Groundwater quality assessment and mapping using multivariate statistics and analytic hierarchy process in Bhubaneswar city, Odisha, India

Abstract

Groundwater, the major drinking water source in an urban area, is vulnerable to deteriorate by its quality due to population pressure and developmental activities. Assessment of and understanding the groundwater chemistry is therefore imperative. Using multivariate statistics and analytic hierarchy process, the groundwater quality of Bhubaneswar, an ever-growing city in eastern India is assessed and elaborated in this paper. Samples collected from the city were found to be dominated by Na-Cl-HCO3, Na-Ca-Cl-HCO3, Na-Cl and mixed hydrochemical facies through Piper trilinear diagram. Silicate weathering had come up as a dominant process for influencing ionic constituents in bore well (> 20 m depth), while anthropogenic intervention was responsible for excess nitrate, K, sulphate and chloride contents in dug well (≤ 3-10 m depth) water. Samples were classified to four clusters using hierarchical cluster analyses and cluster-wise discriminating variables were identified through discriminant function. The discriminating variables (turbidity, Fe, Mn, NO3−, K and pH) which determine the drinkability of water were then ranked through analytic hierarchy process (AHP), A hierarchy was prepared and used to generate the vulnerability map distinguishing low to high quality groundwater endowed localities in the study area.