Comprehensive Evaluation Of Water Quality Research Articles

Spatiotemporal comprehensive evaluation of water quality based on enhanced variable fuzzy set theory: A case study of a landfill in karst area

Water quality assessment is a crucial step in water resource management and pollution prevention, and is essential for achieving sustainable development. Current methods for evaluating water quality often fall short of meeting the needs of water resource management due to the lacks of accuracy and applicability. In this paper, an enhanced water quality evaluation system was established by Principal Component Analysis / Factor Analysis (PCA/FA), Analytic Hierarchy Process / Entropy Weight Method / Game Theory (AHP/EWM/GT) and Variable Fuzzy Set Theory (VFST). The accuracy of this method was verified by evaluating the water quality of a landfill in a karst area and comparing with the conventional evaluation models. The results indicated that the highest influence on groundwater quality in the study area came from human factor, dissolved solid factor, biological factor, and nutritional factor. The quality of surface water and groundwater in the study area was primarily Grade Ⅱ, accounting for 62.5% and 75%, respectively. The predominant groundwater type was HCO3-Ca·Mg, which was strongly affected by karstification. The NH3-N and TP in the surface water had the highest variability, and the variation coefficients of K+, Na+, Ca2+, Cl−, NH3-N, NO3−, TDS, and TH in the groundwater were greater than 1. The surface water quality gradually improved between 2018 and 2019. Overall, the groundwater quality in the southern and central regions was inferior to that in the northern and surrounding areas. There could be a hydraulic link between the surface water and landfill in the research location, while karstification and leachate primarily impacted the groundwater. The water quality evaluation method established in this study can make a significant contribution to water resource management, which has important practical significance for environmental protection and indirect social value to the public.

Assessment of Water Pollution in the Korotoa River: Implications for Ecosystems and Human Welfare in Bogura, Bangladesh

This study presents a comprehensive evaluation of water quality in the Korotoa River, crucial to Bogura, Bangladesh, as it serves as a critical water supply for the city. Despite its significance, the river faces considerable pollution concerns from untreated pollutants emitted by urban and adjacent regions. The research attempts to analyze the level of water pollution and its repercussions on aquatic ecosystems and human usage. Through systematic water sample collection at numerous locations, the project examines physical and chemical features. Results, assessed against environmental criteria, indicate low dissolved oxygen levels and unsatisfactory water quality measures, particularly around confluence locations. The study exposes significant water pollution, necessitating immediate action to maintain aquatic life, ecosystems, and community well-being. Urgent pollution control actions are necessary to restore and preserve the Korotoa River’s natural balance in Bogura, emphasizing the need for education, monitoring, and research. The research provides insights for authorities and stakeholders to reduce pollution, sustaining the river’s critical role in the region’s biodiversity, agriculture, and human activities.

Hydrochemical characteristics and water quality assessment of natural water in the South China Mountains: the case in Lianzhou.

South China Mountain Region has a well-developed water system with the most abundant water in China. Untreated natural water is the main source of drinking water for the local people. This study aimed to investigate the hydrochemical characteristics and trace element concentrations of natural water in the mountainous regions of South China. In this study, 116 water samples were collected. Traditional hydrochemical methods, water quality index (WQI), hazard index (HI), and nutrient speciation of trace elements (NSTE) were used for analysis. In general, the hydrochemical type was mainly Ca-HCO3- type. The hydrochemical characteristics were mainly influenced by the weathering of calcite and silicate rocks. Overall total dissolved solids (TDS) were low, indicating mainly soft and very soft water. The water that met the standards for mineral water had an average concentration of 59.69mg/L for Sr (strontium) and an average concentration of 0.46mg/L for H2SiO3 (silicic acid). Although the water quality index (WQI) indicated that 91.3% of the water samples in the study area were of good quality (WQI < 25), 2.58% of the water samples had significant non-carcinogenic risk (HI > 1) due to the high As and Pb concentrations. The water in the study area contributed significantly to human intake of Sr, Cr, and V, accounting for 8.4, 8.3, and 7.7% of the required daily intake for adults, respectively. It is recommended that a comprehensive water quality evaluation system be constructed to ensure that mountain water is managed for development and safe to drink.

A comprehensive evaluation of water quality and its potential health risks using physicochemical indices in coastal areas of the Gulf of Suez, Red Sea

The Gulf of Suez plays a significant role in Egypt's economy and strategic position in the region, making it a critical waterway domestically and internationally due to being an essential hub for Egypt's oil and gas industry, housing numerous offshore oil and gas fields in the region. This paper aimed to comprehensively present the environmental status of the Gulf of Suez, the Red Sea, and pollution sources using one of the most fundamental ways to evaluate a water body. The Water Quality Index (WQI) measures nitrate levels in marine water and determines their potential harm to human health and the ecosystem. Excessive amounts of nitrate can pose non-carcinogenic health risks. Trophic state index (TSI), trophic index (TRIX), and Organic Pollution Index (OPI) are practical applications for surface water quality investigation and categorization based on contamination level. Principal Component Analysis (PCA), and Cluster Analysis (CA), were used to get better information for the studies on the water quality of surface waters. This study tested 38 subsurface locations during February 2021 for physical, chemical, microbiological, and nutritional salts. The WQI revealed that 71.23% of seawater samples were classified as having good water quality. However, TRIX and TSI metrics indicated eutrophication, with an average mean of 55.20, categorizing the water quality fairly. OPI values ranged between (3.50–3.75) which can be classified as moderate water quality. Finally, the current study's findings indicated the NO3− non-carcinogenic health hazards (HQ < 1) in all groups, but children are at a higher risk of NO3− exposure. Therefore, it can be concluded that Periodic assessments of water quality and strict regulations are necessary to safeguard this vital resource from pollution and ensure the well-being of future generations.

Water quality pollution assessment and source apportionment of lake wetlands: A case study of Xianghai Lake in the Northeast China Plain

Surface water pollution has always posed a serious challenge to water quality management. Improving water quality management requires figuring out how to comprehend water quality conditions scientifically and effectively as well as quantitatively identify regional pollution sources. In this study, Xianghai Lake, a typical lake-type wetland on the Northeast China Plain, was taken as the research area. Based on a geographic information system (GIS) method and 11 water quality parameters, the single-factor evaluation and comprehensive water quality index (WQI) methods were used to comprehensively evaluate the water quality of the lake-type wetland in the level period. Four key water quality parameters were determined by the principal component analysis (PCA) method, and more convenient comprehensive water quality evaluation models, the minimum WQI considering weights (WQImin-w) and the minimum WQI without considering weights (WQImin-nw) were established. The multiple statistical method and the absolute principal component score-multiple liner regression (APCS-MLR) model were combined to analyse the lake pollution sources based on the spatial changes in pollutants. The findings demonstrated that the WQImin-nw model’s water quality evaluation outcome was more accurate when weights were not taken into account. The WQImin-nw model can be used as a simple and convenient way to comprehend the variations in water quality in wetlands of lakes and reservoirs. It was concluded that the comprehensive water quality in the study area was at a “medium” level, and CODMn was the main limiting factor. Nonpoint source pollution (such as agricultural planting and livestock breeding) was the most important factor affecting the water quality of Xianghai Lake (with a comprehensive contribution rate of 31.65%). The comprehensive contribution rates of sediment endogenous and geological sources, phytoplankton and other plants, and water diversion and other hydrodynamic impacts accounted for 25.12%, 19.65%, and 23.58% of the total impact, respectively. This study can provide a scientific method for water quality assessment and management of lake wetlands, and an effective support for migration of migratory birds, habitat protection and grain production security.

Evaluation of water quality pollution and analysis of vertical distribution characteristics of typical Rivers in the Pearl River Delta, South China

Water quality comprehensive evaluation is an essential technical measure for water environment management and treatment. The previous research methods were often insufficient for studying black-sticking water bodies' formation and transformation mechanisms. In view of this, the single pollution index method and the comprehensive water quality identification index method (Iwq) were used to evaluate the pollution characteristics of rivers; the main pollution factors and sources of the watershed were determined by principal component analysis (PCA), and the vertical stratification characteristics of the water bodies were analyzed. The results showed that the total nitrogen (TN) values of pollutants in typical rivers in the Pearl River Delta were higher than the class V water quality standard, and the ammonia nitrogen (NH3−N) pollution level was the second-highest. TN concentration ranges from 4.27 to 19.83 mg/g, and NH3-N concentration ranges from 2.44 to 15.37 mg/g. In addition, in the monitoring of 15 rivers, 11 of them were the inferior V surface water, including five rivers' comprehensive water quality categories for black-stinking water bodies. This may be related to the process of water self-purification and pollutant transport, and rivers in densely populated areas are often subject to discharge from domestic sewage and industrial sewage. The results of the PCA extracted three principal components (PC), accounting for 88.825% of the total variance, with the first and third PCs controlled by human activities and the second PC influenced by natural sources. There is a more apparent vertical stratification of water bodies here in the typical rivers of the Pearl River Delta, and DO was an important factor affecting the vertical distribution of chemical oxygen demand (COD), NH3-N, TN, total phosphorus (TP), sulfide, Ferrum (Fe), and manganese (Mn). The severe lack of DO in deep water bodies led to elevated levels of NH3-N, Fe, and Mn, and gases such as hydrogen sulfide was released under anaerobic conditions, resulting in eutrophication and black-sticking levels in water bodies.

Assessing Landsat-8 atmospheric correction schemes in low to moderate turbidity waters from a global perspective

ABSTRACT Atmospheric correction is one of the major challenges in ocean color remote sensing, thus threatening comprehensive evaluation of water quality within aquatic environments. In this study, five state-of-the-art atmospheric correction (AC) processors (i.e. Acolite, C2RCC, iCOR, L2gen, and Polymer) were applied to Operational Land Imager (OLI) Landsat-8 scenes and evaluated against in situ measurements across various types of waters worldwide. A total of 262 matchups between in situ measured and satellite-derived remote sensing reflectance (R rs) at 20 sites were obtained between August 2013 and August 2021. Classification of optical water types (OWTs) was carried out using in situ measurements with matched satellite observations. OWT-specific analysis demonstrated that L2gen produced the most accurate R rs with R 2 ≥ 0.74 and root mean squared error (RMSE) ≤ 0.0018 sr–1 for the four visible bands of OLI, followed by Polymer, C2RCC, iCOR, and Acolite. In terms of R rs spectral similarity, C2RCC yielded the lowest spectral angle (SA) of 8.55°, followed by L2gen (SA = 9.20°). The advantage and disadvantage of each AC scheme were discussed. Recommendations to improve the accuracy for atmospheric correction were made, such as polarization observations and concurrent aerosol and ocean color measurements.

Water Quality Evaluation and Pollution Source Apportionment of Surface Water in a Major City in Southeast China Using Multi-Statistical Analyses and Machine Learning Models

The comprehensive evaluation of water quality and identification of potential pollution sources has become a hot research topic. In this study, 14 water quality parameters at 4 water quality monitoring stations on the M River of a city in southeast China were measured monthly for 10 years (2011-2020). Multiple statistical methods, the water quality index (WQI) model, machine learning (ML), and positive matrix factorisation (PMF) models were used to assess the overall condition of the river, select crucial water quality parameters, and identify potential pollution sources. The average WQI values of the four sites ranged from 68.31 to 77.16, with a clear trend of deterioration from upstream to downstream. A random forest-based WQI model (WQIRF model) was developed, and the results showed that Mn, Fe, faecal coliform, dissolved oxygen, and total nitrogen were selected as the top five important water quality parameters. Based on the results of the WQIRF and PMF models, the contributions of potential pollution sources to the variation in the WQI values were quantitatively assessed and ranked. These findings prove the effectiveness of ML in evaluating water quality, and improve our understanding of surface water quality, thus providing support for the formulation of water quality management strategies.

Impact of the development and utilization of coastal areas of Liaodong Bay on the environmental quality of seawater

Through variance decomposition, we investigated the impact of the rate of development and utilization intensity of coastal areas and the economic and industrial structure and spatial location on the environmental quality of seawater. The water quality of Liaodong Bay coastal waters was evaluated using the comprehensive water quality evaluation index, Nemerow index, and principal component analysis. Dalian and Huludao were found to have significantly better water quality than Panjin, Yingkou, and Jinzhou near the Liaohe Estuary. Marine functional areas and seawater quality index were spatially correlated, and the intensity of sea area development and utilization had a significant positive correlation with the comprehensive evaluation index of seawater quality and Nemerow index. The per capita gross domestic product of coastal cities and seawater quality index followed an "inverted U-shaped" Kuznets curve. Variance decomposition analysis showed that the intensity of sea area development and utilization cumulatively explained 42.3% of the changes in water quality, while the economic and industrial structure cumulatively explained 31.8%. The direct impact of sea area development and utilization intensity and economic and industrial structure contributed 16.5%, while the interaction between natural geographical location and sea area development and utilization intensity and economic and industrial structure cumulatively explained 58.9% of the changes. Our results strongly support management and control of sea reclamation, comprehensive management of coastal waters, and optimization of coastal industrial structure to improve the environmental quality of coastal waters.

Assessing Heavy Metal Pollution of the Largest Nature Reserve in Tianjin City, China.

Beidagang Wetland (BW) Nature Reserve is centrally situated in Tianjin City, experiencing an extreme industrial development. This study uses index characteristic analysis systems for assessing the individual and combined heavy metal pollution loading in the water during the spring and autumn seasons. By combining the pollution level of single pollutant, a more comprehensive evaluation of water quality in BW was achieved. Water quality was worst during autumn due to high level of Cd and Pb, which indicate the type of anthropogenic activities have a serious effect on heavy metal pollution in BW. In addition, high exchangeable amounts of Cd (> 40%) were found in the sediments of BW, indicating Cd pollution has emerged. There is a need for appropriate abatement actions curbing heavy metal loading and improving water quality of the BW Nature Reserve, thereby ensuring a sustainable management of its ecosystem services.

Distributions of nitrogen and phosphorus in ice-covered water systems and comprehensive evaluation of water quality in reservoirs during the freezing period

ABSTRACT The distributions of nitrogen and phosphorus and the comprehensive water quality of reservoirs during freezing periods constitute weaknesses in water quality management strategies during certain periods. In this paper, ice and water samples of a typical reservoir, Biliuhe reservoir, were collected and analysed, and the comprehensive water quality was evaluated by the variable fuzzy recognition method. The results showed that the effect of ‘salt exclusion’ during ice formation was obvious, with exclusion factors of 10.54 and 1.26 for total nitrogen (TN) and total phosphorus (TP), respectively. The evaluation results showed that the comprehensive water quality of the water column and ice were 2.68 and 1.44, respectively, during the freezing period. When considering the effect of salt exclusion, the TN and TP contents in the surface water of the reservoir were 3.15 and 2.62 times the previous contents, respectively, and the evaluation results showed that the surface water quality decreased by 5%. The effect of salt exclusion during ice formation in winter mainly occurred in the top layer of the water column under ice in the deep reservoir. It is necessary to further study the influence of reservoir sediments on water quality in ice-covered water systems.

Optimization of Sustainable Land Use Management in Water Source Area Using Water Quality Dynamic Monitoring Model.

Land use management is the primary source of resource planning, and the management part of the sustainable ecosystem of water and soil resources is an important evidence for the sustainable development of the economic and social system. This is guided by the concept of sustainable development, and on the basis of the accumulation of relevant research practices and outcomes at home and abroad, water and land based systems are a research object and study the status of water and soil resource utilization, the state of water and soil coupling, and the supply and demand status of water resources. A balance analysis was carried out, and the gray linear programming model was used to optimize the allocation of land resources using the water quality dynamic monitoring model, which achieved the best coupling of water and soil resources and the greatest benefit. In this paper, aiming at the two types of problems in comprehensive water quality evaluation, namely, aiming at indifference and spatiotemporal changes, this article explores a powerful calculation method based on variable identification models and compiles a GIS geostatistical model (it is a computer-based tool that can draw and analyze ground objects; event GIS technology integrates seamless visual effects between map and local analysis services and general data processing services) to perform spatial analysis and visual expression of the evaluation results, in-depth analysis of the connotation, and theory and optimal allocation model of land resources optimal allocation. On the basis of the conceptual framework of the best share of land sources, the theories that should follow in the best share of land sources are discussed, and the available models and their characteristics are analyzed and compared. Experimental results show that, in the data provided by the analysis of water supply and demand balance at the annual spring system site by constructing an energy monitoring model, the water supply conditions of different water sources are rough, but the data of this study shows that the water shortage rate has reached 25%. In addition, the article explains the setting variables for the optimal allocation of land resources in water sources and compares and analyzes the optimization and planning of land resources in water sources.

Comprehensive water quality evaluation based on kernel extreme learning machine optimized with the sparrow search algorithm in Luoyang River Basin, China

Comprehensive water quality evaluation based on kernel extreme learning machine optimized with the sparrow search algorithm in Luoyang River Basin, China

Assessment of Water Quality in A Tropical Reservoir in Mexico: Seasonal, Spatial and Multivariable Analysis.

Agricultural activities are highly related to the reduction of the availability of water resources due to the consumption of freshwater for crop irrigation, the use of fertilizers and pesticides. In this study, the water quality of the Adolfo López Mateos (ALM) reservoir was evaluated. This is one of the most important reservoirs in Mexico since the water stored is used mainly for crop irrigation in the most productive agricultural region. A comprehensive evaluation of water quality was carried out by analyzing the behavior of 23 parameters at four sampling points in the period of 2012-2019. The analysis of the spatial behavior of the water quality parameters was studied by spatial distribution graphs using the Inverse Distance Weighting interpolation. Pearson correlation was performed to better describe the behavior of all water quality parameters. This analysis revealed that many of these parameters were significantly correlated. The Principal Components Analysis (PCA) was carried out and showed the importance of water quality parameters. Ten principal components were obtained, which explained almost 90% of the total variation of the data. Additionally, the comprehensive pollution index showed a slight water quality variation in the ALM reservoir. This study also demonstrated that the main source of contamination in this reservoir occurs near sampling point one. Finally, the results obtained indicated that a contamination risk in the waterbody and further severe ecosystem degradations may occur if appropriate management is not taken.

Groundwater Quality Evaluation of the Dawu Water Source Area Based on Water Quality Index (WQI): Comparison between Delphi Method and Multivariate Statistical Analysis Method

Water quality in the Dawu water source area is primarily studied through the traditional water quality assessment method that measures the chemical parameters of water against the existing standards, which is simple but cannot accurately describe the water quality. Although the water quality index (WQI) proposed by Horton is widely used for comprehensive water quality evaluation, parameter selection and weight determination are primarily based on the Delphi method, which is subjective and random. Moreover, in groundwater evaluation, the focus is primarily laid on general chemical parameters, such as Total Dissolved Solids, hydrogen ion concentration, Electrical Conductivity, and heavy metals, such as Hydrargyrum, Arsenic, and Chromium, with limited consideration for organic pollutants. In this study, WQI technology in combination with the entropy weight method was used to evaluate the groundwater environmental quality of the Dawu water source area, and the scientific results were analyzed by comparing the full index, Delphi, and multivariate statistical analysis methods. The results showed that the groundwater in the Dawu water source area generally had good quality and was potable and that the application of multivariate statistical analysis method was more suitable than the Delphi method in the index selection process.

Characteristics and evaluations of heavy metal contents in irrigation water sources on a suburb farmland in the lower reaches of Xijiang River in the early busy season of farming

Abstract The pollution of heavy metals in irrigation water was related to the management-control of the risk of heavy metals in farmland and the safe production of crops. There were various sources of irrigation water in the suburb farmlands of Xijiang River. We investigated the sources and distribution characteristics of heavy metals in the irrigation water sources on a riverside and inside-dyke farmland of Xijiang River. According to sample test results, it was found that nearly 100% of heavy metals that we were concerned about were detected in the irrigation water sources in the study. The box plot showed that the average content of other elements ranged from 1.65 to 43.75 μg·L−1, and the average level of cadmium was 0.02 μg·L−1 in the studied area. According to quantitative evaluation index and analysis of distribution characteristics, most heavy metals were at relatively low concentration in the irrigation water sources, while mercury content was far greater than other elements, followed by arsenic. Arsenic and mercury had become increasingly prominent problems in local irrigation water sources. River quality was more likely to be affected by river water and agricultural activities, while groundwater quality was more likely to be affected by natural causes. According to single/comprehensive water-quality evaluations, the comprehensive water quality evaluation ranged from level I to level III, but the single-factor index evaluations of mercury in most water samples and arsenic in two groundwater samples were of ‘Inferior’ level. Attention should be paid to the monitoring of mercury and arsenic (in the groundwater) in the studied area. The disposal methods of farmland water inflow and drainage should be increased if necessary, and reducing the influence of human activities on the natural weathering and leaching of heavy metals was an effective measure to avoid risk of agricultural production.

柏条河流域水质及非点源污染综合评估

柏条河流域水质及非点源污染综合评估

An integrated approach for assessing surface water quality: Case of Beni Haroun dam (Northeast Algeria).

In this paper, we use an integrated approach to carry out a comprehensive evaluation of water quality in the Beni Haroun (BH) dam, the largest surface water resource in Algeria. Several techniques have been employed under the same framework, including the Canadian Council Ministers Environment Water Quality Index (CCME-WQI), principal component analysis and factor analysis (PCA/FA), the K-means clustering, and the ordinary least square (OLS) analysis. A data set of 22 physicochemical parameters has been collected, over a period of 11 years, from three sampling stations: Ain Smara (ST1) and Menia (ST2), both located upstream of "Wadi Rhumel," and BH dam station (ST3), located at the dam site. The PCA/FA enables the identification of seven key factors that influence significantly BH dam water quality. The average values of CCME indices at the BH dam were 17, 40, 42, and 32 for drinking, irrigation, industry, and aquatic life purposes, respectively, which indicate poor water quality, according to the CCME categorization scheme. Besides, the K-means algorithm has been proven to be a very useful machine learning tool to detect that the major source of BH dam pollution is "Wadi Rhumel." Finally, OLS analysis, along with the Mann-Kendall test, highlighted the positive trend of BH dam's water quality.

Can Entropy Weight Method Correctly Reflect the Distinction of Water Quality Indices?

Entropy weight method (EWM) is a widely used weighting approach in water quality evaluation that assigns weights according to the discriminating degree of indicators. A higher discrete degree corresponds to a larger weight requirement, and vice versa. By using two water quality evaluation examples, this study proves that the weighting result of EWM cannot accurately reflect the information content and discriminability of indices in many conditions. For the EWM that uses the directly generating quotient (DGQ) in standardization, when the concentration dataset contains many zero values, the EWM results become prone to distortion. Similarly, for the EWM that utilizes the generating quotient after range pretreatment (GQARP) in standardization, when similar maximum values are present in the concentration dataset, the EWM results become prone to distortion. From the distortion weighting results of EWM, those indicators with high pollution degrees can be easily neglected, thereby leading to overoptimistic comprehensive water quality evaluation results. Although the source of distortion in the EWM results can be traced to the standardization and ranging processes, a solution to this problem is not yet available. In sum, the conventional EWM cannot correctly reflect the distinction of water quality indices; and it cannot be directly applied in water quality evaluation.

Application of T-S Fuzzy-Neural Network Model in Water Quality Comprehensive Evaluation

Abstract In order to comprehensively evaluate the water environment quality of Liuxi river Irrigation District in Guangzhou more effectively, the fuzzy neural network based on T-S model was used to evaluate and analyze the water quality characteristics of Liuxi river Irrigation District. Six indexes, including dissolved oxygen, chemical oxygen demand, ammonia nitrogen, permanganate index, total phosphorus and total nitrogen, which have important effects on water quality, were selected to establish an applicable comprehensive evaluation model for water quality. Water quality of two water sampling sections, the upstream Da’ao monitoring section and the downstream Liyuan monitoring section, were sampled and analyzed. The results show that the water quality evaluation results of the upstream Da’ao monitoring section are better than that of the downstream Liyuan monitoring section. The variation trend of water quality grade evaluated by the model is consistent with that of the real index data.