Water

18 pages, 3775 KiB

Open AccessArticle

Water Storage Capacity of Ordovician Limestone Aquifer and Hydrogeological Response Mechanism of Deep Reinjection in North China

by Jianguo Fan, Weixiao Chen, Xianfeng Tan, Jiancai Sui, Qi Liu, Hongnian Chen, Feng Zhang, Ge Chen and Zhimin Xu

Water 2025, 17(13), 1982; https://doi.org/10.3390/w17131982 (registering DOI) - 1 Jul 2025

Abstract

Mine water treatment and emissions have become important factors that restrict the comprehensive benefits of coal enterprises and local economic development, and the use of the deep well recharge method can address the specific conditions of mine surge water. This paper takes the [...] Read more.

Mine water treatment and emissions have become important factors that restrict the comprehensive benefits of coal enterprises and local economic development, and the use of the deep well recharge method can address the specific conditions of mine surge water. This paper takes the actual situation of coal mine water treatment as an example and innovatively carries out dynamic tests for the Ordovician limestone aquifers deep in the mine. Intermittent reinjection test shows that under the same reinjection time, the water level recovery rate during the intermittent period is fast at first and then slow. Moreover, the recovery speed of the water level buried depth slows down with the increase in the reinjection time, which reveals the characteristics of the water level rising rapidly and recovering quickly during the reinjection of the reservoir. The average formation water absorption index is 420.81 m³/h·MPa. The water level buried depth of the long-term reinjection test showed three stages (rapid rise, slow rise, and stable stages), and the water level buried depth was raised to 1.52 m at its highest. Monitoring data from the surrounding 5 km area showed that reinjection did not affect aquifer water levels, verifying the excellent storage capacity of the deep Ordovician fissure-karst aquifer. The variability of well loss under pumping and injection conditions was comparatively analyzed, and the well loss produced by the recharge test was 4.06 times higher than that of the pumping test, which provided theoretical support for the calculation of hydrogeological parameters to eliminate the influence of well loss. This study deepens the understanding of Ordovician limestone aquifers in deep mine water, providing a reference for cheap mine water treatment and sustainable groundwater management in similar mine areas. Full article

(This article belongs to the Section Hydrogeology)

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25 pages, 3103 KiB

Open AccessArticle

Artificial Intelligence-Based Optimization of Renewable-Powered RO Desalination for Reduced Grid Dependence

by Mohammadreza Najaftomaraei, Mahdis Osouli, Hasan Erbay, Mohammad Hassan Shahverdian, Ali Sohani, Kasra Mazarei Saadabadi and Hoseyn Sayyaadi

Water 2025, 17(13), 1981; https://doi.org/10.3390/w17131981 - 1 Jul 2025

Abstract

Water scarcity and the growing demand for sustainable energy solutions have driven the need for renewable-powered desalination. This study evaluates three scenarios for reverse osmosis (RO) desalination powered by photovoltaic (PV), wind turbine (WT), and hybrid PV–WT systems, aiming to minimize the levelized [...] Read more.

Water scarcity and the growing demand for sustainable energy solutions have driven the need for renewable-powered desalination. This study evaluates three scenarios for reverse osmosis (RO) desalination powered by photovoltaic (PV), wind turbine (WT), and hybrid PV–WT systems, aiming to minimize the levelized costs of electricity (LCOE) and water (LCOW) while reducing grid dependence. The city studied is Zahedan, Iran, which has high potential in renewable energy. A multi-objective optimization approach using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), a popular evolutionary algorithm, is employed to determine the optimal number of PV panels and wind turbines. The results show that the hybrid system outperforms single-source configurations, supplying 34.79 MWh of electricity and 34.19 m³ of desalinated water, while achieving the lowest LCOE (2.73 cent/kWh⁻¹) and LCOW (35.33 cent/m⁻³). The hybrid scenario covers 65.49% of the electricity demand and 58.54% of the water demand, significantly reducing reliance on the grid compared to the PV and WT scenarios. Additionally, it ensures greater energy stability by leveraging the complementary nature of PV and WT. These findings highlight the techno-economic feasibility of hybrid renewable-powered desalination as a cost-effective and sustainable solution. Future research should focus on integrating energy storage to further enhance efficiency and minimize grid dependency. Full article

(This article belongs to the Special Issue Computer Modelling Techniques in Environmental Hydraulics and Water Resource Engineering)

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26 pages, 1025 KiB

Open AccessReview

A Review of Harmful Algal Blooms: Causes, Effects, Monitoring, and Prevention Methods

by Christina M. Brenckman, Meghana Parameswarappa Jayalakshmamma, William H. Pennock, Fahmidah Ashraf and Ashish D. Borgaonkar

Water 2025, 17(13), 1980; https://doi.org/10.3390/w17131980 - 1 Jul 2025

Abstract

Harmful Algal Blooms (HABs) are a growing environmental concern due to their adverse impacts on aquatic ecosystems, human health, and economic activities. These blooms are driven by a combination of factors, including nutrient enrichment, environmental factors, and hydrological conditions, leading to the excessive [...] Read more.

Harmful Algal Blooms (HABs) are a growing environmental concern due to their adverse impacts on aquatic ecosystems, human health, and economic activities. These blooms are driven by a combination of factors, including nutrient enrichment, environmental factors, and hydrological conditions, leading to the excessive growth of algae. HABs produce toxins that threaten aquatic biodiversity, contaminate drinking water, and cause economic losses in fisheries and tourism. The causes of HABs are multifaceted, involving interactions between environmental factors such as temperature, light availability, and nutrient levels. Agricultural runoff, wastewater discharge, and industrial pollution introduce excessive nitrogen and phosphorus into water bodies, fueling bloom formation. Climate change further exacerbates the problem by altering precipitation patterns, increasing water temperatures, and intensifying coastal upwelling events, all of which create favorable conditions for HAB proliferation. This review explores the causes, ecological consequences, and potential mitigation strategies for HABs. Effective monitoring and detection methods, including satellite remote sensing, molecular biotechnology, and artificial intelligence-driven predictive models, offer promising avenues for early intervention. Sustainable management strategies such as nutrient load reductions, bioremediation, and regulatory policies can help mitigate the adverse effects of HABs. Public awareness and community involvement also play a crucial role in preventing and managing HAB events by promoting responsible agricultural practices, reducing waste discharge, and supporting conservation efforts. By examining existing literature and case studies, this study underscores the urgent need for comprehensive and interdisciplinary approaches to regulate HABs. Full article

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

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15 pages, 698 KiB

Open AccessArticle

Basic Research on the Adsorption Capacity and Enhancement of Bamboo Charcoal for the Prevention of Nitrate Groundwater Pollution

by Nur Maisarah Mohamad Sarbani, Hiroyuki Harada, Mitsuru Aoyagi, Jun Nishimoto and Seiichiro Yonemura

Water 2025, 17(13), 1979; https://doi.org/10.3390/w17131979 - 30 Jun 2025

Abstract

Pollution of soil and groundwater by chemical fertilizers is an alarming environmental problem. Both bamboo powder and charcoal are known to adsorb nitrates. This study aimed to recommend an effective method by applying a mixture of chemical fertilizers and bamboo charcoal to soil [...] Read more.

Pollution of soil and groundwater by chemical fertilizers is an alarming environmental problem. Both bamboo powder and charcoal are known to adsorb nitrates. This study aimed to recommend an effective method by applying a mixture of chemical fertilizers and bamboo charcoal to soil to prevent NO₃ leaching through adsorption. Magnesium treatment and hydrogelation were investigated to increase the amount of NO₃ adsorption and improve handling properties, and subsequently, their behavior in soil was examined. The maximum adsorption of nitrate in bamboo charcoal powder (BC) with a particle size of 15 µm or less was 4.44 mg/g. When the BC was treated with magnesium chloride (Mg-BC), the maximum adsorption capacity was 99.09 mg/g. The Langmuir adsorption model fits well for both BC and Mg-BC. When Mg-BC was hydrogelized (Gel-Mg-BC), the Freundlich equation provided a better fit, with the maximum adsorption estimated at 25–30 mg/g. When the soil was mixed with Mg-BC hydrogel and treated with a nitric acid solution, the nitrate concentration in the leachate decreased by approximately 15–60% (depending on the feed concentration) compared to that in the leachate from the soil alone. Full article

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

66 pages, 6945 KiB

Open AccessReview

Towards Resilient Cities: Systematic Review of the Literature on the Use of AI to Optimize Water Harvesting and Mitigate Scarcity

by Victor Martin Maldonado Benitez, Oswaldo Morales Matamoros and Jesús Jaime Moreno Escobar

Water 2025, 17(13), 1978; https://doi.org/10.3390/w17131978 - 30 Jun 2025

Abstract

This article develops a systematic literature review with a focus on the optimization of water harvesting through the use of artificial intelligence (AI) applications. These are framed in the search for sustainable solutions to the growing problem of water scarcity in urban environments. [...] Read more.

This article develops a systematic literature review with a focus on the optimization of water harvesting through the use of artificial intelligence (AI) applications. These are framed in the search for sustainable solutions to the growing problem of water scarcity in urban environments. The analysis is oriented towards urban resilience and smart water management, incorporating interdisciplinary approaches such as systems thinking to understand the complex dynamics involved in water governance. The results indicate a growing trend in the utilisation of AI in various domains, including demand forecasting, leak detection, and catchment infrastructure optimization. Additionally, the findings suggest its application in water resilience modelling and adaptive urban planning. The text goes on to examine the challenges associated with the integration of technology in urban contexts, including the critical aspects of governance and regulation of AI, water consumption, energy and carbon emissions from the use of this technology, as well as the regulation of water management in digital transformation scenarios. The study identifies the most representative patents that combat the problem, and in parallel proposes lines of research aimed at strengthening the water resilience and sustainability of cities. The strategic role of AI as a catalyst for innovation in the transition towards smarter, more integrated and adaptive water management systems is also highlighted. Full article

(This article belongs to the Special Issue Urban Stormwater Harvesting, and Wastewater Treatment and Reuse)

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Graphical abstract

18 pages, 5426 KiB

Open AccessArticle

Correction of Pump Characteristic Curves Integrating Representative Operating Condition Recognition and Affine Transformation

by Yichao Chen, Yongjun Zhao, Xiaomai Li, Chenchen Wu, Jie Zhao and Li Ren

Water 2025, 17(13), 1977; https://doi.org/10.3390/w17131977 - 30 Jun 2025

Abstract

To address the need for intelligent scheduling and model integration under spatiotemporal variability and uncertainty in water systems, this study proposes a hybrid correction method for pump characteristic curves that integrates data-driven techniques with an affine modeling framework. Steady-state data are extracted through [...] Read more.

To address the need for intelligent scheduling and model integration under spatiotemporal variability and uncertainty in water systems, this study proposes a hybrid correction method for pump characteristic curves that integrates data-driven techniques with an affine modeling framework. Steady-state data are extracted through adaptive filtering and statistical testing, and representative operating conditions are identified via unsupervised clustering. An affine transformation is then applied to the factory-provided characteristic equation, followed by parameter optimization using the clustered dataset. Using the Hongze Pump Station along the eastern route of the South-to-North Water Diversion Project as a case study, the method reduced the mean blade angle prediction error from 1.73° to 0.51°, and the efficiency prediction error from 7.32% to 1.30%. The results demonstrate improved model accuracy under real-world conditions and highlight the method’s potential to support more robust and adaptive hydrodynamic scheduling models, contributing to the advancement of sustainable and smart water resource management. Full article

(This article belongs to the Special Issue Advancing Sustainable Hydrological Modelling and Smart Water Resource Management)

35 pages, 3147 KiB

Open AccessArticle

Hybrid Optimization Approaches for Impeller Design in Turbomachinery: Methods, Metrics, and Design Strategies

by Abel Remache, Modesto Pérez-Sánchez, Víctor Hugo Hidalgo and Helena M. Ramos

Water 2025, 17(13), 1976; https://doi.org/10.3390/w17131976 - 30 Jun 2025

Abstract

Optimizing the design of impellers in turbomachinery is crucial for improving its energy efficiency, structural integrity, and hydraulic performance in various engineering applications. This work proposes a novel modular framework for impeller optimization that integrates high-fidelity CFD and FEM simulations, AI-based surrogate modeling, [...] Read more.

Optimizing the design of impellers in turbomachinery is crucial for improving its energy efficiency, structural integrity, and hydraulic performance in various engineering applications. This work proposes a novel modular framework for impeller optimization that integrates high-fidelity CFD and FEM simulations, AI-based surrogate modeling, and multi-objective evolutionary algorithms. A comprehensive analysis of over one hundred recent studies was conducted, with a focus on advanced computational and hybrid optimization techniques, CFD, FEM, surrogate modeling, evolutionary algorithms, and machine learning approaches. Emphasis is placed on multi-objective and data-driven strategies that integrate high-fidelity simulations with metamodels and experimental validation. The findings demonstrate that hybrid methodologies such as combining response surface methodology (RSM), Box–Behnken design (BBD), non-dominated sorting genetic algorithm II (NSGA-II), and XGBoost lead to significant improvements in hydraulic efficiency (up to 6.7%), mass reduction (over 30%), and cavitation mitigation. This study introduces a modular decision-making framework for impeller optimization which considers design objectives, simulation constraints, and the physical characteristics of turbomachinery. Furthermore, emerging trends in open-source tools, additive manufacturing, and the application of deep neural networks are discussed as key enablers for future advancements in both research and industrial applications. This work provides a practical, results-oriented framework for engineers and researchers seeking to enhance the design of impellers in the next generation of turbomachinery. Full article

(This article belongs to the Special Issue Hydraulics and Hydrodynamics in Fluid Machinery, 2nd Edition)

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29 pages, 1219 KiB

Open AccessArticle

Interdisciplinary Evaluation of the Săpânța River and Groundwater Quality: Linking Hydrological Data and Vegetative Bioindicators

by Ovidiu Nasca, Thomas Dippong, Maria-Alexandra Resz and Monica Marian

Water 2025, 17(13), 1975; https://doi.org/10.3390/w17131975 - 30 Jun 2025

Abstract

This study was carried out to fill the present research gap in the study area by assessing water chemistry, potential heavy metal contamination, and the associated health risk evaluation that goes along with it in surface water bodies and groundwater in the NE [...] Read more.

This study was carried out to fill the present research gap in the study area by assessing water chemistry, potential heavy metal contamination, and the associated health risk evaluation that goes along with it in surface water bodies and groundwater in the NE of Maramureș County, near the Tisa River. The main methods we applied were Piper, Ficklin–Caboi, and Gibbs diagrams for determining the water typology and chemistry, the Overall Water Quality Index (OWQI) and vegetation cover to determine the water quality, a contamination index for analyzing the contamination degree, and a human health risk assessment through water ingestion after exposure of children and adults. This article’s main findings specify that waters were characterized and classified into the CaMgHCO₃⁻ dominant category of water type, with precipitation, agricultural, and domestic inputs, related to the Cl⁻ (mean ranging between 1.01–5.65 mg/L) and NO₃⁻ (mean ranging between 2.23–5.52 mg/L) content. The OWQI scores indicated excellent quality, below the critical value, ranging between 0.70 and 6.57. The applied risk assessment indicated that the daily intake of toxins is higher in the case of children than in adults, up to four and five times. The hazard quotient scores, ranging between 0.00093 and 0.248 for adults and between 0.0039 and 1.040 for children, indicated that if consumed, the studied waters can pose potential negative effects on children. Full article

(This article belongs to the Special Issue Water Quality Examination: The Investigation of Heavy Metal Contamination, Nutrients, and Organic Pollutants in Aquatic Environments for an Enhanced Prevention and Purification Process)

15 pages, 2276 KiB

Open AccessArticle

Dual Benefits in Yield Enhancement and Grain Desiccation: Irrigation Coupled with Husk Removal Modulates Grain Moisture Dynamics in Maize

by Jia Gao, Keyu Fa, Shoubing Huang, Pu Wang and Zheng Liu

Water 2025, 17(13), 1974; https://doi.org/10.3390/w17131974 - 30 Jun 2025

Abstract

Grain moisture influences grain number formation during the critical period as well as determining the final grain weight during the grain-filling period in maize (Zea mays L.). To clarify the relationships between grain number, grain weight, and grain moisture dynamics, a 2–year [...] Read more.

Grain moisture influences grain number formation during the critical period as well as determining the final grain weight during the grain-filling period in maize (Zea mays L.). To clarify the relationships between grain number, grain weight, and grain moisture dynamics, a 2–year field experiment in a split-plot design was conducted with two irrigation treatments, well irrigation (WI) and no irrigation (NI), and with four husk removal treatments, including no husk removal as control (H₀) and removal of 1/4 (H_1/4), 2/4 (H_2/4), 3/4 (H_3/4), and 4/4 (H_4/4) of the husk layers, respectively. Husk removal reduced the maize grain number, grain dry weight, and yield, and the reductions were larger under no irrigation (33.4–33.5%) than under well irrigation conditions (27.7–33.2%). By contrast, irrigation increased grain water content by 11.1–13.4% and grain dry weight by 6.5–10.4%, regardless of husk removal. Meanwhile, the interactive effects between irrigation and husk removal were significant in grain water content but not in grain yield, reflecting the larger negative effects of husk removal on maize grain yield. In conclusion, husk plays a crucial role in grain number formation during the critical period and grain weight during the grain-filling period, especially in drought conditions, in relation to the trade-offs between yield enhancement and grain desiccation in maize production. Full article

(This article belongs to the Special Issue Sustainable and Efficient Water Use in the Face of Climate Change)

26 pages, 4988 KiB

Open AccessArticle

Simulation and Optimisation Using a Digital Twin for Resilience-Based Management of Confined Aquifers

by Carlos Segundo Cohen-Manrique, José Luis Villa-Ramírez, Sergio Camacho-León, Yady Tatiana Solano-Correa, Alex A. Alvarez-Month and Oscar E. Coronado-Hernández

Water 2025, 17(13), 1973; https://doi.org/10.3390/w17131973 (registering DOI) - 30 Jun 2025

Abstract

Efficient management of groundwater resources is essential for environmental sustainability. This study introduces the development and application of a digital twin (DT) for confined aquifers to optimise water extraction and ensure long-term sustainability. A resilience-based control model was implemented to manage the Morroa [...] Read more.

Efficient management of groundwater resources is essential for environmental sustainability. This study introduces the development and application of a digital twin (DT) for confined aquifers to optimise water extraction and ensure long-term sustainability. A resilience-based control model was implemented to manage the Morroa Aquifer (Colombia). This model integrated historical, hydrogeological, and climatic data acquired from in-situ sensors and satellite remote sensing. Several heuristic methods were employed to optimise the parameters of the objective function, which focused on managing water extraction in aquifer wells: grid search, genetic algorithms (GA), and particle swarm optimisation (PSO). The results indicated that the PSO algorithm yielded the lowest root mean square error (RMSE), achieving an optimal extraction rate of 8.3 l/s to maintain a target dynamic water level of 58.5 m. Furthermore, the model demonstrated the unsustainability of current extraction rates, even under high-rainfall conditions, highlighting the necessity for revising existing water extraction strategies to safeguard aquifer sustainability. To showcase its practical functionality, a DT prototype was deployed in a well within the Morroa piezometric network (Sucre, Colombia). This prototype utilised an ESP32 microcontroller and various sensors (DS18B20, SKU-SEN0161, SKU-DFR0300, SEN0237-A) to monitor water level, pH, dissolved oxygen, and temperature. The implementation of this DT proved to be a crucial tool for the efficient management of water resources. The proposed methodology provided key information to support decision-making by environmental management entities, thereby optimising monitoring and control processes. Full article

(This article belongs to the Special Issue Integrated Approaches to Water Resources and Environmental Management: Innovations in Simulation and Impact Assessment)

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14 pages, 3326 KiB

Open AccessArticle

Performance Study of a Sewage Collection Device for Seawater Pond Recirculating Aquaculture System

by Zhixiang Cao, Zhongming Huang, Zhilong Xu and Yu Zhang

Water 2025, 17(13), 1972; https://doi.org/10.3390/w17131972 - 30 Jun 2025

Abstract

This study addresses the challenge of solid pollutant collection in seawater pond recirculating aquaculture by designing a novel funnel-shaped sewage collection device and evaluating its performance through Computational Fluid Dynamics (CFD) simulations and experimental validation. The results reveal that the device forms a [...] Read more.

This study addresses the challenge of solid pollutant collection in seawater pond recirculating aquaculture by designing a novel funnel-shaped sewage collection device and evaluating its performance through Computational Fluid Dynamics (CFD) simulations and experimental validation. The results reveal that the device forms a rotating flow field, effectively concentrating solid particles in a central low-velocity zone with a diameter of approximately 2 m when the sewage pump is inactive. The optimal bottom dip angle for efficient sewage discharge is determined to be 21 degrees, with flow velocities near the outlet ranging between 0.031 and 0.062 m per second, sufficient to mobilize particles smaller than 5 mm. Prototype testing demonstrates a solid pollutant collection efficiency of 75.7 percent, confirming the device’s practical effectiveness in improving water quality and operational performance. This research offers a validated and efficient solution for solid waste management in aquaculture systems. Full article

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37 pages, 1853 KiB

Open AccessReview

Remote-Sensing Indicators and Methods for Coastal-Ecosystem Health Assessment: A Review of Progress, Challenges, and Future Directions

by Lili Zhao, Xuncheng Fan and Shihong Xiao

Water 2025, 17(13), 1971; https://doi.org/10.3390/w17131971 - 30 Jun 2025

Abstract

This paper systematically reviews the progress of remote-sensing technology in coastal-ecosystem health assessment. Coastal ecosystems, as transitional zones between land and ocean, play vital roles in maintaining biodiversity, carbon sequestration, and coastal protection, but currently face severe challenges from climate change and human [...] Read more.

This paper systematically reviews the progress of remote-sensing technology in coastal-ecosystem health assessment. Coastal ecosystems, as transitional zones between land and ocean, play vital roles in maintaining biodiversity, carbon sequestration, and coastal protection, but currently face severe challenges from climate change and human activities. Remote-sensing technology, with its capability for large-scale, long time-series observations, has become a key tool for coastal-ecosystem health assessment. This paper analyzes the technical characteristics and advantages of optical remote sensing, radar remote sensing, and multi-source data fusion in coastal monitoring; constructs a health-assessment framework that includes water-quality indicators, vegetation and ecosystem function indicators, and human disturbance and landscape change indicators; discusses the application of advanced technologies from traditional methods to machine learning and deep learning in data processing; and demonstrates the role of multi-temporal analysis in revealing coastal-ecosystem change trends through typical case studies of mangroves, salt marshes, and coral reefs. Research indicates that, despite the enormous potential of remote-sensing technology in coastal monitoring, it still faces challenges such as sensor limitations, environmental interference, and data processing and validation. Future development should focus on advanced sensor technology, platform innovation, data-processing method innovation, and multi-source data fusion, while strengthening the effective integration of remote-sensing technology with management practices to provide scientific basis for the protection and sustainable management of coastal ecosystems. Full article

(This article belongs to the Special Issue Remote Sensing in Coastal Water Environment Monitoring)

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28 pages, 3693 KiB

Open AccessArticle

Hydraulic Scale Modeling of Pressurized Sediment Laden Flow

by Kalekirstos G. Gebrelibanos, Kaspar Vereide, Sirak A. Weldemariam, Asli Bor, Asfafaw H. Tesfay and Leif Lia

Water 2025, 17(13), 1970; https://doi.org/10.3390/w17131970 - 30 Jun 2025

Abstract

In hydropower tunnel systems, unlined pressurized tunnels in competent rock are commonly used for cost-effective construction. Incorporating pressurized sand traps at the downstream end of these tunnels can increase plant capacity and improve energy efficiency. The present work focuses on optimizing the performance [...] Read more.

In hydropower tunnel systems, unlined pressurized tunnels in competent rock are commonly used for cost-effective construction. Incorporating pressurized sand traps at the downstream end of these tunnels can increase plant capacity and improve energy efficiency. The present work focuses on optimizing the performance of existing pressurized sand traps. Hydraulic scale models were developed and tested at the Hydraulic Laboratory of NTNU, Within the 960 MW Tonstad Hydropower Plant in southern Norway as a case study. This study compares 1:1 velocity/sediment scaling with Froude scaling through physical experiments, analyzing velocity profiles via Particle Image Velocimetry (PIV) and sediment trap efficiency. Results show that Froude scaling, combined with geometric sediment scaling, provides superior accuracy in trap efficiency scaling across varying factors. However, in many practical hydropower applications, the large scaling factor required for laboratory models results in very small model sediments, leading to cohesion limitations. In such cases, Froude scaling may not be feasible. The 1:1 scaling method provides a conservative alternative. Hence, for practical applications, 1:1 scaling may be more cost-effective and sufficient for designing pressurized sand traps. This study emphasizes the importance of accounting for unscaled parameters and flow phenomena in hydraulic model design. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

25 pages, 1171 KiB

Open AccessArticle

Climate and Groundwater Depth Relationships in Selected Breede Gouritz Water Management Area Subregions Between 2009 and 2020

by Monica M. Correia, Thokozani Kanyerere, Nebo Jovanovic, Jacqueline Goldin and Moyin John

Water 2025, 17(13), 1969; https://doi.org/10.3390/w17131969 - 30 Jun 2025

Abstract

Groundwater resources are changing under the current climate change trajectory. Mitigation and adaptation measures include understanding the inter-working relationships among all climate variables and water resources, specifically groundwater, since it has less direct impacts than surface waters due to its nature. The Breede [...] Read more.

Groundwater resources are changing under the current climate change trajectory. Mitigation and adaptation measures include understanding the inter-working relationships among all climate variables and water resources, specifically groundwater, since it has less direct impacts than surface waters due to its nature. The Breede Gouritz Water Management Area provides an interesting platform to assess these interdependencies, since they have not been assessed before. To assess any underlying dependencies, a multivariate analysis of independent variables including monthly average temperature, summative precipitation, and average evapotranspiration, and a dependent monthly variable, i.e., average groundwater depth, from 14 boreholes was conducted. Moreover, a groundwater depth near-future prediction for each relevant borehole was made. The Multiple Linear Regression model was chosen as the appropriate one since it is cost- and time-effective, entry-level, easy to interpret, and provides a simple and basic understanding of the relationship dependencies. The Kruskal-Wallis test was also performed to elaborate on findings from the Multiple Linear Regression models. Simple linear models incorporating independent and dependent variables can only account for up to 41.7% of the variation in groundwater depth. Groundwater depth is mainly influenced by temperature and evapotranspiration and is expected to be lower for ten dependent variables. The more arid regions in the study area can expect groundwater depth to lower soon and need to use alternative water resources. The temperate west of the study area could expect more favorable outcomes regarding groundwater depth in the near future. Incorporating more variables and using a multi-modal approach to combat non-linear relationships is recommended in future. Full article

(This article belongs to the Special Issue Artificial Intelligence for Sustainable Management of Groundwater Resources: New Developments, Challenges and Untapped Potentials)

21 pages, 4553 KiB

Open AccessArticle

A Quantitative Assessment of the Impacts of Land Use and Natural Factors on Water Quality in the Red River Basin, China

by Changming Chen, Xingcan Chen, Hong Tang, Xuekai Feng, Yu Han, Yuan He, Liqin Yan, Yangyidan He, Liling Yang and Kejian He

Water 2025, 17(13), 1968; https://doi.org/10.3390/w17131968 - 30 Jun 2025

Abstract

The quality of water in the Red River is a complex interplay between human-induced changes and inherent natural variables. This research utilized the snapshot sampling approach, garnering water quality data from 45 sampling sites in the Red River and crafting 24 environmental indicators [...] Read more.

The quality of water in the Red River is a complex interplay between human-induced changes and inherent natural variables. This research utilized the snapshot sampling approach, garnering water quality data from 45 sampling sites in the Red River and crafting 24 environmental indicators related to land use and inherent natural determinants at the catchment scale. Through Spearman rank correlation and redundancy analyses, relationships among land use, natural variables, and water quality were elucidated. Our variance partitioning revealed differentiated impacts of land use and natural factors on water quality. Pivotal findings indicated superior water quality in the Red River, driven mainly by land use dynamics, which showed a distinct geomorphic gradient. Specific land use attributes, like cropland patch density, grassland’s largest patch index, and urban metrics, were pivotal in explaining variations in parameters such as total nitrogen, ammonia, and temperature. Notably, the configuration of land use had a more profound influence on water quality than merely its components. In terms of natural influences, while topography played a dominant role in shaping water quality, other factors like soil and weather had marginal impacts. Elevation was notably linked with metrics like total phosphorus and suspended solids, whereas precipitation and slope significantly determined electrical conductivity and chlorophyll-a models. In sum, incorporating both land use configurations and natural determinants offers a more comprehensive understanding of water quality disparities in the Red River’s ecosystem. For holistic water quality management, the focus should not only be on the major contributors like croplands and urban areas but also on underemphasized areas like grasslands. Tweaking cropland distribution, recognizing the intertwined nature of land use and natural elements, and tailoring land management based on topographical variations are essential strategies moving forward. Full article

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9 pages, 1246 KiB

Open AccessBrief Report

The Role of Abundant Organic Macroaggregates in Planktonic Metabolism in a Tropical Bay

by Marcelo Friederichs Landim de Souza and Guilherme Camargo Lessa

Water 2025, 17(13), 1967; https://doi.org/10.3390/w17131967 - 30 Jun 2025

Abstract

Abundant large organic aggregates, which form mucous webs up to a few decimeters in length, have been observed in Baía de Todos os Santos (BTS), northeastern Brazil. This communication presents preliminary results from field (February 2015) and laboratory (June 2015) experiments that aimed [...] Read more.

Abundant large organic aggregates, which form mucous webs up to a few decimeters in length, have been observed in Baía de Todos os Santos (BTS), northeastern Brazil. This communication presents preliminary results from field (February 2015) and laboratory (June 2015) experiments that aimed to determine preliminary values for respiration and near-maximum photosynthesis and the impact of macroaggregates on respiration rates. The experiments included the determination of respiration in controls, with the mechanical removal and addition of macroaggregates. The field experiment during a flood tide presented the lowest respiration rate (−7.0 ± 0.7 µM L⁻¹ d⁻¹), average net primary production (8.9 ± 4.5 µM L⁻¹ d⁻¹), and gross primary production (16.0 ± 10 µM L⁻¹ d⁻¹), with a ratio of gross primary production to respiration of 2.3. The control experiments during an ebb tide showed a mean respiration rate of 8.7 ± 2.3 µM L⁻¹ d⁻¹, whereas, after macroaggregate removal, this was 9.5 ± 4.5 µM L⁻¹ d⁻¹. In the laboratory experiments, the control sample respiration rate of 18.4 ± 1.4 µM L⁻¹ d⁻¹ was slightly increased to 20.6 ± 0.1 µM L⁻¹ d⁻¹ after aggregate removal. The addition of aggregates to the control sample increased the respiration rate by approximately 3-fold, to 56.5 ± 4.8 µM L⁻¹ d⁻¹. These results indicate that macroaggregates could have an important role in pelagic and benthic respiration, as well as in the whole bay’s metabolism. Full article

(This article belongs to the Special Issue Biogeochemical Cycles in Vulnerable Coastal and Marine Environment)

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20 pages, 1045 KiB

Open AccessArticle

Ancestral Knowledge and River Systems: Pathways to Sustainability, Peace, and Community Resilience

by Ana Carolina Torregroza-Espinosa, Nayerlis Guzmán, Juan Camilo Restrepo, Ana Cristina De la Parra-Guerra, Mónica Acuña Rodríguez, David Alejandro Blanco Álvarez and Rebecca Stumpf

Water 2025, 17(13), 1966; https://doi.org/10.3390/w17131966 - 30 Jun 2025

Abstract

This study offers a unique perspective on the role of ancestral knowledge in sustainable river management and community resilience. Specifically, this study draws on (1) a systematic literature review using the PRISMA methodology and (2) a qualitative analysis of community surveys conducted with [...] Read more.

This study offers a unique perspective on the role of ancestral knowledge in sustainable river management and community resilience. Specifically, this study draws on (1) a systematic literature review using the PRISMA methodology and (2) a qualitative analysis of community surveys conducted with 39 women in Zambrano, Colombia, to examine the impact of ancestral knowledge on sustainability, peace promotion, and community development. The findings highlight that women’s traditional water management practices significantly contribute to environmental sustainability, conflict resolution, and social cohesion. Women play a central role in transmitting and applying ancestral water knowledge, yet they remain marginalized in decision-making processes, often facing barriers to participation in governance structures. Finally, these findings proposed strategies for integrating ancestral knowledge into sustainable resource management policies. This study underscores the urgent need for legal recognition, intercultural dialogue, gender-inclusive governance, and educational programs to ensure the transmission and adaptation of these practices in contemporary contexts. Integrating ancestral knowledge into water management policies is essential for strengthening gender equity, community resilience, and fostering governance models that harmoniously combine traditional and scientific approaches. Full article

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

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31 pages, 5386 KiB

Open AccessArticle

Assessing the Sensitivity of Sociotechnical Water Distribution Systems to Uncertainty in Consumer Behaviors: Social Distancing and Demand Changes During the COVID-19 Pandemic

by Shimon Komarovsky, Brent Vizanko, Emily Berglund and Avi Ostfeld

Water 2025, 17(13), 1965; https://doi.org/10.3390/w17131965 - 30 Jun 2025

Abstract

Water distribution systems (WDSs) exhibit intricate, nonlinear behaviors shaped by both internal dynamics and external influences. The incorporation of additional models, such as contamination or population models, further increases their complexity. This study investigated WDSs under various uncertainty scenarios to enhance system stability, [...] Read more.

Water distribution systems (WDSs) exhibit intricate, nonlinear behaviors shaped by both internal dynamics and external influences. The incorporation of additional models, such as contamination or population models, further increases their complexity. This study investigated WDSs under various uncertainty scenarios to enhance system stability, robustness, and control. In particular, we built upon prior research by exploring an Agent-Based Modeling (ABM) framework integrated within a WDS, focusing on three types of uncertainties: (1) adjustments to existing probabilistic parameters, (2) variations in agent movement across network nodes, and (3) changes in agent distributions across different node types. We conducted our analysis using the virtual city of Micropolis as a testbed. Our findings indicate that while the system remains resilient to uncertainties in predefined probabilistic parameters, substantial and often nonlinear effects arise when uncertainties are introduced in agent mobility and distribution patterns. These results emphasize the significance of understanding how WDSs respond to external behavioral dynamics, which is essential for managing real-world challenges, such as pandemics or shifts in urban behavior. This study underscores the necessity for further research into broader uncertainty categories and emergent effects to enhance WDS modeling and inform decision-making. Full article

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

18 pages, 11466 KiB

Open AccessArticle

Water Footprint Through an Analysis of Water Conservation Policy: Comparative Analysis of Water-Intensive and Water-Efficient Crops Using IoT-Driven ML Models

by Mahdi Moudi, Dan Xie, Lin Cao, Hehuai Zhang, Yunchu Zhang and Bahador Bahramimianrood

Water 2025, 17(13), 1964; https://doi.org/10.3390/w17131964 - 30 Jun 2025

Abstract

Although economic profitability and food security often outweigh water conservation priorities in arid and semi-arid regions, this study investigates irrigation practices by evaluating water footprint and economic feasibility through a comparative analysis of water-intensive and water-efficient crops. In this context, an optimal irrigation [...] Read more.

Although economic profitability and food security often outweigh water conservation priorities in arid and semi-arid regions, this study investigates irrigation practices by evaluating water footprint and economic feasibility through a comparative analysis of water-intensive and water-efficient crops. In this context, an optimal irrigation disparity framework integrated with Internet of Things (IoT) and Machine Learning (ML) mechanisms is proposed to evaluate the effectiveness of water conservation, thereby assessing the potential for enhancing economic profitability. IoT-enabled components are employed to monitor real-time environmental—soil moisture, temperature, and weather—conditions between March and November 2023. This data is processed using a hybrid modeling approach that integrates KNN, GBT, and LSTM algorithms to predict both the duration of cultivation and the water requirements. Finally, the predicted parameters are incorporated into a multi-objective framework aimed at minimizing the disparity in water allocation per net benefit. The final results indicate that saffron required substantially less water—ranging from (19.87 to 28.65 ∗ 10⁶ m³)—compared to watermelon, which consumed (34.61 to 47.07 ∗ 10⁶ m³), while achieving a higher average net profit (33 ∗ 10⁹ IRR) relative to watermelon (31 ∗ 10⁹ IRR). Moreover, saffron consistently approached optimal values across disparity-based objective functions, averaging (0.404). These findings emphasize the dual advantages of saffron as a value-added, water-efficient crop in achieving substantial water conservation while enhancing profitability, offering actionable insights for authorities to incentivize water-efficient crop adoption through subsidies, market mechanisms, or regulatory frameworks. These strategies operationalize technical insights into actionable pathways for balancing food security, economic growth, and environmental resilience. Full article

(This article belongs to the Special Issue Coupled Numerical Modeling of Groundwater Flow and Surface Water Interactions)

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