Spatiotemporal Fingerprinting of Groundwater Contamination Sources in a Landfill Catchment: A Two-Year Multivariate Assessment

Abstract

A two-year (2022–2024) monitoring study investigated spatiotemporal water quality variations across groundwater, surface water, pond water, and leachate at the Doddabidarakallu landfill catchment, Bengaluru, India. A total of 170 samples—130 groundwater, 24 surface water, 8 pond, and 8 leachate—were collected over four seasonal periods (Postmonsoon 2022 [PM2022], Premonsoon 2023 [PRE2023], Postmonsoon 2023 [PM2023], Premonsoon 2024 [PRE2024]) and analyzed for 23 physicochemical parameters. Groundwater was stratified by distance from the landfill (<500 m, 500–1000 m, >1000 m) and aquifer depth (<30 m, 30–80 m, >80 m). Principal Component Analysis (PCA) explained 70–81% of total variance through three components representing mineralization, carbonate weathering, and redox dynamics. Hierarchical Cluster Analysis (HCA) using Ward's linkage identified four hydrochemical clusters per season, characterized by Stiff diagram fingerprints ranging from Ca–Mg–HCO₃ background water to critical contamination hotspots. Paradoxically, far-field groundwater (>1000 m) exhibited higher electrical conductivity (1613–1947 μS cm⁻¹) and nitrate (4.52–18.45 mg L⁻¹) than near-field wells (<500 m) across all seasons, attributable to contaminated ponds, upstream sewage treatment plant (STP) discharge, and industrial inputs—not the landfill. The near-field zone carried a distinct leachate signature of elevated Fe (1.07 mg L⁻¹), Cu (0.64 mg L⁻¹), and Zn (2.78 mg L⁻¹) that attenuated within 1 km. Leachate chemical oxygen demand declined 74% (96,800 to 25,600 mg L⁻¹) from PM2022 to PRE2024, indicating landfill maturation. These findings provide a mechanistic basis for targeted groundwater management in urban landfill catchments.