Rainfall variability has intensified under climate change, with major consequences for fragile mountain regions. The Himalayan district of Udhampur, Jammu and Kashmir, is particularly vulnerable due to its heterogeneous soils, steep terrain, and frequent landslides triggered by rainfall. This study integrates rainfall, soil susceptibility, and landslide data using Geographic Information Systems (GIS) to provide a decadal-scale (2014–2024) assessment of hydro-geomorphic risks. Rainfall data from the Centre for Hydrometeorology and Remote Sensing (CHRS, University of California, Irvine) were spatially interpolated using the Inverse Distance Weighting (IDW) technique to generate annual and decadal rainfall surfaces. Soil data, extracted from the FAO–UNESCO Soil Map of the World and reclassified into susceptibility categories, were assessed for their role in erosion and slope instability. Landslide data, derived from NASA’s global inventory and analyzed through kernel density estimation, were integrated with rainfall and soil layers to identify multi-hazard zones. Overlay analysis revealed that areas dominated by Lithosols, coupled with high rainfall variability and a high frequency of landslide occurrences, represent the most vulnerable regions of Udhampur. The results highlight that hazard susceptibility is not uniform but strongly shaped by the interaction between rainfall intensity, soil characteristics, and topography.
