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Belkhiri, L., Boudoukha, A., Mouni, L.. (1390). A multivariate Statistical Analysis of Groundwater Chemistry Data. , 5(2), 537-544. doi: 10.22059/ijer.2011.338
L. Belkhiri; A. Boudoukha; L. Mouni. "A multivariate Statistical Analysis of Groundwater Chemistry Data". , 5, 2, 1390, 537-544. doi: 10.22059/ijer.2011.338
Belkhiri, L., Boudoukha, A., Mouni, L.. (1390). 'A multivariate Statistical Analysis of Groundwater Chemistry Data', , 5(2), pp. 537-544. doi: 10.22059/ijer.2011.338
Belkhiri, L., Boudoukha, A., Mouni, L.. A multivariate Statistical Analysis of Groundwater Chemistry Data. , 1390; 5(2): 537-544. doi: 10.22059/ijer.2011.338

A multivariate Statistical Analysis of Groundwater Chemistry Data

International Journal of Environmental Research
مقاله 28، دوره 5، شماره 2، تیر 2011، صفحه 537-544    اصل مقاله (845.28 K)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22059/ijer.2011.338
نویسندگان
L. Belkhiri* 1؛ A. Boudoukha2؛ L. Mouni3
1Department of hydraulics, University Hadj Lakhdar 05000 Batna, Algeria
2Research Laboratory in Applied Hydraulics, University Hadj Lakhdar 05000 Batna, Algeria
3Departement de Génie des Procèdes, Faculté de Technologie, Université de Bejaia, Targa, Ouzemour 06000, Algeria
چکیده
Q-mode hierarchical cluster (HCA) and principal component analysis (PCA) were simultaneously
applied to groundwater hydrochemical data from the three times in 2004: June, September, and December,
along the Ain Azel aquifer, Algeria, to extract principal factors corresponding to the different sources of
variation in the hydrochemistry, with the objective of defining the main controls on the hydrochemistry at the
aquifer scale. Hydrochemical data for 54 groundwater samples were subjected to Q-mode hierarchical cluster
and principal component analysis. The study finds, from Q-mode HCA that there are three main hydrochemical
facies namely the less saline water (group 1: Ca-Mg-HCO3), mixed water (group 2: Mg-Ca-HCO3-Cl) and
blended water (group 3: Mg-Ca-Cl-HCO3). In principal component analysis, the first 4 factors explain 72.14%
of the total variance, their loadings allowing the interpretation of hydrochemical processes that take place in
the area. The results of this study clearly demonstrate the usefulness of multivariate statistical analysis in
hydrochemical.
کلیدواژه‌ها
Hydrochemistry؛ Multivariate techniques؛ Q-mode hierarchical cluster analysis؛ Principal component analysis؛ Ain Azel plain؛ Algeria
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