摘要：Principal component analysis (PCA) is an appropriate tool for water quality evaluation and management. Inthe study area, PCA was used for multivariate factor analysis of hydrogeochemical variables of pH, EC,Ca 2+ , Mg 2+ , Na + , K + , HCO 3 - , SO 4 2- , Cl - , NO 3 - , F - , TH and TDS. Influence on chemical composition ofgroundwater quality and statistically characterize (Eigen value ≥ 1 and % of variance) two factors wereextracted as well as identified, principal component-I and II. The principal component-I accounts for 36.62and 39.80% of variance and principal component-II accounts for 17.84 and 18.10% of variance in pre andpost-monsoon seasons respectively. Graphical presentation of the principal component-I and II showedloading relationship between the variables EC, TDS and Ca 2+ as high positive relation; and variables betweenTH, Mg 2+ , NO 3 - and F - as low positive relation in pre-monsoon season. Principal component-I and II showedloading relationship variables between pH, as high positive relation; and variables between HCO 3 - and SO 4 2-as high positive relation in post monsoon seasons respectively. These two principal components results werepredicted for hydrochemical process of rock water interaction, process of degradation products of the ions,process of alkalinity and process of anthropogenesis activity. It was concluded that hydrochemical processis controlled by geogenic and non-geogenic factors.
