Determination of processes affecting groundwater quality in the coastal aquifer beneath Puri city, India: a multivariate statistical approach

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Variability of groundwater quality parameters is linked to various processes such as weathering, organic matter degradation, aerobic respiration, iron reduction, mineral dissolution and precipitation, cation exchange and mixing of salt water with fresh water. Multivariate statistical analyses such as principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied to the standardized data set of eleven groundwater quality parameters (i.e. pH, Ca2+, Mg2+, Na+, K+, Fe3+, alkalinity, NO3−, Cl−, SO42−, TDS) collected during the post-monsoon and the summer seasons in order to elicit hydrologic and biogeochemical processes affecting water quality in the unconfined aquifer beneath Puri city in eastern India. The application of PCA resulted in four factors explaining 73% variance in post-monsoon and 81% variance in summer. The HCA using Ward's method and squared Euclidean distance measure classified the parameters into four clusters based on their similarities. PCA and HCA allowed interpretation of processes. During both post-monsoon and summer seasons, anthropogenic pollution and organic matter degradation/Fe(III) reduction were found dominant due to contribution from on-site sanitation in septic tanks and soak pits in the city. Cation exchange and mineral precipitation were possible causes for increase in Na+ and decrease in Ca2+ concentration in summer. Fresh water recharge during monsoon and Sea water intrusion in summer are attributed as significant hydrologic processes to variations of the groundwater quality at the study site.

Keywords: coastal aquifer, hierarchical cluster analysis, multivariate statistical analysis, principal component analysis, Puri city

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