Effects of soil heterogeneity on susceptibility of shallow landslides

Emir Ahmet Oguz,Ivan Depina,Vikas Thakur

doi:10.1007/s10346-021-01738-x

Emir Ahmet Oguz, Ivan Depina + Show 1 more

Open Access

https://doi.org/10.1007/s10346-021-01738-x

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Abstract

Uncertainties in parameters of landslide susceptibility models often hinder them from providing accurate spatial and temporal predictions of landslide occurrences. Substantial contribution to the uncertainties in landslide assessment originates from spatially variable geotechnical and hydrological parameters. These input parameters may often vary significantly through space, even within the same geological deposit, and there is a need to quantify the effects of the uncertainties in these parameters. This study addresses this issue with a new three-dimensional probabilistic landslide susceptibility model. The spatial variability of the model parameters is modeled with the random field approach and coupled with the Monte Carlo method to propagate uncertainties from the model parameters to landslide predictions (i.e., factor of safety). The resulting uncertainties in landslide predictions allow the effects of spatial variability in the input parameters to be quantified. The performance of the proposed model in capturing the effect of spatial variability and predicting landslide occurrence has been compared with a conventional physical-based landslide susceptibility model that does not account for three-dimensional effects on slope stability. The results indicate that the proposed model has better performance in landslide prediction with higher accuracy and precision than the conventional model. The novelty of this study is illustrating the effects of the soil heterogeneity on the susceptibility of shallow landslides, which was made possible by the development of a three-dimensional slope stability model that was coupled with random field model and the Monte Carlo method.

Highlights

Landslides are one of the major hazards in the world causing adverse consequences to society, such as fatalities (e.g., Haque et al 2016; Petley 2012), injuries to people, economical losses (e.g., Nadim et al 2006), and environmental damages
This study presented the 3-Dimensional Probabilistic Landslide Susceptibility (3DPLS) model which is a Python-based threedimensional soil-column-based limit equilibrium model being able to model the spatial variability of the model parameters on the susceptibility of shallow landslides
The study presented the importance of the spatial variability on the safety of the shallow landslides, and the capacity of the 3DPLS in capturing these effects was validated

Summary

Introduction

Landslides are one of the major hazards in the world causing adverse consequences to society, such as fatalities (e.g., Haque et al 2016; Petley 2012), injuries to people, economical losses (e.g., Nadim et al 2006), and environmental damages. Among the different types of landslides, shallow landslides are one of the most detrimental types due to their high frequency on hillsides, and the capacity to evolve in destructive debris flows. In the landslide hazard and susceptibility mapping, physicalbased models are being increasingly employed as the hydrological and geotechnical aspects of the landslide can be explicitly considered. A wide range of physical-based landslide susceptibility models have been developed ranging from local (i.e., single slope to 10 km2) to national scales (i.e., hundreds to thousands of k m2). Some of the most commonly used models include the distributed Shallow

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