Hillslope hydrology studies have shown that bedrock surface topography maybe the most important factor affecting subsurface flow, and that soil thickness and soil properties related to topography are important factors in shallow landslide prediction. In this study, the physically based H-slider (hillslope-scale shallow landslide-induced debris flow risk evaluation) model was used to evaluate the effects of topography and soil parameterisation reflecting soil depth on shallow landslide prediction accuracy. Two digital elevation models (DEMs; i.e. ground surface and bedrock surface) and three soil thicknesses (average soil thickness, soil thickness to weathered rock and soil thickness to bedrock) and physical soil parameters (cohesion and internal friction angle) at a small hillslope site in Jinbu, Kangwon Prefecture, eastern part of the Korean Peninsula, were considered. Each prediction result simulated with the H-slider model was evaluated by receiver operating characteristic (ROC) analysis for modelling accuracy. The results of the ROC analysis for shallow landslide prediction using the ground surface DEM (GSTO) and the bedrock surface DEM (BSTO) indicated that the prediction accuracy was higher using the GSTO compared to the BSTO. Moreover, the prediction accuracy based on soil parameterisation reflecting soil thickness was highest in all cases. These results imply that the effect of soil parameters on shallow landslide prediction could be larger than the effects of topography and soil thickness. Therefore, we suggest that using soil properties representing the effect of soil thickness can improve the accuracy of shallow landslide prediction, which should contribute to more accurately predicting shallow landsides.
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