期刊
GEOMORPHOLOGY
卷 271, 期 -, 页码 40-54出版社
ELSEVIER
DOI: 10.1016/j.geomorph.2016.07.031
关键词
Shallow landslides; Soil depth; Subsurface flow; Upslope contributing area
资金
- Basic Research Project (Development of an integrated early detection system of landslides based on real-time monitoring) of the Korea Institute of Geoscience and Mineral Resources (KIGAM) - Ministry of Science, ICT and Future Planning of Korea
Shallow landslides are affected by various conditions, including soil depth and subsurface flow via an increase in the pore water pressure. In this study, we evaluate the effect of soil depth and subsurface flow on shallow landslide prediction using the shallow landslide stability (SHALSTAB) model. Three detailed soil depth data-the average soil depth, weathered soil depth, and bedrock soil depth were collected using a knocking pole test at a small hillslope site composed of granite in the Republic of Korea. The SHALSTAB model was applied to a ground surface topographic digital elevation model (DEM) using the three soil depths and upslope contributing area (SCA) assuming subsurface flow calculated from four DEMs: a ground surface topography (GSTO) DEM, weathered soil topography (WSTO) DEM, bedrock topography (BSTO) DEM, and low-level bedrock topography (EBSTO) DEM. The model performance was measured using a receiver operating characteristic (ROC) analysis. While evaluating the effect of the soil depth with SCA using GSTO DEM, it was found that the bedrock soil depth had higher prediction accuracy compared to that of the average soil depth or weathered soil depth. To evaluate the saturated subsurface flow between the soil and bedrock, SCAs calculated using WSTO and BSTO DEMs were applied. From these simulations, we found that SCA from BSTO DEM and the bedrock soil depth affect the shallow landslide prediction; however, these prediction effects are not significantly increased by large differences in the elevation (between the lowest and highest elevation values). Therefore, we considered the influence of the bedrock depression and SCA from EBSTO DEM. In applying SCA from EBSTO, the prediction accuracy was significantly increased compared to the other predictions. Our results demonstrate that the influence of the bedrock topography on the prediction of shallow landslides may be particularly significant at the scale of a hillslope. (C) 2016 Elsevier B.V. All rights reserved.
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