Landslide susceptibility mapping using the infinite slope, SHALSTAB, SINMAP, and TRIGRS models in Serra do Mar, Brazil

Author(s)

do Pinho, Thiago Machado ; Augusto Filho, Oswaldo

• Document type: Journal article
• Source: JOURNAL OF MOUNTAIN SCIENCE; v. 19, n. 4, p. 19-pg., 2022-04-01.

Abstract

Slope failure triggered by heavy rainfall is very common in tropical and subtropical regions and a cause of major social and economic damage. Landslide susceptibility maps can be generated using geographical information systems (GIS) and limit equilibrium slope stability models coupled or not to hydrological equations. This study investigated the efficacy of four models used for slope stability analysis in predicting landslide-susceptible areas in a GIS environment. The selected models are the infinite slope, the shallow slope stability model (SHALSTAB), the stability index mapping (SINMAP), and the transient rainfall infiltration and grid-based regional slope-stability (TRIGRS). For comparisons, the authors (a) included the infinite slope equation in all models, (b) clearly defined input parameters and failure triggering mechanisms for each simulation (soil depth, water table height, rainfall intensity), (c) determined appropriate values for each model to obtain stability levels that represented similar hydrogeotechnical conditions, and (d) considered upper-third areas of landslide scars to estimate the reliability of susceptibility maps using validation indices. An intense rainfall event occurred in Serra do Mar, Brazil in January 2014 triggered hundreds of landslides and was used for back analysis and evaluation of the slope stability analysis models. When rainfall intensity is not considered, the four models produced very similar results. The most reliable landslide susceptibility map was generated using TRIGRS and considering the granite residual granite soils geological-geotechnical unit, subjected to a rainfall intensity of 210 mm for 2 h under unsaturated conditions. (AU)

• FAPESP's process: 17/26081-8 - Application of slope stability analysis models in a GIS environment to predict landslides in the Serra do Mar region, SP
• Grantee: Oswaldo Augusto Filho
• Support Opportunities: Regular Research Grants