A Physically Based Model for the Sequential Evolution Analysis of Rainfall‐Induced Shallow Landslides in a Catchment

Abstract

Debris flows are one of the most common geological disasters in mountainous areas (Iverson, 1997). The materials and water sources of debris flows mainly come from loose materials formed by shallow landslides or river sediment and runoff formed by rainfall. In recent decades, shallow landslides and debris flows have occurred frequently and may be associated with the persistently expanding climatic change in many areas of the world (Bagwari et al., 2021). In China, for instance, during the 10 years from 2010 to 2019, an average of approximately 830 catastrophic debris flow events was reported each year. These disasters seriously affect the safety of the lives and property of people in mountainous areas. Due to the catastrophic damage caused by debris flows, it is beneficial to predict the potential of debris flow occurrence in advance. However, one characteristic of debris flows is the abrupt way they occur, with limited precursory signals (Swanson & Swanston, 1976). The operational prediction of such events remains a very large challenge.The debris material formed by shallow landslides is one of the main sources of debris flows. Predicting the volume, occurrence time and location of shallow landslides is very important for the analysis of debris flow disasters and has an important influence on the scale of debris flow formation and the severity of the disaster. Previous studies have proposed a variety of empirical or theoretical approaches for predicting shallow landslides and slope instability (e.g.,

Geometrical Variation Analysis of Landslides in Different Geological Settings Using Satellite Images: Case Studies in Japan and Sri Lanka

“…Numerous studies have been conducted to develop methods for assessing landslide occurrences. These methods include physically based models [55] and empirical models [56]. While these models provide valuable information about the spatial patterns of landslide susceptibility, there is still a lack of methods for predicting landslide size and mobility.…”

A Hydrodynamic‐Based Physical Unified Modeling for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run‐Out Extent Behavior

“…In calculating the damage process of landslide destabilization, we referred to the soil column failure threshold, mechanical reinforcement and stress transfer process of the root system in the landslide hydrodynamic triggering (LHT) model (Lehmann & Or, 2012) and depth‐resolved landslide hydrodynamic triggering (D‐LHT) model (Jiang et al., 2023) to realize the progressive dynamic failure process of shallow landslides. Compared to the LHT and D‐LHT models, the following modifications have been made in this model: (a) Unlike the LHT model, the sliding surface in this model is not limited to the soil‐rock interface.…”

“…In addition, compared to the traditional infinite slope static model, this model considers the interaction of the block, which describes the dynamic process of block failure (Christensen & Olami, 1992; Olami et al., 1992). As shown in Figure 1c, when the central cell ( i,j ) undergoes destabilization failure, the static equilibrium of the surrounding cells may be disrupted because of soil cohesion, the root systems matrix, and the effects of matric suction (Jiang et et al., 2023). Along the direction of instability of the central cell, the lower cells (blue cells) will experience compressive stress, while the upper cells (orange cells) will experience tensile stress in the downward direction due to interplay of forces between the vegetative roots and soil, which may result in the instability of surrounding cells.…”

“…The computational procedure can be summarized in the following steps: Step 1: The process of precipitation infiltration was calculated using 1‐D Richard’s equation and the VG model. The soil water content at different depths was computed by considering soil hydraulic conductivity and VG model parameters, which are critical factors affecting the soil water content and the infiltration process. Step 2: Any plane parallel to the bedrock surface was assumed to be a potential slip surface, and the factor of safety ( FoS , i.e., the ratio between resisting and driving forces) on each potential slip surface was calculated using the limit analysis method (Jiang et al., 2023). The most dangerous slip surface corresponds to the lowest potential slip surface of the FoS , which was determined based on the following formula: $$$FoS=\frac{{\tau }_{s}}{{W}_{d}}$$$ Step 3: The sliding force and resistance on the most dangerous sliding surface were calculated to assess whether the soil column loses stability along the sliding surface.…”

“…Step 2: Any plane parallel to the bedrock surface was assumed to be a potential slip surface, and the factor of safety ( FoS , i.e., the ratio between resisting and driving forces) on each potential slip surface was calculated using the limit analysis method (Jiang et al., 2023). The most dangerous slip surface corresponds to the lowest potential slip surface of the FoS , which was determined based on the following formula:…”