Village Level Landslide Probability Analysis Based on Weighted Sum Method of Multi-Criteria Decision-Making Process of Darjeeling Himalaya, West Bengal, India

Abstract

AbstractThe Himalayan mountains are highly prone to landslides, and every year a multitude of slide events take place along its entire ranges. Darjeeling Himalayan region of West Bengal is not an exception and also highly prone to landslides. In the Darjeeling Himalayan extents, landslides are the major threat to the lives and properties of the people and also hamper the connectivity and commerce of the region aggravating lopsided development and poor economic condition. Considering the magnitude of landslide frequency and its extremities, this study aims to develop a landslide probability index (LPI) for the projection of landslide probabilities at the village level. The proposed methodology of the LPI is based on the weighted sum method of multi-criteria decision-making processes that involve eight explicitly localised proxy/indicator quantitative analysis, normalisation and weight assignment. The result of the derived LPI is divided into 4 distinct classes, viz. (a) very high landslide probability class comprising 45 villages, (b) high landslide probability class consists of 138 villages, (c) moderate landslide probability class includes 109 villages and (d) 56 villages are in low landslide probability class. It is evident from the study that the nature of landslide phenomenon is resulting from the interaction of contributing physical indicators, i.e. fragile lithology shares 34.58% in the radar diagram as the prime contributor of landslides in the DHR followed by drainage density at 17.91% and high degree of slope at 14.77%, and identification of such drivers of landslide probability can also be used in developing targeted adaptation planning and interventions.KeywordsDarjeeling Himalayan regionLandslide probability indexMulti-criteria decision-makingVillage levelAdaptation planning