Multimodal method for landslide risk analysis

[Display omitted] Quantitative landslide risk analysis is a key step in creating appropriate land use policies. However, regional scale landslide hazard and risk studies are traditionally based on a single, infinite-slope style of failure, belying the differing consequences of a diverse range of fai...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:MethodsX Ročník 6; s. 827 - 836
Hlavní autori: Pollock, William, Grant, Alex, Wartman, Joseph, Abou-Jaoude, Grace
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Netherlands Elsevier B.V 01.01.2019
Elsevier
Predmet:
Coseismic
Engineering
Hazard
landslides
Lebanon
Mass-wasting
Modes of failure
Multimodal Method for Landslide Risk Analysis
Precipitation
risk
risk analysis
Lebanon
Coseismic
Modes of failure
Precipitation
Mass-wasting
Multimodal Method for Landslide Risk Analysis
Hazard
ISSN:2215-0161, 2215-0161
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:[Display omitted] Quantitative landslide risk analysis is a key step in creating appropriate land use policies. However, regional scale landslide hazard and risk studies are traditionally based on a single, infinite-slope style of failure, belying the differing consequences of a diverse range of failure modes. In this paper we expand an existing multimodal coseismic landslide hazard model to create a method for multimodal, multi-trigger quantitative landslide risk analysis and apply it to the country of Lebanon. •Physics-based, mode-specific models for coseismic and precipitation-induced landslides capture the effects of multiple failure types and triggering scenarios.•A new model for analyzing slope stability against rotational failures allows for efficient, regional scale assessments.•Open-source mapping of built-up area is used to identify elements at risk.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Present address: U.S. Geological Survey, 345 Middlefield Rd., Menlo Park, CA 94025, United States.
ISSN:2215-0161
2215-0161
DOI:10.1016/j.mex.2019.04.012