Spatial patterns and health risks of heavy metals in groundwater along an urban–periurban gradient in Kamrup, Assam, India

Background This study investigated the spatial distribution, ecological risks and human health risks of heavy metals in groundwater across the highly built-up urban zone to the less dense surrounding landscapes (urban–periurban interface) of Kamrup district, Assam, India, one of the fastest growing regions in northeast India. Methodology Groundwater samples were collected from 123 sites and groundwater quality was evaluated using heavy metal evaluation index (HEI), degree of contamination (CD), water pollution index (WPI), and heavy metal toxicity load (HMTL). Health risks associated with drinking groundwater was assessed in terms of non-carcinogenic and carcinogenic risks. The Inverse Distance Weighting (IDW) technique was employed to assess the spatial patterns of metal concentrations and health risks in adults and children. Results Fe surpassed WHO and BIS standards in ∼90% of the studied samples. Spatial mapping highlighted distinct enrichment of Cd, Pb and Zn within the urban boundary, while Fe and Ni exhibited wider dispersion. Correlation and pollution indices analysis (HEI, CD, WPI, HMTL) confirmed localized hotspots influenced by both geogenic and anthropogenic sources including use of agrochemicals. Except for Cd in urban zone, the mean hazard quotients (HQ) for other metals were within safe limits (< 1) for adults and children. However, mean HI showed higher values in peri-urban zone as compared to urban zone. Carcinogenic health risks (CR) were primarily due to Cd and Ni for both adults and children with CR > 1 × 10⁻⁶ to 1 × 10⁻⁴. Conclusion Peri-urban zone showed higher contamination and overall groundwater chemistry in the urban–peri-urban region is dominated by Fe, while metals including Cd, Ni, and Pb showed localized enrichment with few sites requiring immediate attention. Integrated urban–peri-urban groundwater quality study using different approaches not only captures spatial heterogeneity, cumulative contamination severity, and differential health risks but can also help in decision making process for effective groundwater management in a growing urban landscape.