Characterization of Drinking Groundwater Quality Using Multivariate Statistical Analysis and Water Quality Index in the Cuvelai-Etosha Basin, Namibia

The quality of groundwater in the Cuvelai-Etosha Basin, a critical water source in northern Namibia, is increasingly influenced by both natural processes and anthropogenic activities. This study characterized the groundwater quality in the basin using multivariate statistical analysis and the Water Quality Index (WQI). Groundwater samples were collected from five wells that support the community across the basin, and a range of physicochemical and bacteriological parameters, including pH, electrical conductivity, total dissolved solids, nitrate, nitrite, dissolved oxygen, chloride, fluoride, ammonia, turbidity, sodium, calcium, magnesium, and E. coli, were analyzed. Multivariate statistical techniques, such as Principal Component Analysis (PCA), Cluster Analysis (CA), and Factor Analysis, were employed to identify patterns, sources, and correlations among the various water quality parameters. The WQI was calculated to provide an integrated measure of water quality, categorizing groundwater according to its suitability for consumption. The wells’ WQI results indication follows: excellent for GW5 (24.41), good for GW3 (58.45) and GW1 (61.57), poor for GW2 (107.76) and GW4 (127.33) for drinking based on the study's parametric indicators weight. WQI varies spatially within the basin, with certain areas exhibiting higher contamination levels due to runoff and inadequate water management practices. About 60% of the groundwater sources fall into the "excellent" to "good" quality categories, indicating minimal health risks and the need for effective management strategies. The PCA and CA revealed that key anions and cations, such as Electrical Conductivity, Total Hardness, Ca, Mg, and Cl, are the major contributors to the water quality, including natural geochemical processes and human-induced activities. This study provides crucial insights into the drinking groundwater quality of the Cuvelai-Etosha Basin and offers a methodological framework for future water quality monitoring and sustainable resource management in semi-arid regions.