Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/nhessd-3-227-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
07 Jan 2015
Review status
This discussion paper is a preprint. It has been under review for the journal Natural Hazards and Earth System Sciences (NHESS). The revised manuscript was not accepted.
Improvement of shallow landslide prediction accuracy using soil parameterisation for a granite area in South Korea
M. S. Kim1, Y. Onda1, and J. K. Kim2 1Department of Integrative Environmental Sciences, Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba 305-8572, Japan
2Quaternary Geology Research Department, Korea Institute of Geoscience and Mineral Resources (KIGAM), 124 Gwahang-no, Yuseong-gu, Daejeon 305-350, Republic of Korea
Abstract. SHALSTAB model applied to shallow landslides induced by rainfall to evaluate soil properties related with the effect of soil depth for a granite area in Jinbu region, Republic of Korea. Soil depth measured by a knocking pole test and two soil parameters from direct shear test (a and b) as well as one soil parameters from a triaxial compression test (c) were collected to determine the input parameters for the model. Experimental soil data were used for the first simulation (Case I) and, soil data represented the effect of measured soil depth and average soil depth from soil data of Case I were used in the second (Case II) and third simulations (Case III), respectively. All simulations were analysed using receiver operating characteristic (ROC) analysis to determine the accuracy of prediction. ROC analysis results for first simulation showed the low ROC values under 0.75 may be due to the internal friction angle and particularly the cohesion value. Soil parameters calculated from a stochastic hydro-geomorphological model were applied to the SHALSTAB model. The accuracy of Case II and Case III using ROC analysis showed higher accuracy values rather than first simulation. Our results clearly demonstrate that the accuracy of shallow landslide prediction can be improved when soil parameters represented the effect of soil thickness.

Citation: Kim, M. S., Onda, Y., and Kim, J. K.: Improvement of shallow landslide prediction accuracy using soil parameterisation for a granite area in South Korea, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-3-227-2015, 2015.
M. S. Kim et al.
M. S. Kim et al.

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Short summary
The accuracy of shallow landslide prediction based on SHALSTAB model varying the input soil data was examined. Soil parameters calculated from a stochastic hydro-geomorphological model were applied to the SHALSTAB model. Results showed that the use of soil properties reflecting soil thickness can improve the accuracy of shallow landslide prediction.
The accuracy of shallow landslide prediction based on SHALSTAB model varying the input soil data...
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