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Slope failures are major natural disasters in Hiroshima prefecture, Japan under intense rainfall conditions. Both people and property were affected severely due to these disastrous events during past few decades. 32,000 planar slopes and valleys were susceptible to failure in Hiroshima prefecture, Japan have been identified by Hiroshima prefectural government and was developed a hazard assessment system thoroughly based on rainfall and past records of the data. However, the developed system can only be accommodated in a large area 5 km x 5km grid, and not be possible to predict the individual slope failure in the region. Geotechnical investigation of natural slopes is challengeable especially when natural slopes having higher gradients and access is difficult and also to estimate shear strength parameters spatially. Recently, authors have conducted a series of in-situ investigations based on the newly developed lightweight dynamic cone penetrometer to examine its applicability in analyzing the slopes covered with weathering remnants of granitic rocks. Six patterns were identified based on the penetration resistance varying with the depth. Semi-variogram analysis showed that the correlated distance of cone resistance varies with 11 to 30 m depending on the depth. A series of laboratory calibration tests based on the lightweight dynamic cone penetration tests, and direct shear tests were conducted at different void ratios and degrees of saturation. Based on the laboratory calibration test results, a method of determining void ratio, e from the data of qd was presented. Based on this, two formulas to evaluate shear strength parameters, cohesion and friction angle, were established with the cone resistance and the degree of saturation. As a whole proposed method can be successfully applied to individual slopes to determine the profile thickness, and to evaluate the shear strength parameters spatially. Based on this, hazard assessment of individual slopes can be made.

Assessment of natural slopes susceptible to failure in heavy rainfall based on in-situ cone resistance data