Publication details for Dr Tom RobinsonKritikos, T., Robinson, T.R. & Davies, T.R.H. Regional coseismic landslide hazard assessment without historical landslide inventories: a new approach. Journal of Geophysical Research: Earth Surface. 2015;120:711-729.
- Publication type: Journal Article
- ISSN/ISBN: 2169-9011 (online)
- DOI: 10.1002/2014JF003224
- Keywords: Coseismic landslides, Fuzzy logic, Hazard, GIS, Ground shaking intensity, Topography.
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
Currently, regional coseismic landslide hazard analyses require comprehensive historical landslide inventories as well as detailed geotechnical data. Consequently, such analyses have not been possible where these data are not available. A new approach is proposed herein to assess coseismic landslide hazard at regional scale for specific earthquake scenarios in areas without historical landslide inventories. The proposed model employs fuzzy logic and geographic information systems to establish relationships between causative factors and coseismic slope failures in regions with well-documented and substantially complete coseismic landslide inventories. These relationships are then utilized to estimate the relative probability of landslide occurrence in regions with neither historical landslide inventories nor detailed geotechnical data. Statistical analyses of inventories from the 1994 Northridge and 2008 Wenchuan earthquakes reveal that shaking intensity, topography, and distance from active faults and streams are the main controls on the spatial distribution of coseismic landslides. Average fuzzy memberships for each factor are developed and aggregated to model the relative coseismic landslide hazard for both earthquakes. The predictive capabilities of the models are assessed and show good-to-excellent model performance for both events. These memberships are then applied to the 1999 Chi-Chi earthquake, using only a digital elevation model, active fault map, and isoseismal data, replicating prediction of a future event in a region lacking historic inventories and/or geotechnical data. This similarly results in excellent model performance, demonstrating the model's predictive potential and confirming it can be meaningfully applied in regions where previous methods could not. For such regions, this method may enable a greater ability to analyze coseismic landslide hazard from specific earthquake scenarios, allowing for mitigation measures and emergency response plans to be better informed of earthquake-related hazards.