Assessment of Dibdibba Groundwater Quality Using the Multivariate Statistical Technique in Zuber area South of Iraq

Thirty-three samples of groundwater were taken from Dibdibba unconfined aquifer in the Zuber area southwestern parts of Basrah governorate south of Iraq to assess the groundwater quality. A statistical multivariate analysis was done using cations and anions, pH, total dissolved solids (TDS), and electrical conductivity (EC) that were measured for drinking, livestock, and construction purposes. Residual sodium bicarbonate (RSBC), Magnesium Ratio (MR), and Permeability index (PI) were used to evaluate the suitability of the present samples for irrigation activity. The quality of groundwater in the study area is unsuitable for drinking water, industrial and building uses. But it is suitable for livestock uses, According to Residual Sodium Carbonate and Magnesium Ratio the groundwater in the study area are suitable for irrigation purposes, but unsuitable for Permeability index. Multivariate analysis results indicate the high positive correlation between Ec and TDS with other constituents, two significant clusters I and II are obtained with significant Ec and TDS responsible for playing the most effective in classifying the present samples. 71.85% and l2.21% of the present of the total variance of the groundwater samples were explained by Factor analyses, Factor I indicated increasing Cl-, Mg+2, Na+, and Ca+2 with the highest weight and Factor II show lower weight average of K+ concentration only. The results confirm the dissolution of sulfate salts and evaporate minerals, in addition to high agricultural lands and farm activities, besides the wastes from chemical construction industries.

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Groundwater quality assessment using multivariate statistical technique and hydro-chemical facies in Birbhum District, West Bengal, India

SN Applied Sciences ◽

10.1007/s42452-019-0841-5 ◽

2019 ◽

Vol 1 (8) ◽

Cited By ~ 2

Author(s):

Niladri Das ◽

Prolay Mondal ◽

Ranajit Ghosh ◽

Subhasish Sutradhar

Keyword(s):

Groundwater Quality ◽

Quality Assessment ◽

West Bengal ◽

Statistical Technique ◽

Multivariate Statistical ◽

Groundwater Quality Assessment ◽

Multivariate Statistical Technique ◽

Birbhum District

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Assessment of groundwater quality around municipal solid waste landfill by using Water Quality Index for groundwater resources and multivariate statistical technique: a case study of the landfill site, Qaem Shahr City, Iran

Environmental Geochemistry and Health ◽

10.1007/s10653-019-00417-0 ◽

2019 ◽

Vol 42 (5) ◽

pp. 1305-1319 ◽

Cited By ~ 3

Author(s):

Hossein Najafi Saleh ◽

Sima Valipoor ◽

Asma Zarei ◽

Mahmood Yousefi ◽

Farzaneh Baghal Asghari ◽

...

Keyword(s):

Water Quality ◽

Municipal Solid Waste ◽

Groundwater Quality ◽

Water Quality Index ◽

Quality Index ◽

Groundwater Resources ◽

Statistical Technique ◽

Multivariate Statistical ◽

Waste Landfill

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DUAL PLS ANALYSIS

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622012500241 ◽

2012 ◽

Vol 11 (05) ◽

pp. 879-891 ◽

Cited By ~ 3

Author(s):

STAN LIPOVETSKY

Keyword(s):

Factor Analysis ◽

Multivariate Analysis ◽

Canonical Correlation ◽

Statistical Technique ◽

Data Sets ◽

Multivariate Statistical ◽

Data Set ◽

Correlation Matrices ◽

Data Merging ◽

Pls Analysis

A new multivariate statistical technique is obtained for comparing and combining two or more data sets each of which has a different number of respondents but the same variables. This approach can be considered as dual to such techniques as partial least squares, also known as inter-battery factor analysis and robust canonical correlation analysis for two data sets. It is shown that the problem can be reduced to the eigenproblem of the product of correlation matrices of each data set. The technique is generalized to three or more data sets in an eigenproblem of block-matrices of the correlations within each data set. This type of multivariate analysis can serve various practical problems of integration of data obtained from heterogeneous sources, particularly, for data merging in constructing data warehouses.

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Correction to: Assessment of groundwater quality around municipal solid waste landfill by using Water Quality Index for groundwater resources and multivariate statistical technique: a case study of the landfill site, Qaem Shahr City, Iran

Environmental Geochemistry and Health ◽

10.1007/s10653-020-00765-2 ◽

2020 ◽

Author(s):

Hossein Najafi Saleh ◽

Sima Valipoor ◽

Asma Zarei ◽

Mahmood Yousefi ◽

Farzaneh Baghal Asghari ◽

...

Keyword(s):

Water Quality ◽

Municipal Solid Waste ◽

Groundwater Quality ◽

Water Quality Index ◽

Quality Index ◽

Groundwater Resources ◽

Statistical Technique ◽

Multivariate Statistical ◽

Waste Landfill

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Total coliforms, arsenic and cadmium exposure through drinking water in the Western Region of Ghana: application of multivariate statistical technique to groundwater quality

Environmental Monitoring and Assessment ◽

10.1007/s10661-014-4167-x ◽

2015 ◽

Vol 187 (2) ◽

Cited By ~ 198

Author(s):

Andrews Obeng Affum ◽

Shiloh Dede Osae ◽

Benjamin Jabez Botwe Nyarko ◽

Samuel Afful ◽

Joseph Richmond Fianko ◽

...

Keyword(s):

Drinking Water ◽

Groundwater Quality ◽

Statistical Technique ◽

Cadmium Exposure ◽

Western Region ◽

Multivariate Statistical ◽

Total Coliforms ◽

Multivariate Statistical Technique ◽

The Western Region

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Hydro-Geochemical Assessment of Groundwater Quality in Aseer Region, Saudi Arabia

Water ◽

10.3390/w10121847 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1847 ◽

Cited By ~ 8

Author(s):

Javed Mallick ◽

Chander Singh ◽

Mohammed AlMesfer ◽

Anand Kumar ◽

Roohul Khan ◽

...

Keyword(s):

Saudi Arabia ◽

Groundwater Quality ◽

Structural Equation ◽

Anthropogenic Activities ◽

Principal Component ◽

Statistical Technique ◽

Climatic Conditions ◽

Geochemical Modelling ◽

Multivariate Statistical ◽

Study Region

Saudi Arabia is an arid country with very limited water resources. The absence of surface water bodies along with erratic rainfall renders groundwater as the most reliable source of potable water in arid and semi-arid regions globally. Groundwater quality is determined by aquifer characteristics regional geology and it is extensively influenced by both natural and anthropogenic activities. In the recent past, several methodologies have been adopted to analyze the quality of groundwater and associated hydro-geochemical process i.e., multivariate statistical analysis, geochemical modelling, stable isotopes, a redox indicator, structural equation modelling. In the current study, statistical methods combined with geochemical modelling and conventional plots have been used to investigate groundwater and related geochemical processes in the Aseer region of Saudi Arabia. A total of 62 groundwater samples has been collected and analyzed in laboratory for major cations and anions. Groundwater in the study region is mostly alkaline with electrical conductivity ranging from 285–3796 μS/cm. The hydro-geochemical characteristics of groundwater are highly influenced by extreme evaporation. Climatic conditions combined with low rainfall and high temperature have resulted in a highly alkaline aquifer environment. Principal component analysis (PCA) yielded principal components explaining 79.9% of the variance in the dataset. PCA indicates ion exchange, soil mineralization, dissolution of carbonates and halite are the major processes governing the groundwater geochemistry. Groundwater in this region is oversaturated with calcite and dolomite while undersaturated with gypsum and halite which suggests dissolution of gypsum and halite as major process resulting into high chloride in groundwater. The study concludes that the combined approach of a multivariate statistical technique, conventional plots and geochemical modelling is effective in determining the factors controlling the groundwater quality.

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