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Multivariate Statistical Analysis of Groundwater Quality of Hassi R'mel, Algeria

Mehdi Metaiche, Hakim Djafer Khodja, Amina Aichour, Nourredine Gaci

Journal of Ecological Engineering

2023

Vol. 24, nr 5

22--31

The quality of Groundwater is characterized by physico-chemical parameters. They determine the way in which this water is used (water supply, irrigation, industry, etc.). This present study gives the highlighting of the hydrogeological and physico-chemical characteristics of aquifer waters in question resulting from the various wells, which aims to; gather, exploit and analyze the data, in order to determine their conformity with potability standards and their suitability for irrigation. Using multivariate statistical techniques including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (ACH) and Diagram Analysis. They are applied to a dataset composed of 17 boreholes with 12 chemical variables over the entire study area, they were sampled in 2020. These boreholes are the principal water resources suppling Hassi R'mel w. Laghouat region in terms of drinking water and irrigation. Obtained results showed that the majority of groundwater in the Hassi R’mel region is hard; where approximately 20% of boreholes are characterized by fairly soft water, and approximately 5% are characterized by very hard water.

Application of Multivariate Statistical Methods to the Hydrochemical Study of Groundwater Quality in the Sahel Watershed, Algeria

Hakim Djafer Khodja, Amina Aichour, Amina Rezig, Djouhra Baloul, Ahmed Ferhati

Journal of Ecological Engineering

2022

Vol. 23, nr 8

341--349

The quality of groundwater is characterized by several numbers of physical and chemical parameters, which determine the use of water (water supply, irrigation, industry). This search paper is a contribution made to know the hydrochemical characteristics of groundwater in the Sahel sub-catchment which belongs to the large Soummam North basin of Algeria. Different multivariate statistical techniques were used such as principal component analysis (PCA), Hierarchical Cluster Analysis (HCA) and Diagram Analysis. These analyses are exercised to a dataset formed from 37 boreholes with 12 chemical variables over the entire surface of the watershed. The samples were collected in 2016. The 37 boreholes are one of the main water resources that supply the wilaya of Bouira with drinking water and irrigation. The analysis of water quality using different methods (ACP, HCA and Diagram) resulted in two chemical kinds: (Chloride, calcium sulfate and magnesium), and (Bicarbonate calcium and magnesium). The results have shown that 74% of the boreholes were contaminated, the rest of boreholes were characterized by a good quality and they have not suffered any contamination and can be consumed without any risk.