From ground motion simulations to landslide occurrence prediction

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.geomorph.2023.108898. This is version 3 of this Preprint.

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Authors

Ashok Dahal , David Alejandro Casto Cruz, Hakan Tanyas , Islam Fadel, Paul Martin Mai, Mark van der Meijde, Cees J. van Westen , Raphaël Huser , Luigi Lombardo 

Abstract

Ground motion simulations solve wave equations in space and time, thus producing detailed estimates of the shaking time series. This is essentially uncharted territory for geomorphologists, for we have yet to understand which ground motion (synthetic or not) parameter, or combination of parameters, is more suitable to explain the coseismic landslide distribution. To address this gap, we developed a method to select the best ground motion simulation using a combination of Synthetic Aperture Radar Interferometry (InSAR) and strong motion data. Upon selecting the best simulation, we further developed a method to extract a suite of intensity parameters, which we used to both bivariately and multivariately analyse coseismic landslide occurrences taking the Gorkha earthquake as a reference. Our results show that beyond the virtually unanimous use of peak ground acceleration, velocity, or displacement in the literature, different shaking parameters could play a more relevant role in landslide occurence. These parameters are not necessarily linked to the peak values but mostly linked to the actual displacement, velocity, frequency content and shaking duration, elements too often neglected in geomorphological analyses. This in turn implies that we have yet to fully acknowledge the complexity of the interactions between full waveforms and hillslope responses.

DOI

https://doi.org/10.31223/X5WM0P

Subjects

Applied Statistics, Earth Sciences, Geomorphology, Geophysics and Seismology, Physical Sciences and Mathematics, Soil Science, Statistical Models, Statistics and Probability

Keywords

Landslide Modeling, Earthquake simulation, Geophysics, Geotatistics, InSAR

Dates

Published: 2023-01-17 08:26

Last Updated: 2023-01-18 08:35

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License

CC-BY Attribution-NonCommercial 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
Yes