Identification of Critical Water Quality Parameters Derived from Principal Component Analysis: Case Study from NOIDA Area in India

Factor analysis is applied to 18 hydrochemical variables of groundwater quality for 33 groundwater samples to interpret the relationships with specific processes that control the quality of groundwater in Noida area which is a part of the National Capital Region (NCR) of Delhi in the river basin of Yamuna. The three factor model for this area explains 79.30% of total variance. Factor 1, which explains 47.25% of the total variance, has strong positive loadings on Mg 2+ , Cl - , SO 4 2- , TH, EC, TDS, Na + .Factor 2 explains 16.75 % of the total variance with moderate positive loadings on K + , HCO 3 , CIA, and Ca 2+ . Factor 3 explains 15.30 % of the total variance with strong positive loadings on Na % and SAR. Factor 1, 2 and 3 can be interpreted as salinity, alkalinity and pollution respectively.The geographical distribution of the factor scores at individual bore wells delineated boundaries, which define where groundwater is affected by salinization, alkalinity and pollution. In this study multivariate analysis reveals that the over-pumping and pollution caused differences in terms of water quality and hence for proper management of groundwater requires rainwater harvesting and water softening techniques to reduce the salinity.Thus, this study shows the effectiveness of multivariate statistical technique factor analysis for analysis and interpretation in the groundwater quality problem.