Evaluation of Toxic Heavy Metal Concentration in Aquifer System for Groundwater System Development Using Multivariate Statistical Techniques

Abstract

Groundwater is a vital resource for human consumption. The study aimed to evaluate toxic metal concentrations in groundwater systems and determine pollutant sources using multivariate methods including cluster analysis (CA), principal factor analysis (PCA), and Pearson correlation coefficient (r). The results were compared with World Health Organization (WHO 2017) and Bureau of Indian Standard (BIS 2012) standards, indicating that Al concentration observed within prescribed values and other Cd, As, Zn, Pb, and Cu were less than the acceptable values, as well as the rest of Fe, Mn, and Ni levels in groundwater were mostly within acceptable values. The PCA results showed three factors (F1, F2, and F3) were responsible for the data structure, which was specified as 37.954%, 23.331%, and 16.132%, as well as total variance of dataset associated with 77.416%, respectively. Factor 1 showed strong positive loading (Cu, Pb, Zn), 2 (Al, Mn), and 3 (As, Ni), which demonstrated the contaminants source from natural and agricultural activities. Moreover, CA results revealed three clusters indicating low to high water pollution due to rock weathering and anthropogenic activities. Overall, results showed that 50% of groundwater samples were acceptable for potable and agricultural uses. Therefore, groundwater treatment is necessary before any use.