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http://dx.doi.org/10.14578/jkfs.2021.110.1.64

Development of a Prediction Technique for Debris Flow Susceptibility in the Seoraksan National Park, Korea  

Lee, Sung-Jae (University Forests of Seoul National University)
Kim, Gil Won (Institute of Agriculture Life Science, Gyeongsang National University)
Jeong, Won-Ok (Korea National Park Research Institute, Korea National Park Service)
Kang, Won-Seok (Department of Forest Conservation, National Institute of Forest Science)
Lee, Eun-Jai (Technology and Management Research Center, National Institute of Forest Science)
Publication Information
Journal of Korean Society of Forest Science / v.110, no.1, 2021 , pp. 64-71 More about this Journal
Abstract
Recently, climate change has gradually accelerated the occurrence of landslides. Among the various effects caused by landslides,debris flow is recognized as particularly threatening because of its high speed and propagating distance. In this study, the impacts of various factors were analyzed using quantification theory(I) for the prediction of debris flow hazard soil volume in Seoraksan National Park, Korea. According to the range using the stepwise regression analysis, the order of impact factors was as follows: vertical slope (0.9676), cross slope (0.6876), altitude (0.2356), slope gradient (0.1590), and aspect (0.1364). The extent of the normalized score using the five-factor categories was 0 to 2.1864, with the median score being 1.0932. The prediction criteria for debris flow occurrence based on the normalized score were divided into four grades: class I, >1.6399; class II, 1.0932-1.6398; class III, 0.5466-1.0931; and class IV, <0.5465. Predictions of debris flow occurrence appeared to be relatively accurate (86.3%) for classes I and II. Therefore, the prediction criteria for debris flow will be useful for judging the dangerousness of slopes.
Keywords
debris flow; landslide; national parks; quantification theory; prediction criteria;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Brand, E.W. 1988. Landslide risk assessment in gong kong, on Landslided. Lausanne 2: 1059-1074.
2 Chau, K.T., Sze, Y.L., Fung, M.K., Wong, W.Y., Fong, E.L. and Chan, L.C.O. 2004. Landslide hazard analysis for hongkong using landslide inventory and GIS. Computers and Geosciences 30(4): 429-443.   DOI
3 Choi, K. 1986. Landslides occurrence and its prediction in Korea. Doctor Philosophy Dissertation kangwon National University korea. pp. 45.
4 Choi, Y.N., Lee, H.H. and Yoo, N.J. 2018. Characteristic analysis and prediction of debris flow-prone area at daeryongsan. Journal of the Korean Association of Geographic Information Studies 21(3): 48-62.   DOI
5 Dai, F.C. and Lee, C.F. 2002. Landslide characteristics and slope in instability modeling using GIS. Lantau Island, Hongkong, Geomorphology 42(2): 213-228.
6 EPOCH (European Community Program). 1993. Temporal occurrence and forecasting of landslides in the european community, Contract No. 900025.
7 Hutchinson, J.N. 1988. Mophological and geotechnical parameters of landslides in relation to geology and hydrology. In Landslides Proc. 5th Int. Symp. on Landslides. Balkema, Rotterdam, pp. 3-35.
8 Jung, K.W., Park, S.J. and Lee, C.W. 2008. Development of the score table for prediction of landslide hazard (A case study of gyeongsangbuk-do province). Journal of Korean Forestry Society 93(7): 332-339.
9 Kim, G.H. and Hwang, J.S. 2011. The estimation of debris flow behaviors in injae landslide area. Korean Journal of Geomatics 29(5): 535-541.   DOI
10 Kang, W.P., Hiroshi, M. Hiroshi, O. and Ma, H.S. 1986. On the determination of slope stability to landslide by quantification(II). Journal Korean Forestry Society 75: 32-37.
11 Kim, K.N., Jang, S.J., Lee, K.Y., Seo, G.B., Kim, B.S. and Chun, K.W. 2015. Prediction of the debris flow-prone area in the hilly district within urban. Journal of the Korean Society of Hazard Mitigation 15(3): 141-146.   DOI
12 Kim, K.S., Kim, W.Y., Chae, B.G., Song, Y.S. and Cho, Y.C. 2005. Engineering geological analysis of landslides on natural slopes induced by rainfall. The Journal of Engineering Geology 15(2): 105-212.
13 Lee, S.J., Lee, E.J. and Ma, H.S. 2019. Analysis of characteristics landslide susceptibility in rugged mountain range in the korean national park. Journal of Korean Forestry Society 108(4): 551-560.
14 Kwon, H.J. 2016. A Study on the characteristics of influential factors and hazard prediction map development of the landslides in mountainous national parks by using spatial information technologies. Doctor of Philosophy Dissertation Kyungpook National University korea. pp. 2.
15 Lee, G.S., Lee, H.J., Go, S.Y. and Cho, G.S. 2014. The evaluation on the prediction ratio of landslide hazard area based on geospatial information. Journal of Cadastre 44(2): 113-124.
16 Lee, J.S., Song, C.G., Kim, H.T. and Lee, S.O. 2015. Risk analysis considering the topography characteristics of debris flow occurrence area. Korean Society of Hazard Mitigation 15(3): 75-82.   DOI
17 Lee, S.J. 2014. Development of prediction technique of landslide using forest environmental factors. Doctor of Philosophy Dissertation Gyeongsang National University korea. pp. 1-6.
18 Lee, S.J. and Ma, H.S. 2018. Development of prediction technique of landslide using forest environmental factors. Journal of Agriculture & Life Sciences 52(4): 63-72.
19 Ma, H.S. 1994. Studies on development of prediction model of landslide hazard and its utilization. Journal of Korean Forestry Society 83(2): 175-190.
20 Ma, H.S. 2001. Landslide Characteristics and recovery direction in korean national parks. Journal of National Park Research 27: 17-21.
21 Kim, P.G. and Han, K.Y. 2017. Numerical modeling for the detection of debris flow using detailed soil map and GIS. Korean Society of Civil Engineers 37(1): 43-59.   DOI
22 Ma, H.S. and Jeong, W.O. 2010. Characteristics analysis of debris flow disaster in korean national parks. The Korea Society For Environmental Restoration And Revegetation Technology 13(4): 52-64.
23 Varnes, D.J. 1978. Slope movement types and processes, In landslides analysis and Control, TRB special Report, 176, National Academy of Science 11-33.
24 Ma, H.S., Kang, W.S. and Lee, S.J. 2014. Prediction and evaluation of landslide hazard based on regional forest environment. Journal of Korean Forestry Society 103(2): 233-239.   DOI
25 Ma, H.S., Kang, W.S. and Lee, S.J. 2015. Prediction of debris flow hazard in high mountain areas. Journal of Agriculture & Life Sciences 49(5): 13-21.   DOI