Application of multivariate statistical techniques in hydrogeochemical evolution of groundwater in a igneous rock and sedimentary aquifer system: a case study of the southern Bam, SE Iran

Abstract

This study presents the usefulness of multivariate statistical techniques, such as correlation matrix, cluster analysis, and factor analysis to evaluate their usefulness to classify the groundwater samples and to identify geochemical processes controlling groundwater geochemistry of the southern Bam, SE Iran. Hydrogeochemical analysis has been conducted on 24 spring locations to portray volcanic and sedimentary hydrogeological system. Based on the hydrochemistry, the groundwater was classified into five types: Ca–Mg–HCO3 (29.16 %), Ca–Mg–SO4–Cl (29.16 %), Na–Cl (20.83 %), Ca–SO4 (16.67 %) and Mg–Na–HCO3–Cl (4.18 %). Nearly 20.83 % of samples have arsenic concentrations above WHO permissible value (10 µg/L) for drinking waters with maximum concentration of aqueous arsenic up to 13.9 mg/L. Result showed that the chemical composition of ground water in district is controlled by the natural weathering processes. Among the chemical weathering processes, silicate weathering was dominant.