Groundwater quality index based on PCA: Wadi El-Natrun, Egypt

Abdelaziz, Shokry; Gad, Mohamed; Tahan, Abdel Hamid M.H. El

doi:10.1016/j.jafrearsci.2020.103964

Cited by 45 publications

(22 citation statements)

References 25 publications

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“…Due to the high relationship between Na + and Cl − , PC1 describes the great difference in the data set, may be hard and salinity. The occurrence of carbonated rocks in the study area and the higher concentration of Na + and Cl − contributed to the high TDS values [60].…”

Section: Principal Component Analysis (Pca) and Correlation Analysis Of Groundwater Variablesmentioning

confidence: 90%

Hydrogeochemical Investigation of Elevated Arsenic Based on Entropy Modeling, in the Aquifers of District Sanghar, Sindh, Pakistan

Ullah

Talib

Rashid

et al. 2021

Water

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Arsenic (As) contamination in drinking groundwater is a common environmental problem in Pakistan. Therefore, sixty-one groundwater samples were collected from various groundwater sources in District Sanghar, Sindh province, Pakistan, to understand the geochemical behavior of elevated As in groundwater. Statistical summary showed the cations and anions abundance in decreasing order of Na+ > Ca2+ > Mg2+ > K+, and HCO3− > Cl− > SO42− > NO3−. Arsenic was found with low to high concentration levels ranging from 5 µg to 25 µg/L with a mean value of 12.9 µg/L. A major water type of groundwater samples was mixed with NaCl and CaHCO3 type, interpreting the hydrochemical behavior of rock–water interaction. Principal component analysis (PCA) showed the mixed anthropogenic and natural sources of contamination in the study area. Moreover, rock weathering and exchange of ions controlled the hydrochemistry. Chloro-alkaline indices revealed the dominance of the reverse ion exchange mechanism in the region. The entropy water quality index (EWQI) exposed that 17 samples represent poor water, and 11 samples are not suitable for drinking.

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Section: Principal Component Analysis (Pca) and Correlation Analysis Of Groundwater Variablesmentioning

confidence: 90%

Hydrogeochemical Investigation of Elevated Arsenic Based on Entropy Modeling, in the Aquifers of District Sanghar, Sindh, Pakistan

Ullah

Talib

Rashid

et al. 2021

Water

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“…It is a comprehensive analysis method that can analyze the statistical law of multiple objects and multiple indices under the condition that they are interrelated. Multivariate statistical techniques have been widely used in water quality data analysis [32][33][34][35][36][37]. These tools help simplify and organize large datasets to explain the observed relationships between several variables [38].…”

Section: Methodsmentioning

confidence: 99%

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

Liu

Zhu

Cui

et al. 2021

Water

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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.

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“…Anbazhagan and Nair (2004) have used the geographical information system (GIS) to represent the spatial variation of various geochemical elements in Panvel Basin, Maharashtra, India. Several multivariate statistical techniques such as cluster analysis (CA), factor analysis (FA), and principal component analysis (PCA) have been employed by many researchers to identify the significant parameters of groundwater quality (Abdelaziz et al 2020). Zheng et al (2016) applied CA, discriminate analysis (DA), PCA, and FA to evaluate the surface water quality and categorized the physicochemical parameters of water quality in the Second Songhua River basin in China.…”

Section: Introductionmentioning

confidence: 99%

“…To assess the surface water and groundwater quality, several approaches have been studied during the last few decades. The water quality index (WQI) tool can be used to assess water quality by transforming a huge number of parameters into a single index (Tyagi et al 2013;Minh et al 2019;Abdelaziz et al 2020). The WQI method was first introduced by Horton (1965) by using ten parameters of water quality.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the groundwater quality of Damodar Fan Delta (India) using fuzzy-AHP MCDM technique

Mahammad

Islam

2021

Appl Water Sci

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In recent years, groundwater pollution has become increasingly a serious environmental problem throughout the world due to increasing dependency on it for various purposes. The Damodar Fan Delta is one of the agriculture-dominated areas in West Bengal especially for rice cultivation and it has a serious constraint regarding groundwater quantity and quality. The present study aims to evaluate the groundwater quality parameters and spatial variation of groundwater quality index (GWQI) for 2019 using the fuzzy analytic hierarchy process (FAHP) method. The 12 water quality parameters such as pH, TDS, iron (Fe−) and fluoride (F−), major anions (SO42−, Cl−, NO3−, and HCO3−), and cations (Na+, Ca2+, Mg2+, and K+) for the 29 sample wells of the study area were used for constructing the GWQI. This study used the FAHP method to define the weights of the different parameters for the GWQI. The results reveal that the bicarbonate content of 51% of sample wells exceeds the acceptable limit of drinking water, which is maximum in the study area. Furthermore, higher concentrations of TDS, pH, fluoride, chloride, calcium, magnesium, and sodium are found in few locations while nitrate and sulfate contents of all sample wells fall under the acceptable limits. The result shows that 13.79% of the samples are excellent, 68.97% of the samples are very good, 13.79% of the samples are poor, and 3.45% of the samples are very poor for drinking purposes. Moreover, it is observed that very poor quality water samples are located in the eastern part and the poor water wells are located in the northwestern and eastern part while excellent water quality wells are located in the western and central part of the study area. The understanding of the groundwater quality can help the policymakers for the proper management of water resources in the study area.

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Groundwater quality index based on PCA: Wadi El-Natrun, Egypt

Cited by 45 publications

References 25 publications

Hydrogeochemical Investigation of Elevated Arsenic Based on Entropy Modeling, in the Aquifers of District Sanghar, Sindh, Pakistan

Hydrogeochemical Investigation of Elevated Arsenic Based on Entropy Modeling, in the Aquifers of District Sanghar, Sindh, Pakistan

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

Evaluating the groundwater quality of Damodar Fan Delta (India) using fuzzy-AHP MCDM technique

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