Garhwal Himalayas is one of the landslide-prone regions of India, which is characterized by frequent landslide occurrences causing damage to property, natural resources, and lives. In this study, the historical landslide records were associated with natural factors (climate, physiography, soil, geology, and vegetation factors) and anthropogenic factors (population density, livestock population, distance from settlements, and distance from road) using the random forest model. On the basis of variable importance value, it was found that the distance to road, vegetation (NDVI mean), slope, distance to water, and distance to the settlement were the most important factors in the model development. It indicated that developmental activities were one of the major factors responsible for landslides in the region. The results showed that 4655.94 km2 was susceptible to landslide hazards, out of which 38.29% area was under high and very high susceptibility class. The results validation using AUC (0.97), kappa coefficient (0.8), and TSS (0.84) showed that the model performance was excellent in predicting the landslides. The results provide information about the sensitive areas which are prone to landslides in the region. The study highlights the significance of scientific development and plantation of deep-rooted trees and grasses in landslide-prone areas.
Soil erosion is one of the most implicit hazards as it degrades quality of water as well as soil in watershed. Lesser Himalayan region is highly susceptible to natural hazards particularly which are instigated by action and movement of water such as soil erosion, flood and mass movements. Hilly watersheds with diversified land uses and fragile ecosystem are responsible for accelerating soil erosion. Satellite based remote sensing data has been used in this study to demonstrate its utilisation in analysing soil erosion susceptible areas in Tons river watershed (India). In this study an attempt is made to understand interrelationship and role of morphometry, hypsometry and land cover together as coupled criteria in soil erosion. Remote sensing data and Multi-Criteria Analytical (MCA) framework has been used to estimate soil erosion susceptibility of sub watersheds of Tons river basin. The watershed was delineated using ArcGIS to generate the natural drainage network and stream orders were defined using Strahler’s method in hydrology tool. Land cover was classified using Forest Survey of India (FSI) forest cover map and ASTER Digital Elevation Model (30m) for calculating morphometric parameters and hypsometric integral for further analysing geological stage with the help of ArcGIS 10.3. Soil erosion susceptibility maps were generated for sub watersheds for each criterion and also for coupled criteria. Outcomes indicated that sub watershed with more vegetation cover and mature geological stage is least prone to erosion. It can be inferred from results that morphometry, land cover and hypsometry all together as coupled criteria can be better indicator for assessing soil susceptibility rather than any single criteria. Also, the study suggested that remote sensing can be one of the most competent tools with lots of scopes to study watershed management and can help efficiently in decision making for formulation of conservation strategies, it is implementation and monitoring.
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