Hydro-chemical characterization of groundwater using multivariate statistics in Hawassa City, Southern Ethiopia

Abstract

ABSTRACT This study characterized the hydro-chemical characteristics of groundwater for assessing the possibility of managed aquifer recharge in Hawassa City. A total of 48 water samples were taken from hand-dug wells and boreholes and examined to determine the water type, critical metrics, and key determinants of water quality. Multivariate statistical techniques such as hierarchical cluster, principal component, and linear discriminant analysis were used. The samples were divided into four variable groups and four case cluster groups. The results depicted the water hardness group (C1), soil salinity group (C2), weak and strong acids forming group (C3), and pollution indicator group (C4). Four water types were identified, Na–HCO3 and Ca–Na–HCO3 (87.5%), Ca–HCO3, and Na–Cl. Na–HCO3 was the dominant in hand-dug wells than in deep boreholes, which may account for evaporation or contaminations. Seven principal components with a cumulative variance of 78.58% were also formed. The first two, hardness and salinity, contributed 25.4 and 11.4% variance, respectively. In linear discriminate analysis, three discriminate functions with eight variables were generated, namely pH, K+, Na+, Ca2+, HCO3−, Cl−, BOD5, and COD. Thus, it is revealed that the decline in water quality attributed to natural and anthropogenic causes.