Water

14 pages, 9624 KiB

Open AccessArticle

Comprehensive Study on the Electrical Characteristics and Full-Spectrum Tracing of Water Sources in Water-Rich Coal Mines

by Donglin Dong, Fangang Meng, Jialun Zhang, Enyu Zhang and Xindong Lin

Water 2024, 16(18), 2673; https://doi.org/10.3390/w16182673 (registering DOI) - 19 Sep 2024

Abstract

This study addresses the complex hydrogeological conditions and frequent inrush water incidents in the Donghuantuo coal mine by proposing a novel spectral tracing technique aimed at rapidly and accurately identifying the sources of inrush water. Through the analysis of electrical data from the [...] Read more.

This study addresses the complex hydrogeological conditions and frequent inrush water incidents in the Donghuantuo coal mine by proposing a novel spectral tracing technique aimed at rapidly and accurately identifying the sources of inrush water. Through the analysis of electrical data from the Donghuantuo mine, the electrical characteristics of the mine floor were examined. Systematic sampling of water from the primary aquifers within the mining area was conducted, followed by detailed spectral measurements, resulting in the establishment of a spectral database for inrush water sources in the Donghuantuo mine. The chaotic sparrow search optimization algorithm (CSSOA) was employed to optimize the key parameters of the random forest (RF) model, leading to the development of the CSSOA-RF spectral tracing identification model. This model demonstrated outstanding classification performance in the test set, achieving an accuracy of 100%. This research offers a novel, more accurate, and reliable method for identifying the sources of inrush water, facilitating the rapid identification of sources in coal-bearing regions of North China and reducing disaster losses. Although the geological structure of the study area is relatively simple, the research achieved significant results in identifying both single and mixed water sources. However, further validation and optimization are needed for its applicability in more complex geological conditions. The findings of this study provide crucial technical support for safe mining operations and hold significant reference value for water hazard prevention in similar regions. Full article

(This article belongs to the Special Issue Innovative Technologies for Mine Water Treatment)

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15 pages, 5769 KiB

Open AccessArticle

The Occurrence of Microplastics Pollution in the Surface Water and Sediment of Lake Chenghai in Southwestern China

by Lizeng Duan, Liancong Luo, Longwu Zhang, Donglin Li, Huayu Li, Tianbao Xu, Jing Xu and Hucai Zhang

Water 2024, 16(18), 2672; https://doi.org/10.3390/w16182672 (registering DOI) - 19 Sep 2024

Abstract

Microplastics (MPs) in freshwater environments, such as lakes, have become a significant issue in recent years. However, studies on the lakes of the Yunnan Plateau have been limited. To understand the pollution status and sources of MPs in Lake Chenghai (LCH), 36 sampling [...] Read more.

Microplastics (MPs) in freshwater environments, such as lakes, have become a significant issue in recent years. However, studies on the lakes of the Yunnan Plateau have been limited. To understand the pollution status and sources of MPs in Lake Chenghai (LCH), 36 sampling sites were selected for the surface water and sediment samples. Morphological identification, compositional analysis, abundance measurement, and spatial distribution mapping of the MPs were carried out. We also performed correlation analyses with hydrological parameters and physicochemical indexes of water and sediments. We aimed to uncover the spatial distribution patterns of the MPs in LCH, along with potential sources. Our findings revealed that all samples contained MPs and all of them were fibers. The abundance of MPs ranged from 90 to 770 n/m³ (329.44 rms) in the water and from 10 to 115 n/kg (43.19 rms) in the sediments, with particle sizes of 1-3 mm and less than 1 mm, respectively. Transparent MPs were prevalent, comprising 68% of the MPs found in the water and 63% in the sediments. The primary components of the MPs were polypropylene (PP), polyethylene terephthalate (PET), and man-made fibers (rayon). The spatial distribution showed an increasing concentration of MPs from south to north in the surface water, whereas the opposite trend was found in the sediments. Human activities, prevailing winds, and the river flowing into the lake influenced the spatial distribution pattern of the MPs. The abundance and assemblage characteristics of the MPs were directly correlated with the factors of nitrogen, phosphorus, and particle size in the water and sediments, but the correlation was not significant. The main source of MPs was the production and livelihoods of the neighboring residents, especially the use of fishing gears and nets. Since LCH shows significant pollution from MPs, there is an urgent need to control and manage the watershed in order to reduce the input of MPs in the future. Full article

(This article belongs to the Special Issue Plateau Lake Water Quality and Biodiversity: Impacts of Human Activity and Trans-regional Water Diversion)

16 pages, 1305 KiB

Open AccessArticle

Biochar Weakens the Efficiency of Nitrification Inhibitors and Urease Inhibitors in Mitigating Greenhouse Gas Emissions from Soil Irrigated with Alternative Water Resources

by Zhen Tao, Yuan Liu, Siyi Li, Baogui Li, Xiangyang Fan, Chuncheng Liu, Chao Hu, Shuiqing Zhang and Zhongyang Li

Water 2024, 16(18), 2671; https://doi.org/10.3390/w16182671 (registering DOI) - 19 Sep 2024

Abstract

While previous studies have suggested that biochar, nitrification inhibitors, and urease inhibitors may reduce soil greenhouse gas emissions, their effectiveness in soils irrigated with alternative water resources remains unclear. To compensate for this, reclaimed water and livestock wastewater were utilized as alternative water [...] Read more.

While previous studies have suggested that biochar, nitrification inhibitors, and urease inhibitors may reduce soil greenhouse gas emissions, their effectiveness in soils irrigated with alternative water resources remains unclear. To compensate for this, reclaimed water and livestock wastewater were utilized as alternative water resources alongside groundwater control. Nitrapyrin and N-(n-butyl) thiophosphoric triamide and biochar were applied to the soil either individually or in combination, and a no-substance treatment (NS) was included for comparison. The results revealed that reclaimed water and livestock wastewater irrigation exacerbated the global warming potential. Compared to the NS, all exogenous substance treatments suppressed nitrous oxide (N₂O) emissions while increasing carbon dioxide (CO₂) emissions, and affecting methane (CH₄) emissions varied across treatments irrespective of the water types. Interestingly, the additional biochar reduced the inhibitory effect of the inhibitors on the greenhouse effect. Using nitrification inhibitors reduced the global warming potential by 48.3% and 50.1% under reclaimed water and livestock wastewater irrigation, respectively. However, when nitrification inhibitors were applied in combination with biochar, the global warming potential was increased by 52.1–83.4% compared to nitrification inhibitors alone, and a similar trend was also observed in the scenario of urease inhibitors, with increases ranging from 8.8 to 35.1%. Therefore, the combined application of biochar and inhibitors should be approached cautiously, considering the potential for increased greenhouse gas emissions. Full article

(This article belongs to the Special Issue Safe Application of Reclaimed Water in Agriculture)

14 pages, 828 KiB

Open AccessArticle

Ichthyoplankton Assemblages from the Coasts of Hamsilos Nature Park, Sinop, Southern Black Sea: Biodiversity, Abundance, and Relationships with Environmental Variables

by Orçin Uygun and Funda Üstün

Water 2024, 16(18), 2670; https://doi.org/10.3390/w16182670 (registering DOI) - 19 Sep 2024

Abstract

This study was conducted using monthly data collected between July 2015 and June 2016 in the marine area of Hamsilos Nature Park, located in Sinop, Southern Black Sea. The primary objectives were to determine the diversity of ichthyoplankton assemblages, examine seasonal variations, assess [...] Read more.

This study was conducted using monthly data collected between July 2015 and June 2016 in the marine area of Hamsilos Nature Park, located in Sinop, Southern Black Sea. The primary objectives were to determine the diversity of ichthyoplankton assemblages, examine seasonal variations, assess spatial differences between the inner and outer parts of Hamsilos Bay, and highlight the ecological relationships of the predominant species with environmental factors. The comprehensive collection during the study resulted in a mean abundance of 2217 eggs.10 m² and 2743 larvae.10 m², with 28 species belonging to 21 families identified. Specifically, Engraulis encrasicolus is the most abundant in spring and summer, Gaidropsarus mediterraneus is the most abundant in autumn, and Sprattus sprattus is the most abundant in winter. A temporal analysis revealed the highest abundances in August, September, and July, with the lowest in April, May, and February. Significant seasonal differences in abundance and diversity were detected. No spatial differences were found between the inner and outer areas of Hamsilos Bay. Small pelagic species dominated the ichthyoplankton community, while demersal species, though diverse, were less abundant. According to the results of the DistLM analysis, the structure of the ichthyoplankton community is influenced by temperature and salinity. During the study, the water temperature ranged from 8.35 °C in February to 25.50 °C in August, and the salinity varied from 17.67 psu in September to 19.04 psu in May. Full article

(This article belongs to the Special Issue Implementation of Biodiversity and Ecosystem Services in Marine Ecosystem Management, 3rd Edition)

16 pages, 2529 KiB

Open AccessArticle

Hydrological Data Projection Using Empirical Mode Decomposition: Applications in a Changing Climate

by Che-Wei Chang, Jung-Chen Lee and Wen-Cheng Huang

Water 2024, 16(18), 2669; https://doi.org/10.3390/w16182669 (registering DOI) - 19 Sep 2024

Abstract

This paper demonstrates the effectiveness and superiority of Empirical Mode Decomposition (EMD) in projecting non-stationary hydrological data. The study focuses on daily Sea Surface Temperature (SST) sequences in the Niño 3.4 region and uses EMD to forecast the probability of El Niño events. [...] Read more.

This paper demonstrates the effectiveness and superiority of Empirical Mode Decomposition (EMD) in projecting non-stationary hydrological data. The study focuses on daily Sea Surface Temperature (SST) sequences in the Niño 3.4 region and uses EMD to forecast the probability of El Niño events. Applying the Mann–Kendall test at the 5% significance level reveals a significant increasing trend in SST changes in this region, particularly noticeable after 1980. This trend is associated with the occurrence of El Niño and La Niña events, which have a recurrence interval of approximately 8.4 years and persist for over a year. The modified Oceanic Niño Index (ONI) proposed in this study demonstrates high forecast accuracy, with 97.56% accuracy for El Niño and 89.80% for La Niña events. Additionally, the EMD of SST data results in 13 Intrinsic Mode Functions (IMFs) and a residual component. The oscillation period increases with each IMF level, with IMF7 exhibiting the largest amplitude, fluctuating between ±1 °C. The residual component shows a significant upward trend, with an average annual increase of 0.0107 °C. These findings reveal that the EMD-based data generation method overcomes the limitations of traditional hydrological models in managing non-stationary sequences, representing a notable advancement in data-driven hydrological time series modeling. Practically, the EMD-based 5-year moving process can generate daily sea temperature sequences for the coming year in this region, offering valuable insights for assessing El Niño probabilities and facilitating annual updates. Full article

(This article belongs to the Special Issue Watershed Hydrology and Management under Changing Climate)

20 pages, 4588 KiB

Open AccessArticle

Dynamic Responses in a Pipe Surrounded by Compacted Soil Suffering from Water Hammer with Fluid–Structure–Soil Interactions

by Qiang Guo, Minyao Xu, Guizhong Xu and Huiling Xu

Water 2024, 16(18), 2668; https://doi.org/10.3390/w16182668 (registering DOI) - 19 Sep 2024

Abstract

The current literature analyzing the dynamic response of coupled pipelines neglects the crucial interplay between the pipelines themselves and these constraints. This overlooked interaction has substantial influence on the fluid–structure coupling response, particularly in scenarios involving continuous constraints. We focus on a piping [...] Read more.

The current literature analyzing the dynamic response of coupled pipelines neglects the crucial interplay between the pipelines themselves and these constraints. This overlooked interaction has substantial influence on the fluid–structure coupling response, particularly in scenarios involving continuous constraints. We focus on a piping system surrounded by compacted soil, which is regarded as unbounded homogeneous elastic soil that suffers from water hammer. This study established a one-dimensional model for water pipe-embedded compacted soil with fluid–structure–soil interaction. Taking fluid–structure–soil interaction into account, fluid–structure interactions (FSIs) include Poisson coupling, junction coupling emerging at the fluid–structure interface, and pipe–soil coupling (PSC) emerging at the pipe–soil interface. In this study, as soil is assumed to be a homogeneous, isotropic elastic material, the coupling responses are more complex than those of an exposed pipe, and the relevant mechanisms justify further exploration to obtain well-predicted results. To mathematically describe this system considering fluid–structure–soil interaction, the four-equation FSI model was modified to accommodate the piping system surrounded by unbounded homogeneous elastic soil, employing the finite volume method (FVM) as a means to tackle and solve the dynamic problems with FSI and PSC, which partitions the computational domain into a finite number of control volumes and discretizes governing equations within each volume. The results were validated by the experimental and numerical results. Then, dynamic FSI responses to water hammer were studied in a reservoir–pipe–reservoir physical system. The hydraulic pressure, pipe wall stress, and axial motion were discussed with respect to different parameters. With the PSC and FSI taken into account, fluid, soil, and pipe signals were obviously observed. The results revealed the structural and fluid modes. Dynamic responses have been proven to be difficult to understand and predict. Despite this, this study provides a tractable method to capture more accurate systematic characteristics of a water pipe embedded in soil. Full article

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

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13 pages, 1477 KiB

Open AccessArticle

In Vitro Potential of Antioxidant Extracts from Gracilaria gracilis Cultivated in Integrated Multi-Trophic Aquaculture (IMTA) for Marine Biobased Sector

by Simona Manuguerra, Rosaria Arena, Eleonora Curcuraci, Giuseppe Renda, Maxime Rannou, Claire Hellio, Concetta Maria Messina and Andrea Santulli

Water 2024, 16(18), 2667; https://doi.org/10.3390/w16182667 - 19 Sep 2024

Abstract

This study aimed to evaluate the antioxidant activity of bioactive compounds extracted from Gracilaria gracilis cultivated in an integrated multi-trophic aquaculture (IMTA) system by different extraction solvents and to investigate the potential capacity of the extracts in cellular systems against environmental pollutants. The [...] Read more.

This study aimed to evaluate the antioxidant activity of bioactive compounds extracted from Gracilaria gracilis cultivated in an integrated multi-trophic aquaculture (IMTA) system by different extraction solvents and to investigate the potential capacity of the extracts in cellular systems against environmental pollutants. The global yields, total polyphenol contents, and antioxidant activity were assessed on G. gracilis by DPPH radical scavenging activity, comparing the antioxidant extraction efficiency of the different solvents (ethanol 80%, acetone 70%, N-hexane, and water). Ethanol extract, granted by the highest extractive yield and antioxidant capacity, was tested in vitro in the Sparus aurata fibroblast (SAF-1) cell line to evaluate its protective role against oxidative stress induced by the chemical flame retardant 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47). The results demonstrate that the cells pretreated with G. gracilis extract were protected against oxidative stress and had improved cell viability, cellular antioxidant defense system, and cell cycle control, as demonstrated by the gene expression on some biomarkers related to the cell cycle (p53) and oxidative stress (nrf2, sod, and cat). These results confirm that bioactive compounds obtained from seaweeds cultivated in IMTAs could contribute to producing high-value ingredients that are able to counteract environmental stressors, for the growth of the marine biobased industrial sector and the expansion of new value chains. Full article

(This article belongs to the Special Issue Aquatic Ecotoxicology: A Tool for Monitoring the Effects of Anthropogenic Chemical Contamination on Fisheries and Aquaculture)

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19 pages, 3666 KiB

Open AccessArticle

Optimization of Secondary Chlorination in Water Distribution Systems for Enhanced Disinfection and Reduced Chlorine Odor Using Deep Belief Network and NSGA-II

by Bo Dong, Shihu Shu and Dengxin Li

Water 2024, 16(18), 2666; https://doi.org/10.3390/w16182666 - 19 Sep 2024

Abstract

This research explores the strategic optimization of secondary chlorination in water distribution systems (WDSs), in order to enhance the efficiency of disinfection while mitigating odor and operational costs and promoting sustainability in water quality management. The methodology integrates EPANET simulations for water hydraulic [...] Read more.

This research explores the strategic optimization of secondary chlorination in water distribution systems (WDSs), in order to enhance the efficiency of disinfection while mitigating odor and operational costs and promoting sustainability in water quality management. The methodology integrates EPANET simulations for water hydraulic and quality modeling with a deep belief network (DBN) within the deep learning framework for accurate chloric odor prediction. Utilizing the non-dominated sorting genetic algorithm-II (NSGA-II), this methodology systematically balances the objectives of chloride dosage and chloramine formation. It combines a chloric odor intensity assessment, a multi-component kinetic model, and dual-objective optimization to conduct a comparative analysis of case studies on secondary chlorination strategies. The optimal configuration with five secondary chlorination stations reduced chloric odor intensity to 1.20 at a cost of USD 40,020.77 per year in Network A while, with eight stations, chloric odor intensity was reduced to 0.88 at a cost of USD 71,405.38 per year in Network B. The results demonstrate a balanced trade-off between odor intensity and operational cost on one hand and sustainability on the other hand, highlighting the importance of precise chlorine management to improve both the sensory and safety qualities of drinking water while ensuring the sustainable use and management of water resources. Full article

(This article belongs to the Section Urban Water Management)

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12 pages, 6807 KiB

Open AccessArticle

Green Synthesis of Iron-Based Nanoparticles Using Pomegranate Leaf Extracts: Characterization, Biomolecules and Indole Removal

by Huifang Sun, Yanjun Liu, Yifan Zhou, Zuliang Chen and Jianfeng Li

Water 2024, 16(18), 2665; https://doi.org/10.3390/w16182665 - 19 Sep 2024

Abstract

This study investigates the synthesis of iron-based nanoparticles (Fe NPs) using pomegranate leaf extracts and their application in removing indole, a persistent organic pollutant commonly found in wastewater. The physicochemical properties of the synthesized Fe NPs and the active biomolecules in the pomegranate [...] Read more.

This study investigates the synthesis of iron-based nanoparticles (Fe NPs) using pomegranate leaf extracts and their application in removing indole, a persistent organic pollutant commonly found in wastewater. The physicochemical properties of the synthesized Fe NPs and the active biomolecules in the pomegranate leaf extracts were comprehensively characterized. Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) analyses revealed that the Fe NPs exhibited quasi-spherical shapes, with sizes ranging from 75 to 105 nm. Energy-Dispersive X-ray Spectroscopy (EDS) confirmed a homogeneous distribution of elements, including C, O, Fe, and S, on the nanoparticle surfaces, with weight percentages of 43.59%, 42.95%, 12.58%, and 0.88%, respectively. Fourier-transform infrared spectroscopy (FTIR) identified key functional groups like −OH, −COOH, and −C=O, which are essential for the capping and stabilization of the nanoparticles. Biomolecules such as ellagic acid (C₁₄H₆O₈) and gallic acid (C₇H₆O₅) functioned as reducing agents, improving nanoparticle dispersion and preventing aggregation. The synthesized Fe NPs quickly achieved 45.5% removal of indole within just 20 min and maintained a stable removal efficiency of approximately 51.4% after 90 min. This performance was attributed to the synergetic interaction between the biomolecules and the nanoparticles, with the monolayer adsorption of indole molecules on the Fe NP surfaces likely setting an upper limit on the maximum achievable removal efficiency. It appears from this study that pomegranate leaf extracts can be effectively utilized to synthesize Fe NPs as a novel and eco-friendly approach, demonstrating promising potential for the rapid removal of indole from aqueous solutions. Full article

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

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21 pages, 10296 KiB

Open AccessArticle

Response to Pumping of Wells in Carbonate and Karst Aquifers and Effect on the Assessment of Sustainable Well Yield: Some Examples from Southern Italy

by Vincenzo Piscopo, Matteo Paoletti and Chiara Sbarbati

Water 2024, 16(18), 2664; https://doi.org/10.3390/w16182664 - 19 Sep 2024

Abstract

Carbonate and karst aquifers are of great importance for human water supplies, for supporting aquatic habitats and providing ecosystem services. Optimizing the groundwater withdrawals is therefore essential for obtaining the maximum flow rate for human purposes while minimizing the negative effects on the [...] Read more.

Carbonate and karst aquifers are of great importance for human water supplies, for supporting aquatic habitats and providing ecosystem services. Optimizing the groundwater withdrawals is therefore essential for obtaining the maximum flow rate for human purposes while minimizing the negative effects on the environment. In particular, when the abstraction of groundwater occurs through wells, the problem of defining the sustainable yield arises. This study analyzes pumping tests conducted in carbonate and karst aquifers in southern Italy to derive indications for defining the sustainable yield of yields. The four examined cases concern the Mesozoic–Cenozoic platform and transition pelagic carbonate rocks characterized by different degree of fracturing and karstification and hosting a carbonate aquifer with variable average groundwater yields. The analysis compared drawdown–time trends and their derivatives for 35 pumping tests with theoretical curves to identify the flow dimension. Parameters useful for examining the well yields were then determined. The results show that the response to the pumping of the investigated aquifers is very variable, both among the different sites and within the same site. Well yields are very different due to aquifer heterogeneity, local hydrostratigraphy and structural setting, and position of the pumping center within the groundwater flow system. To determine the operational pumping rate for a well in this environment, this study emphasizes the importance of analyzing drawdown trends over time to correctly predict the well’s long-term response to pumping. Specifically, when pumping induces a steady-state drawdown response, the focus for defining the sustainable abstraction shifts to the basin or aquifer scale. Conversely, when a transient drawdown response to pumping results, the well’s capacity to capture groundwater becomes the primary factor for well yield and its sustainability. Full article

(This article belongs to the Special Issue Karst Dynamic System and Its Water Resources Environmental Effects, 2nd Edition)

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17 pages, 8248 KiB

Open AccessArticle

Mapping of Soil Erosion Vulnerability in Wadi Bin Abdullah, Saudi Arabia through RUSLE and Remote Sensing

by Majed Alsaihani and Raied Alharbi

Water 2024, 16(18), 2663; https://doi.org/10.3390/w16182663 - 19 Sep 2024

Abstract

This study investigates soil loss in the Wadi Bin Abdullah watershed using the Revised Universal Soil Loss Equation (RUSLE) combined with advanced tools, such as remote sensing and the Geographic Information System (GIS). By leveraging the ALOS PALSAR Digital Elevation Model (DEM), Climate [...] Read more.

This study investigates soil loss in the Wadi Bin Abdullah watershed using the Revised Universal Soil Loss Equation (RUSLE) combined with advanced tools, such as remote sensing and the Geographic Information System (GIS). By leveraging the ALOS PALSAR Digital Elevation Model (DEM), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) rainfall data, and the Digital Soil Map of the World (DSMW), the research accurately evaluates soil loss loads. The methodology identifies significant variations in soil loss rates across the entire watershed, with values ranging from 1 to 1189 tons per hectare per year. The classification of soil loss into four stages—very low (0–15 t/ha/yr), low (15–45 t/ha/yr), moderate (45–75 t/ha/yr), and high (>75 t/ha/yr)—provides a nuanced perspective on soil loss dynamics. Notably, 20% of the basin exhibited a soil loss rate of 36 tons per hectare per year. These high rates of soil erosion are attributed to certain factors, such as steep slopes, sparse vegetation cover, and intense rainfall events. These results align with regional and global studies and highlight the impact of topography, land use, and soil properties on soil loss. Moreover, the research emphasizes the importance of integrating empirical soil loss models with modern technological approaches to identify soil loss-prone locations and precisely quantify soil loss rates. These findings provide valuable insights for developing environmental management strategies aimed at mitigating the impacts of soil loss, promoting sustainable land use practices, and supporting resource conservation efforts in arid and semi-arid regions. Full article

(This article belongs to the Section Water Erosion and Sediment Transport)

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16 pages, 4015 KiB

Open AccessArticle

Enhanced Removal of Refractory Organic Compounds from Coking Wastewater Using Polyaluminum Chloride with Coagulant Aids

by Huifang Sun, Yifan Zhou, Mengfan Du and Zhiping Du

Water 2024, 16(18), 2662; https://doi.org/10.3390/w16182662 - 19 Sep 2024

Abstract

This study explores the enhanced removal of refractory organic compounds from coking wastewater using polyaluminum chloride (PACl) with two different basicity levels (0.5 and 2.5), in combination with coagulant aids such as cationic polyacrylamide (CPAM) and iron ions. The results demonstrated that both [...] Read more.

This study explores the enhanced removal of refractory organic compounds from coking wastewater using polyaluminum chloride (PACl) with two different basicity levels (0.5 and 2.5), in combination with coagulant aids such as cationic polyacrylamide (CPAM) and iron ions. The results demonstrated that both PACl formulations significantly outperformed commercial PACl in terms of COD and color removal, with PACl at the basicity of 2.5 achieving slightly higher efficiency than PACl at the basicity of 0.5. The improved performance was attributed to the higher content of polymeric aluminum species, enhancing charge neutralization and bridging adsorption. The addition of coagulant aids further improved the performance, with PACl at the basicity of 2.5 combined with iron ions achieving the highest COD (48.41%) and color removal (80.77%), due to sweep coagulation and complexation. Organic composition analysis using gas chromatography–mass spectrometry (GC-MS), three-dimensional excitation–emission matrix (3D-EEM) fluorescence spectroscopy, and ultraviolet (UV) spectroscopy indicated that PACl combined with iron ions was the most effective in removing polycyclic aromatic hydrocarbons (PAHs) and nitrogen-, oxygen-, and sulfur-containing heterocyclic compounds. Additionally, a floc analysis showed that the flocs formed with iron ions were more compact and had better settleability compared to those formed with CPAM, further contributing to the improved coagulation efficiency. These results highlight the importance of optimizing the PACl basicity and coagulant aid selection for the enhanced removal of refractory organic compounds from coking wastewater, offering a promising strategy for advanced wastewater treatment. Full article

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

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21 pages, 14185 KiB

Open AccessArticle

An Automated Machine Learning Approach to the Retrieval of Daily Soil Moisture in South Korea Using Satellite Images, Meteorological Data, and Digital Elevation Model

by Nari Kim, Soo-Jin Lee, Eunha Sohn, Mija Kim, Seonkyeong Seong, Seung Hee Kim and Yangwon Lee

Water 2024, 16(18), 2661; https://doi.org/10.3390/w16182661 - 18 Sep 2024

Abstract

Soil moisture is a critical parameter that significantly impacts the global energy balance, including the hydrologic cycle, land–atmosphere interactions, soil evaporation, and plant growth. Currently, soil moisture is typically measured by installing sensors in the ground or through satellite remote sensing, with data [...] Read more.

Soil moisture is a critical parameter that significantly impacts the global energy balance, including the hydrologic cycle, land–atmosphere interactions, soil evaporation, and plant growth. Currently, soil moisture is typically measured by installing sensors in the ground or through satellite remote sensing, with data retrieval facilitated by reanalysis models such as the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and the Global Land Data Assimilation System (GLDAS). However, the suitability of these methods for capturing local-scale variabilities is insufficiently validated, particularly in regions like South Korea, where land surfaces are highly complex and heterogeneous. In contrast, artificial intelligence (AI) approaches have shown promising potential for soil moisture retrieval at the local scale but have rarely demonstrated substantial products for spatially continuous grids. This paper presents the retrieval of daily soil moisture (SM) over a 500 m grid for croplands in South Korea using random forest (RF) and automated machine learning (AutoML) models, leveraging satellite images and meteorological data. In a blind test conducted for the years 2013–2019, the AutoML-based SM model demonstrated optimal performance, achieving a root mean square error of 2.713% and a correlation coefficient of 0.940. Furthermore, the performance of the AutoML model remained consistent across all the years and months, as well as under extreme weather conditions, indicating its reliability and stability. Comparing the soil moisture data derived from our AutoML model with the reanalysis data from sources such as the European Space Agency Climate Change Initiative (ESA CCI), GLDAS, the Local Data Assimilation and Prediction System (LDAPS), and ERA5 for the South Korea region reveals that our AutoML model provides a much better representation. These experiments confirm the feasibility of AutoML-based SM retrieval, particularly for local agrometeorological applications in regions with heterogeneous land surfaces like South Korea. Full article

(This article belongs to the Special Issue Using Machine Learning Methods for Agricultural Water Cycle Assessment)

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16 pages, 7270 KiB

Open AccessArticle

The Drawdown of a Reservoir: Its Effect on Seepage Conditions and Stability of Earth Dams

by Nikolay Aniskin, Andrey Stupivtsev, Stanislav Sergeev and Ilia Bokov

Water 2024, 16(18), 2660; https://doi.org/10.3390/w16182660 - 18 Sep 2024

Abstract

This article addresses the reliability and safety of an earth dam in the case of a change in the reservoir water level. The water level must often be reduced to remove water or as a response to an emergency situation in the process [...] Read more.

This article addresses the reliability and safety of an earth dam in the case of a change in the reservoir water level. The water level must often be reduced to remove water or as a response to an emergency situation in the process of operation of a hydraulic structure. Lower water levels change seepage conditions, such as the surface of depression, values and directions of seepage gradients, seepage rates, and volumetric hydrodynamic loading. Practical hydraulic engineering shows that these changes can have a number of negative consequences. Higher seepage gradients can lead to seepage-triggered deformations in the vicinity of the upstream slope of a structure. Hydrodynamic loads, arising during drawdown, reduce the stability of an upstream slope of a dam and cause its failure. Potential consequences of a drawdown can be evaluated by solving the problem of drawdown seepage for the dam body and base. A numerical solution to this problem is based on the finite element method applied using the PLAXIS 2D software package. Results thus obtained are compared with those obtained using the finite element method in the locally variational formulation. A numerical experiment was conducted to analyze factors affecting the value of the maximum seepage gradient and stability of the earth dam slope. Recommendations were formulated to limit the drawdown parameters and to ensure the safe operation of a structure. Full article

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15 pages, 3540 KiB

Open AccessStudy Protocol

Research on Failure Pressure Prediction of Water Supply Pipe Based on GA-BP Neural Network

by Qingfu Li and Zeyi Li

Water 2024, 16(18), 2659; https://doi.org/10.3390/w16182659 - 18 Sep 2024

Abstract

The water supply pipeline is regarded as the “lifeline” of the city. In recent years, pipeline accidents caused by aging and other factors are common and have caused large economic losses. Therefore, in order to avoid large economic losses, it is necessary to [...] Read more.

The water supply pipeline is regarded as the “lifeline” of the city. In recent years, pipeline accidents caused by aging and other factors are common and have caused large economic losses. Therefore, in order to avoid large economic losses, it is necessary to analyze the failure prediction of pipelines so that the pipelines that are going to fail can be replaced in a timely manner. In this paper, we propose a method for predicting the failure pressure of pipelines, i.e., a genetic algorithm was used to optimize the weights and thresholds of a BP neural network. The first step was to determine the topology of the neural network and the number of input and output variables. The second step was to optimize the weights and thresholds initially set for the back propagation neural network using a genetic algorithm. Finally, the optimized back-propagation neural network was used to simulate and predict pipeline failures. It was proved by examples that compared with the separate back propagation neural network model and the optimized and trained genetic algorithm-back propagation neural network, the model performed better in simulation prediction, and the prediction accuracy could reach up to 91%, whereas the unoptimized back propagation neural network model could only reach 85%. It is feasible to apply this model for fault prediction of pipelines. Full article

(This article belongs to the Section Urban Water Management)

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15 pages, 1391 KiB

Open AccessArticle

Evaluating the Impact of Hotel Classification on Pool Water Consumption: A Case Study from Costa Brava (Spain)

by Núria Arimany-Serrat and Juan-Jose Gomez-Guillen

Water 2024, 16(18), 2658; https://doi.org/10.3390/w16182658 - 18 Sep 2024

Abstract

Swimming pools are key assets in the hotel industry. With climate change and water stress, more sustainable pools are needed in tourist areas. The study examines the relationship between hotel categories and the consumption of water in swimming pools in a Mediterranean coastal [...] Read more.

Swimming pools are key assets in the hotel industry. With climate change and water stress, more sustainable pools are needed in tourist areas. The study examines the relationship between hotel categories and the consumption of water in swimming pools in a Mediterranean coastal region facing water scarcity. The study focuses on the Costa Brava, with a focus on Lloret de Mar, a popular tourist destination. The research employs a combination of data analysis and the utilisation of evaporation models in order to estimate the consumption of water by swimming pools. The findings indicate that hotels in the higher categories, particularly those with three or four stars, contribute a notable proportion of the total water consumption due to their larger pool sizes and higher guest numbers. The study underscores the necessity for the implementation of sustainable water management strategies, particularly in the context of climate change. It recommends the utilisation of pool water-saving technologies as potential solutions. Furthermore, the paper highlights the broader environmental impact of tourism infrastructure on water resources and suggests policy measures to mitigate these effects. The research aligns with global sustainability goals such as the European Green Deal and the 2030 Agenda. Full article

(This article belongs to the Section Water and Climate Change)

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13 pages, 603 KiB

Open AccessArticle

Osmoregulatory Capacity and Non-Specific Food Preferences as Strengths Contributing to the Invasive Success of the Signal Crayfish Pacifastacus leniusculus: Management Implications

by Aldona Dobrzycka-Krahel, Michał E. Skóra, Michał Raczyński and Katarzyna Magdoń

Water 2024, 16(18), 2657; https://doi.org/10.3390/w16182657 - 18 Sep 2024

Abstract

Various biological traits support the invasive success of different organisms. The osmoregulatory capacity and food preferences of the signal crayfish Pacifastacus leniusculus were experimentally tested to determine if they contribute to its invasive success. The osmotic concentrations of haemolymph were determined after acclimation [...] Read more.

Various biological traits support the invasive success of different organisms. The osmoregulatory capacity and food preferences of the signal crayfish Pacifastacus leniusculus were experimentally tested to determine if they contribute to its invasive success. The osmotic concentrations of haemolymph were determined after acclimation of the crustaceans to seven salinities from 0 to 20 PSU. Food preferences were tested using Canadian pondweed Elodea canadensis, and rainbow trout Oncorhynchus mykiss. The results showed that the signal crayfish exhibits a hyper-hypoosmotic regulation pattern in the salinity range from 0 to 20 PSU, enabling them to inhabit both freshwater and brackish environments. Furthermore, the study found signal crayfish to have non-specific food preferences, although fish muscle tissue is more beneficial as a source of energy. Both features, osmoregulatory ability and food preferences, can increase the invasive success of this species as it expands into new areas. The ability to survive in higher salinities compared to the coastal waters of the Baltic Sea along the Polish coastline should be considered in targeted management strategies to control the spread of this invasive species. Full article

24 pages, 9847 KiB

Open AccessArticle

Drought Quantification in Africa Using Remote Sensing, Gaussian Kernel, and Machine Learning

by Fred Sseguya and Kyung-Soo Jun

Water 2024, 16(18), 2656; https://doi.org/10.3390/w16182656 - 18 Sep 2024

Abstract

Effective drought management requires precise measurement, but this is challenging due to the variety of drought indices and indicators, each with unique methods and specific uses, and limited ground data availability. This study utilizes remote sensing data from 2001 to 2020 to compute [...] Read more.

Effective drought management requires precise measurement, but this is challenging due to the variety of drought indices and indicators, each with unique methods and specific uses, and limited ground data availability. This study utilizes remote sensing data from 2001 to 2020 to compute drought indices categorized as meteorological, agricultural, and hydrological. A Gaussian kernel convolves these indices into a denoised, multi-band composite image. Further refinement with a Gaussian kernel enhances a single drought index from each category: Reconnaissance Drought Index (RDI), Soil Moisture Agricultural Drought Index (SMADI), and Streamflow Drought Index (SDI). The enhanced index, encompassing all bands, serves as a predictor for classification and regression tree (CART), support vector machine (SVM), and random forest (RF) machine learning models, further improving the three indices. CART demonstrated the highest accuracy and error minimization across all drought categories, with root mean square error (RMSE) and mean absolute error (MAE) values between 0 and 0.4. RF ranked second, while SVM, though less reliable, achieved values below 0.7. The results show persistent drought in the Sahel, North Africa, and southwestern Africa, with meteorological drought affecting 30% of Africa, agricultural drought affecting 22%, and hydrological drought affecting 21%. Full article

(This article belongs to the Section Hydrology)

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17 pages, 6147 KiB

Open AccessArticle

Short-Term Warming Induces Cyanobacterial Blooms and Antibiotic Resistance in Freshwater Lake, as Revealed by Metagenomics Analysis

by Bharat Manna, Emma Jay, Wensi Zhang, Xueyang Zhou, Boyu Lyu, Gevargis Muramthookil Thomas and Naresh Singhal

Water 2024, 16(18), 2655; https://doi.org/10.3390/w16182655 - 18 Sep 2024

Abstract

Climate change threatens freshwater ecosystems, potentially intensifying cyanobacterial blooms and antibiotic resistance. We investigated these risks in Cosseys Reservoir, New Zealand, using short-term warming simulations (22 °C, 24 °C, and 27 °C) with additional oxidative stress treatments. A metagenomic analysis revealed significant community [...] Read more.

Climate change threatens freshwater ecosystems, potentially intensifying cyanobacterial blooms and antibiotic resistance. We investigated these risks in Cosseys Reservoir, New Zealand, using short-term warming simulations (22 °C, 24 °C, and 27 °C) with additional oxidative stress treatments. A metagenomic analysis revealed significant community shifts under warming. The cyanobacterial abundance increased from 6.11% to 20.53% at 24 °C, with Microcystaceae and Nostocaceae proliferating considerably. The microcystin synthesis gene (mcy) cluster showed a strong association with cyanobacterial abundance. Cyanobacteria exhibited enhanced nutrient acquisition (pstS gene) and an upregulated nitrogen metabolism under warming. Concurrently, antibiotic resistance genes (ARGs) increased, particularly multidrug resistance genes (50.82% of total ARGs). A co-association network analysis identified the key antibiotic-resistant bacteria (e.g., Streptococcus pneumoniae and Acinetobacter baylyi) and ARGs (e.g., acrB, MexK, rpoB2, and bacA) central to resistance dissemination under warming conditions. Oxidative stress exacerbated both cyanobacterial growth and ARGs’ proliferation, especially efflux pump genes (e.g., acrB, adeJ, ceoB, emrB, MexK, and muxB). This study demonstrated that even modest warming (2–5 °C) could promote both toxic cyanobacteria and antibiotic resistance. These findings underscore the synergistic effects of temperature and oxidative stress posed by climate change on water quality and public health, emphasizing the need for targeted management strategies in freshwater ecosystems. Future research should focus on long-term impacts and potential mitigation measures. Full article

(This article belongs to the Section Water and Climate Change)

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