyperparameters of the BiGRU network. On this basis, the prediction model is established, which is applied in the Bengbu sluice to verify its fitting and prediction performance. Eventually, comparison analyses with a traditional stepwise regression model, IKOA–LSTM, and IKOA–GRU, were conducted based on monitoring sequences of three monitoring points. The coefficients of determination of the proposed model were located in the range of 0.974 to 0.988. Correspondingly, the mean absolute error values of the proposed model were the lowest, ranging from 0.074 to 0.064. The results of six evaluation metrics confirm that the proposed model consistently exhibits superior interpretability and is able to serve as a promising tool for sluice seepage prediction. Full article

(This article belongs to the Special Issue Hydraulic Engineering Applications of Artificial Intelligence, Deep Learning, and Digital Twin Technology)

29 pages, 4151 KiB

Open AccessArticle

Lake Water Composition in Oceanic Islands: Insights from REE Content and ⁸⁷Sr/⁸⁶Sr Isotopic Ratio

by José Virgílio Cruz, César Andrade, Letícia Ferreira and Fátima Viveiros

Water 2025, 17(13), 1849; https://doi.org/10.3390/w17131849 (registering DOI) - 21 Jun 2025

Abstract

A study was carried out with a representative data set of volcanic lakes from the Azores archipelago. A total of 672 samples were collected during four field surveys conducted over the year and along the depth. Following water sampling, temperature, pH, and EC [...] Read more.

A study was carried out with a representative data set of volcanic lakes from the Azores archipelago. A total of 672 samples were collected during four field surveys conducted over the year and along the depth. Following water sampling, temperature, pH, and EC were measured, the dissolved CO₂ and alkalinity were determined by titration, and aliquots were taken to perform analysis of major, minor and trace elements, as well as ¹⁸O/¹⁶O, ²H/¹H and ⁸⁷Sr/⁸⁶Sr isotopic ratios. Waters are of meteoric origin and from the Na-HCO₃ to Na-Cl types. The ⁸⁷Sr/⁸⁶Sr ranges between 0.709194 and 0.704294, and most of the lakes depict less radiogenic values than seawater, suggesting a potential contribution from rock dissolution. Along the reciprocal of the Sr vs. ⁸⁷Sr/⁸⁶Sr plot, most samples suggest a linear trend between rock values and rainwater. Samples display considerable variability in the ∑REE, ranging from 0.83 µg L⁻¹ to 13.54 µg L⁻¹, and when chondrite normalized, depict a negative slope, showing an enrichment in light REEs compared to heavy REEs. This pattern is consistent with the one from Azores rocks and bottom sediments from some lakes, and most lakes depict Eu anomalies, resulting from interaction between water and sediments or from incongruent mineral dissolution. Full article

(This article belongs to the Section Hydrology)

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28 pages, 1303 KiB

Open AccessArticle

Bridging the Gap: A Novel Approach to Flood Risk Assessment for Resilience

by Jelena Andreja Radaković, Dragana Makajić-Nikolić and Nebojša Nikolić

Water 2025, 17(13), 1848; https://doi.org/10.3390/w17131848 (registering DOI) - 21 Jun 2025

Abstract

Flood disasters are growing more common and severe as a result of global warming and climate change. These factors intensify weather extremes, resulting in more unpredictable and disastrous floods around the world. Effective flood risk assessment is critical for reducing the socioeconomic and [...] Read more.

Flood disasters are growing more common and severe as a result of global warming and climate change. These factors intensify weather extremes, resulting in more unpredictable and disastrous floods around the world. Effective flood risk assessment is critical for reducing the socioeconomic and environmental consequences of catastrophic events. This work proposes a novel technique for flood risk assessment that combines Event Tree Analysis with Dempster–Shafer evidence theory and an optimization approach. The methodology assesses flood scenarios, as well as probabilities and outcomes, to predict risk pathways and uncertainties. Prevention measures, such as flood defenses, early warning systems, and sustainable land use practices, are evaluated for cost-effectiveness and their contribution to flood resilience. The findings emphasize the relevance of multi-layered mitigation techniques for lowering flood risks and increasing community resilience. The model presented in this paper is modular, and since it depends on expert judgement, it can be used in other geographical or regional settings with adjustments from local data and local expert assessments. Full article

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

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23 pages, 4276 KiB

Open AccessArticle

Water Saving and Carbon Reduction (CO₂) Synergistic Effect and Their Spatiotemporal Distribution Patterns

by Jing Zhao, Hanting Li, Zhiying Liu, Yaoqing Jiang and Wenbin Mu

Water 2025, 17(13), 1847; https://doi.org/10.3390/w17131847 (registering DOI) - 21 Jun 2025

Abstract

Under the dual constraints of rigid water resource management systems and China’s “dual carbon” national strategy, water resource management authorities face pressing practical demands for the coordinated governance of water conservation and carbon dioxide emission reduction. This study comprehensively compiles nationwide data on [...] Read more.

Under the dual constraints of rigid water resource management systems and China’s “dual carbon” national strategy, water resource management authorities face pressing practical demands for the coordinated governance of water conservation and carbon dioxide emission reduction. This study comprehensively compiles nationwide data on water supply/consumption, energy use, water intensity, and CO₂ emissions across Chinese provinces. Employing a non-radial directional distance function (NDDF) model with multiple inputs and outputs, we quantitatively assess provincial water saving and carbon reduction performance during 2000–2021; measure synergistic effects; and systematically examine the spatiotemporal evolution, correlation patterns, and convergence trends of three key indicators: standalone water saving performance, standalone carbon reduction performance, and their synergistic performance—essentially addressing whether “1 + 1 > 2” holds true. Furthermore, we analyze the spatial convergence and clustering characteristics of synergistic effect across regions, delving into the underlying causes of inter-regional disparities in water–carbon synergy. Key findings reveal the following: ① Temporally, standalone water saving and carbon reduction performance generally improved, though the water saving metrics initially declined before stabilizing into sustained growth, ultimately outpacing carbon reduction gains. Synergistic performance consistently surpassed standalone measures, with most regions demonstrating accelerating synergistic enhancement over time. Nationally, water–carbon synergy exhibited early volatile declines followed by steady growth, though the growth rate gradually decelerated. ② Spatially, high-value synergy clusters migrated from the western to eastern regions and the northern to southern zones before stabilizing geographically. The synergy effect demonstrates measurable convergence overall, yet with pronounced regional heterogeneity, manifesting a distinct “high southeast–low northwest” agglomeration pattern. Strategic interventions should prioritize water–carbon nexus domains, leverage spatial convergence trends and clustering intensities, and systematically unlock synergistic potential. Full article

(This article belongs to the Special Issue China Water Forum 2024)

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26 pages, 6348 KiB

Open AccessArticle

Characterization of Groundwater Dynamics and Their Response Mechanisms to Different Types of Compound Stress in a Typical Hilly Plain Area

by Qian Zhang, Meng Zhang, Wanjun Jiang, Yang Hao, Feiwu Chen and Mucheng Zhang

Water 2025, 17(13), 1846; https://doi.org/10.3390/w17131846 - 20 Jun 2025

Abstract

Groundwater is a crucial source of water supply and an important ecological element globally. Research on the dynamic characteristics of groundwater and their causative mechanisms is fundamental to objectively evaluating groundwater resources and their sustainable utilization. Based on the large amount of hydrogeological [...] Read more.

Groundwater is a crucial source of water supply and an important ecological element globally. Research on the dynamic characteristics of groundwater and their causative mechanisms is fundamental to objectively evaluating groundwater resources and their sustainable utilization. Based on the large amount of hydrogeological data collected and analyzed in typical hilly plain areas, a multi-factor weighted comprehensive evaluation system (MFWCES) based on GIS was used to evaluate the response of groundwater dynamics to combined stress elements in Tangshan City. The study area is located in the plains and hilly regions of Tangshan City. The evaluation system was based on seven influencing factors, including hydraulic conductivity, soil media, aquifer thickness, depth of groundwater, land use type, extraction intensity of groundwater, and groundwater evaporation. The results of groundwater dynamics in the study area were obtained by weighted comprehensive evaluation, with their score size ranging from 2.4 to 12.7. The spatial distribution of groundwater dynamics was classified into four categories: rapid response (10.3–12.7), dual response to precipitation and anthropogenic extraction (9.6–10.3), delayed response (7.6–9.6), and strong superimposed response to human activities (2.4–7.6). The related conclusions will provide key references for regional water resource planning, ecological protection, and the development of differentiated groundwater management strategies under compound stress. Full article

(This article belongs to the Special Issue Soil and Groundwater Quality and Resources Assessment, 2nd Edition)

16 pages, 3349 KiB

Open AccessArticle

Linear vs. Non-Linear Regional Flood Estimation Models in New South Wales, Australia

by Nilufa Afrin, Ridwan S. M. H. Rafi, Khaled Haddad and Ataur Rahman

Water 2025, 17(13), 1845; https://doi.org/10.3390/w17131845 - 20 Jun 2025

Abstract

This study aimed to compare linear and non-linear regional flood frequency analysis (RFFA) models where streamflow data of 88 catchments of New South Wales (NSW), Australia, were utilized. The Quantile Regression Technique (QRT) was selected as the linear model and an Artificial Neural [...] Read more.

This study aimed to compare linear and non-linear regional flood frequency analysis (RFFA) models where streamflow data of 88 catchments of New South Wales (NSW), Australia, were utilized. The Quantile Regression Technique (QRT) was selected as the linear model and an Artificial Neural Network (ANN) as the non-linear model. Six different flood quantiles were considered, which are annual exceedance probabilities of 1 in 2 (Q₂), 1 in 5 (Q₅), 1 in 10 (Q₁₀), 1 in 20 (Q₂₀), 1 in 50 (Q₅₀), and 1 in 100 (Q₁₀₀). The selected two RFFA models were compared using a split-sample validation technique (70% data for training and 30% data for testing) and several statistical indices like relative error (RE), absolute median relative error (RE_r), bias, the median ratio of the predicted and observed flood quantiles (Q_r), and the root mean square error (RMSE). The ANN model exhibited smaller bias values for Q₂, Q₅, Q₂₀, and Q₅₀ and smaller Q_r values for Q₁₀, Q₂₀, and Q₅₀. The REr values for the ANN model were found to be lower for smaller return periods (Q₂, Q₅, and Q₁₀). The overall RE_r value considering all six AEPs for the ANN model is 35%, which is 37% for the QRT model. The results of this study could assist to select a suitable RFFA technique for design application in the study area. Full article

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

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21 pages, 1905 KiB

Open AccessArticle

Monitoring and Evaluation of Water Quality from Chirita Lake, Romania

by Madalina Elena Abalasei, Daniel Toma and Carmen Teodosiu

Water 2025, 17(13), 1844; https://doi.org/10.3390/w17131844 - 20 Jun 2025

Abstract

Water management is a significant challenge, stimulating synergies between scientists and practitioners to create new tools and approaches to streamline decision making in this field. The assessment and monitoring of freshwater quality in surface water bodies are crucial for sustainable and safe water [...] Read more.

Water management is a significant challenge, stimulating synergies between scientists and practitioners to create new tools and approaches to streamline decision making in this field. The assessment and monitoring of freshwater quality in surface water bodies are crucial for sustainable and safe water management. The main objectives of this study were to analyze the characteristics and properties of Chirita lake, assess seasonal variations in water quality, determine compliance with national environmental legislation, and perform a comparison with monitoring systems in other European lakes. The study used data that determined water quality indicators for a five-year period, from 2020 to 2024, considering temperature, turbidity, pH, conductivity, alkalinity, hardness, organic matter, nitrates, nitrites, ammonium, and chlorides. The statistical analysis technique based on the Pearson correlation coefficient was used to evaluate the seasonal correlations of water quality parameters in Chirita lake and to extract the essential parameters for assessing seasonal variations in river water quality. The results obtained indicated that the indicators considered important for water quality variation in one season may not be important in another season, except for organic matter and conductivity, which showed a significant contribution to water quality variation throughout the four seasons. This study demonstrated that lake water is classified as first class, according to national regulations. These results provide valuable support for local authorities to develop effective strategies for water quality management and the prevention of eutrophication processes in reservoirs. Full article

(This article belongs to the Special Issue Water and Society: Challenges for Freshwater Quality Under a Climate Change Scenario)

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26 pages, 5097 KiB

Open AccessArticle

Groundwater Vulnerability and Environmental Impact Assessment of Urban Underground Rail Transportation in Karst Region: Case Study of Modified COPK Method

by Qiuyu Zhu, Ying Wang, Yi Li, Hanxiang Xiong, Chuanming Ma, Weiquan Zhao, Yang Cao and Xiaoqing Song

Water 2025, 17(13), 1843; https://doi.org/10.3390/w17131843 - 20 Jun 2025

Abstract

Urbanization always leads to increasing challenges to the groundwater resources in karst regions due to intensive land use, infrastructure development, and the rapid transmission potential of pollutants. This study proposed an improved groundwater vulnerability assessment (GVA) framework by modifying the widely used COP [...] Read more.

Urbanization always leads to increasing challenges to the groundwater resources in karst regions due to intensive land use, infrastructure development, and the rapid transmission potential of pollutants. This study proposed an improved groundwater vulnerability assessment (GVA) framework by modifying the widely used COP (Concentration of flow, Overlying layers, and Precipitation) model, through the integration of three additional indicators: urban underground rail transportation (UURT), land use and cover (LULC), and karst development (K). Guiyang, a typical urbanized karst city in southwest China, was selected as the case study. The improved COP model, namely the COPK model, showed stronger spatial differentiation and a higher Pearson correlation coefficient (

r

) with nitrate concentrations (

r

= 0.4388) compared to the original COP model (R = 0.3689), which validates the effectiveness of the newly introduced indicators. However, both R values remained below 0.5, even after model modification, suggesting that intensive human activities play a role in influencing nitrate distribution. The pollution load index (PI) was developed based on seven types of pollution sources, and it was integrated with the COPK vulnerability index using a risk matrix approach, producing a groundwater risk map classified into five levels. Global Moran’s I analysis (0.9171 for COP model and 0.8739 for COPK model) confirmed strong and significant spatial clustering patterns for the two models. The inclusion of UURT and LULC improved the model’s sensitivity to urban-related pressures and enhanced its capacity to detect local risk zones. It is a scalable tool for groundwater risk assessment in urbanized karst areas and offers practical insights for land use planning and sustainable groundwater management. Full article

(This article belongs to the Special Issue Contaminant Transport, Risk Assessment, and Ecological Impacts in Karst)

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20 pages, 2832 KiB

Open AccessArticle

Short-Term Optimal Scheduling of Pumped-Storage Units via DDPG with AOS-LSTM Flow-Curve Fitting

by Xiaoyao Ma, Hong Pan, Yuan Zheng, Chenyang Hang, Xin Wu and Liting Li

Water 2025, 17(13), 1842; https://doi.org/10.3390/w17131842 - 20 Jun 2025

Abstract

The short-term scheduling of pumped-storage hydropower plants is characterised by high dimensionality and nonlinearity and is subject to multiple operational constraints. This study proposes an intelligent scheduling framework that integrates an Atomic Orbital Search (AOS)-optimised Long Short-Term Memory (LSTM) network with the Deep [...] Read more.

The short-term scheduling of pumped-storage hydropower plants is characterised by high dimensionality and nonlinearity and is subject to multiple operational constraints. This study proposes an intelligent scheduling framework that integrates an Atomic Orbital Search (AOS)-optimised Long Short-Term Memory (LSTM) network with the Deep Deterministic Policy Gradient (DDPG) algorithm to minimise water consumption during the generation period while satisfying constraints such as system load and safety states. Firstly, the AOS-LSTM model simultaneously optimises the number of hidden neurons, batch size, and training epochs to achieve high-precision fitting of unit flow–efficiency characteristic curves, reducing the fitting error by more than 65.35% compared with traditional methods. Subsequently, the high-precision fitted curves are embedded into a Markov decision process to guide DDPG in performing constraint-aware load scheduling. Under a typical daily load scenario, the proposed scheduling framework achieves fast inference decisions within 1 s, reducing water consumption by 0.85%, 1.78%, and 2.36% compared to standard DDPG, Particle Swarm Optimisation, and Dynamic Programming methods, respectively. In addition, only two vibration-zone operations and two vibration-zone crossings are recorded, representing a reduction of more than 90% compared with the above two traditional optimisation methods, significantly improving scheduling safety and operational stability. The results validate the proposed method’s economic efficiency and reliability in high-dimensional, multi-constraint pumped-storage scheduling problems and provide strong technical support for intelligent scheduling systems. Full article

(This article belongs to the Special Issue Recent Advances in Hydraulic Machinery and Its Application in Marine Engineering)

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23 pages, 3456 KiB

Open AccessArticle

Hydrological Implications of Supplemental Irrigation in Cocoa Production Using SWAT Model: Insights from the Upper Offin Sub-Basin, Ghana

by Tewodros T. Assefa, Kekeli K. Gbodji, Gerald Atampugre, Yvonne S. A. Loh, Yared Bayissa and Seifu A. Tilahun

Water 2025, 17(13), 1841; https://doi.org/10.3390/w17131841 - 20 Jun 2025

Abstract

The cocoa production in Ghana, largely reliant on rainfall and undertaken by smallholder farmers, is increasingly endangered by climate change-induced water scarcity. Although supplemental irrigation has been posited as an adaptive measure, its hydrological impacts remain understudied. This current study seeks to bridge [...] Read more.

The cocoa production in Ghana, largely reliant on rainfall and undertaken by smallholder farmers, is increasingly endangered by climate change-induced water scarcity. Although supplemental irrigation has been posited as an adaptive measure, its hydrological impacts remain understudied. This current study seeks to bridge this knowledge gap by employing the Soil and Water Assessment Tool (SWAT) to evaluate the hydrological and water resource implications of supplemental irrigation within the Upper Offin sub-basin of Ghana. High-resolution spatial data and field survey inputs were used to model dry period baseline and irrigation scenarios for cocoa farms with gentle slopes (2%). The results reveal that supplemental irrigation from the shallow aquifer can sustainably support irrigation for up to 5% of the cocoa area (4760 ha) without adversely affecting groundwater flow. Extending irrigation to 30% of the cocoa area (28,540 ha) is feasible with minimal reduction in catchment water yield. This study’s novelty lies in integrating high-resolution data with localized management practices to provide actionable insights for balancing cocoa productivity and water sustainability. The findings offer practical recommendations for policymakers, emphasizing that through solar-powered irrigation the shallow groundwater is a pathway to enhance climate resilience of cocoa productivity. Full article

(This article belongs to the Special Issue Sustainable Water Management in Agricultural Irrigation)

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14 pages, 3500 KiB

Open AccessArticle

Taxonomic and Functional Responses of Macroinvertebrates to Hydrological Changes and Invasive Plants in an NW Patagonia Riparian Corridor (Argentina)

by Melina Mauad, Julieta Massaferro, Lyudmila Kamburska and Angela Boggero

Water 2025, 17(13), 1840; https://doi.org/10.3390/w17131840 - 20 Jun 2025

Abstract

This study assessed the taxonomic and functional diversity of aquatic macroinvertebrate communities in Chacabuco stream, a 5500 ha pioneering open conservation ranch of Nahuel Huapi National Park in Argentina, focusing on the effects of seasonal hydrological regimes along a willow-invaded corridor. Sampling was [...] Read more.

This study assessed the taxonomic and functional diversity of aquatic macroinvertebrate communities in Chacabuco stream, a 5500 ha pioneering open conservation ranch of Nahuel Huapi National Park in Argentina, focusing on the effects of seasonal hydrological regimes along a willow-invaded corridor. Sampling was conducted during the spring of 2018 and the summer and spring of 2019, covering high (spring) and low (summer) water levels. Results showed no significant differences in taxonomic diversity between hydrological periods (p = 0.6), and similar taxonomic diversity during the low- and high-water periods of 2019 due to an extreme drought event. Functional diversity varied significantly (p = 0.009) between hydrological periods, and a significant difference in taxonomic diversity between invasive and native plots (p = 0.0001, R = 0.53) was found, while functional diversity revealed less distinction (p = 0.02, R = 0.08). Functional diversity does not follow the same pattern, showing opportunistic taxa such as predators and collectors equally present during both periods, sign of resilience of these FFGs over the others. This pioneering study in the region highlighted the importance of exploring both taxonomic and functional diversity in riparian ecosystems to assess the impact of seasonal hydrological regimes along a willow-invaded corridor and develop a more comprehensive understanding of riparian ecosystem health. Full article

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

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8 pages, 634 KiB

Open AccessArticle

Growth Response of Submerged Macrophyte Vallisneria denseserrulata to Water Depth (Light Intensity) Changes Varies with Sediment Nutrient Level

by Yudan Lin, Jinyang Yu, Honglong Zheng, Xiufeng Zhang, Yali Tang, Ping Zhong, Shi Fu, Xiaolin He, Xiaoqin Yang, Hu He, Jinlei Yu, Erik Jeppesen and Zhengwen Liu

Water 2025, 17(13), 1839; https://doi.org/10.3390/w17131839 - 20 Jun 2025

Abstract

The re-establishment of submerged macrophytes is crucial for the ecological restoration of eutrophic lakes. Water depth (light intensity) and sediment nutrient levels are key factors influencing the growth of these macrophytes. Although their individual impacts have been extensively studied, their interactive effects remain [...] Read more.

The re-establishment of submerged macrophytes is crucial for the ecological restoration of eutrophic lakes. Water depth (light intensity) and sediment nutrient levels are key factors influencing the growth of these macrophytes. Although their individual impacts have been extensively studied, their interactive effects remain unclear. We conducted a two-factor experiment to investigate the interactive effects of different water depths (50 cm and 190 cm) and sediment nutrient levels (fertile and infertile) on the growth and morphological traits of Vallisneria denseserrulata. We found that biomass, relative growth rate, below/above-ground biomass, ramet number, and leaf number significantly increased with decreasing water depth in fertile sediments, while no significant or less pronounced changes occurred for infertile sediments. The absence or weak responses to increased light intensity in infertile sediments are likely due to photoinhibition, which may be alleviated at higher nutrient levels in fertile sediments. Additionally, V. denseserrulata, in adapting to low-light environments (deeper water), increased plant height at the cost of decreased leaf number and below-ground biomass as water depth increased in fertile sediments. Our study demonstrated significant interactive effects between water depth (light intensity) and sediment nutrient levels on the growth and morphological traits of V. denseserrulata, indicating that their response to water depth (light intensity) strongly depends on sediment fertility. Full article

(This article belongs to the Special Issue Protection and Restoration of Freshwater Ecosystems)

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