A modified indexing approach for assessment of heavy metal contamination in Deepor Beel, India

Abstract

Abstract In the present study, spatial and temporal variability of the heavy metals were investigated for Deepor Beel, India and a modified indexing approach for heavy metal contamination was proposed based on the statistical analyses of the monitored values. Water samples from 23 monitoring stations were collected for a period of one year and subjected to analysis for 7 different heavy metals (Mg, Cr, Cd, Fe, Mn, Cu, and Pb). The observed water quality dataset was first subjected to hierarchical clustering (HCA), which categorized the 23 monitoring locations into 3 statistically independent clusters based on the site similarities i.e. Low pollution (LP), High pollution (HP) and Moderate pollution (MP) respectively. Principal component analysis (PCA) technique was then applied to the three independent clusters to obtain principal components (PCs). These PCs were employed for calculating the weights of each component, from which the proposed heavy metal index (HMI) was estimated. The overall HMI value for Deepor Beel was found to be 123.52, which classified the water in Deepor Beel as “Poor”. Leaching from the contaminated landfill in the proximity to the wetland was found to be a primary source of contamination with respect to heavy metals. The efficacy of HMI was verified by comparing it with the existing heavy metal pollution index (HPI), contamination index (CI) and heavy metal evaluation index (HEI). Results of this study indicate HMI to be a more effective and reliable tool for water quality assessment with respect to heavy metal contamination.