Investigating the dynamic nature of landslide susceptibility in the Indian Himalayan region

Environ Monit Assess. 2024 Feb 13;196(3):257. doi: 10.1007/s10661-024-12440-5.

Abstract

Landslide susceptibility zonation (LSZ) mapping is used to delineate areas prone to landslides and is critical for effective landslide hazard management. The existing methodologies for generating such maps tend to neglect the influence of dynamic environmental variables on landslide occurrences, which may lead to obsolete and erroneous estimates of landslide susceptibility (LS) for a concerned area. Although recent studies have started to report the effects of Land Use/ Land Cover (LULC) variation on LSZ mapping, variations in other dynamic variables like rainfall, soil moisture, and evapotranspiration apart from LULC may also influence slope stability in mountainous regions. The present study investigates the impact of variations in these four variables on the LS distribution, of a selected Indian Himalayan region between 2017 and 2021. Random Forest (RF) susceptibility models are utilized for evaluating the LS for the selected years and geospatial technologies are employed for LS change detection. The results indicate up to 19% variations in the spatial extent for some of the zones of the generated LSZ maps. The research findings of this study are crucial since they reveal the impact of dynamic behavior on LS, which has not been previously documented in the literature.

Keywords: Dynamic environmental variables; Geographical Information System (GIS); Indian Himalayas; Landslide susceptibility analysis; Random Forest algorithm.

MeSH terms

  • Environmental Monitoring
  • Landslides*
  • Safety Management
  • Soil

Substances

  • Soil