A Multivariate Statistical Analysis of Groundwater Chemistry Data in the Highest Bandama Basin at Tortiya (Northern Côte D’Ivoire)

Abstract

The multivariate statistical tools R-mode hierarchical cluster analysis (HCA) and principal component analysis (PCA) were simultaneously applied to groundwater hydrochemical data of the Highest Bandama Basin (Northern of Cote d'Ivoire) to extract principal processes controlling water chemistry. Though the PCA proved to be more robust at unveiling the sources of variation in the hydrochemistry than the R-mode hierarchical cluster analysis (HCA), the combined use of both techniques resulted in more reliable interpretations of the hydrochemistry. They reveal three processes responsible of water chemistry which are mineralization-water residence time, oxidation process and spatial origin of water and degradation of quality. Among these processes, mineralization-water chemistry by mean of water-interaction and weathering of silicate minerals is the most important. The oxidation process underlines the influence of environment conditions and aquifers state in ions acquisition. Indeed, the probable degradation of groundwater is thus revealing.