Author(s): Armah Frederick Ato, Obiri Samuel, Yawson David Oscar, Pappoe Alex Nii Moi, Bismark Akoto
Application of multivariate statistics for the interpretation of surface and groundwater data from Tarkwa, a mining community in the Western region of Ghana, is presented in this study. E ffl uents from extractive industries established over the last half century within the study area are directly discharged onto surrounding land and surface water bodies constituting point and non-point sources of contamination for groundwater in the study area. In the Tarkwa mining area, large deposits of mine wastes, ore stockpiles and waste rocks have become a heap around the place. Twelve parameters including trace elements (Cu, Mn, Cd, Fe, Pb, As, Hg and Zn) and physico-chemical parameters (pH, conductivity, turbidity and total dissolved salts) were monitored on 49 sampling points including surface and groundwater. Data set was analysed using factor analysis (FA). FA identified four factors responsible for data structure explaining 69% of total variance in surface water and two factors in groundwater explaining 79%, and allowed the grouping of selected parameters according to common features. This study underscores the value of multivariate statistical analysis for evaluation and interpretation of the data with a view to stimulating better policy outcomes and decision-making that positively impacts water quality and thus prospectively diminishes the pollution caused by hazardous toxic elements in mining environments.