In India, the active areas with Landslides in the Himalayan region and the ongoing process of development in this area can be impeded by the associated risks and hazards posed by these events. The Garhwal Himalaya region, in particular, has a history of landslides, some of which are well-known and triggered by co-seismic events. While rainfall and earthquakes are commonly acknowledged as the primary factors that cause landslides, the destabilization of hill slopes due to anthropogenic activities, such as rapid urbanization, has emerged as a significant contributor to this phenomenon in the region (Kainthura & Sharma, 2022). Implementing effective planning and management strategies can significantly mitigate the social and economic losses caused by landslides. These strategies encompass various measures such as restricting advancements in landslide-prone regions, utilizing excavation, grading, landscaping, and construction codes, deploying physical strategies such as drainage, slope-geometry revision, and structures to prohibit or regulate landslides, and establishing warning systems to alert the local population of potential hazards( Dai et al., 2002; Islam and Chattoraj, 2023).

The current study focuses on landslide susceptibility mapping (LSM) in the Rudraprayag district, specifically around the Mandakini river valley. The methodology involves the application of the Analytical Hierarchy Process (AHP) integrated with twelve causative factors, including slope, lineament density, drainage density, land use land cover, lithology, Normalized Difference Vegetation Index (NDVI), geomorphology, curvature, topographic wetness index (TWI), Normalized Difference Water Index (NDWI), aspect, and stream power index (SPI). The AUC_ROC curve for the study area yields a satisfactory result of 78.9%. The outcomes indicate that 2.12% of the area is at very low risk, 27.12% is at low risk, 45.37% is at moderate risk, and 25.39% falls within the high to very high-risk zone.

Fig 1:  Landside hazard zonation map with slide locations and 2D spatial variation of factor of safety along a selected vulnerable slope

Model rock or soil slopes can be analysed for stability to identify the critical failure surfaces and spatial variation of factor of safety. In this case RS2 module (@rocscience has been employed. The numerical simulation assessment, conducted using the limit equilibrium method, determines the factor of safety (FoS) for seven vulnerable slopes situated in the very high-risk zone of LSM (Fig. 1). All seven slopes were found to be unstable, with the maximum FoS recorded as 0.67. In light of these findings, it is recommended to conduct strategic slope stability assessments in various vulnerable sections of the Himalayas and similar regions. This proactive approach is crucial for implementing effective and sustainable measures toward disaster mitigation.

References

Dai, F.C., Lee, C.F., Ngai, Y.Y. (2002). Landslide risk assessment and management: an overview. Engineering Geology, Volume 64 (1), 65-87,

Islam, M. A., and Chattoraj, S.L. (2023). Modelling landslides in the Lesser Himalaya region using geospatial and numerical simulation techniques, Abrabian journal of Geoscience, vol. 16 (7), pp.25 , 2023 .

Kainthura, P., Sharma, N., (2022). Hybrid machine learning approach for landslide prediction, Uttarakhand, India. Sci. Rep., 12 (1):20101.