MATEC Web Conf.
Volume 281, 2019International Conference of Engineering Risk (INCER 2019)
|Number of page(s)||8|
|Section||Naturals: Earthquake, Landslide, Forest Fire, Flood, Tsunami, Avalanche|
|Published online||21 May 2019|
Landslide susceptibility mapping based on triggering factors using a multi-modal approach
1 Graduate Student, Civil Engineering Department, Lebanese American University, Lebanon
2 Associate Professor, Civil Engineering Department, Lebanese American University, Lebanon
3 Professor, Civil and Environmental Engineering Department, University of Washington, U.S.A.
4 Doctoral Student, School of Civil, Mining & Environmental Engineering, University of Wollongong, Australia
* Corresponding author: email@example.com
Landslide susceptibility mapping has been done using statistical and physically-based assessment techniques with limited focus on mode-specific models to identify failure modes and runout patterns. Because each failure mode has different consequences, it is essential to identify the failure mode associated with each slope inclination category, triggering factor, and geological setting. This paper presents a multimodal regionalscale assessment procedure for rainfall and earthquake-induced landslides, in the country of Lebanon, where landslide inventories are not available. Three failure modes are studied: debris flows, rock-slope failures, and coherent rotational slides. Areas prone to each mode of failure are identified based on geology and topography, then, using mode-specific models, their susceptibility to landslides is assessed. A runout assessment approach is then presented to identify the influence area of each predicted landslide and to obtain comprehensive susceptibility maps. Field assessment validated the proposed model which was in good agreement with actual slope failures across Lebanon. Therefore, the multimodal approach may be used to assess rainfall-induced landslide susceptibility, especially when landslide inventories are unavailable.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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