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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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26 pages, 8954 KB  
Article
Deep Learning Ensemble for Flood Probability Analysis
by Fred Sseguya and Kyung-Soo Jun
Water 2024, 16(21), 3092; https://doi.org/10.3390/w16213092 - 29 Oct 2024
Cited by 3 | Viewed by 2776
Abstract
Predicting flood events is complex due to uncertainties from limited gauge data, high data and computational demands of traditional physical models, and challenges in spatial and temporal scaling. This research innovatively uses only three remotely sensed and computed factors: rainfall, runoff and temperature. [...] Read more.
Predicting flood events is complex due to uncertainties from limited gauge data, high data and computational demands of traditional physical models, and challenges in spatial and temporal scaling. This research innovatively uses only three remotely sensed and computed factors: rainfall, runoff and temperature. We also employ three deep learning models—Feedforward Neural Network (FNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM)—along with a deep neural network ensemble (DNNE) using synthetic data to predict future flood probabilities, utilizing the Savitzky–Golay filter for smoothing. Using a hydrometeorological dataset from 1993–2022 for the Nile River basin, six flood predictors were derived. The FNN and LSTM models exhibited high accuracy and stable loss, indicating minimal overfitting, while the CNN showed slight overfitting. Performance metrics revealed that FNN achieved 99.63% accuracy and 0.999886 ROC AUC, CNN had 95.42% accuracy and 0.893218 ROC AUC, and LSTM excelled with 99.82% accuracy and 0.999967 ROC AUC. The DNNE outperformed individual models in reliability and consistency. Runoff and rainfall were the most influential predictors, while temperature had minimal impact. Full article
(This article belongs to the Special Issue Machine Learning Methods for Flood Computation)
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20 pages, 8443 KB  
Article
Inversion Model for Permeability Coefficient Based on Random Forest–Secretary Bird Optimization Algorithm: Case Study of Lower Reservoir of C-Pumped Storage Power Station
by Zekai Ma, Zhenzhong Shen and Jiangyin Yang
Water 2024, 16(21), 3096; https://doi.org/10.3390/w16213096 - 29 Oct 2024
Cited by 3 | Viewed by 1514
Abstract
The geological complexity of the karst regions presents significant challenges, with the permeability coefficient being a critical parameter for accurately analyzing seepage behavior in hydraulic engineering projects. To overcome the limitations of traditional inversion methods, which often exhibit low computational efficiency, poor accuracy, [...] Read more.
The geological complexity of the karst regions presents significant challenges, with the permeability coefficient being a critical parameter for accurately analyzing seepage behavior in hydraulic engineering projects. To overcome the limitations of traditional inversion methods, which often exhibit low computational efficiency, poor accuracy, and instability, this study utilizes a finite-element forward model and orthogonal experimental design to establish a sample set for permeability-coefficient inversion. A surrogate model for seepage calculation based on the Random Forest (RF) algorithm is subsequently developed. Furthermore, the Secretary Bird Optimization Algorithm (SBOA) is incorporated to propose an intelligent RF–SBOA inversion method for permeability-coefficient estimation, which is validated through a case study of the C-pumped storage power station. The results demonstrate that the RF model’s predictions for water levels at four boreholes closely align with the measured data, outperforming models such as CART, BP, and SVR. The SBOA effectively identifies the optimal geological permeability coefficient, with the borehole water-level inversion achieving a maximum relative error of only 0.128%, which meets the accuracy requirements for engineering applications. Additionally, the computed distribution of the natural seepage field is consistent with the typical distribution patterns observed in mountain seepage systems. During the normal water-storage phase, both the calculated seepage flow and gradient comply with engineering standards, while the seepage-field distribution aligns with empirical observations. This inversion model provides a rapid and accurate method for estimating the permeability coefficient of strata in the project area, with potential applicability to permeability inversion in other engineering geology contexts, thus demonstrating considerable practical value for engineering applications. Full article
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19 pages, 3110 KB  
Article
The Financial Model for Water and Sanitation Services in Portugal: Lessons from Decades of Subsidies and Questionable Public Policies
by Rui Cunha Marques, Pedro Simões and Eduardo Marques
Water 2024, 16(21), 3087; https://doi.org/10.3390/w16213087 - 28 Oct 2024
Cited by 3 | Viewed by 2986
Abstract
Despite the billions of euros used as subsidies over recent decades, Portugal’s water sector continues to struggle, being characterized by significant inefficiencies and differences between high- and low-performing water and sanitation services (WSSs). Current subsidy policies lack transparency and are not linked to [...] Read more.
Despite the billions of euros used as subsidies over recent decades, Portugal’s water sector continues to struggle, being characterized by significant inefficiencies and differences between high- and low-performing water and sanitation services (WSSs). Current subsidy policies lack transparency and are not linked to performance results, undermining efforts to promote efficiency and sustainability in both environmental and financial dimensions. To address these issues, this article highlights relevant aspects to be taken into account in the redefinition of funding allocation in the Portuguese WSS sector. By implementing performance-based criteria for subsidy allocation and prioritization, regardless of the identity of beneficiaries or providers, we aim to instigate accountability and efficiency in this process. The analysis draws on empirical data to highlight the shortcomings of existing practices and demonstrates the potential benefits of adopting the “user-pays” principle. This principle is able to improve the definition of tariffs aiming for full cost recovery, while still providing for disadvantaged and vulnerable customers through social tariffs or assistance programs. Key findings indicate that coordinated efforts among government agencies, regulators, public and private utilities, and municipalities are essential to develop and promote effective financing strategies. This stakeholder’s cooperation is essential for managing the urban water cycle sustainably and addressing the sector’s long-term challenges. This research implies that a strategic shift in subsidy allocation is required, to develop accountability, efficiency, and equity in the WSS sector. The allocation of financial resources must be better justified to enhance overall performance in the sector. Full article
(This article belongs to the Special Issue Review Papers of Urban Water Management 2024)
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14 pages, 2198 KB  
Review
The Impact of Nanobubble Gases in Enhancing Soil Moisture, Nutrient Uptake Efficiency and Plant Growth: A Review
by Yeganeh Arablousabet and Arvydas Povilaitis
Water 2024, 16(21), 3074; https://doi.org/10.3390/w16213074 - 27 Oct 2024
Cited by 9 | Viewed by 5963
Abstract
Nanobubble (NB) technology in agriculture has received increased interest due to its potential to promote soil moisture retention and plant development. Therefore, this review investigates the impact of various types of NBs—such as oxygen, carbon dioxide, and air—on soil and plant systems. Various [...] Read more.
Nanobubble (NB) technology in agriculture has received increased interest due to its potential to promote soil moisture retention and plant development. Therefore, this review investigates the impact of various types of NBs—such as oxygen, carbon dioxide, and air—on soil and plant systems. Various studies revealed that nanobubble-saturated water (NBSW) increases moisture retention, microbial activity, and nutrient absorption, which contribute to better plant development. However, there are still gaps in understanding the specific roles of different gases regarding their stability, interactions with soil, and long-term agricultural impacts. This review aims to combine previous research by focusing on various types of NBs impact on soil moisture, water quality, and nutrient retention. Challenges include the quick dissolution of particular gases, limited field studies, and scalability. The analysis showed that despite these challenges, NBs have potential for enhancing agriculture by improving soil structure and crop yield. More study is needed to maximize their application, particularly in determining the most effective gas types and concentrations for certain agricultural areas. Full article
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31 pages, 14974 KB  
Article
Defining and Mitigating Flow Instabilities in Open Channels Subjected to Hydropower Operation: Formulations and Experiments
by Miguel Tavares, Modesto Pérez-Sánchez, Oscar E. Coronado-Hernández, Alban Kuriqi and Helena M. Ramos
Water 2024, 16(21), 3069; https://doi.org/10.3390/w16213069 - 26 Oct 2024
Viewed by 1950
Abstract
A thorough literature review was conducted on the effects of free surface oscillation in open channels, highlighting the risks of the occurrence of positive and negative surge waves that can lead to overtopping. Experimental analyses were developed to focus on the instability of [...] Read more.
A thorough literature review was conducted on the effects of free surface oscillation in open channels, highlighting the risks of the occurrence of positive and negative surge waves that can lead to overtopping. Experimental analyses were developed to focus on the instability of the flow due to constrictions, gate blockages, and the start-up and shutdown of hydropower plants. A forebay at the downstream end of a tunnel or canal provides the right conditions for the penstock inlet and regulates the temporary demand of the turbines. In tests with a flow of 60 to 100 m3/h, the effects of a gradually and rapidly varying flow in the free surface profile were analyzed. The specific energy and total momentum are used in the mathematical characterization of the boundaries along the free surface water profile. A sudden turbine stoppage or a sudden gate or valve closure can lead to hydraulic drilling and overtopping of the infrastructure wall. At the same time, a PID controller, if programmed appropriately, can reduce flooding by 20–40%. Flooding is limited to 0.8 m from an initial amplitude of 2 m, with a dissipation wave time of between 25 and 5 s, depending on the flow conditions and the parameters of the PID characteristics. Full article
(This article belongs to the Section Hydraulics and Hydrodynamics)
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15 pages, 5672 KB  
Article
Sustainability of Groundwater Exploitation Under Climate Change Scenarios in a Mountainous Area of South Korea
by Soyoung Woo, Wonjin Kim, Sun Woo Chang, Min-Gyu Kim and Il-Moon Chung
Water 2024, 16(21), 3065; https://doi.org/10.3390/w16213065 - 25 Oct 2024
Viewed by 1602
Abstract
The excessive extraction of groundwater is a globally significant issue, as it can lead to the permanent loss of groundwater system sustainability. Sustainable groundwater requires development that appropriately balances the needs of both humans and the environment. In this study, the exploitable groundwater [...] Read more.
The excessive extraction of groundwater is a globally significant issue, as it can lead to the permanent loss of groundwater system sustainability. Sustainable groundwater requires development that appropriately balances the needs of both humans and the environment. In this study, the exploitable groundwater (EGW) of the So-Yang-gang Dam (SYD) Basin was estimated based on simulated groundwater recharge rates using SWAT, and the sustainability of future groundwater development was evaluated under different climate change scenarios. The EGW in each sub-watershed of the SYD was estimated to range from 60 to 240 mm/year, with higher values in the upstream watersheds. A sustainability index (SI) was evaluated, ranging from 0.56 to 1.0 across various GCMs. The analysis revealed that uniform EGW across a watershed is overestimated value in sub-watersheds with low recharge rates, potentially accelerating groundwater depletion in those areas. Thus, a flexible EGW estimation approach is essential to balance groundwater conservation with human water demands. Full article
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17 pages, 3369 KB  
Article
Seasonal Variations in the Thermal Stratification Responses and Water Quality of the Paldang Lake
by Ju Yeon Son, Hye Jin Han, Yong-Chul Cho, Taegu Kang and Jong Kwon Im
Water 2024, 16(21), 3057; https://doi.org/10.3390/w16213057 - 25 Oct 2024
Cited by 2 | Viewed by 2471
Abstract
We evaluated the thermal and chemical stratifications of Paldang Lake using Schmidt’s stability index (SSI) and the chemical stratification index (IC-i) with weekly data from 2013 to 2022. The temporal trends of stratification were analyzed alongside correlations with meteorological, hydrological, and water quality [...] Read more.
We evaluated the thermal and chemical stratifications of Paldang Lake using Schmidt’s stability index (SSI) and the chemical stratification index (IC-i) with weekly data from 2013 to 2022. The temporal trends of stratification were analyzed alongside correlations with meteorological, hydrological, and water quality variables. Thermal stratification intensified with rising air temperature and sunshine duration, while hydrological factors like discharge and retention time affected SSI during periods with less than five days of water retention. During summer, fewer occurrences of intense rainfall or early rainfall before August led to stronger stratification. In fall, nutrient influx from external sources during summer stimulated algal growth, increasing Chlorophyll-α (Chl-α) concentrations. Summer rainfall had a significant impact on the strength and duration of stratification in Paldang Lake. Annual rainfall patterns and subsequent changes in discharge were key factors affecting the physical environment of the lake, which in turn determined water quality and the extent of algal blooms. We provide insights into the seasonal stratification and water quality variations in temperate river-type reservoirs like Paldang Lake. SSI and IC-i from this research can be applied to understand stratification and mixing dynamics in other lakes. Full article
(This article belongs to the Section Water Quality and Contamination)
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26 pages, 5657 KB  
Review
Application of Metal–Organic Framework-Based Composite Materials for Photodegradation of Dye Pollutants in Wastewater
by Farzaneh Mahmoudi and Leonidas G. Bachas
Water 2024, 16(21), 3051; https://doi.org/10.3390/w16213051 - 24 Oct 2024
Cited by 12 | Viewed by 4056
Abstract
Water pollution is one of the main challenges that severely affects human health and aquatic ecosystems. Chemical pollutants, including industrial waste, agricultural runoff, and clinical sources, can contaminate water. Photocatalytic processes present clean, renewable, and efficient techniques for degrading organic contaminants in wastewater. [...] Read more.
Water pollution is one of the main challenges that severely affects human health and aquatic ecosystems. Chemical pollutants, including industrial waste, agricultural runoff, and clinical sources, can contaminate water. Photocatalytic processes present clean, renewable, and efficient techniques for degrading organic contaminants in wastewater. Metal–organic frameworks (MOFs) are one of the more efficient materials in wastewater remediation due to their significantly high surface area and tunable structures. This review summarizes the development of novel composite materials based on MOFs for the photocatalytic decomposition of dye contaminants in wastewater. Different synthesis methods of MOFs and composite materials are explored. Several strategies for enhancing the photocatalytic activity of MOFs are discussed. Photocatalytic reaction conditions and suggested mechanisms are summarized, particularly for eliminating dye contaminants using MOF-based composite materials. The designed composite materials demonstrate improved stability and photocatalytic activity. This review provides strategies for designing MOF-based composite materials and improving their efficiency and stability for the photocatalytic elimination of dye pollutants in wastewater. Additionally, the review addresses challenges in advancing MOF-based composite materials. Full article
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15 pages, 4796 KB  
Article
Spatial Distribution, Leaching Characteristics, and Ecological and Health Risk Assessment of Potential Toxic Elements in a Typical Open-Pit Iron Mine Along the Yangzi River
by Yifan Zeng, Zuxin Xu and Bin Dong
Water 2024, 16(21), 3017; https://doi.org/10.3390/w16213017 - 22 Oct 2024
Cited by 2 | Viewed by 1140
Abstract
Potential toxic elements (PTEs) pollution in the soil of abandoned open-pit mines can lead to great ecological risk to the areas around the mining districts. This study selected a typical abandoned open-pit iron mine along the Yangzi River in southeast China to investigate [...] Read more.
Potential toxic elements (PTEs) pollution in the soil of abandoned open-pit mines can lead to great ecological risk to the areas around the mining districts. This study selected a typical abandoned open-pit iron mine along the Yangzi River in southeast China to investigate the spatial distribution, leaching characteristics, and ecological and health risk of the soil PTEs (As, Pb, Cd, Ni, Cr, Cu, and Zn). Leaching tests and sequential extraction were applied to study the migration of PTEs under the condition of rainfall. Different risk assessment methods were used to analyze the pollution and ecological risk of PTEs. The contents of As and Cu exceeded the background value of the Chinese soil guideline, with average contents of 50.71 ± 1.59 and 197.47 ± 16.09, respectively. The leaching test and sequential extraction indicated that sites 8 and 9 posed the greatest risk of PTE migration. According to the map of the Nemerow integrated pollution index (NIPI), the pollution level of the middle bare area of the study area was the highest, and Cu possessed the highest pollution index (PI) of 3.92. The average geo-accumulation index (Igeo) of As and Cu was between 1 and 2, reaching the pollution level of moderately contaminated. The average potential ecological risk coefficient (Ei) of As was the highest, and the contributions of As, Cu, and Cd to the potential ecological risk of the whole study area were 46.7%, 29.7%, and 14.3%, respectively. The range of the hazard index (HI) and the range of the As carcinogenic risk (CRAs) of all the sampling sites for children were 1.30–3.94 and 2.19 × 10−4–7.20 × 10−4, and As accounted for more than 85% of the total noncarcinogenic risk, indicating that the comprehensive pollution of PTEs in the study area posed great carcinogenic and noncarcinogenic risks to children. This study can be a proper reference for the subsequent recovery methods and environmental management of the whole mining area. Full article
(This article belongs to the Special Issue Soil and Groundwater Quality and Resources Assessment)
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36 pages, 19498 KB  
Article
Advancing SWAT Model Calibration: A U-NSGA-III-Based Framework for Multi-Objective Optimization
by Huihui Mao, Chen Wang, Yan He, Xianfeng Song, Run Ma, Runkui Li and Zheng Duan
Water 2024, 16(21), 3030; https://doi.org/10.3390/w16213030 - 22 Oct 2024
Cited by 5 | Viewed by 2668
Abstract
In recent years, remote sensing data have revealed considerable potential in unraveling crucial information regarding water balance dynamics due to their unique spatiotemporal distribution characteristics, thereby advancing multi-objective optimization algorithms in hydrological model parameter calibration. However, existing optimization frameworks based on the Soil [...] Read more.
In recent years, remote sensing data have revealed considerable potential in unraveling crucial information regarding water balance dynamics due to their unique spatiotemporal distribution characteristics, thereby advancing multi-objective optimization algorithms in hydrological model parameter calibration. However, existing optimization frameworks based on the Soil and Water Assessment Tool (SWAT) primarily focus on single-objective or multiple-objective (i.e., two or three objective functions), lacking an open, efficient, and flexible framework to integrate many-objective (i.e., four or more objective functions) optimization algorithms to satisfy the growing demands of complex hydrological systems. This study addresses this gap by designing and implementing a multi-objective optimization framework, Py-SWAT-U-NSGA-III, which integrates the Unified Non-dominated Sorting Genetic Algorithm III (U-NSGA-III). Built on the SWAT model, this framework supports a broad range of optimization problems, from single- to many-objective. Developed within a Python environment, the SWAT model modules are integrated with the Pymoo library to construct a U-NSGA-III algorithm-based optimization framework. This framework accommodates various calibration schemes, including multi-site, multi-variable, and multi-objective functions. Additionally, it incorporates sensitivity analysis and post-processing modules to shed insights into model behavior and evaluate optimization results. The framework supports multi-core parallel processing to enhance efficiency. The framework was tested in the Meijiang River Basin in southern China, using daily streamflow data and Penman–Monteith–Leuning Version 2 (PML-V2(China)) remote sensing evapotranspiration (ET) data for sensitivity analysis and parallel efficiency evaluation. Three case studies demonstrated its effectiveness in optimizing complex hydrological models, with multi-core processing achieving a speedup of up to 8.95 despite I/O bottlenecks. Py-SWAT-U-NSGA-III provides an open, efficient, and flexible tool for the hydrological community that strives to facilitate the application and advancement of multi-objective optimization in hydrological modeling. Full article
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15 pages, 5351 KB  
Article
Estimation of Hydraulic and Water Quality Parameters Using Long Short-Term Memory in Water Distribution Systems
by Nadia Sadiki and Dong-Woo Jang
Water 2024, 16(21), 3028; https://doi.org/10.3390/w16213028 - 22 Oct 2024
Cited by 2 | Viewed by 2158
Abstract
Predicting essential water quality parameters, such as discharge, pressure, turbidity, temperature, conductivity, residual chlorine, and pH, is crucial for ensuring the safety and efficiency of water supply systems. This study employs long short-term memory (LSTM) networks to address the challenge of capturing temporal [...] Read more.
Predicting essential water quality parameters, such as discharge, pressure, turbidity, temperature, conductivity, residual chlorine, and pH, is crucial for ensuring the safety and efficiency of water supply systems. This study employs long short-term memory (LSTM) networks to address the challenge of capturing temporal dependencies in these complex processes. Our approach, using a robust LSTM-based model, has demonstrated significant predictive accuracy, as evidenced by substantial R-squared values (e.g., 0.86 for discharge and 0.97 for conductivity). These models have proven particularly effective in handling non-linear patterns and time-series data, which are prevalent in water quality metrics. The results indicate the potential for LSTMs not only to enhance the real-time monitoring of water systems but also to aid in the strategic planning and management of water supply systems. This study’s findings can serve as a basis for further research into the integration of AI in environmental engineering, particularly for predictive tasks in complex, dynamic systems. Full article
(This article belongs to the Special Issue Hydrological-Hydrodynamic Simulation Based on Artificial Intelligence)
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18 pages, 2077 KB  
Article
Ecological Environment Assessment System in River–Riparian Areas Based on a Protocol for Hydromorphological Quality Evaluation
by Lan Duo, Martí Sánchez-Juny and Ernest Bladé i Castellet
Water 2024, 16(21), 3025; https://doi.org/10.3390/w16213025 - 22 Oct 2024
Cited by 2 | Viewed by 1549
Abstract
This paper aims to propose a method for the evaluation of the hydromorphological quality of a river and its riparian areas using three essential components: morphological characterization, river connectivity, and vegetation coverage. The method has been applied to the Tordera river in Catalonia, [...] Read more.
This paper aims to propose a method for the evaluation of the hydromorphological quality of a river and its riparian areas using three essential components: morphological characterization, river connectivity, and vegetation coverage. The method has been applied to the Tordera river in Catalonia, Spain. The general goal is to establish a riparian environment assessment tool by proposing parameters for each of the three mentioned aspects. This approach relies on data collection and evaluation with a simple computational procedure for eliminating subjectivity in the weighting and classification of evaluation levels. In the proposed methodology, the weights of the indicators are determined by the Distance Correlation-Based CRITIC (D-CRITIC) method, and the results are integrated using the Coupling Coordination Degree Model (CCDM). The proposed methodology quantifies assessment parameters and analyzes the environmental problems faced by riparian zones and rivers through the parameters and the results of the CCDM and thus can be used as a basis for proposing methods to improve the ecological situation. The results can be used for the enhancement of the coordination between the development of riparian resources and the requirements of ecosystem protection and utilization, and they can be used to promote the healthy development of ecological environments and the effective use of riparian resources. Full article
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16 pages, 15674 KB  
Article
Delineation of Groundwater Potential Zones Using Geospatial Techniques. Case Study: Roman City and the Surrounding Area in the Northeastern Region, Romania
by Petrut-Liviu Bogdan, Valentin Nedeff, Mirela Panainte-Lehadus, Dana Chitimuș, Narcis Barsan and Florin Marian Nedeff
Water 2024, 16(21), 3013; https://doi.org/10.3390/w16213013 - 22 Oct 2024
Cited by 6 | Viewed by 1757
Abstract
Effective groundwater management is crucial under the current climatic conditions, addressing both qualitative and quantitative aspects. An important step in delineating groundwater potential zones involves remote sensing (RS) data and geographic information systems (GISs), facilitating resource assessment, and the implementation of suitable field [...] Read more.
Effective groundwater management is crucial under the current climatic conditions, addressing both qualitative and quantitative aspects. An important step in delineating groundwater potential zones involves remote sensing (RS) data and geographic information systems (GISs), facilitating resource assessment, and the implementation of suitable field data management. This study introduces the delineation of potential groundwater zones using seven layers and the Multi-Criteria Decision Analysis (MCDA) method. Satty’s Analytic Hierarchy Process (AHP) was employed to rank the seven selected parameters, contributing to the advancement of groundwater research and resource assessment. All seven thematic layers (Rainfall, Geology, Land Use/Land Cover, Drainage Density, Elevation, Slope, and Soil) were prepared and analyzed to delineate groundwater potential zones. The resulting groundwater potential zone map was categorized into four classes, Very Good, Good, Moderate, and Poor, covering areas of 81.53 km2 (45.1%), 56.36 km2 (31.2%), 19.54 km2 (10.8%), and 23.17 km2 (12.8%) of the total area, respectively. The accuracy of the output was validated by comparing it with information on groundwater prospects in the area, and the overall accuracy of the method was approximately 72%. High-yield boreholes were drilled and concentrated in the Very Good groundwater potential zones, while low-yield ones were developed in the Poor areas. Full article
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22 pages, 5549 KB  
Article
Evaluating Hydrologic Model Performance for Characterizing Streamflow Drought in the Conterminous United States
by Caelan Simeone, Sydney Foks, Erin Towler, Timothy Hodson and Thomas Over
Water 2024, 16(20), 2996; https://doi.org/10.3390/w16202996 - 21 Oct 2024
Cited by 2 | Viewed by 2950
Abstract
Hydrologic models are the primary tools that are used to simulate streamflow drought and assess impacts. However, there is little consensus about how to evaluate the performance of these models, especially as hydrologic modeling moves toward larger spatial domains. This paper presents a [...] Read more.
Hydrologic models are the primary tools that are used to simulate streamflow drought and assess impacts. However, there is little consensus about how to evaluate the performance of these models, especially as hydrologic modeling moves toward larger spatial domains. This paper presents a comprehensive multi-objective approach to systematically evaluating the critical features in streamflow drought simulations performed by two widely used hydrological models. The evaluation approach captures how well a model classifies observed periods of drought and non-drought, quantifies error components during periods of drought, and assesses the models’ simulations of drought severity, duration, and intensity. We apply this approach at 4662 U.S. Geological Survey streamflow gages covering a wide range of hydrologic conditions across the conterminous U.S. from 1985 to 2016 to evaluate streamflow drought using two national-scale hydrologic models: the National Water Model (NWM) and the National Hydrologic Model (NHM); therefore, a benchmark against which to evaluate additional models is provided. Using this approach, we find that generally the NWM better simulates the timing of flows during drought, while the NHM better simulates the magnitude of flows during drought. Both models performed better in wetter eastern regions than in drier western regions. Finally, each model showed increased error when simulating the most severe drought events. Full article
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38 pages, 16780 KB  
Review
An Evaluation of Metal Binding Constants to Cell Surface Receptors in Freshwater Organisms, and Their Application in Biotic Ligand Models to Predict Metal Toxicity
by Paul L. Brown and Scott J. Markich
Water 2024, 16(20), 2999; https://doi.org/10.3390/w16202999 - 21 Oct 2024
Cited by 2 | Viewed by 1841
Abstract
Biotic ligand models (BLMs) predict the toxicity of metals in aquatic environments by accounting for metal interactions with cell surface receptors (biotic ligands) in organisms, including water chemistry (metal speciation) and competing cations. Metal binding constants (log KMBL values), which indicate the [...] Read more.
Biotic ligand models (BLMs) predict the toxicity of metals in aquatic environments by accounting for metal interactions with cell surface receptors (biotic ligands) in organisms, including water chemistry (metal speciation) and competing cations. Metal binding constants (log KMBL values), which indicate the affinity of metals for cell surface receptors, are fundamental to BLMs, but have only been reported for a few commonly investigated metals and freshwater species. This review evaluated literature toxicity and uptake data for seven key metals (cadmium (Cd), cobalt (Co), copper (Cu), nickel (Ni), lead (Pb), uranium (U), and zinc (Zn)) and four key competing cations (protons (H), calcium (Ca), magnesium (Mg), and sodium (Na)), to derive average metal binding constants for freshwater organisms/taxa. These constants will improve current BLMs for Cd, Cu, Ni, Pb, and Zn, and aid in developing new BLMs for Co and U. The derived metal binding constants accurately predicted metal toxicity for a wide range of freshwater organisms (75–88% of data were within a factor of two and 88–98% of data were within a factor of three of the ideal 1:1 agreement line), when considering metal speciation, competing cations and the fraction of cell receptors ((fC)M50%) occupied by the metal at the median (50%) effect concentration (EC50). For many organisms, toxicity occurs when 50% of cell surface receptors are occupied by the metal, though this threshold can vary. Some organisms exhibit toxicity with less than 50% receptor occupancy, while others with protective mechanisms show reduced toxicity, even with similar log KMBL values. For Cu, U, and Pb, the toxic effect of the metal hydroxide (as MOH+) must be considered in addition to the free metal ion (M2+), as these metals hydrolyse in circumneutral freshwaters (pH 5.5 to 8.5), contributing to toxicity. Full article
(This article belongs to the Special Issue Ecotoxicity of Pollutants on Aquatic Species)
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23 pages, 2206 KB  
Article
Bottled or Tap Water? Factors Explaining Consumption and Measures to Promote Tap Water
by Iva Zvěřinová, Milan Ščasný and Jan Otáhal
Water 2024, 16(20), 3011; https://doi.org/10.3390/w16203011 - 21 Oct 2024
Cited by 6 | Viewed by 5658
Abstract
The production and consumption of plastic bottled water have several negative environmental impacts worldwide. To identify the barriers and motivations for drinking tap and bottled water, we conducted a nationally representative questionnaire survey among 3411 respondents in the Czech Republic in 2022. People [...] Read more.
The production and consumption of plastic bottled water have several negative environmental impacts worldwide. To identify the barriers and motivations for drinking tap and bottled water, we conducted a nationally representative questionnaire survey among 3411 respondents in the Czech Republic in 2022. People aged 18–34 are moderate consumers of bottled water and very frequent consumers of tap water. Bottled water consumption tends to be less frequent among people with a higher education, while tap water consumption is less frequent among people with lower incomes. The most important factors that explain the frequency of drinking bottled and tap water are taste perception, health concerns and habit. Health concerns about tap water and the unpleasant taste of tap water increase the consumption of bottled water. People with a strong habit of drinking tap water are less likely to consume bottled water. The constructs from the theory of planned behaviour were statistically significant. The results can guide decision-makers in promoting tap water to consumers. To encourage tap water drinking, we suggest measures to increase the availability of tap water in public places in conjunction with campaigns targeting the taste and health perception, as well as the habit, of drinking tap water. Full article
(This article belongs to the Section Water Use and Scarcity)
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16 pages, 2309 KB  
Review
A Review of Strategies and Technologies for Sustainable Decentralized Wastewater Treatment
by Chuqiao Sha, Shuting Shen, Junjun Zhang, Chao Zhou, Xiwu Lu and Hong Zhang
Water 2024, 16(20), 3003; https://doi.org/10.3390/w16203003 - 21 Oct 2024
Cited by 11 | Viewed by 8243
Abstract
The traditional model of centralized wastewater treatment is facing substantial strain due to a confluence of global challenges. Consequently, it is imperative to evaluate the impediments and potential advantages associated with the deployment of decentralized wastewater (DW) treatment technologies and systems. Decentralized wastewater [...] Read more.
The traditional model of centralized wastewater treatment is facing substantial strain due to a confluence of global challenges. Consequently, it is imperative to evaluate the impediments and potential advantages associated with the deployment of decentralized wastewater (DW) treatment technologies and systems. Decentralized wastewater (DW) treatment represents a sustainable approach to managing and purifying wastewater across both urban and rural settings. This literature review provides a detailed examination of current advancements and challenges associated with DW treatment technologies. It specifically addresses their operational efficiency, long-term sustainability, and practical implementation across diverse environments. This review critically analyzes recent studies that highlight innovative methodologies, including the deployment of constructed wetlands, anaerobic digestion processes, and predictive models enhanced by artificial intelligence. A critical focus is placed on the ecological and economic advantages of source separation and resource recovery from wastewater streams. The issue of emerging contaminants, such as microplastics, antibiotics, and steroids, is also discussed, emphasizing the continued need for innovation in treatment technologies. Findings from various life cycle assessments are presented to illustrate the environmental impact and feasibility of decentralized systems relative to centralized alternatives. This comprehensive analysis offers valuable insights into the future trajectories of wastewater treatment research and implementation. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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17 pages, 2874 KB  
Article
The Israeli Water Policy and Its Challenges During Times of Emergency
by Erez Cohen
Water 2024, 16(20), 2995; https://doi.org/10.3390/w16202995 - 20 Oct 2024
Cited by 4 | Viewed by 6685
Abstract
In a time of growing climate crisis, and despite the global warming trend, Israeli citizens routinely enjoy a regular constant supply of clean fresh water thanks to local desalination plants. Establishment of the desalination plants has become a model of water management for [...] Read more.
In a time of growing climate crisis, and despite the global warming trend, Israeli citizens routinely enjoy a regular constant supply of clean fresh water thanks to local desalination plants. Establishment of the desalination plants has become a model of water management for many countries in an era of growing climate crisis. At the same time, Israel’s water sector is faced with challenges and threats related to earthquakes, various states of warfare, and security confrontations. In such times of emergency, Israel’s water sector is particularly vulnerable to disruptions of the water infrastructure and its adequate operation by both contamination of the water sources and damage to the desalination plants. This study examines the challenges of the Israeli water sector that require it to contend with these emergency situations in an era of reliance on desalination plants. The research findings lead to the conclusion that public policy on managing the water sector, manifested in the development and establishment of water desalination plants, has resolved Israel’s water crisis, put an end to its dependency on the amount of precipitation and on natural water sources, and allowed for an increase in water production to match the rise in consumption. Nonetheless, as successful as this public policy may be, it does not consider the possibility of extreme scenarios and does not develop the entire range of steps necessary to confront them, and thus it undermines the ability of the Israeli water sector to provide its citizens with water in times of emergency. Full article
(This article belongs to the Section Urban Water Management)
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15 pages, 16024 KB  
Article
Numerical Simulations of a Permeability Test on Non-Cohesive Soil Under an Increasing Water Level
by Weijie Zhang, Hongxin Chen, Lei Xiong and Liang Chen
Water 2024, 16(20), 2992; https://doi.org/10.3390/w16202992 - 20 Oct 2024
Viewed by 2001
Abstract
With the intensification of global climate change, extreme rainfall events are occurring more frequently. Continuous rainfall causes the debris flow gully to collect a large amount of rainwater. Under the continuous increase in the water level, the water flow has enough power to [...] Read more.
With the intensification of global climate change, extreme rainfall events are occurring more frequently. Continuous rainfall causes the debris flow gully to collect a large amount of rainwater. Under the continuous increase in the water level, the water flow has enough power to carry plenty of loose solids, thus causing debris flow disasters. The intensity of the soil is reduced with the infiltration of rainwater, which is one of the key causes of the disaster. The rise in the water level affects the infiltration behavior. There have been few previous studies on infiltration under variable head. In order to understand the infiltration behavior of soils under the action of water level rises, this paper conducted an indoor permeability test on non-cohesive soil under the condition of an increasing water level. A numerical model was established using the finite element analysis software, Abaqus 6.14, and the pore pressure was increased intermittently to simulate the intermittent increase in the water level. Thereafter, the permeability coefficient and seepage length were changed to interpret the changes in the flow velocity and rate in the permeability test of the non-cohesive soil. The results showed that the finite element numerical simulation method could not reflect the particle movement process in the soil. The test could better reflect the through passage and void plugging phenomenon in soil; when the permeability coefficient alone changed, the velocity of the measuring point with higher velocity changed more violently with the permeability coefficient; when the length of soil seepage diameter was uniformly shortened, the velocity of water flow increased faster and faster. Full article
(This article belongs to the Special Issue Flowing Mechanism of Debris Flow and Engineering Mitigation)
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16 pages, 1805 KB  
Review
The Water–Energy Nexus in 26 European Countries: A Review from a Hydrogeological Perspective
by Somayeh Rezaei Kalvani, Riccardo Pinardi and Fulvio Celico
Water 2024, 16(20), 2981; https://doi.org/10.3390/w16202981 - 19 Oct 2024
Cited by 3 | Viewed by 1905
Abstract
The significance of the interconnection between water and energy, known as the water–energy (WE) nexus, is highly regarded in scientific publications. This study used a narrative review method to analyze the existing WE nexus studies performed before 2024 in 26 European countries. The [...] Read more.
The significance of the interconnection between water and energy, known as the water–energy (WE) nexus, is highly regarded in scientific publications. This study used a narrative review method to analyze the existing WE nexus studies performed before 2024 in 26 European countries. The aim of this study is to provide a comprehensive analysis of the existing WE nexus to identify research gaps and to report a conceptual overview of energy consumption related to groundwater use phases, ranging from the tapping to distribution. This information is valuable as a guideline for any future estimates in this field. The results indicate that the WE nexus in 26 European countries comprises a variety of topics, including the water supply system, wastewater treatment, hydropower, desalination, and biofuel production. Most of the focus has been on fossil fuel production, while water supply and desalination were considered rarely. Italy and Portugal had the largest WE nexus. It is highlighted that there have been no studies on the WE nexus focusing on the groundwater supply system that consider the conceptual hydrological model or hydrodynamic processes. In this work, a view of these aspects was provided by taking into account different hydrogeological and hydraulic scenarios that may affect the amount of energy required for groundwater exploitation. Most scientific publications have focused on quantitative analysis. In the future, it will be necessary for WE nexus models to place a greater emphasis on governance and the implications of the WE nexus approach. Full article
(This article belongs to the Special Issue Water and Energy Synergies)
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22 pages, 2487 KB  
Article
Applying a Comprehensive Model for Single-Ring Infiltration: Assessment of Temporal Changes in Saturated Hydraulic Conductivity and Physical Soil Properties
by Mirko Castellini, Simone Di Prima, Luisa Giglio, Rita Leogrande, Vincenzo Alagna, Dario Autovino, Michele Rinaldi and Massimo Iovino
Water 2024, 16(20), 2950; https://doi.org/10.3390/w16202950 - 16 Oct 2024
Cited by 2 | Viewed by 1690
Abstract
Modeling agricultural systems, from the point of view of saving and optimizing water, is a challenging task, because it may require multiple soil physical and hydraulic measurements to investigate the entire crop cycle. The Beerkan method was proposed as a quick and easy [...] Read more.
Modeling agricultural systems, from the point of view of saving and optimizing water, is a challenging task, because it may require multiple soil physical and hydraulic measurements to investigate the entire crop cycle. The Beerkan method was proposed as a quick and easy approach to estimate the saturated soil hydraulic conductivity, Ks. In this study, a new complete three-dimensional model for Beerkan experiments recently proposed was used. It consists of thirteen different calculation approaches that differ in estimating the macroscopic capillary length, initial (θi) and saturated (θs) soil water contents, use transient or steady-state infiltration data, and different fitting methods to transient data. A steady-state version of the simplified method based on a Beerkan infiltration run (SSBI) was used as the benchmark. Measurements were carried out on five sampling dates during a single growing season (from November to June) in a long-term experiment in which two soil management systems were compared, i.e., minimum tillage (MT) and no tillage (NT). The objectives of this work were (i) to test the proposed new model and calculation approaches under real field conditions, (ii) investigate the impact of MT and NT on soil properties, and (iii) obtain information on the seasonal variability of Ks and other main soil physical properties (θi, soil bulk density, ρb, and water retention curve) under MT and NT. The results showed that the model always overestimated Ks compared to SSBI. Indeed, the estimated Ks differed by a factor of 11 when the most data demanding (A1) approach was considered by a factor of 4–8, depending on the transient or steady-state phase use, when A3 was considered and by a practically negligible factor of 1.0–1.9 with A4. A relatively higher seasonal variability was detected for θi at the MT than NT system. Under both MT and NT, ρb did not change between November and April but increased significantly until the end of the season. The selected calculation approaches provided substantially coherent information on Ks seasonal evolution. Regardless of the approach, the results showed a temporal stability of Ks at least from early April to June under NT; conversely, the MT system was, overall, more affected by temporal changes with a relative stability at the beginning and middle of the season. These findings suggest that a common sampling time for determining Ks could be set at early spring. Soil management affected the soil properties, because the NT system was significantly wetter and more compact than MT on four out of five dates. However, only NT showed a significantly increasing correlation between Ks and the modal pore diameter, suggesting the presence of a relatively smaller and better interconnected pore network in the no-tilled soil. This study confirms the need to test infiltration models under real field conditions to evaluate their pros and cons. The Beerkan method was effective for intensive soil sampling and accurate field investigations on the temporal variability of Ks. Full article
(This article belongs to the Special Issue Soil Dynamics and Water Resource Management)
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25 pages, 2419 KB  
Article
Decision Support Framework for Water Quality Management in Reservoirs Integrating Artificial Intelligence and Statistical Approaches
by Syeda Zehan Farzana, Dev Raj Paudyal, Sreeni Chadalavada and Md Jahangir Alam
Water 2024, 16(20), 2944; https://doi.org/10.3390/w16202944 - 16 Oct 2024
Cited by 8 | Viewed by 3593
Abstract
Planning, managing and optimising surface water quality is a complex and multifaceted process, influenced by the effects of both climate uncertainties and anthropogenic activities. Developing an innovative and robust decision support framework (DSF) is essential for effective and efficient water quality management, so [...] Read more.
Planning, managing and optimising surface water quality is a complex and multifaceted process, influenced by the effects of both climate uncertainties and anthropogenic activities. Developing an innovative and robust decision support framework (DSF) is essential for effective and efficient water quality management, so it can provide essential information on water quality and assist policy makers and water resource managers to identify potential causes of water quality deterioration. This framework is crucial for implementing actions such as infrastructure development, legislative compliance and environmental initiatives. Recent advancements in computational domains have created opportunities for employing artificial intelligence (AI), advanced statistics and mathematical methods for use in improved water quality management. This study proposed a comprehensive conceptual DSF to minimise the adverse effects of extreme weather events and climate change on water quality. The framework utilises machine learning (ML), deep learning (DL), geographical information system (GIS) and advanced statistical and mathematical techniques for water quality management. The foundation of this framework is the outcomes from our three studies, where we examined the application of ML and DL models for predicting water quality index (WQI) in reservoirs, utilising statistical and mathematical methods to find the seasonal trend of rainfall and water quality, exploring the potential connection between streamflow, rainfall and water quality, and employing GIS to show the spatial and temporal variability of hydrological parameters and WQI. Three potable water supply reservoirs in the Toowoomba region of Australia were taken as the study area for practical implementation of the proposed DSF. This framework can serve as a comprehensive mechanism to identify distinct seasonal characteristics and understand correlations between rainfall, streamflow and water quality. This will enable policy makers and water resource managers to enhance their decision making processes by selecting the management priorities to safeguard water quality in the face of future climate variability, including prolonged droughts and flooding. Full article
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19 pages, 11753 KB  
Article
Landslide Deformation Analysis and Prediction with a VMD-SA-LSTM Combined Model
by Chengzhi Wen, Hongling Tian, Xiaoyan Zeng, Xin Xia, Xiaobo Hu and Bo Pang
Water 2024, 16(20), 2945; https://doi.org/10.3390/w16202945 - 16 Oct 2024
Cited by 5 | Viewed by 1692
Abstract
The evolution of landslides is influenced by the complex interplay of internal geological factors and external triggering factors, resulting in nonlinear dynamic changes. Although deep learning methods have demonstrated advantages in predicting multivariate landslide displacement, their performance is often constrained by the challenges [...] Read more.
The evolution of landslides is influenced by the complex interplay of internal geological factors and external triggering factors, resulting in nonlinear dynamic changes. Although deep learning methods have demonstrated advantages in predicting multivariate landslide displacement, their performance is often constrained by the challenges of extracting intricate features from extended time-series data. To address this challenge, we propose a novel displacement prediction model that integrates Variational Mode Decomposition (VMD), Self-Attention (SA), and Long Short-Term Memory (LSTM) networks. The model first employs VMD to decompose cumulative landslide displacement into trend, periodic, and stochastic components, followed by an assessment of the correlation between these components and the triggering factors using grey relational analysis. Subsequently, the self-attention mechanism is incorporated into the LSTM model to enhance its ability to capture complex dependencies. Finally, each displacement component is fed into the SA-LSTM model for separate predictions, which are then reconstructed to obtain the cumulative displacement prediction. Using the Zhonghai Village tunnel entrance (ZVTE) landslide as a case study, we validated the model with displacement data from GPS point 105 and made predictions for GPS point 104 to evaluate the model’s generalization capability. The results indicated that the RMSE and MAPE for SA-LSTM, LSTM, and TCN-LSTM at GPS point 105 were 0.3251 and 1.6785, 0.6248 and 2.9130, and 1.1777 and 5.5131, respectively. These findings demonstrate that SA-LSTM outperformed the other models in terms of complex feature extraction and accuracy. Furthermore, the RMSE and MAPE at GPS point 104 were 0.4232 and 1.0387, further corroborating the model’s strong extrapolation capability and its effectiveness in landslide monitoring. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence, 2nd Edition)
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13 pages, 3859 KB  
Article
Effect of Pipe Materials and Interspecific Interactions on Biofilm Formation and Chlorine Resistance: Turn Enemies into Friends
by Lili Shan, Yunyan Pei, Siyang Xu, Yuhong Cui, Zhengqian Liu, Zebing Zhu and Yixing Yuan
Water 2024, 16(20), 2930; https://doi.org/10.3390/w16202930 - 15 Oct 2024
Cited by 5 | Viewed by 1973
Abstract
Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine [...] Read more.
Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine resistance of 10 dual-species biofilms in polyethylene (PE) and cast iron (CI) pipes were investigated in this paper. The biofilm biomass (heterotrophic bacterial plate count and crystal violet) of dual species in CI pipes is significantly higher than that in PE pipes, but the biofilm activity in CI pipes is significantly lower than that in PE pipes. The interspecific interaction of Sphingomonas-containing group presented synergistic or neutral relationship in PE pipes, whereas the interspecific interaction of the Acidovorax-containing group showed a competitive relationship in CI pipes. Although interspecific relationships may help bacteria resist chlorine, the chlorine resistance was more reliant on dual-species groups and pipe materials. In CI pipes, the Microbacterium containing biofilm groups showed better chlorine resistance, whereas in PE pipes, most biofilm groups with Bacillus exhibited better chlorine resistance. The biofilm groups with more extracellular polymeric substance (EPS) secretion showed stronger chlorine resistance. The biofilm in the PE pipe is mainly protected by EPS, while both EPS and corrosion products shield the biofilms within CI pipe. These results supported that dual-species biofilms are affected by pipe materials and interspecific interactions and provided some ideas for microbial control in two typical pipe materials. Full article
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16 pages, 1420 KB  
Article
Short-Term Effects of Abrupt Salinity Changes on Aquaculture Biofilter Performance and Microbial Communities
by Eliza M. Costigan, Deborah A. Bouchard, Suzanne L. Ishaq and Jean D. MacRae
Water 2024, 16(20), 2911; https://doi.org/10.3390/w16202911 - 13 Oct 2024
Cited by 2 | Viewed by 1853
Abstract
In recirculating aquaculture systems (RASs), ammonia excreted by fish must be converted to the less toxic nitrate before recirculation. Nitrifying microorganisms in biofilters used for this transformation can be sensitive to changes in salinity, which can present issues for systems that raise anadromous [...] Read more.
In recirculating aquaculture systems (RASs), ammonia excreted by fish must be converted to the less toxic nitrate before recirculation. Nitrifying microorganisms in biofilters used for this transformation can be sensitive to changes in salinity, which can present issues for systems that raise anadromous fish such as Atlantic salmon. Freshwater biofilters maintained at a low level of salinity (such as biofilters operated in coastal areas) may be better equipped to handle more drastic salinity shifts; therefore, experiments were performed on freshwater and low-salinity (3 ppt) biofilters to assess their ability to recover nitrification activity after an abrupt change in salinity (3, 20, and 33 ppt). Two-week tests showed full nitrification recovery in freshwater biofilters after a shift to 3 ppt but no ammonia oxidation in 20 or 33 ppt. Low-salinity-adapted filters (transitioned from 0 to 3 ppt) showed a small recovery (about 11%) after a shift to 20 ppt, and no activity when shifted to 33 ppt. Illumina sequencing revealed that, while nitrification was slowed or stopped with shifting salinities, the nitrifiers survived the salinity increases; conversely, the heterotrophic communities were more greatly affected and were reduced in proportion with increasing salinity. This work indicates that biofilters operated at low salinity may recover more quickly after large salinity changes, though this slight benefit may not outweigh the cost of low-level salinity maintenance. Further research into halotolerant heterotrophs in biofilms may increase the effectiveness of nitrifying biofilters under variable salinities. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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16 pages, 7268 KB  
Article
Traffic Intensity as a Factor Influencing Microplastic and Tire Wear Particle Pollution in Snow Accumulated on Urban Roads
by Karolina Mierzyńska, Wojciech Pol, Monika Martyniuk and Piotr Zieliński
Water 2024, 16(20), 2907; https://doi.org/10.3390/w16202907 - 13 Oct 2024
Cited by 5 | Viewed by 3409
Abstract
Traffic-related roads are an underestimated source of synthetic particles in the environment. This study investigated the impact of traffic volume on microplastic (MP) and tire wear particle (TWP) pollution in road snow. An examination was conducted in a medium-sized city situated in northeastern [...] Read more.
Traffic-related roads are an underestimated source of synthetic particles in the environment. This study investigated the impact of traffic volume on microplastic (MP) and tire wear particle (TWP) pollution in road snow. An examination was conducted in a medium-sized city situated in northeastern Poland, known for being one of the cleanest regions in the country. MPs and TWPs were found at all 54 sites, regardless of the intensity of traffic. The average concentration for all samples was 354.72 pcs/L. Statistically significant differences were found between the average values of the particle concentration on low, medium, and heavy traffic roads, amounting to 62.32 pcs/L, 335.97 pcs/L, and 792.76 pcs/L, respectively. Within all three studied groups of roads, MPs and TWPs with the smallest size, ranging from 50 to 200 μm, were prevalent. In all of the studied groups of roads, four analyzed shapes of particles were found, with irregular fragments being the most abundant form (89.23%). The most frequently recorded color among the collected samples was black (99.85%), and the least frequently recorded color was blue, constituting only 0.01%. This study suggests that snow cover on the roads may act like a temporary storage of pollutants during winter particularly in the temperate climate zone and, after thawing can significantly increase the concentration of MPs and TWPs in surface waters. Possible measures to decrease the release of MPs and TWPs into the environment in the city may include reducing the traffic volume and speed, implementing street sweeping, utilizing filtration chambers, and installing stormwater bioretention systems or settling ponds. Full article
(This article belongs to the Section Urban Water Management)
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14 pages, 3023 KB  
Article
Activity Concentration of Natural Radionuclides in Surface Sediments of Major River Watersheds in Korea and Assessment of Radiological Hazards
by Tae-Woo Kang, Mijeong An, Young-Un Han, Hae Jong Yang, Taegu Kang, Soojung Jung, Won-Seok Lee and Won-Pyo Park
Water 2024, 16(20), 2897; https://doi.org/10.3390/w16202897 - 12 Oct 2024
Cited by 2 | Viewed by 1379
Abstract
The assessment of potential radiation hazards in accumulated sediments in aquatic ecosystems is vital for the management and disposal of sediments. Furthermore, preemptive management of radionuclides in terrestrial ecosystems is critical for marine ecosystem conservation. We analyzed the activity concentrations of natural radionuclides [...] Read more.
The assessment of potential radiation hazards in accumulated sediments in aquatic ecosystems is vital for the management and disposal of sediments. Furthermore, preemptive management of radionuclides in terrestrial ecosystems is critical for marine ecosystem conservation. We analyzed the activity concentrations of natural radionuclides (226Ra,232Th, 238U, and 40K) in the surface sediments of major river watersheds in Korea and evaluated the radiation hazards stemming from these activity concentrations. The mean activity concentrations of 226Ra and 238U were lower than the global average, whereas those of 232Th and 40K were higher. The mean values of radium equivalent activity, external hazard index, and internal hazard index calculated from these activity concentrations did not exceed the recommended maximum values. The mean values of absorbed gamma dose rate in air and annual outdoor effective dose rate (AEDRout) were higher than the global average by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) but remarkably lower than the recommended and background values by the International Commission on Radiological Protection (ICRP) and the Korea Institute of Nuclear Safety (KINS). The contribution of 40K and 232Th to the AEDRout mean value was predominant. In conclusion, the surface sediments of major river watersheds in Korea are associated with negligible radiation hazards. These findings provide fundamental data for the management and treatment of sediments in terrestrial and marine ecosystems. Full article
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20 pages, 11684 KB  
Article
Development of a Storm-Tracking Algorithm for the Analysis of Radar Rainfall Patterns in Athens, Greece
by Apollon Bournas and Evangelos Baltas
Water 2024, 16(20), 2905; https://doi.org/10.3390/w16202905 - 12 Oct 2024
Cited by 3 | Viewed by 2160
Abstract
This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the tracking procedure on the basis [...] Read more.
This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the tracking procedure on the basis of their geometrical characteristics and the distance within the weather radar image. A sensitivity analysis was performed to evaluate the preferable thresholds for each case and test the algorithm’s ability to perform in different time step resolutions. Following this, we applied the algorithm to 54 rainfall events recorded by the National Technical University X-Band weather radar, the rainscanner system, from 2018 to 2023 in the Attica region of Greece. Testing of the algorithm demonstrated its efficiency in tracking storm cells over various time intervals and reflecting changes such as merging or dissipation. The results reveal the predominant southwest-to-east storm directions in 40% of cases examined, followed by northwest-to-east and south-to-north patterns. Additionally, stratiform storms showed slower north-to-west trajectories, while convective storms exhibited faster west-to-east movement. These findings provide valuable insights into storm behavior in Athens and highlight the algorithm’s potential for integration into nowcasting systems, particularly for flood early warning systems. Full article
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25 pages, 3175 KB  
Article
Exploring Deep Learning Methods for Short-Term Tide Gauge Water Level Predictions
by Marina Vicens-Miquel, Philippe E. Tissot and F. Antonio Medrano
Water 2024, 16(20), 2886; https://doi.org/10.3390/w16202886 - 11 Oct 2024
Cited by 8 | Viewed by 2778
Abstract
Accurate and timely water level predictions are essential for effective shoreline and coastal ecosystem management. As sea levels rise, the frequency and severity of coastal inundation events are increasing, causing significant societal and economic impacts. Predicting these events with sufficient lead time is [...] Read more.
Accurate and timely water level predictions are essential for effective shoreline and coastal ecosystem management. As sea levels rise, the frequency and severity of coastal inundation events are increasing, causing significant societal and economic impacts. Predicting these events with sufficient lead time is essential for decision-makers to mitigate economic losses and protect coastal communities. While machine learning methods have been developed to predict water levels at specific sites, there remains a need for more generalized models that perform well across diverse locations. This study presents a robust deep learning model for predicting water levels at multiple tide gauge locations along the Gulf of Mexico, including the open coast, embayments, and ship channels, all near major ports. The selected architecture, Seq2Seq, achieves significant improvements over the existing literature. It meets the National Oceanic and Atmospheric Administration’s (NOAA) operational criterion, with the percentage of predictions within 15 cm for lead times up to 108 h at the tide gauges of Port Isabel (92.2%) and Rockport (90.4%). These results represent a significant advancement over current models typically failing to meet NOAA’s standard beyond 48 h. This highlights the potential of deep learning models to improve water level predictions, offering crucial support for coastal management and flood mitigation. Full article
(This article belongs to the Section Oceans and Coastal Zones)
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30 pages, 10054 KB  
Article
Identifying the Layout of Retrofitted Rainwater Harvesting Systems with Passive Release for the Dual Purposes of Water Supply and Stormwater Management in Northern Taiwan
by Hsin-Yuan Tsai, Chia-Ming Fan and Chao-Hsien Liaw
Water 2024, 16(20), 2894; https://doi.org/10.3390/w16202894 - 11 Oct 2024
Cited by 2 | Viewed by 1879
Abstract
Due to its unique climate and geography, Taiwan experiences abundant rainfall but still faces significant water scarcity. As a result, rainwater harvesting systems (RWHSs) have been recognized as potential water resources within both water legal and green building policies. However, the effects of [...] Read more.
Due to its unique climate and geography, Taiwan experiences abundant rainfall but still faces significant water scarcity. As a result, rainwater harvesting systems (RWHSs) have been recognized as potential water resources within both water legal and green building policies. However, the effects of climate change—manifested in more frequent extreme rainfall events and uneven rainfall distribution—have heightened the risks of both droughts and floods. This underscores the need to retrofit existing RWHSs to function as stormwater management tools and water supply sources. In Taiwan, the use of simple and cost-effective passive release systems is particularly suitable for such retrofits. Four key considerations are central to designing passive release RWHSs: the type of discharge outlet, the size of the outlet, the location of the outlet, and the system’s operational strategy. This study analyzes three commonly used outlet types—namely, the orifice, short stub fitting, and drainage pipe. Their respective discharge flow formulas and design charts have been developed and compared. To determine the appropriate outlet size, design storms with 2-, 5-, and 10-year return periods in the Taipei area were utilized to examine three different representative buildings. Selected combinations of outlet diameters and five different outlet locations were assessed. Additionally, probably hazardous rainfall events between 2014 and 2023 were used to verify the results obtained from the design storm analysis. Based on these analyses, the short stub fitting outlet type with a 15 mm outlet diameter was selected and verified. For determining the suitable discharge outlet location, a three-step process is recommended. First, the average annual water supply reliability for different scenarios and outlet locations in each representative building is calculated. Using this information, the maximum allowable decline in water supply reliability and the corresponding outlet location can be identified for each scenario. Second, break-even points between average annual water supply and regulated stormwater release curves, as well as the corresponding outlet locations, are identified. Finally, incremental analyses of average annual water supply and regulated stormwater release curves are conducted to determine the suitable outlet location for each scenario and representative building. For the representative detached house (DH), scenario 2, which designates 50% of the tank’s volume as detention space (i.e., the discharge outlet located halfway up the tank), and scenario 3, which designates 75% (i.e., the discharge outlet at one-quarter of the tank height), are the most suitable options. For the four-story building (FSB), the outlet located at one-quarter of the tank’s height is suitable for both scenarios 2 and 3. For the eight-story building (ESB), scenario 2, with the outlet at one-quarter of the tank’s height, and scenario 3, with the outlet at the lowest point on the tank’s side, are preferred. The framework developed in this study provides drainage designers with a systematic method for determining the key parameters in passive-release RWHS design at the household scale. Full article
(This article belongs to the Special Issue Watershed Hydrology and Management under Changing Climate)
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16 pages, 8312 KB  
Article
Impact of Thinning and Contour-Felled Logs on Overland Flow, Soil Erosion, and Litter Erosion in a Monoculture Japanese Cypress Forest Plantation
by Moein Farahnak, Takanori Sato, Nobuaki Tanaka, Anand Nainar, Ibtisam Mohd Ghaus and Koichiro Kuraji
Water 2024, 16(20), 2874; https://doi.org/10.3390/w16202874 - 10 Oct 2024
Cited by 2 | Viewed by 2017
Abstract
This study investigated the impact of thinning and felled logs (random- and contour-felled logs) on overland flow, soil erosion, and litter erosion in a Japanese cypress forest plantation (2400 tree ha−1) with low ground cover, from 2018 to 2023 in central [...] Read more.
This study investigated the impact of thinning and felled logs (random- and contour-felled logs) on overland flow, soil erosion, and litter erosion in a Japanese cypress forest plantation (2400 tree ha−1) with low ground cover, from 2018 to 2023 in central Japan. Monthly measurements of overland flow and soil and litter erosion were carried out using small-sized traps across three plots (two treatments and one control). In early 2020, a 40% thinning (tree ha−1) was conducted in the two treatment plots. Overland flow increased in the plot with random-felled logs during the first year post-thinning (from 139.1 to 422.0 L m−1), while it remained stable in the plot with contour-felled logs (from 341.8 to 337.1 L m−1). A paired-plot analysis showed no change in overland flow in the contour-felled logs plot compared to the control plot from the pre- to post-thinning periods (pre-thinning Y = 0.41X − 0.69, post-thinning Y = 0.5X + 5.46, ANCOVA: p > 0.05). However, exposure to direct rainfall on uncovered ground areas post-thinning led to increased soil and litter erosion in both treatment plots. These findings suggest that thinning combined with contour-felled logs effectively stabilizes overland flow. Therefore, thinning with contour-felled logs can be considered a viable method for mitigating overland flow in monoculture plantations with low ground cover. Full article
(This article belongs to the Special Issue Forest Hydrology and Watershed Management)
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18 pages, 24214 KB  
Article
A Modified Method for Evaluating the Stability of the Finite Slope during Intense Rainfall
by Xiaoyang Wei, Weizhong Ren, Wenhui Xu, Simin Cai and Longwei Li
Water 2024, 16(20), 2877; https://doi.org/10.3390/w16202877 - 10 Oct 2024
Cited by 3 | Viewed by 1079
Abstract
The Green–Ampt (GA) model is a widely used analytical method to calculate the depth of the wetting front during intense rainfall. However, it neglects the existence of the transition layer and the seepage parallel to the slope surface. Therefore, a modified stratified Green–Ampt [...] Read more.
The Green–Ampt (GA) model is a widely used analytical method to calculate the depth of the wetting front during intense rainfall. However, it neglects the existence of the transition layer and the seepage parallel to the slope surface. Therefore, a modified stratified Green–Ampt (MSGA) model is proposed. A process to assess the stability of the finite slope during a rainfall event is demonstrated by combining the MSGA model and the limit equilibrium method. In the case of the Liangshuijing landslide, the factor of safety presents a negative correlation with the depth of the wetting front. The factor of safety obtained by the stratified Green–Ampt (SGA) model is smaller than that calculated by the MSGA model, and the gap between the factor of safety based on the two methods widens with time. The moving speed of the wetting front accelerates with the increase in the length of the slope surface, and the size effect becomes apparent when the length is short. In the initial stage of infiltration, the effect of the seepage parallel to the slope surface is small. The effect of the seepage cannot be neglected at the latter stage. The result calculated by the MSGA model agrees well with the measured result in the test. Full article
(This article belongs to the Section Hydrology)
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14 pages, 3603 KB  
Article
Investigating a Century of Rainfall: The Impact of Elevation on Precipitation Changes (Northern Tuscany, Italy)
by Matteo Nigro, Michele Barsanti, Brunella Raco and Roberto Giannecchini
Water 2024, 16(19), 2866; https://doi.org/10.3390/w16192866 - 9 Oct 2024
Cited by 3 | Viewed by 2250
Abstract
Precipitation is crucial for water resource renewal, but climate change alters their frequency and amounts, challenging societies for correct and effective water management. However, modifications of precipitation dynamics appear to be not uniformly distributed, both in space and time. Even in relatively small [...] Read more.
Precipitation is crucial for water resource renewal, but climate change alters their frequency and amounts, challenging societies for correct and effective water management. However, modifications of precipitation dynamics appear to be not uniformly distributed, both in space and time. Even in relatively small areas, precipitation shows the coexistence of positive and negative trends. Local topography seems to be a strong driver of precipitation changes. Understanding precipitation changes and their relationship with local topography is crucial for society’s resilience. Taking advantage of a dense and long-lasting (1920–2019) meteorological monitoring network, we analyzed the precipitation changes over the last century in a sensitive and strategic area in the Mediterranean hotspot. The study area corresponds to northern Tuscany (Italy), where its topography comprises mountain ridges and coastal and river plains. Forty-eight rain gauges were selected with continuous annual precipitation time series. These were analyzed for trends and differences in mean annual precipitation between the stable period of 1921–1970 and the last 30-year 1990–2019. The relationship between precipitation changes and local topography was also examined. The results show the following highlights: (i) A general decrease in precipitation was found through the century, even if variability is marked. (ii) The mountain ridges show the largest decrease in mean annual precipitation. (iii) The precipitation change entity over the last century was not homogenous and was dependent on topography and geographical setting. (iv) A decrease in annual precipitation of up to 400 mm was found for the mountainous sites. Full article
(This article belongs to the Section Hydrology)
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17 pages, 4531 KB  
Article
Using Artificial Neural Networks to Predict Operational Parameters of a Drinking Water Treatment Plant (DWTP)
by Stylianos Gyparakis, Ioannis Trichakis and Evan Diamadopoulos
Water 2024, 16(19), 2863; https://doi.org/10.3390/w16192863 - 9 Oct 2024
Cited by 4 | Viewed by 2193
Abstract
The scope of the present study is the estimation of key operational parameters of a drinking water treatment plant (DWTP), particularly the dosages of treatment chemicals, using artificial neural networks (ANNs) based on measurable in situ data. The case study consists of the [...] Read more.
The scope of the present study is the estimation of key operational parameters of a drinking water treatment plant (DWTP), particularly the dosages of treatment chemicals, using artificial neural networks (ANNs) based on measurable in situ data. The case study consists of the Aposelemis DWTP, where the plant operator had an estimation of the ANN output parameters for the required dosages of water treatment chemicals based on observed water quality and other operational parameters at the time. The estimated DWTP main operational parameters included residual ozone (O3) and dosages of the chemicals used: anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas (Cl2(g)). Daily measurable results of water sample analysis and recordings from the DWTP Supervisory Control and Data Acquisition System (SCADA), covering a period of 38 months, were used as input parameters for the artificial neural network (1188 values for each of the 14 measurable parameters). These input parameters included: raw water supply (Q), raw water turbidity (T1), treated water turbidity (T2), treated water residual free chlorine (Cl2), treated water concentration of residual aluminum (Al), filtration bed inlet water turbidity (T3), daily difference in water height in reservoir (∆H), raw water pH (pH1), treated water pH (pH2), and daily consumption of DWTP electricity (El). Output/target parameters were: residual O3 after ozonation (O3), anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas supply (Cl2(g)). A total of 304 different ANN models were tested, based on the best test performance (tperf) indicator. The one with the optimum performance indicator was selected. The scenario finally chosen was the one with 100 neural networks, 100 nodes, 42 hidden nodes, 10 inputs, and 4 outputs. This ANN model achieved excellent simulation results based on the best testing performance indicator, which suggests that ANNs are potentially useful tools for the prediction of a DWTP’s main operational parameters. Further research could explore the prediction of water chemicals used in a DWTP by using ANNs with a smaller number of operational parameters to ensure greater flexibility, without prohibitively reducing the reliability of the prediction model. This could prove useful in cases with a much higher sample size, given the data-demanding nature of ANNs. Full article
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21 pages, 5459 KB  
Article
A Practical, Adaptive, and Scalable Real-Time Control Approach for Stormwater Storage Systems
by Ruijie Liang, Holger Robert Maier, Mark Andrew Thyer and Graeme Clyde Dandy
Water 2024, 16(19), 2844; https://doi.org/10.3390/w16192844 - 7 Oct 2024
Cited by 3 | Viewed by 3612
Abstract
Traditionally, urban stormwater infrastructure systems consist of passive infrastructure that is not actively controlled in response to rainfall events. Recently, real-time control (RTC) has been considered as a means to significantly increase the capacity and lifespan of these systems. This paper introduces the [...] Read more.
Traditionally, urban stormwater infrastructure systems consist of passive infrastructure that is not actively controlled in response to rainfall events. Recently, real-time control (RTC) has been considered as a means to significantly increase the capacity and lifespan of these systems. This paper introduces the target flow control systems (TFCS) approach, which can use real-time control of systems of storages to achieve the desired flow conditions at the locations of interest. The first distinctive feature of this approach is that it does not require calibration to catchment-specific data, unlike existing approaches. This means that the TFCS approach is generally applicable to different catchments and is able to respond to future changes in runoff due to land use and/or climate change. The second distinctive feature is that the approach only requires storage-level information measured in real time with the aid of low-cost pressure sensors. This means that the approach is practical and relatively easy to implement. In addition to the introduction of the novel TFCS approach, a key innovation of this study is that the approach is tested on three case studies, each with different physical configurations and stormwater management objectives. Another key innovation is that the TFCS approach is compared to five RTC approaches, including three of the best-performing advanced approaches from the literature. Comparisons of multiple RTC approaches that consider both performance and practicality across multiple case studies are rare. Results show that the TFCS approach is the only one of the five control approaches analysed that has both the best overall performance and the highest level of practicality. The outcomes highlight the potential of the TFCS approach as a practical RTC approach that is applicable to a wide range of catchments with different stormwater management objectives. By maximizing the performance of existing stormwater storages, the TFCS approach can potentially extend the lifespan of existing infrastructure and avoid costly upgrades due to increased runoff caused by land use and climate change. Full article
(This article belongs to the Special Issue Urban Stormwater Control, Utilization, and Treatment)
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15 pages, 1835 KB  
Article
Comparative Evaluation of Evapotranspiration and Optimization Schemes for Green Roof Runoff Simulations Using HYDRUS-1D
by Hwansuk Kim, Haein Sim, Seungwan Hong, Zong Woo Geem, Hafzullah Aksoy, Yongseok Hong and Jaeyoung Yoon
Water 2024, 16(19), 2835; https://doi.org/10.3390/w16192835 - 6 Oct 2024
Cited by 1 | Viewed by 1258
Abstract
The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In [...] Read more.
The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R2 = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R2 = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R2 = 0.95) than that of the HYDRUS-1D’s own optimization module (R2 = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations. Full article
(This article belongs to the Section Urban Water Management)
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23 pages, 11503 KB  
Article
Novel Framework for Exploring Human–Water Symbiosis Relationship: Analysis, Quantification, Discrimination, and Attribution
by Xi Qin, Qiting Zuo, Qingsong Wu and Junxia Ma
Water 2024, 16(19), 2829; https://doi.org/10.3390/w16192829 - 6 Oct 2024
Viewed by 1568
Abstract
There is an interdependent symbiotic relationship between humans and water; scientific and effective assessment of the human–water symbiosis relationship is of great significance for the promotion of sustainable development. This study developed a novel framework of the human–water symbiosis relationship under an integrated [...] Read more.
There is an interdependent symbiotic relationship between humans and water; scientific and effective assessment of the human–water symbiosis relationship is of great significance for the promotion of sustainable development. This study developed a novel framework of the human–water symbiosis relationship under an integrated perspective, which included theoretical interpretation, quantitative assessment, pattern discrimination, and an attribution analysis. Based on the symbiosis theory, the theoretical analysis of the human–water relationship was carried out to analyze the three basic elements of the human–water system, and then the evaluation index system of the human–water symbiosis system was constructed to quantitatively assess the development level of the human system and the water system. The Lotka–Volterra model was used to identify the symbiotic pattern, and the human–water symbiosis index was calculated to characterize the health state of the human–water symbiosis system. The main influencing factors of the human–water symbiosis system were further identified through an attribution analysis. Finally, a case study was carried out with 18 cities in Henan Province. Results reveal that (a) the proposed method can effectively realize the quantitative characterization of the human–water symbiosis relationship, with good applicability and obvious advantages; (b) the human–water symbiosis pattern of cities in Henan Province is dominated by the “human system parasitizes water system (H+W)” pattern, and more attention should be paid to the water system in the subsequent development of it; and (c) the main factors influencing the human system, the water system, and the human–water symbiosis system are the research and development (R&D) personnel equivalent full-time (H7), per capita water resources (W1), and proportion of water conservancy and ecological water conservancy construction investment (W6), respectively. The findings can provide theoretical and methodological support for the study of the human–water symbiosis relationship and sustainable development in other regions. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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13 pages, 545 KB  
Article
How Top-Down Water Regulation Affects the Financial Performance of Enterprises: The River Chief System in China as an Example
by Peipei Zhao, Jiawen Li and Xin Luo
Water 2024, 16(19), 2827; https://doi.org/10.3390/w16192827 - 5 Oct 2024
Cited by 2 | Viewed by 1518
Abstract
As a top-down type of water regulation, the River Chief System (RCS) in China has effectively enhanced urban water quality. Simultaneously, environmental control significantly impacts the financial performance of enterprises. In recent years, the tension between environmental protection and economic development has escalated, [...] Read more.
As a top-down type of water regulation, the River Chief System (RCS) in China has effectively enhanced urban water quality. Simultaneously, environmental control significantly impacts the financial performance of enterprises. In recent years, the tension between environmental protection and economic development has escalated, underscoring the undeniable economic ramifications of stringent water regulations. Enterprises are the fundamental agents of economic activities and environmental impact, thus becoming the primary targets of water environment regulatory policies. This study adopts the differences-in-differences (DID) method and uses a sample of listed enterprises in the Yangtze River Economic Belt region from 2010 to 2021 to study the impact of the RCS on the financial performance of enterprises. The results show that the RCS harms the financial performance of enterprises. This impact primarily manifests through increased environmental protection investments. Conversely, the RCS does not have a positive influence on enterprises’ technological innovation. This indicates the challenge of stringent top-down environmental regulations in stimulating short-term technological advancements and enhancing enterprise performance. Moreover, the adverse effects of the RCS on financial performance are notably pronounced for non-state-owned enterprises and those located in the upper Yangtze River Economic Belt. This suggests that private enterprises and those in less-developed regions exhibit lower resilience to top-down environmental regulations. Full article
(This article belongs to the Special Issue Studies on Water Resource and Environmental Policies)
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15 pages, 2171 KB  
Article
Experimental Study on the Impact of Sorption-Desorption on Nitrate Isotopes
by Yajing Zhao, Zhenbin Li, Chaoyao Zan, Yiman Li, Yan Zhang and Tianming Huang
Water 2024, 16(19), 2807; https://doi.org/10.3390/w16192807 - 2 Oct 2024
Viewed by 1301
Abstract
Nitrate pollution is a global environmental problem, and mean nitrate levels have risen by an estimated 36% in global waterways since 1990. Tracing nitrate sources is important for water quality management, and nitrate isotopes (δ15N-NO3 and δ18O-NO [...] Read more.
Nitrate pollution is a global environmental problem, and mean nitrate levels have risen by an estimated 36% in global waterways since 1990. Tracing nitrate sources is important for water quality management, and nitrate isotopes (δ15N-NO3 and δ18O-NO3) are commonly used for this purpose because of the different isotopic compositions of different sources. However, the impact of nitrate sorption on matrix and desorption from matrix on N and O isotopic composition of nitrate in liquid phase has not been well clarified. To explore the mechanism for the changes in nitrate concentration and isotopes in liquid phase during sorption and desorption, this study took a shale sample (enriched in clay minerals and commonly exposed in the Earth), conducted a series of laboratory experiments for nitrate sorption and desorption, and studied the impact of sorption and desorption on nitrate N and O isotopic composition in liquid phase. The results showed that the shale sample exhibited a rapid sorption and desorption rate for nitrate in the surface water samples, with the nitrate concentration in the solution decreasing from 14.3 mg/L to 4.1 mg/L within 5 min. The sorption data fit the Langmuir model better than that of the Freundlich model. The maximum possible sorption (Qmax) for the shale sample was estimated to be 46 μg/g. Preliminary laboratory experiments showed that changes in δ15N-NO3 values were not obvious, and changes in δ18O-NO3 values in liquid phase were minor during sorption and desorption of the shale sample, suggesting that nitrogen isotopic fractionation can be neglected, and the sorption of nitrate by the shale sample has a very limited impact on the distribution of nitrate isotopes in liquid phase. However, the impact of nitrate desorption on the nitrate isotopes in liquid phase depends on the isotopic composition of exchangeable nitrate in the solid phase, which may be related to antecedent water–rock interactions. This study provides important information for elucidating the evolution mechanism of nitrate and its isotopic compositions following sorption-desorption, and is conducive to revealing the nitrogen cycle law in the environment. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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21 pages, 2910 KB  
Article
Streamflow Prediction with Time-Lag-Informed Random Forest and Its Performance Compared to SWAT in Diverse Catchments
by Desalew Meseret Moges, Holger Virro, Alexander Kmoch, Raj Cibin, Rohith A. N. Rohith, Alberto Martínez-Salvador, Carmelo Conesa-García and Evelyn Uuemaa
Water 2024, 16(19), 2805; https://doi.org/10.3390/w16192805 - 2 Oct 2024
Cited by 6 | Viewed by 4457
Abstract
This study introduces a time-lag-informed Random Forest (RF) framework for streamflow time-series prediction across diverse catchments and compares its results against SWAT predictions. We found strong evidence of RF’s better performance by adding historical flows and time-lags for meteorological values over using only [...] Read more.
This study introduces a time-lag-informed Random Forest (RF) framework for streamflow time-series prediction across diverse catchments and compares its results against SWAT predictions. We found strong evidence of RF’s better performance by adding historical flows and time-lags for meteorological values over using only actual meteorological values. On a daily scale, RF demonstrated robust performance (Nash–Sutcliffe efficiency [NSE] > 0.5), whereas SWAT generally yielded unsatisfactory results (NSE < 0.5) and tended to overestimate daily streamflow by up to 27% (PBIAS). However, SWAT provided better monthly predictions, particularly in catchments with irregular flow patterns. Although both models faced challenges in predicting peak flows in snow-influenced catchments, RF outperformed SWAT in an arid catchment. RF also exhibited a notable advantage over SWAT in terms of computational efficiency. Overall, RF is a good choice for daily predictions with limited data, whereas SWAT is preferable for monthly predictions and understanding hydrological processes in depth. Full article
(This article belongs to the Special Issue Climate Change and Hydrological Processes)
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30 pages, 2600 KB  
Review
Selection, Planning, and Modelling of Nature-Based Solutions for Flood Mitigation
by James Griffiths, Karine E. Borne, Annette Semadeni-Davies and Chris C. Tanner
Water 2024, 16(19), 2802; https://doi.org/10.3390/w16192802 - 1 Oct 2024
Cited by 9 | Viewed by 11485
Abstract
The use of nature-based solutions (NBSs) for hazard mitigation is increasing. In this study, we review the use of NBSs for flood mitigation using a strengths, weaknesses, opportunities, and threats (SWOT) analysis framework for commonly used NBSs. Approaches reviewed include retention and detention [...] Read more.
The use of nature-based solutions (NBSs) for hazard mitigation is increasing. In this study, we review the use of NBSs for flood mitigation using a strengths, weaknesses, opportunities, and threats (SWOT) analysis framework for commonly used NBSs. Approaches reviewed include retention and detention systems, bioretention systems, landcover and soil management, river naturalisation and floodplain management, and constructed and natural wetlands. Existing tools for identification and quantification of direct benefits and co-benefits of NBSs are then reviewed. Finally, approaches to the modelling of NBSs are discussed, including the type of model and model parameterisation. After outlining knowledge gaps within the current literature and research, a roadmap for development, modelling, and implementation of NBSs is presented. Full article
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35 pages, 10116 KB  
Article
Validation of an Enhanced Drinking Water Temperature Model during Distribution
by Mirjam Blokker, Quan Pan and Karel van Laarhoven
Water 2024, 16(19), 2796; https://doi.org/10.3390/w16192796 - 1 Oct 2024
Cited by 1 | Viewed by 1435
Abstract
Drinking water temperatures are expected to increase in the Netherlands due to climate change and the installation of district heating networks as part of the energy transition. To determine effective measures to prevent undesirable temperature increases in drinking water, a model was developed. [...] Read more.
Drinking water temperatures are expected to increase in the Netherlands due to climate change and the installation of district heating networks as part of the energy transition. To determine effective measures to prevent undesirable temperature increases in drinking water, a model was developed. This model describes the temperature in the drinking water distribution network as a result of the transfer of heat from the climate and above and underground heat sources through the soil. The model consists of two coupled applications. The extended soil temperature model (STM+) describes the soil temperatures using a two-dimensional finite element method that includes a drinking water pipe and two hot water pipes coupled with a micrometeorology model. The extended water temperature model (WTM+) describes the drinking water temperature as a function of the surrounding soil temperature (the boundary temperature resulting from the STM+), the thermal sphere of influence where the drinking water temperature influences the soil temperature, and the hydraulics in the drinking water network. Both models are validated with field measurements. This study describes the WTM+. Previous models did not consider the cooling effect of the drinking water on the surrounding soil, which led to an overestimation of the boundary temperature and how quickly the drinking water temperature reaches this boundary temperature. The field measurements show the improved accuracy of the WTM+ when considering one to two times the radius of the drinking water pipe as the thermal sphere of influence around the pipe. Full article
(This article belongs to the Special Issue Urban Water Systems: Challenges in Current Environment)
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15 pages, 1905 KB  
Article
Effect of Light Intensity on the Growth and Nutrient Uptake of the Microalga Chlorella sorokiniana Cultivated in Biogas Plant Digestate
by Thomas L. Palikrousis, Christos Manolis, Sotirios D. Kalamaras and Petros Samaras
Water 2024, 16(19), 2782; https://doi.org/10.3390/w16192782 - 30 Sep 2024
Cited by 13 | Viewed by 5111
Abstract
This study investigated the effect of light intensity on the growth and nutrient uptake of Chlorella sorokiniana cultivated in nitrogen-rich anaerobic digestion wastewater. Three light intensities (20, 68, and 162 µmol m⁻2 s⁻1) were applied over a 30-day period with [...] Read more.
This study investigated the effect of light intensity on the growth and nutrient uptake of Chlorella sorokiniana cultivated in nitrogen-rich anaerobic digestion wastewater. Three light intensities (20, 68, and 162 µmol m⁻2 s⁻1) were applied over a 30-day period with a 16:8 h light–dark photoperiod. The goal was to understand how light affects biomass productivity, nutrient assimilation, and biochemical composition under varying nitrogen concentrations originating from biogas plant digestate, up to 5 g L⁻1. The results showed that higher light intensities significantly boosted biomass production, achieving a five-fold increase at 162 µmol m⁻2 s⁻1 compared to 20 µmol m⁻2 s⁻1. Nutrient uptake followed a similar pattern, with 94% of ammonium nitrogen removed in 7 days under high light, compared to 55% after 30 days under low light. Phosphorus content was also completely removed after 7 days under light intensities of 68 and 162 µmol m⁻2 s⁻1. Additionally, elevated light intensity led to increased lipid accumulation (from 29.7% to 34%) and reduced protein content (from 30.9% to 26.1%), with carbohydrate content not being affected by light intensity. These findings highlight light intensity as a critical factor for optimizing microalgae cultivation in nitrogen-rich biogas digestate, promoting both effective nutrient removal and biomass production for potential bioenergy applications. Full article
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29 pages, 7501 KB  
Article
Water Resources’ AI–ML Data Uncertainty Risk and Mitigation Using Data Assimilation
by Nick Martin and Jeremy White
Water 2024, 16(19), 2758; https://doi.org/10.3390/w16192758 - 27 Sep 2024
Cited by 7 | Viewed by 1804
Abstract
Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), learns by training and is restricted by the amount and quality of training data. Training involves a tradeoff between prediction bias and variance controlled by model complexity. Increased model complexity decreases prediction [...] Read more.
Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), learns by training and is restricted by the amount and quality of training data. Training involves a tradeoff between prediction bias and variance controlled by model complexity. Increased model complexity decreases prediction bias, increases variance, and increases overfitting possibilities. Overfitting is a significantly smaller training prediction error relative to the trained model prediction error for an independent validation set. Uncertain data generate risks for AI–ML because they increase overfitting and limit generalization ability. Specious confidence in predictions from overfit models with limited generalization ability, leading to misguided water resource management, is the uncertainty-related negative consequence. Improved data is the way to improve AI–ML models. With uncertain water resource data sets, like stream discharge, there is no quick way to generate improved data. Data assimilation (DA) provides mitigation for uncertainty risks, describes data- and model-related uncertainty, and propagates uncertainty to results using observation error models. A DA-derived mitigation example is provided using a common-sense baseline, derived from an observation error model, for the confirmation of generalization ability and a threshold identifying overfitting. AI–ML models can also be incorporated into DA to provide additional observations for assimilation or as a forward model for prediction and inverse-style calibration or training. The mitigation of uncertain data risks using DA involves a modified bias–variance tradeoff that focuses on increasing solution variability at the expense of increased model bias. Increased variability portrays data and model uncertainty. Uncertainty propagation produces an ensemble of models and a range of predictions. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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16 pages, 2262 KB  
Article
Decontamination Potential of Ultraviolet Type C Radiation in Water Treatment Systems: Targeting Microbial Inactivation
by Abayomi Olusegun Adeniyi and Modupe Olufunmilayo Jimoh
Water 2024, 16(19), 2725; https://doi.org/10.3390/w16192725 - 25 Sep 2024
Cited by 4 | Viewed by 5698
Abstract
Access to safe water and sanitation is a critical global challenge, posing significant health risks worldwide due to waterborne diseases. This study investigates the efficacy of ultraviolet type C radiation as a disinfection method for improving water quality. The research elucidates UV-C’s mechanism [...] Read more.
Access to safe water and sanitation is a critical global challenge, posing significant health risks worldwide due to waterborne diseases. This study investigates the efficacy of ultraviolet type C radiation as a disinfection method for improving water quality. The research elucidates UV-C’s mechanism of action, highlighting its ability to disrupt DNA and RNA replication, thereby inactivating pathogens. Furthermore, the study analyses the influence of key factors on UV-C disinfection effectiveness, including water turbidity and the presence of dissolved organic matter, which can attenuate UV-C penetration and reduce treatment efficiency. The experimental results demonstrate a substantial reduction in microbial content following UV-C treatment. River water samples exhibited a 57.143% reduction in microbial load, while well water samples showed a 50% reduction. Notably, Escherichia coli (E. coli) concentrations decreased significantly, with an 83.33% reduction in well water and a 62.5% reduction in borehole water. This study makes a novel contribution to the understanding of UV-C disinfection by identifying the presence of resistant organisms, including Adenoviruses, Bacterial spores, and the Protozoan Acanthamoeba, in water samples. This finding expands the scope of UV-C research beyond easily culturable bacteria. To address this challenge, future investigations should explore synergistic disinfection strategies, such as combining UV-C treatment with advanced oxidation processes. Optimising UV-C system designs and developing robust, real-time monitoring systems capable of detecting and quantifying known and emerging UV-resistant pathogens are crucial for ensuring comprehensive water decontamination. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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25 pages, 398 KB  
Review
Beyond Bioremediation: The Untapped Potential of Microalgae in Wastewater Treatment
by Davide Liberti, Filipa Pinheiro, Beatriz Simões, João Varela and Luísa Barreira
Water 2024, 16(19), 2710; https://doi.org/10.3390/w16192710 - 24 Sep 2024
Cited by 19 | Viewed by 10427
Abstract
Microalgae-based wastewater bioremediation has emerged as a promising and sustainable solution for water purification by harnessing the natural ability of microalgae to absorb and transform pollutants. In the literature, it is possible to find diverse microalgae applications in wastewater treatment, highlighting their efficiency [...] Read more.
Microalgae-based wastewater bioremediation has emerged as a promising and sustainable solution for water purification by harnessing the natural ability of microalgae to absorb and transform pollutants. In the literature, it is possible to find diverse microalgae applications in wastewater treatment, highlighting their efficiency in nutrient removal, heavy metal sequestration, and overall water quality enhancement. Although microalgae demonstrate remarkable potential for wastewater treatment, there is a critical gap in research concerning the utilization of biomass produced during the treatment process, including large-scale biomass harvesting methods, economic viability assessments, and the exploration of innovative downstream applications. By shedding light on these deficiencies, the aim of this review is to encourage further research and development to maximize the potential of microalgae in removing wastewater pollution and the application of biomass derived from the treatment. In conclusion, this review not only underscores the overall efficiency of microalgae in wastewater bioremediation but also emphasizes the necessity of a more comprehensive approach that considers the full lifecycle of microalgae, from wastewater treatment to innovative applications of biomass, addressing both environmental and economic concerns. Full article
(This article belongs to the Special Issue Persistent and Emerging Organic Contaminants in Natural Environments)
28 pages, 910 KB  
Review
Microplastics’ Impact on the Environment and the Challenging Selection of Reliable Key Biomonitors
by Luigi Rosati, Federica Carraturo, Fiore Capozzi, Teresa Chianese, Alessandra La Pietra, Michela Salamone, Valeria Spagnuolo, Ida Ferrandino and Simonetta Giordano
Water 2024, 16(18), 2637; https://doi.org/10.3390/w16182637 - 17 Sep 2024
Cited by 4 | Viewed by 5365
Abstract
Microplastics (MPs) persist for long periods in the environment, causing adverse effects on aquatic and terrestrial ecosystems. The accumulation of MPs in various trophic levels mostly depends on weathering phenomena, their reduced dimensions and the improved bioavailability; this ultimately causes their ingestion by [...] Read more.
Microplastics (MPs) persist for long periods in the environment, causing adverse effects on aquatic and terrestrial ecosystems. The accumulation of MPs in various trophic levels mostly depends on weathering phenomena, their reduced dimensions and the improved bioavailability; this ultimately causes their ingestion by organisms living in different niches. The modern concern about MPs toxicity collides with the current unavailability of standardized and reliable methodologies to assess the risks associated with the exposure of organisms from different habitats. Hence, the identification and selection of appropriate biomonitors for MPs pollution risk assessment should focus on the identification of easy-to-implement assays, rapidly interpretable results (e.g., based on the MPs bioaccumulation capabilities in their tissues) and standardizable methodologies. The present review analyzed some emerging biomonitors exploited for MPs evaluation, selected and examined according to their potential use as specific biological indicators for diverse environments. The research was focused on plants, as biological models for airborne microfibers toxicity evaluation; mussels, as key organisms for the establishment of MPs accumulation in marine environments; land snails, representing emerging organisms selected for studies of MPs’ impact on soil. Furthermore, recent findings evidenced the influence of microplastics on the composition of environmental microbiota, enhancing pathogenic biofilms formation, leading to increased water, soil, food, crops and waste contamination. Disposing of harmonized and validated methods to study MPs’ impact on the environment, integrated with promising machine learning tools, might sensibly support the risk management strategies protecting human and animal health. Full article
(This article belongs to the Section Water and One Health)
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20 pages, 2569 KB  
Article
Seasonal Variability and Hydrological Patterns Influence the Long-Term Trends of Nutrient Loads in the River Po
by Edoardo Cavallini, Pierluigi Viaroli, Mariachiara Naldi, Mattia Saccò, Alessandro Scibona, Elena Barbieri, Silvia Franceschini and Daniele Nizzoli
Water 2024, 16(18), 2628; https://doi.org/10.3390/w16182628 - 16 Sep 2024
Cited by 7 | Viewed by 2277
Abstract
This study investigates the long-term trends (1992–2022) of nitrogen and phosphorus loadings exported by the River Po to the Adriatic Sea, to better analyse how changes in hydrology are affecting the timing and magnitude of river nutrient loads. We used 30 years of [...] Read more.
This study investigates the long-term trends (1992–2022) of nitrogen and phosphorus loadings exported by the River Po to the Adriatic Sea, to better analyse how changes in hydrology are affecting the timing and magnitude of river nutrient loads. We used 30 years of monitoring data in order to (a) identify the main temporal patterns and their interactions at a decadal, annual and seasonal scale, (b) estimate precipitation effects on load formation and evaluate whether and to which extent the hydrological regime affects nutrient export across the years and (c) analyse the nutrient export regime at a monthly scale and the main transport dynamic of N and P chemical species (hydrological vs. biogeochemical control). The long-term analysis shows a general decrease of both P and N loadings, but the trends are different between the elements and their chemical species, as well as undergoing different seasonal variations. We found a statistically significant relationships between precipitation and loads, which demonstrates that precipitation patterns drive the exported load at the intra- and interannual time scales considered in this study. Precipitation-induced load trends trigger seasonal changes in nutrient deliveries to the sea, peaking in spring and autumn. The nitrogen decrease is mainly concentrated in the summer dry period, while total phosphorus diminishes mainly in spring and autumn. This mismatch of N and P results in variable molar N:P ratios within the year. The effects of extreme drought and flood events, along with the progressive decrease in the snowmelt contribution to water fluxes, are expected to exacerbate the variability in the N and P loadings, which in turn is expected to perturbate the biodiversity, food webs and trophic state of the Northern Adriatic Sea. Full article
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22 pages, 3249 KB  
Article
LSTM-Autoencoder Based Detection of Time-Series Noise Signals for Water Supply and Sewer Pipe Leakages
by Yungyeong Shin, Kwang Yoon Na, Si Eun Kim, Eun Ji Kyung, Hyun Gyu Choi and Jongpil Jeong
Water 2024, 16(18), 2631; https://doi.org/10.3390/w16182631 - 16 Sep 2024
Cited by 8 | Viewed by 4015
Abstract
The efficient management of urban water distribution networks is crucial for public health and urban development. One of the major challenges is the quick and accurate detection of leaks, which can lead to water loss, infrastructure damage, and environmental hazards. Many existing leak [...] Read more.
The efficient management of urban water distribution networks is crucial for public health and urban development. One of the major challenges is the quick and accurate detection of leaks, which can lead to water loss, infrastructure damage, and environmental hazards. Many existing leak detection methods are ineffective, especially in complex and aging pipeline networks. If these limitations are not overcome, it can result in a chain of infrastructure failures, exacerbating damage, increasing repair costs, and causing water shortages and public health risks. The leak issue is further complicated by increasing urban water demand, climate change, and population growth. Therefore, there is an urgent need for intelligent systems that can overcome the limitations of traditional methodologies and leverage sophisticated data analysis and machine learning technologies. In this study, we propose a reliable and advanced method for detecting leaks in water pipes using a framework based on Long Short-Term Memory (LSTM) networks combined with autoencoders. The framework is designed to manage the temporal dimension of time-series data and is enhanced with ensemble learning techniques, making it sensitive to subtle signals indicating leaks while robustly dealing with noise signals. Through the integration of signal processing and pattern recognition, the machine learning-based model addresses the leak detection problem, providing an intelligent system that enhances environmental protection and resource management. The proposed approach greatly enhances the accuracy and precision of leak detection, making essential contributions in the field and offering promising prospects for the future of sustainable water management strategies. Full article
(This article belongs to the Special Issue Prediction and Assessment of Hydrological Processes)
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24 pages, 853 KB  
Review
The Convergence of Antibiotic Contamination, Resistance, and Climate Dynamics in Freshwater Ecosystems
by Marcelo Pedrosa Gomes
Water 2024, 16(18), 2606; https://doi.org/10.3390/w16182606 - 14 Sep 2024
Cited by 32 | Viewed by 10983
Abstract
The convergence of antibiotic contamination, antimicrobial resistance (AMR), and climate dynamics poses a critical environmental and public health challenge. Freshwater ecosystems are increasingly threatened by the persistent presence of antibiotics, which, coupled with rising global temperatures, accelerate the development and spread of AMR. [...] Read more.
The convergence of antibiotic contamination, antimicrobial resistance (AMR), and climate dynamics poses a critical environmental and public health challenge. Freshwater ecosystems are increasingly threatened by the persistent presence of antibiotics, which, coupled with rising global temperatures, accelerate the development and spread of AMR. This review examines the sources, pathways, and mechanisms through which antibiotics enter freshwater systems and how climate change exacerbates these processes. This review discusses this convergence’s ecological and human health impacts, highlighting the implications for biodiversity and public health. It also explored the current monitoring and mitigation strategies, including advanced oxidation processes, natural-based solutions, and policy interventions. Finally, this review identifies critical research gaps and proposes future directions for managing the intertwined threats of antibiotic contamination, resistance, and climate change. It emphasizes the need for integrated, multidisciplinary approaches to protect freshwater resources in an increasingly volatile global environment. Full article
(This article belongs to the Special Issue Toxicology in Freshwater Ecosystems)
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