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DOI10.1007/s11069-020-04004-w
Improved rainfall threshold for landslides in data sparse and diverse geomorphic milieu: a cluster analysis based approach
Sajinkumar K.S.; Rinu S.; Oommen T.; Vishnu C.L.; Praveen K.R.; Rani V.R.; Muraleedharan C.
发表日期2020
ISSN0921030X
起始页码639
结束页码657
卷号103期号:1
英文摘要Rainfall-triggered landslides are the most common type of mass movement seen along the tropical belt due to the prevalence of monsoons. These landslides can be forecasted by understanding the spatial and temporal rainfall distribution patterns, and subsequent generation of rainfall threshold (RT). However, deriving a regional RT in a geologically, geographically and physiographically diverse milieu is a formidable task. The data on spatial and intra-seasonal variability of monsoons can be widely dispersed in such diversified terrains. Clustering analysis provides a promising approach to handle such widely dispersed data. This study intends to develop a methodology using 2-stage clustering process to create RT in such terrains by using daily rainfall versus antecedent rainfall and rainfall versus antecedent rainfall versus soil depth. Sixteen rainfall-induced landslides, located in different terrains in the Western Ghats of India, were subjected to this analysis. Majority of the landslides were modeled, and different RTs were derived for different conditions. The landslides belong to four different classes, viz., landslides occurring at steep slopes; those occurring at knickpoints of highland and midland; in the plateau region and others characterized by a thin veneer of soil. Out of 16 landslides subjected to RT, this method was able to model 13 landslides with a success rate of 81.25%, which is a fair figure. © 2020, Springer Nature B.V.
关键词Cluster analysisLandslide characterizationRainfall threshold analysisTropical landslidesWestern Ghats
英文关键词cluster analysis; geomorphology; hazard assessment; landslide; monsoon; rainfall; spatiotemporal analysis; terrain; India; Western Ghats
语种英语
来源期刊Natural Hazards
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/205915
作者单位Department of Geology, University of Kerala, Thiruvananthapuram, Kerala 695 581, India; Department of Geological and Mining Engineering and Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, United States; Department of Civil Engineering and Environment, University of Texas at Arlington, 701 S Nedderman Drive, Arlington, TX 76019, United States; Geological Survey of India, Thiruvananthapuram, Kerala 695 013, India; Central Ground Water Board, Thiruvananthapuram, Kerala 695 004, India
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GB/T 7714
Sajinkumar K.S.,Rinu S.,Oommen T.,et al. Improved rainfall threshold for landslides in data sparse and diverse geomorphic milieu: a cluster analysis based approach[J],2020,103(1).
APA Sajinkumar K.S..,Rinu S..,Oommen T..,Vishnu C.L..,Praveen K.R..,...&Muraleedharan C..(2020).Improved rainfall threshold for landslides in data sparse and diverse geomorphic milieu: a cluster analysis based approach.Natural Hazards,103(1).
MLA Sajinkumar K.S.,et al."Improved rainfall threshold for landslides in data sparse and diverse geomorphic milieu: a cluster analysis based approach".Natural Hazards 103.1(2020).
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