ABSTRACT
Groundwater is one of the major sources of water. It is affected by a number of natural and anthropogenic factors. As groundwater use has increased, issue associated with the quality of groundwater resources have likewise grown in importance. In this study, mathematical modelling technique for water quality index computation and multivariate statistical using Principal Component Analysis (PCA) were employed to evaluate and analyze the variability of ground water quality in parts of Sapele, Delta State, Nigeria. Water samples were collected randomly from Eight (8) boreholes within the study area. The water samples were then subjected to full laboratory analysis in other to determine their physicochemical properties that was used to compute the overall water quality index of the individual water samples. Statistical computations involving the application of principal component analysis for ground water modelling was made using statistical package for the social sciences (SPSS 22 software). Results of the computed water quality indicates a latent variation in ground water quality of the study area. Although the index revealed an adequate ground water quality in the study area, a variation of 54.33% to 91.55% was observed. In addition, results of the principal component analysis (PCA) revealed that; chloride, manganese, total coliform count, total dissolved solids, sodium, iron and pH were the most important variables affecting the quality of the ground water within the study area. These parameters were selected as most critical based on the results of the vertical decentralization of the rotated component matrix in which chloride, manganese, total coliform count, total dissolved solids, sodium, iron and pH were observed to have the highest factor loading of 0.947, 0.861, 0.863, 0.854, 0.882, 0.920 and 0.928 respectively.
