Geo-Environmental Risks and Community-Based Disaster Management in Chamoli, Tehri, Pauri, and Rudraprayag Districts of Uttarakhand

Abstract

The central Himalaya is one of the most hazard-prone regions globally, with Uttarakhand frequently experiencing floods, landslides, earthquakes and glacier-related disasters. Districts such as Chamoli, Tehri, Pauri and Rudraprayag represent high-risk zones due to fragile geomorphology, dense river networks and socio-economic dependencies on hydropower, agriculture and pilgrimage-based tourism. Despite the frequency of disasters, existing research has often been generalized, with limited district-level risk mapping and resilience assessments. This study adopts a secondary data–based approach integrating multi-source datasets. Satellite imagery from Landsat, Sentinel-2, and SRTM was analyzed using GIS techniques to derive slope, elevation, land use, and hydrological features. Hazard zonation was carried out through the Landslide Susceptibility Index (LSI), Flood Hazard Index (FHI) and Seismic Hazard Zonation (SHZ), drawing on Geological Survey of India (GSI), Bureau of Indian Standards (BIS) and NDMA/SDMA datasets. Socio-economic indicators including population density, literacy, and livelihood patterns were extracted from Census 2011 and published vulnerability studies. The integrated analysis reveals that Chamoli and Rudraprayag exhibit very high susceptibility to landslides, floods and glacial hazards, while Tehri demonstrates compound risks from seismic activity and dam-induced vulnerabilities. Pauri shows chronic landslide risks and high out-migration, reflecting both environmental and demographic pressures. A Vulnerability–Resilience Matrix was constructed by combining physical hazards with socio-economic indicators, enabling classification of the four districts into distinct risk categories. The findings highlight the urgent need for district-specific, community-sensitive disaster management strategies in the central Himalaya. By leveraging secondary geospatial and institutional datasets, this study provides a replicable framework for integrating physical hazard mapping with socio-economic vulnerability assessment, supporting evidence-based policy for resilience in Uttarakhand’s disaster-prone districts.