Integrated Multi-Criteria Decision-Making Analysis for Sub-District Scale Landslide Susceptibility Zonation in the Garhwal Himalaya

The Garhwal Himalaya is highly prone to rainfall-induced landslides that disrupt connectivity, endanger lives, and weaken socioeconomic resilience of the region. Rapid urbanization and infrastructure expansion in this fragile terrain have further exacerbated slope instability. This study presents a subdistrict-level landslide susceptibility assessment for 58 subdistricts in the Garhwal region using a multi-criteria decision-making (MCDM) framework. Nine thematic layers used as Landslide Susceptibility Index (LSI) determinants, including slope, aspect, elevation, geology, land use/land cover, soil erosion susceptibility, monsoon rainfall, proximity to rivers, and proximity to roads, were derived using remote sensing datasets and GIS-based analyses. The Analytical Hierarchy Process (AHP) was applied to assign criteria weights. The slope, monsoon rainfall, and geology were identified as the most influential factors, followed by proximity to roads, land use/land cover, proximity to rivers, soil erosion susceptibility, elevation, and aspect. The composite LSI classified subdistricts into five categories: very low to very high. The assessment classified 55% of the subdistricts, particularly in Chamoli, Rudraprayag, and Uttarkashi, as high to very-high susceptibility zones. Validation against 3,484 historical landslide points yielded an Area Under the Curve (AUC) of 0.768, indicating fair predictive performance of the susceptibility model. These findings provide a critical spatial framework for district-level authorities to prioritize disaster mitigation resources and enforce land-use regulations, contributing to the overall climate resilience of the region.