Spatial control of groundwater contamination,using principal component analysis

A study on the geochemistry of groundwater was carried out in a river basin of Andhra Pradesh to probe into the spatial controlling processes of groundwater contamination, using principal component analysis (PCA). The PCA transforms the chemical variables, pH, EC, Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO \(_3^- \) , Cl^?, SO \(_4^{2-} \) , NO \(_3^-\) and F^?, into two orthogonal principal components (PC1 and PC2), accounting for 75% of the total variance of the data matrix. PC1 has high positive loadings of EC, Na⁺, Cl^?, SO \(_4^{2-} \) , Mg²⁺ and Ca²⁺, representing a salinity controlled process of geogenic (mineral dissolution, ion exchange, and evaporation), anthropogenic (agricultural activities and domestic wastewaters), and marine (marine clay) origin. The PC2 loadings are highly positive for HCO \(_3^- \) , F^?, pH and NO \(_3^- \) , attributing to the alkalinity and pollution controlled processes of geogenic and anthropogenic origins. The PC scores reflect the change of groundwater quality of geogenic origin from upstream to downstream area with an increase in concentration of chemical variables, which is due to anthropogenic and marine origins with varying topography, soil type, depth of water levels, and water usage. Thus, the groundwater quality shows a variation of chemical facies from Na⁺ > Ca²⁺ > Mg²⁺ > K⁺: HCO \(_3^- \) > Cl^? > SO \(_4^{2-}>\) NO \(_3^- \) > F^?at high topography to Na⁺ > Mg²⁺ > Ca²⁺ > K⁺: Cl^? > HCO \(_3^- \) > SO \(_4^{2-}>\) NO \(_3^- \) > F^? at low topography. With PCA, an effective tool for the spatial controlling processes of groundwater contamination, a subset of explored wells is indexed for continuous monitoring to optimize the expensive effort.