Landfill contamination and slope instability mapping through multi-source data fusion: advancing multi-hazard detection via 3D modeling, geophysical investigations, and open GIS data

Landfill environments present complex challenges due to subsurface contamination and slope instability, often exacerbated by human-induced changes. Traditional single-method investigations fall short in capturing the multifaceted nature of these systems. This study aims to present an integrated approach combining geophysical surveys, 2D/3D geological modeling, and open-source GIS datasets to enhance landfill characterization and potentially multi-hazard assessment. The case study focuses on a small landfill in Central Italy, located in a narrow valley whose morphology has been altered by backfilling. 83 continuous core boreholes (2.0–20.5 m) supported the construction of high-resolution 3D geological models and 2D cross-sections. Four electrical resistivity tomography (ERT) profiles were performed to probe depths of 25–35 m, while electromagnetic induction (EMI) surveys—acquired at 1–1.5 m spacing—were completed to map shallow conductivity variations. Additionally, historical and contemporary GIS layers were integrated to provide spatial and temporal context, particularly regarding drainage networks and landform modifications. ERT sections revealed very low-resistivity zones (<10 Ω⋅m) consistent with possible leachate presence and potential slip surfaces. EMI surveys identified high-conductivity anomalies (>150 mS/m) spatially overlapping with ERT findings, reinforcing the interpretation of shallow contamination. The stratigraphic and geophysical data delineated structural discontinuities, waste body extent, and pollutant pathways. The spatial convergence of geophysical anomalies with anthropogenic surface alterations and geomorphological indicators highlights co-occurring contamination and slope instability hazards. This integrated approach offers a replicable framework for dynamic landfill monitoring, enhancing the detection of hydrogeological anomalies and supporting more effective strategies for pollution mitigation and risk management.