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Probabilistic approach toward Darjeeling Himalayas landslides-A case study
- Source :
- Cogent Engineering, Vol 5, Iss 1 (2018)
- Publication Year :
- 2018
- Publisher :
- Taylor & Francis Group, 2018.
-
Abstract
- The Himalayan region with its complex geological features, steep slopes, rugged topography, and intense monsoonal rainfall create ideal conditions for landslides. The damage caused due to landslides is immense causing significant loss of life and property initiating a dire need to formulate strategies in minimizing its impact in areas affected by landslides. Several attempts have been presented by various researchers in order to establish rainfall intensity thresholds using various parameters of rainfall conditions. These methods provide deterministic thresholds, i.e., landslide or no landslide; such thresholds are not always suited for landslides. In this paper, rainfall thresholds have been evaluated using a statistical method which results in the probability of landslide occurrence for single or multiple rainfall parameters leading to slide initiation. The results are expressed in terms of probabilities by analyzing two different variants of Bayes theorem, i.e., 1D and 2D. Probabilistic thresholds were calculated for Kalimpong region of Darjeeling Himalayas using available rainfall and landslide data during the year 2010–2016. The probabilities calculated for landslide occurrence were found to be 0.37 for rainfall intensity greater than 10 mm/day. However, the probability for a combination of rainfall intensity of 30 mm/day with duration of 3 days was calculated to be 0.67. The results also depicted that landslides are related to rainfall event parameters especially with rainfall intensity.
Details
- Language :
- English
- ISSN :
- 23311916
- Volume :
- 5
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Cogent Engineering
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.bab35488cf1a4c149d181e2efbdbaff2
- Document Type :
- article
- Full Text :
- https://doi.org/10.1080/23311916.2018.1537539