Improving slope stability estimates by incorporating geophysical and remote sensing monitoring data into hydro-geomechanical modeling

Abstract

Landslides are a major natural hazard, threatening communities and infrastructure worldwide. The mitigation of these hazards relies on the understanding of their causes and triggering processes, directly depending on soil properties, land use, and their variations over time. In this study, we propose a new approach combining geophysics and remote sensing with hydrological and geomechanical modeling to provide a robust estimate of the probability of failure of slopes in endangering the surrounding structures. Knowing that soil properties are site-dependent, it is crucial to analyze their sensitivity in estimating the probability of failure. Therefore, we performed a sensitivity analysis on the seven main parameters (density, friction angle, cohesion, soil thickness, slope, water recharge and saturated hydraulic conductivity) of the hydro-geomechanical model, which highlighted strong sensitivity to variations in soil thickness and cohesion. Based on those results, we used seismic noise measurements to assess soil thickness around our study site, which is a densely developed urban site. We highlighted that relatively thick soil layers (above 2 m) have up to 4 times higher probability of failure. Next, we used remote sensing data to assess vegetation cover. In fact, the presence of vegetation has a significant effect on soil cohesion, especially when the soil layer is relatively thin. The addition of vegetation cover showed an important reduction in the probability of failure when the soil thickness is less than 3 m.