Physically-based landslide susceptibility analysis using Monte Carlo simulation in a tropical mountain basin |
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| Authors: | Roberto J Marin Álvaro J Mattos |
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| Institution: | 1. Infrastructure Investigation Group (GII), Environmental School, Faculty of Engineering, University of Antioquia – UdeA, Medellín, Colombia rjose.marin@udea.edu.co https://orcid.org/0000-0002-3206-0425;3. Geo-Research International (GeoR), Environmental School, Faculty of Engineering, University of Antioquia – UdeA, Medellín, Colombia https://orcid.org/0000-0003-1288-3288 |
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| Abstract: | ABSTRACT Physically-based distributed models are implemented for landslide susceptibility and hazard assessment around the world. Probabilistic methodologies are considered appropriate to study and quantify the uncertainties derived from the input parameters of these models. In this paper, three sets of Monte Carlo simulations, each one with 10,000 iterations, were applied for a slope stability analysis in a small basin of Envigado (Colombia), using the TRIGRS model, to characterise the uncertainty in the landslide assessment. Different parameters to determine the minimum number of realizations required to ensure a small variation in the failure probability were proposed and analyzed. The quality of the landslide susceptibility assessment was studied. Unexpected and probably erroneous results that may be common in the maps generated using this and other similar methodologies were identified and explained. Additionally, the distribution of the factor of safety was calculated for different grid cells of the basin, showing that the probability density function with the best adjustment to the frequency histogram of the factor of safety can vary between grid cells. The assumption of a normal distribution for the factor of safety would be inappropriate and would lead to miscalculations in this case study. |
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| Keywords: | Landslides TRIGRS Monte Carlo failure probability probability density function |
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https://orcid.org/0000-0002-3206-0425;3. Geo-Research International (GeoR), Environmental School, Faculty of Engineering, University of Antioquia – UdeA, Medellín, Colombia