Abstract

The Sichuan-Tibet Railway traverses the Qinghai-Tibet Plateau in China, where giant landslides occur frequently and densely. Accurately assessing the velocity, runout distance, and influenced area of the potential landslides is one of the nonnegligible scientific and technical issues. This study establishes a dynamic model for the landslide runout assessment along the Sichuan-Tibet Railway. The proposed model is based on the shallow water theory and takes into account the mechanism that the friction is weakening with the increase of velocity, the finite difference method is used to solve the governing equations, and the ideal one-dimensional dam break experiment was used to verify the shock-capturing capacity of the numerical methods. The Lagang ancient landslide, only 500 m away from the Jiacha Station of the Sichuan-Tibet Railway, represents the typical environment and development pattern of landslides in this region. Therefore, the proposed model is applied to discuss its effects on the landslide dynamic process and deposit patterns. Besides, 75 sets of numerical experiments were further carried out to explore the sensibility of the three parameters including peak friction coefficient μp, steady friction coefficient μs, and critical velocity Vc in this model. The results indicate that μs determine the lower limit of the friction coefficient, which significantly impacts the landslide runout distance; μp is mainly acting at the initial and final stage and has less influence on the landslide dynamic. By contrast, Vc is the most significant. When the Vc is small, the landslide can quickly reach the threshold velocity after the initial, and the dynamic process has a small correlation with the μp; when the Vc is large, the landslide is difficult to reach the threshold, and the mobility will be limited. It should be noted that the materials, lithology, strength, and micro-cracks of landslides mass formed under the special geological, geomorphic, and climatic conditions in this region may affect the input values when using the friction weakening model on landslides risk assessment.

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