Statistical Appraisal of Major Ion Chemistry of Groundwater: A Case Study from a River-Bounded Rural Area

Abstract

Abstract The present study deals with the application of statistical methods like correlation, factor, cluster and multiple regression analyses to interpret the controlling processes influencing the hydrogeochemisty of a river-dominated area. The groundwater is alkaline and hard but suitable for drinking. Most of the parameters show significant positive correlations with each other. The first three factors explain 83.884% of the variance and can be used to assess the dominant hydrochemical processes in operation. The first factor with strong loadings on total dissolved solids (TDS), total hardness (TH), Ca2+, Mg2+, Na+, HCO3- and F- is the salinity factor. It is geogenic in nature and constituent ions are derived from weathering of basement rocks. The second factor with strong loadings on K+, NO3,- SO42-and Cl- is anthropogenic as the first three ions are present in fertilizers used by people to increase crop production and the fourth is derived from domestic wastes. The third factor strongly loaded on pH and total alkalinity (TA) is the alkalinity factor. The cluster analysis replicates the results of the factor analysis. The multiple regression analysis suggests that Ca2+, Mg2+, HCO3- and SO42- contribute significantly to the bulk chemical composition of the groundwater. The chemical constituents of the groundwater may be attributed to the effects of weathering, mineral dissolution, drainage wastes, septic tank leakage, irrigation-return-flows, chemical fertilizers and/or increase or decrease of chemical variables due to dissolution, precipitation, ion exchange, etc. The study illustrates the usefulness of statistical methods as an effective tool for interpretation of the controlling processes of groundwater chemistry.