Using Graphical and Multivariate Statistical Methods for Geochemical Assessment of Groundwater Quality in Oumé Department (Côte d’Ivoire)

Abstract

The large demand for drinking water in Oumé Department in the Centre western of Cote d’Ivoire is supplied from groundwater sources. This study investigated the geochemical assessment of groundwater quality in Oumé Department by using a hydrochemical approach with graphical and self-organizing maps (SOM) neural network methods. It was carried out for identifying the hydrogeochemical processes related to groundwater quality, conducting a hydrochemical evaluation of the aquifer systems and delineating the various factors controlling the water chemistry and general suitability for drinking purposes. To reach these goals, groundwater was sampled from 91 locations. Results indicated that the groundwater sampled is acid (pH 4.27 - 7.10) and was weakly fairly mineralised with electrical conductivity values obtained in the range of 95 - 1071 μS·cm-1. All calcium (6.8 - 127.59 mg·L-1), magnesium (1.08 - 29.00 mg·L-1), sulphate (0 - 74.9 mg·L-1), chloride (1.2 - 89.8 mg·L-1), sodium (1.2 - 94.27 mg·L-1) and potassium (0.05 - 23.65 mg·L-1) concentrations and almost nitrate concentrations were within of the recent acceptability and healthbased of drinking-water guidelines set by World Health Organization (WHO). Moreover eleven sampling sites only have concentrations of iron above 0.3 mg·L-1 which can stain laundry and cause taste. In the water points, hydrochemical facies was calcium-bicarbonate (Ca-HCO3) type which generally shows less-polluted water quality. Based on pattern analysis, the inter-relationships among the groundwater quality variables due to the contact with different geological formations on the basis of rocks basicity and acidity were extracted and interpreted.