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• W2912053034 abstract "Multivariate statistical techniques have emerged as one of the most effective tools in hydrochemical characterization and the identification of pollution sources in groundwater. Hydrogeochemical data of the 36 wells in the Lower Bhavani River basin in Tamil Nadu are used in this study. Hierarchical cluster analysis(HCA) derived three major clusters, in which cluster 1 has high concentration of Ions (n = 14; avg TDS = 1259 mg/L), followed by cluster 2 (n = 13; avg TDS = 775 mg/L) and cluster 3 (n = 8; avg TDS = 357mg/L). The hydrochemical facies also agree with the cluster hydrochemistry with Na-Cl type (cluster 1), Ca-Mg-Cl (cluster 2), and Ca-HCO3 (cluster 3) showing the influences of anthropogenic and the natural (rock–water interaction related) geochemical patterns. Aqueous Speciation Modeling suggests that the undersaturated Halite (Na-Cl), Gypsum, and Anhydrate minerals in all three clusters, Indicating the possibility for the dissolution of Na, Ca, SO4, and Cl. As in HCA, Principle Component Analysis (PCA) also delivered three major components showing the impact of textile industries and agricultural fertilizers, leakage of sewages and the natural interaction of water with fluorite rich minerals. It is observed that both natural and anthropogenic processes are controlling the variations in the hydrochemical parameters and correlated with land use patterns." @default.
• W2912053034 created "2019-02-21" @default.
• W2912053034 creator A5064271814 @default.
• W2912053034 date "2019-02-12" @default.
• W2912053034 modified "2023-10-13" @default.
• W2912053034 title "Hydrogeochemical and multivariate statistical appraisal of pollution sources in the groundwater of the lower Bhavani River basin in Tamil Nadu" @default.
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• W2912053034 doi "https://doi.org/10.1080/24749508.2019.1574156" @default.
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