GIS-BASED GROUNDWATER AND SOIL QUALITY ASSESSMENT OF HEAVY METAL CONTAMINATION: A CASE STUDY OF INDUSTRIAL AREA OF SAMBRIAL-SIALKOT, PAKISTAN

Abstract

Heavy metal pollution of soils and groundwater is an environmental issue worldwide, especially in those countries where environmental protection policies exist but are not implemented. A study was designed to assess heavy metal pollution in the industrial area of Sialkot. The specific objectives of the study were to generate (a) spatial distribution maps of heavy metals (Ni, Cr, Pb) of the Industrial area of Sambrial-Sialkot and (b) assess the groundwater and soil quality in terms of heavy metals and their vulnerability to pollution using quality Indices. A total of 50 groundwater and soil samples were collected through random sampling. Samples physico-chemical properties (pH, EC, TDS), turbidity, and organic matter were analyzed using standard procedures. Heavy metals (nickel, chromium, and lead) were analyzed using ICP (inductively coupled plasma) optical emission spectrometry. Spatial distribution maps of heavy metal and physicochemical properties of soils and groundwater were generated using the Inverse Distance Weighted technique (IDW). The heavy metals (nickel, chromium, and lead) were above the permissible limits of WHO in soil and groundwater samples. Nickle (-0.61) and chromium (-0.54) had a significant (p<0.05) negative correlation with pH in water samples. Nickle had a significant (p<0.05) positive correlation (0.74) with chromium. In comparison nickel and chromium also had a significant (p<0.05) negative correlation with pH and organic matter. Using various physical-chemical properties, multiple linear regression techniques were used to generate predictive models for heavy metals in soils and groundwater. The spatial distribution maps show high variability in soil and groundwater physicochemical properties and heavy metal concentrations. The results of this study will help the policymaker better implement the environmental policy in the Sialkot industrial area.