Multivariate statistical characterization of groundwater quality in Fesdis, East of Algeria

Journal of Water and Land Development

Safia Khelif^1¹  Abderrahmane Boudoukha^2² 

[1] 05000, Batna, Algeria^1;Algeria^2

关键词: cluster analysis;    Fesdis Plain;    groundwater;    hydrochemistry;    multivariate statistical techniques;    principal component analysis;   

DOI  :  10.2478/jwld-2018-0026

学科分类：农业科学（综合）

来源: Instytut Technologiczno-Przyrodniczego / Institute of Technology and Life Sciences

【 摘 要 】

This study is a contribution to the knowledge of hydrochemical properties of the groundwater in Fesdis Plain, Algeria, using multivariate statistical techniques including principal component analysis (PCA) and cluster analysis. 28 samples were taken during February and July 2015 (14 samples for each month). The principal component analysis (PCA) applied to the data sets has resulted in four significant factors which explain 75.19%, of the total variance. PCA method has enabled to highlight two big phenomena in acquisition of the mineralization of waters. The main phenomenon of production of ions in water is the contact water-rock. The second phenomenon reflects the signatures of the anthropogenic activities. The hierarchical cluster analysis (CA) in R mode grouped the 10 variables into four clusters and in Q mode, 14 sampling points are grouped into three clusters of similar water quality characteristics.

【 授权许可】

Unknown