Journal Description
Water
Water
is a peer-reviewed, open access journal on water science and technology, including the ecology and management of water resources, and is published semimonthly online by MDPI. Water collaborates with the International Conference on Flood Management (ICFM) and Stockholm International Water Institute (SIWI). In addition, the American Institute of Hydrology (AIH), The Polish Limnological Society (PLS) and Japanese Society of Physical Hydrology (JSPH) are affiliated with Water and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, PubAg, AGRIS, CAPlus / SciFinder, Inspec, and other databases.
- Journal Rank: JCR - Q2 (Water Resources) / CiteScore - Q1 (Water Science and Technology)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.5 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journals for Water include: GeoHazards and Hydrobiology.
Impact Factor:
3.4 (2022);
5-Year Impact Factor:
3.5 (2022)
Latest Articles
Spatial Distribution Patterns of Phytoplankton and Their Relationship with Environmental Factors in the Jinjiang River, China
Water 2024, 16(11), 1497; https://doi.org/10.3390/w16111497 (registering DOI) - 24 May 2024
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Our study aims to investigate the water quality and distribution patterns of phytoplankton communities in the Jinjiang River Basin in Quanzhou, as well as their relationship with environmental factors. We integrated data from the national water quality databases of the two main tributaries
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Our study aims to investigate the water quality and distribution patterns of phytoplankton communities in the Jinjiang River Basin in Quanzhou, as well as their relationship with environmental factors. We integrated data from the national water quality databases of the two main tributaries of the West and East Jinjiang Rivers between 2020 and 2023, supplemented by field surveys. Redundancy analysis was used to explore the effect of environmental factors on phytoplankton communities. Our findings revealed that the West Jinjiang River experienced a significant influence from excessive fertilizer use in tea cultivation, leading to an increase in TN concentrations compared to the East Jinjiang River. The abundance of phytoplankton in the Jinjiang River Basin was 105 cells·L−1, with phytoplankton being dominated by Chlorophyta, Cyanphyta, and diatoms, accounting for an average of 50%, 20%, and 19% of the total phytoplankton abundance, respectively. Redundancy analysis indicated that temperature, pH, and nutrient concentrations were important factors influencing the phytoplankton communities. With increasing temperature and nutrients concentrations, the abundance of Chlorophyta and Dinophyta significantly increased. This study provides a solid foundation for the regular “health diagnosis” of crucial rivers and lakes in Quanzhou and supports the establishment of a health guarantee system for rivers and lakes.
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Open AccessArticle
Socio-Spatial Analysis of Water Affordability at Small Scales: A Needs-Based Approach
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Gustavo Romero-Gomez, Elena Domene, Xavier Garcia, Hyerim Yoon and David Saurí
Water 2024, 16(11), 1496; https://doi.org/10.3390/w16111496 (registering DOI) - 24 May 2024
Abstract
Water affordability as a dimension of water poverty is becoming an increasing source of concern in cities of the Global North. Studies on water affordability are either based on water wants and not needs or tend to use spatial scales too large for
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Water affordability as a dimension of water poverty is becoming an increasing source of concern in cities of the Global North. Studies on water affordability are either based on water wants and not needs or tend to use spatial scales too large for effective analyses of local inequities that can truly guide policy actions. In this contribution, we calculate and map a Water Affordability Index (WAI) based on the minimum water requirement of 100 litres/person/day at the scale of the census tract for the Metropolitan Area of Barcelona. We also apply global and local spatial autocorrelation analyses to investigate spatial relationships between the WAI and poverty-related sociodemographic variables. Results show that, even though average WAI values are moderate, the distribution pattern of higher and lower values tends to be clustered in some districts and neighbourhoods of the study area. Bivariate correlations indicate that water affordability is not only related to poverty variables but also to the diversity of water prices. Findings exemplify how the constructed index can complement existing affordability indicators, revealing and mapping important risk groups struggling to meet the costs of essential water needs. Water affordability could be mitigated by supportive water pricing policies for vulnerable households in water poverty hotspots.
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(This article belongs to the Special Issue Socio-Economics of Water Resources Management)
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Open AccessArticle
Evaluation of Algal Control Measures in Eutrophic Reservoirs Based on Aquatic Ecosystem Models
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Zhen Zheng, Tingting Liao, Yafeng Lin, Xueyi Zhu and Haobin Meng
Water 2024, 16(11), 1494; https://doi.org/10.3390/w16111494 (registering DOI) - 24 May 2024
Abstract
The frequency of freshwater cyanobacterial blooms is increasing globally due to climate change and eutrophication, particularly in reservoirs. Reservoir ecosystems exhibit unique characteristics, and there is a complex relationship between factors such as light, temperature, nutrient salts, hydrology, and algal growth. The impact
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The frequency of freshwater cyanobacterial blooms is increasing globally due to climate change and eutrophication, particularly in reservoirs. Reservoir ecosystems exhibit unique characteristics, and there is a complex relationship between factors such as light, temperature, nutrient salts, hydrology, and algal growth. The impact of the other factors on algal growth varies significantly among different reservoirs. Thus, it is crucial to assess the effectiveness of various algal control measures implemented in different reservoirs. This study conducted a comprehensive assessment by establishing a eutrophication model for the Shanzi Reservoir in Fuzhou City. The model incorporated meteorology, hydrology, carbon dynamics, nutrient cycling, and biological communities. The effectiveness of diverse management measures was systematically evaluated. The findings demonstrate that increasing the water level, reducing nutrient salts in sediments, and implementing ecological fish stocking effectively suppressed algal growth to varying degrees and improved nitrogen and phosphorus levels. Lower water levels and ecological fish stocking had a significant impact on algal reproduction, while sediment reduction had a minimal effect. Conversely, lower water levels and ecological fish stocking did not significantly improve nitrogen and phosphorus concentrations in the reservoir, whereas sediment reduction had a noticeable effect. Consequently, the management strategies for the Shanzi Reservoir should prioritize external control measures and the implementation of ecological fish stocking.
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(This article belongs to the Special Issue The Management of Eutrophication, Harmful Algal Bloom and Ecological Health in Freshwater Ecosystems)
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Open AccessArticle
Optimization of the Coupling between Water and Energy Consumption in a Smart Integrated Photovoltaic Pumping Station System
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Zuping Xu and Xing Chen
Water 2024, 16(11), 1493; https://doi.org/10.3390/w16111493 (registering DOI) - 23 May 2024
Abstract
Agricultural irrigation requires significant consumption of freshwater resources and energy. The integration of photovoltaic power generation into irrigation systems has been extensively investigated in order to save the cost of energy. However, current research often neglects the coupling relationship between photovoltaic power generation
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Agricultural irrigation requires significant consumption of freshwater resources and energy. The integration of photovoltaic power generation into irrigation systems has been extensively investigated in order to save the cost of energy. However, current research often neglects the coupling relationship between photovoltaic power generation and irrigation schemes. This study presented a novel smart integrated photovoltaic pump station system to effectively address the issue associated with water and energy consumption in irrigation. An optimization model was proposed to synchronize the energy consumption of irrigation pump stations with photovoltaic power generation, accurately meeting the irrigation water demand while maximizing solar energy utilization. The optimization model incorporates power balance, grid-connected power, and total water demand as constraints while considering pump speed as the decision variable and aiming to minimize daily operational costs. Finally, a high-standard farmland was used as a case study to validate the efficacy of the optimization strategy through two photovoltaic grid-connected policies—one allowing for the sale of surplus power and the other prohibiting it. An improved dynamic programming method was employed to solve for optimal energy consumption schemes under different water demand conditions; the results were compared against traditional methods, revealing potential cost savings ranging from 6.2% to 30.5%. The optimization model and method propose a new operational concept for the irrigation system with photovoltaic generation, effectively utilizing the distinctive features of both irrigation and photovoltaics to optimize water and energy resources.
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(This article belongs to the Section Water-Energy Nexus)
Open AccessArticle
Application of RNN-LSTM in Predicting Drought Patterns in Pakistan: A Pathway to Sustainable Water Resource Management
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Wilayat Shah, Junfei Chen, Irfan Ullah, Muhammad Haroon Shah and Irfan Ullah
Water 2024, 16(11), 1492; https://doi.org/10.3390/w16111492 - 23 May 2024
Abstract
Water is a fundamental and crucial natural resource for human survival. However, the global demand for water is increasing, leading to a subsequent decrease in water availability. This study addresses the critical need for improved water resource forecasting models amidst global water scarcity
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Water is a fundamental and crucial natural resource for human survival. However, the global demand for water is increasing, leading to a subsequent decrease in water availability. This study addresses the critical need for improved water resource forecasting models amidst global water scarcity concerns exacerbated by climate change. This study uses the best weather and water resource forecasting model for sustainable development. Employing a Recurrent Neural Network–Long Short-Term Memory (RNN-LSTM) approach, the research enhances drought prediction capabilities by integrating secondary data of the rainfall, temperature, and ground and surface water supplies. The primary objective is to forecast water resources under changing climatic conditions, facilitating the development of early warning systems for vulnerable regions. The results from the LSTM model show an increased trend in temperature and rainfall patterns. However, a relatively unstable decrease in rainfall is observed. The best statistical analysis result was observed with the LSTM model; the model’s accuracy was 99%, showing that it was quite good at presenting the obtained precipitation, temperature, and water data. Meanwhile, the value of the root mean squared error (RMSE) was about 13, 15, and 20, respectively. Therefore, the study’s results highlight that the LSTM model was the most suitable among the artificial neural networks for forecasting the weather, rainfall, and water resources. This study will help weather forecasting, agriculture, and meteorological departments be effective for water resource forecasting.
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(This article belongs to the Section Hydrology)
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Open AccessArticle
Research and Application of the Mine 3D DC Resistivity Method for Detecting Grouting in the Floor of an Ultrawide Working Face, Taking the Yongmei Xinqiao Coal Mine in Henan Province as an Example
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Ning Li, Maofei Li, Xuhong Wang, Xuerui Tong and Ruosong Sun
Water 2024, 16(11), 1491; https://doi.org/10.3390/w16111491 - 23 May 2024
Abstract
Generally, ground grouting is used to treat confined water areas before mining at the working face, but there is a lack of testing methods for determining the effectiveness of such a grouting treatment on the floor of ultrawide working faces. Therefore, we propose
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Generally, ground grouting is used to treat confined water areas before mining at the working face, but there is a lack of testing methods for determining the effectiveness of such a grouting treatment on the floor of ultrawide working faces. Therefore, we propose a 3D DC resistivity method for mines and apply it to the detection of the effect of grouting on the mine floor. This study took the Yongmei Xinqiao Coal Mine in Henan Province as the research object and used a combination of theoretical analysis, numerical simulation, and measured data analysis to study the effect of the 3D resistivity method on detecting the effect of grouting on the floor of an ultrawide working face in the mine. The research results indicated that compared with the 2D observation mode of same-side power supply and reception, the 3D observation mode of opposite-side power supply and reception using the tunnels on both sides of the working face was more sensitive to the response of the water-rich area 60 m below the coal seam’s floor. Regarding the model’s set-up in this article, when traditional apparent resistivity calculations were used, the apparent resistivity obtained by the 3D observation mode was opposite to the model’s setting, and accurate electrical information of anomalous bodies must be obtained through 3D inversion. The measured data showed that although the ground grouting treatment effectively reduced the water volume in the floor, the treatment’s result was affected by human factors, and the water in the floor was redistributed.
Full article
(This article belongs to the Special Issue Mine Water Safety and Environment, 2nd Edition)
Open AccessArticle
Space-Time Variability of Drought Characteristics in Pernambuco, Brazil
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Ivanildo Batista da Silva Júnior, Lidiane da Silva Araújo, Tatijana Stosic, Rômulo Simões Cezar Menezes and Antonio Samuel Alves da Silva
Water 2024, 16(11), 1490; https://doi.org/10.3390/w16111490 - 23 May 2024
Abstract
Drought is the most complex natural hazard that can occur over large spatial scales and during long time periods. It affects more people than any other natural hazard, particularly in areas with a dry climate, such as the semiarid region of the Brazilian
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Drought is the most complex natural hazard that can occur over large spatial scales and during long time periods. It affects more people than any other natural hazard, particularly in areas with a dry climate, such as the semiarid region of the Brazilian Northeast (NEB), which is the world’s most populated dry area. In this work, we analyzed trends and the spatial distribution of drought characteristics (frequency, affected area, and intensity) based on the Standardized Precipitation Index (SPI) on annual (SPI-12) and seasonal (SPI-3) scales. The study used monthly precipitation data recorded between 1962 and 2012 at 133 meteorological stations in Pernambuco State, Brazil, which is located in the eastern part of the NEB and has more than 80% of its territory characterized by a semiarid climate. The regions of Sertão, Agreste, and Zona da Mata of Pernambuco were considered for comparison. The Mann–Kendall and Sen’s slope tests were used to detect the trend and determine its magnitude, respectively. The results indicated that annual droughts in the state of Pernambuco became more frequent from the 1990s onwards, with summer having the greatest spatial coverage, followed by winter, autumn, and spring. Sertão presented a greater number of stations with a significant positive trend in drought frequency. Regarding the drought-affected area, global events occurred in a greater number of years on an annual scale and during the summer. Trend analysis pointed to an increase in areas with drought events on both scales. As for the drought intensity, the entire state of Pernambuco experienced drought events with high intensity during the autumn. The relationship between drought characteristics indicated an increase in the affected area as the result of an increase in drought intensity.
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(This article belongs to the Special Issue Drought Monitoring and Risk Assessment)
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Stable Isotope Hydrology of Karst Groundwaters in Romania
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Renata Feher, Carmen-Andreea Bădăluță, Traian Brad, Călin Drăgan, Virgil Drăgușin, Dragoș Ștefan Măntoiu, Aurel Perșoiu and Maria-Laura Tîrlă
Water 2024, 16(11), 1489; https://doi.org/10.3390/w16111489 - 23 May 2024
Abstract
In this article we present the first investigation of the stable isotope composition of groundwater in Romania, East-Central Europe, with a focus on the karst areas. Our aim is twofold: (1) to provide a countrywide map with the distribution of stable oxygen and
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In this article we present the first investigation of the stable isotope composition of groundwater in Romania, East-Central Europe, with a focus on the karst areas. Our aim is twofold: (1) to provide a countrywide map with the distribution of stable oxygen and hydrogen isotope ratios in groundwater, and (2) to assess the recharge patterns of karst water. We collected more than 600 water samples from springs and wells across Romania for stable isotope analyses and monitored in detail the stable isotope composition of the waters as they pass through five cave systems. Our data show a spatial distribution of the stable isotope composition of the groundwater with low values in the mountainous area and high values in the surrounding lowlands and the central Transylvanian Depression. However, waters in karst areas induce departures from this distribution, resulting from the fast (hours to days) transfer of waters from high (ponor) to low (spring) altitudes. Water emerging from the karst springs has generally lower δ values than before sinking through the ponors, thus indicating a substantial contribution of winter recharge through diffuse infiltration and seepage. This contribution results in overall dilution of the water entering through ponors, likely resulting in changes in the chemical composition of the water and diluting potential pollutants. Our data call for careful separation between karst and non-karst spring/well waters, as indiscriminate common treatment might lead to erroneous interpretations.
Full article
(This article belongs to the Special Issue Cave Waters: Modern Perspectives for Short to Long-Term Environmental Monitoring)
Open AccessArticle
Optimization of Hydraulic Efficiency and Internal Flow Characteristics of a Multi-Stage Pump Using RBF Neural Network
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Lei Zhang, Dayong Wang, Gang Yang, Qiang Pan, Weidong Shi and Ruijie Zhao
Water 2024, 16(11), 1488; https://doi.org/10.3390/w16111488 - 23 May 2024
Abstract
In order to improve the hydraulic efficiency and internal flow pattern of a multi-stage pump under multiple flow conditions, an intelligent optimization design was proposed for its hydraulic components. Sensitivity analysis was used to select the key parameters influencing the hydraulic efficiency of
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In order to improve the hydraulic efficiency and internal flow pattern of a multi-stage pump under multiple flow conditions, an intelligent optimization design was proposed for its hydraulic components. Sensitivity analysis was used to select the key parameters influencing the hydraulic efficiency of a multi-stage pump. The optimal Latin hypercube sampling and non-dominated sorting genetic algorithm Ⅱ were employed to build a multi-objective optimization system. Moreover, a radial basis function neural network was adopted as the surrogate model of hydraulic efficiency. The research results showed that the impeller outlet width, impeller blade wrap angle, impeller outlet blade angle, and diffuser inlet width were the key factors affecting the hydraulic efficiency. The efficiency of the optimized model increased by 4.35% under the design condition and the matching of the internal flow between the optimized impeller and diffuser was significantly enhanced under the nominal condition. The improved flow pattern could be clearly observed in the flow passage of both the pump impeller and the diffuser. After optimization, the wear performance of the model was also improved compared to the original design. The wear area decreased in size and was distributed more evenly, resulting in a noticeable decrease in the maximum amount of wear.
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(This article belongs to the Special Issue Design and Optimization of Fluid Machinery)
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Open AccessArticle
Study on the Characteristics and Evolution Laws of Seepage Damage in Red Mud Tailings Dams
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Shiqi Chang, Xiaoqiang Dong, Xiaofeng Liu, Xin Xu, Haoru Zhang and Yinhao Huang
Water 2024, 16(11), 1487; https://doi.org/10.3390/w16111487 - 23 May 2024
Abstract
Seepage damage is a significant factor leading to red mud tailings dam failures. Laboratory tests on seepage damage were conducted to investigate the damage characteristics and distribution laws of red mud tailings dams, including soil pressure, infiltration line, pore water pressure, dam displacement,
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Seepage damage is a significant factor leading to red mud tailings dam failures. Laboratory tests on seepage damage were conducted to investigate the damage characteristics and distribution laws of red mud tailings dams, including soil pressure, infiltration line, pore water pressure, dam displacement, and crack evolution. The findings revealed the seepage damage mechanisms of red mud slopes, offering insights for the safe operation and seepage damage prevention of red mud tailings dams. The results showed that the higher the water level is in the red mud tailings dam, the higher position the infiltration line is when it reaches the slope face. At the highest infiltration line point of the slope surface, the increase of pore water pressure is the highest and the change of horizontal soil pressure is the highest. Consequently, increased pore water pressure leads to decreased effective stress and shear strength, increasing the susceptibility to damage. Cracks resulting from seepage damage predominantly form below the infiltration line; the higher the infiltration lines is on the slope surface, the higher the position of the main crack formations is. The displacement of the dam body primarily occurs due to the continuous expansion of major cracks; the higher the infiltration lines are on the slope surface, the larger the displacement of the dam body is.
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(This article belongs to the Special Issue Research Advances in Hydraulic Structure and Geotechnical Engineering)
Open AccessArticle
Characteristics of Anthropogenic Pollution in the Atmospheric Air of South-Western Svalbard (Hornsund, Spring 2019)
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Filip Pawlak, Krystyna Koziol, Wanda Wilczyńska-Michalik, Mikołaj Worosz, Marek Michalik, Sara Lehmann-Konera and Żaneta Polkowska
Water 2024, 16(11), 1486; https://doi.org/10.3390/w16111486 - 23 May 2024
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The character of atmospheric pollution and its impact on surface waters may vary substantially in space, and hence, we add a potentially important location for the studies of atmospheric air pollution to the map of the High Arctic. We have investigated the anthropogenic
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The character of atmospheric pollution and its impact on surface waters may vary substantially in space, and hence, we add a potentially important location for the studies of atmospheric air pollution to the map of the High Arctic. We have investigated the anthropogenic particle characteristics and selected persistent organic pollutant concentrations, in a priorly unmonitored location in the Arctic (Svalbard), exposed to a climatic gradient. Single-particle analysis of PM indicates that besides the prevailing natural aerosol particles, anthropogenic ones were present. The likely anthropogenic origin of some particles was established for spherical Fe-rich or aluminosilicate particles formed in high-temperature processes or metal-rich particles of the chemical composition corresponding to industrial products and atypical for natural minerals; soot, tar balls, and secondary sulfate were also likely of anthropogenic origin. Some of the observed anthropogenic particles could only come from remote industrial sources. POP concentrations indicated a background of LRAT, consistent with the ΣPCB concentrations and volatility profile. However, the ΣDDX composition indicating aged sources and an order of magnitude higher concentrations of both ΣDDXs and ΣHCHs than at other High Arctic monitoring stations indicate their potential source in two types of re-emission from secondary sources, i.e., from seawater and snowpack, respectively.
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Open AccessArticle
Artificial Neural Network (ANN)-Based Water Quality Index (WQI) for Assessing Spatiotemporal Trends in Surface Water Quality—A Case Study of South African River Basins
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Talent Diotrefe Banda and Muthukrishnavellaisamy Kumarasamy
Water 2024, 16(11), 1485; https://doi.org/10.3390/w16111485 - 23 May 2024
Abstract
Artificial neural networks (ANNs) are powerful data-oriented “black-box” algorithms capable of assessing and delineating linear and multifaceted non-linear correlations between the dependent and explanatory variables. Through the years, neural networks have proven to be effective and robust analytical techniques for establishing artificial intelligence-based
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Artificial neural networks (ANNs) are powerful data-oriented “black-box” algorithms capable of assessing and delineating linear and multifaceted non-linear correlations between the dependent and explanatory variables. Through the years, neural networks have proven to be effective and robust analytical techniques for establishing artificial intelligence-based tools for modelling, estimating, and projecting spatial and temporal variations in water bodies. Accordingly, ANN-based algorithms gained increased attention and have emerged as practical alternatives to traditional approaches for hydro-chemical analysis. ANNs are among the widely used computer systems for modelling surface water quality. Considering their wide recognition, resilience, flexibility, and accuracy, the current study employs a neural network-based methodology to construct a novel water quality index (WQI) model suitable for analysing South African rivers. The feed-forward, back-propagated multilayered perceptron model has three parallel-distributed neuron layers interconnected with seventy weighted links orientated laterally from left to right. First, the input layer includes thirteen neuro-nodes symbolising thirteen explanatory variables, including NH3, Ca, Cl, Chl-a, EC, F CaCO3, Mg, Mn, NO3, pH, SO4, and turbidity (NTU). Second, the hidden layer consists of eleven neuro-nodes accountable for computational tasks. Lastly, the output layer features one neuron responsible for conveying network outcomes using a single-digit WQI rating extending from zero to one hundred, where zero represents substandard water quality and one hundred denotes exceptional water quality. The AI-based model was developed using water quality data obtained from six monitoring locations within four drainage basins under the management of the Umgeni Water Board in the KwaZulu-Natal Province of South Africa. The dataset comprises 416 samples randomly divided into training, testing, and validation sets using a proportional split of 70:15:15%. The Broyden–Fletcher–Goldfarb–Shanno (BFGS) technique was utilised to conduct backpropagation training and adjust synapse weights. The dependent variables are the WQI scores from the universal water quality index (UWQI) model developed specifically for South African river basins. The ANN demonstrated enhanced efficiency through an overall correlation coefficient (R) of 0.985. Furthermore, the neural network attained R-values of 0.987, 0.992, and 0.977 for the training, testing, and validation intervals. The ANN model achieved a Nash–Sutcliffe efficiency (NSE) value of 0.974 and coefficient of determination (R2) of 0.970. Sensitivity analysis provided additional validation of the preparedness and computational competence of the ANN model. The typical target-to-output error tolerance for the ANN model is 0.242, demonstrating an adequate predictive ability to deliver results comparable with the target UWQI, having the lowest and highest index ratings of 75.995 and 94.420, respectively. Accordingly, the three-layer neural network is scientifically sound, with index values and water quality evaluations corresponding to the UWQI results. The current research project seeks to document the processes used and the outcomes obtained.
Full article
(This article belongs to the Section Water Quality and Contamination)
Open AccessArticle
Mapping of Groundwater Recharge Zones in Hard Rock Aquifer through Analytic Hierarchy Process in Geospatial Platform
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Deepa Subramani, Pradeep Kamaraj, Umayadoss Saravana Kumar and Chidambaram Sabarathinam
Water 2024, 16(11), 1484; https://doi.org/10.3390/w16111484 - 23 May 2024
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Extensive use of groundwater is a result of the growing population; in relation to this, studies have focused on groundwater conservation measures. This study identified groundwater artificial recharge zones (GWARZs) in the upper Manimuktha sub-basin through the application of remote sensing and GIS.
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Extensive use of groundwater is a result of the growing population; in relation to this, studies have focused on groundwater conservation measures. This study identified groundwater artificial recharge zones (GWARZs) in the upper Manimuktha sub-basin through the application of remote sensing and GIS. A spatial analysis using the analytical hierarchical process (AHP) and weighted overlay analysis (WOA) was employed by integrating several spatial thematic layers such as geology, geomorphology, aquifer thickness, lineament density (LD), drainage density (DD), soil, slope, rainfall, and land use/land cover (LULC) in order to classify the GWARZs. The geomorphology along with lithology, higher aquifer thickness, low lineament densities, higher drainage densities, and gentle slope regions, were identified as suitable areas for artificial recharge zones. The study area was divided up into five classifications based on the integration analysis: excellent (41.1 km2), good (150.6 km2), moderate (123.9 km2), bad (125.5 km2), and very poor (57.7 km2). Excellent and good GWARZs were identified in the eastern and central regions of the study area. The final outcomes of this research were evaluated with seasonal electrical conductivity (EC) variations. The majority of samples with minor seasonal EC variations were observed in the excellent and good GWARZ categories. The results showed that the spatial analysis tool is useful for GWARZ delineation and sustainably managing groundwater resources.
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Open AccessReview
Multi-Interacting Natural and Anthropogenic Stressors on Freshwater Ecosystems: Their Current Status and Future Prospects for 21st Century
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Doru Bănăduc, Angela Curtean-Bănăduc, Sophia Barinova, Verónica L. Lozano, Sergey Afanasyev, Tamara Leite, Paulo Branco, Daniel F. Gomez Isaza, Juergen Geist, Aristoteles Tegos, Horea Olosutean and Kevin Cianfanglione
Water 2024, 16(11), 1483; https://doi.org/10.3390/w16111483 - 23 May 2024
Abstract
The inheritance of historic human-induced disruption and the fierceness of its impact change aquatic ecosystems. This work reviews some of the main stressors on freshwater ecosystems, focusing on their effects, threats, risks, protection, conservation, and management elements. An overview is provided on the
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The inheritance of historic human-induced disruption and the fierceness of its impact change aquatic ecosystems. This work reviews some of the main stressors on freshwater ecosystems, focusing on their effects, threats, risks, protection, conservation, and management elements. An overview is provided on the water protection linked to freshwater stressors: solar ultraviolet radiation, thermal pollution, nanoparticles, radioactive pollution, salinization, nutrients, sedimentation, drought, extreme floods, fragmentation, pesticides, war and terrorism, algal blooms, invasive aquatic plants, riparian vegetation, and invasive aquatic fish. Altogether, these stressors build an exceptionally composite background of stressors that are continuously changing freshwater ecosystems and diminishing or even destroying their capability to create and maintain ongoing natural healthy products and essential services to humans. Environmental and human civilization sustainability cannot exist without the proper management of freshwater ecosystems all over the planet; this specific management is impossible if the widespread studied stressors are not deeply understood structurally and functionally. Without considering each of these stressors and their synergisms, the Earth’s freshwater is doomed in terms of both quantitative and qualitative aspects.
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Open AccessArticle
Landscape Pattern Changes of Aquatic Vegetation Communities and Their Response to Hydrological Processes in Poyang Lake, China
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Zhengtao Zhu, Huilin Wang, Zhonghua Yang, Wenxin Huai, Dong Huang and Xiaohong Chen
Water 2024, 16(11), 1482; https://doi.org/10.3390/w16111482 - 23 May 2024
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Hydrology is an important environmental factor for the evolution of wetland landscape patterns. In the past 20 years, Poyang Lake, the largest freshwater lake in China, has experienced significant inundation shrinkage and water level decrease, posing a significant threat to the local vegetation
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Hydrology is an important environmental factor for the evolution of wetland landscape patterns. In the past 20 years, Poyang Lake, the largest freshwater lake in China, has experienced significant inundation shrinkage and water level decrease, posing a significant threat to the local vegetation community. To explore the potential relationship between aquatic vegetation and hydrological processes in the recent hydrological situation, in this study, the landscape patterns of aquatic vegetation communities in Poyang Lake were studied using time-series Landsat remote sensing images and a support vector machine classifier. The stepwise regression analysis method was adopted to analyze the relationship between the vegetation area and hydrological factors. The results indicated that the area of submerged and emergent vegetation in the entire lake decreased significantly from 2001 to 2017, whereas the area of moist vegetation showed a remarkably increasing trend. The average distribution elevation of the submerged vegetation increased by 0.06 m per year. The corresponding landscape patterns showed that the degree of fragmentation of aquatic vegetation communities in Poyang Lake increased. Several hydrological factors were selected to quantify the potential impact of water level fluctuations. The correlation analysis results indicated that hydrological conditions during the rising- and high-water periods may be the key factors affecting the area of aquatic vegetation. This study systematically investigated the evolution of vegetation communities in Poyang Lake wetlands over the past two decades, which contributes to the protection and management of this unique ecosystem.
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Open AccessReview
Advances in Nanoparticles and Nanocomposites for Water and Wastewater Treatment: A Review
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Jasaswini Tripathy, Akanshya Mishra, Mayank Pandey, Rakesh Ranjan Thakur, Sasmita Chand, Prangya Ranjan Rout and Muhammad Kashif Shahid
Water 2024, 16(11), 1481; https://doi.org/10.3390/w16111481 - 23 May 2024
Abstract
Addressing water scarcity and pollution is imperative in tackling global environmental challenges, prompting the exploration of innovative techniques for effective water and wastewater treatment. Nanotechnology presents promising solutions through the customization of nanoparticles and nanocomposites specifically designed for water purification applications. This review
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Addressing water scarcity and pollution is imperative in tackling global environmental challenges, prompting the exploration of innovative techniques for effective water and wastewater treatment. Nanotechnology presents promising solutions through the customization of nanoparticles and nanocomposites specifically designed for water purification applications. This review delves into recent advancements in nanoparticle-based technologies for water treatment, with a particular focus on their synthesis methodologies, intrinsic properties, and versatile applications. A wide range of nanoparticles, ranging from metal nanoparticles to carbon-based nanomaterials, along with hybrid nanocomposites such as metal/metal oxide-based nanocomposites, polymer-based nanocomposites, and others, were emphasized for eliminating contaminants from water and wastewater matrices. Furthermore, this review elucidates the underlying mechanisms governing pollutant removal processes, encompassing adsorption, catalysis, and membrane filtration, facilitated by nanoparticles. Additionally, it explores the environmental implications and challenges associated with the widespread deployment of nanoparticle-based water-treatment technologies. By amalgamating existing research findings, this review provides valuable insights into the potential of nanoparticles and nanocomposites in mitigating water-related challenges and presents recommendations for future research trajectories and technological advancements in this domain.
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(This article belongs to the Special Issue Innovating Water Treatment with AI, IoT, and Machine Learning: A Focus on Membrane Distillation)
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Open AccessArticle
Explicit Scheme for a Hydrological Channel Routing: Mathematical Model and Practical Application
by
Alfonso Arrieta-Pastrana, Oscar E. Coronado-Hernández and Jairo R. Coronado-Hernández
Water 2024, 16(11), 1480; https://doi.org/10.3390/w16111480 - 23 May 2024
Abstract
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The computation of hydrographs in large watersheds necessitates utilizing channel routing, which calculates the movement of hydrographs along channel branches. Routing methods rely on an implicit scheme to facilitate numerical resolution, which requires more computational time than the explicit scheme. This study presents
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The computation of hydrographs in large watersheds necessitates utilizing channel routing, which calculates the movement of hydrographs along channel branches. Routing methods rely on an implicit scheme to facilitate numerical resolution, which requires more computational time than the explicit scheme. This study presents an explicit scheme channel routing model that offers a versatile approach to open channel flow analysis. The model is based on mass conservation principles and Manning equations, and it can accommodate varying bed slopes, making it highly adaptable to diverse hydraulic scenarios. In addition, the proposed model considers backwater effects, which enhances its applicability in practical scenarios. The model was tested in a practical application on a rectangular channel with a width of 7 m, and the results showed that it can accurately predict outflow hydrographs and handle different flow conditions. Comparative analyses with existing models revealed that the proposed model’s performance in generating water flow oscillations was competitive. Moreover, sensitivity analyses were performed, which showed that the model is highly responsive to parameter variations, such as Manning’s coefficient, bed slope, and channel width. The comparison of peak flows and peak times between the proposed model and existing methods further emphasized the model’s reliability and efficiency in simulating channel routing processes. This research introduces a valuable addition to the field of hydrology by proposing a practical and effective channel routing model that integrates essential hydraulic principles and parameters. The results of the proposed model (lumped routing) are comparable with the solution provided by the Muskingum–Cunge method (distributed routing). It is of utmost importance to note that the proposed model applies to channel branches with bed slopes below 6°.
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Open AccessArticle
Bankline Abutment Scour in Compound Channels
by
Ahmed A. Abdelaziz, Siow Y. Lim and Jong R. Kim
Water 2024, 16(11), 1479; https://doi.org/10.3390/w16111479 - 23 May 2024
Abstract
This paper presents the results of bed scouring near an abutment that spans the entire floodplain width and terminates at the edge of the main channel, termed here as the bankline abutment. The cross section can be divided into a scoured section and
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This paper presents the results of bed scouring near an abutment that spans the entire floodplain width and terminates at the edge of the main channel, termed here as the bankline abutment. The cross section can be divided into a scoured section and an un-scoured section. The scoured bed profile can be approximated using a power function. An analytical method has been suggested to predict the maximum scour depth at bankline abutment. This method is valid irrespective of whether the original bed is at or below the threshold condition of sediment motion. The proposed method is consistent with the experiments from this study and previous studies.
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(This article belongs to the Section Hydraulics and Hydrodynamics)
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Open AccessArticle
Validation and Application of the Diffusive Gradients in Thin-Films Technique for In Situ Measurement of β-Blocker Drugs in Waters and Sediments
by
Yanying Li, Mingzhe Wu, Mengnan Fu, Dongqin Tan, Peng Zhang, Zhimin Zhou and Xiaoyan Li
Water 2024, 16(11), 1478; https://doi.org/10.3390/w16111478 - 22 May 2024
Abstract
The occurrence of β-blocker drugs in aquatic environments worldwide has caused increasing attention to their threat to human health in recent years. It is essential to monitor these widely prescribed pharmaceuticals in natural waters and sediments, helping us investigate their potential risk to
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The occurrence of β-blocker drugs in aquatic environments worldwide has caused increasing attention to their threat to human health in recent years. It is essential to monitor these widely prescribed pharmaceuticals in natural waters and sediments, helping us investigate their potential risk to humans and ecosystems. In this study, a passive sampling technique, diffusive gradients in thin-films (DGT), was systematically developed for eight frequently detected β-blockers. The effective capacities of target compounds were large enough for the devices to deploy for several weeks. The uptake of all compounds was linearly correlated with deployment times during the 7-day laboratory experiment and agreed well with the theoretical line, except for several compounds (e.g., ATL) due to their relatively slow uptake rate. The performance of most compounds was independent of varying pH values and organic matter contents; only a few compounds were affected, while the application in high-salinity environments needs to be conducted with caution. Field deployments of DGT to detect β-blockers in situ in rivers and sediments proved that DGT is an effective tool to monitor β-blocker drugs and their fate in the natural aquatic environment, while DGT probes can provide information for us to investigate the biogeochemical processes occurred in sediment, especially at the sediment–water interface. This novel approach will help us understand the behaviour of β-blocker drugs in the aquatic environment, assess their risks, finally protect human health and maintain the sustainable development of the ecosystem.
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Open AccessBrief Report
Study on Ferritin Gene Expression to Evaluate the Health of White Leg Shrimp (Litopenaeus vannamei) Postlarvae Due to Changes in Water Temperature, Salinity, and pH
by
Chul Won Kim, Ju-Wook Lee, Seung-Won Kang and Han Seung Kang
Water 2024, 16(11), 1477; https://doi.org/10.3390/w16111477 - 22 May 2024
Abstract
The growth and survival of marine organisms are influenced by environmental factors such as water temperature, salinity, and pH. Unsuitable environmental conditions may negatively impact marine organisms. The white leg shrimp (Litopenaeus vannamei), a euryhaline organism highly adapted to salinity, is
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The growth and survival of marine organisms are influenced by environmental factors such as water temperature, salinity, and pH. Unsuitable environmental conditions may negatively impact marine organisms. The white leg shrimp (Litopenaeus vannamei), a euryhaline organism highly adapted to salinity, is a valuable species for aquaculture. This study examined the effects of water temperature, salinity, and pH on the health of postlarvae L. vannamei. Stress levels within the organisms were analyzed through the expression of a biomarker gene. Ferritin was selected as the biomarker gene for analysis. The experimental animal samples used were the hepatopancreas of L. vannamei postlarvae. The analysis was performed by qRT-PCR. The results showed that the adaptation of L. vannamei postlarvae to temperature was dependent on salinity. Under low-salinity conditions (5 psu), ferritin expression increased at 25 °C and 30 °C after 48 h of exposure; however, it decreased after 72 h of exposure. Under normal salinity conditions (27 psu), ferritin expression increased from 24 h to 72 h at water temperatures of 25 °C and 30 °C. These results indicate that low-salinity conditions may enable L. vannamei postlarvae to rapidly adapt to high temperatures. In conclusion, L. vannamei postlarvae adapt more efficiently to high temperatures under low-salinity conditions than that under high-salinity conditions. The results of this study could beneficially impact L. vannamei farming.
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(This article belongs to the Special Issue Impact of Environmental Factors on Aquatic Ecosystem)
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