Recently, the number of disaster occurrence is increasing world widely due to climate changes. Accordingly, the losses of lives and properties resulting from domestic natural disaster is also increasing year by year. In Korea, the average annual numbe...
Recently, the number of disaster occurrence is increasing world widely due to climate changes. Accordingly, the losses of lives and properties resulting from domestic natural disaster is also increasing year by year. In Korea, the average annual number of deaths caused by the steep slope failure, which is one of the representative natural disasters, is about forty-two over the past thirty-six years. To prevent steep slope failure, prediction of locations with high probability of steep slopes' failures is important for the purpose of minimizing the losses resulting from their failures. Therefore, many researchers suggested indices of steep slope failure estimation based on the Rainfall Criteria and Intensity-Duration (I-D) threshold. Studies on constructing hazard maps are actively being conducted with the consideration of topographical factors and geographical information system (GIS). From the implementation of the steep slope failure estimation criteria recommended in the literature to domestic disaster cases, it was found that the existing estimation criteria have limitations because they take an account of three major factors, rainfall, topography, and geotechnical characteristics separately. Furthermore, even with an advanced steep slope analyses using conventional unsaturated soil mechanics, estimations of real steep slope behavior or physics under slope failure were not accurate.
In this study, new analysis and prediction methods on steep slope failure are suggested so that these new methods reflect the rainfall characteristics, topography (including slope angle), and hydro and mechanical properties of unsaturated soils. To consider the realistic mechanism of steep slope failure, unsaturated characteristics (soil-water characteristic curve, unsaturated permeability curve, and shear strength of unsaturated soil) and rainfall infiltration of weathered soils from frequent steep slope failure regions were analyzed. Steep slope infiltration-considered stability analyses were performed for different rainfall characteristics (rainfall intensities and durations) and slope angles by assigning the analyzed hydro and mechanical properties of unsaturated foundations as input parameters. The unsaturated infinite steep slope infiltration-considered stability analyses were conducted using the infiltration model by Mein and Larson (1973) and shear strength model accounting suction stresses. In the analyses, suction profile which expresses in terms of positive pore water pressure within seepage profile exerted from precipitation is adapted based on the results of infiltration model tests and the research by Rahardjo et al. (1995). Stability analysis is performed using unsaturated infinite slope stability theory, and Prediction Criteria for Steep Slope Failure (Hazard Diagram & I-D Equation) are suggested and verified. The Prediction Criteria for Steep Slope Failure are developed based on the boundary criterion representing safety level obtained from safety factor considering rainfall intensity and duration. The suggested Prediction Criteria for Steep Slope Failure consider the rainfall characteristics, steep slope angle, geotechnical characteristics simultaneously and suggest more reliable failure estimation criterion of steep slopes by compensating the problems found from the previous studies. In addition, new prediction model for steep slope failure is suggested based on the dynamic risk analyses for wide area by integrating the safety factor calculated from unsaturated infinite slope stability analysis and GIS. The suggested prediction model for steep slope failure enables steep slope risk assessment based on the major influential factors of steep slope failure, such as rainfall, topographic characteristics (slope angle), engineering properties (unsaturated characteristics) of slopes.
Future studies are required for the improvement of the prediction model for steep slope failure proposed in this study. The improvement should be focused on real-time risk assessment of steep slopes and suggestion of management and disaster warning system of steep slopes based on the real-time risk assessment.