Browse > Article
http://dx.doi.org/10.14578/jkfs.2014.103.2.218

The Prediction of Landslide Potential Area Using SHALSTAB  

Jang, Hyeon Seok (Department of Forest Science, Chungbuk National University)
Lee, Sang Hee (Department of Forest Science, Chungbuk National University)
Kim, Je Su (Department of Forest Science, Chungbuk National University)
Publication Information
Journal of Korean Society of Forest Science / v.103, no.2, 2014 , pp. 218-225 More about this Journal
Abstract
Landslides, one of earth's natural disasters, increase every year due to heavy rainfall, and cause damage to human life and assets. This study used the SHALSTAB to predict places at risk of landslides, in accordance with the intensity of rainfall. The parameter value of transmissivity was $19.58m^2/day$, the internal friction angle $36.3^{\circ}$, and the saturated unit weight $2.03t/m^3$. The slope stability status was classified into four categories, namely: unconditionally stable, stable, unstable and unconditionally unstable. In order to evaluate the applicability of the SHALSTAB, actual landslide areas were checked, with the unstable area under 263 mm rainfall. 85.1% of them were consistent. And so we can identify the distribution of places at risk of landslides, on the basis of the intensity of rainfall by means of SHALSTAB.
Keywords
shallow landslide; SHALSTAB; rainfall intensity;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Lee, M.S., Ryu, J.C. and Kim, K.S. 2009. Development of the Linear Regression Analysis Model to Estimate the Shear Strength of Soils. The journal of Engineering Geology 19(2): 177-189.
2 Lee, S.H. 2005. Application of a physically based hydrologic model to the prediction of shallow landslide potential area using GIS. PhD thesis, Chungbuk National University. pp. 104.
3 Ma, H.-S., Jeong, W.-O. and Park, J.-W. 2008. Development of Prediction Technique of Landslide Hazard Area in Korea National Parks. Journal of Korean Forest Society 97(3): 326-331.   과학기술학회마을
4 Min, C.-S. 2006. Prediction of Landslide Based on the Characteristics of Subsurface Flow. Master's Thesis, Seoul National University. pp. 75.
5 Montgomery, D.R. and Dietrich, W.E. 1994. A Physically-Based Model for the Topographic Control on Shallow Landsliding. Water resources research 30(4): 1153-1171.   DOI   ScienceOn
6 Woo, B.M., Yim, K.B. and Lee, S.W. 1978. Studies on the Landslides and Its Control Measures in Anyang Area. Journal of Korean Forest Society 39:1-34.
7 Yang, I.T., Chun, K.S., Park, J.K. and Lee, S.Y. 2007. An Estimation to Landslide Vulnerable Area of Rainfall Condition using GIS. Journal of the Korean Society for GeoSpatial Information System 15(1): 39-46.   과학기술학회마을
8 Michel, G.P., Kobiyama, M., and Goerl, R.F. 2014, Comparative analysis of SHALSTAB and SINMAP for landslide susceptibility mapping in the Cunha River basin, southern Brazil, J. Soils and Sediments. http://link.springer.com/article/10.1007%2Fs11368-014-0886-4 (2014. 5. 26).
9 Cha, K.S. 2004. Prediction of potential landslide sites using the multicell technique and the landform index. PhD thesis, Seoul National University. pp. 127.
10 Choi, K. 1986. Landslides occurrence and its prediction in Korea. PhD thesis, Kangwon National University. pp. 45.
11 Hong, W.P., Kim, S.K. and Han, J.G. 1990. Prediction of Rainfall - triggered Landslides in Korea. Geotechnical Egineering 6(2): 55-63.
12 Kim, J.S., Kim, N.C. and Lee, H.H. 2000. Application of a Physically Based Model to Shallow landsliding. Journal of the Korea Society of Environmental Restoration Technology 3(1): 62-69.   과학기술학회마을
13 Kim, K.S., Kim, W.Y., Chae, B.G. and Cho, Y.C. 2000. Engineering Geologic Characteristics of Landslide Induced by Rainfall - Boeun, Chungcheong Buk-do -. The Journal of Engineering Geology 10(2): 163-174.
14 Dietrich, W.E. and Montgomery, D.R. 1998. SHALSTAB, A digital terrain model for mapping shallow landslide potential. http://calm.geo.berkeley.edu/geomorph/shalstab (2014. 5. 26).
15 Lee, C.W. 2010. Debris flow characteristics and measures. sanrimji 533: 84-87.