A GIS-based probabilistic analysis model for rainfall-induced shallow landslides in mountainous areas
Landslides are serious natural disasters frequently occurring in the mountainous areas along the Sichuan–Tibet railway. Landslides are often induced by rainfall and greatly threaten people’s lives and property. Via the use of GIS technology, a probabilistic analysis model was proposed for rainfall-i...
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Veröffentlicht in: | Environmental earth sciences 2022-09, Vol.81 (17), Article 432 |
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Sprache: | eng |
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Zusammenfassung: | Landslides are serious natural disasters frequently occurring in the mountainous areas along the Sichuan–Tibet railway. Landslides are often induced by rainfall and greatly threaten people’s lives and property. Via the use of GIS technology, a probabilistic analysis model was proposed for rainfall-induced shallow landslides along the above route. The process of the proposed probabilistic analysis model could be divided into three parts: (i) an infiltration hydrogeological model, (ii) a slope stability model, and (iii) probabilistic analysis. In this model, soil cohesion and internal friction angle were regarded as random parameters. The Green–Ampt model was used to dynamically describe the soil infiltration process during rainfall. Combined with the infinite slope stability model, the failure probability in the study area was analyzed. The model was applied to simulate the Bayi catchment landslide event of August 18, 2010, to evaluate its reliability. Through comparison of the simulation results to landslide occurrence locations, it was determined that the model achieves a satisfactory prediction performance. In addition, compared to deterministic analysis methods and the r.slope model, the proposed probabilistic analysis model achieved a satisfactory evaluation performance. The presented physics-based probabilistic analysis model could provide important theoretical support for hazard prevention in regard to rainfall-induced shallow landslides in mountainous areas. |
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ISSN: | 1866-6280 1866-6299 |
DOI: | 10.1007/s12665-022-10562-y |