DOI: 10.1007/s11069-020-04004-w
论文题名: Improved rainfall threshold for landslides in data sparse and diverse geomorphic milieu: a cluster analysis based approach
作者: Sajinkumar K.S. ; Rinu S. ; Oommen T. ; Vishnu C.L. ; Praveen K.R. ; Rani V.R. ; Muraleedharan C.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期: 1 起始页码: 639
结束页码: 657
语种: 英语
中文关键词: Cluster analysis
; Landslide characterization
; Rainfall threshold analysis
; Tropical landslides
; Western Ghats
英文关键词: cluster analysis
; geomorphology
; hazard assessment
; landslide
; monsoon
; rainfall
; spatiotemporal analysis
; terrain
; India
; Western Ghats
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. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168714
Appears in Collections: 气候变化与战略
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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
Recommended Citation:
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]. Natural Hazards,2020-01-01,103(1)