Abstract
Infiltration and groundwater have been widely considered as the main factors that cause shallow landslides; however, the effect of runoff has received less attention. In this study, an in-house physical-process-based shallow landslide model is developed to demonstrate the influence of runoff. The model is controlled by coupling the shallow water equation (dynamic) and Richards’ equation. An infinite slope stability analysis is applied to evaluate the possibility of regional landslides. A real, small catchment topography is adopted as a demonstration example. The simulation illustrates the variations of runoff and the factor of safety (FS) during a storm. The results indicate that, after the surface becomes saturated, the FS may keep varying due to the increasing pressure head, which is caused by increasing surface water depth. This phenomenon most likely occurs downstream where the slopes easily accumulate water. The depth of the surface water may also be a factor of slope failure. Therefore, it is essential to increase the accuracy of calculating the runoff depth when assessing regional shallow landslides.
Highlights
Landslides occur in many places around the world and pose severe threats to safety and economy.Rainfall is the most recognized triggering factor, in tropical areas
Water that infiltrates the unsaturated soil surfaces may lead to low matric suction and reduce the shear strength of soil, thereby increasing the possibility of slope failure
This study develops an in-house physical-process-based landslide model to observe the influence of runoff on shallow landslides in unsaturated soil
Summary
Landslides occur in many places around the world and pose severe threats to safety and economy. Tarantino and Bosco [5], Collins and Znidarcic [6], and Tsai et al [7] developed shallow landslide models considering both unsaturated and saturated soils, using the Richards’ equation and the extended Mohr–Coulomb failure criterion [8]. These studies have gradually helped demonstrate the mechanism of rainfall-triggered landslides, and this increased understanding allows models to analyze more different factors and issues.
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