Multimodal method for landslide risk analysis.

Coseismic Hazard Mass-wasting Modes of failure Multimodal Method for Landslide Risk Analysis Precipitation

Journal

MethodsX
ISSN: 2215-0161
Titre abrégé: MethodsX
Pays: Netherlands
ID NLM: 101639829

Informations de publication

Date de publication:
2019
Historique:
received: 12 12 2018
accepted: 11 04 2019
entrez: 4 5 2019
pubmed: 3 5 2019
medline: 3 5 2019
Statut: epublish

Résumé

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.

Identifiants

pubmed: 31049299
doi: 10.1016/j.mex.2019.04.012
pii: S2215-0161(19)30100-1
pmc: PMC6484206
doi:

Types de publication

Journal Article

Langues

eng

Pagination

827-836

Références

Proc Natl Acad Sci U S A. 2017 Feb 28;114(9):2189-2194
pubmed: 28202728

Auteurs

William Pollock (W)

Dept. of Civil and Environmental Engineering, University of Washington, 201 More Hall, Seattle, WA 98195, United States.

Alex Grant (A)

Dept. of Civil and Environmental Engineering, University of Washington, 201 More Hall, Seattle, WA 98195, United States.

Joseph Wartman (J)

Dept. of Civil and Environmental Engineering, University of Washington, 201 More Hall, Seattle, WA 98195, United States.

Grace Abou-Jaoude (G)

Dept. of Civil Engineering, Lebanese American University, 304 Bassil Bldg., Byblos, Lebanon.

Classifications MeSH