Landslide and debris flow susceptibility zonation using TRIGRS for the 2011 Seoul landslide event

Abstract

This paper presents the results from the application of a regional, physically based stability model: Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) for a region on Woomyeon Mountain, Seoul, South Korea. This model couples an infinite-slope stability analysis with a one-dimensional analytical solution to predict the transient pore pressure response to the infiltration of rainfall. TRIGRS also adopts the geographic information system (GIS) framework for determining the whole behaviour of a slope. In this paper, we suggest an index for evaluating the results produced by the model. Particular attention is devoted to the prediction of routes of debris flow, using a runoff module.

In this context, the paper compares observed landslide and debris flow events with those predicted by the TRIGRS model. The TRIGRS model, originally developed to predict shallow landslides, has been extended in this study for application to debris flows. The results predicted by the TRIGRS model are presented as safety factor (FS) maps corresponding to transient rainfall events, and in terms of debris flow paths using methods proposed by several researchers in hydrology.

In order to quantify the effectiveness of the model, we proposed an index called LRclass (landslide ratio for each predicted FS class). The LRclass index is mainly applied in regions where the landslide scar area is not well defined (or is unknown), in order to avoid overestimation of the model results. The use of the TRIGRS routing module was proposed to predict the paths of debris flow, especially in areas where the rheological properties and erosion rates of the materials are difficult to obtain. Although an improvement in accuracy is needed, this module is very useful for preliminary spatio-temporal assessment over wide areas. In summary, the TRIGRS model is a powerful tool of use to decision makers for susceptibility mapping, particularly when linked with various advanced applications using GIS spatial functions.