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Risk assessment using quantitative approach: Central Himalaya, Kullu, Himachal Pradesh, India

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Abstract

Himalayan region has actively shown major landslide events in the last two decades. Therefore, risk assessment has been carried out in the study area to assess the risk to anthropogenic activities. The practice of risk assessment is important for rationalizing decision making in the process of development. The growing population, development of infrastructure, and unscientific mining activity in the study area are major factors responsible for majority of landslide incidences. An inventory has been developed for 142 landslides through interpretation of Google Earth image and satellite images [LISS-IV and Carto-sat], frequent field visits and past records of slope failures from various agencies. Thematic layers of all important factors [i.e., relative relief, slope, aspect, geology, soil, land use/land cover, landslide density, and drainage density] were prepared to study the factors responsible for mass movement along the slopes. These thematic layers were produced at a scale of 1:20,000 by using different sources of data in the GIS environment. Hazard zonation of the study area was carried out by using frequency ratio method, and risk assessment was done by using fuzzy logic method. Assessment of landslide vulnerability [probability of damage] was worked out from land use map. Both hazard and land use maps were reclassified and tabulated with the landslide inventory to identify the vulnerability of land use and risk. Based upon various factors, hazard zonation map of the study area is divided into five zones [very high, high, moderate, low, and very low hazard zones], whereas risk assessment is mainly divided into three zones[high-risk zone comprises 1.2% area, while 1.57% area under moderate risk zone and 97.21% area under low-risk zone].

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Correspondence to Rajeshwar Singh Banshtu.

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Banshtu, R.S., Versain, L.D. & Pandey, D.D. Risk assessment using quantitative approach: Central Himalaya, Kullu, Himachal Pradesh, India. Arab J Geosci 13, 219 (2020). https://doi.org/10.1007/s12517-020-5143-0

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