Abstract
This study evaluates the geospatial variability of heavy metal contamination in groundwater within an industrially influenced peri-urban area spanning parts of Guwahati, Assam, and Meghalaya, India. A total of 26 samples were analyzed for nine heavy metals, As, Cd, Cr, Cu, Mn, Ni, Pb, Zn, and Fe, using Atomic Absorption Spectroscopy (AAS) during both pre- and post-monsoon seasons. Index-Based Evaluation (IBE) was employed to assess cumulative contamination levels. Results revealed maximum concentrations of Pb (0.206 mg.L-1), Cd (0.011 mg.L-1), Ni (0.049 mg.L-1), and Mn (1.983 mg.L-1) in the groundwater samples. Metal Index (MI) values ≥ 6 at 21 (pre-monsoon) and 7 (post-monsoon) sites indicated serious contamination, while Heavy Metal Pollution Index (HPI) values > 100 at 22 and 20 sites, respectively, classified the water as unsuitable for drinking. Kernel Density Estimation (KDE) and box plots further supported the temporal patterns of contamination. Geospatial mapping of MI using the Inverse Distance Weighting (IDW) technique revealed that 78% (pre-monsoon) and 69% (post-monsoon) of the area were seriously or strongly affected, while HPI interpolation indicated 97% and 95% of the area under high-pollution zones, respectively. The findings underscore the strong anthropogenic impact of cement and brick industries on groundwater quality, emphasizing the need for continuous monitoring and effluent control. The adopted framework provides a transferable model for early detection, spatial prioritization, and remediation of heavy metal contamination in industrially stressed aquifers globally.