Heavy Metal Contamination in Urban Water Systems near Landfills: Insights from WQI, GIS and Data-Driven Modeling

Urban landfill activities can significantly alter the quality of nearby water systems through the release of metal-enriched leachate, raising concerns for environmental sustainability and public health in rapidly urbanizing regions. This study assesses heavy metal contamination in urban water systems located near landfill sites using an integrated approach combining Water Quality Index (WQI), GIS-based spatial analysis, and data-driven modeling. Groundwater samples were analyzed for key physicochemical parameters and selected heavy metals, including iron (Fe), manganese (Mn), and lead (Pb). Water quality conditions were evaluated using WQI, while spatial mapping was applied to identify contamination patterns and high-risk zones associated with landfill proximity. Data-driven models were employed as exploratory tools to examine inter-parameter relationships under data-limited conditions. The results indicate substantial spatial variability in water quality, with degraded WQI values and elevated heavy metal concentrations observed predominantly near landfill areas. Lead contamination emerged as the most critical concern, frequently exceeding drinking water guideline values and indicating potential public health risk. Although predictive performance of data-driven models was constrained by limited sample size, feature importance analysis provided meaningful insight into key physicochemical and anthropogenic factors influencing heavy metal distribution. Overall, the findings demonstrate that integrated risk-based assessment and spatial analysis offer reliable support for identifying contamination hotspots and informing water quality management in landfill-impacted urban environments.